Potential impacts of future land use and climate change on the Red List status of the Proteaceae in the Cape Floristic Region, South Africa

Using spatial predictions of future threats to biodiversity, we assessed for the first time the relative potential impacts of future land use and climate change on the threat status of plant species. We thus estimated how many taxa could be affected by future threats that are usually not included in current IUCN Red List assessments. Here, we computed the Red List status including future threats of 227 Proteaceae taxa endemic to the Cape Floristic Region, South Africa, and compared this with their Red List status excluding future threats. We developed eight different land use and climate change scenarios for the year 2020, providing a range of best‐ to worst‐case scenarios. Four scenarios include only the effects of future land use change, while the other four also include the impacts of projected anthropogenic climate change (HadCM2 IS92a GGa), using niche‐based models. Up to a third of the 227 Proteaceae taxa are uplisted (become more threatened) by up to three threat categories if future threats as predicted for 2020 are included, and the proportion of threatened Proteaceae taxa rises on average by 9% (range 2–16%), depending on the scenario. With increasing severity of the scenarios, the proportion of Critically Endangered taxa increases from about 1% to 7% and almost 2% of the 227 Proteaceae taxa become Extinct because of climate change. Overall, climate change has the most severe effects on the Proteaceae, but land use change also severely affects some taxa. Most of the threatened taxa occur in low‐lying coastal areas, but the proportion of threatened taxa changes considerably in inland mountain areas if future threats are included. Our approach gives important insights into how, where and when future threats could affect species persistence and can in a sense be seen as a test of the value of planned interventions for conservation.     

Forecasting the combined effects of climate and land use change on Mexican bats

Aim

Climate and land use change are among the most important threatening processes driving biodiversity loss, especially in the tropics. Although the potential impacts of each threat have been widely studied in isolation, few studies have assessed the impacts of climate and land cover change in combination. Here, we evaluate the exposure of a large mammalian clade, bats, to multiple scenarios of environmental change and dispersal to understand potential consequences for biodiversity conservation.

Location

Mexico.

Methods

We used ensemble species distribution models to forecast changes in environmental suitability for 130 bat species that occur in Mexico by 2050s under four dispersal assumptions and four combined climate and land use change scenarios. We identified regions with the strongest projected impacts for each scenario and assessed the overlap across scenarios.

Results

The combined effects of climate and land use change will cause an average reduction in environmental suitability for 51% of the species across their range, regardless of scenario. Overall, species show a mean decrease in environmental suitability in at least 46% of their current range in all scenarios of change and dispersal. Climate scenarios had a higher impact on species environmental suitability than land use scenarios. There was a spatial overlap of 43% across the four environmental change scenarios for the regions projected to have the strongest impacts.

Main conclusions

Combined effects of future environmental change may result in substantial declines in environmental suitability for Mexican bats even under optimistic scenarios. This study highlights the vulnerability of megadiverse regions and an indicator taxon to human disturbance. The consideration of combined threats can make an important difference in how we react to changes to conserve our biodiversity as they pose different challenges.

     

An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction

Land‐cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land‐cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981–1985 and 2001–2005 are correlated with land‐cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land‐cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land‐cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land‐cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction.     

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land‐based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro‐economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.     

Projecting terrestrial biodiversity intactness with GLOBIO 4

Scenario‐based biodiversity modelling is a powerful approach to evaluate how possible future socio‐economic developments may affect biodiversity. Here, we evaluated the changes in terrestrial biodiversity intactness, expressed by the mean species abundance (MSA) metric, resulting from three of the shared socio‐economic pathways (SSPs) combined with different levels of climate change (according to representative concentration pathways [RCPs]): a future oriented towards sustainability (SSP1xRCP2.6), a future determined by a politically divided world (SSP3xRCP6.0) and a future with continued global dependency on fossil fuels (SSP5xRCP8.5). To this end, we first updated the GLOBIO model, which now runs at a spatial resolution of 10 arc‐seconds (~300 m), contains new modules for downscaling land use and for quantifying impacts of hunting in the tropics, and updated modules to quantify impacts of climate change, land use, habitat fragmentation and nitrogen pollution. We then used the updated model to project terrestrial biodiversity intactness from 2015 to 2050 as a function of land use and climate changes corresponding with the selected scenarios. We estimated a global area‐weighted mean MSA of 0.56 for 2015. Biodiversity intactness declined in all three scenarios, yet the decline was smaller in the sustainability scenario (?0.02) than the regional rivalry and fossil‐fuelled development scenarios (?0.06 and ?0.05 respectively). We further found considerable variation in projected biodiversity change among different world regions, with large future losses particularly for sub‐Saharan Africa. In some scenario‐region combinations, we projected future biodiversity recovery due to reduced demands for agricultural land, yet this recovery was counteracted by increased impacts of other pressures (notably climate change and road disturbance). Effective measures to halt or reverse the decline of terrestrial biodiversity should not only reduce land demand (e.g. by increasing agricultural productivity and dietary changes) but also focus on reducing or mitigating the impacts of other pressures.     

A review of influences of land use and land cover change on ecosystems

随着人口的增长和人类社会的发展, 土地利用与土地覆盖变化已经是不可避免。土地利用与土地覆盖变化不仅对生态系统的要素、结构和功能产生深远的影响, 也会对全球变化产生反馈作用。针对土地利用与土地覆盖变化的过程、驱动机制以及在各个方面可能产生的生态环境效应的科学研究已经全面开展。该文综述了土地利用与土地覆盖变化对气候、土壤、生物地球化学循环、生物多样性以及区域生态环境等影响方面的研究进展, 并提出了相关研究的前沿方向展望。随着新技术的不断发展, 学者们将更多地侧重预测未来全球变化背景下的土地利用与土地覆盖变化趋势、合理性以及适应性, 为可持续发展提供基础资料和理论依据。     

Projecting impacts of global climate and land‐use scenarios on plant biodiversity using compositional‐turnover modelling

Nations have committed to ambitious conservation targets in response to accelerating rates of global biodiversity loss. Anticipating future impacts is essential to inform policy decisions for achieving these targets, but predictions need to be of sufficiently high spatial resolution to forecast the local effects of global change. As part of the intercomparison of biodiversity and ecosystem services models of the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services, we present a fine‐resolution assessment of trends in the persistence of global plant biodiversity. We coupled generalized dissimilarity models, fitted to >52 million records of >254 thousand plant species, with the species–area relationship, to estimate the effect of land‐use and climate change on global biodiversity persistence. We estimated that the number of plant species committed to extinction over the long term has increased by 60% globally between 1900 and 2015 (from ~10,000 to ~16,000). This number is projected to decrease slightly by 2050 under the most optimistic scenario of land‐use change and to substantially increase (to ~18,000) under the most pessimistic scenario. This means that, in the absence of climate change, scenarios of sustainable socio‐economic development can potentially bring extinction risk back to pre‐2000 levels. Alarmingly, under all scenarios, the additional impact from climate change might largely surpass that of land‐use change. In this case, the estimated number of species committed to extinction increases by 3.7–4.5 times compared to land‐use‐only projections. African regions (especially central and southern) are expected to suffer some of the highest impacts into the future, while biodiversity decline in Southeast Asia (which has previously been among the highest globally) is projected to slow down. Our results suggest that environmentally sustainable land‐use planning alone might not be sufficient to prevent potentially dramatic biodiversity loss, unless a stabilization of climate to pre‐industrial times is observed.     

土地利用与土地覆盖变化对生态系统的影响

随着人口的增长和人类社会的发展, 土地利用与土地覆盖变化已经是不可避免。土地利用与土地覆盖变化不仅对生态系统的要素、结构和功能产生深远的影响, 也会对全球变化产生反馈作用。针对土地利用与土地覆盖变化的过程、驱动机制以及在各个方面可能产生的生态环境效应的科学研究已经全面开展。该文综述了土地利用与土地覆盖变化对气候、土壤、生物地球化学循环、生物多样性以及区域生态环境等影响方面的研究进展, 并提出了相关研究的前沿方向展望。随着新技术的不断发展, 学者们将更多地侧重预测未来全球变化背景下的土地利用与土地覆盖变化趋势、合理性以及适应性, 为可持续发展提供基础资料和理论依据。     

Large‐scale impact of climate change vs. land‐use change on future biome shifts in Latin America

Climate change and land‐use change are two major drivers of biome shifts causing habitat and biodiversity loss. What is missing is a continental‐scale future projection of the estimated relative impacts of both drivers on biome shifts over the course of this century. Here, we provide such a projection for the biodiverse region of Latin America under four socio‐economic development scenarios. We find that across all scenarios 5–6% of the total area will undergo biome shifts that can be attributed to climate change until 2099. The relative impact of climate change on biome shifts may overtake land‐use change even under an optimistic climate scenario, if land‐use expansion is halted by the mid‐century. We suggest that constraining land‐use change and preserving the remaining natural vegetation early during this century creates opportunities to mitigate climate‐change impacts during the second half of this century. Our results may guide the evaluation of socio‐economic scenarios in terms of their potential for biome conservation under global change.     

Winners and losers of national and global efforts to reconcile agricultural intensification and biodiversity conservation

Closing yield gaps within existing croplands, and thereby avoiding further habitat conversions, is a prominently and controversially discussed strategy to meet the rising demand for agricultural products, while minimizing biodiversity impacts. The agricultural intensification associated with such a strategy poses additional threats to biodiversity within agricultural landscapes. The uneven spatial distribution of both yield gaps and biodiversity provides opportunities for reconciling agricultural intensification and biodiversity conservation through spatially optimized intensification. Here, we integrate distribution and habitat information for almost 20,000 vertebrate species with land‐cover and land‐use datasets. We estimate that projected agricultural intensification between 2000 and 2040 would reduce the global biodiversity value of agricultural lands by 11%, relative to 2000. Contrasting these projections with spatial land‐use optimization scenarios reveals that 88% of projected biodiversity loss could be avoided through globally coordinated land‐use planning, implying huge efficiency gains through international cooperation. However, global‐scale optimization also implies a highly uneven distribution of costs and benefits, resulting in distinct “winners and losers” in terms of national economic development, food security, food sovereignty or conservation. Given conflicting national interests and lacking effective governance mechanisms to guarantee equitable compensation of losers, multinational land‐use optimization seems politically unlikely. In turn, 61% of projected biodiversity loss could be avoided through nationally focused optimization, and 33% through optimization within just 10 countries. Targeted efforts to improve the capacity for integrated land‐use planning for sustainable intensification especially in these countries, including the strengthening of institutions that can arbitrate subnational land‐use conflicts, may offer an effective, yet politically feasible, avenue to better reconcile future trade‐offs between agriculture and conservation. The efficiency gains of optimization remained robust when assuming that yields could only be increased to 80% of their potential. Our results highlight the need to better integrate real‐world governance, political and economic challenges into sustainable development and global change mitigation research.     

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.     

A socio‐ecological model for predicting impacts of land‐use and climate change on regional plant diversity in the Austrian Alps

Climate and land‐use change jointly affect the future of biodiversity. Yet, biodiversity scenarios have so far concentrated on climatic effects because forecasts of land use are rarely available at appropriate spatial and thematic scales. Agent‐based models (ABMs) represent a potentially powerful but little explored tool for establishing thematically and spatially fine‐grained land‐use scenarios. Here, we use an ABM parameterized for 1,329 agents, mostly farmers, in a Central European model region, and simulate the changes to land‐use patterns resulting from their response to three scenarios of changing socio‐economic conditions and three scenarios of climate change until the mid of the century. Subsequently, we use species distribution models to, first, analyse relationships between the realized niches of 832 plant species and climatic gradients or land‐use types, respectively, and, second, to project consequent changes in potential regional ranges of these species as triggered by changes in both the altered land‐use patterns and the changing climate. We find that both drivers determine the realized niches of the studied plants, with land use having a stronger effect than any single climatic variable in the model. Nevertheless, the plants' future distributions appear much more responsive to climate than to land‐use changes because alternative future socio‐economic backgrounds have only modest impact on land‐use decisions in the model region. However, relative effects of climate and land‐use changes on biodiversity may differ drastically in other regions, especially where landscapes are still dominated by natural or semi‐natural habitat. We conclude that agent‐based modelling of land use is able to provide scenarios at scales relevant to individual species distribution and suggest that coupling ABMs with models of species' range change should be intensified to provide more realistic biodiversity forecasts.     

Hotspots of uncertainty in land‐use and land‐cover change projections: a global‐scale model comparison

Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.     

Projected climate and land use change alter western blacklegged tick phenology,seasonal host‐seeking suitability and human encounter risk in California

Global environmental change is having profound effects on the ecology of infectious disease systems, which are widely anticipated to become more pronounced under future climate and land use change. Arthropod vectors of disease are particularly sensitive to changes in abiotic conditions such as temperature and moisture availability. Recent research has focused on shifting environmental suitability for, and geographic distribution of, vector species under projected climate change scenarios. However, shifts in seasonal activity patterns, or phenology, may also have dramatic consequences for human exposure risk, local vector abundance and pathogen transmission dynamics. Moreover, changes in land use are likely to alter human–vector contact rates in ways that models of changing climate suitability are unlikely to capture. Here we used climate and land use projections for California coupled with seasonal species distribution models to explore the response of the western blacklegged tick (Ixodes pacificus), the primary Lyme disease vector in western North America, to projected climate and land use change. Specifically, we investigated how environmental suitability for tick host‐seeking changes seasonally, how the magnitude and direction of changing seasonal suitability differs regionally across California, and how land use change shifts human tick‐encounter risk across the state. We found vector responses to changing climate and land use vary regionally within California under different future scenarios. Under a hotter, drier scenario and more extreme land use change, the duration and extent of seasonal host‐seeking activity increases in northern California, but declines in the south. In contrast, under a hotter, wetter scenario seasonal host‐seeking declines in northern California, but increases in the south. Notably, regardless of future scenario, projected increases in developed land adjacent to current human population centers substantially increase potential human–vector encounter risk across the state. These results highlight regional variability and potential nonlinearity in the response of disease vectors to environmental change.     

Land‐use change outweighs projected effects of changing rainfall on tree cover in sub‐Saharan Africa

Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub‐Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R² = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century.     

Will climate change promote future invasions?

Biological invasion is increasingly recognized as one of the greatest threats to biodiversity. Using ensemble forecasts from species distribution models to project future suitable areas of the 100 of the world's worst invasive species defined by the International Union for the Conservation of Nature, we show that both climate and land use changes will likely cause drastic species range shifts. Looking at potential spatial aggregation of invasive species, we identify three future hotspots of invasion in Europe, northeastern North America, and Oceania. We also emphasize that some regions could lose a significant number of invasive alien species, creating opportunities for ecosystem restoration. From the list of 100, scenarios of potential range distributions show a consistent shrinking for invasive amphibians and birds, while for aquatic and terrestrial invertebrates distributions are projected to substantially increase in most cases. Given the harmful impacts these invasive species currently have on ecosystems, these species will likely dramatically influence the future of biodiversity.     

Downscaling land‐use data to provide global 30″ estimates of five land‐use classes

Land‐use change is one of the biggest threats to biodiversity globally. The effects of land use on biodiversity manifest primarily at local scales which are not captured by the coarse spatial grain of current global land‐use mapping. Assessments of land‐use impacts on biodiversity across large spatial extents require data at a similar spatial grain to the ecological processes they are assessing. Here, we develop a method for statistically downscaling mapped land‐use data that combines generalized additive modeling and constrained optimization. This method was applied to the 0.5° Land‐use Harmonization data for the year 2005 to produce global 30″ (approx. 1 km²) estimates of five land‐use classes: primary habitat, secondary habitat, cropland, pasture, and urban. The original dataset was partitioned into 61 bio‐realms (unique combinations of biome and biogeographical realm) and downscaled using relationships with fine‐grained climate, land cover, landform, and anthropogenic influence layers. The downscaled land‐use data were validated using the PREDICTS database and the geoWiki global cropland dataset. Application of the new method to all 61 bio‐realms produced global fine‐grained layers from the 2005 time step of the Land‐use Harmonization dataset. Coarse‐scaled proportions of land use estimated from these data compared well with those estimated in the original datasets (mean R²: 0.68 ± 0.19). Validation with the PREDICTS database showed the new downscaled land‐use layers improved discrimination of all five classes at PREDICTS sites (P < 0.0001 in all cases). Additional validation of the downscaled cropping layer with the geoWiki layer showed an R² improvement of 0.12 compared with the Land‐use Harmonization data. The downscaling method presented here produced the first global land‐use dataset at a spatial grain relevant to ecological processes that drive changes in biodiversity over space and time. Integrating these data with biodiversity measures will enable the reporting of land‐use impacts on biodiversity at a finer resolution than previously possible. Furthermore, the general method presented here could be useful to others wishing to downscale similarly constrained coarse‐resolution data for other environmental variables.     

Surrogate species protection in Bolivia under climate and land cover change scenarios

The Amazon rainforest covers more than 60% of Bolivia’s lowlands, providing habitat for many endemic and threatened species. Bolivia has the highest rates of deforestation of the Amazon biome, which degrades and fragments species habitat. Anthropogenic habitat changes could be exacerbated by climate change, and therefore, developing relevant strategies for biodiversity protection under global change scenarios is a necessary step in conservation planning.In this research we used multi-species umbrella concept to evaluate the degree of habitat impacts due to climate and land cover change in Bolivia. We used species distribution modeling to map three focal species (Jaguar, Lowland Tapir and Lesser Anteater) and assessed current protected area network effectiveness under future climate and land cover change scenarios for 2050.The studied focal species will lose between 70% and 83% of their ranges under future climate and land-cover change scenarios, decreasing the level of protection to 10% of their original ranges. Existing protected area network should be reconsidered to maintain current and future biodiversity habitats.     

The fate of Amazonian ecosystems over the coming century arising from changes in climate,atmospheric CO2, and land use

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO₂ levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias‐corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land‐use change scenarios. We assess the relative roles of climate change, CO₂ fertilization, land‐use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO₂ fertilization will enhance vegetation productivity and alleviate climate‐induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land‐use change and climate‐driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO₂ impacts varies considerably, depending on both the climate and land‐use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors – climate change, CO₂ fertilization effects, fire, and land use – to the fate of the Amazon over the coming century.     

A model-based framework for assessing the vulnerability of low dispersal vertebrates to landscape fragmentation under environmental change

Environmental changes are driving rapid geographic shifts of suitable environmental conditions for species. These might survive by tracking those shifts, however successful responses will depend on the spatial distribution of suitable habitats (current and future) and on their connectivity. Most herptiles (i.e., amphibians and reptiles) have low dispersal abilities, and therefore herptiles are among the most vulnerable groups to environmental changes. Here we assessed the vulnerability of herptile species to future climate and land use changes in fragmented landscapes. We developed and tested a methodological approach combining the strengths of Species Distribution Models (SDMs) and of functional connectivity analysis. First, using SDMs we forecasted current and future distributions of potential suitable areas as well as range dynamics for four herptile species in Portugal. SDM forecasts for 2050 were obtained under two contrasting emission scenarios, translated into moderate (low-emissions scenario) or large (high-emissions scenario) changes in climate and land use conditions. Then, we calculated and analysed functional connectivity from areas projected to lose environmental suitability towards areas keeping suitable conditions. Landscape matrix resistance and barrier effects of the national motorway network were incorporated as the main sources of fragmentation. Potential suitable area was projected to decrease under future conditions for most test species, with the high-emissions scenario amplifying the losses or gains. Spatiotemporal patterns of connectivity between potentially suitable areas signalled the most important locations for maintaining linkages and migration corridors, as well as potential conflicts due to overlaps with the current motorway network. By integrating SDM projections with functional connectivity analysis, we were able to assess and map the vulnerability of distinct herptile species to isolation or extinction under environmental change scenarios. Our framework provides valuable information, with fairly low data requirements, for optimizing biodiversity management and mitigation efforts, aiming to reduce the complex and often synergistic negative impacts of multiple environmental change drivers. Implications for conservation planning and management are discussed from a global change adaptation perspective.