EcoNicheS: enhancing ecological niche modeling, niche overlap and connectivity analysis using the shiny dashboard and R package

EcoNicheS (https://github.com/armandosunny/EcoNicheS) is a comprehensive R package built on a Shiny dashboard that offers an intuitive and streamlined workflow for creating ecological niche models (ENMs) and landscape connectivity models. It incorporates tools for niche modeling, overlap analysis, and connectivity modeling, leveraging robust algorithms from the biomod2 suite. EcoNicheS is designed to simplify the technical complexities of ENMs, bridging the gap between advanced modeling techniques and user accessibility. The package offers an interactive interface for streamlined data input, model parameterization, and result visualization. Its comprehensive toolset includes occurrence data processing, pseudoabsence point generation, urbanization filters, and ecological connectivity modeling, distinguishing it from other platforms. EcoNicheS integrates innovative workflows with dynamic output visualizations while emphasizing reproducibility and comparability across statistical methods. Its practical applications span diverse research fields, including biogeography, epidemiology, evolutionary studies, climate change impacts, landscape connectivity, and biodiversity conservation. This versatility makes EcoNicheS a valuable resource for advancing in ecological and conservation science.

Predicting the invasiveness of alpine newts in the UK

Predicting invasion risk to novel environments is essential for risk management and conservation decision making but the evolutionary lineage at which to make these predictions is often unclear. Here we predict the current suitability across the United Kingdom (UK) for the alpine newt Ichthyosaura alpestris, a species with a complex evolutionary history, a broad native range, a growing number of introduced populations and anecdotal reports of ecological consequences to native amphibian communities. We use species distribution and ecological niche modelling to predict environmental suitability of the alpine newt in the UK at both the species-level and lineage-level and to quantify evolutionary lineage niche overlap. We show good model transferability at the species-level and parts of the UK-especially central and eastern England and parts of central and northern Scotland-to be highly environmentally suitable for the alpine newt. Our findings provide evidence of environmental niche differences at the lineage-level, with the Greek lineage being distinct from most other lineages, but with low confidence in maxent predictions for the Greek, Balkan and Italian lineages due to high levels of extrapolation. In contrast, the niche of the UK records appear to share the same niche as the Central lineage. We find 66% of currently known alpine newt records to fall within areas predicted to be environmentally suitable at the species-level, providing a series of testable hypotheses to better understand the invasion ecology of this species in the UK.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10530-025-03543-2.

Assessment of climate change impact on landscape tree distribution and sustainability in South Korea using MaxEnt-based modeling

The rapidly changing climate is impacting species globally at an unprecedented rate, including humans. Consequently, extensive research is being conducted on the impacts of climate change on indigenous and vulnerable species. However, landscape trees, which are cultivated and managed by humans, receive less attention despite their significant role in urban environments. Landscape tree also have specific climatic ranges and environmental requirements, making them susceptible to climate change. In this study, we predicted the future sustainability of three native landscape trees (Stewartia koreana, Betula ermanii, and Taxus cuspidata) using maximum entropy (MaxEnt) models under SSP2-4.5 and SSP5-8.5 climate scenarios. A time-series analysis of suitability was conducted, and the resulting maps were overlaid to classify regions of suitability. The findings indicate a general northward shift in climate suitability and a potential reduction in long-term suitable areas for all three species. Under the SSP2-4.5 scenario, potential suitable area for S. koreana increased, while those for B. ermanii, T. cuspidata decreased by the 2090s. Under the SSP5-8.5 scenario, suitable areas for S. koreana, B. ermanii, T. cuspidata decreased by 33.6%, 98.9%, and 90.1%, respectively. The climate suitability classification ("Sustainable suitability", "Risk", "Inflow", "Lost", and "Variable" regions) effectively identified areas of sustainability and risk, as well as regions requiring management. A notable decline in "Sustainable suitability" regions, which remained suitable from the present to the 2090s, was observed under the SSP5-8.5 scenario relative to SSP2-4.5. The methods utilized in this study offer valuable insights for future landscape planning and conservation. This research underscores the need for adaptive strategies to mitigate potential economic and ecological impacts of climate change by utilizing species distribution models for sustainable landscape planning and tree conservation.

Climate change impacts on worldwide ecological niche and invasive potential of Sternochetus mangiferae

BACKGROUND

Present climate studies on invasive species imply that climate change will alter the habitat suitability of invasive pests, especially given the projected rise in average global temperatures by the end of 2100. However, globally, limited information exists on the habitat suitability of the mango stone weevil, Sternochetus mangiferae Fabricius, which impedes the development of early detection and preventive measures. Herein, we used the MaxEnt model to estimate the potential global geographical distribution of S. mangiferae.

RESULTS

Our results revealed that thermal conditions played a significant role in explaining the invasion risk of S. mangiferae. Habitat suitability was found in all continents, except Antarctica. Under the present condition, habitat suitability covered 5.67 × 107 km2. For ssp126, habitat suitability will decrease from the 2060s (5.58 × 107 km2) and 2080s (5.57 × 107 km2). Similarly, under ssp585, suitable areas will decrease from 5.62 × 107 to 5.51 × 107 km2 for the 2060s and 2080s, respectively.

CONCLUSION

Our study has estimated variability in the habitat suitability of S. mangiferae which establishes a foundation for determining global risk assessment and response plans for the pest. This study also identifies areas where the pest is inherently more vulnerable to the impacts of changing climates and enables forecasting of its potential distribution in a dynamic world. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Variable impacts of land-based climate mitigation on habitat area for vertebrate diversity

Pathways to achieving net zero carbon emissions commonly involve deploying reforestation, afforestation, and bioenergy crops across millions of hectares of land. It is often assumed that by helping to mitigate climate change, these strategies indirectly benefit biodiversity. Here, we modeled the climate and habitat requirements of 14,234 vertebrate species and show that the impact of these strategies on species' habitat area tends not to arise through climate mitigation, but rather through habitat conversion. Across locations, reforestation tends to provide species more habitat through both land-cover change and climate mitigation, whereas habitat loss from afforestation and bioenergy cropping typically outweighs the climate mitigation benefits. This work shows how and where land-based mitigation strategies can be deployed without inadvertently reducing the area of habitat for global biodiversity.

Conservation challenges for Brazilian primates and the role of protected areas in a changing climate

The negative effects of land-use changes on biodiversity significantly contribute to climate change. Primates are among the animals most affected by these changes, because of their high dependence on forest cover where a lack of forest connectivity can limit their dispersal and segregate their populations. In this sense, protected areas (PAs) are crucial for conserving endangered primates, especially endemic species. Using species distribution models, we assessed the impact of climate change and deforestation on the geographic distribution of 35 endangered Brazilian primates. We also evaluated the potential of PAs to retain suitable habitats for primate species under current conditions (baseline) and four future climate scenarios (optimistic and pessimistic, both for the periods 2041-2060 and 2061-2080), as well as the capacity of PAs to preserve species' geographic representation both now and in the future. Our findings indicate that most primate taxa would experience a significant loss of suitable area (> 90%) in both pessimistic and optimistic scenarios. For future scenarios, the loss could exceed 98% for 10 taxa, particularly Amazonian species. Regarding PAs potential to retain suitable areas for maintaining the richness of threatened primates, only 8.6% harbor more species than expected by chance (1-6 taxa) in the baseline conditions, with a decrease in future scenarios. Results suggest that taxa already threatened with extinction are inadequately protected by PAs in the baseline conditions and even less so in future scenarios. Given the restricted geographic distribution and current population decline for most taxa, we emphasize the need to increase the number of PAs to ensure population viability and prevent future extinction.

Impacts of Climate Change Conditions on the Potential Distribution of Anoplophora glabripennis and Its Host Plants, Salix babylonica and Salix matsudana, in China

The Anoplophora glabripennis (Motschulsky) is a phytophagous pest that is seriously endangering Salix babylonica Linn. and S. matsudana Koidz. Poor control can damage local ecosystems, resulting in economic losses and management risks. In the context of climate change, the climatic ecological niche of organisms is no longer compatible with the surrounding environment. To mitigate the effects of climate change, some organisms respond adaptively to climate change through different mechanisms and in different ways. In this study, an optimized MaxEnt model was used to explore the potential distribution areas of A. glabripennis and its host plants, S. babylonica and S. matsudana, in response to current and future climate and to determine their movement routes and relative dynamics. The results show that the optimized model exhibits the lowest complexity and excellent prediction accuracy. It is important to note that both temperature and precipitation are the main environmental factors affecting the distribution of suitable habitats for A. glabripennis and its host plants. This is evidenced by the mean temperature of the warmest quarter and precipitation of the wettest month being the main environmental factors affecting the distribution of suitable habitats for the host plants. Similarly, the minimum temperature of the coldest month and precipitation seasonality are the primary bioclimatic variables constraining the dispersal of A. glabripennis. Under climate change, the suitable areas of both S. babylonica and S. matsudana are declining, while the suitable areas of A. glabripennis are expanding in future climates. Furthermore, three species exhibited a proclivity for migration to higher latitudes in response to climate change. In conclusion, this study contributes to our understanding of the biogeographic characteristics of these A. glabripennis, S. babylonica, and S. matsudana and provides a basis for the formulation of timely conservation strategies to reduce the potential impacts of climate change. This is of great significance for the rational management, utilization, and protection of forest ecosystems in China.

Ship collision risk threatens whales across the world's oceans

After the near-complete cessation of commercial whaling, ship collisions have emerged as a primary threat to large whales, but knowledge of collision risk is lacking across most of the world's oceans. We compiled a dataset of 435,000 whale locations to generate global distribution models for four globally ranging species. We then combined >35 billion positions from 176,000 ships to produce a global estimate of whale-ship collision risk. Shipping occurs across 92% of whale ranges, and <7% of risk hotspots contain management strategies to reduce collisions. Full coverage of hotspots could be achieved by expanding management over only 2.6% of the ocean's surface. These inferences support the continued recovery of large whales against the backdrop of a rapidly growing shipping industry.

Predicting the Impact of Climate Change on Corylus Species Distribution in China: Integrating Climatic, Topographic, and Anthropogenic Factors

This study investigates the impact of climate change on the distribution of Corylus species in China using the MaxEnt model. Key environmental variables, such as Bio6 (mean temperature of the coldest month) and human footprint, emerged as significant determinants of habitat suitability. The study reveals substantial shifts in suitable habitats due to global warming and increased precipitation, with notable expansion towards higher latitudes. Species like Corylus heterophylla Fisch. ex Bess. and Corylus mandshurica Maxim. demonstrate resilience in extreme conditions, highlighting the importance of specific ecological traits for conservation. Future projections under various SSP scenarios predict continued habitat expansion, emphasizing the need for targeted conservation strategies to address the critical role of human activities. This research highlights the complex interplay between climatic, topographic, and anthropogenic factors in shaping Corylus habitats, advocating for integrated adaptive management approaches to ensure their sustainability amid ongoing climate change.

Predictions of species distributions based only on models estimating future climate change are not reliable

Changes in climate and land use are the most often mentioned factors responsible for the current decline in species diversity. To reduce the effect of these factors, we need reliable predictions of future species distributions. This is usually done by utilizing species distribution models (SDMs) based on expected climate. Here we explore the accuracy of such projections: we use orchid (Orchidaceae) recordings and environmental (mainly climatic) data from the years 1901-1950 in SDMs to predict maps of potential species distributions in 1980-2014. This should enable us to compare the predictions of species distributions in 1980-2014, based on records of species distribution in the years 1901-1950, with real data in the 1980-2014 period. We found that the predictions of the SDMs often differ from reality in this experiment. The results clearly indicate that SDM predictions of future species distributions as a reaction to climate change must be treated with caution.

Modeling the Current and Future Distribution of Indianthus virgatus (Roxb.) Suksathan & Borchs.: A Monotypic Plant Endemic to the Western Ghats-Sri Lanka Biodiversity Hotspot

Species distribution modeling (SDM) is an essential tool in ecology and conservation for predicting species distributions based on species presence/absence data and environmental variables. The present study aimed to understand the distribution pattern and habitat suitability of Indianthus virgatus under current and future climate change scenarios (2050 and 2070) using MaxEnt (3.4.4) and Wallace Ecological Modeling (v2.1.2) tools. The study also intended to identify key environmental predictors of I. virgatus' distribution. Species occurrence data were collected from various sources, including herbarium (online and physical), field surveys, and online databases, yielding 105 unique locations in the Western Ghats (WG) of India and Sri Lanka. We used 19 bioclimatic variables and elevation data sourced from WorldClim for modeling. The MaxEnt and Wallace models showed excellent performance in predicting the distribution of I. virgatus, with area under the curve values of 0.958 (± 0.002) and 0.93, respectively. In MaxEnt modeling, Temperature Seasonality (bio4) was the most significant environmental parameter, followed by the Precipitation of the Coldest Quarter (bio19). In contrast, the Annual Mean Temperature (bio1), Temperature Seasonality (bio4), and Annual Precipitation (bio12) were among the key contributors in Wallace EcoMod. Both the models predicted relatively lesser areas in the species' distribution range as highly suitable habitats (HSH) in India and Sri Lanka. We found divergent trends in predicting I. virgatus distributions using MaxEnt and Wallace EcoMod, particularly for future projections. Nevertheless, both models predicted significant habitat loss under future climate change scenarios, especially under RCP85, with varying degrees of suitability across India and Sri Lanka. Overall, our findings on expected habitat loss under future climate change scenarios highlight the importance of conserving I. virgatus, which has already been declared critically endangered (CR) in Sri Lanka.

Spatial match-mismatch between predators and prey under climate change

Climate change is driving a rapid redistribution of life on Earth. Variability in the rates, magnitudes and directions of species' shifts can alter spatial overlap between predators and prey, with the potential to decouple trophic interactions. Although phenological mismatches between predator requirements and prey availability under climate change are well-established, 'spatial match-mismatch' dynamics remain poorly understood. We synthesize global evidence for climate-driven changes in spatial predator-prey overlap resulting from species redistribution across marine and terrestrial domains. We show that spatial mismatches can have vastly different outcomes for predator populations depending on their diet specialization and role within the wider ecosystem. We illustrate ecosystem-level consequences of climate-driven changes in spatial predator-prey overlap, from restructuring food webs to altering socio-ecological interactions. It remains unclear how predator-prey overlap at the landscape scale relates to prey encounter and consumption rates at local scales, or how the spatial reorganization of food webs affects ecosystem function. We identify key research directions necessary to resolve the scale of ecological impacts caused by species redistribution under climate change.

The role of species interactions in shaping the geographic pattern of ungulate abundance across African savannah

Macroecologists traditionally emphasized the role of environmental variables for predicting species distribution and abundance at large scale. While biotic factors have been increasingly recognized as important at macroecological scales, producing valuable biotic variables remains challenging and rarely tested. Capitalizing on the wealth of population density estimates available for African savannah ungulates, here we modeled species average population density at 100 × 100 km as a function of both environmental variables and proxies of biotic interactions (competition and predation) and estimated their relative contribution. We fitted a linear mixed effect model on 1043 population density estimates for 63 species of ungulates using Bayesian inference and estimated the percentage of total variance explained by environmental, anthropogenic, and biotic interactions variables. Environmental and anthropogenic variables were the main drivers of ungulate population density, with NDVI, Distance to permanent water bodies and Human population density showing the highest contribution to the variance. Nonetheless, biotic interactions altogether contributed to a quarter of the variance explained, with predation and competition having a negative effect on species density. Despite the limitations of modelling biotic interactions in macroecological studies, proxies of biotic interactions can enhance our understanding of biological patterns at broad spatial scales, uncovering novel predictors as well as enhancing the predictive power of large-scale models.

Unveiling the urban colonization of the Asian water monitor (Varanus salvator) across its distribution range using citizen science

Background

This study aims to investigate the urban colonization of the Asian water monitor (Varanus salvator) across its entire range of distribution, addressing the paucity of research on this species in urban ecosystems. The research spans the geographic range of the Asian water monitor, focusing on urbanized areas where the species accumulates more observations (Bangkok, Colombo, Jakarta, Kuala Lumpur and Singapore).

Methods

We conducted a systematic review to comprehensively assess the current knowledge of the species' presence in cities. Additionally, citizen science data from repositories like GBIF (Global Biodiversity Information facility ) were utilized to analyze the distribution patterns of V. salvator in urban environments. To elucidate urban distribution and correct collection biases, observations were weighted by sampling effort, using as a proxy all squamate occurrences available from 2010-2023, including V. salvator.

Results

Despite the widespread presence of the Asian water monitor in numerous cities within its distribution range, the available studies on the topic appear to be scarce. Existing research primarily consists of descriptive reports on diet and behavior. Our findings indicate that V. salvator predominantly colonizes green patches in urban areas, such as parks and small gardens. Larger cities exhibit higher records, potentially due to both permanent populations and increased citizen science reporting.

Conclusions

The Asian water monitor, as the largest lizard with established populations in cities, remains scarcely studied on a broader scale. However, the urban design of each city seems relevant to understand the distribution patterns within each context. Our study highlights the need for further research to explore the ecological and human dimensions associated with the species' presence in urban environments.

The importance of geography in forecasting future fire patterns under climate change

An increasing amount of California's landscape has burned in wildfires in recent decades, in conjunction with increasing temperatures and vapor pressure deficit due to climate change. As the wildland-urban interface expands, more people are exposed to and harmed by these extensive wildfires, which are also eroding the resilience of terrestrial ecosystems. With future wildfire activity expected to increase, there is an urgent demand for solutions that sustain healthy ecosystems and wildfire-resilient human communities. Those who manage disaster response, landscapes, and biodiversity rely on mapped projections of how fire activity may respond to climate change and other human factors. California wildfire is complex, however, and climate-fire relationships vary across the state. Given known geographical variability in drivers of fire activity, we asked whether the geographical extent of fire models used to create these projections may alter the interpretation of predictions. We compared models of fire occurrence spanning the entire state of California to models developed for individual ecoregions and then projected end-of-century future fire patterns under climate change scenarios. We trained a Maximum Entropy model with fire records and hydroclimatological variables from recent decades (1981 to 2010) as well as topographic and human infrastructure predictors. Results showed substantial variation in predictors of fire probability and mapped future projections of fire depending upon geographical extents of model boundaries. Only the ecoregion models, accounting for the unique patterns of vegetation, climate, and human infrastructure, projected an increase in fire in most forested regions of the state, congruent with predictions from other studies.

Modeling the current and future habitat suitability of Neltuma pallida in the dry forest of northern Peru under climate change scenarios to 2100

The development of anthropic activities and climate change effects impact worldwide species' ecosystems and habitats. Habitats' adequate prediction can be an important tool to assess current and future trends. In addition, it allows strategies development for their conservation. The Neltuma pallida of the forest region in northern Peru, although very significant, has experienced a decline in recent years. The objective of this research is to evaluate the current and future distribution and conservation status of N. pallida in the Peruvian dry forest under climate change (Location: Republic of Peru). A total of 132 forest presence records and 10 variables (bioclimatic, topographic, and soil) were processed and selected to obtain the current and future distribution for 2100, using Google Earth Engine (GEE), RStudio, and MaxEnt. The area under the curve values fell within the range of 0.93-0.95, demonstrating a strong predictive capability for both present and future potential habitats. The findings indicated that the likely range of habitats for N. pallida was shaped by factors such as the average temperature of wettest quarter, maximum temperature of warmest month, elevation, rainfall, and precipitation of driest month. The main suitable areas were in the central regions of the geographical departments of Tumbes, Piura, and Lambayeque, as well as in the northern part of La Libertad. It is critical to determine the habitat suitability of plant species for conservation managers since this information stimulates the development of policies that favor sustainable use programs. In addition, these results can contribute significantly to identify new areas for designing strategies for populations conserving and recovering with an ecological restoration approach.

Boosting biodiversity monitoring using smartphone-driven, rapidly accumulating community-sourced data

Comprehensive biodiversity data is crucial for ecosystem protection. The Biome mobile app, launched in Japan, efficiently gathers species observations from the public using species identification algorithms and gamification elements. The app has amassed >6 million observations since 2019. Nonetheless, community-sourced data may exhibit spatial and taxonomic biases. Species distribution models (SDMs) estimate species distribution while accommodating such bias. Here, we investigated the quality of Biome data and its impact on SDM performance. Species identification accuracy exceeds 95% for birds, reptiles, mammals, and amphibians, but seed plants, molluscs, and fishes scored below 90%. Our SDMs for 132 terrestrial plants and animals across Japan revealed that incorporating Biome data into traditional survey data improved accuracy. For endangered species, traditional survey data required >2000 records for accurate models (Boyce index ≥ 0.9), while blending the two data sources reduced this to around 300. The uniform coverage of urban-natural gradients by Biome data, compared to traditional data biased towards natural areas, may explain this improvement. Combining multiple data sources better estimates species distributions, aiding in protected area designation and ecosystem service assessment. Establishing a platform for accumulating community-sourced distribution data will contribute to conserving and monitoring natural ecosystems.

Risk of spread of the Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) in Ghana

The impact of invasive species on biodiversity, food security and economy is increasingly noticeable in various regions of the globe as a consequence of climate change. Yet, there is limited research on how climate change affects the distribution of the invasive Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera:Liviidae) in Ghana. Using maxnet package to fit the Maxent model in R software, we answered the following questions; (i) what are the main drivers for D. citri distribution, (ii) what are the D. citri-specific habitat requirements and (iii) how well do the risk maps fit with what we know to be correctly based on the available evidence?. We found that temperature seasonality (Bio04), mean temperature of warmest quarter (Bio10), precipitation of driest quarter (Bio17), moderate resolution imaging spectroradiometer land cover and precipitation seasonality (Bio15), were the most important drivers of D. citri distribution. The results follow the known distribution records of the pest with potential expansion of habitat suitability in the future. Because many invasive species, including D. citri, can adapt to the changing climates, our findings can serve as a guide for surveillance, tracking and prevention of D. citri spread in Ghana.

A standard approach for including climate change responses in IUCN Red List assessments

The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red-list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red-list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments.

Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area

Correlative species distribution models (SDMs) are important tools to estimate species' geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species' physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models' sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-024-00226-0.

Rising Temperatures, Falling Leaves: Predicting the Fate of Cyprus's Endemic Oak under Climate and Land Use Change

Endemic island species face heightened extinction risk from climate-driven shifts, yet standard models often underestimate threat levels for those like Quercus alnifolia, an iconic Cypriot oak with pre-adaptations to aridity. Through species distribution modelling, we investigated the potential shifts in its distribution under future climate and land-use change scenarios. Our approach uniquely combines dispersal constraints, detailed soil characteristics, hydrological factors, and anticipated soil erosion data, offering a comprehensive assessment of environmental suitability. We quantified the species' sensitivity, exposure, and vulnerability to projected changes, conducting a preliminary IUCN extinction risk assessment according to Criteria A and B. Our projections uniformly predict range reductions, with a median decrease of 67.8% by the 2070s under the most extreme scenarios. Additionally, our research indicates Quercus alnifolia's resilience to diverse erosion conditions and preference for relatively dry climates within a specific annual temperature range. The preliminary IUCN risk assessment designates Quercus alnifolia as Critically Endangered in the future, highlighting the need for focused conservation efforts. Climate and land-use changes are critical threats to the species' survival, emphasising the importance of comprehensive modelling techniques and the urgent requirement for dedicated conservation measures to safeguard this iconic species.

Incorporating eco-evolutionary information into species distribution models provides comprehensive predictions of species range shifts under climate change

As climate changes increasingly influence species distributions, ecosystem functions, and biodiversity, the urgency to understand how species' ranges shift under those changes is great. Species distribution models (SDMs) are vital approaches that can predict species distributions under changing climates. However, SDMs based on the species' current occurrences may underestimate the species' climatic tolerances. Integrating species' realized niches at different periods, also known as multi-temporal calibration, can provide an estimation closer to its fundamental niche. Based on this, we further proposed an integrated framework that combines eco-evolutionary data and SDMs (phylogenetically-informed SDMs) to provide comprehensive predictions of species range shifts under climate change. To evaluate our approach's performance, we applied it to a group of related species, the Chrysanthemum zawadskii species complex (Anthemidae, Asteracee). First, we investigated the niche differentiation between species and intraspecific lineages of the complex and estimated their rates of niche evolution. Next, using both standard SDMs and our phylogenetically-informed SDMs, we generated predictions of suitability areas for all species and lineages and compared the results. Finally, we reconstructed the historical range dynamics for the species of this complex. Our results showed that the species and intraspecific lineages of the complex had varying degrees of niche differentiation and different rates of niche evolution. Lineage-level SDMs can provide more realistic predictions for species with intraspecific differentiation than species-level models can. The phylogenetically-informed SDMs provided more complete environmental envelopes and predicted broader potential distributions for all species than the standard SDMs did. Range dynamics varied among the species that have different rates of niche evolution. Our framework integrating eco-evolutionary data and SDMs contributes to a better understanding of the species' responses to climate change and can help to make more targeted conservation efforts for the target species under climate change, particularly for rare species.

Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

TreeGOER: A database with globally observed environmental ranges for 48,129 tree species

The TreeGOER (Tree Globally Observed Environmental Ranges) database provides information for most known tree species of their environmental ranges for 38 bioclimatic, eight soil and three topographic variables. It is based on species distribution modelling analyses of more than 44 million occurrences. The database can be accessed from https://doi.org/10.5281/zenodo.7922927. Statistics that include 5% and 95% quantiles were estimated for a cleaned and taxonomically standardized occurrence data set with different methods of outlier detection, with estimates for roughly 45% of species being based on 20 or more observation records. Where sufficient representative observations are available, the ranges provide useful preliminary estimates of suitable conditions particularly for lesser-known species under climate change. Inferred core bioclimatic ranges of species along global temperature and moisture index gradients and across continents follow the known global distribution of tree diversity such as its highest levels in moist tropical forests and the 'odd man out' pattern of lower levels in Africa. To demonstrate how global analyses for large numbers of tree species can easily be done in R with TreeGOER, here I present two case studies. The first case study investigated latitudinal trends of tree vulnerability and compared these with previous results obtained for urban trees. The second case study focused on tropical areas, compared trends in different longitudinal zones and investigated patterns for the moisture index. TreeGOER is expected to benefit researchers conducting biogeographical and climate change research for a wide range of tree species at a variety of spatial and temporal scales.

Predicting the distribution of Ixodes ricinus and Dermacentor reticulatus in Europe: a comparison of climate niche modelling approaches

BACKGROUND

The ticks Ixodes ricinus and Dermacentor reticulatus are two of the most important vectors in Europe. Climate niche modelling has been used in many studies to attempt to explain their distribution and to predict changes under a range of climate change scenarios. The aim of this study was to assess the ability of different climate niche modelling approaches to explain the known distribution of I. ricinus and D. reticulatus in Europe.

METHODS

A series of climate niche models, using different combinations of input data, were constructed and assessed. Species occurrence records obtained from systematic literature searches and Global Biodiversity Information Facility data were thinned to different degrees to remove sampling spatial bias. Four sources of climate data were used: bioclimatic variables, WorldClim, TerraClimate and MODIS satellite-derived data. Eight different model training extents were examined and three modelling frameworks were used: maximum entropy, generalised additive models and random forest models. The results were validated through internal cross-validation, comparison with an external independent dataset and expert opinion.

RESULTS

The performance metrics and predictive ability of the different modelling approaches varied significantly within and between each species. Different combinations were better able to define the distribution of each of the two species. However, no single approach was considered fully able to capture the known distribution of the species. When considering the mean of the performance metrics of internal and external validation, 24 models for I. ricinus and 11 models for D. reticulatus of the 96 constructed were considered adequate according to the following criteria: area under the receiver-operating characteristic curve > 0.7; true skill statistic > 0.4; Miller's calibration slope 0.25 above or below 1; Boyce index > 0.9; omission rate < 0.15.

CONCLUSIONS

This comprehensive analysis suggests that there is no single 'best practice' climate modelling approach to account for the distribution of these tick species. This has important implications for attempts to predict climate-mediated impacts on future tick distribution. It is suggested here that climate variables alone are not sufficient; habitat type, host availability and anthropogenic impacts, not included in current modelling approaches, could contribute to determining tick presence or absence at the local or regional scale.

Biophysical models accurately characterize the thermal energetics of a small invasive passerine bird

Effective management of invasive species requires accurate predictions of their invasion potential in different environments. By considering species' physiological tolerances and requirements, biophysical mechanistic models can potentially deliver accurate predictions of where introduced species are likely to establish. Here, we evaluate biophysical model predictions of energy use by comparing them to experimentally obtained energy expenditure (EE) and thermoneutral zones (TNZs) for the common waxbill Estrilda astrild, a small-bodied avian invader. We show that biophysical models accurately predict TNZ and EE and that they perform better than traditional time-energy budget methods. Sensitivity analyses indicate that body temperature, metabolic rate, and feather characteristics were the most influential traits affecting model accuracy. This evaluation of common waxbill energetics represents a crucial step toward improved parameterization of biophysical models, eventually enabling accurate predictions of invasion risk for small (sub)tropical passerines.

Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution of alien species. Since citizen science presence-only data suffer from some fundamental issues, efforts have been made to combine these data with those provided by scientifically structured surveys. Surprisingly, only a few studies proposing data integration evaluated the contribution of this process to the effective sampling of species' environmental niches and, consequently, its effect on model predictions on new time intervals. We relied on niche overlap analyses, machine learning classification algorithms and ecological niche models to compare the ability of data from citizen science and scientific surveys, along with their integration, in capturing the realized niche of 13 invasive alien species in Italy. Moreover, we assessed differences in current and future invasion risk predicted by each data set under multiple global change scenarios. We showed that data from citizen science and scientific surveys captured similar species niches though highlighting exclusive portions associated with clearly identifiable environmental conditions. In terrestrial species, citizen science data granted the highest gain in environmental space to the pooled niches, determining an increased future biological invasion risk. A few aquatic species modelled at the regional scale reported a net loss in the pooled niches compared to their scientific survey niches, suggesting that citizen science data may also lead to contraction in pooled niches. For these species, models predicted a lower future biological invasion risk. These findings indicate that citizen science data may represent a valuable contribution to predicting future spread of invasive alien species, especially within national-scale programmes. At the same time, citizen science data collected on species poorly known to citizen scientists, or in strictly local contexts, may strongly affect the niche quantification of these taxa and the prediction of their future biological invasion risk.

Climate change and carnivores: shifts in the distribution and effectiveness of protected areas in the Amazon

Background

Carnivore mammals are animals vulnerable to human interference, such as climate change and deforestation. Their distribution and persistence are affected by such impacts, mainly in tropical regions such as the Amazon. Due to the importance of carnivores in the maintenance and functioning of the ecosystem, they are extremely important animals for conservation. We evaluated the impact of climate change on the geographic distribution of carnivores in the Amazon using Species Distribution Models (SDMs). Do we seek to answer the following questions: (1) What is the effect of climate change on the distribution of carnivores in the Amazon? (2) Will carnivore species lose or gain representation within the Protected Areas (PAs) of the Amazon in the future?

Methods

We evaluated the distribution area of 16 species of carnivores mammals in the Amazon, based on two future climate scenarios (RCP 4.5 and RCP 8.5) for the year 2070. For the construction of the SDMs we used bioclimatic and vegetation cover variables (land type). Based on these models, we calculated the area loss and climate suitability of the species, as well as the effectiveness of the protected areas inserted in the Amazon. We estimated the effectiveness of PAs on the individual persistence of carnivores in the future, for this, we used the SDMs to perform the gap analysis. Finally, we analyze the effectiveness of PAs in protecting taxonomic richness in future scenarios.

Results

The SDMs showed satisfactory predictive performance, with Jaccard values above 0.85 and AUC above 0.91 for all species. In the present and for the future climate scenarios, we observe a reduction of potencial distribution in both future scenarios (RCP4.5 and RCP8.5), where five species will be negatively affected by climate change in the RCP 4.5 future scenario and eight in the RCP 8.5 scenario. The remaining species stay stable in terms of total area. All species in the study showed a loss of climatic suitability. Some species lost almost all climatic suitability in the RCP 8.5 scenario. According to the GAP analysis, all species are protected within the PAs both in the current scenario and in both future climate scenarios. From the null models, we found that in all climate scenarios, the PAs are not efficient in protecting species richness.

The earliest Ethiopian wolf: implications for the species evolution and its future survival

In 2017, a hemimandible (MW5-B208), corresponding to the Ethiopian wolf (Canis simensis), was found in a stratigraphically-controlled and radio-isotopically-dated sequence of the Melka Wakena paleoanthropological site-complex, on the Southeastern Ethiopian Highlands, ~ 2300 m above sea level. The specimen is the first and unique Pleistocene fossil of this species. Our data provide an unambiguous minimum age of 1.6-1.4 Ma for the species' presence in Africa and constitutes the first empirical evidence that supports molecular interpretations. Currently, C. simensis is one of the most endangered carnivore species of Africa. Bioclimate niche modeling applied to the time frame indicated by the fossil suggests that the lineage of the Ethiopian wolf faced severe survival challenges in the past, with consecutive drastic geographic range contractions during warmer periods. These models help to describe future scenarios for the survival of the species. Projections ranging from most pessimistic to most optimistic future climatic scenarios indicate significant reduction of the already-deteriorating territories suitable for the Ethiopian Wolf, increasing the threat to the specie's future survival. Additionally, the recovery of the Melka Wakena fossil underscores the importance of work outside the East African Rift System in research of early human origins and associated biodiversity on the African continent.

A quixotic view of spatial bias in modelling the distribution of species and their diversity

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

Combining environmental niche models, multi-grain analyses, and species traits identifies pervasive effects of land use on butterfly biodiversity across Italy

Understanding how species respond to human activities is paramount to ecology and conservation science, one outstanding question being how large-scale patterns in land use affect biodiversity. To facilitate answering this question, we propose a novel analytical framework that combines environmental niche models, multi-grain analyses, and species traits. We illustrate the framework capitalizing on the most extensive dataset compiled to date for the butterflies of Italy (106,514 observations for 288 species), assessing how agriculture and urbanization have affected biodiversity of these taxa from landscape to regional scales (3-48 km grains) across the country while accounting for its steep climatic gradients. Multiple lines of evidence suggest pervasive and scale-dependent effects of land use on butterflies in Italy. While land use explained patterns in species richness primarily at grains ≤12 km, idiosyncratic responses in species highlighted "winners" and "losers" across human-dominated regions. Detrimental effects of agriculture and urbanization emerged from landscape (3-km grain) to regional (48-km grain) scales, disproportionally affecting small butterflies and butterflies with a short flight curve. Human activities have therefore reorganized the biogeography of Italian butterflies, filtering out species with poor dispersal capacity and narrow niche breadth not only from local assemblages, but also from regional species pools. These results suggest that global conservation efforts neglecting large-scale patterns in land use risk falling short of their goals, even for taxa typically assumed to persist in small natural areas (e.g., invertebrates). Our study also confirms that consideration of spatial scales will be crucial to implementing effective conservation actions in the Post-2020 Global Biodiversity Framework. In this context, applications of the proposed analytical framework have broad potential to identify which mechanisms underlie biodiversity change at different spatial scales.

Present and future distribution of Faidherbia albida in Cabo Verde as revealed by climatic modelling and LULC analysis

Climate change poses one of the most significant challenges to conserve biodiversity, especially in tropical dry islands, as is the case of Cabo Verde (northeast Atlantic Ocean). This archipelago has a low percentage of forest cover and hosts only seven native tree species, among them, Faidherbia albida (Delile) A.Chev. (Fabaceae). Therefore, protective afforestation is extremely important in Cabo Verde, one of the most vulnerable West African countries to climate change. With this work, we aimed to estimate the current distribution and potential shifts in suitable areas for F. albida under climate change, using species distribution models (i.e., random forest, generalized linear and additive models), covering its distribution range in Cabo Verde and mainland Africa. The best model was then projected for the studied area, at two different slice times, using Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. Based on current bioclimatic variables, we estimated that almost two thirds of Cabo Verde’s territory is highly suitable for F. albida, which contrasts with its current occurrence. By overlaying the present habitat suitability with land use and land cover data, we concluded that habitat availability and suitability could be constrained by that factor. On average, the predicted suitable habitat for future distributions gradually decreases by 2080 under both scenarios compared with the current, with a smaller effect of RCP4.5 than of RCP8.5. Local authorities can benefit from this research and develop actions to promote sustainable reforestation in Cabo Verde, which should include native tree species that are best adapted to the local climate and could thus contribute to mitigate the effects of climate change.

Projected Shifts in Bird Distribution in India under Climate Change

Global climate change is causing unprecedented impacts on biodiversity. In India, there is little information available regarding how climate change affects biodiversity at the taxon/group level, and large-scale ecological analyses have been lacking. In this study, we demonstrated the applicability of eBird and GBIF (Global Biodiversity Information Facility), and produced national-scale forecasts to examine the possible impacts of climate change on terrestrial avifauna in India. Using data collected by citizen scientists, we developed fine-tuned Species Distribution Models (SDMs) and predicted 1091 terrestrial bird species that would be distributed in India by 2070 on two climatic surfaces (RCP 4.5 and 8.5), using Maximum Entropy-based species distribution algorithms. Of the 1091 species modelled, our findings indicate that 66–73% of bird species in India will shift to higher elevations or shift northward, and 58–59% of bird species (RCP 4.5 and 8.5) would lose a portion of their distribution ranges. Furthermore, distribution ranges of 41–40% of bird species would increase. Under both RCP scenarios (RCP 4.5 and 8.5), bird species diversity will significantly increase in regions above 2500 m in elevation. Both RCP scenarios predict extensive changes in the species richness of the western Himalayas, Sikkim, northeast India, and the western Ghats regions by 2070. This study has resulted in novel, high-resolution maps of terrestrial bird species richness across India, and we predict predominantly northward shifts in species ranges, similar to predictions made for avifauna in other regions, such as Europe and the USA.

Seasonal variation in thermoregulatory capacity of three closely related Afrotropical Estrildid finches introduced to Europe

A species' potential geographical range is largely determined by how the species responds physiologically to its changing environment. It is therefore crucial to study the physiological mechanisms that species use to maintain their homeothermy in order to address biodiversity conservation challenges, such as the success of invasions of introduced species. The common waxbill Estrilda astrild, the orange-cheeked waxbill E. melpoda, and the black-rumped waxbill E. troglodytes are small Afrotropical passerines that have established invasive populations in regions where the climate is colder than in their native ranges. As a result, they are highly suitable species for studying potential mechanisms for coping with a colder and more variable climate. Here, we investigated the magnitude and direction of seasonal variation in their thermoregulatory traits, such as basal (BMR), summit (M_sum) metabolic rates and thermal conductance. We found that, from summer to autumn, their ability to resist colder temperatures increased. This was not related to larger body masses or higher BMR and M_sum, but instead, species downregulated BMR and M_sum toward the colder season, suggesting energy conservation mechanisms to increase winter survival. BMR and M_sum were most strongly correlated with temperature variation in the week preceding the measurements. Common waxbill and black-rumped waxbill, whose native ranges encompass the highest degree of seasonality, showed the most flexibility in metabolic rates (i.e., stronger downregulation toward colder seasons). This ability to adjust thermoregulatory traits, combined with increased cold tolerance, may facilitate their establishment in areas characterized by colder winters and less predictable climates.

Relocation of bioclimatic suitability of Portuguese grapevine varieties under climate change scenarios

Introduction

Climate change has been driving warming trends and changes in precipitation patterns and regimes throughout Europe. Future projections indicate a continuation of these trends in the next decades. This situation is challenging the sustainability of viniculture and, thus, significant efforts towards adaptation should be then carried out by local winegrowers.

Method

Ecological Niche Models were built, using the ensemble modelling approach, to estimate the bioclimatic suitability of four main wine-producing European countries, namely France, Italy, Portugal, and Spain, in the recent past (1989-2005), for the cultivation of twelve Portuguese grape varieties. The models were then used to project the bioclimatic suitability to two future periods (2021- 2050 and 2051-2080) to better understand the potential shifts related to climate change (modeled after Intergovernmental Panel on Climate Change's Representative Concentration Pathways 4.5 and 8.5 scenarios). The models were obtained with the modeling platform BIOMOD2, using four bioclimatic indices, namely the "Huglin Index", the "Cool Night index", the "Growing Season Precipitation index", and the "Temperature Range during Ripening index" as predictor variables, as well as the current locations of the chosen grape varieties in Portugal.

Results

All models performed with high statistical accuracy (AUC > 0.9) and were able to discriminate several suitable bioclimatic areas for the different grape varieties, in and around where they are currently located but also in other parts of the study area. The distribution of the bioclimatic suitability changed, however, when looking at future projections. For both climatic scenarios, projected bioclimatic suitability suffered a considerable shift to the north of Spain and France. In some cases, bioclimatic suitability also moved towards areas of higher elevation. Portugal and Italy barely retained any of the initially projected varietal areas. These shifts were mainly due to the overall rise in thermal accumulation and lower accumulated precipitation in the southern regions projected for the future.

Conclusion

Ensemble models of Ecological Niche Models were shown to be valid tools for winegrowers who want to adapt to a changing climate. The long-term sustainability of viniculture in southern Europe will most likely have to go through a process of mitigation of the effects of increasing temperatures and decreasing precipitation.

Bat responses to climate change: a systematic review

Understanding how species respond to climate change is key to informing vulnerability assessments and designing effective conservation strategies, yet research efforts on wildlife responses to climate change fail to deliver a representative overview due to inherent biases. Bats are a species-rich, globally distributed group of organisms that are thought to be particularly sensitive to the effects of climate change because of their high surface-to-volume ratios and low reproductive rates. We systematically reviewed the literature on bat responses to climate change to provide an overview of the current state of knowledge, identify research gaps and biases and highlight future research needs. We found that studies are geographically biased towards Europe, North America and Australia, and temperate and Mediterranean biomes, thus missing a substantial proportion of bat diversity and thermal responses. Less than half of the published studies provide concrete evidence for bat responses to climate change. For over a third of studied bat species, response evidence is only based on predictive species distribution models. Consequently, the most frequently reported responses involve range shifts (57% of species) and changes in patterns of species diversity (26%). Bats showed a variety of responses, including both positive (e.g. range expansion and population increase) and negative responses (range contraction and population decrease), although responses to extreme events were always negative or neutral. Spatial responses varied in their outcome and across families, with almost all taxonomic groups featuring both range expansions and contractions, while demographic responses were strongly biased towards negative outcomes, particularly among Pteropodidae and Molossidae. The commonly used correlative modelling approaches can be applied to many species, but do not provide mechanistic insight into behavioural, physiological, phenological or genetic responses. There was a paucity of experimental studies (26%), and only a small proportion of the 396 bat species covered in the examined studies were studied using long-term and/or experimental approaches (11%), even though they are more informative about the effects of climate change. We emphasise the need for more empirical studies to unravel the multifaceted nature of bats' responses to climate change and the need for standardised study designs that will enable synthesis and meta-analysis of the literature. Finally, we stress the importance of overcoming geographic and taxonomic disparities through strengthening research capacity in the Global South to provide a more comprehensive view of terrestrial biodiversity responses to climate change.

Effects of climate and land-cover change on the conservation status of gibbons

Species shift their distribution in response to climate and land-cover change, which may result in a spatial mismatch between currently protected areas (PAs) and priority conservation areas (PCAs). We examined the effects of climate and land-cover change on potential range of gibbons and sought to identify PCAs that would conserve them effectively. We collected global gibbon occurrence points and modeled (ecological niche model) their current and potential 2050s ranges under climate-change and different land-cover-change scenarios. We examined change in range and PA coverage between the current and future ranges of each gibbon species. We applied spatial conservation prioritization to identify the top 30% PCAs for each species. We then determined how much of the PCAs are conserved in each country within the global range of gibbons. On average, 31% (SD 22) of each species' current range was covered in PAs. PA coverage of the current range of 9 species was <30%. Nine species lost on average 46% (SD 29) of their potential range due to climate change. Under climate-change with an optimistic land-cover-change scenario (B1), 12 species lost 39% (SD 28) of their range. In a pessimistic land-cover-change scenario (A2), 15 species lost 36% (SD 28) of their range. Five species lost significantly more range under the A2 scenario than the B1 scenario (p = 0.01, SD 0.01), suggesting that gibbons will benefit from effective management of land cover. PA coverage of future range was <30% for 11 species. On average, 32% (SD 25) of PCAs were covered by PAs. Indonesia contained more species and PCAs and thus has the greatest responsibility for gibbon conservation. Indonesia, India, and Myanmar need to expand their PAs to fulfill their responsibility to gibbon conservation. Our results provide a baseline for global gibbon conservation, particularly for countries lacking gibbon research capacity.

Climate change threatens the distribution of major woody species and ecosystem services provision in southern Africa

In southern Africa, woody vegetation provides essential ecological, regulation, and cultural ecosystem services (ES), yet many species and ecosystems are increasingly threatened by climate change and land-use transformations. We investigated the effect of climate change on the distribution of eight species in 18 countries in southern Africa, covering 36% of the continent. We proposed a loser/winner ranking of the species based on the changes in land climatic suitability within their historical distribution and future gains and losses of suitable areas. We interpreted these findings in terms of changes in key ES (timber, food, and energy) provision and identified hotspots of ES provision decline. We used species presence data from the Global Biodiversity Information Facility, climatic data from the AfriClim dataset, and the MaxEnt algorithm to project the changes in species-specific land climatic suitability. Among the eight investigated species, the baseline suitability range of Mopane (Colophosperm mopane) was least affected by climate change. At the same time, the area of its future distribution was projected to double, rendering it a regional winner. Another two species, manketti (Schinziophyton rautanenii) and leadwood (Combretum imberbe) showed high future gains too; however, the impact on their baseline suitability range differed between the climatic scenarios. The baseline range of African rosewood (Guibourtia coleosperma) declined entirely, and the future gains were negligible, rendering the species a regional loser. The effect of climate change was particularly severe on timber-producing species (four out of eight species), while species providing food (four species) and energy (four species) were affected less. Our projections portrayed distinct hotspot and coldspot areas, where climatic suitability for multiple species was concurrently projected to decline or persist. This assessment can inform spatially targeted adaptation and conservation actions and strategies, which are currently lacking in many African regions.

Climate change will redefine taxonomic, functional, and phylogenetic diversity of Odonata in space and time

Climate change is rearranging the mosaic of biodiversity worldwide. These broad-scale species re-distributions affect the structure and composition of communities with a ripple effect on multiple biodiversity facets. Using European Odonata, we asked: i) how climate change will redefine taxonomic, phylogenetic, and functional diversity at European scales; ii) which traits will mediate species' response to global change; iii) whether this response will be phylogenetically conserved. Using stacked species distribution models, we forecast widespread latitudinal and altitudinal rearrangements in Odonata community composition determining broad turnovers in traits and evolutionary lineages. According to our phylogenetic regression models, only body size and flight period can be partly correlated with observed range shifts. In considering all primary facets of biodiversity, our results support the design of inclusive conservation strategies able to account for the diversity of species, the ecosystem services they provide, and the phylogenetic heritage they carry in a target ecosystem.

Simulation Tests of Methods in Evolution, Ecology, and Systematics: Pitfalls, Progress, and Principles

Complex statistical methods are continuously developed across the fields of ecology, evolution, and systematics (EES). These fields, however, lack standardized principles for evaluating methods, which has led to high variability in the rigor with which methods are tested, a lack of clarity regarding their limitations, and the potential for misapplication. In this review, we illustrate the common pitfalls of method evaluations in EES, the advantages of testing methods with simulated data, and best practices for method evaluations. We highlight the difference between method evaluation and validation and review how simulations, when appropriately designed, can refine the domain in which a method can be reliably applied. We also discuss the strengths and limitations of different evaluation metrics. The potential for misapplication of methods would be greatly reduced if funding agencies, reviewers, and journals required principled method evaluation.

Recommendations for quantifying and reducing uncertainty in climate projections of species distributions

Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

Mapping the Distribution and Dispersal Risks of the Alien Invasive Plant Ageratina adenophora in China

Identifying the distribution dynamics of invasive alien species can help in the early detection of and rapid response to these invasive species in newly invaded sites. Ageratina adenophora, a worldwide invasive plant, has spread rapidly since its invasion in China in the 1940s, causing serious damage to the local socioeconomic and ecological environment. To better control the spread of this invasive plant, we used the MaxEnt model and ArcGIS based on field survey data and online databases to simulate and predict the spatial and temporal distribution patterns and risk areas for the spread of this species in China, and thus examined the key factors responsible for this weed’s spread. The results showed that the risk areas for the invasion of A. adenophora in the current period were 18.394° N–33.653° N and 91.099° E–121.756° E, mainly in the tropical and subtropical regions of China, and densely distributed along rivers and well-developed roads. The high-risk areas are mainly located in the basins of the Lancang, Jinsha, Yalong, and Anning Rivers. With global climate change, the trend of continued invasion of A. adenophora is more evident, with further expansion of the dispersal zone towards the northeast and coastal areas in all climatic scenarios, and a slight contraction in the Yunnan–Guizhou plateau. Temperature, precipitation, altitude, and human activity are key factors in shaping the distribution pattern of A. adenophora. This weed prefers to grow in warm and precipitation-rich environments such as plains, hills, and mountains; in addition, increasing human activities provide more opportunities for its invasion, and well-developed water systems and roads can facilitate its spread. Measures should be taken to prevent its spread into these risk areas.

Accounting for niche truncation to improve spatial and temporal predictions of species distributions

Species Distribution Models (SDMs) are essential tools for predicting climate change impact on species’ distributions and are commonly employed as an informative tool on which to base management and conservation actions. Focusing only on a part of the entire distribution of a species for fitting SDMs is a common approach. Yet, geographically restricting their range can result in considering only a subset of the species’ ecological niche (i.e., niche truncation) which could lead to biased spatial predictions of future climate change effects, particularly if future conditions belong to those parts of the species ecological niche that have been excluded for model fitting. The integration of large-scale distribution data encompassing the whole species range with more regional data can improve future predictions but comes along with challenges owing to the broader scale and/or lower quality usually associated with these data. Here, we compare future predictions obtained from a traditional SDM fitted on a regional dataset (Switzerland) to predictions obtained from data integration methods that combine regional and European datasets for several bird species breeding in Switzerland. Three models were fitted: a traditional SDM based only on regional data and thus not accounting for niche truncation, a data pooling model where the two datasets are merged without considering differences in extent or resolution, and a downscaling hierarchical approach that accounts for differences in extent and resolution. Results show that the traditional model leads to much larger predicted range changes (either positively or negatively) under climate change than both data integration methods. The traditional model also identified different variables as main drivers of species’ distribution compared to data-integration models. Differences between models regarding predicted range changes were larger for species where future conditions were outside the range of conditions existing in the regional dataset (i.e., when future conditions implied extrapolation). In conclusion, we showed that (i) models calibrated on a geographically restricted dataset provide markedly different predictions than data integration models and (ii) that these differences are at least partly explained by niche truncation. This suggests that using data integration methods could lead to more accurate predictions and more nuanced range changes than regional SDMs through a better characterization of species’ entire realized niches.

Projected climate change impacts on the phylogenetic diversity of the world's terrestrial birds: more than species numbers

Ongoing climate change is a major threat to biodiversity. As abiotic tolerances and dispersal abilities vary, species-specific responses have the potential to further amplify or ameliorate the ensuing impacts on species assemblages. Here, we investigate the effects of climate change on species distributions across non-marine birds, quantifying its projected impact on species richness (SR) as well as on different aspects of phylogenetic diversity globally. Going beyond previous work, we disentangle the potential impacts of species gains versus losses on assemblage-level phylogenetic diversity under climate change and compare the projected impacts to randomized assemblage changes. We show that beyond its effects on SR, climate change could have profound impacts on assemblage-level phylogenetic diversity and composition, which differ significantly from random changes and among regions. Though marked species losses are most frequent in tropical and subtropical areas in our projections, phylogenetic restructuring of species communities is likely to occur all across the globe. Furthermore, our results indicate that the most severe changes to the phylogenetic diversity of local assemblages are likely to be caused by species range shifts and local species gains rather than range reductions and extinctions. Our findings highlight the importance of considering diverse measures in climate impact assessments.

Climate Change Reveals Contractions and Expansions in the Distribution of Suitable Habitats for the Neglected Crop Wild Relatives of the Genus Vigna (Savi) in Benin

Sustainable conservation of crop wild relatives is one of the pathways to securing global food security amid climate change threats to biodiversity. However, their conservation is partly limited by spatio-temporal distribution knowledge gaps mostly because they are not morphologically charismatic species to attract conservation attention. Therefore, to contribute to the conservation planning of crop wild relatives, this study assessed the present-day distribution and predicted the potential effect of climate change on the distribution of 15 Vigna crop wild relative taxa in Benin under two future climate change scenarios (RCP 4.5 and RCP 8.5) at the 2055-time horizon. MaxEnt model, species occurrence records, and a combination of climate- and soil-related variables were used. The model performed well (AUC, mean = 0.957; TSS, mean = 0.774). The model showed that (i) precipitation of the driest quarter and isothermality were the dominant environmental variables influencing the distribution of the 15 wild Vigna species in Benin; (ii) about half of the total land area of Benin was potentially a suitable habitat of the studied species under the present climate; (iii) nearly one-third of the species may shift their potentially suitable habitat ranges northwards and about half of the species may lose their suitable habitats by 5 to 40% by 2055 due to climate change; and (iv) the existing protected area network in Benin was ineffective in conserving wild Vigna under the current or future climatic conditions, as it covered only about 10% of the total potentially suitable habitat of the studied species. The study concludes that climate change will have both negative and positive effects on the habitat suitability distribution of Vigna crop wild relatives in Benin such that the use of the existing protected areas alone may not be the only best option to conserve the wild Vigna diversity. Integrating multiple in situ and ex situ conservation approaches taking into account “other effective area-based conservation measures” is recommended. This study provides a crucial step towards the development of sustainable conservation strategies for Vigna crop wild relatives in Benin and West Africa.