Synergistic effects of climate and land‐use change influence broad‐scale avian population declines

Climate and land‐use changes are expected to be the primary drivers of future global biodiversity loss. Although theory suggests that these factors impact species synergistically, past studies have either focused on only one in isolation or have substituted space for time, which often results in confounding between drivers. Tests of synergistic effects require congruent time series on animal populations, climate change and land‐use change replicated across landscapes that span the gradient of correlations between the drivers of change. Using a unique time series of high‐resolution climate (measured as temperature and precipitation) and land‐use change (measured as forest change) data, we show that these drivers of global change act synergistically to influence forest bird population declines over 29 years in the Pacific Northwest of the United States. Nearly half of the species examined had declined over this time. Populations declined most in response to loss of early seral and mature forest, with responses to loss of early seral forest amplified in landscapes that had warmed over time. In addition, birds declined more in response to loss of mature forest in areas that had dried over time. Climate change did not appear to impact populations in landscapes with limited habitat loss, except when those landscapes were initially warmer than the average landscape. Our results provide some of the first empirical evidence of synergistic effects of climate and land‐use change on animal population dynamics, suggesting accelerated loss of biodiversity in areas under pressure from multiple global change drivers. Furthermore, our findings suggest strong spatial variability in the impacts of climate change and highlight the need for future studies to evaluate multiple drivers simultaneously to avoid potential misattribution of effects.     

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.     

Changes in genetic diversity and differentiation in Red‐cockaded woodpeckers (Dryobates borealis) over the past century

Red‐cockaded woodpeckers (RCW; Dryobates borealis) declined after human activities reduced their fire‐maintained pine ecosystem to <3% of its historical range in the southeastern United States and degraded remaining habitat. An estimated 1.6 million RCW cooperative breeding groups declined to about 3,500 groups with no more than 10,000 birds by 1978. Management has increased RCW population abundances since they were at their lowest in the 1990s. However, no range‐wide study has been undertaken since then to investigate the impacts of this massive bottleneck or infer the effects of conservation management and recent demographic recoveries. We used mitochondrial DNA sequences (mtDNA) and nine nuclear microsatellite loci to determine if range‐wide demographic declines resulted in changes to genetic structure and diversity in RCW by comparing samples collected before 1970 (mtDNA data only), between 1992 and 1995 (mtDNA and microsatellites), and between 2010 and 2014 (mtDNA and microsatellites). We show that genetic diversity has been lost as detected by a reduction in the number of mitochondrial haplotypes. This reduction was apparent in comparisons of pre‐1970 mtDNA data with data from the 1992–1995 and 2010–2014 time points, with no change between the latter two time points in mtDNA and microsatellite analyses. The mtDNA data also revealed increases in range‐wide genetic differentiation, with a genetically panmictic population present throughout the southeastern United States in the pre‐1970s data and subsequent development of genetic structure that has remained unchanged since the 1990s. Genetic structure was also uncovered with the microsatellite data, which like the mtDNA data showed little change between the 1992–1995 and 2010–2014 data sets. Temporal haplotype networks revealed a consistent, star‐like phylogeny, suggesting that despite the overall loss of haplotypes, no phylogenetically distinct mtDNA lineages were lost when the population declined. Our results may suggest that management during the last two decades has prevented additional losses of genetic diversity.     

Biodiversity and the mitigation of climate change through bioenergy: impacts of increased maize cultivation on farmland wildlife

The public promotion of renewable energies is expected to increase the number of biogas plants and stimulate energy crops cultivation (e.g. maize) in Germany. In order to assess the indirect effects of the resulting land‐use changes on biodiversity, we developed six land‐use scenarios and simulated the responses of six farmland wildlife species with the spatially explicit agent‐based model system ALMaSS. The scenarios differed in composition and spatial configuration of arable crops. We implemented scenarios where maize for energy production replaced 15% and 30% of the area covered by other cash crops. Biogas maize farms were either randomly distributed or located within small or large aggregation clusters. The animal species investigated were skylark (Alauda arvensis), grey partridge (Perdix perdix), European brown hare (Lepus europaeus), field vole (Microtus agrestis), a linyphiid spider (Erigone atra) and a carabid beetle (Bembidion lampros). The changes in crop composition had a negative effect on the population sizes of skylark, partridge and hare and a positive effect on the population sizes of spider and beetle and no effect on the population size of vole. An aggregated cultivation of maize amplified these effects for skylark. Species responses to changes in the crop composition were consistent across three differently structured landscapes. Our work suggests that with the compliance to some recommendations, negative effects of biogas‐related land‐use change on the populations of the six representative farmland species can largely be avoided.     

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.     

Simulating the effects of climate change on the distribution of an invasive plant,using a high resolution,local scale,mechanistic approach: challenges and insights

The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model (PSS[gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant (Gunnera tinctoria) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate‐induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread‐rate and intensity of G. tinctoria invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters.     

Hybridization selects for prime‐numbered life cycles in Magicicada: An individual‐based simulation model of a structured periodical cicada population

We investigate competition between separate periodical cicada populations each possessing different life‐cycle lengths. We build an individual‐based model to simulate the cicada life cycle and allow random migrations to occur between patches inhabited by the different populations. We show that if hybridization between different cycle lengths produces offspring that have an intermediate life‐cycle length, then predation acts disproportionately to select against the hybrid offspring. This happens because they emerge in low densities without the safety‐in‐numbers provided by either parent population. Thus, prime‐numbered life cycles that can better avoid hybridization are favored. However, we find that this advantage of prime‐numbered cycles occurs only if there is some mechanism that can occasionally synchronize emergence between local populations in sufficiently many patches.     

A process‐based approach to modelling impacts of climate change on the damage niche of an agricultural weed

Predicting the impact of climate change on the damage niche of an agricultural weed at a local scale requires a process‐based modelling approach that integrates local environmental conditions and the differential responses of the crop and weed to change. A simulation model of the growth and population dynamics of winter wheat and a competing weed, Sirius 2010, was calibrated and validated for the most economically damaging weed in UK cereals, Alopecurus myosuroides. The model was run using local‐scale climatic scenarios generated by the LARS‐WG weather generator and based on the HadCM3 projections for the periods 2046–2065 and 2080–2099 to predict the impact of climate change on the population dynamics of the weed and its effect on wheat yields. Owing to rising CO₂ concentration and its effect on radiation use efficiency of wheat, weed‐free wheat yields were predicted to increase. The distribution of the weed was predicted to remain broadly similar with a possible northward shift in range. Local‐scale variation in the impact of climate change was apparent owing to variation in soil type and water holding capacity. The competitive balance was shifted in favour of the deeper rooted crop under climate change, particularly on sites with lighter soils, owing to more frequent and severe drought stress events. Although the damage niche of A. myosuroides was predicted to reduce under climate change, it is likely that weeds with contrasting physiology, such as C4 species, will be better adapted to future conditions and pose a more serious threat.     

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.     

Metabolic approaches to understanding climate change impacts on seasonal host‐macroparasite dynamics

Climate change is expected to alter the dynamics of infectious diseases around the globe. Predictive models remain elusive due to the complexity of host–parasite systems and insufficient data describing how environmental conditions affect various system components. Here, we link host–macroparasite models with the Metabolic Theory of Ecology, providing a mechanistic framework that allows integrating multiple nonlinear environmental effects to estimate parasite fitness under novel conditions. The models allow determining the fundamental thermal niche of a parasite, and thus, whether climate change leads to range contraction or may permit a range expansion. Applying the models to seasonal environments, and using an arctic nematode with an endotherm host for illustration, we show that climate warming can split a continuous spring‐to‐fall transmission season into two separate transmission seasons with altered timings. Although the models are strategic and most suitable to evaluate broad‐scale patterns of climate change impacts, close correspondence between model predictions and empirical data indicates model applicability also at the species level. As the application of Metabolic Theory considerably aids the a priori estimation of model parameters, even in data‐sparse systems, we suggest that the presented approach could provide a framework for understanding and predicting climatic impacts for many host–parasite systems worldwide.     

Simulation of greenhouse gases following land‐use change to bioenergy crops using the ECOSSE model: a comparison between site measurements and model predictions

This article evaluates the suitability of the ECOSSE model to estimate soil greenhouse gas (GHG) fluxes from short rotation coppice willow (SRC‐Willow), short rotation forestry (SRF‐Scots Pine) and Miscanthus after land‐use change from conventional systems (grassland and arable). We simulate heterotrophic respiration (R_h), nitrous oxide (N₂O) and methane (CH₄) fluxes at four paired sites in the UK and compare them to estimates of R_h derived from the ecosystem respiration estimated from eddy covariance (EC) and R_h estimated from chamber (IRGA) measurements, as well as direct measurements of N₂O and CH₄ fluxes. Significant association between modelled and EC‐derived R_h was found under Miscanthus, with correlation coefficient (r) ranging between 0.54 and 0.70. Association between IRGA‐derived R_h and modelled outputs was statistically significant at the Aberystwyth site (r = 0.64), but not significant at the Lincolnshire site (r = 0.29). At all SRC‐Willow sites, significant association was found between modelled and measurement‐derived R_h (0.44 ≤ r ≤ 0.77); significant error was found only for the EC‐derived R_h at the Lincolnshire site. Significant association and no significant error were also found for SRF‐Scots Pine and perennial grass. For the arable fields, the modelled CO₂ correlated well just with the IRGA‐derived R_h at one site (r = 0.75). No bias in the model was found at any site, regardless of the measurement type used for the model evaluation. Across all land uses, fluxes of CH₄ and N₂O were shown to represent a small proportion of the total GHG balance; these fluxes have been modelled adequately on a monthly time‐step. This study provides confidence in using ECOSSE for predicting the impacts of future land use on GHG balance, at site level as well as at national level.     

Land tenure shapes black bear density and abundance on a multi‐use landscape

Global biodiversity is decreasing rapidly. Parks and protected lands, while designed to conserve wildlife, often cannot provide the habitat protection needed for wide‐ranging animals such as the American black bear (Ursus americanus). Conversely, private lands are often working landscapes (e.g., farming) that have high human footprints relative to protected lands. In southwestern Alberta, road densities are highest on private lands and black bears can be hunted year‐round. On protected lands, road densities are lowest, and hunting is prohibited. On public lands under the jurisdiction of the provincial government (Crown lands), seasonal hunting is permitted. Population estimates are needed to calculate sustainable harvest levels and to monitor population trends. In our study area, there has never been a robust estimate of black bear density and spatial drivers of black bear density are poorly understood. We used non‐invasive genetic sampling and indices of habitat productivity and human disturbance to estimate density and abundance for male and female black bears in 2013 and 2014 using two methods: spatially explicit capture–recapture (SECR) and resource‐selection functions (RSF). Land tenure best explained spatial variation in black bear density. Black bear densities for females and males were highest on parkland and lowest on Crown lands. Sex ratios were female‐biased on private lands, likely a result of lower harvests and movement of females out of areas with high male density. Synthesis and application: Both SECR and RSF methods clearly indicate spatial structuring of black bear density, with a strong influence based on how lands are managed. Land tenure influences the distribution of available foods and risk from humans. We emphasize the need for improved harvest reporting, particularly for non‐licensed hunting on private land, to estimate the extent of black bear harvest mortality.     

Measured and modelled effect of land‐use change from temperate grassland to Miscanthus on soil carbon stocks after 12 years

Soil organic carbon (SOC) is an important carbon pool susceptible to land‐use change (LUC). There are concerns that converting grasslands into the C₄ bioenergy crop Miscanthus (to meet demands for renewable energy) could negatively impact SOC, resulting in reductions of greenhouse gas mitigation benefits gained from using Miscanthus as a fuel. This work addresses these concerns by sampling soils (0–30 cm) from a site 12 years (T₁₂) after conversion from marginal agricultural grassland into Miscanthus x giganteus and four other novel Miscanthus hybrids. Soil samples were analysed for changes in below‐ground biomass, SOC and Miscanthus contribution to SOC (using a ¹³C natural abundance approach). Findings are compared to ECOSSE soil carbon model results (run for a LUC from grassland to Miscanthus scenario and continued grassland counterfactual), and wider implications are considered in the context of life cycle assessments based on the heating value of the dry matter (DM) feedstock. The mean T₁₂ SOC stock at the site was 8 (±1 standard error) Mg C/ha lower than baseline time zero stocks (T₀), with assessment of the five individual hybrids showing that while all had lower SOC stock than at T₀ the difference was only significant for a single hybrid. Over the longer term, new Miscanthus C₄ carbon replaces pre‐existing C₃ carbon, though not at a high enough rate to completely offset losses by the end of year 12. At the end of simulated crop lifetime (15 years), the difference in SOC stocks between the two scenarios was 4 Mg C/ha (5 g CO₂‐eq/MJ). Including modelled LUC‐induced SOC loss, along with carbon costs relating to soil nitrous oxide emissions, doubled the greenhouse gas intensity of Miscanthus to give a total global warming potential of 10 g CO₂‐eq/MJ (180 kg CO₂‐eq/Mg DM).     

Climate‐associated genetic variation in Fagus sylvatica and potential responses to climate change in the French Alps

Local adaptation patterns have been found in many plants and animals, highlighting the genetic heterogeneity of species along their range of distribution. In the next decades, global warming is predicted to induce a change in the selective pressures that drive this adaptive variation, forcing a reshuffling of the underlying adaptive allele distributions. For species with low dispersion capacity and long generation time such as trees, the rapidity of the change could impede the migration of beneficial alleles and lower their capacity to track the changing environment. Identifying the main selective pressures driving the adaptive genetic variation is thus necessary when investigating species capacity to respond to global warming. In this study, we investigate the adaptive landscape of Fagus sylvatica along a gradient of populations in the French Alps. Using a double‐digest restriction‐site‐associated DNA (ddRAD) sequencing approach, we identified 7,000 SNPs from 570 individuals across 36 different sites. A redundancy analysis (RDA)‐derived method allowed us to identify several SNPs that were strongly associated with climatic gradients; moreover, we defined the primary selective gradients along the natural populations of F. sylvatica in the Alps. Strong effects of elevation and humidity, which contrast north‐western and south‐eastern site, were found and were believed to be important drivers of genetic adaptation. Finally, simulations of future genetic landscapes that used these findings allowed identifying populations at risk for F. sylvatica in the Alps, which could be helpful for future management plans.     

气候变化对东北濒危动物驼鹿潜在生境的影响

气候变化是造成生物多样性下降和物种灭绝的主要因素之一。研究气候变化对物种生境,尤其是濒危物种生境影响对未来保护物种多样性和保持生态系统功能完整性具有重要意义。以驼鹿乌苏里亚种(Alces alces cameloides)为研究对象,选取了对驼鹿分布可能存在影响的22个环境因子,利用最大熵(Maxent)模型模拟了驼鹿基准气候条件下在我国东北的潜在生境分布,并预测了RCP4.5和RCP8.5两种气候变化情景下2041—2060年(2050s)、2061—2080年(2070s)驼鹿潜在分布,采用接收工作曲线下面积(AUC)对模型预测能力进行评估。研究结果表明:最大熵模型预测驼鹿潜在生境分布的精度较高(平均AUC值为0.845),22个环境因子中,年均温、最暖季均温、年降水、平均日较差是影响驼鹿生境分布的主要因子。基准气候条件下,驼鹿的潜在生境面积占研究区域总面积的36.4%,潜在生境分布区主要在大、小兴安岭。随着时间的推移,研究区内驼鹿当前潜在生境面积明显减少,而新增潜在生境面积较少,总面积呈现急剧减少的趋势,其中RCP8.5情景减少程度大于RCP4.5情景。至2050s阶段,当前潜在生境面积平均将减少62.3%,新增潜在分布面积平均仅为3.6%,总潜在生境面积最高将减少65.6%,平均将减少58.8%;至2070s阶段,当前潜在生境面积平均将减少75.8%,新增潜在分布面积平均仅为1.9%,总潜在生境面积最高将减少93.1%,平均减少73.9%。空间分布上,驼鹿的潜在生境的几何中心将先向西北移动,然后再向高纬度地区西南方向迁移,至2050s阶段,潜在分布生境的几何中心在RCP4.5和RCP8.5情景下的迁移距离分别为183.5 km和210.8 km;至2070s阶段,相应情景下的迁移距离将缩短至28.7 km和33.8 km。潜在生境分布整体呈现向高海拔、高纬度迁移的趋势。