Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space.
We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur.
Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.
Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their significance for carbon sequestration at a global level, along with recent change trends.
Remote sensing data show that in 2010, 43% of all agricultural land globally had at least 10% tree cover and that this has increased by 2% over the previous ten years. Combining geographically and bioclimatically stratified Intergovernmental Panel on Climate Change (IPCC) Tier 1 default estimates of carbon storage with this tree cover analysis, we estimated 45.3 PgC on agricultural land globally, with trees contributing >75%.
Between 2000 and 2010 tree cover increased by 3.7%, resulting in an increase of >2 PgC (or 4.6%) of biomass carbon. On average, globally, biomass carbon increased from 20.4 to 21.4 tC ha−1. Regional and country-level variation in stocks and trends were mapped and tabulated globally, and for all countries. Brazil, Indonesia, China and India had the largest increases in biomass carbon stored on agricultural land, while Argentina, Myanmar, and Sierra Leone had the largest decreases.
Climate change affects not only water resources but also water demand for irrigation. A large proportion of the world’s agriculture depends on groundwater, especially in arid and semi-arid regions In several regions, aquifer resources face depletion. Groundwater recharge has been viewed as a by-product of irrigation return flow, and with climate change, aquifer storage of such flow will be vital. A general review, for a broad- based audience, is given of work on global warming and groundwater resources, summarizing the methods used to analyze the climate change scenarios and the influence of these predicted changes on groundwater resources around the world (especially the impact on regional groundwater resources and irrigation requirements).
Future challenges of adapting to climate change are also discussed. Such challenges include water-resources depletion, increasing irrigation demand, reduced crop yield, and groundwater salinization. The adaptation to and mitigation of these effects is also reported, including useful information for water-resources managers and the development of sustainable groundwater irrigation methods. Rescheduling irrigation according to the season, coordinating the groundwater resources and irrigation demand, developing more accurate and complete modeling prediction methods, and managing the irrigation facilities in different ways would all be considered, based on the particular cases.
This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (win- ter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO2 effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified.
Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982–2006) and three SRES scenarios (B1, B2 and A1B, 2040–2064) under rainfed and irrigated conditions, using a process-based crop model, SIMPLACE <lintul5, drunir,="" heat="">. We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr?1). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO2 effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe.
Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irri- gation and CO2 effects, they should both be considered in the simulation of climate change impacts on crop produc- tion and water availability, particularly for crops and regions with a high proportion of irrigated crop area.
Changing natural conditions determine the land’s suitability for agriculture. The growing demand for food, feed, fiber and bioenergy increases pressure on land and causes trade-offs between different uses of land and ecosystem services. Accordingly, an inventory is required on the changing potentially suitable areas for agriculture under changing climate conditions. We applied a fuzzy logic approach to compute global agricultural suitability to grow the 16 most important food and energy crops according to the climatic, soil and topographic conditions at a spatial resolution of 30 arc seconds.
We present our results for current climate conditions (1981–2010), considering today’s irrigated areas and separately investigate the suitability of densely forested as well as protected areas, in order to investigate their potentials for agriculture. The impact of climate change under SRES A1B conditions, as simulated by the global climate model ECHAM5, on agricultural suitability is shown by comparing the time-period 2071–2100 with 1981–2010. Our results show that climate change will expand suitable cropland by additionally 5.6 million km2, particularly in the Northern high latitudes (mainly in Canada, China and Russia). Most sensitive regions with decreasing suitability are found in the Global South, mainly in tropical regions, where also the suitability for multiple cropping decreases.
We present a pan-European irrigation map based on regional European statistics, a European land use map and a global irrigation map. The map provides spatial information on the distribution of irrigated areas per crop type which allows determining irrigated areas at the level of spatial modelling units. The map is a requirement for a European scale assessment of the impacts of irrigated agriculture on water resources based on spatially distributed modelling of crop growth and water balance. The irrigation map was compiled in a two step procedure.
First, irrigated areas were distributed to potentially irrigated crops at a regional level (European statistical regions NUTS3), combining Farm Structure Survey (FSS) data on irrigated area, crop-specific irrigated area for crops whenever available, and total crop area. Second, crop-specific irrigated area was distributed within each statistical region based on the crop distribution given in our land use map. A global map of irrigated areas with a 5′ resolution was used to further constrain the distribution within each NUTS3 based on the density of irrigated areas.
The constrained distribution of irrigated areas as taken from statistics to a high resolution dataset enables us to estimate irrigated areas for various spatial entities, including administrative, natural and artificial units, providing a reasonable input scenario for large-scale distributed modelling applications. The dataset bridges a gap between global datasets and detailed regional data on the distribution of irrigated areas and provides information for various assessments and modelling applications.
In Southern Europe, irrigated agriculture is by far the largest consumer of freshwater resources. However, consistent information on irrigation water use in the European Union is still lacking. We applied the crop growth model EPIC to calculate irrigation requirements in the EU and Switzerland, combining available regional statistics on crop distribution and crop specific irrigated area with spatial data sources on soils, land use and climate. The model was applied at a 10×10km grid using different irrigation strategies over a period of 8years.
The irrigation requirements reflect the spatial distribution of irrigated areas, climatic conditions and crops. Simulated net irrigation requirements range from 53mm/yr in Denmark to 1120mm/yr in Spain, translating into estimated volumetric net irrigation requirements of 107mio.m3 and 35,919mio.m3, respectively. We estimate gross irrigation demands to be 1.3–2.5 times higher than field requirements, depending on the efficiency of transport and irrigation management.
A comparison with national and regional data on water abstractions for irrigation illustrates the information deficit related to currently available reported data, as not only model limitations but also different national approaches, country-specific uncertainties (illegal or unrecorded abstractions), and restrictions of actual water use come into play. In support of European environmental and agricultural policies, this work provides a large-scale overview on irrigation water requirements in Europe applying a uniform approach with a sufficiently high spatial resolution to support identification of hot spots and regional comparisons. It will also provide a framework for national irrigation water use estimations and supports further analysis of agricultural pressures on water quantity in Europe.
Annual row crops dominate agriculture around the world and have considerable negative environmental impacts, including significant greenhouse gas emissions. Transformative land-use solutions are necessary to mitigate climate change and restore critical ecosystem services. Alley cropping (AC)—the integration of trees with crops—is an agroforestry practice that has been studied as a transformative, multifunctional land-use solution. In the temperate zone, AC has strong potential for climate change mitigation through direct emissions reductions and increases in land-use efficiency via overyielding compared to trees and crops grown separately. In addition, AC provides climate change adaptation potential and ecological benefits by buffering alley crops to weather extremes, diversifying income to hedge financial risk, increasing biodiversity, reducing soil erosion, and improving nutrient-and water-use efficiency.
The scope of temperate AC research and application has been largely limited to simple systems that combine one timber tree species with an annual grain. We propose two frontiers in temperate AC that expand this scope and could transform its climate-related benefits: (i) diversification via woody polyculture and (ii) expanded use of tree crops for food and fodder. While AC is ready now for implementation on marginal lands, we discuss key considerations that could enhance the scalability of the two proposed frontiers and catalyze widespread adoption.
Substantial investment in climate change research has led to dire predictions of the impacts and risks to biodiversity. The Intergovernmental Panel on Climate Change fourth assessment report(1) cites 28,586 studies demonstrating significant biological changes in terrestrial systems(2). Already high extinction rates, driven primarily by habitat loss, are predicted to increase under climate change(3-6). Yet there is little specific advice or precedent in the literature to guide climate adaptation investment for conserving biodiversity within realistic economic constraints(7).
Here we present a systematic ecological and economic analysis of a climate adaptation problem in one of the world's most species-rich and threatened ecosystems: the South African fynbos. We discover a counterintuitive optimal investment strategy that switches twice between options as the available adaptation budget increases. We demonstrate that optimal investment is nonlinearly dependent on available resources, making the choice of how much to invest as important as determining where to invest and what actions to take.
Our study emphasizes the importance of a sound analytical framework for prioritizing adaptation investments(4). Integrating ecological predictions in an economic decision framework will help support complex choices between adaptation options under severe uncertainty. Our prioritization method can be applied at any scale to minimize species loss and to evaluate the robustness of decisions to uncertainty about key assumptions.
This review focuses on biotic responses during intervals of time in the fossil record when the magnitude and rate of climate change exceeded or were comparable with those predicted to occur in the next century (Solomon et al. 2007). These include biotic responses during: (a) the Paleo-Eocene Thermal Maximum and early Eocene Climatic Optimum, (b) the mid-Pliocene warm interval, (c) the Eemian, and (d) the most recent glacial-interglacial transition into the Holocene.
We argue that although the mechanisms responsible for these past changes in climate were different (i.e., natural processes rather than anthropogenic), the rate and magnitude of climate change were often similar to those predicted for the next century and therefore highly relevant to understanding future biotic responses. In all intervals we examine the fossil evidence for the three most commonly predicted future biotic scenarios, namely, extirpation, migration (in the form of a permanent range shift), or adaptation. Focusing predominantly on the terrestrial plant fossil record, we find little evidence for extirpation during warmer intervals; rather, range shifts, community turnover, adaptation, and sometimes an increase in diversity are observed.