Unveiling the Conservation Biogeography of a Data-Deficient Endangered Bird Species under Climate Change

It remains a challenge to identify the geographical patterns and underlying environmental associations of species with unique ecological niches and distinct behaviors. This in turn hinders our understanding of the ecology as well as effective conservation management of threatened species. The white-eared night heron (Gorsachius magnificus) is a non-migratory nocturnal bird species that has a patchy distribution in the mountainous forests of East Asia. It is currently categorized as “Endangered” on the IUCN Red List, primarily due to its restricted range and fragmented habitat. To improve our knowledge of the biogeography and conservation of this species, we modeled the geographical pattern of its suitable habitat and evaluated the potential impacts of climate change using ecological niche modeling with a maximum entropy approach implemented in Maxent. Our results indicated that the amount of suitable habitat in all of East Asia was about 130 000 km², which can be spatially subdivided into several mountain ranges in southern and southwestern China and northern Vietnam. The extent of suitable habitat range may shrink by more than 35% under a predicted changing climate when assuming the most pessimistic condition of dispersal, while some more suitable habitat would be available if the heron could disperse unrestrainedly. The significant future changes in habitat suitability suggested for Gorsachius magnificus urge caution in any downgrading of Red List status that may be considered. Our results also discern potentially suitable areas for future survey efforts on new populations. Overall, this study demonstrates that ecological niche modeling offers an important tool for evaluating the habitat suitability and potential impacts of climate change on an enigmatic and endangered species based on limited presence data.     

The Combined Use of Correlative and Mechanistic Species Distribution Models Benefits Low Conservation Status Species

Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs) can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa), an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution) which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5). We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local adaptations to cold temperatures deserved more attention in terms of modelling, but further in conservation planning as well.     

Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli''s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species'' distribution, instead of building new models that are based on climate change variables only.     

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.     

气候变化下青藏高原两种云杉植物的潜在适生区预测

为了预测未来气候变化下云杉属植物的适宜生境,选择青藏高原暗针叶林的两种重要建群植物丽江云杉（Picea likiangensis）和紫果云杉（Picea purpurea）作为研究对象,采用MaxEnt模型预测21世纪50年代（2050s）和70年代（2070s）两物种在未来气候情景下的潜在分布,并结合ArcGIS计算物种分布面积和空间格局变化。结果表明：（1）丽江云杉的潜在适宜分布区主要集中在四川西南部和西藏东部。紫果云杉潜在适宜分布区主要集中在四川西北部、甘肃南部、青海东南部,以及西藏东部地区。（2）在未来两个时期丽江云杉的分布面积总体呈增加趋势,紫果云杉呈先增加后减少的趋势,但与其现代分布面积相比,两种云杉的总适生区面积都有不同程度的增加。（3）丽江云杉适宜生境未来可能会向北迁移,而紫果云杉可能会向西迁移。（4）影响丽江云杉和紫果云杉潜在地理分布的主要气候因子为最暖季降水量和最暖季均温。研究结果可为丽江云杉和紫果云杉在未来气候变化情景下的可持续管理提供一定的理论依据和参考价值。     

Use of Phytosociological Databases for Species Distribution Models

Species Distribution Models are key in modern ecological studies. They employ information about species locations and environmental factors to generate statistical functions that predict the potential distribution of species on the basis of landscape suitability. Although these models are powerful and useful tools, often the required information about species distribution is lacking, and the only resources are pre-collected museum data. Phytosociological databases contain a myriad of relevés with precious information, but are often considered to be the exclusive ownership of vegetation scientists. Our study tested the efficiency of a phytosociological database in the building of Species Distribution Models, including spatial autocorrelation (SAC) as a predictor to evaluate its effects on model performance. Spatial autocorrelation (SAC) is a natural characteristic of species distribution that depends on exogenous and endogenous processes. The latter??s effects could be overestimated by a subjective sample choice. We chose Festuca riccerii, an Italian endemic species. We split the whole dataset (671 relevés) into a calibration (443 relevés) and testing set (228 relevés) and performed a GLM on these data to identify the main ecological factors that lead distribution in order to build a Species Distribution Model. The dataset??s efficiency was assessed by testing the predicting power of the calibrated model on the testing subset. The phytosociological database proved to be good for building model (AUC?=?0.821), providing a useful basis for fast and low cost ecological analysis, and could be used subsequently for more detailed analyses.     

Climate Change Risks and Conservation Implications for a Threatened Small-Range Mammal Species

Background

Climate change is already affecting the distributions of many species and may lead to numerous extinctions over the next century. Small-range species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modeling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, even for rare and cryptic species.

Methodology/Principal Findings

We used species distribution modeling to assess the climate sensitivity, climate change risks and conservation implications for a threatened small-range mammal species, the Iberian desman (Galemys pyrenaicus), which is a phylogenetically isolated insectivore endemic to south-western Europe. Atlas data on the distribution of G. pyrenaicus was linked to data on climate, topography and human impact using two species distribution modeling algorithms to test hypotheses on the factors that determine the range for this species. Predictive models were developed and projected onto climate scenarios for 2070–2099 to assess climate change risks and conservation possibilities. Mean summer temperature and water balance appeared to be the main factors influencing the distribution of G. pyrenaicus. Climate change was predicted to result in significant reductions of the species'' range. However, the severity of these reductions was highly dependent on which predictor was the most important limiting factor. Notably, if mean summer temperature is the main range determinant, G. pyrenaicus is at risk of near total extinction in Spain under the most severe climate change scenario. The range projections for Europe indicate that assisted migration may be a possible long-term conservation strategy for G. pyrenaicus in the face of global warming.

Conclusions/Significance

Climate change clearly poses a severe threat to this illustrative endemic species. Our findings confirm that endemic species can be highly vulnerable to a warming climate and highlight the fact that assisted migration has potential as a conservation strategy for species threatened by climate change.     

气候变化情景下物种适宜生境预测研究进展

气候变化能够引起物种分布范围、生物物候等一系列生态现象和过程的变化,进而加速物种灭绝的速率。气候变化被认为是21世纪全球生物多样性面临的最主要威胁之一,将给未来的生物多样性保护工作带来严峻的挑战。利用物种分布模型预测气候变化情景下物种适宜生境的变化正成为当前的研究热点。本研究总结目前气候变化情景下物种适宜生境预测的最新方法及取得的主要成果。在研究方法上,多物种分布模型、多气候情景基础上的集合预测方法正成为目前研究采用的主要手段;在研究结果上,未来气候变化将有可能导致物种适宜生境面积减少,范围向高纬度、高海拔地区移动。最后本研究指出目前气候变化情景下物种适宜生境预测研究中存在的主要不足及今后的发展方向。     

Incorporating Climate Change and Exotic Species into Forecasts of Riparian Forest Distribution

We examined the impact climate change (CC) will have on the availability of climatically suitable habitat for three native and one exotic riparian species. Due to its increasing prevalence in arid regions throughout the western US, we predicted that an exotic species, Tamarix, would have the greatest increase in suitable habitat relative to native counterparts under CC. We used an ecological niche model to predict range shifts of Populus fremontii, Salix gooddingii, Salix exigua and Tamarix, from present day to 2080s, under five general circulation models and one climate change scenario (A1B). Four major findings emerged. 1) Contrary to our original hypothesis, P. fremontii is projected to have the greatest increase in suitable habitat under CC, followed closely by Tamarix. 2) Of the native species, S. gooddingii and S. exigua showed the greatest loss in predicted suitable habitat due to CC. 3) Nearly 80 percent of future P. fremontii and Salix habitat is predicted to be affected by either CC or Tamarix by the 2080s. 4) By the 2080s, 20 percent of S. gooddingii habitat is projected to be affected by both Tamarix and CC concurrently, followed by S. exigua (19 percent) and P. fremontii (13 percent). In summary, while climate change alone will negatively impact both native willow species, Tamarix is likely to affect a larger portion of all three native species'' distributions. We discuss these and other results in the context of prioritizing restoration and conservation efforts to optimize future productivity and biodiversity. As we are accounting for only direct effects of CC and Tamarix on native habitat, we present a possible hierarchy of effects- from the direct to the indirect- and discuss the potential for the indirect to outweigh the direct effects. Our results highlight the need to account for simultaneous challenges in the face of CC.     

How Can Model Comparison Help Improving Species Distribution Models?

Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs). However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT) that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagus sylvatica L., Quercus robur L. and Pinus sylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.     

The Role of Hybridization in the Distribution,Conservation and Management of Aquatic Species

Reviews in Fish Biology and Fisheries -     

Combined Use of Systematic Conservation Planning,Species Distribution Modelling,and Connectivity Analysis Reveals Severe Conservation Gaps in a Megadiverse Country (Peru)

Conservation planning is crucial for megadiverse countries where biodiversity is coupled with incomplete reserve systems and limited resources to invest in conservation. Using Peru as an example of a megadiverse country, we asked whether the national system of protected areas satisfies biodiversity conservation needs. Further, to complement the existing reserve system, we identified and prioritized potential conservation areas using a combination of species distribution modeling, conservation planning and connectivity analysis. Based on a set of 2,869 species, including mammals, birds, amphibians, reptiles, butterflies, and plants, we used species distribution models to represent species'' geographic ranges to reduce the effect of biased sampling and partial knowledge about species'' distributions. A site-selection algorithm then searched for efficient and complementary proposals, based on the above distributions, for a more representative system of protection. Finally, we incorporated connectivity among areas in an innovative post-hoc analysis to prioritize those areas maximizing connectivity within the system. Our results highlight severe conservation gaps in the Coastal and Andean regions, and we propose several areas, which are not currently covered by the existing network of protected areas. Our approach helps to find areas that contribute to creating a more representative, connected and efficient network.     

气候变化背景下中国冷杉属植物地理分布模拟分析

中国是世界上冷杉属（Abies Mill.）植物种类最为丰富、分布地域最广的国家,也是研究冷杉属植物分布成因与规律的关键地区。本文通过中国数字植物标本馆、全球生物多样性信息数据库和相关文献三种途径收集我国冷杉属植物的地理分布数据,结合当前和未来气候情景,应用最大熵模型（MaxEnt）模拟冷杉属植物的潜在分布,并使用GIS的空间分析功能做生境适宜性分析,评估我国各地区对冷杉属植物的保护能力。结果显示：（1）四川西南部、云南北部、西藏自治区东南部是我国冷杉属植物分布的热点地区;（2）在未来气候变化情景下,我国冷杉属植物的适宜生境面积将明显减少;（3）适宜生境在未来有向北迁移的趋势;（4）就各地区保护能力而言,在当前气候情景下,云南省的保护能力最高,在未来,我国西部地区的保护能力呈上升趋势,中部和东部地区呈下降趋势。本研究可为冷杉属植物的保护工作提供一定的理论依据和参考价值。     

Using Species Distribution Models to Predict Potential Landscape Restoration Effects on Puma Conservation

A mosaic of intact native and human-modified vegetation use can provide important habitat for top predators such as the puma (Puma concolor), avoiding negative effects on other species and ecological processes due to cascade trophic interactions. This study investigates the effects of restoration scenarios on the puma’s habitat suitability in the most developed Brazilian region (São Paulo State). Species Distribution Models incorporating restoration scenarios were developed using the species’ occurrence information to (1) map habitat suitability of pumas in São Paulo State, Southeast, Brazil; (2) test the relative contribution of environmental variables ecologically relevant to the species habitat suitability and (3) project the predicted habitat suitability to future native vegetation restoration scenarios. The Maximum Entropy algorithm was used (Test AUC of 0.84 ± 0.0228) based on seven environmental non-correlated variables and non-autocorrelated presence-only records (n = 342). The percentage of native vegetation (positive influence), elevation (positive influence) and density of roads (negative influence) were considered the most important environmental variables to the model. Model projections to restoration scenarios reflected the high positive relationship between pumas and native vegetation. These projections identified new high suitability areas for pumas (probability of presence >0.5) in highly deforested regions. High suitability areas were increased from 5.3% to 8.5% of the total State extension when the landscapes were restored for ≥ the minimum native vegetation cover rule (20%) established by the Brazilian Forest Code in private lands. This study highlights the importance of a landscape planning approach to improve the conservation outlook for pumas and other species, including not only the establishment and management of protected areas, but also the habitat restoration on private lands. Importantly, the results may inform environmental policies and land use planning in São Paulo State, Brazil.     

Coevolution and the Effects of Climate Change on Interacting Species

Background

Recent studies suggest that environmental changes may tip the balance between interacting species, leading to the extinction of one or more species. While it is recognized that evolution will play a role in determining how environmental changes directly affect species, the interactions among species force us to consider the coevolutionary responses of species to environmental changes.

Methodology/Principle Findings

We use simple models of competition, predation, and mutualism to organize and synthesize the ways coevolution modifies species interactions when climatic changes favor one species over another. In cases where species have conflicting interests (i.e., selection for increased interspecific interaction strength on one species is detrimental to the other), we show that coevolution reduces the effects of climate change, leading to smaller changes in abundances and reduced chances of extinction. Conversely, when species have nonconflicting interests (i.e., selection for increased interspecific interaction strength on one species benefits the other), coevolution increases the effects of climate change.

Conclusions/Significance

Coevolution sets up feedback loops that either dampen or amplify the effect of environmental change on species abundances depending on whether coevolution has conflicting or nonconflicting effects on species interactions. Thus, gaining a better understanding of the coevolutionary processes between interacting species is critical for understanding how communities respond to a changing climate. We suggest experimental methods to determine which types of coevolution (conflicting or nonconflicting) drive species interactions, which should lead to better understanding of the effects of coevolution on species adaptation. Conducting these experiments across environmental gradients will test our predictions of the effects of environmental change and coevolution on ecological communities.     

Accommodating Species Climate-Forced Dispersal and Uncertainties in Spatial Conservation Planning

Spatial conservation prioritization should seek to anticipate climate change impacts on biodiversity and to mitigate these impacts through the development of dynamic conservation plans. Here, we defined spatial priorities for the conservation of amphibians inhabiting the Atlantic Forest Biodiversity Hotspot that overcome the likely impacts of climate change on the distribution of this imperiled fauna. First, we built ecological niche models (ENMs) for 431 amphibian species both for current time and for the mid-point of a 30-year period spanning 2071–2099 (i.e. 2080). For modeling species'' niches, we combined six modeling methods and three different climate models. We also quantified and mapped model uncertainties. Our consensus models forecasted range shifts that culminate with high species richness in central and eastern Atlantic Forest, both for current time and for 2080. Most species had a significant range contraction (up to 72%) and 12% of species were projected to be regionally extinct. Most species would need to disperse because suitable climatic sites will change. Therefore, we identified a network of priority sites for conservation that minimizes the distance a given species would need to disperse because of changes in future habitat suitability (i.e. climate-forced dispersal) as well as uncertainties associated to ENMs. This network also maximized complementary species representation across currently established protected areas. Priority sites already include possible dispersal corridors linking current and future suitable habitats for amphibians. Although we used the a top-ranked Biodiversity Hotspot and amphibians as a case study for illustrating our approach, our study may help developing more effective conservation strategies under climate change, especially when applied at different spatial scales, geographic regions, and taxonomic groups.     

Climate Change and the Geographic Distribution of Infectious Diseases

Our ability to predict the effects of climate change on the spread of infectious diseases is in its infancy. Numerous, and in some cases conflicting, predictions have been developed, principally based on models of biological processes or mapping of current and historical disease statistics. Current debates on whether climate change, relative to socioeconomic determinants, will be a major influence on human disease distributions are useful to help identify research needs but are probably artificially polarized. We have at least identified many of the critical geophysical constraints, transport opportunities, biotic requirements for some disease systems, and some of the socioeconomic factors that govern the process of migration and establishment of parasites and pathogens. Furthermore, we are beginning to develop a mechanistic understanding of many of these variables at specific sites. Better predictive understanding will emerge in the coming years from analyses regarding how these variables interact with each other.     

The Use of Habitat Models in Conservation of Rare and Endangered Leafhopper Species (Hemiptera,Auchenorrhyncha)

For conservation of Auchenorrhyncha species, knowledge of their habitat requirements is essential. However, for most species there is no ‘quantitative’ knowledge that would allow e.g. spatially explicit predictions. Such predictions can be made by habitat models, which quantify the relationship between the environment and the occurrence of species. In two plot-based case studies – the endangered leafhopper Verdanus bensoni in mountainous grasslands and four endangered Auchenorrhyncha in urban brownfields – we used habitat models to quantify the habitat requirements of these five species and to exemplify their use for creating habitat suitability maps. In the first case study, the multivariate model showed that occurrence probabilities of the leafhopper V. bensoni increase with both decreasing nitrogen indicator values and decreasing tree cover. On urban brownfields, successional age was a driving factor for species’ occurrence. Site age largely determines a range of vegetation characteristics, which, in multivariate models, often replaced the variable age. Internal validation showed the robustness of all models. The models allow predictions of habitat quality under different management regimes (e.g. response to fertilization or abandonment for V. bensoni or to different turnover rates on brownfield sites). We discuss the application of habitat models in the conservation of Auchenorrhyncha, especially the use of habitat suitability maps.