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Simulating soil N2O emissions in arable Eastern ScotlandMyrgiotis, Vasileios January 2018 (has links)
Nitrous oxide (N2O) is a powerful greenhouse gas and a major contributor to ozone layer depletion. The application of nitrogenous fertilisers to agricultural soils is a major source of N2O on a global scale. Arable soils receive significant rates of synthetic nitrogen (N) and thus have a considerable N2O footprint. The reduction of the N2O footprint of agricultural systems is a key target for those countries that seek to reduce their contribution to climate change and achieve a more sustainable agriculture. These twin targets are part of Scotland's agro-environmental policy. Because soil N2O emissions vary significantly both temporally and spatially, measuring N2O emissions across wide agricultural areas is impractical. However, the quantification of the N2O footprint of important agricultural regions is very valuable to scientists, farmers and policymakers alike. In this context, agro-ecosystem biogeochemistry models are scientific tools, which are developed using in-depth knowledge on the underlying processes, and are used to quantify N2O emissions across spatial and temporal scales. In Scotland, arable agriculture is concentrated at the Eastern part of the country where wheat, barley and oilseed rape are the most widely cultivated crops. The main aim of this study was to quantify the amount of N2O that is emitted from arable soils due to the cultivation of these three crops in Eastern Scotland by using the Landscape-DNDC model. Landscape-DNDC is a mechanistic biogeochemistry model that describes the flows of energy, water and nutrients in agricultural ecosystems. As part of the study, the parametric sensitivities of key model outputs have been quantified using well-established sensitivity analysis methods, which were tailored in order to consider the particularities of N cycling in arable soils. Driven by the fact that the existence of spatiotemporal uncertainties around field-measured soil N2O data complicates the evaluation of model performance, a novel model evaluation algorithm has been developed and was used to assess the model's predictive accuracy. By combining the knowledge of the model's parametric sensitivity with the abilities of the evaluation algorithm, nine key parameters of Landscape-DNDC were calibrated to UK edaphoclimatic conditions (using the Metropolis-Hastings Bayesian calibration algorithm). Model calibration led to improved prediction of field-measured soil N2O emissions at a set of sites. The model was then coupled to geographically explicit data on climate, soil N2O and crop management and used to simulate N2O emissions from the arable soils of Eastern Scotland. The results show that, on average, 0.59 % of the applied fertiliser N (kg N ha-1) was lost to the atmosphere as N2O. This factor is much lower than the generic N2O emission factor (EF) of 1% and closer to the UK cropland-specific N2O EF (i.e. 0.79%). The predicted annual N2O was the combined result of different drivers (i.e. fertiliser rate, soil and climate variables) but the geographic distribution of the estimated N2O EFs revealed some hotspots of high N2O EF (larger than 1%). Interestingly, these hotspots were caused by the cultivation of winter oilseed rape on soils with high bulk density and clay content. The comparison of the simulated yields per hectare with respective measured data and of the simulated nitrate (NO-3 ) leaching and crop N uptake factors with respective literature-based values showed that the prediction of soil N2O was not made at the expense of realistic prediction of other important aspects of agro-ecosystem biogeochemistry. Also, the study found that the simulated N2O is almost twice as sensitive to soil input uncertainty as the simulated NO-3 is, while, crop N uptake is rather insensitive to this source of uncertainty. Finally, the study shows that the uncertainty around the nine calibrated model parameters affects the prediction of NO-3 leaching strongly but its role in regards to the simulation of N2O emissions is small.
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Climate-smart agriculture and rural livelihoods : the case of the dairy sector in MalawiArakelyan, Irina January 2017 (has links)
Over the last decade climate-smart agriculture (CSA) has been promoted as a new approach to deal with the impacts of climate change on agriculture while simultaneously trying to mitigate emissions and improve food security. This approach suggests that these multiple goals – adaptation, mitigation and food security - could be achieved simultaneously by adopting specific technologies. At its core, CSA describes agricultural interventions that can 1) sustainably increase agricultural productivity, and hence food security and farm incomes; 2) help adapt and build resilience of agricultural systems to climate change; and 3) reduce greenhouse gas emissions from agriculture (including crops, livestock and fisheries). The main focus of CSA is on smallholder producers, many of whom are already marginalized by existing food production systems, their livelihoods increasingly affected by changes in climate. Unsustainable agricultural practices are common amongst these groups. However, there is an increasing awareness of the need to sustain the natural resource base in order to maintain or increase productivity. Malawi is one of the poorest and least developed countries in the world, with chronic food insecurity affecting large parts of the population, and climate variability increasingly noticeable across the country. Agriculture is practiced predominantly on small holdings, with more than 80% of the population depending on land-based income. In this context, the introduction of climate-smart projects and technologies with the potential to deliver triple wins could improve farmers’ incomes and food security, increase their resilience to climate change impacts, as well as deliver global benefits via climate change mitigation. This dissertation looks at the adoption levels of various, potentially climate-smart agricultural practices by smallholder dairy farmers in Malawi, with the view of establishing the current level of engagement in these practices, and identifying the factors that influence adoption. Results show the importance of the socio-economic and institutional factors in explaining the probability of adopting different agricultural practices. In particular, the findings indicate the importance of well-informed and targeted extension support as one of the major enabling factors for the adoption of improved practices. The findings further show that farmers’ climate change perceptions play a key role in the adoption of climate-smart practices. Overall, the thesis concludes that a number of currently unsustainable dairy farm management practices could be improved upon to achieve double or triple-win benefits within a reasonably short timescale, many of them at low cost. In addition, limited adoption rates of several sustainable practices that are already in place could be improved with the provision of more training, knowledge sharing and extension advice and support on the benefits of these practices. However, the thesis argues that before implementing projects and policies that promise triple wins, a careful evaluation of benefits, including mitigation, adaptation, and food security, and risks must be carried out, as triple wins will not be achievable in many cases due to the local and external constraints including lack of skills and knowledge, and lack of funding. In this respect, whether climate-smart agriculture could become a globally sustainable approach to the climate change problem in agriculture, remains to be seen.
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Effect of Climate Change on Farmers' Choice of Crops: An Econometric Analysis2013 October 1900 (has links)
Climate change is being observed through increased average temperatures world-wide, as well as through increased frequency of extreme events, such as floods and droughts. As climate is an uncontrollable yet essential input in the agriculture industry, the impact of climate change may have on crop production in Saskatchewan is of importance. The main objective of this study is to investigate how farmers adapt to climate change by switching their crop mix, and how this crop mix may change under future climate change scenarios. A fractional multinomial logit (FMNL) model was used to assess how total area of cropland has changed over a thirty year time period. The panel data included variables to represent the land characteristics of Saskatchewan (i.e. the three major soil zones - Black, Dark Brown and Brown), climatic variables to represent average monthly temperature and precipitation, and price and policy variables in order to assess how average seeded area of each crop group changed. With these results, a simple simulation model was developed to evaluate how the area of each crop group in a base year comparison (2000) would change under future climate scenarios for each soil zone.
The results from the FMNL model indicate that crop allocation depends largely on the price of other crop groups and temperatures in the spring (April) and summer (July). Climate plays and important role in the major crop groups, such as wheat, canola and pulses. Cool, dry springs are the ideal conditions when choosing nearly all crops, while hot, wet summers increase the choice to leave land to summerfallow. Policy and the different soil zones also play a significant role in area allocation decisions. Changes in policies such as the removal of the Crow’s Nest Pass Agreement, and the removal of oats from the Canadian Wheat Board (CWB) marketing, had a negative impact on the choice to grow wheat, as expected. The different soil zones in Saskatchewan played an important role in area allocation for a majority of the crops, having a negative effect on the choice of wheat over every other crop group except pulses and summerfallow.
Three climate change scenarios were simulated for each soil zone and compared to a base area (year 2000 area seeded) of crop groups. The findings from the projected changes in climate indicate that the area allocated to wheat will continue to decrease into the future, following current trends. The average projected decline in wheat area from the base years by 2099 ranges between 3.5% to 4.6% in the Black soil zone, between 2.7% and 2.9% in the Dark Brown and 2.7% to 4% in the brown soil zone, depending on climate change scenario. Interestingly, the area left to summerfallow is projected to increase over the future climate change scenarios. The choice of wheat is preferred over pulses, feed and forages, while the choice of specialty oilseeds (flaxseed, mustard seed and canary seed) are projected to become preferred over wheat in the future.
The major conclusion from this research are: (i) following current trends, the area devoted to spring wheat and durum wheat would continue to decline into the future; (ii) Area devoted to wheat remains a preferred choice over pulses, feed and forages while specialty oilseeds represent a viable alternative choice to wheat and (iii) most significantly, summerfallow area would increase. This is in contrast to the current trend of declining summerfallow area as a result of tighter crop rotations. This finding was observed throughout all three soil zones as well as for all three climate change projection periods. This will have major implications on individual farmers as well as the economy in Saskatchewan, as summerfallow does not produce a crop in the year it is chosen. It is therefore important to determine a possible new crop mix that would benefit from the projected change in climate. This study could be improved by including a measure of profitability for each crop group and introducing a new crop group that is better suited to the projected change in climate in Saskatchewan.
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Simulations of water balance conditions and cli-mate variability for Sustainable Agriculture and Energy in the Lower Rufiji Basin.Hamisi, Rajabu January 2013 (has links)
This study provides a long-term understanding of the impact of climate varia-bility and land use on seasonal water balance conditions for sustainable agricul-ture development, hydropower generation and ecosystem stability in the Lower Rufiji Basin. The severity of soil drought, extreme flooding and salinity intru-sion in the lower Rufiji floodplains are currently increasing smallholder poverty and enhance the sensitivity on the natural wetlands for shifting farming and livestock pastures. The CoupModel and SWAT hydrological model were ap-plied to assess and compare the impact of climate variability on the water bal-ance. The monthly river discharge was used for calibrating and validating the runoff at the Stiegler's Gorge. The simulated results for water balance compo-nents at Stiegler's Gorge showed 55% of accumulated precipitation is lost through evapotranspiration and 42 % is river runoffs for downstream agricul-ture and ecosystem services. The evaluation of the models simulation perfor-mance and posterior distribution of parameter behavioral value indicates the (GLUE) calibration method in the CoupModel agreed satisfactory with the Bayesian calibration (BC). The minimal variance in the Bayesian Calibration posterior parameter distribution was observed in the parameter for regulating water uptake from (CritThresholDry) and soil moisture availability for soil evaporation(PsiRs_ip). The SWAT simulation showed that south of the central floodplains has high risk of soil drought. The overall assessment implies that drought and river runoff dynamics in the LRB is affected by upstream land use activities. The strategies for building smallholder resilience towards climate change and land use impact requires collective and coordinated water manage-ment actions powered by individual, institutional, financial and technological adaptation.
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Futterpflanzen und Klimawandel : Bewertung von Arten und Sorten landwirtschaftlicher Futterpflanzen in ihrer Reaktion auf veränderte klimatische BedingungenSteffen, Edwin, Bergknecht, Silvia 04 December 2006 (has links)
Es wird ein Überblick über mögliche Auswirkungen des Klimawandels auf den Anbau von Futterpflanzen gegeben, um daraus eventuelle Auswirkungen auf den Ackerfutterbau im Freistaat Sachsen abzuleiten.
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Trade and environment: the environmental impacts of the agricultural sector in South AfricaKengni, Bernard January 2012 (has links)
No description available.
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Trade and environment: the environmental impacts of the agricultural sector in South AfricaKengni, Bernard January 2012 (has links)
No description available.
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Trade and environment: the environmental impacts of the agricultural sector in South AfricaKengni, Bernard January 2012 (has links)
Magister Legum - LLM / South Africa
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Necessidades hídricas das culturas milho e feijão-caupi influenciadas pelas mudanças climáticas no semiárido nordestino / Requirements water of cowpea and maize in climate change conditions in the semiarid the brazilian northeastCavalcante Junior, Edmilson Gomes 23 September 2015 (has links)
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Previous issue date: 2015-09-23 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The overall objective of this study was to assess the impacts that climate change may lead to the development and evapotranspiration of maize and cowpea in the Brazilian semiarid region. The study was conducted in the municipalities of Apodi, Ipanguaçu and Mossoro, the state of Rio Grande do Norte. The determination of crop evapotranspiration, in its different phases, was held by lysimeters of weighing. To check the influence of climate change on culture water consumption were simulated changes in the temperature and relative humidity of the air, through the PRECIS climate model. We evaluated two scenarios of emissions based on the report Intergovernmental Panel on Climate Change: a pessimist called A2 and optimistic B2. The corn crop coefficient suffered greater influence of climate change, because culture has a higher size compared to the reference culture thereby its aerodynamic properties were more influenced by the reduction in relative humidity simulated by the model. Temperatures will be well above the limit tolerated by crops, which could have a negative impact on their development and productivity. With rising temperatures, both cultures have their reduced cycle. The reduction in the cycle also cause a decrease in the total evaporation of the cultures. With the additions expected in air temperature and the decrease in relative humidity , the daily evapotranspiration rate will be higher and will direct effect on irrigation systems, because even occurring a reduction in total evapotranspiration , will require a greater intensity of irrigation to meet the daily demand of crops / O objetivo geral do presente trabalho foi verificar os impactos que as mudanças climáticas podem provocar sobre o desenvolvimento e a evapotranspiração do milho e do feijão-caupi, no semiárido brasileiro. O trabalho foi desenvolvido nos municípios de Apodi, Ipanguaçu e Mossoró, pertencentes ao estado do Rio Grande do Norte. A determinação da evapotranspiração da cultura, em suas diferentes fases, foi realizada através de lisímetros de pesagem. Para verificar a influência das mudanças climáticas sobre o consumo hídrico da cultura foram simuladas alterações na temperatura e na umidade relativa do ar, através do modelo climático PRECIS. Foram avaliados dois cenários de emissões baseados no relatório do IPCC (Intergovernmental Panel on Climate Change): um pessimista denominado A2 e um otimista B2. O coeficiente de cultivo do milho sofreu maior influência das mudanças climáticas, pois a cultura apresenta um porte mais elevado, em comparação com a cultura de referência, com isso, suas propriedades aerodinâmicas foram mais influenciadas pela redução da umidade relativa simulada pelo modelo. As temperaturas ficarão muito acima do limite tolerado pelas culturas, o que poderá repercutir negativamente no seu desenvolvimento e consequentemente no rendimento. Com o aumento nas temperaturas, ambas as culturas terão seus ciclos reduzidos. A redução no ciclo também provocará uma diminuição na evapotranspiração total das culturas. Com os acréscimos esperados na temperatura do ar e a redução na umidade relativa, a taxa diária da evapotranspiração ficará maior e apresentará efeito direto sobre os sistemas de irrigação, pois mesmo ocorrendo uma redução na evapotranspiração total, necessitarão de uma maior intensidade de irrigação para atender a demanda diária das culturas
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Trees in the Andes:: Sustainable livelihood strategies for risk reductionJost, François Paul 10 October 2016 (has links)
High mountain regions including the Andean region are very sensitive to climate change. Farmers in the central Andes of Peru are increasingly being exposed to the impacts of climate variability. This transdisciplinary research uses field laboratories, combining the farming system and the sustainable livelihood approaches, to carry out social, ecological, and financial assessments so as to identify sustainable and resilient livelihood strategies for small-scale Andean farmers.
The first research step studies and characterizes farm household systems, influenced by their biophysical and socioeconomic contexts, for which two vulnerability indices were elaborated. Focused on the climate variability, the five livelihood assets and the three IPCC’s vulnerability components, these indices show the highly sensitive conditions of most communities with poor health conditions, access to infrastructure and public services. Farmers’ capacity of response is often limited by the low on-farm diversity and lack of organization. Thereafter, sustainable livelihood strategies were identified. These include on-farm intensification and non-farm labor intensification for lowland and better-access communities. In the middle-access and highland communities, where temporary migration is a common coping strategy, sustainable scenarios include an increment in diversification strategies through agrobiodiversity and a larger share of tree-based production systems.
Furthermore, research step II explores local strategies to cope with agricultural droughts and evaluates, by means of natural resource assessment methods, agroforestry systems as an alternative to reduce their negative effects. Mainly affected by the increasing variation in precipitation events, farmers identify off-farm and on-farm diversification as adaptive strategies against agricultural droughts that reduce the weather dependence and covariance between livelihood activities. Among the introduction of more resistant crop and pasture varieties, the incorporation of trees in their system is desired because of their positive influence in soil moisture and crop yields. Soil moisture in agroforestry systems with eucalyptus trees is 10-20% higher than in agricultural systems during the beginning of the wet season. Differences in the soil moisture during the end of the dry season and in the potato yield are not evident between these systems, although an area without sowing reduced the agricultural output in 13-17% in agroforestry systems.
Research step III seeks to maximize the efficiency of resource allocation in farm household systems by developing a linear programming optimization model. This financial assessment underpinned the need of additional off-farm activities for resource-scarcer farmers. In addition, under interest rates below 15% the model includes tree-based production systems as part of the optimal solution. However, with increasing interest rates, a higher share of land is used to cover household’s basic needs and fewer resources are available for capital accumulation activities such as forestry. Variations introduced in the model show that pasture systems are more sensitive to changes in the production outputs, whereas variation in farm worker wages and tree prices affected less the optimal solutions, making farming systems less sensitive to these market changes.
Finally, the incorporation of tree-based systems have proved to be a sustainable and resilient livelihood strategy against climate variability available for particular farm household systems of the study area.:1 Introduction - 1 -
1.1 Introduction and justification - 1 -
1.2 Objectives and thesis statements - 2 -
1.3 Outline - 3 -
1.4 Definition of terms - 5 -
1.4.1 Vulnerability - 5 -
1.4.2 Resilience - 7 -
1.4.3 Agroforestry systems - 8 -
1.4.4 Farming system approach - 9 -
1.4.5 Farm household system - 10 -
1.4.6 Sustainable livelihood approach - 10 -
2 Framework and study site - 14 -
2.1 Theoretical framework - 14 -
2.2 Methodological framework - 18 -
2.2.1 Field laboratories - 18 -
2.2.2 Methods - 19 -
2.2.3 Methodology applied in research step I:
Vulnerability in Achamayo - 21 -
2.2.4 Methodology applied in research step II:
Agroforestry systems and agricultural droughts - 29 -
2.2.5 Methodology applied in research step III:
Modeling small farm production systems - 33 -
2.2.6 Selection of case studies - 34 -
2.3 Study area - 35 -
2.3.1 Soils and topography - 35 -
2.3.2 Weather - 37 -
2.3.3 Agro-ecological zones and vegetation - 38 -
2.3.4 Climate change - 40 -
2.3.5 Socioeconomic characteristics - 42 -
2.3.6 Population - 43 -
2.3.7 External determinants - 71 -
2.4 Case studies - 47 -
2.4.1 Lowland communities (L) - 49 -
2.4.2 Middle access communities (M) - 50 -
2.4.3 Highland communities (H) - 51 -
3 Vulnerability in Achamayo - 53 -
3.1 Results - 53 -
3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 -
3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 -
3.2 Discussion - 71 -
3.2.1 Climate variability and extreme events - 71 -
3.2.2 Human capital - 71 -
3.2.3 Social capital - 71 -
3.2.4 Natural capital - 71 -
3.2.5 Physical capital - 71 -
3.2.6 Financial capital - 71 -
3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 -
3.3 Conclusion - 92 -
4 Agroforestry systems and agricultural droughts - 95 -
4.1 Results - 96 -
4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 -
4.1.2 Agricultural droughts in the farm household systems - 97 -
4.1.3 Farming forestry systems and land-use decision-making - 102 -
4.1.4 Influence of trees in the soil moisture and yield - 104 -
4.2 Discussion - 110 -
4.2.1 Climate change and agricultural droughts - 110 -
4.2.2 Farm forestry systems and land-use decision-making - 115 -
4.2.3 Influence of trees in the soil moisture and yield - 117 -
4.3 Conclusion - 121 -
5 Modeling small farm production systems: optimization of resource allocation - 123 -
5.1 Methodology - 124 -
5.1.1 Optimization Model - 126 -
5.1.2 Plan of optimization - 128 -
5.1.3 Production systems - 131 -
5.1.4 Constraints - 134 -
5.2 Results - 138 -
5.2.1 Model - 138 -
5.2.2 Interest rates - 142 -
5.2.3 Sensitivity analyses - 146 -
5.3 Discussion - 151 -
5.3.1 Cash flows - 151 -
5.3.2 Model outcomes - 152 -
5.3.3 Interest rates - 155 -
5.3.4 Sensitivity analyses - 159 -
5.4 Conclusion - 169 -
6 Synthesis - 171 -
6.1 Lessons learned - 171 -
6.1.1 Research step I - 172 -
6.1.2 Research step II - 175 -
6.1.3 Research step III - 176 -
6.2 Conclusions & outlook - 179 -
6.2.1 General conclusions - 179 -
6.2.2 Outlook - 181 -
References - 185 -
Appendix - 199 - / Las zonas montañosas, incluyendo la región andina son muy sensibles al cambio climático. Los agricultores de los Andes centrales del Perú están cada vez más expuestos a los efectos de la variabilidad climática. Esta investigación transdisciplinaria utiliza laboratorios de campo (field laboratories), combinando los enfoques de sistemas agrícolas y de medios de vida sostenibles, para llevar a cabo evaluaciones sociales, ecológicas y financieras con el fin de identificar estrategias sostenibles y resilientes para los agricultores andinos de pequeña escala.
La primera fase de la investigación caracteriza a los sistemas agrícolas familiares, influenciados por sus contextos biofísicos y socioeconómicos, para lo cual se elaboraron dos índices de vulnerabilidad centrados en la variabilidad del clima, los cinco activos de los medios de vida y los tres componentes de la vulnerabilidad del IPCC. Estos índices muestran las condiciones de alta sensibilidad de la mayoría de las comunidades, con malas condiciones de salud y poco acceso a la infraestructura y a los servicios públicos. La capacidad de respuesta de los agricultores es a menudo limitada por la baja diversidad en las actividades agrícolas y la falta de organización. Posteriormente se identificaron las estrategias de medios de vida sostenibles. Estas incluyen la intensificación en las actividades agrícolas y la intensificación del trabajo no agrícola en las comunidades de zonas bajas y con mejor acceso. En las comunidades con menor acceso y zonas altas la migración temporal es una estrategia de afrontamiento común. Los escenarios sostenibles en estas comunidades incluyen un incremento en las estrategias de diversificación p. ej. a través de un aumento de la biodiversidad agrícola y una mayor proporción de sistemas de producción asociados con árboles.
Por otra parte, la segunda fase de la investigación explora las estrategias locales para hacer frente a las sequías agrícolas y evalúa, por medio de métodos de evaluación de recursos naturales, los sistemas agroforestales como alternativa para reducir sus efectos negativos. Afectados principalmente por el aumento en la variación de las precipitaciones, los pequeños agricultores identifican a la diversificación de actividades dentro y fuera de sus parcelas agrícolas como una estrategia de adaptación frente a las sequías agrícolas que reduce la dependencia climática y la covarianza entre las actividades de subsistencia. Dentro de la introducción de variedades de cultivos y pastos más resistentes, como parte de la solución, los agricultores desean la incorporación de árboles en su sistema debido a su influencia positiva en la humedad del suelo y en los rendimientos de los cultivos. La humedad del suelo en sistemas agroforestales con árboles de eucalipto es un 10-20% mayor que en los sistemas agrícolas durante el comienzo de la estación húmeda. Las diferencias en la humedad del suelo durante el final de la estación seca y en el rendimiento de los cultivos de papa no son evidentes entre estos dos sistemas.
A pesar de esto, el espacio sin siembra dejado en los sistemas agroforestales redujo la producción agrícola en un 13-17%. La tercera fase de la investigación busca maximizar la eficiencia en la asignación de recursos en los sistemas agrícolas familiares mediante el desarrollo de un modelo de optimización de programación lineal. Esta evaluación financiera respalda la necesidad de actividades adicionales no-agrícolas para agricultores con recursos más escasos. Además, con tasas de interés por debajo del 15%, el modelo siempre incluye a los sistemas de producción forestales y/o agroforestales como parte de las soluciones óptimas. Sin embargo, con el aumento de las tasas de interés, una mayor proporción de tierra se utiliza para cubrir las necesidades básicas del hogar y menos recursos están disponibles para las actividades de acumulación de capital como la silvicultura. Las variaciones introducidas en el modelo muestran que los sistemas de pastoreo son más sensibles a los cambios en los condiciones de producción. Por otro lado, la variación en los salarios de los trabajadores agrícolas y en los precios de los árboles afectan en un menor grado las soluciones óptimas, proporcionando sistemas agrícolas menos sensibles a estos cambios en el mercado.
Finalmente, la incorporación de árboles en los sistemas agrícolas ha demostrado ser una estrategia de vida sostenible y resiliente a la variabilidad climática disponible para determinados sistemas agrícolas familiares de la zona de estudio.:1 Introduction - 1 -
1.1 Introduction and justification - 1 -
1.2 Objectives and thesis statements - 2 -
1.3 Outline - 3 -
1.4 Definition of terms - 5 -
1.4.1 Vulnerability - 5 -
1.4.2 Resilience - 7 -
1.4.3 Agroforestry systems - 8 -
1.4.4 Farming system approach - 9 -
1.4.5 Farm household system - 10 -
1.4.6 Sustainable livelihood approach - 10 -
2 Framework and study site - 14 -
2.1 Theoretical framework - 14 -
2.2 Methodological framework - 18 -
2.2.1 Field laboratories - 18 -
2.2.2 Methods - 19 -
2.2.3 Methodology applied in research step I:
Vulnerability in Achamayo - 21 -
2.2.4 Methodology applied in research step II:
Agroforestry systems and agricultural droughts - 29 -
2.2.5 Methodology applied in research step III:
Modeling small farm production systems - 33 -
2.2.6 Selection of case studies - 34 -
2.3 Study area - 35 -
2.3.1 Soils and topography - 35 -
2.3.2 Weather - 37 -
2.3.3 Agro-ecological zones and vegetation - 38 -
2.3.4 Climate change - 40 -
2.3.5 Socioeconomic characteristics - 42 -
2.3.6 Population - 43 -
2.3.7 External determinants - 71 -
2.4 Case studies - 47 -
2.4.1 Lowland communities (L) - 49 -
2.4.2 Middle access communities (M) - 50 -
2.4.3 Highland communities (H) - 51 -
3 Vulnerability in Achamayo - 53 -
3.1 Results - 53 -
3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 -
3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 -
3.2 Discussion - 71 -
3.2.1 Climate variability and extreme events - 71 -
3.2.2 Human capital - 71 -
3.2.3 Social capital - 71 -
3.2.4 Natural capital - 71 -
3.2.5 Physical capital - 71 -
3.2.6 Financial capital - 71 -
3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 -
3.3 Conclusion - 92 -
4 Agroforestry systems and agricultural droughts - 95 -
4.1 Results - 96 -
4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 -
4.1.2 Agricultural droughts in the farm household systems - 97 -
4.1.3 Farming forestry systems and land-use decision-making - 102 -
4.1.4 Influence of trees in the soil moisture and yield - 104 -
4.2 Discussion - 110 -
4.2.1 Climate change and agricultural droughts - 110 -
4.2.2 Farm forestry systems and land-use decision-making - 115 -
4.2.3 Influence of trees in the soil moisture and yield - 117 -
4.3 Conclusion - 121 -
5 Modeling small farm production systems: optimization of resource allocation - 123 -
5.1 Methodology - 124 -
5.1.1 Optimization Model - 126 -
5.1.2 Plan of optimization - 128 -
5.1.3 Production systems - 131 -
5.1.4 Constraints - 134 -
5.2 Results - 138 -
5.2.1 Model - 138 -
5.2.2 Interest rates - 142 -
5.2.3 Sensitivity analyses - 146 -
5.3 Discussion - 151 -
5.3.1 Cash flows - 151 -
5.3.2 Model outcomes - 152 -
5.3.3 Interest rates - 155 -
5.3.4 Sensitivity analyses - 159 -
5.4 Conclusion - 169 -
6 Synthesis - 171 -
6.1 Lessons learned - 171 -
6.1.1 Research step I - 172 -
6.1.2 Research step II - 175 -
6.1.3 Research step III - 176 -
6.2 Conclusions & outlook - 179 -
6.2.1 General conclusions - 179 -
6.2.2 Outlook - 181 -
References - 185 -
Appendix - 199 - / Hochgebirgsregionen einschließlich der Andenregion sind gegenüber dem Klimawandel sehr empfindlich. Die in den zentralen Anden von Peru lebenden Bauern sind mehr und mehr den Auswirkungen durch Klimaschwankungen ausgesetzt. Diese transdisziplinäre Forschung nutzt Feldlabore, die das System der landwirtschaftlichen Bewirtschaftung und Ansätze zur nachhaltigen Lebensunterhaltssicherung kombinieren, um soziale, ökologische und ökonomische Erhebungen durchzuführen, so dass nachhaltige Livelihood-Strategien für die Kleinbauern in den Anden aufgezeigt werden können.
Der erste Forschungsschritt untersucht und charakterisiert die bäuerlichen Haushaltssysteme, die durch ihre biophysikalischen und sozioökonomischen Kontexte beeinflusst sind. Hierfür wurden zwei Vulnerabilitätsindizes herausgearbeitet, die Klimavariabilität und die fünf Güter des Sustainable Livelihood-Konzepts im Fokus haben, sowie die drei Vulnerabilitätskomponenten des Intergovernmental Panel on Climate Change (IPCC). Diese Indizes decken die hochgradige Sensitivität für die meisten Gemeinden auf, aufgrund des schlechten Gesundheitszustandes sowie dem Mangel an Infrastruktur und öffentlichen Dienstleistungen. Die Fähigkeit der Bauern damit umzugehen, ist zumeist begrenzt durch eine geringe Diversität und fehlende Organisation auf den Farmen. Anschließend werden nachhaltige Livelihood-Strategien aufgezeigt. Diese umfassen die Intensivierung der Arbeit in der Landwirtschaft und der Arbeitskraft außerhalb der Landwirtschaft für Gemeinden im Flachland sowie besser erreichbare Gemeinden. In Hochlandgemeinden und Gemeinden die schwer zugänglich sind, ist temporäre Migration eine geläufige Bewältigungsstrategie. Nachhaltige Szenarien in diesen Gemeinden beinhalten eine höhere Anzahl an Diversifizierungsstrategien wie die Steigerung von Agro-Biodiversität und dem Anteil an baumbasierten Produktionssystemen.
Forschungsschritt II untersucht lokale Strategien, um die landwirtschaftliche Dürre zu bewältigen und bewertet – mit Hilfe von Naturressourcenbewertungsverfahren – Agroforstsysteme als eine Alternative, um die negativen Auswirkungen der Trockenzeiten zu verringern. Beeinträchtigt durch zunehmende Niederschlagsschwankungen, identifizieren Bauern die Diversifizierung von landwirtschaftlichen und nicht-landwirtschaftlichen Aktivitäten als Anpassungsstrategie bei landwirtschaftliche Dürre, wodurch die Abhängigkeit vom Wetter und die Kovarianz zwischen den Aktivitäten für den Lebensunterhalt reduziert werden kann. Neben der Einführung resistenterer Kultur- und Weidepflanzen, ist die Einbeziehung von Bäumen in das System wünschenswert, aufgrund ihres positiven Einflusses auf die Bodenfeuchte und Erträge. Die Bodenfeuchte in agroforstwirtschaftlichen Systemen mit Eukalyptusbäumen ist während der beginnenden Feuchtperiode 20% höher als in landwirtschaftlichen Systemen. Die Unterschiede der Bodenfeuchte am Ende der Trockenzeit und bezüglich des Kartoffelertrags sind zwischen diesen Systemen nicht markant, obwohl eine Fläche, auf der keine Saat ausgebracht wurde, den landwirtschaftlichen Ertrag in Agroforstsystemen um 13 bis 17% mindert.
Forschungsschritt III versucht die Effizienz der Ressourcenzuordnung in Farmhaushaltssystemen zu maximieren, indem ein Optimierungsmodell mit Hilfe der linearen Programmierung entwickelt wird. Diese ökonomische Erhebung unterstreicht die Notwendigkeit zusätzlicher nichtlandwirtschaftlicher Aktivitäten für ressourcenärmere Bauern. Bei Zinsraten unter 15% umfasst das Model baumbasierte Produktionssysteme als einen Teil der optimalen Lösung. Mit steigenden Zinsraten wird jedoch eine größere Bodenfläche dazu verwendet, um die Grundbedürfnisse der Haushalte zu decken und es stehen weniger Ressourcen für Aktivitäten zur Kapitalanhäufung wie Forstwirtschaft zur Verfügung. Die in das Modell involvierten Variationen zeigen, dass Weidesysteme sensibler auf Veränderungen des Produktionsausstoßes reagieren. Schwankungen bei den Löhnen der Farmer und Veränderungen der Baumpreise beeinträchtigen hingegen die optimalen Lösungen weniger. Dadurch sind die landwirtschaftlichen Systeme gegenüber Marktschwankungen weniger anfällig.
Abschließend erweist sich, dass – für bestimmte Farmhaushaltssysteme im Untersuchungsgebiet – die Einbeziehung baumbasierter Systeme als nachhaltige und resiliente Livelihood-Strategie angesichts von Klimaschwankungen nützlich ist.:1 Introduction - 1 -
1.1 Introduction and justification - 1 -
1.2 Objectives and thesis statements - 2 -
1.3 Outline - 3 -
1.4 Definition of terms - 5 -
1.4.1 Vulnerability - 5 -
1.4.2 Resilience - 7 -
1.4.3 Agroforestry systems - 8 -
1.4.4 Farming system approach - 9 -
1.4.5 Farm household system - 10 -
1.4.6 Sustainable livelihood approach - 10 -
2 Framework and study site - 14 -
2.1 Theoretical framework - 14 -
2.2 Methodological framework - 18 -
2.2.1 Field laboratories - 18 -
2.2.2 Methods - 19 -
2.2.3 Methodology applied in research step I:
Vulnerability in Achamayo - 21 -
2.2.4 Methodology applied in research step II:
Agroforestry systems and agricultural droughts - 29 -
2.2.5 Methodology applied in research step III:
Modeling small farm production systems - 33 -
2.2.6 Selection of case studies - 34 -
2.3 Study area - 35 -
2.3.1 Soils and topography - 35 -
2.3.2 Weather - 37 -
2.3.3 Agro-ecological zones and vegetation - 38 -
2.3.4 Climate change - 40 -
2.3.5 Socioeconomic characteristics - 42 -
2.3.6 Population - 43 -
2.3.7 External determinants - 71 -
2.4 Case studies - 47 -
2.4.1 Lowland communities (L) - 49 -
2.4.2 Middle access communities (M) - 50 -
2.4.3 Highland communities (H) - 51 -
3 Vulnerability in Achamayo - 53 -
3.1 Results - 53 -
3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 -
3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 -
3.2 Discussion - 71 -
3.2.1 Climate variability and extreme events - 71 -
3.2.2 Human capital - 71 -
3.2.3 Social capital - 71 -
3.2.4 Natural capital - 71 -
3.2.5 Physical capital - 71 -
3.2.6 Financial capital - 71 -
3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 -
3.3 Conclusion - 92 -
4 Agroforestry systems and agricultural droughts - 95 -
4.1 Results - 96 -
4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 -
4.1.2 Agricultural droughts in the farm household systems - 97 -
4.1.3 Farming forestry systems and land-use decision-making - 102 -
4.1.4 Influence of trees in the soil moisture and yield - 104 -
4.2 Discussion - 110 -
4.2.1 Climate change and agricultural droughts - 110 -
4.2.2 Farm forestry systems and land-use decision-making - 115 -
4.2.3 Influence of trees in the soil moisture and yield - 117 -
4.3 Conclusion - 121 -
5 Modeling small farm production systems: optimization of resource allocation - 123 -
5.1 Methodology - 124 -
5.1.1 Optimization Model - 126 -
5.1.2 Plan of optimization - 128 -
5.1.3 Production systems - 131 -
5.1.4 Constraints - 134 -
5.2 Results - 138 -
5.2.1 Model - 138 -
5.2.2 Interest rates - 142 -
5.2.3 Sensitivity analyses - 146 -
5.3 Discussion - 151 -
5.3.1 Cash flows - 151 -
5.3.2 Model outcomes - 152 -
5.3.3 Interest rates - 155 -
5.3.4 Sensitivity analyses - 159 -
5.4 Conclusion - 169 -
6 Synthesis - 171 -
6.1 Lessons learned - 171 -
6.1.1 Research step I - 172 -
6.1.2 Research step II - 175 -
6.1.3 Research step III - 176 -
6.2 Conclusions & outlook - 179 -
6.2.1 General conclusions - 179 -
6.2.2 Outlook - 181 -
References - 185 -
Appendix - 199 - / Regiões altomontanas, incluindo os Andes são extremamente sensíveis aos impactos das mudanças climáticas. Pequenos agricultores da região central dos Andes Peruanos estão progressivamente sendo expostos aos impactos das variações climáticas. A presente investigação transdisciplinar utiliza “field laboratories”, combinando os enfoques de sistemas rurais e dos meios de subsistência sustentáveis, visando uma avaliação social, ecológica e financeira, com intuito de se identificar estratégias resilientes e sustentáveis para os pequenos agricultores Andinos.
A primeira etapa do presente estudo investiga e caracteriza os sistemas rurais, influenciados por seus contextos biofísicos e socioeconômicos, para os quais foram elaborados dois índices de vulnerabilidade focados na variabilidade climática, nos recursos dos meios de vida (cinco capitais) e nos três componentes da vulnerabilidade do IPCC. Esses índices mostram as condições altamente sensíveis da maioria das comunidades, com más condições de saúde, acesso à infra-estrutura e serviços públicos. A capacidade de resposta dos pequenos agricultores é frequentemente limitada pela baixa diversificação de actividades na exploração agricola e falta de organização. Posteriormente, foram identificadas estratégias de subsitência sustentáveis. Estas incluem a intensificação tanto do trabalho rural, quanto do não-agrícola para as comunidades de terras baixas e mais acessíveis. Para as comunidades altomontanas e com menor acesso, a migração temporária é uma estratégia de enfrentamento comum. Cenários sustentáveis para essas comunidades incluem um incremento nas estratégias de diversificação p. ex. aumentando a agrobiodiversidade e a parcela dos sistemas de produção florestais.
A segunda etapa da pesquisa explora estratégias locais para lidar com as secas agrícolas e investiga, por meio de métodos de avaliação de recursos naturais, sistemas agroflorestais como alternativa para reduzir os seus efeitos negativos. Afetado principalmente pelo aumento da variação da precipitação, os agricultores identificam a diversificação tanto no trabalho rural, quanto no não-agrícola, como estratégias adaptativas contra secas agrícolas que reduzam a dependência do clima e covariância entre atividades de subsitência. Entre a introdução de culturas e de pastagens de variedades mais resistentes, a incorporação de árvores em seu sistema é desejada por conta da sua influência positiva na umidade do solo e no rendimento das culturas. A umidade do solo em sistemas agroflorestais com árvores de eucalipto é de 10-20% maior do que em sistemas agrícolas durante o início da estação chuvosa. As diferenças na umidade do solo durante o final da estação seca e na produtividade da batata não são evidentes entre estes dois sistemas. Apesar disso, o espaço sem semeadura deixado em sistemas agroflorestais reduziu a produção agrícola em 13-17%.
A terceira etapa da presente investigação visa maximizar a eficiência da alocação de recursos em sistemas agrícolas familiares por meio do desenvolvimento de um modelo de otimização de programação linear. Esta avaliação financeira sustenta a necessidade de atividades não-agrícolas adicionais para agricultores com recursos escassos. Ademais, sob taxas de juros abaixo de 15%, o modelo inclui sistemas de produção florestais como parte da solução ideal. Contudo, com o aumento das taxas de juros, uma parcela maior da propriedade é usada para garantir as necessidades básicas, e portanto, menos recursos do agregado familiar estão disponíveis para atividades de acumulação de capital, tais como a silvicultura. Variações introduzidas no modelo mostram que sistemas de pastagem são mais sensíveis a mudanças nas condições de produção. Ademais, variaçãoes nos salários dos trabalhadores agrícolas e nos preços de árvores afetam menos as soluções ótimas, tornando os sistemas agrícolas menos sensíveis a estas mudanças do mercado.
Por fim, a incorporação de sistemas florestais provaram ser uma estratégia de subsistência sustentável e resiliente contra a variação climática para determinados sistemas de agricultura familiar da área de estudo.:1 Introduction - 1 -
1.1 Introduction and justification - 1 -
1.2 Objectives and thesis statements - 2 -
1.3 Outline - 3 -
1.4 Definition of terms - 5 -
1.4.1 Vulnerability - 5 -
1.4.2 Resilience - 7 -
1.4.3 Agroforestry systems - 8 -
1.4.4 Farming system approach - 9 -
1.4.5 Farm household system - 10 -
1.4.6 Sustainable livelihood approach - 10 -
2 Framework and study site - 14 -
2.1 Theoretical framework - 14 -
2.2 Methodological framework - 18 -
2.2.1 Field laboratories - 18 -
2.2.2 Methods - 19 -
2.2.3 Methodology applied in research step I:
Vulnerability in Achamayo - 21 -
2.2.4 Methodology applied in research step II:
Agroforestry systems and agricultural droughts - 29 -
2.2.5 Methodology applied in research step III:
Modeling small farm production systems - 33 -
2.2.6 Selection of case studies - 34 -
2.3 Study area - 35 -
2.3.1 Soils and topography - 35 -
2.3.2 Weather - 37 -
2.3.3 Agro-ecological zones and vegetation - 38 -
2.3.4 Climate change - 40 -
2.3.5 Socioeconomic characteristics - 42 -
2.3.6 Population - 43 -
2.3.7 External determinants - 71 -
2.4 Case studies - 47 -
2.4.1 Lowland communities (L) - 49 -
2.4.2 Middle access communities (M) - 50 -
2.4.3 Highland communities (H) - 51 -
3 Vulnerability in Achamayo - 53 -
3.1 Results - 53 -
3.1.1 Sustainable Livelihood Vulnerability Index (S-LVI) - 53 -
3.1.2 IPCC Livelihood Vulnerability Index (LVI-IPCC) - 68 -
3.2 Discussion - 71 -
3.2.1 Climate variability and extreme events - 71 -
3.2.2 Human capital - 71 -
3.2.3 Social capital - 71 -
3.2.4 Natural capital - 71 -
3.2.5 Physical capital - 71 -
3.2.6 Financial capital - 71 -
3.2.7 Livelihood strategies following the S-LVI and LVI-IPCC indices - 86 -
3.3 Conclusion - 92 -
4 Agroforestry systems and agricultural droughts - 95 -
4.1 Results - 96 -
4.1.1 Farmers’ experience and perception on climate variability and agricultural droughts - 96 -
4.1.2 Agricultural droughts in the farm household systems - 97 -
4.1.3 Farming forestry systems and land-use decision-making - 102 -
4.1.4 Influence of trees in the soil moisture and yield - 104 -
4.2 Discussion - 110 -
4.2.1 Climate change and agricultural droughts - 110 -
4.2.2 Farm forestry systems and land-use decision-making - 115 -
4.2.3 Influence of trees in the soil moisture and yield - 117 -
4.3 Conclusion - 121 -
5 Modeling small farm production systems: optimization of resource allocation - 123 -
5.1 Methodology - 124 -
5.1.1 Optimization Model - 126 -
5.1.2 Plan of optimization - 128 -
5.1.3 Production systems - 131 -
5.1.4 Constraints - 134 -
5.2 Results - 138 -
5.2.1 Model - 138 -
5.2.2 Interest rates - 142 -
5.2.3 Sensitivity analyses - 146 -
5.3 Discussion - 151 -
5.3.1 Cash flows - 151 -
5.3.2 Model outcomes - 152 -
5.3.3 Interest rates - 155 -
5.3.4 Sensitivity analyses - 159 -
5.4 Conclusion - 169 -
6 Synthesis - 171 -
6.1 Lessons learned - 171 -
6.1.1 Research step I - 172 -
6.1.2 Research step II - 175 -
6.1.3 Research step III - 176 -
6.2 Conclusions & outlook - 179 -
6.2.1 General conclusions - 179 -
6.2.2 Outlook - 181 -
References - 185 -
Appendix - 199 -
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