ALBERT

Description: Since 1990, the IPCC has produced five Assessment Reports (ARs) including agriculture. Using a database of the ca. 2,100 cited experiments and simulations in the five ARs, our conclusions are that crop yields decline but with large statistical variation. Livestock effects have almost been quantitatively absent. Mitigation assessments need better to link emissions and their mitigation with food production and security; agriculture has been dealt with inconsistently between the IPCC five ARs. IPCC needs to examine interactions between crop resource use efficiencies and include production and nonproduction aspects of food security. Abstract Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to impacts on yields via crop type, region, and whether adaptation was included. Quantitative data on impacts and adaptation in livestock farming have been extremely scarce in the ARs. The main conclusions from impact and adaptation are that crop yields will decline, but that responses have large statistical variation. Mitigation assessments in the ARs have used both bottom‐up and top‐down methods but need better to link emissions and their mitigation with food production and security. Relevant policy options have become broader in later ARs and included more of the social and nonproduction aspects of food security. Our overall conclusion is that agriculture and food security, which are two of the most central, critical, and imminent issues in climate change, have been dealt with an unfocussed and inconsistent manner between the IPCC five ARs. This is partly a result of not only agriculture spanning two IPCC working groups but also the very strong focus on projections from computer crop simulation modeling. For the future, we suggest a need to examine interactions between themes such as crop resource use efficiencies and to include all production and nonproduction aspects of food security in future roles for integrated assessment models.

Description: The projected impact of 1.5 and 2.0°C warming above the pre‐industrial period on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impacts of warming of 〈2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade. Abstract Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming 〉2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by −2.3% to 7.0% under the 1.5°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impact of warming 〈2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.

Description: How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modelling of endotherm distributions remains limited in the current literature. Using the American pika ( Ochotona princeps ) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface-activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface-activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5°C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate-change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate-adaptation actions, management strategies, and conservation plans. This article is protected by copyright. All rights reserved.

Description: Agriculture satisfies the basic need of society to produce food but must do so without undermining the world's capacity to sustain future food production and ecosystem services (Foley et al ., 2011; Rockström et al ., 2009; Foley et al ., 2005). Operating on a planet with finite resources and boundaries, agriculture must operate within three limits (Beddington et al ., 2012); 1) the quantity of food supply that can be produced under a given climate, 2) the quantity of food demanded by a growing and economically changing population, and 3) the impact of food production on the environment. Currently, agriculture and land-use change (LUC) are responsible for ~1/4 of total greenhouse gas (GHG) emissions from human activities (Smith et al ., 2014). As the human population grows, and is projected to move toward a more animal-based diet, it is projected that crop- and livestock production need to increase by 48% and 80% by 2050, respectively (FAO, 2006). It has been suggested that this could elevate agricultural non-CO 2 emissions 76% by 2050 relative to 1995 (Popp et al ., 2010). Yet agriculture has large potentials for mitigating climate change, even at relatively low cost (Smith et al ., 2014; Smith et al ., 2008; Nabuurs et al ., 2007; Schneider & Smith, 2009). This article is protected by copyright. All rights reserved.

Description: Forecasting the consequences of climate change is contingent upon our understanding of the relationship between biodiversity patterns and climatic variability. While the impacts of climate change on individual species have been well-documented, there is a paucity of studies on climate-mediated changes in community dynamics. Our objectives were to investigate the relationship between temporal turnover in avian biodiversity and changes in climatic conditions and to assess the role of landscape fragmentation in affecting this relationship. We hypothesized that community turnover would be highest in regions experiencing the most pronounced changes in climate, and that these patterns would be reduced in human-dominated landscapes. To test this hypothesis, we quantified temporal turnover in avian communities over a 20-year period using data from the New York State Breeding Atlases collected during 1980-85 and 2000-05. We applied Bayesian spatially-varying intercept models to evaluate the relationship between temporal turnover and temporal trends in climatic conditions and landscape fragmentation. We found that models including interaction terms between climate change and landscape fragmentation were superior to models without the interaction terms; suggesting that the relationship between avian community turnover and changes in climatic conditions was affected by the level of landscape fragmentation. Specifically, we found weaker associations between temporal turnover and climatic change in regions with prevalent habitat fragmentation. We suggest that avian communities in fragmented landscapes are more robust to climate change than communities found in contiguous habitats because they are comprised of species with wider thermal niches and thus are less susceptible to shifts in climatic variability. We conclude that highly fragmented regions are likely to undergo less pronounced changes in composition and structure of faunal communities as a result of climate change, whereas those changes are likely to be greater in contiguous and unfragmented habitats. This article is protected by copyright. All rights reserved.

Description: Since 1990, the IPCC has produced five Assessment Reports (ARs) including agriculture. Using a database of the ca. 2,100 cited experiments and simulations in the five ARs, our conclusions are that crop yields decline but with large statistical variation. Livestock effects have almost been quantitatively absent. Mitigation assessments need better to link emissions and their mitigation with food production and security; agriculture has been dealt with inconsistently between the IPCC five ARs. IPCC needs to examine interactions between crop resource use efficiencies and include production and nonproduction aspects of food security. Abstract Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to impacts on yields via crop type, region, and whether adaptation was included. Quantitative data on impacts and adaptation in livestock farming have been extremely scarce in the ARs. The main conclusions from impact and adaptation are that crop yields will decline, but that responses have large statistical variation. Mitigation assessments in the ARs have used both bottom‐up and top‐down methods but need better to link emissions and their mitigation with food production and security. Relevant policy options have become broader in later ARs and included more of the social and nonproduction aspects of food security. Our overall conclusion is that agriculture and food security, which are two of the most central, critical, and imminent issues in climate change, have been dealt with an unfocussed and inconsistent manner between the IPCC five ARs. This is partly a result of not only agriculture spanning two IPCC working groups but also the very strong focus on projections from computer crop simulation modeling. For the future, we suggest a need to examine interactions between themes such as crop resource use efficiencies and to include all production and nonproduction aspects of food security in future roles for integrated assessment models.

Description: The world's freshwater biotas are declining in diversity, range and abundance, more than in other realms, with human appropriation of water. Despite considerable data on the distribution of dams and their hydrological effects on river systems, there are few expansive and long analyses of impacts on freshwater biota. We investigated trends in waterbird communities over 32 years, (1983–2014), at three spatial scales in two similarly sized large river basins, with contrasting levels of water resource development, representing almost a third (29%) of Australia: the Murray–Darling Basin and the Lake Eyre Basin. The Murray–Darling Basin is Australia's most developed river basin (240 dams storing 29,893 GL) while the Lake Eyre Basin is one of the less developed basins (1 dam storing 14 GL). We compared the long-term responses of waterbird communities in the two river basins at river basin, catchment and major wetland scales. Waterbird abundances were strongly related to river flows and rainfall. For the developed Murray–Darling Basin, we identified significant long-term declines in total abundances, functional response groups (e.g., piscivores) and individual species of waterbird ( n  = 50), associated with reductions in cumulative annual flow. These trends indicated ecosystem level changes. Contrastingly, we found no evidence of waterbird declines in the undeveloped Lake Eyre Basin. We also modelled the effects of the Australian Government buying up water rights and returning these to the riverine environment, at a substantial cost (〉3.1 AUD billion) which were projected to partly (18% improvement) restore waterbird abundances, but projected climate change effects could reduce these benefits considerably to only a 1% or 4% improvement, with respective annual recovery of environmental flows of 2,800 GL or 3,200 GL. Our unique large temporal and spatial scale analyses demonstrated severe long-term ecological impact of water resource development on prominent freshwater animals, with implications for global management of water resources. Long-term declining trends in waterbird numbers, at the total numbers, different species and functional response groups, were detected in the Murray–Darling Basin, with its rivers developed by dams. In comparison, there were few trends in the similarly sized but undeveloped Lake Eyre Basin. These two river basins cover near one-third of the Australian continent. These trends in waterbird numbers were consistent at the scale of the entire basin, the two main rivers in each basin and for ten of the most important wetlands in each river basin. These results were from surveys over more than three decades and indicate the long-term impacts of water resource developments on ecosystems, critical for rehabilitation and development of rivers around the world.

Description: Threatened and endangered species are more vulnerable to climate change due to small population and specific geographical distribution. Therefore, identifying and incorporating the biological processes underlying a species’ adaptation to its environment are important for determining whether they can persist in situ. Correlative models are widely used to predict species’ distribution changes, but generally fail to capture the buffering capacity of organisms. Giant pandas ( Ailuropoda melanoleuca ) live in topographically complex mountains and are known to avoid heat stress. Although many studies have found that climate change will lead to severe habitat loss and threaten previous conservation efforts, the mechanisms underlying panda's responses to climate change have not been explored. Here, we present a case study in Daxiangling Mountains, one of the six Mountain Systems that giant panda distributes. We used a mechanistic model, Niche Mapper, to explore what are likely panda habitat response to climate change taking physiological, behavioral and ecological responses into account, through which we map panda's climatic suitable activity area (SAA) for the first time. We combined SAA with bamboo forest distribution to yield highly suitable habitat (HSH) and seasonal suitable habitat (SSH), and their temporal dynamics under climate change were predicted. In general, SAA in the hottest month (July) would reduce 11.7-52.2% by 2070, which is more moderate than predicted bamboo habitat loss (45.6-86.9%). Limited by the availability of bamboo and forest, panda's suitable habitat loss increases, and only 15.5-68.8% of current HSH would remain in 2070. Our method of mechanistic modeling can help to distinguish whether habitat loss is caused by thermal environmental deterioration or food loss under climate change. Furthermore, mechanistic models can produce robust predictions by incorporating ecophysiological feedbacks and minimizing extrapolation into novel environments. We suggest that a mechanistic approach should be incorporated into distribution predictions and conservation planning. This article is protected by copyright. All rights reserved.