Predicting the potential global distribution of Ageratina adenophora under current and future climate change scenarios

AimInvasive alien species (IAS) threaten ecosystems and humans worldwide, and future climate change may accelerate the expansion of IAS. Predicting the suitable areas of IAS can prevent their further expansion. Ageratina adenophora is an invasive weed over 30 countries in tropical and subtropical regions. However, the potential suitable areas of A. adenophora remain unclear along with its response to climate change. This study explored and mapped the current and future potential suitable areas of Ageratina adenophora.LocationGlobal.TaxaAsteraceae A. adenophora (Spreng.) R.M.King & H.Rob. Commonly known as Crofton weed.MethodsBased on A. adenophora occurrence data and climate data, we predicted its suitable areas of this weed under current and future (four RCPs in 2050 and 2070) by MaxEnt model. We used ArcGIS 10.4 to explore the potential suitable area distribution characteristics of this weed and the “ecospat” package in R to analyze its altitudinal distribution changes.ResultsThe area under the curve (AUC) value (>0.9) and true skill statistics (TSS) value (>0.8) indicated excelled model performance. Among environment factors, mean temperature of coldest quarter contributed most to the model. Globally, the suitable areas for A. adenophora invasion decreased under climate change scenarios, although regional increases were observed, including in six biodiversity hotspot regions. The potential suitable areas of A. adenophora under climate change would expand in regions with higher elevation (3,000–3,500 m).Main conclusionsMean temperature of coldest quarter was the most important variable influencing the potential suitable area of A. Adenophora. Under the background of a warming climate, the potential suitable area of A. adenophora will shrink globally but increase in six biodiversity hotspot regions. The potential suitable area of A. adenophora would expand at higher elevation (3,000–3,500 m) under climate change. Mountain ecosystems are of special concern as they are rich in biodiversity and sensitive to climate change, and increasing human activities provide more opportunities for IAS invasion.     

Response of the endangered tropical dry forests to climate change and the role of Mexican Protected Areas for their conservation

Assuming that co‐distributed species are exposed to similar environmental conditions, ecological niche models (ENMs) of bird and plant species inhabiting tropical dry forests (TDFs) in Mexico were developed to evaluate future projections of their distribution for the years 2050 and 2070. We used ENM‐based predictions and climatic data for two Global Climate Models, considering two Representative Concentration Pathway scenarios (RCP4.5/RCP8.5). We also evaluated the effects of habitat loss and the importance of the Mexican system of protected areas (PAs) on the projected models for a more detailed prediction of TDFs and to identify hot spots that require conservation actions. We identified four major distributional areas: the main one located along the Pacific Coast (from Sonora to Chiapas, including the Cape and Bajío regions, and the Balsas river basin), and three isolated areas: the Yucatán peninsula, central Veracruz, and southern Tamaulipas. When considering the effect of habitat loss, a significant reduction (~61%) of the TDFs predicted area occurred, whereas climate‐change models suggested (in comparison with the present distribution model) an increase in area of 3.0–10.0% and 3.0–9.0% for 2050 and 2070, respectively. In future scenarios, TDFs will occupy areas above its current average elevational distribution that are outside of its present geographical range. Our findings show that TDFs may persist in Mexican territory until the middle of the XXI century; however, the challenges about long‐term conservation are partially addressed (only 7% unaffected within the Mexican network of PAs) with the current Mexican PAs network. Based on our ENM approach, we suggest that a combination of models of species inhabiting present TDFs and taking into account change scenarios represent an invaluable tool to create new PAs and ecological corridors, as a response to the increasing levels of habitat destruction and the effects of climate change on this ecosystem.     

Shifts in the ecological niche of Lutzomyia peruensis under climate change scenarios in Peru

The Peruvian Andes presents a climate suitable for many species of sandfly that are known vectors of leishmaniasis or bartonellosis, including Lutzomyia peruensis (Diptera: Psychodidae), among others. In the present study, occurrences data for Lu. peruensis were compiled from several items in the scientific literature from Peru published between 1927 and 2015. Based on these data, ecological niche models were constructed to predict spatial distributions using three algorithms [Support vector machine (SVM), the Genetic Algorithm for Rule‐set Prediction (GARP) and Maximum Entropy (MaxEnt)]. In addition, the environmental requirements of Lu. peruensis and three niche characteristics were modelled in the context of future climate change scenarios: (a) potential changes in niche breadth; (b) shifts in the direction and magnitude of niche centroids, and (c) shifts in elevation range. The model identified areas that included environments suitable for Lu. peruensis in most regions of Peru (45.77%) and an average altitude of 3289 m a.s.l. Under climate change scenarios, a decrease in the distribution areas of Lu. peruensis was observed for all representative concentration pathways. However, the centroid of the species' ecological niche showed a northwest direction in all climate change scenarios. The information generated in this study may help health authorities responsible for the supervision of strategies to control leishmaniasis to coordinate, plan and implement appropriate strategies for each area of risk, taking into account the geographic distribution and potential dispersal of Lu. peruensis.     

Effects of late quaternary climate change on Palearctic shrews

The Late Quaternary was a time of rapid climatic oscillations and drastic environmental changes. In general, species can respond to such changes by behavioral accommodation, distributional shifts, ecophenotypic modifications (nongenetic), evolution (genetic) or ultimately face local extinction. How those responses manifested in the past is essential for properly predicting future ones especially as the current warm phase is further intensified by rising levels of atmospheric carbon dioxide. Here, we use ancient DNA (aDNA) and morphological features in combination with ecological niche modeling (ENM) to investigate genetic and nongenetic responses of Central European Palearctic shrews to past climatic change. We show that a giant form of shrew, previously described as an extinct Pleistocene Sorex species, represents a large ecomorph of the common shrew (Sorex araneus), which was replaced by populations from a different gene‐pool and with different morphology after the Pleistocene Holocene transition. We also report the presence of the cold‐adapted tundra shrew (S. tundrensis) in Central Europe. This species is currently restricted to Siberia and was hitherto unknown as an element of the Pleistocene fauna of Europe. Finally, we show that there is no clear correlation between climatic oscillations within the last 50 000 years and body size in shrews and conclude that a special nonanalogous situation with regard to biodiversity and food supply in the Late Glacial may have caused the observed large body size.     

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.     

Improving the interpretability of climate landscape metrics: An ecological risk analysis of Japan's Marine Protected Areas

Conservation efforts strive to protect significant swaths of terrestrial, freshwater and marine ecosystems from a range of threats. As climate change becomes an increasing concern, these efforts must take into account how resilient‐protected spaces will be in the face of future drivers of change such as warming temperatures. Climate landscape metrics, which signal the spatial magnitude and direction of climate change, support a convenient initial assessment of potential threats to and opportunities within ecosystems to inform conservation and policy efforts where biological data are not available. However, inference of risk from purely physical climatic changes is difficult unless set in a meaningful ecological context. Here, we aim to establish this context using historical climatic variability, as a proxy for local adaptation by resident biota, to identify areas where current local climate conditions will remain extant and future regional climate analogues will emerge. This information is then related to the processes governing species’ climate‐driven range edge dynamics, differentiating changes in local climate conditions as promoters of species range contractions from those in neighbouring locations facilitating range expansions. We applied this approach to assess the future climatic stability and connectivity of Japanese waters and its network of marine protected areas (MPAs). We find 88% of Japanese waters transitioning to climates outside their historical variability bounds by 2035, resulting in large reductions in the amount of available climatic space potentially promoting widespread range contractions and expansions. Areas of high connectivity, where shifting climates converge, are present along sections of the coast facilitated by the strong latitudinal gradient of the Japanese archipelago and its ocean current system. While these areas overlap significantly with areas currently under significant anthropogenic pressures, they also include much of the MPA network that may provide stepping‐stone protection for species that must shift their distribution because of climate change.     

How to survive a glaciation: the challenge of estimating biologically realistic potential distributions under freezing conditions

Correlative ecological niche models are increasingly used to estimate potential distributions during the Last Glacial Maximum (LGM) for biogeographical research. In the case of presence‐background/pseudoabsences techniques, cold environments that are poorly represented in existing geography can complicate the process of model calibration and transfer into more extreme cold environments that were very common during the LGM (non‐analog conditions). This may lead to biologically unrealistic estimations. Using one cold‐adapted North American mammal, we explore a real scenario to better understand the effect of restricting the range of environmental conditions over which niche models are calibrated and then transferred to LGM conditions. We performed two sets of experiments in Maxent: 1) we calibrated models in the context of only present‐day climate conditions, which is the most common practice, and compared predictions under LGM conditions based on two extrapolation methods (clamping versus unconstrained); 2) we calibrated single models using both present‐day and LGM conditions as part of the same background in order to include more extreme environments in the model calibration. Our experiments led to dramatically different estimates of species’ potential distributions, showing notable differences with respect to latitudinal and elevational shifts during the LGM. Models calibrated using present‐day climates yielded biologically unrealistic estimations, suggesting that species survived in the glaciers during the LGM. Even more unrealistic estimations were achieved when clamping was enforced as the method to extrapolate. Models calibrated in the context of both modern and past climates reduced the required degree of extrapolation and allowed more realistic potential distributions, suggesting that the species avoided extremely cold conditions during the LGM. This study alerts to the possibility of obtaining implausible potential distributions during the LGM due to restricted background datasets and offers recommendations that should promote better strategies to estimate distributional changes during glaciations.     

Projecting the future of an alpine ungulate under climate change scenarios

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

Dispersal limitations increase vulnerability under climate change for reptiles and amphibians in the southwestern United States

Species conservation plans frequently rely on information that spans political and administrative boundaries, especially when predictions are needed of future habitat under climate change; however, most species conservation plans and their requisite predictions of future habitat are often limited in geographical scope. Moreover, dispersal constraints for species of concern are not often incorporated into distribution models, which can result in overly optimistic predictions of future habitat. We used a standard modeling approach across a suite of 23 taxa of amphibians and reptiles in the North American deserts (560,024 km² across 13 ecoregions) to assess impacts of climate change on habitat and combined landscape population dispersal simulations with species distribution modeling to reduce the risk of predicting future habitat in areas that are not available to species given their dispersal abilities. We used 3 general circulation models and 2 representative concentration pathways (RCPs) to represent multiple scenarios of future habitat potential and assess which study species may be most vulnerable to changes forecasted under each climate scenario. Amphibians were the most vulnerable taxa, but the most vulnerable species tended to be those with the lowest dispersal ability rather than those with the most specialized niches. Under the most optimistic climate scenario considered (RCP 2.6; a stringent scenario requiring declining emissions from 2020 to near zero emissions by 2100), 76% of the study area may experience a loss of >20% of the species examined, while up to 87% of the species currently present may be lost in some areas under the most pessimistic climate scenario (RCP 8.5; a scenario wherein greenhouse gases continue to increase through 2100 based on trajectories from the mid-century). Most areas with high losses were concentrated in the Arizona and New Mexico Plateau ecoregion, the Edwards Plateau in Texas, and the Southwestern Tablelands in New Mexico and Texas, USA. Under the most pessimistic climate scenario, all species are predicted to lose some existing habitat, with an average of 34% loss of extant habitat across all species. Even under the most optimistic scenario, we detected an average loss of 24% of extant habitat across all species, suggesting that changing climates may influence the ranges of reptiles and amphibians in the Southwest.     

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale‐dependent context.     

Regional analysis of the impacts of climate change on cheatgrass invasion shows potential risk and opportunity

Interactions between climate change and non-native invasive species may combine to increase invasion risk to native ecosystems. Changing climate creates risk as new terrain becomes climatically suitable for invasion. However, climate change may also create opportunities for ecosystem restoration on invaded lands that become climatically unsuitable for invasive species. Here, I develop a bioclimatic envelope model for cheatgrass ( Bromus tectorum ), a non-native invasive grass in the western US, based on its invaded distribution. The bioclimatic envelope model is based on the Mahalanobis distance using the climate variables that best constrain the species' distribution. Of the precipitation and temperature variables measured, the best predictors of cheatgrass are summer, annual, and spring precipitation, followed by winter temperature. I perform a sensitivity analysis on potential cheatgrass distributions using the projections of 10 commonly used atmosphere–ocean general circulation models (AOGCMs) for 2100. The AOGCM projections for precipitation vary considerably, increasing uncertainty in the assessment of invasion risk. Decreased precipitation, particularly in the summer, causes an expansion of suitable land area by up to 45%, elevating invasion risk in parts of Montana, Wyoming, Utah, and Colorado. Conversely, increased precipitation reduces habitat by as much as 70%, decreasing invasion risk. The strong influence of precipitation conditions on this species' distribution suggests that relying on temperature change alone to project future change in plant distributions may be inadequate. A sensitivity analysis provides a framework for identifying key climate variables that may limit invasion, and for assessing invasion risk and restoration opportunities with climate change.     

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。     

The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change

Species are the unit of analysis in many global change and conservation biology studies; however, species are not uniform entities but are composed of different, sometimes locally adapted, populations differing in plasticity. We examined how intraspecific variation in thermal niches and phenotypic plasticity will affect species distributions in a warming climate. We first developed a conceptual model linking plasticity and niche breadth, providing five alternative intraspecific scenarios that are consistent with existing literature. Secondly, we used ecological niche‐modeling techniques to quantify the impact of each intraspecific scenario on the distribution of a virtual species across a geographically realistic setting. Finally, we performed an analogous modeling exercise using real data on the climatic niches of different tree provenances. We show that when population differentiation is accounted for and dispersal is restricted, forecasts of species range shifts under climate change are even more pessimistic than those using the conventional assumption of homogeneously high plasticity across a species' range. Suitable population‐level data are not available for most species so identifying general patterns of population differentiation could fill this gap. However, the literature review revealed contrasting patterns among species, urging greater levels of integration among empirical, modeling and theoretical research on intraspecific phenotypic variation.     

气候变化背景下青藏高原藏羚羊生境时空格局演变

气候变化可能导致物种分布范围变化甚至导致物种灭绝。为了解气候变化对青藏高原旗舰种和濒危种-藏羚羊（Pantholops hodgsonii）的潜在分布区影响,收集了316个藏羚羊实际点位分布数据和70个文献点位分布数据与温度季节性变化（Bio4）,海拔,最干月降雨（Bio14）等9个影响因子,采用最大熵模型（MaxEnt）进行建模,预测SSP126、SSP585极端压迫情景和SSP245中间压迫情景下的T1（2001-2018年）,T2（2021-2040年）,T3（2041-2060年）,T4（2061-2080年）,T5（2081-2100年）5个时期的潜在分布区。研究结果表明：（1）在不同气候变化情景下,藏羚羊核心生境主要分布在可可西里、羌塘、阿尔金国家级自然保护区和三江源国家公园;（2）温度季节性变化（Bio4）和海拔被认为是最关键的两个环境因子;（3）随着温室气体排放强度的增强,藏羚羊的核心区生境向高海拔和高纬度地区扩张;（4）有43.18%的保护空缺区在保护区外,未受到有效保护。总之,研究藏羚羊的地理分布对于气候变化的响应与适应,根据适宜生境演变规律做出有效的保护措施,对藏羚羊种群的长期监测、保护、有效管理甚至重建具有重要现实意义。     

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.     

Predicting the influence of wolf-provided carrion on scavenger community dynamics under climate change scenarios

Climate change poses an immediate threat to the persistence and distribution of many species, yet our ability to forecast changes in species composition is hindered by poor understanding of the extent to which higher trophic‐level interactions may buffer or exacerbate the adverse effects of warming. We incorporated species‐specific consumption data from 240 wolf‐killed elk carcasses from Yellowstone National Park into stochastic simulation models to link trends in the El Niño Southern Oscillation (ENSO) to food procurement by a guild of scavengers as a function of gray wolf reintroduction. We find that a shift in ENSO towards the El Niño (warming) phase of the cycle coincident with increasing global temperatures reduces carrion for scavengers, particularly those with strong seasonal patterns in resource use such as grizzly bears. Wolves alleviate these warming‐induced food shortages by rendering control over this crucial resource to biotic rather than abiotic factors. Ecosystems with intact top predators are likely to exhibit stronger biotic regulation and should be more resistant to climate change than ecosystems lacking them.     

Dramatic loss of seagrass habitat under projected climate change in the Mediterranean Sea

Although climate warming is affecting most marine ecosystems, the Mediterranean is showing earlier impacts. Foundation seagrasses are already experiencing a well‐documented regression in the Mediterranean which could be aggravated by climate change. Here, we forecast distributions of two seagrasses and contrast predicted loss with discrete regions identified on the basis of extant genetic diversity. Under the worst‐case scenario, Posidonia oceanica might lose 75% of suitable habitat by 2050 and is at risk of functional extinction by 2100, whereas Cymodocea nodosa would lose only 46.5% in that scenario as losses are compensated with gained and stable areas in the Atlantic. Besides, we predict that erosion of present genetic diversity and vicariant processes can happen, as all Mediterranean genetic regions could decrease considerably in extension in future warming scenarios. The functional extinction of Posidonia oceanica would have important ecological impacts and may also lead to the release of the massive carbon stocks these ecosystems stored over millennia.