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.

Adaptation options under climate change for multifunctional agriculture: a simulation study for western Switzerland

Besides its primary role in producing food and fiber, agriculture also has relevant effects on several other functions, such as management of renewable natural resources. Climate change (CC) may lead to new trade-offs between agricultural functions or aggravate existing ones, but suitable agricultural management may maintain or even improve the ability of agroecosystems to supply these functions. Hence, it is necessary to identify relevant drivers (e.g., cropping practices, local conditions) and their interactions, and how they affect agricultural functions in a changing climate. The goal of this study was to use a modeling framework to analyze the sensitivity of indicators of three important agricultural functions, namely crop yield (food and fiber production function), soil erosion (soil conservation function), and nutrient leaching (clean water provision function), to a wide range of agricultural practices for current and future climate conditions. In a two-step approach, cropping practices that explain high proportions of variance of the different indicators were first identified by an analysis of variance-based sensitivity analysis. Then, most suitable combinations of practices to achieve best performance with respect to each indicator were extracted, and trade-offs were analyzed. The procedure was applied to a region in western Switzerland, considering two different soil types to test the importance of local environmental constraints. Results show that the sensitivity of crop yield and soil erosion due to management is high, while nutrient leaching mostly depends on soil type. We found that the influence of most agricultural practices does not change significantly with CC; only irrigation becomes more relevant as a consequence of decreasing summer rainfall. Trade-offs were identified when focusing on best performances of each indicator separately, and these were amplified under CC. For adaptation to CC in the selected study region, conservation soil management and the use of cropped grasslands appear to be the most suitable options to avoid trade-offs.

Is there a common pattern of future gas-phase air pollution in Europe under diverse climate change scenarios?

Climate change alone influences future levels of tropospheric ozone and their precursors through modifications of gas-phase chemistry, transport, removal, and natural emissions. The goal of this study is to determine at what extent the modes of variability of gas-phase pollutants respond to different climate change scenarios over Europe. The methodology includes the use of the regional modeling system MM5 (regional climate model version)-CHIMERE for a target domain covering Europe. Two full-transient simulations covering from 1991–2050 under the SRES A2 and B2 scenarios driven by ECHO-G global circulation model have been compared. The results indicate that the spatial patterns of variability for tropospheric ozone are similar for both scenarios, but the magnitude of the change signal significantly differs for A2 and B2. The 1991–2050 simulations share common characteristics for their chemical behavior. As observed from the NO2 and α-pinene modes of variability, our simulations suggest that the enhanced ozone chemical activity is driven by a number of parameters, such as the warming-induced increase in biogenic emissions and, to a lesser extent, by the variation in nitrogen dioxide levels. For gas-phase pollutants, the general increasing trend for ozone found under A2 and B2 forcing is due to a multiplicity of climate factors, such as increased temperature, decreased wet removal associated with an overall decrease of precipitation in southern Europe, increased photolysis of primary and secondary pollutants as a consequence of lower cloudiness and increased biogenic emissions fueled by higher temperatures.

Recent trends in Inner Asian forest dynamics to temperature and precipitation indicate high sensitivity to climate change

Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area ‘browning’ during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prior-year lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.