Back to the future: using historical climate variation to project near‐term shifts in habitat suitable for coast redwood

Studies that model the effect of climate change on terrestrial ecosystems often use climate projections from downscaled global climate models (GCMs). These simulations are generally too coarse to capture patterns of fine‐scale climate variation, such as the sharp coastal energy and moisture gradients associated with wind‐driven upwelling of cold water. Coastal upwelling may limit future increases in coastal temperatures, compromising GCMs’ ability to provide realistic scenarios of future climate in these coastal ecosystems. Taking advantage of naturally occurring variability in the high‐resolution historic climatic record, we developed multiple fine‐scale scenarios of California climate that maintain coherent relationships between regional climate and coastal upwelling. We compared these scenarios against coarse resolution GCM projections at a regional scale to evaluate their temporal equivalency. We used these historically based scenarios to estimate potential suitable habitat for coast redwood (Sequoia sempervirens D. Don) under ‘normal’ combinations of temperature and precipitation, and under anomalous combinations representative of potential future climates. We found that a scenario of warmer temperature with historically normal precipitation is equivalent to climate projected by GCMs for California by 2020–2030 and that under these conditions, climatically suitable habitat for coast redwood significantly contracts at the southern end of its current range. Our results suggest that historical climate data provide a high‐resolution alternative to downscaled GCM outputs for near‐term ecological forecasts. This method may be particularly useful in other regions where local climate is strongly influenced by ocean–atmosphere dynamics that are not represented by coarse‐scale GCMs.     

Uncertainties in the projection of species distributions related to general circulation models

Ecological Niche Models (ENMs) are increasingly used by ecologists to project species potential future distribution. However, the application of such models may be challenging, and some caveats have already been identified. While studies have generally shown that projections may be sensitive to the ENM applied or the emission scenario, to name just a few, the sensitivity of ENM‐based scenarios to General Circulation Models (GCMs) has been often underappreciated. Here, using a multi‐GCM and multi‐emission scenario approach, we evaluated the variability in projected distributions under future climate conditions. We modeled the ecological realized niche (sensu Hutchinson) and predicted the baseline distribution of species with contrasting spatial patterns and representative of two major functional groups of European trees: the dwarf birch and the sweet chestnut. Their future distributions were then projected onto future climatic conditions derived from seven GCMs and four emissions scenarios using the new Representative Concentration Pathways (RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC) AR5 report. Uncertainties arising from GCMs and those resulting from emissions scenarios were quantified and compared. Our study reveals that scenarios of future species distribution exhibit broad differences, depending not only on emissions scenarios but also on GCMs. We found that the between‐GCM variability was greater than the between‐RCP variability for the next decades and both types of variability reached a similar level at the end of this century. Our result highlights that a combined multi‐GCM and multi‐RCP approach is needed to better consider potential trajectories and uncertainties in future species distributions. In all cases, between‐GCM variability increases with the level of warming, and if nothing is done to alleviate global warming, future species spatial distribution may become more and more difficult to anticipate. When future species spatial distributions are examined, we propose to use a large number of GCMs and RCPs to better anticipate potential trajectories and quantify uncertainties.     

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.     

Climate change scenarios and models yield conflicting predictions about the future risk of an invasive species in North America

• 1 The pea leafminer Liriomyza huidobrensis (Blanchard) (Diptera: Agromyzidae) is an invasive species in North America and a serious economic pest on a wide variety of crops. We developed a bioclimatic envelope model (BEM) for this species and examined the envelope's potential location in North America under various future climates.
• 2 We compared the future bioclimatic envelopes for L. huidobrensis using either simple scenarios comprising uniform changes in temperature/precipitation or climate projections from general circulation models (GCMs). Our simple scenarios were: (i) an increase of 0.1°C per degree in latitude with a 20% increase in summer precipitation and a 20% decrease in winter precipitation and (ii) an overall increase of 3°C everywhere, also with the same changes in precipitation. For GCM‐modelled climate change, we used the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre climate model (HadCM3), each in combination with two scenarios from the Special Report on Emissions Scenarios (A2 and B2).
• 3 The BEM results using the simple scenarios were more similar to each other than to the results obtained using GCM projections. The results were also qualitatively different (i.e. spatially different and divergent) depending on which GCM‐scenario combination was used.
• 4 This modelling exercise illustrates that: (i) results using first approximation simple climate change scenarios can give predictions very different from those that use GCM‐modelled climate projections (comprising a result that has worrying implications for empirical impact research) and that (ii) different GCM‐models using the same scenario can give very different results (implying strong model dependency in projected biological impacts).

     

Migrate or stay: terrestrial primary productivity and climate drive anadromy in Arctic char

A shift in the magnitude and timing of animal migrations is one of the most documented ecological effects of climate change. Although migrations are largely driven by spatial variation in resource gradients, few studies connect expected changes in primary production with geographic patterns in migratory behavior. Here, we link lake primary production to the occurrence of sea migrations in the partially anadromous salmonid Arctic char (Salvelinus alpinus L.). We compiled presence/absence records of anadromous char populations spanning productivity and temperature gradients along the Norwegian coast. The probability of anadromy decreased with increasing migration distance, maximum slope of the migration route and lake productivity. There was a significant interaction between lake productivity and migration distance. The negative effect of longer migration distances was more severe in lakes with higher productivity, indicating reduced relative profitability of migration with increased feeding opportunities in freshwater. Lake productivity was mainly driven by terrestrial primary production in the catchment. We predicted future distributions of anadromous char given downscaled temperature and precipitation changes projected by two different emission scenarios and global climate models (GCMs). Projected increases in temperature and precipitation in 2071–2100 increased terrestrial primary production and, compared to the control scenario (1961–1990), decreased the range of anadromous populations. The prevalence of anadromy decreased by 53% in the HadAm3H GCM with the A2 emission scenario, 61% in HadAm3H with the B2 scenario and 22% in ECHAM4 with the B2 scenario. Cross‐ecosystem studies (e.g., terrestrial to freshwater) are critical for understanding ecological impacts of climate change. In this case, climate‐driven increases in terrestrial primary production are expected to increase primary production in lakes and ultimately reduce the prevalence of anadromy in Arctic char populations.     

Projecting the future of an alpine ungulate under climate change scenarios

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key “early warning signs” about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37‐year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate‐driven effects influence mountain goat populations, we developed an age‐structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70‐year time window (2015–2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., “thermoneutral”) summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%–86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate‐linked bottom‐up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence.     

Linking climate change projections for an Alaskan watershed to future coho salmon production

Climate change is predicted to dramatically change hydrologic processes across Alaska, but estimates of how these impacts will influence specific watersheds and aquatic species are lacking. Here, we linked climate, hydrology, and habitat models within a coho salmon (Oncorhynchus kisutch) population model to assess how projected climate change could affect survival at each freshwater life stage and, in turn, production of coho salmon smolts in three subwatersheds of the Chuitna (Chuit) River watershed, Alaska. Based on future climate scenarios and projections from a three‐dimensional hydrology model, we simulated coho smolt production over a 20‐year span at the end of the century (2080–2100). The direction (i.e., positive vs. negative) and magnitude of changes in smolt production varied substantially by climate scenario and subwatershed. Projected smolt production decreased in all three subwatersheds under the minimum air temperature and maximum precipitation scenario due to elevated peak flows and a resulting 98% reduction in egg‐to‐fry survival. In contrast, the maximum air temperature and minimum precipitation scenario led to an increase in smolt production in all three subwatersheds through an increase in fry survival. Other climate change scenarios led to mixed responses, with projected smolt production increasing and decreasing in different subwatersheds. Our analysis highlights the complexity inherent in predicting climate‐change‐related impacts to salmon populations and demonstrates that population effects may depend on interactions between the relative magnitude of hydrologic and thermal changes and their interactions with features of the local habitat.     

Towards European climate risk surfaces: the extent and distribution of analogous and non-analogous climates 1931–2100

Aim Climate is an important determinant of species distributions. We assess different aspects of risk arising from future climate change by quantifying changes in the spatial distribution of future climatic conditions compared with the recent past. Location Europe. Methods A 10′ × 10′ resolution gridded data set of five climate variables was used to calculate expected changes to the area, distance and direction of 1931–60 climatic conditions under the HadCM3 climate model for four future climate scenarios based on different rates of greenhouse gas emissions (SRES scenarios). Three levels of tolerance ranges determined the thresholds for which future conditions are considered analogous to 1931–60 (pre‐warming) conditions. Results For many parts of Europe, areas with pre‐warming analogous climate conditions will be smaller and further away in the future than they are now. For any location in Europe, areas with pre‐warming analogous mean annual temperature conditions will, on average, be reduced between 23.7% (B1 scenario) and 49.7% (A1FI scenario) by 2100 when assuming a medium tolerance range. The mean distance to these areas will, on average, increase between 272 km (B1) and 645 km (A1FI). These changes are more pronounced for temperature than for water availability variables and also for narrow tolerance ranges compared to wide tolerance ranges. Using a combined measure of both temperature and precipitation variables, areas with prewarming analogous conditions are predicted to be in a more northeasterly direction in the future, but there are considerable regional differences within Europe. Main conclusions The results suggest that, for some parts of Europe, the loss of area with any suitable climatic conditions represents the greatest risk to biodiversity, but in other regions the distances that species may have to move to reach suitable climatic conditions may be a greater problem. Quantifying the distance and direction in analyses of change of climatically suitable areas can add additional information for climate change risk assessments.     

Predicting differential effects of climate change at the population level with life-cycle models of spring Chinook salmon

Habitat conditions mediate the effects of climate, so neighboring populations with differing habitat conditions may differ in their responses to climate change. We have previously observed that juvenile survival in Snake River spring/summer Chinook salmon is strongly correlated with summer temperature in some populations and with fall streamflow in others. Here, we explore potential differential responses of the viability of four of these populations to changes in streamflow and temperature that might result from climate change. First, we linked predicted changes in air temperature and precipitation from several General Circulation Models to a local hydrological model to project streamflow and air temperature under two climate‐change scenarios. Then, we developed a stochastic, density‐dependent life‐cycle model with independent environmental effects in juvenile and ocean stages, and parameterized the model for each population. We found that mean abundance decreased 20–50% and the probability of quasi‐extinction increased dramatically (from 0.1–0.4 to 0.3–0.9) for all populations in both scenarios. Differences between populations were greater in the more moderate climate scenario than in the more extreme, hot/dry scenario. Model results were relatively robust to realistic uncertainty in freshwater survival parameters in all scenarios. Our results demonstrate that detailed population models can usefully incorporate climate‐change predictions, and that global warming poses a direct threat to freshwater stages in these fish, increasing their risk of extinction. Because differences in habitat may contribute to the individualistic population responses we observed, we infer that maintaining habitat diversity will help buffer some species from the impacts of climate change.     

Projecting insect voltinism under high and low greenhouse gas emission conditions

We develop individual-based Monte Carlo methods to explore how climate change can alter insect voltinism under varying greenhouse gas emissions scenarios by using input distributions of diapause termination or spring emergence, development rate, and diapause initiation, linked to daily temperature and photoperiod. We show concurrence of these projections with a field dataset, and then explore changes in grape berry moth, Paralobesia viteana (Clemens), voltinism that may occur with climate projections developed from the average of three climate models using two different future emissions scenarios from the International Panel of Climate Change (IPCC). Based on historical climate data from 1960 to 2008, and projected downscaled climate data until 2099 under both high (A1fi) and low (B1) greenhouse gas emission scenarios, we used concepts of P. viteana biology to estimate distributions of individuals entering successive generations per year. Under the low emissions scenario, we observed an earlier emergence from diapause and a shift in mean voltinism from 2.8 to 3.1 generations per year, with a fraction of the population achieving a fourth generation. Under the high emissions scenario, up to 3.6 mean generations per year were projected by the end of this century, with a very small fraction of the population achieving a fifth generation. Changes in voltinism in this and other species in response to climate change likely will cause significant economic and ecological impacts, and the methods presented here can be readily adapted to other species for which the input distributions are reasonably approximated.     

Climate change‐induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands

Drylands occur worldwide and are particularly vulnerable to climate change because dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability and change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding. We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change‐induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation. Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change‐induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, that is, leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water‐limited ecosystems.     

Future climate change effects on US forest composition may offset benefits of reduced atmospheric deposition of N and S

Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) are important drivers of forest demography. Here we apply previously derived growth and survival responses for 94 tree species, representing >90% of the contiguous US forest basal area, to project how changes in mean annual temperature, precipitation, and N and S deposition from 20 different future scenarios may affect forest composition to 2100. We find that under the low climate change scenario (RCP 4.5), reductions in aboveground tree biomass from higher temperatures are roughly offset by increases in aboveground tree biomass from reductions in N and S deposition. However, under the higher climate change scenario (RCP 8.5) the decreases from climate change overwhelm increases from reductions in N and S deposition. These broad trends underlie wide variation among species. We found averaged across temperature scenarios the relative abundance of 60 species were projected to decrease more than 5% and 20 species were projected to increase more than 5%; and reductions of N and S deposition led to a decrease for 13 species and an increase for 40 species. This suggests large shifts in the composition of US forests in the future. Negative climate effects were mostly from elevated temperature and were not offset by scenarios with wetter conditions. We found that by 2100 an estimated 1 billion trees under the RCP 4.5 scenario and 20 billion trees under the RCP 8.5 scenario may be pushed outside the temperature record upon which these relationships were derived. These results may not fully capture future changes in forest composition as several other factors were not included. Overall efforts to reduce atmospheric deposition of N and S will likely be insufficient to overcome climate change impacts on forest demography across much of the United States unless we adhere to the low climate change scenario.     

Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050

In the aftermath of the 2015 pandemic of Zika virus (ZIKV), concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature‐dependent transmission model for ZIKV to project climate change impacts on transmission suitability risk by mid‐century (a generation into the future). Based on these model predictions, in the worst‐case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.     

Precipitation‐drainage cycles lead to hot moments in soil carbon dioxide dynamics in a Neotropical wet forest

Soil CO₂ concentrations and emissions from tropical forests are modulated seasonally by precipitation. However, subseasonal responses to meteorological events (e.g., storms, drought) are less well known. Here, we present the effects of meteorological variability on short‐term (hours to months) dynamics of soil CO₂ concentrations and emissions in a Neotropical wet forest. We continuously monitored soil temperature, moisture, and CO₂ for a three‐year period (2015–2017), encompassing normal conditions, floods, a dry El Niño period, and a hurricane. We used a coupled model (Hydrus‐1D) for soil water propagation, heat transfer, and diffusive gas transport to explain observed soil moisture, soil temperature, and soil CO₂ concentration responses to meteorology, and we estimated soil CO₂ efflux with a gradient‐flux model. Then, we predicted changes in soil CO₂ concentrations and emissions under different warming climate change scenarios. Observed short‐term (hourly to daily) soil CO₂ concentration responded more to precipitation than to other meteorological variables (including lower pressure during the hurricane). Observed soil CO₂ failed to exhibit diel patterns (associated with diel temperature fluctuations in drier climates), except during the drier El Niño period. Climate change scenarios showed enhanced soil CO₂ due to warmer conditions, while precipitation played a critical role in moderating the balance between concentrations and emissions. The scenario with increased precipitation (based on a regional model projection) led to increases of +11% in soil CO₂ concentrations and +4% in soil CO₂ emissions. The scenario with decreased precipitation (based on global circulation model projections) resulted in increases of +4% in soil CO₂ concentrations and +18% in soil CO₂ emissions, and presented more prominent hot moments in soil CO₂ outgassing. These findings suggest that soil CO₂ will increase under warmer climate in tropical wet forests, and precipitation patterns will define the intensity of CO₂ outgassing hot moments.     

Amazon's vulnerability to climate change heightened by deforestation and man‐made dispersal barriers

Species migrations in response to climate change have already been observed in many taxonomic groups worldwide. However, it remains uncertain if species will be able to keep pace with future climate change. Keeping pace will be especially challenging for tropical lowland rainforests due to their high velocities of climate change combined with high rates of deforestation, which may eliminate potential climate analogs and/or increase the effective distances between analogs by blocking species movements. Here, we calculate the distances between current and future climate analogs under various climate change and deforestation scenarios. Under even the most sanguine of climate change models (IPSL_CM4, A1b emissions scenario), we find that the median distance between areas in the Amazon rainforest and their closest future (2050) climate analog as predicted based on just temperature changes alone is nearly 300 km. If we include precipitation, the median distance increases by over 50% to >475 km. Since deforestation is generally concentrated in the hottest and driest portions of the Amazon, we predict that the habitat loss will have little direct impact on distances between climate analogs. If, however, deforested areas also act as a barrier to species movements, nearly 30% or 55% of the Amazon will effectively have no climate analogs anywhere in tropical South America under projections of reduced or Business‐As‐Usual deforestation, respectively. These ‘disappearing climates’ will be concentrated primarily in the southeastern Amazon. Consequently, we predict that several Amazonian ecoregions will have no areas with future climate analogs, greatly increasing the vulnerability of any populations or species specialized on these conditions. These results highlight the importance of including multiple climatic factors and human land‐use in predicting the effects of climate change, as well as the daunting challenges that Amazonian diversity faces in the near future.     

Projected Changes in Terrestrial Carbon Storage in Europe under Climate and Land-use Change, 1990–2100

Changes in climate and land use, caused by socio-economic changes, greenhouse gas emissions, agricultural policies and other factors, are known to affect both natural and managed ecosystems, and will likely impact on the European terrestrial carbon balance during the coming decades. This study presents a comprehensive European Union wide (EU15 plus Norway and Switzerland, EU*) assessment of potential future changes in terrestrial carbon storage considering these effects based on four illustrative IPCC-SRES storylines (A1FI, A2, B1, B2). A process-based land vegetation model (LPJ-DGVM), adapted to include a generic representation of managed ecosystems, is forced with changing fields of land-use patterns from 1901 to 2100 to assess the effect of land-use and cover changes on the terrestrial carbon balance of Europe. The uncertainty in the future carbon balance associated with the choice of a climate change scenario is assessed by forcing LPJ-DGVM with output from four different climate models (GCMs: CGCM2, CSIRO2, HadCM3, PCM2) for the same SRES storyline. Decrease in agricultural areas and afforestation leads to simulated carbon sequestration for all land-use change scenarios with an average net uptake of 17–38 Tg C/year between 1990 and 2100, corresponding to 1.9–2.9% of the EU*s CO₂ emissions over the same period. Soil carbon losses resulting from climate warming reduce or even offset carbon sequestration resulting from growth enhancement induced by climate change and increasing atmospheric CO₂ concentrations in the second half of the twenty-first century. Differences in future climate change projections among GCMs are the main cause for uncertainty in the cumulative European terrestrial carbon uptake of 4.4–10.1 Pg C between 1990 and 2100.     

Assessing the impacts of climate change and land transformation on Banksia in the South West Australian Floristic Region

Aim To determine the potential combined effects of climate change and land transformation on the modelled geographic ranges of Banksia. Location Mediterranean climate South West Australian Floristic Region (SWAFR). Methods We used the species distribution modelling software Maxent to relate current environmental conditions to occurrence data for 18 Banksia species, and subsequently made spatial predictions using two simple dispersal scenarios (zero and universal), for three climate‐severity scenarios at 2070, taking the impacts of land transformation on species’ ranges into account. The species were chosen to reflect the biogeography of Banksia in the SWAFR. Results Climate‐severity scenario, dispersal scenario, biogeographic distribution and land transformation all influenced the direction and magnitude of the modelled range change responses for the 18 species. The predominant response of species to all climate change scenarios was range contraction, with exceptions for some northern and widespread species. Including land transformation in estimates of modelled geographic range size for the three climate‐severity scenarios generally resulted in smaller gains and larger declines in species ranges across both dispersal scenarios. Including land transformation and assuming zero dispersal resulted, as expected, in the greatest declines in projected range size across all species. Increasing climate change severity greatly increased the risk of decline in the 18 Banksia species, indicating the critical role of mitigating future emissions. Main conclusions The combined effects of climate change and land transformation may have significant adverse impacts on endemic Proteaceae in the SWAFR, especially under high emissions scenarios and if, as expected, natural migration is limiting. Although these results need cautious interpretation in light of the many assumptions underlying the techniques used, the impacts identified warrant a clear focus on monitoring across species ranges to detect early signs of change, and experiments that determine physiological thresholds for species in order to validate and refine the models.     

Climate change and annual survival in a temperate passerine: partitioning seasonal effects and predicting future patterns

Predicting climate change impacts on population size requires detailed understanding of how climate influences key demographic rates, such as survival. This knowledge is frequently unavailable, even in well‐studied taxa such as birds. In temperate regions, most research into climatic effects on annual survival in resident passerines has focussed on winter temperature. Few studies have investigated potential precipitation effects and most assume little impact of breeding season weather. We use a 19‐year capture–mark–recapture study to provide a rare empirical analysis of how variation in temperature and precipitation throughout the entire year influences adult annual survival in a temperate passerine, the long‐tailed tit Aegithalos caudatus. We use model averaging to predict longer‐term historical survival rates, and future survival until the year 2100. Our model explains 73% of the interannual variation in survival rates. In contrast to current theory, we find a strong precipitation effect and no effect of variation in winter weather on adult annual survival, which is correlated most strongly to breeding season (spring) weather. Warm springs and autumns increase annual survival, but wet springs reduce survival and alter the form of the relationship between spring temperature and annual survival. There is little evidence for density dependence across the observed variation in population size. Using our model to estimate historical survival rates indicates that recent spring warming has led to an upward trend in survival rates, which has probably contributed to the observed long‐term increase in the UK long‐tailed tit population. Future climate change is predicted to further increase survival, under a broad range of carbon emissions scenarios and probabilistic climate change outcomes, even if precipitation increases substantially. We demonstrate the importance of considering weather over the entire annual cycle, and of considering precipitation and temperature in combination, in order to develop robust predictive models of demographic responses to climate change. Synthesis Prediction of climate change impacts demands understanding of how climate influences key demographic rates. In our 19‐year mark‐recapture study of long‐tailed tits Aegithalos caudatus, weather explained 73% of the inter‐annual variation in adult survival; warm springs and autumns increased survival, wet springs reduced survival, but winter weather had little effect. Robust predictions thus require consideration of the entire annual cycle and should not focus solely on temperature. Unexpectedly, survival appeared not to be strongly density‐dependent, so we use historical climate data to infer that recent climate change has enhanced survival over the four decades in which the UK long‐tailed tit population has more than doubled. Furthermore, survival rates in this species are predicted to further increase under a wide range of future climate scenarios.     

Aspects of climate change prediction relevant to crop productivity

Projected changes in surface climate are reviewed at a range of temporal scales, with an emphasis on tropical northern Africa--a region considered to be particularly vulnerable to climate change. Noting the key aspects of 'weather' affecting crop yield, we then consider relevant and projected change using output from a range of state of the art global climate models (GCMs), and for different future emission scenarios. The outputs from the models reveal significant inter-model variation in the change expected by the end of the twenty-first century for even the lowest IPCC emission scenario. We provide a set of recommendations on future model diagnostics, configurations and ease of use to close further the gap between GCMs and smaller-scale crop models. This has the potential to empower countries to make their own assessments of vulnerability to climate change induced periods of food scarcity.     

Modelling the influence of predicted future climate change on the risk of wind damage within New Zealand's planted forests

Wind is the major abiotic disturbance in New Zealand's planted forests, but little is known about how the risk of wind damage may be affected by future climate change. We linked a mechanistic wind damage model (ForestGALES) to an empirical growth model for radiata pine (Pinus radiata D. Don) and a process‐based growth model (cenw ) to predict the risk of wind damage under different future emissions scenarios and assumptions about the future wind climate. The cenw model was used to estimate site productivity for constant CO₂ concentration at 1990 values and for assumed increases in CO₂ concentration from current values to those expected during 2040 and 2090 under the B1 (low), A1B (mid‐range) and A2 (high) emission scenarios. Stand development was modelled for different levels of site productivity, contrasting silvicultural regimes and sites across New Zealand. The risk of wind damage was predicted for each regime and emission scenario combination using the ForestGALES model. The sensitivity to changes in the intensity of the future wind climate was also examined. Results showed that increased tree growth rates under the different emissions scenarios had the greatest impact on the risk of wind damage. The increase in risk was greatest for stands growing at high stand density under the A2 emissions scenario with increased CO₂ concentration. The increased productivity under this scenario resulted in increased tree height, without a corresponding increase in diameter, leading to more slender trees that were predicted to be at greater risk from wind damage. The risk of wind damage was further increased by the modest increases in the extreme wind climate that are predicted to occur. These results have implications for the development of silvicultural regimes that are resilient to climate change and also indicate that future productivity gains may be offset by greater losses from disturbances.