Why decadal to century timescale palaeoclimate data are needed to explain present‐day patterns of biological diversity and change

The current distribution of species, environmental conditions and their interactions represent only one snapshot of a planet that is continuously changing, in part due to human influences. To distinguish human impacts from natural factors, the magnitude and pace of climate shifts, since the Last Glacial Maximum, are often used to determine whether patterns of diversity today are artefacts of past climate change. In the absence of high‐temporal resolution palaeoclimate reconstructions, this is generally done by assuming that past climate change occurred at a linear pace between widely spaced (usually, ≥1,000 years) climate snapshots. We show here that this is a flawed assumption because regional climates have changed significantly across decades and centuries during glacial–interglacial cycles, likely causing rapid regional replacement of biota. We demonstrate how recent atmosphere‐ocean general circulation model (AOGCM) simulations of the climate of the past 21,000 years can provide credible estimates of the details of climate change on decadal to centennial timescales, showing that these details differ radically from what might be inferred from longer timescale information. High‐temporal resolution information can provide more meaningful estimates of the magnitude and pace of climate shifts, the location and timing of drivers of physiological stress, and the extent of novel climates. They also produce new opportunities to directly investigate whether short‐term climate variability is more important in shaping biodiversity patterns rather than gradual changes in long‐term climatic means. Together, these more accurate measures of past climate instability are likely to bring about a better understanding of the role of palaeoclimatic change and variability in shaping current macroecological patterns in many regions of the world.     

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform a continent‐wide climate change vulnerability assessment whereby we compare the baseline climate of the protected area network in North America (Canada, United States, México—NAM) to the projected end‐of‐century climate (2071–2100). We estimated the projected pace at which climatic conditions may redistribute across NAM (i.e., climate velocity), and identified future nearest climate analogs to quantify patterns of climate relocation within, among, and outside protected areas. Also, we interpret climatic relocation patterns in terms of associated land‐cover types. Our analysis suggests that the conservation capacity of the NAM protection network is likely to be severely compromised by a changing climate. The majority of protected areas (~80%) might be exposed to high rates of climate displacement that could promote important shifts in species abundance or distribution. A small fraction of protected areas (<10%) could be critical for future conservation plans, as they will host climates that represent analogs of conditions currently characterizing almost a fifth of the protected areas across NAM. However, the majority of nearest climatic analogs for protected areas are in nonprotected locations. Therefore, unprotected landscapes could pose additional threats, beyond climate forcing itself, as sensitive biota may have to migrate farther than what is prescribed by the climate velocity to reach a protected area destination. To mitigate future threats to the conservation capacity of the NAM protected area network, conservation plans will need to capitalize on opportunities provided by the existing availability of natural land‐cover types outside the current network of NAM protected areas.     

Climate change considerations are fundamental to management of deep‐sea resource extraction

Climate change manifestation in the ocean, through warming, oxygen loss, increasing acidification, and changing particulate organic carbon flux (one metric of altered food supply), is projected to affect most deep‐ocean ecosystems concomitantly with increasing direct human disturbance. Climate drivers will alter deep‐sea biodiversity and associated ecosystem services, and may interact with disturbance from resource extraction activities or even climate geoengineering. We suggest that to ensure the effective management of increasing use of the deep ocean (e.g., for bottom fishing, oil and gas extraction, and deep‐seabed mining), environmental management and developing regulations must consider climate change. Strategic planning, impact assessment and monitoring, spatial management, application of the precautionary approach, and full‐cost accounting of extraction activities should embrace climate consciousness. Coupled climate and biological modeling approaches applied in the water and on the seafloor can help accomplish this goal. For example, Earth‐System Model projections of climate‐change parameters at the seafloor reveal heterogeneity in projected climate hazard and time of emergence (beyond natural variability) in regions targeted for deep‐seabed mining. Models that combine climate‐induced changes in ocean circulation with particle tracking predict altered transport of early life stages (larvae) under climate change. Habitat suitability models can help assess the consequences of altered larval dispersal, predict climate refugia, and identify vulnerable regions for multiple species under climate change. Engaging the deep observing community can support the necessary data provisioning to mainstream climate into the development of environmental management plans. To illustrate this approach, we focus on deep‐seabed mining and the International Seabed Authority, whose mandates include regulation of all mineral‐related activities in international waters and protecting the marine environment from the harmful effects of mining. However, achieving deep‐ocean sustainability under the UN Sustainable Development Goals will require integration of climate consideration across all policy sectors.     

Population‐level thermal performance of a cold‐water ectotherm is linked to ontogeny and local environmental heterogeneity

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The Paris Agreement objectives will likely halt future declines of emperor penguins

The Paris Agreement is a multinational initiative to combat climate change by keeping a global temperature increase in this century to 2°C above preindustrial levels while pursuing efforts to limit the increase to 1.5°C. Until recently, ensembles of coupled climate simulations producing temporal dynamics of climate en route to stable global mean temperature at 1.5 and 2°C above preindustrial levels were not available. Hence, the few studies that have assessed the ecological impact of the Paris Agreement used ad‐hoc approaches. The development of new specific mitigation climate simulations now provides an unprecedented opportunity to inform ecological impact assessments. Here we project the dynamics of all known emperor penguin (Aptenodytes forsteri) colonies under new climate change scenarios meeting the Paris Agreement objectives using a climate‐dependent‐metapopulation model. Our model includes various dispersal behaviors so that penguins could modulate climate effects through movement and habitat selection. Under business‐as‐usual greenhouse gas emissions, we show that 80% of the colonies are projected to be quasiextinct by 2100, thus the total abundance of emperor penguins is projected to decline by at least 81% relative to its initial size, regardless of dispersal abilities. In contrast, if the Paris Agreement objectives are met, viable emperor penguin refuges will exist in Antarctica, and only 19% and 31% colonies are projected to be quasiextinct by 2100 under the Paris 1.5 and 2 climate scenarios respectively. As a result, the global population is projected to decline by at least by 31% under Paris 1.5 and 44% under Paris 2. However, population growth rates stabilize in 2060 such that the global population will be only declining at 0.07% under Paris 1.5 and 0.34% under Paris 2, thereby halting the global population decline. Hence, global climate policy has a larger capacity to safeguard the future of emperor penguins than their intrinsic dispersal abilities.     

The relative importance of climatic effects, wildfires and management for future forest landscape dynamics in the Swiss Alps

Forest landscape dynamics result from the complex interaction of driving forces and ecological processes operating on various scales. Projected climate change for the 21st century will alter climate‐sensitive processes, causing shifts in species composition and also bringing about changes in disturbance regimes, particularly regarding wildfires. Previous studies of the impact of climate change on forests have focused mainly on the direct effects of climate. In the present study, we assessed the interactions among forest dynamics, climate change and large‐scale disturbances such as fire, wind and forest management. We used the Land Clim model to investigate the influence, interactions and the relative importance of these different drivers of landscape dynamics in two case study areas of the European Alps. The simulations revealed that projected future climate change would cause extensive forest cover changes, beginning in the coming decades. Fire is likely to become almost as important for shaping the landscape as the direct effects of climate change, even in areas where major wildfires do not occur under current climatic conditions. The effects of variable wind disturbances and harvesting regimes, however, are less likely to have a considerable impact on forest development compared with the direct effects of climate change coupled with the indirect effects of increased fire activity. We conclude that the joint direct and indirect effects of climate change are likely to have major consequences for mountain forests in the European Alps, including their ability to provide protection against natural hazards.     

Predicting species responses to climate change: demography and climate microrefugia in California valley oak (Quercus lobata)

Anticipating species movement under climate change is a major focus in conservation. Bioclimate models are one of the few predictive tools for adaptation planning, but are limited in accounting for (i) climatic tolerances in preadult life stages that are potentially more vulnerable to warming; and (ii) local‐scale movement and use of climatic refugia as an alternative or complement to large‐scale changes in distribution. To assess whether these shortfalls can be addressed with field demographic data, we used California valley oak (Quercus lobata Nee), a long‐lived species with juvenile life stages known to be sensitive to climate. We hypothesized that the valley oak bioclimate model, based on adults, would overpredict the species' ability to remain in the projected persisting area, due to higher climate vulnerability of young life stages; and underpredict the potential for the species to remain in the projected contracting area in local‐scale refugia. We assessed the bioclimate model projections against actual demographic patterns in natural populations. We found that saplings were more constricted around surface water than adults in the projected contracting area. We also found that the climate envelope for saplings is narrower than that for adults. Saplings disappeared at a summer maximum temperature 3 °C below that associated with adults. Our findings indicate that rather than a complete shift northward and upward, as predicted by the species bioclimate model, valley oaks are more likely to experience constriction around water bodies, and eventual disappearance from areas exceeding a threshold of maximum temperature. Ours is the first study we know of to examine the importance of discrete life stage climate sensitivities in determining bioclimate modeling inputs, and to identify current climate change‐related constriction of a species around microrefugia. Our findings illustrate that targeted biological fieldwork can be central to understanding climate change‐related movement for long‐lived, sessile species.     

Evidence of genomic adaptation to climate in Eucalyptus microcarpa: Implications for adaptive potential to projected climate change

Understanding whether populations can adapt in situ or whether interventions are required is of key importance for biodiversity management under climate change. Landscape genomics is becoming an increasingly important and powerful tool for rapid assessments of climate adaptation, especially in long‐lived species such as trees. We investigated climate adaptation in Eucalyptus microcarpa using the DArTseq genomic approach. A combination of F_ST outlier and environmental association analyses were performed using >4200 genomewide single nucleotide polymorphisms (SNPs) from 26 populations spanning climate gradients in southeastern Australia. Eighty‐one SNPs were identified as putatively adaptive, based on significance in F_ST outlier tests and significant associations with one or more climate variables related to temperature (70/81), aridity (37/81) or precipitation (35/81). Adaptive SNPs were located on all 11 chromosomes, with no particular region associated with individual climate variables. Climate adaptation appeared to be characterized by subtle shifts in allele frequencies, with no consistent fixed differences identified. Based on these associations, we predict adaptation under projected changes in climate will include a suite of shifts in allele frequencies. Whether this can occur sufficiently rapidly through natural selection within populations, or would benefit from assisted gene migration, requires further evaluation. In some populations, the absence or predicted increases to near fixation of particular adaptive alleles hint at potential limits to adaptive capacity. Together, these results reinforce the importance of standing genetic variation at the geographic level for maintaining species’ evolutionary potential.     

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near‐term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.     

Multiscale climate change impacts on plant diversity in the Atacama Desert

Comprehending ecological dynamics requires not only knowledge of modern communities but also detailed reconstructions of ecosystem history. Ancient DNA (aDNA) metabarcoding allows biodiversity responses to major climatic change to be explored at different spatial and temporal scales. We extracted aDNA preserved in fossil rodent middens to reconstruct late Quaternary vegetation dynamics in the hyperarid Atacama Desert. By comparing our paleo‐informed millennial record with contemporary observations of interannual variations in diversity, we show local plant communities behave differentially at different timescales. In the interannual (years to decades) time frame, only annual herbaceous expand and contract their distributional ranges (emerging from persistent seed banks) in response to precipitation, whereas perennials distribution appears to be extraordinarily resilient. In contrast, at longer timescales (thousands of years) many perennial species were displaced up to 1,000 m downslope during pluvial events. Given ongoing and future natural and anthropogenically induced climate change, our results not only provide baselines for vegetation in the Atacama Desert, but also help to inform how these and other high mountain plant communities may respond to fluctuations of climate in the future.     

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.     

Timescale analyses of fluctuations in coexisting populations of a native and invasive tree squirrel

1. Competition from invasive species is an increasing threat to biodiversity. In Southern California, the western gray squirrel (Sciurus griseus, WGS) is facing competition from the fox squirrel (Sciurus niger, FS), an invasive congener.
2. We used spectral methods to analyze 140 consecutive monthly censuses of WGS and FS within a 11.3 ha section of the California Botanic Garden. Variation in the numbers for both species and their synchrony was distributed across long timescales (>15 months).
3. After filtering out annual changes, concurrent mean monthly temperatures from nearby Ontario Airport yielded a spectrum with a large semi‐annual peak and significant spectral power at long timescales (>28 months). The cospectrum between WGS numbers and temperature revealed a significant negative correlation at long timescales (>35 months). Cospectra also revealed significant negative correlations with temperature at a six‐month timescale for both WGS and FS.
4. Simulations from a model of two competing species indicate that the risk of extinction for the weaker competitor increases quickly as environmental noise shifts from short to long timescales.
5. We analyzed the timescales of fluctuations in detrended mean annual temperatures for the time period 1915–2014 from 1218 locations across the continental USA. In the last two decades, significant shifts from short to long timescales have occurred, from <3 years to 4–6 years.
6. Our results indicate that (i) population fluctuations in co‐occurring native and invasive tree squirrels are synchronous, occur over long timescales, and may be driven by fluctuations in environmental conditions; (ii) long timescale population fluctuations increase the risk of extinction in competing species, especially for the inferior competitor; and (iii) the timescales of interannual environmental fluctuations may be increasing from recent historical values. These results have broad implications for the impact of climate change on the maintenance of biodiversity.

     

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data‐based evaluations of emergent ecosystem responses to climate and CO₂ at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO₂ in ten ecosystem models with the sensitivities found in tree‐ring reconstructions of NPP and raw ring‐width series at six temperate forest sites. These model‐data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO₂ in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree‐ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm‐growing season temperatures, while tree‐ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO₂ drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO₂ sensitivity. Fire in model simulations reduced model sensitivity to climate and CO₂, but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO₂ in individual models.     

Population responses to observed climate variability across multiple organismal groups

A major challenge in ecology is to understand how populations are affected by increased climate variability. Here, we assessed the effects of observed climate variability on different organismal groups (amphibians, insects, mammals, herbaceous plants and reptiles) by estimating the extent to which interannual variation in the annual population growth rates (CV_λ) and the absolute value of the long-term population growth rate (|log λ|) were associated with short-term climate variability. We used empirical data (≥ 20 consecutive years of annual abundances) from 59 wild populations in the Northern Hemisphere, and quantified variabilities in population growth rates and climatic conditions (temperature and precipitation in active and inactive seasons) calculated over four- and eight-year sliding time windows. We observed a positive relationship between the variability of growth rate (CV_λ) and the variability of temperature in the active season at the shorter timescale only. Moreover, |log λ| was positively associated with the variability of precipitation in the inactive season at both timescales. Otherwise, the direction of the relationships between population dynamics and climate variability (if any) depended largely on the season and organismal group in question. Both CV_λ and |log λ| correlated negatively with species' lifespan, indicating general differences in population dynamics between short-lived and long-lived species that were not related to climate variability. Our results suggest that although temporal variation in population growth rates and the magnitude of long-term population growth rates are partially associated with short-term interannual climate variability, demographic responses to climate fluctuations might still be population-specific rather than specific to given organismal groups, and driven by other factors than the observed climate variability.     

Spatial heterogeneity in climate change effects decouples the long‐term dynamics of wild reindeer populations in the high Arctic

The ‘Moran effect’ predicts that dynamics of populations of a species are synchronized over similar distances as their environmental drivers. Strong population synchrony reduces species viability, but spatial heterogeneity in density dependence, the environment, or its ecological responses may decouple dynamics in space, preventing extinctions. How such heterogeneity buffers impacts of global change on large‐scale population dynamics is not well studied. Here, we show that spatially autocorrelated fluctuations in annual winter weather synchronize wild reindeer dynamics across high‐Arctic Svalbard, while, paradoxically, spatial variation in winter climate trends contribute to diverging local population trajectories. Warmer summers have improved the carrying capacity and apparently led to increased total reindeer abundance. However, fluctuations in population size seem mainly driven by negative effects of stochastic winter rain‐on‐snow (ROS) events causing icing, with strongest effects at high densities. Count data for 10 reindeer populations 8–324 km apart suggested that density‐dependent ROS effects contributed to synchrony in population dynamics, mainly through spatially autocorrelated mortality. By comparing one coastal and one ‘continental’ reindeer population over four decades, we show that locally contrasting abundance trends can arise from spatial differences in climate change and responses to weather. The coastal population experienced a larger increase in ROS, and a stronger density‐dependent ROS effect on population growth rates, than the continental population. In contrast, the latter experienced stronger summer warming and showed the strongest positive response to summer temperatures. Accordingly, contrasting net effects of a recent climate regime shift—with increased ROS and harsher winters, yet higher summer temperatures and improved carrying capacity—led to negative and positive abundance trends in the coastal and continental population respectively. Thus, synchronized population fluctuations by climatic drivers can be buffered by spatial heterogeneity in the same drivers, as well as in the ecological responses, averaging out climate change effects at larger spatial scales.     

Carbon–Temperature–Water change analysis for peanut production under climate change: a prototype for the AgMIP Coordinated Climate‐Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate‐Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO₂]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO‐Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO₂], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain‐fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.     

Continent‐scale global change attribution in European birds ‐ combining annual and decadal time scales

Species attributes are commonly used to infer impacts of environmental change on multiyear species trends, e.g. decadal changes in population size. However, by themselves attributes are of limited value in global change attribution since they do not measure the changing environment. A broader foundation for attributing species responses to global change may be achieved by complementing an attributes‐based approach by one estimating the relationship between repeated measures of organismal and environmental changes over short time scales. To assess the benefit of this multiscale perspective, we investigate the recent impact of multiple environmental changes on European farmland birds, here focusing on climate change and land use change. We analyze more than 800 time series from 18 countries spanning the past two decades. Analysis of long‐term population growth rates documents simultaneous responses that can be attributed to both climate change and land‐use change, including long‐term increases in populations of hot‐dwelling species and declines in long‐distance migrants and farmland specialists. In contrast, analysis of annual growth rates yield novel insights into the potential mechanisms driving long‐term climate induced change. In particular, we find that birds are affected by winter, spring, and summer conditions depending on the distinct breeding phenology that corresponds to their migratory strategy. Birds in general benefit from higher temperatures or higher primary productivity early on or in the peak of the breeding season with the largest effect sizes observed in cooler parts of species' climatic ranges. Our results document the potential of combining time scales and integrating both species attributes and environmental variables for global change attribution. We suggest such an approach will be of general use when high‐resolution time series are available in large‐scale biodiversity surveys.     

Quality–quantity trade‐offs drive functional trait evolution in a model microalgal ‘climate change winner’

Phytoplankton are the unicellular photosynthetic microbes that form the base of aquatic ecosystems, and their responses to global change will impact everything from food web dynamics to global nutrient cycles. Some taxa respond to environmental change by increasing population growth rates in the short‐term and are projected to increase in frequency over decades. To gain insight into how these projected ‘climate change winners’ evolve, we grew populations of microalgae in ameliorated environments for several hundred generations. Most populations evolved to allocate a smaller proportion of carbon to growth while increasing their ability to tolerate and metabolise reactive oxygen species (ROS). This trade‐off drives the evolution of traits that underlie the ecological and biogeochemical roles of phytoplankton. This offers evolutionary and a metabolic frameworks for understanding trait evolution in projected ‘climate change winners’ and suggests that short‐term population booms have the potential to be dampened or reversed when environmental amelioration persists.     

A 2 °C warmer world is not safe for ecosystem services in the European Alps

Limiting the increase in global average temperature to 2 °C is the objective of international efforts aimed at avoiding dangerous climate impacts. However, the regional response of terrestrial ecosystems and the services that they provide under such a scenario are largely unknown. We focus on mountain forests in the European Alps and evaluate how a range of ecosystem services (ES) are projected to be impacted in a 2 °C warmer world, using four novel regional climate scenarios. We employ three complementary forest models to assess a wide range of ES in two climatically contrasting case study regions. Within each climate scenario we evaluate if and when ES will deviate beyond status quo boundaries that are based on current system variability. Our results suggest that the sensitivity of mountain forest ES to a 2 °C warmer world depends heavily on the current climatic conditions of a region, the strong elevation gradients within a region, and the specific ES in question. Our simulations project that large negative impacts will occur at low and intermediate elevations in initially warm‐dry regions, where relatively small climatic shifts result in negative drought‐related impacts on forest ES. In contrast, at higher elevations, and in regions that are initially cool‐wet, forest ES will be comparatively resistant to a 2 °C warmer world. We also found considerable variation in the vulnerability of forest ES to climate change, with some services such as protection against rockfall and avalanches being sensitive to 2 °C global climate change, but other services such as carbon storage being reasonably resistant. Although our results indicate a heterogeneous response of mountain forest ES to climate change, the projected substantial reduction of some forest ES in dry regions suggests that a 2 °C increase in global mean temperature cannot be seen as a universally ‘safe’ boundary for the maintenance of mountain forest ES.