Adapting to climate change through sustainable land management: experiences of a pilot project in Tajikistan

Tajikistan is particularly exposed to the risks of climate change. Its widely degraded landscapes are badly prepared to cope with changes in precipitation patterns, increased temperatures, droughts, and the spread of pests and disease. Sustainable land management (SLM) provides a “basket of opportunities” to address these challenges, particularly for increasing land productivity, improving livelihoods, and protecting ecosystems. Within the Pilot Program for Climate Resilience (PPCR) in Tajikistan 70 SLM technologies and approaches on how to implement SLM were documented with the World Overview of Conservation Approaches and Technologies (WOCAT ) tools in 2011. For this purpose a climate change adaptation module was developed and tested in order to enhance the understanding about climate change resilience of SLM practices and community workshops conducted to on adaptation mechanisms by rural communities in Tajikistan. The analysis came up with four guiding principles for applying SLM for adapting to climate change: 1. Diversification of land use technologies and farm incomes; 2. Intensification of use of natural resources; 3. Expansion of highly productive land use technologies; 4. Protection of land and livelihoods from extreme weather events. Furthermore, SLM must be up-scaled from isolated plots to entire zones or landscapes and the project developed the concept of three concentric villages zones, the in-, near- and off-village zones. Land users, advisors, and decision- and policy makers face the task of finding management practices that best suit site-specific conditions. This task is most efficiently addressed in collaborative effort, and building up and managing a respective knowledge platform.

Buffer capacity: capturing a dimension of resilience to climate change in African smallholder agriculture

Building resilience to climate change in agricultural production can ensure the functioning of agricultural-based livelihoods and reduce their vulnerability to climate change impacts. This paper thus explores how buffer capacity, a characteristic feature of resilience, can be conceptualised and used for assessing the resilience of smallholder agriculture to climate change. It uses the case of conservation agriculture farmers in a Kenyan region and examines how their practices contribute to buffer capacity. Surveys were used to collect data from 41 purposely selected conservation agriculture farmers in the Laikipia region of Kenya. Besides descriptive statistics, factor analysis was used to identify the key dimensions that characterise buffer capacity in the study context. The cluster of practices characterising buffer capacity in conservation agriculture include soil protection, adapted crops, intensification/irrigation, mechanisation and livelihood diversification. Various conservation practices increase buffer capacity, evaluated by farmers in economic, social, ecological and other dimensions. Through conservation agriculture, most farmers improved their productivity and incomes despite drought, improved their environment and social relations. Better-off farmers also reduced their need for labour, but this resulted in lesser income-earning opportunities for the poorer farmers, thus reducing the buffer capacity and resilience of the latter.

Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options

Experts working on behalf of international development organisations need better tools to assist land managers in developing countriesmaintain their livelihoods, as climate change puts pressure on the ecosystemservices that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories andmethods. This reviewtherefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change,whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change.

Climate change and infectious diseases of wildlife: Altered interactions between pathogens, vectors and hosts

Infectious diseases result from the interactions of host, pathogens, and, in the case of vector-borne diseases, also vectors. The interactions involve physiological and ecological mechanisms and they have evolved under a given set of environmental conditions. Environmental change, therefore, will alter host-pathogen-vector interactions and, consequently, the distribution, intensity, and dynamics of infectious diseases. Here, we review how climate change may impact infectious diseases of aquatic and terrestrial wildlife. Climate change can have direct impacts on distribution, life cycle, and physiological status of hosts, pathogens and vectors. While a change in either host, pathogen or vector does not necessarily translate into an alteration of the disease, it is the impact of climate change on the interactions between the disease components which is particularly critical for altered disease risks. Finally, climate factors can modulate disease through modifying the ecological networks host-pathogen-vector systems are belonging to, and climate change can combine with other environmental stressors to induce cumulative effects on infectious diseases. Overall, the influence of climate change on infectious diseases involves different mechanisms, it can be modulated by phenotypic acclimation and/or genotypic adaptation, it depends on the ecological context of the host-pathogen-vector interactions, and it can be modulated by impacts of other stressors. As a consequence of this complexity, non-linear responses of disease systems under climate change are to be expected. To improve predictions on climate change impacts on infectious disease, we suggest that more emphasis should be given to the integration of biomedical and ecological research for studying both the physiological and ecological mechanisms which mediate climate change impacts on disease, and to the development of harmonized methods and approaches to obtain more comparable results, as this would support the discrimination of case-specific versus general mechanisms

Long-term climate change commitment and reversibility: An EMIC Intercomparison

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. Most EMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs for RCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination of CO2 emissions in all EMICs. Restoration of atmospheric CO2 from RCP to preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2.

Multiple greenhouse-gas feedbacks from the land biosphere under future climate change scenarios

Atmospheric concentrations of the three important greenhouse gases (GHGs) CO2, CH4 and N2O are mediated by processes in the terrestrial biosphere that are sensitive to climate and CO2. This leads to feedbacks between climate and land and has contributed to the sharp rise in atmospheric GHG concentrations since pre-industrial times. Here, we apply a process-based model to reproduce the historical atmospheric N2O and CH4 budgets within their uncertainties and apply future scenarios for climate, land-use change and reactive nitrogen (Nr) inputs to investigate future GHG emissions and their feedbacks with climate in a consistent and comprehensive framework1. Results suggest that in a business-as-usual scenario, terrestrial N2O and CH4 emissions increase by 80 and 45%, respectively, and the land becomes a net source of C by AD 2100. N2O and CH4 feedbacks imply an additional warming of 0.4–0.5 °C by AD 2300; on top of 0.8–1.0 °C caused by terrestrial carbon cycle and Albedo feedbacks. The land biosphere represents an increasingly positive feedback to anthropogenic climate change and amplifies equilibrium climate sensitivity by 22–27%. Strong mitigation limits the increase of terrestrial GHG emissions and prevents the land biosphere from acting as an increasingly strong amplifier to anthropogenic climate change.

Adapting agricultural land management to climate change: a regional multi-objective optimization approach

In several regions of the world, climate change is expected to have severe impacts on agricultural systems. Changes in land management are one way to adapt to future climatic conditions, including land-use changes and local adjustments of agricultural practices. In previous studies, options for adaptation have mostly been explored by testing alternative scenarios. Systematic explorations of land management possibilities using optimization approaches were so far mainly restricted to studies of land and resource management under constant climatic conditions. In this study, we bridge this gap and exploit the benefits of multi-objective regional optimization for identifying optimum land management adaptations to climate change. We design a multi-objective optimization routine that integrates a generic crop model and considers two climate scenarios for 2050 in a meso-scale catchment on the Swiss Central Plateau with already limited water resources. The results indicate that adaptation will be necessary in the study area to cope with a decrease in productivity by 0–10 %, an increase in soil loss by 25–35 %, and an increase in N-leaching by 30–45 %. Adaptation options identified here exhibit conflicts between productivity and environmental goals, but compromises are possible. Necessary management changes include (i) adjustments of crop shares, i.e. increasing the proportion of early harvested winter cereals at the expense of irrigated spring crops, (ii) widespread use of reduced tillage, (iii) allocation of irrigated areas to soils with low water-retention capacity at lower elevations, and (iv) conversion of some pre-alpine grasslands to croplands.