Current Climate Scenarios Research Articles

School building-stock climate resilience: evaluating London’s school stock overheating performance

ABSTRACT Indoor environmental quality (IEQ) in classrooms is crucial for students’ health, wellbeing, and academic success. Rising outdoor temperatures due to climate change pose a significant risk – overheating in schools can negatively affect cognitive performance and health for both students and staff.This study examines the risk of overheating in primary and secondary schools in London, focusing on the impact of current and future climate scenarios. Using the UK Department for Education’s Building Bulletin 101 (BB101) as a framework, the study integrates data from various sources, including GIS form data and a national school survey, to develop a ‘one-by-one’ school stock thermal model called the Modelling Platform for Schools (MPS). This model, built using EnergyPlus, allows for the analysis of school thermal performance at national, regional, and individual levels.The results show that by the 2050s, under a medium emissions scenario, average summer temperatures in schools could reach nearly 30°C – 7% higher than current levels. The study also developed an overheating-risk regression model for London schools and explored potential mitigation strategies, such as extending summer holidays or adjusting school activities to times when overheating risk is lower.

Reef Adapt: A tool to inform climate-smart marine restoration and management decisions.

A critical component of ecosystem restoration projects involves using genetic data to select source material that will enhance success under current and future climates. However, the complexity and expense of applying genetic data is a barrier to its use outside of specialised scientific contexts. To help overcome this barrier, we developed Reef Adapt ( www.reefadapt.org ), an innovative, globally applicable and expandable web platform that incorporates genetic, biophysical and environmental prediction data into marine restoration and assisted gene flow planning. The Reef Adapt tool provides maps that identify areas with populations suited to user-specified restoration/recipient sites under current and future climate scenarios. We demonstrate its versatility and practicality with four case studies of ecologically and evolutionarily diverse taxa: the habitat-forming corals Pocillopora damicornis and Acropora kenti, and macroalgae Phyllospora comosa and Ecklonia radiata. Reef Adapt is a management-ready tool to aid restoration and conservation efforts amidst ongoing habitat degradation and climate change.

Climate change is expected to reduce the potential distribution of Ceiba glaziovii in Caatinga, the largest area of dry tropical forest in South America

Ecological niche modeling is a widely used tool to predict species distribution considering current, past, or future climate change scenarios across different geographic areas. Modeling scenarios allow researchers to assess the impacts of climate change on species distribution and identify priority areas for conservation. This study aimed to model the current and future potential distribution of Ceiba glaziovii under different climate change scenarios in Brazil. The MaxEnt algorithm was used to correlate species occurrence points with bioclimatic variables in current and future climate scenarios. Four General Circulation Models (GCMs) from CMIP6 were employed: BCC-CSM2-MR, CNRM-CM6-1, IPSL-CM6A-LR, and MIROC6, considering optimistic and pessimistic projections. The contribution of variables and model accuracy were assessed using the Jackknife statistical test and the Area Under the Curve (AUC) parameter. AUC values for current and future scenarios demonstrated high accuracy. The bioclimatic variables of precipitation and temperature were the main contributors to determining areas with higher habitat suitability. In the future climate scenario, there was a reduction in areas with good climatic suitability for all four GCMs, considering optimistic and pessimistic projections. Among the areas with high habitat suitability, the IPSL-CM6A-1 model in the optimistic projection showed the smallest reduction, while in the pessimistic scenario, all areas with high suitability disappeared. The species' climatic niche is expected to decrease under all tested climate change scenarios. The central areas of the Caatinga and its transition zones exhibit the highest climatic suitability in current and future scenarios and should be prioritized for the species' conservation.

Combined impacts of climate and land use scenarios on sediment loads in small agricultural watershed in Tunisia

This study investigates the impact of conservation practices, specifically mulching and terracing, on soil erosion in the Kamech watershed (2.6 km²) situated in the Cap Bon region of northeastern Tunisia, under both current and future climate scenarios. Utilizing the Soil and Water Assessment Tool (SWAT) model, the research evaluates the effectiveness of these Best Management Practices (BMPs) in reducing soil loss, revealing significant reductions of 1.5 t ha⁻¹ yr⁻¹ for mulching and 2 t ha⁻¹ yr⁻¹ for terracing. The findings indicate that these practices play a crucial role in enhancing soil conservation amidst climate change challenges, including altered precipitation patterns and increased temperatures. Additionally, the study highlights a notable decline in average monthly rainfall projected for the period 2051 to 2100 under the RCP8.5 scenario, further emphasizing the importance of implementing effective soil management strategies. This paper indicates that both methods, mulching and terracing, significantly contribute to reducing soil erosion under future scenarios (2051-2100). Their implementation proves essential for effective soil conservation, helping to mitigate the impacts of climate change and maintain soil health in the Kamech watershed. The results contribute to a better understanding of BMP performance in addressing soil erosion, water quality, and hydrological responses in the face of evolving environmental conditions. By enhancing our understanding of these interactions, this research aims to provide valuable insights for sustainable watershed management, particularly in regions prone to water scarcity and land degradation.

Investigation of the impact of diverse climate conditions on the cultivation suitability of Cinnamomum cassia using the MaxEnt model, HPLC and chemometric methods in China

Cinnamomum cassia Presl. is a subtropical plant that is used for food and medicine. Climate change has changed the suitable habitats of medicinal plants, which might have repercussions for the efficacy of herbal remedies. In this study, the potential distribution in each period of Cinnamomum cassia was predicted and the quality in different suitable habitats was evaluated. According to the results, (1) precipitation, temperature, and soil are the primary environmental variables influencing C. cassia distribution. (2) The high-suitable habitats of current climate scenarios were predominantly located in the southern regions (Guangdong and Guangxi etc.) of China, with an area of 706,129.08 km2. Under future climate scenarios, suitable habitats will increasingly move northward, with a greater concentration south of the Yangtze River, particularly in the 2090s SSP585 scenario, the total area of newly extended suitable habitat reaches 312,963.53 km2. (3) HPLC and FTIR, combined with chemometrics, can be effective methods for identifying different suitable habitats of C. cassia. The content of trans-cinnamaldehyde (0.85%) is significantly higher in the high suitability habitat compared to the medium-low suitability habitat (0.30%). Our findings can offer valuable guidance for the identification of suitable C. cassia cultivation areas in China, as well as for the evaluation of C. cassia resource quality and the rational use of resources in different suitable habitats.

Identifying key monitoring areas for tree insect pest risks in China under climate change.

Climate change can exacerbate pest population growth, posing significant threats to ecosystem functions and services, social development, and food security. Risk assessment is a valuable tool for effective pest management that identifies potential pest expansion and ecosystem dispersal patterns. We applied a habitat suitability model coupled with priority protection planning software to determine key monitoring areas (KMA) for tree insect pest risks under climate change and used forest ecoregions and nature reserves to assess the ecological risk of insect pest invasion. Finally, we collated the prevention and control measures for reducing future pest invasions. The KMA for tree insect pests in our current and future climate is mainly concentrated in eastern and southern China. However, with climate change, the KMA gradually expands from southeastern to northeastern China. In the current and future climate scenarios, ecoregions requiring high monitoring levels were restricted to the eastern and southern coastal areas of China, and nature reserves requiring the highest monitoring levels were mainly distributed in southeastern China. Tree insect pest invasion assessment using ecoregions and nature reserves identified that future climates increase the risk of pest invasions in forest ecoregions and nature reserves, especially in northeastern China. The increased risk and severity of tree insect pest invasions require implementing monitoring and preventative measures in these areas. We effectively assessed the pest invasion risks using forest ecoregions and nature reserves under climate change. Our assessments suggest that monitoring and early prevention should focus on southeastern and northeastern China.

Simulation of Responsive Envelopes in Current and Future Climate Scenarios: A New Interactive Computational Platform for Energy Analyses

Despite the strong interest concerning the responsive façades, today there are still few built examples and few tools to assess their benefits due to the complex description of the phenomenon. Energy simulations should consider the interactions between a time-varying environment and an environment-dependent envelope, increasing the intricacy of the problem; moreover, these strong environment–envelope interlinkages increase the importance of the location and climate scenarios considered. The aim of this study is to provide a tool to easily model these phenomena in different geographical and climate contexts. For this purpose, an innovative interactive computational platform (ICP) was developed based on EnergyPlus as a simulation engine, Python as a simulation manager, and Grasshopper as a user interface. Thanks to a single user-friendly environment, the users can simply select the climate scenario, the location, the responsive technology, and its main properties to set and run the dynamic energy simulation. After an overview of the current state of the art, this study provides a description of the structure and workflow adopted for developing this platform and details regarding its functioning and input management. Finally, the platform was tested to run an evolutionary optimization of an electrochromic window control strategy in different climate scenarios.

Prediction of Potential Suitable Distribution Areas for Northeastern China Salamander (Hynobius leechii) in Northeastern China

The Northeastern China Salamander (Hynobius leechii) is classified as a rare, nationally protected Class II wild animal in China. Its population is declining, and its habitat is deteriorating. This study aimed to predict the distribution of suitable habitats for the Northeastern China Salamander under both current and future climate scenarios, utilizing the MaxEnt model optimized through ENMeval parameters. Species distribution data were collected from field surveys, existing literature, amphibian records in China, and the Global Biodiversity Information Network. A total of 97 records were compiled, with duplicate records within the ENMTools grid unit removed, ensuring that only one record existed within every 5 km. Ultimately, 58 distinct distribution points for the Northeastern China Salamander were identified. The R software package ‘ENMeval 2.0’ was employed to optimize the feature complexity (FC) and regularization multiplier (RM), and the optimized model was applied to assess the suitable distribution regions for the Northeastern China Salamander under present and future climate conditions. The findings indicated that rainfall and temperature are the primary environmental factors influencing Hynobius. Currently, the suitable habitat for the Northeastern China Salamander constitutes 6.6% of the total area of Northeastern China. Projections for the periods of 2050 and 2070 suggest that suitable habitats for the Northeastern China Salamander will continue to expand towards higher latitudes across three climate scenarios. While this study focuses solely on climate change factors and acknowledges certain limitations, it serves as a reliable reference and provides essential information for the distribution and conservation of the Northeastern China Salamander.

Global change drives potential niche contraction and range shift of globally threatened African vulture

Human-induced global change poses an increasingly severe threat to biodiversity, with species having limited population sizes being particularly vulnerable. Mapping and modeling the distribution ranges of such species, along with detecting potential range shifts and contractions at both local and regional scales, are essential for developing effective conservation plans. Ruppell's vulture Gyps rueppelli, an ecologically important bird species native to Africa, is experiencing a rapid decline in its range. The purpose of this study is to map and model potential regional spatio-temporal distribution of Ruppell's vulture in Africa, alongside detecting the possibility of the species' range shifts and contractions. A total of 804 rarefied localities were identified where the Ruppell's vulture was the dominant bird species. This study employed the Maximum Entropy (MaxEnt) algorithm to perform species distribution modeling for the Ruppell's vulture. The modeling considered current climate conditions (1970s-2000s) as a baseline, along with two future climate change scenarios (Shared Socioeconomic Pathways: SSPs 245 and 585) for two future time periods (2050s and 2070s). The model's performance was evaluated by optimizing settings and examining the Area under the Receiver Operating Characteristic Curve (AUC-ROC). Among the 13 bioclimatic and anthropogenic variables included in the model, four (isothermality, cropland expansion, anthropogenic biomes, and urban expansion (in order of importance)) emerged as the most influential drivers of Ruppell's vulture regional distribution. All considered Species distribution models (SDMs) achieved high predictive performance, with AUC-ROC values exceeding 0.9.The model predicted a total of approximately 19,453 ha of suitable habitat for Ruppell's vultures in Africa, with East Africa identified as the most prominent region under the current climate scenario. Isothermality (38.8%) was the primary factor influencing Ruppell's vulture distribution, followed by agricultural expansion (29.9%) and anthropogenic biomes (7.2%) in the face of global change. The results reveal considerable future habitat loss (up to 61%) for Ruppell's vultures in the study area, alongside an eastward range shift (longitudinal axis) by the 2050s under projected climate change scenarios. These imply that Ruppell's vultures face imminent population decline and range shift due to significant habitat loss and climate change. Hence, prioritizing the development and implementation of a coordinated conservation program that incorporates captive breeding and assisted migration is critical to save this vulture species in its native African range.

Prediction of the potential distribution of a raspberry (Rubus idaeus) in China based on MaxEnt model

Rubus idaeus is a pivotal cultivated species of raspberry known for its attractive color, distinct flavor, and numerous health benefits. It can be used in pharmaceutical, cosmetics, agriculture and food industries not only as fresh but also as a processed product. Nowadays due to climatic changes, genetic diversity of cultivars has decreased dramatically. However, until now, the status of wild R. idaeus resources in China have not been exploited. In this study, we investigated the resources of wild R. idaeus in China to secure its future potential and sustainability. The MaxEnt model was used to predict R. idaeus suitable habitats and spatial distribution patterns for current and future climate scenarios, based on wild domestic geographic distribution data, current and future climate variables, and topographic variables. The results showed that, mean temperature of the coldest quarter (bio11), precipitation of the coldest quarter (bio19), precipitation of the warmest quarter (bio18), and temperature seasonality (bio4) were crucial factors affecting the distribution of R. idaeus. Presently, the suitable habitats were mainly distributed in the north of China including Xinjiang, Inner Mongolia, Gansu, Ningxia, Shaanxi, Shanxi, Hebei, Beijing, Liaoning, Jilin, Heilongjiang. According to our results, in 2050s, the total suitable habitat area of R. idaeus will increase under SSP1-2.6 and then will be decreased with climate change, while in the 2090s, the total suitable habitat area will continue to decrease. From the present to the 2090s, the centroid distribution of R. idaeus in China will shift towards the east and the species will always be present in Inner Mongolia. Our results provide wild resource information and theoretical reference for the protection and rational utilization of R. idaeus.

Phytoclimatological study in the high plains of Sétif: application of the bioclimatic classification system (Algeria)

The Global Bioclimatic Classification System (WBCS) by Rivas-Martínez is an effective approach to reflect and study the role of climate in determining the potential distribution of natural vegetation at various temporal and spatial scales. In particular, the diversity of physical characteristics in the Setifian high plains leads to the complexity of large-scale phytogeographic belts. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), have been created for the study area based on Rivas-Martínez's global bioclimatic classification system for current and future climate scenarios, using the parallel climate model from CMIP5 (Coupled Model Intercomparison Project) under the intermediate greenhouse gas emission scenario (RCP4.5). Precipitation and temperature data from the "WorldClim" dataset were used as the data source. These climatic variables were reduced to a spatial resolution of 1 km. The objective is to understand how the climate is evolving in this region, what the consequences are, and what the future holds for these natural ecosystems. A phytosociological study complemented by satellite image analysis reveals a high diversity of pre-forestry formations. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and the magnitude of change, 2) identify and locate the new projected isobioclimates, and 3) explore the compositional changes in vegetation types among analogous isobioclimatic zones. The ordination of the relationships between vegetation and bioclimates shows a strong correlation between Rivas-Martinez indices and the distribution and composition of vegetation. Changes in ombrotype, thermotype, bioclimate, ombrotype, and isobioclimate differed between the current and future series. The resulting map presents 9 isobioclimatic units, which are advantageous for confirming the diagnosis of bioclimatic characteristics and describing the relationships between climatic variables and the corresponding distributions of natural vegetation. We identified eight different isobioclimates for the current period (1979-2013) and seven for the future period (2050), three thermotype horizons for both the current and future periods, and finally, four ombrotype horizons for the period (1979-2013), while two ombrohorizons represent the period (2050). This approach is useful for explaining territorial diversity in environmental applications related to ecological adaptation assessment, nature conservation, landscape regionalization, and planning.

Climate change favors expansion of three Eucalyptus species in China.

Eucalyptus has become one of the most widely planted species in tropical and subtropical regions in China, with important economic, ecological, and social values. However, it is currently unclear how climate change will affect different Eucalyptus species. Therefore, it is urgent to investigate the potential distribution and dynamics of Eucalyptus under current and future climate scenarios. In this study, we analyzed the potential distribution patterns of the three main Eucalyptus species (Eucalyptus grandis, Eucalyptus urophylla, and Eucalyptus tereticornis) under current and future climatic conditions (2041-2060 and 2061-2080) using the optimized MaxEnt model, which integrates a variety of environmental data including climate, topography, soil, and human influence. We also identified the main factors affecting the potential distributions of the three main Eucalyptus species. The model indicated that E. grandis exhibited heightened sensitivity to the mean temperature of the coldest quarter (7.0-20.0 °C) and annual mean temperature (11.9-24.2 °C), whereas E. urophylla displayed heightened sensitivity to precipitation of the warmest quarter (272-1694mm) and annual precipitation (812-2624mm). Conversely, E. tereticornis demonstrated heightened sensitivity to annual mean temperature (12.7-24.5°C) and temperature seasonality (63.8-598.9). Under the current climate, E. tereticornis had the widest suitable distribution area (124.91 × 104 km²), followed by E. grandis (124.89 × 104 km²) and E. urophylla (119.81 × 104 km²). Under future climate change scenarios, the suitable ranges of E. grandis, E. urophylla and E. tereticornis will continue to expand. This study highlights the importance of climate change in Eucalyptus distribution and provides quantified potential distribution maps for three Eucalyptus species under current and future climate conditions in China. This research offers valuable scientific insights pertinent to the management and rational site selection for Eucalyptus plantations.

Climate Change and Building Renovation: The Impact of Historical, Current, and Future Climatic Files on a School in Central Italy

Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants’ comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building’s current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building’s energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building’s energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%.

Maxent modelling reveals suitable habitat remains unchanged for Carcinus maenas in Australia

ABSTRACT This study assesses the habitat suitability of the invasive green crab, Carcinus maenas, in Australia using MaxEnt modelling under current and future climate scenarios. The species has significant ecological impacts, displacing native species and altering habitats. Using 90 occurrence points from the Global Biodiversity Information Facility, the MaxEnt model shows high performance (Area Under the Curve value of 0.99), indicating reliable predictions. Currently, the green crab's habitat suitability along the Australian coast ranges from high to medium in Tasmania, Victoria, New South Wales and South Australia and low in Western Australia and South Queensland. Future projections suggest a decrease in suitable habitats, confined to Tasmania, Victoria, Adelaide and New South Wales. These findings can guide the development of long-term management and conservation plans for C. maenas, with an emphasis on areas with consistent habitat suitability. Additionally, further field and laboratory experiments are recommended to understand the species’ tolerance to environmental changes. Recognising the ecological impact of C. maenas is crucial for informed decision-making to preserve Australia's ecosystems and ensure the sustainable coexistence of native species amidst invasive threats.

Host genetics shapes Pinus radiata phenotypic plasticity under drought and is linked with root-associated soil microbiome shifts

Under current and future climate scenarios, identifying drought-resistant tree species, tree genotypes, and beneficial interactions between trees and their root-associated soil microbiomes is becoming more imperative for maintaining tree health and sustaining increasingly vulnerable forests. We designed a genotype x soil x watering x time glasshouse experiment using Pinus radiata as a model tree to assess the magnitude of the effect of host genotype and root-associated soil microbiome on the phenotype response (functional traits, metabolome, nutrients) under drought. We identified the shikimate pathway as a critical metabolic pathway for Pinus radiata drought resistance, with the shikimic acid intermediate being one of the strongest drought signals, besides downstream metabolites such as flavonoids and phenylpropanoids. Overall, we found that the host genotype diversity was a key actor in the observed phenotype response of P. radiata to drought. In contrast, the microbiome was attributed a minor supporting role. Contrary to our hypothesis, dry soils could not support drought-sensitive genotypes under drought stress. Instead, the drought-resistant genotype was able to leverage locally adaptive bacteria to match local selective drought pressures at the expense of tree growth. This highlights the significance of finding specific combinations of tree genotype and mutualistic microbial communities that would thrive under future environmental pressures.

Past, present, and future potential distributions of the African multipurpose tree Detarium senegalense (Fabaceae)

Background and aims – Climate change induces increasing temperatures and drought, with possible profound shifts in species’ presence and distribution. Ecological niche models are widely used to assess plant species responses to climate change. However, such data are scarce for West Africa, particularly for vulnerable multipurpose species. This study focuses on modelling the ecological niche and the conservation status of the multipurpose tree Detarium senegalense to improve insights into its habitat suitability in West Africa under past, present, and future climatic conditions. This will provide an essential basis for setting up global management plans through efficient conservation and ecological restoration policies. Material and methods – The potential distribution of D. senegalense under past, current, and future climate scenarios were assessed using four algorithms including generalized additive models (GAM), generalized linear models (GLM), random forest (RF), and Maximum Entropy (MaxEnt). We also assessed the shift direction of suitable habitats and the conservation status of the species based on IUCN criteria. Overall, 220 occurrences were combined with a set of five bioclimatic variables to run the models. Key results – Models performed well with good values of AUC (0.92) and TSS (0.73). Isothermality (41.10%) and Precipitation of Wettest Month (21.50%) contributed most to the distribution of the species. The distribution of D. senegalense was relatively constant from the past to the present but could decrease in the next decades. In the future, only 17.70% and 13.98% of the areas were predicted to be suitable under respectively ssp245 and ssp585. In protected areas, the suitable areas under ssp245 were estimated at 21.01% with a decrease of 2.50% and 14.60% with a decrease of 8.61% under ssp585 by 2050. The direction of the distribution shifted to the south-east under future climate scenarios. The conservation status assessment of the species is Least Concern (LC). Conclusion – This study improves our understanding of the past, present-day, and future distribution of the species and provides support to better manage the conservation of D. senegalense in West Africa.

Potentially suitable geographical area for Colletotrichum acutatum under current and future climatic scenarios based on optimized MaxEnt model.

Global climate warming has led to changes in the suitable habitats for fungi. Colletotrichum acutatum, a common fungus causing anthracnose disease, is widely distributed in southern China. Currently, research on the relationship between C. acutatum and environmental warming was limited. In this study, MaxEnt and ArcGIS software were used to predict the suitable habitats of C. acutatum under current and future climate conditions based on its occurrence records and environmental factors. The optimal MaxEnt model parameters were set as feature combination (FC) = lp and regularization multiplier (RM) = 2.6. Bio15, Bio12, Bio09, and Bio19 were identified as the main environmental factors influencing the distribution of C. acutatum. Under current climate conditions, C. acutatum was distributed across all continents globally, except Antarctica. In China, C. acutatum was primarily distributed south of the Qinling-Huaihe Line, with a total suitable area of 259.52 × 104 km2. Under future climate conditions, the potential suitable habitat area for C. acutatum was expected to increase and spread towards inland China. The results of this study provided timely risk assessment for the distribution and spread of C. acutatum in China and offer scientific guidance for monitoring and timely controlled of its distribution areas.

Projection of the Potential Global Geographic Distribution of the Solanum Fruit Fly Bactrocera latifrons (Hendel, 1912) (Diptera: Tephritidae) Based on CLIMEX Models

The solanum fruit fly Bactrocera latifrons (Diptera: Tephritidae) is an invasive alien insect that causes huge economic losses to pepper and other solanaceous plant industries. It is mainly distributed in South and Southeast Asia, SW Europe, Western USA, and in some African countries. However, the potential global geographical distribution of B. latifrons is unknown. Therefore, in this study, based on the current (1981–2010) and future (2040–2059) climatic scenarios determined using the CNRM-CM5, Access1.0, GFDL-ESM-2M, and NorESM1-M models, we used a species distribution model (CLIMEX 4.0) to project the potential global geographic distribution of B. latifrons to prevent further invasion and harm. In the current climate scenario, South America (1286.06 × 104 km2), Africa (1435.47 × 104 km2), and Oceania (410.66 × 104 km2) have the largest proportions of suitable land areas for B. latifrons colonization. Under all four future climate models, the global potential suitable area for Bactrocera latifrons is projected to decrease and shift towards higher latitudes. This study provides an important baseline upon which researchers, quarantine personnel, and governments can develop the appropriate control strategies against B. latifrons.

Habitat Suitability Modeling of Endemic Genus Chimonanthus in China under Climate Change

Climate change has significantly altered in the distribution of plant and animal species, potentially resulting in either species expansion or extinction. The genus Chimonanthus, an economically significant and endemic group in China, holds substantial medicinal and ornamental value; however, its wild resources are limited. There is a paucity of knowledge regarding the distribution characteristics of the genus Chimonanthus species and the critical ecological factors influencing habitat suitability. Utilizing species distribution data and environmental variables, we performed simulations and analyses to identify suitable habitats, evaluate the primary environmental factors influencing distribution, determine potential distribution areas and centroids, and predict changes in suitable areas under three future climate scenarios (SSP-126, SSP-245, SSP-585) employing MaxEnt and ArcGIS. These findings indicated that the Area Under Curve (AUC) values exceeded 0.97 for all five Chimonanthus species, suggesting that the model predictions are highly accurate. The primary environmental variables influencing the distribution of C. grammatus are temperature, particularly isothermality (BIO3), and the mean temperature of warmest quarter (BIO10). However, precipitation of warmest quarter (BIO18) was an important environmental factor limiting the distributions of C. praecox, C. nitens, C. salicifolius and C. zhejiangensis. In the current period, the area of habitat suitability for C. praecox is the largest, at 2,498,600 km2, while that for C. zhejiangensis is the smallest, at 700,400 km2. The five Chimonanthus species are distributed mainly in southern China under the current climate scenario and will migrate to higher latitudes under future climate scenarios. C. nitens had high niche overlap and range overlap with C. zhejiangensis and C. salicifolius, respectively. A similar situation occurs between C. zhejiangensis and C. salicifolius. These findings suggest that there may be strong interspecific competition among adjacent species. Our results indicate that the establishment of nature reserves at current distribution sites within optimal areas is crucial for the conservation of germplasm resources, particularly for C. grammatus and C. salicifolius. The data generated from this research can serve as a valuable reference for the selection of in situ conservation sites, the determination of appropriate planting locations, the scientific introduction of species, and the development of long-term conservation and management strategies for Chimonanthus.

Modeling the Impacts of Climate Change on Potential Distribution of Betula luminifera H. Winkler in China Using MaxEnt

Betula luminifera H. Winkler, a fast-growing broad-leaved tree species native to China’s subtropical regions, possesses significant ecological and economic value. The species’ adaptability and ornamental characteristics make it a crucial component of forest ecosystems. However, the impacts of global climate change on its geographical distribution are not well understood, necessitating research to predict its potential distribution shifts under future climate scenarios. Our aims were to forecast the impact of climate change on the potential suitable distribution of B. luminifera across China using the MaxEnt model, which is recognized for its high predictive accuracy and low sample data requirement. Geographical coordinate data of B. luminifera distribution points were collected from various databases and verified for redundancy. Nineteen bioclimatic variables were selected and screened for correlation to avoid overfitting in the model. The MaxEnt model was optimized using the ENMeval package, and the model accuracy was evaluated using the Akaike Information Criterion Correction (delta.AICc), Training Omission Rate (OR10), and Area Under the Curve (AUC). The potential distribution of B. luminifera was predicted under current and future climate scenarios based on the Shared Socio-economic Pathways (SSPs). The optimized MaxEnt model demonstrated high predictive accuracy with an AUC value of 0.9. The dominant environmental variables influencing the distribution of B. luminifera were annual precipitation, minimum temperature of the coldest month, and standard deviation of temperature seasonality. The potential suitable habitat area and its geographical location were predicted to change significantly under different future climate scenarios, with complex dynamics of habitat expansion and contraction. The distribution centroid of B. luminifera was also predicted to migrate, indicating a response to changing climatic conditions. Our findings underscore the importance of model optimization in enhancing predictive accuracy and provide valuable insights for the development of conservation strategies and forest management plans to address the challenges posed by climate change.