Linking Species Richness, Litter Chemical Diversity, and Soil Carbon Dynamics in the Atlantic Forest, Bahia Brazil

Permanent Link: http://ufdc.ufl.edu/UFE0022672/00001

Material Information

Title: Linking Species Richness, Litter Chemical Diversity, and Soil Carbon Dynamics in the Atlantic Forest, Bahia Brazil
Physical Description: 1 online resource (166 p.)
Language: english
Creator: Epps, Kimberly
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009


Subjects / Keywords: biodiversity, chemical, ecosystem, microbial, midinfrared
Soil and Water Science -- Dissertations, Academic -- UF
Genre: Soil and Water Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation


Abstract: LINKING SPECIES RICHNESS, LITTER CHEMICAL DIVERSITY, AND SOIL CARBON DYNAMICS IN THE ATLANTIC FOREST, BAHIA BRAZIL By Kimberly Y. Epps April 2009 Chair: Nicholas B. Comerford Major: Soil Science The high productivity and high species diversity of tropical forests amidst the supposed nutrient limitation of tropical soils prompt the question, 'Does the botanical diversity of tropical forests assist in the maintenance of nutrient bioavailability?' The primary objective of this research was to establish the relationship, if any, between plant-litter diversity and litter decomposition employing tree species of the biodiversity hotspot of the Atlantic Rain Forest of southern Bahia, Brazil. The central hypothesis was that the chemical diversity of leaf mixtures is a predictor of microbially mediated processes such as leaf litter decomposition. Two aspects central to this work were (1) the development of a chemical diversity index of leaf mixtures and (2) the use of infrared spectroscopy to chemically characterize each species. Field and laboratory studies targeted the impact of plant litter diversity on soil properties and processes. The objective of the field study was to evaluate and compare cocoa production systems and adjacent areas of secondary forest for tree species diversity, inflows of leaf litter mass and nutrients, and stocks of nutrients in surface soils. Results indicated that despite slightly lowered tree density and tree diversity compared to secondary forest, traditional cocoa production systems constituted an agroforestry system that closely resembles secondary forest in terms of biomass production and carbon and nutrient inputs to surface soil. A laboratory incubation study was conducted to test the ability of the chemical diversity index and chemical identity the comprehensive chemical fingerprint of individual species by infrared spectroscopy to predict rates of carbon mineralization of species mixtures. Infrared spectral regions were identified that explained as much as 87% of the variation in carbon mineralization of leaf mixtures. Chemical diversity as a solo parameter showed no correlation with mixture decomposition, but in conjunction with chemical traits, predicted rates of carbon mineralization when mixtures were grouped by the presence of a 'key' species. Results suggest that chemical diversity may be most effective in predicting the decomposition of mixtures dominated in quantity or behavior by a single species.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Kimberly Epps.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Comerford, Nicholas B.

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Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0022672:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022672/00001

Material Information

Title: Linking Species Richness, Litter Chemical Diversity, and Soil Carbon Dynamics in the Atlantic Forest, Bahia Brazil
Physical Description: 1 online resource (166 p.)
Language: english
Creator: Epps, Kimberly
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009


Subjects / Keywords: biodiversity, chemical, ecosystem, microbial, midinfrared
Soil and Water Science -- Dissertations, Academic -- UF
Genre: Soil and Water Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation


Abstract: LINKING SPECIES RICHNESS, LITTER CHEMICAL DIVERSITY, AND SOIL CARBON DYNAMICS IN THE ATLANTIC FOREST, BAHIA BRAZIL By Kimberly Y. Epps April 2009 Chair: Nicholas B. Comerford Major: Soil Science The high productivity and high species diversity of tropical forests amidst the supposed nutrient limitation of tropical soils prompt the question, 'Does the botanical diversity of tropical forests assist in the maintenance of nutrient bioavailability?' The primary objective of this research was to establish the relationship, if any, between plant-litter diversity and litter decomposition employing tree species of the biodiversity hotspot of the Atlantic Rain Forest of southern Bahia, Brazil. The central hypothesis was that the chemical diversity of leaf mixtures is a predictor of microbially mediated processes such as leaf litter decomposition. Two aspects central to this work were (1) the development of a chemical diversity index of leaf mixtures and (2) the use of infrared spectroscopy to chemically characterize each species. Field and laboratory studies targeted the impact of plant litter diversity on soil properties and processes. The objective of the field study was to evaluate and compare cocoa production systems and adjacent areas of secondary forest for tree species diversity, inflows of leaf litter mass and nutrients, and stocks of nutrients in surface soils. Results indicated that despite slightly lowered tree density and tree diversity compared to secondary forest, traditional cocoa production systems constituted an agroforestry system that closely resembles secondary forest in terms of biomass production and carbon and nutrient inputs to surface soil. A laboratory incubation study was conducted to test the ability of the chemical diversity index and chemical identity the comprehensive chemical fingerprint of individual species by infrared spectroscopy to predict rates of carbon mineralization of species mixtures. Infrared spectral regions were identified that explained as much as 87% of the variation in carbon mineralization of leaf mixtures. Chemical diversity as a solo parameter showed no correlation with mixture decomposition, but in conjunction with chemical traits, predicted rates of carbon mineralization when mixtures were grouped by the presence of a 'key' species. Results suggest that chemical diversity may be most effective in predicting the decomposition of mixtures dominated in quantity or behavior by a single species.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Kimberly Epps.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Comerford, Nicholas B.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0022672:00001

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2009 Kimberly Y. Epps 2


To Vera Jean and Omar Jamal, in whose hearts no bitterness could take root 3


ACKNOWLEDGMENTS Little can be accomplished in solitude. From its inception to its completion, this work is beholden to a cast of thousands. Foremost, I thank my mother, Yvonne D. Epps, for her steadfast encouragement and unconditional love, my family consisting of the Shareef-EppsMinter-Perkins-Justice-Runge Units, and its draf ted members Joyce Dow, Toni Greene-Garner, and Edith Yamanoha. My life of science began at my kindergarten disc overy that stars were fiery balls of gas. Since then I have been fortunate to have been influenced by phenomenal teachers and mentors along the years. I express sincere gratitude to Mrs. Rosenthal (3rd grade) and Mrs. Millet (4th grade) of P.S. 95Q; Mrs. Proimos (6th grade) and Mr. Ytuarte (7th grade) of the Immaculate Conception School of Jamaica; Mme. Gerton (F rench), Mr. Gordon (Physics), Mr. Greenberg (Geometry), and Mr. Kelly (English) of Bronx Science; Prof. Shirlynn Spacapan (Psychology) and Prof. Art Benjamin (Fun Math) of HMC; Dr. Paul Marcotte (Int ernational Agricultural Development) Dr. Bill Rains (Agronomy), and Dr. Kate Scow (Soil Microbiology) of U.C. Davis. For training my eyes, ears, head a nd hands, I thank She ila Pinkel (Photography, Pomona), Marti Kanin and Julie Hochman (Cello). For unparalleled training in field grit and economy, I am indebted to Dr. Eliska Rejmankova of U.C. Davis. Here at my current home in Gator Country, I thank my doctoral committee for expanding my horizons while tightening my scientific in vestigation skills: Wende ll Cropper for introducing me to the wonders of open source code and to the genius of Ramon Margalef; Willie Harris for being a model thinker and professor; Quintino Ar ajo for my immersion in the scientific and artistic culture of cacao; and P.K. Nair and Nige l Smith for grounding my inquiries in application and human need. Adding to the embarrassment of riches have been my behind-the-scenes advisors, Jim Reeves (USDA); Nairam Barros (U FV), Jack Ewel (UF); Al Medvitz (UCD); 4


Mark Van Horn (UCD); Arliclio de Quei roz Paiva (UESC); Rosana Higa (EMBRAPA Floresta), George Sodr (CEPLAC); Yuncong Li (UF); and Virupax Baligar (USDA) with whom it would be a pleasure and honor to c onsider future research plans. For bringing me up to speed on soil microbi ology and the wonders of Biolog, I thank Cory Krediet and Max Teplitski. For my crash course in the Atlantic Rain Forest I am grateful for the technical orientation of Andr M. Amorim and Jo s Limo da Paixo of the CEPLAC Herbarium as well as to my dear friend, right hand, and mateiro superior Agnaldo Oliveira da Silva. I acknowledge the support of the comm unity of the Assentamento Frei Vantuy and in particular, the leadership of Masa Fontana and Marlene Re bouas. The expertise and daily efforts of Dr. Helena Serdio, Jos Nelson Machado, Ce lso, Claudionou, Osmario of CEPLAC-CEPEC; Edilson Fernando da Silva, Seu Jos Alberto, Lu is Claudio de Almeida Barbosa, Antnio Lelis Pinheiro, Vernica, and Aldemir at the Federal University of Vio sa were indispensible to my work, as were the time and tutelage of the in imitable DRIFTS-Squad, Barry Francis and Tanesha Simmons of USDA-EMBUL. For their willingness to brav e dangers ranging from vigila nte wasps and busted boots to sievers lung, pipettors thumb and dishpan hands, I thank my Brothers and Sisters in Soil past and present: Dalton Abdala, Kahl il Apuzen-Ito, Elena Azuaje, Chri stine Bliss, Lizette Borges Gmez, Oldair Vinhas Costa, Eric Carvalho, Joy Futrell, Antnio and Emanuela GamaRodrigues, Sarah Johnson, Franci sco Lpes Neto, Isabel Lopez-Zamora, Melissa Martin, Edson Mrcio Matiello, Marina Morales, Deoyani Sarkhot, Shinjiro Sa to, Sharon Schnabel, Lauren Serra, Lisa Stanley, Aja Stoppe, Dashuai Sun, Ken van Rees, Marcela Quintero, and especially, Barbara Cade-Menun for leading the way down the dirt path. 5


For reminding me that life is not a one-note samb a, but rather a frevo, forr and at times a choro, I thank Abby Lces; Ana Amelia Guimares Araujo; Anthony Heric; Arceli Trindade da Silva; Ayesha Nibbe; Carol Souza; Charlotte Norri s; David Giles; David Healy; Flora Piasentin; Francisco Chico de Vale; Glria Fidelis da Paixo; Jina Kim; Justine Di Fiore; Katie Painter; Kipp Sutton; Larry Dieterich; the Rainha das A guas, Maria Apareida; Maria Mariano; Maura Barros; Michelle Young; Morena Maia; Neyde Alice Pereira; O Paulozo; Prashanth Ak; Rozeli Shiroma; Scott Looney; and Sylvia Ward. I am grateful for those who kept my heart and belly fed Renata Santiago, Judite de Ilhus; Regina Alvez Fe rreira; Jean Rissman; Karen van Epen; Danielle Calin; Paty Guerra; Gustavo Dantas; Ana Elisa DelArco; Cecilia and Wilton Carvalho; Halter Maia; Ivani de Brito; Snia Sampaio, and Gina Gonalves dos Santos. This work was performed under the authori zation of CNPq and IB AMA Permit No. RMC 004/05. I am grateful to the kind attentiveness of Dr. Francisco Guerra who led us along the way to authorization. For their financial support, I th ank the generous contribu tions of the University of Florida Alumni Fellowship; the Graduate Wo men in Science-Nell I. Mondy Award; the Ford Foundation Pre-Doctoral Diversity Fellowship an d the Epps-Tadross-Minter-Painter Student Emergency Funds. Above all, I welcome the opportunity to once again express my deep gratitude for the otherworldly patience, good humor, cheerleadership and translati on abilities of my advisor and role model, Nicholas B. Comerford. Lastly, for giving me the home of my spirit, a second mother tongue, and a very, very fine dog, I thank Bahia, herself. 6


TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........9 LIST OF FIGURES.......................................................................................................................11 ABSTRACT...................................................................................................................................13 CHAPTER 1 INTRODUCTION................................................................................................................. .15 2 CHEMICAL DIVERSITY HIGH LIGHTING A SPECIES RICHNESS AND ECOSYSTEM FUNCTION DISCONNECT.........................................................................17 Introduction................................................................................................................... ..........17 Materials and Methods...........................................................................................................22 Characterization of Leaf Tissue.......................................................................................22 Mathematical Treatmen t of Spectral Data.......................................................................23 Results and Discussion......................................................................................................... ..24 Experimental Ramifications of Chemical Diversity........................................................27 Conclusion..............................................................................................................................30 3 THE EFFECT OF CHEMICAL IDENTITY AND CHEMICAL DIVERSITY ON THE DECOMPOSITION OF TROPICAL LEAF MIXTURES.....................................................38 Introduction................................................................................................................... ..........38 Materials and Methods...........................................................................................................41 Leaf Material Collection and Characterization...............................................................41 Calculation of Chemical Diversity..................................................................................42 Incubation Study..............................................................................................................43 Microbial Community-Level Physiological Profiling.....................................................45 Statistics...........................................................................................................................47 Results.....................................................................................................................................49 Species Identity on Carbon Mineralization of Mixtures.................................................49 Chemical Identity on Carbon Mineralization of Mixtures..............................................50 Identification of Functional Chemical Traits..................................................................52 Microbial Functional Diversity and Non-additive Effects..............................................53 Discussion...............................................................................................................................54 Importance of Species Identity and Chem ical Identity on Ca rbon Mineralization.........54 Which Traits?..................................................................................................................57 Microbial Underpinnings of Non-Additive Effects.........................................................59 Conclusion..............................................................................................................................60 7


4 TREE SPECIES DIVERSITY AND NUTRIENT CYCLING POTENTIALS OF SMALL-SCALE CACAO PRODUCTION SYSTEMS AND SECONDARY FOREST FRAGMENTS IN SOUTHERN BAHIA, BRAZIL..............................................................91 Introduction................................................................................................................... ..........91 Materials and Methods...........................................................................................................94 Site Selection and Characterization.................................................................................94 Species Inventory and Tree Diversity.............................................................................95 Forest Floor.....................................................................................................................96 Litterfall Production........................................................................................................96 Soil Nutrient Status..........................................................................................................9 6 Statistical Analysis..........................................................................................................9 7 Results and Discussion......................................................................................................... ..98 Tree Density and Species Inventory................................................................................98 Litter Production, Standing Biomass.............................................................................102 Nutrient Inflows through Litterfall................................................................................103 Soil Nutrient Status........................................................................................................104 Conclusion............................................................................................................................106 5 OVERVIEW AND SYNTHESIS.........................................................................................127 APPENDIX A USING INFRARED SPECTROSCOPY TO DETERMINE THE RELATIVE CONTRIBUTION OF ORGANIC INPUTS TO SURFACE SOIL ORGANIC MATTER..............................................................................................................................132 Introduction................................................................................................................... ........132 Materials and Methods.........................................................................................................133 Study Site and Sampling...............................................................................................133 Single-species stands..............................................................................................133 Mixed-species stands..............................................................................................134 Sample Preparation........................................................................................................135 Spectral Analysis and Isotopic Carbon Analysis...........................................................135 Statistical Analysis........................................................................................................135 Results and Discussion......................................................................................................... 136 Relative Importance of Aboveand Belowground Inputs.............................................136 Interpretation................................................................................................................. 138 Conclusion............................................................................................................................140 LIST OF REFERENCES.............................................................................................................147 BIOGRAPHICAL SKETCH.......................................................................................................165 8


LIST OF TABLES Table page 2-1 Published mineral nutrition studies repor ting total nutrient concentrations used to investigate the chemical diversity (CDQ) and species richness relationship.....................32 3-1 Initial foliar total nutrient concentrat ions of 10 tropical tree species used in the incubation study.................................................................................................................64 3-2 Species composition and abbreviation code s of the 21 leaf mixtures observed in the incubation study.................................................................................................................65 3-3 Chemical diversity indices of leaf mi xtures according to th e mode of chemical characterization of material: total nutrient concentration (Total), mid-infrared (MIR) and near-infrared spectroscopy (NIR)...............................................................................66 3-4 Kendalls Tau correlation coefficient of total nutrient concentrations with decomposition responses of leaf-mixtures.........................................................................67 3-5 Summary of repeated measures ANOVA for effects of mixture composition on net respired CO2 of 21 leaf mixtures at Day 80.......................................................................68 3-6 Summary of factorial ANOVA for e ffects of mixture composition on the carbon mineralization rate constant, a, of 21 leaf mixtures...........................................................68 3-7 Expected and observed carbon mineraliza tion rates and non-additiv e effect of paired litter treatments in incubation study...................................................................................69 3-8 Summary of factorial ANOVA for effect s of mixture compositi on on interactions of net CO2, I net CO2, and the C mineralization rate constant, I a, of 21 leaf mixtures............70 3-9 Summary of selected successful models relating chemical identity (1/ ) to net evolved CO2 and C mineralization rate of 21 leaf mixtures..............................................71 3-10 Summary of successful models relating chemical identity (1/ ) and chemical diversity (CDQ) on C mineralization rate of 21 leaf mixtures...........................................71 3-11 Summary of successful models of the relationship of chemical identity and chemical diversity on the decomposition responses of INGA leaf mixtures (n=7).........................72 3-12 Summary of successful models of the relationship of chemical identity and chemical diversity on the decomposition responses of EMBA leaf mixtures (n=7).........................73 3-13 Summary of successful models of the relationship of chemical identity and chemical diversity on the decomposition responses of PAUM leaf mixtures (n=7).........................73 9


3-14 Discriminant analysis of non-additive effects observed in the C mineralization rates of 21 leaf mixtures, performed on the first f our PCA factor scores of the spectra of key and companion species................................................................................................74 3-15 Spectral traits of key species (MIR) cont ributing to successful m odels of leaf-mixture decomposition processes and their pote ntial physiochemical interpretation.....................75 3-16 Kendalls Tau correlation between microb ial functional diversity (Gini coefficient) and mean substrate use of 31 EcoPlate substrates and the decom position responses of mixed leaf treatments.........................................................................................................7 6 4-1 Soil chemical properties and particle size distribution of cacao and secondary forest study sites in the Assentamento Fr ei Vantuy, Ilhus, Bahia, Brazil................................109 4-2 Summary of the floristic diversity of four cabruca site s (0.25 ha) located in the Frei Vantuy Settlement, Ilhus, Bahia, Brazil.........................................................................110 4-3 Summary of the floristic diversity of four secondary fo rest sites (0.25 ha) located in the Frei Vantuy Settlement, Ilhus, Brazil.......................................................................111 4-4 Phytosociological parameters (excl uding cacao) of cabrucas in southern Bahia observed in other studies..................................................................................................112 4-6 Tree species ( 5 cm DBH) identified in the selected study areas of cabruca and secondary forest in the Assentamento Frei Vantuy, Ilhus, Bahia, Brazil......................114 4-7 Mean total nutrient concentrations of su rface soil (0-10cm) and litter and total annual input of nutrients through litterfall in traditional cacao sy stems and adjacent secondary forest sites in the Assentamento Frei Vantuy, Ilhus, Bahia, Brazil..............118 10


LIST OF FIGURES Figure page 2-1 Chemical diversity (CDQ) as a function of species ri chness of eight litter species native to the Atlantic Forest region of southern Bahia......................................................33 2-2 The effect of the removal of species from a mixture on chemical diversity under assumption of equal species abundance, and DRIFTS characterization of the assemblage in Fig. 2-1.......................................................................................................34 2-3 The relationship of foliar CDQ diversity with species richness of two different temperate forest communities. .........................................................................................35 2-4 The idiosyncrasy of additive studies..................................................................................36 3-1 Diffuse reflectance infrared spectra of 10 litter species.....................................................77 3-2 Chemical diversity (normalized to the maximum value) of all possible mixtures of 10 selected tropical species as a function of species richness, as characterized by total nutrient concentrations. ....................................................................................................7 8 3-3 Chemical diversity (normalized to the maximum value) of all possible mixtures of 10 selected tropical species as a function of species richness, as characterized by midinfrared spectroscopy (MIR). ............................................................................................79 3-4 Chemical diversity (normalized to the maximum value) of all possible mixtures of 10 selected tropical species as a function of species richness, as characterized by nearinfrared spectroscopy (NIR). ............................................................................................80 3-5 Carbon mineralization of ten individual tropical species and the control treatment. .......81 3-6 The effect of key species on d ecomposition responses after 80 days................................82 3-7 Dynamic nature of non-additi ve effects on cumulative evolved CO2 between litter pairs over the course of incubation....................................................................................83 3-8 Interaction effects of nitrogen-fixing and non nitrogen-fixing leaf mixtures....................84 3-9 Predicted versus observed interactions occurring in C mineralization rate constant and net evolved CO2 (Day 80) of the 21 mixed-litter treatments. ...................................85 3-10a Chart of spectral traits, one each from key and companion species, contributing to successful models of the form response ~ 1/ key + 1/ comp where response is net evolved CO2 (Day 30)........................................................................................................86 11


3-10b Chart of spectral traits, one each from key and companion species, contributing to successful models of the form response ~ 1/ key + 1/ comp where response is net evolved CO2 (Day 80)........................................................................................................87 3-11 Chart of spectral traits, one each from key and companion species, contributing to successful models of the form response ~ 1/ key + 1/ comp where response is the carbon mineralization rate constant, a ...............................................................................88 3-12 Principal components anal ysis of the single-substrate utilization profile of the 31 microbial communities litter treatments extracted from the final time step the incubation study.................................................................................................................89 3-13 Mean substrate use (AWCD) and fu nctional diversity (G INI) of microbial communities extracted from 21 litter-pair treatments grouped by key species.................90 4-1 Location of study area among land use types in the municipality of Ilhus, Bahia, Brazil......................................................................................................................... .......119 4-2 Approximate locations of observed tradit ional cacao and secondary forest study sites in the Assentamento Frei Vantuy, Ilhus, Bahia, Brazil..................................................120 4-3 Example of forest structure of secondary forest fragments.............................................121 4-4 Example of forest st ructure of cabruca systems..............................................................122 4-5 Diameter class distribution of stem s in two secondary forest fragments.........................123 4-6 Monthly litterfall in cacao and secondary forest collected from the period September 2005 to August 2006........................................................................................................124 4-7 Standing biomass on the fo rest floor of forested plot s in May and November, 2005.....125 4-8 Total organic matter content and or ganic matter distribution among particle size fractions of cacao and secondary forest sites...................................................................126 A-1 Sum of squared differences from of orga nic inputs plotted agai nst each other at the 0-5 cm and 5-10 cm depths. ...........................................................................................143 A-2 Isotopic carbon signature s of 18 single-species plots......................................................144 A-3 Sum of squared differences between fo rest floor litter and root litter in a multispecies forested system atop a clayey soil, based on non-combusted and combusted (cleaned) spectra.............................................................................................................. 145 A-4 Sum of squared differences between fo rest floor litter and root litter in a multispecies forested system atop a sandy so il, based on non-combusted and combusted (cleaned) spectra.............................................................................................................. 146 12


Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy LINKING SPECIES RICHNESS, LITTER CHEMICAL DIVERSITY, AND SOIL CARBON DYNAMICS IN THE ATLANTIC FOREST, BAHIA, BRAZIL By Kimberly Y. Epps May 2009 Chair: Nicholas B. Comerford Major: Soil and Water Science The high productivity and high sp ecies diversity of tropical forests amidst the supposed nutrient limitation of tropical soils prompt the question, Does the botanical diversity of tropical forests assist in the maintenance of nutrient bi oavailability? The pr imary objective of this research was to establish the relationship, if any, between plant-litter diversity and litter decomposition employing tree species of the biodivers ity hotspot of the Atla ntic Rain Forest of southern Bahia, Brazil. The centr al hypothesis was that the chemical diversity of leaf mixtures is a predictor of microbially mediated processes such as leaf litter de composition. Two aspects central to this work were (1) the development of a chemical diversity index of leaf mixtures and (2) the use of infrared spectroscopy to chemically characterize each species. Field and laboratory studies targeted the impact of plant litter divers ity on soil properties and processes. The objective of the field study was to evaluate and compare cocoa production systems and adjacent areas of secondary forest fo r tree species diversity, inflows of leaf litter mass and nutrients, and stocks of nutrients in surface soils. Results indicated that despite slightly lowered tree density and tree diversity compar ed to secondary fore st, traditional cocoa production systems constituted an agroforestry system that closely resembles secondary forest in terms of biomass production and carbon and nutrient inputs to surface soil. 13


14 A laboratory incubation study was conducted to test the ability of the chemical diversity index and chemical identitythe comprehensive chemical fingerprint of individual species by infrared spectroscopyto predict rates of carbon mineralization of species mixtures. Infrared spectral regions were identified that explained as much as 86% of the variation in carbon mineralization of leaf mixtures Chemical diversity as a solo parameter showed no correlation with mixture decomposition, but in conjunction with chemical traits, predicted rates of carbon mineralization when mixtures we re grouped by the presence of a key species. Results suggest that chemical diversity may be most effective in predicting the decomposition of mixtures dominated in quantity or behavi or by a single species.


CHAPTER 1 INTRODUCTION The transformation of plant litter into soil organic matter and the attendant liberation of nutrients form the backbone of the terrestri al biogeochemical cycle. Organic matter decomposition is a complex series of interchange s between plant material, mineral substrate and the decomposer community that is the precursor to an array of ecosystem functions such as the recycling of nutrients from dead to living ma tter that drives ecosystem productivity and carbon sequestration. Confident as we have become in predicting the degradation of litter derived from single species using litter quality parameters such as initial nitrogen (N ) content, or lignin:N ratios, our predictions fail when we apply the sa me relationships to the decay of mixed organic substrates. The departure of mixtures from th e mean response of their individual constituents, known as non-additive effects, signals a gap in our understanding of the mechanisms operating in the breakdown of multiple and single substrates. Given the prevalence of mixed litter decomposition, either in the contex t of multi-species assemblages or differently aged litterfall of the same species, soil organic carbon models that do not incorporat e the phenomenon of nonadditive effects of diverse litte r mixtures are inadequate to pr edict soil C dynamics and potential modifications brought by climate change. The aim of this work was to predict the non-a dditive response of leaf mixtures and to identify the initial chemical traits correlated with them. The effort to define leaf mixture diversity in terms of leaf chemis try led to supporting investigations in the application of diffuse reflectance infrared Fourier tr ansform spectroscopy (DRIFTS) on the relationship between the chemistry of organic matter inputs to soil and soil properties. Las tly, live systems of contrasting tree species diversity of similar climate, soil and annual rates of organic biomass to soil through 15


16 litterfall provided the basis of a field-level compar ison of the effect of litter chemical diversity on soil properties. The role of the definition of diversity on the ability to establish firm connections between litter mixture diversity and deco mposition was addressed in Chapte r 2. A new index of chemical diversity based was introduced based on the chemical composition of constituents within the plant assemblage. Chapter 3 relates an incubation study dire cted at (i) modeling the decomposition of mixtures constructed from the leaves of 10 tropica l tree species, using either the chemical traits of mixture constituents, the chemical diversity of the mixture, or both and (ii) determining the relationship between the non-additive effects of leaf mixtures and th e functional dive rsity of their associated microbial communities. In Chapter 4, the tree species diversity and soil nutrient status of traditional cocoa production systems, representing a low diversity land use was compared to that of proximal secondary forests within the biodiversity hotspot of the Atlantic Rain Forest in Bahia, Brazil. Lastly, Chapter 5 highlights the key findings of the work, notes the inherent limitations of the approaches taken, recommends ways of overcoming them and suggests investigatory pathways to further elucidate the role of plant chemical diversity in te rrestrial biogeochemical cycling.


CHAPTER 2 CHEMICAL DIVERSITY HIGHLIGHTI NG A SPECIES RICHNESS AND ECOSYSTEM FUNCTION DISCONNECT1 Introduction The spatial distribution of tree species, f ungal hyphal networks, intersecting root systems and successions of litterfall ensure that litter inter actions are the rule rather than the exception in forest ecosystems. It is well established that the chemical nature of individual leaf litters affects rates of decomposition, the primary engine of nutri ent recycling in terrestri al ecosystems (Swift et al. 1979). However, the role of plant litter diversity on litter decomposition and nutrient mineralization continues to be the subject of inquiry in natu ral and planned ecosystems of tropical and temperate climate zones (Finzi & Canham, 1998; Rothe &Binkley, 2001; Zimmer 2002; Gama-Rodrigues et al. 2003). To date, studies of dive rsity effects on varied aspects of nutrient turnover have recognized the non-additi ve effect of mixed litte r interactions, but have failed to generalize either the magnitude or direction of the interactions in relation to either the number of species present or to functi onal group richness (Gartner & Cardon, 2004; Httenschwiler et al. 2005). In fact, the recurrent outcome of these works suggests that species identity surpasses species diversity as the ma in driver of decompos ition-related processes (Wardle et al. 1997; Gastine et al. 2003; de Deyn et al. 2004). Furthermore, recent works have shown mixture interactions among even intra-species litters, sugge sting that genetic variations within species leading to litter quality differences may be of equal or greater significance than species designations (Madritc h & Hunter, 2005; Schweitzer et al. 2005). The hypothesis that litter interactions during decomposition stem, in part, from the effects of resource heterogeneity on fungal, bacterial an d arthropod composition and activity is not new 1 This chapter was published in Oikos Volume 116, No. 11, pp. 1831-1840, and is cited as Epps et al ., 2007 in the remainder of the text. 17


(Seastedt, 1984; Chapman et al ., 1988; Blair et al ., 1990). However, the principal approach employed thus far to test this hypothesisgenera ting mixtures by varying species or functional group richnessmay be partly responsible for th e current failure to validate the hypothesis. Two assumptions encumber these experiments. First, species richness is made equivalent to difference in the trait or traits pertinent to the observed activity and, second, this difference is presumed to increase systematically with richne ss. Containing little explicit information of litter quality, diversity values based on taxonomy or growth habit provide little basis for the prediction of biochemically mediated ecosystem functions such as decomposition and mineralization. In the few experiments that define litter mixtures by initial nutr ient concentrations (Hoorens et al. 2003), the problems persist. The sele ction of the grouping characteristic assumes that the characteristic is a driving fact or of the ecosystem func tion under investigation. Furthermore, the criteria used to assign mixtur es into categories based on the chosen nutrient (e.g. high, medium and low concentrations or lowcontrast versus high-contrast mixtures) are arbitrary. While bearing more relevant info rmation than taxonomic cat egorizations, simple classification schemes are nonetheless problematic because they are limited to characterization via a single nutrient. The articulation of a clear relationship between litt er diversity and nutrient cycling processesif it existsrequires a cont inuous variable representative of compositional heterogeneity that is founded on multiple attributes of litter quality. With the future goal of linking plant biodive rsity with ecosystem processes related to nutrient cycling, I explicitly defi ne the functional dive rsity of a litter (or foliar) mixture as the degree of compositional heterogeneity between its constituents. In this paper, I present an index of chemical diversity (CD) to quantify the compositional heterogeneity of litter mixtures as constructed from three main components: 1) the traits used to describe the composition of the 18


members of the set, 2) a coefficient of dissim ilarity based on these traits, and 3) a summary measure of the trait dissimilarity between members. The use of foliar chemical and phys ical attributes as functional traits is an appropriate and rational choice when the function to be described is decomposability. Yet, the selection of traits is not trivial. Within a given climate regime, univariate characteri stics such as total nitrogen (N), phosphorus (P), or lignin:N ratios have been co rrelated to the decomposition of single-species litters (Melillo et al. 1982; Nwoke et al. 2004; Palm & Sanchez ,1991, respectively). However, no single litter quality variable can predict even monospecific decomposition behavior under all conditions (Smith et al. 1998). Similarly, the traits that give rise to litt er interactions may vary according to environmental conditions, making a pr iori trait selection to compute a relevant chemical diversity index a gamble. Further co mplicating the issue, the time and cost of the discrete analyses commonly empl oyed in plant tissue characteriz ation discourage the undertaking of exhaustive chemical inventories for a large number of species. As a solution, I explore diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), as a rapid and cost-effective alternative to a battery of wet chemistry assays. Infrared spectra contain qualitative and quantitative information of inor ganic and organic compounds and improved calibration techniques enable its increasingly effective use to determine nutrient contents and carbon profiles of feeds, manures and soils (Reeves, 1998), and even to predict decomposition patterns of single spec ies and organic residues (Shepherd et al. 2005). Furthermore, DRIFTS is a non-destructive technique that can preserve potentially key information that may be lost in traditional digest s. Coupled with multivariate techniques, such as principal components analysis and advanced linear or non-linea r modeling approaches, DRIFTS 19


may facilitate both the post hoc weighting of suites of traits th at contribute most to chemical diversity, and the identif ication of those that exert more control over litter interactions. The choice is similarly challenging in deriving a single value to expres s the diversity of the selected traits. Recently proposed continuous measures of functional diversity able to accommodate multiple traits are functiona l attribute diversity, FAD2, (Walker et al. 1999); average functional attribut e diversity (Heemsbergen et al., 2004); FD (Petchey & Gaston, 2002) and; quadratic entropy (Rao, 1982; Botta-Dukt, 2005). The advantages of quadratic entropy that recommend it as the basis of a chemical divers ity index are its ability to incorporate relative abundance and pairwise trait differences, its flex ibility to integrate multiple traits, and its insensitivity to the number of species. Raos Quadratic Entropy is defined as the average dissimilarity dij between two randomly selected species i and j from a pool of R species with replacement. The chemical diversity index, CDQ, is interpretable, therefore, as the mean chemical heterogeneity of a mixture, and is calculated as (2-1) ijj R i R j i Qd CD11where i and j are the relative abundances by biomass of species i and j respectively, and dij, the dissimilarity coefficient representing the compositional difference between them. I adopt a standardized Euclidean distance dij, as a dissimilarity coefficient, n k jkik ijtt n d1 21 (2-2) 20


where tik and tjk are the values of chem ical trait k of species i and j respectively in chemical trait space of dimension n. The square root, sum of squa red trait differences, is divided by the number of traits, n, such that the index is not directly affected by the number of traits (Botta-Dukt 2005). At once, it is necessary to consider the follo wing contested properties of quadratic entropy that warrant close attention to its applica tion as a measure of functional diversity: i) The maximum value of diversity is not necessarily reached at uniform frequency distribution of species (evenness); ii) The elimination of species can result in an increase in the diversity value. The mathematical properties of quadratic entropy that delin eate its behavior are well treated in recent works by Shimatani (2001), Izsk and Szeidel (2002), Pavoine et al. (2005) and Ricotta (2005). In summary, the metric used to calculate dissimilarity, dij, dictates the conformity or nonconformity of quadratic entrop y to accepted diversity index axioms. The ideal metric for a well-behaved index founded on Raos quadratic entropy is one that is ultrametric (see Pavoine et al ., 2005). Commonly used dissimilarity m easures in ecology based on rooted trees, such as taxonomic distinct ness (Clarke & Warwick, 1998), or on gene frequencies, as in Neis genetic distance (Nei, 1972), ar e ultrametric. However, the op tions of dissimilarity metrics conducive to continuous, quantitative variables such as nutrient con centrations Euclidean distance, Bray-Curtis coefficient (Bray & Cu rtis, 1957), and the Gower distance (Gower, 1971), for example are not. The unavoidable adoption of a dissimilarity metric that leads to unconventional patterns of func tional diversity with species richness need not discount its validity. Chemical diversity, expressed as a weig hted mean of compositional dissimilarity, lends it great interpretive power of the descrip tion of litter mixtures per unit biomass. 21


The aim of the current study was to observe how chemical diversity changes with species richness and how this relationship varies under diffe ring environments or assemblages. In brief, the study shows that the relationship between chemical dive rsity and species richness suggests that detritivore resource heterogeneity, as represented by chemical diversity, varies within levels of species richness, revealing th e weakness of number of species as a predictor of litter-qualitydependent processes. Moreover, it is shown that species identity can be confounded with chemical diversity such that the presence of a species with unique composition can alter the heterogeneity of a mixture. Lastly, it is also confirmed that the relationship between species diversity and chemical trait diversity for identical species assemblages changes in response to the environmental context. The points discussed below illustrate why predictive patterns of decomposition behavior as a function of richne ss have remained elusive, and how chemical diversity may yield new insight into the nutrient-supplying f unction of plant communities. Materials and Methods Characterization of Leaf Tissue The examples illustrated are drawn from pub lished and recently gathered data from tropical and temperate forest-systems (Table 2-1). For each dataset of R species an R x n trait matrix was constructed and standardized by subt racting the mean trait value and dividing by the mean absolute deviation of each trait before the calculation of the dissimilarity matrix. Leaf traits were designated as the total tissue concentrations of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) expressed as percent of total dry weight. These analyses were chosen for an initial invest igation of the behavior of chemical diversity because they are the most widely published in fo rest mineral nutrition studies, of which very few provide information at a species level. 22


Two methods of chemical characterization, tota l nutrient analysis and diffuse reflectance infrared Fourier transform spectroscopy, were perf ormed on recently gathered material from the Atlantic Forest region of southern Bahia, to asse ss their relative practicality. Freshly fallen leaf litter from 35 year-old, replicated plots of eight native species were collected from the arboretum of the Ecological Station Pau Bras il in Porto Seguro, Brazil (16 23 S 39 11 W). The site is situated on Ultisols derived from Tertiary sedime nts and experiences mean annual temperature of 23C and mean annual precipitati on of 1696 mm. Leaves were dried at 60C for 48 hours and ball milled in a SPEX 8000M Mixe r/Mill (SPEX SamplePrep LLC, Metuchen, NJ). Total N was analyzed by dry combustion and total tissue concentr ations of P, K, Ca and Mg were determined by HCl digestion after combustion in a muffle furnace for 5 hours at 500 C (Miller, 1998). Total P was determined by colorimetry using the molybdate blue method, and total cation concentrations were measured by atomic ab sorption spectroscopy. For characterization via DRIFTS, spectra were obtained from non-d iluted ground samples using a Digilab FTS-7000 spectrophotometer (Varian, Inc., Walnut Creek, CA) equipped with a KBr beam-splitter, DTGS detector, and an AutoDIFF autosampler (Pike T echnologies, Madison, WI). Spectral grade KBr was used as a background. Spectra were collect ed as interferograms at a resolution of 4 cm-1 in the mid-infrared range (4000 to 400 cm-1). Sixty-four scans were averaged to form each spectral signature and expressed in units of pseudo-absorbance (log reflectance-1). Mathematical Treatment of Spectral Data Before statistical analyses, raw spectral data were subjected to baseline and multiplicative scatter correction followed by first derivative tran sformation to minimize variations arising from optical effects due to particle size (Martens & Ns, 1989). Multiplicat ive scatter correction compensates for additive and/or multiplicative eff ects in spectral data. Normalization (samplewise scaling) of data was not used in order to preserve information on the absolute and relative 23


amounts of chemical constituents. Each baseline-cor rected spectral point was treated as a trait and the Euclidean distance between the averag e spectra of each species was calculated as described above. Clustering was performed by the unweighted pair-group clustering method using arithmetic averages (UPG MA). All calculations and gr aphical output were performed using the R environment for statistical computing (R Development Core Team, 2006) and code written by the author. Results and Discussion The CDQ of all possible litter combinations ge nerated from eight species native to the Atlantic Forest characterized by total nutrient co ncentrations (a) and DRIFTS (b) are represented in Fig. 2-1. Each point represen ts a unique combination of species drawn from the total pool, R, at each level of species richness, S, with the num ber of combinations appearing at each richness level determined by the combinatorial R!/S! (R-S )!. In all mixtures, species are present at uniform distribution. Gray points represent mixt ures containing the most chemically distinct species, as determined by the last clustered sp ecies. To permit comparison between the two techniques, the CDQ values were scaled to a 0-to-1 range through division by the maximum value. Juxtaposition of the two forms of characterization demonstrates the effect of trait selection on CDQ. Imbiruu ( Bombax macrophyllum L.), a waxy, broadleaf species, is the most distinct species with respect to total el emental concentrations. In contra st, using DRIFTS distinguishes vinhtico ( Plathymenia foliolosa L.), a legume. DRIFTS is part icularly attractive for chemical characterization for several reasons First, its adoption reduces th e risk of neglecting critical traits that govern litter interactions. Total nut rient concentration profiles do not contain explicit information on carbon, whose forms, includi ng cellulose, lipids a nd secondary compounds, affect leaf decomposability. Furthermore, in a single snapshot, an infrared spectrum can 24


supply a time-dependent biochemi cal definition of substrate avai lability to decomposers that takes into account the shifting importance of litter quality pa rameters over the course of decomposition (Joffre et al. 2001). DRIFTS also f acilitates the use of post hoc statistical regression techniques to identify and assign weights to spectral regions (chemical traits) most accountable for response variables, permitting an optimization process that can determine the maximum contribution of chemical diversity to the observed respons e. Advantageously, this can be accomplished without prior knowledge of the driv ing traits or the covariance between them. Lastly, the inclusion of a greater number of traits, inherent in the employment of DRIFTS, also has the effect of stabilizing computed dissi milarities between species (Ehrlich, 1964) and, consequently, the geometry of the relationship. One of the anticipated features of the chemi cal diversity versus species richness curve is the occurrence of maximum diversity before maximum species richness is reached. This implies that the addition of a species to a collection may reduce the over all chemical diversity of the mixture and, conversely, that species removal may increase chemical diversity (Fig. 2-2). In its relevance to the CDQ, the loss or gain in species is equiva lent to a change in relative abundance because functional diversity is computed across units of biomass and not species, per se. Analogously, the attainment of maximum heteroge neity can occur at abundances outside of evenness as a result of the dissimilarity matrix. This contentious behavior of quadratic entropy reflects a desirable property of the CDQ in terms of exhibiting trait dilution of the mixture. The occurrence of overlapping com position of foliar material means that even the inclusion of a chemically distinct species will contribute to th e homogenization of the assemblage. While not a startling observation (the possibilities of leaf and litter chemistries are constrained by their function as terrestrial plant tissue), the CDQ maximum suggests an upper limit to diversity effects 25


caused by compositional differences. The strength of this feature is that it enables the valid comparison of mixtures across values of speci es richness and across species assemblages because CDQ is a summary of the chemical heterogeneity per unit biomass. The relative abundance of species combined w ith species characteris tics determines the overall substrate heterogeneity as viewed by decomposers (Dangles & Malmqvist, 2004). The addition of an identical species results in a reduction of CDQ because of the increase in that species relative abundance. Predictably, mixtur es that approximate monocultures earn low CDQ values. It should be noted, how ever, that low values of CDQ occur between similar, high-quality species mixes (or high-quality monocultures) as it does between similar low-quality species mixes (or low-quality monocultures) Thus, the index has the capaci ty to isolate the effect of mixture heterogeneity from that of mean mixture quality on obser ved processes, especially at low values of chemical diversity. Another recognizable aspect of the CDQ-richness curve is that of Hustons variance reduction effect (Huston, 1997)the decrease in th e range of diversity va lues with increasing richness as a consequence of overlapping species pool s. Because the rate of this reduction is not the same for all mixtures, it may be interpreted as a characteristic of the assemblage in question. Figure 2-3 contrasts the envelopes of two temp erate forest communities as described by total nutrient concentrations. A slow reduction of the variation in CDQ suggests strong clustering among the member-species su ch that within-group CDQ is very low but across-group heterogeneity is high. Compact curves indicate a more gradual different iation of species (less clustering). Therefore, the cu rve is a restatement of the topology of the cluster dendrogram. Areas worthy of further expl oration include the investigation of the behavior of CDQ under other dissimilarity metrics, as well as the comparison of CDQ with measures of molecular 26


diversity or complexity of litter mixtures. The establishment and monitoring of species assemblages of varying CDQ in litter-mix experiments is the first call to action to test its correlation with quality-dependent ecosystem processes. Experimental Ramification s of Chemical Diversity The variation of functional trait diversity with species richness is fundamental in establishing the species diversity -ecosystem function relationshi p (Petchey & Gaston, 2006). The relationship between species ri chness and chemical diversity c onsistently shows that species diversity cannot act as a proxy for functional diversity (Naeem & Wright, 2003). Therefore, attempts to predict ecosystem functions such as decomposition and mineralization using the number of species ar e inherently doomed. The range in chemical diversity within levels of species richness reveals the weakness of species number to describe litter di versity in the context of detriti vore-mediated processes. This range within species rich ness mimics the wide error bars associated with the responses observed in many litter-mix experiments. Because logistical constraints discourage the inclusion of all possible combinations of species mixtures, an idiosyncratic response to increased richness is highly probable when mixtures are chosen at ra ndom. Even studies base d on additive designs do not offer a failsafe solution because the successi ve addition of species is not guaranteed to correspond with proportional increases in substrate he terogeneity. As a result, investigations of mixtures relying on species richness are encumb ered by both the chemical diversity within richness levels and the non-uniform directionality of chemical dive rsity with increasing richness. Negative, positive and idiosyncratic relationships between chemical diversity and species richness are all possible from additive series of assemblages generated from the same pool (Fig. 2-4a). Assuming that resource he terogeneity elicits a positive (o r negative), linear response of litter decomposition, the results seen to date in litter-mix studie s may be the direct consequence 27


of the choice of a richness gradient as the independent variable. The use of a monotonic independent variable such as chemical divers ity has the potential to yield a consistent unidirectional response of decomposition with litte r functional diversity. The categorical nature of species richness also favors the conclusion that species identity, rather than species diversity, di ctates mixture behavior. As il lustrated, combinations containing the most chemically distinct species tend to e xhibit greater chemical diversity, showing that species identity helps to define mixture diversit y. While unique traits may not be synonymous with unique behavior, the fact th at the addition or removal of a key species may simultaneously result in altered mixture heterogeneity undersco res the importance of appropriate experimental design to gauge the relative influence of species diversity and species identity on nutrient release processes. Monitoring Potential of the Chemical Diversity Index Foliar and litter chemical composition are routinely used as predictors of single-species behavior under specific environmental conditions As a summary of plant community chemical makeup, the chemical diversity index is, by nature, the product of multiple abiotic and biotic interactions, including but not limited to, inter-species genetic differences, inter-specific competition, inherent soil nutrient bioavailability, climate, and, even, herbivory. Beyond the realm of litter decomposition studies, an immediat e and compelling application of the chemical diversity index is that of the monitoring of the chemical diversity of vegetation communities in conjunction with standard biodive rsity inventories. The addition of chemical diversity in diversity assessments permits the comparison of the functional potentia l of assemblages over time and over environmental and climatic gradient s, which species lists cannot provide. Figure 2-5 illustrates the patterns in ch emical diversity versus richness of identical species assemblages 28


occurring over a soil chronoseque nce (Fig. 2-5a) and of different but proximate forest types (Fig. 5b). Figure 2-5a demonstrates th at chemical traits and by exte nsion, functional traits, are not conserved across environments. Therefore, id entical communities, as defined by taxonomical character, are not likely to ex ert the same control on ecological processes in all environments because their relative functions are defined by the very environments in which they are encountered. When mapped on the landscape, such informati on may help reveal broad scale patterns of resource heterogeneity that may impact related ecosystem properties such as detritivore and herbivore communities and activity (Armbrecht et al. 2004; Dehlin et al. 2006; Swan & Palmer, 2006). While mean foliar or litter nutrient con centrations may appear eq ual across systems, how these nutrients are pack aged and distributed among its memb er species has the potential to explain trophic responses inasmuch as they are driven by resource heterogeneity. The value of the chemical diversity index may lie in its ability to monitor the biochemical variability of plant tissue within communities that simultaneously determines both consumer preference and decomposition (Pastor & Cohen, 1997) (See Fig. 5b). The mechanisms that bring about the co-exi stence of species may also determine how species express themselves in the environment (Cardinale et al. 2000; Mouquet et al. 2002). Aboveground species diversity and productivity already show firm positive relationships under conditions of niche differentiation (Tilman, 1999) The effect of the diversity-productivity relationship on foliar and litter chemical compos ition and relative species abundance may play an important role in linking aboveground speci es diversity to belo wground diversity and processes. Because litter a nd foliar properties (species, abu ndance and chemistry) of plant communities vary ontogenetically and seasonally, such aboveground-belowground linkages are 29


necessarily contextually dependent (Blomqvist et al. 2000). The chemical diversity index is a dynamic variable that awaits broad-scale testing and application in varied systems under multiple conditions. The current limitation of the index is the lack of sufficient data with which to determine the statistical significance of diversity differences between mixtures. Due to the variability of composition within species and the propagation of error in the calculation of the index, it is difficult to discriminate levels of chemical dive rsity between assemblages with confidence. This is especially true with increased species richness as the pair-wise error in trait differences is compounded during the computation of the index (Fig. 2-4b). However, for low species richness it is possible to confirm significant differences between mixtures. Yet, the variation of litter/foliar composition within species and even within individuals need not compromise the viability of the chemical diversity index. Rather, it calls for careful and systematic sampling techniques in order to first make credible clai ms to species differences and later to predict responses that may occur as a result. Conclusion The poor predictability of litter species diversity on decomposition processes may be a consequence of our current failure to appropr iately measure litter f unctional diversity. A measure of functional diversity based on species chemical composition, the chemical diversity index, CDQ, is shown to vary within species richness levels, which may account, in part, for the idiosyncratic and species-dependent responses obse rved in early litter-mix studies. The potential for chemical diversity to correlate with species in teractions as they occur in litter-mix studies is tenable because it is derive d from variables known to predict the behavior of individual species. Because of its ability to distill community patterns of foliar nut rient distribution under different environmental conditions, the chemical diversity index may also prove a valuable 30


31 monitoring tool, supplementing existing indices ba sed on taxonomy. Whether chemical diversity can be used to predict how plan t diversity influences environmen tal processes on a larger scale remains to be established.


Table 2-1. Published mineral nutrition studies re porting total nutrient concentrations used to investigate the chemical diversity (CDQ) and species richness relationship. Region Leaf form/ context foliage (f); litter (l) Reference Brazilian Atlantic Forest l, arboretum, tropical lowland rain forest (Montagnini et al. 1995) New Hampshire* f, temperate forest (NERC, 2006) Estonia f, meadow (Niinemets & Kull, 2003) Jamaica f, tropical montane rain forest (Tanner et al ., 1977) Hawaii f, tropical montane rain forest (Vitousek et al. 1995) Data from the MAPBG Project was selected wh ere all five nutrient concentrations (N, P, K, Ca and Mg) were reported and more than three samples were listed. Nutrient concentration values were averaged within each species. 32


33 A B Figure 2-1. Che m ical diversity (CDQ) as a function of species ri chness of eight litter species native to the Atlantic Forest region of southern Bahia as characterized by A) total nutrient concentrations, N, P, K, Ca and Mg, and by B) diffus e reflectance infrared Fourier transfor m spectroscopy (DRIFTS) under equal species distribution. Gray points a r e as sem b lages contain i ng th e m o st chemically dis tin ct spec ies a s illus t r ated in their respective dendrogram s. The m ost chemically dis tin ct spec ies sh if ts f r om im biruu (Bombax macrophyllum L.) to vinhtico ( Plathymenia foliolosa L.) em ploying DRIFTS. Assem blages are shown under assum ption of equal species abundance (This study, 2007).


-20%-15%-10%-5%0%5% Amescla Arapau Arapat Gindiba Imbiruu Jatob Sapucaia VinhticoSpecies RemovedRelative Change From CDQFinal Figure 2-2. The effect of the removal of species from a mixture on chemical diversity under assumption of equal species abundance, and DRIFTS characterization of the assemblage in Fig. 2-1. 34


35 Figure 2-3. The relationship of foliar CDQ diversity with species richness of two different temperate forest communities. A) Est onia, wooded meadow (Niinemets & Kull, 2003); B) New Hamphire, coni fer forest (NERC, 2006). A A B


36 Figure 2-4. The idiosyncrasy of additive studies. A) Negative, positive and idiosyncratic relationships between chemical diversity a nd species richness are possible from three series of additive mixtures derived from the same species pool. B) The same series depicted with error bars (Montagnini et al. 1995). B CDQ 0 0. 1 0. 2 0. 3 0. 4 0. 5 0 6 0 4 8 1 21 6 2 02 4Sp ec i e s R i ch nes s Ne g a t i v e Po s i t i v e I d i o sycr a t i c -0 .2 0 0. 2 0. 4 0. 6 0. 8 1 0 4 8 1 21 6 2 02 4Spec i es R i chne ssCDQ A


37 A B Figure 2-5. Potential of CDQ as a monitor i ng to ol acros s co mm unities. A) Identical species assem blages across a soil chronosequence (Vitousek et a l 1995). B) Different species assem b lages in different environm ents (T anner, 1977). Assemblages are shown under assum ptions of equal species abundance.


CHAPTER 3 THE EFFECT OF CHEMICAL IDENTITY AND CHEMICAL DIVERSITY ON THE DECOMPOSITION OF TROPICAL LEAF MIXTURES Introduction Decomposition of plant litter releases nutrients from dead organic matter and makes them potentially available again for uptake by plants and is a primary conduit of carbon into the soil (Berg & McClaugherty, 2008). In the latter half of the 20th century, concern over accelerated rates of loss of plant diversity and shift in species composition in vegetation communities fueled research into the role of indi vidual species and plant diversit y on ecosystem processes including soil carbon dynamics (Hobbie, 1992; Silver et al., 1996; Hooper & Vitousek, 1998; Daz et al ., 2004; Rodrguez-Loinaz et al. 2008) Gleixner et al ., 1995; Bunker, 2005; Sauer et al ., 2007; Gnankambang et al ., 2008; Schulp et al. 2008). Although the basic factors governing litter decompositionlitter quality, environment, and the decomposer communityhave been recognized for nearly a century (Tenney &Waksman 1929), the decay of mixtures comprising multiple species, which typify most ecosystems, has proven more resistant to generalization (Gartner & Cardon, 2004 ). Understanding the pro cesses involved in the breakdown of mixedspecies litter is important in understanding the role of species diversity in natural ecosystem functioning and in designing agronomic ecosystem s that cycle nutrients and sequester carbon effectively. The usual approach in attempti ng to understand mixed-species decay involves observation of mixtures of species, defined by species or functi onal group richness. This study took another approach that defi ned individual and mixtures of foliar material by chemical identity and chemical diversity based on infrared spectroscopy. Subjugating taxonomic identity for chemical composition, I sought to predict the respiration rates of leaf mixtures. The enigma of mixed-substrate decay persis ts, in part, because of our incomplete understanding of single-substrate decomposition. The principal controls of litter decomposition 38


are climate, soil decomposer community, soil fertil ity and litter physical a nd chemical properties. Under constant environmental conditions of clim ate and soil mineralogy, litter biochemistry is the determinant of litter decomposition (Swift et al ., 1979; Coteaux et al. 1995). Controlling for physical properties such as particle size that contribute to quality (Rovira & Vallejo, 2002), litter chemistry has been shown to dictate litter mass loss (Preston & Trofymow, 2000; PrezHarguindeguy et al. 2001; Raich et al ., 2007), nutrient mineralization rates (Nwoke et al ., 2004) and the composition and activity of the decomposer community (Salamon et al ., 2006). Chemical traits shown to predict single-lit ter decomposition rates in clude C:N, lignin:N, polyphenolic content, and N, P, Ca, a nd, recently Mn concentrations (Aber et al ., 1990; Palm & Sanchez, 1991; Httenschwile r & Vitousek, 2000; Trofymow et al. 1995; Nwoke et al ., 2004; Berg et al ., 2007). However, the relative importance of chemical traits and their relationship with litter decomposition vary with environmental context and, in particular, with site fertility (Vanlauwe et al ., 1997; Seneviratne, 1999). Hence, genera lizations of the relationship between litter chemistry and deco mposition rates of single-species litt er remain understandably coarse. The phenomenon of non-additive effects of mixed-litter decomposition is the observation that when two species decay together, the rate of decomposition of the resultant mixture is not the mean of the rates as weighted by their appearance in the mixture. At times positive and at others negative, the commonness of non-additive effects warns that patterns of individual species are insufficient to predict the decay of litter mixtures (Gartner & Cardon, 2004; Httenschwiler et al ., 2005). Contrasting litter chemistr ies has been proposed to control the interactions observed in mixed litte r decomposition (Seastedt, 1986; Chapman et al ., 1988) and the roster of initial litter characterist ics purported to drive mixed-litter decomposition lignin:N, Ca, P and N concentrationsmirror those that predict single-litter decay (Hu et al ., 39


2006; Liu et al., 2007; Amatangelo, 2008; Gnankambary et al. 2008; Prez-Harguinedeguy et al ., 2008). Characterization of litter mixt ures by contrasting chemical qualities (high versus low C:N or initial N concentrations), as in the studies by Smith and Bradford (2003) and Hoorens et al (2003), offer representations of quality hetero geneity of litter mixtures. However, the shortcomings of this approach are the a priori selection of quality char acteristics that may not be relevant to the response variable under the conditions of the study and the arbitrary classification of high and low nutrient levels. A potential solution to the advance selection of chemical traits is diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) The infrared absorption spectrum of a sample provides a summary of its mineral and organic composition, as molecular bonds absorb energies in proportion to their c oncentration (Stuart, 1997). Extens ive applications of infrared spectroscopy in the analysis of organic compounds has led to the identification of spectral regions and their associated chemical moieties, including compounds releva nt to leaf chemistry and decomposition, such as lignin and cellu lose (Crawford & Crawford, 1980; Card et al ., 1988; Reeves, 1993). Infrared spectroscopy as the basis for the characterization of leaf species and a means for the determination of th e compositional di versity of leaf mixtur es may reduce the risk of omitting litter quality parameters critical to the analysis. Furthermore, the use of infrared spectroscopy in conjunction with the chemical diversity index, a summary of the compositional heterogeneity of species assemblages (Epps et al ., 2007), enables a con tinuous, quantitative metric of the diversity of leaf mixtures. The purpose of this study was to predict rates and non-additive e ffects of microbial respiration on leaf mixtures usi ng chemical identity and chemical diversity and to identify traits 40


or suites of traits that consistently correlated wi th mineralization rates. In seeking to understand the underlying microbial interactions that give rise to litter interactions, I tested the hypothesis that positive non-additive effects (e levated microbial respiration) were correlated with greater microbial functional diversity as defined by community-level physio logical profiling. Materials and Methods Leaf Material Collection and Characterization Fresh leaves were collected from mature trees of 15 species common to th e Atlantic Forest of southern Bahia and the Zona da Mata of Mi nas Gerais in the arboretum of the Federal University of Viosa in the state of Minas Ge rais, Brazil, (20 46' S, 42 52' W; 651 m mean altitude, 21C MAT, 1450-1800 mm MAP) betw een February 2007 and May 2007. Samples were gathered from one to five individuals, t ypically from the lower canopy, and composited, in order to gain sufficient material for subsequent analyses. Leaves were discarded if they were very young, very old or showed signs of excessive herbivory or ot her damage. To remove dust, insects, and foreign matter, leaves were immers ed quickly in a mild detergent solution and the surface residues were loosened by gentle rubbing. Afterward, leaves were quickly submerged in deionized water to rinse away re sidues; blotted dry; loosely pack ed in large brown paper bags; and dried in a convection oven at 65C for 72 hours, then ground to 10 mesh (< 1mm). Petioles were removed before grinding, but the rachis a nd petiolules of compound leaves were included. Ground leaf material was stored in paper envelo pes or small brown paper bags within sealed plastic bags and refrigerated at 4C until analyzed. Total nutrient concentrations of foliar ma terial were determined using combustion followed by an HCl-digest (Miller et al. 1998). Total P was determined by the ascorbic acid reduction molybdate-blue procedure and read for blue color development at 880nm in a 1-cm cell. Total K was determined using atom ic absorption spectroscopy (Perkin Elmer AA200, 41


Perkin Elmer, Inc., Watham, MA) with an oxygen-acetylene flame. Total Ca and Mg concentrations were also determined by atom ic absorption spectroscopy using a nitrous oxideacetylene flame after the addition of 0.25% LaO3 at 1:10 (w:v). Total carbon and nitrogen were determined by gas combustion using a Shimadzu TOC-VCPH Analyzer (Shimadzu Scientific, Columbia, MD). Analyses were performed in quin tuplicate with the inclus ion of NIST standard reference material (SRM) 1545 (peach l eaves) and SRM 1515 (apple leaves). Foliar material was also characterized using di ffuse reflectance infrared Fourier transform spectroscopy in the near-inf rared (NIR: 1000 2500 nm) and the mid-infrared (MIR: 2500 25000 nm) regions. Spectra were obtained on a DigiLab FTS-7000 FTIR instrument (Varian, Inc., Walnut Creek, CA) equipped with a Pike AutoDiff 60-cup autosampler (PIKE Technologies, Madison, WI), and either a KBr beam -splitter and a deuterated trigylcine sulfate (DTGS) detector (MIR) or a quartz beam-splitter a nd indium antinomide (InSb) detector (NIR). Spectra were collected as interf erograms normalized against reference spectra of KBr and sulfur in the midand near-IR, respectively, in order to remove the effects of the detector and the environment (moisture, CO2). Each spectrum resulted from the average of 64 scans taken at a resolution of 4 cm-1 and were recorded in units (1/log reflectance). Spectra were baseline corrected using standard normal va riate correction (Martens & Ns, 1989). In addition to the ten species, 21 leaf mixtures, prepar ed by homogenizing the ground fo liage of two species in equal proportions of dry mass (see Incuba tion Study), were also scanned for a composite spectrum. Calculation of Chemical Diversity Using three separate approaches of chemical characterization of l eaf material (total nutrient concentrations, MIR and NIR spectroscopy) the chemical diversity index, CDQ, a measure of chemical heterogeneity of a mixture (Epps et al ., 2007) was calculated for 21 leaf mixtures (see 42


Incubation Study). The chemical diversity of a mi xture is defined as the mean dissimilarity in chemical traits of two ra ndomly selected species from a mixture of R species ijj R i R j i Qd CD11 (3-1) where i is the relative abundance by dry weight of species i and the dissimilarity, dij, is the Euclidean distance between all n traits describing species i and j (3-2). For this experiment R = 2. n k jkik ijttd1 2 (3-2) Incubation Study In February 2008, a decomposition experiment was conducted to measure the rate of carbon mineralization of leaf mixtures. Ten tropical tree species common to the secondary forests of the Atlantic Rain Forest region in southern Bahia (T able 3-1) were selected for this study from a preliminary study of 15 species. In the preliminary study, 0.5 g of each foliage type was incubated alone in 25 g of soil at 60% field capacity in the dark fo r 30 days at 28C. Treatments were replicated four times. Evolved CO2 was assayed at regular intervals using the base trap method to gauge the relative microbial respiration rates associated with each species. Inga affinis (= INGA), and Balfourodendron reidelianum (= PAUM) exhibited lowest and highest mineralization rates o the 15 species and were. Cecropia sp. (EMBA), displayed a middle response. The remaining seven species were select ed in order to maximi ze the representation of species among vegetation families and to span th e broadest possible range of litter chemical composition as determined by the chemical diversity index of pairs based on MIR characterization. Only one of the spec ies chosen was an exotic species. Artocarpus heterophylla (= JAQU) was included because of its dominance in many secondary forest systems in southern Bahia (Mori et al ., 1983; Sambuichi et al., 2008). Based on these preliminary findings (not 43


reported), 32 treatments were generated: 10 single-species treatments, 21 litter-pairs and a control with no leaf additions (Tab le 3-2). The paired treatments were formed on the basis of the three key species, each one of which was paired with seven companion species. Ground leaves were mixed with acid-washed and rinsed sand (100 mesh) in sterilized, sealed plastic containers in the ratio of 0.500 ( 0.001) g litter to 25.000 ( 0.005) g sand, equivalent to 2.0% OM by dry weight. Quartz sand was used in order to minimize the effects of sorption of nutrients (especially phosphorus). Leaf mixtures consis ted of equal dry mass of each species. To each container, 2.0 ml of inoculant was added (8% gravimetric water content or approximately 60% field capacity). The inocul ant was prepared from a suspension made by incubating 10 g of topsoil with 1 L of sterilize d, deionized water for three days in the dark at 28C. The suspension was vacuum-filtered through a 0.45 m filter, and the resultant filtrate was diluted 1:10 with sterilized deionized water. A control treat ment (sand plus inoculant, no foliar material), and a blank treatment (no sa nd, tissue or inoculant) were included. All treatments were replicated four times. A completely randomized design was used for the placement of microcosms in the incubator. Microc osms were incubated in the dark at 28C, in a forced-air convection incubator (Isotemp, Th ermo Fisher Scientific, Waltham, MA). Microbially respired CO2 was measured by the alkaline trap method at 11 intervals over 80 days (2, 4, 10, 14, 22, 30, 40, 50, 60, 70, and 80 days). A scintillation vial containing 20.0 ml of 0.5 M NaOH was placed in each container. At each time interval, the exposed base traps were removed and capped and the vials placed in sealed containers until titration. Cumulative evolved CO2 was expressed per gram of added carbon, calc ulated as the total dry weight of added substrate multiplied by the loss on ignition. 44


Specific carbon mineralization rates were obtained by fitting the model (3-3) to the change in cumulative CO2 evolved over time, t measured in days. tatCOCum ln)(2 (3-3) The time-dependent rate, k, is equal to the rate constant a divided by the time t Because the quantity, ln t is a constant at a specified time interval and the same for all treatments, the value of the rate constant, a was used interchangeably with the carbon mineralization rate. Microbial Community-Level Physiological Profiling Potential catabolic activity of the microbial co mmunity associated with each of the leaf treatments investigated in the above inc ubation study was assessed using Biolog EcoPlatesTM. Each plate contains 96 wells c onsisting of three replicates of 31 single carbon substrates and a water blank. The wells also contain tetrazolium dye which produces formazan, a blue compound, in proportion to microbial catabolic activity upon the substrate. The catabolic profiles of the incubated treatments were determined as follows: At the end of the 80-day incubation period, a bulked tissue/ sand sample was formed by combining equal dry weight of material from a ll replicates. Under asep tic conditions, 1.0 g of equivalent dry weight of composited litter/sand material into a 50 ml centrifuge tube to which was added 10.0 mL of sterilized 50 mol phosphate buffer solution adju sted to pH 6.5 (the mean pH of foliar extracts used in the study). Each tube was subjected to two vortex/ sonication cycles. This suspension was immediately passe d through a sterilized Whatman GF/C filter to remove large particulate matter and dissolved or ganic carbon and again through a Whatman 0.22 m filter to concentrate the bacteria onto the filter The filter was transferred into a sterilized centrifuge tube and eluted with 15 ml of the same sterilized, pH-adjusted buffer solution. Using this extraction approach, the introduction of carbon sources with the inoculant was greatly 45


reduced. Consequently, the absorbance values read from each well could be attributed more faithfully to the microbial use of the intended su bstrate rather than the use of plant-derived, added substrate. Wells were inoculated with 250 l of microbial extracts. Color development in the wells was quantified using a Victor3 Multilabel Plate Reader (Perkin Elmer, Inc., Waltham, MA) to record absorbance at 590nm. Plates were incubate d in the dark at 28C over seven days and read at time intervals of 0, 16, 40, 64, 88, and 160 hour s. Key species, control, and blank treatments were duplicated. Differences in the microbial biomass supporte d by a food resource are a valid effect of resource quality. Optical density of the control (w ater) well was used as an estimate of inoculum density. To standardize treatme nt responses by microbial biomass, substrate absorbance values were normalized of by that of the water control at each time interval (Compton et al ., 2004). Individual carbon-source utiliza tion was determined at each ti me interval as the mean of replicated normalized absorbance values. Becaus e the rate of substrate utilization is also a critical indicator of the microbial community, the time course of color development for each substrate was incorporated by calculating total s ubstrate use as the trapezoidal area under the absorbance versus time curve for each carbon source (Guckert et al ., 1996). Two measures, average well color developmen t (AWCD) and the Gini coefficient (GINI) were used as summaries of microbial activity th at incorporated all substrates. Average well color development for each treatment was calculated for all time intervals as wi ia AWCD a 93 193 1 (3-4) where a is the absorbance at 590 nm for the ith well, w is the mean absorbance of the water blank and 93 is the total number of wells (Garland & Mills, 1991). Microbial fu nctional diversity was 46


quantified using the Gini coefficient, a measur e of the unequal use of carbon sources. Following Harch et al (1997), the coefficient was calculated as N i N j jia aN GINI11 2a 2 1 (3-5) where ai and aj are the mean absorbance values of wells i and j respectively, and is the AWCD. A Gini value of zero represents and even use of substrates or perfect equality, whereas a Gini value of 1 is perfect inequality (only one substrate consumed). Greater inequality in substrate use is synonymous with decreased f unctional diversity or preferential resource utilization. Thus, a smaller Gini coeffici ent indicates greater functional diversity. Statistics Leaf chemical traits were either discrete analyte concentrations of the selected nutrients or, in the case of spectral characterization, absorban ce values at individual wavelengths. Spectral functional traits, or simply spectral traits, re fer to absorbance at a particular energy level designated by wavenu mber units or cm-1. Spectral traits are henceforth abbreviated in the text as 1/ The effects of species identity and mixtur e composition on initial nutrient parameters; cumulative evolved CO2; C mineralization rates; inoculum density; AWCD; and single-carbon substrate utilization were tested with one way ANOVA followed by pair-wise comparisons of means using Tukeys HSD or, where appropriate, T ukeys HSD test for unequal n. Correlations between leaf chemical traits and deco mposition responses (cumulative evolved CO2, C mineralization constant, net CO2 interaction and mineralization rate interaction) were evaluated using Kendalls Tau. Interactions, or non-additive effects, of the two response variables net evolved CO2 and C mineralization rate, were calculated as the re lative difference between the expected and the 47


observed responses (Wardle et al ., 1997). To estimate the variance of expected values, the average response of all possible combinations of the four replicates of both mixture constituents was calculated. Two-tailed t-tests were used to evaluate the difference between the expected and observed values from zero. Interactions occu rring in substrate utilization profiles were calculated and tested in the same manner. A generalized linear model was used to determine the significance of chemical composition and chemical diversity on the deco mposition of single and mixed treatments. Continuous response variables were final net evolved CO2 after 80 days (net CO2), the carbon mineralization rate coefficient, a, and their respective non-additive effects, I net CO2 and Ia. Mixture composition was defined ei ther categorically by the identities of the key and companion species, or by continuous variables vis--vis one of the three chem ical characterization approaches. All possible oneand two-parame ter combinations of chemical identity and chemical diversity were generated and incorporat ed into linear regression models of the form 21, traittraitfy (3-6) or QCDtraitfy ,1 (3-7) When chemical identity and chemical diversity were incl uded in the same model, both parameters employed the same characterizati on method (i.e. only the NIR-derived diversity index was included in a model with NIR spectral traits). To reduce computational time, regressions were performed on spectra that had been smoothed by averaging every fourth data point. In this manner, NIR spectra were redu ced from 3113 points to 778 points and MIR from 1868 points to 467 points. Successful models were defined as those in which all model parameters were significant at p<0.05 in univari ate analysis and the whole model adjusted R2 exceeded 0.65. 48


Principal components analysis was performed se parately on the covariance matrix of the spectral profiles of single-species litters in the nearand mid-IR regions. Discriminant analysis using the PCA factor scores of the spectra of key and companion species comprising the 21 litter pairs was performed to determine whether spectral information was adequate to classify mixture non-additive effects as antagonistic, additive, or synergistic. Pr incipal components analysis was also conducted on the carbon-source utilization profiles of all 31 lit ter treatments in order to observe the relationships between their respective microbial communities. Discriminant analysis was performed on the substrate-use profiles to determine whether potential microbial catabolic activ ity could differentiate the litter interactions observed in the incubation study. Where necessary, response variables were natu ral log-transformed in order to meet the assumptions of statistical tests. Normality was determined using the Kolmogorov-Smirnov test for normality and homoskedasticity was tested with the Brown and Forsythe homogeneity of variance. When transformation did not succeed in meeting the assumptions, the Kruksal-Wallis non-parametric test for the comparison of multiple means was used. All statistical analyses were performed at significance level =0.05 and were conducted in R (R Foundation for Statistical Computing, 2005) and Statistica 7 (StatSoft, Inc., 2004). Results Species Identity on Carbon Mineralization of Mixtures The ten tropical species selected for this study represented seven families and included leguminous and non-leguminous sp ecies and expressed a wide range of initial nutrient composition (Table 3-1, Fig 3-1) and carbon mineralization rates (Fig 3-5). Each mode of characterization captured a different portrait of chemical quality and, by extension, chemical diversity (Table 3-3, Figs. 3-2 through 3-4). Leaf mixtures with the most contrasting 49


compositions differed by characterization Balfourodendron reidelianum and Plathymenia fololiosa (PVIN) by total nut rient composition; Cecropia sp. and Cabralea canjerana (ECANJ) by MIR; and B. reidelianum and Chorisia speciosa (PAPAI) by NIR (Table 3-3). Identity of the key species was a strong predic tor of leaf-mixture respiration rates (Table 3-6) and the C mineralization of mixtures mirro red the trend observed in the mineralization of individual key species (PAUM>EMBA>INGA) (Fig. 3-6). Interactions between litters were common. Of the 21 litter-pairs, 11 experienced significant interactions in C mineralization rates, eight of them positive (Table 3-7). N on-additive effects in net evolved CO2 changed in both direction and magnitude over time declining along the course of decomposition (Fig. 3-7). As with whole-mixture mineralization rates, in teractions were also correlated with the presence of key species Mixtures containing B. reidelianum showed greater synergistic interactions than mixtures based on Cecropia sp. or I. affinis (Fig. 3-6). Residues of nitrogen-fixing species have been demonstrated to promote the decomposition of litters of poorer quality (Fyles & Fyles, 1993; Rothe & Binkley 2001; Xiang & Bauhus, 2007). Two of the ten base sp ecies were nitrogen-fixers, I. affinis and P. fololiosa (10 pairs). Despite the fact that the nitrogen fixers gene rated the least net microbi al respiration and the slowest C mineralization rates, the ten pairs containing N-fixers exhibited stronger positive nonadditive effects than thos e without (Fig. 3-8). Chemical Identity on Carbon Mineralization of Mixtures A summary of successful models of the 21 litte r pairs appear in Ta bles 3-9 and 3-10. Individual spectral traits from key species and companion species explained as much as 87% of the variation in both net evolved CO2 and C mineralization rate of the 21 leaf mixtures (Table 39). Models that included interaction terms betw een the key and companion spectral traits were not successful according to the criteria. No mode ls based solely on the spectral traits of one 50


mixture component were successful. By contrast, lignin: N of leaf mixtures, based on the ratio of associated spectral peaks from 1515-1500cm-1 (lignin) and 1680-1630cm-1 (proteins) (Reeves, 1993), explained only 71% of mixture car bon mineralization (D ata not shown). Chemical diversity alone supplie d no significant relationships to mineralization rate or net respired CO2. Models incorporating chemical iden tity and mixture chemical diversity as dependent variables showed cl ear relationships for net CO2 and C mineralizati on rates of all 21 leaf pairs (Table 3-10). Under characterization by total nutrient concentrations, a factorial regression model incorporating ch emical heterogeneity and the to tal phosphorus concentration of the key species accounted for 88% of the variability in net CO2 evolved from leaf mixtures. Only the MIR region provided significant spectral traits in conjunction with chemical diversity to explain 67% of variation in C mineraliz ation rate of mixtures (Table 3-10). The same model-building appro ach was applied to subsets of the 21 leaf mixtures, grouped by key species (n=7). When the presence of key species was incorporated into the model, the chemical identity of the companion species and mixture chemical diversity explained as much as 98% of the variation in all four decomposition response variable s, including the strength and magnitude of interactions (Tables 3-11 to 3-13) Figure 3-9 shows a su mmary of the predicted versus observed decomposition response patterns of each pair-group in which the regression results of all successful spectral traitschemical di versity pairings are feat ured in one plot for a given response variable, for succinctness. Discriminant analysis on the PCA factor scor es of the spectra of the key and companion species comprising the mixture successfully classified the 21 litter pairs into three distinct groups by non-additive effect, with a confidence interval of 95% (Table 3-14). Both spectral regions 51


provided sufficient information for discrimi nation by non-additive effect, whereas mineral concentration profile s were inadequate. Identification of Functional Chemical Traits The search for spectral traits th at yielded successful models hi ghlighted distinct regions of the midand near-infrared spectra that correlated with leaf mixture deco mposition. Considerable overlap of the spectral traits correlated with single and mixed litter decomposition occurred, but traits unique to each litte r context (single vs. mixed), and each process, were apparent and, in the case of the dynamic variable, cumulative CO2 released, the spectral traits contributing to successful models and the regression coefficien t associated with the model changed with time (Data not shown). Table 3-15 lists the complete inventory of significant spectral traits contributing to the model y = f(1/ key, 1/ comp) and their associated molecular functional groups. As defined earlier, a spectral trait refers to an absorbance value at a particular location in the infrared spectrum that represen ts the vibrational frequency of molecular bonds. However, it should be noted that outside of pure compounds, there is no unique correlation between a spectral location and a particular functional group due to overlap ping; thus, the functional groups listed here represent the most probable contributors to the absorbance feature. However, when the mixtures were grouped by key species, models formed from companion spectral traits and mixture chemical di versity consistently explained 93%-99% of the variation in net respired CO2 and C mineralization rate (Tab les 3-11 through Table 3-13). The spectral traits contributing to successful models varied for each decomposition response, but most importantly, for each key sp ecies. For example, using CDQ as the index of mixture diversity, net respired CO2 was explained with spectral traits 1/ comp =1258.5 cm-1, 1683 cm-1 and 1143 cm-1 in mixtures of INGA, EMBA and PAUM, respectively. 52


Whether using condensed spectral informati on as represented by latent vectors in discriminant analysis or indi vidual spectral traits, this study provides first evidence that nonadditive effects can be predicte d using litter chemical traits. Microbial Functional Diversity and Non-additive Effects On a per substrate basis, fewer than half of the 31 substrates exhibited significant correlations with net evolved CO2 at 80 days or the C mineralizati on rate constant. Interestingly, significant non-additive responses in the utilization of individual subs trates were also observed. That is, for a mixture comprised of litter A and litter B, the resultant microbial community of the mixture did not behave as the mean response of the original microbial communities, A and B, plus the inoculum. Principal component analysis of the substrate utilization profiles of litter pairs showed strong clustering of mixed-litter communities around that of their key species (Figure 3-12). Discriminant anal ysis of single substrate use wa s unable to categorize treatments by the non-additive effects. Mean carbon utilization (AWCD) of microbi al communities of litter treatments was not significantly correlated with C mine ralization rate and net evolved CO2 of the incubation study. The Gini coefficient of microbial communitie s associated with each litter treatment was negatively correlated with mean substrate use (T able 3-16) suggesting th at greater functional diversity of the microbial community corresponded with low car bon substrate utilization. The Gini coefficient also showed significant, positiv e correlation with C mineralization rate and net evolved CO2 of the leaf-mixtures incubation study, as well as their non-additive effects (Table 316). Thus, decreasing microbial functional diversity was associated with greater mineralization response and positive non-additive effects. In contrast to litter incubation responses, mean carbon utilization was greater in litter pair s associated with th e slowly respiring I. affinis than with either Cecropia sp. or B. reidelianum for nearly all time intervals. Pairs containing I. affinis 53


also exhibited signifi cantly greater substrate-use diversity than Cecropia sp. or B. riedelianum at 64 and 88 hours (Figure 3-13). Discussion Decomposition of mixed species is the rule in agricultural a nd natural environments. The non-additive behavior of heteroge neous substrates has been docu mented for well over a century (Heal et al ., 1995) and although it is accepted that th e simple weighted average of the decomposition response of component species are inadequate to describe the behavior of mixtures, the solution to the mixe d-species effect is forthcoming. This experiment sought to model patterns of microbial resp iration the outcome of substr ate preference and substrate-use efficiency in response to mixed substrates. Given that the richness level of the mixtures observed in this study was constant at R=2, the effect of species richness on decomposition response could not be investigated. However, the wide variation in microbial re spiration in response to substrates that was observed within this richness level (over 200% from the slowest and fastest rates) underscores the weakness in using richness to differentiate mixture behavior when it is evident that composition will play a pivotal role. Importance of Species Identity and Chem ical Identity on Carbon Mineralization Mixed litter behavior was well determined by the deco mposition patterns of their key species (Fig. 3-6), with key speci es accounting for 7% to 73% of the total sum of squares (Tables 3-5 and 3-6). The experiment was designed in anticipation of this result, based on the assumption that under additive effects the mean re sponse of the three groups would be separated by the difference in response generated by the three base-species. However, as stated earlier in the description of the experimental design, the individual performance of Cecropia sp. and B. riedelianum in this experiment did not differ significantly, contrary to the results of a trial run 54


conducted in another soil medium in which C mineralization rate and net evolved CO2 of B. riedelianum was greater. Yet, the behavi or of leaf mixtures founded on B. riedelianum differed significantly from those based on Cecropia sp. Both the mineraliza tion rate and net evolved CO2 of PAUM-mixtures was significantly greater than those of EMBA. Thus, while additive effects of species may be similar due to their expr ess decomposition trajectories, their non-additive effects can significantly diverge. The results corroborate those of Ball et al. (2008) which state that sp ecies identity dictates both additive and non-additive effects. From this, it can be inferred that species associated with non-additive effects should possess qual ity characteristics responsible fo r such effects. Thus it is likely that the underlying cause of species iden tity or mixture composition on the behavior of litter mixtures is the chemi cal nature of the species. While very few published works have used a quantitative measure of the chemical similarity of litter mixtures, a couple of studi es have notably generated mixtures with the awareness of litter quality in mind. Chapman et al ., 2007, in creating mixtures of four temperate tree species comprising conifers and broadleaf sp ecies, found the stronges t synergisms to occur between most similar pairings (conifers). Using diverse orga nic substrates ranging from wood chips to feces, Dehlin et al (2006) found no significant differences between expected and observed values for basal microbi al respiration of organic matt er pairs of obvious contrasting quality. In this experiment, chemical heterogeneity, by itself, showed no si gnificant correlation with mixture decomposition response. The litter pair most similar in composition as assessed by CDQ in all modes of chemical char acterization contained the species Inga affinis and Plathymenia foliolosa (IVIN), which, while showing signi ficant, synergisms in both net CO2 and 55


C mineralization rate, did not display the most dramatic interactions. The next most similar pairing was that of EPAI (neither of thes e leguminous species) which showed only additive effects. Thus, the finding of Chapman et al (2007) that positive non-additive effects are more common among more homogenous mixtures is not generalizable. The mismatch between mass loss as was followed in the Chapman study, and microbial respiration, as followed here may prevent the direct comparison of results. Microb ial respiration is indicative of the rate with which the decomposing soil community utilizes the substrate. B ecause the amount of CO2 respired per unit of carbo n incorporated is a matte r of microbial use efficiency, without direct measure of microbial growth and energy expe nditure through producti on of exudates and enzymes the two cannot be directly correlated. However, in studies in which both mass loss and microbial respiration were m onitored during the decomposition of mixed litters, where mass loss yielded non-additive results, th e same was true of microbial re spiration, i.e. synergies in mass loss corresponded to synergies in microbial respiration (Briones & Ineson, 1996; Bardgett & Shine, 1999). In the present study, chemical diversity a nd chemical identity explained 67% of the variation in net respired CO2. However, two parameters of chemical identity proved better predictors than one spectral trait and chemical diversity (R2=0.86). This is a similar but stronger relationship than that uncove red by to Prez-Harguinedeguy et al (2008) who also constructed significant models of mi xed-litter decomposition using chemical diversity in conjunction with a litter quality trait. In that study, chemical heterogeneity was defined as the coefficient of variation in initial nitrogen and fiber contents, lignin, cellu lose, and hemicellulose, between mixture components. The linear model inco rporating nitrogen content and chemical heterogeneity accounted for 29% of the decompos ition response of 26 litter mixtures containing 56


two to five species under field conditions (litterbags, unground). Their success in constructing a significant model using un-ground foliar material under field conditions provides further evidence that mixture chemical diversity and chemi cal identity are critical functional traits that contribute to determin ing mixture behavior. While not providing successful models for mixe d-litter respiration, total nutrients K, Ca and Mg significantly correlated with net CO2, and C mineralization rate and their interactions (Table 3-4). In their investigation of mixed temperate species Briones and Ineson (1996) found evidence of transfer of Ca and Mg during th e decomposition of eucalyptus when paired in mixtures with oak or ash, both pairs exhibiting enhanced respirat ion. In this experiment, K correlated significantly with minera lization rate interaction which s uggests that elevated transfer of K between species may correspond with increased respiration rate. Which Traits? Over 250 spectral traits were found to be predictors of C mineralization rates, corresponding to polysaccharides, proteins and even water content. The generalization of the predictive capacity of pairs of spec tral traits that formed successful models in this experiment to mixtures of other species is undetermined While the pair of spectral traits 1644 cm-1 and 1428 cm-1 of leaf mixtures provided grea ter explanation of net respired CO2 than lignin:N in this experiment, further studies are required to determ ine whether these two traits, or others, can be used reliably in other contexts. Context dependence of trait signifi cance is restricted not only to conditions of the physical environment (Jonss on & Wardle, 2008) but also to the resource environment. This is to say that while most of the traits are present in some quantity, whether in single or mixed litter situations, for some spectral traits, their relative importance is enhanced by the presence of other traits. That the sets of spectral tra its relevant to net evolved CO2 and mineralization rate were not identical, may distinguish quality char acteristics linked to 57


palatability (recalcitrance) from quality characte ristics associated with the bioavailability of supporting nutrients. Recalcitrance may cause a lag in substrate use as enzymes are produced, consequently suppressing mineralization rates, whereas nutrients availability may allow the greater substrate utilization, which in turn can stimulate microbial grow th and, ultimately, CO2 production. The same is certainly true of spectral traits that are predictors in conjunction with the chemical diversity index. In the case of l eaf mixtures grouped by key species, the suite of critical, mixture-defining traits of the co mpanion species varied with each key species, suggesting species-specific diversity effects. It is interesting to note that for a given spectral trait, the model yielded a positive or negative coefficient. The full implications of this are not yet clear. Yet, it can be speculated that depe nding on the chemical mo iety represented by the spectral trait, the mechanism underlying the deco mposition response may be positively affected by chemical heterogeneity. For example, give n a spectral trait which by itself is a strong predictor, associated with an inhibitor, (a ne gative coefficient), a model showing the significant contribution of heterogeneity may mean that th e effects of inhibitory compounds are mitigated (or intensified) by increased (decreased) complex ity. This might be considered a dampening or dilution effect. For B. reidelianum the relationships between the companion spectral trait and mixture diversity and net CO2 were negative suggesting that any deviation of the companion species away from the indepe ndently rapidly mineralizing, B. reidelianum was likely to result in lowered microbial activity. In contrast, where interactions arise from the transfer of nutri ents or the use of available carbon sources to aid in the degradation of more recalcitrant carbon forms or nutrient poor litters (priming or nurse effect), a pos itive coefficient may appear. Knowledge of the physiochemical 58


quality associated with the spectra l trait as well as the sign of the interaction term between the spectral trait and diversity index as portrayed in the model may provi de clues as to the nature of the mechanism. Because more th an one spectral trait can create a successful model, it can be inferred that more than one mechanism ma y be underway (Httenschwiler, 1995). Within the scope of this study, more cannot be concluded about specific litter quality traits or specific mechanisms triggered from the microbial interactions resulting from these qualities. However, these results hold promise for the ab ility to demystify the underpinnings of mixed substrate behavior in the immediate future. Microbial Underpinnings of Non-Additive Effects In this experiment, the use of ground leaves and its setting in a controlled laboratory environment focused on the activity of the microbi al community as the sole agents of litter decomposition. Litter interacti ons are, in fact, the result of interactions occurring in the microbial community. The response of a community to food resource quality, of which diversity may play a part, can include changes in microbi al species composition, relative abundance and trophic interactions (Little et al. 2008). Plant species identity can also play a signifi cant role in the composition of the microbial community via their influence on the quantity an d quality of carbon reso urce (Carney & Matson, 2006). As observed in the be havior of net evolved CO2 and C mineralization ra te of the 31 litter treatments, the overall patterns of single-C-source utilization were strong ly dependent on the key species. Microbial responses to food resource diversity were non-additive. Based on the assumption that microbial substrate activity is a direct consequence of microbial species demographics, the response of microbial community composition to litter mixtures was also nonadditive. The initial microbial communities of a mixture comprised of species A and B were the community residing on the foliage of species A, plus that of species B, as well as the inoculum 59


derived from the forest soil. In natural envi ronments, this should be expected, each litter bringing with it its associated phyllosphere community and the surface soil community introducing its own members. In this study, microbial composition, as proxied by activity, tended more toward that of the key species (F ig. 3-12). These two obs ervations that plant species dictate microbial compositi on and that substrate diversity affects functional diversity of the microbial community are examples of top down effects of resource on the decomposer food web. In all, these and other results indicate a greater complexity to the microbial response to substrate heterogeneity which may be partitioned into the separate but related effects of litter colonization and resource use. Results of microbial community analysis should be interpreted with extreme caution. Conclusi ons were drawn from a single Bi olog plate for most treatments and where treatments were duplicated, as in the ca se of key species and the blank differences in the response of some wells. The high variation of response observed within the same plate also advises replication of treatments at the plate-le vel. Also, the microbial communities drawn from litter mixtures was extracted at the final stage of the litter incubation st udy and therefore may be identical nor perform analogously to the community present at time zero. Lastly, Biolog results are the consequence of culturable bacteria a nd therefore may not be representative of the communities responsible for actual observed activities on litters. Conclusion The influence of forest species diversity on soil-centered ecosystem processes has taken on increased importance because of the rate at which species composition and distribution of vegetation communities are rapidly changing. Until now, our ability to predict these changes has limited by the fact that the functional traits driv ing litter interactions have not been identified even while these interacti ons are commonly observed. 60


Number of species or taxonomic measures of diversity may be valid for assessing resource use but not resource supply. In terspecies differences and phenotypic differences emerge such that a given species assume different litter tra its and characteri stics under differing environmental conditions, including aboveground plant diversity. Moreover, should species richness prove a good predictor in a particular setti ng, it may not be applicable to other groups of species. Functional traits to de scribe individual speci es and species mixtures relevant to the process being observed are desirable. I hypothesized that a strictly quantitative ap proach of characterizing species identity (chemical identity), as well as mixture dive rsity (chemical diversity), would enable the elucidation of clear, and potentially transfer able relationships between litter makeup and decomposition behavior. The exploration of simple models constructed solely on chemical identity the infrared spectral fingerprint and chemical diversity yiel ded robust relationships with all four process variables. The incorporation of species identity, chemical identity and chemical diversity of mixtures enabled the pred iction the strength and magnitude of interactions. The main questions of the study and their conclusions are: Can interactions and net mixture decompos ition patterns be predicted by comprehensive initial leaf chemistry profiles or mixture chemical diversity? Microbial respiration in response to leaf mixtures was successfully modeled by leaf chemistry of component species and by the foliar chemistry of one species in conjunction with the chemical diversity of the mixture. The use of leaf chemistries (chemical identity) of both mixture constituents provided a model w ith greater explanatory power th an the model constructed with only one species and the mixture di versity. However, when the iden tity of the key species of the pair was taken into account, C mineralization rate, net evolved CO2 and, most importantly, the deviations of these values from the expected were also modeled with th e chemical identity of 61


only one member of the mixture pl us mixture chemical diversity. This is the first time that the direction and magnitude of mixed-litter interact ions have been strongly correlated with leaf mixture chemistry. Which diversity measure and which traits can best model mixture trajectories? All three analytical methods em ployed to chemically characte rize individual leaf species and mixture diversity (total nutrie nt concentrations and nearand mid-infrared spectroscopy) provided successful models of CO2 evolution rates and interactions However, the flexibility and capacity for calibration of both carbon forms and mineral nutrients of mid-infrared diffuse reflectance spectroscopy recommends it over the other modes. Do microbial interactions mirror litter inte ractions over the course of decomposition? Single-substrate use patterns of microbial commun ities extracted from leaf-mixture treatments did not provide ready interpretation of litter interactions. In general, catabolic profiles of microbial communities derived from litter mixtur es clustered around those of the single key species as was observed in the respiration of the litter mixtures, themselves. I hypothesized that strong positive interactio ns would be significantly correlated with high functional diversity. Where correlations were significant, the reverse was true: lower catabolic diversity signifying specialization in substrate use, correlated with greater net CO2 evolution. The implication of this work is that the potential exists for chemical diversity to be used in conjunction with vegetation chemistry to model car bon dynamics in real systems. More explicit representation of litter quality in complex litter sy stems is possible. This can prove a valuable asset in investigating tropical forest systems with high plant species diversity and chemical composition (Httenschwiler et al ., 2008; Townsend et al ., 2008) and even more possibilities arise in landscape level analysis with the adve nt of new technologies to capture snapshots of forest canopy chemical composition as in satellite-infrared analysis (Huber et al ., 2008). The 62


63 representation of litter quality using infrared sp ectra in to model litter decomposition and N mineralization has already been established (Gillon et al ., 1999; Bruun et al ., 2005; Shepherd et al ., 2005). The ability to efficien tly analyze litter chem istry with DRIFTS along the course of decomposition with minimal sample preparation a nd alteration recommends this approach to the investigations of the dynamic asp ects of microbial response to sh ifting litter composition. As with other chemometric an alyses, the calibration of non-additive effects is plausible, in which the decomposition trajectory of a set of litter mixtures can be monitored under the required environmental conditions and used as a training set for unknown, experimental mixtures. Lastly, the interactions of biochemical consti tuents that drive the interactions in rates which in turn may lead to great er understanding of the microbial impetus and general food web. The effect of extrinsic factors the perception of litter quality should follow the approach of Rodriguez-Loinaz et al. (2008) in which soil enzyme activity is investigated with vegetation diversity since enzymes control rates of nutrient cycling processes.


Table 3-1. Initial foliar total nutrie nt concentrations of 10 tropical tree species used in the incubation study. Scientific name Family Abbrev. P (%) K (%) Ca (%) Mg (%) Ash (%) Alchornea sp. Euphorbeaceae DOCE 0.18f 0.98ab 1.21cd 0.04b 6.17b Artocarpus heterophylla Moraceae JAQU 0.13c 1.68c 1.41d 0.06c 12.21f Balfourodendron reidelianum Rutaceae PAUM 0.18f 3.05f 0.96bc 0.21f 10.74d Cabralea canjerana (Vell.) Mart. Meliaceae CANJ 0.11a 1.08b 2.04f 0.09c 8.56c Cassia ferruginea Caesalpinaceae CANA 0.14cd 0.97a 2.23g 0.05b 9.20c Cecropia sp. Cecropiaceae EMBA 0.16e 2.59e 1.39d 0.11d 11.32de Chorisia speciosa Bombaceae PAIN 0.14cd 1.99d 1.98e 0.11d 10.12d Inga affinis Mimosaceae IGA 0.13c 0.96a 0.78b 0.02a 5.40b Lecythis pisonis Lecythidaceae SAPU 0.14cd 0.96a 1.42d 0.19e 9.01c Plathymenia fololiosa Mimosaceae VINHA 0.12b 0.88a 0.28a 0.03a 3.17a Different lower-case letters indicate significant differences in composition be tween species (p=0.05, Tukeys HSD). 64


Table 3-2. Species composition and abbreviation codes of the 21 leaf mixtures observed in the incubation study. Companion Key species species Inga affinis Cecropia sp. Balfourodenron reidelianum Alchornea sp. IDOC EDOC PDOC Artocarpus heterophylla IJAQ EJAQ PJAQ Cabralea canjerana ICANJ ECANJ PCANJ Cassia ferruginea ICANA ECANA PCANA Chorisia speciosa IPAI EPAI PAPAI Lecythis pisonis ISAP ESAP PSAP Plathymenia fololiosa IVIN EVIN PVIN 65


Table 3-3. Chemical diversity indices of leaf mixtures accord ing to the mode of chemical characterization of material: total nutrient con centration (Total), mid-infrared (MIR) and nearinfrared spectroscopy (NIR). Treatment CDQ Total MIR NIR ECANA 0.464 0.462 0.375 ECANJ 0.547 0.846 0.441 EDOC 0.472 0.539 0.697 EJAQ 0.305 0.433 0.644 EPAI 0.262 0.295 0.317 ESAP 0.414 0.675 0.335 EVIN 0.727 0.537 0.576 ICANA 0.463 0.548 0.272 ICANJ 0.472 0.526 0.463 IDOC 0.333 0.382 0.215 IJAQ 0.455 0.473 0.320 IPAI 0.521 0.570 0.738 ISAP 0.499 0.458 0.572 IVIN 0.205 0.252 0.157 PAPAI 0.512 0.538 0.858 PCANA 0.729 0.618 0.465 PCANJ 0.779 0.529 0.468 PDOC 0.634 0.524 0.347 PJAQ 0.583 0.625 0.440 PSAP 0.507 0.368 0.671 PVIN 0.864 0.439 0.412 66


Table 3-4. Kendalls Tau correlation coeffici ent of total nutrient concentrations with decomposition responses of leaf-mixtures. Bold values are si gnificant at p<0.05. Response P (%) K (%) Ca (%) Mg (%) Ash Net CO2 0.200 0.454 0.273 0.303 0.428 a 0.222 0.424 0.303 0.402 0.432 I Net CO2 -0.068 0.231 0.167 0.145 0.249 I a -0.054 0.262 0.235 0.176 0.335 Net CO2 = net respired CO2 at 80 days; a = C mineralization rate constant; I Net CO2 = interaction of Net CO2; Ia = interaction of C mineraliza tion rate where interaction is calculated as the percent difference from expected value. 67


Table 3-5. Summary of re peated measures ANOVA for effect s of mixture composition on net respired CO2 of 21 leaf mixtures at Day 80. Net CO2 df SS MS F p Intercept 1 2258969 2258969 7452.203 0.000000 Key 2 86277 43139 142.311 0.000000 Companion 6 16497 2749 9.070 0.000000 Key x Companion 12 6900 575 1.897 0.0517 Residuals 63 19097 303 Whole model R2 adj = 0.92 (F = 18.09; df = 20; p = 0.00). Table 3-6. Summary of factorial ANOVA for effects of mixture composition on the carbon mineralization rate constant, a of 21 leaf mixtures. a df SS MS F p Intercept 1 145304.0 145304.0 10695.78 0.000000 Key 2 6988.8 3494.4 257.22 0.000000 Companion 6 918.5 153.1 11.27 0.000000 Key x Companion 12 849.3 70.8 5.21 0.000006 Residuals 63 828.7 13.6 Whole model R2 adj = 0.89 (F = 32.5; df = 20; p = 0.00). 68


Table 3-7. Expected and observed carbon minera lization rates and non-additive effect of paired litter treatments in incubation study. Values presented are means standard error, in parentheses. Treatment apair expected apair observed Additive = No interaction ISAP 22.5 (3.3) 24.8 (3.6) ICANA 24.5 (2.3) 29.4 (3.8) IDOC 26.3 (2.5) 27.2 (0.7) ICANJ 30.6 (2.9) 30.3 (2.0) IJAQ 31.7 (8.6) 31.7 (0.4) EDOC 41.9 (2.2) 38.4 (6.0) ECANJ 46.2 (2.6) 42.9 (6.3) PCANJ 47.5 (3.6) 47.4 (1.7) EPAI 53.8 (2.5) 52.9 (4.8) Antagonistic = Negative interaction IPAI 38.2 (2.8) 34.8 (0.8) PAPAI 53.5 (6.2) 48.8 (2.8) Synergistic = Positive interaction IVIN 19.6 (2.9) 25.2 (3.6) EVIN 35.2 (2.6) 39.9 (2.3) PVIN 36.1 (4.2) 44.1 (2.0) ESAP 38.1 (3.0) 52.4 (5.6) PSAP 38.8 (4.8) 49.7 (2.9) ECANA 40.1 (1.9) 52.1 (4.3) PCANA 41.3 (3.4) 51.1 (4.0) PDOC 42.7 (4.1) 55.2 (1.8) PJAQ 44.7 (15.6) 54.6 (3.6) EJAQ 45.9 (11.2) 54.4 (5.0) Non-additive designations were determined by co mparison of the observed and expected values by two-tailed t-tests at p < 0.05. 69


Table 3-8. Summary of fact orial ANOVA for effects of mixtur e composition on interactions of net CO2, I net CO2, and the C mineralization rate constant, I a of 21 leaf mixtures. I net CO2 df SS MS F p Intercept 1 23731.5 23731.52 66.90 0.000000 Key 2 23572.3 11786.15 33.23 0.000000 Companion 6 12100.6 2016.76 5.69 0.000017 Key x Companion 12 8161.6 680.14 1.92 0.033843 Residuals 209 74133.3 354.70 I a df SS MS F p Intercept 1 2993.6 2993.6 26.82 0.000230 Key 2 300.7 150.4 1.35 0.296687 Companion 6 3004.9 500.8 4.49 0.013059 Residuals 12 1339.6 111.6 Whole model (I net CO2) R2 adj = 0.31 (F = 6.2; df = 20; p = 0.000). Whole model (I a) R2 adj = 0.52 (F = 3.7; df = 8; p = 0.021). 70


Table 3-9. Summary of se lected successful models relating chemical identity (1/ ) to net evolved CO2 and C mineralization rate of 21 leaf mixtures. Estimate Std. error t-value p Whole model Net CO2 Intercept -410.3 68.9 -5.95 1.2 e-05 F = 27.1 1/ key (1644 cm-1) 292.1 28.5 10.26 6.0 e-09 df = 2,18 1/ comp (1428 cm-1) 157.1 52.7 2.98 0.008 p =1.6 e-08 R2 = 0.86 R2 adj = 0.85 a Intercept -960.69 92.99 -10.33 5.4 e-09 F = 60.2 1/ key (2315 cm-1) -886.60 84.17 -10.53 4.0 e-09 df = 2,18 1/ comp (611 cm-1) 28.61 9.31 3.07 0.0066 p =1.1 e-08 R2 = 0.87 Radj 2 = 0.86 Model: response = trait1 + trait 2. Table 3-10. Summary of successful models relating chemical identity (1/ ) and chemical diversity (CDQ) on C mineralization rate of 21 leaf mixtures. Estimate Std. error t-value p Whole model apair Intercept -170.1 62.6 -2.72 0.0146 F = 11.3 1/ key (2585 cm-1) -338.3 99.1 3.42 0.0033 df = 3,17 CDQ (MIR) 270.0 126.9 2.13 0.0482 p = 0.0026 1/ key CDQ 421.9 198.3 2.13 0.0483 R2 = 0.67 Radj 2 = 0.61 Model: response = trait1 CDQ. 71


Table 3-11. Summary of successful models of the relationship of chemical identity and chemical diversity on the decomposition re sponses of INGA leaf mixtures (n=7). Estimate Std. error t-value p Whole model Net CO2 Intercept -2126 262 -8.10 0.0039 F = 105 1/ key (1258.5 cm-1) 1865 223 8.36 0.0036 df = 3, 3 CDQ (MIR) 4675 553 8.46 0.0035 p = 0.0016 1/ key CDQ -3880 470 -8.26 0.0037 R2 = 0.99 R2 adj = 0.98 apair Intercept -355.5 65.2 -5.46 0.012 F = 31.9 1/ key (1174 cm-1) 312.0 54.5 5.73 0.011 df = 3, 3 CDQ (MIR) 769.1 136.2 5.65 0.011 p = 0.0089 1/ key CDQ -623.3 114.1 -5.46 0,012 R2 = 0.97 R2 adj = 0.94 I net CO2 Intercept 3508 438 8.00 0.0041 F = 36.3 1/ key (1258.5 cm-1) -2948 372 -7.92 0.0042 df = 3, 3 CDQ (MIR) -7199 923 -7.80 0.0044 p = 0.0074 1/ key CDQ 6061 784 7.73 0.0045 R2 = 0.97 R2 adj = 0.95 I a Intercept 371.5 94.8 3.92 0.030 F = 76.8 1/ key (2531cm-1) 444.9 138.6 3.21 0.049 df = 3, 3 CDQ (MIR) -1110.5 192.1 -5.78 0.010 p = 0.0025 1/ key CDQ -1391.2 277.9 -5.01 0.015 R2 = 0.99 R2 adj= 0.97 Model: response = trait1 CDQ. 72


Table 3-12. Summary of successful models of the relationship of chemical identity and chemical diversity on the decomposition res ponses of EMBA leaf mixtures (n=7). Estimate Std. error t-value p Whole model Net CO2 Intercept -269.4 46.9 -5.74 0.01050 F = 116 1/ key (1683 cm-1) 501.6 49.3 10.17 0.00203 df = 3, 3 CDQ (MIR) 1307.2 103.1 12.68 0.00106 p = 0.0013 1/ key CDQ -1450.4 109.8 -13.21 0.00094 R2 = 0.99 R2 adj = 0.98 I net CO2 Intercept -54.8 40.8 -1.34 0.272 F = 32.7 1/ key (3271.75 cm-1) 194.8 49.3 3.95 0.029 df = 3, 3 CDQ (MIR) -555.3 115.2 -4.82 0.017 p = 0.0086 1/ key CDQ 433.7 120.2 3.61 0.037 R2 = 0.97 R2 adj =0.94 Model: response = trait1 CDQ. Table 3-13. Summary of successful models of the relationship of chemical identity and chemical diversity on the decomposition res ponses of PAUM leaf mixtures (n=7). Estimate Std. error t-value p Whole model Net CO2 Intercept 1752 210 8.34 0.0036 F = 26.4 1/ key (1143 cm-1) -1308 171 -7.66 0.0046 df = 3, 3 CDQ (MIR) -2607 371 -7.03 0.0059 p = 0.0177 1/ key CDQ 2192 298 7.35 0.0052 R2 = 0.96 R2 adj = 0.93 apair Intercept 520.7 54.8 9.50 0.0025 F = 36.2 1/ key (1135 cm-1) -394.4 44.6 -8.84 0.0031 df = 3, 3 CDQ (MIR) -772.9 93.0 -8.31 0.0037 p =0.0074 1/ key CDQ 649.2 75.2 8.63 0.0033 R2 = 0.97 R2 ad j = 0.95 Model: response = trait1 CDQ. 73


74 Table 3-14. Discriminant analysis of non-additive effects obs erved in the C mineralization rates of 21 leaf mixtues, performed on the first four PCA factor scores of the spectra of key and companion species in the mid(MIR) and near-infrared (NIR). Region = MIR ADD SYN SYN D = 7.015 F(6,13) = 3.999 p = 0.017 ANT D = 15.945 F(6,13) = 3.141 p = 0.039 D = 26.292 F(6,13) = 5.747 p = 0.006 Region = NIR ADD SYN SYN D = 5.711 F(6,13) = 3.256 p = 0.035 ANT D = 17.920 F(6,13) = 3.529 p = 0.027 D = 26.278 F(6,13) = 5.272 p = 0.006 Distances are the squared Mahalanobis distance. ADD= additive; SYN=synergistic; ANT=antagonistic.


Table 3-15. Spectral traits of key spec ies (MIR) contributing to su ccessful models of litter-pair decompos ition processes and their potential physiochemical interpretation. Trait (cm-1) Functional group Litter quality Trait (cm-1) Functional group Litter quality Trait (cm-1) Functional group Litter quality Trait (cm-1) Functional group Litter quality 3649.5 2462 1706 1413 CH2, CH3 (1450-1375) alkanes 3642 2454 1698 1405 3634 2446 1690.25 C=O (1705-1685) aliphatics, unsaturated 1397 3588 2438.75 1683 1390 3580 2431 1675 1382 3572.25 2423 1667 1374 3565 2415.25 1659.75 1366.5 3557 2408 1652 1359 3549 2400 1644 1351 3541.75 2392 1636.25 1297 3534 2385 1629 1289 3526 2377 1621 C=O (1680-1630) N-H (1650-1640) N-H (1640-1550) N-H, (1640-1550) amides 1282 3518.25 2369 1613 1066 3511 2361.5 1582.5 1019.25 3503 2354 1575 1012 C-O-C (1300-1050) C-O (1200-1020) esters, alcohols 3495 C-O, NH (3600-3200) alcohols, phenols, amides, amines 2346 1567 1004 2546.75 2338 1521 973 2531 2331 1513 965.25 2523.5 2323 1505 (1509) lignin 958 2516 2315 1498 950 2508 2307.5 1490 765 2500 2300 1482 757 2492.75 2292 C C, C N, S-H, (2600-2100) alkynes, nitriles, thiols 1459 749.5 2485 1775 1451 742 2477 1767.75 1428 734 2469.25 OH (3400-2500) C C, C N, S-H, (2600-2100) carboxylic acid 1760 1420.5 CH2, CH3 (1450-1375) alkanes 726 CH, CH (1000-650) CH (900-650) alkenes, aromatics Values in plain text are spectral traits shared by C mineralization rate and Net CO2. Bold values are significant contributors to models of Net CO2 only. Bold, italicized values indicate spectral traits significant for C mineralization rate onl y. Adapted from Barbosa (2007) Table 3-1. 75


Table 3-16. Kendalls Tau correl ation between microbial functional diversity (Gini coefficient) and mean substrate use of 31 EcoPlate subs trates and the decom position responses of mixed leaf treatments. Bolded valu es denote significance at p < 0.05. AWCD Rate Constant, a Net CO2 I a I Net CO2 Gini -0.588 0.432 0.505 0.242 0.500 76


B A Figure 3-1. Diffuse refl ectance infrared spectra of 10 litter species. A) Mid-infrared spectra; B) Near-infrared spectra. 77


B A Figure 3-2. Chemical diversity (normalized to the maximum value) of all possibl e mixtures of 10 selected tropical species as a function of species richness, as characte rized by total nutrient con centrations. Each point re presents a potential litter mixture. Points in blue are mixtures that contain the most chemically distinct species. Nested dendrograms show the clustering of species by their compositional sim ilarity as characterized by the approach. 78


B A Figure 3-3. Chemical diversity (normalized to the maximum value) of all possibl e mixtures of 10 selected tropical species as a function of species richness, as characteri zed by mid-infrared spectroscopy (MIR). Ea ch point represents a potential litter mixture. Points in blue are mixtures that contain the most chemically distinct species. Nested dendrograms show the clustering of species by their compositional sim ilarity as characterized by the approach. 79


80 Figure 3-4. Chemical diversity (normalized to the maximum value) of all possibl e mixtures of 10 selected tropical species as a function of species richness, as characteri zed by near-infrared spectroscopy (NIR). Each point represents a potential litter mixture. Points in blue are mixtures that contain the most chemically distinct species. Nested dendrograms show the clustering of species by their compositional si milarity as characterized by the approach B A


Figure 3-5. Carbon mineralizati on of ten individual tropical sp ecies and the control treatment (no litter addition). Error shown is SE. 81


B D C A Figure 3-6. The effect of key species on decom p osition responses after 80 days. A) net evolved CO2; B) C m i neralization constant, a ; C) percent deviation f r om expected evolved net CO2 (net C O2 inte rac tion ) and; D ) pe rcent d eviation from expected C m i neralization rate constan t (rate in tera c tion). 82


Figure 3-7. Dynamic nature of non-a dditive effects on cumulative evolved CO2 between litter pairs over the course of incubation A) afte r 30 days; B) after 80 days. Asterisks (*) denote significant interactions at confidence limit = 0.95. 83


B A Figure 3-8. Interaction effect s of nitrogen-fixing and non nitroge n-fixing leaf m i xtures. A) Net CO2 interac t ions; B ) C m i neraliza t ion rate inte r action s. 84


Figure 3-9. Predicted versus obs erved interactions occurring in C mineralization rate constant and net evolved CO2 (Day 80) of the 21 mixed-litter tr eatments. Predicted values are the result of linea r regression analysis of the form (response ~ 1/ comp *CD) when separated by key species. The predicted valu es represent all successful models for the respective decomposition response variable A) C mineralization rate constant interaction; B) Net CO2 (Day 80) interaction. 85


C A B Figure 3-10 a. Chart of spectral traits, one each f r om key and com p anion species, contributing to successful models of the for m response ~ 1/ key + 1/ comp where response is net evolved CO2 (Day 30). A) The intersection of key-species and com p ani on-species spectr al tra i ts; B ) Spectr al traits of th e key species and the co efficient of determ inatio n (R2) of the associated m odel; C) Spectral traits of the com p anion species and the coefficient of determ ination (R2) of the associated m odel. 86


Figure 3-10b. Chart of spectral traits, one each from key and companion species, contributing to successful models of the form response ~ 1/ key + 1/ comp where response is net evolved CO2 (Day 80). A) The intersection of key-species and companion-species spectral traits; B) Spectral traits of the key species and the coefficient of determination (R2) of the associated model; C) Spectral traits of the companion species and the coefficient of determination (R2) of the associated model. C B A 87


B C A Figure 3-11. Chart of spectral traits, one each fro m key and com p anion species, contributing to successful models of the for m response ~ 1/ key + 1/ comp where response is the carbon m i neralization rate constant, a A) The intersection of key-species and com p anion-species spectral traits; B) Sp ectral traits of the key species and the coefficient o f determ ination (R2) of the associated m odel; C) Spectral traits of the com p anion species and the coefficient of determ ination (R2) of the associated m odel. 88


Figure 3-12. Principal components analysis of the single-substrat e utilization profile of the 31 microbial communities litter treatments extracted from the final time step the incubation study. 89


90 Figure 3-13. Mean substrate use (AWCD) a nd functional diversity (GINI) of microbial communities extracted from 21 litter-pair treatments grouped by key species, as determined by Biolog Ecoplate community-lev el physiological profiles analysis. A) 64 hours; B) 88 hours; C) 160 hours. B C A


CHAPTER 4 TREE SPECIES DIVERSITY AND NUTRIENT CYCLING POTENTIALS OF SMALLSCALE CACAO PRODUCTION SYSTEMS AND SECONDARY FOREST FRAGMENTS IN SOUTHERN BAHIA, BRAZIL Introduction Cacao production is limited to three principal growing regions in the world Africa, Latin America and Southeast Asia and occurs near ly exclusively in the worlds zones of high floristic and faunal diversity, the so -called biodiversity hotspots (Myers et al ., 2000). The area of south Bahia, imbedded in the Atlantic Ra in Forest, may be the most environmentally significant region of cacao production in the worl d due to its high plant and animal endemism and its rapidly shrinking area (Donald, 2004; Thomas et al ., 1998). According to some accounts, less than eight percent of the original cover of the Atlantic Forest remains and these persist as isolated fragments in an agricultural and increas ingly urbanized landscape (Morellato & Haddad, 2000). While forest fragmentation can adversel y affect tree species and structure through geometry, isolation and disturbance (Hill & Curr an, 2003), the floristic diversity of Atlantic Forest remnants remains high (Tabanez & Viana, 2000; Thomas, 2003). Despite the encroachment of urban and agricultural developm ent, 300 new species and five new genera were reported between 1978 and 1980 (Dean, 1995). Within the heart of Brazils Cacao Coast a hot zone of floristic diversity was recently recognized as supporting th e second greatest tree species density in the world (Martini et al ., 2007) and discoveries of new plant species remain unabated (Barneby & Grimes, 1994; Thom as, 1997; Amorim, 2002; de Oliveira et al ., 2004; Goldenberg & Amorim, 2006). Traditional cacao production, locally known as cabruca an agroforestry system characterized by selective thinning of the forest understory prio r to the establishment of cacao seedlings (Rice & Greenberg, 2000) comprises roughly 70% of cacao production in southern 91


Bahia (Arajo et al ., 1998). Since the economic blows d ealt to the region by declining cocoa prices in the world mark et and the introduction of Moniliophthora pernciosa the fungal pathogen causing witchs broom disease, the gran d plantation system of cacao that had shaped the culture and economy of southeastern Bahia gave way. Large fazendas were abandoned, converted to pasture or sold to the government as part of a plan of land reform (da Fonseca et al ., 2003). The result is that today, small-scale producers with average land-holdings of < 10 ha significantly outnumber larg er plantations (Landau et al ., 2003). Cabrucas role as the destroyer or preserver of forest cover has been the focu s of many discussions centered on regional forest conservation strategies (Vinha & Silva 1982; Alger 1998; Greenberg, 1998; da Fonseca et al ., 2003). Yet, sufficient scientific evidence to support the claims of sustainability and biodiversity of cabrucas, especially in the c ontext of increasingly ba lkanized land-holding is still lacking. At the same time, secondary forests are increas ingly the most prevalen t forest type around the globe (Brown & Lugo, 1990). The FAO estim ates that degraded secondary and heavily logged forests constitute 60% of the worlds fore st cover (FAO, 2005). Si nce the arrival of the Portuguese to Porto Seguro in s outhern Bahia, the Atlantic Ra in Forest of Brazil has been reduced to 2-8% of its original cover (CIT). In 1974, primary fo rest accounted for 7.03% of total land use whereas secondary forest and cabruca co mprised 12.62% and 3.84%, respectively, of land use in southern Bahia (CEP LAC, 1976). Recent geographical a ssessments of the district of Ilhus, the center of Brazils cacao producing region, attribute 68. 3 thousand ha (40%) of its land cover to cacao, and 26.75% to areas of conservation or preservation (Santana et al ., 2003). Excluding environmental protection zones, natural forest fragments in the district account for a meager 5% of land cover, as es timated by optical methods (Saatchi et al ., 2001). Even as the concept of pristine native forests is being challe nged, the diminishing area of native forests 92


necessitates the better understa nding of the interac tions occurring in the broad array of ecosystems termed secondary forests. Efforts to conserve endangered species and to restore vanishing forest cover in the Brazilian Atlantic Forest highlig ht the role that economically significant activit ies, such as traditional shade-cacao production, can play in restoring and maintaining ecosystem services formerly supplied by native forest (da Fonseca et al ., 2003). While several studies have been recently undertaken on the structure and diversity of shade-cacao systems in southeastern Bahia (Schulz et al ., 1994; Sambuichi, 2002; Sambuichi & Hari dasan 2007) few studies have focused on small-holder cacao systems which comprise the majority of cacao production (see Machado et al ., 2005) and even fewer on the status of the sec ondary forests in their proximity (see Lobo, 2007). Given the dominance of secondary forests in the landscape over pr imary forest in the region, the monitoring of secondary forests is essential in order to provide a reference for more managed agroforest systems and to question the valid ity of the use of secondary forests as such a reference. Studies of species diversity and nutri ent cycling of both system s at the level of local management are integral to inform conservati on strategies of both secondary forests and cabrucas to deliver ecosystem services such as so il conservation, carbon a nd nutrient storage and habitat afforded by floristic biodiversity, as we ll as economic services generated by cacao and non-timber forest products. The objectives of this study we re: 1) to assess differences in floristic composition between cabrucas and secondary forest 2) to determine the overall inputs to and stocks of nutrients and to the soil and lastly, 3) to co mpare the tree diversity and nutrient cycling status of forests fragments with primary forests as depicted in the literature. 93


Materials and Methods Site Selection and Characterization The study sites were located within the Projeto Assentamento Frei Vantuy, an agricultural settlement occupied by a former landless community in the district of Ilhus, Bahia, (14 48 09 S, 39 07 54 W) situated alongside the principal highw ay connecting Ilhus and Itabuna (Fig. 41). The native vegetation of the area has been categorized as lowland Southern Bahian Wet Forest and displaying the classi c rain forest structure of em ergent, canopy, understory and herbaceous layers (Thomas, 2003). A mean annua l temperature of 23.3C and rainfall between 1800-2000 mm (CEPLAC, 2006), without a distinct dry season classify the region as Af under the Kppen climate system. The settlement resides on a patchwork soils and contain the Itabuna and CEPEC soil units classified in the Brazilian and U.S. taxonomic systems as Alissolos Crmicos (Typic and Orthoxic Hapludults) a nd Luvissolos Crmicos (Typic Hapludalfs), respectively, and in the low lying areas Neo ssolos Flvicos (Typic Tr opofluvents) (Santana et al ., 2003). With the exception of the Fluvents, these soils are unusually high in inherent fertility relative to other soil t ypes in the district and as such are prime areas for cacao production. The Frei Vantuy Settlement was established in 2003 by 33 families as a part of the national program of agrarian reform. The settlemen t, totaling 479 ha comprises 159 non-contiguous hectares of forest reserve, of which, approximately 80 ha is forest in various stages of regeneration. The land is partitioned among the families. As decreed by law, each landholder must set aside a percentage of his or her holdings to forest cover. The primary appeal of this site was the nature of the community small-scale, family-owned cacao systems, in contrast to larger, plantation systems. Furthermore, the proximity of the community to the research and extension activities of the campus of the State University of Santa Cruz (UESC) as well as that of the Executive Commission on the Cacao Management Plan (CEPLAC) suggested that the 94


growers have been exposed to and sensitized to programs on the environmental education, the importance of the maintenance of forest cover an d diversity. As such, the secondary forests in this study were assumed to be representative of best-case management scenarios. Eight paired plots were chosen to encompass a range of soil properties (Table 4-1) and topographies occurring in the site with the stipula tion that forest and cacao plots were as close as possible and reasonably mature (> 50 years old) (Fig. 4-2). Plot history and management were determined from interviews w ith the landholders and corroborate d with long-term residents and workers from the area. Individu al study plots of 50 m x 50 m were demarcated within the forest and cabruca sites (Figs. 4-3, 4-4) to investig ate tree community composition, nutrient delivery through litterfall and soil nutrient stocks. Plot s were subdivided into 25-10 m x 10 m sub-plots to facilitate the inventor y and sampling processes. Species Inventory and Tree Diversity The common name and occurrence of trees and palms with stems 5 cm DBH (height = 1.3m) within each site were firs t identified with the aid of a know ledgeable local farmer raised and residing on the grounds of th e settlement. Tree cuttings were collected and used to identify trees to the family, genus and, where possible, to the species level, with the consultation of the herbarium of CEPLAC. Voucher specimens were not catalogued. Trees classified as unknown were used only in stem density counts and not in the enumeration of species richness. For two of the forest fragment plots, JR and VR, the family and stem size of all individuals was recorded to determine tree horizontal structur e. The complete area (2500 m2) of VR was surveyed for diameter class distribution but, due to time cons traints, only 6 of the 25 subplots in JR (600 m2) were measured. 95


Forest Floor Standing organic matter was harvested in April/ May 2005 and again in November 2005. Forest floor was sampled by a random toss method. For each plot, ten subplots were chosen beforehand by a random number generator. A 50 cm x 50 cm metal frame was thrown within each selected subplot and all matter within the frame was collected with the aid of a knife. Material was dried at 60C for 48 hours, weighed and averaged to calculate the dry weight of standing biomass per hectare for each plot. The re moval and burning of floor material in May is common practice in cacao production systems in preparation for cacao harvest. Forest floor measures were taken prior to clearin g in all plots except one (VIC). Litterfall Production Wooden collection boxes of internal area 1.0 m2 were constructed with nylon mesh bottoms with openings of 1 mm2, resting 20 cm above the ground. Ten boxes were evenly distributed in a regular grid formation in each 0.25 ha plot and rotated every two weeks to maximize area coverage. Material was collect ed bi-weekly, dried at 60C for 48 hours and weighed. Soil Nutrient Status Soil was sampled within each of the 2510 m x 1 0m subplots at each site. Ten soil samples were taken with a soil corer from the 010 cm depth and bulked to create a single sample for each subplot. Composite soil samples for each site were gene rated by combining aliquots of equal weight from the 25 subplot samples after air-drying and si eving to < 2 mm. For composite-plot samples, particle size distribution was determined by the hydrometer method (Gee & Bader, 1986); pH was determined in H2O (1:2 soil to solution ratio) and 1.0M KCl (1:2 ratio) using a glass electrode pH meter; and exchangeable cations by ammoniumacetate extraction (CSIRO 1985). Gr avimetric water content was determined by drying the soil 96


at 105C for 24 hours. Total nutrient concentratio ns (P, K, Ca, Mg, Zn) were determined at the sub-plot and whole plot levels using the sulfuric acid peroxide di gest method (Gasparatos & Haidouti, 2001). Phosphorus in the extracts wa s determined colorimetrically by the vanadium blue method, and the absorbance of the blue co lor was read at 725nm (Olsen & Sommers, 1982). Calcium and magnesium were determined by at omic absorption (Perkin Elmer AAnalyst 200, Perkin Elmer, Inc., Waltham MA), using an ac etylene-nitrous oxide flame after addition of 0.25% w:v La2O3. Potassium concentrations were determined using atomic absorption spectrometry with an oxygen-acetylene flame. For each study plot, a 1-kg composited soil sample was formed from all 25 s ubplots. In triplicate, a 250g subsam ple was sieved into four size classes (<53 m, 53-150 m, 150-250 m and 250 m-2 mm) by dry-sieving for 5 minutes using a mechanical shaker. Each size cl ass was weighed for size-class di stribution and further analyzed for total P and loss on ignition (L OI). LOI was determined by combustion at 400C for 16 hours in order to remove organic matter. Th e low temperature was set to minimize the dehydroxylation of clay minerals (Nelson & So mmers, 1996) during the co mbustion of organic matter. Total C and N of whole, composited soils were determined by dry combustion on a Shimadzu TOC-V total carbon and n itrogen analyzer equipped with an SSM-5000A solid sample combustion unit (Shimadzu Scientific Instruments, Columbia, MD). Statistical Analysis Within plot species diversity as described by Margalefs diversity (DMG), and the Shannon information index (H ) were employed in order to assist the comparison of species diversity across studies. While imperfect in compensati ng for differing sampling intensities and areas (Magurran, 2003), both measures in corporate richness and number of individuals and provide a better alternative to the direct co mparison of richness values. Jacca rds similarity coefficient was used to compare the similarity of species composition within cabruca systems and secondary 97


forest plots. Differences betw een the eight study plots in soil and litter nut rients, and litterfall and standing biomass were determined by one-w ay analysis of variance (ANOVA) followed by Tukeys Honestly Significant Differences test (HSD). Comparisons of measured parameters between the two land uses were performed using the two-tailed, paired Students t-test. Where necessary, data were log-transformed to conform to the assumptions of normality and homogeneity of variance; if transformed data failed to meet the required assumptions, the Kruksal-Wallis ANOVA and median test were used to distinguish differences between plots and the Wilcoxon signed rank test was used to separa te differences between land uses. Significant differences in monthly litterfall rates and seasona l standing biomass within plots and within land uses were also determined using dependent t-test s. All statistical analyses were performed at a 95% confidence interval using STAT ISTICA 7 (StatSoft, Inc., 2004). Results and Discussion Tree Density and Species Inventory Stem density, species richness and diversity of all cabruca and forest plots are summarized in Tables 4-2 and 4-3. In all, 733 individua ls representing 41 species in 23 families were identified within the four cacao systems obser ved. Cabrucas were dominated by Moraceae, Araliaceae, Anacardaceae, Fabaceae and Urticaceae. Within the secondary forest sites, 1108 individuals were surveyed, comprising 96 species from 35 families. Excluding palms, Moraceae, Araliaceae, Lauraceae, Lecythidac eae and Fabaceae dominated secondary forest assemblages, with the species Arthocarpus sp., Didymopanax morototonii and Eschweilera ovata constituting 37% of the individuals encountered. Stem de nsity in the cabruca averaged 183 and 44 individuals 5cm DBH per 0.25 ha with and wi thout cacao, respectively, and 277 individuals in secondary forest Given the same sampling effort s in both land uses, cabrucas presented one-third the number of species found in adjacent forest fragments. These findings are 98


consistent with those of Rolim and Chiarello (2 004) which showed depre ssed species richness in areas of cabruca relative to lesser disturbed fore st. Of the 38 native species observed within the cabruca systems, 30 coincide with species observed in the combined plots of secondary forest, or approximately 30% of native species encountered in secondary forest sites. This result has implications for cabruca systems acting as a potentia l seed source for adjacent secondary forests. Compared to published reports of other cacao production systems in the region (Table 46), the cabrucas observed here are typical. On a per hectare basis, the tree density encountered in these systems was over twice that as in cab rucas reported by Hummel (1995) and Sambuichi (2002) with the same size limit. However, in a survey of cabrucas located approximately 40 km from the study site, 35 to 133 ind. ha-1 10 cm DBH excluding cacao were observed (Alves, 1990 as cited in Sambuichi, 2002), suggesting that the stem density of cabrucas in the present study were sparse in comparison. With regard to tree species diversity, th e cabrucas observed in this study were relatively impoverished, as meas ured with and without the presence of cacao H avg = 2.64 0.09 and H avg = 1.17 0.08, respectivel y. According to recen t literature, the least floristically diverse cabruca system in the regi on is an abandoned cabru ca site (O1) with a Shannon diversity value, H = 3.31 (Sambuichi & Haridasan, 2007). Cabrucas established in another former landless community settlement, potentially similar in parcel size as those experienced in this study still demonstrated hi gher diversity values with the inclusion of cacao, where Shannon diversity H = 1.86 (Machado et al ., 2005). Among themselves, the four cabrucas were dissimilar in floristic composition. High variability in tree density and species diversity and composition are trademarks of agroforestry systems and reflect not only environmental controls such as geography and c limate, but also land-ow ner preference and land management history (Schroth & Harvey, 2007). 99

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The distribution of plant families in cacao syst ems differ markedly from that of typical Atlantic Forest. Myrtaceae, Sapotaceae, C aesalpinaceae, Lauraceae and Chrysobalanaceae comprise the five most important species in nativ e south Bahian moist fore st in terms of stem density and basal area (Mori et al ., 1983). In an assessment of three local cabruca systems, Fabaceae, Moraceae and Lecythidaceae emerged as the most important families by stem density and basal area (Lobo, 2007). Dominance by Moraceae due to Ficus spp. as observed in the sites of this study is common to disturbed areas (Sambuichi & Haridasan, 2007). However the reestablishment of Myrtaceae, Sapotaceae and Chrysobalanaceae and their attendant shadetolerant species in aban doned cabrucas suggest that cabrucas have the capac ity to regenerate and revert to a state closer to th at of primary forest with tim e (Sambuichi & Haridasan, 2007). Several measures indicate that the secondary forest sites observed in this study were under or recovering from disturbance (Table 4-3). Total stem density (1108 ind. ha-1) was lower than primary forest in the region but within the ra nge of other secondary forests and fragmented systems of lowland humid Atlantic forest. Native stands, an example of which is a site in the Serra do Conduru State Park, he ld as many as 2450 ind. ha-1 (Martini et al ., 2007) in the same diameter class limit. Based on the size distributi on of the two forest frag ments JR and VR (Fig. 4-5), the frequencies of stems exceeding 10 cm DBH were 138 and 148 ind. 0.25 ha-1, (or 550 and 598 ind. ha-1) respectively, compared to 891.26 ha in the nearby Una Biological Reserve (Mori et al ., 1983), and 493-842 ind. ha-1 in montane tropical forests in upper Amazonia (Gentry, 1988). Other secondary forests of the Atlantic rain forest exhib it densities in the range of 800 ind. ha-1 (Elias Jr., 1998). Declines in stem density from interior forest to fragmented forest to forest edge to secondary fo rest correlate with increased forest disturbance (Santos et al ., Oliveira 100

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et al ., 2008). The relative spar seness of the observed secondary si tes relative to interior primary forests in the region alludes to a history of disturbance in the secondary sites. In the currency of species richness, the obs erved secondary forest sites (44-57 species 5 cm DBH per 0.25 ha; H avg = 2.74 0.18, DMGavg = 8.45 1.22) were impoverished relative to other patches of secondary forest. In the same diameter class limit, Elias Jr. (1998) catalogued 106 individuals in 800 species (H =3.96); at 15 cm DBH fragments in middle and advanced stage exhibited tree diversity in dices 3.16 and 3.77, respectively. In contrast, a site of primary forest within the Serra Grande National Park, less than 50 km away from the study sites, held 2450 stems 5cm DBH and 458 species in one hectare (Thomas et al., 2008) and in the Una Reserve, 178 species in 600 sa mpled individuals were catalogued in one hectare (Mori et al ., 1983). These two native sites rende r Margalef diversity indices of 58.6 and 27.7, dwarfing the most floristically diverse of the secondar y forest sites observe d in this study (DMG=10.26). The crowning glory of the region is the Serra do Conduru State Park where 144 tree species 5 cm DBH were inventoried in 0.1 hectare. (Martini et al ., 2007). Considerable overlap in the co mposition of forest species enc ountered in this work and in the published species rosters of secondary and pr imary forests in the re gion cited above was evident. Despite their proximity, secondary forest sites exhibited low floris tic similarity (Table 43) a phenomenon regularly observed in native stands. Spatial heterogeneity of vegetation species is the outcome of multiple factors including hi story and geography which determine the regional species pool, as well as the inte ractions between plan t and animal species (Ricklefs, 1987). Human intervention also plays a pa rt. The presence of exotic plan tation trees would be expected in cabrucas, due to their historic al economic importance in the region; however the impact of introduced species on un-managed forested systems was striking. Exotic sp ecies appearing in all 101

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secondary forest areas were dend palm (Elaeis guineensis N. J. Jacquin), and jackfruit ( Artocarpus heterophyllus Linn.). Jackfruit accounted for the majority of all stems in three of the four secondary forest plots, accounting for 20-26 % of the individuals counted Jussara palm ( Euterpe edulis Mart.) was the most dominant sp ecies, appearing in all four forest sites, and comprising be tween 6% and 23% of stems. Didymopanax morototoni was the second most frequently occurring sp ecies and alongside other pioneers, Tapirira guianensis and Pterocarpus violaceaus are indicative of early succession stands (Santos et al ., 2008). Of the four secondary sites, JR situated in the largest forest fragment appeared to be of least disturbance as evidenced by the greater presence of shade tolerant species such as Sloanea obtusifolia Virola gardneri Mabea occidentalis (Santos et al ., 2008), the high density of jussara palm, an economically lucrative and ecologically threatened species (Matos & Bovi, 2004), as well as the relatively low frequency of introduc ed species. In contrast, the site VR appeared to be the most disturbed site with 51% of its basal area dominated by jackfruit. Litter Production, Standing Biomass Mean monthly litterfall produced from Se ptember 2005 to August 2006, which included leaves, branches, flowers, fruits and seeds, was 0.81 0.32 Mg ha-1 in areas of cacao production, and 0.80 0.32 Mg ha-1 in secondary forest. The peak pe riod of litterfall in cabruca systems corresponded to the leaf-drop cycle of cacao trees in October. Forest systems also experienced peak litterfall from October th rough December, in accordance with the observations of native forests by Mori et al ., (1983). On an annual basis, the am ount of litterfall was statistically insignificant between cabruca and secondary fore st, but rates of monthly deposition differed between the land uses (Fig. 4-6). Annual litterfall rates for the two systems were 9.45 0.25 Mg ha-1 and 9.42 0.25 Mg ha-1 in cabruca and forest, respectively. Equal rates of organic inputs within the two systems are interesting in light of the fact that the stem density of cabrucas was 102

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significantly lower than forests. These rates ar e within the range observed for lowland tropical rain forests, annual 5.5 to 14.4 Mg ha-1 (Greenland et al ., 1992) and cacao production systems in Brazil, 9.0 and 14.0 Mg ha-1 when cacao was shaded with Erythrina or Ficus (de Oliveira Leite & Valle, 1990). The amount of standing litter material in ar eas of cabruca and secondary forest areas was 5.6 0.3 Mg ha-1 and 5.9 0.8 Mg ha-1, respectively for the mont h of May 2005 and 5.4 1.1 Mg ha-1 and 4.9 1.7 Mg ha-1 in November (Fig. 4-7). These two periods represent six months and one month after the peak leaf-drop period. With the exception of one plot (JC), no significant seasonal differences in standing biomass appeared within individual plots and no significant differences between land-uses were found. Nutrient Inflows through Litterfall Litterfall is one of the principal mechanisms for the transfer of nutrients into the soil. While nutrients are extracted from cabruca systems thr ough seed harvest, much is returned through litter. Litter nutrient concentra tions of both cacao and secondary fo rest sites reflect the relatively high nutrient status of the soils on which they are situated (Table 4-7). Total P and K concentrations of secondary forest foliar litter were two to three times th at of the mean total P and K concentrations of native species assemb lages on coastal tabuleiro soils (Montagnini et al ., 1995; Silva 1990). Cabruca li tterfall was nutrient rich in comparison to sec ondary forest sites for elements P, K, and Mg. However, in conjuncti on with litter biomass, only annual rates of P addition through litterfall showed significant diffe rences between the two systems. Again, cabrucas exceeded total P inputs relative to secondary forests at a rate of 6.2 0.3 kg ha-1 yr-1 versus 4.4 0.3 kg ha-1 yr-1. Because litter nutrients were assessed only once with material gathered over the course of a year, it was not possible to obs erve the probable seasonal 103

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differences in inputs which may occur as a function of both litter biomass and litterfall concentrations. Soil Nutrient Status Total nutrient concentrati ons in surface soil from the 0 to 10cm depth differed significantly between cabruca and se condary forest systems with respect to P, Ca and Mg. Bulk densities of paired plots were assumed equivalent and concentra tions directly comparable. This could be attributed to the addi tion of fertilizers to boost cacao production. Th e most commonly used fertilizers are superphosphate or triple superphosphate which would augment both P and Ca levels. Liming is also recommended at the rates 2,000 kg ha-1 yr-1 for clayey soils and 1,000 ha-1 yr-1 for sandy soils (Chepote et al ., 2003). However, according to the land proprietors, no additions of fertilizer or lime were applied after the establishment of cacao seedlings and each plot is at least 50 years ol d. Calcium and magnesium wh ich did not exhibit significant differences in annual inputs through litter be tween the two land uses nonetheless exhibited greater accumulation in cabruca soils, suggesting a history of the use of the calcareous amendments. Despite the possibility of fertiliz ation at low levels within the cabruca systems, it is also likely that the extra P supplied to cabrucas deri ves from the litter of cac ao itself, as supported by the greater quantities entering into the soil as litter. Phosphorus sufficiency is commonly observed in cacao agroforestry systems (Ofori-Frimpong et al ., 1999). The difference in Mg levels observed between the land uses may also arise from the surface deposition of cacao leaves. Annan-Afful et al (2004) found significantly greater concen trations of Mg in cacao leaves and of exchangeable Mg in cacao-plantation topsoi ls than in other land uses along a toposequence which included primary forest, fallow, mi xed cropping, and traditional rice farming. 104

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Significantly greater organic matter concentr ations were also demonstrated cabrucas relative to secondary forest. De spite the observation th at total inputs of OM through litterfall do not differ on an annual basis between the two systems, the concentration of soil organic matter in the whole soil and in all soil pa rticle size fractions of cabru ca systems surpassed that of secondary forest. Figure 4-8 illustrates the distribution of organic material among soil aggregates of varying size. For both land uses, the greate st quantity of organic material resided in the largest size fraction (250 m to 2.0 mm), while the highes t concentrations consistently appeared in the smaller fractions (not shown) a common trend. Higher soil Ca content may facilitate OM sequestration and the formation of Ca-hum ic compounds in cabruca soils. Proper design and management of agroforestry systems, including cabruca, can make them effective carbon sinks (Montagnini & Nair, 2004). Based upon th e rate of carbon inputs through litterfall, standing biomass and th e total quantity of carbon in the so il, cabruca as managed in this region is as effective at C se questration as secondary forest. In cacao systems of southern Cameroon, soil carbon levels exceeded that of secondary forest (Duguma et al ., 2001). Similar trends were documented in West African cacao plantations that after 25 years approached the litterfall production rates and soil carbon stores of primary forest (Annan-Afful et al ., 2005; Isaac et al ., 2005). However, as important as the quantity of carbon stored is, so is its long-term stability. Soil organic matter is afforded physical or chemical protection from microbial degradation via three principle mechanismsits inherent biochemical recalcitrance, associ ations with surface minerals, and occlusion within soil aggregates (Sollins et al ., 1996; Six et al ., 1999). Assuming for a moment, similar litterfall chemistries between the two land uses, the greater partitioning of SOM to smaller soil size fractions in secondary forests may mean greater stores of more stable 105

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carbon. Even in forested sandy soils where the fo rmation of aggregates is weak compared to soils richer in clay, showed that with decreasing particle size, th e greater the energy required to access the associated organic matter and th e greater protection afforded (Sarkhot et al ., 2007). More work in determining the re lative stability of the carbon pr esent in cabrucas and secondary forests is necessary. Conclusion The predominance of secondary forests warran ts deeper understandi ng of their nutrient dynamics and species composition to ensure wise use and management for future generations (Ewel, 1979). In the specific cas e of the Atlantic Fo rest which also suppo rts the cacao producing region of southern Bahia, the regeneration of primary forest may be beyond reach, but a functioning and profitable mosai c of cabruca and secondary fore st (Rolim & Chiarello, 2004) is presently attainable. Realizing this goal re quires the acknowledgment of and reconciliation of potentially competing conservation goals. The results of this study show that despite slightly lowered tree density and tree diversity compared to secondary forest, traditional cacao production presen ts an agroforestry system which closely resembles secondary forest in terms of biomass produc tion, carbon inputs and nutrient delivery. Because these results show that lowered floristic diversity of cabrucas can maintain or increase stocks of soil carbon as s econdary forest, it is crucial to distinguish the importance between the potentially conflicting ecosystem services of enhancing floristic diversity (and by extension w ildlife diversity) and carbon sequ estrationthe two additional commodities often promoted in environmentally-conscious cacao products. Future research efforts should include landscape-level models on the effect of different degrees of forest fragmentation interspersed with cabrucas and agricultural activities to establish critical limits beyond which various ecosystem se rvices such as wildli fe habitat, carbon 106

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sequestration, water are (Cassano et al ., 2008). Understanding the spec ific thresholds to each particular ecosystem service will enable a more informed discussion of the trade-offs between increasing productivity and economic ambitions and biodiversity goals (Franzen & Mulder, 2007). Threats to secondary forests and fragments of varying stag es of regeneration include selective extraction, fragmenta tion, and biological invasion (Ph illips, 1997). Evidence of all three activities was apparent in the fragments investigated in this study. Connectivity with healthy forest is essential to ma intain secondary forests. Proxim ity to native forest stands is crucial as decay, degradation, and in reverse, recovery, is dependent on dispersal factors (Cardoso da Silva & Tabarelli, 2000). However, recovery, as measured by forest structure and tree species diversity can take on the order of 300 years (Liebsch et al ., 2008). Addressing the problems instigated by edge effects and forest se paration is crucial to la ndscape regeneration and the maintenance of forest landscape (Laurance et al., 2002; Santos et al ., 2008). The severe fragmentation observed in this study with many forest fragments < 0.5 ha may be a common occurrence in the cacao growi ng region of southern Bahia, and may accelera te with the settlement of hundreds of families in the movement of land reform. It is therefore critical to consider the management practices or partitioning of land within land settlements as part of a broader landscape management plan. It is important to note that th ree significant reserv es lie within 50 km of the study sites the Una Biological Reserve, Serra do Conduru State Park and the Se rra Grande National Park. If at their best cabrucas reflect the historical diversity of th e region and are recipients or benefactors of local diversity sources, the disa ppearance or fragmentation of these refuges will precipitate the decline in the diversity of cabruca systems as well. 107

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108 Programs that promote environmental certification in a similar vein as organic certification have been proposed to encourage the adoption of practices such as reduced weeding in cabrucas to allow the recruitment of native forest species (Bed et al ., 2007). While such measures could prove beneficial, the local farming communities and environmental policy makers should first articulate priorities of ecosystem services fo r solutions to forest degradation and economic stagnation to be effective.

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Table 4-1. Soil chemical properties and particle size distribution of cacao and secondary forest study sites in the Assentamento Frei Vantuy, Ilhus, Bahia, Brazil. Site pH Coarse sand Fine sand Silt Clay Base saturation 1:2 (H2O) 1:2 (KCl) % Dry weight % Cacao JC 5.1 4.3 21.2 15.1 25.3 38.4 39.9 EVC 5.1 4.5 13.5 11.6 23.1 51.8 47.3 AC 5.3 4.9 22.2 12.9 31.5 33.4 70.2 VIC 5.1 4.5 48.7 19.2 16.9 15.2 57.1 Secondary forest JR 4.7 4.0 22.0 19.6 25.2 33.2 16.4 BR 4.9 4.6 32.4 16.9 23.0 27.7 62.6 BBR 5.0 4.8 27.9 16.3 24.4 31.4 67.3 VR 4.4 3.9 64.5 20.7 6.1 8.7 22.9 Site names were formed by the name of the propri etor (e.g. J= Josadabes; EV= Joo Evangelista; A= Aldienor; B= Brito; V=VI= Virgnia) and la nd-use type (C= Cacao/ Cabruca; R= Forest Reserve). 109

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Table 4-2. Summary of the floristic diversity of four cabruca sites (0.25 ha) located in the Frei Vantuy Settlement, Ilhus, Bahia, Brazil. Va lues in parentheses represent diversity parameters excluding cacao. JC EVC AC VIC No. of individuals 172 (41) 182 (37) 201 (59) 178 (40) No. of species 18 (17) 21 (20) 24 (23) 16(15) Margalefs Diversity Index 3.31 (4.58) 3.85 (5.54) 4.34 (5.40) 2.89 (3.80) Shannon Information Index (H ) 1.14 (2.59) 1.05 (2.92) 1.42 (2.77) 1.05 (2.29) Pielous Evenness Index (J ) 0.39 (0.90) 0.35 (0.96) 0.45 (0.88) 0.38 (0.85) Jaccards Similarity Coefficient JC EVC AC VIC -0.26 0.19 0.21 0.26 -0.19 0.21 0.19 0.19 -0.22 0.21 0.21 0.22 -Site names were formed by the name of the proprietor (e.g. J = Josadabes; EVC = Joo Evangelista; A = Aldienor; VI=Virgnia) and land -use type (C = Cacao/Cabruca). Stem densities include unidentified species. Diversity para meters do not include unidentified species. 110

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111 Table 4-3. Summary of the floristic diversity of four secondary forest s ites (0.25 ha) located in the Frei Vantuy Settlement, Ilhus, Brazil. JR BR BBR VR No. of individuals 308 301 260 239 No. of species 46 44 46 57 Margalefs Diversity Index 7.88 7.55 8.13 10.26 Shannon Information Index (H ) 2.85 2.49 2.87 2.76 Pielous Evenness Index (J ) 0.79 0.66 0.75 0.67 Jaccards Similarity Coefficient JR BR BBR VR -0.22 0.18 0.17 0.22 -0.38 0.20 0.18 0.38 -0.23 0.17 0.20 0.23 -Site names were formed by the name of the prop rietor (e.g. J = Josadabes; B =BB= Brito; V = Virgnia) and land-use type (R = Forest Reserve). Stem densiti es include unidentified species. Diversity parameters do not include unidentified species.

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Table 4-4. Phytosociological parameters (excluding cacao) of cabrucas in southern Bahia observed in other studies. Author Location System Area (ha) DBH (cm) Stems Species H Sambuichi, 2002 Fazenda Novo Horizonte, Ilhus-BA, 14 37 S, 39 16 W Cabruca 2.6 5 138 41 3.35 Hummel, 1995 Fazenda Serra Grande, Ilhus-BA, 14 45 S, 39 14 W Cabruca 2.6 5 145 40 NA Sambuichi & Haridasan 2007 Ilhus-BA, 14 41 -14 44 S, 39 09 -39 12 W O1 O2 O3 N1 N2 Cabruca Old Old Old New New 3 10 47 158 175 102 355 46 85 113 82 180 3.31 3.34 3.99 3.54 4.22 Lobo, 2007 Fazenda Pau Brasil, Ibirapitanga-BA, 14 10 S, 39 24 W Fazenda Bom Retiro, Pira do Norte-BA, 13 48 S, 39 24 W Fazendo Vapor, Ubat, BA 14 13 S, 39 3 W Cabruca 1 15 152 120 180 43 36 52 3.29 3.24 3.97 NS= Not specified Stem densities in cabruca systems do not include cacao Results reported on a per hectare basis; point-centered quarter method 112

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113 Table 4-5. Phytosociological paramete rs of forest fragments in southern Bahia, observed in other studies. Author Location System Area (ha) DBH (cm)Stems Species H Lobo, 2007 Fazenda Nova Esperana, ItapBA, 14 10 S, 39 24 W Fazenda Marinda, Jussari-BA, 15 11 S, 39 30 W 2 Forest Medium Advanced 1 15 80 249 35 72 3.16 3.77 Elias Jr., 1998 Veracruz Florestal Ltd., Eunapolis-BA, 16 22 S, 39 34 W 2 Forest 1 5 800 106 3.96 Martini et al ., 2007 Serra do Conduru State Park, Bahia, Brazil Old growth forest (OGF) Old logged forest (OLF) Recently logged forest (RLF) 1 Forest 0.1 4.8 254 263 253 144 137 134 NS NS= Not specified; NA= Not available Stem densities in cabruca systems do not include cacao Results reported on a per hectare basis; point-centered qu arter sampling method

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Table 4-6. Tree species ( 5 cm DBH) identified in the selected study areas of cabruca and secondary forest in the Assentamento Frei Vantuy, Ilhus, Bahia, Brazil. Occurrence Family/ Scientific name Common name 2 Forest Cabruca ANACARDACEAE Anacardium occidentale L. Cajueiro vermelho 1 Tapirira sp. Pau-pombo 14 Astronium sp. Aroeira 1 Spondias sp.1 Cajarana 2 Spondias sp. 2 Cajazeira 6 15 ANNONACEAE Duguetia magnolioidea Maas. Bacumux 6 2 Guatteria sp. Pindaiba preta 7 Xylopia sp. 1 Pindaiba 5 Xylopia sp. 2 Pindaiba vermelho 2 APOCYNACEAE Aspidosperma sp. Piti 2 Himatanthus sp. Janauba 5 Macoubea guianensis Aublet Pau de leite 1 ARALIACEAE Didymopanax morototoni Decne & Planch. Matatauba 59 17 ARECACEAE Bactris sp. Tucum mirim 8 Elaeis guineensis N.J. Jacquin Dend 98 Euterpe edulis (Mart.) Jussara 163 Polyandrococos caudescens (Mart.) Bur 1 Syagrus oleracea Pat 11 BOMBACEAE Eriotheca macrophyllum Imbiruu 5 1 Hydrogaster sp. Bomba de gua 1 BORAGINACEAE Cordia sp. 1 Baba de boi 1 Cordia sp. 2 Claraiba 6 2 BURSERACEAE Protium sp. Amescla 12 CARYOCARACEAE Caryocar sp. Pequi doce 1 CHRYSOBALANACEAE Couepia sp. Oit 1 114

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Table 4-6. Continued. Occurrence Family/ Scientific name Common name 2 Forest Cabruca CLUSIACEAE Garcinia sp Oland 2 Symphonia sp. Landirana 1 Tovomita sp. Mangue 15 COMBRETACEAE Terminalia brasilensis Ara da gua 2 ELAEOCARPACEAE Sloanea obtusifolia Gindiba 5 1 ERYTHROXILACEAE Erythroxylum sp. Peroba-rosa 10 EUPHORBIACEAE Cnidoscolus marcgravii Pohl. Peno 1 Hyeronima alchorneoides Cajueiro 2 1 Mabea sp. 1 Cambreau 7 Mabea sp. 2 Cambreau mirim 2 Tetrorchidium rubruvenium Coarana brava 3 1 FABACEAE (CAESALPINOIDEAE) Apuleia sp. Jita-peba 1 Arapatiella sp. Arapat Caesalpinia ferrea leiostachya Pau ferro 1 1 Cassia multijuga Cob 6 16 Copaifera sp. Pau leo 1 Tachigalia multijuga Ingauu 6 1 Zollernia sp. Mocataba 1 FABACEAE (MIMOSOIDEAE) Inga affinis Ing cipo 2 2 Inga sp. 1 Ing 4 Inga sp. 2 Ing vermelho 1 Pithecolobium polycephalum Monz 1 FABACEAE (PAPILIONOIDEAE) Andira sp. Angelim 1 Erythrina sp. Eritrina 2 Lonchocarpus sp. Cabelouro 1 Machaerium angustfolium Vog. Sete cascas 15 2 Pterocarpus sp. Pau sangue 3 2 FLACOURTIACEAE Banara sp. 1 Carpotroche brasiliensis Sapucainha 1 115

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Table 4-6. Continued. Occurrence Family/ Scientific name Common name 2 Forest Cabruca LAURACEAE Cryptocarya sp. Louro cravo 33 5 Nectandra sp. 1 Louro canela 1 Nectandra sp. 2 Louro graveto 3 Nectandra sp. 3 Louro sabo 11 7 Nectandra sp. 4 Louro verdadeiro 6 Nectandra sp. 5 Louro bosta 1 LECYTHIDACEAE Cariniana sp. Jequitib 1 Eschweilera ovata (Cambess.) Miers Biriba 47 Lecythis lurida (Miers.) Mori Inhaiba 2 Lecythis pisonis Cambess. Sapucaia 1 1 MALVACEAE Sterculia chicha (St. Hill) Samuma 35 1 Theobroma cacao Cacaueira 6 556 MELASTOMATACEAE Miconia sp. 1 Mundururu 13 1 Miconia sp. 2 Mundururu branco 3 Miconia sp. 3 Mundururu ferro 3 3 Miconia sp. 4 Mundururu folha de lixa 5 Miconia sp. 5 Mundururu tresquinha 2 Tibouchina sp. Mundururu vermelho 2 MELIACEAE Cedrela sp. Cedro-rosa 4 Guarea sp. 1 Carrapeta 5 Guarea sp. 2 Cedro cabacinha 2 1 MONIMIACEAE Mollinedia sp. Caf preto 28 MORACEAE Artocarpus sp. Jaqueira 195 30 Brosimum sp. Conduru 13 Ficus sp. Gameleira 1 Ficus insipida Willd. Gameleira-branca 2 2 Ficus gomelleira Kunthe et Bouch Gameleira-preta 5 3 Helicostylus sp. Amora 2 Sorocea sp. Amora branca 1 MYRISTICACEAE Virola gardnerii Bicuba 1 116

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Table 4-6. Continued. Occurrence Family/ Scientific name Common name 2 Forest Cabruca MYRTACEAE Eugenia sp. 1 Batinga 4 Eugenia sp. 2 Murta 5 1 Eugenia sp. 3 Murta branca 11 5 Eugenia sp. 4 Murta preta 4 1 Psidium sp. Ara branco 3 Syzygium aromaticum Cravinho 1 NYCTAGINACEAE Guapira sp. Farinha-seca 15 OLACACEAE Olacaceae sp. 1 POLYGONACEAE Coccoloba sp. P de bolo 1 2 RUBIACEAE Genipa americana Jenipapo 5 2 Rubiaceae sp. Pau cravo 2 RUTACEAE Citrus sp. Tangerina 1 Zanthoxylum sp. Paparaiba de espinho 3 8 SAPINDACEAE Cupania sp. Camboat 9 SAPOTACEAE Manilkara sp. Parajuzinho 1 Manilkara salzmanii Maaranduba 1 Pouteria sp. 1 Abiu da mata 5 Pouteria sp. 2 Bapeba 3 1 SIMAROUBACEAE Simarouba sp. Paparaiba 30 10 ULMACEAE Trema micrantha Curindiba 1 URTICACEAE Cecropia sp. Embauba 1 14 Pouroma guianensis Aubl. Tararanga 1 UNIDENTIFIED Unidentified sp. 1-3 6 Unidentified sp. 4-9 48 Total 1108 733 117

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Table 4-7. Mean total nutrient concentrations of surface soil (0-10cm) and litter and total annual input of nutrients through litterfall in traditional cacao systems and adjacent secondary forest sites in the Assentamento Frei Vantuy, Ilhus, Bahia, Brazil. N P K Ca Mg Cabruca Soil (ug g-1) 336.6* (5.1) 102.0 (5.1) 621.8* (27.5) 521.8* (25.4) Litter (% dry weight) 0.064* (0.002) 0.43* (0.05) 1.46 (0.09) 0.37* (0.03) Litter (kg ha-1 yr-1) 6.24* (0.45) 42.04 (5.74) 141.33 (9.16) 35.77 (2.00) Secondary Forest Soil (ug g-1) 248.2* (11.2) 92.9 (4.3) 439. (26.7) 284.6* (12.1) Litter (% dry weight) 0.046* (0.003) 0.31* (0.03) 1.46 (0.19) 0.28* (0.05) Litter (kg ha-1 yr-1) 4.42* (0.20) 30.02 (3.17) 141.74 (22.40) 26.23 (4.06) Error reported in parentheses is SE. Values ma rked with an asterisk represent significant differences between land uses at P< 0.05. 118

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Ma p s c o urtes y of Faria Filho & Ara u j o 2003Figure 4-1. Location of study are a a m ong land use types in the m unicipality of Ilhus Bahia, B r azil. 119

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1 km 6 5 4 3 1 2 1 Josadabes Cabruca (JC); Josa dab es Fores t R eserve (JR ) 2 Britos Forest Reserve (BR); Br itos Second F orest Reserve (BBR) 3 Aldienors Cabruca (A C) 4 Joao Evangelistas Cabruca (EVC) 5 V i rginias C abruca (V IC ); V i rgin ia s Fores t R eserve (V R ) 6 Low inundated clearing LEGEND N Figure 4-2. Approxim a te locations of observed traditional cacao and secondary forest study sites in the Assen t am ento Frei Vantuy, Ilh us, Bahia, Brazil. 120

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C B A Figure 4-3. Exam ple of forest structure of seco n d ary forest f r agm ents. A) Josadabes forest reserve (JR); B) Looking up at the canopy of Britos forest reserve II (BBR); C) U nderstory of Josadabes reserv e (JR ) 121

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C B A Figure 4-4. Exam ple of forest structure of cab ru ca system s. A) The shade and cacao layers of V i rginias c abruca (V IC ); B ) Josad a bes cab ru ca (JC ) ; C ) Flo o r of V i rginias cab ruca (V IC ). 122

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0 25 50 75 100 125 150 175 2000-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 > 100DBH (cm)No. Individuals 0.1 ha, 199 ind. A 0 25 50 75 100 125 150 175 2000-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 > 100DBH (cm)No. Individuals 0.25 ha, 289 ind. B Figure 4-5. Diameter class distribution of stems in two seco ndary forest fragments. A) Josadabes Reserve (JR); B) Virginias Reserve (VR). 123

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0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 SepOctNovDecJanFebMarAprMayJunJulAugMg/ ha Cabruca Forest Figure 4-6. Monthly litterfall in cacao and secondary forest collected from the period September 2005 to August 2006. Error bars represent SE. 124

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Figure 4-7. Standing biomass on the forest floor of forest ed plots in May and November, 2005. A) All eight forest systems. B) Cabruca ve rsus secondary forest systems. Error bars represent SE. CACAO FOREST 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0JCEVCACVICJRBRBBRVRMg/ha May November A 0.0 2.0 4.0 6.0 8.0 10.0MAY NOVEMBERMg/ha Cacao Forest B 125

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126 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 JCEVCACVICJRBRBBRVRPlotmg OM/ g soil < 53um 150um 53um 250um 150um 2 mm 250um A CAC AO FOREST 0% 20% 40% 60% 80% 100% J C EV C A C VI C J R BR BB R VRPl o t% T o t a l OM < 53u m 15 0u m 53u m 25 0u m 150u m 2 m m 2 50u m B CAC AO FOREST Figure 4-8. Total organic m atter content and organic m atter distribut ion am ong particle size fractions of cacao and secondary forest si tes. A) T o tal o r ganic m atter content per gram of oven dry soil; B ) Organic m atter dist ribution by soil particle size class. Error bars rep r ese n t SE.

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CHAPTER 5 OVERVIEW AND SYNTHESIS The role of species diversity in maintaining critical ecosystem functions ranks among the most contentious scientific debates of our time. How we respond to the rapid changes in the redistribution of species across th e planet in this age of accelerat ed globalization rests as much upon our understanding of how species behave and interact within different environments as upon our priorities between biodiversity pr eservation and resource management. Today, carbon is arguably the most talked about chemical element, thanks to the mainstreaming of discussions surrounding globa l warming. With popularity come fads and scams. Throughout the developing world, carbon sequestration, along with biodiversity and organic are terms pitched to small farmi ng communities as an environmental cash cow. Because of the high expectations of the car bon market to offset past and future CO2 production, scrutiny of the conditions under which long-term carbon storage is possible is necessary as are multidisciplinary efforts to quantify realistic carbon sequestration rates under well-defined environmental and human-use conditions. Real scientific data are necessary to form the basis of the carbon market for both producers and consumers alike. The importance of vegetation diversity on eco system functions such as carbon dynamics, including sequestration is yet undetermined. The inab ility to predict the longterm effect of plant diversity or even of individual species on the terrestrial carbon cy cle is a liability in a growing carbon credit market. Because of its intersec tion with the global economy, the question of diversity and ecosystem function is not strictly an academic exercise. The models used to estimate soil carbon storage potentials should be the best available and suited to the particular environment in which a carbon manageme nt plan is to be executed. 127

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The aim of this work was to establish a firm relationship between plant litter diversity, and the soil ecosystem function of decomposition, whos e principal objectives were i) to compare the capacity of small-scale traditiona l agroforestry system (low tree species diversity) and secondary forest (high tree species diversity ) to provide selected ecosystem services and ii) to predict the decomposition behavior of litter mixtures under controlled conditions. Chapter 2 developed analytical and conceptual tools used in the litter-m ix prediction efforts described in Chapter 3. In Chapter 4, two land-uses provided tropical forest systems of differing tree diversity in which to contrast the direct and indire ct effects of species compositi on and diversity on soil functions. The setting was staged in an area dependent on dwindling forest res ources for income and where the term biodiversity was perhaps of greater economic interest than ecological for those concerned. In such an environment, the confla tion of science and philo sophy can be detrimental to both the producer who may not receive the crop (or monetary) yields promised or to the consumer who may pay to support a false product. Selling biodiversity as a scientifically grounded management practice to growers, especially vulnerabl e small-scale growers demands universally validated and repeatable results. In the Atlantic Rain Forest region of sout hern Bahia, a land formerly dominated by cacao production, reforestation projects flourish in the effort to reclaim lands degraded by the proliferation of pasture following the devasta tion of the cacao production due to witchs broom in the 1990s. In particular, the resurgence of cabruca, the traditional, method of cacao production has become favored by institutions formerly predisposed toward high-input, full-sun, large-scale plantation production. This work has shown that select ed functions related to nutrient delivery such as litterfall production, carbon storage, and so il nutrient status were supp lied equally well by managed, 128

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production-oriented forest system s as by natural stands. Howe ver, the functional parity is misleading. This is due in part to the great variation in what is designated secondary forest and also to the selected functions observed. Hence the choice of ecosystem function will determine the level of importance of diversity in maintaining it. If the function desired can be accomplished by a few productive species as by multip le species, priorities between potentially conflicting goals of conservation and service must be drawn. For this region, such results underscore the importance of dialog between the conservation and cacao-producing communities on the priorities of cabruca systems and the need to investigate th e effect of size of land-holding on species diversity, forest structure and soil properties. The prediction of soil ecosystem services as a function of land cover and land use is the cornerstone of soil organic carbon models from Century to NuCM Yet these models ignore the predominance of mixed substrates and use simp lified estimates based on homogenous soil inputs which has been shown by many studies to be inadequate to describe rates of carbon mineralization and nutrient release. In tropical forest systems, th e shortcomings of such models, even if conservatively estimated at only a fe w percent in prediction accuracy, when integrated over the area covered by tropical forests, co uld represent a miscalculation on the order of gigatons of carbon either sequestered in th e soil or released to the atmosphere. Few studies have sought to predict litter mixture be havior, particularly the magnitude and direction of litter interactions that occur during mixed litter decomposition. Fewer have attempted to devise an alternative measure of litter mixture diversity based on multiple chemical traits. The principal contribution of this work was the successful modeling of the carbon mineralization of leaf mixtures on the basis of chemical ident ity and a novel construct, and mixture chemical diversity. Thes e two concepts supersede the fo rmer taxonomic descriptions of 129

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mixtures by species identity and species richness. By adopting litter chemistry as relevant functional traits to decomposition processes I have demonstrated the possibility to predict not only aggregate mixture behavior bu t also the strength and magnitude of litter interactionsa feat not yet noted in the published literature. Wh ile limited in scope becau se of its controlled laboratory setting, the use of ground litter tissue and the limitation to two species mixtures, the results presented here, in conjunction with continuous evolution models of decomposition incorporating IR, provide a mechanistic footing on which to advance SOM models. As a summary of chemical heterogeneity the chemical diversity index (CDQ) offers a snapshot of resource heterogeneity that can al so be extended to live-vegetation systems. An unanticipated finding was uniqueness of the rela tionship between foliar chemical diversity and species richness for a vegetation community. B ecause foliar chemistry is the outcome of interspecies and environmental interactions, an index that summarizes chemistries of many species can serve as a monitoring tool in conjun ction with other measures. Furthermore, the index is dynamic because even while the species composition of a vegetation community may remain constant, its chemical profile will not. Future Work The importance of vegetation diversity on ecosystem functions such as wildlife preservation and aesthetics are well established. Its relevance to so il-based functions, in particular carbon dynamics, including sequestration is yet undecided. The inability to predict the effect of plant diversity or ev en of individual species on the te rrestrial carbon cycl e over the long term is a liability in a growing carbon credit market. Because of its intersection with global economy, the question of diversity and ecosystem f unction is not strictly an academic exercise. The models used to estimate so il carbon storage potentials should be the best available and suited to the particular environment in which a carbon management plan is to be executed. 130

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131 Further development of this work should include the following: Documentation of the spatial a nd temporal variability in th e chemical heterogeneity of litter mixtures under field conditions Expansion to mixtures comprise d of more than two species; Robustness to changes in relative abundance (unequa l species distribution); Field-level studies which include the effect of litter particle size and the importance of litter chemistry on macro and mesofauna and; Investigation of the environm ental mediation (mineralogy, mo isture, soil nutrients, pH, CO2 enrichment) of microbial community a nd activity on the uti lization of mixed substrates. Field testing of reforestation using chemical heterogeneity as a t ool in defining site biodiversity, while limiting the number of species required for reforestation. Changes in climate, such as shifts in precipitation patterns, elevated CO2 and increased temperature, stand to influence biogeochemical cycl es via their affect on the worlds vegetation. This may entail alterations in the species composition of plant communities, enhanced aboveand belowground productivity or modifications in plant chemistry and morphology. In a CO2rich world, the impact of relatively swift cha nges in vegetation chemistry and seasonality on the millennia of give and take between insects and plants carries implications for pest incidence and pollination. The use of litter chemistry as the st arting point of decomposition pathways enhances our ability to foresee the changes that climat e change can impart on soil ecosystem functions.

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APPENDIX A USING INFRARED SPECTROSCOPY TO DETERMINE THE RELATIVE CONTRIBUTION OF ORGANIC INPUTS TO SURFACE SOIL ORGANIC MATTER Introduction Soil boasts the largest reservoi r of organic carbon in terrestrial ecosystems, (Post et al 1982, Schimel 1995) whose stores are pr incipally subsidized by the death and transformation of plant biomass litterfall, root turnover and root exudates. The relative contribution of aboveground and belowground i nputs to soil carbon (quantity and quality) is an important element in determining management strategies for the maintenance and sequestration of soil carbon in forested syst ems. Past studies using carbon isotope methods and/or litterand r oot-exclusion experiments in te mperate and tropical forest systems have reported root re spiration and root decomposition as grea ter contributors to soil CO2 efflux than that deriving from th e decomposition of aboveground litter deposition (Bowden et al ., 1993; Li et al ., 2004, Sulzman et al ., 2005). Root biomass has been also shown to be the dominant sour ce of new and stable carbon in surface soil horizons (Balesdent & Balabane, 1996; Gale & Cambardella, 2000; Hobbie et al ., 2004; Rasse et al ., 2005). The majority of studies m onitoring the dynamics of soil carbon employ field designs based on root and litter exclusion experiments followed by carbon isotopic labeling or nuclear magnetic resona nce (NMR) spectroscopy, both expensive and time-consuming methods. Diffuse reflectan ce infrared spectroscopy (DRIFTS) is a technique swiftly gaining popular ity in the environmental sc ience community because of the facility, economy and versatil ity with which it can determin e an array of properties of organic and inorgani c materials. This study explored the use of DRIFTS to assess the rela tive contribution of leafand root-derived inputs to soil carbon. Using replicated suites of foliage, litter, soil and 132

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roots of mono-specific plots of 10 tropical fo rest species, I asked: How does the spectral fingerprint of soil organic matter under a single species compare to t hose of foliage, litter and fine roots of the same species and how doe s this relationship cha nge with depth? The inquiry was extended to natural and manage d multi-species forested systems to see whether the trends observed under neat, monospecific conditions were maintained in polycultural conditions. Materials and Methods Study Site and Sampling Single-species stands Samples were drawn from a 35-year-old arboretum established in the Pau Brasil Ecological Station, in Porto Seguro, Brazil in the state of Bahia (16' S, 39 11'W) whose mean annual temperature and precipita tion classify the clim ate as Af in the Koppen system. Soils were classi fied as Oxisols (Montagnini et al ., 1995) with sandy surface textures. Live foliage, litter and so il were sampled in June 2004, from 19 plots representing ten tropical tree species native to the Brazilian Atlantic Rain Forest of southern Bahia (Table A-1). Plots measuri ng approximately 2 m x 2 m contained three to five mature trees of one species. Understo ry growth was supressed due to frequent cutting. Species were selected based on the f acility to collect suffici ent foliage and litter material for subsequent analysis with preference for those wi th replicate plots. Freshly senesced litter was collected from the soil surface by hand and selected on the basis of color and apparent lack of fungal colonization. Foliage was collected from the lower canopy using a tree pruner. Leaves showing signs of extreme insect damage were discarded. Soil was collected from the 05 cm and 5-10 cm depth with a shovel from three random locations within the plot after the removal of the litter layer. From this soil 133

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material, coarse and fine roots of undetermined viability were extrac ted by sieving and by hand. Fine roots (< 2mm) were retained for later analysis. Mixed-species stands Material from mixed-species stands were gathered from forest fragments of the Atlantic Rain Forest in southern Bahia, lo cated in the heart of the cacao-producing region between Itabuna and Ilhus (14' S, 39 10' W) within the same climate zone as the research station. Sixteen 10 m x 10 m plots in high clay soils (54%) under secondary forest and nine 10 m x 10 m plots on sa ndy soils (70%) from secondary forest and cabruca a traditional cacao production system we re sampled (Chapter 4). Traditional cacao production is characterized by the thinning of the forest cover and planting cacao in the understory, thereby preserving some of the inherent tree sp ecies diversity (CIT). By the accounts of local inhabitants, the areas under cabruca had been under production for at least 50 years. The presence of the palm jussara, Euterpe edulis and the absence of common plantation trees, such as jackfruit ( Artocarpus heterophylla ) marked the forest stand on clay soil as mature. The fragment of forest on sandy soils had been uncut for at least 50 years but showed signs of disturbance on its perimeter. Mean stem density of the secondary forest and cacao plots was 12 tree s per 10 x 10 m plot, with 2-5 species per 100 m2 subplot in the instance of the cacao-pr oduction area, and 4-13 species per 100 m2 in secondary forest (Chapter 4) In a departure from the mono -specific stands, in lieu of freshly senesced litter, forest floor was co llected from a 50 cm x 50 cm frame randomly tossed three times within each subplot and pool ed to form a composite sample. Soil was collected from the 0-10 cm depth using a shovel, again from three random locations within each subplot. Roots were extracted from a 20 cm x 20 cm x 10 cm block carved from the soil near the center of each subplot. 134

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Sample Preparation Soils were air dried, sieved to < 2mm and ball-milled after the removal of large bits of organic matter. Roots, foliage and forest floor were dried at 60C for 48 hours and ball-milled prior to spectral analysis. S ub-samples of ground soil and tissue materials were combusted at 400C for 16h (Nelson & Sommers, 1996) and 500C for five hours (CIT), respectively, to generate ashed samples. Spectral Analysis and Isotopic Carbon Analysis Combusted and non-combusted soil a nd tissue samples were chemically characterized using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Spectra were scanned on a Digila b7000 Series infrared spectrometer without KBr dilution in the mid-infrared region (4000 cm-1 to 400 cm-1) at a resolution of 4 cm-1. A total of 64 scans, normalized against an IR-grade KBr standard, were averaged to generate a final spectrum for each sample. Spectra were transformed using the standard normal variate method to correct for baseline drift (Barnes et al ., 1989). Prepared samples of soil (0-5cm), litter and roots derived from the single-species plots were analyzed for natural 13C isotopic ratios using an inductively-coupled plasma mass-spectrometer (Elan 9000, Perkin Elmer, Waltham, MA). Statistical Analysis The sum of squared differences (SSD) between the soil spectra of 18 single species plots and the spectra of their respective inputs was used as a simple graphical comparison to gauge the similarity between soil organi c matter and organic inputs. The SSD was computed by summing the difference between the absorbance values of spectra of organic inputs (foliage, li tter and roots) from soil sp ectra over all wavepoints, W or 135

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2 1iORG iSOM W iabs abs SSD (3-1) Ash-subtraction is a mathematical technique that amplifies the signal of the organic component by reducing the spec tral contribution of the i norganic fraction (Westerhaus et al. 2004). The SSD between soil and organic inputs was determ ined for ash-subtracted and non-ash subtracted spectra. Values of the SSD (both whole and ash-subtracted) calculated from roots (y) were plotted agains t those of litter and foliage (x). The clustering of points on the y=x line indicates equal contribution of the two inputs, while a deviation from the line indicates dominance of one of the input s. Points clustered below the 1:1 line exhibit a sm aller SSD of the input represented along the vertical axis relative to the input represented along the horizontal axis. The re gression line best representing the points was used to test the alternative hypothesis HA 1. Significant differences in isotopic ratios be tween soil and litter and soil and roots were determined by the two-tailed Student ttest for dependent samples, performed at 95% confidence level. Analysis was conducte d in R version 2.5.1 (R Development Core Team, 2006). Results and Discussion Relative Importance of Above and Belowground Inputs In the monoculture systems, comparison of the single-species SSD relative to soil organic matter of three inputs foliage, litter, and rootsshowed greater similarity between the soil and root spectra than between soil and foliage, and soil and litter spectra (Fig. A1). As means of comparison, the relationship between SSDlitter and SSDfoliage was plotted and found not to differ significantly from unity (Fig. A-1A). The equivalence of litter 136

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and foliage relative to soil organic matte r (SOM) was conserved with soil depth, confirming the interpre tability of the graphical method. The slopes of SSDroot versus SSDfoliage and SSDroot versus SSDlitter differed significantly from 0 and 1 within 95% confidence interval (Fig. A-1 B,C). This relationship was exaggerated at the 5-10 cm de pth; the spectra of r oots were closer to those of the soil than were fo liar or litter spectra, as suggested by the decrease in slope. However, while a trend of increasing similarity of SOM to root matter with depth was observed, the effect was not significant. The use of ash-subtracted spectra enhanced the organic matter signal, particularly in soil spectra. While the slopes were greater in the analysis of ash-subtracted soil, litter and root matter, the associated confidence in tervals were much narrower and significant difference from unity was maintained (Fig. A-1D). Interestingly, the computed SSD of root, litter and foliage were not similar between replicates of single-species plots. Such discrepancies could arise from site differences that can lead to subtle changes in the quantity and quality of carbon supplied to the soil by roots and foliage, including but not limited to, light availability, soil moisture content and surrounding tree density. The most distal points in Fig. A-1 were replicates of species clustered below the1:1 line but occurred on poor ly drained soils in a low-lying section of the arboretum. Delta 13C data of soil, root and l itter inputs of the single-sp ecies plots also indicated greater similarity between soil and roots (Fig. A-2). The isotopic signature of 13C differed significantly for all three substrates (P<0.001), a nd the difference between soil 137

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and root signatures were si gnificantly lower than that of soil and litter signatures (P<0.001). In the multi-species systems, evidence to suggest the dominance of root-derived carbon in the SOM was ambivalent. Following the same analysis, the spectral signature of the top 10 cm of the clayey soil under s econdary forest bore greater similarity to the non-combusted spectral profile of roots than to that of surfac e-deposited litter (Fig. A-3). The relationship was strengthened when employing ash-subtracted spectra. In contrast, neither roots nor litter dominated in the sec ondary forest and cabru ca systems situated on the sandy soil. A possible explanation for this is the relative instability of these systems. Because of the high activity expressed thr ough the extraction of species in the cabruca system and the influence of new, introduced species in the forest fragment, sufficient time may not have passed for an equi librium between aboveground vegetation and belowground soil carbon to occur, thereby blurring the parentage soil carbon signature. Interpretation This study centered on the application of infrared spectrosc opy to discern the relative similarity in chemical composition of surface and subsurface inputs to that of soil organic matter. Soil organic matter spectra were found to resemble root matter more closely than litter in mono-specific plots and in one of the mu lti-species plots. The direct comparison of initial inputs and SOM signatures assumes that the decomposition trajectories taken by root and litter are suffici ently unique that thei r end-products can be directly associated with them. This includes the possibility in which recalcitrant compounds of inputs are conserved despite transformations brought on by the action of the decomposer community and, therefore, able to serve as biomarkers. In the case of 138

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litter-derived material, such id entifiers may be secondary me tabolites rich in phenolics, and, in the case of roots, pol ymers such as suberin (Rasse et al ., 2005). Natural carbon isotope abunda nce has been used to tr ack aboveand belowground carbon allocation in grassland and forested systems (Peterson & Fry, 1987; Staddon, 2004) and to monitor soil carbon dynamics (Balesdent et al ., 1987) arising from shifts in vegetation communities such as cropping systems (Vitorello et al ., 1989), C3 versus C4 plants (Dzurec et al. 1985) or legumes and non-l eguminous species (Rao, 1994). Because the isotopic signature of organic matter is strongly influenced by its consumers, 13C is also a helpful tool in charting food webs (Rothe & Gleixner, 2000; Ruess et al ., 2005). Preferential inco rporation of lighter 12C by soil fauna leads to the enrichment of residual materials in the heavier 13C isotope. The enrichment in natural 13C from litter to roots (Fig. A-2) arises from multiple processes by which photosynthetic C is fracti onated and partitioned amongst plant organs (Badeck et al ., 2005). The observed proximity of the 13C soil and roots has several viable interpretations. The first is that, assuming the same degree of decomposition and decomposition trajectory undergone by root and litter, root carbon is a significantly greater contributor to SOM than plant carbon. However, if litter were preferentially consumed by decomposers over root matter, litter-derived end products could constitute the majority of SOM through the greater exposure of litter to microbial activity, even while its original isotopic signa ture is more distant to SOM. In the absence of information about decomposition pathways, interpretation of 13C values is inconclusive. Consumers of litter detritus exhibit pref erence for carbon forms and leaf litter has been commonly to be the pr eferred substrate over root matter (Kramer & Gleixner, 139

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2008). However, a recent study conducted in a temperate forest syst em demonstrated a stark contrast in the degrading communities of rootand leaf-derived materials, with the majority of soil invertebrates obtainin g their carbon from roots (Pollierer et al ., 2007). Under such a scenario, the proximity of th e carbon isotopic signatu re of roots and SOM supports the interpretation that root-derived OM constitutes a greater proportion of SOM than litter-derived OM and that th e spectral analysis is corroborated. Already used successfully to calibrate a nd predict NMR-determined alkyl C and Oalkyl C contents (Leifeld, 2006), which are key functional groups used for studying the structure and turnover of SOM, DRIFTS presents a potential tool in the quantifying the relative contribution of various inputs to soil carbon. It s utility in calibration and prediction can permit greater sample throughput which can facilitate the expansion of spatial coverage for landscap e-level assessments as well as finer scaled sampling over soil particle size fractions. An advantage over isotopic analysis is that no assumptions of decomposition trajectory or d ecomposition community have to be made. If successful, this approach can help to identify the domin ant source of soil organic matter and its final destination may be useful in evaluating soil carbon management strategies in forested systems. Conclusion Using DRIFTS as the basis for chemical characterization, greater similarity between soil organic matter and fine-root inputs than between SOM and leaf litter was observed. Many studies have used rootand litter-exclusi on experiments or isotopic ratios for determining the relative contributi on of organic inputs to soil carbon. This method potentially offers a faster, cost-effec tive technique for a qualitative assessment with no field-level experiment al manipulation and minimal sample preparation. Once 140

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141 validated by traditional methods, DRIFTS anal ysis presents a valuable monitoring tool for land management practices in which carbon sequestration is a primary objective.

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Table A-1. Ten tropical forest species used to analyze fo liage, litter, r oot inputs to soil organic matter. Common name Scientific name Duplicated? Amescla mirim Protium sp. Y Angico branco Anadenathera peregrina N Arapau Sclerolobium chrysophyllum Y Arapati Arapatiella psilophylla Y Gindiba Sloanea obtusifolia Y Imbiruu Bombax macrophyllum Y Jatob Hymenaea sp. Y Pau marfim Balfourodendron riedelianum Y Sapucaia Lecythis pisonis Y Vinhtico Plathymenia foliolosa Y 142

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D C B A Fig. A-1. Sum of squared differences from of or ganic inputs plotted agains t each other at the0-5 cm and 5-10 cm depths. A) Foliage vs. L itter. B) Roots vs. Foliage. C) Roots vs. Litte r. D ) R oots vs. Litter f o r ash-su btrac t ed so il. 143

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Fig. A-2. Isotopic carbon signa tures of 18 single-species plots. 144

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B A Fig. A-3. Sum of squared differences between f o re st floor litter and root litter in a m u lti-spec i es forested system atop a clayey soil, base d on non-com busted and com busted (cleaned) spectra A) Non-com busted; B) Ash-subtracted spectra. 145

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146 Fig. A-4. Sum of squared differences between fore st floor litter and root litter in a multi-species forested system atop a sandy soil, based on non-combusted and combusted (cleaned) spectra A) Non-combusted; B) Ash-subtracted spectra. B A

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LIST OF REFERENCES Aber JD, Melillo JM, McClaugherty CA. 1990. Predicting long-term patterns of mass-loss, nitrogen dynamics, and soil organic-matter formation from initial fine litter chemistry in temperate forest ecosystems. Canadian Journal of Botany 68: 2201-2208. Alger K. 1998. The reproduction of the cocoa industry and biodiversity in southern Bahia, Brazil. Proceedings of the Smithsonian Institution, Washington, DC. http://nationalzoosiedu/Conservati onAndScience/ MigratoryBirds/ Research/Cacao/paperscfu (accessed April 2006). Amatangelo KL. 2008. Biomass and biochemistry: litter impacts on community and ecosystem processes. Ph.D thesis, Stanford University, USA. Annan-Afful E, Iwashima N, Otoo E, Owus u-Sekyere E, Asubonteng KO, Kamidohzono A, Masunaga T, Wakatsuki T. 2005. Land-use dynamics and nutri ent characteristics of soils and plants along topo-sequences in inland vall ey watersheds of Ashanti Region, Ghana. Soil Science and Plant Nutrition 50: 633-647. Arajo M, Alger K, Rocha R, Mesquita CAB. 1998. A Mata Atlntica do sul da Bahia: situao atual, aes e perspectivas. Rese rva da Biosfera da Mata Atlntica-MABUNESCO. Caderno 8:1-36. Armbrecht I, Perfecto I, Vandermeer J. 2004. Enigmatic biodiversity correlations: Ant diversity responds to diverse resources. Science 304: 284-286. Badeck FW, Tcherkez G, Nogues S, Piel C, Ghashghaie J. 2005. Post-photosynthetic fractionation of stble carbon isotopes between plant organsa widespread phenomenon. Rapid Communications in Mass Spectrometry 19: 1381-1391. Balesdent J, Balabane M. 1996. Major contribution of roots to soil carbon storage inferred from maize cultivated soils. Soil Biology and Biochemistry 28: 1261-1263. Balesdent J, Mariotti A, Guillet B. 1987. Natural C-13 abundance as a tracer for studies of soil organic-matter dynamics. Soil Biology and Biochemistry 19: 25-30. Ball BA, Hunter MD, Kominoski JS Swan CM, Bradford MA. 2008. Consequences of nonrandom species loss for decomposition dynamics: experimental evidence of additive and non-additive effects. Journal of Ecology 96: 303-313. Barbosa LCA. 2007. Espectroscopia no infravermelho na caracterizao de compostos orgnicos. Viosa, Brazil: Editora UFV. Bardgett RD, Shine A. 1999. Linkages between plan t litter diversity, soil microbial biomass and ecosystem function in temperate grasslands. Soil Biology and Biochemistry 31: 317-321. Barnes RJ, Dhanoa MS, Lister SJ. 1989. Standard normal variate transformation and detrending of near-infrared diffuse reflectance spectra. Applied Spectroscopy 43: 772-777. 147

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Bed L, Arajo M, Faria D, Schroth G. 2007. Biodiversity friendly certification of cocoa landscapes in Bahia, Brazil Accessed on the web 01/16/09 at http://web.catie.ac.cr/cd_multiestrata/presentaciones_orales/session3/Biodiversity.pdf Beer J. 1988. Litter production and nutrient cycling in a coffee ( Coffea arabica ) or cacao ( Theobroma cacao) plantations with shade trees. Agroforestry Systems 7: 103-114. Ben-Dor E, Banin A. 1995. Near-infrared analysis as a rapi d method to simultaneously evaluate several soil properties. Soil Science Society of America Journal 59: 364-372. Berg B, McClaugherty C. 2008. Plant litter: Decomposition, humus formation, carbon sequestration, 2nd Edition. Berlin, Germany: Springer-Verlag. Berg B, Steffen KT, McClaugherty C. 2007. Litter decomposition is dependent on litter Mn concentrations. Biogeochemistry 82: 29-39. Blair JM, Parmelee RW, Beare MH. 1990. Decay rates, nitrogen fluxes and decomposer communities of singleand mixed-species foliar litter. Ecology 7: 1976-1985. Blomqvist MM, Olff H, Blaauw MB, Bo ngers, T, van der Putten WH. 2000. Interactions between aboveand below-ground biota: importance for small-scale vegetation mosaics in a grassland ecosystem. Oikos 90: 582-298. Bobo KS, Waltert M, Sainge NM, Njok agor J, Fermon H, Mhlenberg M. 2006. From forest to farmland: Species richness patterns of trees and understorey plants along a gradient of forest conversion in Southwestern Cameroon. Biodiversity and Conservation 15: 40974117. Botta-Dukt Z. 2005. Raos quadratic entropy as a measure of functional diversity based on multiple traits. Journal of Vegetation Science 16: 533-540. Bowden RD, Nadelhoffer KJ, Boone RD, Melillo JM, Garrison JB. 1993. Contributions of aboveground litter, belowground litter, and root respiration to total so il respiration in a temperate mixed hardwood forest. Canadian Journal of Forest Research 23: 1402-1407. Bray JR, Curtis JT. 1957. An ordination of the upland forest communities of Southern Wisconsin. Ecological Monographs 27: 325-349. Briones MJI, Ineson P. 1996. Decomposition of eucalyptus leaves in litter mixtures. Soil Biology and Biochemistry 28: 1381-1388. Brown S, Lugo AE. 1982. The storage and production of orga nic matter in tropical forests and their role in the global carbon cycle. Biotropica 14: 161-187. Brown S, Lugo AE. 1990. Tropical secondary forests. Journal of Tropical Ecology 6: 1-32. 148

PAGE 149

Bruun S, Stenberg B, Breland TA, Gudmund sson J, Henriksen TM, Jensen LS, Korsth A, Luxhi J, Plmason F, Pedersen A, Salo T. 2005. Empirical predictions of plant material C and N mineralization patterns fr om near infrared spectroscopy, stepwise chemical digestion and C/N ratios. Soil Biology and Biochemistry 37: 2283-2296. Bunker DE, DeClerck F, Bradford JC,Colwell RK, Perfecto I, Phillips OL, Sankaran M, Naeem S. 2005. Species loss and aboveground carbon storage in a tropical forest. Science 310: 1029-1031. Card DH, Peterson DL, Matson PA. 1988. Prediction of leaf chemistry by the use of visible and near infrared spectroscopy. Remote Sensing of Environment 26:123-157. Cardinale BJ, Nelson K, Palmer MA. 2000. Linking species diversity to the functioning of ecosystems: On the importance of environmental context. Oikos 91: 175-183. Cardoso da Silva JM, Tabarelli M. 2000. Tree species impoverishment and the future flora of the Atlantic forest of northeast Brazil. Nature 404:72-74. Carney KM, Matson PA. 2006. The influence of tropical plan t diversity and composition on soil microbial communities. Microbial Ecology 52: 226-238. Cassano CR, Schroth G, Faria D, Delabie JHC, Bed L. 2008. Landscape and farm scale management to enhance biodiversity cons ervation in the cocoa producing region of southern Bahia, Brazil. Biodiversity and Conservation DOI 10.1007/s10531-008-9526-x. CEPLAC Comisso Executiva Do Plan o Da Lavoura Cacaueira. 1976. Dinmica do uso da terra: Diagnstico scio-econmico da regio cacaueira, Volume 3 de Oliveira Leite J, ed. Ilhus, Brazil: IICA/CEPLAC. CEPLAC Comisso Executiva Do Plan o Da Lavoura Cacaueira. 2006. Departamento de Meteorologia, CEPLAC-CEPEC. Chapman K, Whittaker JB, Heal OW. 1988. Metabolic and faunal activity in litters of tree mixtures compared with pure stands. Agriculture, Ecosystems and the Environment 24: 3340. Chapman SK, Koch GW. 2007. What type of diversity yiel ds synergy during mixed litter decomposition in a natural forest system? Plant and Soil 299:153-162. Chepote RE, Sodr GA, Reis EL, Pacheco RG, Marrocos PCL, Serdio MH, Valle RR. 2005. Recomendaes de corretivos e fertilizan tes na cultura do cacaueiro no Sul da Bahia 2 aproximao Ilhus, Brazil: CEPLAC/CEPEC. Clarke KR, Warwick RM. 1998. A taxonomic distinctness index and its statistical properties. Journal of Applied Ecology 35: 523-531. 149

PAGE 150

Cohen MJ, Prenger JP, DeBusk WF. 2005. Visible-near infrared re flectance spectroscopy for rapid, nondestructive assessm ent of wetland soil quality. Journal of Envir onmental Quality 34: 1422-1434. Compton JE, Watrud LS, Porteus LA, DeGrood S. 2004. Response of soil microbial biomass and community composition to chronic ni trogen additions at Harvard forest. Forest Ecology and Management 196: 143-158. Conn C, Dighton J. 2000. Litter quality influences on decomposition, ectomycorrhizal community structure and mycorrhizal ro ot surface acid pho sphatase activity. Soil Biology and Biochemistry 32: 489-496. Coteaux MM, Bottner P, Berg B. 1995. Litter decomposition, climate and litter quality. Trends in Ecology and Evolution 10: 63-66. Crawford DL, Crawford RL. 1980. Microbial degradation of lignin. Enzyme and Microbial Technology 2:11-22. da Fonseca GAB. 1985. The vanishing Brazilian Atlantic forest. Biological Conservation 34: 17-34. da Fonseca GAB, Alger KN, Pinto LP, Arajo M, Cavalcanti R. 2003. Corredores de biodiversidade: O corredor central da Mata Atlntica. In: Prado PI Landau EC, Moura RT, Pinto LPS, Fonseca GAB, Alger K, orgs. Corredor de Biodiversidade da Mata Atlntica do Sul da Bahia Publication on CD-ROM, Ilhus, Bahia: IESB/ CI/ CABS/ UFMG/ UNICAMP. Dalal RC, Henry RJ. 1986. Simultaneous determination of mo isture, organic carbon, and total nitrogen by near IR refl ectance spectrophotometry. Soil Science Society of America Journal 50: 120-123. Dangles O, Malmqvist P. 2004. Species richness-decomposition relationships depend on species dominance. Ecology Letters 7: 395-402. de Deyn GB, Raaijmakers CE, van Ruijven J, Berendse F, van der Putten WH. 2004. Plant species identity and diversity on different trophic levels of nematodes in the soil food web. Oikos 106: 576-586. de Oliveira Leite J, Valle RR. 1990. Nutrient cycling in the cacao ecosystem: Rain and throughfall as nutrient sources for the soil and cacao tree. Agriculture, Ecosystems and the Environment 32: 143-154. Dean W. 1995. With broadax and firebrandthe destructi on of the Brazilian Atlantic Forest. Berkeley, USA: University of California Press. Dehlin H, Nilsson MC, Wardle DA. 2006. Aboveground and belowground responses to quality and heterogeneity of organic inputs to the boreal forest. Oecologia 150: 108-118. 150

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Daz S, Hodgson JG, Thompson K, Cabido M, Cornelissen JHC, Jalili A, MontserratMart G, Grime JP, Zarrinkamar F, Asri Y, Band SR, Basconcelo S, Castro-Dez P, Funes G, Hamzehee B, Khoshnevi M, P rez-Harguindeguy N, Prez-Rontom MC, Shirvany FA, Vendramini F, Yazdani S, Abbas-Azimi R, Bogaard A, Boustani S, Charles M, Dehghan M, de Torres-Espuny L, Falczuk V, Gu errero-Campo J, Hynd A, Jones G, Kowsary E, Kazemi-Saeed F, Maestro-Martnez M, Romo-Dez A, Shaw S, Siavash B, Villar-Salvador P, Zak MR. 2004. The plant traits that drive ecosystems: Evidence from three continents. Journal of Vegetation Science 15: 295-304. Donald PF. 2004. Biodiversity impacts of some agri cultural commodity production systems. Conservation Biology 18: 17-37. Duguma B, Gochowski J, Bakala J. 2001. Smallholder cacao ( Theobroma cacao Linn) cultivation in agroforestry systems of West and Central Africa: Challenges and opportunities. Agroforestry Systems 51: 177-188. Dzurec RS, Boutton TW, Caldwell MM, Smith BN. 1985. Carbon isotope ratios of soil organic matter and their use in assessing community composition changes in Curlew Valley, Utah. Oecologia 66: 17-24. Ehrlich PR. 1964. Some axioms of taxonomy. Systematic Zoology 13: 109-123. Elias Jr. E. 1998. Florstica e estrutura fitossociolgica de fragmentos de Fl oresta Atlntica do municpio de Eunpolis-Bahia. Masters thes is, Federal University of Viosa, Brazil. Epps KY, Comerford NB, Reeves JB, Cropper WP, Araujo QR. 2007. Chemical diversityhighlighting a species richnessecosystem function disconnect. Oikos 116: 1831-1840. Ewel JJ. 1979. Natural systems as models for the desi gn of sustainable systems of land use. Agroforestry Systems 45: 1-21. Faria D, Paciencia MLB, Di xo M, Laps RR, Baumgarten J. 2007. Ferns, frogs, lizards, birds and bats in forest fragments and shade cacao plantations in two contrasting landscapes in the Atlantic forest, Brazil. Biodiversity and Conservation 16: 2335-2357. Faria Filho AF, Arajo QR. 2003. Zoneamento do meio fisico do m unicpio de Ilhus, Bahia, Brasil, utilizando a tcnica de geoprocessamento CEPLAC/CEPEC. Boletim Tcnico No. 187. 20 pp. Finzi AC, Canham CD. 1998. Non-additive effects of litter mixtures on ne t N mineralization in a southern New England forest. Forest Ecology and Management 105: 129-136. Franzen M, Mulder MB. 2007. Ecological, economic and social perspectives on cocoa production worldwide. Biodiversity and Conservation 16: 3835-3849. Fyles JW, Fyles IH. 1993. Interaction of Douglas-f ir with red alder and sa lal foliage litter during decomposition. Canadian Journal of Forest Research 23: 358-361. 151

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Gale WJ, Cambardella CA. 2000. Carbon dynamics of surface residueand root-derived organic matter under simulated no-till. Soil Science Society of America Journal 64: 190195. Gama-Rodrigues AC, Barros NF, Santos ML. 2003. Decomposio e liberao de nutrientes do folhedo de espcies florestais nativas em plantios puros e mistos no sudeste da Bahia. Revista Brasileira de Cincia de Solo 27: 1021-1031. Garland JL, Mills AL. 1991. Classification and characteriza tion of heterotrophic microbial communities on the basis of patterns of community-level sole-carbon-source utilization. Applied and Environm ental Microbiology 57: 2351-2359. Gartner TB, Cardon ZG. 2004. Decomposition dynamics in mi xed-species leaf litter. Oikos 104: 230-246. Gasparatos D, Haidouti C. 2001. A comparison of wet oxidation methods for determination of total phosphorus in soils. Journal of Plant Nutrition and Soil Science 164: 435-439. Gastine A, Scherer-Lorenzen M, Leadley PW. 2003. No consistent effect s of plant diversity on root biomass, soil biota and soil abiotic c onditions in temperate grassland communities. Applied Soil Ecology 24: 101-111. Gee GW, Bader JW. 1986. Particle-size analysis-Hydromet er method. In: Klute A, ed. Methods of soil analysis: Part 1 Physic al and mineralogical methods, 2nd Edition. Madison, USA: ASA-SSSA, 383-411. Gentry AH. 1988. Tree species richness of upper Amazonian forest. Proceedings of the National Academy of Sciences 85: 156-159. Gillon D, Houssard C, Joffre R. 1999. Using near-infrared reflectance spectroscopy to predict carbon, nitrogen and phosphorus content in heterogeneous plant material. Oecologia 118: 173-182. Gleixner G, Kramer C, Hahn V, Sasche D. 1995. The effect of biodiversity on carbon storage in soils. In: Scherer-Lorenzen M, Krner C, Schulze ED eds. Forest diversity and function Berlin, Germany: Springer, 165-183. Gnankambary Z, Bayala J, Malmer A, Nyberg G, Hien V. 2008. Decomposition and nutrient release from mixed plant litters of contrasting quality in an agroforestry parkland in the south-Sudanese zone of West Africa. Nutrient Cycling in Agroecosystems 82: 1-13. Gower JC. 1971. A general coefficient of similar ity and some of its properties. Biometrics 27: 857-871. Greenberg R. 1998. Biodiversity in the cacao agroecosystem: Shade management and landscape considerations. Proceedings of the First International Workshop on Sustainable Cocoa Growing, Panama, 3/30-4/02, 1998 Smithsonian Migratory Bird Center, Panama. http://www.nationalzoosiedu/smbc/Research/Cacao/ cacaoasp. 152

PAGE 153

Greenland PJ, Wild A, Adams D. 1992. Organic Matter Dynamics in Soils of the TropicsFrom Myth to Complex Reality. In: Lal R, Sanchez PA, eds. Myth and science of soils of the tropics Madison, USA: SSSA/ ASA, 17-23. Harch BD, Correll RL, Meech W, Kirkby CA, Pankhurst CE. 1997. Using the Gini coefficient with Biolog substrate utilization data to provide an alternative quantitative measure for comparing bacterial soil communities. Journal of Microbiological Methods 30: 91-101. Hartemink AE. 2005. Nutrient stocks, nutrient cycling, and soil changes in cocoa ecosystems: A review. Advances in Agronomy 86: 227-253. Httenschwiler S. 1995. Effect of tree species diversity on l itter quality and decomposition. In: Scherer-Lorenzen M, Krner C, Schulze ED eds. Forest diversity and function Berlin, Germany: Springer, 149-164. Httenschwiler S, Aeschlimann B, Couteaux M-M, Roy J, Bonal D. 2008. High variation in foliage and leaf litter chemistry among 45 tree species of a neotropical rainforest community. New Phytologist 179: 165-175. Httenschwiler S, Tiunov AV, Scheu S. 2005. Biodiversity and li tter decomposition in terrestrial ecosystems. Annual Review of Ecology, Evolution and Systematics 36: 191-218. Httenschwiler S, Vitousek PM. 2000. Role of polyphenols in terrestrial ecosystem nutrient cycling. Trends in Evolution and Ecology 6: 238-243. Heal OW, Anderson JM, Swift MJ. 1995. Plant litter quality and deco mposition: An historical overview. In: Cadisch G, Giller KE (eds) Driven by nature: Pl ant litter quality and decomposition, pp 3-32. Hector A, Joshi J, Scherer-Lorenzen M, Schm id B, Spehn EM, Wacker L, Weilenmann M, Bazeley-White E, Beierkuhnlein C, Caldei ra MC, Dimitrakopolous PG, Finn JA, Huss-Danell K, Jumpponen A, Leadley PW, Loreau M, Mulder CPH, Ne hver C, Palmborg C, Read DJ, Siamantziouras ASD, Terry AC, Troumbis AY. 2007. Biodiversity and ecosystem f unctioning: Reconciling the resu lts of experimental and observational studies. Functional Ecology 21: 998-1002. Heemsbergen DA, Berg MP, Loureau M, van Hal JR, Faber JH, Verhoef HA. 2004. Biodiversity effects on soil pro cesses explained by interspeci fic functional dissimilarity. Science 306: 1019-1020. Heffernan B. 1985. Exchangeable cations and cation ex change capacity of acid soils In: B Heffernan, ed. A handbook of methods of inorganic chem ical analysis for forest soils, foliage and water. Canberra, Australia: CSIRO, 113-120. Hendricks JJ, Nadelhoffer KJ, Aber JD. 1993. Assessing the role of fine roots in carbon and nutrient cycling. Trends in Ecology and Evolution 8: 174-178. 153

PAGE 154

Herv BD, Vidal S. 2008. Plant biodiversity and vegetation st ructure in traditional cocoa forest gardens in southern Cameroon under different management. Biodiversity and Conservation 17: 1821-1835. Hill JL, Curran PJ. 2003. Area, shape and isolation of tropical tree forest fragments: Effects on tree species diversity and imp lications for conservation. Journal of Biogeography 30: 1391-1403. Hobbie EA, Johnson MG, Rygiewicz PT, Tingey DT, Olszyk DM. 2004. Isotopic estimates of new carbon inputs into litter and soils in a f our-year climate change experiment with Douglas-fir. Plant and Soil 259: 331-343. Hobbie SE. 1992. Effects of plant-species on nutrient cycling. Trends in Ecology and Evolution 7: 336-339. Hooper DU, Vitousek PM. 1998. Effects of plant composition and diversity on nutrient cycling. Ecological Monographs 68: 121-149. Hoorens B, Aerts R, Stroetenga M. 2003. Does initial litter chemis try explain litter mixture effects on decomposition? Oecologia 137: 578-586. Hu YL, Wang SL, Zeng DH. 2006. Effects of single Chinese fir and mixed leaf litters on soil chemical, microbial properties and soil enzyme activities. Plant and Soil 282: 379-386. Huber S, Kneubhler M, Psomas A, Itten K, Zimmerman NE. 2008. Estimating foliar biochemistry from hyperspectral data in mixed forest canopy. Forest Ecology and Management 256: 491-501. Huston MA. 1997. Hidden treatments in ecological expe riments: Re-evaluating the ecosystem function of biodiversity. Oecologia 110: 449-460. Isaac ME, Gordon AM, Thevathasan N, Oppong SK, Quashie-Sam J. 2005. Temporal changes in soil carbon and nitrogen in west African multistrata agroforestry systems: A chronosequence of pools and fluxes. Agroforestry Systems 65: 23-31. Izsk J, Szeidl L. 2002. Quadratic diversity: Its maximizati on can reduce the richness of species. Environmental and Ecological Statistics 9: 423-430. Joffre R, gren G, Gillon D, Bosatta E. 2001. Organic matter quality in ecological studies: Theory meets experiment. Oikos 93: 451-458. Jonsson M, Wardle DA. 2008. Context dependency of litter-mixing effects on decomposition and nutrient release across a long-term chronosequence. Oikos 117: 1674-1682. Kanmegne J, Smaling EMA, Brussaard L, Gansop-Kouomegne A, Boukong A. 2006. Nutrient flows in smallholder production syst ems in the humid forest zone of southern Cameroon. Nutrient Cycling in Agroecosystems 76: 233-248. 154

PAGE 155

King JS, Pregitzer KS, Zak DR, Holmes WE, Schmidt K. 2005. Fine root chemistry and decomposition in model communities of north-temperate tree species show little response to elevated atmospheric CO2 and varying soil re source availability. Oecologia 146: 318328. Kramer C, Gleixner G. 2008. Soil organic matter in soil depth profiles: Distinct carbon preferences of microbial groups during carbon transformation. Soil Biology and Biochemistry 40: 425-433. Krebs CJ. 1989. Ecological methodology New York, USA: Harper & Row. Laurance WF, Lovejoy TE, Vasconcelos HL Bruna EM, Didham, RK, Stouffer PC, Gascon C, Bierregaard RO, Laurance SG, Sampaio E. 2002. Ecosystem decay of Amazonian forest fragments: A 22-year investigation. Conservation Biology 16: 605-618. Leifeld J. 2006. Application of diffuse re flectance FT-IR spectroscopy and partial least squares regression to predict NMR properties of soil organic matter. European Journal of Soil Science 57: 846-857. Li Y, Xu M, Sun OJ, Cui W. 2004. Effects of root and l itter exclusion on soil CO2 efflux and microbial biomass in wet tropical forests. Soil Biology and Biochemistry 36: 2111-2114. Liebsch D, Marques MCM, Goldenberg R. 2008. How long does the Atlantic Rain Forest take to recover after disturbance? Changes in species composition and ecological features during secondary succession. Biological Conservation 141: 1717-1725. Little AEF, Robinson CJ, Peterson SB, Raffa KF, Handelsman J. 2008. Rules of engagement: Interspecies interactions that regulate microbial communities. Annual Review of Microbiology 62: 375-401. Liu P, Sun OJ, Huang J, Li L. 2007. Nonadditive effects of litte r mixtures on dcomposition and correlation with initial litter N and P c oncentrations in grassl and plant species of northern China. Biology and Fertility of Soils 44: 211-216. Lobo DEVP. 2007. Agroecossistema cacaueiro da Ba hia: Cacau-cabruca e fragmentos florestais na conservao de espcies ar breas. Ph.D thesis, Universidade Estadual Paulista, Brazil. Machado ELM, Higashikawa EM, Macedo RLG, Venturin N, Naves ML, Gomes JE. 2005. Anlise da diversidade entre sistemas agrofl orestais em asssentamentos rurais no sul da Bahia. Revista Cientfica Eletrni ca de Engenharia Florestal 5:1-14 http://www.revista.inf.br/florestal/. Madritch MD, Hunter MD. 2005. Phenotypic variation in oak li tter influences shortand longterm nutrient cycling th rough litter chemistry. Soil Biology and Biochemistry 37: 319-327. Magurran AE. 2003. Measuring biological diversity. Oxford, UK: Blackwell. 155

PAGE 156

Martens H, Ns T. 1989. Multivariate calibration Chichester, UK: Wiley. Martini AMZ, Fiaschi P, Amorim AM, da Paixo JL. 2007. A hot-point with in a hot-spot: A high diversity site in Brazils Atlantic Forest. Biodiversity and Conservation 16: 31113128. Mathers NJ, Jalota RK, Dalal RC, Boyd SE. 2007. 13C-NMR analysis of decomposing litter and fine roots in the semi-arid Mu lga Lands of southern Queensland. Soil Biology and Biochemistry 39: 993-1006. McCarty GW, Reeves III JB, Reeves VB, Follett RF, Kimble JM. 2002. Mid-infrared and near-infrared diffuse reflectance spec troscopy for soil carbon measurement. Soil Science Society of America Journal 66: 640-646. McTiernan KB, Ineson P, Coward PA. 1997. Respiration and nutrient release from tree leaf litter mixtures. Oikos 78: 527-538. Melillo JM, Aber JD, Muratore JF. 1982. Nitrogen and lignin contro l of hardwood leaf litter decomposition dynamics. Ecology 63: 621-626. Miller RO. 1998. High temperature oxidation: Dry ashing. In: Kalra YP, ed. Handbook of reference methods for plant analysis Boca Raton, USA: CRC Press, 53-56. Miltner A, Zech W. 1998. Beech leaf litter degradation a nd transformation as influenced by mineral phases. Organic Geochemistry 28: 457-463. Montagnini F, Fanzeres A, Guimares da Vinha S. 1995. The potentials of 20 indigenous tree species for soil rehabilitation in the Atlantic Forest region of Bahia, Brazil. Journal of Applied Ecology 32: 841-856. Montagnini F, Nair PKR. 2004. Carbon sequestration: An u nderexploited environmental benefit of agroforestry systems. Agroforestry Systems 61-2: 281-295. Morellato LPC, Haddad CFB. 2000. Introduction: The Brazilian Atlantic Forest. Biotropica 32: 786-792. Mori SA, Boom BM, Carvalho AM, Santos TS. 1983. Southern Bahian moist forest. The Botanical Review 49: 155-232. Mouquet N, Moore JL, Loreau M. 2002. Plant species richness and community productivity: Why the mechanism that promotes coexistence matters. Ecology Letters 5: 56-65. Murphy J, Riley JP. 1962. A modified single solution me thod for the determination of phosphate in natural waters. Analytica Chimica Acta 27: 31-36. Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J. 2000. Biodiversity hotspots for conservation priorities. Nature 403: 853-858. 156

PAGE 157

Naeem S, Wright JP. 2003. Disentangling biodiversity e ffects on ecosystem functioning: Deriving solutions to a seem ingly insurmountable problem. Ecology Letters 6: 567-579. Nair PKR. 1989. Agroforestry systems in the tropics Dordrecht, the Netherlands: Kluwer Academic/ICRAF. Nei M. 1972. Genetic distances between populations. American Naturalist 106: 283-292. Nelson DW, Sommers LE. 1996. Total Carbon, Organic Carbon a nd Organic Matter. In: Bartels JM, ed. Methods of soil analysis, Part 3: Chemical methods Madison, USA: SSSA-CSAACS, 961-1010. NERC Northeastern Ecosystem Research Cooperative. 2006. Foliar chemistry database. USDA Forest Service Northeastern Research Station and University of New Hampshire Complex Systems Research Ce nter. www.folchem.sr.unh.edu. Niinemets U, Kull K. 2003. Leaf structure vs nutrient relations hips vary with soil conditions in temperate shrubs and trees. Acta Oecologica 24: 209-219. Nwoke OC, Vanlauwe B, Diels J, Sanginga N, Osonubi O. 2004. Impact of residue characteristics on phosphorus availability in West African moist savanna soils. Biology and Fertility of Soils 39: 422-428. Nye PH. 1961. Organic and nutrient cycles und er a moist tropical forest. Plant and Soil 13: 333346. Oliveira MA, Santos AMM, Tabarelli M. 2008. Profound impoverished of the large-tree stand in a hyper-fragmented landscape of the Atlantic forest. Forest Ecology and Management 256: 1910-1917. Orwin KH, Wardle DA, Greenfield LG. 2006. Ecological consequences of carbon substrate identity and diversity in a laboratory study. Ecology 87: 580-593. Palm CA, Sanchez PA. 1991. Nitrogen release from the leaves of some tropical legumes as affected by their lignin and polyphenolic contents. Soil Biology and Biogeochemistry 23: 83-88. Pasquini C. 2003. Near infrared spectroscopy: Fundament als, practical asp ects and analytical applications. Journal of the Brazil ian Chemical Society 14: 198-219. Pastor J, Cohen Y. 1997. Herbivores, the functional diversity of plants species, and the cycling of nutrients in ecosystems. Theoretical Population Biology 51: 165-179. Pavoine S, Ollier S, Pontier D. 2005. Measuring, diversity from dissimilarities with Rao's quadratic entropy: Are any dissimilarities suitable? Theoretical Population Biology 67: 231-239. 157

PAGE 158

Prez-Harguindeguy N, Diaz S, Cornelissen JHC, Vendramini F, Cabido M, Castellanos A. 2000. Chemistry and toughness predict leaf litter decomposition rates over a wide spectrum of functional types and taxa in central Argentina. Plant and Soil 218: 21-30. Prez-Harguindeguy N, Blundo CM, Gurvich DE, Daz S, Cuevas E. 2008. More than the sum of its parts? Assessing litter heterogeneity effects on the decomposition of litter mixtures through leaf chemistry. Plant and Soil 303: 151-159. Petchey OL, Gaston KJ. 2002. Functional diversity (FD), sp ecies richness and community composition. Ecology Letters 5: 402-411. Petchey OL, Gaston KJ. 2006. Functional diversity : Back to basics and looking forward. Ecology Letters 9: 741-758. Peterson BJ, Fry B. 1987. Stable isotopes in ecosystem studies. Annual Review of Ecology and Systematics 18: 293-320. Phillips OL. 1997. The changing ecology of tropical forests. Biodiversity and Conservation 6: 291-311. Pollierer MM, Langel R, Krner C, Maraun M, Scheu S. 2007. The underestimated importance of belowground carbon input for forest soil animal food webs. Ecology Letters 10: 729 736. Post WM, Emanuel WR, Zinke PJ, Stangenberger AG. 1982. Soil carbon pools and world life zones. Nature 298: 156-159. Preston CM, Trofymow JA. 2000. Variability in litter quality and its relationship to litter decay in Canadian forests. Canadian Journal of Botany-Revu e Canadienne de Botanique 78: 1269-1287. Qu XH,Wang JG. 2008. Effect of amendments with differe nt phenolic acids microbial biomass, activity, and community diversity. Applied Soil Ecology 39: 172-179. R Development Core Team. 2006. R: A language and environment for statistical computing R Foundation for Statistical Co mputing, Vienna, Austria. ISBN 3-900051-07-0-URL http://www.R-project.org. Raich JW, Russell AE, Bedoya-Arrieta R. 2007. Lignin and enhanced l itter turnover in tree plantations of lowland Costa Rica. Forest Ecology and Management 239: 128-135. Rao CR. 1982. Diversity and dissimilarity co efficients: A unified approach. Theoretical Population Biology 21: 24-43. Rao IM, Ayarza MA, Thomas, RJ. 1994. The use of carbon-isotope ratios to evaluate legume contribution to soil enhancement in tropical pastures. Plant and Soil 162: 177-182. 158

PAGE 159

Rasse DP, Rumpel C, Dignac M-F. 2005. Is soil carbon mostly root carbon? Mechanisms for a specific stabilization. Plant and Soil 269: 341-356. Rassmussen C, Southard RJ, Horwath WR. 2006. Mineral control of organic matter mineralization in a range of te mperate conifer forest soils. Global Change Biology 12: 834-847. Reeves III JB. 1993. Infrared spectroscopic studies on forage and by-product fibre fractions and lignin determination residues. Vibrational Spectroscopy 5: 303-310. Reeves III JB. 1998. Improvement in Fourier nearand mid-infrared diffuse reflectance spectroscopic calibrations through the use of a samp le transport device. Applied Spectroscopy 50: 965-969. Rice RA, Greenberg R. 2000. Cacao cultivation and conservation of biological diversity. Ambio 29: 167-173. Ricotta C. 2005. A note on functional diversity measures. Basic Applied Ecology 6: 479-486. Rodrguez-Loinaz G, Onaindia M, Amez aga I, Mijangos I, Garbisu C. 2008. Relationship between vegetation diversity a nd soil functional diversity in native mixed-oak forests. Soil Biology and Biochemistry 40: 49-60. Rolim SG, Chiarello AG. 2004. Slow death of Atlantic Forest trees in cocoa agroforestry in southeastern Brazil. Biodiversity and Conservation 13: 2679-2694. Rothe A, Binkley D. 2001. Nutritional interactions in mixed species forests: A synthesis. Canadian Journal of Forest Research 31: 1855-1870. Rothe J, Gleixner G. 2000. Do stable isotopes reflect the f ood web development in regenerating ecosystems? Isotopes in Environmental and Health Studies 36: 285-301. Rovira P, Vallejo VR. 2002. Mineralization of carbon and ni trogen from plant debris, as affected by debris size and depth of burial. Soil Biology and Biochemistry 34: 327-339. Ruess L, Tiunov AI, Haubert D, Richnow HH, Hggblom, Scheu S. 2005. Carbon stable isotope fractionation and trophic transfer of fatty acids in fungal based soil food chains. Soil Biology and Biochemistry 37: 945-953. Saatchi S, Agosti D, Alger K, Delabie J, Musinsky J. 2001. Examining fragmentation and loss of primary forest in the sout hern Bahian Atlantic Forest of Brazil with radar imagery. Conservation Biology 15: 867-875. Salamanca EF, Kaneko N, Katagiri S. 1998. Effects of leaf litter mixtures on the decomposition of Quercus serrata and Pinus densiflora using field and laboratory microcosm methods. Ecological Engineering 10: 53-73. 159

PAGE 160

Salamon JA, Alphei J, Ruf A, Schaefer M, Scheu S, Schneider K, Suhrig A, Maraun M. 2006. Transitory dynamic effects in the soil i nvertebrate community in a temperate deciduous forest: Effects of resource quality. Soil Biology and Biochemistry 38: 209-221. Sambuichi RHR. 2002. Fitossociologia e diversidade de espcies arbreas em cabraca na regio sul da Bahia, Brasil. Acta Botanica Brasileira 16: 89-101. Sambuichi RHR, Haridasan M. 2003. Nutrio mineral das espcies arboreas em cabrucas na regio sul da Bahia. VI Congresso de Ecologia do Brasil, 9-14, November, CE. Anais de trabalhos Completos 3: 351-352. Sambuichi RHR, Haridasan M. 2007. Recovery of species richne ss and conservation of native Atlantic forest trees in the cacao plantations of southern Bahia in Brazil. Biodiversity and Conservation 16: 3681-3701. Santana SO, Ramos JV, Ruiz MAM, Arajo QR, Almeida HA, Faria Filho, AF, Mendona JR, Santos LFC. 2003. Zoneamento agroecolgico do muni cipio de Ilhus, Bahia, Brasil CEPLAC/CEPEC. Boletim Tcnico No. 186. 44pp. Santos BA, Peres CA, Oliveira MA, Grillo A, Alves-Costa CP, Tabarelli M. 2008. Drastic erosion in functional attribut es of tree assemblages in Atlantic forest fragments of northeastern Brazil. Biological Conservation 141: 249-260. Sarkhot DV, Comerford NB, Jokela EJ, Reeves III JB, Harris WG. 2007. Aggregation and aggregate carbon in a forested sout heastern coastal plain Spodosol. Soil Science Society of America Journal 71: 1779-1787. Sato S, Comerford NB. 2006. Organic anions and phosphorus de sorption and bioa vailability in a humid Brazilian Ultisol. Soil Science 171: 695-705. Sauer TJ, Cambardella CA, Brandle JR. 2007. Soil carbon and tree litter dynamics in a red cedar-scotch pine shelterbelt. Agroforestry Systems 71: 163-174. Savitzky A, Golay MJE. 1964. Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry 36: 1627-1639. Scheu S. 1995. Linkages between tree diversity, soil fauna and ecosystem processes. In: SchererLorenzen M, Krner C, Schulze ED eds. Forest diversity and function. Berlin, Germany: Springer, 211-233. Schimel DS. 1995. Terrestrial ecosystems and the carbon-cycle. Global Change Biology 1: 7791. Schimel JP, Httenschwiler S. 2007. Nitrogen transfer between decomposing leaves of different N status. Soil Biology and Biochemistry 39: 1428-1436. 160

PAGE 161

Schulp CJE, Nabulars GJ, Verburg PH, de Waal RW. 2008. The effect of tree species on carbon stocks in forest floor and mineral soil and implications for soil carbon inventories. Forest Ecology and Management 256: 482-490. Schulz B, Becker B, Gtsch E. 1994. Indigenous knowledge in a modern sustainable agroforestry system-a case study from eastern Brazil. Agroforestry Systems 25: 59-69. Schulze ED. 2006. Biological controls of th e terrestrial carbon sink. Biogeosciences 3: 147-166. Schweitzer JA, Bailey JK, Hart SC, Whitham TG. 2005. Non-additive effects of mixing cottonwood genotypes on litter decomposition and nutrient dynamics. Ecology 86: 28342840. Schwendener CM, Lehmann J, de Camargo PB. 2005. Nitrogen transfer between highand low-quality leaves on a nutrient-poor Oxisol determined by 15N enrichment. Soil Biology and Biochemistry 37: 787-794. Schroth G, Harvey CA. 2007. Biodiversity conservation in cocoa production landscapes: An overview. Biodiversity and Conservation 16: 2237-2244. Seastedt TR. 1984. The role of microarthropods in decomposition and mineralization processes. Annual Review of Entomology 29: 25-46. Seneviratne G. 2000. Litter quality and nitrogen release in tropical agriculture: A synthesis. Biology and Fertility of Soils 31: 60-64. Shepherd KD, Vanlauwe B, Gachengo CN, Palm CA. 2005. Decomposition and mineralization of organic residues pred icted using near infrared spectroscopy. Plant and Soil 277: 315-333. Shepherd KD, Walsh MG. 2002. Development of spectral libraries for characterization of soil properties. Soil Science Society of America Journal 66: 988-998. Shimatani K. 2001. On the measurement of species divers ity incorporating species differences. Oikos 93: 135-147. Silver WL, Brown S, Lugo AE. 1996. Effects of changes in biodi versity on ecosystem function in tropical forests. Conservation Biology 10: 17-24. Six J, Guggenberger K, Paustian L, Haumaier, Elliott ET, Zech W. 2001. Sources and composition of soil organic matter fractions between and within soil aggregates. European Journal of Soil Science 52: 607-618. Smith CK, Gholz HL, De Assis Oliveira F. 1998. Fine litter chemistry, early-stage decay and nitrogen dynamics under plan tations and primary forest in lowland Amazonia. Soil Biology and Biochemistry 30: 2159-2169. 161

PAGE 162

Smith VC, Bradford MA. 2003. Do non-additive effects on decomposition in litter-mix experiments result from differences in resource quality between litters? Oikos 102: 235242. Sonwa DJ, Nkongmeneck BA, Weise SF, Tc hatat M, Adesina AA, Janssens MJJ. 2007. Diversity of plants in cocoa agroforests in the humid forest zone of Southern Cameroon. Biodiversity and Conservation 16: 2385-2400. Staddon PL. 2004. Carbon isotopes in functional soil ecology. Trends in Ecology and Evolution 19: 148-154. Stahl PD, Christensen M. 1992. In vitro mycelial interactions among members of a soil microfungal community. Soil Biology and Biochemistry 24: 309-316. StatSoft, Inc. 2004. STATISTICA (data analysis so ftware system), version 7. www.statsoft.com. Stuart B. 1997. Biological applications of infrared spectroscopy Chichester, UK: Wiley. Sulzman EW, Brant JB, Bowden RD, Lajtha K. 2005. Contribution of aboveground litter, belowground litter, and rhizos phere respiration to soil CO2 efflux in an old growth coniferous forest. Biogeochemistry 73: 231-256. Swan CM, Palmer MA. 2006. Composition of speciose leaf litte r alters stream detritivore growth, feeding activity and leaf breakdown. Oecologia 147: 469-478. Swift MJ, Heal OW, Anderson JM. 1979. Decomposition in terrestrial ecosystems Oxford, UK: Blackwell. Tabanez AAJ, Viana VM. 2000. Patch structure within Brazilian Atlantic Forest fragments and implications for conservation. Biotropica 34: 925-933. Tanner EVJ. 1977. Four montane rain forests of Jamaica: A quantitative characterization of the floristics, the soils and the foliar mineral le vels and a discussion of the interrelations. Journal of Ecology 65: 883-918. Tenney FG, Waksman SA. 1929. Composition of natural organic materials and their decomposition in the soil: IV The nature and the rapidity of decom position of the various organic complexes in different plant materials, under aerobic conditions. Soil Science 28: 55-84. Thomas WW. 2003. Natural Vegetation Types in Southern Bahia. In: Prado PI, Landau EC, Moura RT, Pinto LPS, Fonseca GAB, Alger K, orgs. Corredor de biodiversidade da Mata Atlntica do sul da Bahia. Publicao em CD-ROM, Ilhus Brazil: IESB/ CI / CABS / UFMG / UNICAMP. Thomas WW, de Carvalho AAMV, Amorim AMA, Garrison J, Arbelaez AL. 1998. Plant endemism in two forests in southern Bahia, Brazil. Biodiversity Conservation 7: 311-322. 162

PAGE 163

Thompson J, Proctor J, Viana V, Milliken W, Rater JA, Scott DA.1992. Ecological studies on a lowland evergreen forest on Maraca Island, Roraima, Brazil. I. Physical environment, forest structure and leaf chemistry. Journal of Ecology 80: 689-703. Tian G, Brussard L, Kang BT. 1995. Plant residue decomposition in the humid tropicsinfluence of chemical composition and soil fauna. In: Reddy VM ed. Soil organisms and litter decomposition in the tropics Boulder, USA: Westview Press. Tilman D. 1999. The ecological consequences of changes in biodiversity: A search for general principles. Ecology 80: 1455-1474. Townsend AR, Asner GP, Cleveland CC. 2008. The biogeochemical heterogeneity of tropical forests. Trends in Ecology and Evolution 23: 424-431. Trofymow JA, Moore TR, Titus B, Prescott C, Morrison I, Siltanen M, Smith S, Fyles J, Wein R, Camir C, Duschene L, Kozak L, Kranabetter M, Visser S. 2002. Rates of litter decomposition over 6 year s in Canadian forests: Infl uence of litter quality and climate. Canadian Journal of Forest Research 32: 789-804. Trofymow JA, Preston CM, Prescott CE. 1995. Litter quality and its po tential effect on decay rates of materials from Canadian forests. Water Air and Soil Pollution 82: 215-226. Trumbore SE. 2006. Carbon respired by terrestrial ecosystems-recent progress and challenges. Global Change Biology 12: 141-153. Vanlauwe B, Diels J, Sanginga N, Merckx R. 1997. Residue quality and decomposition: An unsteady relationship? In: Cadisch G, Giller KE (eds) Driven by nature: Plant litter quality and decomposition, pp157-166. Vinha SG, da Silva LAM. 1982. rvores aproveitadas como sombreadoras de cacaueiros no sul da Bahia e norte do Esprito Sant o. Ilhus, Brazil: CEPLAC-CEPEC. Violle C, Navas ML, Vile D, Kazakou E, Fortunel C, Hummel I, Garnier E. 2007. Let the concept of trait be functional! Oikos 116: 882-892. Viscarra-Rossel RA. 2008. ParLeS: Software for chemometri c analysis of spectroscopic data. Chemometrics and Intellig ent Laboratory Systems 90: 72-83. Vitorello VA, Ceri CC, Andreux F, Feller C, Victoria RL. 1989. Organic-matter and natural C-13 distribution in forested and cultivated Oxisols. Soil Science Society of America Journal 53: 773-778. Vitousek P, Gerrish G, Turner D, Walker L, Muellerdombois D. 1995. Litterfall and nutrient cycling in 4 Hawaiian montane rain forests. Journal of Tropical Ecology 11: 189-203. Waksman SA, Tenney FG. 1928. Composition of natural organic materials and their decomposition in the soil. III: The influence of nature of plant upon the rapidity of its decomposition. Soil Science 26: 155-171. 163

PAGE 164

164 Walker B, Kinzig A, Langridge J. 1999. Plant attribute diversity, resilience, and ecosystem function: The nature and significance of dominant and minor species. Ecosystems 2: 95113. Wardle DA, Bonner KI, Nicholson KS. 1997. Biodiversity and plant litter: experimental evidence which does not suppor t the view that enhanced species richness improves ecosystem function. Oikos 79: 247-258. Weber KP, Grove JA, Gehder M, Anderson WA, Legge RL. 2007. Data transformations in the analysis of community-level substr ate utilization data from microplates. Journal of Microbiological Methods 69: 461-469. Westerhaus M, Workman Jr. J, Reeves II JB, Mark H. 2004. Quantitative analysis. In: Roberts CA, Workman Jr. J, Reeves III JB, eds. Near Infrared Reflectance Spectroscopy, Agronomy Monograph no. 44 Madison, USA: ASA/ CSA/ SSSA, 133-174. Williams BL. 1994. Interactions between tree species and their effects on nitrogen and phosphorus transformations in the forest floor. In: Boyle TJB, Boyle CEB, eds. Biodiversity, temperate ec osystems, and global change Berlin, Germany: Springer-Verlag, 357-370. Xiang W, Bauhus J. 2007. Does the addition of leaf litter from N-fixing Acacia mearnsii accelerate leaf decomposition of Eucalyptus globulus ? Australian Journal of Botany 55: 576-583. Zimmer M. 2002. Is decomposition of woodland leaf litte r influenced by its species richness? Soil Biology and Biochemistry 34: 277-284.

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BIOGRAPHICAL SKETCH The author was born and raised in Jamaica, New York in an auspicious year for New Yorkers (Subway Series, Woodstock, alleged men on Moon). At the age of five, after hearing that stars were round, self-luminous gaseous spheres instead of the silver things that adorned her kindergarten drawings, she decided on a future in astrophysics. Epps was given a good start at Eastwood Elementary (aka P.S. 95Q), the Im maculate Conception School, and the Bronx High School of Science. She remained faithful to her original plan and entere d Harvey Mudd College in Claremont, California, from which she graduate d with a degree in physic s with an emphasis in astrophysics. Immediately thereafter, the author strayed from the heavenly spheres and headed south, literally, to New Orlean s, Louisiana and attemp ted to establish a car eer in photography but was instead waylaid by music after spotting a cello for sale in th e window of Werleins. Some years of lessons and music production followed, to varying degrees of succe ss, and her return to the West Coast marked an exciting and eclectic period during which she served the community as a waitress, fisherman, cook, st ore clerk, and SAT tutor. The inescapable necessity of reliable income led the author to the San Francisco School where she began as a part-time algebra teacher and left four years late r as the eighth grade teacher. Af ter graduating a second time from the eighth grade, Ms. Epps entered the Unite d States Peace Corps as a volunteer in the Agroforestry Program in Cameroon, Central Africa, where she was introduced to soil in all of its glory and, became fascinated with phosphorus. Returning early from Peace Corps service, Ms Epps entered gra duate school at the University of California Davis in the Program in International Agricultural Development with an emphasis in soil science. She later applied to the Department of Soil Science from which she earned her masters degree. A visit to the Univ ersity of Florida to resolve laboratory trouble

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with a method of sequential phos phorus fractionation of wetland se diments led her to converse with Dr. Nicholas B. Comerford to whom she is grateful for all that followed.