Changes In Habitat Suitability Research Articles

Species Distribution Modeling of Ixodes ricinus (Linnaeus, 1758) Under Current and Future Climates, with a Special Focus on Latvia and Ukraine

This study assesses the impact of climate change on the distribution of Ixodes ricinus, which transmits Lyme disease, a growing public health concern. Utilizing ensemble models from the R package ‘flexsdm’ and climate data from WorldClim, ENVIREM, and CliMond, we project habitat suitability changes for the focus species. The models, validated against Lyme disease incidence rates, predict a 1.5-fold increase in suitable habitats in Latvia, contrasted with a 4.5-fold decrease in suitable habitats within Ukraine over the coming decades. SHAP values are analyzed to determine the most influential climatic features affecting tick distribution, providing insights for future vector control and disease prevention strategies. The optimal bioclimatic environment for I. ricinus seems to be an intricate balance of moderate temperatures, high humidity, and sufficient rainfall (bio7, 14, 18, 29). Also, radiation during the wettest quarter (bio24) significantly influences tick distribution in northern countries. This implies an increased presence of ticks in Scandinavian countries, Baltic states, etc. These findings largely coincide with our projections regarding bioclimatic suitability for ticks in Latvia and Ukraine. These shifts reflect broader patterns of vector redistribution driven by global warming, highlighting the urgent need to adapt public health planning to the evolving landscape of vector-borne diseases under climate change.

Spatio-temporal analysis of habitat suitability for the endangered oriental white stork (Ciconia boyciana) in the wetland ecosystem of northeast China

Human-induced habitat transformation often leads to habitat degradation and loss, impacting suitable habitats for endangered and rare species. This study was conducted to assess suitable habitats for the endangered oriental white stork in the wetland ecosystem of northeast China, to facilitate successful species-habitat conservation. The study incorporated field surveys, literature reviews, vegetation index calculations, eDNA for assessing prey abundance and land use and land cover classification for the years 2000, 2011, and 2022. A fuzzy logic-based habitat model was developed to map suitable habitats for the oriental stork. Generalized Linear Models (GLM) and Principal Component Analysis (PCA) were used to assess the influence of various environmental variables on habitat suitability changes. Roosting locations of the oriental stork were used as reference points to evaluate the impact of environmental factors on habitat suitability. The results indicate that 20% of the area is highly suitable for the stork, 73.4% is moderately suitable, and 5.6% is less or not suitable. Habitats near lakes and rivers, with low Normalized Difference Vegetation Index (NDVI) and high Normalized Difference Water Index (NDWI), are more suitable compared to areas close to roads and built-up zones. Prey abundance, particularly fish, is a crucial determinant of oriental stork presence and survival. Marshlands, swamps, and water bodies were identified as the most suitable habitats, as they interface with lotic and lentic ecosystems providing abundant prey for the storks. Our findings emphasize the importance of ongoing efforts to protect wetland ecosystems and habitats for endangered and rare bird species. Priority should be given to habitats identified as critical roosting areas for the oriental stork.

Assessing puma habitat suitability in Uruguay’s Grasslands: exploring source-sink dynamics and conservation implications

ABSTRACT Pumas (Puma concolor) have a broad geographic range across the Americas and are globally listed as Least Concern. However, in Uruguay’s Pampas Grasslands, they are considered Data Deficient and regionally endangered in Argentina and Brazil. Understanding the distribution and population status of pumas is crucial for their conservation. This study examines puma occurrence in Uruguay’s Grasslands within a regional context, assessing habitat suitability and recent land use changes. Using a Species Distribution Model (SDM) in MaxEnt with 224 occurrence records (1999–2011) and bioclimatic and topographic predictors, we found intermediate habitat suitability in the Pampas Grasslands, indicating a naturally sparse puma population. The highest suitability was along riverbanks and riparian areas. Recent land use changes have transformed suitable habitats into areas less likely to support pumas, affecting a significant portion of Uruguay’s land. Our results suggest source-sink dynamics, where Uruguayan puma records likely represent dispersing individuals from established subpopulations in Eastern Argentina and Southern Brazil.

Predicting the potential habitat suitability of Saussurea species in China under future climate scenarios using the optimized Maximum Entropy (MaxEnt) model

The Saussurea species, renowned for its biodiversity and medicinal significance in high-elevation regions, faces endangerment due to climate change and human activities. Despite this, conservation research on Saussurea has been limited. To fill the knowledge gap, this study employed the optimized MaxEnt model to simulate Saussurea's habitat suitability and analyze key environmental factors influencing its distribution. Additionally, considering the sensitivity of Saussurea habitats to climate change, this research also simulated the changes in suitable habitat and distribution centroid shifts of Saussurea under different climate scenarios (SSP126, SSP245, SSP370, and SSP585) for the periods 2040s, 2060s, 2080s and 2100s. Findings indicated that Saussurea's suitable habitat was primarily located in the Qinghai-Tibet Plateau, notably within the Himalayas and Hengduan Mountains. The areas of extremely and moderately suitable habitats were 1.106 × 10⁵ km2 and 3.436 × 10⁵ km2, respectively. Elevation, Isothermality (Bio3), and Temperature Annual Range (Bio7) were identified as the main environmental factors. Future projections suggest severe habitat fragmentation and a decrease in suitable habitat areas. By 2100, the total area of suitable Saussurea habitat will decrease under the SSP126, SSP245, SSP370, and SSP585 scenarios to 8.658 × 10⁵ km2, 6.971 × 10⁵ km2, 5.811 × 10⁵ km2, and 5.979 × 10⁵ km2, respectively. Additionally, a slight southeastward shift in the distribution centroid was observed. This study is expected to provide guidance for the conservation of Saussurea and alpine plant biodiversity.

Predicting the Impact of Climate Change on the Selection of Reintroduction Sites for the South China Tiger (Panthera tigris amoyensis) in China.

The South China tiger (Panthera tigris amoyensis) is a tiger subspecies unique to China and one of the top ten endangered species in the world. It used to play an important role in the overall function of the ecosystem. This study rationally screened out key prey species of the South China tiger-the Chinese serow, Chinese goral, tufted deer, water deer, Chinese muntjac, red muntjac, sambar deer, and wild boar. Candidate sites for the rewilding and reintroduction of the South China tiger were derived by exploring changes in suitable habitats for the prey using the MaxEnt model. The results show that: (1) by 2070, except for the high-suitability areas of water deer and Chinese muntjac, the areas of suitable habitats for the other six prey species would all have decreased significantly; (2) the location of the high-suitability area of the South China tiger obtained by superimposing the suitable areas of the eight prey species would be almost stable in 2050 and 2070, but the habitat index of some high- and medium-suitability areas would decrease and turn into low-suitability areas; (3) the core candidate sites were 83,415 km2 in total, of which 25,630 km2 overlapped with existing protected areas, accounting for 30.7% of the core candidate sites, and the remaining 69.3% of the core candidate sites were mostly distributed around the protected areas; (4) the maximum core candidate site area was projected to be 10,000 km2 by 2070, which could support a small population of 23 male tigers and 66 female tigers to survive and reproduce in the wild. This study revealed the core candidate sites for the rewilding of South China tigers and estimated the number of tigers that could be reintroduced to these areas, providing a preliminary research basis for promoting the rewilding of South China tigers in China.

Unveiling Wheat’s Future Amidst Climate Change in the Central Ethiopia Region

Quantifying how climatic change affects wheat production, and accurately predicting its potential distributions in the face of future climate, are highly important for ensuring food security in Ethiopia. This study leverages advanced machine learning algorithms including Random Forest, Maxent, Boosted Regression Tree, and Generalised Linear Model alongside an ensemble approach to accurately predict shifts in wheat habitat suitability in the Central Ethiopia Region over the upcoming decades. An extensive dataset consisting of 19 bioclimatic variables (Bio1–Bio19), elevation, solar radiation, and topographic positioning index was refined by excluding collinear predictors to increase model accuracy. The analysis revealed that the precipitation of the wettest month, minimum temperature of the coldest month, temperature seasonality, and precipitation of the coldest quarter are the most influential factors, which collectively account for a significant proportion of habitat suitability changes. The future projections revealed that up to 100% of the regions currently classified as moderately or highly suitable for wheat could become unsuitable by 2050, 2070, and 2090, illustrating a dramatic potential decline in wheat production. Generally, the future of wheat cultivation will depend heavily on developing varieties that can thrive under altered conditions; thus, immediate and informed action is needed to safeguard the food security of the region.

Differential impact of climate and land use change on habitat suitability of migrant passerines according to habitat preferences

Our study contributes to the ongoing dialogue on the impact of climate and habitat changes on migratory bird species, particularly focusing on how these effects vary based on species’ habitat preferences. We used citizen science data for 22 African-Eurasian migratory bird species and categorized them into five groups based on habitat preferences, following the classification methodology of Atkinson et al. (2014). Using ensemble species distribution modeling (SDM), we projected changes in potentially suitable habitats across Africa from 2040 to 2100 under contrasting climate and land use scenarios. Our results indicate a differential impact of climate and land use changes on habitat suitability, with species preferring habitats with shrubs and trees being the most vulnerable. Conversely, other group species, such as open country-grassland and farmland birds could experience a significant increase in suitable habitat. We anticipate a profound change in habitat suitability, with the western part of South Africa becoming unsuitable for most species, while an increase in suitable habitat is expected in the Sahel. Bioclimatic rather than land use variables emerged as the primary drivers of these changes. The extent of change in habitat suitability will be strongly influenced by the Shared Socio-economic Pathways followed by human societies.

Traversing the land-sea interface: A climate change risk assessment of terrestrially breeding marine predators.

Terrestrially breeding marine predators have experienced shifts in species distribution, prey availability, breeding phenology, and population dynamics due to climate change worldwide. These central-place foragers are restricted within proximity of their breeding colonies during the breeding season, making them highly susceptible to any changes in both marine and terrestrial environments. While ecologists have developed risk assessments to evaluate climate risk in various contexts, these often overlook critical breeding biology data. To address this knowledge gap, we developed a trait-based risk assessment framework, focusing on the breeding season and applying it to marine predators breeding in parts of Australian territory and Antarctica. Our objectives were to quantify climate change risk, identify specific threats, and establish an adaptable assessment framework. The assessment considered 25 criteria related to three risk components: vulnerability, exposure, and hazard, while accounting for uncertainty. We employed a scoring system that integrated a systematic literature review and expert elicitation for the hazard criteria. Monte Carlo sensitivity analysis was conducted to identify key factors contributing to overall risk. We identified shy albatross (Thalassarche cauta), southern rockhopper penguins (Eudyptes chrysocome), Australian fur seals (Arctocephalus pusillus doriferus), and Australian sea lions (Neophoca cinerea) with high climate urgency. Species breeding in lower latitudes, as well as certain eared seal, albatross, and penguin species, were particularly at risk. Hazard and exposure explained the most variation in relative risk, outweighing vulnerability. Key climate hazards affecting most species include extreme weather events, changes in habitat suitability, and prey availability. We emphasise the need for further research, focusing on at-risk species, and filling knowledge gaps (less-studied hazards, and/or species) to provide a more accurate and robust climate change risk assessment. Our findings offer valuable insights for conservation efforts, given that monitoring and implementing climate adaptation strategies for land-dependent marine predators is more feasible during their breeding season.

Climate change could fuel urinary schistosomiasis transmission in Africa and Europe.

The freshwater snail Bulinus truncatus is an important intermediate host for trematode parasites causing urogenital schistosomiasis, a tropical disease affecting over 150 million people. Despite its medical importance, uncertainty remains about its global distribution and the potential impacts of climate change on its future spread. Here, we investigate the distribution of B. truncatus, combining the outputs of correlative and mechanistic modelling methods to fully capitalize on both experimental and occurrence data of the species and to create a more reliable distribution forecast than ever constructed. We constructed ensemble correlative species distribution models using 273 occurrence points collected from different sources and a combination of climatic and (bio)physical environmental variables. Additionally, a mechanistic thermal suitability model was constructed, parameterized by recent life-history data obtained through extensive lab-based snail-temperature experiments and supplemented with an extensive literature review. Our findings reveal that the current suitable habitat for B. truncatus encompasses the Sahel region, the Middle East, and the Mediterranean segment of Africa, stretching from Southern Europe to Mozambique. Regions identified as suitable by both methods generally coincide with areas exhibiting high urogenital schistosomiasis prevalence. Model projections into the future suggest an overall net increase in suitable area of up to 17%. New suitable habitat is in Southern Europe, the Middle East, and large parts of Central Africa, while suitable habitat will be lost in the Sahel region. The change in snail habitat suitability may substantially increase the risk of urogenital schistosomiasis transmission in parts of Africa and Southern Europe while reducing it in the Sahel region.

Fish and tips: Historical and projected changes in commercial fish species' habitat suitability in the Southern Hemisphere

Global warming has significantly altered fish distribution patterns in the ocean, shifting towards higher latitudes and deeper waters. This is particularly relevant in high-latitude marine ecosystems, where climate-driven environmental changes are occurring at higher rates than the global average. Species Distribution Models (SDMs) are increasingly being used for predicting distributional shifts in habitat suitability for marine species as a response to climate change. Here, we used SDMs to project habitat suitability changes for a range of high-latitude, pelagic and benthopelagic commercial fish species and crustaceans (10 species); from 1850 to two future climate change scenarios (SSP1–2.6: low climate forcing; and SSP5–8.5: high climate forcing). The study includes 11 Large Marine Ecosystems (LME) spanning South America, Southern Africa, Australia, and New Zealand. We identified declining and southward-shifting patterns in suitable habitat areas for most species, particularly under the SSP5–8.5 scenario and for some species such as Argentine hake (Merluccius hubbsi) in South America, or snoek (Thyrsites atun) off Southern Africa. Geographical constraints will likely result in species from Southern Africa, Australia, and New Zealand facing the most pronounced habitat losses due to rising sea surface temperatures (SST). In contrast, South American species might encounter greater opportunities for migrating southward. Additionally, the SSP5–8.5 scenario predicts that South America will be more environmentally stable compared to other regions. Overall, our findings suggest that the Patagonian shelf could serve as a climate refuge, due to higher environmental stability highlighting the importance of proactive management strategies in this area for species conservation. This study significantly contributes to fisheries and conservation management, providing valuable insights for future protection efforts in the Southern Hemisphere.

Dynamic shifts of functional diversity through climate-resilient strategies and farmland restoration in a mountain protected area

Land-use land-cover (LULC) change contributes to major ecological impacts, particularly in areas undergoing land abandonment, inducing modifications on habitat structure and species distributions. Alternative land-use policies are potential solutions to alleviate the negative impacts of contemporary tendencies of LULC change on biodiversity.This work analyzes these tendencies in the Montesinho Natural Park (Portugal), an area representative of European abandoned mountain rural areas. We built ecological niche models for 226 species of vertebrates (amphibians, reptiles, birds, and mammals) and vascular plants, using a consensus modelling approach available in the R package ‘biomod2’. We projected the models to contemporary (2018) and future (2050) LULC scenarios, under four scenarios aiming to secure relevant ecosystem services and biodiversity conservation for 2050: an afforestation and a rewilding scenario, focused on climate-smart management strategies, and a farmland and an agroforestry recovery scenario, based on re-establishing human traditional activities. We quantified the influences of these scenarios on biodiversity through species habitat suitability changes for 2018–2050. We analyzed how these management strategies could influence indices of functional diversity (functional richness, functional evenness and functional dispersion) within the park.Habitat suitability changes revealed complementary patterns among scenarios. Afforestation and rewilding scenarios benefited more species adapted to habitats with low human influence, such as forests and open woodlands. The highest functional richness and dispersion was predicted for rewilding scenarios, which could improve landscape restoration and provide opportunities for the expansion and recolonization of forest areas by native species. The recovery of traditional farming and agroforestry activities results in the lowest values of functional richness, but these strategies contribute to complex landscape matrices with diversified habitats and resources. Moreover, this strategy could offer opportunities for fire suppression and increase landscape fire resistance. An integrative approach reconciling rewilding initiatives with the recovery of extensive agricultural and agroforestry activities is potentially an harmonious strategy for supporting the provision of ecosystem services while securing biodiversity conservation and functional diversity within the natural park.

Uncertainty in consensus predictions of plant species' vulnerability to climate change

AbstractAimVariation in spatial predictions of species' ranges made by various models has been recognized as a significant source of uncertainty for modelling species distributions. Consensus approaches that combine the results of multiple models have been employed to reduce the uncertainty introduced by different algorithms. We evaluate how estimates of habitat suitability, projected using species distribution models (SDMs), varied among different consensus methods relative to the variation introduced by different global climate models (GCMs) and representative concentration pathways (RCPs) used for projection.LocationCalifornia Floristic Province (California, US portion).MethodsWe modelled the current and future potential distributions of 82 terrestrial plant species, developing model predictions under different combinations of GCMs, RCPs, time periods, dispersal assumptions and SDM consensus methods commonly used to combine different species distribution modelling algorithms. We assessed how each of these factors contributed to the variability in future predictions of species habitat suitability change and aggregate measures of proportional change in species richness. We also related variability in species‐level habitat change to species' attributes.ResultsAssuming full dispersal capacity, the variability between habitat predictions made by different consensus methods was higher than the variability introduced by different RCPs and GCMs. The relationships between species' attributes and variability in future habitat predictions depended on the source of uncertainty and dispersal assumptions. However, species with small ranges or low prevalence tended to be associated with high variability in range change forecasts.Main ConclusionsOur results support exploring multiple consensus approaches when considering changes in habitat suitability outside of species' current distributions, especially when projecting species with low prevalence and small range sizes, as these species tend to be of the greatest conservation concern yet produce highly variable model outputs. Differences in vulnerability between diverging greenhouse gas concentration scenarios are most readily observed for end‐of‐century time periods and within species' currently occupied habitats (no dispersal).

Prediction of the potential distribution of Chimonobambusautilis (Poaceae, Bambusoideae) in China, based on the MaxEnt model.

Chimonobambusautilis is a unique edible bamboo species valued for its economic and nutritional benefits. However, its existence in natural habitats is at risk due to environmental shifts and human interventions. This research utilised the maximum entropy model (MaxEnt) to predict potential habitats for Ch.utilis in China, identifying key environmental factors influencing its distribution and analysing changes in suitable habitats under future climate conditions. The results show that the results of the MaxEnt model have high prediction accuracy, with an AUC (Area Under the receiver operating characteristic Curve) value of 0.997. Precipitation in the driest month (Bio14), altitude (Alt) and isothermality (Bio03) emerged as the primary environmental factors influencing the Ch.utilis distribution. Currently, the suitable habitats area for Ch.utilis is 10.55 × 104 km2. Projections for the 2050s and 2090s indicate potential changes in suitable habitats ranging from -3.79% to 10.52%. In general, the most suitable habitat area will decrease and shrink towards higher latitude areas in the future. This study provides a scientific basis for the introduction, cultivation and conservation of Ch.utilis.

Implications of Ecological Drivers on Roan Antelope Populations in Mokala National Park, South Africa

Climate change has massive global impacts and affects a wide range of species. Threatened species such as the roan antelope (Hippotragus equinus) are particularly vulnerable to these changes because of their ecological requirements. Attempts to address concerns about the roan’s vulnerability have not been well documented in South African protected areas. This study identifies the landscape use and distribution of the roan as well as habitat and forage suitability changes to help inform management decisions for the conservation of roan. We used fine- and broad-scale data from Mokala National Park, South Africa that includes roan occurrence data, vegetation condition indices, vegetation (structure and plant species composition), elevation and temperature differences, and precipitation strata to construct a suitability framework using the Maximum Entropy (Maxent) and Random Forest statistical package. In Mokala National Park, roan occurred in the Schmidtia pappophoroides–Vachellia erioloba sparse woodland, Senegalia mellifera–Vachellia erioloba closed woodland, Senegalia mellifera–Vachellia tortilis open shrubland, Vachellia erioloba–V. tortilis closed woodland and Rhigozum obovatum–Senegalia mellifera open shrubland. The veld (vegetation) condition index (VCI) improved from 2019 (VCI < 50%) to 2021 (VCI > 60%), with the proportion of palatable grass species (Schmidtia pappophoroides and Eragrostis lehmanniana) also increasing. This study identified four key climatic conditions affecting roan distribution, namely annual mean daily temperature range, temperature seasonality, minimum temperatures of the coldest month, and precipitation of the wettest month. These results suggest that the conservation of roan antelope should consider these key variables that affect their survival in preferred habitats and foraging areas in anticipation of changing ecological conditions.

Defining humpback whale (Megaptera novaeangliae) potential distribution in the Great Barrier Reef Marine Park: a two-way approach

Context Humpback whale (Megaptera novaeangliae) populations have been recovering from whaling but are now facing threats from changing food availability due to ocean warming and changes in habitat suitability. There is uncertainty over whether opportunistic observations can produce reliable species distribution models (SDMs) and adequately inform conservation management. Aims To compare SDMs for humpback whales in the Great Barrier Reef Marine Park based on different opportunistic sightings datasets and evaluate the impact different sources of opportunistic data have on our understanding of humpback whale habitat relationships. Methods Maximum entropy modelling (Maxent) was used to create predictive models for humpback whale distributions. Sighting data from citizen science and opportunistic observations from various other databases were used. Models were compared to evaluate disparities and predictive capabilities. Key results Distinct environmental variables [bathymetry, distance to the coast] were identified as the most relevant for each SDM. The best-fitting model diverged from an existing model, with humpback whale distribution predicted to be closer to shore. Areas with the highest habitat suitability were concentrated in the north-eastern coastal region across all models developed in this study. Conclusions This study demonstrates that, with careful application and consideration, citizen science data can enhance our understanding of humpback whale distributions and contribute to their conservation. The research underlines the importance of embracing diverse data sources in SDM, despite the challenges posed by opportunistic data. Implications The study provides valuable insights for conservation management and informs strategies to protect humpback whale populations in changing environmental conditions.

Impacts of Climate Change on the Habitat Suitability and Natural Product Accumulation of the Medicinal Plant Sophora alopecuroides L. Based on the MaxEnt Model.

Sophora alopecuroides L., a perennial herb in the arid and semi-arid regions of northwest China, has the ecological functions of windbreaking and sand fixation and high medicinal value. In recent years, global warming and human activities have led to changes in suitable habitats for S. alopecuroides, which may affect the accumulation of natural products. In this study, MaxEnt 3.4 and ArcGIS 10.4 software were used to predict the distribution of potentially suitable habitats for S. alopecuroides in China under climate change. Furthermore, the geographical distribution of S. alopecuroides as affected by human activities, the differences in the content of natural products of S. alopecuroides between different suitable habitats, and the correlation between natural products and environmental factors were analyzed. The results showed that suitable habitats for S. alopecuroides were projected to expand in the future, and the major environmental factors were temperature (Bio1), rainfall (Bio18), and soil pH (pH). When Bio1, Bio18, and pH were 8.4283 °C, 7.1968 mm, and 9.9331, respectively, the distribution probability (P) of S. alopecuroides was the highest. After adding a human activity factor, the accuracy of the model prediction results was improved, and the area of suitable habitats was greatly reduced, showing a fragmented pattern. Meanwhile, habitat suitability had a specific effect on the content of natural products in S. alopecuroides. Specifically, the content of natural products in S. alopecuroides in wild habitats was higher than that in artificial cultivation, and highly suitable habitats showed higher contents than those in non-highly suitable habitats. The contents of total alkaloids and total flavonoids were positively correlated with human activities and negatively correlated with land use types. Among them, total alkaloids were negatively correlated with aspect, and total flavonoids were positively correlated with aspect. In addition, it is suggested that Xinjiang should be the priority planting area for S. alopecuroides in China, and priority should be given to protection measures in the Alashan area. Overall, this study provides an important foundation for the determination of priority planting areas and resource protection for S. alopecuroides.

Environmental and Biogeographic Drivers behind Alpine Plant Thermal Tolerance and Genetic Variation.

In alpine ecosystems, elevation broadly functions as a steep thermal gradient, with plant communities exposed to regular fluctuations in hot and cold temperatures. These conditions lead to selective filtering, potentially contributing to species-level variation in thermal tolerance and population-level genetic divergence. Few studies have explored the breadth of alpine plant thermal tolerances across a thermal gradient or the underlying genetic variation thereof. We measured photosystem heat (Tcrit-hot) and cold (Tcrit-cold) thresholds of ten Australian alpine species across elevation gradients and characterised their neutral genetic variation. To reveal the biogeographical drivers of present-day genetic signatures, we also reconstructed temporal changes in habitat suitability across potential distributional ranges. We found intraspecific variation in thermal thresholds, but this was not associated with elevation, nor underpinned by genetic differentiation on a local scale. Instead, regional population differentiation and considerable homozygosity within populations may, in part, be driven by distributional contractions, long-term persistence, and migrations following habitat suitability. Our habitat suitability models suggest that cool-climate-distributed alpine plants may be threatened by a warming climate. Yet, the observed wide thermal tolerances did not reflect this vulnerability. Conservation efforts should seek to understand variations in species-level thermal tolerance across alpine microclimates.

Fire suppression and land-use strategies drive future dynamics of an invasive plant in a fire-prone mountain area under climate change

Woody invasive alien species can have profound impacts on ecosystem processes and functions, including fire regulation, which can significantly affect landscape resilience. Acacia dealbata, a widespread invasive alien plant in the Iberian Peninsula, holds well-known fire-adaptation traits (e.g., massive soil seed banks and heat-stimulated seed germination). In this study, we assess to what extent fire suppression and land-use strategies could affect the potential distribution of A. dealbata in a fire-prone transboundary protected mountain area of Portugal and Spain, using Habitat Suitability Models. Specifically, we predicted changes in habitat suitability for A. dealbata between years 2010 and 2050. We explored the potential impacts of two land-use strategies ('Business-as-usual' or 'High Nature Value farmlands') combined with three levels of fire suppression effectiveness using the biomod2 package in R. We also considered the potential effects of two climate change scenarios (RCP4.5 and RCP8.5). Our modeling approach demonstrated a strong capacity to predict habitat suitability using either climate or land-cover information alone (AUC climate = 0.947; AUC LC = 0.957). According to climate-based models, A. dealbata thrives under conditions characterized by higher precipitation seasonality, higher precipitation in the warmest month, and higher minimum temperature in the coldest month. Regarding land cover, A. dealbata thrives mainly in landscapes dominated by urban areas and evergreen forest plantations. Our models forecasted that habitat suitability by 2050 could either increase or decrease depending on the specific combinations of fire suppression, land-use, and climate scenarios. Thus, a combination of business-as-usual and fire-exclusion strategies would enhance habitat suitability for the species. Conversely, management promoting High Nature Value farmlands would decrease the available suitable habitat, particularly under low fire suppression efforts. These findings suggest that promoting sustainable farming activities could impede the spread of A. dealbata by reducing habitat availability, while strategies aiming at fire-exclusion could facilitate its expansion, likely by enabling establishment and large seed production. This study highlights the complex interplay between fire-prone invasive species, fire and land-use strategies, and climate change; and thus the need to consider the interactions between land-use and fire management to promote invasive species control and landscape resilience.

Assessing the efficiency of bird habitat conservation strategies in farmland ecosystems

Land use changes negatively impact agroecosystems, where the loss of wildlife habitats is increasingly threatening global biodiversity. Ecological conservation strategies that seek to reduce habitat destruction are important and strongly rely on understanding the spatial and temporal dynamics of land use change. In recent years, an expert-based approach using the Analytic Network Process (ANP) has been applied commonly to wildlife habitat assessment, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-s) model is a well-known simulation tool used to predict land use dynamics. Although their effectiveness has been proven widely, existing studies have yet to integrate the two approaches into ecological modeling for conserving bird habitats under the influence of land use changes. Thus, there is a notable research gap regarding the potential synergies of the ANP and CLUE-s models to evaluate the spatial nonstationarity between bird habitats and land use patterns. In this study, we integrated use of the ANP to identify suitable habitats for birds on farmland with the CLUE-s model to predict future changes in habitat suitability by 2035. Our study aims to evaluate the efficiency of various conservation strategies for bird habitat in farmland ecosystems within the Zhuoshui River basin in Taiwan. We formulated conservation strategies to protect areas of farmland based on their relative suitability as bird habitats. The research findings reveal a significant reduction of farmland habitats coinciding with expanding built-up areas and forests, while designating farmland areas for conservation purposes effectively ensures the maintenance of bird habitats amidst these transformations. Conserving highly suitable farmland habitats (those whose suitability values ranked at or above the 75th percentile) presents the most effective strategy to mitigate the impacts of land use change on bird habitats. Under this strategy, changes in farmland habitats lead to a notable decrease of 16.4 % in low and very low suitability, whereas farmland habitats with moderate and high suitability significantly expand by 879.8 % and 225.9 %, respectively. Farmland habitats characterized by high suitability are concentrated in the western region of the Zhuoshui River basin, accounting for 2289 hectares. These findings underscore the magnitude of habitat loss resulting from land use changes outside conserved areas. Our research emphasizes the importance of implementing conservation strategies for bird habitats, providing policymakers with a framework to manage farmland ecosystems effectively.

Improving species distribution forecasts by measuring and communicating uncertainty: An invasive species case study.

Forecasting invasion risk under future climate conditions is critical for the effective management of invasive species, and species distribution models (SDMs) are key tools for doing so. However, SDM-based forecasts are uncertain, especially when correlative statistical models extrapolate to nonanalog environmental domains, such as future climate conditions. Different assumptions about the functional form of the temperature-suitability relationship can impact predicted habitat suitability under novel conditions. Hence, methods to understand the sources of uncertainty are critical when applying SDMs. Here, we use high-resolution predictions of lake water temperatures to project changes in habitat suitability under future climate conditions for an invasive macrophyte (Myriophyllym spicatum). Future suitability was predicted using five global circulation models and three statistical models that assumed different species-temperature functional responses. The suitability of lakes for M. spicatum was overall predicted to increase under future climate conditions, but the magnitude and direction of change in suitability varied greatly among lakes. Variability was most pronounced for lakes under nonanalog temperature conditions, indicating that predictions for these lakes remained highly uncertain. Integrating predictions from SDMs that differ in their species-environment response function, while explicitly quantifying uncertainty across analog and nonanalog domains, can provide a more robust and useful approach to forecasting invasive species distribution under climate change.