Ensemble Species Distribution Models Research Articles

Range Dynamics of Striped Field Mouse (Apodemus agrarius) in Northern Eurasia under Global Climate Change Based on Ensemble Species Distribution Models.

The striped field mouse (Apodemus agrarius Pallas, 1771) is a widespread species in Northern Eurasia. It damages crops and carries zoonotic pathogens. Its current and future range expansion under climate change may negatively affect public health and the economy, warranting further research to understand the ecological and invasive characteristics of the species. In our study, we used seven algorithms (GLM, GAM, GBS, FDA, RF, ANN, and MaxEnt) to develop robust ensemble species distribution models (eSDMs) under current (1970-2000) and future climate conditions derived from global circulation models (GCMs) for 2021-2040, 2041-2060, 2061-2080, and 2081-2100. Simulation of climate change included high-, medium-, and low-sensitivity GCMs under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We analyzed the habitat suitability across GCMs and scenarios by constructing geographical ranges and calculating their centroids. The results showed that the range changes depended on both the sensitivity of GCMs and scenario. The main trends were range expansion to the northeast and partial loss of habitat in the steppe area. The striped field mouse may form a continuous range from Central Europe to East Asia, closing the range gap that has existed for 12 thousand years. We present 49 eSDMs for the current and future distribution of A. agrarius (for 2000-2100) with quantitative metrics (gain, loss, change) of the range dynamics under global climate change. The most important predictor variables determining eSDMs are mean annual temperature, mean diurnal range of temperatures, the highest temperature of the warmest month, annual precipitation, and precipitation in the coldest month. These findings could help limit the population of the striped field mouse and predict distribution of the species under global climate change.

Potential impacts of climate change on the distribution of echinoderms in the Yellow Sea and East China Sea

To detect potential impacts of climate change on the distribution of common echinoderm species in the Yellow Sea (YS) and East China Sea (ECS), species distribution models (SDMs) were applied. Ensemble SDMs were constructed and were in good model performance for six of the eight selected common echinoderm species. Under future climate scenarios, the brittle stars Ophiopholis mirabilis, Amphioplus depressus and the sea cucumber Protankyra bidentata were projected to expand in the southwestern areas of the YS, the ECS, and the coastal areas of the YS and ECS, respectively; the brittle stars Stegophiura sladeni, Amphiura digitula and Amphiura vadicola will likely contract their ranges in the south distribution areas and expand in the north, showing a northward movement trend. Temperature was the most important environmental variable influencing the distribution of the latter three echinoderms. Our findings will improve our understanding of the impacts of climate change on marine species distributions.

Assessing potential European areas of Pierce's disease mediated by insect vectors by using spatial ensemble model.

Pierce's disease (PD) is a serious threat to grape production in Europe. This disease is caused by Xylella fastidiosa and is mediated by insect vectors, suggesting its high potential for spread and necessity for early monitoring. In this study, hence, potential distribution of Pierce's disease varied with climate change and was spatially evaluated in Europe using ensemble species distribution modeling. Two models of X. fastidiosa and three major insect vectors (Philaenus spumarius, Neophilaenus campestris, and Cicadella viridis) were developed using CLIMEX and MaxEnt. The consensus areas of the disease and insect vectors, along with host distribution, were evaluated using ensemble mapping to identify high-risk areas for the disease. Our predictions showed that the Mediterranean region would be the most vulnerable to Pierce's disease, and the high-risk area would increase three-fold due to climate change under the influence of N. campestris distribution. This study demonstrated a methodology for species distribution modeling specific to diseases and vectors while providing results that could be used for monitoring Pierce's disease by simultaneously considering the disease agent, vectors, and host distribution.

Wagering with an incomplete deck—refining conservation plans for the New Mexico Meadow Jumping Mouse (Zapus luteus luteus)

Abstract Limited sampling for imperiled taxa inhibits effective management by obscuring windows into ecological and evolutionary processes and ultimately thwarting thoughtful conservation efforts. We report eight new locations for the endangered New Mexico Meadow Jumping Mouse (Zapus luteus luteus) detected across three states that expand their known distribution. When combined with existing curated museum records, we develop an ensemble species distribution model to evaluate persistence of populations over the next 50 years. Predicted distributions indicate complex future changes, including regional expansion and the likelihood that half of the designated critical habitat areas will be unsuitable by 2070. Three of the newly discovered populations occur where predicted climate conditions suggest extirpation is likely. Importantly, indices of historical sampling efforts show that recognized and potential distributions are mismatched, highlighting vast areas that have been insufficiently surveyed. Ongoing habitat degradation and climate disruption are projected to synergistically erode genetic diversity across four of the five divergent phylogroups. Considering these combined results, a holistic sampling strategy is needed to more completely document the distribution of jumping mice and facilitate genomic analyses aimed at establishing a roadmap for improving our understanding of geographic variation and adaptive potential. Current management efforts are not only costly, but they are lacking key biological insights, essentially wagering actions with an incomplete deck of cards.

Monitoring spatiotemporal impacts of changes in land surface temperature on near eastern fire salamander (Salamandra infraimmaculata) in the Middle East

Persistence and coexistence of many pond-breeding amphibians depend on seasonality. Temperature, as a seasonal climate component, affects numerous physical and biological processes of pond-breeding amphibians. Satellite-derived land surface temperature (LST) is the radiative skin temperature of the land surface, which has received less attention in spatiotemporal seasonal habitat monitoring. The present study aims to evaluate the increasing and decreasing effects of LST trends at two levels: (1) habitat suitability and connectivity; (2) individual population sites and their longitudinal distribution (with increasing longitude).Habitat suitability modeling was conducted based on an ensemble species distribution model (eSDM). Using electrical circuit theory, the connectivity of interior and intact habitat cores was investigated. An average seasonal LST was prepared separately for each season from 2003 to 2021 and entered into Mann-Kendall (MK) analysis to determine the spatiotemporal effects of LST changes using the Z-Score (ZMK) at two confidence levels of 95 and 99%. Based on the results, in winter, 28.12% and 70.70% of the suitable habitat were affected by an increasing trend of LST at 95% and 99% confidence levels, respectively. The highest spatial overlap of the decreasing trend of LST with the suitable habitat occurred in summer and was 6.4% at the 95% confidence level and 4.2% at the 99% confidence level. Considering population site at 95% confidence interval, the increasing trend of LST was calculated to be 20.2%, 9.5%, 4.2%, and 6.3% of localities in winter, spring, summer, and autumn, respectively. At the 99% confidence level, these percentages reduced to 8.5%, 3.1%, 1%, and 1%, respectively. During winter and summer, based on the results of the longitudinal trend, an increasing trend of LST was observed in sites. Localities of Hatay and Iica village in Turkey experienced seasonally asynchronous climate change regimes. The approach used in this study allowed us to create a link between the life cycle and seasonal changes on a micro-scale (breeding sites) and macro-scale (distribution and connectivity). Findings of this paper can be effectively used by conservation managers to preserve S. infraimmaculata's metapopulation.

Conservation of Chinese Theaceae species under future climate and land use changes

AbstractAimClimate and land use changes are two major pervasive and growing global causes of rapid changes in the distribution patterns of biodiversity, challenging the future effectiveness of protected areas (PAs), which were mainly designed based on a static view of biodiversity. Therefore, evaluating the effectiveness of protected areas for protecting the species threatened by climate and land use change is critical for future biodiversity conservation.LocationChina.MethodsHere, using distributions of 200 Chinese Theaceae species and ensemble species distribution models, we identified species threatened by future climate and land use change (i.e. species with predicted loss of suitable habitat ≥30%) under scenarios incorporating climate change, land use change and dispersal. We then estimate the richness distribution patterns of threatened species and identify priority conservation areas and conservation gaps of the current PA network.ResultsOur results suggest that 36.30%–51.85% of Theaceae species will be threatened by future climate and land use conditions and that although the threatened species are mainly distributed at low latitudes in China under both current and future periods, the mean richness of the threatened species per grid cell will decline by 0.826–3.188 species by the 2070s. Moreover, we found that these priority conservation areas are highly fragmented and that the current PA network only covers 14.21%–20.87% of the ‘areas worth exploring’ and 6.91%–7.91% of the ‘areas worth attention’.Main ConclusionsOur findings highlight the necessity of establishing new protected areas and ecological corridors in priority conservation areas to protect the threatened species. Moreover, our findings also highlight the importance of taking into consideration the potential threatened species under future climate and land use conditions when designating priority areas for biodiversity conservation.

Nesting Habitat Selection and Suitable Breeding Habitat of Blue-Crowned Laughingthrush: Implication on Its Habitat Conservation

Understanding the impact of human disturbance on the breeding habitat selection of endangered species is critical to improving their conservation. Blue-crowned Laughingthrush Pterorhinus courtoisi (Ménégaux, 1923) syn. Garrulax courtoisi (Passeriformes: Leiotrichidae) is an endangered species in China. To explore the nesting habitat selection of the Blue-crowned Laughingthrush and its response to human disturbance during the breeding period, we conducted a field survey at its nesting sites in Wuyuan County and Dexing City, Jiangxi Province, from March to July 2021 and in June 2022. At the home range scale (200 m) the results of a principal component analysis (PCA) showed that this species had a clear preference for infrastructure construction, grassland, farmland and bare land. At the microhabitat scale (12.26 m), we compared the ecological parameters of a nest plot and control plot using a Kruskal–Wallis H test and found that there were significant differences in the vegetation coverage, crown breadth, shrub coverage, herb maximum height, herb average height and herb species number of the nesting area between the two groups. Ensemble species distribution models showed that the suitable habitat of the Blue-crowned Laughingthrush covered an area of 108.63 km2. Distance to waterways, deciduous broadleaved forests and roads were the main factors impacting the habitat distribution of the Blue-crowned Laughingthrush. Our study suggests that (1) it is highly important to improve the protection of breeding sites and suitable living areas close to the settlements and preserve a certain nesting habitat selection space for the Blue-crowned Laughingthrush during the breeding period; and (2) it is necessary to continue to monitor the potential suitable breeding habitat. This study provides a scientific basis for the protection of the Blue-crowned Laughingthrush by local forestry bureaus and conservation departments in the future.

Change in habitat suitability of the invasive Snowflake coral (Carijoa riisei) during climate change: An ensemble modelling approach

Global species range dynamics are intrinsically influenced by the interplay between human activities and climate compatibility. Snowflake coral (Carijoa riisei) is a soft octacoral species that belongs to the family Clavulariidae and can rapidly grow to colonise new habitats. This species has successfully colonised numerous habitats, displacing native species and disrupting the ecological balance in the introduced habitats. Recent investigations into species invasions in aquatic ecosystems suggest that anthropogenic activities and climate change will accelerate the introduction, establishment, and spread of invasive species to new habitats. In this study, we utilised ensemble species distribution modelling to investigate shifts in the invasive potential of Snowflake coral in current and future climatic settings on a global scale. Future distribution was forecasted using four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0, and 8.5) across two periods (2040–2050 and 2090–2100). The results accurately predicted the known distributional range of the species. Temperature, distance to the port, and bathymetry were identified as the three most significant predictor variables. The low and medium habitat suitability regions increased in all scenarios and periods. In the high habitat suitability category, only RCP 4.5 and RCP 6.0 in the 2090–2100 period exhibited an increase in percentage area. Under the worst-case climate scenario, RCP 8.5 (2090–2100), the high-suitability regions displayed a surprising decline in area percentage, which can be attributed to the temperature thresholds of the species. Our findings indicate that the species has a greater potential to spread under current climatic conditions than previously reported, and its expansion may further accelerate in the future. This highlights the urgent need for more intensive surveys employing advanced detection tools and the implementation of proactive management measures to protect vulnerable ecosystems that could be impacted by this species.

Host, environment, and anthropogenic factors drive landscape dynamics of an environmentally transmitted pathogen: Sarcoptic mange in the bare-nosed wombat.

Understanding the spatial dynamics and drivers of wildlife pathogens is constrained by sampling logistics, with implications for advancing the field of landscape epidemiology and targeted allocation of management resources. However, visually apparent wildlife diseases, when combined with remote-surveillance and distribution modelling technologies, present an opportunity to overcome this landscape-scale problem. Here, we investigated dynamics and drivers of landscape-scale wildlife disease, using clinical signs of sarcoptic mange (caused by Sarcoptes scabiei) in its bare-nosed wombat (BNW; Vombatus ursinus) host. We used 53,089 camera-trap observations from over 3261 locations across the 68,401 km2 area of Tasmania, Australia, combined with landscape data and ensemble species distribution modelling (SDM). We investigated: (1) landscape variables predicted to drive habitat suitability of the host; (2) host and landscape variables associated with clinical signs of disease in the host; and (3) predicted locations and environmental conditions at greatest risk of disease occurrence, including some Bass Strait islands where BNW translocations are proposed. We showed that the Tasmanian landscape, and ecosystems therein, are nearly ubiquitously suited to BNWs. Only high mean annual precipitation reduced habitat suitability for the host. In contrast, clinical signs of sarcoptic mange disease in BNWs were widespread, but heterogeneously distributed across the landscape. Mange (which is environmentally transmitted in BNWs) was most likely to be observed in areas of increased host habitat suitability, lower annual precipitation, near sources of freshwater and where topographic roughness was minimal (e.g. human modified landscapes, such as farmland and intensive land-use areas, shrub and grass lands). Thus, a confluence of host, environmental and anthropogenic variables appear to influence the risk of environmental transmission of S. scabiei. We identified that the Bass Strait Islands are highly suitable for BNWs and predicted a mix of high and low suitability for the pathogen. This study is the largest spatial assessment of sarcoptic mange in any host species, and advances understanding of the landscape epidemiology of environmentally transmitted S. scabiei. This research illustrates how host-pathogen co-suitability can be useful for allocating management resources in the landscape.

Dramatic loss of seagrass Zostera marina L. suitable habitat under projected climate change in coastal areas of the Bohai Sea and Shandong peninsula, China

Seagrass is an important foundational species in marine ecosystems that plays an important role in providing ecosystem services. However, seagrass distribution and suitable habitat have rapidly declined in recent decades because of climate change and human-mediated disturbances. To achieved better conservation and management of the seagrass Zostera marina, an important representative seagrass in northern China, studies must investigate how this species responds to climate change. Here, we used an ensemble species distribution model to forecast the potential distribution and future suitable habitat change for the eelgrass Z. marina in coastal areas of the Bohai Sea and Shandong Peninsula, China. Two future climate scenarios, RCP 4.5 and RCP 8.5, were considered, which represent stable and high levels of greenhouse gas emissions, respectively. The ensemble model accurately predicted the current Z. marina distribution and performed better than the single-algorithm methods of random forest, generalized boosting model and maximum entropy according to performance matrices (AUC and TSS). The distance to land (78.50 ± 3.51%) and the maximum sea surface temperature (11.90 ± 0.25%) were the most important variables determining the distribution of Z. marina, while the contributions of other variables, maximum sea surface current velocity (3.80 ± 0.33%), minimum surface salinity (2.15 ± 0.22%) and water depth (1.74 ± 0.24%) were relatively low. Under future climate scenarios, the suitable habitat of Z. marina was predicted to decrease by more than half by the 2050s, whereas under the pessimistic greenhouse gas emission scenario (RCP 8.5), suitable Z. marina habitat was predicted to decrease by nearly 80% by the end of this century. The loss of Z. marina seagrass beds will have important ecological effects on the marine ecosystem. Our results not only provide valuable information to assist in identifying potential Z. marina meadows, but also have important implications for guiding conservation and management of Z. marina in the northern coastal region of China.

Not the expected poleward migration: Impact of climate change scenarios on the distribution of two endemic evergreen broad-leaved Quercus species in China

One of the key strategies for species to respond to climate change is range shift. It is commonly believed that species will migrate towards the poles and higher elevations due to climate change. However, some species may also shift in opposite directions (i.e., equatorward) to adapt to changes in other climatic variables beyond climatic isotherms. In this study, we focused on two evergreen broad-leaved Quercus species endemic to China and used ensemble species distribution models to project their potential distribution shifts and extinction risk under two shared socioeconomic pathways of six general circulation models for the years 2050 and 2070. We also investigated the relative importance of each climatic variable in explaining range shifts of these two species. Our findings indicate a sharp reduction in the habitat suitability for both species. Q. baronii and Q. dolicholepis are projected to experience severe range contractions, losing over 30 % and 100 % of their suitable habitats under SSP585 in the 2070s, respectively. Under the assumption of universal migration in future climate scenarios, Q. baronii is expected to move towards the northwest (~105 km), southwest (~73 km), and high elevation (180–270 m). The range shifts of both species are driven by temperature and precipitation variables, not only annual mean temperature. Specifically, precipitation seasonality and temperature annual range were the most crucial environmental variables, causing the contraction and expansion of Q. baronii and contraction of Q. dolicholepis, respectively. Our results highlight the importance of considering additional climatic variables beyond the annual mean temperature to explain species range shifts in multiple directions.

Predicting potential distribution and range dynamics of Aquilegia fragrans under climate change: insights from ensemble species distribution modelling.

Climate change is one of the primary causes of species redistribution and biodiversity loss, especially for threatened and endemic important plant species. Therefore, it is vital to comprehend "how" and "where" priority medicinal and aromatic plants (MAPs) might be effectively used to address conservation-related issues under rapid climate change. In the present study, an ensemble modelling approach was used to investigate the present and future distribution patterns of Aquilegia fragrans Benth. under climate change in the entire spectrum of Himalayan biodiversity hotspot. The results of the current study revealed that, under current climatic conditions, the northwest states of India (Jammu and Kashmir, Himachal Pradesh and the northern part of Uttarakhand), the eastern and southern parts of Pakistan Himalaya have highly suitable climatic conditions for the growth of A. fragrans. The ensemble model exhibited high forecast accuracy, with temperature seasonality and precipitation seasonality as the main climatic variables responsible for the distribution of the A. fragrans in the biodiversity hotspot. Furthermore, the study predicted that future climate change scenarios will diminish habitat suitability for the species by -46.9% under RCP4.5 2050 and -55.0% under RCP4.5 2070. Likewise, under RCP8.5, the habitat suitability will decrease by -51.7% in 2050 and -94.3% in 2070. The current study also revealed that the western Himalayan area will show the most habitat loss. Some currently unsuitable regions, such as the northern Himalayan regions of Pakistan, will become more suitable under climate change scenarios. Hopefully, the current approach may provide a robust technique and showcases a model with learnings for predicting cultivation hotspots and developing scientifically sound conservation plans for this endangered medicinal plant in the Himalayan biodiversity hotspot.

Use of Ensemble Model for Modeling the Larval Fish Habitats of Different Ecological Guilds in the Yangtze Estuary

Estuaries provide nursery habitats for a variety of fish species of different ecological guilds and have complicated environmental conditions. In this study, we applied ensemble species distribution models (SDMs) to four abundant and different ecological guild larval fish species (Hemiculter bleekeri (freshwater guild), Pseudolaubuca sinensis (freshwater guild), Coilia mystus (brackish water guild), and Engraulis japonicus (marine guild)) to explore their suitable habitats and the fish–habitat relationships in the Yangtze Estuary. The results showed that random forest (RF) demonstrated the best performance in all single algorithms and the surface range envelop (SRE) model was scarcely accurate. The ensemble SDMs demonstrated a superior predictive ability compared with any single algorithm, with the true skill statistic (TSS) and the area under the receiver operating characteristic curve (AUC) scores being above 0.899 and 0.641, respectively. Binary presence–absence maps showed the different spatial distribution patterns of the four species. We primarily found the freshwater species (P. sinensis and H. bleekeri) present in the South Branch (west of 122° E), whereas we found the marine species (E. japonicus) anywhere except inside the South Branch (west of 121.8° E). The area for P. sinensis (1615.93 km2) was relatively larger than that for H. bleekeri (1136.87 km2). We predicted that the brackish water species (C. mystus) would most likely be present inside the North Branch (west of 122° E), Eastern Chongming, and outside the South Branch (east of 121.8° E). Salinity, as a key environmental variable, contributed to the spatial variability. A low salinity (sea surface salinity (SSS) < 3) was beneficial for P. sinensis and H. bleekeri but was not suitable for E. japonicus. The SSS suitable range for C. mystus was 5–10 and 12–20. Multiple ecological guild species dwelled in the confluence of salt and fresh water. Our results will play an important role in the design of specific conservation strategies for fishery resources in this area.

Distribution update of water deer (Hydropotes inermis) and prediction of their potential distribution in Northeast China

Human interventions have a great potential of spatially cornering and limiting species, therefore investigating the species distribution is one of the most crucial issues for managing wildlife populations and suggesting robust conservation strategies. Water deer (Hydropotes inermis) are widespread in China throughout history and are endemic to East Asia. However, they disappeared from Northeast China for years. We rediscovered the water deer in a previous study in Jilin Province, China. Then, we conducted further research in Northeast China to determine their distribution status, supplying fundamental data for the recovery and expansion of their population. An interview survey, line transect survey and infrared camera monitoring were carried out in some counties/cities in Northeast China from June to December 2021. The results showed that the water deer were distributed in Wuchang city of Heilongjiang Province, Changbai Korean Autonomous County, Baishan Municipal District, Ji’an city, Hunchun city, Huadian city, Antu County and Helong County of Jilin Province, Benxi Manchu Autonomous County, Huanren Manchu Autonomous County, Kuandian Manchu Autonomous County, Fengcheng city and Donggang city of Liaoning Province. The ensemble species distribution model constructed by sdm within the TSS of various models that were set as weight revealed that the potential distribution area of the water deer in the study area was 8764.66 km2 (28.77% of the study area). Combining recent studies concerning the distribution of water deer and the current study, we updated the distribution of wild water deer in Northeast China, which is vital for their conservation worldwide.

Predicting the Habitat Suitability for Angelica gigas Medicinal Herb Using an Ensemble Species Distribution Model

The distribution shift of forest species due to the fact of climate change may negatively affect ecosystem services including the production of medicinal resources. Climate change impact assessments of habitat range changes are essential to sustainably manage forest resources. A change in the habitat suitability due to the fact of climate change was predicted for Angelica gigas, which has high economic value among forest medicinal resources in South Korea. The habitat suitability was predicted by an ensemble species distribution model that combined the results of nine single algorithm models using the committee averaging method. A total 168 occurrence data and 10 environmental variables were used for the single algorithm models. The area under the receiver operation characteristic curve (AUC) and true skill statistic (TSS) were applied to evaluate the models’ performance, and the contribution of the environmental variables was calculated as an important value for each single algorithm model. Climate change scenarios were projected to predict future habitat suitability. The future suitable habitat for A. gigas was gradually reduced to the high mountain regions of the eastern part of South Korea regardless of the climate change scenarios. The main environmental variable was the annual mean temperature, and the rise in temperature due to the fact of climate change was found to have a negative effect on the habitat suitability for A. gigas. The decline in the habitat suitability for A. gigas, a major forest medicinal resource, is expected to result in the reduction in its production. Therefore, it is required to establish adaptation measures to mitigate the negative impact of this decrease, such as protecting the natural habitats of A. gigas.

How future climate and tree distribution changes shape the biodiversity of macrofungi across Europe

AbstractAimClimate change is affecting biodiversity at an accelerating rate. Despite the importance of fungi in ecosystems in general, and in the global carbon and nitrogen cycle in particular, there is little research on the response of fungi to climate change compared with plants and animals. Earlier studies show that climatic factors and tree species are key determinants of macrofungal diversity and distribution at large spatial scales. However, our knowledge of how climate change will affect macrofungal diversity and distribution in the future remains poorly understood.LocationEurope.MethodsUsing openly available occurrence data of 1845 macrofungal species from eight European countries (i.e. Norway, Sweden, Finland, Denmark, Netherlands, Germany, France and Spain), we built ensemble species distribution models to predict macrofungal response to climate change alone and combined climate and tree distribution change under the IPCC special report on 2080 emissions scenarios (SRES A2 and B2).ResultsConsidering climate change alone, we predict that about 77% (74.1%–80.7%) of the modelled species will expand their distribution range, and around 57% (56.1%–58.4%) of the modelled area will have an increase in macrofungal species richness. However, when considering the combined climate and tree species distribution change, only 50% (50%–50.9%) of the species are predicted to expand their distribution range and 49% (47.4%–51.1%) of the modelled area will experience an increase in macrofungal species richness.Main ConclusionsOverall, our models projected that large areas would exhibit increased macrofungal species richness under future climate change. However, tree species distribution might play a restrictive role in the future distributional shifts of macrofungi. In addition, macrofungal responses appear heterogeneous, varying among species and regions. Our findings highlight the importance of including tree species in the projection of climate change impacts on the macrofungal diversity and distribution on a continental scale.

Current and Future Habitat Suitability Models for Four Ticks of Medical Concern in Illinois, USA.

The greater U.S. Midwest is on the leading edge of tick and tick-borne disease (TBD) expansion, with tick and TBD encroachment into Illinois occurring from both the northern and the southern regions. To assess the historical and future habitat suitability of four ticks of medical concern within the state, we fit individual and mean-weighted ensemble species distribution models for Ixodes scapularis, Amblyomma americanum, Dermacentor variabilis, and a newly invading species, Amblyomma maculatum using a variety of landscape and mean climate variables for the periods of 1970-2000, 2041-2060, and 2061-2080. Ensemble model projections for the historical climate were consistent with known distributions of each species but predicted the habitat suitability of A. maculatum to be much greater throughout Illinois than what known distributions demonstrate. The presence of forests and wetlands were the most important landcover classes predicting the occurrence of all tick species. As the climate warmed, the expected distribution of all species became strongly responsive to precipitation and temperature variables, particularly precipitation of the warmest quarter and mean diurnal range, as well as proximity to forest cover and water sources. The suitable habitat for I. scapularis, A. americanum, and A. maculatum was predicted to significantly narrow in the 2050 climate scenario and then increase more broadly statewide in the 2070 scenario but at reduced likelihoods. Predicting where ticks may invade and concentrate as the climate changes will be important to anticipate, prevent, and treat TBD in Illinois.

Machine learning ensemble species distribution modeling of an endangered arid land tree Tecomella undulata: a global appraisal

Machine learning ensemble species distribution modeling of an endangered arid land tree Tecomella undulata: a global appraisal

Distribution of important medicinal plant species in Nepal under past, present, and future climatic conditions

Climate change is causing shifts in the habitat, distribution, ecology, and phenology of Himalayan plants. These changes are predicted to continue, jeopardizing the survival of medicinal plant species and local livelihoods that rely on them. We analyzed the present and future diversity and distribution of medicinal plant species influenced by different climate change scenarios, and calculated the climatic niche of the species using ensemble species distribution modeling (eSDM). We compiled 1041 (N) geospatial data of seven high-value medicinal plant species of Nepal: Aconitum spicatum (n = 100), Allium wallichii (n = 151), Bergenia ciliata (n = 48), Nardostachys jatamansi (n = 121), Neopicrorhiza scrophulariiflora (n = 94), Paris polyphylla (n = 310) and Valeriana jatamansi (n = 217) including over 85 % from field surveys and the rest from literature and online database. We used bioclimatic variables from Models for Interdisciplinary Research on Climate (MIROC) of version MIROC6, and selected Shared Socioeconomic Pathways (SSP)2-4.5 and SSP5-8.5 for the year of 2050 and 2070 for modeling. We found elevation, mean diurnal and annual temperature ranges (BIO2 and BIO7), and precipitation of warmest and coldest quarters (BIO18 and BIO19) to be the most high weight cofactors for projecting the future potential distribution of high-value medicinal plants in Nepal. Results showed that the suitable range of distribution for high-value medicinal plants would increase and concentrate in mountainous areas of central Nepal, but decline in (sub)tropical and temperate areas, suggesting both in-situ and ex-situ conservation practices, respectively.

Robust identification of potential habitats of a rare demersal species (blackspot seabream) in the Northeast Atlantic

Species distribution models (SDM) are commonly used to identify potential habitats. When fitting them to heterogeneous, opportunistically collated presence/absence data, imbalance in the number of presence and absence observations often occurs, which could influence results. To robustly identify potential habitats for blackspot seabream (Pagellus bogaraveo) throughout its distribution area in the Northeast Atlantic and the western Mediterranean Sea, we used an ensemble species distribution modelling (eSDM) approach, modelling gridded presence–absence data with environmental predictors for two types of occurrence data sets. The first data set displayed the observed unbalanced spatially heterogeneous presence/absence ratio and the second a balanced presence/absence ratio. The data covered the full distribution area, including the European Atlantic shelf, the Azorean region and the Western Mediterranean Sea. Across these regions, populations display variable status. The main environmental predictors for potential habitats were bathymetry and annual maximum SST. The fitted ensemble compromise (eSDM) was projected over the whole grid to create a habitat suitability map. This map exhibited higher probabilities of presence for the balanced-ratio data set. A binary presence–absence map was then generated using optimized presence probability thresholds for four validation indices. Using the true skill statistic to optimize the threshold, the surface areas of the binary presence–absence map was 53% smaller for the balanced data set than for the observed unbalanced data set. However, the choice of validation index had an even greater impact (up to 15 000%). This indicates that studies using opportunistic data for SDM fitting need to pay attention to the effects of presence/absence data imbalance and the choice of validation index to fully evaluate uncertainty.