Incorporating intraspecific variation into species distribution models improves distribution predictions,but cannot predict species traits for a wide-spread plant species

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic-alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific-level SDMs with a species-level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic- and habitat-informed SDMs are considerably more accurate than a species-level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific-level SDMs. We emphasize the need to carefully examine how to best define intraspecific-level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often-assumed relationships are not supported in our study.     

Incorporating microclimate into species distribution models

Species distribution models (SDMs) have rapidly evolved into one of the most widely used tools to answer a broad range of ecological questions, from the effects of climate change to challenges for species management. Current SDMs and their predictions under anthropogenic climate change are, however, often based on free‐air or synoptic temperature conditions with a coarse resolution, and thus fail to capture apparent temperature (cf. microclimate) experienced by living organisms within their habitats. Yet microclimate operates as soon as a habitat can be characterized by a vertical component (e.g. forests, mountains, or cities) or by horizontal variation in surface cover. The mismatch between how we usually express climate (cf. coarse‐grained free‐air conditions) and the apparent microclimatic conditions that living organisms experience has only recently been acknowledged in SDMs, yet several studies have already made considerable progress in tackling this problem from different angles. In this review, we summarize the currently available methods to obtain meaningful microclimatic data for use in distribution modelling. We discuss the issue of extent and resolution, and propose an integrated framework using a selection of appropriately‐placed sensors in combination with both the detailed measurements of the habitat 3D structure, for example derived from digital elevation models or airborne laser scanning, and the long‐term records of free‐air conditions from weather stations. As such, we can obtain microclimatic data with a relevant spatiotemporal resolution and extent to dynamically model current and future species distributions.     

Integrating metabolic performance,thermal tolerance,and plasticity enables for more accurate predictions on species vulnerability to acute and chronic effects of global warming

Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q₁₀ for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade‐off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing temperature helps providing more accurate predictions on species vulnerability to warming.     

Incorporating spatial autocorrelation into species distribution models alters forecasts of climate‐mediated range shifts

Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad‐scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment‐only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment‐only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate forecasts lead to ineffective prioritization of conservation activities and potentially to avoidable species extinctions.     

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。     

Combining physiological threshold knowledge to species distribution models is key to improving forecasts of the future niche for macroalgae

Species distribution models (SDM) are a useful tool for predicting species range shifts in response to global warming. However, they do not explore the mechanisms underlying biological processes, making it difficult to predict shifts outside the environmental gradient where the model was trained. In this study, we combine correlative SDMs and knowledge on physiological limits to provide more robust predictions. The thermal thresholds obtained in growth and survival experiments were used as proxies of the fundamental niches of two foundational marine macrophytes. The geographic projections of these species’ distributions obtained using these thresholds and existing SDMs were similar in areas where the species are either absent‐rare or frequent and where their potential and realized niches match, reaching consensus predictions. The cold‐temperate foundational seaweed Himanthalia elongata was predicted to become extinct at its southern limit in northern Spain in response to global warming, whereas the occupancy of southern‐lusitanic Bifurcaria bifurcata was expected to increase. Combined approaches such as this one may also highlight geographic areas where models disagree potentially due to biotic factors. Physiological thresholds alone tended to over‐predict species prevalence, as they cannot identify absences in climatic conditions within the species’ range of physiological tolerance or at the optima. Although SDMs tended to have higher sensitivity than threshold models, they may include regressions that do not reflect causal mechanisms, constraining their predictive power. We present a simple example of how combining correlative and mechanistic knowledge provides a rapid way to gain insight into a species’ niche resulting in consistent predictions and highlighting potential sources of uncertainty in forecasted responses to climate change.     

Sea warming and fish distribution: the case of the small pelagic fish, Sardinella aurita, in the western Mediterranean

This study analyses the temporal and spatial changes in abundance and distribution of the warm water species round sardinella (Sardinella aurita) in the western Mediterranean over the last decades in relation to sea water temperature. In the western Mediterranean basin (1950–2003), a significant positive relationship was found between round sardinella landings and temperature anomalies. Along a latitudinal gradient off the Mediterranean Iberian coast (1989–2004), a gradual increase in species abundance was observed from south to north, with a certain time lag going northwards, associated with the increase in sea water temperature. The abundance of round sardinella in the two warmest and southernmost areas was positively and significantly correlated with sea surface temperature registered during the start of gonad maturation the previous year. In addition, the positive relationship established between water temperature and abundance of round sardinella in the coldest and northernmost study area demonstrates that there is a temperature limit for the distribution of this species in the western Mediterranean. In addition, this study analyses round sardinella larvae distribution and abundance in the summers of 2003 and 2004, and conducts a comparison with the situation 20 years ago (summer 1983). Results show a marked increase in larval abundance during the last decades and the present appearance of larvae in the northernmost study areas, where they did not occur 20 years ago. This indicates the successful reproduction of round sardinella in the northern part of the Mediterranean, where the species has expanded, confirming its establishment in the area.     

Thermally tolerant corals have limited capacity to acclimatize to future warming

Thermal stress affects organism performance differently depending on the ambient temperature to which they are acclimatized, which varies along latitudinal gradients. This study investigated whether differences in physiological responses to temperature are consistent with regional differences in temperature regimes for the stony coral Oculina patagonica. To resolve this question, we experimentally assessed how colonies originating from four different locations characterized by >3 °C variation in mean maximum annual temperature responded to warming from 20 to 32 °C. We assessed plasticity in symbiont identity, density, and photosynthetic properties, together with changes in host tissue biomass. Results show that, without changes in the type of symbiont hosted by coral colonies, O. patagonica has limited capacity to acclimatize to future warming. We found little evidence of variation in overall thermal tolerance, or in thermal optima, in response to spatial variation in ambient temperature. Given that the invader O. patagonica is a relatively new member of the Mediterranean coral fauna, our results also suggest that coral populations may need to remain isolated for a long period of time for thermal adaptation to potentially take place. Our study indicates that for O. patagonica, mortality associated with thermal stress manifests primarily through tissue breakdown under moderate but prolonged warming (which does not impair symbiont photosynthesis and, therefore, does not lead to bleaching). Consequently, projected global warming is likely to cause repeat incidents of partial and whole colony mortality and might drive a gradual range contraction of Mediterranean corals.     

Conservation physiology of marine fishes: advancing the predictive capacity of models

At the end of May, 17 scientists involved in an EU COST Action on Conservation Physiology of Marine Fishes met in Oristano, Sardinia, to discuss how physiology can be better used in modelling tools to aid in management of marine ecosystems. Current modelling approaches incorporate physiology to different extents, ranging from no explicit consideration to detailed physiological mechanisms, and across scales from a single fish to global fishery resources. Biologists from different sub-disciplines are collaborating to rise to the challenge of projecting future changes in distribution and productivity, assessing risks for local populations, or predicting and mitigating the spread of invasive species.     

基于物种分布模型评价土壤因子对我国毛竹潜在分布的影响

基于单类别支持向量机方法的物种分布模型, 利用政府间气候变化专门委员会(IPCC)气候情景模式和联合国粮食与农业组织(FAO)的全球土壤数据, 模拟1981-2099年我国毛竹(Phyllostachys edulis)的潜在空间分布及变化趋势, 比较考虑土壤因子前后模拟结果的差异, 旨在探究土壤因子对毛竹潜在空间分布模拟结果的影响。结果表明, 仅以气候因子为模拟变量和同时考虑气候与土壤因子为模拟变量的毛竹潜在空间分布模拟均具有较高精度, 毛竹潜在分布区表现为面积增加并向北扩张。模拟因子重要性分析表明表征温暖程度的气候因子在毛竹潜在分布模拟中起主导作用, 而表征土壤质地和酸碱性的土壤因子以限制性作用为主。同时考虑气候与土壤因子的模拟结果具有较高的模拟效率, 且在未来气候变化情景模式下毛竹潜在分布区面积增幅与向北迁移幅度均小于仅使用气候因子的模拟, 表明土壤要素对毛竹潜在分布具有明显的限制作用, 该结果对现在的毛竹潜在分布模拟研究具有重要的补充作用。     

Contrasting growth changes in two dominant species of a Mediterranean shrubland submitted to experimental drought and warming

BACKGROUND AND AIMS: Climate projections predict drier and warmer conditions in the Mediterranean basin in the next decades. The possibility of such climatic changes modifying the growth of two Mediterranean species, Erica multiflora and Globularia alypum, which are common components of Mediterranean shrublands, was assessed. METHODS: A field experiment was performed from March 1999 to March 2002 to prolong the drought period and to increase the night-time temperature in a Mediterranean shrubland, where E. multiflora and G. alypum are the dominant species. Annual growth in stem diameter and length of both species was measured and annual stem biomass production was estimated for 1999, 2000 and 2001. Plant seasonal growth was also assessed. KEY RESULTS: On average, drought treatment reduced soil moisture 22 %, and warming increased temperature by 0.7-1.6 degrees C. Erica multiflora plants in the drought treatment showed a 46 % lower annual stem elongation than controls. The decrease in water availability also reduced by 31 % the annual stem diameter increment and by 43 % the annual stem elongation of G. alypum plants. New shoot growth of G. alypum was also strongly reduced. Allometrically estimated biomass production was decreased by drought in both species. Warming treatment produced contrasting effects on the growth patterns of these species. Warmer conditions increased, on average, the stem basal diameter growth of E. multiflora plants by 35 %, raising also their estimated stem biomass production. On the contrary, plants of G. alypum in the warming treatment showed a 14 % lower annual stem growth in basal diameter and shorter new shoots in spring compared with controls. CONCLUSIONS: The results indicate changes in the annual productivity of these Mediterranean shrubs under near future drier and warmer conditions. They also point to alterations in their competitive abilities, which could lead to changes in the species composition of these ecosystems in the long term.     

Climate warming moderates the impacts of introduced sportfish on multiple dimensions of prey biodiversity

Human‐assisted introductions of exotic species are a leading cause of anthropogenic change in biodiversity; however, context dependencies and interactions with co‐occurring stressors impede our ability to predict their ecological impacts. The legacy of historical sportfish stocking in mountainous regions of western North America creates a unique, natural quasiexperiment to investigate factors moderating invasion impacts on native communities across broad geographic and environmental gradients. Here we synthesize fish stocking records and zooplankton relative abundance for 685 mountain lakes and ponds in the Cascade and Canadian Rocky Mountain Ranges, to reveal the effects of predatory sportfish introduction on multiple taxonomic, functional and phylogenetic dimensions of prey biodiversity. We demonstrate an innovative analytical approach, combining exploratory random forest machine learning with confirmatory multigroup analysis using multivariate partial least‐squares structural equation models, to generate and test hypotheses concerning environmental moderation of stocking impacts. We discovered distinct effects of stocking across different dimensions of diversity, including negligible (nonsignificant) impacts on local taxonomic richness (i.e. alpha diversity) and trophic structure, in contrast to significant declines in compositional uniqueness (i.e. beta diversity) and body size. Furthermore, we found that stocking impacts were moderated by cross‐scale interactions with climate and climate‐related land‐cover variables (e.g. factors linked to treeline position and glaciers). Interactions with physical morphometric and lithological factors were generally of lesser importance, though catchment slope and habitat size constraints were relevant in certain dimensions. Finally, applying space‐for‐time substitution, a strong antagonistic (i.e. dampening) interaction between sportfish predation and warmer temperatures suggests redundancy of their size‐selective effects, meaning that warming will lessen the consequences of introductions in the future and stocked lakes may be less impacted by subsequent warming. While both stressors drive biotic homogenization, our results have important implications for fisheries managers weighing the costs/benefits of stocking—or removing established non‐native populations—under a rapidly changing climate.     

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.     

Genetic structure and life history are key factors in species distribution models of spiny lobsters

AimWe incorporated genetic structure and life history phase in species distribution models (SDMs) constructed for a widespread spiny lobster, to reveal local adaptations specific to individual subspecies and predict future range shifts under the RCP 8.5 climate change scenario.LocationIndo‐West Pacific.MethodsMaxEnt was used to construct present‐day SDMs for the spiny lobster Panulirus homarus and individually for the three genetically distinct subspecies of which it comprises. SDMs incorporated both sea surface and benthic (seafloor) climate layers to recreate discrete influences of these habitats during the drifting larval and benthic juvenile and adult life history phases. Principle component analysis (PCA) was used to infer environmental variables to which individual subspecies were adapted. SDM projections of present‐day habitat suitability were compared with predictions for the year 2,100, under the RCP 8.5 climate change scenario.ResultsIn the PCA, salinity best explained P. h. megasculptus habitat suitability, compared with current velocity in P. h. rubellus and sea surface temperature in P. h. homarus. Drifting and benthic life history phases were adapted to different combinations of sea surface and benthic environmental variables considered. Highly suitable habitats for benthic phases were spatially enveloped within more extensive sea surface habitats suitable for drifting larvae. SDMs predicted that present‐day highly suitable habitats for P. homarus will decrease by the year 2,100.Main conclusionsIncorporating genetic structure in SDMs showed that individual spiny lobster subspecies had unique adaptations, which could not be resolved in species‐level models. The use of sea surface and benthic climate layers revealed the relative importance of environmental variables during drifting and benthic life history phases. SDMs that included genetic structure and life history were more informative in predictive models of climate change effects.     

Climate controls the distribution of a widespread invasive species: implications for future range expansion

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Large‐scale distribution of tuna species in a warming ocean

Tuna are globally distributed species of major commercial importance and some tuna species are a major source of protein in many countries. Tuna are characterized by dynamic distribution patterns that respond to climate variability and long‐term change. Here, we investigated the effect of environmental conditions on the worldwide distribution and relative abundance of six tuna species between 1958 and 2004 and estimated the expected end‐of‐the‐century changes based on a high‐greenhouse gas concentration scenario (RCP8.5). We created species distribution models using a long‐term Japanese longline fishery dataset and two‐step generalized additive models. Over the historical period, suitable habitats shifted poleward for 20 out of 22 tuna stocks, based on their gravity centre (GC) and/or one of their distribution limits. On average, tuna habitat distribution limits have shifted poleward 6.5 km per decade in the northern hemisphere and 5.5 km per decade in the southern hemisphere. Larger tuna distribution shifts and changes in abundance are expected in the future, especially by the end‐of‐the‐century (2080–2099). Temperate tunas (albacore, Atlantic bluefin, and southern bluefin) and the tropical bigeye tuna are expected to decline in the tropics and shift poleward. In contrast, skipjack and yellowfin tunas are projected to become more abundant in tropical areas as well as in most coastal countries' exclusive economic zones (EEZ). These results provide global information on the potential effects of climate change in tuna populations and can assist countries seeking to minimize these effects via adaptive management.     

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.     

Genetic trials improve the transfer of Douglas‐fir distribution models across continents

Climate change is likely to result in novel conditions with no analogy to current climate. Therefore, the application of species distribution models (SDMs) based on the correlation between observed species’ occurrence and their environment is questionable and calls for a better understanding of the traits that determine species occurrence. Here, we compared two intraspecific, trait‐based SDMs with occurrence‐based SDMs, all developed from European data, and analyzed their transferability to the native range of Douglas‐fir in North America. With data from 50 provenance trials of Douglas‐fir in central Europe multivariate universal response functions (URFs) were developed for two functional traits (dominant tree height and basal area) which are good indicators of growth and vitality under given environmental conditions. These trials included 290 North American provenances of Douglas‐fir. The URFs combine genetic effects i.e. the climate of provenance origin and environmental effects, i.e. the climate of planting locations into an integrated model to predict the respective functional trait from climate data. The URFs were applied as SDMs (URF‐SDMs) by converting growth performances into occurrence. For comparison, an ensemble occurrence‐based SDM was developed and block cross validated with the BIOMOD2 modeling platform utilizing the observed occurrence of Douglas‐fir in Europe. The two trait based SDMs and the occurrence‐based SDM, all calibrated with data from Europe, were applied to predict the known distribution of Douglas‐fir in its introduced and native range in Europe and North America. Both models performed well within their calibration range in Europe, but model transfer to its native range in North America was superior in case of the URF‐SDMs showing similar predictive power as SDMs developed in North America itself. The high transferability of the URF‐SDMs is a testimony of their applicability under novel climatic conditions highlighting the role of intraspecific trait variation for adaptation planning in climate change.