Climate change may reveal currently unavailable parts of species' ecological niches

The ability of climatic niche models to predict species extinction risks can be hampered if niches are incompletely quantified. This can occur when niches are estimated considering only currently available climatic conditions, disregarding the fact that climate change can open up portions of the fundamental niche that are currently inaccessible to species. Using a new metric, we estimate the prevalence of potential situations of fundamental niche truncation by measuring whether current ecological niche limits are contiguous to the boundaries of currently available climatic conditions for 24,944 species at the global scale in both terrestrial and marine realms and including animals and plants. We show that 12,172 (~49%) species are showing niche contiguity, particularly those inhabiting tropical ecosystems and the marine realm. Using niche expansion scenarios, we find that 86% of species showing niche contiguity could have a fundamental niche potentially expanding beyond current climatic limits, resulting in lower-yet still alarming-rates of predicted biodiversity loss, particularly within the tropics. Caution is therefore advised when forecasting future distributions of species presenting niche contiguity, particularly towards climatic limits that are predicted to expand in the future.

Future changes in society and climate may strongly shape wild large-herbivore faunas across Europe

Restoring wild communities of large herbivores is critical for the conservation of biodiverse ecosystems, but environmental changes in the twenty-first century could drastically affect the availability of habitats. We projected future habitat dynamics for 18 wild large herbivores in Europe and the relative future potential patterns of species richness and assemblage mean body weight considering four alternative scenarios of socioeconomic development in human society and greenhouse gas emissions (SSP1-RCP2.6, SSP2-RCP4.5, SSP3-RCP7.0, SSP5-RCP8.5). Under SSP1-RCP2.6, corresponding to a transition towards sustainable development, we found stable habitat suitability for most species and overall stable assemblage mean body weight compared to the present, with an average increase in species richness (in 2100: 3.03 ± 1.55 compared to today's 2.25 ± 1.31 species/area). The other scenarios are generally unfavourable for the conservation of wild large herbivores, although under the SSP5-RCP8.5 scenario there would be increase in species richness and assemblage mean body weight in some southern regions (e.g. + 62.86 kg mean body weight in Balkans/Greece). Our results suggest that a shift towards a sustainable socioeconomic development would overall provide the best prospect of our maintaining or even increasing the diversity of wild herbivore assemblages in Europe, thereby promoting trophic complexity and the potential to restore functioning and self-regulating ecosystems. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Potential sources of time lags in calibrating species distribution models

The Anthropocene is characterized by a rapid pace of environmental change and is causing a multitude of biotic responses, including those that affect the spatial distribution of species. Lagged responses are frequent and species distributions and assemblages are consequently pushed into a disequilibrium state. How the characteristics of environmental change-for example, gradual 'press' disturbances such as rising temperatures due to climate change versus infrequent 'pulse' disturbances such as extreme events-affect the magnitude of responses and the relaxation times of biota has been insufficiently explored. It is also not well understood how widely used approaches to assess or project the responses of species to changing environmental conditions can deal with time lags. It, therefore, remains unclear to what extent time lags in species distributions are accounted for in biodiversity assessments, scenarios and models; this has ramifications for policymaking and conservation science alike. This perspective piece reflects on lagged species responses to environmental change and discusses the potential consequences for species distribution models (SDMs), the tools of choice in biodiversity modelling. We suggest ways to better account for time lags in calibrating these models and to reduce their leverage effects in projections for improved biodiversity science and policy.

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.

Modeling the Wintering Habitat Distribution of the Black Stork in Shaanxi, China: A Hierarchical Integration of Climate and Land Use/Land Cover Data

Species distribution models (SDMs) are effective tools for wildlife conservation and management, as they employ the quantification of habitat suitability and environmental niches to evaluate the patterns of species distribution. The utilization of SDMs at various scales in a hierarchical approach can provide additional and complementary information, significantly improving decision-making in local wildlife conservation initiatives. In this study, we considered the appropriate spatial scale and data resolution to execute species distribution modeling, as these factors greatly influence the modeling procedures. We developed SDMs for wintering black storks at both the regional and local scales. At the regional scale, we used climatic and climate-driven land use/land cover (LULC) variables, along with wintering occurrence points, to develop models for mainland China. At the local scale, we used local environmental variables and locally gathered wintering site data to develop models for Shaanxi province. The predictions from both the regional and local models were then combined at the provincial level by overlapping suitable areas based on climatic and local conditions. We compared and evaluated the resulting predictions using seven statistical metrics. The national models provide information on the appropriate climatic conditions for the black stork during the wintering period throughout China, while the provincial SDMs capture the important local ecological factors that influence the suitability of habitats at a finer scale. As anticipated, the national SDMs predict a larger extent of suitable areas compared to the provincial SDMs. The hierarchical prediction approach is considered trustworthy and, on average, yields better outcomes than non-hierarchical methods. Our findings indicate that human-driven LULC changes have a significant and immediate impact on the wintering habitat of the black stork. However, the effects of climate change seem to be reducing the severity of this impact. The majority of suitable wintering habitats lie outside the boundaries of protected areas, highlighting the need for future conservation and management efforts to prioritize addressing these conservation gaps and focusing on the protection of climate refuges.

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.

Ecological Niche Modelling Approaches: Challenges and Applications in Vector-Borne Diseases

Vector-borne diseases (VBDs) pose a major threat to human and animal health, with more than 80% of the global population being at risk of acquiring at least one major VBD. Being profoundly affected by the ongoing climate change and anthropogenic disturbances, modelling approaches become an essential tool to assess and compare multiple scenarios (past, present and future), and further the geographic risk of transmission of VBDs. Ecological niche modelling (ENM) is rapidly becoming the gold-standard method for this task. The purpose of this overview is to provide an insight of the use of ENM to assess the geographic risk of transmission of VBDs. We have summarised some fundamental concepts and common approaches to ENM of VBDS, and then focused with a critical view on a number of crucial issues which are often disregarded when modelling the niches of VBDs. Furthermore, we have briefly presented what we consider the most relevant uses of ENM when dealing with VBDs. Niche modelling of VBDs is far from being simple, and there is still a long way to improve. Therefore, this overview is expected to be a useful benchmark for niche modelling of VBDs in future research.

Multiscale ecological niche modeling exhibits varying climate change impacts on habitat suitability of Madrean Pine-Oak trees

Anthropogenic climate change and increasing greenhouse gas emissions are expected to globally impact the biological function, community structure, and spatial distribution of biodiversity. Many existing studies explore the effect of climate change on biodiversity, generally at a single spatial scale. This study explores the potential effects of climate change on the habitat suitability of seven tree species at two distinct spatial scales: the Coronado National Forest (CNF), a local management area, and the Sierra Madre Occidental (SMO), an ecoregional extent. Habitat suitability was determined by extrapolating Ecological Niche Models (ENMs) based on citizen-science tree occurrence records into future climatic conditions using projected 30-year normals for two anthropogenic emissions scenarios through the end of the century. These ENMs, examined at a spatial resolution of 1 km2, are constructed using a mean average ensemble of three commonly used machine learning algorithms. The results show that habitat suitability is expected to decrease for all seven tree species at varying degrees. Results also show that climate-forcing scenario choice appears to be far less important for understanding changes in species habitat suitability than the spatial scale of modeling extent. Additionally, we observed non-linear changes in tree species habitat suitability within the SMO and CNF dependent on forest community type, latitude, and elevational gradient. The paper concludes with a discussion of the necessary steps to verify the estimated alters of these tree species under climate change. Most importantly, provides a framework for characterizing habitat suitability across spatial scales.

The performance of protected-area expansions in representing tropical Andean species: past trends and climate change prospects

Protected area (PA) extent has increased significantly over the last 150 years globally, but it is yet unclear whether progress in expanding coverage has been accompanied by improved performance in ecological representation. Here, we explore temporal trends in the performance of PA networks in representing > 16,000 vertebrate and plant species in tropical Andean countries based on species bioclimatic niche modelling. We use a randomization analysis to assess whether representation gains over time (1937-2015) are the expected consequence of increasing the overall area of the network or the result of better designed networks. We also explore the impact of climate change on protected-area representation based on projected species distributions in 2070. We found that PAs added in the last three to four decades were better at representing species diversity than random additions overall. Threatened species, amphibians and reptiles are the exception. Species representation is projected to decrease across PAs under climate change, although PA expansions over the last decade (2006-2015) better represented species' future bioclimatic niches than did sites selected at random for most evaluated groups. These findings indicate an unbalanced representation across taxa, and raises concern over under-represented groups, including threatened species, and species' representation under climate change scenarios. However, they also suggest that decisions related to locating protected areas have become more strategic in recent decades and illustrate that indicators tracking representativeness of networks are crucial in PA monitoring frameworks.

On the importance of invasive species niche dynamics in plant conservation management at large and local scale

Predicting the distribution of Invasive alien species (IAS) using species distribution models is promising for conservation planning. To achieve accurate predictions, it is essential to explore species niche dynamics. New approaches are necessary for bringing this analysis to real conservation management needs. Using multi-site comparisons can provide great useful insights to better understand invasion processes. Exploring the fine-scale niche overlap between IAS and native species sharing a location can be a key tool for achieving the implementation of local species conservation actions, which can play a fundamental role in the global management of IAS. This can also increase society’s awareness of the threat of IAS. In this context, here, we explored two key research demands. First, we studied the large-scale niche dynamics of the invasive species Paraserianthes lophantha (Willd.) I.C. Nielsen’s considering different invaded areas. The analysis compared niches of the native range (South Western Australia) with the Australian invaded range (eastern Australia); the native range with the European invaded range, and its full Australian range (native plus invaded range) with the European invaded range. Second, we perform a fine-scale niche overlap analysis at landscape scale in Spain. We studied the niche overlap between P. lophantha and a species with remarkable conservation interest (Quercus lusitanica Lam). All the niche analyses were realized following a well-established ordination (principal component analysis) approach where important methodological aspects were compared and analyzed. Our multi-site study of P. lophantha large-scale niche dynamics detected niche shifts between the Australian ranges demonstrating that the species is labile and may potentially adapt to further European climate conditions and spread its invasive range. Comparative analysis between the European and the full Australian ranges supports that calibrate models including the Australian invasive information is promising to accurate predict P. lophantha European potential distribution. The fine-scale study of niche overlap further explained the potential of this IAS and can be used as a model example of how these local studies can be used to promote the implementation of conservation actions in situ as a complement to large-scale management strategies.

Ecological niche models applied to post-megafire vegetation restoration in the context of climate change

Climate change and land-use changes are the main drivers altering fire regimes and leading to the occurrence of megafires. Current management policies mainly focus on short-term restoration without considering how climate change might affect regeneration dynamics. We aimed to test the usefulness of ecological niche models (ENMs) to integrate the effects of climate change on tree species distributions into post-fire restoration planning. We also examined different important conceptual and methodological aspects during this novel process. We constructed ENM at fine spatial resolution (25 m) for the four main tree species (Pinus pinaster, Quercus pyrenaica, Q. faginea and Q. ilex) in an area affected by a megafire in Central Spain at two scales (local and regional), two periods (2 and 14 years after the fire) at the local scale, and under two future climate change scenarios. The usefulness of ENMs as support tools in decision-making for post-fire management was confirmed for the first time. As hypothesized, models developed at both scales are different, since they represent different scale dependent drivers of species distribution patterns. However, both provide objective information to be considered by stakeholders in combination with other sources of information. Local models generated with vegetation data 14 years after the fire provided valuable information about local and current vegetation dynamics (i.e., current microecology spatial niche prediction). Regional models are capable of considering a higher proportion of the climatic niche of species to generate reliable climate change forecasts (i.e., future macroclimate spatial niche forecast). The use of precise ENMs provide both an objective interpretation of potential habitat conditions and the opportunity of examining vegetation patches, that can be very valuable in managing restoration of areas affected by megafires under climate change conditions.