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Effects of Conservation Tillage in Soil Carbon Sequestration and Net Revenues of Potato-Based Rotations in the Colombian...

Permanent Link: http://ufdc.ufl.edu/UFE0025114/00001

Material Information

Title: Effects of Conservation Tillage in Soil Carbon Sequestration and Net Revenues of Potato-Based Rotations in the Colombian Andes
Physical Description: 1 online resource (103 p.)
Language: english
Creator: Quintero, Marcela
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: aggregates, agriculture, carbon, revenues, soil, tillage
Soil and Water Science -- Dissertations, Academic -- UF
Genre: Soil and Water Science thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: EFFECTS OF CONSERVATION TILLAGE IN SOIL CARBON SEQUESTRATION AND NET REVENUES OF POTATO-BASED ROTATIONS IN THE COLOMBIAN ANDES Over 60% of the world?s carbon is held in both soils (more than 41%) and the atmosphere (as carbon dioxide; 20%)). However, soil disturbance is redistributing the carbon, augmenting the atmospheric carbon pool. Thus, a part of carbon dioxide increase in the atmosphere is thought to come from agriculture, affecting not just climate change but also productivity and sustainability of agriculture and natural resources. This study was undertaken to investigate the contribution of conservation tillage practices in potato-based rotations of the Fuquene Lake watershed in the Colombian Andes, to reduce Greenhouse Gases (GHG) emissions, sequester soil carbon, to rehabilitate water and carbon-related soil characteristics, and to understand the opportunity costs of changing from conventional to conservation tillage. Field soil sampling was conducted in 7-years old conservation tillage farms and in farms with conventional tillage practices. Soil samples were analyzed in the lab to determine Soil Organic Carbon stocks, SOC in soil aggregates by applying ultrasound, and water-related physical characteristics. In addition GHG net emissions were calculated for conservation and conventional tillage, and contrasted with net revenues. As a result, conservation tillage in potato-based systems improved in a 7 year period the soil organic matter and carbon content in these disturbed soils. The soil carbon concentration in the whole profile was 29% higher under conservation tillage than under conventional tillage sites and the carbon content was higher by 45%. C content improvement specially occurred in the subsoil (A2 horizon) increasing by 177% although most of the C is stored in the top A1 horizon. This improvement was correlated to the enhancement of soil physical characteristics related with soil water movement and storage such us bulk density, AWC, saturated hydraulic conductivity and mesoporosity. In another hand OM in aggregates represented more than 80% of total OM of these soils and was positively affected by conservation tillage. This improvement showed a preferential C sequestration in smaller macroaggregates ( < 2 mm). The aggregate dispersion energy curves further suggest this is happening in microaggregates within the smaller macroaggregates fraction. A complementary tradeoff between the economic and environmental benefits was found for our study site. This relies on the fact net farmer revenues were increased ?by reduced machinery operations and fertilizers applications?, while GHG emissions were reduced ?by increasing soil carbon retention and reducing GHG emissions from machinery operations?. Thus, although conservation tillage practices are not widely adopted in the watershed, payments for net GHG removals could increase more the net revenues and facilitate the investment to cover initial extra costs of conservation agriculture (ie. cultivation of oat as cover crop).
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 Marcela Quintero.
Thesis: Thesis (M.S.)--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: UFE0025114:00001

Permanent Link: http://ufdc.ufl.edu/UFE0025114/00001

Material Information

Title: Effects of Conservation Tillage in Soil Carbon Sequestration and Net Revenues of Potato-Based Rotations in the Colombian Andes
Physical Description: 1 online resource (103 p.)
Language: english
Creator: Quintero, Marcela
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: aggregates, agriculture, carbon, revenues, soil, tillage
Soil and Water Science -- Dissertations, Academic -- UF
Genre: Soil and Water Science thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: EFFECTS OF CONSERVATION TILLAGE IN SOIL CARBON SEQUESTRATION AND NET REVENUES OF POTATO-BASED ROTATIONS IN THE COLOMBIAN ANDES Over 60% of the world?s carbon is held in both soils (more than 41%) and the atmosphere (as carbon dioxide; 20%)). However, soil disturbance is redistributing the carbon, augmenting the atmospheric carbon pool. Thus, a part of carbon dioxide increase in the atmosphere is thought to come from agriculture, affecting not just climate change but also productivity and sustainability of agriculture and natural resources. This study was undertaken to investigate the contribution of conservation tillage practices in potato-based rotations of the Fuquene Lake watershed in the Colombian Andes, to reduce Greenhouse Gases (GHG) emissions, sequester soil carbon, to rehabilitate water and carbon-related soil characteristics, and to understand the opportunity costs of changing from conventional to conservation tillage. Field soil sampling was conducted in 7-years old conservation tillage farms and in farms with conventional tillage practices. Soil samples were analyzed in the lab to determine Soil Organic Carbon stocks, SOC in soil aggregates by applying ultrasound, and water-related physical characteristics. In addition GHG net emissions were calculated for conservation and conventional tillage, and contrasted with net revenues. As a result, conservation tillage in potato-based systems improved in a 7 year period the soil organic matter and carbon content in these disturbed soils. The soil carbon concentration in the whole profile was 29% higher under conservation tillage than under conventional tillage sites and the carbon content was higher by 45%. C content improvement specially occurred in the subsoil (A2 horizon) increasing by 177% although most of the C is stored in the top A1 horizon. This improvement was correlated to the enhancement of soil physical characteristics related with soil water movement and storage such us bulk density, AWC, saturated hydraulic conductivity and mesoporosity. In another hand OM in aggregates represented more than 80% of total OM of these soils and was positively affected by conservation tillage. This improvement showed a preferential C sequestration in smaller macroaggregates ( < 2 mm). The aggregate dispersion energy curves further suggest this is happening in microaggregates within the smaller macroaggregates fraction. A complementary tradeoff between the economic and environmental benefits was found for our study site. This relies on the fact net farmer revenues were increased ?by reduced machinery operations and fertilizers applications?, while GHG emissions were reduced ?by increasing soil carbon retention and reducing GHG emissions from machinery operations?. Thus, although conservation tillage practices are not widely adopted in the watershed, payments for net GHG removals could increase more the net revenues and facilitate the investment to cover initial extra costs of conservation agriculture (ie. cultivation of oat as cover crop).
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 Marcela Quintero.
Thesis: Thesis (M.S.)--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: UFE0025114:00001


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1 EFFECTS OF CONSERVATION TILLAGE IN SOIL CARBON SEQUESTRATION AND NET REVENUES OF POTATO-BASED ROTATIONS IN THE COLOMBIAN ANDES By MARCELA QUINTERO A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2009

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2 2009 Marcela Quintero

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3 To my husband, family and mentors

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4 ACKNOWLEDGMENTS I want to express my special gratitude to my advisor Dr. Nicholas Comerford for his constant and wise support and advice during my Mast er studies and this research work. Also, for understanding my time constraints resulting from being studying and working at the same time overseas; for facilitating the trips and accommodati on to the University of Florida; for teaching me lab methods to investigate soil carbon in aggr egates; and specially for knowing how to orient my work in such a keen manner that still allowed me to be creative. I wish also to thank to my co-advisor Ruben D. Estrada, from CIAT (Intern ational Center for Trop ical Agriculture), who has been my mentor during my last 7 years of pr ofessional experience and encouraged me to take the challenge of getting involved in this Distance Educa tion Master Program offering his constant support and flexibility for allowing me to take the courses. His past contribution to my professional experience by teachi ng me methods for economic assessment of production systems and to prepare myself for multidisciplinary work has been indispensable for this work. Also, I would like to thank Dr. Janaki Alavalapati for accepting being part of the advisory committee although I was not in his department and even mo re for offering me a forest resources economic course by distance which at that moment was no t completely design for overseas students. His presence in the committee permitted to have a multidisciplinary advice which was important for ensuring that all disciplines addressed in this thesis we re adequately reviewed. I also wish to thank Arnulfo Rodriguez, a CI AT technician, whose he lp was crucial during the field work by helping me to dig several pits in the soil and taking adequately soil samples. Also for his willingness to learn about sonication procedures and therefore, helping me in the lab analyzing the samples with this procedure. I also acknowledge the Andean Watersheds Project (CONDESANConsortium for Sustainable Deve lopment of the Andean Ecoregion; and GTZ Technical German Cooperation) and the CGIAR (Consultative Group for International

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5 Agricultural Research) Challenge Program on Water & Food for providing the needed financial support to cover tuition fees and fo r permitting me to include this re search work as part of their research projects. Also, I thank CIAT for empl oying me while I was studying and for offering an adequate environment and facilitie s for conducting this research. Also, I want to express my gratitude to W ilson Otero and Diego Lopez from GTZ and the regional environmental authority (CARRegional Autonomous Corporation) and its conservation agriculture ex tension agents for providing economic data about these systems in the study area. Also, to all farmers of Carmen de Car upa municipality (Colombia) that allowed me to take soil samples in their parcels and helped me to coordinate the field visits. To finalize, my special gratitude to my family for been very respectful and supportive dur ing the development of my career and to my husband for constantly encouraging me to keep working on my thesis and for understanding when familiar time had to be sacrif iced to dedicate myself to activities of this research work.

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4 LIST OF TABLES ...........................................................................................................................9 LIST OF FIGURES .......................................................................................................................11 ABSTRACT ...................................................................................................................... .............12 CHAPTER 1 INTRODUCTION ................................................................................................................ ..14 Importance of Soil Aggregation and So il Management Practices for Carbon Sequestration ................................................................................................................. ......14 The Need to Measure Soil Organic Carbon (S OC) in Conservation Tillage Sites in the Andes and Its Economic Returns ........................................................................................15 2 EFFECTS OF CONSERVATION TILLAGE ON SOIL ORGANIC CARBON (SOC) AND SOIL PHYSICAL CHARACTERISTICS ....................................................................18 Introduction .................................................................................................................. ...........18 Materials and Methods ...........................................................................................................21 Study Sites .......................................................................................................................21 Laboratory Methods ........................................................................................................22 Data Analyses ..................................................................................................................23 Results .....................................................................................................................................23 Soil Descriptions, Physical Characteristics and Horizon Differences .............................23 Effect of Conservation and Conventi onal Tillage on Soil Characteristics ......................25 Soil Carbon Content a nd Tillage Systems .......................................................................25 Discussion .................................................................................................................... ...........26 Conclusions .............................................................................................................................30 3 EFFECTS OF CONSERVATION AND CONVENTIONAL AGRICULTURE ON AGREGATED ORGANIC CARBON (AOM) OF ANDEAN SOILS ..................................35 Introduction .................................................................................................................. ...........35 Materials and Methods ...........................................................................................................38 Study Site .........................................................................................................................38 Laboratory Methods ........................................................................................................39 Data Analyses ..................................................................................................................41 Results .....................................................................................................................................42 Total AOM ......................................................................................................................43 Aggregation Hierarchy ....................................................................................................44 Discussion .................................................................................................................... ...........44

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7 Higher AOM and Soil Organic Matter (SOM) in Conservation Tillage .........................44 Higher AOM and SOM in Smaller Macroaggregates .....................................................45 Other Considerations .......................................................................................................47 Conclusions .............................................................................................................................49 4 EFFECTS OF CONSERVATION TILL AGE ON ECONOMIC RETURNS AND GREENHOUSE GAS (GHG) REDUCTIONS IN THE ANDES ..........................................55 Introduction .................................................................................................................. ...........55 Methods ..................................................................................................................................57 Economic Analysis ..........................................................................................................57 Net GHG Removals .........................................................................................................59 Nitrous oxide (N2O) emissions from fertilizers .......................................................60 GHG emissions from burning of fossil fuel .............................................................60 Emissions from livestock .........................................................................................61 Results .....................................................................................................................................63 Economic Analysis ..........................................................................................................63 Net GHG Removals .........................................................................................................63 Discussion .................................................................................................................... ...........64 Conclusions .............................................................................................................................68 5 SUMMARY AND CONCLUSIONS .....................................................................................74 The Rehabilitation Ability of C onservation Tillage in Disturbed Paramo Soils ...................74 In Which Soil Fraction Soil Organic Car bon (SOC) and Soil Organic Matter (SOM) Improvements Are Occurring? ............................................................................................75 Changing To Conservation Tillage: A Trad e Off Between Net Economic Revenues And Net Greenhouse Gas (GHG) Removals?.............................................................................76 Further Research Needs ..........................................................................................................78 General Conclusions ...............................................................................................................79 APPENDIX A DESCRIPTION OF SOIL PROFILES ...................................................................................81 B EFFECTS OF DIFFERENT MANAGEMENT SYSTEMS AND ENERGY INPUTS ON AGGREGATED ORGANIC MATTER (AOM) .............................................................83 C DESCRIPTION OF A MODEL FOR THE ECONOMIC, SOCIAL, AND ENVIRONMENTAL EVALUATION OF LAND USE (ECOSAUT) ..................................90 Information on Production Systems .......................................................................................90 Agriculture .......................................................................................................................90 Livestock1 ........................................................................................................................91 Information Related To Externalities .....................................................................................92 Sedimentation Processes .................................................................................................92 Availability of Water in Water Resources .......................................................................92 Carbon Sequestration .......................................................................................................92

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8 Water Pollution ................................................................................................................92 Information Related to Climatic Risks ...................................................................................93 LIST OF REFERENCES ...............................................................................................................94 BIOGRAPHICAL SKETCH .......................................................................................................103

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9 LIST OF TABLES Table page 2-1 Effects of treatment and horizon on soil characteristics ...................................................31 2-2 Comparison of soil character istics across soil horizons ...................................................32 2-3 Comparison of soil characteristics across soil treatments .................................................33 2-4 Correlation between physical soil characteristics a nd soil organic matter (SOM) ...........34 2-5 Effects of treatment and horizon on soil carbon content ..................................................34 2-6 Effects of horizon and tr eatment on soil carbon content ..................................................34 3-1 Effects of management systems, aggregate size and energy level on %AOM (Aggregated Organic Matter) for horizon A1 and A2 .......................................................50 3-2 Analysis of variance of %AOM and energy levels per size fraction classes in Horizon 1 ..................................................................................................................... ......50 3-3 Analysis of variance of %AOM and energy levels per size fraction classes in Horizon A2.........................................................................................................................50 3-4 Comparison between %AOM in differe nt management systems and horizons for size fraction 2 (2 mm) ....................................................................................................50 3-5 Duncan test post hoc for AOM and size fractions from Horizons A1 and A2 ...............53 4-1 Summary of annual inputs cost, pro ducts prices, productivity and livestock parameters used in economic analysis. ..............................................................................70 4-2 Economic benefits from conventional and conservation tillage in potato-based systems in Fuquene watershed (Colombia)*. ....................................................................72 4-3 Annual average values for potato production under two tillage systems .........................72 4-4 Carbon stock changes and Greenhouse gas (GHG) emissions of conventional tillage practices in potato-based production systems in Fuquene watershed, Colombia ..............73 4-5 Carbon stock changes and GHG emissions of conservation tillage practices in potato-based production systems in Fuquene watershed, Colombia .................................73 A-1 Description of soil profiles in conser vation and conventional tillage sites of the Upper Fuquene Lake watershed .........................................................................................81 B-1 Effect of treatment and energy levels in %AOM in aggregates of size fraction 3 (1 mm) in the horizon 1. .........................................................................................................83

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10 B-2 Effect of treatment and energy levels in %AOM in aggregates of size fraction 3 (1 mm) in the horizon 2. .........................................................................................................84 B-3 Effect of treatment and energy levels in %AOM in aggregates of size fraction 4 (0.5 mm) in the horizon 2. .............................................................................................85 B-4 Analysis of variance of AOM (g/g), en ergy levels and treatments per size fraction classes in two horizons.......................................................................................................8 6 B-5 Comparison between AOM and SOC (g/g ) (Soil Organic Carbon) in different management systems, horizons and size fractions. ............................................................86 B-6 Effect of treatment and energy levels on AOM(g/g) in aggregates of size fraction 3 (1 mm) in the horizon 2. ................................................................................................87 B-7 Effect of treatment and energy levels on AOM(g/g) in aggregates of size fraction 4 (0.5 mm) in the horizon 2. .............................................................................................88 B-8 Analysis of variance of Tota l %AOM using the log of 101-AOM% ..............................88 B-9 Non parametric analysis of % AOM in Horizon 1 ...........................................................89 C-1 Principal variables and decision al ternatives in the optimization model ..........................91

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11 LIST OF FIGURES Figure page 2-1 Soil profiles in six different sites. A C) Sites with conservation agriculture; DE) Sites with conventi onal agriculture. ...................................................................................31 2-2 Volumetric water content at different matrix potentials in selected soil profile horizons ...................................................................................................................... ........32 2-3 Volumetric water content at different tillage systems in selected soil profile horizons ...33 3-1 Aggregated organic matte r (percent of total organic matter) of all aggregates size fractions from horizon A1 (top horizon) ............................................................................51 3-2 Aggregated organic matte r (percent of total organic matter) of all size fractions aggregates of horizon A2 ...................................................................................................51 3-3 Effect of different management syst ems on aggregated organic matter (g/g) of different size fractions horizon A1. ...................................................................................52 3-4 Effect of different management syst ems on aggregated organic matter (g/g) of different size fractions horizon A2. ...................................................................................52 3-5 Effect of different management syst ems on aggregated organic matter (g/g) of different size fractions of horizon A2. ...............................................................................53 3-6 Non-parametric analysis of %AOM in Conservation agricult ure vs. Conventional agriculture for size fraction 2 (>2mm) and Horizon A1. ...................................................54 3-7 Non-parametric analysis of %AOM in Conservation agricult ure vs. Conventional agriculture for size fraction 3 (>1mm) and Horizon A1. ...................................................54 B-1 Aggregated organic matter (percent of total organic matter) of > 5 mm and 0.5 mm aggregates size fractions, released with different energy inputs, in two management systems. ........................................................................................................89

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12 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science EFFECTS OF CONSERVATION TILLAGE IN SOIL CARBON SEQUESTRATION AND NET REVENUES OF POTATO-BASED ROTA TIONS IN THE COLOMBIAN ANDES By Marcela Quintero August 2009 Chair: Nicholas B. Comerford Major: Soil and Water Sciences Over 60% of the worlds carbon is held in bot h soils (more than 41%) and the atmosphere (as carbon dioxide; 20%)). However, soil distur bance is redistributi ng the carbon, augmenting the atmospheric carbon pool. Thus, a part of car bon dioxide increase in the atmosphere is thought to come from agriculture affecting not just climate ch ange but also productivity and sustainability of agriculture and natural resour ces. This study was undertak en to investigate the contribution of conservation till age practices in potato-based rotations of the Fuquene Lake watershed in the Colombian Andes, to redu ce Greenhouse Gases (GHG) emissions, sequester soil carbon, to rehabilitate water and carbon-rela ted soil characteristics, and to understand the opportunity costs of changing from conventional to conservation ti llage. Field soil sampling was conducted in 7-years old conservation tillage fa rms and in farms with conventional tillage practices. Soil samples were anal yzed in the lab to determine Soil Organic Carbon stocks, SOC in soil aggregates by applying ultrasound, and wate r-related physical char acteristics. In addition GHG net emissions were calculated for conserva tion and conventional tillage, and contrasted with net revenues. As a result, conservation tilla ge in potato-based systems improved in a 7 year period the soil organic matter and carbon conten t in these disturbed soils. The soil carbon

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13 concentration in the whole profile was 29% higher under conservation tillage than under conventional tillage sites and the carbon cont ent was higher by 45%. C content improvement specially occurred in the subsoil (A2 horizon) increasing by 177% although most of the C is stored in the top A1 horizon. This improvement was correlated to th e enhancement of soil physical characteristics related with soil wate r movement and storage such us bulk density, AWC, saturated hydraulic conductivity and mesopor osity. In another hand OM in aggregates represented more than 80% of total OM of these soils and was positively affected by conservation tillage. This improvement showed a preferential C sequestration in smaller macroaggregates (<2 mm). The aggregate disper sion energy curves further suggest this is happening in microaggregates within the sma ller macroaggregates fraction. A complementary tradeoff between the economic and environmenta l benefits was found for our study site. This relies on the fact net farmer revenues were increased by reduced machinery operations and fertilizers applications, while GHG emissi ons were reduced by increasing soil carbon retention and reducing GHG emissions from machinery operati ons. Thus, although conservation tillage practices ar e not widely adopted in the watershed, payments for net GHG removals could increase more the net revenues and f acilitate the investment to cover initial extra costs of conservation agriculture (ie. cultivation of oat as cover crop).

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14 CHAPTER 1 INTRODUCTION Over 60% of the worlds carbon is held in bot h soils (more than 41%) and the atmosphere (as carbon dioxide; 20%)) (Sundquist, 1993; Stevenson, 1994). However, soil disturbance is redistributing the carbon, augmenting the atmo spheric carbon pool. Thus a part of carbon dioxide increase in the atmosphere is thought to have come from agriculture, affecting not just climate change but also productivity and sustai nability of agriculture and natural resources (Robbins, 2004). Therefore, the importance of Soil Organic Carbon (SOC) is being recognized because of its impact on global climate cha nge. However this posses an opportunity for management alternatives in agricultural lands that beyond produc ing food can provide ecosystems services such as provision of good quality water, water fl ow regulation and carbon sequestration (Clay, 2004; Boody et al., 2005; Robertson and Swinton 2005; Swinton et al., 2006; De la Torre et al., 2004) One example of these alternatives is conservation tillage for which there is a growing interest to be adopt ed by farmers due precisely to environmental benefits (Kern and Johnson, 1993; Burke et al., 1995) and to the fact that carbon sequestered in the soil and other ecosystem servi ces can eventually be traded. Importance of Soil Aggregation and Soil Man agement Practices for Carbon Sequestration Jastrow et al. (1996) found that nearly 90% of Soil Organic Matter (SOM ) was found within soil aggregates that can be macroaggregate s (>0.25 mm) or microaggregates (0.05.25 mm) (Edwards and Bremmer, 1967; Maeda et al., 1977). Kong et al. (2005) showed that the relationship between C input and SOC sequest ration was dominated by the increase in SOC within macroaggregates which amount is genera lly reduced by cultivation (Tisdall and Oades, 1982) by being less stable and therefore, susceptible to tillage disruption (Elliot, 1986; Cambardella and Elliot, 1993). Upon disruption, an increase or flush in C mineralization is

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15 observed (Angers and Chenu, 1997), augmenting the atmospheric carbon pool. However with certain soil management practi ces the SOM protection from de composition can be enhanced. Management systems involving high C inputs and re duced tillage should fa vor C storage directly by reducing aggregate breakdown and by enhanc ing SOM-mediated aggregation (Kern and Johnson, 1993; Burke et al., 1995). Thus, although there are other ways to protect SOM (and SOC) such as by adsorption to clay minerals and by isolation in soil micr opores (Bossuyt et al. 2002), physical protection within stable macroaggregat es is important since it is sensitive to the type of soil management applied in agricultural areas. The Need to Measure Soil Organic Carbon (S OC) in Conservation Tillage Sites in the Andes and Its Economic Returns Agricultural sinks will not be eligible fo r the Clean Development Mechanism before 2012 (FAO, 2002) and they are also not considered in the Kyoto Protoc ol. However, the soil is a C sink and it is worth researching how soil carbon is benefited from agricultural practices so that one is prepared for CDM or other opportunities th at will inevitably r ecognize this sink (e.g. BioCarbon Fund, GEF). In this sense research is needed to elucidate two facts from the farmer and market perspective that poses methodological challenges for those interested in developing carbon payments schemes in the agriculture sector From the market perspective, agricultural lands will be only accepted as sinks if the sequest ered carbon is additiona l to that one already existing in the baseline (An tle et al., 2007) after discounti ng GHG emissions caused by the carbon sequestering practices. From the farmers perspective, changing to conservation tillage may imply an opportunity cost equal to the difference between the highest -returning practice and the practice that yields the most soil carbon (Antle et al., 2007). So it is assumed that a farmer will be willing to change if th at opportunity costs is compensa ted or if the new alternative produces equal or higher net returns.

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16 In Colombia, conservation agriculture practices in volving reduced tillage and cover crops were adapted by the GTZ and the environmen tal authority (CAR) to OM-rich soils of Paramos neotropical alpine grasslands that is the transition between the forest and the snowline (from about 3300 m to about 4800 m above sea level) in the Andes (Poulenar d et al., 2003), that were disturbed many decades ago and cultivated with potato and pastures This process started in1999 in the steep conditions of the region as a mean to reduce soil losses and improve water quality and quantity. As a result, farmers in so me watersheds adopted these practices offering nowadays an extraordinary opportun ity to investigate the contri bution of these practices to reduce Greenhouse Gases (GHG) emissions, sequeste r soil carbon, to rehabilitate water and carbon-related soil characteristics, and to unders tand the opportunity costs of changing from conventional to conservation tillage. This kind of research then provide results very relevant nowadays that carbon markets fo r agricultural areas are increa singly gaining importance and especially for the Andes were studies about the potential of conservation tillage in this mountainous, highly populated a nd productive areas for delive ring both, environmental and economic benefits are scarce. Thus, objectives of this research were: 1. To determine if and how soil ch aracteristics under potato-based rotations on soils that were formerly paramos are rehabilitated by cons ervation tillage practices; 2. To determine if SOM can be increased in already OM-rich soils by conservation tillage 3. To estimate the amount of aggregated organic matter (AOM) in stable soil macroaggregates under potato-based rotations using conventional tillage vs. reduced tillage with cover crops. 4. To determine the opportunity costs of implem enting conservation till age in the study area 5. To estimate the net GHG removals caused by cons ervation and conventiona l tillage systems.

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17 To address these objectives, chapter 2 focuses on objectives 1 and 2. For the first objective the hypothesis was that conservation tillage, by applying reduced tilla ge and increasing C inputs to the soil, improves saturated hydraulic conductivity, porosity, available water content and reduces the bulk density; which implies rehabilitation with respect to conventiona l tillage. The second objective relied on the hypothesi s that, in spite the still hi gh OM content of these soils, conservation tillage increases SOC and SOM with respect to c onventional tillage. Chapter 3 addresses objectiv e 3 by studying the AOM in soil macroaggregates using a sonication technique. The hypotheses tested were: 1) Conservation agriculture increases OM in the aggregate organic matter pool, and 2) The OM cont ained in aggregates is different across size fractions being greater in smaller macroaggregates. Chapter 4 focuses on objectives 4 and 5. For determining the opportunity costs and to determine the GHG removals economic and carbon estimations for conventional tillage were conducted to characterize the business as usual scenario or the baseline and later compared with estimations for conservation tillage. The hy pothesis tested was that there is a competitive trade off between economic and carbon sequestration benefits derived from conservation tillage and for this reason carbon payment schemes are n eeded to bear the opportunity costs of changing from conventional to conservation tillage. Chapter 5 provides an integral summary of results and conclusions of the overall chapters and gives recommendations about futu re research needs.

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18 CHAPTER 2 EFFECTS OF CONSERVATION TILLAGE ON SOIL ORGANIC CARBON (SOC) AND SOIL PHYSICAL CHARACTERISTICS Introduction The agriculture role in society is changing in industrialized and developing countries. Rather than being considered only as a means to produce food, it is becoming a solution to deliver raw material for industrie s and ecosystem services. It is now seen as an alternative to mitigate climate change and improve water qualit y. These ecosystem services are related to soil functions and for this reason, the fact of prom oting farming systems that produce both food and ecosystem services is becoming more important (Lal, 2007). Lal et al., (2007) consider an increase in so il organic carbon (SOC) a crucial factor in enhancing soil, air and water quality. Management practices that increase C inputs in farming systems and apply reduced or non-tillage farmi ng practices should incr ease SOC (e.g., Denef et al., 2004; Bossyut et al., 2002; Kong et al., 2005; Kuo et al., 1997; Rasmussen et al., 1980; Cole et al., 1993). It is well established that increases in SOC are accompanied by increased soil aggregation, plant available wa ter capacity, ion exchange capac ity, soil biodiversity (Lal and Bruce, 1999), and crop yields (e.g. Pretty and Ball, 2001). Reduced tillage, combined with crop residue retention (conservation tillage), is a farming practice that can increase SOC and improve soil structure and soil stability while facilitating better drainage and water holding capacity; li miting the potential for water logging or drought (Holland 2004; Govaerts et al., 2007; Zibilske and Bradford 2007; Lichter et al., 2008). Conservation tillage counters the adverse effect of conventional tillage, namely the destruction of soil aggregates, which reduces the soils ability to hold plant available water (Patio-Ziga et al., 2008). Also when soil aggregates are destroye d by tillage and conventional ploughing, soil organic matter becomes available for decompos ition (Bronick and Lal, 2004), decreasing SOC.

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19 Patio-Ziga et al. (2008) found that disturbing a Mollisol in Mexico to make beds for a maize-wheat rotation decreased soil organic C content within 6 years by 10% compared to soil under non-tilled beds. The IPCC (2000) reported increases of 0.32 to 0.36 t SOC ha-1 y-1; while in Brazil, soil carbon sequestra tion was increased by conservation tillage when maize was rotated with mucuna (15.5 Mg CO2 ha-1) during 8 years, compared to a net emission of 4.32 Mg CO2 ha1 from the traditional maize/fallow plot (E vers and Agostini, 2000). Thus, soil conservation practices (minimum tillage rotations, cover crops and others ) result in soil carbon increases. However, such increases are not perpetual sin ce there is a carbon seque stration saturation point (20 to 50 years) (Lal and Bruce, 1999). For exam ple, in Canadas cooler climates with high organic matter soils, C inputs a nd no-till practices did not produce any significant change in soil C (Campbell et al., 1991; Carter and Rennie, 198 2; Doyle et al., 2004); suggesting that those soils were C saturated (Six et al., 2002). There is a growing interest among farmers to adopt management practices such us conservation tillage due to all the described environmental benefits (Kern and Johnson, 1993; Burke et al., 1995) and to the fact that carbon se questered in the soil th rough appropriate farming practices can be traded. Howeve r measurement, monitoring and verification techniques are still required (Lal, 2007). In the high Andes of Ecuador, Venezuela and Colombia is found the Paramo ecosystem; a neotropical alpine grassl and that is the transition between th e forest and the snowline (from about 3300 m to about 4800 m above sea le vel) (Poulenard et al., 2003). Paramo soils are nonallophanic Andisols dominated by organo-metalic complexes (Van Wambeke, 1992) formed by the wet and cold conditions. These soils are reco gnized by a high water rete ntion capacity, very high infiltration rate, very slow sediment lo ss (Poulenard et al., 2001) and high organic matter

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20 (Van Wambeke, 1992). However, when these soils are disturbed and used for cultivation, runoff is increased and the saturated hydraulic conduc tivity is reduced (Poulenard, et al., 2001). In Colombia, conservation tilla ge technology was adapted to th ese soils located generally in steep conditions by the GTZ and the envir onmental authority (CAR) since 1999 as a measure for soil and water conservation. As a result, some farmers in some watersheds adopted these practices. The Fuquene watershed is an exampl e where these practices were introduced as a measure to control the sediments that are releas ed from potato farms on very steep slopes and OM-riched volcanic soils and that are causi ng the eutrophication of Lake Fuquene. Thus, this study was conducted in this watershed and the objectives were 1) to determine if and how soil characteristics under potato-based rotations on soils that were formerly paramos are rehabilitated by conservation tillage practices; and 2) if SOM can be increased in these already OM-rich soils. For the first objective the hypothe sis was that conservation tillage, by applying reduced tillage and increasing C inputs to th e soil, improves saturated hydraulic conductivity, porosity, available water content and reduces the bulk de nsity; which imply a rehabilitation with respect to conventional tillage. Th e rationale behind this is that conventional tillage in Andosols negatively modifies these charact eristics by disrupting soil aggregates and compacting the soil. The relevance of the results is that it would provi de insights into the potential for conventional tillage to rehabilitate conventional tillage si tes in these high elevation unique ecosystems; something that is presently poorly underst ood. The second objective relied on the hypothesis that, in spite the still high OM content of th ese soils, conservation til lage increases SOC and SOM with respect to conventional tillage. The rati onale is that once these soils were disrupted by intensive tillage and were not enriched with additional sources of OM, th e C stocked in the soil

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21 had been released to the atmosphere and would not be recuperated due to the lack of additional C inputs. The results of this research are important as they provide insights a bout the role of these practices to rehabilitate conven tional tillage sites and to provide bundled ecosystem services by improving 1) water-related soil characteristics that affect water quality and 2) SOC and the soils potential to sequester C. This is relevant for the Andean regi on because intensive management practices associated with high ag ricultural productivity risks the soil capacity to deliver food and ecosystem services. Providing insights about the potential of storing soil carbon in these areas by implementing conservation tillage, carbon trade sche mes could become incentives to increase the adoption of these practices in the Andes. It is worth noting that curr ently Colombian national GHG emissions are attributed to agricultural la nd use change, making conservation tillage a potential significant component of meas ures to counteract these emissions. Materials and Methods Study Sites The study sites were agricultura l parcels located in the upper part of the Lake Fuquene watershed ( 2985 m.a.s.l.) which is located in the valleys of Ubat and Chiquinquir, north of Bogot, the capital of Colombia (South Amer ica) (N 05 20 W 73 51). The soils of this location are Andisols classifi ed as Lithic Hapludands (IGAC 2000). These agricultural areas used to be alpine Andean grasslands ( pramos ), a typical yet unique A ndean natural ecosystem. The temperature is stable throughout the year with mean annual values between 12.2C. The mean monthly humidity varies between 70 and 80%. The annual mean precipitation is 610 mm (JICA, 2000). Parcels are traditionally used by farmers to grow potatoes with a pasture rotation each 2 years. However some farmers are practicing conservation tillage by growing potatoes with

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22 reduced tillage and an oat cover crop. Therefore, in this st udy two types of parcels were selected: 1) parcels with conventio nal tillage and 2) parcels with conservation tillage. Each used the prescribed treatment during the last 7 years. Three sites per system were selected. The six sites were selected with the same characteristics in terms of: 1) landscape position; 2) land use; 3) slope; and 4) rainfall. Thus a ll of them were located in back slope positions, with linear and moderate slopes, under potato-based rotati ons and the same rainfall and regimen. At each site, two pits were dug in May 2007 and soil horizons were identified and described in each pit. Soil samples per horizon were taken using 3 cylinders per horizon of 2.5 cm height to determine the water retention curv es, bulk density and poros ity; and 5-cm diameter cylinders per horizon for determining saturated hydraulic conductivity. Additional fresh samples were taken. Five-hundred g of soil was taken per horizon to determine organic matter, carbon concentration, and soil texture. Laboratory Methods The sand size distribution and soil texture were determined using the Bouyoucos method (Bouyoucos, 1936). The carbon concentration was dete rmined using the method of Walkley and Black as described in Nelson and Sommers ( 1996). Soil Organic matter (SOM) was determined by loss of ignition (Schulte and Hopkins, 1996) The carbon content was estimated using two approaches: the volume-based approach where th e bulk density and the average thickness of horizons were used to estimate soil volume and the carbon concentration for that volume; and the equivalent soil mass (mass-depth) to correct fo r differences in soil bul k density, allowing more precise and accurate quantitative comparisons of so il constituents. This last approach permits one to account for unequal soil masses or densities (Ellert et al., 2002).

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23 The undisturbed samples were used to dete rmine soil bulk density by the cylinder method (Elliot et al., 1999; Klute, 1986); water retention curves at matrix potentials between 0 and 1.5 MPa using a pressure-plate extractor (Soil Surv ey Staff, 1996; Klute, 1986); and saturated hydraulic conductivity with a permeameter using th e constant head method (Klute and Dirksen, 1986). In addition, the total porosity (TP) was determined using the particle (Dp) and bulk density (Db) values, where TP = (1 (Db / Dp) 100). The pore size distribution was derived from the water retention curves by relating so il water content with different soil matrix potentials. The water content at 1500, 75 a nd between 75 cm was used for determining micropores, macropores and mesopores, respectively. Data Analyses SOM SOC and physical characteristic data were shown to have near normal distributions. An analysis of variance (ANOVA) was a pplied to the data using a factorial design after variables were shown to have near normal distributions. The main effects were type of tillage (conservation vs. conventional) a nd horizons. Preliminary analyses indicated that Horizon 3 was not different between treatments, therefore the ANOVA for SOM and SOC and other physical characteristics involved only the first two horizons. Duncan post hoc mean separations were used to analyze the effect of horiz on, treatment and their interactio n. To determine possible relation between SOM or SOC and soil physical characteri stics, a simple correlation was conducted for all soil horizons. Results Soil Descriptions, Physical Charac teristics and Horizon Differences In general, three horizons were found in the 12 profiles with an average thickness of 78 cm (horizon A1, top), 39 cm (horizon A2) and 49 cm (horizon C, bottom). The main differences between horizon descriptions was th at the percent of clay increases with depth and the color was

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24 very dark in the first two horizons while the third one was mostly ye llowish. The horizon A1 consisted of silty-loam or loam soils with dark moist colors: very dark gray, very dark grayish brown and black (10 YR 2.5/1, 10 YR 3/2 or 10 YR 3/1) ; moderate to strong and subangular blocky or granular structure; and fri able to very friable consistency. The A2 horizon had clay, clay-loam, loam or silty-loam soil textures with dark colors: brownish black, black, brown or very dark grayish brown (7.5YR 3/2, 10 YR 2.5/1, 10YR 4/3, 10YR 3/2 or 7.5YR 4/2). The structure was mostly moderate and its shap e was very variable (subangular blocky, angular blocky, platy, moderate or massive). The consistency was mostly friable to very friable. The C horizon was very different from the other two horizons. The moist colors were lighter than those found in the upper horizons: light olive, yello wish brown, light gray, brown, brownish yellow and in a few cases dark brown (10Y 5/4, 10YR 5/4, 10YR 6/1, 10YR 4/3, 10YR 6/5, 7.5YR 5/2, 5YR 7/1, 10YR 3/3, 10YR 5/6). The soil was structureless, weak or in some cases moderate. The structure shape was mostly massive and sometimes was angular blocky or subangular blocky. The consistency was variab le from very friable or friable to firm or very firm. Figure 2-1 represents soil profiles for the six sites w ith conservation and conventional agriculture are shown. The detailed field soil desc riptions for each of the 12 soil profiles are available in Appendix A. The bulk density, saturated hydraulic conductivit y, available water content (AWC), total porosity, macroporosity, mesoporosity, microporosity, SOC and SOM showed no interactions between main effects allowing the ability to cont rast treatments and horizons separately (Table 2-1). Horizons were different for satura ted hydraulic conductiv ity, AWC, macropores, mesopores, micropores and SOC at p<0.05. The micr opores increase with depth while the other

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25 characteristics decreased with depth (Table 22). Instead porosity, bulk density and SOM did not show differences across horizons. With regard to soil water, water content at different matrix potenti als was different across horizons (Figure 2-2). As the so il dried the A2 horizon held as much as 10% more water than A1 at equal matric potentials. This is consistent with the increase in microporosity evident in the A2 horizon. At saturation, total water content was equivalent in the two horizons as indicated by similar bulk densities. Effect of Conservation and Conventional Tillage on Soil Characteristics The tillage system had a significant effect on saturated hydraulic conductivity, AWC and mesopores ( p<0.05) and on bulk density, volumet ric water content, SOM and SOC (p <0.1); Table 2-2). The bulk density was lower in conservation tillage while the other characteristics were higher under conservation tillage (Table 2-3). At p<0.1 there was a significant interacti on treatment*horizon, being the mean volumetric water content higher in H2 of cons ervation tillage sites (figure 2-3). Simple correlation analyses showed that total organic matter (g /Kg) was negatively correlated in both treatments with bulk density and positively correlated with hydraulic conductivity, total porosity, macroporosity and meso-porosity (Tab le 2-4). In general, bulk density had a negative correlation with satura ted hydraulic conductivity, total porosity and macro porosity. Soil Carbon Content and Tillage Systems The horizon depth used in the C content calc ulation based in the soil volume corresponded to the average of all depths measured per horizon regardless of the treatment due to the fact that horizon depth was not statistically different betw een treatments (data not shown). The C content was estimated using the mass equivalent met hod for which the C content was calculated for

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26 successive layers of 6635 Mg ha-1 and 3943 Mg ha-1 representing horizon A1 and A2, respectively. This corresponded to the average soil mass calculate d per site according to bulk density and soil depths. With these averaged soil masses the soil depth was adjusted in order to ensure that final C contents were repr esenting the same amount of soil mass. The results obtained with both methods, soil volu me and soil mass equivalent showed that carbon content was different by tr eatment at p<0.1 and by horizon at p<0.05. According to the results obtained with the mass equivalent method the A1 horizon had the highest carbon content with 1097 t C ha-1; while the A2 has an average content of 406 t C ha-1 (Table 2-6). With respect to treatment, conservation tillage sites had an average carbon conten t in the soil pr ofile of 891 t C ha-1 vs. 612 t C ha-1 in conventional tillage; a 45% in crease due to conservation tillage. Discussion The study sites corresponded to crop ping areas that formerly were paramos Moreover, the conservation tillage areas were previously under conven tional tillage. Therefor e, the results of this study highlight the ability of conservation ti llage to recover the soil characteristics of the paramo ecosystem once impacted by conventional till age practices. Basic physical properties of paramo soils are high organic C content, open and porous structure,a very high porosity, a rapid hydraulic conductivity and high wate r retention (Buytaert et al., 2006) Bulk density is known to range from as low as 0.15 g cm3 in wet conditions and weat hered soils to about 0.9 g cm3 in younger soils of dryer regions (Buyt aert et al., 2005). In this sens e reductions on bulk density or increases on hydraulic conductivity, porosity, C content, AWC and water retention in paramo disturbed soils under conservation tillage sites will imply an improvement with respect to conventional tillage. In the Fuquene watershed, conservation tilla ge has improved the AWC, the saturated hydraulic conductivity and the mesoporosity by 30, 56 and 30% respectively (p<0.05). Also,

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27 bulk density was reduced by 15% and SOM and SO C concentrations were increased by 23 and 33% respectively (p<0.1). The improvement in AW C is a function of the increased mesoporosity under conservation tillage, which is corroborated with the strong correlation found between these two soil characteristics. The AWC characteristic of conserva tion tillage (9.56%) is in the range reported by Diaz and Paz (2002) for other Colombian paramos (6%) where they also related its changes to mesoporosity differences attributable to land use change. With respect to saturated hydraulic conduc tivity, the improvement is explained by the avoidance of soil crusting or soil air exposure complicated by conventional agriculture and corrected by conserva tion tillage in the paramos (Poulenard et al., 2001). This effect has been identified in other environments throughout th e world where long-term conservation tillage systems (no-till or reduced tilla ge) and a residue cover that protects soil porosity (in our case specifically mesoporosity), soil infiltration and avoids surface crusts caused by intense rain events (Burwell, 1966; Mahboubi et al., 1993; Azooz and Arshad; 1996, 2001) can combat the deleterious influence of conventional tillage. The effect of impr oving saturated hydraulic conductivity is also related to the enhancement of por e interconnectivity in conservation tillage systems as suggested by Strudley et al. (2008). Given the insignif icant change in total porosity, the only explanation for increased saturated cond uctivity is the improved interconnection of soil pores. Apart from the improvement in these physical soil characteristics, conservation tillage improved SOC. Soil C concentrations in conserva tion and conventional tilla ge sites are in the range reported for undisturbed or recolonized humid paramos In Northern Ecuador and Colombia the A horizon has been repo rted to have from 101 to 212 g C Kg-1 (Podjoweski et al., 2002; Poulenard et al., 2003; E. Amezquita et al., unpublished data. 2005) while this study

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28 recorded 152 and 178 g Kg-1 in conventional and conservati on tillage sites, respectively. Although our conventional tillage va lues are in that normal range, conservation tillage showed a marked improvement in the C concentration and in the average C content for the whole soil profile ( 100 cm depth) with respect to conventional tillage of 29 and 45%, respectively. The average C content has changed from 612 to 891 t ha-1. Particularly interesting is a 177% increase in the deeper A2 horizon (from 215 to 596 t ha-1) although most of the C is stored in the top A1 horizon (1097 t ha-1). This increase in C content with depth caused by conservation tillage illustrates that redistribution of C is occurring th roughout the soil profile; and is consistent with other reports (i.e. Carter and Rennie, 1982; VandenBygaart et al., 2002; Beare et al., 1994). This clearly visible effect is attributed to the effect of oat cover crop r oots that tend to be deep roots in these soils. Also, the improvements in C with de pth may be related with the fact that under conservation tillage the vegetation cover is kept and then the soil surface is not exposed to air and sun which otherwise favors the mineralization of the organic matter due to organic-mineral complexes get separated releasing the organic ma tter susceptible to decomposition by the action of microorganisms (Hofstede, 2001; Stevenson, 1986). The general improvement in SOC also indicates that conservation tillage has shortened the gap between SOC in conventional tillage and in undisturbed paramos a 45% increase over conve ntional tillage. Edwards et al. (1992) found that conversion from conventiona l tillage to conservation tillag e in soybeans and corn systems rotated with wheat during winter in a Hapludult of Southern US A also increased soil organic carbon on average by 31% over a 10 yr period. Alt hough the initial organic matter conditions are different between the soils studied by Edwa rds et al. (1992) and our Andosols (9.8 g Kg-1 vs 170 g Kg-1 under conventional tillage), c onservation tillage improves thos e initial levels of organic matter, even in OM-rich soils. This confirms this studies second objective showing that

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29 conservation tillage is effective in increasing soil OM even in soil that have a high OM content; at least in these unique paramos ecosystems. With respect to organic ma tter found in other disturbed paramos the average organic matter concentration of conventional tillage sites (170 g Kg-1, Table 2-3) is similar to the concentration found in other potato systems in Southern Colombian paramos (100 g Kg-1, Diaz & Paz, 2002) and other parcels located in th e Fuquene watershed (0.1 5 g/g, E.Amezquita et al., unpublished data, 2005). The average organic matter content of conservation tillage sites (0.22 g/g, Table 2-3) is instead similar to the content reported also by Diaz & Paz (2002) of 0.17.24 g/g in sites that were previously pastures and that were recently cultivated with potato. These authors attributed this to the remaini ng effect of pasture roots on the organic matter content that may be similar to the effect of the oat roots in our conser vation tillage system. The organic matter content is also similar to the averaged organic matter reported by E.Amezquita et al. (unpublished data, 2005) for undisturbed paramos of the Fuquene watershed (0.24 g/g) Thus, conservation tillage presented higher C concentrations (and organic matter) similar to undisturbed paramos ,; confirming this studies first object ive that conservation tillage can be used to rehabilitate soil unde r potato production in the region. This positive effect of conservation tillage on the or ganic matter and carbon conten ts has been reported by many studies. Grant (1997) and Black and Tanaka (1997) recognized that the long term use of conservation tillage increase soil organic ca rbon, enhance soil quali ty and improve soil resilience. It has been suggested that the increase in soil orga nic carbon associated with the adoption of conservation tillage will continue for a period of 25 to 50 yr depending on climatic conditions, soil characteristics, and production management practices (Franzluebbers, 1997; Franzluebbers et al., 1999; Hunt et al., 1996; Wood et al.,1991; Zobeck et al., 1995).

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30 The relevance of these results lies in the fact that while most soil paramos studies have reported how land use changes m odify the unique properties of paramos soils none have explored how better management practi ces in agriculture can rehabilitate them. The question left unanswered by this study site relates to the time frame for which improvements on SOC and organic matter will be achieved with cons ervation tillage, and al so under which baseline conditions conservation til lage could improve dist urbed soil properties in paramos It only suggests that these changes can be brought about in as little as 7 years. Conclusions Conservation tillage in potato-based system s improved in a 7 year period the soil organic matter and carbon content in disturbed soils of the paramos of Colombia. The soil carbon concentration in the whole profile was 29% higher under conservation tillage than under conventional tillage sites and the carbon cont ent was higher by 45%. C content improvement specially occurred in the subsoil (A2 horizon) increasing by 177% although most of the C is stored in the top A1 horizon. This improvement was attributed to th e enhancement of soil physical characteristics related with soil wate r movement and storage such us bulk density, AWC, saturated hydraulic conductivity and mes oporosity. These improvements reflect that conservation tillage, is allowing the rehabilitation of carbon and wa ter-related soil characteristics compared to conventional tillage systems.

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31 A B C D E F Figure 2-1. Soil profiles in six different sites. AC) Sites with conser vation agriculture; DE) Sites with conven tional agriculture. Table 2-1. Effects of treatment and horizon on soil characteristics p-values Main effects/soil characteristic Bulk density (g cm-3) Sat. Hydraulic Conductivity (cm h-1) Porosity (%) Macropores (%) Mesopores (%) Micropores (%) SOM (g/Kg) SOC (g/Kg) AWC (%) Treatment 0.078 0.024* 0.135 0.503 0.000* 1 0.02 0.057 0.000* Horizon 0.345 0.016* 0.517 0.000* 0.003* 0.001* 0.000* 0.001* 0.003* Treatment*Horizon 0.124 0.688 0.148 0.282 0.598 0.497 0.413 0.452 0.598 *Significant at 5% (p < 0.05). Significant at 10% (p < 0.1).

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32 Table 2-2. Comparison of soil characteristics across soil horizons Bulk density (g cm-3) Sat. Hydraulic Conductivity (cm h-1) Porosity (%) Macropores (%) Mesopores (%) Micropores (%) SOM (g/Kg) SOC (g/Kg) Horizon I 0.81 (a)* 18.5 (a) 65.6 (a) 25.1 (a) 9.2 (a) 30.2 (a) 230 (a) 160 (a) Horizon II 0.96 (a) 7.6 (b) 63.6 (a) 15.1 (b) 6.9 (b) 41.5 (b) 150 (b) 80 (b) *Within a soil characteristic, the means followed by di fferent letters are statistically different at p < 0.05 and show the effect of horizon. Horizon 1 Horizon 2 0 75 100015000Matrix potential (cm) 20 25 30 35 40 45 50 55 60 65 70 75% volumetric water Figure 2-2. Volumetric water cont ent at different matrix potenti als in selected soil profile horizons Note: Vertical bars de note 0.95 confidence intervals. Horizon 1: A1, Horizon 2: A2.

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33 Treatment 1 Treatment 2 12Horizon 36 38 40 42 44 46 48 50 52 54 56 58 60% volumetric water Figure 2-3. Volumetric wate r content at different tillage systems in selected soil profile horizons Note: Vertical bars de note 0.95 confidence intervals. Treatment 1: Conservation agriculture; Treatment 2: Conventional agriculture. Table 2-3. Comparison of soil characteristics across soil treatments Bulk density (g cm-3) Sat. Hydr Conduct. (cm h-1) Porosity (%) Macropores (%) Mesopores (%) Micropores (%) SOM (g/Kg) SOC (g/Kg) AWC (%) Conservation agriculture 0.81 (a)* 18.1 (a) 66.1 (a) 21.5 (a) 9.5 (a) 35.8 (a) 220 (a) 150 (a) 9.56 (a) Conventional agriculture 0.96 (b) 8.0 (b) 62.6 (a) 19.7 (a) 6.6 (b) 35.8 (a) 170 (b) 100 (b) 6.67(b) *Within a soil characteristic, the means followed by di fferent letters are statistically different at p < 0.05 and show the effect of horizon. Significantly different at p<0.1. Significantly different at p<0.05

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34 Table 2-4. Correlation between physical soil ch aracteristics and soil organic matter (SOM) r SOM (g/Kg) Bulk density (g/cm2) Sat. Hyd. Cond. cm/h Porosity Macropores Mesopores Micropores AWC SOM (g/Kg) 1.00 Bulk density (g/cm2) -0.72* 1.00 Sat. Hyd. Cond. cm/h 0.49* -0.43* 1.00 Porosity 0.63* -0.98* 0.35 1.00 Macropores 0.53* -0.57* 0.61* 0.52* 1.00 Mesopores 0.52* -0.29 0.63* 0.22 0.46* 1.00 Micropores -0.10 -0.23 -0.44* 0.32 -0.62* -0.52* 1.00 AWC 0.52* -0.29 0.63* 0.22 0.46* 1.00* -0.52* 1.00 Marked correlations are significant at p < 0.05 Table 2-5. Effects of treatment and horizon on soil carbon content p-values Main effects/soil characteristic C content Volume-based approach C Content Mass equivalent approach Treatment 0.061 0.062 Horizon 0.000* 0.000* Treatment*Horizon 0.479 0.706 Significant different at p<0.05. Significant different at p<0.1 Table 2-6. Effects of horizon and treatment on soil carbon content Horizon C (t/ha) Volumebased approach* C (t/ha) Mass equivalent approach* Treatment C (t/ha) Volumebased approach C (t/ha) Mass equivalent approach A1 1066 (a) 1097 (a) Conservation agriculture 749(a) 891(a) A2 273 (b) 406 (b) Conventional agriculture 591(b) 612(b)* Mean values with different letter inside the same column are si gnificantly different at p<0.05. Mean values with different lett er inside the same column are significantly diffe rent at p<0.1

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35 CHAPTER 3 EFFECTS OF CONSERVATION AND C ONVENTIONAL AGRICULTURE ON AGREGATED ORGANIC CARBON (AOM) OF ANDEAN SOILS Introduction Over 60% of the worlds carbon is held in bot h soils (more than 41%) and the atmosphere (as carbon dioxide; 20%)) (Sundquist, 1993; Stevenson, 1994). However, soil disturbance is redistributing the carbon, augmenting the atmo spheric carbon pool. When soil aggregates are disrupted by tillage practices the decomposition of Soil Organic Matter (SOM) is enhanced (Six et al., 1998). Thus, a part of carbon dioxide increase in the atmo sphere is thought to have come from agriculture, affecting not just climate cha nge but also productivity and sustainability of agriculture and natura l resources (Robbins, 2004). Therefore, the importance of Soil Organic Carbon (SOC) is being recognized because of its impact on global climate change. Jastrow et al. (1996) found that nearly 90% of SOM was found within soil aggregates. Aggregates, particulary aggregates in volcanic soils, have been cl assified into macroaggregates (>0.25 mm) and microaggregates (0.05.25 mm) (E dwards and Bremmer, 1967; Maeda et al. 1977). Jastrow (1996) and Six et al (1999) found that the majority of C in macroaggregates was aggregated organic carbon and that long term C sequestration w ithin micro and macroaggregates is mainly found to be aggregat ed-C. Kong et al. (2005) showed that the relationship between C input and SOC sequestration was dominated by the increase in SOC within macroaggregates. However, macroaggregates are less stable by being more susceptib le to tillage disruption (Elliot, 1986; Cambardella and Elliot, 1993). Disrupting macroaggregates exposes the microaggregate carbon pool to decomposers which affect the accumulation of SOC (Bajracharya et al., 1997). The most direct evidence of the role of soil structure in protecting SOM from decomposition comes when soil aggregates are disrupted. Upon disruption, an increase or flus h in C mineralization is observed (Angers and

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36 Chenu, 1997). Beare et al. (1994) s howed that the level of physical protection varies with soil management practices. Generally, there is more aggregate protection in no-till soils than in cultivated ones. Thus, the fa te of SOM protected within aggregates will depend upon its decomposability and on the persistence of aggregates which is related to th eir stability in water and resistance to other mechanical stresses. Several researchers found more macroaggregates in non-tillage or re duced tillage systems compared with conventional tillage soils (Car ter, 1992; Beare et al., 1994; Six et al., 2000) suggesting that changes in SOM protected in aggr egates should be noticed by studying the effect of management practices on macroagregates. Ti sdall and Oades (1982) found that cu ltivation generally results in reduced stability and am ount of macroaggregates but does not affect microaggregate stability. In consequence, the SOM that bind microaggregates into macroaggregates has been suggested to be th e primary source of organic matter lost upon cultivation (Elliot, 1986). Thus, although there are other ways to protect SOM (and SOC) such as by adsorption to clay mine rals and by isolation in soil micr opores (Bossuyt et al., 2002), physical protection within stable macroaggregates is important since it is sensitive to the type of soil management applied in agricultural areas. Management systems involving high C inputs a nd reduced tillage shou ld favor C storage directly by reducing aggregat e breakdown and by enhancing SO M-mediated aggregation. For example, establishment of perennial grasses or legumes in poorly-structure d soils contributed to macroaggregation, which favored the protection of labile C and, as a consequence, the long-term C storage (Angers, 1992). Similar results have b een obtained by Carter (1992) and Beare et al. (1994) when no-tillage was practi ced. Therefore, soil conservation practices are recommended in order to increase SOC sequestration. Also, cons ervation farming practices can contribute by

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37 avoiding soil moisture and temperature changes that exacerbate SOC depletions. For these reasons, practices such as non-tillage and redu ced tillage are increasingly adopted by farmers (Kern and Johnson, 1993; Burke et al., 1995). Agricultural sinks will not be eligible fo r the Clean Development Mechanism before 2012 (FAO, 2002) and they are also not considered in the Kyoto Protoc ol. However, the soil is a C sink and it is worth researching how to measure carbon so that one is prepared for CDM or other opportunities that will inevitabl y recognize this sink (e.g. BioCarbon Fund, GEF). Measurement of SOC can be direct by monito ring actual soil carbon, and/or indirect by estimating carbon sequestration by monitoring land uses (Post et al., 2001). In fact, direct m easurements are needed for indirect ones since trying to compensate farmers per hectare for certain recommended practice (indirect method) requires good numbers be available. Only after that can indirect monitoring be established. In Colombia, conservation agri culture practices in volving reduced tillage and cover crops were adapted by the GTZ and the environmental authority (CAR), starting in1999 to the steep conditions of the region As a result, farmers in some watersheds adopted these practices. The Fuquene watershed is an example where these prac tices were introduced to control the sediments released from potato farms on very steep slopes and the OM-riched volcanic soils and that are causing the eutrophication of Lake Fuquene. This lake provides potable water to more than half a million people downstream. Although the benefits of conservation agriculture to reduce sediments and to increase net income of farmers are recognized (Rubiano et al., 2006) there are no studies with reference to the impact of these practices on so il carbon sequestration. The objective of this research was to estimate the amount of AOM in stable soil macroaggregates under two different management systems in the Lake Fuquene watershed: 1)

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38 potato-based rotations using conventional tillag e and 2) potato-based ro tations using reduced tillage with cover crops. To achieve this, the AOM in soil macroaggregates was measured using a sonication technique. The study was focused on macroaggregates since these are the fractions where tillage effects on AOM are evidenced (see explanation above). The hypotheses were: 1) Conservation agriculture increases OM in the aggregate organic matter pool, and 2) The OM contained in aggregates is different acro ss size fractions being greater in smaller macroaggregates. The first hypothesis is based on results from other studies that reported improved soil aggregation and increased SOC leve ls with no-till compar ed with conventional tillage (e.g. Carter, 1992; Franzlue bbers et al., 1995; Si x et al., 1999; Paustian et al., 2000). The second hypothesis is expected si nce the distribution of SOM among aggregate size fractions can be very heterogeneous (Angers and Chenu, 1997) and Kong et al. (2005) a nd Denef et al. (2004) found that with non-tillage the AOM is higher in smaller macroaggregates than in larger ones. Materials and Methods Study Site The study sites were agricultura l parcels located in the upper part of the Lake Fuquene watershed ( 2985 m a.s.l.) located in the va lleys of Ubat and Chiquinquir, north of Bogot, the capital of Colombia (South America) (N 05 20 W 73 51). The soils in this region are Andosols and are classified as Lithic Hapludands (IGAC, 2000). These agricultural areas used to be alpine Andean grasslands ( pramos ), a typical Andean natural ecosystem. The temperature is stable throughout the year with mean annual values between 12.2C. The mean monthly humidity varies between 70 and 80%. The annual mean precipitation is 610 mm (JICA, 2000; IDEAM (climatic station data), 2004). The parcels are traditionally used by farmers to grow potatoes using conventional tillage with a 2 year rotation w ith pasture. However some farm ers are practicing conservation

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39 agriculture by growing potatoes w ith reduced tillage and an oat c over crop. Therefore, in this study two types of parcels were selected: 1) parcels with conventi onal tillage and 2) parcels with conservation agriculture dur ing the last 7 years. Three sites per system were selected. The six sites were selected with the same characteristics in terms of: 1) landscape position; 2) land cover; 3) slope; and 4) ra infall intensity. At each site, two pits were dug in May 2007. Soil horizons were identified in each pit, and one soil sample of 500 gr. was taken in the middle of each of th e identified horizon for aggregation and carbon analyses. In general, three horizons were found in the profiles with average thicknesses of 78 cm (horizon A1, top), 39 cm (A2) and 49 cm (C). Laboratory Methods The 35 fresh samples were segregated and cl assified by size using dry sieving with a nest of sieves representing 5, 2 (larger macroaggregates), 1, 0.5 and <0.5 mm (smaller macroaggregates) screen sizes1. Field moist samples were used to avoid changes associated with drying (Maeda et al. 1977). The samples were sieved in a mechan ical shaker for 5 minutes. To examine the AOM content, SOM content of eac h aggregate size class was extracted using a sonication procedure (North, 1976; Six et al., 2001; Swanston et al., 2005; Sarkhot et al., 2006). Through this procedure, different ultrasound energy inputs are applied to a ggregates allowing to release some of the SOM in the aggregates and other part remain s in the aggregates even after sonication. Thus, this procedure permits to measur e the aggregate stability as well as the amount of carbon held inside the aggregates (Sarkhot et al., 2006). In this study, the organic matter extracted from the aggregate by sonication was called AOM (aggregat e OM) as it contained fine organic matter from inside aggregates. Organic matter remaining in the same particle size class 1 Macroaggregates from each size fraction were labeled as : SF1 (> 5mm size fraction), SF2 (2 5 mm size fraction), SF3 (1 2 mm size fraction), SF4 (0.5 1 mm si ze fraction) and SF5 (<0.5 mm size fraction).

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40 after sonication was termed particulate organic matter (POM). Up to ten different levels of energy were applied (from 5.1 to 11 kJ) to see how different is the AOM (g/g) in aggregates of varying dispersion energy. A Sonic Dismembrator (Fisher Scientific, model 550) was used to apply these energy levels. The energy levels we re obtained by combining different amplitudes (20 to 60%) and time periods (1 to 5 minutes). The pulse method (60 sec ON and 30 sec OFF) was used to avoid an excessi ve rise in temperature. Up to 10 sub-samples of approximately 5 g we re separated per each of the 5 size fractions derived from the 35 fresh samples. To each sub-sample one of the ten energy levels were applied. The energy levels were applied starting from the lowest and incrementing it until reaching the maximum level (11 kJ) or before in cases where a sub-sample was completely breakdown. The actual energy inputs (J/mL) were calculated based on the particle size density (g/cc) and the initial soil weight (g) availa ble for each sample, the water volume used for sonication (mL), the energy output (Joules) given by the sonicator for each run, and a correction factor (0.7) that corresponds to the ratio of energy output give n by the sonicator energy output calculated by rise in temperature of a given mass of water (Sarkhot et al., 2007). Before sonicating the sub-samples, a suspensi on was prepared in a 250 ml beaker with 100 ml of water. The probe of the sonicator was imme rsed into the beaker at a depth of 8 cm. After sonicating, the suspension was passed through the sieve corresponding to the original size fraction class of the sub-sample. In all cases, one of the ten sub-samples was suspended in water and not subjected to sonica tion to estimate the OM that is water-dispersible. The OM passing through the sieve (AOM) and remaining on it (POM+remaining AOM) were measured through the loss on ignition proce dure, and %AOM was calculated as percentage of total SOM (AOM+POM). All SOM measuremen ts were converted to estimates of SOC

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41 concentration by multiplying by the Van Bemmelen factor of 0.58 (Lal et al., 1998). With the overall results it was possible to relate percen tage of AOM (an in consequence of carbon in aggregates) and the actual AOM concentration w ith different energy inpu ts for both conventional and conservation agricu lture soil samples. Data Analyses Because the measured energy inputs showed a minimum variance across soil samples (data not shown), the effect of energy (J) on %AOM was analyzed using energy class categories, ranging from 1 (3.5 J/mL) to 10 (75.5 J/mL). The effect of different energy levels, treatment and size fraction were analyzed for the % of AOM released after sonicati on by applying an ANOVA analysis using STATISTICA (Version 7; 2004). This analysis was done separately for the surface 2 horizons. Horizon 3 was excluded from anal ysis since it was present at a depth greater than 1 m; tillage effects on SOM (g/g) were not significant (data not shown) ; and the sample size was small in some size fractions of the smaller macroaggregates. Also, SF 5 was excluded from all analyses because the low number of observations in this size fraction. Differences were considered significant at p<0.05. Further statistical analysis was done separately for %AOM of each size fraction to analyze the effects of energy level and treatment. A post hoc comparison procedure with the Duncan adjustment was used to compare %AOM in size fractions where treatment had a significant e ffect. Since energy levels showed a significant effect on %AOM in all size fractions, a post hoc Duncan analysis was conducted to compare %AOM differences across the different energy levels for each size fraction. The %AOM was transformed to the actual value of AOM (g/g) released after applying different energy levels in each sample. An anal ysis of variance (ANOVA) was done to see the effect of treatment, energy, horizon and size fraction on the AOM (g/g). Since there were significant interactions Treatment*Size fraction; Treatment*Energy level and Size

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42 fraction*Energy level for the two horizons, a furthe r analysis of variance was done separately per size fraction. A post hoc Duncan analysis was co nducted for the main ef fects and significant interactions when existing into each size fr action. The AOM (g/g) and the energy (J/mL) were plotted per size fraction and treatment. In addition, the total %AOM (the maximum obtained with the energy levels spectrum used) were analyzed. Non-parametric analysis was done to determine th e variability of total %AOM in conservation and convent ional agriculture systems. Al so an analysis of variance (ANOVA) was conducted to determine the signifi cance of treatment, size fraction class and horizon as main effects. To do this, the total %AOM data was transformed as the inverse of log AOM (%) to normalize the data on the inverse of log %AOM. Since the effect of size fraction was significant (p<0.05) then a post hoc Duncan Analysis was conducted to identify differences between size fractions. Results Size Fraction x Energy Level and Size Fraction x Treatment interactions for Horizon A1 make direct interpretation of the main effects for Treatment, Size Fraction and Energy Level impractical (Table 3-1). Horizon A2 was char acterized by a three way interaction among all main effects (Table 3-1). Subsequent analysis of variance for each size fraction showed that, for both horizons, as the ultrasonic energy applied to the soil increased, more aggregates were destroyed, increasing the amount of AOM removed (Figure 3-1, 3-2). SF2, in both horizons, was directly influenced by tillage treatment. The %AOM, across all energy levels, was uniformly higher with the more conservative system (Table 3-4). In contrast, SF3 for Horizon A1 and SF3/SF4 for Horizon A2 showed significant inte raction with the Energy level (Table 3-2; 3-3). The post-hoc Duncan Mean Separation of the Treatment*Energy level interaction showed that the differences between management sy stems were due to the %AOM

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43 released after applying energy levels. At lower energy levels, treatment differences were small. However, for SF3 of the two horizons, cons ervation agriculture had higher %AOM when applying energy levels 7 and 8 (17 and 32 J/mL, respectively). In SF4 of horizon 2, the %AOM was also higher in conservation agriculture at energies of 17, 22 and 28 J/mL. (Figures 3-1 and 3-2, Table B-1, B-2 and B-3). SF1 in both horiz ons and SF4 from horizon 1 were unaffected by the tillage system (Table 3-2 and 3-3, Figure A-1) The %AOM*Energy (J/mL) curves indicated that, for all size fractions, the curve eventually flattened; indicating that all AOM was released with the exception of size fraction class 1 (>5mm) which did not reac h a plateau within the Energy ra nge used in th is study (figure B-1, 3-1 and 3-2). After converting the %AOM to AOM (g/g), the analysis of variance showed that the size fractions 2,3, and 4 had a significantly higher concentration of AOM in conservation agriculture samples from both horizons (figure 33 and figure 3-4, table B5). For size fraction 1 there is no treatment effect. Als o, size fractions 3 and 4 of horiz on A2 had exhibited a significant Treatment*Energy (J/mL) interaction (Table B-4), showing that main differences were that AOM (g/g) was released differentially with Energy Level. In SF 3, the differences are given in levels 7, 8 and 9. In SF 4 the differences are in energy levels 5, 6, 7 and 8. (Figure 3-5, Table B-6 and Table B-7). Total AOM The total aggregated organi c matter corresponds to the ma ximum %AOM released after applying the highest Energy Levels The ANOVA analysis results showed a significant effect of size fractions on the log invers e of total %AOM and no signifi cant effect of the different treatments (Table B-8). The subsequent post-hoc Duncan Mean Separations of the size fractions indicated that the smaller macroaggregates ( 1mm and 0.5 mm) held more total AOM as a % of the total AOM than did the larger macroaggr egates (>5 and 2 mm) (Table 3-5). However,

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44 since the SF1 (> 5mm size fraction) curve did no t reach a plateau, the %AOM released at the highest level should not be considered as the Total %AOM. In general, the total %AOM released after applying the highest energy (8.4 kJ) was high on most soil samples (>80% of total organic matter), and only 17% of soil samples released <80% of the total organic matter. This means that about 80% of the total or ganic carbon is in the aggregate pool. The non-parametric analysis, which compared the median values of total %AOM, showed differences between treatments in SF2 and SF3 of horizon A1 (Table B-9), with the higher values seen for the conservation tillage system. Also there was a higher variability of total AOM (%) in samples from conventional agriculture (figure 3-6 and 3-7). Aggregation Hierarchy All the aggregate energy dispersion curves exhibited a step-wise pattern. All curves present steps at similar Energy Levels. In general, a firs t step is recognized at about 17 J/mL, a second step is reached at about 32 J/mL and, in some cases, a third one at 57 J/mL. This third step was seen for SF2. Conservation agriculture, as me ntioned above, produced different curves for SF3 of both horizons and SF4 of horizon A2. In SF3, the effect of conservation agriculture was to accentuate the third step of the curve. It is wort h saying that this third step was not pronounced in the conventional agriculture sites (figure 3-2 and 3-3). For SF4 in the horizon A2, the effect of conservation agriculture was main ly on the second step making it more pronounced (Figure 3-3). Discussion Higher AOM and Soil Organic Matter (SOM) in Conservation Tillage The greater amount of %AOM and SOM (g /g) in aggregates from soils under conservation agriculture was aligne d with results from other studi es that also found greater SOC in no-till compared to conventiona l tillage for a variety of so ils types (e.g. Alfisol, Oxisol, Mollisol, Ultisol; Denef et al., 2004; Bossyut et al., 2002). However, most of the SOM and SOC

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45 studies were concentrated in supe rficial soil horizons ( 20 cm depth; Bossuyt et al., 2002). This study explored differences to an average dept h of 117 cm. Higher values of SOM (g/g) with conservation agriculture suggest ed that SOM improvements were promoted throughout the soil profile. Also the low variability of SOM (g/g ) in the first 76 cm of depth (horizon A1) demonstrated the uniformity of the effects of conservation agriculture on total %AOM. This uniformity in change caused by reduced tillage or notill systems has been reported in other studies for other soil characteris tics; but never to this soil de pth. Boone et al. (1986), Carter 1992, found that soil macroporosity was improve d uniformly throughout the soil profile particularly in the horizon just below the depth that corresponds to the plow level. Increases in macroporosity were related to improvements in organic matter, which is recognized as an agent responsible for soil aggregation. This was corrobo rated with findings from this study area were increments on organic carbon were positively correlated with macroposotiy (Quintero, chapter 2). Also, the higher amount of OM found under conser vation reflects the effect of the roots from the cover crops (oats). The penetration of these root s deep into the soil (per sonal observations) is expected to cause a flush of microbial activity at a lower depth, causing the formation of aggregate binding agents, thus enhancing the form ation of aggregates (B ossuyt et al., 2002); and therefore the physical protection of OM by these aggregates. Higher AOM and SOM in Smaller Macroaggregates Bossuyt et al. (2002) found in Ultisols, that microaggregate-protected and micro within macroaggregate-protected C was higher in no-till (NT) systems than in conventional tillage systems. This was a result of disruption avoidanc e of macroaggregates char acteristic of no-till systems. The reason is that when disruption of macro aggregates is avoided, residue that forms the center of a macro aggregate decomposes into finer organic matter that gradually becomes encrusted with clay particles and microbial pr oducts, forming micro aggregates within macro

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46 aggregates (Oades, 1984). Contrary when macroaggr egates are disrupted by conventional tillage, OM is released and never has the time to form microaggregates, resul ting in a much smaller amount of microaggregates within macroaggreg ates (Six et al., 1998, 1999, 2000). Thus although these results suggest that micro aggregates are important for ensuring SOM protection, macro aggregates stabilization is important for th is protection to occur (Bossuyt et al., 2002) Six et al. (1999) suggested that a reduced rate of macroaggregate turnover under no-till increases the formation of microa ggregates in which C is stabilized and sequestered in the long term. The same author found later that th e amount of microaggregates protected in macroaggregates was two times greater with no-till compared to conservation tillage (Six et al., 2000). Similarly, Denef et al. ( 2004) reported for a Mollisol a nd increase of microaggreates within smaller macroaggregates (0.25 2 mm size) between 20% with no-till compared to conventional treatment. We postulate that highe r amounts of SOM in SF2, SF3 and SF4 found in this study, and specially a relative greater incr ease of AOM in SF3 and SF4 (0.5 2 mm size) with respect to conventional agriculture, should also related to an incr ease of microaggregates within these smaller macroaggregat es. While this was not teste d, it should be looked into in future studies. The rationale behind this is that most of the AOM in SF3 and SF4 was released at certain energy levels. The pattern of aggregatio n explained by Oades and Waters (1991) for Mollisols and Alfisols consisted in a hierarchical structure where larger, weaker aggregates break down to release smaller, stronger aggregates, befo re breaking down into primary particles. These distinct units that are bonded and organized forming aggregat es can be separated as defined by our aggregate dispersion energy curves. When increas ing levels of energy are applied, aggregates of most soils fall apar t into smaller aggregates in a st epwise manner (Duiker, 2002). Based on this we inferred that at those specific ener gy levels where we found more AOM and that are

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47 noted clearly by a step-wise curve denoting a hier archical order of aggr egation, corresponds to the energy level where the macroaggregat es broke down into microaggregates. Denef et al. (2004) found in di fferent soil types that 91% of the difference in total SOC between no-till and conventional tillage was explained by the C associated with microaggregates that were is olated from smaller macroaggreg ates (0.25 2 mm) Considering that this study found more than 80% of the total carbon in aggreg ates, we suggest that the 29% difference in Total SOM (g/g) be tween conservation tilla ge and conventional tillage (Chapter 2), is explained by increments of AOM in SF2, SF3 a nd SF4. Kong et al. (2005) also found that the majority of the accumulation of SOC due to additional C inputs in agricultural lands was preferentially sequestered in the microaggregat es within-small-macroaggregates (mM). For this reason they proposed the use of the mM fraction as an indicator fo r C sequestration potential in agroecosystems. This corresponds to the same macroaggregate fract ion for which we found improvements of AOM. In horizon A1 (0 cm ) the differences between conservation agriculture and conventional agriculture were 37, 33 and 30% for SF2, SF3 and SF4 respectively, and 58, 99 y 98% in SF2, SF3 and SF4 of horizon 2 (78117 cm). Thus, this study confirms the findings of Denef et al. (2004) and Kong et al. (2005) in that most changes in total SOC were e xplained by differences in AOM caused by no-till (in our case reduced tillage) in smaller macroaggregates (0.2 5 2 mm). Therefore our results tentatively support Kong et al. (2005) in the use of the mi croaggregate-within small macroaggregate fraction as an potential indicator of l ong term C sequestration in agricultu ral lands. Further studies on the protection mechanisms invoked by this relations hip should be the topic of future studies. Other Considerations Studies have shown a positive linear relati onship between SOC and the proportion of crop residues returned to so il (Kuo et al., 1997; Rasmussen et al ., 1980; Cole et al., 1993). Our study

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48 supports these previous results, showing that th e incorporation of cover crops in the potato rotation and reduced tillage in creased SOM even though these volcanic soils in the Andes are already naturally high in organic matter (15% with conventional agriculture). This counters the results of others who reported that for high OM soils varying C inputs did not have any effect on SOC levels; indicating a state of soil C saturation (Campbell et al ., 1991; Six et al., 2002). Also, our results showed that major changes were ev ident in the lower horizon. In this case this treatment effect in th e lower horizon suggests a significant am ount of roots penetrating to this depth from the oats cultivated as cover crop twic e per year prior to the potato cultivation. The role of plant roots and vesicula r-arbuscular mycorrhizal hyphae associated with roots is already recognized as being important biding agents at the scale of macroaggregates (Tisdall and Oades, 1982, Cambardella, 2002). Considering the thic kness of this horizon, this increment on AOM (g/g) can have important repercussions on the soil carbon content (Chapter 2). With regard to size fractions and C sequest ration our results s howed a preferential C sequestration in smaller macroaggregates (<2 mm ) also found by Kong et al. (2005), Six et al. (2000), Bossuyt et al., (2002) and Denef et al. (2 004) (see above). Also the higher values of %AOM derived from smaller macroaggregates (SF3 and SF4) suggests that in these fractions the C has a slower turnover that the C in bigger macroaggregates (>2 mm). Based on Kong et al. (2005) findings, where increases on C stabilizat ion in the smaller macroaggregates were associated to greater aggregate stability and l ong-term sequestration we suggest in the same direction, that the higher AOM and SOM in sma ller macroaggregates in our soils is linked to greater C and aggregates stability and in consequence is contributing to long term C sequestration in the Andes. In addition, increase s of AOM may be related to improvement of soil structure. The conservation agriculture curves for SF3 and SF4 had bett er defined hierarchal

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49 steps than did the conventiona l agriculture curves. Since we ll defined steps indicate well developed structure, we suggest that conservation ag riculture in these Andean soils also improves structure. To summarize, reduced tillage is ensuring the protection of the AOM added in smaller macroaggregates. There are evidences of the role of aggregate structure in physically protecting organic matter from microbial decomposition. In studies where aggregat es were crushed or grounded, C and N mineralization rates increased greatly when the aggregate structure was disrupted. This is attributable to the expos ure of organic matter, which was previously inaccessible to microbial a ttack (Cambardella, 2002). Conclusions In the Andosols analyzed in this study, the soils had more than 80% of total OM as AOM, and conservation agriculture invol ving reduced tillage and cover crops in these Andean soils increased AOM. This study was able to evaluate the effects of conservation and conventional agriculture by studying differences on AOM. The major differences on AOM were seen to occur in smaller macroaggregates (0.5 1 mm size frac tions). The aggregate dispersion energy curves further suggest this is happening in microaggregates within the smaller macroaggregates fraction. Similar results have been obtained for other soils suggesting that smaller macroaggregates can be used to evaluate potential of long term C sequestration in Alfiso ls, Mollisols, Ultisols and now Andosols.

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50 Table 3-1. Effects of management systems, aggregate size and energy level on %AOM (Aggregated Organic Matte r) for horizon A1 and A2 Horizon A1 (p value) Horizon A2 (p value) Treatment 0.057 .000* Size Fraction Class 0.000* .000* E level 0.000* 0.000* Treatment*Size Fraction Class .003* .000* Treatment*E level 0.254 0.192 Size Fraction Class*E level .000* 0.155 Treatment*Size Fraction Class*E level 0.182 .025* Treatments: Conservation and conventional tillage;* Significan t at 5% (p = 0.05). Table 3-2. Analysis of variance of %AOM and en ergy levels per size frac tion classes in Horizon 1 p-values SF 1 (>5mm) SF 2 (2mm) SF 3 (1mm) SF 4 (0.5mm) Treatment 0.06 .019* .013* 0.14 E level 0.000*0.000*0.000* 0.000* Treatment*E level 0.700.41 .024* 0.28 Treatments: Conservation and conventional tillage ;* Significant at 5% (p = 0.05). Table 3-3. Analysis of variance of %AOM and en ergy levels per size frac tion classes in Horizon A2 p-values SF 1 (>5mm) SF 2 (2mm) SF 3 (1mm) SF 4 (0.5mm) Treatment 0.52 .026* .000* .000* E level .000* 0.000* 0.000* .000* Treatment*E level 0.62 0.63 .036* .017* Treatments: Conservation and conventiona l tillage;* Significant at 5% (p < 0.05). Table 3-4. Comparison between %AOM in different management systems and horizons for size fraction 2 (2 mm) Horizon 1 Horizon 2 Treatment %AOM Mean Duncan group %AOM Mean Duncan group Conservation tillage 33.0 a41.6 a Conventional tillage 27.8 b 33.9 b Mean values with different lett er inside the same column are significantly diffe rent at p<0.05

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51 0 20 40 60 80 100 120 01020304050607080Energy (J/mL)Mean %AOM released Conservation and Conventional agriculture SF4 Conservation agriculture SF3 Conventional agriculture SF3 Conservation and Conventional agriculture SF2 Conservation and Conventional a g riculture SF1 Figure 3-1. Aggregated organic ma tter (percent of total organic matter) of all aggregates size fractions from horizon A1 (top horizon), rel eased with different energy inputs in two potato management systems 0 20 40 60 80 100 120 01020304050607080Energy (J/mL)Mean %AOM released Conservation agriculture SF4 Conventional agriculture SF4 Conservation agriculture -SF3 Conventional agriculture SF3 Conservation and conventional agriculture SF2 Conservation and conventional agriculture SF1 Figure 3-2. Aggregated organic ma tter (percent of total organic matter) of all size fractions aggregates of horizon A2, released with different energy inputs in two potato management systems

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52 Treatment*Size fraction; Unweighted Means Current effect: F(3, 525)=5.9586, p=.00053 Effective hypothesis decomposition Vertical bars denote 0.95 confidence intervals Treatment 1 Treatment 2 1234 Size fraction 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20AOM (g/g) Figure 3-3. Effect of different management sy stems on aggregated organic matter (g/g) of different size fractions hori zon A1.(Treatment 1: conservation tillage; treatment 2: conventional tillage) Treatment*Size fraction; LS Means Current effect: F(3, 267 )=9.7526, p=.00000 Effective hyp othesis deco mposition Vertical ba rs denote 0.95 confidence intervals Treatment 1 Treatment 2 1234 Size fraction 0 .02 0 .04 0 .06 0 .08 0 .10 0 .12 0 .14 0 .16 0 .18AOM (g/g) Figure 3-4. Effect of different management sy stems on aggregated organic matter (g/g) of different size fractions horizon A2. (Treat ment 1: conservation tillage; treatment 2: conventional tillage)

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53 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 01020304050607080 Energy (J/mL)SOM (g/g) released Conservation agriculture SF1 Conventional Agriculture SF1 Conservation agriculture SF2 Conventional agriculture SF2 Conservation agriculture SF3 Conventional agriculture SF3 Conservation agriculture SF4 Conventional agriculture SF4 Figure 3-5. Effect of different management sy stems on aggregated organic matter (g/g) of different size fractions of horizon A2. Table 3-5. Duncan test post hoc for AOM a nd size fractions from Horizons A1 and A2 Size Fraction Class Log Inverse AOM% Mean %AOM Duncan group* 1 1.02 74.8 b 2 0.84 85.4 b 3 0.37 96.8 a 4 0.20 99.3 a Size fraction classes: 1 (> 5mm size fraction), 2 (2 mm size frac tion), 3 (1 mm size fraction), 4 (0.5 mm size fraction) and 5 (<0.5 mm size fraction). Mean values with different letter inside the same column ar e significantly different at p<0.05.

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54 Boxplot by Group Variable: AOM(%) Median 25%-75% Min-Max 12 treatment 30 40 50 60 70 80 90 100 110AOM(%) Figure 3-6. Non-parametric analysis of %AOM in Conservati on agriculture vs Conventional agriculture for size fraction 2 (>2mm) and Horizon A1. (Treatment 1: conservation tillage; treatment 2: conventional tillage) Boxplot by Group Variable: AOM(%) Median 25%-75% Min-Max 12 treatment 94 95 96 97 98 99 100AOM(%) Figure 3-7. Non-parametric analysis of %AOM in Conservati on agriculture vs Conventional agriculture for size fraction 3 (>1mm) and Horizon A1. (Treatment 1: conservation tillage; treatment 2: conventional tillage)

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55 CHAPTER 4 EFFECTS OF CONSERVATION TILL AGE ON ECONOMIC RETURNS AND GREENHOUSE GAS (GHG) REDUCTIONS IN THE ANDES Introduction Management alternatives in agricultural lands can provide ecosystem services beyond the production of food (Clay, 2004; Boody et al., 20 05; Robertson and Swinton, 2005; Swinton et al., 2006; De la Torre et al., 2004) such as carbon sequest ration. In fact, research has shown that agricultural soil carbon sequestrati on could be cost effective, and would have other economic and environmental co-benefits (Antle et al., 2007). One example of these alternatives is conservation tillage for which ther e is a growing interest to be adopted by farmers due precisely to environmental benefits (Kern and Johnson, 1993; Burke et al., 1995) and to the fact that carbon sequestered in the soil can eventually be traded. In consequence, there is increasing interest in schemes of Payment for Environmental Services (PES) to encourage the provision of ecosystem serv ices from agricultural lands. However few examples of such schemes exist (Bohlen et al., 2009). With re gard to water-related services provided by agricultural practices there are some PES schemes in the Andes. Nevertherless, most of them have been crea ted without sound analysis documenting impacts of land uses and practices in the serv ices resulting in schemes that instead of paying for the service are paying for a land use change that is believe to affect positively the ES (Porras et al., 2008). For carbon sequestration there are studies that reported benefits of practices such us conservation tillage (Denef et al., 2004; Bossyut et al., 2002; K ong et al., 2005; Kuo et al., 1997; Rasmussen et al., 1980; Cole et al., 1993). However, the fact that this will not be eligible as a sink for the Clean Development Mechanism before 2012 (FAO, 2002) and they are also not considered in the Kyoto Protocol might have delayed the implementatio n of carbon payments in agricultural areas compared to the state of advance of the car bon market for the forestry and

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56 industrial sectors. However, th e soil is a C sink over 41% of wo rlds carbon is held in soils (Sundquist, 1993; Stevenson, 1994) and it is worth researching how soil carbon is benefited from agricultural practices so that one is prepared for CDM or other opportunities that will inevitably recognize this sink (e.g. BioCarbon Fund, GEF). In this sense re search should contribute to elucidate two facts from the fa rmer and market perspective th at poses methodological challenges for those interested in developing carbon paymen ts schemes. From the market perspective, agricultural lands will be only accepted as sinks if the sequestered carbon is additional to that one already existing in the baselin e (Antle et al., 2007) after discounting GHG emissions caused by the carbon sequestering practices. From the fa rmers perspective, changing to conservation tillage may imply an opportunity cost equal to the difference between the highest-returning practice and the practice that yi elds the most soil carbon (Antle et al., 2007). So it is assumed that a farmer will be willing to change if that opportunity costs is compensated or if the new alternative produces equal or higher net returns. In Colombia, conservation tillage technology was adapted to soils of Paramos neotropical alpine grasslands th at is the transition between th e forest and the snowline (from about 3300 m to about 4800 m above sea level) in the Andes (Poulenar d et al., 2003), that were disturbed many decades ago and cultivated with potato and pastures Conservation tillage practices that manage crop residues with minimum tillage were adapted and promoted by the GTZ and the environmental authority (CAR ) since 1999 as a measure for soil and water conservation. As a result, some farmers in some watersheds adopted these practices. After some years of being adopted in some farms, this cases offer an extraordinary op portunity to investigate the contribution of these pract ices to reduce Greenhouse Gases (GHG) emissions and sequester

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57 soil carbon, and to understand the opportunity costs of changing from conventional to conservation tillage. Being said this, the objectives of this chapter is to determine the opportunity costs of implementing conservation tillage in the study area and to determine the net GHG removals caused by these practices. For determining the opportunity costs and to determine the GHG removals economic and carbon estimations for conventional tillage were conducted to characterize the business as usual scenario or the baseline. Th e conventional tillage data came from the same study area where conservation tilla ge was adopted as the point of comparison must be the typical common practice for the time and location of the a ssessment (Uri et al., 1999). The relevance of comparing ne t returns of conventional vs conservation tillage as a means to determine the opportunity cost, and the estimated net GHG removals is that this permits to identify possible trade offs betw een economic and carbon sequestration benefits derived from these practices giving an idea of how feasible this practices are for farmers and for the society interested on reducing GHG. Moreover, the results are very relevant nowadays that carbon markets for agricultural areas are increasingly gaining importance and especially for the Andes were studies about the potential of conservation tilla ge in this mountainous, highly populated and productive areas fo r delivering both, carbon sequest ration services and economic benefits are scarce. Methods Economic Analysis To determine the opportunity costs it was n ecessary to estimate th e net returns of a business as usual scenario (c onventional tillage) and the propos ed scenario to sequester soil carbon (conservation tillage). Annual net revenu es for each treatment were determined by

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58 subtracting production and input ex penses from gross revenue as described by Zentner et al. (2002). Two treatments were assessed, a busin ess as usual rotation where there is not incorporation of a cover crop and uses conventional tillage; and the carbon sequestering rotation which incorporated oat as cover crop and reduced tillage. The incorporation of oat as cover crop occurs typically in the conservation tillage rotation 4 months ahead potato is sowed. The rotations were tested for a 7 year period, for wh ich variations on SOC were analyzed in Chapter 2 and 3. The rotations are: i) ryegrass-potat o-potato-ryegrass-ryegrass-potatopotato and ii) ryegrass-oat-potato-potato-ryegra ss-ryegrass-oat-potato-potato as they were practiced in the study area. Economic data of growing potato with convent ional and conservation tillage was based on economic data for this specific production systems in the study area, particularly from GTZ-CAR (unpublished data, 2000, 2006) and Lopez (2009, pe rs. comm.). Later all economic data was expressed on a total rotation ba sis covering the 2000 period thus they include the costs and returns for all crops comprising the rotation sy stems. Therefore, rotation-based budgets were developed. Inputs used in each cropping system were included in the analysis, considering only variable costs such us field operations (plo wing, disking, planting, cultivating, harvesting, etc.) and materials (seed, herbicide, fungicide, fertilizer, etc.). Since the purpose of this economic analysis was to compare returns between conser vation and conventional ti llage, fixed costs such as cost of land, land taxes, etc were excluded from calculations because they were assumed to be the same for the two treatments. All inputs costs and prices valued at 2000 and 2006 in Colombian pesos were converted in dollars, and from there average values were derived and held constant for the economic analysis of the rotati ons. Later, net revenue and annual cash flows were expressed in net present value terms applyi ng a discount rate of 5%. Net revenue was then

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59 the result of discounting va riable costs and labor costs from gr oss returns. In table 1, there is a summary of inputs cost, products prices, producti vity and livestock parameters used in the economic analysis. To facilitate this analysis the ECOSAUT model was used. It uses linear programming to optimize net income from different land-use and management systems (Quintero et al., 2006). It was employed here to evaluate the economic impacts of the two rotations and to determine the optimal one in terms of net return. In addition the obtained net return from conventional tillage system was compared with the actual rental price of land to validate our estimations (the current rental price per hectare is $1200 ha-1yr-1, according to Otero, 2009, comm.pers.). However it mignt be noticed that most of producers owned the land and there are few tenants in the area. Net GHG Removals The net GHG removals by conservation tillage were estimated as the difference between changes in soil organic carbon stock and the emissi on sources. The emissions considered in this estimation were N2O emissions from fertilizers, CH4 and N2O from fossil fuel burning caused by soil preparation and transportation of farm products and; CH4 and N2O by grazing animals (cattle). The estimations were done in a hectare basis per each of the two rotations (treatments) economically assessed as well. Changes in soil organic carbon we re derived from chapter 2 of this manuscript. Thus, the marginal soil organic carbon content found in conservation tillage systems when compared with conventional tillage was in terpreted as the change in SOC. However, only 80% of this was considered in the estimation since this is the average amount of SOC found in soil aggregates and therefore, the more protected in these soils (Chapter 3). This value was converted to CO2 using the conversion factor 3.667 (tCO2 t-1C).

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60 Nitrous oxide (N2O) emissions from fertilizers Emissions of nitrous oxide from nitrogen fe rtilization were based on the methodological tool approved by the Clean Developmen t Mechanism (CDM) Executive Board: Estimation of direct nitrous oxide emission from nitrogen fertilization1. The estimation was given by: 0 1 2228 44N t fertilizerGWP EF ONF (4.1) ) 1(GASF ttFrac NF (4.2) where: fertilizerON2= the direct N2O emission as a result of nitrogen application in time t*; t CO2-e. Ft = amount of fertilizer nitrogen applied at time t adjusted for volatilization as NH3 and NOx; t N N,t = amount of fertilizer nitrogen applied at time t; t N EF1 = emission factor for em issions from N inputs; t N2O-N (t N input)-1 FracGASF = fraction that volatilises as NH3 and NOx for fertilizers; dimensionless GWPN2O = Global Warming Potential for N2O; t CO2-e./t N2O These N2O emissions were estimated considering the Intergovernmental Panel on Climate Change (IPCC) default value of the emission fact or for emissions from N inputs (0.0125), the Global Warming Potential for N2O (= 310 for the first commitment period) and the IPCC default value for the fraction that volatilizes as NH3 and NOx for synthetic fertilizers (0.1). GHG emissions from burning of fossil fuel These emissions result from the use of machiner y and vehicles during site preparation and transportation of harvest and inputs. Th ese emissions estimation was based on the methodological tool approved by the CDM Executive Board: Estimation of GHG emissions related to fossil fuel combustion in A/R CDM project activities15. The estimation was given by: 1

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61 2, COVehicle FuelBurnEE (4.3) and: 1 ,) (2t t xyt xy xy COVehiclemption FuelConsu EF E (4.4) where: EFuelBurn = total GHG emissions due to fossil fuel combustion from vehicles; t CO2-e. yr-1 EVehicle,CO2 = total CO2 emissions due to fossil fuel combustion from vehicles; t CO2-e. yr-1 x = vehicle type y = fuel type EFxy = CO2 emission factor for vehicle type x with fuel type y; dimensionless FuelConsumptionxyt = consumption of fuel type y of vehicle type x at time t ; liters xytxytxyt xyteknption FuelConsum (4.5) nxyt = number of vehicles kxyt = kilometers traveled by each of vehicle type x with fuel type y at time t ; km exyt = fuel efficiency of vehicle type x with fuel type y at time t ; liters km-1 For the soil preparation component estimations were made using a consumption of 15 l hr-1. For transportation, soil preparation machinery fuel efficiency is 0.38 l Km-1 and of vehicles for transporting fertilizers is 0.075 l Km-1. Seeds and labor forces usua lly are not transported in the study area as seeds are produced in the farm and mo st of labor is familiar or contracted in the same neighborhood. The emission factor (EF) used for the calculation of emissions from fossil fuel burning were 2.83 Kg CO2e l-1 for diesel and 2.33 Kg CO2e l-1 for gasoline (default IPCC values). Emissions from livestock Emissions from nitrous oxide and methane are caused by enteric digestion and manure management. These emissions estimation was based on the methodology approved by the CDM

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62 Executive Board: Afforestation or reforestation on degraded land allowing for silvopastoral activities2. The estimation was given by: ONO ManureN CH ManureCH livestockGWP EF GWP EF Pop E2 2 4 4 CH4 Enteric* EF (4.6) Where, Elivestock = total GHG emissions due to livestock population in the study area; t CO2-e yr-1 Pop = population of livestock in the study area; head EFEnteric CH4 = Emission factor for enteric methane production for livestock; kg CH4 head-1 yr-1 EFManureCH4= Emission factor for methane production from manure for livestock; kg CH4 head-1 yr-1 EFManureN2O= Emission factor for nitrous oxide production from manure for livestock; kg N2O head1 yr-1 GWPCH4 = Global warming potential for CH4 (IPCC default = 21); kg CO2-e kg-1 CH4 GWPN2O = Global warming potential for N2O (IPCC default = 310); kg CO2-e kg-1 N2O And, anure depositedm rate O ManureNEF TAM N E *365* 1000 *2 (4.7) Where, Nrate = Excretion rate for livestock; kg N (1000 kg animal mass)-1 day-1 TAM = Typical animal mass; kg head-1 EFdepostiedmanure = Emission factor for N2O emissions from dung and urine deposited on pasture; kg N2O-N (kg N input) -1 1000 = Conversion factor; kg to tonnes 365 = Conversion factor; days to years For the calculation cattle population was held constant in time (2 animals ha-1) and with a typical mass of 450 kg head-1. EFEntericCH4 was 56; EFManureCH4, was 1 since manure is left on pasture instead of being collected and stored; Nrate was 0.36 and EFdepostiedmanure was 0.02. All these values were taken from IPCC default values (IPCC, 2006). 2 < http://cdm.unfccc.int/methodologies/ARmethodologies/approved_ar.html >

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63 To conduct all emission estimations, the TARA M v1.3 tool (Tool for Afforestation and Reforestation Approved Methodolog ies) (Pedroni and Rodriguez-Noriega, 2006) was used for calculations only consider ing its components for GHG emissions estimations. Results Economic Analysis When the ECOSAUT model was run to look for an optimal solution the one that maximizes net revenues in a hectare giving the two treatments as the only land use alternatives, the conservation tillage rotation was the optimal so lution. The 7-year cumulative net revenues for the assessed rotations indicated that conservati on tillage rotation increa sed the net revenues by 17% compared to the conventional tillage rotation. This increment is due to particularly the improvement on potato income in 23% when cons ervation tillage is practiced (Table 4-2). This improvement was high enough to compensate the additional investment required in the conservation tillage rotation that is the produc tion costs of incorporating oat as a cover crop in the rotation ($337 ha-1 yr-1). A greater net return from potato cropping using conservation tillage practices was related to a reduction of production costs by 11% an d to an increment of potato productivity by 10%. Lower production costs were due mainly to a reduction on fertilizers and machinery costs rather than in a substantia l reduction on the use of workdays which instead was similar in both, conservation an d conventional tillage (table 4-3). Net GHG Removals The soil carbon stock change used for estimating the net GHG removals was 818 tCO2 ha-1 which is equal to the 80% of the marginal so il carbon stock (chapter 2) expressed in tCO2. With respect to GHG emissions findings showed that these are reduced with conservation tillage by 21% compared to conventional tillage. This re duction is caused primar ily by the reduction of CO2 emissions from fossil fuel burning mainly from machinery during si te preparation and of

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64 N2O emissions from nitrogen fertilization. This reduction compensates the emissions caused by the incorporation of oat to the conservation tillage rotation which involves additional fertilization (Table 4-4, 4-5). With respect to the net GHG re movals, when emissions of conservation tillage were discounted to the SOC stock changes achieved with conserva tion tillage, the net GHG removal is equal to 788 tCO2e for a 7-yr period. Discussion The purpose of the economic analysis was to determine the opportunity cost of implementing conservation tillage by farmers of the Upper Fuquene watershed. The rational behind this was that for a farmer to change from conventional to conservation tillage, he must bear an opportunity cost (Antle et al., 2007) which is the difference in this case between conventional tillage and the conservation tillage returns. Therefore, only conservation tillage systems capable of producing equi valent or greater yi elds and returns than conventional tillage are likely to be readily accepted by the producer (Muller et al., 1981). The results of this study showed that conser vation tillage increases net return implying a negative opportunity cost and therefore a net economic benefit for the farmer. Our results compared well to the current rental price of a hectare of land in th e study area (US$1870 vs. $1200, for the simulated conventional tillage sy stem vs, the actual rental price of land, respectively) if we take into account that net revenue should no t only be a retribution to land price but also to the administrative costs, being this last the difference between the two values. This explains the fact that currently land is cul tivated by its owners instead of being rented as they can get greater returns cult ivating by themselves and using th eir own labor in most of the activities. Also, we suggest that as net revenues increases with the conservation tillage system as less the willingness of owner to rent their land will be.

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65 On the other hand, better mean net returns from conservation tillage are also reported by Sandretto (2001) and Jeong and Forster (2003) who attributed this to d ecreases in input costs particularly due to reduced labor hours due to a decrease in the number of trips to crop fields, reduced machinery wear, and a saving in fuel co nsumption. In our case reduction of input costs are only related to reduced machinery ope rations and fertilizers applications. In another hand, conservation tillage reduces GHG emissions and increases the soil carbon stock resulting in a positive net GHG removal. This is in line with other st udies that consider two main effects of conservation tillage in carbon em issions: i) an increase on soil carbon retention because less organic matter is loss to oxidati on as mixing the soil and soil temperature are reduced; and ii) carbon emissions ar e reduced because it requires fewer machinery operations (Uri et al., 1999) Thus the results of this study indicate that c onservation tillage is a win-win alternative for Fuquene farmers by benefiting economically the farmer and by providing clearly an ecosystem service or in other words there is a complementary tradeoff between the economic and environmental benefits. However, Uri et al. (1999) recognized th at conservation tillage on highly erodible land will unquestionably resu lt in an increase in social be nefits, but the expected gains will be modest. In the same sense a 17% of incr ease in net revenues in our study area could be not enough to overcome the possible aversion to risk of farmers (or other adoption barriers) and to encourage them to make an additional investment to cover in itial extra costs of conservation agriculture (ie. cultivation of oat as cover crop). This fact may explain why this practice is not widely adopted in the Fuquene watershed (Curre ntly there are about 180 0 ha implementing these practices of 16933 ha under potat o production in the watershed, (Otero, pers. comm.2009; Quintero and Otero, 2006)). This same situa tion has been described by Sandretto (2001) who

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66 showed that although mean net returns on reduced til lage practices are equal to or greater than the returns from conventional tillage, mainly because of decreases in input costs, yet conservation tillage practices have been adopt ed on only 35% of US agricultural lands. The factors that has been reported as barriers to adoption of conservation agriculture practices are various and different. One the additional risk s perceived by farmers when adopting reduced tillage including the human and/or physical capital investments that producers may have to incur (De la Torre et al., 2004). Also, the availability of credit to assist wi th conservation tillage increased need for purchased inputs (such green manure cover crop seeds, herbicides, etc) is another factor. In fact, successful experiences of conservation agriculture practices adoption in Latin America have demonstrated the importance of credit as an important enabling factor (FAO, 2001). In another hand, according to Tweeten (1995), for farmers with short-term planning horizons the benefits of conservation agricultu re are not immediate becoming this as an additional barrier for adoption. Also, there may be other barriers particular to culture and recent history (Nyagumbo, 1997), and to information aspects such as contact with extension agents, availability to technical assistance, attendance to field demonstrations and plots, etc. (FAO, 2001). Therefore, our results show that although conservation tillage practices are feasible in mountainous areas and low income countries as is our study area, some barriers may be existing constraining a wide adoption of these practices. One of these may be the required investment and therefore credits or other fina ncial or economic incentive may be important for enhancing the adoption (Carcamo et al., 1994). In fact, this has been demonstr ated in the study area were a small revolving fund was created to provide credits to farmers willing to implement conservation tillage in their potato-based pr oduction systems. The credits we re created only to cover the

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67 required investment to implement the cover crop as the potato production costs are assumed to be covered by the farmers as they are used to do. This system, although small, has proven to be effective since 2005 incorporating about 180 small farmers every ye ar and using the capital of the fund at its maximum capacity (Quinter o and Otero, 2006; R ubiano et al., 2006). However, a mechanism to reach a widely adopt ion of these practices is required weather by incrementing the capacity of the fund or by pr oviding an extra incentive. This last may be come via payments for the net GHG removals. Taking into account 788 tCO2 ha-1 in 7 years could mean an extra income of US$450 yr-1 (assuming a carbon price of $4 tCO2 which is a conservative price. It is assu med a constant carbon price as currently carbon contracts are negotiated in a constant price basis). This carbon payment could alone cover oat production costs that are around $377 ha-1 and increased the net revenues the rest of years of the rotation when oat is not cultivated (in a 7yr period oat is cultivat ed twice), This may mean to the farmer a 29% increase in net return instead of 17% caused by the economic benefits of conservation tillage alone. Although this estimation is based on a conserva tive carbon price of US$4 tCO2, this price already covers the cost of sequestering 1 tCO2 in the 7y r-period. If we consider that this cost may be equal to the additional investment the fa rmer had to incur, which is the oat production cost (US$377 x 2), then each ton of CO2 required an additional investment of US$1. Of course, this calculation does not include the costs of technical assistance that is currently provided by the regional environmental authority (CAR). It is worth noting that thes e results and the values s hould not be generalized and extrapolated to any situation wh ere conservation tillage is practic e, since the potential for soil carbon sequestration depends on the type of crop grown, the cropping pattern, the type of soil

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68 and the climatic conditions (Donigian et al., 199 4; Uri et al., 1999). Moreover for our study site the identified carbon sequestration potential can not be extrapolat ed in time assuming a linear behavior of it as carbon increases are not perp etual. It is believed that there is a carbon sequestration saturation point (20 to 50 years) (Lal and Br uce, 1999) depending on climatic conditions, soil characteristics, and production management practices (Franzluebbers, 1997; Franzluebbers et al., 1999; Hunt et al., 1996; Wood et al.,1991; Zobeck et al., 1995). To finalize, it is recognized that off-site bene fits of conservation tilla ge are not only related to carbon sequestration and theref ore financial incentives should be designed on this basis. Carbon sequestration by conservatio n tillage can imply various othe r co-benefits for society such as soil retention and therefore th e reduction of downstream sedime ntation, regulation of rivers flows (FAO, 2001) as soil water characteristics influencing water movement and storage are improved (Quintero, chapter 2), among others. T hus, showing all conservation tillage benefits for society together may be a strong strategy to design robust and stable fi nancial incentives for enhancing adoption of conservati on agriculture in the Andes. Conclusions The results of this study indi cated that conservation tillage in the upper Fuquene watershed (Colombia) is a win-win alternative as it increases net revenues benefiting economically the farmer and reduced GHG emissions. In other word s there is a complementary tradeoff between the economic and environmental be nefits.Better net returns are e xplained basically by reduced machinery operations and fertilizers applica tions. In another hand, net GHG removals are positive due to increments on soil organic ca rbon and reductions on GHG emissions caused by machinery operations and fertilizers.

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69 However, these practices are not widely a dopted in the watershed but payment for net GHG removals (and possibly to other ecosystem se rvices such us regulation of river flows and reduction of sedimentation) could increase furthermore net returns and facilitate the investment to cover initial extra costs of conservation agri culture (ie. cultivation of oat as cover crop).

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70Table 4-1. Summary of annual inputs cost, products prices, productivity a nd livestock parameters used in economic analysis (bas ed on GTZ and CAR, unpublished data, 2000, 2006) (all values are in hectare basis and are constant values). 2000 [a] 2006 [b] Traditional Conservation Traditional Conservation Quantity Price or Cost (Unit) Price or Cost (Total) Quantity Price or Cost (Unit) Price or Cost (Total) Quantity Price or Cost (Unit) Price or Cost (Total) Quantity Price or Cost (Unit) Price or Cost (To tal) POTA TO LAND PREPARATION Machinery (hours) 11 8.99 97 3 8.99 27 14 13.13 184 7 13.13 92 Animal work (hours) 8 2.41 19 8 2.41 19 Inputs (herbicide) (lt) 4 7.74 27 2 7.74 15 Labor (Day's work) 2 6.14 9 1 6.14 8 Sub-Total 133 50 203 111 SOWING Inputs Seeds (Kg) 1575 0.15 235 1500 0.15 224 1104 0.19 210 1104 0.19 210 Fertilizers (NPK 13-16-6) (Kg) 1200 0.30 363 1300 0.30 394 1200 0.44 525 1500 0.44 657 Organic manure (i.e. chicken manure) (Kg) 1750 0.05 93 Ca and P (i.e. Calfos) (Kg) 525 0.05 29 1000 0.08 83 1000 0.08 83 Insecticides (lt) 0.7 11.57 9 Labor (Day's work) 11 6.14 64 15 6.14 93 13 8.76 114 13 8.76 114 Sub-Total 757 749 933 1064 CROP HEALTH Inputs [c] 563 396 360 460 Labor (Day's work) 34 6.14 208 24 6.14 148 31 8.76 271 34 8.76 298 Sub-Total 772 544 631 757 WEED CONTROL, EARTHING UP, etc Labor (Day's work) 17 6.14 104 16 6.14 98 27 8.76 236 14 10.95 153 Inputs (fertilizers NPK 15-15-15) (kg) 650 0.29 191 559 0.29 164 600 0.41 244 Sub-Total 295 262 481 153 HARVEST Packing and Transportation (US$/50Kg) 386 1.08 418 424 1.09 463 562 1.41 793 651 1.12 727 Labor (Day's work) 43 6.14 264 41 6.14 250 74.3 8.76 651 81.8 8.76 716 Sub-Total 682 712 1444 1443 PRODUCTION Productivity (kg $) 24125 0.13 3185 26500 0.13 3500 29750 0.27 8010 32750 0.28 9084

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71Table 4-1. Continued. 2000 [a] 2006 [b] Traditional Conservation Traditional Conservation Quantity Price or Cost (Unit) Price or Cost (Total) Quantity Price or Cost (Unit) Price or Cost (Total) Quantity Price or Cost (Unit) Price or Cost (Total) Quantity Price or Cost (Unit) Price or Cost (Tot al) OAT Land preparation 4 13.37 53 Fertilizers (NPK 15-15-15) 200 0.89 178 Ca (Kg) 1000 0.07 71 Seeds (Kg) 80 33 Labor (#workdays) 1 8.92 9 Raygrass Cattle Labor (#workdays) 20 8.92 178 Meat sale price (US$/t) 1000 Milk sale price (US$/t) 180 Annual health costs (US$/animal) 60 Annual cattle nutritional requirements (per animal) Energy (megacalories x 1000/yr) 4.8 Protein (t/yr) 0.21 Nutritional composition of pasture Energy (megacalories/kg) 2.7 Protein (kg of protein/kg dry matter) 0.17 Dry matter (%) 20 [a] Express in dollars at 2000: Exchange rate = US$1873/1 Colombian peso. [b] Express in dollars at 2006: Exchange rate = US$22 84/1 Colombian peso. [c] Includes different type of crop health products

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72 Table 4-2. Economic benefits from conventional and conservation til lage in potato-based systems in Fuquene watershed (Colombia)*. Characteristic Rotations Conventional tillage C onservation tillage Net income (US$) 13,092 15,280 Marginal income n.a. 2,188 Average annual income (US$) 1.870 2,183 Marginal annual income n.a. 313 Income due to potato (US$) 11,689 14,341 Marginal potato income n.a. 2,652 Income due to milk 4,119 4,119 Marginal milk income n.a. n.a Income due to meat 105 105 Marginal meat income n.a. n.a Use of workdays 564 554 Marginal change (%) n.a. -2 Estimations made in a hectare basis and fo r a 7-yr period and discounted by a 5% rate Table 4-3. Annual average values for pot ato production under two tillage systems Characteristic Conventional tillage Conservation tillage Change (%) Production costs (US$ ha-1)* 2077 1857 -11 Labor costs ($US ha-1) 909 906 0 Potato productivity (kg ha-1) 26937 29625 10 Potato sale price (US$ kg-1) 0.217 0.217 0 Use of workdays (ha-1) 126 122 -3 Without including labor costs

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73 Table 4-4. Carbon stock changes and Greenhouse gas (GHG) emissions of conventional tillage practices in potato-based production systems in Fuquene watershed, Colombia Year Crop/cover Carbon stock changes (tCO2e yr-1) GHG emissions (tCO2e yr-1) SOC CO2 due to use of fossil fuels N2O due to nitrogen fertilization CH4 and N2O due to livestock increase 1 ryegrass n.a. 0 0 6.3 2 potato n.a. 0.56 4.37 0 3 potato n.a. 0.56 4.37 0 4 ryegrass n.a. 0 0 6.3 5 ryegrass n.a. 0 0 6.3 6 potato n.a. 0.56 4.37 0 7 potato n.a. 0.56 4.37 0 Sub-total n.a. 2.24 17.48 18.9 Total 38.62 Table 4-5. Carbon stock changes and GHG emissions of conservation tillag e practices in potatobased production systems in F uquene watershed, Colombia Year Crop/cover Carbon stock changes GHG emissions (tCO2e yr-1) SOC (tCO2e yr-1) CO2 due to use of fossil fuels N2O due to nitrogen fertilization CH4 and N2O due to livestock increase 1 ryegrass-oat 116.9 0.18 0.33 6.3 2 potato 116.9 0.24 2.43 0 3 potato 116.9 0.24 2.43 0 4 ryegrass 116.9 0 0 6.3 5 ryegrass-oat 116.9 0.18 0.33 6.3 6 potato 116.9 0.24 2.43 0 7 potato 116.9 0.24 2.43 0 Total 818.3 1.32 10.38 18.9 Total GHG emissions 30.6 Net GHG removal 787.7

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74 CHAPTER 5 SUMMARY AND CONCLUSIONS The Rehabilitation Ability of Co nservation Tillage in Disturbed Paramo Soils The results of this study highlight the ability of conservation tillage to recover the soil characteristics of the paramo ecosystem once im pacted by conventional ti llage practices. In the Fuquene watershed, conservati on tillage has improved the AWC, the saturated hydraulic conductivity and the mesoporosity by 30, 56 a nd 30% respectively. Al so, bulk density was reduced by 15%. These improvements result from the correcting effect of conservation tillage on soils where soil porosity and soil infiltration were compromised by conventional agriculture which indeed causes soil crusting or soil air exposure (Poulenar d et al., 2001). Apart from the improvement in these physical soil characteristics, conservation tillage improved SOC. Conservation tillage showed a ma rked improvement in the C concentration and in the average C content for the whole soil profile ( 100 cm depth) with re spect to conventional tillage. This indicates that conservation til lage has shortened the gap between SOC in conventional tillage and in undisturbed paramos a 45% increase in C co ntent over conventional tillage (from 612 to 891 t ha-1). Particularly interesting is a 177% increase in the deeper A2 horizon (from 215 to 596 t ha-1) although most of the C is stored in the top A1 horizon (1097 t ha-1). This clearly visible effect is attributed to the effect of oat cover cr op roots that tend to be deep roots in these soils. Also, the improvements in C with depth may be related with the fact that under conservation tillage the vegetation cover is kept and then the soil surface is not exposed to air and sun which otherwise favors th e mineralization of the organic matter due to organic-mineral complexes get separated re leasing the organic matter susceptible to decomposition by the action of microorganism s (Hofstede, 2001; Stevenson, 1986). Although this effect has been showed for a variety of so il types and environments (e.g. Alfisol, Oxisol,

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75 Mollisol, Ultisol; Denef et al., 2004; Bossyut et al., 2002; Edwards et al.,1992; Grant, 1997; and Black and Tanaka, 1997) what is interesting from this study is that conservation tillage improves those initial levels of organic matter, even in our OM-rich soils proper of paramos ecosystems. In addition, most of the SOM and SOC studies were concentrated in superf icial soil horizons (20 cm depth; Bossuyt et al., 2002) contrasting with this study that explored differences to an average depth of 117 cm. In general, the relevanc e of these results lies in the fact that while most soil paramos studies have reported how land use changes modify the unique properties of paramos soils none have explored how better management practices in agriculture can rehabilitate them. In Which Soil Fraction Soil Organic Carbon (SOC) and Soil Organic Matter (SOM) Improvements Are Occurring? Considering that more than 80% of the total carbon was in aggregates and that AOM increased in SF2, SF3 and SF4 could indicate that the 29% difference in Total SOM (g/g) between conservation tillage and conventional tillage (Chapter 2) can be explained by increments of AOM in these size fractions that correspond to small macr oaggregates. In horizon A1 (0 cm) the differences between conservation agricu lture and conventional ag riculture were 37, 33 and 30% for SF2, SF3 and SF4 respectively, and 58, 99 y 98% in SF2, SF3 and SF4 of horizon 2 (78 cm).Thus, this study confirms the findings of Denef et al. (2004) and Kong et al. (2005) in that most changes in total SOC were expl ained by differences in AOM caused by no-till (in our case reduced tillage) in smaller macroaggregates (0.25 2 mm). Therefore our results tentatively support Kong et al. (2005) in th e use of the microaggregate-within small macroaggregate fraction as a potential indicator of long term C sequest ration in agricultural lands. Bossuyt et al. (2002) and Six et al. (1999) showed that same results are explained by the enhancement of microaggregate-protected and micro within macroaggregate-protected C in

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76 conservation tillage systems than in conventional tillage systems. This wa s a result of disruption avoidance of macroaggregates characteristic of no-till systems permitting the formation of microaggregates in which C is stabilized and seques tered in the long term. The role of plant roots from cover crop should be playing an important ro le as biding agent by ensuring the formation of macroaggreates (Tisdall and Oades, 1982, Cambar della, 2002). Thus, we postulate that higher amounts of SOM in SF2, SF3 and SF4 found in th is study, and specially a relative greater increase of AOM in SF3 and SF4 (0.5 2 mm size) with respect to conventional agriculture, should also be related to an in crease of microaggregat es within these sma ller macroaggregates. The rationale behind this is that most of the AOM in SF3 and SF4 was released at certain energy levels that may correspond to the energy leve l where the macroaggregates broke down into microaggregates. It is worth mentioning that the application of different ultrasound energy levels permitted the separation of larger, weaker aggregates into smaller, stronger aggregates, before breaking down into primary particles. This hierarchical order of aggregation was noted clearly by a step-wise curve. Based on Kong et al. (2005) findings, where in creases on C stabilization in the smaller macroaggregates were associated to greater aggregate stability and long-term sequestration, we suggest in the same direction, that the higher AOM and SOM in smaller macroaggregates in our soils is linked to greater C and aggregates stability and in cons equence is contributing to long term C sequestration in the Andes. Greater stabil ity in conservation tillage was suggested in the aggregates dispersion curves where clear er step-wise curves were obtained. Changing To Conservation Tillage: A Trade O ff Between Net Economic Revenues And Net Greenhouse Gas (GHG) Removals? Chapter 4 results showed that conservation tillage increases net return implying an absence of opportunity costs and therefore a net economic benefit for the farmer. Better net returns from

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77 conservation tillage were attributed to decreases in input cost s particularly due to reduced machinery operations and fertilizers applications In another hand, cons ervation tillage reduced GHG emissions and increased the soil carbon stoc k resulting in a positive net GHG removal (788 vs 39 tCO2 ha-1 in conventional tillage ) and in line w ith other studies that consider two main effects of conservation tillage in carbon emissions: i) an incr ease on soil carbon retention because less organic matter is loss to oxidati on as mixing the soil and soil temperature are reduced; and ii) carbon emissions ar e reduced because it requires fewer machinery operations (Uri et al., 1999). Thus the results of this study indicate that conservation tillage is a win-win alternative for Fuquene farmers by benefiting ec onomically the farmer and by providing clearly an ecosystem service or in other words there is a complementary rat her than a competitive tradeoff between the economic a nd environmental benefits. Although this, a 15% of increase in net revenue s in our study area could be not enough to overcome the possible aversion to risk of farmers and to encourage them to make an additional investment to cover initial extra costs of conserva tion agriculture (ie. cultivation of oat as cover crop). This fact may explain why this practice is not widely adopted in the Fuquene watershed. Therefore, our results showed that although c onservation tillage practic es are feasible in mountainous areas and low income countries as is our study area, the required investment could be constraining the adoption and therefore credits may be import ant for enhanci ng the adoption (Carcamo et al., 1994) or by providing an extra incentive. This last may be come via payments for the net GHG removals. This could add up to US$450 yr-1 (based on 788 tCO2 ha-1 in 7 years (see chapter 4), and assuming a flat carbon price of $4 tCO2 which is a conservative price). This carbon payment could alone cover oat production co sts and increased the net revenues of the farmer by 29% instead of 15% caused by the econo mic benefits of conservation tillage alone.

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78 It is worth noting that thes e results and the values s hould not be generalized and extrapolated to any situation wh ere conservation tillage is practic e, since the potential for soil carbon sequestration depends on the type of crop grown, the cropping pattern, the type of soil and the climatic conditions (Donigian et al., 199 4; Uri et al., 1999). Moreover for our study site the identified carbon sequestration potential can not be extrapolat ed in time assuming a linear behavior of it as carbon increases are not perp etual. It is believed that there is a carbon sequestration saturation point (20 to 50 years) (Lal and Br uce, 1999) depending on climatic conditions, soil characteristics, and production management practices (Franzluebbers, 1997; Franzluebbers et al., 1999; Hunt et al., 1996; Wood et al.,1991; Zobeck et al., 1995). Further Research Needs Although, it has been suggested that the increas e in soil organic carbon associated with the adoption of conservation tillage will continue for a period of 25 to 50 yr depending on climatic conditions, soil characteristics, and production management practices (Franzluebbers, 1997; Franzluebbers et al., 1999; Hunt et al., 1996; Wood et al.,1991; Zobeck et al., 1995), still the question left unanswered by this study site relates to the time frame for which improvements on SOC and organic matter will be achieved with conservation tillage, and also under which baseline conditions conservation t illage could improve disturbed soil properties in paramos. It only suggests that these changes can be brought about in as little as 7 years. On the other hand, further studies on the protection mechanis ms favoring C sequestration in smaller macroaggregates should be the topic of future studies as also should be confirmed if this is related to an increase of microaggregates with in these smaller macroaggregates as suggested by our results. To finalize, it is suggested to evaluate th e impacts on soil carbon and water-related soil properties of using in this conservation tillage system, other type of green manure cover crops

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79 (i.e. turnip and common vetch). Based on the evid enced important role of roots to increase soil carbon in the subsoil, it is suggested to eval uate the trade off be tween the economic and environmental benefits (carbon se questration and soil water reten tion and infiltration) of using the above-ground biomass of the cover crop for feed ing animals keeping the root biomass in the soil vs. leaving the above-gr ound biomass as residues. General Conclusions Conservation tillage in potato-based system s improved in a 7 year period the soil organic matter and carbon content in disturbed soils of the paramos of Colombia. The soil carbon concentration in the whole profile was 29% higher under conservation tillage than under conventional tillage sites and the carbon cont ent was higher by 45%. C content improvement specially occurred in the subso il (A2 horizon) increasing by 177% although most of the C is stored in the top A1 horizon. This improveme nt was correlated to the enhancement of soil physical characteristics related with soil wate r movement and storage such us bulk density, AWC, saturated hydraulic conductivity and mes oporosity. These improvements confirm this studies first objective that cons ervation tillage can be used to rehabilitate soil under potato production in the region. On the other hand OM in aggregates is importa nt in these soils by re presenting more than 80% of total OM of these soils and by been positively affected by c onservation tillage. This improvement showed a preferential C sequestrati on in smaller macroaggregates (<2 mm). Also the higher values of %AOM derived from smaller macroaggregates (SF3 and SF4) suggests that in these fractions the C has a sl ower turnover that the C in bigg er macroaggregates (>2 mm). The aggregate dispersion energy curves further suggest this is happeni ng in microaggregates within the smaller macroaggregates fraction. Sim ilar results have been obtained for other soils

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80 suggesting that smaller macroaggregates can be used to evaluate potential of long term C sequestration in Alfisols, Molliso ls, Ultisols and now Andosols. To finalize when these environmental benefits were weight up with the economic impacts of conservation tillage, a complementary tradeoff between the economic and environmental benefits was found for our study site. This relies on the fact net farmer revenues were increased by reduced machinery operations and fertiliz ers applications, while GHG emissions were reduced by increasing soil carbon retention and reducing GHG emissions from machinery operations. Thus, although conservation tillage practices are not wide ly adopted in the watershed payments for net GHG removals could in crease more the net revenues and facilitate the investment to cover initial extra costs of conservation agriculture (ie. cultivation of oat as cover crop).

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81 APPENDIX A DESCRIPTION OF SOIL PROFILES Table A-1. Description of soil pr ofiles in conservation and conven tional tillage site s of the Upper Fuquene Lake watershed Horizon Texture Color Structure Consisten cy Redoximorphic Features* Pedon depth(cm ). No Lowe r depth (cm) Boun d dist. USD A Class Cla y % Hue Valu e Chrom a Grad e Shape** Moist Redox conce n. Redo x deple t. Red.matr ix Conservation tillage site 1 140 1 55 sil 19 10 YR 2.5 1 mo sbk fr N N N 2 105 g sl 9 7.5 YR 3 2 mo abk fi Y N N 3 c c 51 10 Y 5 4 mo sbk fi Y N N Conservation tillage site 2 140 1 34 l 26 10 YR 3 2 st gr vfr N N N 2 89 c sil 22 10 YR 2.5 1 mo gr vfr Y N N 3 120 g c 46 10 YR 3 2 mo abk vfi Y N N 4 a cl 39 10 YR 5 4 st ma vfi Conservation tillage site 3 140 1 140 sil 12 10 YR 2.5 1 st gr fr N N N Conservation tillage site 4 130 1 130 sil 13 10 YR 2.5 1 st gr fr N N N Conservation tillage site 5 150 1 72 g sil 23 10Y R 2.5 1 st gr fr 2 123 c sic 42 10 YR 4 3 sl ma vfr Y N 3 sic 46 10 YR 6 1 sl ma vfr Y Y Y (yes), N (No) Boundary distinctness: g (gradual), c (clear), d (diffuse). USDA class: sil (silty loam), cl (clay loam), c (clay), l (loam), sl (sandy loam), sic (silty clay) Grade: mo (moderate), st (strong), wk (weak), sl (structureless) ** Shape: gr (granular), abk (angular blocky), sbk (subangular blocky), ma (massive), pl (platy) Consistence: fr (friable), vfi (very firm), vfr (very friable)

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82 Table A-1. Continued Horizon Texture Color Structure Consistenc y Redoximorphic Features Pedon depth(cm) No. Lowe r depth (cm) Bound dist. USDA Class*** Clay % Hue Val ue Chroma Grade Shape Moist Redox concen. Redox deplet. Red. matri x Conservation tillage site 6 150 1 110 d sil 22 10YR 2.5 1 st gr fr N N N 2 135 c l 17 10 YR 2.5 1 mo pl fr Y N Y 3 c 48 10 YR 4 3 mo pl fr Y N N Conventional tillage site 7 144 1 70 c sil 25 10YR 2.5 1 st gr vfr N N N 2 90 g c 54 10 YR 3 2 mo pl fr Y N N 3 sic 44 10 YR 6 5 sl ma vfr Y Y Conventional tillage site 8 150 1 93 c sil 22 10YR 2.5 1 st gr vfr N N N 2 123 g cl 30 7.5 YR 4 2 mo abk vfr Y N N 3 sic 42 7.5 YR 5 2 sl ma vfr Y N Y Conventional tillage site 9 150 1 55 c l 18 10YR 2.5 1 st gr vfr N N N 2 75 g cl 39 10 YR 3 2 mo abk vfr N N N 3 l 21 5 YR 7 1 sl ma vfr Y N Y Conventional tillage site 10 150 1 60 d sil 17 10YR 3 1 mo sbk fr N N N 2 123 c l 24 10 YR 2.5 1 st abk fr N N N 3 cl 35 10 YR 3 3 mo abk fr Y N N Conventional tillage site 11 150 1 25 c l 25 10YR 3 2 mo gr fi N N N 2 35 g cl 36 10 YR 2.5 1 st sbk fr N N N 3 150 c 65 10 YR 5 6 wk abk vfi Y N N Conventional tillage site 12 130 1 25 c l 26 10YR 3 2 mo gr fi N N N 2 35 g c 45 10 YR 2.5 1 st sbk fr N N N 3 130 c 65 10 YR 5 6 wk abk vfi Y N N Y (yes), N (No); Boundary distinctness: g (gradual), c (clear), d (diffuse). *** USDA class: sil (silty loam), cl (clay loam), c (clay), l (loam), sl (sandy loam), sic (silty clay) Grade: mo (moderate), st (strong), wk (weak), sl (structureless) Shape: gr (granular), abk (angular blocky), sbk (subangular blocky), ma (massive), pl (platy) Consistence: fr (friable), vfi (very firm), vfr (very friable)

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83 APPENDIX B EFFECTS OF DIFFERENT MANAGEMENT SYSTEMS AND ENERGY INPUTS ON AGGREGATED ORGANIC MATTER (AOM) Table B-1. Effect of treatment and energy levels in %AOM in a ggregates of size fraction 3 (1 mm) in the horizon 1. Treatment* E level** %AOM Mean Duncan group ** 1 0 19.2 a 1 1 19.3 a 1 3 21.2 a 1 2 21.4 a 2 0 21.9 a 2 2 22.5 a 2 1 23.8 a 2 3 26.4 a 2 5 26.4 a 2 4 27.7 a 2 6 31.6 a 1 4 34.3 a 1 5 35.2 a 1 6 35.9 a 2 7 54.7 b 2 8 69.6 b 1 7 87.9 c 1 8 88.1 c 2 9 93.3 c 2 10 97.2 c 1 9 98.6 c 1 10 98.7 c Treatment 1: Conservation tillage; Treatment 2: Conventional tillage ** Energy levels: 1(3.4 J/ml), 2 (10.3 J/ml), 3 (10. 9 J/ml), 4 (17.0 J/ml), 5 (22.8 J/ml), 6 (28.5 J/ml), 7(32.6 J/ml), 8 (40.7 J/ml), 9 (57.6 J/ml) and 10 (75.4 J/ml). **Mean values with different letter inside the same column are significantly different

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84 Table B-2. Effect of treatment and energy levels in %AOM in a ggregates of size fraction 3 (1 mm) in the horizon 2. Treatment* E level** %AOM Mean Duncan group ** 2 2 16.2 a 2 1 16.4 a 2 0 16.9 a 2 3 19.7 a 1 2 20.1 a 2 6 20.8 a 2 4 21.5 a 1 1 21.8 a 2 5 22.2 a 1 3 23.5 a 1 0 25.0 ab 1 4 33.3 ab 1 5 35.7 ab 1 6 36.2 ab 2 7 50.0 b 2 8 50.8 b 2 9 82.3 c 1 7 98.2 c 2 10 98.5 c 1 8 99.2 c 1 10 99.5 c 1 9 99.8 c Treatment 1: Conservation tillage; Treatment 2: Conventional tillage ** Energy levels: 1(3.4 J/ml), 2 (10.3 J/ml), 3 (10. 9 J/ml), 4 (17.0 J/ml), 5 (22.8 J/ml), 6 (28.5 J/ml), 7(32.6 J/ml), 8 (40.7 J/ml), 9 (57.6 J/ml) and 10 (75.4 J/ml). *** Mean values with different letter inside the sa me column are significantly different at p<0.05

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85 Table B-3. Effect of treatment and energy levels in %AOM in aggregates of size fraction 4 (0.5 1 mm) in the horizon 2. Treatment* E level** %AOM Mean Duncan group ** 2 0 18.4 a 2 1 21.0 a 2 2 21.9 a 2 3 25.1 a 2 4 25.9 a 2 6 27.1 a 2 5 31.0 ab 1 0 32.9 ab 1 2 35.0 ab 1 1 35.4 ab 1 3 46.1 abc 2 8 66.0 bcd 2 7 72.2 cd 1 4 89.4 d 1 5 93.9 d 1 6 96.4 d 1 10 99.3 d 1 8 99.5 d 1 7 99.6 d 2 9 99.6 d 1 9 99.6 d 2 10 100.0 d Treatment 1: Conservation tillage; Treatment 2: Conventional tillage ** Energy levels: 1(3.4 J/ml), 2 (10.3 J/ml), 3 (10. 9 J/ml), 4 (17.0 J/ml), 5 (22.8 J/ml), 6 (28.5 J/ml), 7(32.6 J/ml), 8 (40.7 J/ml), 9 (57.6 J/ml) and 10 (75.4 J/ml). *** Mean values with different letter inside the sa me column are significantly different at p<0.05

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86 Table B-4. Analysis of variance of AOM (g/g), energy levels and trea tments per size fraction classes in two horizons Horizon 1 / p-values Horizon 1 / p-values Size Class 1 (5mm) Size Class 2 (2mm) Size Class 3 (1mm) Size Class 4 (0.5mm) Size Class 1 (5mm) Size Class 2 (2mm) Size Class 3 (1mm) Size Class 4 (0.5mm) Treatment 0.774 .001* .000* .000* 0.102.000* .000* .000* E level 0.000* 0.000* 0.000* 0.000* .000* .000* 0.000* .000* Treatment*E level 0.984 0.060.0980.6140.9530.164 .010* .035* Significant at 5% (p < 0.05). Table B-5. Comparison between AOM and SOC (g/g) (Soil Organic Carbon) in different management systems, horizons and size fractions. AOM (g/g) Mean SOC (g/g) Mean Horizon 1 Horizon 2 Horizon 1 Horizon 2 Treatment Size Class 2 (2mm) Size Class 3 (1mm) Size Class 4 (0.5mm) Size Class 2 (2mm) Size Class 2 (2mm) Size Class 3 (1mm) Size Class 4 (0.5mm) Size Class 2 (2mm) Conventional tillage 0.06 (a)* 0.09(a) 0.13(a) 0.04(a) 0.03 (a) 0.05(a) 0.08(a) 0.02(a) Conservation tillage 0.08 (b) 0.12(b) 0.17(b) 0.07(b) 0.05(b) 0.07(b) 0.10(b) 0.04(b) *The means followed by different le tters within a same column are statistically different at p < 0.05

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87 Table B-6. Effect of treatment and energy levels on AOM(g/g) in aggregates of size fraction 3 (1 mm) in the horizon 2. Treatment* Energy level** AOM (g/g) Mean Duncan group*** 2 1 0.02 a 2 0 0.02 a 2 2 0.02 a 2 3 0.02 a 2 6 0.02 a 2 5 0.03 a 2 4 0.03 a 1 2 0.04 a 1 1 0.04 a 1 3 0.04 a 1 0 0.05 a 1 4 0.06 a 2 8 0.06 a 2 7 0.07 a 1 5 0.07 a 1 6 0.07 a 2 9 0.13 b 2 10 0.15 bc 1 7 0.18 c 1 8 0.19 c 1 10 0.19 c 1 9 0.19 c Treatment 1: Conservation tillage; Treatment 2: Conventional tillage ** Energy levels: 1(3.4 J/ml), 2 (10.3 J/ml), 3 (10. 9 J/ml), 4 (17.0 J/ml), 5 (22.8 J/ml), 6 (28.5 J/ml), 7(32.6 J/ml), 8 (40.7 J/ml), 9 (57.6 J/ml) and 10 (75.4 J/ml). *** Mean values with different letter inside the sa me column are significantly different at p<0.05

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88 Table B-7. Effect of treatment and energy levels on AOM(g/g) in aggregates of size fraction 4 (0.5 mm) in the horizon 2. Treatment* Energy level** AOM (g/g) Mean Duncan group*** 2 0 0.03 a 2 1 0.03 a 2 3 0.04 a 2 2 0.04 a 2 4 0.04 a 2 6 0.04 a 2 5 0.05 ab 1 0 0.06 ab 1 2 0.06 ab 1 1 0.06 ab 1 3 0.09 ab 2 8 0.10 abc 2 7 0.12 bcd 1 4 0.16 cd 2 9 0.17 d 2 10 0.17 d 1 5 0.17 d 1 6 0.18 d 1 10 0.18 d 1 8 0.18 d 1 7 0.18 d 1 9 0.18 d Treatment 1: Conservation tillage; Treatment 2: Conventional tillage ** Energy levels: 1(3.4 J/ml), 2 (10.3 J/ml), 3 (10. 9 J/ml), 4 (17.0 J/ml), 5 (22.8 J/ml), 6 (28.5 J/ml), 7(32.6 J/ml), 8 (40.7 J/ml), 9 (57.6 J/ml) and 10 (75.4 J/ml). *** Mean values with different letter inside the sa me column are significantly different at p<0.05 Table B-8. Analysis of variance of Total %AOM using the log of 101-AOM% Aggregated Organic Matt er in Horizon 1 and 2 SS dfMS F p Horizon 0.387 1 0.387 1.58 0.212 Size Fraction Class 9.679 4 2.42 9.88 .000* treatment 0.304 1 0.304 1.24 0.269 Horizon*Size Fraction Class 0.178 4 0.045 0.182 0.947 Horizon*treatment 0.003 1 0.003 0.014 0.907 Size Fraction Class*treatment 1.247 4 0.312 1.273 0.288 Horizon*Size Fraction Class*treatment 0.292 4 0.073 0.298 0.878 Significant at 5% (p < 0.05).

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89 Table B-9. Non parametric analysis of % AOM in Horizon 1 Aggregated Organic Matter Treatment 1 Treatment 2 Size fraction Median Median p value 5 mm 59 81 0.2801 2 5 mm 97 86 0.0308* 1 2 mm 98.7 97.8 0.0308* 0.5 1 mm 99.6 99.2 1 Significant at 5% (p < 0.05). 0 20 40 60 80 100 120 020406080100 Energy (J/mL)%AOM released Horizon 1 > 5mm size fraction Horizon 2 > 5mm size fraction Horizon 1 0.5 -1mm size fraction Horizon 1 2-5 mm size fraction Horizon 2 2-5 mm size fraction Figure B-1. Aggregated organi c matter (percent of total organic matter) of > 5 mm and 0.5 mm aggregates size fractions, released with different energy inputs, in two management systems.

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90 APPENDIX C DESCRIPTION OF A MODEL FOR THE EC ONOMIC, SOCIAL, AND ENVIRONMENTAL EVALUATION OF LAND USE (ECOSAUT) The ECOSAUT model uses linear programming to optimize net income from different land-use systems, taking into account soci al, economic, and environmental criteria (Quintero et al., 2006). It has been employed to evaluate the so cioeconomic impacts of land use alternatives in past studies (i.e. Quintero et al., 2009; Rubiano et al., 2006) and therefore, to support stakeholders in making decisions about multiple land-use options. To use this model it is required to know the system to be modeled and how each variable affects the activities in the syst em and how the system affects th e variables. It has been found that ECOSAUT is useful for analyzing wh at could be the possible impacts of land use/management alternatives at a plot or wate rshed scale which is useful to demonstrate the environmental and socioeconomic impacts to de cision-makers; and for analyzing trade offs between land use scenarios and different type s of benefits (environmental, social and economical). According to Quintero et al. (2006) the m odel was built on the basis of the relationship between decision variables and decision alternatives. Decision variables correspond to the constraints established by the systems bi ological and economic capacities, farmer considerations, or regional policie s. Decision alternatives refer to activities that are carried out in the system to maintain its functioning. Table C1 presents the principal decision variables and alternatives considered in this model. Once these variables and alternatives were interrelated, the model was built, using an Excel spreadsheet. On this spreadsheet, a matrix for making optimizations was prepared, using linear programm ing. The type of information that the user should enter depending on the analysis objectives is described below. Information on Production Systems Agriculture Crops and forages that are part of the production system Design of rotations over 5 years (or 10 semesters) Costs of establishing each crop or forage ($/ha) Labor used for each crop per semester The value of a work day for purchase and sale (the option of generating income by working outside the farm is also considered) Yield per selected crop per semester or harvest (t/ha) Prices of agricultural and livestock products ($/t) Management practices (e.g., infilt ration ditches and live barriers)* Area used for each management practice (ha) Costs of implementing each management practice ($/ha) Time of rotation in which management practices are implemented Optional: depending on the case, entering data on this variable may not be necessary.

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91 Table C-1. Principal variables and decision alternatives in the optimization model VARIABLES DECISION ALTERNATIVES SCENARIOS Rotations of crops (ha/ yr) with/without minimum tillage & Permanent forests (ha) Permanent pastures with/without green manures Supplements for feeding cattle N o. cows Farm incomes (sales of meat, milk, wood, harvest) (t/yr) Environmental incomes for environmental services idd( 3 /)d N and P pollution residual waters (t/yr or sem.) Buys & sells labor according to job profiles Bank loans Net incomes (n yr) (objective function) X X X X X X X X X Capital X X X X X X Cash flows (by sem. or yr) X X X X X X X X Land availability (upper, medium and downstream watershed) (ha) X X X Erosion thresholds by land use (t/sem.) X X X Hydrological balance, contribution to the superficial aquifer (m3/ha/sem.) X X X X X N contributed to water flows by land uses (t/ha/sem.) X X X X X X CO2 fixation by vegetative cover (t/ha/sem.) X X X Labor profiles by land uses (no. workdays/sem.)X X X X Wood production by planted forests (t/ha) X Wood production by native forests (t/ha) X Energy production for lives tock (megacal./K/ha)X X X X Protein production for livestock (kg dry matter/ha) X X X X Dairy production (t/sem./individual) X Meat production (t/sem./individual) X X X indicates the presence of a relationship between an a lternative and a variable. The X could be a value that indicates the magnitude of the relationship (e.g. ton of sediments, $, hectares, etc.) Livestock1 Weight per animal unit (kg) Livestocks water consump tion (L/day per animal) Milk production (L/day per animal) Meat production (kg/animal per semester) Concentrate value ($/t) Composition of concentrates for livestock feed: Metabolizable energy (t megacalories/t concentrates) Digestible protein (t/t concentrates)

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92 Nitrogen and phosphorus inputs released to water resources from the intake of concentrates (t/t) Protein and energy generated by forages (gra sses, green forages, and crop residues): Percentage of residues from each crop destined for livestock feed (%) Percentage of dry matte r per forage type (%) Energy content of each forage type (megacalories/kg) Protein contents of each forage type (kg protein/kg dry matter) Protein digestibility (%) Information Related To Externalities Sedimentation Processes Sediment yield per land c over per semester (t/ha) Sediment yield per land cover per semester on implementing manageme nt practices (t/ha) Availability of Water in Water Resources Water yield per land cover per semester (t/ha) Water yield per land cover per semester on implementing management practices (t/ha) Sale price of water per semester ($/m3) Carbon Sequestration Capture of carbon dioxide per seme ster per land c over/use (t/ha) Value of carbon dioxide emission removals ($/t) Water Pollution Nitrogen and phosphorus inputs (l eachates) from fertilizers per land cover/use (t/ha per semester or year) Nitrogen and phosphorus inputs from erosion per land cover/use (t/ha pe r semester or year) Nitrogen and phosphorus inputs from livestock inta ke of forages (t/ha per semester or year) Nitrogen and phosphorus inputs from livestock intake of concentrates (tons of N + P per ton of concentrates) Depending on the particular environmental problems, not all th e externalities (considered) listed here would necessarily be (motive for study) used as inputs to the simulation. The model has been applied us ing hydrological information generated by hydrological modelling

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93 Information Related to Climatic Risks Impact of frosts on production of each crop or forage (% of reduc tion in production) per semester or year. Impact of drought on production of each crop or forage (% of re duction in production). For further information about the model see: http://www.condesan.org/index.shtml?apc=Ea--mic-x-x4-&x=7603

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94 LIST OF REFERENCES Angers, D. A. and C. Chenu. 1997. Dynamics of Soil Aggregation and C Sequestration. P 199 206. In Lal, R., Kimble, J.M., Follet, R.F. a nd Stewart, B.A. (eds). Soil Processes and the Carbon Cycle. CRC Press. Boca Raton, USA. Angers, D.A. 1992. Changes in soil aggregation and organic carbon under corn and alfalfa. Soil Sci. Soc. Am. J. 56:1244. Antle, J.M., S.M. Capalbo, K. Paustian and M. Kamar Ali. 2007. Estimating the economic potential for agricultural soil carbon sequestration in the Central United States using an aggregate econometric-process simulati on model. Climatic Change 80:145. Azooz, R.H., and M.A. Arshad. 1996. Soil infiltr ation and hydraulic co nductivity under longterm no-tillage and conventional tillage sy stems. Can. J. Soil Sci. 76 (2): 143. Azooz, R.H., and M.A. Arshad. 2001. Soil water dryi ng and recharge rates as affected by tillage under continuous barley and barl eycanola cropping systems in northwestern Canada. Can. J. Soil Sci. 81 (1): 45. Bajracharya, R.M., Lal, R. and Kimble, J.M. 1997. Soil Organic Ca rbon Distribution in Aggregates and Primary Particle Fractions as Influenced by Erosion Phases and Landscape Positios. p. 353. In Lal, R., Kimble, J.M., Follet, R.F. and Stewart, B.A. (eds). Soil Processes and the Carbon Cycle. CRC Press. Boca Raton, USA. Beare, M.H., P.F. Hendrix, and D.C. Coleman. 1994. Water-stable aggreg ates and organic matter fractions in conventional and no-tillage soils. Soil Sci. Soc. Am. J. 58:777. Black, A. and D. Tanaka. 1997. A Conservation T illage Cropping Systems Study in the Northern Great Plains of the United States, p. 335. In Paul, E., K. Paustien, E. Elliott and C. Cole (eds.), Soil Organic Matter in Temper ate Agroecosystems. CRC Press, Boca Raton, FL. Bohlen, P.J., S. Lynch, L. Shabman, M. Clark, S. Shucklas and Swain, H. 2009. Paying for environmental services from agricu ltural lands: an example from the northern Everglades. Front Ecol Environ. 7(1): 46. Boody, G., B. Vondracek, D.A. Andow, M. Krinke J. Westra, J. Zimmerman, P. Welle. 2005. Multifunctional agriculture in the US. BioScience. 55: 27. Boone, F.R., K.H. van der Werf, B. Kroesbergen, B.A. ten Hag and A. Boers. 1986. The effect of compaction of the arable layer in sandy soil on the growth of maize for silage. I. Mechanical impedance. Netherlands Jour nal of Agricultural Science. 34: 155. Bossuyt, H., J. Six, and P.F. Hendrix. 2002. A ggregate-Protected Carbon in No-tillage and Conventional Tillage Agroecosystems Using Ca rbon-14 Labeled Plant Residue. Soil Sci. Soc. Am. J. 66:1965.

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95 Bouyoucos, G. 1936. Directions for making mechanic al analysis of soil by hydrometer method. Soil Sci. 4: 225. Bronick C.J. and R. Lal. 2004. Soil structur e and management: a review. Geoderma 124:3 Burke, I.C., E.T. Elliott, and C.V. Cole. 1995. Influence of macroclimate, landscape position and management on soil organic matter in agroecosystems. Ecol. Appl. 5:124. Burwell, R. E., R. R. Allmars, and L. L. Slone ker. 1966. Structural alteration of soil surfaces by tillage and rainfall. J. Soil and Water Cons. 21: 61. Buytaert, W., R. Celleri, B. De Bivre, R. Hofste de, F. Cisneros, G. Wyseure, and J. Deckers. 2006. Human impact on the hydrology of the Andean pramos. Earth Science Reviews 79:53. Buytaert, W., J. Sevink, B.D.Leeuw, J. Deckers. 2005. Clay mineralogy of the soils in the south Ecuadorian pramo region. Geoderma 127, 114. Cambardella, C.A. and E.T. Elliott. 1993. Methods for physical separation and characterization of soil organic matter fractions. Geoderma 56: 449. Cambardella, C.A. 2002. Aggregation and organic matter, p. 52. In: Lal, R. 2002.(Eds) Encyclopedia of Soil Sciences. School of Na tural Resources. The Ohio State University. Marcel Dekker, Inc. NY. USA. Campbell C.A., K.E. Bowren, M. Schnitzer, R.P. Zentner and L. Townley-Smith. 1991. Effect of crop rotations and fertili zation on soil biochemical properties in a thick Black Chernozem. Can. J. Soil Sci. 71: 377. Carcamo, J., J. Alwang, G. Norton. 1994. On -site economic evaluation of soil conservation practices in Honduras.Agric ultural Economics 11: 257. Carter, M.R. 1992. Influence of reduced tillage systems on organic matter, microbial biomass, macro-aggregate distribution and structural stab ility of the surface soil in a humid climate. Soil Tillage Res. 23:361. Carter, M. R., and D. A. Rennie. 1982. Cha nges in soil quality under zero tillage farming systems: Distribution of microbial biomass and mineralizable C and N potentials. Canadian Journal of Soil Science 62:587. Carter, M.R., 1992. Characterizing the soil physic al condition in reduced tillage systems for winter wheat on a fine sandy loam using small cores. Can. J. Soil Sci. 72, 395 Clay J. 2004. World agriculture and the envi ronment: a commodity-by-commodity guide to impacts and practices. Washington, DC: Island Press. Cole, C.V., K. Flach, J. Lee, D. Sauerbeck, and B. Stewart. 1993. Agricultural sources and sinks of carbon. Water Air Soil Pollut.70:111.

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96 De la Torre, D., C.M. Hellwinckle, and Larson, J.A. 2004. Enhancing Agri cultures Potential to Sequester Carbon: A Framework to Estimate Incentive Levels for Reduced Tillage. Environmental Management 33: 229. Denef, K., J. Six, R. Merckx, K. Paustian. 2004. Carbon Sequestration in Microaggregates of No-Tillage Soils with Different Clay Mineralogy. Soil Sci. Soc. Am. J. 68:1935 Daz E.B. and L.P Paz. 2002. Evaluacin del rgime n de humedad del suelo bajo diferentes usos, en los paramos Las Animas (Municipio de Silvia) y Piedra de Len (Municipio de Sotar).Departamento del Cauca. MSc thesis. Fundacion Universitaria de Popayan. Popayn, Colombia. Donigian, A., T. Barnwell, T., R. Jackson, A. Patwardhan, K. Weinrich, A. Rowell, R. Chinnaswamy, and C. Cole. 1994, Alternative Management Practices Affecting Soil Carbon in Agroecosystems of the Central U.S., U.S. Environmental Protection Agency, Washington, DC. Doyle, G., C.W. Rice, D.E. Peterson, J. St eichen. 2004. Biologically Defined Soil Organic Matter Pools as Affected by Rotation and Tillage. Environmental Management 33: 528 S538 Duiker, S.W. 2002. Aggregation, p. 49. In: La l, R. 2002.(Eds) Encyclopedia of Soil Sciences. School of Natural Resources. The Ohio State University. Marcel Dekker, Inc. NY. USA. Edwards A.P. and J.M. Bremmer. 1967. Micr oaggregates in soils. J. Soil Sci. 18:64 Edwards, J.H., C. W. Wood, D. L. Thurlow, and M. E. Ruf. 1992. Tillage and Crop Rotation Effects on Fertility Status of a Hapl udult Soil. Soil Sci. Soc. Am. J. 56:1577 Ellert, B.H., H. H. Janzen, and T. Entz. 2002. Assessment of a Method to Measure Temporal Change in Soil Carbon Storage. Soil Sci. Soc. Am. J. 66:1687 Elliott, E.T., 1986. Aggregate structure and ca rbon, nitrogen and phosphorus in native and cultivated soils. Soil Sci. Soc. Am. J., 50: 627. Elliot, E.; Heil, J.; Kelly, E. and Monger, H.C. 1999. Soil Structural and Other Physical Properties. In. Robertson, G.P; Coleman, D.; Bledsoe, C. and Sollins, P. (Eds). Standard Soil Methods for Long-term Ecological Rese arch. LTER. New York, Oxford University Press. USA. Evers, G. and A. Agostini. 2000. No-tillage fa rming for sustainable land management: Lessons from the 2000 Brazil study tour. Rome, Italy: FAO. FAO, 2001. The economics of conserva tion agriculture. Rome, Italy. FAO. 2002. The state of food and agri culture 2002. Rome, Italy: FAO.

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97 Franzluebbers, A.J., F.M. Hons, and D.A. Zube rer. 1995. Tillage and crop effects on seasonal dynamics of soil CO2 evolution, water conten t, temperature, and bulk density. Appl. Soil Ecol. 2:95. Franzluebbers, A. 1997. Soil microbial bioma ss and mineralizble carbon of water-stable aggregates. Soil Sci. Soc. of Amer. J. 61, pp. 1090. Franzluebbers, A., G.Langdale, a nd H. Schomberg. 1999. Soil car bon, nitrogen, and aggregation in response to type and frequency of tillage Soil Sci. Soc. of Amer. J. 63, pp. 349. Govaerts, B., K.D. Sayre, K. Lichter, L. De ndooven, J. Deckers.2007. Influence of permanent raised bed planting and residue management on p hysical and chemical soil quality in rain fed maize/wheat systems. Plant Soil 291:39 Grant, F. 1997. Changes in soil organic matter unde r different tillage and rotations: mathematical modeling in ecosystems. Soil Sci. Soc. of Amer. J. 61: 1159. Hofstede, R., 2001. El impacto de las actividades humanas sobre el pramo. In: Mena, P., G. Medina y R. Hofstede (Eds.). Los pramos del Ecuador. Particularidades, problemas y perspectivas. Abya Yala/Proyecto Pramo. Quito. Holland, J.M. 2004. The environmental consequences of adopting conservati on tillage in Europe: reviewing the evidence. Ag ric Ecosyst Environ 103:1 Hunt, P. G. 1996. Changes in carbon content of a Norfolk loamy sand after 14 years of conservation or conventional tillage. J. of Soil and Water Conserv. 51: 255. Instituto Geogrfico Agustn Codazzi (IGAC). 2000. Estudio general de suelos y zonificacin de tierras del Departamento de Cundinamarca. Bogota, Colombia. IPCC. 2000. Land use, land-use change and fore stry. Cambridge, UK: Intergovernmental Panel on Climate Change. IPCC. 2006. Guidelines for National Greenhouse Gas Inventories Agriculture, Forestry and Other Land Use. Volume 4. http://www.ipccnggip.iges.or.jp/public/2006gl/vol4.html Jastrow, J.D. 1996. Soil aggregate formation and the accrual of particulate and mineralassociated organic matter. Soil Biol. Biochem. 28: 665. Jastrow, J.D., T.W. Boutton, and R.M. Millar. 1996.Carbon dynamics of aggregate-associated organic matter estimated by carbon-13 natura l abundance. Soil Sci. Soc. Am. J. 60: 801 807. Jeong, H., and L. Forster. 2003. Em pirical Investigation of Agricultural Extern alities: Effects of Pesticide Use and Tillage System on Surface Water. Department of agricultural, Environmental and Development Economics. Th e Ohio State University. Working Paper: AEDE-WP-0034-03.December 2003. Ohio.

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99 Nyagumbo, I. 1997. Socio-cultural constraints to small-holder farming development projects in Zimbabwe: a review of experiences from farm er participatory rese arch in conservation tillage. The Zimbabwe Science News, 31(2): 42. Oades, J.M. 1984. Soil organic matter and structural stability: Mechanisms and implications for management. Plant Soil 76:319. Oades, J.M., and A.G. Waters. 1991. Aggregate hierarchy in soils Aust. J. Soil Res. 29:815. Patio-Ziga, L., J. A. Ceja-Navarro, B. Gov aerts, M. Luna-Guido, K. D. Sayre, and L. Dendooven. The effect of different tillage and residue management practices on soil characteristics, inorganic N dynamics and emi ssions of N2O, CO2 and CH4 in the central highlands of Mexico: a laboratory study. Plant Soil DOI 10.1007/s11104-008-9722-1 Paustian, K., J. Six, E.T. Elliott, and H.W. Hunt. 2000. Management options for reducing CO2 emissions from agricultural soils. Biogeochemistry 48:147. Pedroni, L. and P. Rodriguez-Noriega, 2006. Tool for afforestation and reforestation approved methodologies TARAM. Version 1.3. CATI E World Bank. Turri alba. Costa Rica. Podwojewski, P., L. Poulenard, T. Zambrana, and R. Hofstede. 2002. Overgrazing effects on vegetation cover and properties of volcanic as h soil in the pramo of Llangahua and La Esperanza (Tungurahua, Ecuador). Soil Use and Management 18:45. Porras I, Grieg-Gran M, and Neves, N. 2008. A ll that glitters: A review of payments for watershed services in developing countries. Na tural Resource Issues No. 11. International Institute for Environment and Development. London, UK. Post, W., R. Izaurralde, L. Ma nn, and N. Bliss. 2001. Monitoring and verifying changes or organic carbon in soil. Climatic Change 51:73. Poulenard, J., P. Podwojewski, J.L Janeau, a nd J. Collinet. 2001. Runoff and soil erosion under rainfall simulation of Andisols from the Ecuadorian Paramo: effect of tillage and burning. Catena 45:185. Poulenard, J., P. Podwojewski, A.J. Herbillon. 2003. Characteristics of non-allophanic Andisols with hydric properties from the Ecua dorian paramos. Geoderma 117: 267 Pretty, J., and A. Ball. 2001. Agricultural infl uences on carbon emissions and sequestration: a review of evidence and the emerging trading options. University of Essex, Centre for Environment and Society, Ocassional Paper 2001-03. Quintero, M. and W. Otero. 2006. Mecanismo de financiacin para promover Agricultura de Conservacin con pequeos productores de la cuenca de la laguna de Fquene. Su diseo, aplicacin y beneficios. Internationa l Potato Center. Lima. Peru.

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101 Soil Survey Laboratory Staff. 1996. Soil survey laboratory manual. Soil survey investigation report No. 42. USDANRCS. U.S. Governme nt Printing Office, Washington, D.C Stevenson, F.J. 1986. Cycles of soil: carbon, nitrogen, phosphorus, sulfur, micronutrient. John Wiley & Sons, New York. Stevenson, F.J. 1994. Humus chemistry: Gene sis, composition, reactions. 2nd edition. John Wiley and Sons, New York. Strudley, M.W., T.R. Green, J. C. Ascough II. 2008. Tillage effects on soil hydraulic properties in space and time: State of the scie nce. Soil & Tillage Research 99:4 Sundquist, E.T. 1993. The global carbon dioxide budget. Science 259:936. Swanston, C.W., M.S. Torn, P.J. Hanson, J.R. Southon, C.T. Garten, E.M. Hanlon, and L. Ganio. 2005. Initial characterization of processes of soil carbon stabili zation using forest standlevel radiocarbon enri chment. Geoderma 128: 52. Swinton M, F. Lupi, G.P. Robertson and D. A. Landis. 2006. Ecosystem services from agriculture: looking beyond the usual suspects. Am J Agric Econ. 88: 1160. Tisdall, J.M., and J.M. Oades. 1982. Organic ma tter and water-stable aggr egate and soil organic aggregates in soils. J. Soil Sci. 33:141. Tweeten, L. 1995. The structure of agriculture: implications for soil and water conservation. Journal of Soil and Water Conservation, 50: 347. Uri, N. D., J. D. Atwood, and J. Sanabria. 1999. The Environmental benefits and costs of conservation tillage. Environmental Geology 38: 111 Van Wambeke, A., 1992. Soils of the Tropics: Properties and Appraisa l. McGraw-Hill, New York. VandenBygaart, A. J., X. M. Tang, B. D. Kay, and J. D. Aspinall. 2002. Variability in carbon sequestration potential in no-till soil landscap es of southern Ontari o. Soil and Tillage Research 65:231. Wood, C., J. Edwards, and C. Cummins. 1991. Tillage and crop rotation effects on soil organic matter in a typic hapludalt of Northern Al abama. J. of Sustain. Agri. 2: 31. Zentner, R.P., G.P. Lafond, D.A. Derksen, C.A. Campbell. Tillage method and crop diversification: effect on economic returns and riskiness of cropping systems in a Thin Black Chernozem of the Canadian Prai ries. Soil & Tillage Research 67: 9 Zibilske, L.M., J.M. Bradford. 2007. Soil aggregation, aggregate ca rbon and nitrogen, and moisture retention induced by conservation tillage. Soil Sci Soc Am J 71:793

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102 Zobeck, T., N. Rolong, D. Fryear, J. Bilbro, and B. Allen. 1995. Properties of recently tilled sod, 70-year cultivated soil, J. of Soil and Water Conserv. 50: 210.

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103 BIOGRAPHICAL SKETCH Ecologist from the Javeriana University in B ogot, Colombia and Master Candidate of the University of Florida at the Water and Soil Depa rtment. She is a student, a CIAT (International Center for Tropical Agriculture) employee and a consultant. She works most of her time for CIAT, and during her last 5 years she worked as a project member of the Challenge Program on Water and Food (CPWF) project named E nvironmental Services Promoting Rural Development in the Andean region (South America). Her core work experience has been on analyzing ecosystem services as well as its valuation and quantification in Peru, Colombia, Ecuador and Nicaragua. Marcela ha s been involved in many other projects at CIAT. In addition to her participation at the CPWF project, she is currently responsible at CIAT of a carbon sequestration project in Colombia negotiated wi th the BioCarbon Fund of the World Bank; and is part of the research team working on a project in Nicaragua to assess the socioeconomic and environmental trade offs of legume-based system s. Also, she collaborated with the Theme 2 of the CPWF supporting two African projects in the application of the ECOSAUT (Economic, Social, and Environmental Evalua tion of Land Use) model, developed in the Andes and now being applied in other regions. She was awarded as Outstandi ng Young Scientist at CIAT for year 2006. As a consultant, she co llaborates with other instituti ons such as the GTZ (Technical German Cooperation), CONDESAN (Consortium fo r Sustainable Development of the Andean Ecorregion) and The Katoomba Group.