Species Distribution Modelling Approach Research Articles

A new look at genetic variability in pomegranate: landscape genetics and structural equation modeling (SEM)

Pomegranate (Punica granatum L.) is an important horticultural plant in Iran and has been a food source since ancient times. Despite several genetic diversity studies conducted on these taxa, there are no reports on the landscape genetics of these important plants in Iran, nor is there any information on the effects of environmental, spatial, and climatic variables on the genetic structure of pomegranate. Therefore, this study used genetics, structural equation modeling (SEM), and species distribution modeling (SDM) approaches to explore the above-mentioned objectives. We used both cytogenetic and molecular analyses (SSR and SCoT markers) of several pomegranate samples along with environmental, spatial, and climatic variables. The redundancy analysis (RDA) analysis showed a significant positive association between terminal chiasmata with the longitudinal distribution of the pomegranate accession, while total chiasma number and interstitial chiasmata have an association with the altitude. The spatial PCA analysis indicated the role played by both global and local spatial variables in the cytogenetic variability like the univalent and terminal chiasmata formation. The Mantel test indicates that the cytogenetic difference in pomegranate plants is not related to their geographical distance, while the Moran I test result shows that geographical regions with similar spatial conditions affect the cytogenetic structuring of pomegranate plants in a similar way. SEM methods showed a strong negative association between bivalent formation and the environmental variables, while they showed both positive and negative associations between some of the environmental variables and different kinds of chiasmata. The sPCA analysis of molecular data showed a significant global, and local, spatial structuring of the molecular data and the genetic cline formation within the pomegranate accessions studied. Similarly, the spatial PCA analysis of climate variables, precipitation, and temperature revealed a significant structuring of genetic diversity and the formation of genetic clines by these factors. RDA analysis identified some of the loci that are significantly associated with temperature and precipitation. Therefore, both geographical/ or spatial variables and climate factors contribute to the genetic structure of the pomegranate accessions studied. SEM models based on genetic data revealed a positive association between environmental and climate variables with genetic diversity parameters and SSR-SCoT molecular loci studied. Climate change is unlikely to hurt pomegranate growing areas due to the high genetic diversity of pomegranate plants and the diverse genetic lineages present in the country.

Interactive effects of predation and climate on the distributions of marine shellfish in the Northwest Atlantic

As climate change transforms marine environments globally, species distributions correspondingly shift to locations where conditions have become or remain favourable. The ability to model these distributional shifts has been facilitated by species distribution models (SDMs). However, current SDM approaches have largely ignored climate‐driven changes in species interactions, which ultimately can have an important influence on species distributions. In this study, we utilize a long‐term, large‐scale dataset spanning 48 years and approximately 30 degrees latitude across the Canadian Atlantic shelf. We examine how climate influences the distribution and predation patterns of two invertebrates, northern shrimp Pandalus borealis and snow crab Chionoecetes opilio, aiming to evaluate the impacts of climate change on prey distributions. We found that both invertebrate species have a pronounced predicted response to climate change, with a northern shift in the distribution of northern shrimp and an overall reduction in abundance of both snow crab and shrimp associated with warming temperatures. Including predatory interactions as predictors in the SDMs (either directly via predator densities or via estimated predation rates) improved prediction accuracy for northern shrimp but not for snow crab. This is consistent with the ecology of these two species, as northern shrimp is more vulnerable to predation than snow crab. We found that the projections of future northern shrimp distributions are sensitive to the predicted spatial distribution and abundance of predators, highlighting the inherent complexity of predicting species response to climate change. Collectively, these results contribute to a broader literature that seeks to improve the capabilities of models to predict the effects of species interactions on species distributions under changing ecological conditions.

Intercontinental invasion dynamics of Cercopagis pengoi, an IUCN-listed planktonic invasive species

Predicting the spread of invasive species and understanding the role of niche dynamics in niche transferability are critical challenges in the management of biological invasions, both theoretically and practically. We used complementary species distribution modelling approaches, such as multivariate niche analysis and reciprocal distribution models, to test the niche conservatism hypothesis and to predict the potential distribution of the fishhook waterflea, Cercopagis pengoi. Our analysis indicated a significant similarity between its native and invasive ranges, suggesting that a subset of the Ponto-Caspian propagules may have been the founders of European populations. However, our results contradict the niche conservatism hypothesis, showing that C. pengoi has not fully occupied the available niche within its current invasive ranges. Moreover, we observed a notable niche expansion, reflecting a significant shift in niche following its intercontinental introduction in North America. Given the suitability of new environments for the expansion of C. pengoi and its tendency to evade detection prior to population surges, we recommend a focus on early detection through monitoring of both water columns and bottom sediments. This should be complemented by strict enforcement of ballast water regulations to curtail its spread in North America, Europe, and other suitable non-native regions globally.

Distribution and survival of medicinal and aromatic plants is threatened by the anticipated climate change

Changing climatic scenarios has been recognized as a prominent threat to biodiversity globally. Given the decline in biodiversity, there are more and more local, national, and global awareness campaigns as well as legislative initiatives devoted to biodiversity conservation. The present study aims to increase our knowledge and understanding of the distribution of six medicinal and aromatic plants (MAPs) in Jammu Kashmir, India under present and future climatic scenarios using an ensemble species distribution modelling approach. Results of the present study revealed changes in the habitat range of the plant species due to changing climatic scenarios leading to the expansion or contraction of their distribution range. A significant decline in the suitable habitats of Arisaema jacquemontii, Lamium album, Phytolacca acinosa and Urtica dioica is predicted. Podophyllum hexandrum and Thymus linearis are predicted to expand their distribution ranges, however, losing their currently suitable habitats. Thus, the present study recommends that these MAPs should be prioritized for conservation and abrupt appraisal of their present population status and updated IUCN categorization should be carried out. Furthermore, to provide more reliable information for conservation decision-making under future climate scenarios, more thorough models that take into account both the biotic and abiotic factors contributing to species persistence should be used.

Assessing the impact of climate change on the potential distribution of the Carthaginian tree frog (Hyla carthaginiensis): a species distribution modelling approach integrating different dispersal scenarios

Assessing the impact of climate change on the potential distribution of the Carthaginian tree frog (Hyla carthaginiensis): a species distribution modelling approach integrating different dispersal scenarios

An ensemble model predicts an upward range shift of the endemic and endangered Yellow-throated Apalis (Apalis flavigularis) under future climate change in Malawi.

Climate change poses a significant threat to endemic and endangered montane bird species with limited elevation and temperature ranges. Understanding their responses to changes in climate is essential for informing conservation actions. This study focused on the montane dwelling Yellow-throated Apalis (Apalis flavigularis) in Malawi, aiming to identify key factors affecting its distribution and predicting its potential distribution under different climate change scenarios. Using an ensemble species distribution modeling approach, we found that the mean temperature of the driest quarter (Bio9), mean temperature of the wettest quarter (Bio8), and precipitation seasonality (Bio15) were the most important variables that influenced the distribution of this species. Across future climate scenarios, the species' geographic range declined where range losses varied from 57.74% (2050 RCP 6.0) to 82.88% (2070 RCP 6.0). We estimate its current range size to be 549 km2 which is lower than some previous estimates of its spatial distribution. Moreover, our projections indicate that under future climate scenarios, the species will shift to higher elevations with a large proportion of suitable areas located outside forests, posing challenges for adaptation. Our results suggest that the species may be under greater threat than previously thought; hence, urgent conservation actions are required. We recommend reinforcing the protection of areas predicted to remain suitable under future climate scenarios and the development of a species conservation action plan.

Distribution Model Reveals Rapid Decline in Habitat Extent for Endangered Hispid Hare: Implications for Wildlife Management and Conservation Planning in Future Climate Change Scenarios.

The hispid hare, Caprolagus hispidus, belonging to the family Leporidae is a small grassland mammal found in the southern foothills of the Himalayas, in India, Nepal, and Bhutan. Despite having an endangered status according to the IUCN Red List, it lacks studies on its distribution and is threatened by habitat loss and land cover changes. Thus, the present study attempted to assess the habitat suitability using the species distribution model approach for the first time and projected its future in response to climate change, habitat, and urbanization factors. The results revealed that out of the total geographical extent of 188,316 km2, only 11,374 km2 (6.03%) were identified as suitable habitat for this species. The results also revealed that habitat significantly declined across its range (>60%) under certain climate change scenarios. Moreover, in the present climate scenario protected areas such as Shuklaphanta National Park (0.837) in Nepal exhibited the highest mean extent of habitat whereas, in India, Dibru-Saikhowa National Park (0.631) is found to be the most suitable habitat. Notably, two protected areas in Uttarakhand, India, specifically Corbett National Park (0.530) and Sonanandi Wildlife Sanctuary (0.423), have also demonstrated suitable habitats for C. hispidus. Given that protected areas showing a future rise in habitat suitability might also be regarded as potential sites for species translocation, this study underscores the importance of implementing proactive conservation strategies to mitigate the adverse impacts of climate change on this species. It is essential to prioritize habitat restoration, focused protection measures, and further species-level ecological exploration to address these challenges effectively. Furthermore, fostering transboundary collaboration and coordinated conservation actions between nations is crucial to safeguarding the long-term survival of the species throughout its distribution range.

Assessing the Distribution and Richness of Mammalian Species Using a Stacking Species Distribution Model in a Temperate Forest.

This study was conducted as an effort to examine the association between mammalian species richness and environmental, anthropogenic, and bioclimate factors in the Province of Chungnam, Korea, using a stacked species distribution model (SSDM) approach. An SSDM model was constructed using an extensive dataset collected from 1357 mammal sampling points and their corresponding forest, geographical, anthropogenic, and bioclimatic information. Distance to forest edge, elevation, slope, population density, and distance to water channels were identified as important variables for determining species richness, whereas the impact of bioclimate variables was less important. The endemism map showed a strong correlation with species richness, suggesting the important role of endemic species. Overestimation was observed in areas with lower species richness. However, the findings of the study still demonstrated that valuable insights can be obtained through the use of the SSDM, which may be helpful to land managers, aiding in the effective management of wildlife habitats, particularly in regions with an abundance of species richness and endemism.

Looking for reliable species distribution models for low‐density cetacean species: Compared effectiveness of SDMs for G. griseus, G. melas, Z. cavirostris in the Mediterranean Sea based on long‐term fixed‐transect data

Abstract The EU regulative framework for the protection of marine biodiversity and habitats requires the assessment of species' conservation status and the identification of core habitats to design adequate conservation and management plans. However, the identification of distribution range and habitat‐use of pelagic large‐range, migratory species, such as cetaceans, is challenging. Species distribution models (SDMs) are increasingly used in conservation planning to identify species priority areas. However, the quality of SDMs varies widely depending on the representativeness of data and the appropriateness of the modelling techniques. Since 2007, the Fixed Line Transect Mediterranean Monitoring Network (FLT Med Net) has been continuously monitoring cetaceans throughout the year in the Mediterranean basin using passenger ferries as observation platforms that perform repetitive surveys along fixed trans‐border transects. With the aim of defining a standard analytical approach, the data collected by the FLT Med Net on rarer Mediterranean cetacean species (i.e., Grampus griseus, Globicephala melas, Ziphius cavirostris) are used here to assess the performance of commonly used SDMs, including GLM, GAM, GAM‐Negative Binomial, GAM‐tweedy, MaxEnt and Random Forest. Models were built and evaluated using a total of 296 FLT Med Net sighting data and cross‐validated using 145 independent data points. Under testing conditions, almost all methods exhibited good performance, with Random Forest being the best model in several cases. However, when evaluated with the independent dataset, many models yielded inconsistent results or notably low performance. Only MaxEnt demonstrated consistent efficiency and reliability in both cases, showing results less affected by unequal sampling or small sample size. Results confirm the importance of robust standard SDM approaches based on representative data such as the FLT Med Net data to identify reliable priority areas for the species and to assess the long‐term coherence and effectiveness of spatial protection measures.

Land use predicts proportion of West Nile virus vector‐competent mosquitoes

AbstractLand use and land cover (LULC) change has been identified as an important driver of emerging mosquito‐borne zoonotic diseases. However, studies are often limited to individual vector species, despite the potential for interspecific variation in vector competency within mosquito assemblages. This variation can affect transmission hazard, particularly in complex multi‐vector disease systems. Here, we used a joint species distribution modeling approach that included mosquito species vector competency for West Nile virus (WNV) as a trait to understand community‐level responses to land cover and predict joint species distributions in Manatee County, Florida. We assembled species presence/absence data across 61 sites and 44 species sampled from 2016 to 2020 and percent land cover within 2500 m of trap locations for five common land cover types. These data were used to investigate patterns in species richness and community‐weighted proportions of WNV‐competent vector species. The results revealed that land cover effects on individual species aligned with known habitat associations: the highest proportions of WNV‐competent species were predicted in less diverse urbanized areas, and species richness increased as urbanized areas decreased. Our findings highlight the value of community‐level analyses to predict joint vector distributions that can inform where greatest transmission hazard may occur. This information can be used by public health agencies, mosquito control, and land managers to plan more effective and optimized prevention and control efforts.

Can species distribution models using remotely sensed variables inform reintroductions? Trialling methods with Carterocephalus palaemon the Chequered Skipper Butterfly

AbstractDespite large numbers of reintroduction projects taking place and the high cost involved, there is a generally low success rate. Insects in particular are understudied within reintroduction ecology, with guidelines focusing on more iconic vertebrate taxa. Species distribution models (SDMs) examine the associations between species observations and environmental variables to find the conditions in which populations could survive. This study utilises two frequently used SDM approaches, a regression model (general linear model (GLM)) and a machine learning method (MaxEnt) to model habitat suitability for Chequered Skipper, Carterocephalus palaemon, butterflies, which are being reintroduced to Northamptonshire following extinction in England. We look at how SDMs using widespread remotely sensed variables could be used to inform the reintroduction process by finding areas of suitable habitat that were previously overlooked. These remotely sensed variables have the potential to inform reintroductions without extensive on the ground research as they cover huge areas and are widely available. We found that both models are successful in discriminating between presences and absences, using only a limited number of explanatory variables. We conclude that these wide-scale SDMs are useful as a first step in the decision-making process in determining appropriate sites for reintroductions, but that they are less accurate when establishing precisely where species should be placed.

Examining the co-occurrences of human threats within terrestrial protected areas.

Human threats to biodiversity are prevalent within protected areas (PAs), undermining their effectiveness in halting biodiversity loss. Certain threats tend to co-occur, resulting in amplified cumulative impact through synergistic effects. However, it remains unclear which threats are related the most. We analyzed a dataset of 71 human threats in 18013 terrestrial PAs of the European Union's Natura 2000 network, using a Joint Species Distribution Modelling approach, to assess the threats' co-occurrence patterns and potential drivers. Overall, threats were more frequently correlated positively than negatively. Threats related to agriculture and urbanization were correlated strongly with most other threats. Approximately 70% of the variance in our model was explained by country-specific factors, indicating the importance of local drivers. Minimizing the negative impact of key threats can likely reduce the impact of related threats. However, more research is needed to understand better the relationships among threats and, importantly, their combined impact on biodiversity.

The Range Potential of North American Tree Species in Europe

European forest ecosystems are projected to change severely under climate change especially due to an anticipated decline in the distribution of major tree species in Europe. Therefore, the adaptation of European forests appears necessary and urgent. While spontaneous adaptation mechanisms bear a large self-guided potential, we focus on quantifying the potential of management-guided mechanisms. Besides other possible tree species groups for adaptation, non-native tree species from North America have a long tradition in Europe, yet their full distribution potential is not completely revealed. We applied an ensemble species distribution model approach to six North American species, using combined occurrence data from the native and naturalized ranges to gain more insights into the species suitability in the introduced area in 2070 (2061–2080) under the emission scenarios RCP 4.5 and 8.5. Our findings support the assumption that there is unreported species potential in the introduced area beyond their current distribution. Next to northeastern range shifts projected for all species, we identified Abies grandis, Liriodendron tulipifera, Quercus rubra, and Robinia pseudoacacia with increasing range potentials in the future. P. ponderosa and P. menziesii var. menziesii are projected to show a steady and decreased range potential under RCP 4.5 and 8.5, respectively.

Dark future for a black salamander: effects of climate change and conservation implications for an endemic alpine amphibian

Climate change is threatening several montane species across the world, including a large number of endemics, needing the development of forward-looking conservation strategies to foster their future survival. In this context, Species Distribution Models (SDMs) represent a useful method to forecast changes in species’ habitat suitability under different scenarios of global warming, often advising conservation frameworks with credible, defensible and repeatable information. In this paper, we estimate the environmental and bioclimatic suitability for an endemic mountain amphibian (Salamandra lanzai) in the western European Alps through an SDM approach, considering both current and future scenarios, to address short- and long-term management and conservation actions, and to update the current IUCN extinction risk assessment. The ensemble model forecasts predict a dramatic decline of the climatically suitable area for the Lanza’s alpine salamander in the next 20–40 years, even considering an optimistic CO2 emissions scenario, leading to a theoretical extinction of this species in 2100 in case the worst global warming prediction will be actualised. This underlines the urgent need for up-to-date conservation and management strategies to ensure the successful mitigation of climate change effects on S. lanzai, especially by adapting and improving the network of protected areas, immediately removing additional threats and identifying possible management actions able to increase fine-scale habitat suitability and connectivity among populations. In addition, a significant range contraction in the future has to be considered when assessing the extinction risk for this species, possibly exacerbating the effect of other threatening factors, such as the spread of lethal pathogens. Keywords: Salamandra lanzai, ensemble models, environmental suitability, bioclimatic suitability, future projections

Species distribution modelling of the yellow-necked mouse, Sylvaemus tauricus, with special reference to Ukraine

Rodents are essential components of many terrestrial ecosystems and have several beneficial activities in nature, such as soil aeration and insect control, however, rodents are also sources of zoonotic pathogens. As pests they are known to be reservoirs of tick-borne zoonotic infections of viral, bacterial and protozoan origin, and are important hosts of the immature stages of Ixodes ticks. Recent studies in Europe have demonstrated the role of rodents, especially Sylvaemus mice and Myodes voles, in the epidemiology of tick-borne bacterial zoonoses, such as Lyme borreliosis and anaplasmosis. In particular, the yellow-necked mouse, Sylvaemus tauricus (Pallas, 1811; syn.: Apodemus flavicollis (Melchior, 1834)), supports the transmission of the most important pathogens carried by the castor bean tick, Ixodes ricinus. Using a species distribution modelling approach, an assessment was carried out of the probability of presence of the yellow-necked mouse in different parts of Ukraine and a search accomplished to find effective environmental factors that play roles in its distribution. We considered this task important given the ecological and epidemiological significance of this particular rodent species and the urgency of the problem exacerbated by Russia’s armed aggression in Ukraine. Results showed a broad potential for the distribution of the species in the western and central parts of Ukraine, and in the Crimea. Areas predominantly in western and central Ukraine, and in the Crimea, are highly favourable for the mouse, whereas in the south and, to a smaller scale, in the easternmost part of the country they are the least favourable. Amongst the bioclimatic environmental factors that play roles in shaping the species’ niche are the ones that are fully or mostly temperature-related (for instance, annual mean temperature, continentality, etc.). Other factors in a declining order of their roles are associated with soil and land cover features, cloud frequency and standardised human impact. A moderate, though statistically significant, correlation has been found between the distribution of the Lyme disease agent Borrelia burgdorferi s. l. and predicted habitat suitability values for S. tauricus.

Downscaling future land cover scenarios for freshwater fish distribution models under climate change

The decreasing freshwater biodiversity trend can be attributed to anthropogenic impacts in terms of climate and land cover change. For targeted conservation efforts, mapping and understanding the distribution of freshwater organisms consists of an important knowledge gap. Spatial modelling approaches offer valuable insights into present-day biodiversity patterns and potential future trajectories, however methodological constraints still hamper the applicability of addressing future climate and land cover change concurrently in one modelling workflow. Compared to climate-only projections, spatially explicit and high-resolution land cover projections have seen less attention, and the lack of such data challenges modelling efforts to predict the possible future effects of land cover change especially on freshwater organisms. Here we demonstrate a workflow where we downscale future land cover projection data from the Shared Socioeconomic Pathway (SSP) scenarios for South America at 1 km2 spatial resolution, to then predict the future habitat suitability patterns of the Colombian fish fauna. Specifically, we show how the land cover data can be converted from plain numbers into a spatially explicit representation for multiple SSP scenarios and at high spatial resolution, employing freshwater-specific downscaling aspects when spatially allocating the land cover category grid cells, and how it can be fitted into an ensemble species distribution modelling approach of 1209 fish species. Our toolbox consists of a suite of open-source tools, including Dinamica EGO, R, GRASS GIS and GDAL, and we provide the code and necessary steps to reproduce the workflow for other study areas. We highlight the feasibility of the downscaling, but also underline the potential challenges regarding the spatial scale and the size of the spatial units of analysis.

Hydrographr: An R package for scalable hydrographic data processing

Abstract Freshwater ecosystems are considered biodiversity hotspots, but assessing the spatial distribution of species remains challenging. One major obstacle lies in the complex geospatial processing of large amounts of data, such as stream network, sub‐catchment and basin data, that are necessary for addressing the longitudinal connectivity among water bodies. Workflows thus need to be scalable, especially when working across large spatial extents and at high spatial resolution. This in turn requires advanced command‐line GIS skills and programming language integration, which often poses a challenge for freshwater researchers. To address this challenge, we developed the package hydrographr that provides scalable hydrographic data processing in R. The package contains functions for downloading data of the high‐resolution Hydrography90m dataset, processing, reading and extracting information, as well as assessing network distances and connectivity. While the functions are, by default, tailored toward the Hydrography90m data, they can also be generalised toward other data and purposes, such as efficient cropping and merging of raster and vector data, point‐raster extraction, raster reclassification and data aggregation. The package depends on the open‐source software GDAL/OGR, GRASS‐GIS and the AWK programming language in the Linux environment, allowing a seamless language integration. Since the data is processed outside R, hydrographr allows creating scalable geo‐processing workflows. We illustrate the hydrographr functions using two workflows that focus on (i) a freshwater species distribution modelling approach, and (ii) assessing stream connectivity given the fragmentation by dams. We also provide a detailed guide for the initial installation of the required software. Windows users need to first enable the Windows Subsystem for Linux (WSL) feature, and can then follow the same software installation as Linux users. hydrographr is maintained on GitHub at https://github.com/glowabio/hydrographr. hydrographr provides a set of key functions for processing freshwater geospatial data. We expect that the package will support the freshwater‐related research communities given the easy‐to‐use wrapper functions that allow capitalizing on powerful open‐source command‐line software, which may otherwise require a steep learning curve. Users can thus perform large‐scale freshwater‐specific longitudinal connectivity and network analyses across large geographic extents while staying within the R environment.

Seasonal dynamics of phytoplankton community assembly at the Blanes Bay Microbial Observatory (BBMO), NW Mediterranean Sea

The dynamics of phytoplankton biomass and community composition is important for the functioning of marine ecosystems and ocean biogeochemical cycles. However, there is a shortage of studies addressing the interannual seasonal patterns of phytoplankton community assembly due to sampling limitations. Here we study the seasonal dynamics of eight major phytoplankton groups over a 12 year period (2006 to 2018) using a time-series of taxonomic composition from the Blanes Bay Microbial Observatory (BBMO) in the North Western Mediterranean Sea: dinoflagellates, diatoms, coccolithophores, Prochlorococcus, Synechococcus, picoeukaryotes, nanoeukaryotes, and photosynthetic nanoflagellates. We combine the analysis of biotic factors (primary production, phytoplankton taxa, cell abundance, cell size, chlorophyll-a concentration, and phytoplankton biomass) and abiotic factors (nutrients, temperature, and irradiance) to provide a coherent picture of the observed seasonal patterns of phytoplankton community assembly. The BBMO ecosystem is seasonally heterogeneous in community composition, displaying large fluctuating alternations in phytoplankton group dominance throughout the year. The seasonal succession of phytoplankton groups tends to repeat itself every year in a regular fashion, being the seasonal variability of the phytoplankton groups larger than their interannual variability. We compute α-diversity, a measure of the effective richness of phytoplankton groups. The seasonality of α-diversity shows that it is lowest during winter and highest during summer. We compute temporal β-diversity, a measure of compositional heterogeneity of the phytoplankton community. The data show a sinusoidal behavior of β-diversity as a function of the temporal distance between samples, with a period of one year. We use the mirror index (1 - β-diversity) at a temporal distance of one month to compute the phytoplankton group turnover. The seasonality of turnover shows that it is highest during spring and autumn. To evaluate the validity of niche and neutral theories in predicting the interannual sinusoidal behavior of β-diversity, we performed numerical simulations using a mechanistic model. The results provide support to the niche theory for marine phytoplankton ecology and community assembly. The phytoplankton groups appear to follow their specific ecological niches, tracking the seasonal changes in environmental conditions. The ecological implications of these findings are that marine phytoplankton groups appear to fill distinct environmental niches and thus may have different functional roles in the ecosystem. Furthermore, they may be predictable using both mechanistic and species distribution modeling approaches. The climatological time-series presented here can be an excellent testing ground for evaluating the performance of these marine ecosystem models having an explicit representation of different phytoplankton groups.

Predicting future conservation areas while avoiding sympatry in two alpine amphibians severely threatened by climate change

Climate change will cause important declines in environmental suitability, especially when living at high elevations. The critically endangered Salamandra lanzai from the Alps may be severely exposed to future climate change effects and its suitable climate niche may shrink or shift. Another Alpine salamander (S. atra) is present in the region, which in case of spatial overlap may represent a risk for S. lanzai. It is urgent to estimate the effect of future climate change on these species and identify priority areas for conservation while preventing their sympatry. With a species distribution modelling (SDM) approach, we projected the current and future climate suitability of both salamander species. We accounted for uncertainty related to the methods (model replicates) and climate projections (data source, global circulation model and scenario) to provide a consensus map for practitioners. This map also takes into account potential sympatry with S. atra by penalizing the suitability scores of S. lanzai by the scores of S. atra. We predict a severe effect of climate change on both species distributions. Most of the current habitats are projected to become largely unsuitable by 2070, regardless of the climatology and scenario. We identified important spatial disagreements between projections based on different data sources, mostly due to precipitation projections and daily temperature variation. This highlights the need to account for multiple climatologies in mountainous environments. The habitat of both species is highly fragmented, which is expected to limit distributional shifts through natural dispersion. We suggest to explore the possibility of translocation for the most threatened populations and simultaneously develop captive breeding programs. Biotic interactions are rarely accounted for in SDMs, and we encourage the documentation of species with similar ecological requirements to improve the relevance of SDMs for future conservation planning.

Incorporating intraspecific variation into species distribution models improves climate change analyses of a widespread West African tree species (Pterocarpus erinaceus Poir, Fabaceae)

Climate change is predicted to affect species distribution worldwide. Most of the methods used to evaluate such impact so far assume that species respond to the environmental gradients in a uniform way along their distribution range. Because populations occupying different niches may differ in their response to climate change due to local adaptation, accounting for intraspecific variation in species distribution models (SDMs) may yield more reliable predictions for widely distributed species. Pterocarpus erinaceus Poir is a highly valued but endangered tree species, which occurs in the Sudanian (SZ), Sudano-Guinean (SGZ) and Guinean (GZ) ecological zones of Benin. Here, we used two (whole-species and intraspecific-level) SDM approaches to evaluate how local adaptation, quantified through niche differentiation, influences the potential impact of climate change on the distribution of P. erinaceus in Benin. The maximum entropy (MaxEnt) algorithm was employed to simulate the current and future distributions of the species under various Shared Socioeconomic Pathways (SSPs) climate scenarios. The results showed three distinct populations of the species according to the ecological zones of Benin. The intraspecific populations displayed no niche overlap and thus were considered as locally adapted. Mean diurnal range was the main variable that determined the current distribution of the SZ population (percent contribution of 45.9%) while the distribution of the SGZ and GZ populations were determined by isothermality (percent contribution of 58.7% and 76.2%, respectively). While the whole-species SDMs showed that climate change would lead to significant reductions in the species suitable habitats in SZ under SSP2–4.5, SSP1–2.6, and SSP5–8.5, the SDMs based on intraspecific populations indicated a high decrease in habitat suitability in the GZ and an upward shift of the SGZ towards the SZ under the future climate scenarios. Our results suggest that incorporating intraspecific variation into SDMs improves predictions of the impact of climate change and helps to identify appropriate population-based conservation strategies.