Integrating intraspecific differentiation in species distribution models: Consequences on projections of current and future climatically suitable areas of species

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.

Unveiling the Potential Distribution of the Highly Threatened Madeira Pipistrelle (Pipistrellus maderensis): Do Different Evolutionary Significant Units Exist?

The isolation of islands has played a significant role in shaping the unique evolutionary histories of many species of flora and fauna, including bats. One notable example is the Madeira pipistrelle (Pipistrellus maderensis), which inhabits the Macaronesian archipelagos of the Azores, Madeira, and the Canary Islands. Despite the high biogeographic and conservation importance of this species, there is limited information on its ecology and evolutionary history across different archipelagos. In our study, we employed species distribution models (SDMs) to identify suitable habitats for the Madeira pipistrelle and determine the environmental factors influencing its distribution. Additionally, we conducted molecular comparisons using mitochondrial DNA data from various Macaronesian islands. Molecular analyses provided compelling evidence for the presence of distinct Evolutionary Significant Units on the different archipelagos. We identified distinct haplotypes in the populations of Madeira and the Canary Islands, with a genetic distance ranging from a minimum of 2.4% to a maximum of 3.3% between samples from different archipelagos. In support of this, SDMs highlighted relevant dissimilarities between the environmental requirements of the populations of the three archipelagos, particularly the climatic niche. Our research demonstrates that deeper investigations that combine ecological, morphological, and genetic areas are necessary to implement tailored conservation strategies.

Dealing with disjunct populations of vascular plants: implications for assessing the effect of climate change

Species distribution models are the most widely used tool to predict species distributions for species conservation and assessment of climate change impact. However, they usually do not consider intraspecific ecological variation exhibited by many species. Overlooking the potential differentiation among groups of populations may lead to misplacing any conservation actions. This issue may be particularly relevant in species in which few populations with potential local adaptation occur, as in species with disjunct populations. Here, we used ecological niche modeling to analyze how the projections of current and future climatically suitable areas of 12 plant species can be affected using the whole taxa occurrences compared to occurrences from geographically disjunct populations. Niche analyses suggest that usually the disjunct group of populations selects the climatic conditions as similar as possible to the other according to climate availability. Integrating intraspecific variability only slightly increases models' ability to predict species occurrences. However, it results in different predictions of the magnitude of range change. In some species, integrating or not integrating intraspecific variability may lead to opposite trend in projected range change. Our results suggest that integrating intraspecific variability does not strongly improve overall models' accuracy, but it can result in considerably different conclusions about future range change. Consequently, accounting for intraspecific differentiation may enable the detection of potential local adaptations to new climate and so to design targeted conservation strategies.

Aggregate population-level models informed by genetics predict more suitable habitat than traditional species-level model across the range of a widespread riparian tree

Identifying and predicting how species ranges will shift in response to climate change is paramount for conservation and restoration. Ecological niche models are the most common method used to estimate potential distributions of species; however, they traditionally omit knowledge of intraspecific variation that can allow populations to respond uniquely to change. Here, we aim to test how population X environment relationships influence predicted suitable geographic distributions by comparing aggregated population-level models with species-level model predictions of suitable habitat within population ranges and across the species’ range. We also test the effect of two variable selection methods on these predictions–both addressing the possibility of local adaptation: Models were built with (a) a common set, and number, of predictors and, (b) a unique combination and number of predictors specific to each group’s training extent. Our study addresses the overarching hypothesis that populations have unique environmental niches, and specifically that (1) species-level models predict more suitable habitat within the ranges of genetic populations than individual models built from those groups, particularly when compared models are built with the same set of environmental predictors; and (2) aggregated genetic population models predict more suitable habitat across the species’ range than the species-level model, an = d this difference will increase when models are trained with individualized predictors. We found the species models predicted more habitat within population ranges for two of three genetic groups regardless of variable selection, and that aggregated population models predicted more habitat than species’ models, but that individualized predictors increased this difference. Our study emphasizes the extent to which changes to model predictions depend on the inclusion of genetic information and on the type and selection of predictors. Results from these modeling decisions can have broad implications for predicting population-level ecological and evolutionary responses to climate change.

Maxent Modelling Predicts a Shift in Suitable Habitats of a Subtropical Evergreen Tree (Cyclobalanopsis glauca (Thunberg) Oersted) under Climate Change Scenarios in China

Climate change has caused substantial shifts in the geographical distribution of many species. There is growing evidence that many species are migrating in response to climate change. Changes in the distribution of dominant tree species induced by climate change can have an impact not only on organisms such as epiphytes and understory vegetation, but also on the whole ecosystem. Cyclobalanopsis glauca is a dominant tree species in the mingled evergreen and deciduous broadleaf forests of China. Understanding their adaptive strategies against climate change is important for understanding the future community structure. We employed the Maxent framework to model current suitable habitats of C. glauca under current climate conditions and predicted it onto the climate scenarios for 2041–2060 and 2081–2100 using 315 occurrence data. Our results showed that annual precipitation was the most critical factor for the distribution of C. glauca. In the future, increasing precipitation would reduce the limitation of water on habitats, leading to an expansion of the distribution to a higher latitude and higher altitude. At the same time, there were habitat contractions at the junction of the Jiangxi and Fujian Provinces. This study can provide vital information for the management of C. glauca, and serve as a reminder for managers to protect C. glauca in the range contraction areas.

Diminished warming tolerance and plasticity in low-latitude populations of a marine gastropod

Models of species response to climate change often assume that physiological traits are invariant across populations. Neglecting potential intraspecific variation may overlook the possibility that some populations are more resilient or susceptible than others, creating inaccurate predictions of climate impacts. In addition, phenotypic plasticity can contribute to trait variation and may mediate sensitivity to climate. Quantifying such forms of intraspecific variation can improve our understanding of how climate can affect ecologically important species, such as invasive predators. Here, we quantified thermal performance (tolerance, acclimation capacity, developmental traits) across seven populations of the predatory marine snail (Urosalpinx cinerea) from native Atlantic and non-native Pacific coast populations in the USA. Using common garden experiments, we assessed the effects of source population and developmental acclimation on thermal tolerance and developmental traits of F1 snails. We then estimated climate sensitivity by calculating warming tolerance (thermal tolerance - habitat temperature), using field environmental data. We report that low-latitude populations had greater thermal tolerance than their high latitude counterparts. However, these same low-latitude populations exhibited decreased thermal tolerance when exposed to environmentally realistic higher acclimation temperatures. Low-latitude native populations had the greatest climate sensitivity (habitat temperatures near thermal limits). In contrast, invasive Pacific snails had the lowest climate sensitivity, suggesting that these populations are likely to persist and drive negative impacts on native biodiversity. Developmental rate significantly increased in embryos sourced from populations with greater habitat temperature but had variable effects on clutch size and hatching success. Thus, warming can produce widely divergent responses within the same species, resulting in enhanced impacts in the non-native range and extirpation in the native range. Broadly, our results highlight how intraspecific variation can alter management decisions, as this may clarify whether management efforts should be focused on many or only a few populations.

MaxEnt Modeling Based on CMIP6 Models to Project Potential Suitable Zones for Cunninghamia lanceolata in China

Cunninghamia lanceolata (Lamb.) Hook. (Chinese fir) is one of the main timber species in Southern China, which has a wide planting range that accounts for 25% of the overall afforested area. Moreover, it plays a critical role in soil and water conservation; however, its suitability is subject to climate change. For this study, the appropriate distribution area of C. lanceolata was analyzed using the MaxEnt model based on CMIP6 data, spanning 2041–2060. The results revealed that (1) the minimum temperature of the coldest month (bio6), and the mean diurnal range (bio2) were the most important environmental variables that affected the distribution of C. lanceolata; (2) the currently suitable areas of C. lanceolata were primarily distributed along the southern coastal areas of China, of which 55% were moderately so, while only 18% were highly suitable; (3) the projected suitable area of C. lanceolata would likely expand based on the BCC-CSM2-MR, CanESM5, and MRI-ESM2-0 under different SSPs spanning 2041–2060. The increased area estimated for the future ranged from 0.18 to 0.29 million km2, where the total suitable area of C. lanceolata attained a maximum value of 2.50 million km2 under the SSP3-7.0 scenario, with a lowest value of 2.39 million km2 under the SSP5-8.5 scenario; (4) in combination with land use and farmland protection policies of China, it is estimated that more than 60% of suitable land area could be utilized for C. lanceolata planting from 2041–2060 under different SSP scenarios. Although climate change is having an increasing influence on species distribution, the deleterious impacts of anthropogenic activities cannot be ignored. In the future, further attention should be paid to the investigation of species distribution under the combined impacts of climate change and human activities.

Beta diversity of aquatic macroinvertebrate assemblages associated with leaf patches in neotropical montane streams

Over 70% of the total channel length in all river basins is formed by low order streams, many of which originate on mountaintops. Headwater streams play fundamental roles in processing and transporting terrestrial and aquatic organic matter, often harboring high biodiversity in bottom leaf patches deposited from riparian vegetation. The objective of this study was to assess the variation in taxonomic composition (measured by beta diversity of aquatic macroinvertebrates) among stream sites located in the Espinhaço Meridional Mountain Range, part of a UNESCO Biosphere Reserve in eastern Brazil. We tested two hypotheses. (a) Taxa turnover is the main reason for differences in aquatic insect assemblages within stream sites; we predicted that turnover would be higher than nestedness in all stream sites. (b) Stream site altitude and catchment elevation range are the main explanatory variables for the differences in beta diversity; we predicted that local stream site variables would account for only minor amounts of variation. In both dry and wet seasons, we sampled twice in two habitat types (five leaf patches in pools and five in riffles) in each of nine stream sites distributed in three different river basins. We computed average pairwise beta diversity among sampling stations and seasons in each stream site by using Jaccard and Bray-Curtis indices, and calculated the percentages of diversity resulting from turnover and nestedness. Finally, we tested the degree that local- or catchment-level predictor variables explained beta diversity. We found that turnover was the main component of beta diversity and that both dissolved oxygen and elevation range best explained Bray-Curtis beta diversity. These results reinforce the importance of leaf patches in montane (sky islands) Neotropical savanna streams as biodiversity hotbeds for macroinvertebrates, and that both local and landscape variables explained beta diversity.

Species versus within-species niches: a multi-modelling approach to assess range size of a spring-dwelling amphibian

Species Distribution Models (SDMs) can be used to estimate potential geographic ranges and derive indices to assess species conservation status. However, habitat-specialist species require fine-scale range estimates that reflect resource dependency. Furthermore, local adaptation of intraspecific lineages to distinct environmental conditions across ranges have frequently been neglected in SDMs. Here, we propose a multi-stage SDM approach to estimate the distributional range and potential area of occupancy (pAOO) of Neurergus kaiseri, a spring-dwelling amphibian with two climatically-divergent evolutionary lineages. We integrate both broad-scale climatic variables and fine-resolution environmental data to predict the species distribution while examining the performance of lineage-level versus species-level modelling on the estimated pAOO. Predictions of habitat suitability at the landscape scale differed considerably between evolutionary level models. At the landscape scale, spatial predictions derived from lineage-level models showed low overlap and recognised a larger amount of suitable habitats than species-level model. The variable dependency of lineages was different at the landscape scale, but similar at the local scale. Our results highlight the importance of considering fine-scale resolution approaches, as well as intraspecific genetic structure of taxa to estimate pAOO. The flexible procedure presented here can be used as a guideline for estimating pAOO of other similar species.

Reconstructing hotspots of genetic diversity from glacial refugia and subsequent dispersal in Italian common toads (Bufo bufo)

Genetic diversity feeds the evolutionary process and allows populations to adapt to environmental changes. However, we still lack a thorough understanding of why hotspots of genetic diversity are so 'hot'. Here, we analysed the relative contribution of bioclimatic stability and genetic admixture between divergent lineages in shaping spatial patterns of genetic diversity in the common toad Bufo bufo along the Italian peninsula. We combined population genetic, phylogeographic and species distribution modelling (SDM) approaches to map ancestral areas, glacial refugia, and secondary contact zones. We consistently identified three phylogeographic lineages, distributed in northern, central and southern Italy. These lineages expanded from their ancestral areas and established secondary contact zones, before the last interglacial. SDM identified widespread glacial refugia in peninsular Italy, sometimes located under the present-day sea-level. Generalized linear models indicated genetic admixture as the only significant predictor of the levels of population genetic diversity. Our results show that glacial refugia contributed to preserving both levels and patterns of genetic diversity across glacial-interglacial cycles, but not to their formation, and highlight a general principle emerging in Mediterranean species: higher levels of genetic diversity mark populations with substantial contributions from multiple genetic lineages, irrespective of the location of glacial refugia.

Niche divergence of evolutionarily significant units with implications for repopulation programs of the world's largest amphibians

The niche divergence and potential climate change-induced loss of evolutionarily significant units (ESUs) of flagship amphibian species in China, the Chinese giant salamander clade, were investigated. We tested niche-related ecological hypotheses and identified suitable habitats that are essential for the conservation of ESUs in response to future climate change according to ecological niche models (ENMs). We predicted the localized habitat loss crisis of ESUs induced by global climate heating using the predicted climate derived from two representative concentration pathway (RCP) scenarios 2.6 and 8.5, respectively. In our study, a niche conservatism pattern was found between the two distinctive northern and southern ESUs with sufficient distributional records, but their niches were not equivalent. Furthermore, there was neither abrupt environmental change in nor remarkable biogeographic barriers between the suitable habitats of the species, as indicated by random linear, blob and ribbon range-breaking tests. Under the low-emission scenario RCP2.6, the northern ESU had a moderate loss of suitable range, while the southern ESU had range expansion in the 2070s. The climatic velocities were low in the ranges of both ESUs. However, under the high-emission scenario RCP8.5, the climatic velocities were found to become larger in the suitable ranges of both ESUs. Moreover, the northern ESU had severe habitat loss, bringing it to the edge of extinction, while the southern ESU also had intensified range loss. Considering this, climatic velocity can be an effective indicator of range loss. We argued conclusively that conservation prioritization of ESUs should effectively take into account the underlying geographic and ecological mechanisms driving the speciation process. The conservation of ESUs should consider the conservation of both evolutionary potential and ecological adaptation capacity of each lineage. The present study provided practical guidelines for repopulation programs for endangered species and the conservation of evolutionary diversity.

Climate change enforces to look beyond the plant - the example of pollinators

Within global crop production 1961-2012, the share of pollinator independent crops increased twofold, but fourfold of pollinator dependent crops. Balanced diets within the boundaries of our planet require even more pollinator dependent crops. Particularly, Low and Middle Income Countries in the drylands produce pollinator dependent crops. However, climate change and agriculture increasingly cause risks for pollinators. Common reward-based seeding of wildflower strips is too expensive for these countries. Breeding towards pollinator independent crops might accelerate loss of pollinators. Recent publications warned that pollinator loss can reduce other ecosystem services supporting crop production. A new alternative approach called Farming with Alternative Pollinators (FAP) might fill the gap. FAP creates on-farm habitable conditions for pollinators and increases productivity and incomes per surface.

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

While biological distributions are not static and change/evolve through space and time, nonstationarity of climatic and land-use conditions is frequently neglected in species distribution models. Even recent techniques accounting for spatiotemporal variation of species occurrence basically consider the environmental predictors as static; specifically, in most studies using species distribution models, predictor values are averaged over a 50- or 30-year time period. This could lead to a strong bias due to monthly/annual variation between the climatic conditions in which species' locations were recorded and those used to develop species distribution models or even a complete mismatch if locations have been recorded more recently. Moreover, the impact of land-use change has only recently begun to be fully explored in species distribution models, but again without considering year-specific values. Excluding dynamic climate and land-use predictors could provide misleading estimation of species distribution. In recent years, however, open-access spatially explicit databases that provide high-resolution monthly and annual variation in climate (for the period 1901-2016) and land-use (for the period 1992-2015) conditions at a global scale have become available. Combining species locations collected in a given month of a given year with the relative climatic and land-use predictors derived from these datasets would thus lead to the development of true dynamic species distribution models (D-SDMs), improving predictive accuracy and avoiding mismatch between species locations and predictor variables. Thus, we strongly encourage modelers to develop D-SDMs using month- and year-specific climatic data as well as year-specific land-use data that match the period in which species data were collected.