Ensemble Species Distribution Models Research Articles

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.

Coastal Melaleuca wetlands under future climate and sea-level rise scenarios in the Mekong Delta, Vietnam: vulnerability and conservation

Melaleuca wetland ecosystems play crucial roles in ecology and human livelihood, yet the ecosystems are vulnerable to climate change and relative sea-level rise (SLR) impacts. Documents and research on climate change and SLR impacts on coastal Melaleuca wetlands in the Mekong Delta, Vietnam, are currently limited. Therefore, the present study aimed to identify changes in habitat suitability for a coastal Melaleuca wetland species in response to different future climate change and SLR scenarios, in the West Sea of the Mekong Delta, with the aid of an ensemble species distribution model (SDM) and the Sea Level Affecting Marshes Model (SLAMM). Melaleuca species occurrence records, bioclimatic and eco-physiological variables were utilized to predict potential distribution of the species in response to current and future climate scenarios (i.e. RCP4.5 and 8.5) for the year 2070. Wetland maps for 2020, a digital elevation model (DEM) and localized site-specific parameters (i.e. historic trend of SLR, erosion, subsidence and overwash) were utilized as input data for SLAMM to simulate spatial distribution of Melaleuca/forested wetlands under the two SLR scenarios. The final habitat suitability for the Melaleuca wetland species was identified based on these two resultant datasets, climatic suitability and spatial distribution of the wetlands. Simulated results suggested mean losses in suitable habitat of 29.8% and 58.7% for stable and subsidence scenarios, respectively, for the year 2070 in comparison to the baseline scenario. SLR combined with considerable subsidence rate was suggested as one of the main drivers responsible for the habitat suitability loss. The findings obtained from the current work are useful sources for planning conservation areas for the Melaleuca wetlands, to protect and preserve the ecosystems and their important services under future climate and SLR scenarios.

Designing a large-scale track-based monitoring program to detect changes in species distributions in arid Australia.

Monitoring trends in animal populations in arid regions is challenging due to remoteness and low population densities. However, detecting species' tracks or signs is an effective survey technique for monitoring population trends across large spatial and temporal scales. In this study, we developed a simulation framework to evaluate the performance of alternative track-based monitoring designs at detecting change in species distributions in arid Australia. We collated presence-absence records from 550 2-ha track-based plots for 11 vertebrates over 13years and fitted ensemble species distribution models to predict occupancy in 2018. We simulated plausible changes in species' distributions over the next 15years and, with estimates of detectability, simulated monitoring to evaluate the statistical power of three alternative monitoring scenarios: (1) where surveys were restricted to existing 2-ha plots, (2) where surveys were optimized to target all species equally, and (3) where surveys were optimized to target two species of conservation concern. Across all monitoring designs and scenarios, we found that power was higher when detecting increasing occupancy trends compared to decreasing trends owing to the relatively low levels of initial occupancy. Our results suggest that surveying 200 of the existing plots annually (with a small subset resurveyed twice within a year) will have at least an 80% chance of detecting 30% declines in occupancy for four of the five invasive species modeled and one of the six native species. This increased to 10 of the 11 species assuming larger (50%) declines. When plots were positioned to target all species equally, power improved slightly for most compared to the existing survey network. When plots were positioned to target two species of conservation concern (crest-tailed mulgara and dusky hopping mouse), power to detect 30% declines increased by 29% and 31% for these species, respectively, at the cost of reduced power for the remaining species. The effect of varying survey frequency depended on its trade-off with the number of sites sampled and requires further consideration. Nonetheless, our research suggests that track-based surveying is an effective and logistically feasible approach to monitoring broad-scale occupancy trends in desert species with both widespread and restricted distributions.

Habitat suitability and connectivity modeling predict genetic population structure and priority control areas for invasive nutria (Myocastor coypus) in a temperate river basin.

The nutria (Myocastor coypus), also known as the coypu, is a semi-aquatic, invasive rodent native to South America that causes damage to natural riverine and wetland habitats in many parts of the world, including South Korea. Understanding habitat use, connectivity, and gene flow of nutria populations is critical for the sound management of local and regional ecosystems. Here, we assessed habitat suitability and connectivity in relation to the genetic structure of nutria populations in the Nakdong River Basin of South Korea. A total of 321 nutria occurrence sites and seven environmental variables were used to perform ensemble habitat suitability modeling using five species distribution models (SDMs), including boosted regression trees, maximum entropy model, random forest, generalized linear model, and multivariate adaptive regression splines. Using graph and circuit theory approaches, we assessed the population gene flow and current flow betweenness centrality (CFBC) of suitable habitats derived from the ensemble SDM. All SDMs performed well with a range of test AUC values from 0.962 to 0.970 (mean = 0.966) with true skill statistic values over 0.8. The minimum temperature of the coldest month, mean temperature of the warmest quarter, precipitation of the driest quarter, and distance from water bodies were important predictors in nutria habitat modeling. Nutria population gene flow was significantly correlated with the least-cost path distance on a cost resistance surface based on ensemble habitat suitability modeling and roads (Mantel's r = 0.60, p < 0.05). Finally, the CFBC positively correlated with the genetic diversity of nutria populations was used to identify priority control areas. Habitat suitability and connectivity modeling not only revealed environmental conditions and areas that support the survival and spread of nutrias, but also improved our understanding of the animals' genetic population structure, thereby indicating priority areas to target for eradication.

Climatic Variability Caused by Topographic Barrier Prevents the Northward Spread of Invasive Ageratina adenophora.

Ageratina adenophora (Spreng.) R.M.King & H.Rob. is one of the most threatening invasive alien plants in China. Since its initial invasion into Yunnan in the 1940s, it spread rapidly northward to southern Mount Nyba in Sichuan, which lies on the eastern edge of the Qinghai-Tibet Plateau. During fieldwork, we found an interesting phenomenon: A. adenophora failed to expand northward across Mount Nyba, even after the opening of the 10 km tunnel, which could have served as a potential corridor for its spread. In this work, to explore the key factors influencing its distribution and spread patterns, we used a combination of ensemble species distribution models with the MigClim model. We found that the temperature annual range (TAR), precipitation of driest month (PDM), highway density (HW), and wind speed (WS) were the most predominant factors affecting its distribution. The north of Mount Nyba is not suitable for A. adenophora survival due to higher TAR. The spatial-temporal dynamic invasion simulation using MigClim further illustrated that the northward invasion of A. adenophora was stopped by Mount Nyba. Overall, Mount Nyba may act as a topographic barrier that causes environmental differences between its south and north sides, preventing the northward invasion of A. adenophora. However, other suitable habitats on the northern side of the mountain still face challenges because A. adenophora is likely to invade via other routes. Therefore, long-term monitoring is needed to prevent human-induced long-distance spread events.

Aridity could have driven the local extinction of a common and multivoltine butterfly

AbstractIdentifying which species are being negatively impacted by climate change and the mechanisms driving their decline is essential to effectively protect biodiversity.Coenonympha pamphilusis a common and generalist butterfly, widely distributed throughout the Western Palearctic, being multivoltine in southern Europe. Previous studies indicate that it will not be substantially affected by climate change; however, it has seemingly disappeared from the southeast of the Iberian Peninsula in the last decades.Here, we aim to determine if it has effectively disappeared from this area, as well as identify the environmental conditions limiting its distribution and the potential causes behind this a priori local extinction.We downloaded all the occurrence records ofC. pamphilusand analysed their spatial and temporal trends. To identify the climatic variables driving the distribution of this butterfly in the Iberian Peninsula, we performed an ensemble species distribution model (SDM), combining 600 individual models produced with 6 algorithms.We confirmed thatC. pamphilushas not been observed in the southeast of the Iberian Peninsula since 2008. Aridity was the main factor limiting the distribution ofC. pamphilusin our ensemble SDM, with areas with high aridity being unsuitable for this species.We hypothesise that multivoltinism is the mechanism driving this local extirpation, as high aridity is causing host plants (Poaceae) to wither prematurely, precluding the development of the second and/or third generations of the butterfly. Even though generalist species are theoretically more resilient to climate change, other traits such as multivoltinism may increase their vulnerability and need to be further investigated.

Bat dynamics modelling as a tool for conservation management in subterranean environments.

Bat species inhabit subterranean environments (e.g., caves and mines) in small areas with specific microclimatic conditions, during various periods of their life cycle. Bats can be negatively influenced by microclimatic changes within their roosts if optimal habitat patches become unavailable. Therefore, proper management solutions must be applied for the conservation of vulnerable bat populations, especially in show caves. We have pursued an ensemble species distribution modelling approach in subterranean environments to identify sensible patches for bats. Using multi-annual temperature monitoring and bat distribution surveys performed within ten caves and mines, including show caves, we modelled relevant habitat patches for five bat species. The temperature-based variables generated from this approach proved to be effective when processed via species distribution models, which generated optimal validation results, even for bats that were heavily clustered in colonies. Management measures are proposed for each show cave to help in long-time conservation of hibernation and maternity colonies. These measures include creating suitable microclimatic patches within the caves by ecological reconstruction measures, tourist management practices in relation to bats, and show cave fitting recommendations. This approach has never been performed at this scale due to the complex geostatistical challenges involving subterranean environment mapping and can be further used as best practice guidelines for future conservation projects.