Incorporating local adaptation into forecasts of species’ distribution and abundance under climate change

Populations of many species are genetically adapted to local historical climate conditions. Yet most forecasts of species’ distributions under climate change have ignored local adaptation (LA), which may paint a false picture of how species will respond across their geographic ranges. We review recent studies that have incorporated intraspecific variation, a potential proxy for LA, into distribution forecasts, assess their strengths and weaknesses, and make recommendations for how to improve forecasts in the face of LA. The three methods used so far (species distribution models, response functions, and mechanistic models) reflect a trade‐off between data availability and the ability to rigorously demonstrate LA to climate. We identify key considerations for incorporating LA into distribution forecasts that are currently missing from many published studies, including testing the spatial scale and pattern of LA, the confounding effects of LA to nonclimatic or biotic drivers, and the need to incorporate empirically based dispersal or gene flow processes. We suggest approaches to better evaluate these aspects of LA and their effects on species‐level forecasts. In particular, we highlight demographic and dynamic evolutionary models as promising approaches to better integrate LA into forecasts, and emphasize the importance of independent model validation. Finally, we urge closer examination of how LA will alter the responses of central vs. marginal populations to allow stronger generalizations about changes in distribution and abundance in the face of LA.     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

Mutualism influences species distribution predictions for a bromeliad‐breeding anuran under climate change

Ecological niche models, or species distribution models, have been widely used to identify potentially suitable areas for species in future climate change scenarios. However, there are inherent errors to these models due to their inability to evaluate species occurrence influenced by non‐climatic factors. With the intuit to improve the modelling predictions for a bromeliad‐breeding treefrog (Phyllodytes melanomystax, Hylidae), we investigate how the climatic suitability of bromeliads influences the distribution model for the treefrog in the context of baseline and 2050 climate change scenarios. We used point occurrence data on the frog and the bromeliad (Vriesea procera, Bromeliaceae) to generate their predicted distributions based on baseline and 2050 climates. Using a consensus of five algorithms, we compared the accuracy of the models and the geographic predictions for the frog generated from two modelling procedures: (i) a climate‐only model for P. melanomystax and V. procera; and (ii) a climate‐biotic model for P. melanomystax, in which the climatic suitability of the bromeliad was jointly considered with the climatic variables. Both modelling approaches generated strong and similar predictive power for P. melanomystax, yet climate‐biotic modelling generated more concise predictions, particularly for the year 2050. Specifically, because the predicted area of the bromeliad overlaps with the predictions for the treefrog in the baseline climate, both modelling approaches produce reasonable similar predicted areas for the anuran. Alternatively, due to the predicted loss of northern climatically suitable areas for the bromeliad by 2050, only the climate‐biotic models provide evidence that northern populations of P. melanomystax will likely be negatively affected by 2050.     

Parapatric species and the implications for climate change studies: a case study on hares in Europe

Parapatry is a biogeographical term used to refer to organisms whose ranges do not overlap, but are immediately adjacent to each other; they only co‐occur – if at all – in a narrow contact zone. Often there are no environmental barriers in the contact zones, hence competitive interaction is usually advocated as the factor that modulates species distribution ranges. Even though the effects of climate change on species distribution have been widely studied, few studies have explored these effects on the biogeographical relationships between closely related, parapatric, species. We modelled environmental favourability for three parapatric hare species in Europe – Lepus granatensis, L. europaeus and L. timidus – using ecogeographical variables and projected the models into the future according to the IPCC A2 emissions scenario. Favourabilities for present and future scenarios were combined using fuzzy logic with the following aims: (i) to determine the biogeographical relationships between hare species in parapatry, that is L. granatensis/L. europaeus and L. europaeus/L. timidus and (ii) to assess the effects of climate change on each species as well as on their interspecific interactions. In their contact area L. granatensis achieved higher favourability values than L. europaeus, suggesting that if both species have a similar population status, the former species may have some advantages over the latter if competitive relationships are established. Climate change had the most striking effect on the distribution of L. timidus, especially when interspecific interactions with L. europaeus were taken into account, which may compromise the co‐existence of L. timidus. The results of this study are relevant not only for understanding the distribution patterns of the hares studied and the effects of climate change on these patterns, but also for improving the general application of species distribution models to the prediction of the effects of climate change on biodiversity.     

气候变化下寒露林蛙在中国的潜在地理分布

近几十年来,全球变暖对全球生物多样性及其地理分布产生了重要影响,特别是对气候变化敏感的两栖动物.寒露林蛙(Rana hanluica)是中国特有种,但在濒危物种红色名录中处于无危状态.为了评估寒露林蛙种群的生存现状,掌握该物种在中国的潜在分布区,以及在未来气候变化条件下适宜生境区的变化,本研究利用最大熵(MaxEnt)...     

Modelling both dominance and species distribution provides a more complete picture of changes to mangrove ecosystems under climate change

Dominant species influence the composition and abundance of other species present in ecosystems. However, forecasts of distributional change under future climates have predominantly focused on changes in species distribution and ignored possible changes in spatial and temporal patterns of dominance. We develop forecasts of spatial changes for the distribution of species dominance, defined in terms of basal area, and for species occurrence, in response to sea level rise for three tree taxa within an extensive mangrove ecosystem in northern Australia. Three new metrics are provided, indicating the area expected to be suitable under future conditions (E_occupied), the instability of suitable area (E_instability) and the overlap between the current and future spatial distribution (E_overlap). The current dominance and occurrence were modelled in relation to a set of environmental variables using boosted regression tree (BRT) models, under two scenarios of seedling establishment: unrestricted and highly restricted. While forecasts of spatial change were qualitatively similar for species occurrence and dominance, the models of species dominance exhibited higher metrics of model fit and predictive performance, and the spatial pattern of future dominance was less similar to the current pattern than was the case for the distributions of species occurrence. This highlights the possibility of greater changes in the spatial patterning of mangrove tree species dominance under future sea level rise. Under the restricted seedling establishment scenario, the area occupied by or dominated by a species declined between 42.1% and 93.8%, while for unrestricted seedling establishment, the area suitable for dominance or occurrence of each species varied from a decline of 68.4% to an expansion of 99.5%. As changes in the spatial patterning of dominance are likely to cause a cascade of effects throughout the ecosystem, forecasting spatial changes in dominance provides new and complementary information in addition to that provided by forecasts of species occurrence.     

Fish introductions reveal the temperature dependence of species interactions

A major area of current research is to understand how climate change will impact species interactions and ultimately biodiversity. A variety of environmental conditions are rapidly changing owing to climate warming, and these conditions often affect both the strength and outcome of species interactions. We used fish distributions and replicated fish introductions to investigate environmental conditions influencing the coexistence of two fishes in Swedish lakes: brown trout (Salmo trutta) and pike (Esox lucius). A logistic regression model of brown trout and pike coexistence showed that these species coexist in large lakes (more than 4.5 km²), but not in small, warm lakes (annual air temperature more than 0.9–1.5°C). We then explored how climate change will alter coexistence by substituting climate scenarios for 2091–2100 into our model. The model predicts that brown trout will be extirpated from approximately half of the lakes where they presently coexist with pike and from nearly all 9100 lakes where pike are predicted to invade. Context dependency was critical for understanding pike–brown trout interactions, and, given the widespread occurrence of context-dependent species interactions, this aspect will probably be critical for accurately predicting climate impacts on biodiversity.     

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub‐disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.     

气候变化情景下孑遗植物绵刺在中国的潜在地理分布

绵刺(Potaninia mongolica Maxim.)为我国西北干旱、半干旱地区孑遗濒危荒漠植物,具有重要的生态作用。预测过去、当代及未来气候变化情景下绵刺植物在中国的潜在地理分布区和迁移路线,将为绵刺的保护利用及种群合理建立提供一定的科学依据。基于绵刺在中国的73个有效分布点和8个环境因子变量,利用MaxEnt模型和ArcGIS软件预测末次间冰期、末次盛冰期、当代及未来绵刺在中国的潜在地理分布变化,综合分析影响绵刺分布的主要环境因子及其适宜范围,并用检验受试者工作特征(ROC)曲线下面积(AUC)评估模型的精确度。结果表明：(1)MaxEnt模型预测精确度极高,受试者工作特征(ROC)曲线下面积(AUC)值为0.988,预测显示当代绵刺主要分布在内蒙古中西部地区(阿拉善地区)、宁夏东北部和西北部、甘肃中东部、新疆中部和西部少量狭长分布区,潜在地理分布的总适生区面积约是51.94×10⁴ km~2;(2)影响绵刺潜在地理分布的重要环境因子变量是降雨(最干月降雨量、年均降雨量、最湿月降雨量、最冷季度平均降雨量)和温度(最热月的最高温);(3)从末次间冰期到末次...     

Predicting the distributions of Pouteria adolfi-friederici and Prunus africana tree species under current and future climate change scenarios in Ethiopia

Distributions of potential ranges of plant species are not yet fully known in Ethiopia where high climatic variability and vegetation types are found. This study was undertaken to predict distributions of suitable habitats of Pouteria adolfi-friederici and Prunus africana under current and two future climate scenarios (RCP 4.5 and RCP 8.5 in 2050 and 2070) in Ethiopia. Eleven environmental variables with less correlation coefficients (r < 0.7) were used to make the prediction. Shifting in extents of habitat suitability and effects of elevation, solar radiation and topographic position in relation to the current and future climatic scenarios were statistically analysed using independent t-test and linear model. We found decreasing area of highly suitable habitat from 0.51% to 0.46%, 0.36% and 0.33%, 0.24% for Prunus africana and 1.13% to 1.02%, 0.77% and 0.76%, 0.60% for Pouteria adolfi-friederici, under RCP 4.5 and RCP 8.5 by 2050 and 2070 respectively. Moist and dry afromontane forests are identified as the most suitable habitat for both species. Overall, our results suggest that climate change can promote dynamic suitable habitat niches under different future climate scenarios. Therefore, biodiversity conservation strategies should take into account habitat suitability dynamics issues and identify where to conserve species before implementing conservation practices.     

基于Maxent模型的未来气候变化情景下胡杨在中国的潜在地理分布

胡杨(Populus euphratica)是全世界干旱和半干旱区急需优先保护的林木基因资源,预测未来气候变化情景下胡杨在中国的潜在地理分布将为胡杨种群资源的保护和管理提供科学依据,并为绿洲恢复过程中胡杨的合理种植和配置提供有价值的理论指导。本研究基于胡杨在中国地区的92条有效分布记录和10个环境因子变量,利用Maxent模型和ArcGIS软件预测了未来气候变化情景下胡杨在中国的潜在地理分布,综合环境因子变量贡献率及置换重要值、刀切法检验评估制约现代胡杨潜在地理分布的重要因子,采用响应曲线确定环境因子变量的适宜区间,定量确定胡杨未来受威胁的潜在地理分布区域和面积。结果表明：（1）Maxent模型的预测准确度极高,受试者工作曲线面积（AUC值）达0.932,现代胡杨潜在地理分布的总适生区面积为289.94×104km2,主要位于内蒙古中西部地区（额济纳旗和阿拉善地区）、新疆大部分地区、甘肃北部和西北部地区、青海中西部地区和宁夏北部地区;（2）影响胡杨的潜在地理分布的主要环境因子变量为气温因子变量（年均温和最冷月最低温）和降水因子变量（最湿月降水量和最干季降水量）,最湿月降水量是影响胡杨潜在地理分布的关键因素;（3）在未来4种气候变化情景下,胡杨不同等级潜在地理分布区的面积较现代潜在地理分布区面积均有不同程度的缩小,且整体上看胡杨的潜在地理分布区有向高海拔区域迁移的趋势。     

气候变化情景下祁连圆柏在青海省的适宜分布区预测

祁连圆柏具有良好的水土保持功能,是青海省高寒干旱地区造林绿化的优良乡土树种之一,预测未来气候变化情景下祁连圆柏在青海省的潜在地理分布将为祁连圆柏的经营管理和引种栽培提供理论指导.本研究基于实地调查和资料搜集获得88个有效地理分布样点,利用Maxent模型和ArcGIS空间分析技术对当前气候条件下祁连圆柏在青海省的潜在地...     

Contrasting patterns of change in the distribution and abundance of farmland birds in relation to farming system in lowland Britain

Patterns of change in distribution (presence/absence) and abundance since the late 1960s were examined in 20 species of farmland bird in southern Britain in predominantly arable (eastern), predominantly mixed (central) and predominantly grassland (western) regions. Comparisons were made between changes in distribution and in abundance to determine whether these measures show similar relationships to environmental change. Local extinctions of selected species and reductions in species richness were significantly greater in the predominantly grassland region. Decreases in abundance were greatest in seven species in the predominantly arable region, two in the mixed region and nine in the grassland region. Changes in distribution and abundance showed consistent patterns in three species, turtle dove Streptopelia turtur L., yellow wagtail Motacilla flava L. and reed bunting Emberiza schoeniclus L. In another four species, grey partridge Perdix perdix L., lapwing Vanellus vanellus L., tree sparrow Passer montanus L. and corn bunting Miliaria calandra L., decreases in abundance were greatest in the arable region, yet declines in distribution were lowest. For other individual species, changes in distribution were too small to draw any conclusions in relation to farm type. We suggest that modern grassland systems are suboptimal habitats compared to arable or mixed agricultural land for many farmland species that occur at relatively low density in the more western, grass‐dominated region. Declines in abundance are therefore more likely to lead to local extinction in these areas than in eastern areas where abundance is higher. However, the role of changes in grassland management on bird populations requires further research. It is suggested that conclusions drawn from changes in distribution alone, in the absence of supporting data on changes in abundance, may be misleading where the aim is to assess how large‐scale spatial dynamics of populations relate to environmental change.     

物种分布模型理论研究进展

利用物种分布模型估计物种的真实和潜在分布区,已成为区域生态学与生物地理学中非常活跃的研究领域。然而,到目前为止,这项技术的理论基础仍然存在不足之处,一些关键的生态过程未能被有效纳入到物种分布模型的理论框架中,从而为解释物种分布模型预测的结果带来了诸多困惑。鉴于此,总结了物种分布模型的理论基础;系统探讨了物种分布模型与物种分布区的关系;特别指出了物种分布模型研究中存在的理论问题;重点阐述了物种分布模型未来的发展方向。研究认为,物种分布模型与生态位理论、源-库理论、种群动态理论、集合种群理论、进化理论等具有重要的联系;正确理解物种分布模型的预测结果与物种分布区的关系,有赖于对影响物种分布的3个主要因素(环境条件、物种相互作用与物种迁移能力)做出定量的分离;目前物种分布模型主要存在的问题是未能将物种的相互作用和物种的迁移能力有效纳入到模型的构建过程中;未来物种分布模型的发展应该加强模型背后理论框架的研究,并进一步加强整合物种相互作用过程、种群动态过程、迁移过程和物种进化过程等内容。研究还认为,从更高的理论层次模拟功能群和群落结构将是未来物种分布模型的重要发展方向。     

Environmental gradients shift the direction of the relationship between native and alien plant species richness

Aim

To assess how environmental, biotic and anthropogenic factors shape native–alien plant species richness relationships across a heterogeneous landscape.

Location

Banks Peninsula, New Zealand.

Methods

We integrated a comprehensive floristic survey of over 1200 systematically located 6 × 6 m plots, with corresponding climate, environmental and anthropogenic data. General linear models examined variation in native and alien plant species richness across the entire landscape, between native‐ and alien‐dominated plots, and within separate elevational bands.

Results

Across all plots, there was a significant negative correlation between native and alien species richness, but this relationship differed within subsets of the data: the correlation was positive in alien‐dominated plots but negative in native‐dominated plots. Within separate elevational bands, native and alien species richness were positively correlated at lower elevations, but negatively correlated at higher elevations. Alien species richness tended to be high across the elevation gradient but peaked in warmer, mid‐ to low‐elevation sites, while native species richness increased linearly with elevation. The negative relationship between native and alien species richness in native‐dominated communities reflected a land‐use gradient with low native and high alien richness in more heavily modified native‐dominated vegetation. In contrast, native and alien richness were positively correlated in very heavily modified alien‐dominated plots, most likely due to covariation along a gradient of management intensity.

Main conclusions

Both positive and negative native–alien richness relationships can occur across the same landscape, depending on the plant community and the underlying human and environmental gradients examined. Human habitat modification, which is often confounded with environmental variation, can result in high alien and low native species richness in areas still dominated by native species. In the most heavily human modified areas, dominated by alien species, both native and alien species may be responding to similar underlying gradients.