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Labor, Soil Quality, and Yield in Conventional and Ecological Small-Scale, Tropical Agroecosystems

Permanent Link: http://ufdc.ufl.edu/UFE0021597/00001

Material Information

Title: Labor, Soil Quality, and Yield in Conventional and Ecological Small-Scale, Tropical Agroecosystems
Physical Description: 1 online resource (84 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: agriculture, agroecology, developing, ecological, labor, smallscale, soil, sustainable
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Small-scale agriculture in the developing tropics is often concomitant with rural poverty. High labor requirements can impose a social burden that negatively affects quality of life. Degrading soil quality (SQ) can reduce future productivity. Economic returns are low, because yield per person (or labor productivity) is not sufficient to provide basic necessities. At the center of this problem is the nature of small-scale farming in the developing tropics. The most sustainable management would simultaneously lower labor inputs, increase SQ, and increase yields. Ecological approaches depend on ecological cycles and relationships within the agroecosystem for management, while conventional approaches look outside the agroecosystem for management options. In our study, we measured labor and labor productivity, SQ and SQ efficiency, and yield of field-scale agroecosystems using either conventional or ecological management. A cross-sectional design with referral sampling was used to study 18 agroecosystems during the June-August 2006 agricultural season in in Leon, Nicaragua. The studied agroecosystems were small-scale sesame farms with sandy- loam andisols in a tropical dry climate. A management index identified the approach to overall agroecosystem management on a scale from conventional to ecological. A semi-structured interview was employed to gather data labor and yield data for Sesamum indicum production. Soil sampling and indicator analysis measured soil quality. These included % organic matter, acidity, phosphorus availability, biotic activity, and bulk density at two depths. T-tests and Mann-Whitney were used to test for differences between the two groups. Total labor requirements were not different between managements, nor was labor productivity. Labor amounts (man-days/Mz) differed significantly only for fertilization (p < .05) and disease management (p < .10), with ecological agroecosystems requiring more labor. Conventional agroecosystem allotted a greater proportion of their total labor to weed (p < .10) and insect pest (p < .10) management than did ecological agroecosystems. Labor productivity was not different between treatments for any practices or in totality, though very small sample sizes lowers confidence in these results. Labor results indicate that where techniques are different, ecological management practices often require more labor. The exception is insect pest control. Where techniques are similar, there is no difference in labor between managements. No soil quality indicator or efficiency was affected by management regime. Therefore, in most respects ecological sustainability did not change with management. This contrasts with most studies to date. Yield was similarly not different between management, indicating that ecological management does not necessarily lead to yield reductions. Given all this, it seems that neither agroecosystem is more sustainable. This may be due to similarity in inputs between all small-scale systems, regardless of management type.
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.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Popenoe, Hugh L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021597:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021597/00001

Material Information

Title: Labor, Soil Quality, and Yield in Conventional and Ecological Small-Scale, Tropical Agroecosystems
Physical Description: 1 online resource (84 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: agriculture, agroecology, developing, ecological, labor, smallscale, soil, sustainable
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Small-scale agriculture in the developing tropics is often concomitant with rural poverty. High labor requirements can impose a social burden that negatively affects quality of life. Degrading soil quality (SQ) can reduce future productivity. Economic returns are low, because yield per person (or labor productivity) is not sufficient to provide basic necessities. At the center of this problem is the nature of small-scale farming in the developing tropics. The most sustainable management would simultaneously lower labor inputs, increase SQ, and increase yields. Ecological approaches depend on ecological cycles and relationships within the agroecosystem for management, while conventional approaches look outside the agroecosystem for management options. In our study, we measured labor and labor productivity, SQ and SQ efficiency, and yield of field-scale agroecosystems using either conventional or ecological management. A cross-sectional design with referral sampling was used to study 18 agroecosystems during the June-August 2006 agricultural season in in Leon, Nicaragua. The studied agroecosystems were small-scale sesame farms with sandy- loam andisols in a tropical dry climate. A management index identified the approach to overall agroecosystem management on a scale from conventional to ecological. A semi-structured interview was employed to gather data labor and yield data for Sesamum indicum production. Soil sampling and indicator analysis measured soil quality. These included % organic matter, acidity, phosphorus availability, biotic activity, and bulk density at two depths. T-tests and Mann-Whitney were used to test for differences between the two groups. Total labor requirements were not different between managements, nor was labor productivity. Labor amounts (man-days/Mz) differed significantly only for fertilization (p < .05) and disease management (p < .10), with ecological agroecosystems requiring more labor. Conventional agroecosystem allotted a greater proportion of their total labor to weed (p < .10) and insect pest (p < .10) management than did ecological agroecosystems. Labor productivity was not different between treatments for any practices or in totality, though very small sample sizes lowers confidence in these results. Labor results indicate that where techniques are different, ecological management practices often require more labor. The exception is insect pest control. Where techniques are similar, there is no difference in labor between managements. No soil quality indicator or efficiency was affected by management regime. Therefore, in most respects ecological sustainability did not change with management. This contrasts with most studies to date. Yield was similarly not different between management, indicating that ecological management does not necessarily lead to yield reductions. Given all this, it seems that neither agroecosystem is more sustainable. This may be due to similarity in inputs between all small-scale systems, regardless of management type.
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.
Thesis: Thesis (M.S.)--University of Florida, 2008.
Local: Adviser: Popenoe, Hugh L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021597:00001


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3a79d0c2c0ac517677ff87fdd4cef0edf4ebd5fa







LABOR, SOIL QUALITY, AND YIELD INT CONVENTIONAL AND ECOLOGICAL
SMALL-SCALE, TROPICAL AGROECOSYSTEMS























By

ALVARO ALEJANDRO VALLE


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2008

































O 2008 Alvaro Alej andro Valle



































A mi familiar









ACKNOWLEDGMENTS

The completion of this work was made possible only through the assistance, guidance, and

patience of my committee. Special thanks go to the head of my committee, Dr. Hugh Popenoe,

for willingly extending his practical and philosophical guidance, time (revision after revision),

enormous store of tropical experience, frankness, and hospitality at the HLP ranch. Dr. Marilyn

Swisher is an expert on conducting science. Her didactic ability, insistence on conducting

fundamentally correct work, and openness to ideas have all been incredibly appreciated. Dr.

Robert McSorley has been a model agroecologist for me, and I thank him for this. The earnest

enthusiasm, rational and clear opinion, and indispensable scientific understanding will not be

forgotten.

Further, I would like to thank personnel of UNAN-Leon. I am often inspired by their

intellectual tenacity in the face of limited recognition. Marlon Molina, Adrian Catin, and Don

Anibal are especially thanked for their earnest effort, local knowledge of Leon, and friendship

during the summer of 2006. Needless to say, this study was critically dependent on the advice,

research, and genuine support of Dra. Xiomara Castillo. I am indebted to these persons. Finally,

the staff at Laboratorios Quimicos SA made it explicitly clear why they are the foremost

environmental testing laboratory in Nicaragua.

A Tropical Environment and Development Fellowship from the Compton Foundation

financed this effort. Their intentions, and their desire to support third world research, are

honorable. Thanks to Dr. Susan Jacobson, Anne Fitzgerald, and everyone else involved with the

Compton Foundation.












TABLE OF CONTENTS


page


ACKNOWLEDGMENTS .............. ...............4.....


LIST OF TABLES ................. ...............7......._.....


LIST OF FIGURES .............. ...............8.....


AB S TRAC T ......_ ................. ............_........9


CHAPTER


1 INTRODUCTION ................. ...............11.......... ......


Rural Poverty ................. ...............11.......... .....
S mall- S cale Agri culture ................. ...............11...............
Sustainability .............. .. ...............12...
Sustainable Management ................. ...............14.......... ......
Research ................. ...............16.................


2 LITERATURE REVIEW ................. ...............18................


Energy Inputs and Effieiency .............. ...............18....
Ecosystem Effects and Effieiency .............. ...............20....
O utput .............. ...............25....
Obj ectives ................. ...............26.......... .....
Hypotheses............... ...............2

3 METHODOLOGY .............. ...............28....


Research Context ................. ...............28.................

Agronomy ................. ...............28.......... ......
Ecology ................. ...............29.......... ......
Research Design ................. ...............3.. 1..............
Sample Selection .................. ..... ...............3
Instrument, Procedure, and Analysis ................. ...............33................
Management Index .............. ...............33....
Index construction ............. ..... .__ ...............33...
Indexing procedure............... ...............3
Index score .............. ...............35....
Semi-Structured Interview............... ...............3

Soil Quality Assessment............... ...............3
Soil Sampling .............. ...............39....
Soil Quality Analysis............... ...............40
Statistical Analysis............... ...............42













4 RE SULT S .............. ...............44....


Census Population .............. .... ...............44..

Energy Inputs and Productivity .............. ...............44....
Ecological Indicators and Efficiency ................. ...............45................

O utput ................. ...............1.......... ......


5 DI SCUS SSION ................. ...............48................


Census Population ................. ...............48...
Labor Inputs and Productivity .............. ...............49....
All Management ................. ...............49.......... .....
F ertilizati on ........._.__....... .__. ...............50..
Disease ........._.__....... .__. ...............5 1...
W eeds .............. ...............52....
Insect Pests .............. .. ...... ...............53

Soil Quality and Ecological Efficiency .............. ...............54....
Y ield .............. ...............57....
Conclusions............... ..............5


APPENDIX


A PROTOCOLS .............. ...............60....


B INDEX ................. ...............63.......... ......


C SEMI- STRUCTURED INTERVIEW ................. ......... ...............66......


D DE SCRIPTIVE STATISTIC S............... ...............7


LIST OF REFERENCES ................. ...............76........... ....


BIOGRAPHICAL SKETCH .............. ...............84....










LIST OF TABLES


Table page

4-1 Results of Mann-Whitney U test for labor amounts (man-days/Mz), percent of total
labor (%), and labor productivity (Qt/(man-day)) between conventional and
ecological growers. ............. ...............46.....

4-2 Sample sizes for labor productivities per practice. ............. ...............46.....

4-3 Calculated p-values of soil quality indicator and efficiency means between
conventional (n=10) and ecological (n=8) farms using t-test for independent samples....47

B-1 Indicator rankings by experts............... ...............64

B-2 Individual indicator scores by replicate. ............. ...............65.....

D-1 Mean and standard deviation of response variables. ........._... ...._.. ........_........74











LIST OF FIGURES


Figure page

3-1 Original management indicators. ............. ...............43.....

3-2 Final management indicators. ............. ...............43.....

3-3 Index scoring example. ............. ...............43.....

4-1 Histogram of replicate management index scores. ............. ...............45.....

A-1 Protocol for management index construction. ............. ...............60.....

A-2 Interview protocol ................. ...............61................

A-3 Soil sampling protocol. ............. ...............62.....









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

LABOR, SOIL QUALITY, AND PRODUCTION INT CONVENTIONAL AND ECOLOGICAL
SMALL-SCALE, TROPICAL AGROECOSYTEMS

By

Alvaro Alej andro Valle

May 2008

Chair: Hugh Popenoe
Major: Interdisciplinary Ecology

Small-scale agriculture in the developing tropics is often concomitant with rural poverty.

High labor requirements can impose a social burden that negatively affects quality of life.

Degrading soil quality (SQ) can reduce future productivity. Economic returns are low, because

yield per person (or labor productivity) is not sufficient to provide basic necessities. At the

center of this problem is the nature of small-scale farming in the developing tropics. The most

sustainable management would simultaneously lower labor inputs, increase SQ, and increase

yields.

Ecological approaches depend on ecological cycles and relationships within the

agroecosystem for management, while conventional approaches look outside the agroecosystem

for management options. In our study, we measured labor and labor productivity, SQ and SQ

efficiency, and yield of Held-scale agroecosystems using either conventional or ecological

management. A cross-sectional design with referral sampling was used to study 18

agroecosystems during the June-August 2006 agricultural season in in Leon, Nicaragua. The

studied agroecosystems were small-scale sesame farms with sandy- loam andisols in a tropical

dry climate. A management index identified the approach to overall agroecosystem management

on a scale from conventional to ecological. A semi-structured interview was employed to gather









data labor and yield data for Sesamnum indicum production. Soil sampling and indicator analysis

measured soil quality. These included % organic matter, acidity, phosphorus availability, biotic

activity, and bulk density at two depths. T-tests and Mann-Whitney were used to test for

differences between the two groups.

Total labor was not different between managements, nor was labor productivity. Labor

amounts (man-days/Mz) differed significantly only for fertilization (p<.05) and disease

management (p<. 10), with ecological agroecosystems requiring more labor. Conventional

agroecosystem allotted a greater proportion of their total labor to weed (p<. 10) and insect pest

(p<. 10) management than did ecological agroecosystems. Labor productivity was not different

between treatments for any practices or in totality, though very small sample sizes lowers

confidence in these results. Labor results indicate that where techniques are different, ecological

management practices often require more labor. The exception is insect pest control. Where

techniques are similar, there is no difference in labor between managements.

No soil quality indicator or efficiency was affected by management regime. Therefore, in

most respects ecological sustainability did not change with management. This contrasts with

most studies to date. Yield was similarly not different between management, indicating that

ecological management does not necessarily lead to yield reductions. Given all this, it seems

that neither agroecosystem is more sustainable. This may be due to similarity in inputs between

all small-scale systems, regardless of management type.









CHAPTER 1
INTTRODUCTION

Rural Poverty

Approximately 2.5 billion rural people are living on small farms in the developing world

(International Food Policy Research Institute (IFPRI) 2007). Asians and Africans comprise the

bulk of this figure, but there are also 19 million rural dwellers (two thirds are poor) in Central

America who are ostensibly tied to small-scale agriculture (Soto 2003). Nicaragua is one of the

Central American nations with a poor agricultural populace. Forty three percent of Nicaragua' s

total population is rural (Food and Agriculture Organization (FAO) 2006), and 68.5% of this

rural population is poor (World Resources Institute (WRI) 2005). Considering the high rate of

poverty, economic sustainability may be low. Some focus on sustainable productivity of small-

scale agroecosystems is needed to alleviate tropical rural poverty, especially where this poverty

is extreme, entrenched, or widespread (IFPRI 2007, World Bank 2003, WRI 2005). To this end,

we conducted a study on the sustainability of small-scale field production on a western

Nicaraguan andisol typical of tropical, developing nations.

Small-Scale Agriculture

Poor people and small-scale farmers suffer from the same fundamental problem: both lack

access to resources required to secure a livelihood (Beets 1992, Adger 1999). In the case of

small-scale tropical growers, these are mainly land and agronomic inputs of all types (Beets

1992). Even if land is available, deficient agronomic resources can constrict the ability to

cultivate additional land or properly cultivate present crops (Alwang and Siegel 1999). These

agronomic limits include meager extension services (especially for non-traditional cash crops),

limited or insecure credit options, expensive or unattainable inputs, available and willing labor,

lacking irrigation infrastructure, and prohibitive mechanization costs. Moreover, restricted









access to agronomic resources forces tropical smallholders to rely on local agroecosystems for

management support (Altieri 2002, WRI 2005).

What the development community constitutes as small-scale agriculture is contextually

dependent on geographic location, agronomic support, and market environment (IFPRI 2007).

61% of all agricultural holdings in Nicaragua are under 14 ha, and 47% are less than seven

hectares (FAO 2001). Only 7% of all land in Nicaragua is irrigated (FAO 2006), and we

observed virtually no irrigation except on sugarcane and peanut- the domain of large- scale

agriculture. Mechanization is usually limited to tractor rental for pre-planting tillage. Our study

site is near the Leon (0.5 million inhabitants), Managua (1.2 million), and international (via Pan

American highway) markets. Small-scale growers of Leon simultaneously produce for

consumption, for markets, and with traditional and modern technologies. This reflects the

modern small-scale agriculturalist in the Mesoamerican tropics (Popenoe and Swisher 1998).

Given all this, and after consultation with local experts, the upper limit of small-scale holding is

set at 10 manzanas (16.80 acres or 6.41 hectares) of ownership or land under production. After

this point, we observed that economic production and agricultural scale resembles a more mid-

scale operation.

Sustainability

Tropical rural poverty is evidence of low economic sustainability in small-scale

production. Low economic sustainability can be attributed to low labor productivity, which is

output per person laboring (in our case, the owner-farmer), because labor productivity, in effect,

is the economic return to the grower once the product is sold. With all else held equal, the

established relationship describes increasing economic returns as labor productivity increases.

Labor productivity can be increased by the mechanisms of intensification or extensification,

where land is available. For either mechanism, there must be access to various agronomic









resources. One of those resources, labor, must become more available in one of three ways to

allow further work: willing labor must become available, labor saving machinery must be

introduced, or productivity of Hield labor must increase. In the absence of labor changes,

intensification can proceed through better management of possessed resources. The central

problem for the small-scale tropical farmer is that both mechanisms are near impossible because

access to agronomic resources (including labor and credit), access to land, and research for

improved management is limited at best. Even where land is available, a lack of agronomic

resources still negates the possibility of extensification. In the absence of outside investment or

institutional support, most tropical growers will suffer from vulnerability to ecological and

economic flux, weak terms of trade, and a near impossibility to pull themselves out of poverty.

(Kiker 1993, Tomich et al. 2001).

Soil has a pivotal role in increasing economic sustainability through crop production. Soil

processes and functions are critically involved in primary production. Thus, a critical objective

in achieving economic sustainability in the tropics and improving rural livelihoods is maintaining

and improving the ecological basis of small farm sustainability- soil quality (Lal 1991, Stocking

2003). Smallholder African farmers, for example, investing in soil conservation often achieve

higher land productivity (Byringiro and Reardon 1996), effectively intensifying and increasing

economic returns. For agriculture, soil quality is the capacity of an agroecosystem soil to

support sustainable plant production (Soil Science Society of America (SSSA) 1997). It is a

holistic concept that recognizes the interacting physical, chemical, and biological properties that

make soil so important for sustainable production in the tropics. Making soil the holistic basis

for production is particularly salient where extension services, context- appropriate research,









consulting services, and other support for agro technical soil management is presently out of

reach.

The andisols of this study are derived from high silica, pyroclastic ej ecta from periodic

volcanic eruptions. With high temperatures and an ustic moisture regime, this parent material

has a high Si to Al ratio and unique allophane- type clays. Allophane is amorphous clay with

comparatively high cation exchange capacities, due to the high surface area and many positively

charged exchanged sites. In combination with prevalence of silica oxides, and to lesser degree

iron oxides, allophane soils retain much organic matter and are infamous phosphorous fixers.

This frequently makes phosphorus a limiting nutrient in andisol agriculture. Consequently,

organic matter percentages in dark, native soils are many times above 5% and long-term

phosphorus fixation levels are often around 50% (Joergenson and Castillo 2001). In general, the

high percentage of organic matter, strong structure, high native fertility, and deep rooting depth

makes andisols productive soils, although easily eroded. The ecological sustainability is stronger

than for the indigent smallholder in many other developing nations. Nonetheless, conserving and

enhancing soil quality is important for the many rural poor whose land is their only real wealth

(WRI 2005). (Parfitt 1989)

Sustainable Management

Relatively immediate improvements to labor productivity and rural poverty, without

intensive investment, can be garnered by increasing sustainability through better agroecosystem

management (Beets 1992, WRI, 2005). The most sustainable management would lower labor

requirements, increase soil quality, and enhance yields to impart economic sustainability and

ecological sustainability. Any management development that positively affected any of these

three variables would increase some facet of sustainability. Due to the integrated nature of

sustainability, however, an effect on one sustainability facet is likely to affect another. For










example, more socially sustainable production, such as with lower labor requirements, improves

economic sustainability through increased labor productivity. It may also improve ecological

sustainability, since labor is determinant of soil conserving strategies (Marenya and Barrett

2007).

The spectrum of management approaches ranges from conventional to ecological. Wholly

conventional approaches manage agroecosystems from an external perspective, depending on

extra-agroecosystem options to systematically control biological communities and supply crop

needs. Fully ecological approaches manage agroecosystem from an internal perspective,

utilizing the agroecosystem's own ecosystematic functions, processes, and cycles to regulate

biological communities and support plant growth. A large range of combined approaches exist.

Some combinations, such as integrated pest management, are widely used. The quality of

materials often changes with approach, but it is not the fundamental difference. Hence,

substituting organic inputs for inorganic inputs may make management more environmentally

friendly, but it does not indicate a completely ecological management. (Gliessman 2007)

This difference in perspective leads to practical distinction between management regimes.

Ecological management strives for a diversity of crops; fertilizes mainly with organic additions,

recycled nutrients, or through biological fixation; eschews industrially-synthesized pesticides in

favor of alternative methods that prevent pest population; conserves and builds because soil is

viewed as the basis of production; and often uses locally-adapted, heirloom, and traditional

cultivars and crops. Conventional management grows one or very few crops; fertilizes mainly

with imported inorganic fertilizers; applies chemically-synthesized pesticides for pest control;

uses soil mostly as a media for nutrient additions and physical support; and typically sows with

industrially enhanced/modified/treated seed of commercially ubiquitous varieties. We will refer










to agroecosystems managed ecologically as ecological agroecosystems and those managed

conventionally as conventional agroecosystems. We note that organic agroecosystems fall under

the heading of ecological agroecosystems.

Research

The main inquiry of this investigation determines which management is likely to produce

the most sustainable agriculture in this context. We test the hypotheses that ecologically based

management is the most sustainable management for resource poor, small-scale farmers in the

tropics, as Altieri (2002) and other have suggested. There is some evidence from Philippine

small-scale farmers that they themselves perceive this to be true (Mendoza 2004). We will

answer this question and test the hypothesis by comparing labor, soil quality, and yield in

conventional and ecological agroecosystems. This is not a legitimate sustainability analysis,

since the requisite temporal element of sustainability was not pursued in any fashion. Rather,

this is a management analysis that serves as a measured proxy of sustainability. Utility of the

analysis is based upon the assumption that response in a reasonably typical year will be similar in

the future if management and ecological conditions do not drastically change.

An agroecosystems framework is employed in this observational study. This perspective

attempts to understand ecosystem functioning and processes as flows of matter/energy from

input pools, to internal pools, to the output. Each pool is affected by the flow from the previous

pool. The premise of this is that agricultural fields can be viewed as ecosystems. As these fields

contain the components and structure of a natural ecosystem, it is valid to view them as managed

ecosystems.

Field scale agroecosystems of sandy loam, andisols under small-scale production of late

rainy season Sesa~num indicum will serve as experimental populations. Growers managing these

systems produce varying products during the early rainy season followed by sesame. Sesame









labor inputs will be measured for each approach. Soil quality effects of this management will be

measured using chemical (percent organic matter, acidity, and phosphorus availability),

biological (biotic activity), and physical (structure as bulk density) indicators. Production is

measured as yield.

Sustainable agricultural development has been seriously undermined by an inability to

fully consider the complex interrelationships involved in production (Lal 1991). This is

addressed by calculating labor productivity (output/labor input) and soil quality efficiency (soil

quality effect/labor input) in response to a management range. Soil quality efficiency is a term

we derived to examine how much soil quality improvement one gains for a given labor input. In

reality, it is the same in concept as any other productivity measurement in that it measures output

(internal SQ effect) for a given amount of input effort (management labor).









CHAPTER 2
LITERATURE REVIEW

Energy Inputs and Efficiency

The scientific community generally contends that there are decreasing energy inputs and

concurrently increasing energy efficiency as management becomes more ecological (Powers and

McSorley 2001). Pimentel et al. (1983) were of the first to find midwestern organic cornfields to

be more energy efficient than conventional growers using high-input techniques. Diverse

systems-- including Mediterranean olive groves (Kaltsas et al. 2007), Australian pasture-cereal

crop rotations (Nguyen and Hayes 1995), and Danish integrated grain- livestock operations

(Dalgaard et al. 2001)- reassert claims of increased energetic efficiency with lower overall

energetic inputs. Overwhelmingly, reduced dependence on synthetic fertilizers and pesticides,

created and transported with fossil fuels, are the main factors in decreasing energy inputs and

increasing energy efficiency in ecologically managed systems (Mader et al. 2002, Sartori et al.

2005). This trend for overall energy inputs holds true after 21 years of production, even

including increased fossil fuel usage by tractors for fertilization with organic manures (Pimentel

et al. 2005). Clements et al. (1995) affirm that reduced herbicide use in more ecological

approaches decreases energy inputs and increases efficiency, despite the usual increases in fossil

fuels for mechanical cultivation. They add that this is true as long as cultivation is used in

moderation.

Whether these developed world findings can be transferred to small-scale tropical systems,

where pesticide are less available and cultivation is often manual, is questionable. Labor is a

relatively minor portion of overall energetic inputs in developed world agriculture, since

mechanization and accessible agronomic inputs can substitute for manual labor (Giampietro and

Pimentel 1990). Understandably, labor is usually excluded, largely discounted, or subsumed in










energy assessments of most comparative management studies (Loake 2001). There are,

however, a few occasions where labor was tracked in the developed world. The Rodale study of

Pimentel et al. (2005) indicates that the diversified, legume- based organic rotations required

35% more labor throughout the growing season to manage more cover crops, cultivate more

often, and handle manure applications when needed. This mirrors findings of Karlen et al.

(1995) that measured up to 75% more labor in a few cases, due mostly to increased cultivation

and handling of manure, in lowa corn/soy Hields. Nguyen and Hayes (1995) Eind the labor inputs

to be higher in the cereal crop portion of their pasture- cereal crop rotations under an alternative

management, but labor requirements were lower and productivity higher over the entire cycle

under alternative management. The reasons for increased labor were similar to the other studies.

The small olive growers in the Kaltsas et al. (2007) study spend more time walking around to

inspect insect baiting traps, than their conventional counterpart spraying pesticides on foot.

The utility of these Eindings is tempered by the fact that labor increases came mostly as

more tractor time. In terms of social sustainability, this cannot be considered the same as

wielding a machete or even spending more time on one's feet. Loake (2001) addresses this

critical distinction between driving a tractor and the physical exertion of more manual labor by

comparing the human energy efficiency of labor on highly mechanized conventional farms to

organic farms using no mechanization. Her results indicate that organic farming in the UK is by

far more physically stressful, some days expending more energy than is gained, both because

more labor is required and because of the physical nature of the work. This is not entirely

surprising, but lends empirical evidence for assessing labor inputs as a matter of social

sustainability, especially where the returns to that labor are lower than desirable.









A few authors have looked at labor requirements for tropical, small-scale growers. In

flooded rice, eight man-days more were required in the organic system for nutrient management

(spreading rice straw and applying compost), but two man-days less were required for organic

land preparation because soil tilth had improved under this management, making more extensive

tillage unnecessary. Despite the initial increases of labor in the organic system, labor decreased

throughout the season and summed to 47.5 overall man-days/ha for organic farming and 52.5 for

conventional farms. These figures were adjusted to take into account the labor intensity of

practices. Additionally, these authors found energy efficiency to increase with organic

management, again largely due to reduction in inorganic fertilizers and synthetic pesticides

(Mendoza 2004). These findings are not mirrored in small-scale Bangladeshi agriculture, where

labor was taken as a measure of social sustainability and found not to be different between

ecological and conventional agriculture (Rasul and Thapa 2003). It seems that evidence of

management's effect on labor in small-scale tropical farming is scant and inconclusive.

Ecosystem Effects and Efficiency

The decreased use of industrially synthesized fertilizers and pesticides causes changes in

agroecosystem structures, processes, and interactions (Drinkwater et al. 1995). Ecological

management has shown changes in agroecosystem biological diversity (Menalled et al. 2007,

Morandin and Winston 2005), in nutrient cycling (Clark et al. 1998, Tortensson et al. 2006), and

in root disease suppression (Bulluck et al. 2001). The effect of management on soil quality is

measured via concrete chemical, biological, and physical indicators that address the integrated

ability of soil to actively support plant production.

Organic matter is often used as an overriding soil quality indicator because of its critical

role in nutrient storage, soil stabilization, ion exchange capacity, biological health, and a myriad

other influences (Reeves 1997, Tiessen et al. 2001). It may be especially important in small-









scale, tropical systems, where soil organic matter is the maj or nutrient cache and determinant of

soil biological activity. Generally speaking, increases in organic matter increase the ability of

the soil to support plant production. A maximum can be reached before soil quality decreases

(Sojka et al. 2001), but this usually only happens with excessive manure applications of the type

from intensive dairy operations.

A long-term, organic, legume- based rotation in Pennsylvania increased organic matter

markedly as residues were incorporated (Drinkwater et al. 1998). Fleissbach et al. (2006),

Widmer et al. (2006), and Manna et al. (2005) recently confirmed the common view that organic

fertilizers or soil- conserving additions, as in ecological agriculture, increases soil organic matter.

This may have positive effects for agroecosystems. Mendoza (2004), for example, explains that

decreased labor for small-scale rice was mainly due to improved soil tilth associated with

increased soil organic matter. The benefits of increased soil organic matter may not be

immediate, however, as measurable increases in organic matter may accrue only after an

extended period of accumulation (Fleissbach et al. 2006, Monokrousos et al. 2006). Since

ecological management fertilizes mainly with organic matter, and attempts to conserve the soil

basis of production with organic additions, it is logical that increases in soil organic matter are

often seen (Lotter 2003).

The chemical indicator of acidity also has a large influence on the ability of soil to support

primary production. In a very general sense, a pH closer to neutrality allows for the production

of a greater number of crops, avoids aluminum/micronutrient toxicity and sodicity, and allows

for greater microbial diversity, valuable in root disease suppression. In the case of tropical

andisols, an increase in pH is an increase in soil quality. Mader et al. (2003), Fleissbach et al.

(2006), Bulluck et al. (2002), and Reagonald (1988) all found pH to increase in differing soils









with organic matter additions (for multiple goals) typical in ecological management. The main

reasons for an increase in pH with ecological management can be reduced to three. Several of

these effects can be in play in any of the studies above. Firstly, significant applications of

synthetic fertilizers and certain pesticides in conventional agriculture are known to acidify soil.

Avoiding these raises pH. Secondly, as manure is a common organic fertilizer, and as manure

often contains salt minerals in differing proportion, an increase in pH may result in acid soils.

Finally, even where organic manures are not used, increases of organic inputs, with composts or

green manures, can raise pH when low (Ouedraogo 2001). This buffering effect depends on

continual additions of organic matter, though, as increased microbial decomposition near

neutrality decreases organic matter rapidly (Hugh Popenoe, personal communication, 2007).

This may cause pH to drop again, where soils are naturally acidic, after the buffering agent is

removed

A more specific indicator of soil quality, given the nature of phosphorus restrictions in

andisols, is phosphorus (P) availability. In lowland, tropical soils with high P fixing capacities,

Lawrence and Schlesinger (2001) demonstrate that long- term agricultural management of

organic matter can affect P distribution, even if total P does not change or is not imported. The

relation between distribution, plant availability, and organic fertilizers was seen in flooded rice

(inceptisol) cultivation (Salaque et al. 2004). This team reports that greater concentrations of

labile and relatively labile P fractions when organic fertilizers (cow dung and ash) were included.

Moreover, these 2 fractions were most affected by plant uptake in the control; so that increases in

concentrations of these 2 fractions increased plant available P. Reddy et al. (2005) examine the

role of organic matter in P availability and find, after 16 weeks of alfisol study, redistributions of

P in favor of labile, colloidal P when crop residues are used instead of inorganic fertilizer. On









vertisols of higher clay content, with the same methodology, the distribution of P was similar,

albeit with a much less drastic effect than in alfisols (Reddy et al. 2001). This lends support to

the idea that relatively invariable soil properties become more influential, and organic matter

less, as the P Eixing capacities become greater. In at least one study, the authors find no

ecologically significant effect on P dynamics with differing fertilizers, indicating that soil

properties were more at play in controlling soil P dynamics than input matter (He et al. 2006).

Castillo and Joergenson (2001) in andisols of the same study area as ours, also Eind soil

properties to be more determinate in the availability of P to biomass then the management

regime, even though more P was clearly seen to increase with conventional management. There

is the possibility that organo- P complexes may increases unavailability in andisols due to the

nature of P occlusion in high organic matter andisols (Borie and Zunino 1983). We should note

that rhizosphere association of arbuscular mychorrhizae play a significant role in plant uptake of

P (Plenchette et al. 2005), but that this does not necessarily translate into greater yields (Ryan

and Graham 2002).

Soil microbes essentially govern nutrient cycling and community stability in the soil

ecosystem and to a major extent control nutrient supply and disease. Microbial activity has been

measured as a sensitive indicator of soil quality under differing management (Marinari et al.

2006) and during different stages of the same management (Monokrousos et al. 2006). Long-

term experiments have concluded that more ecological management results in sustained

increases in microbiological activity and nutrient cycling (including P) (Mader et al. 2002).

Increased microbiological activity with ecological management also suggests that fundamental

differences in agroecosystem ecology are responsible for functional discrepancies between

managements (Drinkwater et al. 1995, Clark et al. 1999). Clark et al (1999), for example,










reported increases in nitrogen mineralization (indicative of higher microbiological activity) that

allowed for increased nutrient cycling to all plants, including weeds. Increased microbiological

activity and diversity, prompted by ecological management, has led to suppression of soil borne

disease and positive effects on crops (Bulluck et al. 2002).

Research has more recently documented the influences of manure quantity and type in soil

microbial community size and composition (Fleissbach et al. 2006). They find the type of

organic inputs, and consequently soil organic carbon, influences the microbiotic activity and soil

quality. The organo-mineral complexes of andisols, for example, may limit C availability to

microbes (Oades 1995), explaining the substantial build up of organic matter in andisols.

Interestingly, Marinari et al. (2006) was not able to relate differences in microbial biomass to

organic matter. Other distinctions between managements, such as in pesticide use, can therefore

also influence soil biology (Hansen et al. 2001). Plenchette et al. (2005) reviewed studies of the

management effect on beneficial mychorrhizae. They conclude that conventional agriculture's

reliance on chemically synthesized pesticides is more deleterious to mychorrhizae than

ecological management not using such inputs. Following suit, Castillo and Joergenson (2001)

attribute increased basal respiration in ecological agroecosystems to decreased pesticide use and

increased diversity of organic residues from more diverse cropping systems.

A priority for soil quality in the 21st century must be the physical management of soils

(Lal 1991, Stocking 2003). Soil erosion in andsiols can be a problem in and of itself, not to

mention the disease and aeration problems that puddling from poor structure can cause. Within

the same soil type and texture, organic matter will be the primary impactor of physical structure.

Since increases in organic matter are more often seen with ecological management, decreases in









measured bulk density are expected with more ecological management. A less compacted soil

improves physical structure for plant growth.

Output

Most comparative management research examines output ability of conventional and

alternative systems. Stanhill (1990), who reviewed 205 comparative studies, estimated an

average 10% yield loss by organic systems. He included agroecosystems recently converted to

ecological management. These agroecosystems may not be as optimized for production as they

might be in the future. Letter (2003), nonetheless, agreed with the estimated yield losses. Often

weeds are blamed for decreased yields under ecological management. One study saw declines of

20% to 35% in wheat yields, despite increases in most soil quality measures, due perhaps to

increased weeds (Mader et al., 2002). Clark et al. (1999) posit that weeds proliferate in

ecological systems exactly because soil quality is higher, for all plants, under ecological

management.

Researchers have also measured similar or higher yields in ecological agroecosystems.

Fresh pepper yields in Florida were similar in both managements (Chellemi et al. 2004), while

Mendoza (2004) saw rice yields increase with organic management. Mendoza (2004) relates this

to disease suppression, more organic matter, and better physical soil structure. Letter (2003)

noticed a trend of increasing ecological yields in drought years, while better climatological years

produced higher conventional yields. He attributes this either to increased mychorrhizal hyphae

or increased organic matter. Both offer drought resistance. Increases in corn and soybean yields

during drought was corroborated by a 22 year field trial at the Rodale Institute that also

highlighted yield similarities among management regimes, especially after an initial transition

period (Pimentel et al. 2005). Yet, an interesting investigation by Martini et al. (2004) negates

the that so called "transition effect" is due to soil quality changes, hypothesizing rather that









increasing ecological management experience increases yields after transition. This favors the

argument that ecological yields do not differ by management type alone.

Either approach may be more desirable under a given set of physical conditions. Similar

tomato yields in California prompted researchers to hypothesize that although differing

ecological processes and pathways can be working on the cropping system, they can ultimately

lead to the same agronomic response (Drinkwater et al. 1995). Clark et al. (1999) also find a

difference in agroecosystem ecology under differing management, but in this case, yields were

decreased in the ecological management. We may not know enough about ecological

management to produce higher output even though it is agronomically possible (Lotter 2003).

Research attempting to establish which management approach is best should be critically

assessed in respect to their validity. Many of these studies are conducted by experts under

controlled conditions and warrant closer examination of generalizability. These studies also

often attempt to eliminate confounding factors by using the same varieties to compare yields,

even though the ideal genotype for conventional agricultural systems may be fundamentally

different from those of ecological agriculture (Van Bueren et al. 2002). This is an integral piece

of the management, and yet is not often explored. The decreases in conventional yields during

drought, normally attributed solely to soil quality matter, could very plausibly be explained by

variety differences.

Obj ectives

The obj ective of this investigation is compare labor, soil quality, and yields of small-scale

field agriculture in the developing tropics. We do this to ascertain whether conventional or

ecological agroecosystems, as defined in the introduction, are likely to be more sustainable.

Furthermore, we attempt to build understanding of tropical agroecosystems.










Hypotheses

1. Labor inputs will be higher, and labor productivity lower, in ecological agroecosystems.

2. Values of soil quality indicators and efficiencies will be higher under ecological
management.

3. Yields will be higher under conventional management.









CHAPTER 3
METHODOLOGY

This research was carried out in the department of Leon, Nicaragua. Farms in the

municipalities of La Ceiba, Leon, and Chacaraseca were sampled from late June to early August

2006 by myself and two assistants- Marlon Molina and Adrien Catin of the Universidad

Nacional de Nicaragua- Leon (UNAN-Leon). Yield data collection, and the return of soil

laboratory results for each participant, took place during January 2007.

Research Context

Agronomy

During the 1970s, the area of Leon was a very profitable monoculture of cotton

(Gossypium hirsutum). Leon produced the highest global yields of long-staple varieties for a

period (Hugh Popenoe, personal communication, 2006). Consequently, this allowed for deep

tillage and heavy pesticide use on both large and small land holdings. Heavy machinery and

poor soil management promoted soil erosion during winter. Ecological disaster ensued as pest

resistance elevated pesticide application to uneconomic, ineffective, and unhealthy rates. Later,

land reforms were initiated and many small-scale operations became the norm. Growers were

organized into cooperatives with machinery to share. Subsequent economic depression,

exacerbated by the collapse of the Soviet Union, hastened the virtually complete withdrawal of

production support. Small grower cooperatives are still common, with the machinery retained by

individuals who now rent their services. Cooperatives have limited negotiation power, as

evidenced by frequent broken contracts. Small-scale growers in cooperatives or otherwise are

alone in marketing and selling. This is a new phenomenon because previous small-scale growers

sold to committed large landholders or government entities.










Only 7% of all arable land in Nicaragua is irrigated (FAO 2005). Therefore, most

production occurs only during the rainy season (May- November). Common crops during the

beginning of the rainy season include field corn, Cucurbitaceous species, yucca (Manihot

esculenta), and fallow hay, with much variation among farmers and between years. All growers

plant sesame in the late rainy season, and in this study, they would be asked about labor inputs

and production for sesame. The strategic need for a single crop to compare yields and labor

amongst management systems was the maj or impetus for this. Furthermore, similarity in an

export commodity allowed for ecological participants to be found via sampling frames of

cooperative lists. Coffee has been used for this purpose, but coffee production systems are

essentially agroforestry systems and not field production. Additionally, sesame seed is the

domain of small- scale, manual labor systems of developing nations and so is an appropriate

selection for the tropical population of interest in this study. Sesame production is not new in

Nicaragua, but has taken on greater importance for the small-scale grower as higher-value export

crops are pursued.

Ecology

The Leon climate is typical of deciduous tropical forest ecosystems. Average annual

rainfall is approximately 1500 mm with an average temperature of 26. 1 C with more then 85% of

this rain coming between May and November (Instituto Nacional de Estudios Territorriales

(INETER) 2006). Temperatures vary little throughout the year.

We collected soil samples during a normal dry period within the rainy season. In 2006, the

start of the rainy season was dryer than normal. The dry period within the rainy season was drier

and longer than historic norms. Labor and yield data would be taken for production during the

second half of the rainy season (August-November). August had -26% less rain; September had

-55% less; October had 37.6% more rain; and November had 88% more precipitation than









historic norms (1972-2000) (INETER 2006). In the last month, seed sets and plants are

particularly vulnerable to Phytopthera infection. Farmers expressed some concern over

excessive rain in November, but ultimately did not seem to be affected by widespread fungal

infections.

Leon, the department, is on the Pacific coastal plain of Nicaragua and is in the shadow of

an active volcanic corridor running the length of the department from North to South. These

soils have been formed by pyroclastic ejecta and are characterized by a high Si/Al proportion and

distinguished by the presence of amorphous clay called allophane. Their andisol identity is

confirmed in several locations. The latest surveys performed by the present-day soils division of

INETER classify them all as ashy, isohypothermic mollic vitrandept of the series Leon, Ceiba,

Cerro Negro, or Guadalupe under the 1972 United States Department of Agriculture (USDA)

taxonomy (Ministerio de Agricultura y Ganaderia (MAG) 1974). Also, these soils are classified

as Vitric Andisols under the 1974 FAO system (Castillo and Joergensen, 2001). These soils

would most likely be presently classified as sandy, isohyperthermic, vitric haplustand.

Roughly 75% of the sampled farms were in the Leon and Ceiba series, with the other 25%

in either Cerro Negro or Guadalupe series (MAG 1974). In the absence of trustworthy GPS

coordinates it was impossible to say with absolute certainty into which series they were

classified. This may be of little consequence, since the qualitative description of series from the

1974 survey are all effectively the same: 90cm effective depth, less than 4% slope, sandy loam

texture, good drainage, and moderate erosion (MAG 1974). Certain soils may have changed

series, due to agriculture and hurricane effects, without changing their volcanic parent material

or sandy-loam texture.









Because at least five observed textures of andisols exist within Leon and because basic soil

characteristics can change drastically with differing texture, it was necessary to assure that all the

farms in the study were of similar texture. We selected sandy-loam to be the soil texture in

common because this was the most prevalent texture in the farming communities where we

expected to find fields includable in our study. The present-day location of sandy loam texture

was also crosschecked with Dr. Xiomara Castillo of UNAN-Leon, with presidents of

cooperatives, with the farmers themselves, and with the texture by feel method when in the field.

This soil texture was chosen because of its relatively close proximity to Leon. This allowed for

many logistical conveniences that would have otherwise made soil sample collection difficult.

Research Design

Our research design is intended to test three hypotheses. We hypothesize that:

1. Labor inputs will be higher, and labor productivity lower, in ecological
agroecosystems.

2. Values of soil quality indicators and efficiencies will be higher values under ecological
management.

3. Yields will be higher under conventional management.

An on-farm, observational study with a cross-sectional design is used to test these three

hypotheses. The maj ority of comparative management research has used true experiments on

research stations with researcher- led design and management. There is evidence, however, that

grower management will lead to different recommendations for on-farm production (Sumith and

Abetsiriwardena 2005). As Drinkwater (2002) notes, "the most important advantage of on-farm

studies is that systems under study are realistic in terms of scale, management practice and

constraints faced by the farmer and therefore offer an opportunity to study intact

agroecosystems".










Cross-section is an appropriate design when there are two existing groups and no

previously applied experimental intervention can be identified or will be applied. There is,

therefore, no control group. This compromises internal validity to a reasonable degree. External

validity is robust. The on-farm approach allows us to sample working agroecosystems with all

the factors of interest as equal to most small-scale agroecosystems in Nicaragua as possible.

Sample Selection

Our individual sampling units are agroecosystems. An agroecosystem is defines as set of

contiguous fields growing late rainy-season sesame on sandy-loam vertisols in Leon. All or only

part of fields may be planted in sesame (justification in introduction). A small-scale system is a

maximum holding of 10 Mz (6.42 ha) (rented or owned), worked primarily by the same owner-

farmer (with hired help for certain tasks), with no irrigation, and using no mechanization post-

planting. Our resulting theoretical population is composed of tropical agroecosystems that 1) are

small-scale, (2) have been managed in the same manner for at least three years. Growers must

have grown sesame at least once within the last 3 years. This ensured that labor as reported

would be accurate. Due to our non-probabilistic sampling scheme, we can only extend our

finding to members of the theoretical population connected, in some manner, to a cooperative of

sesame growers. This is not a maj or restriction, as most sesame growers will be connected to a

cooperative either formally or informally.

Referral sampling is the sampling approach used in this study. Because it was impossible

to identify eligible participants a priori, referral sampling granted us the only real chance of

finding agroecosystems of the accessible population. The initial sampling frame came from lists

of cooperatives provided by Cooperativa Del Campo S.A. of Leon, Nicaragua, which lead to a

list of members of sesame producing cooperatives. We identified members of Cooperativa La

Esperanza of La Ceiba, Leon (President Sra. Querube Perez) and the Asosiacion de Productores









Ecologico de Nicaragua (APRENIC) of Leon, Nicaragua (Director-Manuel Caballero) as the

accessible population. We visited each farm and made participation inquiries. After data

collection, we asked for referrals. We did this until we could find no further sesame producers in

our accessible population. We took a census of the accessible population.

Instrument, Procedure, and Analysis

Refer to Appendix A for schematic protocol of index construction and other information

Management Index

A management index (delivered during semi-structured interview) was created to measure

the management approach on a scale. Indices are useful for robustly measuring an underlying

variable not easily measured by a single indicator (Bernard 2002). Management indices have

been used effectively in translating qualitative management differences into quantitative measure

(Mas and Dietsch 2003).

We found no satisfactory indexing method in the literature. Thus, one was constructedd.

Then, we collected the responses to these questions as part of the semi-structured interview.

Finally, we analyzed the management approach of each agroecosystem by using a summative

score based on responses to indicators.

Index construction

We asked 10 experts a question by phone and email. What five indicators are most

capable of distinguishing between conventional and non-conventional management? I did not

mention, unless asked by the expert respondents, that this would be for Central American, small-

scale operations. We retained those indicators that had at least 50% consensus. There were

seven indicators mentioned by at least 5/10 respondents as capable indicators, and two indicators

with 4/10 responses. Given contextual appropriateness and personal opinion, we included the










two indicators with only 40% consensus. The original nine indicators, in question form, are

listed in Figure 3-1.

After screening with growers outside the theoretical population, consulting with Dra.

Castillo of the UNAN-Leon, and testing on our first 3 participants, questions with asterisks (*)

were later dropped. They were either contextually nonsensical (items 6 and 7) or participants

were unclear and varying in their understanding of environmental harm (item 8).

Ranking the influence of individual indicators on an overall management approach

strengthened the index. Ranking was used instead of scoring to force respondents to consider

their relative importance. We asked a set of 11 experts to rank the six final indicators from most

capable to least capable in distinguishing managements (see Appendix B). The ranking of each

indicator came by selecting the mode of the responses. Where there were two or more modes for

an indicator, they were averaged to arrive at a final mode and ranking for that indicator. This

only happened once with the Diversity indicator. When two separate indicators showed the same

ranking, the indicator with more highest- ranks was established as a more influential indicator.

The Pest Control and Diversity indicators were both initially ranked as the third most influential

indicator, but Pest Control received three number one rankings while Diversity received only two

number one rankings. The six labeled indicators are shown in order of decreasing influence in

Figure 3-2.

Indexing procedure

Each indicator was formulated as a question with five possible answers. These questions

were presented during the semi-structured interview. Indicators 2,3,and 6 were formulated as

questions of type A, as seen in the list below. These use relative measures to gauge whether a

response indicates ecological or conventional management, with higher score indicating more

ecological management. Indicators 1,4, and 5 are formulated, as questions of type B, using a









scale from least to most ecological. The numbers in parentheses indicate the weight of each

response, with responses that indicated more ecological management having higher values.

A. What is the dependence on organic (0) versus inorganic (IO) fertilizers?
(1) Only IO (2) more IO than O (3) equal (4) more IO than O (5) only O fertilizer

B. What is the level of on- farm material recycling (manures, kitchen, and crop residues)?
(1) No recycling (2) low (3) medium (4) high (5) everything possible recycled

During data collection, we noticed that for questions of type B, separating between no

recycling and low, and between high and everything possible recycled, was difficult. Their

responses tended to be arbitrary decisions between closely related answers. This presented

problems of robustness in the measure of that indicator. To combat this, we collapsed the five

possible responses to three --low, medium, and high- and adjusted points to 1-2- 3 respectively.

Index score

After indicator questions had been presented in the semi- structured interview, we

determined the management index score of each agroecosystem. Actual scores for each indicator

and tabulations can be found in Appendix B. Figure 3-3 illustrates scoring for a hypothetical

agroecosystem exhibiting the maximum level of ecological management. More influential

indicators have high indicator weights. In this example, the response points shown are always

the maximum possible score, indicating the most ecological approach. Multiplying the indicator

points by the response points arrives at each indicator score. The final index score is a sum of

the indicator scores and then divided by 6 to standardize the scores.

The smallest possible score is 3.533. This indicates a fully conventional management.

The largest possible score is 13.833. This indicates a fully ecological management. The midway

point is 8.665. Scores below 8.665 indicate ecological management. Score above 8.665 indicate

conventional management.









Semi-Structured Interview

A semi-structured interview was conducted to ascertain the management approach and

gather labor and yield data. Semi-structured interviews are useful when one would like the

discretion to follow leads, but still needs a pattern to recuperate necessary information (Bernard

2002).

Appendix C contains the interview guide. There were Hyve basic components in the semi-

structured interview: 1) eligibility establishment, 2) management indexing questions, 3) basic

crop production information, 4) management labor, and 5) yield. Interviews with agroecosystem

managers generally lasted from 20 to 25 minutes, and the maj ority of this was for measuring the

labor inputs elicited by differing managements.

Management labor was divided into four practices used for direct Hield management.

Breaking down labor into management practices allowed for precision, as well as a measure of

the overall effects of management on individual practices. The four management practices were:

fertilization, weed control, insect control, and disease control. We selected management

practices that are common components of Hield management. The practices must require labor

input that is affected by management approach. We did not include pre-plant tillage, for

example, because all growers hired tractors to prepare equally. Seeding and harvesting also were

done equally and management approach played no clear role in these practices.

After documenting eligibility and obtaining consent, a quick orientation and background

assessment quelled hesitations of the participants, elucidated doubts, and assisted us in asking

more appropriately phrased questions. Presumably, this would allow us to gather the

forthcoming labor data in a more efficient and precise manner. One day of labor was set the

length of time it takes to complete the task for the day. During most of the season, this is about 4

to 6 hours in the morning. On other days, it can be longer or shorter.









Asking about tasks within individual management practices divided the labor data

collection. Farmers, like all managers, break up their practices into daily tasks throughout the

season. We exploited this organization conveniently to procedurally ascertain labor inputs. We

would first ascertain the order, procedure, and nature of a particular management practice. After

this was clear, we could begin to gather data about labor inputs, phrasing our question

individually based upon a grower' s management style. The typical number of instances a

particular task was carried out, the number of workers required, and the number of days with

these workers was investigated on a per month basis. Inquiring on a per month basis accounted

for labor variability during the season, and thus increased accuracy in labor accounting.

Finally, in January 2007, we resumed the last section of the interview. Land under

sesame, seed used, and yields in quintales (1 Qt=46 kg) per Mz were documented. Additionally,

we asked for any related commentary.

In order to compare labor inputs for management practices, we calculated them as simple

labor amount of man-days/Mz and as a percentage of the total labor. Labor amounts include the

labor required by individual management techniques and the agroecosystem ecology it created.

Assuming that growers limited labor is distributed according to management needs, percent of

total labor might indicate differences in the nature of agroecosystems under differing

managements. This is especially true where qualitative differences of techniques within

approaches are controlled.

Soil Quality Assessment

To test the hypothesis that soil quality will be positively correlated with increasingly

ecological management, we assessed soil quality through the use of five individual indicators.

These indicators assess the capacity of these andisols to support the function of sustainable plant

production. The utility of multiple empirical indicators to assess the concept of soil quality for









sustainability has been established for some time (Bellotti 1998, Doran and Parkin 1996). The

natural resources conservation arm of the USDA (2001) is promoting soil quality assessment as a

conservation-planning tool. New Zealand's government has found soil quality to be useful as a

national planning and assessment tool. (Lilburne et al. 2004). The most current methodological

research revolves around prioritizing the utility of different indicators for combination into an

index (Shukla and Ebinger 2006, Yemefack et al. 2006, Xu et al. 2006, Erkossa et al. 2007) and

for delimitation of differentially managed fields (Monokrousos et al. 2006). There are many

different indicators. Nonetheless, there persists a lack of a tested, accepted, and recognized

index.

There are several additional reasons why we decided against using or constructing an

index. Constructing our own, or using any particular index, precludes close comparison with

other data where different indexes or uncombined indicators have been used. Furthermore,

analyzing individual indicator' s responses to management might more clearly elucidate

management- sensitive indicators for andisols.

In building our own minimum data set (MDS) of indicators, our financial and technical

capacities were a major determinant. Indicators needed to be affordable, practically collected as

soil samples, and reasonably analyzable given the limited expertise, laboratory space, and

technology available for soil analysis of the researcher and Laboratories Quimicos SA

(LAQUISA, Carreterra Leon, km 33.5). The indicators needed to be plain and common enough

to be potentially compared and understood by various grower, academic, and development

audiences. Additionally, they must be contextually appropriate (Karlen et al. 2003). Thus, we

specifically studied a review and investigation by Andrews and Carroll (2001), a comparative

management study on Nicaraguan andisols (Castillo and Joergenson, 2001), a practical manual









of the USDA (2001), and an Organization for Tropical Studies (OTS) agroecology field course

guide (Swisher 2003). These sources shared similar restrictions, goals, or audiences as this

study. Karlen et al. (2003), and Herrick (2000) were consulted for general procedures and

considerations in choosing a contextually appropriate and indicative set of biological, physical,

and chemical soil quality indicators. The indicators are percent organic matter (%OM),

phosphorus availability (PA), acidity (pH), bulk density (BD), and biotic activity (BA).

Soil Sampling

To measure the indicators, we first collected soil samples as described in the protocol in

Appendix A. The soil sampling design was a systematic Z transect, with sub sampling, across

contiguous fields meeting the operational agroecosystem requirements. We stayed 5 paces from

field borders to minimize confounding factors (i.e. tractor marks etc.) With this design, we could

move along expeditiously, cover the entire field without bias, and avoid damaging crops.

Whenever a field was not rectangular, we divided the field into approximately three equal land

areas and adjusted the lengths of the 3 diagonals (of the Z) accordingly.

For %OM, PA, and pH, we collected 7 sub samples with a manual soil auger to a depth of

30 cm across each diagonal. These 7 subsamples (about 2/3 liter each) were homogenized in a

bucket to create 1 sample per diagonal. The 3 resulting diagonal samples would serve as the 3

subsamples (about V/2 liter) for each replicate. The subsampling increased the precision of our

measurements, since there would be 1 sample value per field. Diagonal sub- samples were

delivered in sealed, marked plastic bags.

For BD and BA, we collected 7 samples across the field on the same Z transect. After

using a shovel to dig a flat-walled hole of 40 cm depth, we used a hammer-in style soil corer

(100mm3 5-cm- deep cylindrical core) to extract a sample from the sidewall. Core ends were

sharp and in good condition. BD samples were collected at a 0-15 cm and 15-30 cm horizons.









Biotic activity samples were collected at the 2.5- 7.5 cm depth from the top of the soil. The

protocol was realized with 2 subsamples on the 1st diagonal, 2 subsamples on the 2nd diagonal,

and 3 subsamples on the last. These 7 sub-samples would be averaged to arrive at one response

value for each agroecosystem.

Soil Quality Analysis

All analyses were done at Laboratorios Quimicos S.A. (LAQUISA) chemical laboratory.

It is the foremost environmental testing laboratory in Nicaragua. The six indicators follow.

Descriptions include the ecological rationale for using the indicator, the method of analysis, and

the criteria for interpretation.

Percent organic matter (%OM) measures the amount of organic matter in the soil. The

%OM will have an overriding effect on all soil functions and properties. We used the Walkley-

Black (1969) method (with no procedural deviations) to measure the % organic carbon of highly

stable humic and fulvic acids. We used a conversion factor of 1.74 to translate this into %OM of

the soils for ease of communication to a wide range of audiences. An increasing quality of soil is

indicated by an increase in the %OM.

Acidity (pH) is also an ecosystem state variable that plays a role in nutrient availability,

biological presence and control, and aluminum and iron toxicity to plants. Acidity was

determined using 2 parts deionized water solution to 1 part topsoil sample. pH was detected by

calomel electrode. Lower pH soils indicate poorer soils.

Phosphorus availability (PA) is of particular interest in allophane soils with high

phosphorus P sorption capacities. High sorption capacity is due to a very high surface area of

allophane and its affinity to fix P anions from the soil solution (Parfitt 1989). High fixing

capacities do not allow P to move freely through the soil solution and be taken up by the plant

roots (Parfitt 1989). Determining the potential availability of P is critical to the functional









capacity of soils for sustained production. To determine the potential availability of P to the

plants, a P fractionation was performed at LAQUISA using the Tiessen and Moir (1993)

modification of the Hedley et al. (1982) fractionation procedure. Lawrence and Schlesinger

(2001) have used it successfully to trace changes in soil P availability in tropical soils with high

P fixing capacities. Finally, I confirmed the appropriateness of the methods for the andisols

under study with an expert (Nicholas Comerford, personal communication, 2006).

Four main fractions are analyzed. The first 2 fractions are easily absorbable and

colloidal/solution P. These represent relatively available soil P. The last 2 fractions are

relatively occluded and fixed, and therefore unavailable. Increasing amounts of resin- P and

NaHCO-P in the first 2 fractions and increasing percentages of total P in the first 2 fractions

would primarily indicate an increasing soil quality. More P in the first 2 fractions indicates a

greater capacity to sustain strong plant growth. Using a P fractionation method to proxy plant-

available P does not take into account the symbiotic uptake pathways of P, which are known to

be important in providing plants with P.

The amount of biotic activity (BA) serves as a very important indicator of soil quality,

especially where nutrient availability is driven mostly by biotic processes (Drinkwater et al.

1995, Monokrousos et al. 2006). Biotic activity is a maj or component of a higher quality soil,

especially where this is the primary nutrient transformer and controller of rhizosphere pathogens.

Microbial activity was measured by way of basal respiration, which is the amount of carbon

dioxide (CO2) TOSpired by soil microbes. We used a soil corer in the 2.5 cm-7.5 cm area of the

topsoil to gather and transport a soil core for direct use in incubation jars. The core was placed

directly into the j ar to minimize perturbation and oxidation. Basal respiration was measured

after 24 hr incubation in clean 1-gallon glass j ars with a soil core, a 20 ml portion of water, and









10ml IM NaOH. This was done in a non-air-conditioned laboratory with natural lighting at the

UNAN-Leon, Campus Agropecuario. Samples remained in the corer for collection in order to

minimize perturbation and oxidation. CO2 captured in the NaOH solution was delivered to

LAQUISA in the Paraffin and masking- taped Gerber baby-food bottles as NaOH receptors

within the incubation jar. Samples were daily delivered to LAQUISA for titration with

concentrated HCL.

The main physical quality indicator is bulk density (BD). Good soil structure is essential

to prevent andisol erosion, puddling- facilitated disease, root stunting, and anoxia to soil

biological communities. We decided that bulk density is a good general measure of structure.

We therefore measured bulk density at the topsoil (0-15 cm) and subsoil (15-30 cm). Bulk

densities were determined by weighing after drying in an oven at 110 C for 24 hours. The soil

core that collected the sample determined the volume. The first 3 replicates accumulated 24 hrs

of drying over two weeks (as opposed to one 24 hr period), since we were not sending these to

LAQUISA until regular electricity for ovens failed at the UNAN-Leon. Since compaction is a

concern, improving soil quality will be evidenced by decreases in bulk density. Bulk density

cores were emptied into brown paper bags. These were delivered to LAQUISA and transferred

directly into an oven.

Statistical Analysis

Each agroecosystem was placed in the conventional (n=10) or ecological (n=8) treatment.

To compare the means of independent variables, t-tests were performed when the variables were

normally distributed. T-test variables were tested for homogeneity of variance using a Levene

test. Independent variables that did not initially meet assumptions of normality were log

transformed. A Shapiro-Wilke test (p<.05) was used to test for non- normality. If independent

variables still did not meet assumptions of normality, or sample sizes were too small, a Mann-










Whitney test was used to test for differences in the medians of the samples. Considering the

normal amount of variability in an observational study and the small-sample size, statistical

significance is set at p < .10. All statistical analyses were done using SPSS (Chicago, Illinois).


1. Dependence on synthetic, chemical vs. any alternative pest control (8)
2. Dependence on inorganic vs. Organic fertilizer (6)
3. Level of on farm recycling (5)
4. Level of conservation of soil and its' properties (6)
5. Level of crop diversity in time and space (5)
*6. Level of water conservation (5)
*7. Level of fossil fuel usage (5)
*8. Level of environmental protection (4)
9. Dependence on commercial, modified vs. local, traditional seed (4)

Figure 3-1. Original management indicators. Number of responses out of 10 is in parentheses.



1. Soil Conservation (Level of conservation of soil and its' properties) (6)
2. Fertilization (Dependence on inorganic vs. Organic fertilizer) (5)
3. Pest Control (Dependence on synthetic, chemical vs. any alternative pest control)(4)
4. Diversity (Level of crop diversity in time and space) (3)
5. Recycling (Level of on farm recycling) (2)
6. Seed (Dependence on commercial, modified vs. local, traditional seed) (1)

Figure 3-2. Final management indicators. The number in parentheses indicates the point value.
Higher values indicate more influential indicators.



Indicator points Response points = Indicator Score

Soil Conserv. 6 3 = 18+
Fertilization 5 5 = 25+
Pest Control 4 5 = 20+
Diversity 3 3 = 9+
Recycling 2 3 = 6+
Seed 1 5 = 5+

Sum Indicator Score = 82.99 == Standardized Index Score=13.833
6 indicators 6

Figure 3-3. Index scoring example. A hypothetical response with the highest ecological score is
shown.









CHAPTER 4
RESULTS

Census Population

The census population consists of 18 total replicate Hields in a binomial distribution. There

is a notable absence of management scores between eight and ten (Figure 4-1). The lowest index

score was 4.333, and the highest was 13.833.

Energy Inputs and Productivity

Table 4-1 presents medians and p- values for labor (both as absolute inputs and as a

percentage of total) and labor productivity using the Mann-Whitney-U test. The sample sizes of

the productivity variables (Table 4-2) differed from those of labor inputs (n=10 for conventional

and n=8 for ecological). This is because only seven of 18 interviewed growers actually planted

late-season sesame. Additionally, within those seven, some did not manage for insect pests or

disease. We could not calculate labor productivity for these growers.

Labor inputs for overall management were not significantly affected by management

regime. Of the four practices, only for disease and fertilization did management approach

significantly affect the amount of labor required. In both cases, ecological management required

more labor. Though not significantly different for disease control and fertilization, the

proportion of total labor allocated to insect pest management significantly differed by

management type. Conventional producers expended a greater proportion of their time

managing pests than ecological producers.

There were no significant differences in labor productivity between conventional and

ecological management.










Ecological Indicators and Efficiency

Table 4-3 presents means and p-values of soil quality indicators and their ecological

efficiencies. For all independent variables, the means of ten conventional replicates and eight

ecological replicates were tested for differences using a t-test for independent samples. Soil

quality indicators and their efficiencies did not significantly differ in any case.

Output

The median yield for Hyve conventional agroecosystems was 10.125. The median yield for

the ecological agroecosystems was 12.000. These did not significantly differ (p=. 195).


4.5
F 4-
r 3.5-
e 3
4 2.5-
u 2-
e 1.5-
n 1-
c 0.5-
y` 0 I I


Miana gement Score


Figure 4-1. Histogram of replicate management index scores. Scores below and above 8.665
indicate conventional (n=10) and ecological (n=8) agroecosystems, respectively.










Table 4-1. Results of Mann-Whitney U test for labor amounts (man-days/Mz), percent of total
labor (%), and labor productivity (Qt/(man-day)) between conventional and
ecological growers. P-values calculated for overall and per-practice management.

Variable Median P-value


(@) and (*) indicate significance at p=. 100 and p=.050, respectively.





Table 4-2. Sample sizes for labor productivities per practice.
Variable Treatment
Conventional Ecological


Fertilization 5 2
Weeds 5 2
Insect Pests 5 1
Disease 4 1


Conventional


Ecological


Overall
Labor
Productivity

Fertilization
Labor
% of total
Productivity

Weeds
Labor
% of total
Productivity

Insect Pest
Labor
% of total
Productivity

Disease
Labor
% of total
Productivity


19.500
0.530



3.250
13.940
4.091



15.083
69.620
0.764



2.476
17.690
6.863



0.375
0.810
11.750


27.700
0.444



5.750
25.690
16.091



15.600
64.540
0.437



1.440
6.360
5.333



1.798
4.580
48.000


0.230
0.439


0.050*
0.155
0.699



0.859
0.374
0.439



0.195
0.090@
0.380



0.067@
0.143
0.157









Table 4-3. Calculated p-values of soil quality indicator and efficiency means between
conventional (n=10) and ecological (n=8) farms using t-test for independent samples.

Variable Mean P-value
Conventional Ecological
% OM 2.301 2.231 0.802
Efficiency 0.115 0.071 0.161

Acidity (pH) 6.460 6.566 0.271
Efficiency 0.331 0.217 0.196

Basal respiration (mg/cm3) 11.031 11.081 0.985
Efficiency 0.474 0.342 0.498

P 1st fraction (ug/g soil) 9.941 12.396 0.599
Efficiency 0.494 0.410 0.742
% of total P 1.268 1.920 0.320
Efficiency 0.001 0.001 0.990

P 2nd fraction (ug/g soil) 94.128 76.668 0.362
Efficiency 4.270 2.396 0.195
% of total P 1 1.456 1 1.217 0.904
Efficiency 0.601 0.605 0.266

P 3rd fraction (ug/g soil) 342.081 298.425 0.323
Efficiency 16.820 9.501 0.121
% of total P 45.128 44.547 0.922
Efficiency 2.345 1.472 0.187

P 4th fraction (ug/g soil) 248.879 229.283 0.537
Efficiency 12.323 7.212 0.144
% of total P 32.991 33.797 0.741
Efficiency 1.689 1.117 0.203

P total (ug/g soil) 729.440 645.520 0.305
Efficiency 37.351 21.340 0.112

Bulk density (0-15) cm (g/cm3) 1.175 1.210 0.393
Efficiency 0.764 0.040 0.109

Bulk density (15-30) cm (g/cm3) 1.166 1.990 0.516
Efficiency 0.059 0.040 0.217


(@) and (*) indicate significance at p=. 100 and p=.050, respectively.









CHAPTER 5
DISCUSSION

Census Population

Several unpredicted reasons accounted for a smaller than preferred sample size. Low

prices and broken contracts in 2005 kept many farmers from sowing sesame in 2006. During our

sampling period, some growers were in Costa Rica as hired labor instead of cultivating their own

Shields; therefore, we could not interview them. The paradox of smallholders neglecting their

Shields in favor of casual labor has previously been tied to Einancing and labor constraints

(Alwang 1999). Renting of small parcels is common, so that Einding farms managed by the same

person, in the same manner, for three years became increasingly difficult. Finally, increased

peanut prices had caused land prices to increase, so that some farmers were either renting their

lands to large- scale peanut growers or land renting was now prohibitively expensive.

Agroecosystems around Leon meeting our operational needs and logistical possibilities

consequently became difficult to aind. The sustainability of small-scale sesame in Leon is

seemingly negatively affected by economic and agricultural trends in the area.

The distribution of the census into two groups, separated by an absence of scores between

eight and ten, indicates that small-scale growers here do not often mix approaches equally. They

tend to follow a more singular management approach. This may be a result of growers'

connections to cooperatives. Ecological growers connected to Asociacion de Productores

Ecologico de Nicaragua, and conventional growers connected to Cooperativa La Esperanza,

may have been absorbing similar knowledge through their cooperative. Growers outside these

cooperatives may be receiving information from diffuse or different sources with a less unified

message, increasing the likelihood of more mid-range management scores if a population of

these independent growers is examined.









Labor Inputs and Productivity


All Management

Our stated hypothesis was that total labor inputs would be higher, and labor productivity

lower, in ecological management. This hypothesis was not supported by the data of total labor

inputs and productivity. Only seven total values were used to compare overall labor

productivity, and this weakens the validity of these results. Sample size for labor inputs was

adequate, and non-signifieance can be partially attributed to sizeable variability in labor within

treatments. Two conventional growers, for example, used no labor for pest control, while an

equal amount used nine man-days. This variability suggests that total labor was driven primarily

by individual decisions in pursuing practices. When summed, this variability confounds a

possible effect of management. Individually perceived benefits and costs of labor-intensive

practices may drive that variability. Individuality is more likely when standardized

recommendations for management are unavailable or growers are relatively new to the crop.

Both conditions are common with sesame in Leon. Additionally, individual economic ability

may affect the labor dedicated to practices. Even though we assumed economic ability to be

generally similar among farmers, even a small difference can have a disproportionately large

impact when economic capital is small. For example, buying synthetic insecticides this year, and

using labor to apply it, can vary depending on the previous year' s profits or unforeseen expenses

during season. We did not control for these confounding factors.

Measuring no significant difference in total labor is rare. Studies, such as Pimentel et al.

(2005) and Karlen et al. (1995), more commonly find overall labor to increase with more

ecological management. Those results confirm common perceptions of ecological management

in temperate areas (Lotter 2003). For the fewer studies examining manual labor as the main

energetic input, at least one study found lower labor requirements with ecological management










(Mendoza 2005). Others have found ecological management practices to be more labor intensive

(Kaltsas et al. 2007). Even though data is reported less clearly than Mendoza (2005), Rasul and

Thapa (2003) do mirror our finding of no significant differences in labor inputs. However, their

study subj ect was small-scale rice agriculture.

Whether the actual management techniques, or an agroecosystem's ecology (weeds,

insects, etc.), determined total labor inputs was not investigated. This is because total labor

includes various practices with potentially different techniques, making it particularly difficult to

separate the effect of ecology from technique. Because both managements include the same

practices, we can safely say that agroecosystem ecology was not different enough to precipitate

changes in total labor. When technique differences are eliminated, and the proportional

importance of labor per practices is measured, assessing if agroecosystem ecology is different

between managements is more feasible. A different proportion of total labor for a practice when

techniques are similar, and total labor is not significantly different as it is here, indicates that

management is responding to different agroecosystem ecology. Here we examine practices

individually to assess whether technique differences or ecological differences affected labor

requirements.

Fertilization

Fertilization was significantly different between management. Ecological management

required more labor because the technique was more labor intensive. Collecting and spreading

manure, composts, fertilizer teas, or other organic fertilizers is often documented as requiring

more labor as tractor time (Karlen et al. 1995) or manual input (Mendoza 2005). Two growers

were actively and consistently pursuing manure fertilization. These growers registered the

highest labor values, and had a strong influence on our measurement of labor in ecological










agroecosystems. The results indicate that ecological fertilization techniques- especially where

manure is involved- are more labor intensive than those of conventional management.

While cover cropping can reduce labor compared to other organic fertilization techniques

(Drinkwater et al. 1998), managing cover crops still requires more labor than inorganic

fertilization (Pimentel et al. 2005). Our results do not address this issue because cover crop use

was completely lacking. During the rainy season, no participant was willing to cover crop any

available land if it could be cash cropped. Additionally cover cropping is most feasible when

seed and information are available, neither of which did we observe or seek. This highlights the

fact that laborsaving organic fertilization methods are not always applicable to the small-scale,

tropical context, for the reasons mentioned.

Most growers seemingly relied on incorporated residues and natural andisol fertility to an

extent. It is true that many conventional growers were fertilizing inorganically, and many

ecological growers were applying organic fertilizers. Yet given the observed amounts,

fertilization seemed mostly supplementary (unconfirmed). Relying on incorporation and soil

fertility may be an appropriate strategy for all growers. Fertilizing organically requires higher

labor inputs, inorganic fertilizers can be relatively expensive, and there was no advantage of in

terms of labor productivity of pursuing one fertilizer management strategy over another.

Disease

Labor for disease management practices differed significantly between managements, with

ecological management requiring more labor. We attribute this to technique differences in

controlling the primary sesame pathogen- a Phytopthera fungus. Conventional management

used industrially- synthesized fungicides, since it was relatively accessible and needed only in

limited quantities if properly applied. Ecological growers, on the other hand, were either liming

the soil around the plant base or removing whole plants to prevent transmission. Liming










presumably raised pH enough to kill off the soil borne fungus. Diluting concentrated fungicides

in water and applying with a manual sprayer was apparently more labor efficient than hauling

bags of lime or pulling plants out by hand. The higher labor requirements of ecological disease

control and fertilization techniques could be due to concentration. Inorganic nutrients are more

concentrated than organic ones. Similarly, synthetic substances are more concentrated

fungicides than lime. In both cases, the more concentrated substance required less labor.

Weeds

Finding no significant difference of weed management labor between managements can be

explained by the similarity in practices. All growers used animal-drawn cultivation followed by

manual weeding, except for one ecological grower who used goat herbivory and one

conventional grower who applied herbicides. Hence, 88% of farmers were managing weeds

ecologically by defacto. Understandably, labor inputs were not affected by management specific

technique. Most studies, Clements et al. (1995) and Loake (2001) for example, have found

weeding labor to be higher with ecological management. In those studies, however, cultivation

substitutes for herbicides. In our study context, strategies were similar and did not substitute for

herbicides. Differences in labor requirements were consequently not seen.

This exposes a weakness in our management index. Grouping all pest management under

the same indicator question resulted in a few erroneous readings of fully conventional pest

control, when weed control was not conventional. Our management definitions- based on

internal versus external perspectives- do not clearly account for tillage as either ecological or

conventional. It raises the question whether not using herbicides, without any other deliberate

intervention, should be equated with ecological management. We contend that it should not, and

further agroecosystem study should more fully consider the degree of purposeful ecological

manipulation of weed populations in characterizing management.










Percentage of total labor used for weed control was not significantly different between

treatments, despite similar techniques. This suggests that weeds were not more prominent in

either system. Organically managed tomato fields have shown more weeds than conventional

fields as a result of differing agroecosystem ecology (Clark et al. 1998). These authors suggest

increased nutrient cycling to all plants, from greater microbial activity and organic matter,

promoted weeds under organic management. Neither of those ecological aspects differed by

treatment in our study. The agroecosystem ecology in respect to weeds was, hence, not very

different between managements. Weed control labor as a percentage of total was consequently

not affected.

Insect Pests

Results for this practice were interesting: labor as man-days/Mz was not significantly

affected by management but percentage of total labor was. Both managements apply liquids

using a backpack sprayer and removing insects manually from plants. A case for similarity of

technique could be made based on this. What they were applying was different, however.

Ecological growers applied Neem/ Capsicum/Allium teas to repel pests, while conventional

growers applied industrially synthesized insecticides. Because of the very different ecological

consequences of insect repellants versus insecticides, our opinion is of differing techniques for

combating insect pests. Additionally, diverse cropping and trap crops are strategies for insect

pest management in ecological management not pursued in conventional management.

From this point of view, a lower percentage of labor for insect pest management suggests

one of two things. Firstly, there could be fewer pests in ecological management. Theory would

predict this, since ecological management can lower pest populations by increasing beneficial

populations (Mader et al. 2002). Ecological farmers often report fewer pest problems- and

consequently less labor for insect pest management- than their conventional counterparts, despite









not using synthetic insecticides (Lotter 2003). Our results, because techniques are distinct

enough, may alternately be explained by higher labor efficiency of repellants. Practical

experience shows that repellants and other non-toxic approaches are less effective and may

require more labor for the same effect (Buss and Park-Brown 2006). One might assume

botanical repellants to be more labor intensive because they breakdown faster, do not kill, and

may require more applications than synthetic insecticides. Based on this assumption, less labor

proportionally with repellents would be explained by smaller pest populations in ecological

agroecosystems. This indicates different ecology of ecological and conventional

agroecosystems. Kaltsas et al. (2007), however, find technique difference to induce higher labor

needs in organic olive groves.

The fact that labor as man-days/Mz did not differ significantly between management

conflicts the proportional labor findings. Normalizing on a percentage scale may have made the

data more amenable to statistical analysis than when presented as man-days. Moreover, the

effect of outliers would be diminished when labor is presented as a percentage.

Soil Quality and Ecological Efficiency

Management did not affect soil quality indicators and their efficiencies. This contradicts

our hypothesis and most literature predicting ecological management to result in greater soil

quality. Three reasons may explain this discrepancy.

A fundamental premise of soil quality studies is that soil- affecting inputs will be distinct

as a result of discrete management. Moreover, the magnitude of soil quality change depends on

the degree of input dissimilarity (quantitative or qualitative) between managements. This premise

is not fully met in the study context, since all management is low-input and systems are rather

similar. For example, though fertilizer materials and labor were different between management,

most agroecosystems seemingly relied to a large or complete extent on natural soil fertility and









incorporated residues. Both managements may have had, for all ecological purposes, a common

fertilizer- the soil itself. Failing to measure lower pH in conventional agroecosystems suggest

that ecologically significant rate of inorganic fertilizers were not applied. Moreover, percent

organic matter itself was unaffected. This is the indicator most consistently associated with

distinction in inputs. Other evidence for similarity was in biotic activity. Fewer pesticides in

ecological agroecosystems can result in higher soil biotic activity (Plenchette et al. 2005). Since

percent organic matter was not different, any difference in soil biotic activity would have been

more directly tied to differences in pesticide inputs. We measured no difference in biotic

activity, indicating similar pesticide inputs between management.

The ecological context of this study provides a second possible explanation for a lack of an

affect. The ecological metabolism in tropical soils is rapid, especially in the wet-season when

most organic additions were made. This makes increasing soil organic matter difficult.

Measurable increases in organic matter may accrue only after an extended period of

accumulation in many soils (Fleissbach et al. 2006, Monokrousos et al. 2006). This period of

accumulation may be longer in the tropic because organic matter is decomposed rapidly.

Without increased organic matter in ecological agroecosystems, correlated increases in biotic

activity, P availability, pH, and bulk density may be too slight to detect. This tropical effect

must be tempered by known organic matter occlusion by andisols that allows for accumulation.

Intense sunlight during the soil-sampling period may sterilize topsoil and cause biotic

activity to measure equally between managements. We attempted to minimize sterilization by

extracting samples 2.5- 7.5 cm below the soil surface and incubating samples. This may have

had little effect. No difference in biotic activity does not, however, mean that biotic composition

is also unchanged. Widmer et al. (2006) and Marinari et al. (2006) found changes in biotic










composition with management. Also, soil quality measurements were taken one to two months

prior during a dry period. Biotic activity could very feasibly be altogether distinct during rains.

Andisols soils provide a unique ecological context even within the tropics. The P

fractionation shows that management does not induce functionally salient changes in P

availability of andisols. Other studies have found management, by way of organic matter, to

affect P fractions (Salaque et al. 2004, Reddy et al. 2005). Our results differ from Castillo and

Joergenson (2001) who found less total P with ecological management in andisols around Leon.

Their sample size was larger than ours, they used a different P extraction method, the soil

textures were somewhat distinct, and the effect they found was not terribly immense. This may

explain the discrepancies between our results and theirs. Finding no difference in P fractions

based on treatment supports He et al. (2006) and Reddy et al. (2001). They argue that as P Eixing

capacities become greater, P dynamics are more influenced by inherent soil properties than by

management. Our results cannot directly support these studies because they experimentally

altered percent organic matter to proxy ecological management. We did not measure such a

change necessary to validly support their conclusions.

Finally, confounding factors may have played a role. Deep tillage from the cotton years

left soils with sizeable differences in organic matter. Given primitive mechanization, already

high amounts, and a tropical ecology, three years may be insufficient for ecological management

to increase organic matter. Additionally, high pesticide applications floating in from adjacent

peanut Hields may have affected biotic activity. Finally, we did not sample Hields at the same

point in their tillage schedule. Some had been disked once, others twice, and some none. In

combination with random cattle and human trampling, this likely confounded the effect of










management on bulk density. Since organic matter did not differ between treatments, it is

unlikely we would have measured a significant difference in bulk density anyhow.

Yield

Sesame yield was not affected by management regime. The sample sizes for each

treatment were extremely small, so this finding should be taken with some caution. Having said

that, the salient point here is that ecological yields were not reduced as compared to conventional

yields. This contradicts extensive reviews by Stanhill (1990) and Lotter (2003) predicting slight

yield losses with ecological management, as well as what seems to be a commonly held belief

among agricultural scientists. At the same time, it lends some support to Rasul and Thapa (2003)

and Mendoza (2004) that ecological management does not necessarily lead to yield reductions in

the developing context.

Many determinants of yield did not seem to differ in an ecologically significant manner

between management. There was no difference in soil quality indicators between managements.

Although there is some evidence for greater insect pest populations in conventional

agroecosystems, no growers reported them to be uncontrollable or economically damaging.

Labor used to manage weeds- which can depress yields when herbicides are not used (Clark et

al. 1999, Lotter 2003)- was not more prevalent in either management. Both agroecosystems

were likely limited by P and seemingly used soil reserves as their main nutrient source, though

this is unconfirmed. Finally, both agroecosystems used the ICTA-R and Linea 2000 sesame

cultivar. The Drinkwater et al. (1995) hypothesis that different managements may ultimately

lead to similar agronomic response was not testable in our study because managements were too

similar. Finding no significant difference in yield was not, therefore, entirely surprising.









Conclusions

The obj ective of this study was to ascertain which type of management is likely to produce

a more sustainable agroecosystem. Our results indicate that sustainability of sesame

agroecosystems in Leon did not differ between conventional and ecological management. The

maj or sustainability parameters- overall labor inputs, soil quality, and yield- were mostly

unaffected by management. Neither management is more likely to augment labor productivity of

small-scale farming through intensification or extensifieation. Similarly, soil quality for long-

term productive capacity did not differ by management regime. The economic and ecological

sustainability consequently did not differ in any ecologically significant manner, nor were their

maj or labor reductions to improve quality of life.

Sustainability was likely similar because in-common restraints of small-scale sesame

production on tropical andisols were more determinant of sustainability than management

regime. For example, because neither management adequately addressed energy limitation of

weed control in small-scale systems, high labor requirements were not lessened by either

management. P availability, in another example, was also not improved by a particular

management. Beyond strategies of each management, it is unclear whether any extension

service had informed farmers of P Eixation of andisol or of saturation techniques to overcome

such Eixation. In the end, all agroecosystems were of relatively low energy and information

input. From experience we know one of these should increase to promote sustainability.

Our conclusions do not support the hypothesis of Altieri (2002) and others that ecological

management will increase small-scale, tropical sustainability over conventional management.

We note that ecological management research has not been as institutionally supported as

conventional management; comparing the sustainability may be of limited utility until ecological

strategies are improved (Lotter 2003). Still, results suggest that development organizations










should not fully veer from traditional efforts to improve access to energy, land, and financing in

favor of implementing ecological management. Ecological management, at least in Nicaraguan

sesame, does not seem to be a panacea for the low sustainability of small-scale, tropical

agriculture. Additionally, from the comments of growers, it seems that market access and

negotiating power may be a more powerful determinant of sesame sustainability in Nicaragua

than management regime.













Assemble List of Indicators
I. Ask 7 UF and 4 Nicaraguan agriculture experts to freelist the 6 criteria
most useful in discerning between managements
II. Keep those mentioned by 50% and nearly 50% but with self-judjed potential



Finalize List of Useful Indicators
I. Compose indicators as 8 directed questions with response range
II. Pre-test on similar farmers and first 3 of study
III. Discard contextually invalid or agronimaclly nonsensical indicators



Determine Relative Importance of Indicators
I. Ask 9 original and 2 new experts to rank indicators from 1 to 6
in oder of increasing discernment capability
II. Determine mode



A. If 2 simultaneous modes for ranking responses of 1 indicator
average values and use quotient as mode
B. If 2 indicators with same rank(as established by mode)
choose indicator with more top-rankings as higher rank



Determine Management Score for Replicate
I. Assign point value(1-6) to indicators based on rank(highest rank-highest value)
and to indicator question responses by farmers(most ecological-highest value)
II. Determine management score for each replicate


I. Score each indicator- (indicator value X response value)
II. Sum scores of indicators fro overall management score
III. Divide by number of indicaors(6) to standardize final score
IV. Determine range of possible values


APPENDIX A
PROTOCOLS


Figure A-1. Protocol for management index construction.










Participant Consent
I. Deliver IRB consent form, read aloud if necessary
II. Obtain written consent



Eligibility Establishment
I. Ask requierimientos generals to document fulfillment of
operationalized agroecosystem concept


Formal Participant Orientation
I. Explain objectives and significance of study
II. Emphasize private nature of this study without prejudg. of "better" mgmt..
III. Clarify that index covers all crops and labor, yield specific to sesame



Background Information
I. Ask question in information general de cultivos
II. Ask questions in manor de obra
III. Clarify 3 technical points before labor data collection



A. 1 "day" of work is not a set # of hrs but a relative measure to each tarea
B. Labor inputs should be for plot size of sesame this year
C. Responses should be for a "typical" year with ackowledgement of variability



Labor Inputs Documentation
I. Ask farmer about the progression of tasks within each practice
II. Use this and background information to formulate labor questions individually
III. Collelet labor data about each task within a particular practice



A. Inquire on how many distinct occasions within the season a task is performed
B. if more than once, establish wherein the season each occasion occurs
C. For each task occasion, askhow many days,with how many men does the task last



Interview Closing and Yield
A. Close with asking participants have any further questions
B. Restate commitment to bring back soil analysis results and gather yield data later
C. Gather sesame plot size, seed type, yield, and commentary on next visit


Figure A-2. Interview protocol








Characterization of Field
I. Affirm texture with farmers and use texture by feel method
II. Nofe salient field characteristics
III. Enlist farmer in dematcation of study fields


Taking Samples
I. For bulk densities(BD) and basal respiration, take individual samples every third point
II. For %0oM,Pfrac, pH take 1 collective soil sample at every point


IA. Use hammer corer to extract (0-15,15-30)cm BD cores from sidewall in 50cm hole
IB. Use same instrument to extract basal respiration core from 2.5-7.5cm in soil
IC. Imnmediately place BD samples into labeled brown paper bags
and cap the basal respiration cores to transport in core sleeve



IIA. Use soil auger to gather soil sample to 30cm, do not clear off top.
IIB. Place each sample into a colelctive bucket
IIC. Homogenize 7 sub-samples to extract I sample for each diagonal
IID. Place and mark approx. I liter of soil samples per diagonal


Locating Sampling Points
I. Visuallyi divide field into three equal area, accomadate incongruities
II. Pace each of the 1/3 section diagonals(making a Z across field) individually
III. Divide # of paces byi 7 to get number of paces b/w sampling pointson each diagonal


Figure A-3. Soil sampling protocol.









APPENDIX B
INDEX





Rank 2 5 3 1 4 6
Points 5 2 4 6 3 1


Table B-1. Indicator rankings by experts.


Expert
Jimmy Jones
Peter Hildebrand
Hugh Popenoe
Danielle Treadwell
Robert McSorley
Mickie Swisher
Lori Unruh Snyder
Raymand Gallagher
Freddy Aleman
Alvaro Valle
Roberto Swisher


A (fertilizer source)
2
3


B(recycling)
4
4


C (pest control)
1
5


D (soil consery.)
3
2


E (crop diversity)
6


F(seeds)
5
6
6
6
6
4
3
5
6
6
3


Mode
2


Mode
4


Mode
3


Mode
1


Mode
3
Adj. Mode


Mode
6













F(seeds)
3~ed
3
1
3
4
5
5
1
5
4
5
3
4
4
2
1
5
3


II
III
Il'

VIII
IX
X
XI
XII
XIII
XIV
XV
~nXVI
XVII
XVIII
XIX
XX


Table B-2. Individual indicator scores by replicate.

Replicate A(fertilizer source) B(recycling) C(pest control) D(soil conservation)


E(crop diversity)
2
1
1
2
2
2
2
2
2
3
3
1
3
2
2
2
2
2









APPENDIX C
SEMI-STRUCTURED INTERVIEW

REQUIERIMIENTOS GENERALS
1. Cuantas Mz siembra usted en total?
2. Usa riego en estos cultivos
3. Has sembrado aj onj oli/ptros cultivos en los ultimos tres anos en ese campo.
4. Has usado manej o bien distinto en los ultimos tres anos en estos cultivos.
5. Si si cuales practices han sido bien distintos.

INFORMATION GENERAL DE LOS CULTIVOS
1. Cuantas Mz de ajonjoli sembrado este ano y el pasado
2. Que tipo de semilla usan usted?
3. Que cultivos de la primera estan sembrado en el mismo campo del ajonj oli.
4. Como estan arreglado en el campo y como esten sembrado en relacion de uno al otro.
5. Cuanto toma desde que se siembra estos cultivos hast que se cosechan.
6. Hay un rubro entire la primera y la postrera?
7. Cuanto producio usted el ano pasado por Mz.

ENTREVISTA
ORAL INTERVIEW- Indexing questions
1. A que nivel depiende usted en los abonos organicos vs. quimicos (urea, compeleto) para
fertilizacion? a. solo organic b. mas organic que quimico c. igual d. mas quimico que organic
e. solo quimico, sintetico

2. Cual es su nivel de reciclaje de materials de la finca (excrementos animates, residues,
vegetacion de la finca, residues de las casa)?
a) ningun reciclaje b) niveles bajos c) niveles medianos d) niveles altos e) todos possible reciclado

3. En el control de plagas y maelezas, cuanto depiende usted en el control quimico vs. control
cultural, natural (manipulacion de interaccion y ciclos), o alternative?
a) solo quimico b) mas quimico que natural c) igual d) mas natural que quimico e) todo natural
sin quimico

4. Cual es su nivel de actividad en la conservation de suelos y sus propiedades, sea en el tipo de
labranza, agregacion de material organic, plants de cobertura, barreras de erosion, o otros?
a) ningunas actividades activas b) niveles bajos c) nivels medianos d) nivels altos e) en todo
practice de suelo se consider la conservation de suelo, y practices solo para conservation de
suelo

5. Cual es su nivel de diversidad in tipos de cultivos y combinaciones entire una parcela y ano a
ano? a) ningun(monocultivo mismo cada ano) b) niveles baj os(1-2 cultivos cada ano-no cambian
por ano o reverse) c) niveles medianos(varios cultivos en el ano y cambian regularmente) d)
niveles altos(varios cultivos en el ano y cambian cada ano) e) niveles altisimo (maximo variacion
en el ano, entire anos, y en el espacio(varias alturas, relay, etc.)










6. Cual es su nivel de dependencia en semillas modificada, mejorado, commercials vs. semillas
tradacionales, tipicas, y de variedad local?
a). solo tradicionels,t, y local b) mas t, t, vl que modificade, mej orada commercials c) Igual d)
mas semillas modificada commercialmentte y mej orada que traditional, tipicas, e) todas son
comerciales, modificadas, y mejoradas.

A=1st mes antes del siembro
B=1st mes, C= 2nd meS D=3rd meS despues de sembrar

MANO DE OBRA
Cuantos trabaj adores de aqui de la casa y empleados son..



Tipo:l # todo el tiempo # parte del ia o por # de ninos trabaj ando
dia

Mess A B C D A B C D A B C D


Para las preguntas siguintes, cuenta una person como .5 persona si solo trabajo medio dia, como
los ninos,

FERTILIZACION
Fertiliza o agrega abonos parafertilizar usted?
Por favor cuenatame de sus practices de fertilzacion?
Si usa abonos organicos, por favor describe sus collection y transformation de al materials
orgamicos.
De sus practices describido, cuales son.

Tipo:l(see key # de veces la # de dias la # de personas Se hace al
below) tareas se hace tareas se hace requirida para mismo
como describido como describido hacer la tarea tiempo
que otra
cosa
Months A B C D A B C D A B C D


C=de la casa, E=empleado











O=solo abono organic, I-solo quimico fetilizantes, OI=organic y quimicos juntos, CRi =
comprar o recibir quimicos, CRo= comprar o recibir abonos organicos, R=recoger material
organic para abono, T= transformar material organic= quimicos(((Fertilizante, urea,
complete)) == abono organo, compost, bocashi(compost especial)

Usa maquinaria para cualquier de estas practices o transport?
Si si, mire la tabla

Tipo:l Descripcion # de set # de animals # de personas
de maqunaria completes. por equipo necesario para
modelo ano operar
maqinaria


M=manual, C=caballo, B=buey, CO=Maquinaria combustible, T=transporte, P=practicas del
campo
rotoveter- monocultivador, arado discos o grades

OTROS ADITIVOS(no para fertilizacion)
Usa usted cualquier otros aditivos al suelo que no sean fertilizantes?
Si si por favor describelos


Tipo:l # de veces la # de dias la # de personas Mismo tiempo
tareas se hace tareas se hace requirida para de fertilizacion o
como como hacer la tarea otro aditivos
describido describido
Mess A B C D AIB C D A B C ID


C=obertura de cualquier tipo, CA=cal, MO-material organic N=Micronutrients
AC=acondicianador de suelo, CRq= compra o recibe aditivos, R=recoger material organic,
T=transformar material organic

Espicificar. Cobertura- cascaria de arroz, sacate seco, cobertura, tapa con secate,
Material organic= compost, excremento animals; Abono foliares,

Usa maquinaria para cualquier de estas practices o transport?
Si si, mire la tabla












Tipo:l Descripcion de # de set # de animals por # de personas
maqunaria completes. equipo necesario para
modelo ano operar
maqumanari


M=manual, C=caballo, B=buey, CO=Maquinaria combustible, T=transporte, P=practicas del
campo rotoveter- monocultivador, arado, discos o grades

MANTENIMIENTO
Maniteine usted estos aparatos usados para practices de manej o.
Si si, describe el mantenimiento y mire la tabla.


Tipo~l # de veces la # de dias la # de personas Otras notas
tareas se hace tareas se hace requirida para
como como hacer la tarea
describido describido
Mess A B CD AB CD ABC D


Tipo:l # de veces la # de dias la tareas # de personas
tareas se hace se hace como requirida para hacer
como describido describido la tarea
Mess A IB C D A B C ID A B C ID


R=reparara aparatos o maqunaria, M=manual, C=caballo, B=buey, CO=Maquinaria combustible,
rotoveter- monocultivador, arado dsicos o grades


PREPARATION de SUELOS
Prepara su suelos, labranza.
Si si, por favor cuentame como hace esas cosas.


M=1abranza manual, MC=1abranza de maquina

Usa maquinaria para cualquier de estas practices o transport?
Si si, mire la tabla












Tipo:l Descripcion # de set # de animals # de personas
de maqunaria completes. por equipo necesario para
modelo ano operar
maquinania


M=manual, C=caballo, B=buey, CO=Maquinaria combustible, T=transporte, P=practicas del
camporotoveter- monocultivador, arado discos o grades

MALEZAS
Control las malas hierbas o malezas usted?
Si si describe por favor sus practices de manej o de las malezas
De las practices desecribidas cuales son


Tipo:l # de veces la # de dias la # de personas Mismo tiempo o uso
tareas se hace tareas se hace requirida para de fertilizacion,
como como hacer la tarea preparation, o
describido describido cultivacion, o
sembrada
Mess ABCD ABCD ABC D




CRhs=comprar o recibir herbicidas sinteticos, industriales, CRHN =Compra o recibir herbicidas
naturales, R=recoger material para control natural, T=transformar material organic para control
natural, S=sintetico, industrial herbicidas aplicado solo, Nc=herbicidos naturales, commercial
aplicado natural, Nf-herbidos naturales de la finca aplicado solas SN= sintetico y natural juntos,
C=Compost de cobertura., CR=cobertura de otra, CU=cultivacion


Usa maquinaria para cualquier de estas practices o transport?
Si si, mire la tabla

Tipo:l Descripcion de # de set # de animals por # de personas
maqunaria completes. equipo necesario para
modelo ano operar
maquinaria



M=manual, C=caballo, B=buey, CO=Maquinaria combustible, T=transporte, P=practicas del
camporotoveter- monocultivador, arado discos o grades
















Type:l # de veces la # de dias la # de personas Mismo tiempo o uso
tarea se hace tareas se hace requirida para de fert., prep, insect,
como como hacer la tarea maleza, o otros
describido describido control de insects
Months A B CD AB CDAB C D


CRhs=comprar o recibir venenos sinteticos, industriales, CRHN =Compra o recibir venenos
naturales, R=recoger material para control natural, T=transformar material organic para control
natural, S=sintetico, industrial venenos aplicado solo, Nc=venenos naturales, commercial
aplicado natural, Nf=venenos naturales de la finca aplicado solas SN= sintetico y natural juntos,
CT=cultivo trampa., BV=barrera viva, F=remover fisicamente

Usa maquinaria para cualquier de estas practices o transport?
Si si, mire la tabla

Tipo:l Descripcion de # de set # de animals por # de personas
maqunaria completes. equipo necesario para
modelo ano operar
maqunaria


INSECTOS
Control los insects( o las plagas) o no?
Si si, digame como control insects usted en el campo
De las practices describidas, cuales son..


M=manual, C=caballo, B=buey, CO=Maquinaria combustible, T=transporte, P=practicas del
manej o

ENFERMEDADES
Control o no para enfermedaddes (se hielo, o se quema- hongo- pata prieta) usted.
Si si, describe usted su control de
Of the practices you described (see key), what are the...
If cultural methods are used, please describe












Type:l # de veces # de dias la # de personas otras notos o
la tareas se tareas se requirida para control o
hace como hace como hacer la tarea aplicacion de
describido describido herbicidas,
veneos, compost,
peo otro
Months ABCD AB CID AB C D


CRhs=comprar o recibir venenos sinteticos, industriales, CRHN =Compra o recibir venenos
naturales, R=recoger material para control natural, T=transformar material organic para control
natural, S=sintetico, industrial venenos aplicado solo, Nc=venenos naturales, commercial
aplicado natural, Nf=venenos naturales de la finca aplicado solas SN= sintetico y natural juntos,
CT=cultivo trampa., BV=barrera viva, F=remover fisicamente, CC= control cultural de otro tipo.

MECANIZACION
Usa maquinaria para cualquier de estas practices o transport?
Si si, mire la tabla

Tipo:l Descripcion de # de set # de animals por # de personas
maqunaria completes. equipo necesario para
modelo ano operar
maquinania


M=manual, C=caballo, B=buey, CO=Maquinaria combustible, T=transporte, P=practicas del
manej o

SIEMBRA, COSECHA, y RESIDUOS
Describe como siembra.
Describe como cosecha
Describe su manej o de residuos(rastroj o de la cosecha).
De las practices describidas, cuales osn las..











Type:l # de veces la # de dias la # de personas mismo tiempo de
tareas se hace tareas se hace requirida para otras practices
como como hacer la tarea
describido describido
Months ABCD ABCD ABC D


C=harvest, R= residue se dej an en sima, I=incorporas los residues, Q=quemar los residues,
R=recoger para otros usos, S= siembra, CR= comprar recinir semillas, P=prepar semillas,

Usa maquinaria para cualquier de estas practices o transport?
Si si, mire la tabla

Tipo:l Descripcion de # de set # de animals por # de personas
maqunaria completes. equipo necesario para
modelo ano operar
maquinaria





M=manual, C=caballo, B=buey, CO=Maquinaria combustible, T=transporte, P=practicas del
manej o









APPENDIX D
DESCRIPTIVE STATISTICS

Table D-1. Mean and standard deviation of response variables.
Response Variables Mean SD

% Organic Matter 2.270 0.583

Acidity 6.507 0.216

Basal respiration 11.054 5.128

Bulk Density (0-15)cm 1.190 0.082

Bulk Density (15-30)cm 1.181 0.102

Phosphorous Profile (ug/g soil)
Pl 14.411 13.549
P2 86.368 37.289
P3 322.678 99.623
P4 240.170 69.641
PT 708.687 165.443

Phosphorous Profile (% of total)
Pl 1.979 1.887
P2 12.856 5.326
P3 44.819 9.380
P4 33.399 5.205

Soil Quality Indicator Efficiencies
% Organic matter 0.12 0.116

Acidity 0.367 0.341

Basal respiration 0.679 0.710

Bulk density (0-15)cm 0.067 0.064

Bulk density (15-30)cm 0.066 0.066

P fractions (ug/g soil)
Pl 0.654 0.596
P2 5.686 9.078
P3 17.383 19.277
P4 13.195 15.614
PT 39.861 48.030











P fractions (% of total)
Pl 0.094 0.081
P2 0.805 1.053
P3 2.462 2.172
P4 1.846 1.739

Labor inputs (man-days/Mz)

Fertilization 5.518 6.243

Weed control 18.06 13.160

Insect pest control 3.676 5.258

Disease control 0.962 1.300

Total labor 27.242 17.510


Labor productivity (Qt/man-day)

Fertilization 27.489 40.786

Weed control 0.703 0.363

Insect pest control 5.487 4.769

Disease control 18.967 16.266


Labor Inputs (% of total)

Fertilization 20.362 16.949

Weed control 67.741 20.466

Insect pest control 15.227 15.101

Disease control 3.777 5.183


Production (Qt/Mz)
Yield 11.361 1.596










LIST OF REFERENCES


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Development, 27(2), 249-269.

Akobundu, L.O. 1987. Weed Science in the Tropics. Principles and Practices. Wiley, Chichester,
UK.

Altieri, M.A. 2002. Agroecology: the science of natural resource management for poor farmers
in marginal environments. Agriculture, Ecosystems, and Environment, 93(12), 1-24.

Alwang, J., Siegel, P.B. 1999. Labor shortages on small landholdings in Malawi: implications
for policy reform. World Development, 27(8), 1461-1475.

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BIOGRAPHICAL SKETCH

Alvaro Valle earned a B.A. in biology from Tufts University (Medford, MA) in 2003.

Before coming to the University of Florida (UF), he worked in the outdoors in various positions.

After completing his M. S. degree in interdisciplinary ecology, he plans to join the Horticulture

Department at UF, ultimately hoping to infuse some revolution into the agricultural "sciences."





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1 LABOR, SOIL QUALITY, AND YIELD IN CONVENTIONAL AND ECOLOGICAL SMALL-SCALE, TROPIC AL AGROECOSYSTEMS By ALVARO ALEJANDRO VALLE 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 2008

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2 2008 Alvaro Alejandro Valle

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3 A mi familia

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4 ACKNOWLEDGMENTS The com pletion of this work was made possibl e only through the assistance, guidance, and patience of my committee. Special thanks go to the head of my committee, Dr. Hugh Popenoe, for willingly extending his practical and philosophical guidance, time (revision after revision), enormous store of tropical experience, frankness, and hospitality at the HLP ranch. Dr. Marilyn Swisher is an expert on conducting science. Her didactic ability, insistence on conducting fundamentally correct work, and openness to ideas have all been incredibly appreciated. Dr. Robert McSorley has been a model agroecologist for me, and I thank him for this. The earnest enthusiasm, rational and clear opi nion, and indispensable scientific understanding will not be forgotten. Further, I would like to thank personnel of UNAN-Leon. I am often inspired by their intellectual tenacity in the f ace of limited recognition. Marlon Molina, Adrian Catin, and Don Anibal are especially thanked for their earnest effort, local knowledge of Leon, and friendship during the summer of 2006. Needless to say, this study was critic ally dependent on the advice, research, and genuine support of Dra. Xiomara Casti llo. I am indebted to these persons. Finally, the staff at Laboratorios Quimicos SA made it explicitly clear why they are the foremost environmental testing laboratory in Nicaragua. A Tropical Environment and Development Fellowship from the Compton Foundation financed this effort. Their intentions, and th eir desire to support th ird world research, are honorable. Thanks to Dr. Susan Jacobson, Anne F itzgerald, and everyone el se involved with the Compton Foundation.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........7 LIST OF FIGURES.........................................................................................................................8 ABSTRACT.....................................................................................................................................9 CHAP TER 1 INTRODUCTION..................................................................................................................11 Rural Poverty..........................................................................................................................11 Small-Scale Ag riculture ........................................................................................................ ..11 Sustainability..........................................................................................................................12 Sustainable Management........................................................................................................ 14 Research....................................................................................................................... ...........16 2 LITERATURE REVIEW.......................................................................................................18 Energy Inputs and Efficiency.................................................................................................18 Ecosystem Effects and Efficiency.......................................................................................... 20 Output.....................................................................................................................................25 Objectives...............................................................................................................................26 Hypotheses..............................................................................................................................27 3 METHODOLOGY................................................................................................................. 28 Research Context....................................................................................................................28 Agronomy........................................................................................................................28 Ecology............................................................................................................................29 Research Design..............................................................................................................31 Sample Selection....................................................................................................................32 Instrument, Procedure, and Analysis...................................................................................... 33 Management Index.......................................................................................................... 33 Index construction....................................................................................................33 Indexing procedure................................................................................................... 34 Index score...............................................................................................................35 Semi-Structured Interview...............................................................................................36 Soil Quality Assessment.................................................................................................. 37 Soil Sampling.................................................................................................................. 39 Soil Quality Analysis....................................................................................................... 40 Statistical Analysis........................................................................................................... .......42

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6 4 RESULTS...............................................................................................................................44 Census Population..................................................................................................................44 Energy Inputs and Productivity.............................................................................................. 44 Ecological Indicators and Efficiency...................................................................................... 45 Output.......................................................................................................................................1 5 DISCUSSION.........................................................................................................................48 Census Population..................................................................................................................48 Labor Inputs and Productivity................................................................................................ 49 All Management..............................................................................................................49 Fertilization.................................................................................................................. ....50 Disease.............................................................................................................................51 Weeds..............................................................................................................................52 Insect Pests......................................................................................................................53 Soil Quality and Ecological Efficiency.................................................................................. 54 Yield.......................................................................................................................................57 Conclusions.............................................................................................................................58 APPENDIX A PROTOCOLS.........................................................................................................................60 B INDEX....................................................................................................................................63 C SEMI-STRUCTURED INTERVIEW.................................................................................... 66 D DESCRIPTIVE STATISTICS................................................................................................ 74 LIST OF REFERENCES...............................................................................................................76 BIOGRAPHICAL SKETCH.........................................................................................................84

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7 LIST OF TABLES Table page 4-1 Results of Mann-Whitney U test for labor am ounts (man-days/Mz ), percent of total labor (%), and labor pr oductivity (Qt/(man-day)) between conventional and ecological growers.............................................................................................................46 4-2 Sample sizes for labor productivities per practice. ...........................................................46 4-3 Calculated p-values of soil quality indicator and efficiency means between conventional (n=10) and ecological (n=8) farm s using t-test for independent sam ples.... 47 B-1 Indicator rankings by experts............................................................................................. 64 B-2 Individual indicator scores by replicate. ............................................................................65 D-1 Mean and standard deviation of response variables.......................................................... 74

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8 LIST OF FIGURES Figure page 3-1 Original management indicators........................................................................................ 43 3-2 Final management indicators............................................................................................. 43 3-3 Index scoring example...................................................................................................... .43 4-1 Histogram of replicate managem ent index scores............................................................. 45 A-1 Protocol for manageme nt index construction....................................................................60 A-2 Interview protocol......................................................................................................... .....61 A-3 Soil sampling protocol..................................................................................................... ..62

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9 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 LABOR, SOIL QUALITY, AND PRODUCTI ON IN CONVENTIONAL AND ECOLOGICAL SMALL-SCALE, TROPIC AL AGROECOSYTEMS By Alvaro Alejandro Valle May 2008 Chair: Hugh Popenoe Major: Interdisciplinary Ecology Small-scale agriculture in the developing tropic s is often concomitant with rural poverty. High labor requirements can impose a social burden that negatively affects quality of life. Degrading soil quality (SQ) can reduce future pr oductivity. Economic returns are low, because yield per person (or labor productivi ty) is not sufficient to provide basic necessities. At the center of this problem is the nature of small-sc ale farming in the developing tropics. The most sustainable management would simultaneously lo wer labor inputs, increase SQ, and increase yields. Ecological approaches depend on ecological cycles and relationships within the agroecosystem for management, while conventiona l approaches look outside the agroecosystem for management options. In our study, we meas ured labor and labor productivity, SQ and SQ efficiency, and yield of field-scale agroecosystems using either conventional or ecological management. A cross-sectional design w ith referral sampling was used to study 18 agroecosystems during the June-August 2006 agricultural season in in Leon, Nicaragua. The studied agroecosystems were small-scale sesame farms with sandyloam andisols in a tropical dry climate. A management index identified the approach to ove rall agroecosystem management on a scale from conventional to ecological. A semi -structured interview wa s employed to gather

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10 data labor and yield data for Sesamum indicum production. Soil sampling a nd indicator analysis measured soil quality. These included % organic matter, acidity, phosphorus availability, biotic activity, and bulk density at two depths. T-te sts and Mann-Whitney were used to test for differences between the two groups. Total labor was not different between managements, nor wa s labor productivity. Labor amounts (man-days/Mz) differed significantly on ly for fertilization (p<.05) and disease management (p<.10), with ecological agroecosy stems requiring more labor. Conventional agroecosystem allotted a greater pr oportion of their tota l labor to weed (p<.10) and insect pest (p<.10) management than did ecological agroeco systems. Labor productivity was not different between treatments for any practices or in to tality, though very small sample sizes lowers confidence in these results. Labor results indica te that where techniques are different, ecological management practices often require more labor. The exception is insect pest control. Where techniques are similar, there is no di fference in labor between managements. No soil quality indicator or efficiency was a ffected by management regime. Therefore, in most respects ecological sustaina bility did not change with management. This contrasts with most studies to date. Yield was similarly not different between mana gement, indicating that ecological management does not necessarily lead to yield reductions. Given all this, it seems that neither agroecosystem is more sustainable. This may be due to similarity in inputs between all small-scale systems, regardless of management type.

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11 CHAPTER 1 INTRODUCTION Rural Poverty Approxim ately 2.5 billion rural people are livi ng on small farms in the developing world (International Food Policy Resear ch Institute (IFPRI) 2007). Asians and Africans comprise the bulk of this figure, but there are also 19 million rural dwellers (two thirds are poor) in Central America who are ostensibly tied to small-scale agriculture (Soto 2003). Ni caragua is one of the Central American nations with a poor agricultur al populace. Forty three percent of Nicaraguas total population is rural (Food and Agriculture Organization (FAO) 2006), and 68.5% of this rural population is poor (World Resources Institute (WRI) 2005). Considering the high rate of poverty, economic sustainability may be low. So me focus on sustainable productivity of smallscale agroecosystems is needed to alleviate tr opical rural poverty, especi ally where this poverty is extreme, entrenched, or widespread (I FPRI 2007, World Bank 2003, WRI 2005). To this end, we conducted a study on the sustainability of small-scale field production on a western Nicaraguan andisol typical of tropical, developing nations. Small-Scale Agriculture Poor people and sm all-scale farmers suffer from the same fundamental problem: both lack access to resources required to secure a livelihood (Beets 1992, Adger 1999). In the case of small-scale tropical growers, these are mainly land and agronomic input s of all types (Beets 1992). Even if land is available, deficient agronomic resources can constrict the ability to cultivate additional land or properly cultivate present crops (Alwang and Siegel 1999). These agronomic limits include meager extension serv ices (especially for non-traditional cash crops), limited or insecure credit options expensive or unattainable input s, available and willing labor, lacking irrigation infrastructure, and prohibitive mechanization costs. Moreover, restricted

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12 access to agronomic resources forces tropical sma llholders to rely on local agroecosystems for management support (Altieri 2002, WRI 2005). What the development community constitutes as small-scale agriculture is contextually dependent on geographic location, agronomic s upport, and market environment (IFPRI 2007). 61% of all agricultural holdings in Nicaragua are under 14 ha, and 47% are less than seven hectares (FAO 2001). Only 7% of all land in Nicaragua is irrigated (FAO 2006), and we observed virtually no irrigation except on sugar cane and peanutthe domain of largescale agriculture. Mechanization is us ually limited to tractor rental fo r pre-planting tillage. Our study site is near the Leon (0.5 million inhabitants), Managua (1.2 million), and international (via Pan American highway) markets. Small-scale growers of Leon simultaneously produce for consumption, for markets, and with traditional and modern technologies. This reflects the modern small-scale agriculturalist in the Mesoamerican trop ics (Popenoe and Swisher 1998). Given all this, and after consultation with local e xperts, the upper limit of small-scale holding is set at 10 manzanas (16.80 acres or 6.41 hectares ) of ownership or land under production. After this point, we observed that economic production and agricultural scale resembles a more midscale operation. Sustainability Tropical rural poverty is evidence of low economic sustainability in small-scale production. Low economic sustainability can be at tributed to low labor productivity, which is output per person laboring (in our case, the owner-f armer), because labor productivity, in effect, is the economic return to the grower once the pr oduct is sold. With all else held equal, the established relationship describe s increasing economic re turns as labor productivity increases. Labor productivity can be increased by the mechan isms of intensification or extensification, where land is available. For either mechanis m, there must be access to various agronomic

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13 resources. One of those resource s, labor, must become more available in one of three ways to allow further work: willing labor must become available, labor saving machinery must be introduced, or productivity of fi eld labor must increase. In the absence of labor changes, intensification can proceed through better manage ment of possessed resources. The central problem for the small-scale tropical farmer is th at both mechanisms are near impossible because access to agronomic resources (including labor a nd credit), access to land, and research for improved management is limited at best. Even where land is available, a lack of agronomic resources still negates the possibility of extensific ation. In the absence of outside investment or institutional support, most tropical growers w ill suffer from vulnerability to ecological and economic flux, weak terms of trade, and a near impossibility to pull th emselves out of poverty. (Kiker 1993, Tomich et al. 2001). Soil has a pivotal role in in creasing economic sustainability through crop production. Soil processes and functions are critically involved in primary producti on. Thus, a critical objective in achieving economic sustainabil ity in the tropics and improving rural livelihoods is maintaining and improving the ecological basis of small farm sustainabilitysoil qual ity (Lal 1991, Stocking 2003). Smallholder African farmers, for example, investing in soil conservation often achieve higher land productivity (Byringi ro and Reardon 1996), effectivel y intensifying and increasing economic returns. For agriculture, soil quality is the capacity of an agroecosystem soil to support sustainable plant producti on (Soil Science Society of Am erica (SSSA) 1997). It is a holistic concept that recognizes the interacting ph ysical, chemical, and biol ogical properties that make soil so important for sustainable production in the tropics. Making soil the holistic basis for production is particularly salient where exte nsion services, contextappropriate research,

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14 consulting services, and other support for agro te chnical soil management is presently out of reach. The andisols of this study are derived from high silica, pyroc lastic ejecta from periodic volcanic eruptions. With high temperatures and an ustic moisture regime, this parent material has a high Si to Al ratio and unique allophanety pe clays. Allophane is amorphous clay with comparatively high cation exchange capacities, du e to the high surface area and many positively charged exchanged sites. In combination with prev alence of silica oxides, and to lesser degree iron oxides, allophane soils retain much orga nic matter and are infamous phosphorous fixers. This frequently makes phosphorus a limiting nutrient in andisol agriculture. Consequently, organic matter percentages in dark, native soils are many times above 5% and long-term phosphorus fixation levels are ofte n around 50% (Joergenson and Cast illo 2001). In general, the high percentage of organic matter, strong structur e, high native fertility, and deep rooting depth makes andisols productive soils, although easily eroded. The ecological sustainability is stronger than for the indigent smallholder in many other developing nations. None theless, conserving and enhancing soil quality is important for the many ru ral poor whose land is th eir only real wealth (WRI 2005). (Parfitt 1989) Sustainable Management Relatively immediate improvem ents to labor productivity and rura l poverty, without intensive investment, can be garnered by increa sing sustainability thr ough better agroecosystem management (Beets 1992, WRI, 2005). The most sustainable management would lower labor requirements, increase soil quality, and enhance yields to impart economic sustainability and ecological sustainability. Any management deve lopment that positively affected any of these three variables would increase some facet of sust ainability. Due to the integrated nature of sustainability, however, an effect on one sustainab ility facet is likely to affect another. For

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15 example, more socially sustainable production, su ch as with lower labor requirements, improves economic sustainability through increased labor productivity. It may also improve ecological sustainability, since labor is de terminant of soil conserving st rategies (Marenya and Barrett 2007). The spectrum of management approaches ranges from conventional to ecological. Wholly conventional approaches manage agroecosystems from an external perspective, depending on extra-agroecosystem options to systematically control biological communities and supply crop needs. Fully ecological approaches manage ag roecosystem from an internal perspective, utilizing the agroecosystems own ecosystematic functions, processes, and cycles to regulate biological communities and support pl ant growth. A large range of combined approaches exist. Some combinations, such as integrated pest management, are widely used. The quality of materials often changes with approach, but it is not the fundamental difference. Hence, substituting organic inputs for inorganic inputs may make mana gement more environmentally friendly, but it does not indicate a completely ecological management. (Gliessman 2007) This difference in perspective leads to practic al distinction between management regimes. Ecological management strives for a diversity of crops; fertilizes mainly with organic additions, recycled nutrients, or through biol ogical fixation; eschews industrial ly-synthesized pesticides in favor of alternative methods that prevent pest population; conserves a nd builds because soil is viewed as the basis of productio n; and often uses locally-ada pted, heirloom, and traditional cultivars and crops. Conventiona l management grows one or very few crops; fertilizes mainly with imported inorganic fertilizers; applies chem ically-synthesized pestic ides for pest control; uses soil mostly as a media for nutrient additio ns and physical support; a nd typically sows with industrially enhanced/modified/treat ed seed of commercially ubiquitous varieties. We will refer

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16 to agroecosystems managed ecologically as ecological agroecosystems and those managed conventionally as conventional agroecosystems. We note that organic agroecosystems fall under the heading of ecologi cal agroecosystems. Research The m ain inquiry of this inve stigation determines which mana gement is likely to produce the most sustainable agriculture in this context. We test th e hypotheses that ecologically based management is the most sustainable management for resource poor, small-scale farmers in the tropics, as Altieri (2002) and other have suggest ed. There is some evidence from Philippine small-scale farmers that they themselves perc eive this to be true (Mendoza 2004). We will answer this question and test the hypothesis by comparing la bor, soil quality, and yield in conventional and ecological agroecosystems. This is not a legitimate sustainability analysis, since the requisite temporal element of sustaina bility was not pursued in any fashion. Rather, this is a management analysis that serves as a measured proxy of sustai nability. Utility of the analysis is based upon the assumption that response in a reasonably typical year will be similar in the future if management and ecological conditions do not drastically change. An agroecosystems framework is employed in this observational study. This perspective attempts to understand ecosystem functioning and processes as flows of matter/energy from input pools, to internal pools, to the output. Each pool is affected by the flow from the previous pool. The premise of this is that agricultural fields can be viewed as ecosystems. As these fields contain the components and structur e of a natural ecosystem, it is va lid to view them as managed ecosystems. Field scale agroecosystems of sandy loam, andi sols under small-scale production of late rainy season Sesamum indicum will serve as experimental populations. Growers managing these systems produce varying products during th e early rainy season followed by sesame Sesame

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17 labor inputs will be measured for each approach. So il quality effects of this management will be measured using chemical (percent organic matter, acidity, and phosphorus availability), biological (biotic activity), and physical (structure as bulk dens ity) indicators. Production is measured as yield. Sustainable agricultural development has been seriously undermined by an inability to fully consider the complex inte rrelationships involved in pr oduction (Lal 1991). This is addressed by calculating labor productivity (outpu t/labor input) and soil qua lity efficiency (soil quality effect/labor input) in response to a mana gement range. Soil quality efficiency is a term we derived to examine how much soil quality impr ovement one gains for a given labor input. In reality, it is the same in concept as any other pr oductivity measurement in that it measures output (internal SQ effect) for a given amount of input effort (management labor).

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18 CHAPTER 2 LITERATURE REVIEW Energy Inputs and Efficiency The scientific community generally contends that there are d ecreasing energy inputs and concurrently increasing energy efficiency as ma nagement becomes more ecological (Powers and McSorley 2001). Pimentel et al. (1983) were of the first to find mi dwestern organic cornfields to be more energy efficient than conventional gr owers using high-input techniques. Diverse systems-including Mediterranean olive groves (Kaltsas et al. 2007), Australian pasture-cereal crop rotations (Nguyen and Hayes 1995), and Danish integrated grainlivestock operations (Dalgaard et al. 2001) reassert claims of increased energetic efficiency with lower overall energetic inputs. Overwhelmingly, reduced depe ndence on synthetic fertilizers and pesticides, created and transported with fossil fuels, are th e main factors in decreasing energy inputs and increasing energy efficiency in ecologically managed systems (Mader et al. 2002, Sartori et al. 2005). This trend for overall energy inputs holds true after 21 year s of production, even including increased fossil fuel usage by tractors fo r fertilization with orga nic manures (Pimentel et al. 2005). Clements et al (1995) affirm that reduced he rbicide use in more ecological approaches decreases energy inputs and increases efficiency, despite the usual increases in fossil fuels for mechanical cultivation. They add that th is is true as long as cultivation is used in moderation. Whether these developed world findings can be transferred to small-scale tropical systems, where pesticide are less availabl e and cultivation is often manual, is questionable. Labor is a relatively minor portion of overall energetic inpu ts in developed world agriculture, since mechanization and accessible agronomic inputs can substitute for manual labor (Giampietro and Pimentel 1990). Understandably, labor is usuall y excluded, largely discounted, or subsumed in

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19 energy assessments of most comparative mana gement studies (Loake 2001). There are, however, a few occasions where labor was tracked in the developed world. The Rodale study of Pimentel et al. (2005) indicates that the diversified, legumebased organic rotations required 35% more labor throughout the growing season to manage more cover crops, cultivate more often, and handle manure applications when neede d. This mirrors findings of Karlen et al. (1995) that measured up to 75% more labor in a few cases, due mostly to increased cultivation and handling of manure, in Iowa corn/soy fields Nguyen and Hayes (19 95) find the labor inputs to be higher in the cereal crop portion of their pasturecereal crop rota tions under an alternative management, but labor requirements were lower and productivity higher over the entire cycle under alternative management. The reasons for incr eased labor were similar to the other studies. The small olive growers in the Kaltsas et al (2007) study spend more time walking around to inspect insect baiting traps, than their conventional counterpa rt spraying pesticides on foot. The utility of these findings is tempered by th e fact that labor increases came mostly as more tractor time. In terms of social sustai nability, this cannot be considered the same as wielding a machete or even spending more time on ones feet. Loake (2001) addresses this critical distinction between dr iving a tractor and the physical exertion of more manual labor by comparing the human energy efficiency of labor on highly mechanized conventional farms to organic farms using no mechanization. Her results indicate that organic farming in the UK is by far more physically stressful, some days expend ing more energy than is gained, both because more labor is required and because of the physical nature of the work. This is not entirely surprising, but lends empirical ev idence for assessing labor inpu ts as a matter of social sustainability, especially where the returns to that labor are lower than desirable.

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20 A few authors have looked at labor requireme nts for tropical, small-scale growers. In flooded rice, eight man-days more were required in the organic system for nutrient management (spreading rice straw and applyi ng compost), but two man-days less were required for organic land preparation because soil tilth had improved under this management, making more extensive tillage unnecessary. Despite the in itial increases of labor in the organic system, labor decreased throughout the season and summed to 47.5 overall ma n-days/ha for organic farming and 52.5 for conventional farms. These figures were adjusted to take into account the labor intensity of practices. Additionally, these authors found en ergy efficiency to increase with organic management, again largely due to reduction in inorganic fertilizers a nd synthetic pesticides (Mendoza 2004). These findings are not mirrored in small-scale Bangladeshi agriculture, where labor was taken as a measure of social sustai nability and found not to be different between ecological and conventional agriculture (Rasul and Thapa 2003). It s eems that evidence of managements effect on labor in small-scale tropical farming is scant and inconclusive. Ecosystem Effects and Efficiency The decreased use of industrially synthesized fe rtilizers and pesticides causes changes in agroecosystem structures, processes, and inte ractions (Drinkwater et al. 1995). Ecological management has shown changes in agroecosyst em biological diversity (Menalled et al. 2007, Morandin and Winston 2005), in nu trient cycling (Clark et al. 1998, Tortensson et al. 2006), and in root disease suppression (Bulluck et al. 2001). The effect of manage ment on soil quality is measured via concrete chemical, biological, and physical indicators that address the integrated ability of soil to activ ely support plant production. Organic matter is often used as an overriding soil quality indicator because of its critical role in nutrient storage, soil st abilization, ion exchange capacity, biological health, and a myriad other influences (Reeves 1997, Tiessen et al. 2001) It may be especially important in small-

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21 scale, tropical systems, where soil organic matte r is the major nutrient ca che and determinant of soil biological activity. Generall y speaking, increases in organic matter increase the ability of the soil to support plant production. A maximum can be reached before soil quality decreases (Sojka et al. 2001), but this usua lly only happens with excessive manure applications of the type from intensive dairy operations. A long-term, organic, legumebased rotation in Pennsylvani a increased organic matter markedly as residues were incorporated (Drinkwat er et al. 1998). Fleissbach et al. (2006), Widmer et al. (2006), and Manna et al. (2005) recently confirmed the common view that organic fertilizers or soilconserving additions, as in ecological agriculture, increases soil organic matter. This may have positive effects for agroecosystem s. Mendoza (2004), for example, explains that decreased labor for small-scale rice was mainly due to improved soil tilth associated with increased soil organic matter. The benefits of increased soil organic matter may not be immediate, however, as measurable increases in organic matter may accrue only after an extended period of accumulation (Fleissbach et al. 2006, Monokrousos et al. 2006). Since ecological management fertilizes mainly with or ganic matter, and attempts to conserve the soil basis of production with organic additions, it is logical that incr eases in soil organic matter are often seen (Lotter 2003). The chemical indicator of acidity also has a large influence on the ab ility of soil to support primary production. In a very gene ral sense, a pH closer to neut rality allows for the production of a greater number of crops, a voids aluminum/micronutrient toxi city and sodicity, and allows for greater microbial diversity, valuable in root disease supp ression. In the case of tropical andisols, an increase in pH is an increase in so il quality. Mader et al. ( 2003), Fleissbach et al. (2006), Bulluck et al. (2002), and Reagonald (1988) all found pH to increase in differing soils

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22 with organic matter additions (for multiple goals) typical in ecological management. The main reasons for an increase in pH with ecological management can be reduced to three. Several of these effects can be in play in any of the studies above. Firstly, signi ficant applications of synthetic fertilizers and certain pe sticides in conventional agriculture are known to acidify soil. Avoiding these raises pH. Secondly, as manure is a common organic fertilizer, and as manure often contains salt minerals in differing proportion, an increase in pH may result in acid soils. Finally, even where organic manures are not used, increases of orga nic inputs, with composts or green manures, can raise pH when low (Ouedr aogo 2001). This buffering effect depends on continual additions of organic matter, though, as increased microbial decomposition near neutrality decreases organi c matter rapidly (Hugh Popenoe, personal communication, 2007). This may cause pH to drop again, where soils ar e naturally acidic, after the buffering agent is removed A more specific indicator of soil quality, given the nature of phosphorus restrictions in andisols, is phosphorus (P) availa bility. In lowland, tropical so ils with high P fixing capacities, Lawrence and Schlesinger (2001) demonstrate that longterm agricultural management of organic matter can affect P distribution, even if total P does not change or is not imported. The relation between distribution, plant availability, and organic fertil izers was seen in flooded rice (inceptisol) cultivation (Salaque et al. 2004). This team reports that greater concentrations of labile and relatively labile P fractions when organic fertilizers (cow dung and ash) were included. Moreover, these 2 fractions were most affected by pl ant uptake in the control; so that increases in concentrations of these 2 fractions increased plant av ailable P. Reddy et al. (2005) examine the role of organic matter in P availability and find, after 16 weeks of alfisol study, redistributions of P in favor of labile, colloidal P when crop residues are used instea d of inorganic fertilizer. On

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23 vertisols of higher clay content, with the sa me methodology, the distribution of P was similar, albeit with a much less drastic e ffect than in alfisols (Reddy et al. 2001). This lends support to the idea that relatively invariable soil propert ies become more influential, and organic matter less, as the P fixing capacities become greater. In at least one st udy, the authors find no ecologically significant effect on P dynamics with differing fertilizers, indicating that soil properties were more at play in controlling so il P dynamics than input matter (He et al. 2006). Castillo and Joergenson (2001) in andisols of the same study area as ours, also find soil properties to be more determinate in the availa bility of P to biomass then the management regime, even though more P was clearly seen to increase with conventional management. There is the possibility that organoP complexes may increases unavailability in andisols due to the nature of P occlusion in high organic matter andisols (Borie and Zunino 1983). We should note that rhizosphere association of arbuscular mychorrh izae play a significant ro le in plant uptake of P (Plenchette et al. 2005), but that this does not necessarily translate into greater yields (Ryan and Graham 2002). Soil microbes essentially govern nutrient cycl ing and community stability in the soil ecosystem and to a major extent control nutrient supply and disease. Microbial activity has been measured as a sensitive indicator of soil quality under differing management (Marinari et al. 2006) and during different stages of the same management (Monokrousos et al. 2006). Longterm experiments have concluded that more ecological management results in sustained increases in microbiological activ ity and nutrient cycling (includi ng P) (Mader et al. 2002). Increased microbiological activity with ecological management also suggests that fundamental differences in agroecosystem ecology are res ponsible for functional discrepancies between managements (Drinkwater et al. 1995, Clark et al. 1999). Clark et al (1999), for example,

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24 reported increases in nitrogen mineralization (ind icative of higher microbiological activity) that allowed for increased nutrient cycling to all plan ts, including weeds. Increased microbiological activity and diversity, prompted by ecological ma nagement, has led to suppression of soil borne disease and positive effects on cr ops (Bulluck et al. 2002). Research has more recently documented the infl uences of manure quantity and type in soil microbial community size and composition (Fleissbach et al. 2006). They find the type of organic inputs, and consequently soil organic carbon, influences th e microbiotic activity and soil quality. The organo-mineral complexes of andiso ls, for example, may limit C availability to microbes (Oades 1995), explaining the substantial build up of organic matter in andisols. Interestingly, Marinari et al. ( 2006) was not able to relate diffe rences in microbial biomass to organic matter. Other distinctions between manage ments, such as in pesticide use, can therefore also influence soil biology (Hanse n et al. 2001). Plenchette et al (2005) reviewed studies of the management effect on beneficial mychorrhizae. They conclude that c onventional agricultures reliance on chemically synthesized pesticides is more deleterious to mychorrhizae than ecological management not using such inputs. Following suit, Castillo and Joergenson (2001) attribute increased basal respiration in ecological agroecosystems to decreased pesticide use and increased diversity of organic residues from more diverse cropping systems. A priority for soil quality in the 21st century must be the physical management of soils (Lal 1991, Stocking 2003). Soil erosion in andsiols can be a problem in and of itself, not to mention the disease and aeration problems that puddling from poor structure can cause. Within the same soil type and texture, organic matter will be the primary im pactor of physical structure. Since increases in organic matter are more often seen with ecological management, decreases in

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25 measured bulk density are expected with more ecological management. A less compacted soil improves physical structure for plant growth. Output Most com parative management research ex amines output ability of conventional and alternative systems. Stanhill (1990), who revi ewed 205 comparative studies, estimated an average 10% yield loss by organic systems. He included agroecosystems recently converted to ecological management. These agroecosystems may not be as optimized for production as they might be in the future. Lotter (2003), nonetheless, agreed with the estimated yield losses. Often weeds are blamed for decreased yields under ecological management One study saw declines of 20% to 35% in wheat yields, despite increases in most soil quality measures, due perhaps to increased weeds (Mader et al., 2002). Clark et al. (1999) posit that weeds proliferate in ecological systems exactly because soil quality is higher, for all plants, under ecological management. Researchers have also measured similar or higher yields in ecological agroecosystems. Fresh pepper yields in Florida were similar in both managements (Chellemi et al. 2004), while Mendoza (2004) saw rice yields increase with or ganic management. Mendoza (2004) relates this to disease suppression, more organic matter, a nd better physical soil stru cture. Lotter (2003) noticed a trend of increa sing ecological yields in drought years, while better climatological years produced higher conventional yields. He attributes this either to increased mychorrhizal hyphae or increased organic matter. Bo th offer drought resistance. Increas es in corn and soybean yields during drought was corroborated by a 22 year field trial at the Rodale Institute that also highlighted yield similarities among management re gimes, especially afte r an initial transition period (Pimentel et al. 2005). Yet, an interest ing investigation by Martin i et al. (2004) negates the that so called transition effect is due to soil quality changes, hypothesizing rather that

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26 increasing ecological management experience increas es yields after trans ition. This favors the argument that ecological yields do no t differ by management type alone. Either approach may be more desirable under a given set of physical conditions. Similar tomato yields in California prompted researchers to hypothesize that although differing ecological processes and pathways can be work ing on the cropping system, they can ultimately lead to the same agronomic response (Drinkwater et al. 1995). Clark et al. (1999) also find a difference in agroecosystem ecology under differing management, but in this case, yields were decreased in the ecological management. We may not know enough about ecological management to produce higher output even thoug h it is agronomically possible (Lotter 2003). Research attempting to establish which manageme nt approach is best should be critically assessed in respect to their validity. Many of these studies are conducted by experts under controlled conditions and warrant closer examination of generalizability. These studies also often attempt to eliminate confounding factors by using the same varieties to compare yields, even though the ideal genotype for conventiona l agricultural systems may be fundamentally different from those of ecological agriculture (Van Bueren et al. 2002). This is an integral piece of the management, and yet is not often explored. The decreases in conventional yields during drought, normally attributed solely to soil quality matter, could very plausibly be explained by variety differences. Objectives The objectiv e of this investigation is compare labor, soil quality, and yields of small-scale field agriculture in the devel oping tropics. We do this to as certain whether conventional or ecological agroecosystems, as defined in the introduction, are likely to be more sustainable. Furthermore, we attempt to build und erstanding of tropical agroecosystems.

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27 Hypotheses 1. Labor in puts will be higher, and labor produc tivity lower, in ecological agroecosystems. 2. Values of soil quality i ndicators and efficiencies w ill be higher under ecological management. 3. Yields will be higher under conventional management.

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28 CHAPTER 3 METHODOLOGY This research was carried out in the depa rtm ent of Leon, Nicaragua. Farms in the municipalities of La Ceiba, Leon, and Chacaraseca were sampled from late June to early August 2006 by myself and two assistantsMarlon Molina and Adrien Catin of the Universidad Nacional de NicaraguaLeon (UNA N-Leon). Yield data collect ion, and the return of soil laboratory results for each participant, took place during January 2007. Research Context Agronomy During the 1970s, the area of Leon was a very profitable m onoculture of cotton ( Gossypium hirsutum ). Leon produced the highest global yi elds of long-staple varieties for a period (Hugh Popenoe, personal communication, 2006). Consequently, this allowed for deep tillage and heavy pesticide us e on both large and small land holdings. Heavy machinery and poor soil management promoted soil erosion during winter. Ecological disa ster ensued as pest resistance elevated pesticide application to uneconomic, ineffective, and u nhealthy rates. Later, land reforms were initiated and many small-scale operations became the norm. Growers were organized into cooperatives with machinery to share. Subsequent economic depression, exacerbated by the collapse of the Soviet Union, hastened the virtually co mplete withdrawal of production support. Small grower cooperatives are still common, w ith the machinery retained by individuals who now rent thei r services. Cooperatives have limited negotiation power, as evidenced by frequent broken contracts. Small-scale growers in cooperatives or otherwise are alone in marketing and selling. This is a ne w phenomenon because previous small-scale growers sold to committed large landholde rs or government entities.

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29 Only 7% of all arable land in Nicaragua is irrigated (FAO 2005). Therefore, most production occurs only during the rainy season (MayNovember). Common crops during the beginning of the rainy season include fiel d corn, Cucurbitaceous species, yucca ( Manihot esculenta ), and fallow hay, with much variation among farmers and between years. All growers plant sesame in the late rainy season, and in this study, they would be asked about labor inputs and production for sesame. The strategic need fo r a single crop to comp are yields and labor amongst management systems was the major impetu s for this. Furthermore, similarity in an export commodity allowed for ecological partic ipants to be found via sampling frames of cooperative lists. Coffee has been used for th is purpose, but coffee production systems are essentially agroforestry systems and not field production. Additionally, sesame seed is the domain of smallscale, manual labor systems of developing nations and so is an appropriate selection for the tropical populati on of interest in this study. Sesame production is not new in Nicaragua, but has taken on greater importance for the small-scale grower as higher-value export crops are pursued. Ecology The Leon clim ate is typical of deciduous tr opical forest ecosystems. Average annual rainfall is approximately 1500 mm with an averag e temperature of 26.1 C with more then 85% of this rain coming between May and November (In stituto Nacional de Es tudios Territorriales (INETER) 2006). Temperatures vary little throughout the year. We collected soil samples during a normal dry period within the rainy season. In 2006, the start of the rainy season was dryer than normal. The dry period within the rainy season was drier and longer than historic norms. Labor and yield data would be taken for production during the second half of the rainy season (August-November). August had -26% less rain; September had -55% less; October had 37.6% more rain; and November had 88% more precipitation than

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30 historic norms (1972-2000) (INETER 2006). In th e last month, seed sets and plants are particularly vulnerable to Phytopthera infection. Farmers expressed some concern over excessive rain in November, but ultimately did not seem to be affected by widespread fungal infections. Leon, the department, is on the Pacific coastal pl ain of Nicaragua and is in the shadow of an active volcanic corridor running the length of the department from North to South. These soils have been formed by pyroclastic ejecta an d are characterized by a high Si/Al proportion and distinguished by the presence of amorphous clay called allophane. Their andisol identity is confirmed in several locations. The latest surveys pe rformed by the presentday soils division of INETER classify them all as ashy, isohypothermic mollic vitrandept of the series Leon, Ceiba, Cerro Negro, or Guadalupe under the 1972 United States Department of Agriculture (USDA) taxonomy (Ministerio de Agricultura y Ganaderia (MAG) 1974). Also, these soils are classified as Vitric Andisols under the 1974 FAO system (C astillo and Joergensen, 2001). These soils would most likely be presently classified as sandy, isohyperthermic, vitric haplustand. Roughly 75% of the sampled farms were in th e Leon and Ceiba series, with the other 25% in either Cerro Negro or Guad alupe series (MAG 1974). In th e absence of trustworthy GPS coordinates it was impossible to say with absolute certainty into which series they were classified. This may be of little consequence, since the qualitative description of series from the 1974 survey are all effectively the same: 90cm ef fective depth, less than 4% slope, sandy loam texture, good drainage, and moderate erosion (MAG 1974). Certain so ils may have changed series, due to agriculture and hu rricane effects, without changing their volcanic parent material or sandy-loam texture.

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31 Because at least five observed textures of a ndisols exist within Leon and because basic soil characteristics can change drastically with differing texture, it was necessary to assure that all the farms in the study were of similar texture. We selected sandy-loam to be the soil texture in common because this was the most prevalent texture in the farming communities where we expected to find fields includa ble in our study. The present-day location of sandy loam texture was also crosschecked with Dr. Xiomara Castillo of UNAN-Leon, with presidents of cooperatives, with the farmers themselves, and with the texture by feel method when in the field. This soil texture was chosen because of its relati vely close proximity to Leon. This allowed for many logistical conveniences that would have ot herwise made soil sample collection difficult. Research Design Our research design is intended to test three hypotheses. W e hypothesize that: 1. Labor inputs will be higher, and labor productivity lower, in ecological agroecosystems. 2. Values of soil quality indicators and efficiencies will be higher values under ecological management. 3. Yields will be higher under conventional management. An on-farm, observational study with a cross-sec tional design is used to test these three hypotheses. The majority of comparative manage ment research has used true experiments on research stations with research erled design and management. Th ere is evidence, however, that grower management will lead to different r ecommendations for on-farm production (Sumith and Abetsiriwardena 2005). As Drinkw ater (2002) notes, the most important advantage of on-farm studies is that systems under study are realistic in terms of scale, management practice and constraints faced by the farmer and theref ore offer an opportunity to study intact agroecosystems.

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32 Cross-section is an appropriate design when there are two existing groups and no previously applied experimental intervention can be identified or will be applied. There is, therefore, no control group. This compromises internal validity to a reasonable degree. External validity is robust. The on-farm approach allows us to sample working agroecosystems with all the factors of interest as equal to most small-scale agroecosystems in Nicaragua as possible. Sample Selection Our individual sam pling units are agroecosystems. An agroecosystem is defines as set of contiguous fields growing late rainy-season sesa me on sandy-loam vertisols in Leon. All or only part of fields may be planted in sesame (justification in introduction). A small-scale system is a maximum holding of 10 Mz (6.42 ha) (rented or owned), worked primarily by the same ownerfarmer (with hired help for certa in tasks), with no irrigation, and using no mechanization postplanting. Our resulting theoretica l population is composed of tropi cal agroecosystems that 1) are small-scale, (2) have been managed in the same manner for at least three years. Growers must have grown sesame at least once within the last 3 years. This ensured that labor as reported would be accurate. Due to our non-probabilis tic sampling scheme, we can only extend our finding to members of the theoretical population c onnected, in some manner, to a cooperative of sesame growers. This is not a major restriction, as most sesame growers will be connected to a cooperative either formally or informally. Referral sampling is the sampling approach used in this study. Because it was impossible to identify eligible participants a priori referral sampling granted us the only real chance of finding agroecosystems of the accessible population. The initial sampling frame came from lists of cooperatives provided by Cooperativa Del Campo S.A. of Leon, Nicaragua, which lead to a list of members of sesame producing c ooperatives. We iden tified members of Cooperativa La Esperanza of La Ceiba, Leon (President Sra. Querube Perez) and the Asosiacion de Productores

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33 Ecologico de Nicaragua (APRENIC) of Leon, Nicaragua (Director-M anuel Caballero) as the accessible population. We visited each farm and made participation inquiries. After data collection, we asked for referrals. We did this until we could find no further sesame producers in our accessible population. We took a census of the accessible population. Instrument, Procedure, and Analysis Refer to Appendix A for schem atic protocol of index construction and other information Management Index A m anagement index (delivered during semi-str uctured interview) was created to measure the management approach on a scale. Indices are useful for robustly measuring an underlying variable not easily measured by a single indicat or (Bernard 2002). Mana gement indices have been used effectively in translating qualitative management differences into quantitative measure (Mas and Dietsch 2003). We found no satisfactory indexing method in th e literature. Thus, one was constructed. Then, we collected the responses to these questions as part of the semi-structured interview. Finally, we analyzed the management approach of each agroecosystem by using a summative score based on responses to indicators. Index construction We asked 10 experts a question by phone and em ail. W hat five indicators are most capable of distinguishing between conventiona l and non-conventional management? I did not mention, unless asked by the expert respondents, that this would be for Central American, smallscale operations. We retained those indicators that had at least 50% consensus. There were seven indicators mentioned by at least 5/10 respo ndents as capable indicators, and two indicators with 4/10 responses. Given contextual approp riateness and personal opinion, we included the

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34 two indicators with only 40% consensus. The original nine in dicators, in question form, are listed in Figure 3-1. After screening with growers outside the theoretical population, c onsulting with Dra. Castillo of the UNAN-Leon, and testing on our first 3 participants, questions with asterisks (*) were later dropped. They were either contextua lly nonsensical (items 6 and 7) or participants were unclear and varying in their unders tanding of environmental harm (item 8). Ranking the influence of individual indicat ors on an overall management approach strengthened the index. Ranking was used instea d of scoring to force respondents to consider their relative importance. We as ked a set of 11 experts to rank th e six final indica tors from most capable to least capable in distinguishing mana gements (see Appendix B). The ranking of each indicator came by selecting the mode of the responses. Where there were two or more modes for an indicator, they were averaged to arrive at a final mode and ranking for that indicator. This only happened once with the Diversity indicator. When two separate indicators showed the same ranking, the indicator with more hi ghestranks was established as a more influential indicator. The Pest Control and Diversity indi cators were both initially ranked as the third most influential indicator, but Pest Control received three number one rankings while Diversity received only two number one rankings. The six labeled indicators are shown in order of decreasing influence in Figure 3-2. Indexing procedure Each indicator was formulated as a q uestion wi th five possible answers. These questions were presented during the semi-s tructured interview. Indicato rs 2,3,and 6 were formulated as questions of type A as seen in the list below. These use relative measures to gauge whether a response indicates ecological or conventional management, with higher score indicating more ecological management. Indicators 1,4, and 5 are formulated, as questions of type B using a

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35 scale from least to most ecological. The numbe rs in parentheses indicate the weight of each response, with responses that indicated more ecological management having higher values. A. What is the dependence on organic (O) versus inorganic (IO) fertilizers? (1) Only IO (2) more IO than O (3) equal (4) more IO than O (5) only O fertilizer B. What is the level of onfarm material re cycling (manures, kitchen, and crop residues)? (1) No recycling (2) low (3) medium (4 ) high (5) everything possible recycled During data collection, we noticed that for questions of type B, separating between no recycling and low and between high and everything possible recycled was difficult. Their responses tended to be arbitrary decisions between closely related answers. This presented problems of robustness in the measure of that indi cator. To combat this, we collapsed the five possible responses to three low, medium, and highand adjusted points to 1-23 respectively. Index score After indicator questions had been presented in the semistructured interview, we determined the management index score of each agroecosystem. Actu al scores for each indicator and tabulations can be found in Appendix B. Figure 3-3 illustrates scoring for a hypothetical agroecosystem exhibiting the maximum level of ecological management. More influential indicators have high indicator weights. In this example, the response points shown are always the maximum possible score, indicating the most ecological approach. Multiplying the indicator points by the response points arrives at each indicator score. The final index score is a sum of the indicator scores and then divi ded by 6 to standardize the scores. The smallest possible score is 3.533. This i ndicates a fully conventional management. The largest possible score is 13.833. This indica tes a fully ecological management. The midway point is 8.665. Scores below 8.665 indicate ecolo gical management. Score above 8.665 indicate conventional management.

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36 Semi-Structured Interview A se mi-structured interview was conducted to ascertain the manage ment approach and gather labor and yield data. Semi-structured interviews are useful when one would like the discretion to follow leads, but st ill needs a pattern to recuperate necessary information (Bernard 2002). Appendix C contains the interview guide. There were five basic components in the semistructured interview: 1) eligibility establishmen t, 2) management indexing questions, 3) basic crop production information, 4) management labor, a nd 5) yield. Interviews with agroecosystem managers generally lasted from 20 to 25 minutes, and the majority of this was for measuring the labor inputs elicited by di ffering managements. Management labor was divided into four pract ices used for direct field management. Breaking down labor into manage ment practices allowed for preci sion, as well as a measure of the overall effects of management on individual practices. The f our management practices were: fertilization, weed control, insect control, and disease control. We selected management practices that are common compone nts of field management. The practices must require labor input that is affected by management approac h. We did not include pre-plant tillage, for example, because all growers hire d tractors to prepare equally. S eeding and harvesting also were done equally and management approach played no clear role in these practices. After documenting eligibility and obtaining consent, a quick orientation and background assessment quelled hesitations of the participants elucidated doubts, and assisted us in asking more appropriately phrased questions. Presum ably, this would allow us to gather the forthcoming labor data in a more efficient a nd precise manner. One day of labor was set the length of time it takes to complete the task for th e day. During most of the season, this is about 4 to 6 hours in the morning. On other days, it can be longer or shorter.

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37 Asking about tasks within individual mana gement practices divided the labor data collection. Farmers, like all managers, break up their practices into da ily tasks throughout the season. We exploited this organization conveniently to procedurally ascertain labor inputs. We would first ascertain the order, pr ocedure, and nature of a particular management practice. After this was clear, we could begin to gather data about labor inputs phrasing our question individually based upon a growers management style. The typical number of instances a particular task was carried out, the number of workers required, and the number of days with these workers was investigated on a per month ba sis. Inquiring on a pe r month basis accounted for labor variability during the season, and thus increased accuracy in labor accounting. Finally, in January 2007, we resumed the last section of the interview. Land under sesame, seed used, and yields in quintales (1 Qt=46 kg) per Mz were do cumented. Additionally, we asked for any related commentary. In order to compare labor inputs for manageme nt practices, we calculated them as simple labor amount of man-days/Mz and as a percentage of the total labor. Labor amounts include the labor required by individual management techniques and the agroecosystem ecology it created. Assuming that growers limited labor is distribut ed according to management needs, percent of total labor might indicate di fferences in the nature of agroecosystems under differing managements. This is especially true wher e qualitative differences of techniques within approaches are controlled. Soil Quality Assessment To test the h ypothesis that soil quality w ill be positively correlated with increasingly ecological management, we assessed soil quality th rough the use of five individual indicators. These indicators assess the capacity of these andisols to support the function of sustainable plant production. The utility of multiple empirical indi cators to assess the con cept of soil quality for

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38 sustainability has been established for some time (Bellotti 1998, Doran and Parkin 1996). The natural resources conservation arm of the USDA (2001) is promoti ng soil quality assessment as a conservation-planning tool. New Zealands government has found soil quality to be useful as a national planning and assessment tool. (Lilburne et al. 2004). The most current methodological research revolves around prioritizing the utility of different indicators for combination into an index (Shukla and Ebinger 2006, Yemefack et al 2006, Xu et al. 2006, Erkossa et al. 2007) and for delimitation of differentially managed fiel ds (Monokrousos et al. 2006). There are many different indicators. Nonetheless, there persis ts a lack of a tested, accepted, and recognized index. There are several additional reasons why we decided against using or constructing an index. Constructing our own, or using any part icular index, precludes close comparison with other data where different indexes or uncombine d indicators have been used. Furthermore, analyzing individual i ndicators responses to management might more clearly elucidate managementsensitive indicators for andisols. In building our own minimum data set (MDS) of indicators, our fi nancial and technical capacities were a major determinant. Indicators n eeded to be affordable, practically collected as soil samples, and reasonably analyzable given the limited expertise, laboratory space, and technology available for soil analysis of the researcher and Laboratories Quimicos SA (LAQUISA, Carreterra Leon, km 33.5). The indi cators needed to be plain and common enough to be potentially compared and understood by various grower, academic, and development audiences. Additionally, they mu st be contextually appropriate (Karlen et al. 2003). Thus, we specifically studied a review and investigation by Andrews and Carroll (2001), a comparative management study on Nicaraguan andisols (Cas tillo and Joergenson, 2001), a practical manual

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39 of the USDA (2001), and an Organization for Tr opical Studies (OTS) agroecology field course guide (Swisher 2003). These sour ces shared similar restrictions goals, or audiences as this study. Karlen et al. (2003), and Herrick (2000 ) were consulted for general procedures and considerations in choosing a contextually appr opriate and indicative se t of biological, physical, and chemical soil quality indicators. The indicators are percent organic matter (%OM), phosphorus availability (PA), aci dity (pH), bulk density (BD) and biotic activity (BA). Soil Sampling To m easure the indicators, we first collected soil samples as described in the protocol in Appendix A. The soil sampling design was a systematic Z transect, with sub sampling, across contiguous fields meeting the operational agroecosystem requirements. We stayed 5 paces from field borders to minimize confounding factors (i.e. tr actor marks etc.) With this design, we could move along expeditiously, cover the entire fi eld without bias, and avoid damaging crops. Whenever a field was not recta ngular, we divided the field into approximately three equal land areas and adjusted the lengths of th e 3 diagonals (of the Z) accordingly. For %OM, PA, and pH, we collected 7 subsampl es with a manual soil auger to a depth of 30 cm across each diagonal. These 7 subsamples (about 2/3 liter each) were homogenized in a bucket to create 1 sample per diagonal. The 3 resulting diagonal samples would serve as the 3 subsamples (about liter) for each replicate. The subsampling increased the precision of our measurements, since there would be 1 sample value per field. Diagonal subsamples were delivered in sealed, marked plastic bags. For BD and BA, we collected 7 samples across the field on the same Z transect. After using a shovel to dig a flat-wal led hole of 40 cm depth, we used a hammer-in style soil corer (100mm3 5-cmdeep cylindrical core) to extract a sa mple from the sidewall. Core ends were sharp and in good condition. BD samples were co llected at a 0-15 cm and 15-30 cm horizons.

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40 Biotic activity samples were collected at the 2.5 7.5 cm depth from the top of the soil. The protocol was realized with 2 subsamples on the 1st diagonal, 2 subsamples on the 2nd diagonal, and 3 subsamples on the last. These 7 sub-samples would be averaged to arrive at one response value for each agroecosystem. Soil Quality Analysis All analyses were done at Laboratorios Quim icos S.A. (LAQUISA) chemical laboratory. It is the foremost environmental testing laborato ry in Nicaragua. The six indicators follow. Descriptions include the ecological rationale for using the indicat or, the method of analysis, and the criteria for interpretation. Percent organic matter (%OM) measures the am ount of organic matter in the soil. The %OM will have an overriding effect on all soil func tions and properties. We used the WalkleyBlack (1969) method (with no procedural deviations ) to measure the % organic carbon of highly stable humic and fulvic acids. We used a convers ion factor of 1.74 to translate this into %OM of the soils for ease of communication to a wide range of audiences. An increasing quality of soil is indicated by an in crease in the %OM. Acidity (pH) is also an ecosystem state variable that plays a role in nutrient availability, biological presence and control, and aluminum and iron toxicity to plants. Acidity was determined using 2 parts deionized water solution to 1 part topsoil sample. pH was detected by calomel electrode. Lower pH soils indicate poorer soils. Phosphorus availability (PA) is of particular interest in allophane soils with high phosphorus P sorption capacities. High sorption cap acity is due to a very high surface area of allophane and its affinity to fix P anions from the soil solution (Parfitt 1989). High fixing capacities do not allow P to move freely through the so il solution and be taken up by the plant roots (Parfitt 1989). Determining th e potential availability of P is critical to the functional

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41 capacity of soils for sustained production. To dete rmine the potential availability of P to the plants, a P fractionation was performed at L AQUISA using the Tiesse n and Moir (1993) modification of the Hedley et al. (1982) fract ionation procedure. Lawrence and Schlesinger (2001) have used it successfully to trace changes in soil P availabi lity in tropical soils with high P fixing capacities. Finally, I confirmed the a ppropriateness of the meth ods for the andisols under study with an expert (Nicholas Comerford, personal communication, 2006). Four main fractions are analyzed. The fi rst 2 fractions are ea sily absorbable and colloidal/solution P. These represent relatively available soil P. The last 2 fractions are relatively occluded and fixed, and therefore unava ilable. Increasing amounts of resinP and NaHCO-P in the first 2 fractions and increasing percentages of total P in the first 2 fractions would primarily indicate an incr easing soil quality. More P in th e first 2 fractions indicates a greater capacity to sustain str ong plant growth. Using a P fr actionation method to proxy plantavailable P does not take into account the symbio tic uptake pathways of P, which are known to be important in providing plants with P. The amount of biotic activity (BA) serves as a very importa nt indicator of soil quality, especially where nutrient availability is driven mostly by biotic processes (Drinkwater et al. 1995, Monokrousos et al. 2006). Biotic activity is a major component of a higher quality soil, especially where this is the primary nutrient tran sformer and controller of rhizosphere pathogens. Microbial activity was measured by way of basal respiration, which is the amount of carbon dioxide (CO2) respired by soil microbes. We used a soil corer in the 2.5 cm-7.5 cm area of the topsoil to gather and transport a soil core for direct use in incu bation jars. The core was placed directly into the jar to minimize perturbation and oxidation. Basal resp iration was measured after 24 hr incubation in clean 1gallon glass jars with a soil core, a 20 ml portion of water, and

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42 10ml 1M NaOH. This was done in a non-air-cond itioned laboratory with natural lighting at the UNAN-Leon, Campus Agropecuario. Samples remain ed in the corer for collection in order to minimize perturbation and oxidation. CO2 captured in the NaOH solution was delivered to LAQUISA in the Paraffin and maskingtaped Gerber baby-food bottles as NaOH receptors within the incubation ja r. Samples were daily delivere d to LAQUISA for titration with concentrated HCL. The main physical quality indicator is bulk density (BD). G ood soil structure is essential to prevent andisol erosion, pudd lingfacilitated disease, r oot stunting, and anoxia to soil biological communities. We decided that bulk de nsity is a good general measure of structure. We therefore measured bulk density at the tops oil (0-15 cm) and subso il (15-30 cm). Bulk densities were determined by weighing after dr ying in an oven at 110 C for 24 hours. The soil core that collected the sample determined the volume. The first 3 replicates accumulated 24 hrs of drying over two weeks (as opposed to one 24 hr period), since we were not sending these to LAQUISA until regular electricity for ovens fa iled at the UNAN-Leon. Since compaction is a concern, improving soil quality will be evidenced by decreases in bulk density. Bulk density cores were emptied into brown paper bags. Th ese were delivered to LAQUISA and transferred directly into an oven. Statistical Analysis Each agroecosystem was placed in the conventio nal (n=10) or ecologica l (n=8) treatment. To compare the means of independent variables, t-tests were performed when the variables were normally distributed. T-test variab les were tested for homogeneity of variance using a Levene test. Independent variables that did not ini tially meet assumptions of normality were log transformed. A Shapiro-Wilke test (p<.05) was us ed to test for nonnormality. If independent variables still did not meet assumptions of nor mality, or sample sizes were too small, a Mann-

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43 Whitney test was used to test for differences in the medians of the samples. Considering the normal amount of variability in an observational study and the small-sample size, statistical significance is set at p < .10. All statistical analyses were done using SPSS (Chicago, Illinois). 1. Dependence on synthetic, chemical vs any alternative pest control (8) 2. Dependence on inorganic vs. organic fertilizer (6) 3. Level of on farm recycling (5) 4. Level of conservation of soil and its properties (6) 5. Level of crop diversity in time and space (5) *6. Level of water conservation (5) *7. Level of fossil fuel usage (5) *8. Level of environmental protection (4) 9. Dependence on commercial, modified vs. local, traditional seed (4) Figure 3-1. Original management i ndicators. Number of responses out of 10 is in parentheses. 1. Soil Conservation (Level of conser vation of soil and its properties) ( 6) 2. Fertilization (Dependence on inor ganic vs. organic fertilizer) ( 5 ) 3. Pest Control (Dependence on synthetic, chem ical vs. any alternat ive pest control)(4 ) 4. Diversity (Level of crop di versity in time and space) (3) 5. Recycling (Level of on farm recycling) ( 2) 6. Seed (Dependence on commercial, modified vs. local, traditional seed) ( 1) Figure 3-2. Final management indicat ors. The number in parentheses indicates the point value. Higher values indicate more influential indicators. Indicator points Res ponse points = Indicator Score Soil Conserv. 6 3 = 18+ Fertilization 5 5 = 25+ Pest Control 4 5 = 20+ Diversity 3 3 = 9+ Recycling 2 3 = 6+ Seed 1 5 = 5+ --------Sum Indicator Score = 82.99 ==Standardized Index Score = 13.833 6 indicators 6 Figure 3-3. Index scoring example. A hypothetical response with the highest ecological score is shown.

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44 CHAPTER 4 RESULTS Census Population The census population consists of 18 total replicate fields in a binom ial distribution. There is a notable absence of manageme nt scores between eight and ten (Figure 4-1). The lowest index score was 4.333, and the highest was 13.833. Energy Inputs and Productivity Table 4-1 presents m edians and pvalues for labor (both as absolute inputs and as a percentage of total) and labor productivity using the Mann-Whitney -U test. The sample sizes of the productivity variables (Table 4-2) differed fr om those of labor input s (n=10 for conventional and n=8 for ecological). This is because only seven of 18 interviewed growers actually planted late-season sesame. Additionally, within those seven, some did not manage for insect pests or disease. We could not calculate la bor productivity for these growers. Labor inputs for overall management were not significantly affected by management regime. Of the four practices, only for disease and fertilization did management approach significantly affect the amount of labor required. In both cases, ecological management required more labor. Though not significan tly different for disease c ontrol and fertilization, the proportion of total labor alloca ted to insect pest manage ment significantly differed by management type. Conventional producers expended a greater proportion of their time managing pests than ecol ogical producers. There were no significant di fferences in labor productivity between conventional and ecological management.

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45 Ecological Indicators and Efficiency Table 4-3 presents means and p-values of soil quality indicators and their ecological efficiencies. For all independent variables, the means of ten c onventional replicates and eight ecological replicates were tested for differences using a t-test for independent samples. Soil quality indicators and their efficiencies did not significantly differ in any case. Output The m edian yield for five conventional ag roecosystems was 10.125. The median yield for the ecological agroecosystems was 12.000. Th ese did not significantly differ (p=.195). Figure 4-1. Histogram of replicate management index scores. Scores below and above 8.665 indicate conventional (n=10) and ecologi cal (n=8) agroecosystems, respectively.

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46 Table 4-1. Results of Mann-Whitney U test for labor amounts (man-days/Mz), percent of total labor (%), and labor pr oductivity (Qt/(man-day)) between conventional and ecological growers. P-values calculated for overall and per-practice management. (@) and (*) indicate significance at p=.100 and p=.050, respectively. Table 4-2. Sample sizes for la bor productivities per practice. Variable Median P-value Conventional Ecological Overall Labor 19.500 27.700 0.230 Productivity 0.530 0.444 0.439 Fertilization Labor 3.250 5.750 0.050* % of total 13.940 25.690 0.155 Productivity 4.091 16.091 0.699 Weeds Labor 15.083 15.600 0.859 % of total 69.620 64.540 0.374 Productivity 0.764 0.437 0.439 Insect Pest Labor 2.476 1.440 0.195 % of total 17.690 6.360 0.090@ Productivity 6.863 5.333 0.380 Disease Labor 0.375 1.798 0.067@ % of total 0.810 4.580 0.143 Productivity 11.750 48.000 0.157 Variable Treatment Conventional Ecological Fertilization 5 2 Weeds 5 2 Insect Pests 5 1 Disease 4 1

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47 Table 4-3. Calculated p-values of soil qual ity indicator and efficiency means between conventional (n=10) and ecological (n=8) farm s using t-test for independent samples. (@) and (*) indicate significance at p=.100 and p=.050, respectively. Variable Mean P-value Conventional Ecological % OM 2.301 2.231 0.802 Efficiency 0.115 0.071 0.161 Acidity (pH) 6.460 6.566 0.271 Efficiency 0.331 0.217 0.196 Basal respiration (mg/cm3) 11.031 11.081 0.985 Efficiency 0.474 0.342 0.498 P 1st fraction (ug/g soil) 9.941 12.396 0.599 Efficiency 0.494 0.410 0.742 % of total P 1.268 1.920 0.320 Efficiency 0.001 0.001 0.990 P 2nd fraction (ug/g soil) 94.128 76.668 0.362 Efficiency 4.270 2.396 0.195 % of total P 11.456 11.217 0.904 Efficiency 0.601 0.605 0.266 P 3rd fraction (ug/g soil) 342.081 298.425 0.323 Efficiency 16.820 9.501 0.121 % of total P 45.128 44.547 0.922 Efficiency 2.345 1.472 0.187 P 4th fraction (ug/g soil) 248.879 229.283 0.537 Efficiency 12.323 7.212 0.144 % of total P 32.991 33.797 0.741 Efficiency 1.689 1.117 0.203 P total (ug/g soil) 729.440 645.520 0.305 Efficiency 37.351 21.340 0.112 Bulk density (0-15) cm (g/cm3) 1.175 1.210 0.393 Efficiency 0.764 0.040 0.109 Bulk density (15-30) cm (g/cm3) 1.166 1.990 0.516 Efficiency 0.059 0.040 0.217

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48 CHAPTER 5 DISCUSSION Census Population Several unpredicted reasons accounted for a sm a ller than preferred sample size. Low prices and broken contracts in 2005 kept many farmers from sowing sesame in 2006. During our sampling period, some growers were in Costa Rica as hired labor instead of cultivating their own fields; therefore, we could not interview them The paradox of small holders neglecting their fields in favor of casual labor has previously been tied to financi ng and labor constraints (Alwang 1999). Renting of small parcels is co mmon, so that finding farms managed by the same person, in the same manner, for three years became increasingly difficult. Finally, increased peanut prices had caused land prices to increase, so that some farmers were either renting their lands to largescale peanut growers or land renting was now prohibitively expensive. Agroecosystems around Leon meeting our operati onal needs and logistical possibilities consequently became difficult to find. The sustainability of small-scale sesame in Leon is seemingly negatively affected by economic and agricultural trends in the area. The distribution of the census into two groups, separated by an absence of scores between eight and ten, indicates that sma ll-scale growers here do not often mix approaches equally. They tend to follow a more singular management appr oach. This may be a result of growers connections to cooperatives. Ec ological growers connected to Asociacion de Productores Ecologico de Nicaragua and conventional growers connected to Cooperativa La Esperanza may have been absorbing similar knowledge th rough their cooperative. Growers outside these cooperatives may be receiving info rmation from diffuse or different sources with a less unified message, increasing the likelihood of more mid -range management scores if a population of these independent growers is examined.

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49 Labor Inputs and Productivity All Management Our stated hypothesis w as that total labor inputs would be higher, and labor productivity lower, in ecological management. This hypothesi s was not supported by the data of total labor inputs and productivity. Only seven total va lues were used to compare overall labor productivity, and this weakens the validity of th ese results. Sample size for labor inputs was adequate, and non-significance can be partially attrib uted to sizeable variab ility in labor within treatments. Two conventional growers, for exampl e, used no labor for pest control, while an equal amount used nine man-days. This variability suggests that total labor was driven primarily by individual decisions in pursuing practices. When summed, this variability confounds a possible effect of management. Individually perceived benefits and costs of labor-intensive practices may drive that variability. Individuality is mo re likely when standardized recommendations for management are unavailable or growers are relatively new to the crop. Both conditions are common with sesame in Leon. Additionally, individual economic ability may affect the labor dedicated to practices. Even though we assumed economic ability to be generally similar among farmers, even a small difference can have a di sproportionately large impact when economic capital is small. For exam ple, buying synthetic ins ecticides this year, and using labor to apply it, can vary depending on the previous years profits or unforeseen expenses during season. We did not cont rol for these confounding factors. Measuring no significant difference in total labor is rare. Studies, such as Pimentel et al. (2005) and Karlen et al. (1995) more commonly find overall labor to increase with more ecological management. Those results confirm common perceptions of ecological management in temperate areas (Lotter 2003). For the fewe r studies examining manual labor as the main energetic input, at least one study found lower labor requirements with ecological management

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50 (Mendoza 2005). Others have found ecological mana gement practices to be more labor intensive (Kaltsas et al. 2007). Even though data is repo rted less clearly than Mendoza (2005), Rasul and Thapa (2003) do mirror our finding of no significant di fferences in labor input s. However, their study subject was small-scale rice agriculture. Whether the actual management techniques, or an agroecosystems ecology (weeds, insects, etc.), determined total labor inputs was not investigated. This is because total labor includes various practices with potentially different techniques, ma king it particularly difficult to separate the effect of ecology from technique. Because both managements include the same practices, we can safely say that agroecosystem ecology was not different enough to precipitate changes in total labor. When technique differences are el iminated, and the proportional importance of labor per practices is measured, assessing if agroecosystem ecology is different between managements is more feasible. A differe nt proportion of total labor for a practice when techniques are similar, and total labor is not significantly different as it is here, indicates that management is responding to different agroecosystem ecology. Here we examine practices individually to assess whether technique differences or ecologi cal differences affected labor requirements. Fertilization Fertilization was significantly different between m anagement. Ecological management required more labor because the technique was mo re labor intensive. Collecting and spreading manure, composts, fertilizer teas, or other orga nic fertilizers is often documented as requiring more labor as tractor time (Karlen et al. 1995) or manual input (M endoza 2005). Two growers were actively and consistently pursuing manure fertilization. These growers registered the highest labor values, and had a strong influence on our measurement of labor in ecological

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51 agroecosystems. The results indicate that ecolo gical fertilization techniquesespecially where manure is involvedare more labor intensiv e than those of conventional management. While cover cropping can reduce labor compared to other organic fertilization techniques (Drinkwater et al. 1998), managing cover crops still requires more labor than inorganic fertilization (Pimentel et al. 2005) Our results do not address th is issue because cover crop use was completely lacking. During the rainy season no participant was willing to cover crop any available land if it could be cash cropped. Additionally cover cropping is most feasible when seed and information are available, neither of wh ich did we observe or seek. This highlights the fact that laborsaving organic fert ilization methods are not always applicable to th e small-scale, tropical context, for the reasons mentioned. Most growers seemingly relied on incorporated residues and natural andisol fertility to an extent. It is true that ma ny conventional growers were fertilizing inorganically, and many ecological growers were applying organic fertilizers. Yet given the observed amounts, fertilization seemed mostly supplementary (unc onfirmed). Relying on incorporation and soil fertility may be an appropriate strategy for all growers. Fertilizing or ganically requires higher labor inputs, inorganic fertilizer s can be relatively expensive, a nd there was no advantage of in terms of labor productivity of pursuing one fe rtilizer management strategy over another. Disease Labor for disease m anagement practices diffe red significantly between managements, with ecological management requiring mo re labor. We attribute this to technique differences in controlling the primary sesame pathogena Phytopthera fungus. Conventional management used industriallysynthesized fungicides, sin ce it was relatively accessible and needed only in limited quantities if properly app lied. Ecological growers, on th e other hand, were either liming the soil around the plant base or removing w hole plants to prevent transmission. Liming

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52 presumably raised pH enough to kill off the so il borne fungus. Diluting concentrated fungicides in water and applying with a manual sprayer was apparently more labor efficient than hauling bags of lime or pulling plants out by hand. The higher labor requirements of ecological disease control and fertilization techniques could be due to concentration. Inorganic nutrients are more concentrated than organic ones. Similarly, synthetic substances are more concentrated fungicides than lime. In both cases, the more concentrated substance required less labor. Weeds Finding no significant difference of weed m ana gement labor between managements can be explained by the similarity in practices. All growers used animal-drawn cultivation followed by manual weeding, except for one ecological grower who used goat herbivory and one conventional grower who applied herbicides. Hence, 88% of farmers were managing weeds ecologically by defacto Understandably, labor inputs were not affected by management specific technique. Most studies, Clements et al. (1995) and Loake (2001) for example, have found weeding labor to be higher with ecological management. In those studies, however, cultivation substitutes for herbicides. In our study context, strategies were similar and did not substitute for herbicides. Differences in labor requ irements were consequently not seen. This exposes a weakness in our management index. Grouping all pest management under the same indicator question resulted in a few erroneous readings of fully conventional pest control, when weed control was not conventional. Our management definitionsbased on internal versus external perspe ctivesdo not clearly account for ti llage as either ecological or conventional. It raises the question whether not using herbicides, wit hout any other deliberate intervention, should be equated w ith ecological management. We contend that it should not, and further agroecosystem study should more fully c onsider the degree of purposeful ecological manipulation of weed populations in characterizing management.

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53 Percentage of total labor used for weed c ontrol was not significan tly different between treatments, despite similar techniques. This s uggests that weeds were not more prominent in either system. Organically managed tomato fi elds have shown more weeds than conventional fields as a result of differing agroecosystem eco logy (Clark et al. 1998). These authors suggest increased nutrient cycling to all plants, from greater microbi al activity and organic matter, promoted weeds under organic management. Ne ither of those ecological aspects differed by treatment in our study. The agroecosystem ecology in respect to weeds was, hence, not very different between managements. Weed control la bor as a percentage of total was consequently not affected. Insect Pests Results f or this practice were interesting: labor as man-days/M z was not significantly affected by management but percentage of tota l labor was. Both managements apply liquids using a backpack sprayer and removing insects ma nually from plants. A case for similarity of technique could be made based on this. What they were a pplying was different, however. Ecological growers applied Neem/ Capsicum/ Allium teas to repel pests, while conventional growers applied industrially synthesized insecticid es. Because of the very different ecological consequences of insect repellants versus insec ticides, our opinion is of differing techniques for combating insect pests. Additi onally, diverse cropping and trap crops are strategies for insect pest management in ecological management not pursued in conventional management. From this point of view, a lower percentage of labor for insect pest management suggests one of two things. Firstly, ther e could be fewer pests in ecologi cal management. Theory would predict this, since ecological management can lower pest populations by increasing beneficial populations (Mader et al. 2002). Ecological farmers often repor t fewer pest problemsand consequently less labor for insect pest manageme ntthan their conventiona l counterparts, despite

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54 not using synthetic insecticides (Lotter 2003). Our results, because techniques are distinct enough, may alternately be explained by higher labor efficiency of repellants. Practical experience shows that repellants and other nontoxic approaches are less effective and may require more labor for the same effect (B uss and Park-Brown 2006). One might assume botanical repellants to be more labor intensiv e because they breakdown faster, do not kill, and may require more applications than synthetic in secticides. Based on th is assumption, less labor proportionally with repellents w ould be explained by smaller pe st populations in ecological agroecosystems. This indicates different ecology of ecological and conventional agroecosystems. Kaltsas et al. (2007), however find technique differenc e to induce higher labor needs in organic olive groves. The fact that labor as man-days/Mz did not differ significantly between management conflicts the proportional labor findings. Normaliz ing on a percentage scale may have made the data more amenable to statistical analysis th an when presented as man-days. Moreover, the effect of outliers would be diminished when labor is presented as a percentage. Soil Quality and Ecological Efficiency Managem ent did not affect soil quality indicators and their effi ciencies. This contradicts our hypothesis and most literature predicting ecol ogical management to result in greater soil quality. Three reasons may explain this discrepancy. A fundamental premise of soil quality studies is that soilaffecting inputs will be distinct as a result of discrete management. Moreover, the magnitude of soil quality change depends on the degree of input dissimilarity (quantitative or qualitative) between managements. This premise is not fully met in the study cont ext, since all management is lo w-input and systems are rather similar. For example, though fertilizer material s and labor were different between management, most agroecosystems seemingly relied to a large or complete extent on natural soil fertility and

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55 incorporated residues. Both managements ma y have had, for all ecological purposes, a common fertilizerthe soil itself. Failing to measure lower pH in conventional agroecosystems suggest that ecologically significant rate of inorganic fertilizers were not applied. Moreover, percent organic matter itself was unaffected. This is th e indicator most consistently associated with distinction in inputs. Other evid ence for similarity was in biotic activity. Fewer pesticides in ecological agroecosystems can result in higher soil biotic activity (Plenchette et al. 2005). Since percent organic matter was not different, any differe nce in soil biotic ac tivity would have been more directly tied to differences in pesticide inputs. We measured no difference in biotic activity, indicating similar pestic ide inputs between management. The ecological context of this study provides a second possible explanation for a lack of an affect. The ecological metabolism in tropical soils is rapid, especially in the wet-season when most organic additions were made. This makes increasing soil organic matter difficult. Measurable increases in organic matter may accrue only after an extended period of accumulation in many soils (Fleissbach et al. 2006, Monokrousos et al. 2006). This period of accumulation may be longer in the tropic because organic matter is decomposed rapidly. Without increased organic matter in ecological ag roecosystems, correlated increases in biotic activity, P availability, pH, and bulk density may be too slight to detect. This tropical effect must be tempered by known organic matter occl usion by andisols that allows for accumulation. Intense sunlight during the soil-sampling pe riod may sterilize topsoil and cause biotic activity to measure equally between managements. We attempted to minimize sterilization by extracting samples 2.57.5 cm below the soil surface and incubating samples. This may have had little effect. No difference in biotic activity does not, howeve r, mean that biotic composition is also unchanged. Widmer et al. (2006) and Marinari et al. (2006) found changes in biotic

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56 composition with management. Also, soil quality measurements were taken one to two months prior during a dry period. Biotic activity could ve ry feasibly be altogether distinct during rains. Andisols soils provide a unique ecological context even within the tropics. The P fractionation shows that management does not induce functionally salient changes in P availability of andisols. Ot her studies have found management by way of organic matter, to affect P fractions (Salaque et al. 2004, Reddy et al. 2005). Our re sults differ from Castillo and Joergenson (2001) who found less to tal P with ecological manageme nt in andisols around Leon. Their sample size was larger th an ours, they used a differe nt P extraction method, the soil textures were somewhat distinct and the effect they found was not terribly immense. This may explain the discrepancies between our results and theirs. Find ing no difference in P fractions based on treatment supports He et al. (2006) and Reddy et al. (2001). They argue that as P fixing capacities become greater, P dynamics are more infl uenced by inherent soil properties than by management. Our results cannot directly support these studies because they experimentally altered percent organic matter to proxy ecological management. We did not measure such a change necessary to validly support their conclusions. Finally, confounding factors may have played a role. Deep tillage from the cotton years left soils with sizeable differences in organi c matter. Given primitive mechanization, already high amounts, and a tropical ecol ogy, three years may be insuffici ent for ecological management to increase organic matter. Additionally, high pesticide applications floating in from adjacent peanut fields may have affected biotic activity. Finally, we did not sample fields at the same point in their tillage schedule. Some had been disked once, others twice, and some none. In combination with random cattle and human trampling, this likely confounded the effect of

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57 management on bulk density. Since organic matt er did not differ between treatments, it is unlikely we would have measured a signi ficant difference in bulk density anyhow. Yield Sesam e yield was not affected by management regime. The sample sizes for each treatment were extremely small, so this finding should be taken with some caution. Having said that, the salient point here is th at ecological yields were not reduc ed as compared to conventional yields. This contradicts extensive reviews by Stanhill (1990) and Lotter (2003) predicting slight yield losses with ecological management, as well as what seems to be a commonly held belief among agricultural scientists. At the same time it lends some support to Rasul and Thapa (2003) and Mendoza (2004) that ecological management does not necessarily lead to yield reductions in the developing context. Many determinants of yield did not seem to differ in an ecologically significant manner between management. There was no difference in soil quality indicators between managements. Although there is some evidence for greater insect pest populations in conventional agroecosystems, no growers reported them to be uncontrollable or economically damaging. Labor used to manage weedswhich can depress yi elds when herbicides are not used (Clark et al. 1999, Lotter 2003)was not more prevalent in either management. Both agroecosystems were likely limited by P and seemingly used soil reserves as their ma in nutrient source, though this is unconfirmed. Finally, both agroecosy stems used the ICTA-R and Linea 2000 sesame cultivar. The Drinkwater et al. (1995) hypothesis that different managements may ultimately lead to similar agronomic response was not test able in our study because managements were too similar. Finding no significant difference in yiel d was not, therefore, entirely surprising.

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58 Conclusions The objectiv e of this study was to ascertain wh ich type of management is likely to produce a more sustainable agroecosystem. Our resu lts indicate that sustainability of sesame agroecosystems in Leon did not differ between conventional and ecological management. The major sustainability parametersoverall labor in puts, soil quality, and yieldwere mostly unaffected by management. Neither management is more likely to augment labor productivity of small-scale farming through intensification or ex tensification. Similarly, soil quality for longterm productive capacity did not differ by mana gement regime. The economic and ecological sustainability consequently did not differ in a ny ecologically significant manner, nor were their major labor reductions to improve quality of life. Sustainability was likely similar because in -common restraints of small-scale sesame production on tropical andisols we re more determinant of sust ainability than management regime. For example, because neither manageme nt adequately addressed energy limitation of weed control in small-scale systems, high la bor requirements were not lessened by either management. P availability, in another exam ple, was also not improved by a particular management. Beyond strategies of each manage ment, it is unclear whether any extension service had informed farmers of P fixation of an disol or of saturation techniques to overcome such fixation. In the end, all agroecosystems were of relatively low energy and information input. From experience we know one of thes e should increase to promote sustainability. Our conclusions do not support the hypothesis of Altieri (2002) and others that ecological management will increase small-scale, tropical sustainability over conventional management. We note that ecological management research has not been as institu tionally supported as conventional management; comparing the sustainabi lity may be of limited utility until ecological strategies are improved (Lotter 2003). Still, results suggest that development organizations

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59 should not fully veer from traditional efforts to improve access to energy, land, and financing in favor of implementing ecological management. Ecological management, at least in Nicaraguan sesame, does not seem to be a panacea for the low sustainability of small-scale, tropical agriculture. Additionally from the comments of growers, it seems that market access and negotiating power may be a more powerful determinant of sesame sustainability in Nicaragua than management regime.

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60 60 APPENDIX A PROTOCOLS I. Score each indicator= (indicator value X response value) II. Sum scores of indicators fro overall management score III. Divide by number of indicaors(6) to standardize final score IV. Determine range of possible values Determine Management Score for Replicate I. Assign point value(1-6) to indicators based on rank(highest rank=highest value) and to indicator question responses by farmers(most ecological=highest value) II. Determine management score for each replicate A. If 2 simultaneous modes for ranking responses of 1 indicator average values and use quotient as mode B. If 2 indicaotors with same rank(as established by mode) choose indicator with more top-rankings as higher rank Determine Relative Importance of Indicators I. Ask 9 origional and 2 new experts to rank indicators from 1 to 6 in oder of increasing discernment capability II. Determine mode Finalize List of Useful Indicators I. Compose indicators as 8 directed questions with reponse range II. Pre-test on similar farmers and first 3 of study III. Discard contextually invalid or agronimaclly nonsensical indicators Assemble List of Indicators I. Ask 7 UF and 4 Nicaraguan agriculture experts to freelist the 6 criteria most useful in discerning between managements II. Keep those mentioned by 50% and near ly 50% but with self-judjed potential Figure A-1. Protocol for mana gement index construction.

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61 Interview Closing and Yield A. Close with asking participants have any further questions B. Restate commitment to bring back soil analysis results and gather yield data later C. Gather sesame plot size, seed type, yield, and commentary on next visit A. Inquire on how many distinct o ccassions within the season a task is performed B. if more than once, establish wherein the season each occassion occurs C. For each task occassion, askhow many days,with how many men does the task last Labor Inputs Documentation I. Ask farmer about the progresion of tasks within each practice II. Use this and background information to formulate labor questions individually III. Collelct labor data about each task within a particular practice A. 1 "day" of work is not a set # of hrs but a relative measure to each tarea B. Labor inputs should be for plot size of sesame this year C. Responses should be for a "typical" year with ackowledgement of variab ility Background Information I. Ask question in informaction general de cultivos II. Ask questions in mano de obra III. Clarify 3 technical points before labor data collection Formal Participant Orientation I. Explain objectives and significance of study II. Emphasize private nature of this study without prejudg. of "better" mgmt.. III. Clarify that index covers all crops and labor, yield specific to sesame Eligibility Establishment I. Ask requierimientos generales to document fulfillment of operationalized agroecosystem concept Participant Consent I. Deliver IRB consent form, read aloud if necessary II. Obtain written consent Figure A-2. Interview protocol

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62 IIA. Use soil auger to gather soil sample to 30cm, do not clear off top. IIB. Place each sample into a colelctive bucket IIC. Homogenize 7 sub-samples to extract 1 sample for each diagonal IID. Place and mark approx. 1 liter of soil samples per diagonal IA. Use hammer corer to extract (0-15,15-30)cm BD cores from sidewall in 50cm hole IB. Use same instrument to extract basal respiration core from 2.5-7.5cm in soil IC. Immediately place BD samples into labeled brown paper bags and cap the basal respiration cores to transport in core sleeve Taking Samples I. For bulk densities(BD) and basal respiration, take individual samples every third point II. For %OM,Pfrac, pH take 1 collective soil sample at every point Locating Sampling Points I. Visually divide field into three equal area, accomadate incongruities II. Pace each of the 1/3 section diagonals(making a Z across field) individually III. Divide # of paces by 7 to get number of paces b/w sampling pointson each diagonal Characterization of Field I. Affirm texture with farmers and use texture by feel method II. Nofe salient field characteristics III. Enlist farmer in dematcation of study fields Figure A-3. Soil sampling protocol.

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63 APPENDIX B INDEX

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64 Table B-1. Indicator rankings by experts. Expert A (fertilizer source) B (recycling) C (pest control) D (s oil conserv.) E (crop diversity) F(seeds) Jimmy Jones 2 4 1 3 6 5 Peter Hildebrand 3 4 5 2 1 6 Hugh Popenoe 4 2 5 1 3 6 Danielle Treadwell 4 3 5 1 2 6 Robert McSorley 3 4 2 1 5 6 Mickie Swisher 2 6 1 5 3 4 Lori Unruh Snyder 2 6 1 4 5 3 Raymand Gallagher 4 3 6 1 2 5 Freddy Aleman 3 2 5 1 4 6 Alvaro Valle 3 2 4 5 1 6 Roberto Swisher 2 6 1 5 4 3 Mode Mode Mode Mode Mode Mode 2 4 3 1 3 6 Adj. Mode 3 Rank 2 5 3 1 4 6 Points 5 2 4 6 3 1

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65 Table B-2. Individual indicat or scores by replicate. Replicate A(fertilizer source) B(recycling) C(pest co ntrol) D(soil conservation) E(crop diversity) F(seeds) I 1 1 1 1 2 3 II 1 1 3 1 1 3 III 1 3 1 2 1 1 IV 2 1 2 2 2 3 V 3 2 3 1 2 4 VIII 1 2 2 1 2 5 IX 5 2 4 2 2 5 X 1 2 2 1 2 1 XI 5 2 5 2 2 5 XII 5 3 4 3 3 4 XIII 5 3 4 3 3 5 XIV 5 2 5 1 1 3 XV 1 2 1 2 3 4 XVI 5 3 5 2 2 4 XVII 5 3 5 3 2 2 XVIII 3 3 2 2 2 1 XIX 5 3 5 2 2 5 XX 4 3 1 1 2 3

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66 APPENDIX C SEMI-STRUCTURED INTERVIEW REQUIE RIMIENTOS GENERALES 1. Cuantas Mz siembra usted en total? 2. Usa riego en estos cultivos 3. Has sembrado ajonjoli/ptros cultivos en los ultimos tres anos en ese campo. 4. Has usado manejo bien distinto en lo s ultimos tres anos en estos cultivos. 5. Si si cuales practicas han sido bien distintos. INFORMACION GENERAL DE LOS CULTIVOS 1. Cuantas Mz de ajonjoli sembrado este ano y el pasado 2. Que tipo de semilla usan usted? 3. Que cultivos de la primera estan sembrado en el mismo campo del ajonjoli. 4. Como estan arreglado en el campo y como esten sembrado en relacion de uno al otro. 5. Cuanto toma desde que se siembra es tos cultivos hast que se cosechan. 6. Hay un rubro entre la primera y la postrera? 7. Cuanto producio usted el ano pasado por Mz. ENTREVISTA ORAL INTERVIEWIndexing questions 1. A que nivel depiende usted en los abonos organicos vs. quimi cos (urea, compeleto) para fertilizacion? a. solo organico b. mas organico que quimico c. igual d. mas quimico que organico e. solo quimico, sintetico 2. Cual es su nivel de reciclaje de materiales de la finca (excrementos animales, residues, vegetacion de la finca, residuos de las casa)? a) ningun reciclaje b) niveles bajos c) niveles medi anos d) niveles altos e) todos posible reciclado 3. En el control de plagas y maelezas, cuanto depiende usted en el control quimico vs. control cultural, natural (manipulacion de inte raccion y ciclos), o alternativo? a) solo quimico b) mas quimico que natural c) igual d) mas natural que quimico e) todo natural sin quimico 4. Cual es su nivel de actividad en la conservacion de suelos y sus propiedades, sea en el tipo de labranza, agregacion de material organica, plantas de cobertura, barreras de erosion, o otros? a) ningunas actividades activas b) niveles bajos c) nivels medianos d) nivels altos e) en todo practica de suelo se considera la conservacion de suelo, y practic as solo para conservacion de suelo 5. Cual es su nivel de diversidad in tipos de cultivos y combinaciones entre una parcela y ano a ano? a) ningun(monocultivo mismo cada ano) b) niveles bajos(1-2 cultivos cada ano-no cambian por ano o reverso) c) niveles medianos(varios cu ltivos en el ano y cambi an regularmente) d) niveles altos(varios cultivos en el ano y cambian cada ano) e) niveles a ltisimo (maximo variacion en el ano, entre anos, y en el espa cio(varias alturas, relay, etc.)

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67 6. Cual es su nivel de dependencia en semilla s modificada, mejorado, commerciales vs. semillas tradacionales, tipicas, y de variedad local? a). solo tradicionels,t, y local b) mas t, t, vl que modificade, mejorada commerciales c) Igual d) mas semillas modificada commercialmentte y mejorada que tradicional, tipicas, e) todas son comerciales, modificadas, y mejoradas. A=1st mes antes del siembro B=1st mes, C= 2nd mes D=3rd mes despues de sembrar MANO DE OBRA Cuantos trabajadores de aqui de la casa y empleados son.. C=de la casa, E=empleado Para las preguntas siguintes, cu enta una person como .5 persona si solo trabajo medio dia, como los ninos, FERTILIZACION Fertiliza o agrega abonos parafertilizar usted? Por favor cuenatame de sus practicas de fertilzacion? Si usa abonos organicos, por fa vor describa sus collecion y tran sformacion de al materiales organicos. De sus practicas describido, cuales son. Tipo: # todo el tiempo # parte del ia o por dia # de ninos trabajando Mes A B C D A B C D A B C D Tipo: (see key below) # de veces la tareas se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea Se hace al mismo tiempo que otra cosa Month A B C D A B C D A B C D

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68 O=solo abono organico, I=solo quimico fetilizantes, OI=organic y quimicos juntos, CRi = comprar o recibir quimicos, CRo= comprar o recibir abonos organicos, R=recoger material organico para abono, T= transformar material organico= quimicos( ((Fertilizante, urea, completo)) == abono organo, compost, bocashi(compost especial) Usa maquinaria para cualquier de estas practicas o transporte? Si si, mire la tabla M=manual, C=caballo, B=buey, CO=Maquinaria co mbustible, T=transporte, P=practicas del campo rotovetermonocultivador, arado discos o grados OTROS ADITIVOS(no para fertilizacion) Usa usted cualquier otros aditivos al suelo que no sean fertilizantes? Si si por favor describelos C=obertura de cualquier tipo, CA=cal, MO =material organica N=Micronutrients AC=acondicianador de suelo, CRq= compra o r ecibe aditivos, R=recoger material organico, T=transformar material organico Espicificar. Coberturacascar ia de arroz, sacate seco, c obertura, tapa con secate, Material organico= compost, excremento animals; Abono foliares, Usa maquinaria para cualquier de estas practicas o transporte? Si si, mire la tabla Tipo: Descripcion de maqunaria modelo ano # de set completos. # de animals por equipo # de personas necesario para operar maquinaria Tipo: # de veces la tareas se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea Mismo tiempo de fertilizacion o otro aditivos Mes A B C D AB C D AB C D

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69 M=manual, C=caballo, B=buey, CO=Maquinaria co mbustible, T=transporte, P=practicas del campo rotovetermonocultivador, arado, discos o grados MANTENIMIENTO Maniteine usted estos aparatos usados para practicas de manejo. Si si, describe el mantenimiento y mire la tabla. R=reparara aparatos o maqunaria, M=manual, C=caballo, B=buey, CO=Maquinaria combustible, rotovetermonocultivador, arado dsicos o grados PREPARACION de SUELOS Prepara su suelos, labranza. Si si, por favor cuentame como hace esas cosas. M=labranza manual, MC=labranza de maquina Usa maquinaria para cualquier de estas practicas o transporte? Si si, mire la tabla Tipo: Descripcion de maqunaria modelo ano # de set completos. # de animals por equipo # de personas necesario para operar maquinaria Tipo # de veces la tareas se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea Otras notas Mes A B C D AB CD AB C D Tipo: # de veces la tareas se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea Mes A B C D A B C D A B C D

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70 M=manual, C=caballo, B=buey, CO=Maquinaria co mbustible, T=transporte, P=practicas del camporotovetermonocultivador, arado discos o grados MALEZAS Controlo las malas hierbas o malezas usted? Si si describa por favor sus practiceas de manejo de las malezas De las practicas desccribidas cuales son CRhs=comprar o recibir herbicidas sinteticos, in dustriales, CRHN =Compra o recibir herbicidas naturales, R=recoger material para control natura l, T=transformar material organico para control natural, S=sintetico, industrial herbicidas aplicado solo, Nc=her bicidos naturales, commercial aplicado natural, Nf=herbidos natu rales de la finca aplicado solas SN=sintetico y natural juntos, C=Compost de cobertura., CR=cobe rtura de otra, CU=cultivacion Usa maquinaria para cualquier de estas practicas o transporte? Si si, mire la tabla M=manual, C=caballo, B=buey, CO=Maquinaria co mbustible, T=transporte, P=practicas del camporotovetermonocultivador, arado discos o grados Tipo: Descripcion de maqunaria modelo ano # de set completos. # de animals por equipo # de personas necesario para operar maquinaria Tipo: # de veces la tareas se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea Mismo tiempo o uso de fertilizacion, preparacion, o cultivacion, o sembrada Mes A B C D AB CD AB C D Tipo: Descripcion de maqunaria modelo ano # de set completos. # de animals por equipo # de personas necesario para operar maquinaria

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71 INSECTOS Control los insectos( o las plagas) o no? Si si, digame como controla insectos usted en el campo De las practicas describidas, cuales son.. CRhs=comprar o recibir venenos sinteticos, i ndustriales, CRHN =Compra o recibir venenos naturales, R=recoger material para control natura l, T=transformar material organico para control natural, S=sintetico, industrial venenos apli cado solo, Nc=venenos naturales, commercial aplicado natural, Nf=venenos naturales de la fi nca aplicado solas SN=sinte tico y natural juntos, CT=cultivo trampa., BV=barrera viva, F=remover fisicamente Usa maquinaria para cualquier de estas practicas o transporte? Si si, mire la tabla M=manual, C=caballo, B=buey, CO=Maquinaria co mbustible, T=transporte, P=practicas del manejo ENFERMEDADES Controla o no para enfermedaddes (se hi elo, o se quemahongopata prieta) usted. Si si, describe usted su control de Of the practices you describe d (see key), what are the If cultural methods are used, please describe Type: # de veces la tarea se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea Mismo tiempo o uso de fert., prep, insect, maleza, o otros control de insectos Month A B C D AB CD AB C D Tipo: Descripcion de maqunaria modelo ano # de set completos. # de animals por equipo # de personas necesario para operar maquinaria

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72 CRhs=comprar o recibir venenos sinteticos, i ndustriales, CRHN =Compra o recibir venenos naturales, R=recoger material para control natura l, T=transformar material organico para control natural, S=sintetico, industrial venenos apli cado solo, Nc=venenos naturales, commercial aplicado natural, Nf=venenos naturales de la fi nca aplicado solas SN=sinte tico y natural juntos, CT=cultivo trampa., BV=barrera viva, F=remover fi sicamente, CC= contro cu ltural de otro tipo. MECANIZACION Usa maquinaria para cualquier de estas practicas o transporte? Si si, mire la tabla M=manual, C=caballo, B=buey, CO=Maquinaria co mbustible, T=transporte, P=practicas del manejo SIEMBRA, COSECHA, y RESIDUOS Describe como siembra. Describe como cosecha Describe su manejo de resi duos(rastrojo de la cosecha). De las practicas describidas, cuales osn las.. Type: # de veces la tareas se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea otras notos o contro o aplicacion de herbicidas, veneos, compost, prep, o otro Month A B C D AB CD AB C D Tipo: Descripcion de maqunaria modelo ano # de set completos. # de animals por equipo # de personas necesario para operar maquinaria

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73 C=harvest, R= residuo se dejan en sima, I= incorporas los residuos, Q=quemar los residuos, R=recoger para otros usos, S= siembra, CR= comprar recinir semillas, P=prepar semillas, Usa maquinaria para cualquier de estas practicas o transporte? Si si, mire la tabla M=manual, C=caballo, B=buey, CO=Maquinaria co mbustible, T=transporte, P=practicas del manejo Type: # de veces la tareas se hace como describido # de dias la tareas se hace como describido # de personas requirida para hacer la tarea mismo tiempo de otras practicas Month A B C D AB CD AB C D Tipo: Descripcion de maqunaria modelo ano # de set completos. # de animals por equipo # de personas necesario para operar maquinaria

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74 APPENDIX D DESCRIPTIVE STATISTICS Table D-1. Mean and standard deviation of response variables. Response Variables Mean SD % Organic Matter 2.270 0.583 Acidity 6.507 0.216 Basal respiration 11.054 5.128 Bulk Density (0-15)cm 1.190 0.082 Bulk Density (15-30)cm 1.181 0.102 Phosphorous Profile (ug/g soil) P1 14.411 13.549 P2 86.368 37.289 P3 322.678 99.623 P4 240.170 69.641 PT 708.687 165.443 Phosphorous Profile (% of total) P1 1.979 1.887 P2 12.856 5.326 P3 44.819 9.380 P4 33.399 5.205 Soil Quality Indicator Efficiencies % Organic matter 0.12 0.116 Acidity 0.367 0.341 Basal respiration 0.679 0.710 Bulk density (0-15)cm 0.067 0.064 Bulk density (15-30)cm 0.066 0.066 P fractions (ug/g soil) P1 0.654 0.596 P2 5.686 9.078 P3 17.383 19.277 P4 13.195 15.614 PT 39.861 48.030

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75 P fractions (% of total) P1 0.094 0.081 P2 0.805 1.053 P3 2.462 2.172 P4 1.846 1.739 Labor inputs (man-days/Mz) Fertilization 5.518 6.243 Weed control 18.06 13.160 Insect pest control 3.676 5.258 Disease control 0.962 1.300 Total labor 27.242 17.510 Labor productivity (Qt/man-day) Fertilization 27.489 40.786 Weed control 0.703 0.363 Insect pest control 5.487 4.769 Disease control 18.967 16.266 Labor Inputs (% of total) Fertilization 20.362 16.949 Weed control 67.741 20.466 Insect pest control 15.227 15.101 Disease control 3.777 5.183 Production (Qt/Mz) Yield 11.361 1.596

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83 Xu, M., Zhao, Y., Liu, G., Wilson, G.V. 2006. Identification of Soil Quality Factors and Indicators for The Loess Plateau of China. Soil Science 171(5).

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84 BIOGRAPHICAL SKETCH Alvaro Valle earned a B.A. in biology from Tufts University (Medford, MA) in 2003. Bef ore coming to the University of Florida (UF), he worked in the outdoors in various positions. After completing his M.S. degree in interdisciplinary ecology, he plans to join the Horticulture Department at UF, ultimately hoping to infuse some revolution into the agricultural sciences.