Integrating dynamic environmental predictors and species occurrences: Toward true dynamic species distribution models

The future of plant diversity within a Mediterranean endemism centre: Modelling the synergistic effects of climate and land-use change in Peloponnese, Greece

Climate- and land-use change stand as primary threats to terrestrial biodiversity. Yet, their synergistic impacts on species distributions remain poorly understood. To address this knowledge gap, we conducted the first-ever comprehensive species distribution analysis on an entire regional endemism centre within an eastern Mediterranean country, incorporating dynamic land-use/land-cover change data together with climate change scenarios. Specifically, we apply species distribution modelling and spatial data analysis techniques to compare the individual and synergistic effects of these environmental drivers on the endemic vascular flora of Peloponnese, focusing on potential range contractions, altitudinal shifts, and habitat fragmentation levels. Moreover, we identify fine-scale present and potential future endemism hotspots within our study area, incorporating taxonomic and phylogenetic information. Overall, we aim to enhance our current understanding of endemism patterns and contribute to the development of future-proof conservation strategies for safeguarding Greece's endangered endemic flora. The integration of land-use change projections with climate change yielded less severe impacts compared to the effects anticipated when considering climatic variables alone. Most taxa are expected to undergo significant range declines and nearly half might experience increased habitat fragmentation, due to the synergistic effects of climate- and land-use change. We identified endemism hotspots, which are concentrated in or along the main Peloponnesian mountain massifs. However, our predictions indicate that areas presently recognized as endemism hotspots will undergo a concerning area decline, across all future scenarios considered in this study. Our findings highlight the importance of including dynamic land-use variables alongside climatic predictors when projecting species distributions under global change. Moreover, we showed that endemism hotspots are not static and considering their potential geographic shifts is paramount to delineate effective forward-looking conservation strategies.

Ecological forecasts of insect range dynamics: a broad range of taxa includes winners and losers under future climate

Species distribution models are the primary tools to project future species' distributions, but this complex task is influenced by data limitations and evolving best practices. The majority of the 53 studies we examined utilized correlative models and did not follow current best practices for validating retrospective or future environmental data layers. Despite this, a summary of results is largely unsurprising: shifts toward cooler regions, but otherwise mixed dynamics emphasizing winners and losers. Harmful insects were more likely to show positive outcomes compared with beneficial species. Our restricted ability to consider mechanisms complicates interpretation of any single study. To improve this area of modeling, more classic field and lab studies to uncover basic ecology and physiology are crucial.

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.

Predicting the spatial expansion of an animal population with presence-only data

Predictive models can improve the efficiency of wildlife management by guiding actions at the local, landscape and regional scales. In recent decades, a vast range of modelling techniques have been developed to predict species distributions and patterns of population spread. However, data limitations often constrain the precision and biological realism of models, which make them less useful for supporting decision-making. Complex models can also be challenging to evaluate, and the results are often difficult to interpret for wildlife management practitioners. There is therefore a need to develop techniques that are appropriately robust, but also accessible to a range of end users. We developed a hybrid species distribution model that utilises commonly available presence-only distribution data and minimal demographic information to predict the spread of roe deer (Capreolus caprelous) in Great Britain. We take a novel approach to representing the environment in the model by constraining the size of habitat patches to the home-range area of an individual. Population dynamics are then simplified to a set of generic rules describing patch occupancy. The model is constructed and evaluated using data from a populated region (England and Scotland) and applied to predict regional-scale patterns of spread in a novel region (Wales). It is used to forecast the relative timing of colonisation events and identify important areas for targeted surveillance and management. The study demonstrates the utility of presence-only data for predicting the spread of animal species and describes a method of reducing model complexity while retaining important environmental detail and biological realism. Our modelling approach provides a much-needed opportunity for users without specialist expertise in computer coding to leverage limited data and make robust, easily interpretable predictions of spread to inform proactive population management.

Key Factors behind the Dynamic Stability of Pairs of Egyptian Vultures in Continental Spain

Conservation science aims to identify the factors influencing the distribution of threatened species, thereby permitting the implementation of effective management strategies. This is key for long-lived species that require long-term monitoring such as the worldwide endangered Egyptian vulture (Neophron percnopterus). We studied temporal and spatial variations in the distribution of breeding pairs and examined the intrinsic and anthropic factors that may be influencing the abundance of breeding territories in continental Spain. Based on the census data of breeding pairs from 2000, 2008, and 2018, we used Rank Occupancy-Abundance Profiles to assess the temporal stability of the population and identified the spatial heterogeneity through a Local Index of Spatial Autocorrelation analysis. The GLMs showed that the abundance distribution was mainly influenced by the abundance of griffon vultures (Gyps fulvus) and cattle at a regional scale. Nonparametric comparisons showed that the presence of wind farms had a significant negative effect on local breeding pairs abundance, but that supplementary feeding stations and food resource-related variables had a positive impact. In light of these findings, we recommend a hierarchical approach in future conservation programs involving actions promoting regional-scale food resource availability and highlight the need to address the negative impact of wind farms at local levels.

Modelling the effects of topographic heterogeneity on distribution of Nitraria tangutorum Bobr. species in deserts using LiDAR-data

Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and solar insolation). Species Distribution Models (SDMs) can be used to understand these relationships. We used data acquired from the important desert plant Nitraria tangutorum Bobr. communities and desert topographic factors extracted from LiDAR (Light Detection and Ranging) data of one square kilometer in the inner Mongolia region of China to develop SDMs. We evaluated the performance of SDMs developed with a variety of both the parametric and nonparametric algorithms (Bioclimatic Modelling (BIOCLIM), Domain, Mahalanobi, Generalized Linear Model, Generalized Additive Model, Random Forest (RF), and Support Vector Machine). The area under the receiver operating characteristic curve was used to evaluate these algorithms. The SDMs developed with RF showed the best performance based on the area under curve (0.7733). We also produced the Nitraria tangutorum Bobr. distribution maps with the best SDM and suitable habitat area of the Domain model. Based on the suitability map, we conclude that Nitraria tangutorum Bobr. is more suited to southern part with 0-20 degree slopes at an elevation of approximately 1010 m. This is the first attempt of modelling the effects of topographic heterogeneity on the desert species distribution on a small scale. The presented SDMs can have important applications for predicting species distribution and will be useful for preparing conservation and management strategies for desert ecosystems on a small scale.

The role of reservoir species in mediating plague's dynamic response to climate

The distribution and transmission of Yersinia pestis, the bacterial agent of plague, responds dynamically to climate, both within wildlife reservoirs and human populations. The exact mechanisms mediating plague's response to climate are still poorly understood, particularly across large environmentally heterogeneous regions encompassing several reservoir species. A heterogeneous response to precipitation was observed in plague intensity across northern and southern China during the Third Pandemic. This has been attributed to the response of reservoir species in each region. We use environmental niche modelling and hindcasting methods to test the response of a broad range of reservoir species to precipitation. We find little support for the hypothesis that the response of reservoir species to precipitation mediated the impact of precipitation on plague intensity. We instead observed that precipitation variables were of limited importance in defining species niches and rarely showed the expected response to precipitation across northern and southern China. These findings do not suggest that precipitation-reservoir species dynamics never influence plague intensity but that instead, the response of reservoir species to precipitation across a single biome cannot be assumed and that limited numbers of reservoir species may have a disproportional impact upon plague intensity.

Climate change and the potential distribution of the glassy-winged sharpshooter (Homalodisca vitripennis), an insect vector of Xylella fastidiosa

Biological invasions represent a major threat for biodiversity and agriculture. Despite efforts to restrict the spread of alien species, preventing their introduction remains the best strategy for an efficient control. In that context preparedness of phytosanitary authorities is very important and estimating the geographical range of alien species becomes a key information. The present study investigates the potential geographical range of the glassy-winged sharpshooter (Homalodisca vitripennis), a very efficient insect vector of Xylella fastidiosa, one of the most dangerous plant-pathogenic bacteria worldwide. We use species distribution modeling (SDM) to analyse the climate factors driving the insect distribution and we evaluate its potential distribution in its native range (USA) and in Europe according to current climate and different scenarios of climate change: 6 General Circulation Models (GCM), 4 shared socioeconomic pathways of gas emission and 4 time periods (2030, 2050, 2070, 2090). The first result is that the climate conditions of the European continent are suitable to the glassy-winged sharpshooter, in particular around the Mediterranean basin where X. fastidiosa is present. Projections according to future climate conditions indicate displacement of climatically suitable areas towards the north in both North America and Europe. Globally, suitable areas will decrease in North America and increase in Europe in the coming decades. SDM outputs vary according to the GCM considered and this variability indicated areas of uncertainty in the species potential range. Both potential distribution and its uncertainty associated to future climate projections are important information for improved preparedness of phytosanitary authorities.

Decomposing the spatial and temporal effects of climate on bird populations in northern European mountains

The relationships between species abundance or occurrence versus spatial variation in climate are commonly used in species distribution models to forecast future distributions. Under "space-for-time substitution", the effects of climate variation on species are assumed to be equivalent in both space and time. Two unresolved issues of space-for-time substitution are the time period for species' responses and also the relative contributions of rapid- versus slow reactions in shaping spatial and temporal responses to climate change. To test the assumption of equivalence, we used a new approach of climate decomposition to separate variation in temperature and precipitation in Fennoscandia into spatial, temporal, and spatiotemporal components over a 23-year period (1996-2018). We compiled information on land cover, topography, and six components of climate for 1756 fixed route surveys, and we modeled annual counts of 39 bird species breeding in the mountains of Fennoscandia. Local abundance of breeding birds was associated with the spatial components of climate as expected, but the temporal and spatiotemporal climatic variation from the current and previous breeding seasons were also important. The directions of the effects of the three climate components differed within and among species, suggesting that species can respond both rapidly and slowly to climate variation and that the responses represent different ecological processes. Thus, the assumption of equivalent species' response to spatial and temporal variation in climate was seldom met in our study system. Consequently, for the majority of our species, space-for-time substitution may only be applicable once the slow species' responses to a changing climate have occurred, whereas forecasts for the near future need to accommodate the temporal components of climate variation. However, appropriate forecast horizons for space-for-time substitution are rarely considered and may be difficult to reliably identify. Accurately predicting change is challenging because multiple ecological processes affect species distributions at different temporal scales.

The New Dominator of the World: Modeling the Global Distribution of the Japanese Beetle under Land Use and Climate Change Scenarios

The spread of invasive species is a threat to global biodiversity. The Japanese beetle is native to Japan, but alien populations of this insect occur in North America, and recently, also in southern Europe. This beetle was recently included on the list of priority species of European concern, as it is a highly invasive agricultural pest. Thus, in this study, we aimed at (i) assessing its current distribution range, and identifying areas of potential invasion, and (ii) predicting its distribution using future climatic and land-use change scenarios for 2050. We collected species occurrences available on the citizen science platform iNaturalist, and we combined species data with climatic and land-use predictors using a Bayesian framework, specifically the integrated nested Laplace approximation, with a stochastic partial differential equation. We found that the current distribution of the Japanese beetle was mainly, and positively, driven by the percentage of croplands, the annual range of temperature, habitat diversity, percentage of human settlements, and human population density; it was negatively related to the distance to airports, elevation, mean temperature diurnal range, wetlands, and waters. As a result, based on current conditions, the Japanese beetle is likely to occur in 47,970,200 km2, while its distribution will range from between 53,418,200 and 59,126,825 km2, according to the 2050 climatic and land-use change scenarios. We concluded that the Japanese beetle is a high-risk invasive species, able to find suitable conditions for its colonization in several regions around the globe, especially in light of ongoing climatic change. Thus, we strongly recommend strict biosecurity checks and quarantines, as well as regular pest management surveys, in order to reduce its spread.

Effects of climate change and land cover on the distributions of a critical tree family in the Philippines

Southeast Asian forests are dominated by the tree family Dipterocarpaceae, whose abundance and diversity are key to maintaining the structure and function of tropical forests. Like most biodiversity, dipterocarps are threatened by deforestation and climate change, so it is crucial to understand the potential impacts of these threats on current and future dipterocarp distributions. We developed species distribution models (SDMs) for 19 species of dipterocarps in the Philippines, which were projected onto current and two 2070 representative concentration pathway (RCP) climate scenarios, RCP 4.5 and 8.5. Current land cover was incorporated as a post-hoc correction to restrict projections onto intact habitats. Land cover correction alone reduced current species distributions by a median 67%, and within protected areas by 37%. After land cover correction, climate change reduced distributions by a median 16% (RCP 4.5) and 27% (RCP 8.5) at the national level, with similar losses in protected areas. There was a detectable upward elevation shift of species distributions, consisting of suitable habitat losses below 300 m and gains above 600 m. Species-rich stable areas of continued habitat suitability (i.e., climate macrorefugia) fell largely outside current delineations of protected areas, indicating a need to improve protected area planning. This study highlights how SDMs can provide projections that can inform protected area planning in the tropics.

Toward reliable habitat suitability and accessibility models in an era of multiple environmental stressors

Global biodiversity declines, largely driven by climate and land-use changes, urge the development of transparent guidelines for effective conservation strategies. Species distribution modeling (SDM) is a widely used approach for predicting potential shifts in species distributions, which can in turn support ecological conservation where environmental change is expected to impact population and community dynamics. Improvements in SDM accuracy through incorporating intra- and interspecific processes have boosted the SDM field forward, but simultaneously urge harmonizing the vast array of SDM approaches into an overarching, widely adoptable, and scientifically justified SDM framework. In this review, we first discuss how climate warming and land-use change interact to govern population dynamics and species' distributions, depending on species' dispersal and evolutionary abilities. We particularly emphasize that both land-use and climate change can reduce the accessibility to suitable habitat for many species, rendering the ability of species to colonize new habitat and to exchange genetic variation a crucial yet poorly implemented component of SDM. We then unite existing methodological SDM practices that aim to increase model accuracy through accounting for multiple global change stressors, dispersal, or evolution, while shifting our focus to model feasibility. We finally propose a roadmap harmonizing model accuracy and feasibility, applicable to both common and rare species, particularly those with poor dispersal abilities. This roadmap (a) paves the way for an overarching SDM framework allowing comparison and synthesis of different SDM studies and (b) could advance SDM to a level that allows systematic integration of SDM outcomes into effective conservation plans.

Predicting Microhabitat Suitability for an Endangered Small Mammal Using Sentinel-2 Data

Accurate mapping is a main challenge for endangered small-sized terrestrial species. Freely available spatio-temporal data at high resolution from multispectral satellite offer excellent opportunities for improving predictive distribution models of such species based on fine-scale habitat features, thus making it easier to achieve comprehensive biodiversity conservation goals. However, there are still few examples showing the utility of remote-sensing-based products in mapping microhabitat suitability for small species of conservation concern. Here, we address this issue using Sentinel-2 sensor-derived habitat variables, used in combination with more commonly used explanatory variables (e.g., topography), to predict the distribution of the endangered Cabrera vole (Microtus cabrerae) in agrosilvopastorial systems. Based on vole surveys conducted in two different seasons over a ~176,000 ha landscape in Southern Portugal, we assessed the significance of each predictor in explaining Cabrera vole occurrence using the Boruta algorithm, a novel Random forest variant for dealing with high dimensionality of explanatory variables. Overall, results showed a strong contribution of Sentinel-2-derived variables for predicting microhabitat suitability of Cabrera voles. In particular, we found that photosynthetic activity (NDI45), specific spectral signal (SWIR1), and landscape heterogeneity (Rao’s Q) were good proxies of Cabrera voles’ microhabitat, mostly during temporally greener and wetter conditions. In addition to remote-sensing-based variables, the presence of road verges was also an important driver of voles’ distribution, highlighting their potential role as refuges and/or corridors. Overall, our study supports the use of remote-sensing data to predict microhabitat suitability for endangered small-sized species in marginal areas that potentially hold most of the biodiversity found in human-dominated landscapes. We believe our approach can be widely applied to other species, for which detailed habitat mapping over large spatial extents is difficult to obtain using traditional descriptors. This would certainly contribute to improving conservation planning, thereby contributing to global conservation efforts in landscapes that are managed for multiple purposes.