How Can Climate Robust Agroecosystems Be Designed? Coupling Agroecology and the Resilience Approach

Generating On-Field Knowledge


Master's Thesis, 2017

105 Pages, Grade: 1,3


Excerpt

TABLEOF CONTENTS

ABSTRACT

LIST OF FIGURES

LIST OF ABBREVIATIONS

1. INTRODUCTION
1.1 AGRICULTURE AND CLIMATE CHANGE
1.2 AGROECOLOGY AS A MANAGEMENT APPROACH
1.3 ENHANCING AGROECOSYSTEM RESILIENCE WITH AGROECOLOGICAL MANAGEMENT
1.4 STUDY AREA
1.5 STRUCTURE OF THESIS

2.THEORETICALFRAMEWORK
2.1. SYSTEMS THINKING AND AGRICULTURE
2.1.2 ADAPTIVE CYCLE
2.1.2 RESILIENCE
2.1.4 ADAPTIVE CAPACITY
2.1.5 ADAPTIVE MANAGEMENT
2.2 MANAGING RESILIENT AGROECOSYSTEMS
2.2.2 ECOSYSTEM SERVICES IN AGROECOSYSTEMS
2.2.3 AGROECOLOGY AS A MANAGEMENT APPROACH

3. FRAME OF RESEARCH
3.1 STATE OF RESEARCH
3. 2 STUDY SITE ALHUÉ

4. METHODS
4.1 DEVELOPMENT OF RESILIENCE ASSESSMENT FRAMEWORK
4.2 DATA COLLECTION AND APPLICATION OF THE MANUAL
4.2.1 SEMINARS AND WORLD CAFÉ
4.2.2 MAPPING

5. DEVELOPMENT OF RESILIENCE ASSESSMENT FRAMEWORK
5.1 BASELINE ECOSYSTEM DIAGNOSTIC ANALYSIS
5.2 RESPONSE CAPACITY ASSESSMENT
5.2.1 RESILIENCE DIMENSION: ABSORPTIVE CAPACITY
5.2.1.1 FUNCTIONAL AND RESPONSE DIVERSITY OVER TEMPORAL AND SPATIAL SCALES
5.2.1.2 EXTENT AND QUALITY OF CONNECTIVITY
5.2.2 RESILIENCE DIMENSION: ADAPTIVE CAPACITY
5.2.2.1 REFLECTIVE AND SHARED LEARNING AND KNOWLEDGE MANAGEMENT
5.2.2.2 SURPRISE AND DISTURBANCE MANAGEMENT
5.2.3 RESILIENCE DIMENSION: TRANSFORMATIVE CAPACITY
5.2.3.1 DEGREE OF SELF-ORGANIZATION
5.3.3.2 COUPLING WITH LOCAL RESOURCES
5.3 CHOOSING ADAPTATION STRATEGIES
5.4. MONITORING AND ADAPTATION OF PRACTICES

6. APPLICATION OF THE FRAMEWORK
6.1 BASELINE DIAGNOSTICS ANALYSIS
6.2 RESPONSE CAPACITY ASSESSMENT
6.2.1. RESILIENCE DIMENSION: ABSORPTIVE CAPACITY
6.2.1.1 FUNCTIONAL AND RESPONSE DIVERSITY OVER TEMPORAL AND SPATIAL SCALES
6.2.1.2 CONNECTIVITY
6.2.2. RESILIENCE DIMENSION: ADAPTIVE CAPACITY
6.2.2.1 KNOWLEDGE MANAGEMENT
6.2.2.2. SURPRISE AND DISTURBANCE MANAGEMENT
6.2.3. RESILIENCE DIMENSION: TRANSFORMATIVE CAPACITY
6.2.3.1 SELF-ORGANIZATION
6.2.3.2 COUPLING WITH LOCAL RESOURCES
6.3 CHOOSING ADAPTATION STRATEGIES
6.4. MONITORING AND ADAPTATION OF STRATEGIES

7.1 DISCUSSION OF METHODS
7.2 DISCUSSION OF RESULTS
7.2.1 DISCUSSION OF THE AGROECOSYSTEM RESILIENCE ASSESSMENT TOOL
7.2.2 DISCUSSION OF THE FRAMEWORK APPLICATION TO ALHUÉ

8. OUTLOOK

9. REFERENCES

10. APPENDIX
10.1 VENSIM MODEL
10. 2 LITERATUREREVIEW
10.3 SYSTEMDIAGNOSTICSANALYSIS
10.4 RESPONSECAPACITYASSESSMENT
10.5 SOILASSESSMENTEXAMPLE
10. 5 RESULTS FROM THEWORLDCAFÉ
10. 6 INTERVIEWS WITH COMMUNITY MEMBERS
10.7 SOILANALYSISRESULTS92

Acknowledgement

I want to express my gratitude to all professors and teachers who participate in the Global Change Manage- ment program and contribute to my overall learning experience throughout the last years. My special ap- preciation goes to Prof. Dr. Martin Welp from the Faculty of Forest and Environment at University for Sus- tainable Development Eberswalde, for his qualified comments on and guidance during my work. With the same appreciation, I want to thank Prof. Dr. Hans-Peter Piorr from the Faculty of Landscape Management and Nature Conservation, for his valuable comments and for opening the possibility of visiting Chile and in- volving with the project.

Special appreciation goes to Andres Martin, Head of the Environmental Consultant Agency Andalué for the intense cooperation during the months I worked in the project.

Finally, I want to thank my parents for enduring and continuous support during the years of my studies.

„We must learn from farmers’ experience. Pragmatic, field-based and farmer-centric education can and must play a key role in making agriculture stronger and more sustainable At the end of the day, sustainable intensification will be the result of the collective action of millions of small -scale farmers, who through their daily decisions determine the trajectory of agricultural ecosystems across the world”

José Graziano da Silva, Director-General,

Food and Agriculture Organization of the United Nations (FAO)

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ABSTRACT

Agroecosystems are confronted with an urgently needed paradigm shift from productivity gains at the expense of environmental stability and socio-cultural integrity to environmentally and socially resilient agroecosystems. The purpose of this investigation is the development of an agroecosystem resilience assessment tool, which serves farmers and farming communities for assessing and enhancing the robustness of their farming systems, and which generates scientific data about agroecological practices that enhance resilience.

Over the past 50 years, the intensification of agriculture via the use of high-yielding crop varieties, productivity-increasing fertilizers and pesticides and improved irrigation systems has led to a substantial increase of food production (Evenson and Gollin 2003) and simultaneous ecosystem degradation (Kremen and Miles 2012). The consequence is a reduction of biodiversity and a loss of key ecosyste m services to and from agriculture, such as soil fertility, soil water holding capacity, nutrient cycling, weed control, pest control, disease control, pollination services, carbon sequestration, energy-use efficiency etc. (Kremen and Miles 2012). Agricultural systems are not only main contributors to greenhouse gas emissions and climate change, but are highly vulnerable to climatic shocks and stresses themselvels. Both farmers and researchers are confronted with uncertainty and surprise considering future developments of agriculture under a climate change scenario. Approaches to combine food production with long-term ecosystem functioning must involve farmers and their traditional ecological knowledge about seed varieties, climatic patterns and cultural context.

This study contributes to data generation about links between agroecology and resilience by presenting an ecosystem-based assessment tool that can be used by farmers to identify strengths and weaknesses of their agroecosystems and enhance their resilience through adaptive agroecological management.

The tool combines resilience theory with agroecological principles and practices and was developed based on literature review. The assessment consists of a four-step approach: (I) Agroecosystem Diagnostic Analysis, (ii) Response Capacity Assessment, (iii) Choice of Adaptation Practices and (I) Monitoring and Adaptation of Practices.

The Agroecosystem Resilience Assessment Framework was applied to the Agricultural Community Alhué in Central Chile. Results show that coupling agroecology with resilience theory can help farmers identify key vulnerabilities of their agroecosystem and facilitates the design of culturally and environmentally adequate strategies for agroecosystem management. It contributes to the identification of locally best suited agroecological and social practices by disseminating local knowledge and integrating it in a scientific framework.

ZUSAMMENFASSUNG

Agroökosysteme sind mit einem Paradigmenwechsel konfrontiert – ein Wandel von Produktivität zu Lasten von Ökosystemstabilität und sozio-kultureller Integrität hin zu sozial und ökologisch resilienten Agroökosystemen.

Fokus dieser Arbeit ist die Entwicklung einer Methode zur Bewertung der Robustheit von Agroökosystemen. Zweck des Instruments sind sowohl die Bewertung und Verbesserung der Agroökosystemrobustheit durch Landwirt_innen und landwirtschaftliche Gemeinschaften, als auch die Erhebung von Daten über Resilienz fördernde agroökologische Praktiken.

Landwirtschaftliche Intensivierung durch Hochleistungssorten, produktionssteigernde synthetische Dünger und Pestizidmittel sowie verbesserte Bewässerungssysteme haben in den letzten 50 Jahren zu ständiger Produktivitätssteigerung bei gleichzeitig stattfindender Ökosystemdegradation stattgefunden. Biodiversitätsreduktion und Verlust elementarer Ökosystemdienstleistungen wie Bodenfruchtbarkeit, Wasserrückhaltekapazität, Nährstoffkreislauf, Schädlings- und Unkrautregulierung, Bestäubung etc. sind die Konsequenz. Die globale Landwirtschaft trägt maßgeblich zur Emission klimaschädlicher Treibhausgase bei; gleichzeitig werden die Folgen des Klimawandels vor allem die Lebensmittelsicherung treffen.

Dem Verlust lokalen, traditionellen landwirtschaftlichen Wissens kann nur durch gezielte Zusammenarbeit zwischen Landwirt_innen und Wissenschaftler_innen entgegengewirkt werden. Die Entwicklung von Methoden zur Kombination von Lebensmittelproduktion und Naturschutz müssen die Beteiligung von Landwirt_innen und ihrem Wissen über Saatgutvielfalt, klimatische Gegebenheiten und den kulturellen Kontext in den Fokus nehmen.

Um die genannten Herausforderungen anzugehen wurde im Rahmen dieser Arbeit ein Instrument entwickelt, welches von Landwirt_innen genutzt werden kann, um die Robustheit ihrer Landwirtschaftssysteme zu bestimmen und Anpassungsstrategien zu entwickeln.

Der Bewertungsprozess beinhaltet vier Schritte: (i) Diagnostische Auswertung des Agroökosystems, (ii) Bewertung der Reaktionsfähigkeit, (iii) Auswahl von Anpassungspraktiken und (iv) Begleitung und Anpassung der Praktiken.

Die Methode wurde exemplarisch für die landwirtschaftliche Gemeinschaft Alhué in Zentralchile angewandt. Ergebnisse zeigen, dass die Verbindung von Agroökologie mit Resilienztheorie Landwirt_innen helfen kann, Stärken und Schwächen ihrer Agroökosysteme zu identifizieren und umwelt- und sozialverträgliche Strategien für ihr Agroökosystemmanagement zu entwickeln. Es trägt zur Identifizierung lokal angepasster agroökologischer und sozialer Praktiken bei, sowie zu deren Vervielfältigung und Integration in den Wissenschaftsdiskurs.

LIST OF FIGURES

FIGURE 1: CHANGES IN CROP YIELD DUE TO CLIMATIC CHANGES UNTIL 2050

FIGURE 2: SOCIAL ECOLOGICAL SYSTEM

FIGURE 3: AGROECOSYSTEM

FIGURE 4: MULTIFUNCTIONALITY OF AGROECOSYSTEMS

FIGURE 5: ADAPTIVE CYCLE ILLUSTRATED BY RAFORD

FIGURE 6: RESILIENCE, CONNECTEDNESS AND CAPACITY IN THE ADAPTIVE CYCLE

FIGURE 7: PANARCHY

FIGURE 8: ECOSYSTEM SERVICES AND DISSERVICES FROM AGRICULTURE

FIGURE 9: MAP OF CHILE

FIGURE 10: MAP OF THE METROPOLITAN REGION

FIGURE 11: PRECIPITATION AND TEMPERATURE IN ALHUÉ

FIGURE 12: COMMUNITY AREA WITH HYDROLOGY

FIGURE 13: COMMUNITY MEMBERS PARTICIPATING IN A WORLD CAFE, MAY 2016

FIGURE 14: MAPPING OF LAND AREA AND IMPORTANT FEATURES, MAY 2016

FIGURE 15: PUSH-AND-PULL SYSTEM WITH MAIZE

FIGURE 16: AGROECOSYSTEM RESILIENCE ASSESSMENT EXAMPLE

FIGURE 17: TOPOGRAPHY OF PROJECT SITE VISUALIZED WITH SATELLITE IMAGE

FIGURE 18: REFORESTATION AND AGRICULTURE AREA

FIGURE 19: SOIL OF CULTIVATION AREA

FIGURE 25: RESULTS FROM WORLD CAFÉ METHOD

LIST OF ABBREVIATIONS

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1. INTRODUCTION

1.1 AGRICULTURE AND CLIMATE CHANGE

In human history, the survival or decay of civilizations has oftentimes crucially depended on the sustainability of their agricultural systems (Diamond 2005). Ever since people have settled, farms have been essential in providing people with food, clothing, animals, medicine, fuels and raw materials (Heichel 1976).

However, modern industrial agricultural and livestock systems contribute to environmental degradation and ecosystem function loss worldwide. According to the IPCC, Agriculture, Forestry and Other Land Use (AFOLU) are responsible for almost 25% of anthropogenic greenhouse gas emissions (Smith et al. 2014) and thereby contribute to climate change. Paradoxically, agriculture is also projected to be one of the sectors most affected by climate change, with which „diverse, severe, and location-specific impacts on agricultural production are anticipated” (Altieri et al. 2015:869). Temperature, sunlight and water availability and a delicate balance of gases in the atmosphere are the key biophysical factors influencing plant growth, which is why „farming is the human endeavor most vulnerable to the effects of clim ate change“ (Altieri et al. 2015:870).

An increasing amount of greenhouse gases in the atmosphere, such as carbon dioxide and methane, is expected to cause a rise of the global surface temperature of 1.4 to 5.8°C, leading to various changes in climatic patterns. These include altered precipitation and transpiration regimes, increased frequency of extreme weather events such as heavy rainfalls and droughts, and modified weed, pest and pathogen behaviour (Morton 2007). These events individually and collectively impose stresses on plants and al ter the capability of crop varieties to respond to these changes. A high degree of uncertainty about intensity and magnitude of the predicted changes adds to uncertainties about crop reactions to the anticipated changes (Altieri et al. 2015).

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Figure 1: Changes in crop yield due to Climatic Changes until 2050 (The World Bank 2010).

Research models on the effects of climate change on agriculture suggest a decrease in agricultural production in the long-term (Fig. 1), with significant location-specific differences (see Parry et al. 2004, Adams et al. 1998). An increased CO2 concentration in the atmosphere has the potential to increase plant growth in the first place, however, this increase in productivity is expected to even out with decreases due to unexpected events (Parry et al. 2015). High-latitude regions are expected to face short-term increases in crop productivity due to extended growing seasons brought about by higher temperatures, while predictions for tropical regions indicate significant production losses (Kreft et al. 2015), which is on the one hand due to events of flooding and pest increase, on the other hand due to the fact that normal temperatures ranges in the tropics fall in a narrower range than those in higher latitudes, and all deviations are expected to have significant effects (Martin, 2015). In semi-arid regions, higher temperatures will accelerate soil water evaporation and transpiration, and thereby increase the demand for water due to increased irrigation needs in dry periods. Agriculture will have to face increased competition for water with other water users such as the industry or urban use. Having a direct effect on reproduction and survival rate, temperature is a main driver of pest population dynamics. Higher average temperatures could lead to a doubling of reproductive cycles of certain pest populations throughout the year. In spatial terms, insect populations could shift their habitat further northwards, invade new regions and merge with endemic pest populations. Changing wind patterns can also influence the spread of pest populations and weed seeds to areas previously undisturbed by these invaders (Altieri et al. 2015).

Considering economic consequences, production declines will predominantly hit lower-income countries, oftentimes coinciding with political, social and economic instability (Martin 2015, Altieri et al. 2015). The agro-industry will have to compete with other sectors about input resources on which it heavily depends, such as water, petroleum and land.

The capacity of agroecosystems to adapt to changing climatic patterns is considered a key factor that will determine the severity of climate change impacts on food production (Altieri et al. 2015). Nevertheless, conventional agroecosystems are predicted to be vulnerable to the expected climatic changes.

Negative social and environmental externalities, as well as increasing vulnerability to predicted climatic changes show the necessity of a paradigm shift in agricultural production. It is a global imperative to find ways of combining the achievement of food security and the reduction of farmers’ vulnerability, as aimed at with the Sustainable Development Goals (SDGs), with ecologically sustainable agroecosystem management over the long-term (Kremen and Miles 2012, United Nations 2017).

1.2 AGROECOLOGY AS A MANAGEMENT APPROACH

Agroecology, ecology applied to agriculture, comprises a variety of traditional, often indigenous farming practices, which combine high efficiency in production with maintaining key agroecosystem functions. Agroecological practices have been applied worldwide for decades, having evolved in different contexts as a scientific discipline in the 1930s, as a social movement, and as a practice (Wezel et al. 2009).

Apart from the production of food through diversified farming practices, agroecological practices aim at maintaining ecosystem functioning and thereby enhance the provision of other ecosystem services such as biodiversity, carbon sequestration, water retention, or weed control (Zhang et al. 2007). These diversified farming practices increase agroecosystem resilience in the face of disturbances caused by climate change and related changes. A projected increase in main average temperature as well as an increase in extreme weather events will require dynamic on field management responses (Altieri et al. 2015). An increased irrigation demand in drought periods has to be complemented by agroecosystem resilience in periods of heavy rainfalls. Insect development and survival is extremely influenced by temperature, thus pest management will require experiments and on-field learning strategies (Altieri et al. 2015).

Creating effective mechanisms of understanding and preserving successful practices and translating them into concrete tools is a necessity for various reasons:

It empowers small-scale farmers to build climate resilient agroecosystems that ensure the preservation of their ecosystem and its long-term productivity even in times of disturbance. Despite the rapid globalization of industrial agriculture throughout the last 40 years, 98% of all farmers are small -scale or family farmers 1, and they satisfy more than half of the global food demand (Graeub et al. 2016). Nevertheless, small-scale farmers are among the most vulnerable occupational groups, being exposed to agricultural risks, climatic uncertainties, oftentimes socio-political instability and varying crop prices. 80% of the world’s poor are living in rural areas, of which 70% are farmers or fishermen (IFAD 2011). Projected changes in yield due to changing climate is expected to affect countries in the global south over- proportionally, creating a need for developing adaptation strategies in these regions for both industrialized farming systems and family farms.

It closes the gap between scientific and experimental knowledge, creating a two-directional dialogue between scientists and farmers. Traditional Ecologic Knowledge (TEK), as opposed to scientific knowledge, is a “knowledge-practice-belief-complex” (Berkes et al. 2000:1252), often encoded in practices and rituals invisible for scientific approaches. However, combining traditional with new knowledge holds the potential for creating farming systems that prevent ecosystem degradation and turn out resilient in the face of unexpected change. The need for increasing scientific research on agroecology in order to create climate resilient farming systems has been expressed both by international organizations2, researchers3, and institutions representing farmers (Via Campesina 2017).

1.3 ENHANCING AGROECOSYSTEM RESILIENCE WITH AGROECOLOGICAL MANAGEMENT

Focus of this investigation is the development of an ecosystem-based resilience assessment tool, that allows farmers to monitor their practices and that generates scientific data about agroecosystem resilience.

The development process was guided by two questions:

Does the coupling of agroecology with the resilience approach have the potential to help farmers design robust agroecosystems?

What can we learn from community-based approaches for designing agroecosystems in a participatory way?

To answer these questions, a resilience assessment framework was designed, comprising a system diagnostic analysis that depicts the current state of an agroecosystem, with a subsequent response capacity assessment, showing the system’s absorptive, adaptive and transformative capacity. In an adaptive learning process, agroecological practices are implemented as a measure to address the weak points of each agroecosystem assessed. Agroecosystems are understood as an inseparable union of farmers and their ecosystems. The tool is exemplarily applied to an Agricultural Community in Central Chile. The study argues that coupling the resilience approach and agroecology can promote the successful development of environmentally sustainable and socio-culturally adequate strategies, which strengthen farmer’s resilience and the learning capacity of the whole social ecological system.

1.4 STUDY AREA

This investigation is embedded in the long-time project Parque Agroecologico Tralhuenes Comunidad Agricola Villa Alhué, which aims at the development of an agroecological project in Alhué, a rural area in central Chile. In joint work with a farming community of 136 families, the park encompasses an area of 1000 hectare and a reforestation as well as an agricultural production site. The project is executed by the farming community and the environmental agency Andalué Ambiental. It is financed and supervised by the Global Environmental Facility (GEF), the United Nations Development Programme (UNDP) and Comunidades Mediterraneas Sostenibles (CMS). It contains a socio-cultural, an environmental and an economic dimension in all of which sustainable management is targeted. The investigation was carried out within this community in the period from January to June 2016.

1.5 STRUCTURE OF THESIS

This thesis presents a participatory approach for the development of an indicator framework for assessing agroecosystem resilience.

The second chapter consists of the presentation of key concepts and theories the analysis is based on. I will give a brief introduction to systems theory and resilience of social ecological systems, before clearly defining the concept by looking at agroecosystem resilience and its components.

Chapter 3 provides an overview of the frame of research and the study site in Chile.

In chapter 4, I describe methods used for both the development of the resilience assessment framework and for its application to the Chilean context.

In Chapter5, this framework and its potential for generating knowledge about links between agroecology and community resilience is tested with data drawn from an ongoing community-based natural resource management process in Alhué, Chile.

This application is based on data obtained from interviews with stakeholders, two participative seminars with the community members, previously collected information within the local community and literature reviews, all of which are presented in detail.

Chapter 6 concludes with a discussion of advantages and pitfalls of the methods used, possibilities of adjusting it and further insights gained in the field of agroecology research. An outlook on further research of interest is presented.

This thesis will contribute to agroecology research and enlarge the body of knowledge on agroecology and its application. Furthermore, it will provide an example of adaptive, community-based natural resource management in agroecosystems, and therewith promote the dialogue between different scientific disciplines and between science and small-scale farmers.

2. THEORETICAL FRAMEWORK

In order to investigate on the potential of coupling agroecology with the resilience approach, I present an introduction into the theoretical frameworks of systems theory and agroecology. I further present links between agroecology and resilience and existing approaches to measuring resilience in agroecosystems.

2.1. SYSTEMS THINKING AND AGRICULTURE

System theory is rooted in the understanding that social-ecological systems (SES) are not organized sets of disconnected parts, but networks of complex dynamic patterns that are in constant evolution. They are emergent phenomena with non-linear behavioral patterns, which are not explicable by looking at the sum of its parts (Gunderson 2000:430). Analyzing and understanding abrupt change in system dynamics and behavior is a key objective of systemic approaches.

Berkes and Folke explicitly eliminate the separation between social systems and ecologic systems, referring to the fact that with a few exceptions in history, including the Western societies in the last 400 years, human societies have generally considered themselves to be part of nature, not separate or even opposed to it (Berkes and Folke 1998). In many traditional and indigenous cosmovisions, land, water and the human environment are considered a unit, one and indivisible. Other authors share this opinion, stating that social-ecological systems are “neither humans embedded in an ecological system nor ecosystems embedded in human systems” (Walker et al. 2006a:1). Rather, both systems encompass social and ecological components, which are identifiable, but which cannot be separated from each other for analytic or practical purposes (Walker et al. 2006b). They are embedded in a context of political, cultural, institutional and economic factors (Figure 2).

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Figure 2: Social Ecological System, own illustration.

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Figure 3: Agroecosystem, own illustration.

Agroecosystems (AES) embody all the complexity a SES can possibly have (Darnhofer et al. 2010a), because the resource system with its resource units, i.e. the farm, is inseparably linked to the human system, incorporating both the management system and the user system, i.e. the farmer (Fig. 3). The agroecosystem thus consists of a social system, an ecologic system, and the interlinkages between both. The social subsystem comprises all humans working on or associated to the agricultural production site. It encompasses the farmer's mental models, preferences, and anything else making up his or her social and cultural capital (Darnhofer et al. 2010b). It can have different organizational scales, ranging from the farmer, his or her family, the community or a corporate farm. According to scale, the unit of interest can be the farmer, his or her family, or the farming community. The ecologic subsystem is the natural surrounding of the farmer. Depending on his, her or their living reality, the ecologic subsystem extends from the physical production site to the landscape level. It encompasses biophysical components such as soil, water, predators, nutrient and energy flows, as well as the provision of ecosystem services. According to the lenses looked through, spatial scales range from the field level over the landscape level or even to the national, international and global scale. The interlinkages describe agroecosystem production, and are created by the farmer through modification of the natural system according to his/her preferences and production plans. These interlinkages refer both to the human components changing the ecosystem, in the case of the farmer by intentionally intervening in the life-cycle of plants and harvesting them, and the human component adapting to changes in the ecologic system, e.g. by planting drought resistant crops or increasing irrigation. Subsystems that emerge between the farmer and the ecosystems include crops, animals, finances, etc. (Darnhofer et al. 2010b). The agroecosystem itself is embedded in context-specific political, economic, institutional and cultural circumstances, which influence developments within the agroecosystem and which are in turn influenced by developments of the agroecological system and its subsystems.

The main function of agroecosystems is the production of food, clothing, animals, medicine, fuels and raw materials (Heichel 1976) through agricultural activities. The OECD defines an agroecosystem as „an ecosystem under agricultural management, connected to other ecosystems“ (OECD 2001). However, while this definition emphasizes the management part of an ecosystem, it largely omits the question who is managing the system in what context. Rather, AES are a „manifestation of cultural and social factors in relation with non-human environmental factors” (Tomich et al. 2011:196), producing a wide range of socio-cultural, environmental and economic benefits (Fig. 4).

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Figure 4: Multifunctionality of Agroecosystems (McIntyre et al. 2009).

Social ecological systems with interlinked human-nature activities, which aim at the production of food and other goods for human use through agriculture. Several heuristics are used to describe system dynamics. These are applicable for all kinds of SES, and are exemplified here for agroecosystems.

2.1.2 ADAPTIVE CYCLE

Ecosystems are subject to constant change. System alterations and succession have changing effects on system structures, processes and functions (Burkhard et al. 2011). However, ecosystem development follows general patterns, characterized by changing ecosystem behavior and coping with changes, as observed by Holling (1986). He observed a sequence of events starting with a phase of efficient exploitation, which eventually and unexpectedly led to a shift in ecosystem behavior, a change in the provision of ecosystem services and system functions. Based on this observation, he deducted the picture of a four–stage ecosystem renewal cycle, consisting of a sequence of phases each ecosystem goes through:

Exploitation (r) – Conservation (K) – Release (Ω) – Reorganization (α)

The exploitation or growth phase (r) is characterized by efficient exploitation of readily available resources and the accumulation of structure, matter, energy and information (Burkhard et al. 2011). Increasing structure and connections among system components require higher energy levels to maintain them, leading to a phase of slowdown of net growth. This conservation phase (K) is characterized by high interconnectedness due to accumulation and little flexibility. Disturbance lets the system reach a tipping point, introducing the next phase of collapse and release (Ω) of accumulated structures and resources. This phase prepares the way for renewal and reorganization (α) of available information and resources, eventually leading to a new growth phase (Walker et al. 2006a,Fig. 5.).

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Figure 5: Adaptive Cycle illustrated by Raford (2010).

Disturbance and system collapse have since been understood as crucial for system development and in the best case are beneficial for improving a system’s diversity and robustness in the long- term (Burkhard et al. 2011, Walker et al. 2006b). Collapse in the form of energy release and subsequent reorganization are part of each system cycle. Analyzing social change through technological innovation and political events, Schumpeter called this phenomenon a phase of creative destruction, where system components are rearranged in a new way that guarantees the maintenance of its functions and better adaptation to changed outer circumstances (Schumpeter 1942). The general pattern of unexpected change after a relatively stable phase of continuous exploitation can be explained by management, which is “actively blocking out environmental variability and feedbacks that govern change” (Berkes and Folke 1998:11). Small perturbations and disturbances inherent to the system dynamics are suppressed, fixing the system cycle in one state, and leading to an accumulation of disturbance potential. The system maintains its functions, though far away from a state of equilibrium, until a critical threshold is passed.

Several authors describe the observation of these four stages of the adaptive cycle in system analyses , including ecosystems (e.g. Holling 1986), social systems (e.g. Westley et al. 2002), institutional systems (e.g. Janssen 2002), and social-ecological systems (e.g. Gunderson et al. 1995, Holling et al. 2002).

All subsystems of agroecological systems as well as their various subsystems are semi-autonomous and undergo constant, non-linear changes and adaptive cycles. This holds true for the ecologic subsystem (e.g. natural succession of plants), for the social subsystem (e.g. change of cultivation preferences), and also for the interlinkages of the ecologic and the social system (e.g. switching from synthetic to organic fertilizer use). Historic analyses of agroecosystems have shown that they are likely to spend most of the time in phases of gradual change, interrupted by abrupt, episodic disturbances (Darnhofer et al. 2010b). Intensified, industrial agriculture systems exhibit a common pattern of stabilization, ignoring the natural tendency of systems to go through cycles characterized by collapses and reorganization. This command- and-control approach has led to the progressive decline of agroecosystems and the industrial agricultural model as a whole (Allison and Hobbs 2004). Some new approaches to farming, e.g. integrated pest management, allow for small amounts of disturbance and system collapses within the system, thereby allowing it to better cope with disturbance it in the long-term (Shea et al. 2002).

2.1.2 RESILIENCE

The magnitude of disturbance a system can absorb before changing state is referred to as its resilience. A loss of resilience, initially unobservable, moves the system further away from its equilibrium state and closer to critical thresholds. Ultimately, when passing this threshold, an irreversible shift of state is the consequence, changing the systems structure by “changing the variables and processes that control behavior” (Berkes and Folke 1998:6).

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Figure 6: Resilience, connectedness and ca- pacity in the adaptive cycle (Allison and Hobbs 2004).

Resilience is directly related to the phases of the adaptive cycle. Fig. 6 depictures attributes of a SES (resilience, connectedness and potential) in different phases of the adaptive cycle. When accumulating structure due to available resources, resilience is high. Towards the end of the conservation phase, when limits of growth are reached and the system faces a state of saturation, little flexibility due to high connectedness leads to increased vulnerability to external shocks. Vulnerability is the flipside of resilience - in the case of loss of resilience, a system becomes vulnerable to shocks and disturbances which it was previously able to absorb. Loss of important system functions and components can be the consequence. Small events can cause a rapid collapse (Gunderson et al 2000:430). The resilience of the systems determines the magnitude of disturbance it can absorb without collapsing, and determines whether the collapse leads to renewal within the same state or flips the system in another development path (Berkes and Folke 1998:35 2). Systems theory distinguishes between engineering and ecologic resilience. Engineering resilience defines resilience by the time a system needs to return to a steady state or an equilibrium. Measuring resilience becomes a measurement of distance from and return time to the equilibrium point (Gunderson 2000). Implicit assumption is the existence of one equilibrium around which the system oscillates and to which it will eventually return. Ecological resilience assumes multiple equilibria possible. Ecological resilience describes the width of a stability domain and describes the amount of disturbance the system can absorb without switching to an unknown, different stability domain (Gunderson 2000). However, resilience is not always positive; systems entering in pathologic states (Holling et al. 1996), e.g. a body invaded by a severe disease can be very resistant to medication, making it a resilient system which won’t allow for change. Societies can be stuck in a poverty cycle, making them unable to shift to a more positive pathway (Campbell et al. 2012). Allison and Hobbs (2004) find the Australian agricultural system to be in a “lock- up trap”, where an unsustainably managed agroecosystem is highly resilient and does not allow for a regime shift which could initiate a more sustainable development.

The resilience concept has been applied to development and humanitarian sectors, social protection, mental and physical health, war and conflict as well as business (Schipper and Langston 2015, Martin - Breen and Anderies 2011).

Resilience in agroecosystems describes the capacity of the system to continue producing food and raw materials even if facing long-term or permanent changes (Lin et al. 2011). Decreases in resilience result from a loss of biodiversity, soil, water or overall productivity when facing external or internal shocks or stresses (Altieri et al. 2015). Applying resilience thinking to farming systems recognizes the understanding of agriculture as a complex, permanently adaptive system. It requires moving away from prevailing analytical equilibrium thinking, including its assumptions of linearity, homogeneity, predictability and optimization (Scoones et al. 2007:27).

Assessing the resilience of agroecosystems requires linking multiple spatial (field, farm, landscape / local, regional, national, international etc.), temporal (day, week, month, season etc.) and organizational scales (farmer, household, community etc.), on which the system and its subsystems undergo change. This hierarchical structure of scales with nested systems is called panarchy (Fig. 7).

Abbildung in dieser Leseprobe nicht enthalten

Figure 7: Panarchy (Resilience Alliance 2017).

Resilience in AES derives from three essential capacities:

1) The capacity of a system to absorb disturbance while maintaining functions and structure. Disturbances to agroecosystems can take the form of climatic events, e.g. extreme weather events, they can be of economic nature, e.g. input price increase, output price decrease, inputs availability, access to markets or uncertainty to land tenure, or management related, e.g. plant pests, animal diseases, overgrazing etc. (Groot et al. 2008). These disturbances can either manifest in discrete events in time, referred to as pulses or shocks, e.g. heavy rainfalls, or unexpected changes at stock markets, or as more gradual and cumulative pressures, referred to as presses or stresses, e.g. continuous nutrient extraction from agricultural soils, or continuous application of synthetic fertilizers (Resilience Alliance 2010). Typically, pulses provoke rapid system collapses, while presses slowly push the system towards an invisible threshold until change occurs. Different strategies are needed to cope with each type of change and its causes, which is why it is important to distinguish between pulses and presses (Darnhofer et al. 2010 a). However, different social and ecological configurations paired with spatial and temporal processes produce non-static resilience effects of SES (Carlisle 2014), which is why it is not possible to determine magnitude of a shock or stress per se.

Resilience assessment approaches generally distinguish between measuring general or specific resilience. General resilience describes the system’s overall robustness of functioning, while specific resilience refers to particular kinds of disturbance, e.g. floods or hurricanes, or a particular aspect of the system that might be affected by disturbance (Darnhofer et al. 2010a).

A combined assessment framework applies to the system as a whole as well as to its parts. It recognizes the interconnectedness of all subsystems, dimensions and functions, which is why the goal is not to deduct unambiguous cause-effect relations, but links, relations and interactions between system components and resilience dimensions. In agricultural systems, the level of existing biodiversity can make the difference between the system being stressed or resilient when confronting biodiversity and redundancy can make the difference of the system being collapsing or being resilient (Darnhofer et al. 2010b, Altieri et al. 2015, Lin et al. 2011).

2) The capacity of a system to learn and adapt to changing circumstances. This capacity describes the amount of learning, combining experiences and knowledge as well as adjustments to external forces the system is able to create (Douxchamps et al. 2017:11). It's the system’s capacity to cope with novel situations without losing options for the future and adapt its functioning to new sets of conditions in changing circumstances. Adaptation refers to finding new states of stable equilibriums despite facing permanent changes in internal or external systems, and changes in the interaction patterns with these systems (Lopez-Riadura et al. 2005). Adaptation in AES refers to adjustments that farmers make to reduce risks (Altieri et al 2015: 883). A farmer's adaptive capacity depends on the individual or collective reserves of human and social capital. These include attributes such as maintenance of traditional knowledge and skills, networks between farmers, their community and its institutions, adoption of new practices and innovation etc. (Altieri et al. 2015). In an adaptive system, each management decision is viewed as an opportunity for future learning to adapt to uncertainty and surprise (Folke et al. 2005).

3) The capacity of a system to self-organize, also referred to its transformability. Transformability refers to the ability of a system to move to new stability domains and create new system dynamics in case the initial state has been overcome due to a system collapse (Douxchamps et al. 2017). Transformability is part of a system's capacity of self-organization, which not only describes a system's behavior in the situation of reorganization after a system collapse, but also in all other phases of the adaptive cycle.

2.1.4 ADAPTIVE CAPACITY

Change occurs within the system, its components and variables, as well as changing outer system conditions. Adaptive capacity describes a system‘s ability to cope with shifting stability landscapes. This can either refer to the ability to return to a previous stability domain after disturbance, or adapt to new system configurations after a system shift to a new stable state with a new equilibrium. Enhancing a system’s capability to cope with changes in the face of uncertainty and unpredictability promises its long-time functioning (Folke et al. 2002:4). The degree to which a system can build and increase this adaptive capacity determines its resilience (Carpenter et al. 2001). Folke et al. (2002: 7f) identify three elements that sustain adaptive capacity of socio-ecological systems are (according to Folke et al.): (I) Learning to live with change and uncertainty, (ii) Nurturing diversity for resilience and (iii) Combining knowledge systems.

2.1.5 ADAPTIVE MANAGEMENT

The recognition that “surprises are inevitable, that knowledge will always be incomplete, and that human interaction with ecosystems will always be evolving” (Gunderson 2000:433) requires corresponding ecosystem management responses. Adaptive management aims at implementing policies that enable social and institutional learning processes, which in turn enable flexible and adaptive social responses to ecosystem change, particularly during periods of crisis and reorganization (Gunderson 2000). It treats policies as hypotheses around a set of desired system outcomes, with incomplete knowledge about system behavior (Folke et al. 2002:20). Management actions become the treatment to evaluate or test these hypotheses (Gunderson 2000:434).

In practice, local and indigenous community contexts often show adaptive management principles in dealing with the organization of community-based natural resources (Folke et al 2002:21). Many self- organized community systems show emphasis on “learning, innovation and flexibility, recognition of inherent uncertainty in social-ecological systems across scales, and a non-deterministic world view in response to system uncertainty” (Armitage 2003:2). This similarity is no coincidence – long-term maintenance of ecosystem function is often essential for the perseverance of local communities over time, the creation of flexible and dynamically evolving principles for the use of natural resources within their communities, and an establishment of social institutions regulating their use is a logic consequence of this necessity (Armitage 2003). This is the case even more when maintenance and protection of the resource is not guaranteed by external (governmental or private) institutions.

Adaptive management is “learning by doing and doing to learn” (Shea et al. 2002:928). However, differences between active (AAM) and passive adaptive management (PAM) exist (Armitage 2003). PAM derives learning from the results of previous management attempts. The consequences of different strategies are predicted based on previous experience (Shea et al. 2002). AAM follows the same logic, but includes an actual plan for learning about the managed system. Different resource management strategies or policies are tested based on previously formulated hypotheses, and are implemented after monitoring, evaluation and adaptation. Flexible, reactive institutions and organizational arrangements facilitate the process of modifying these policies based on the learning results (Armitage 2003). AAM describes an ex- ante experimental approach, while PAM describes ex-post evaluations.

In agricultural system, active adaptive pest management has been applied as a means of biological pest control. In an experimental design, selected crops, separated in space, receive certain pest populations and their natural enemies or simply pest predator combinations that promise success. Ecological theory serves as a backbone for predicting the outcome, however, the experimental design allows adaptations of practice and theory at all stages of the experiment (Shea et al. 2002).

2.2 MANAGING RESILIENT AGROECOSYSTEMS

Creating resilient agroecosystems requires the identification of farming practices that enhance agroecosystem resilience. One possible approach is to identify ecosystem services provided by agroecosystems, and relate them to practices that enhance the provision of these ecosystem services.

2.2.2 ECOSYSTEM SERVICES IN AGROECOSYSTEMS

The Millenium Ecosystem Assessment derives four categories of ecosystem services that contribute to the linkages between ecosystems and human well-being. These categories are provisioning services, regulating services, supporting services and cultural services (MA 2005). Agroecosystems are ecosystems that are primarily managed to optimize the production of food, fuel and fiber (Zhang et al. 2007), and thereby the production of provisioning services. As such, they depend on supporting services such as soil formation and water cycling for the production of these outputs. At the same time, agroecosystems themselves provide ecosystem services, among which yield or harvest quality and quantity are the ones most directly related with human use. However, with corresponding management, they can provide a wide range of not only provisioning, but also regulating, supporting and cultural ecosystem services, such as biodiversity, soil quality, nutrient management, water holding capacity, weed control, disease control, pest control, pollination, carbon sequestration and energy-use efficiency (Kremen and Miles 2012).

Abbildung in dieser Leseprobe nicht enthalten

Figure 8: Ecosystem services and disservices from agriculture, own illustration.

Zhang et al. (2007) distinguish between ecosystem services and dis-services provided to and received by agroecosystems. Ecosystem services to agriculture describe processes and services that agroecosystems depend on in order to produce yield, such as soil structure and nutrient cycling. Dis-services to agriculture are services that reduce productivity or increase production costs, such as herbivory and competition for water between agricultural systems. On the output-side, agroecosystems produce food and other goods, and, if adequately managed, contribute to soil formation and climate change mitigation through carbon sequestration. Dis-services from agriculture are negative externalities caused by management decisions. They include habitat loss, nutrient run-off and pesticide poisoning (Zhang et al. 2007). Trade-offs between ecosystem services and dis-services to agricultural systems will influence cultivation and design decisions. However, Zhang et al. emphasize the need for research on cause-effect relations between supporting and provisioning agricultural ecosystem services, especially with respect to soil fertility, soil microbi al interactions and crop yield. Figure 8 illustrates the ecosystem services agroecosystems can provide.

All ecosystem services are connected and product of as well as input to interaction. Soil fertility for instance comprises of different biological, chemical and physical components. Soil fertility is improved by the increase of soil organic matter, which in turn has positive effects on nutrient cycling and nutrient availability as well as water holding capacity and water infiltration. The improvement of all these ecosystem services in turn promote plant growth and thus plant productivity and yield (Mäder et al. 2002).

Improved soil organic matter increases macrobiotic soil biodiversity, with positive impacts on carbon sequestration (Lal 2004).

Kremen and Miles assess the ecological performance of biologically diverse farming systems in comparison to conventional farming systems. They cluster agroecosystem services to and from agroecosystems into four categories: Inputs to agroecosystems, outputs from agroecosystems, adaptation of farming to environmental change and mitigation of externalities associated with farming (Kremen and Miles 2012). While inputs, outputs and mitigation services are equivalent to supporting, regulating and provisioning services, they create a new category for the resilience of agroecosystems in the face of extreme climate events.

Maintaining diversity across scales furthermore enhances agroecosystem resilience in the face of disturbance, such as drought, hurricanes or heavy rainfalls (Kremen and Miles 2012).

Ecosystem services of AES are essential inputs to farms, but moreover they are global public goods and as such, often become subject to the free-rider problematic – while benefits are available to all, the provision is costly for a few. While food demand and production has increased during the industrialization of agriculture over the past decades, many regulating and supporting services have correspondingly decreased (Millennium Ecosystem Assessment 2005). The recognition that agriculture is not only provider of food but can itself be provider of global ecosystem services such as carbon sequestration or water purification explains the necessity to identify agroecosystem attributes that enhance these behaviors and design farming systems correspondingly (Kremen and Miles 2012).

Agroecosystems that provide wide range of services and functions increase both utility for humans, and resilience of the systems themselves. According to their practices, different farming philosophies contribute to the diversification of agroecosystems and the provision of agroecosystem services. Agroecology will be used as an example of farm management that integrates the production of food with the provision of a wide range of ecosystem services and social benefits. A Vensim diagram in the appendix demonstrates the interlinkages between agroecological practices and ecosystem services generated, where agroecological practices are grouped into practices that enhance soil fertility, practices that improve water availability and practices that enhance biological pest control.

2.2.3 AGROECOLOGY AS A MANAGEMENT APPROACH

Based on the large body of investigation and experience, Francis et al. (2003) provide one of the broadest currently used definitions of agroecology, describing it as “the integrative study of the ecology of the entire food systems, encompassing ecological, economic and social dimensions”. Gliessman (2007) includes the practical application, defining agroecology as: “the science of applying ecological concepts and principles to the design and management of sustainable food systems”.

Agroecology has evolved in different regions of the world throughout the 20th century and according to its context, is referred to as a scientific discipline, an agricultural practice or a political and social movement (Wezel et al. 2014). In the contemporary discourse, agroecology in the broadest sense is understood a combination of the sciences of ecology and agronomy with the political economy of food production and consumption (Shiney Varghese and Karen Hansen-Kuhn 2013), and its recognition as a scientific discipline, a social movement and a set of practices are strongly intertwined (Wezel et al. 2014).

The first scientific agroecological studies emerged between 1930 and 1960 when agronomists and ecologists discovered common interests in crop development, and used ecological methods and insights from zoology, agronomy and botany to investigate on commercial crops and plants (Francis et al. 2003). With intensification of production and the green revolution starting in the late 1970s, interest in the ecology of agricultural systems increased, both on a scientific basis and as a way to protect natural resources by the creation of sustainable agroecosystems (Wezel et al. 2014). The agroecological concept evolved from a focus on the flied scale, to the farm, to landscape agroecosystems, and eventually to a holistic, systemic perspective including the whole food system (Francis et al. 2003, Gliessman 2007, Wezel et al. 2014).

During the 1970s, agroecological practices evolved in countries of the global south as a response to the negative effects of agricultural modernization on small-scale farmers, denial of access to land, and depletion of natural resources through intensified agricultural practices (Wezel et al. 2014). The development and promotion of agroecological practices was a means of searching for ways to promote food sovereignty and autonomy. Social movements began demanding policies and institutions to be transformed to support agroecology and to empower food producers, allowing agroecology to fulfill its potential to contribute to food and nutrition security. The international peasant organization Via Campesina understands agroecology as a political tool in the quest for food sovereignty by raising debate about production and prices, encouraging economies based on solidarity, sustainability and redistribution (Via Campesina 2017).

This link between practical application and political vision led to the formation of globally connected, regionally acting organizations. The Latin American Scientific Society of Agroecology (SOCLA) was founded in 2007 with the goal of promoting scientific exchange, discussion and experience with agroecology in Latin America. Following the example of the Brazilian Agroecological Society, national chapters and local groups are encouraged to organize research, training or broadcasting activities, thereby enlarging the network and creating knowledge hotspots in Latin America and the Caribbean (SOCLA 2017). SOCLA defines agroecology as “a scientific discipline that uses ecological theory to study, design, manage and evaluate agricultural systems that are productive but also resource conserving" (Agroecology in Action 2017).

In 2014, FAO launched the first International Symposium on Agroecology for Food Security and Nutrition, thereby recognizing the need for agricultural systems to suit the needs of the farmers and their families (Gliessman and Tittonell 2015).

Agroecology is not a set of farming practices, but promotes practices that allow agroecosystems mimic the functions of local ecosystems (Altieri 2002). Focus of agroecological research are interactions of biophysical and chemical system components such as mineral cycles, energy transformations and soil life, and their interaction with other system components such as contextual socio-economic relationships or site-specific, traditional and cultural legacy of farming systems.

Agroecological practices are highly context dependent and differ according to cultural and social context, climatic conditions, land size and overall vision. However, common agroecological principles and characteristics can be found across implementation sites. Altieri et al. (2015) and other authors (Snapp and Pound 2008) refer to five universal principles which characterize agroecological systems:

(I) Enhancing the recycling of biomass and optimizing organic matter decomposition and therewith nutrient availability and cycling.
(ii) Strengthening the immune system of agricultural systems through the enhancement of species and genetic diversity and heterogeneity over temporal and spatial scales.
(iii) Securing favorable soil conditions for plant growth, particularly by managing organic matter and enhancing soil biotic activity.
(iv) Minimizing losses of energy, water, solar radiation, nutrients and genetic resources by way of microclimate management, water harvesting and soil management through increased soil cover and agrobiodiversity.
(v) Enhancing of beneficial biological interactions and synergisms among agrobiodiversity components and thereby promoting key ecological processes and functions.

Some authors add a sixth principle rooted in cultural considerations (e.g. Infante Lira and San Martin Fuentes 2016):

(vi) Considering cultural bases of traditional systems for the design and strengthening of agroecosystems.

Another key characteristic is the combination of traditional and local knowledge with methods and advances from various disciplines (Wezel et al. 2014) with the goal of presenting an alternative to a high input, chemical-intensive agriculture promoted by international corporations and contributing to a more autonomous, environmentally sound and socially appropriate form of agriculture. SOCLA names this combination of elements of traditional farmers’ knowledge with elements of modern ecologi cal, social and agronomic science a “dialogue of wisdoms, from which principles for designing and managing biodiverse and resilient farms are derived” (SOCLA 2015).

Some authors prefer speaking of agroecology as an inherent feature of farming systems, and the use of agroecological practices recognizes and enhances the potential of this feature (Restrepo et al. 2000).

This systemic approach makes agroecology a trans-discipline with a wide range of research fields, from climate change impacts on agriculture, to agricultural research and technology and the combination of indigenous agricultural practices with new knowledge (Vanloqueren and Baret 2009, Berkes et al. 2000). Agroecology differs from other environment friendly farming practices in several characteristics. Climate- Smart Agriculture for instance aims at increasing productivity and incomes while removing greenhouse gas emissions and building resilience to climate change (CCAFS and UNFAO 2014). However, critics emphasize the lack of criteria for climate-smart measures . Unlike the EU organic label, there are no requirements that must be fulfilled for a product to be sold as originating from climate-smart production. In this sense, genetically-modified and drought-resistant seeds are as climate smart as other practices that don’t generate greenhouse gas emissions (Schmitt 2016). Agroecology aims at enhancing self-regulating ecosystem cycles and functions, thereby enhancing a variety of ecosystem services, of which food production is only one (Kremen et al. 2007). Being a holistic approach, agroecology provides the system knowledge and derives context specific practices that can be implemented by organic or conventional farms. The emphasis on underlying ecosystem characteristics makes agroecological practices strongly site- specific, which is why the development of universal agroecological standards or certification systems is not desirable in the first place.

3. FRAME OF RESEARCH

As mentioned in the introduction, aim of this investigation is to address the above described gaps and challenges, and to present the process of developing an agroecosystem-based resilience assessment tool, that allows farmers to monitor their practices and that generates scientific data about agroecosystem resilience.

The development process was guided by two research questions:

- Does the coupling of agroecology with the resilience approach have the potential to help farmers design robust agroecosystems?
- What can we learn from community-based approaches for designing agroecosystems in a participatory way?

3.1 STATE OF RESEARCH

Various authors have provided evidence of the positive links between agroecological food production, ecosystem functioning and community development. Kremen and Miles (2012) describe the provision of ecosystem services by agroecosystems managed with a focus on diversity, Altieri et al. (2015) describe how agroecological measures enhance resilience in rural contexts, and give examples of how social peasant movements contributed to a shift from dependence on the agro-industry to food sovereignty in Latin American communities (Altieri and Toledo 2011).

Some research has been directed to the development of indicators for agroecosystem resilience (Cabell and Oelofse 2012), the development of biodiversity indicators (Herzog et al. 2012) and sustainability indicators on farm level (Rigby et al. 2001). However, there is no consensus on how to best measure agroecosystem resilience and how to monitor this development (Cabell and Oelofse 2012). Various approaches to resilience measurement have been made through mathematical models (e.g. Fletcher et al. 2006), computer simulation models (Huntingford et al. 2013) or the creation of step -wise conceptual models (e.g. Resilience Alliance 2010). Measuring resilience directly would require predicting thresholds, in conditions where "the only sure way to detect a threshold in a complex system is to cross it" (Carpenter et al. 2005:941). Indicators for resilience measurement are subject to change according to spatial and temporal developments of the system, its subsystems and the systems it is embedded in, which is why the relationship between resilience and resilience indicators is dynamic, complex and multidimensional. Resilience measurement faces the challenge of developing simple and operational tools that can address complexity. Carpenter et al. (2005) suggest the use of resilience surrogates instead of indicators, thereby acknowledging "that important aspects of resilience in SES may not be directly observable, but must be inferred indirectly (...) In general, practitioners will need a suite of resilience surrogates that jointly represent the key features of resilience, in context, for the particular SES at hand" (Carpenter et al. 2005:941).

According to Carpenter et al. (2005:942), the use surrogates instead of indicators is possible if

- The surrogates directly relate to a particular theoretical notion of resilience
- The surrogates are consistent and repeatable
- The context dependency of these surrogates is made explicit
- The surrogate can be used for a range of SES or in an SES over time
- The surrogate is part of a set of complementary surrogates that address multiple aspects of resilience. Since agroecosystem resilience “is an emergent property of a system, arising from the unique interaction between farmer, farm and context” (Cabell and Oelofse 2012: 18), factors contributing to or diminishing resilience will depend on each agroecosystem context.

Various participative methods have been suggested in order to close the gap between rural communities' and scientists' knowledge, such as the Participatory Rural Appraisal Method (PRA, Chambers 1994), Participative Action Research (Putnam et al. 2014) or Rapid Rural Appraisal (Conway and McCracken 1990). A key aspect is the combination of locally relevant empirical knowledge with scientific, process-based knowledge (see Duru et al. 2015), which requires participative approaches to data generation and communication between on-field and scientific knowledge. All authors emphasize the need for research directed in the development of concrete tools, that on the one hand help transfer scientific knowledge to farmers, and on the other hand enable communication and translation of farmer ’s knowledge to scientists (Duru et al. 2015, Altieri et al. 2015), thereby creating a two-directional dialogue. This knowledge exchange should follow a path where "scientists must improve their understanding of the farmer and his practice and vice versa" (Duru et al. 2015:1270), or, as Chambers (1980:3) puts it: "The challenge is to listen to and learn from farmers, encouraging them to express their categories, meanings and priorities".

3.2 STUDY SITE ALHUÉ

This chapter includes a description of climatic, ecologic, social, economic and institutional characteristics of the study site.

Abbildung in dieser Leseprobe nicht enthalten

Figure 9: Map of Chile, adapted from Fundación Chile (2017).

Alhué is a small town located in the midst of the coastal mountain range in the Chilean Metropolitan region 4. It is part of the administrative district Melipilla Province, one of six provinces in the Santiago Metropolitan Region of Chile. With a total surface of 84.363,9 ha, of which 4.275,6 ha are of agriculture use and 52.913,1 ha are covered by forest, Alhué is considered rural area (SIT CONAF 2017). Alhué, in the indigenous tongue Mapudungun “Soul of the Dead”, and according to the legend the place where the devil was born, counts with a population of 4646 inhabitants and an area of 845 m2 (Ministerio de Desarrollo Social 2014). Founded in 1755 as Villa de San Geronimo de la Sierra de Alhué, the town is divided in five administrative districts, namely Villa Alhué, Toro, Tolua, Yerbas Buenas y Carén.

With mean annual precipitation values of 300 mm, it is considered a dryland area (Observatorio Latinoamericano de Conflictos Ambientales 2013). The mean day temperatures vary between an average of 23.3°C in the hottest month January and 10.7°C in the coldest month July. Alhué is characterized by temperate warm climate with little precipitation. It almost exclusively rains in the winter months June – August, with mean precipitation values of 121mm in July, whereas the rest of the year is characterized by sunny days and little air humidity (Climate Data 2016).

Abbildung in dieser Leseprobe nicht enthalten

Figure 10: Map of the Metropolitan Region (light green) with Province Melipilla (green) and commune Alhué (dark green), adapted from Museo de Alhué (2017).

Abbildung in dieser Leseprobe nicht enthalten

Figure 11: Precipitation and Temperature in Alhué (Climate Data 2017).

A particular feature of Alhué is the confluence of two rivers; stream Alhué and stream Caren, which eventually lead into the fresh water lake Rapel. Apart from these water resources, there are various small water reservoirs (Observatorio Latinoamericano de Conflictos Ambientales 2013). Alhué is surrounded by three mining companies extracting gold, silber and copper.

[...]


1 No unambiguous definition for family farms exist, both FAO and HLPE understand agricultural, forestry, fisheries, pastoral and aquaculture production carried out by family members on a land size often not exceeding two hectares as smallholder or family farms (Graeub et al. 2016).

2 In 2014, FAO for the first time launched the International Symposium on Agroecology for Food Security and Nutrition, aiming at promoting agroecological research and practice (Gliessman and Tittonell 2015). The UNCTAD Trade and Environment Report published in 2013 explicitly refers to agroecological practices as a large-scale alternative for conventional agricultural practices (UNCTAD 2013).

3 In October 2016, the Union of Concerned Scientists made a Call for Public Investment in Agroecological Research, currently signed by 467 scientists from different fields (Union of Concerned Scientists, 2016).

4 Exact location: latitude: -33.350, longitude: -71.133 (Google Maps 2017).

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Title
How Can Climate Robust Agroecosystems Be Designed? Coupling Agroecology and the Resilience Approach
Subtitle
Generating On-Field Knowledge
College
The University of Applied Sciences in Eberswalde
Grade
1,3
Author
Year
2017
Pages
105
Catalog Number
V490217
ISBN (eBook)
9783668968394
ISBN (Book)
9783668968400
Language
English
Tags
Agroecology, Resilience, Agriculture, Sustainability
Quote paper
Carmen Schwartz (Author), 2017, How Can Climate Robust Agroecosystems Be Designed? Coupling Agroecology and the Resilience Approach, Munich, GRIN Verlag, https://www.grin.com/document/490217

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