Ensemble distribution models in conservation prioritization: from consensus predictions to consensus reserve networks

Future climatically suitable areas for bats in South Asia

Climate change majorly impacts biodiversity in diverse regions across the world, including South Asia, a megadiverse area with heterogeneous climatic and vegetation regions. However, climate impacts on bats in this region are not well-studied, and it is unclear whether climate effects will follow patterns predicted in other regions. We address this by assessing projected near-future changes in climatically suitable areas for 110 bat species from South Asia. We used ensemble ecological niche modelling with four algorithms (random forests, artificial neural networks, multivariate adaptive regression splines and maximum entropy) to define climatically suitable areas under current conditions (1970-2000). We then extrapolated near future (2041-2060) suitable areas under four projected scenarios (combining two global climate models and two shared socioeconomic pathways, SSP2: middle-of-the-road and SSP5: fossil-fuelled development). Projected future changes in suitable areas varied across species, with most species predicted to retain most of the current area or lose small amounts. When shifts occurred due to projected climate change, new areas were generally northward of current suitable areas. Suitability hotspots, defined as regions suitable for >30% of species, were generally predicted to become smaller and more fragmented. Overall, climate change in the near future may not lead to dramatic shifts in the distribution of bat species in South Asia, but local hotspots of biodiversity may be lost. Our results offer insight into climate change effects in less studied areas and can inform conservation planning, motivating reappraisals of conservation priorities and strategies for bats in South Asia.

Transnational conservation to anticipate future plant shifts in Europe

To meet the COP15 biodiversity framework in the European Union (EU), one target is to protect 30% of its land by 2030 through a resilient transnational conservation network. The European Alps are a key hub of this network hosting some of the most extensive natural areas and biodiversity hotspots in Europe. Here we assess the robustness of the current European reserve network to safeguard the European Alps' flora by 2080 using semi-mechanistic simulations. We first highlight that the current network needs strong readjustments as it does not capture biodiversity patterns as well as our conservation simulations. Overall, we predict a strong shift in conservation need through time along latitudes, and from lower to higher elevations as plants migrate upslope and shrink their distribution. While increasing species, trait and evolutionary diversity, migration could also threaten 70% of the resident flora. In the face of global changes, the future European reserve network will need to ensure strong elevation and latitudinal connections to complementarily protect multifaceted biodiversity beyond national borders.

Clay and climatic variability explain the global potential distribution of Juniperus phoenicea toward restoration planning

Juniperus phoenicea is a medicinal conifer tree species distributed mainly in the Mediterranean region, and it is IUCN Red Listed species, locally threatened due to arid conditions and seed over-collection for medicinal purposes, particularly in the East-Mediterranean region. Several studies have addressed the potential distribution of J. phoenicea using bioclimatic and topographic variables at a local or global scale, but little is known about the role of soil and human influences as potential drivers. Therefore, our objectives were to determine the most influential predictor factors and their relative importance that might be limiting the regeneration of J. phoenicea, in addition, identifying the most suitable areas which could be assumed as priority conservation areas. We used ensemble models for species distribution modelling. Our findings revealed that aridity, temperature seasonality, and clay content are the most important factors limiting the potential distribution of J. phoenicea. Potentially suitable areas of the output maps, in which J. phoenicea populations degraded, could be assumed as decision-support tool reforestation planning. Other suitable areas, where there was no previous tree cover are a promising tool for afforestation and conservation planning. Finally, conservation actions are needed for natural habitats, particularly in the arid and semi-arid regions, which are highly threatened by global warming.

Climatic niche shifts in introduced species

Predictions of future biological invasions often rely on the assumption that introduced species establish only under climatic conditions similar to those in their native range. To date, 135 studies have tested this assumption of 'niche conservatism', yielding contradictory results. Here we revisit this literature, consider the evidence for niche shifts, critically assess the methods used, and discuss the authors' interpretations of niche shifts. We find that the true frequency of niche shifts remains unknown because of diverging interpretations of similar metrics, conceptual issues biasing conclusions towards niche conservatism, and the use of climatic data that may not be biologically meaningful. We argue that these issues could be largely addressed by focussing on trends or relative degrees of niche change instead of dichotomous classifications (shift versus no shift), consistently and transparently including non-analogous climates, and conducting experimental studies on mismatches between macroclimates and microclimates experienced by the study organism. Furthermore, an observed niche shift may result either from species filling a greater part of their fundamental niche during the invasion (a 'realised niche shift') or from rapid evolution of traits adapting species to novel climates in the introduced range (a 'fundamental niche shift'). Currently, there is no conclusive evidence distinguishing between these potential mechanisms of niche shifts. We outline how these questions may be addressed by combining computational analyses and experimental evidence.

Quest for New Space for Restricted Range Mammals: The Case of the Endangered Walia Ibex

Populations of large mammals have declined at alarming rates, especially in areas with intensified land use where species can only persist in small habitat fragments. To support conservation planning, we developed habitat suitability models for the Walia ibex (Capra walie), an endangered wild goat endemic to the Simen Mountains, Ethiopia. We calibrated several models that differ in statistical properties to estimate the spatial extent of suitable habitats of the Walia ibex in the Simen Mountains, as well as in other parts of the Ethiopian highlands to assess potentially suitable areas outside the current distribution range of the species. We further addressed the potential consequences of future climate change using a climate model with four emission scenarios. Model projections estimated the potential suitable habitat under current climate to 501–672 km2 in Simen and 6,251–7,732 km2 in other Ethiopian mountains. Under projected climate change by 2,080, the suitable habitat became larger in Simen but smaller in other parts of Ethiopia. The projected expansion in Simen is contrary to the general expectation of shrinking suitable habitats for high-elevation species under climate warming and may partly be due to the ruggedness of these particular mountains. The Walia ibex has a wide altitudinal range and is able to exploit very steep slopes, allowing it to track the expected vegetation shift to higher altitudes. However, this potential positive impact may not last long under continued climate warming, as the species will not have much more new space left to colonize. Our study indicates that the current distribution range can be substantially increased by reintroducing and/or translocating the species to other areas with suitable habitat. Indeed, to increase the viability and prospects for survival of this flagship species, we strongly recommend human-assisted reintroduction to other Ethiopian mountains. Emulating the successful reintroduction of the Alpine ibex that has spread from a single mountain in Italy to its historical ranges of the Alps in Europe might contribute to saving the Walia ibex from extinction.

Assessment and prioritization of cultural ecosystem services in the Sahara-Sahelian region

Desert environments remain largely neglected by the society and their potential to provide benefits to people remain understudied. Hotspots of cultural ecosystem services have been identified in some deserts; yet, knowing which countries need to strengthen efforts to satisfy people's demand for those services is timely needed. Here, we show the performance of countries within the Earth's largest warm region - the Sahara-Sahel - in managing cultural ecosystem services. Using the most-advanced decision-support tools and updated databases on biodiversity features and constrains to ecosystem services and on socioeconomic indicators, we identified national priorities for cultural services management. We also identified countries that are missing opportunities for local sustainable development. About 34% of Sahara-Sahel is prioritized for cultural ecosystem services, particularly in the main mountains and waterbodies of the region and along the Western and Eastern coastal limits. Algeria, Egypt, Libya, Morocco, Senegal, and Tunisia are performing better in managing their cultural services given the availability of such services in their territories. Burkina Faso, Cameroon, Chad, Egypt, Libya, Mali, Niger, Nigeria, Sudan, and South Sudan need to urgently improve their ease of mobility, governance, safety, socioeconomic and health systems to foster ecosystem services demand. Cameroon, Eritrea, and Senegal are receiving far less tourists than what their ecosystems can handle and need to improve their local conditions for better marketing international tourists able to economically contribute to sustainable development through ecotourism programs. The approach developed here serves as a framework for conserving the last world wild ecosystems and is replicable to other contexts where regional planning for ecosystem management is compulsory.

How citizen science could improve species distribution models and their independent assessment

Species distribution models (SDM) have been increasingly developed in recent years, but their validity is questioned. Their assessment can be improved by the use of independent data, but this can be difficult to obtain and prohibitive to collect. Standardized data from citizen science may be used to establish external evaluation datasets and to improve SDM validation and applicability.We used opportunistic presence-only data along with presence-absence data from a standardized citizen science program to establish and assess habitat suitability maps for 9 species of amphibian in western France. We assessed Generalized Additive and Random Forest Models' performance by (1) cross-validation using 30% of the opportunistic dataset used to calibrate the model or (2) external validation using different independent datasets derived from citizen science monitoring. We tested the effects of applying different combinations of filters to the citizen data and of complementing it with additional standardized fieldwork.Cross-validation with an internal evaluation dataset resulted in higher AUC (Area Under the receiver operating Curve) than external evaluation causing overestimation of model accuracy and did not select the same models; models integrating sampling effort performed better with external validation. AUC, specificity, and sensitivity of models calculated with different filtered external datasets differed for some species. However, for most species, complementary fieldwork was not necessary to obtain coherent results, as long as the citizen science data were strongly filtered.Since external validation methods using independent data are considered more robust, filtering data from citizen sciences may make a valuable contribution to the assessment of SDM. Limited complementary fieldwork with volunteer's participation to complete ecological gradients may also possibly enhance citizen involvement and lead to better use of SDM in decision processes for nature conservation.

Projecting the Impact of Climate Change on the Spatial Distribution of Six Subalpine Tree Species in South Korea Using a Multi-Model Ensemble Approach

Climate change is recognized as a major threat to global biodiversity and has already caused extensive regional extinction. In particular danger are the plant habitats in subalpine zones, which are more vulnerable to climate change. Evergreen coniferous trees in South Korean subalpine zones are currently designated as a species that need special care given their conservation value, but the reason for their decline and its seriousness remains unclear. This research estimates the potential land suitability (LS) of the subalpine zones in South Korea for six coniferous species vulnerable to climate change in the current time (1970–2000) and two future periods, the 2050s (2041–2060) and the 2070s (2061–2080). We analyze the ensemble-averaged loss of currently suitable habitats in the future, using nine species distribution models (SDMs). Korean arborvitae (Thuja koraiensis) and Khingan fir (Abies nephrolepis) are two species expected to experience significant habitat losses in 2050 (−59.5% under Representative Concentration Pathway (RCP) 4.5 to −65.9% under RCP 8.5 and −56.3% under RCP 4.5 to −57.7% under RCP 8.5, respectively). High extinction risks are estimated for these species, due to the difficulty of finding other suitable habitats with high LS. The current habitat of Korean fir (Abies koreana), listed as a threatened species on the International Union for Conservation of Nature (IUCN) Red List, is expected to decrease by −23.9% (RCP 4.5) to −28.4% (RCP 8.5) and −36.5% (RCP 4.5) to −36.7% (RCP 8.5) in the 2050s and 2070s, respectively. Still, its suitable habitats are also estimated to expand geographically toward the northern part of the Baekdudaegan mountain range. In the context of forest management and adaptation planning, the multi-model ensemble approach to mapping future shifts in the range of subalpine tree species under climate change provides robust information about the potential distribution of threatened and endanger

A GIS-based policy support tool to determine national responsibilities and priorities for biodiversity conservation

Efficient biodiversity conservation requires that limited resources be allocated in accordance with national responsibilities and priorities. Without appropriate computational tools, the process of determining these national responsibilities and conservation priorities is time intensive when considering many species across geographic scales. Here, we have developed a computational tool as a module for the ArcGIS geographic information system. The ArcGIS National Responsibility Assessment Tool (NRA-Tool) can be used to create hierarchical lists of national responsibilities and priorities for global species conservation. Our tool will allow conservationists to prioritize conservation efforts and to focus limited resources on relevant species and regions. We showcase our tool with data on 258 bird species and various biophysical regions, including Environmental Zones in 58 Asian countries and regions. Our tool provides a decision support system for conservation policy with attractive and easily interpretable visual outputs illustrating national responsibilities and priorities for species conservation. The graphical output allows for smooth integration into assessment reports, such as the European Article 17 report, the Living Planet Index report, or similar regional and global reports.

Meta-replication, sampling bias, and multi-scale model selection: A case study on snow leopard (Panthera uncia) in western China

Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi-scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai-Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape-specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles' overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape-specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low-contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi-scale response of snow leopards to environmental attributes and confirms the role of meta-replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction.

A multi-scale, integrative modeling framework for setting conservation priorities at the catchment scale for the Freshwater Pearl Mussel Margaritifera margaritifera

The identification and prioritization of sites for conservation actions to protect biodiversity in lotic systems is crucial when economic resources or available areas are limited. Challenges include the incorporation of multi-scale interactions, and the application of species distribution models (SDMs) to rare organism with multiple life stages. To support the planning of conservation actions for the highly endangered Freshwater Pearl Mussel Margaritifera margaritifera (FPM), this paper aims at developing an ecohydrological modeling cascade including a hydrological model (SWAT) and a hydraulic model (HEC-RAS). Building on hydrology and hydraulics, Random Forest models for potential risk to juveniles due to sand accumulation, SDMs for adults habitat niche, and a landscape connectivity assessment of dispersal potential were developed. The feasibility of such models integration was tested in the Aist catchment (630 km²) in Austria. The potential FPM habitat and the sand accumulation risk for the whole catchment were predicted with good accuracy. Results show that while the potentially suitable habitats for adults FPM cover 34% of the river network, only few habitat patches can maximize the dispersal potential (4% of the river network) and even less are showing limited impact of accumulations (3.5% of river network). No habitat patch that meets all the three criteria is available, suggesting approaches that target the patch-specific critical life stage-factors are promising for conservation.

Identifying priority conservation areas in a Saharan environment by highlighting the endangered Cuvier's Gazelle as a flagship species

Monitoring populations and designing effective conservation actions for endangered species present significant challenges. An accurate understanding of current distribution, ecological traits and habitat requirements is imperative in formulating conservation strategies. Recent surveys on the southernmost Cuvier’s Gazelle (Gazella cuvieri) population, an ungulate endemic to North Africa, showcase its importance in terms of numbers and genetic diversity. This population inhabits a remote region in the extreme north-western portion of the Sahara Desert and has not been well studied. Here, we examine the potential distribution of Cuvier’s Gazelle and the environmental factors limiting the species in a Saharan environment, by combining broad-scale field survey data and species distribution models. Our objective was to identify high priority conservation areas in the southernmost known portion of the species’ distribution by modelling habitat selection at the landscape scale using a predictive distribution map. Our results show that the distribution of Cuvier’s Gazelle is strongly related to mountainous areas with heterogeneous terrain and remoteness from large human settlements over other ecological factors that had less impact on the species’ presence and distribution. We also provide a quantitative estimate of the potential distribution range of Cuvier’s Gazelle in southern Morocco, identifying two well-demarcated key areas. The two core areas currently contain enough rugged terrain isolated from human encroachment to support the endangered species in this harsh desert environment. We encourage the implementation of conservation planning for Cuvier’s Gazelle as an “umbrella species”, which will confer effective protection to higher-quality habitat zones and co-occurring species, leading to sustainable and ecologically responsible development in the region.

Dynamic shifts within volatile fatty acid-degrading microbial communities indicate process imbalance in anaerobic digesters

Buildup of volatile fatty acids (VFAs) in anaerobic digesters (ADs) often results in acidification and process failure. Understanding the dynamics of microbial communities involved in VFA degradation under stable and overload conditions may help optimize anaerobic digestion processes. In this study, five triplicate mesophilic completely mixed AD sets were operated at different organic loading rates (OLRs; 1-6 g chemical oxygen demand [COD] L_R^-1day^-1), and changes in the composition and abundance of VFA-degrading microbial communities were monitored using amplicon sequencing and taxon-specific quantitative PCRs, respectively. AD sets operated at OLRs of 1-4 g COD L_R^-1day^-1 were functionally stable throughout the operational period (120 days) whereas process instability (characterized by VFA buildup, pH decline, and decreased methane production rate) occurred in digesters operated at ≥ 5 g COD L_R^-1day^-1. Though microbial taxa involved in propionate (Syntrophobacter and Pelotomaculum) and butyrate (Syntrophomonas) degradation were detected across all ADs, their abundance decreased with increasing OLR. The overload conditions also inhibited the proliferation of the acetoclastic methanogen, Methanosaeta, and caused a microbial community shift to acetate oxidizers (Tepidanaerobacter acetatoxydans) and hydrogenotrophic methanogens (Methanoculleus). This study's results highlight the importance of operating ADs with conditions that promote the maintenance of microbial communities involved in VFA degradation.

Habitat patches for newts in the face of climate change: local scale assessment combining niche modelling and graph theory

Triturus cristatus and Triturus marmoratus are two protected and declining newts occurring in the administrative department of Vienne, in France. They have limited dispersal abilities and rely on the connectivity between habitats and their suitability. In a warming climate, the locations of suitable habitats are expected to change, as is the connectivity. Here, we wondered how climate change might affect shifts in habitat suitability and connectivity of habitat patches, as connectivity is a key element enabling species to realize a potential range shift. We used ecological niche modelling (ENM), combining large-scale climate suitability with local scale, high-resolution habitat features, to identify suitable areas for the two species, under low and high warming scenarios (RCP 2.6 and RCP 8.5). We associated it with connectivity assessment through graph theory. The variable 'small ponds' contributed most to land cover-only ENMs for both species. Projections with climate change scenarios revealed a potential impact of warming on suitable habitat patches for newts, especially for T. cristatus. We observed a decrease in connectivity following a decrease in patch suitability. Our results highlight the important areas for newt habitat connectivity within the study area, and define those potentially threatened by climate warming. We provide information for prioritizing sites for acquisition, protection or restoration, and to advise landscape policies. Our framework is a useful and easily reproducible way to combine global climate requirements of the species with detailed information on species habitats and occurrence when available.

Assessing the exposure of forest habitat types to projected climate change-Implications for Bavarian protected areas

AIM

Due to their longevity and structure, forest ecosystems are particularly affected by climate change with consequences for their biodiversity, functioning, and services to mankind. In the European Union (EU), natural and seminatural forests are protected by the Habitats Directive and the Natura 2000 network. This study aimed to assess the exposure of three legally defined forest habitat types to climate change, namely (a) Tilio-Acerion forests of slopes, screes, and ravines (9180*), (b) bog woodlands (91D0*), and (c) alluvial forests with Alnus glutinosa and Fraxinus excelsior (91E0*). We analyzed possible changes in their Bavarian distribution, including their potential future coverage by Natura 2000 sites. We hypothesized that protected areas (PAs) with larger elevational ranges will remain suitable for the forests as they allow for altitudinal distribution shifts.

METHODS

To estimate changes in range size and coverage by PAs, we combined correlative species distribution models (SDMs) with spatial analyses. Ensembles of SDM-algorithms were applied to two climate change scenarios (RCP4.5 and RCP8.5) of the HadGEM2-ES model for the period 2061-2080.

RESULTS

Our results revealed that bog woodlands experience the highest range losses (>2/3) and lowest PA coverage (max. 15% of sites with suitable conditions). Tilio-Acerion forests exhibit opposing trends depending on the scenario, while alluvial forests are less exposed to climatic changes. As expected, the impacts of climate change are more pronounced under the "business as usual" scenario (RCP8.5). Additionally, PAs in flat landscapes are more likely to lose environmental suitability for currently established forest habitat types.

MAIN CONCLUSIONS

Based on these findings, we advocate the expansion of the Natura 2000 network particularly in consideration of elevational gradients, connectivity, and projected climatic suitability. Nonclimatic stressors on forest ecosystems, especially bog woodlands, should be decreased and climate change mitigation efforts enhanced. We recommend transferring the approach to other habitat types and regions.

Xylella fastidiosa: climate suitability of European continent

The bacterium Xylella fastidiosa (Xf) is a plant endophyte native to the Americas that causes diseases in many crops of economic importance (grapevine, Citrus, Olive trees etc). Xf has been recently detected in several regions outside of its native range including Europe where little is known about its potential geographical expansion. We collected data documenting the native and invaded ranges of the Xf subspecies fastidiosa, pauca and multiplex and fitted bioclimatic species distribution models (SDMs) to assess the potential climate suitability of European continent for those pathogens. According to model predictions, the currently reported distribution of Xf in Europe is small compared to the large extent of climatically suitable areas. The regions at high risk encompass the Mediterranean coastal areas of Spain, Greece, Italy and France, the Atlantic coastal areas of France, Portugal and Spain as well as the southwestern regions of Spain and lowlands in southern Italy. The extent of predicted climatically suitable conditions for the different subspecies are contrasted. The subspecies multiplex, and to a certain extent the subspecies fastidiosa, represent a threat to most of Europe while the climatically suitable areas for the subspecies pauca are mostly limited to the Mediterranean basin. These results provide crucial information for the design of a spatially informed European-scale integrated management strategy, including early detection surveys in plants and insect vectors and quarantine measures.

Update of the Scientific Opinion on the risks to plant health posed by Xylella fastidiosa in the EU territory

EFSA was asked to update the 2015 EFSA risk assessment on Xylella fastidiosa for the territory of the EU. In particular, EFSA was asked to focus on potential establishment, short- and long-range spread, the length of the asymptomatic period, the impact of X. fastidiosa and an update on risk reduction options. EFSA was asked to take into account the different subspecies and Sequence Types of X. fastidiosa. This was attempted throughout the scientific opinion but several issues with data availability meant that this could only be partially achieved. Models for risk of establishment showed most of the EU territory may be potentially suitable for X. fastidiosa although southern EU is most at risk. Differences in estimated areas of potential establishment were evident among X. fastidiosa subspecies, particularly X. fastidiosa subsp. multiplex which demonstrated areas of potential establishment further north in the EU. The model of establishment could be used to develop targeted surveys by Member States. The asymptomatic period of X. fastidiosa varied significantly for different host and pathogen subspecies combinations, for example from a median of approximately 1 month in ornamental plants and up to 10 months in olive, for pauca. This variable and long asymptomatic period is a considerable limitation to successful detection and control, particularly where surveillance is based on visual inspection. Modelling suggested that local eradication (e.g. within orchards) is possible, providing sampling intensity is sufficient for early detection and effective control measures are implemented swiftly (e.g. within 30 days). Modelling of long-range spread (e.g. regional scale) demonstrated the important role of long-range dispersal and the need to better understand this. Reducing buffer zone width in both containment and eradication scenarios increased the area infected. Intensive surveillance for early detection, and consequent plant removal, of new outbreaks is crucial for both successful eradication and containment at the regional scale, in addition to effective vector control. The assessment of impacts indicated that almond and Citrus spp. were at lower impact on yield compared to olive. Although the lowest impact was estimated for grapevine, and the highest for olive, this was based on several assumptions including that the assessment considered only Philaenus spumarius as a vector. If other xylem-feeding insects act as vectors the impact could be different. Since the Scientific Opinion published in 2015, there are still no risk reduction options that can remove the bacterium from the plant in open field conditions. Short- and long-range spread modelling showed that an early detection and rapid application of phytosanitary measures, consisting among others of plant removal and vector control, are essential to prevent further spread of the pathogen to new areas. Further data collection will allow a reduction in uncertainty and facilitate more tailored and effective control given the intraspecific diversity of X. fastidiosa and wide host range.

Temperature and hydrologic alteration predict the spread of invasive Largemouth Bass (Micropterus salmoides)

The successful establishment of an aquatic invasive alien species can be mediated by a suite of environmental factors, including climate and anthropogenic disturbance. Dams and reservoirs are thought to promote freshwater fish invasion success through hydrological alterations but the evidence for their role in the global invasion of Largemouth Bass (Micropterus salmoides) on a landscape scale is limited. Here, we examine the distribution of Largemouth Bass, one of the most widely introduced fish in the world, from the Iberian Peninsula using species distribution models (SDMs), including an ensemble forecast. We used these models to test the role of twelve environmental predictors expected to influence the distribution of Largemouth Bass, including the reservoir storage capacity at local and upstream reaches. We found that the predictive accuracy, based on AUC criteria, of the ensemble model was higher than any of the six individual SDMs for Largemouth Bass. The most influential predictor of bass distribution included in our model of the Iberian Peninsula was temperature, where warmer temperatures were generally associated with bass presence, and cooler temperatures with absence. In addition to warmer temperatures, increasing storage of local and upstream reservoirs increased predicted presence, suggesting an important role of reservoirs in mediating the invasive success of this fish. Our results indicate that although natural climatic factors may be crucial in the successful invasion of Largemouth Bass, hydrological alteration (e.g., regulated flow regimes and lentic habitats associated with dams and reservoirs) may be important. Understanding the drivers promoting the establishment of this global invader will be important in identifying areas at risk and in developing future efforts to control its spread, especially when those drivers are ongoing anthropogenic disturbances such as the construction and operation of dams and reservoirs.

Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping

In this research, eight individual machine learning and statistical models are implemented and compared, and based on their results, seven ensemble models for flood susceptibility assessment are introduced. The individual models included artificial neural networks, classification and regression trees, flexible discriminant analysis, generalized linear model, generalized additive model, boosted regression trees, multivariate adaptive regression splines, and maximum entropy, and the ensemble models were Ensemble Model committee averaging (EMca), Ensemble Model confidence interval Inferior (EMciInf), Ensemble Model confidence interval Superior (EMciSup), Ensemble Model to estimate the coefficient of variation (EMcv), Ensemble Model to estimate the mean (EMmean), Ensemble Model to estimate the median (EMmedian), and Ensemble Model based on weighted mean (EMwmean). The data set covered 201 flood events in the Haraz watershed (Mazandaran province in Iran) and 10,000 randomly selected non-occurrence points. Among the individual models, the Area Under the Receiver Operating Characteristic (AUROC), which showed the highest value, belonged to boosted regression trees (0.975) and the lowest value was recorded for generalized linear model (0.642). On the other hand, the proposed EMmedian resulted in the highest accuracy (0.976) among all models. In spite of the outstanding performance of some models, nevertheless, variability among the prediction of individual models was considerable. Therefore, to reduce uncertainty, creating more generalizable, more stable, and less sensitive models, ensemble forecasting approaches and in particular the EMmedian is recommended for flood susceptibility assessment.

Habitat assessment of Marco Polo sheep (Ovis ammon polii) in Eastern Tajikistan: Modeling the effects of climate change

Identifying the factors predicting the high-elevation suitable habitats of Central Asian argali wild sheep and how these suitable habitats are affected by the changing climate regimes could help address conservation and management efforts and identify future critical habitat for the species in eastern Tajikistan. This study used environmental niche models (ENMs) to map and compare potential present and future distributions of suitable environmental conditions for Marco Polo argali. Argali occurrence points were collected during field surveys conducted from 2009 to 2016. Our models showed that terrain ruggedness and annual mean temperature had strong correlations on argali distribution. We then used two greenhouse gas concentration trajectories (RCP 4.5 and RCP 8.5) for two future time periods (2050 and 2070) to model the impacts of climate change on Marco Polo argali habitat. Results indicated a decline of suitable habitat with majority of losses observed at lower elevations (3,300-4,300 m). Models that considered all variables (climatic and nonclimatic) predicted losses of present suitable areas of 60.6% (6,928 km2) and 63.2% (7,219 km2) by 2050 and 2070, respectively. Results also showed averaged habitat gains of 46.2% (6,106 km2) at much higher elevations (4,500-6,900 m) and that elevational shifts of habitat use could occur in the future. Our results could provide information for conservation planning for this near threatened species in the region.

Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land-use change projections with the latest developments in network-connectivity research and spatial, multipurpose conservation prioritization. We used land-use change simulations to explore robustness of species' habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land-use change. The application of connectivity criteria alongside habitat-quality criteria for protected-area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade-offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.

Prioritizing conservation areas for coastal plant diversity under increasing urbanization

Coastal urban expansion will continue to drive further biodiversity losses, if conservation targets for coastal ecosystems are not defined and met. Prioritizing areas for future protected area networks is thus an urgent task in such urbanization-threatened ecosystems. Our aim is to quantify past and future losses of coastal vegetation priority areas due to urbanization and assess the effectiveness of the existing protected area network for conservation. We conduct a prioritization analysis, based on 82 coastal plants, including common and IUCN red list species, in a highly-urbanized but biotically diverse region, in South-Eastern France. We evaluate the role of protected areas, by taking into account both strict and multi-use areas. We assess the impact of past and future urbanization on high priority areas, by combining prioritization analyses and urbanization models. We show that half of the highly diverse areas have already been lost due to urbanization. Remaining top priority areas are also among the most exposed to future urban expansion. The effectiveness of the existing protected area (PA) network is only partial. While strict PAs coincide well with top priority areas, they only represent less than one third of priority areas. The effectiveness of multi-use PAs, such as the Natura 2000 network, also remains limited. Our approach highlights the impact of urbanization on plant conservation targets. By modelling urbanization, we manage to identify those areas where protection could be more efficient to limit further losses. We suggest to use our approach in the future to expand the PA network in order to achieve the 2020 Aichi biodiversity targets.

Identifying appropriate protected areas for endangered fern species under climate change

The management of protected areas (PAs) is widely used in the conservation of endangered plant species under climate change. However, studies that have identified appropriate PAs for endangered fern species are rare. To address this gap, we must develop a workflow to plan appropriate PAs for endangered fern species that will be further impacted by climate change. Here, we used endangered fern species in China as a case study, and we applied conservation planning software coupled with endangered fern species distribution data and distribution modeling to plan conservation areas with high priority protection needs under climate change. We identified appropriate PAs for endangered fern species under climate change based on the IUCN protected area categories (from Ia to VI) and planned additional PAs for endangered fern species. The high priority regions for protecting the endangered fern species were distributed throughout southern China. With decreasing temperature seasonality, the priority ranking of all endangered fern species is projected to increase in existing PAs. Accordingly, we need to establish conservation areas with low climate vulnerability in existing PAs and expand the conservation areas for endangered fern species in the high priority conservation regions.

Species interactions in occurrence data for a community of tick-transmitted pathogens

Interactions between tick species, their realized range of hosts, the pathogens they carry and transmit, and the geographic distribution of species in the Western Palearctic were determined based on evidence published between 1970-2014. These relationships were linked to remotely sensed features of temperature and vegetation and used to extract the network of interactions among the organisms. The resulting datasets focused on niche overlap among ticks and hosts, species interactions, and the fraction of the environmental niche in which tick-borne pathogens may circulate as a result of interactions and overlapping environmental traits. The resulting datasets provide a valuable resource for researchers interested in tick-borne pathogens, as they conciliate the abiotic and biotic sides of their niche, allowing exploration of the importance of each host species acting as a vertebrate reservoir in the circulation of tick-transmitted pathogens in the environmental niche.

Bioacoustics for species management: two case studies with a Hawaiian forest bird

The management of animal endangered species requires detailed information on their distribution and abundance, which is often hard to obtain. When animals communicate using sounds, one option is to use automatic sound recorders to gather information on the species for long periods of time with low effort. One drawback of this method is that processing all the information manually requires large amounts of time and effort. Our objective was to create a relatively “user‐friendly” (i.e., that does not require big programming skills) automatic detection algorithm to improve our ability to get basic data from sound‐emitting animal species. We illustrate our algorithm by showing two possible applications with the Hawai'i ‘Amakihi, Hemignathus virens virens, a forest bird from the island of Hawai'i. We first characterized the ‘Amakihi song using recordings from areas where the species is present in high densities. We used this information to train a classification algorithm, the support vector machine (SVM), in order to identify ‘Amakihi songs from a series of potential songs. We then used our algorithm to detect the species in areas where its presence had not been previously confirmed. We also used the algorithm to compare the relative abundance of the species in different areas where management actions may be applied. The SVM had an accuracy of 86.5% in identifying ‘Amakihi. We confirmed the presence of the ‘Amakihi at the study area using the algorithm. We also found that the relative abundance of ‘Amakihi changes among study areas, and this information can be used to assess where management strategies for the species should be better implemented. Our automatic song detection algorithm is effective, “user‐friendly” and can be very useful for optimizing the management and conservation of those endangered animal species that communicate acoustically.

Making spatial prioritizations robust to climate change uncertainties: a case study with North American birds

Spatial prioritizations are essential tools for conserving biodiversity in the face of accelerating climate change. Uncertainty about species' responses to changing climates can complicate prioritization efforts, however, and delay conservation investment. In an effort to facilitate decision-making, we identified three hypotheses about species' potential responses to climate change based on distinct biological assumptions related to niche flexibility and colonization ability. Using 314 species of North American birds as a test case, we tuned separate spatial prioritizations to each hypothesis and assessed the degree to which assumptions about biological responses affected the perceived conservation value of the landscape and prospects for individual taxa. We also developed a bet-hedging prioritization to minimize the chance that incorrect assumptions would lead to valuable landscapes and species being overlooked in multispecies prioritizations. Collectively, these analyses help to quantify the sensitivity of spatial prioritizations to different assumptions about species' responses to climate change and provide a framework for enabling efficient conservation investment despite substantial biological uncertainty.

Disentangling host, pathogen, and environmental determinants of a recently emerged wildlife disease: lessons from the first 15 years of amphibian chytridiomycosis research

The amphibian fungal disease chytridiomycosis, which affects species across all continents, recently emerged as one of the greatest threats to biodiversity. Yet, many aspects of the basic biology and epidemiology of the pathogen, Batrachochytrium dendrobatidis (Bd), are still unknown, such as when and from where did Bd emerge and what is its true ecological niche? Here, we review the ecology and evolution of Bd in the Americas and highlight controversies that make this disease so enigmatic. We explore factors associated with variance in severity of epizootics focusing on the disease triangle of host susceptibility, pathogen virulence, and environment. Reevaluating the causes of the panzootic is timely given the wealth of data on Bd prevalence across hosts and communities and the recent discoveries suggesting co-evolutionary potential of hosts and Bd. We generate a new species distribution model for Bd in the Americas based on over 30,000 records and suggest a novel future research agenda. Instead of focusing on pathogen "hot spots," we need to identify pathogen "cold spots" so that we can better understand what limits the pathogen's distribution. Finally, we introduce the concept of "the Ghost of Epizootics Past" to discuss expected patterns in postepizootic host communities.

Departures from the Energy-Biodiversity Relationship in South African Passerines: Are the Legacies of Past Climates Mediated by Behavioral Constraints on Dispersal?

Legacies of paleoclimates in contemporary biodiversity patterns have mostly been investigated with global datasets, or with weakly dispersive organisms, and as a consequence been interpreted in terms of geographical or physical constraints. If paleoclimatic legacies also occurred at the regional scale in the distributions of vagile organisms within biomes, they would rather suggest behavioral constraints on dispersal, i.e., philopatric syndromes. We examined 1) the residuals of the regression between contemporary energy and passerine species richness in South African biomes and 2) phylogenetic dispersion of passerine assemblages, using occupancy models and quarter-degree resolution citizen science data. We found a northeast to southwest gradient within mesic biomes congruent with the location of Quaternary mesic refugia, overall suggesting that as distance from refugia increased, more clades were lacking from local assemblages. A similar but weaker pattern was detected in the arid Karoo Biomes. In mobile organisms such as birds, behavioral constraints on dispersal appear strong enough to influence species distributions thousands of years after historical range contractions.

Avian Conservation Areas as a Proxy for Contaminated Soil Remediation

Remediation prioritization frequently falls short of systematically evaluating the underlying ecological value of different sites. This study presents a novel approach to delineating sites that are both contaminated by any of eight heavy metals and have high habitat value to high-priority species. The conservation priority of each planning site herein was based on the projected distributions of eight protected bird species, simulated using 900 outputs of species distribution models (SDMs) and the subsequent application of a systematic conservation tool. The distributions of heavy metal concentrations were generated using a geostatistical joint-simulation approach. The uncertainties in the heavy metal distributions were quantified in terms of variability among 1000 realization sets. Finally, a novel remediation decision-making approach was presented for delineating contaminated sites in need of remediation based on the spatial uncertainties of multiple realizations and the priorities of conservation areas. The results thus obtained demonstrate that up to 42% of areas of high conservation priority are also contaminated by one or more of the heavy metal contaminants of interest. Moreover, as the proportion of the land for proposed remediated increased, the projected area of the pollution-free habitat also increased. Overall uncertainty, in terms of the false positive contamination rate, also increased. These results indicate that the proposed decision-making approach successfully accounted for the intrinsic trade-offs among a high number of pollution-free habitats, low false positive rates and robustness of expected decision outcomes.