Future Climate Scenarios Research Articles

Global Distribution Prediction of Cyrtotrachelus buqueti Guer (Coleoptera: Curculionidae) Insights from the Optimised MaxEnt Model.

Cyrtotrachelus buqueti Guer is a major pest affecting bamboo forests economically, causing significant damage to bamboo forests in Sichuan Province, China. To understand how C. buqueti responds to future climate conditions, an optimized Maximum Entropy Model (Maxent) was used to simulate the potential global distribution patterns of C. buqueti under current climate conditions and three different future climate scenarios and to analyze the dominant factors influencing its distribution. The results indicate that Bio18 (precipitation of the warmest quarter), Bio04 (temperature seasonality), Bio06 (minimum temperature of the coldest month), and Bio02 (mean diurnal temperature range) are the main environmental factors affecting the distribution of this species. The global area of high-suitability habitats for C. buqueti is 9.00 × 104 km2, primarily distributed in China. Under three different future climate scenarios, there are varying degrees of expansion in both the total suitable habitat and the medium-suitability areas for C. buqueti. Under the SSP5-8.5 scenario, the medium-suitability area of the species increases the most, reaching 9.83 × 104 km2. Additionally, these findings can serve as a reference for developing and implementing control strategies, assisting relevant authorities in more effectively managing and controlling this pest, and mitigating its potential threats to bamboo forest ecosystems and economies.

Shrinking suitable habitat of a sub-Arctic foundation kelp under future climate scenarios.

Climate change has profound effects on the distribution of kelp forests in the Arctic and sub-Arctic. However, studies on the responses of kelps to climate change, particularly along the sub-Arctic regions of the Alaska coast, are limited. Eualaria fistulosa is a foundational kelp species in the Aleutian Islands, with an east-west distribution that extends from Japan to southern southwest Alaska. In this study, we utilized a species distribution model (SDM) to explore changes in the future habitat suitability of E. fistulosa under contrasting Shared Socioeconomic Pathway (SSP) scenarios. Our model exhibited relatively high predictive performance, validating our SDM predictions. Notably, the SDM results indicate that minimum sea surface temperature, annual range in sea surface temperatures, and annual mean current velocities are the three most important predictor variables determining E. fistulosa's distribution. Furthermore, the projected geographic distribution of Eualaria is generally consistent with its observed occurrence records. However, under high emission scenarios (SSP5-8.5), E. fistulosa is predicted to contract its distribution range by 9.0% by 2100, with widespread disappearance along the southeast Alaskan coast and limited northward migration to Kamchatka Krai in Russia and Bristol Bay in Alaska. These findings contribute valuable insights for conservation strategies via addressing climate-induced alterations in sub-Arctic kelp distribution.

The Biodiversity and Climate Variability Experiment (BioCliVE): Quantifying the role of biodiversity in buffering ecosystems against climatic variability

Extreme climate events such as floods and droughts are becoming increasingly frequent and intense across the world. Future climate scenarios predict both an increase in individual extreme events, as well as chronic changes in climatic seasonality. Yet, the combined and relative effects of these pressures on ecosystems remain unknown. Concurrently, human-induced ecological disruption is accelerating species extinction rates, which are estimated to be 100 to 1000 times greater than pre-human levels. This is alarming as greater biological diversity is thought to buffer ecosystem functioning against extreme climate events, thereby safeguarding the provisioning of essential ecological services that contribute to human well-being. However, how and to what extent biodiversity buffers ecosystems against climate variability remains unclear. We recently constructed experimental grassland communities in a mesocosm-based field design representing a realistic gradient of plant diversity. Both extreme events (drought and flood) and a change in seasonality of precipitation are manipulated in a full factorial design to quantify the effects of future seasonal shifts and extremes in precipitation. We will: 1) determine to what extent higher biological diversity ensures that grasslands can continue to provide multiple ecosystem services even in the context of climate change and 2) unravel the fundamental mechanisms by which this is achieved including species asynchrony and positive species interactions. Results of our experimental approach will advance our understanding of the buffering potential of plant diversity and contribute to the development of strategies for sustainable service provisioning of our ecosystems in the face of climate change.

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.

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.

Wet creatures in a warming world: How climate change will impact the future distribution of anuran amphibians from Brazilian semiarid region?

The world has been going through a climate crisis that has led to a substantial increase in global temperatures. Consequently, amphibians, ectothermic animals that depend on water to survive/reproduce, are under increasing threat. In this research, we compared the influence of climate change on the geographic distribution between anuran species with occurrence restricted to the Brazilian semi-arid region (Caatinga domain) and widely distributed congeneric species, with occurrence in multiple biomes. We hypothesized that climate change would be more harmful for species of restricted distribution than for those widely distributed. For this purpose, using ecological niche modeling, we designed potential distribution models for current and four future climate scenarios, and compared two metrics (climatic suitability and index of extent of occurrence) between restricted and widely distributed species. The results revealed that the climatic suitability did not differ among current climatic conditions and those expected for 2050 and 2090, nor differed between species with distribution restricted to the Caatinga and widely distributed ones. On the other hand, contrary to our predictions, while species with wide distributions would tend to retract their extent of occurrence in future times, species with restricted distributions would expand their ranges. These results suggest that species with current distribution restricted to Caatinga biome might be relatively favored by the climate changes predicted for the next 80 years. However, we discuss that this result should be interpreted with very caution, because many ecological and conservation requirements need to be guaranteed so that these predictions can actually occur. Our findings contributed to the understanding of the effects of climate change on closely related taxa, with different distribution patterns, revealing particularities of the anuran amphibians that occur in semi-arid environments in response to climate changes predicted for this century.

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.

Spatial heterogeneity in the potential distribution of Aedes mosquitoes in India under current and future climatic scenarios

Aedes is the most globally distributed mosquito genus in the 21st century and transmits various arboviral diseases. The rapid expansion of Ae. Aegypti and Ae. albopictus breeding habitats is a significant threat to global public health, driven by temperature and precipitation changes. In this study, bioclimatic variables were employed to predict the spatial distribution of Ae. aegypti and Ae. albopictus in India. The reference coordinate points of (n = 583) Aedes occurrences at a scale of ∼1 km and nineteen bioclimatic factors were retrieved to train SDM (Species Distribution Models) for both species. Maximum entropy modelling was used to predict the species’ fundamental climatic niche distributions. Future projections were made using global climate models for 2021–2040 and 2081–2100 separately. The models performed reasonably well (AUC > 0.77). Both species thrived in reduced diurnal temperature and higher annual mean temperatures, with suitability increasing alongside precipitation. Ae. aegypti’s projected present and future distribution was broader than that of Ae. Albopictus. The expansion of Aedes suitability varied under different future climatic scenarios. Suitability for Ae. aegypti could expand from between 17.6 and 41.1 % in 2100 under SSP (shared socioeconomic pathways) scenarios 1 and 3, respectively, whereas for Ae. albopictus suitability increased from between 10.2 and 25 % under SSP scenarios 1 and 3 respectively. Preparing for future epidemics and outbreaks requires robust vector distribution models to identify high-risk areas, allocate resources for surveillance and control, and implement prevention strategies.

High-resolution projections of future FWI conditions for Portugal according to CMIP6 future climate scenarios

Wildfires are catastrophes of natural origin or initiated by human activities with high disruptive potential. "Portugal, located in western Iberia, has recently experienced several large fire events, including megafires, due to a combination of factors such as orography, vegetation, climate, and socio-demographic conditions that contribute to fuel accumulation.". One approach to studying fire danger is to use fire weather indices that are commonly used to quantify meteorological conditions that can lead to fire ignition and spread. This study aims to provide high-resolution (~ 6 km) future projections of the Fire Weather Index (FWI) for Portugal using the Weather Research and Forecasting (WRF) model, forced by the Max Planck Institute (MPI) model from the CMIP6 suite, under three emission scenarios (SSP2-4.5, SSP3-7.0, and SSP58.5) for the present period (1995–2014) and two future periods (2046–2065 and 2081–2100). The results show good agreement between FWI and its subcomponents from the WRF and reanalysis. The modelled FWI reproduced the climatological distribution of fire danger Projections indicate an increase in days with very high to extreme fire danger (FWI > 38) across all scenarios and time frames, with the southern and northeastern regions experiencing the most significant changes. The southern and northeastern parts of the territory experienced the largest changes, indicating significant changes between the scenarios and regions. This study suggests that FWI and its subcomponents should be investigated further. Our results highlight the importance of creating new adaptation measures, especially in the areas most at risk, prepared in advance by different players and authorities, so that the increasing risk of wildfires can be mitigated in the future.

Diversity pattern of Symplocos tree species in China under climate change scenarios: Toward conservation planning

Symplocos, a genus rich in endemic and keystone species in China's subtropical forests, plays a vital role in maintaining biodiversity. Climate change impacts on Symplocos trees affect ecosystem composition, dynamics, and functions. This study delves into the potential ramifications of climate change on the distribution and richness of Symplocos species across China under different climatic conditions. A comprehensive analysis was conducted using occurrence records of 29 species of Symplocos, focusing on habitat suitability modeling and spatial analysis, to demonstrate the possible effects of climate change on the distribution and diversity patterns of Symplocos species in China. Environmental data, including bioclimatic variables, were collected, and the future climate scenarios were projected using the combined average of the two global climate models. Four modeling algorithms were applied in an ensemble species distribution models to assess the distribution of Symplocos species and decipher the pattern of species richness and endemism. The results indicate high accuracy and performance of the models with a mean AUC of 0.94 and TSS of 0.77, particularly the random forest. The analysis identified key bioclimatic variables influencing Symplocos species distribution, with precipitation patterns (precipitation of driest month and precipitation of warmest quarter) and temperature variability (temperature mean diurnal range) playing significant roles. Predictions suggest a reduction in Symplocos species richness over the next six decades, particularly in southern and southwestern China, with potential gains in other regions. Overall, this study highlights the vulnerability of Symplocos species to climate change and underscores the importance of proactive conservation efforts and forest plantations to mitigate future loss in Symplocos species diversity.

Ecophysiology of Mediterranean Chestnut (Castanea sativa Mill.) Forests: Effects of Pruning Studied through an Advanced IoT System

Chestnut (Castanea sativa Mill.) forests in the Mediterranean region are facing increasing abandonment due to a combination of factors, ranging from climate change to socioeconomic issues. The recovery of chestnut ecosystems and their preservation and valorization are key to ensuring the supply of the wide spectrum of ecosystem services they provide and to preventing detrimental environmental shifts. The study’s objective was to provide evidence on the effects of different management options on the ecophysiology of chestnut forests, with diverse pruning intensities (low, medium, and high intensity versus no pruning) tested in an abandoned chestnut stand in central Italy with the aim of recovering and rehabilitating it for fruit production. Innovative Internet of Things (IoT) ‘Tree Talker’ devices were installed on single trees to continuously monitor and measure ecophysiological (i.e., water transport, net primary productivity, foliage development) and microclimatic parameters. Results show a reduction in water use in trees subjected to medium- and high-intensity pruning treatments, along with a decrease in the carbon sequestration function. However, interestingly, the results highlight that trees regain their usual sap flow and carbon sink activity at the end of the first post-pruning growing season and fully realign during the following year, as also confirmed by the NDVI values. As such, this paper demonstrates the efficacy of recovering and managing abandoned chestnut forests, and the initial setback in carbon sequestration resulting from pruning is rapidly remedied with the advantage of reviving trees for fruit production. Additionally, the reduced water demand induced by pruning could represent a promising adaptation strategy to climate change, bolstering the resilience of chestnut trees to prolonged and intensified drought periods, which are projected to increase under future climate scenarios, particularly in the Mediterranean region.

Combining mathematical models and machine learning algorithms to predict the future regional-scale actual transpiration by maize

Plants on the land surface play a vital role in the hydrological water cycle as they transport soil water to the atmosphere through transpiration. Root water uptake (RWU) is considered a crucial step in this process as it is the first stage of transpiration, directly determining the actual transpiration (Ta) of plants. However, accurately measuring RWU or Ta in situ poses significant challenges. Here, we establish an overall approach of combining mathematical models and machine learning algorithms to obtain high-precision (500 m×500 m) regional-scale daily Ta maps for various future climate patterns. The Hydrus-1D and AquaCrop models were employed to calculate the total RWU fluxes across the entire root zone, aiming to achieve Ta at a point scale. A machine learning model was developed using the CatBoost algorithm and environmental covariates extracted from the Google Earth Engine (GEE) platform to upscale these point-scale Ta to the regional scale. Furthermore, a total of 22 CMIP6 Earth System Models (ESMs) were evaluated, and among them, ACCESS-CM2 and ACCESS-ESM1–5 were selected for simulating future climate scenarios. Based on the established machine learning model and selected ESMs, regional-scale Ta maps were generated from 2020 to 2100 for the SSP245 and SSP585 (Shared Socioeconomic Pathways) scenarios. The results indicate that near-surface specific humidity, mean near-surface air temperature, latitude, and surface downwelling shortwave radiation are the critical factors influencing regional-scale Ta. As greenhouse gas emissions intensify and temperatures rise, regional-scale Ta is enhanced, leading to an accelerated transfer of soil water to atmospheric water. Under the SSP245 scenario, Ta increases on average by 0.55–1.16 % every 20 years, with its incremental value ranging from 7.14∙10−4 to 8.65∙10−4 cm day−1, while under the SSP585 scenario, Ta increases more significantly, achieving an average increase of 0.64–1.81 % every 20 years, with its incremental value ranging from 1.595∙10−3 to 2.821∙10−3 cm day−1. This study provides a robust integrated approach to assess the future regional-scale Ta providing valuable insights into the underlying water cycle mechanisms and regional water requirements for future climate scenarios.

Meta-Analysis and MaxEnt Model Prediction of the Distribution of Phenacoccus solenopsis Tinsley in China under the Context of Climate Change.

Phenacoccus solenopsis Tinsley is a pest that poses a significant threat to agricultural crops, especially cotton, and is now widely distributed across many regions worldwide. In this study, we performed a meta-analysis on the collected experimental data and found that within the suitable temperature range, the survival rate of P. solenopsis increases with rising temperatures, indicating that climate plays a decisive role in its distribution. Using the MaxEnt model this study predicted that under three future climate scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5), the distribution of P. solenopsis will expand and move towards higher latitudes. Climate change is the primary factor influencing changes in pest distribution. We conducted a meta-analysis of P. solenopsis, including seven independent studies covering 221 observation results, and examined the impact of temperature ranging from 18 °C to 39 °C on the developmental cycle of P. solenopsis. As the temperature rises, the development cycle of P. solenopsis gradually decreases. Additionally, by combining the MaxEnt model, we predicted the current and potential future distribution range of P. solenopsis. The results show that under future climate warming, the distribution area of P. solenopsis in China will expand. This research provides a theoretical basis for early monitoring and control of this pest's occurrence and spread. Therefore, the predictive results of this study will provide important information for managers in monitoring P. solenopsis and help them formulate relevant control strategies.

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.

Geographic distribution and impacts of climate change on the suitable habitats of two alpine Rhododendron in Southwest China

Mountains of Southwest China (MSC) serve as a prominent geographical distribution center for Rhododendron delavayi and Rhododendron irroratum (Ericaceae). These mountains are currently experiencing an unparalleled warming trend, which poses severe challenges to the survival of these keystone alpine Rhododendron species. However, the geographical distribution responses of these species to climate change remain incompletely understood and are often overlooked. Here, we constructed ensemble models (EMs) using ten models of five algorithms to calibrate ecological niche models and predict suitable habitat areas for the two Rhododendron species across four climate emission scenarios over three distinct periods. Our analysis indicated the higher importance of elevation than temperature and precipitation in shaping the spatial distribution of the two alpine Rhododendron species. The current suitable habitats of R. delavayi and R. irroratum have areas spanning 14.85 × 104 and 11.01 × 104 km2, respectively, which are mostly distributed in the western and central regions of MSC. The suitable habitat of R. delavayi is projected to decrease by 15.09–75.31 %, but the potential habitat of R. irroratum is expected to shrink by12.71 % to 76.8 % in different future climate scenarios. The suitable habitats of these species may become confined in a “summit trap” within relatively low-altitude regions, whereas habitats distributed at high altitudes may serve as “biological refuges.” The future distribution of the two alpine Rhododendron species will shift to high altitudes in westward and northward regions, with substantial thermal and hydrothermal changes as the primary drivers of habitat alteration and migration patterns. The losses or benefits for species under climate warming depend on their ecological niches and geographical location, which provide a geographical guidance for the long-term conservation and sustainable use of species and essential insights into the spatial conservation assessment of alpine plant groups in biodiversity hotspots in the future.

Synergistic effects of climate and land use change on khulan (Equus hemionus hemionus) habitat in China

Climate and land use change are the primary drivers causing the reduction of habitat range for many species worldwide, especially wide-ranging and large-bodied ungulates. For instance, khulan (Equus hemionus hemionus), a flagship species inhabiting desert regions of Asia, exhibits heightened vulnerability to habitat loss and fragmentation due to their extensive habitat requirements. We simulated suitable khulan habitats in China across 20 scenarios, including the past (1980–2000), current (2001–2022), and future (2050 s and 2070 s) climate and land use change scenarios. For each scenario, we identified the suitable habitat area and evaluated the effectiveness of protected areas (PAs). Our findings revealed a decline in khulan habitat area from 133,006 km2 in the past to 60,141 km2 at present. Future scenarios indicate further reductions in potential khulan habitat, with more negative impacts resulting from climate change than land use change. Northern Xinjiang is expected to persist as a primary area of both in-situ and ex-situ refugia for khulan in future scenarios. Although suitable habitat within existing PAs is smaller than that outside, the rates of habitat loss and fragmentation outside the PAs surpass those inside PAs. These findings emphasize the importance of effective management strategies for PAs as crucial goals for ongoing conservation efforts for the khulan. Our models suggest that future suitable habitat for khulan will be situated along the international border between China and Mongolia, adjacent to protected areas in Mongolia utilized by khulan. Enhancing connectivity between these habitats could significantly contribute to improving both the climate and genetic resilience of khulan populations.

Present and future distribution of the deep-sea habitat-forming sponge - Pheronema carpenteri ( ) in a changing ocean

Sponges play vital roles in the ecosystem function of the deep sea. Some species, such as the birds' nest sponge Pheronema carpenteri, can form highly structured and dense habitats (i.e., aggregations), which contribute to the increase of nearby biodiversity. Climate change is expected to have a pronounced impact on the deep sea, particularly on Vulnerable Marine Ecosystems such as those formed by the glass sponge Pheronema carpenteri. These ecosystems are especially vulnerable to climate change and other anthropogenic activities since they are formed by sensitive species with slow growth rates and limited dispersal capability, which can hinder their adaptive capability and recovery after disturbance. The impact that climate change will have on Pheronema carpenteri remains unclear, although it is expected to influence the species' available suitable habitat and distribution range. The aim of this study was to predict the distribution of the glass sponge Pheronema carpenteri both for present day and under several future climate scenarios in the North Atlantic. An ensemble modelling approach was employed, combining Maximum Entropy, Generalized Additive Models and Random Forest techniques. Changes in available suitable habitat were projected to present day and to three future climatic scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). Depth, temperature and dissolved oxygen were identified as the key predictor variables of habitat suitability, which patterns suggest a strong influence of the Mediterranean Outflow Water in shaping the present day distribution of the species, particularly in the eastern North Atlantic. Our results indicate a potential expansion of available suitable habitat in the northernmost region of the study area, with a contraction at lower latitudes, more prominent in the Portuguese archipelago of the Azores. Under the worst-case scenario (RCP 8.5), the area of suitable habitat will likely double compared to present, occupying approximately 6% of the total study area. The management and conservation of areas where Pheronema aggregations can occur should be articulated between different countries, particularly in the Northeast Atlantic since, cumulatively, most of Pheronema's climate refugia occurs within their EEZs. Nonetheless, a significant proportion of the species' climate refugia is located in areas within the High Seas (i.e., Rockall plateau).

"Two zones and three centers" distribution and suitable areas shift of an evergreen oak in subtropical China under climate scenarios.

Understanding the impact of climate change on the geographical distribution of species is a fundamental requirement for biodiversity conservation and resource management. Quercus oxyphylla, an evergreen oak endemic to China, plays a crucial role in maintaining the ecological stability in subtropical regions and high economic value attributed to its dark and high-density heartwood, but the existing resources are close to endangered. Currently, limited knowledge exists regarding its distribution and potential influences of climate change on suitable areas. This study utilized 63 occurrence records and Biomod2 platform, to predict changes in suitable areas for Q. oxyphylla under future climate change. The results revealed that (1) Q. oxyphylla showed a pattern of three disjunctive geographical centers in the eastern subregion of subtropical evergreen broad-leaved forest region (IVA): Qinling-Daba Mountains, Nanling Mountains and Wuyi Mountains center. Currently, the highly suitable areas concentrated in two zones divided by the Yangtze River, that is, the northern subtropical evergreen and deciduous broad-leaved forest zone (IVAii) and the mid-subtropical evergreen broad-leaved forest zone (IVAi). (2) The temperature-related variables, such as annual temperature range (Bio7), the mean diurnal range (Bio2), and annual mean temperature (Bio1), were identified as the key determinants of the distribution pattern. Because of its considerable climatic variations in temperature and water conditions, Q. oxyphylla's habitat displayed a wider climate niche and strong physiological tolerance to climate change. (3) Under future climate scenarios, the suitable area of the species was expected to overall expand with significant regional differences. The suitable area in IVAi was expected to expand significantly northward while that in IVAii was expected to gradually shrink. To address the impact of climate change, it is necessary to develop conservation plans focused around the three distribution centers, implement localized and regional conservation policies, and conduct educational outreach among local people.

Global prospects for cultivating Centella asiatica: An ecological niche modeling approach under current and future climatic scenarios

Centella asiatica is a medicinal plant recognized for its various benefits contributed by its metabolites and has been used as a food supplement since prehistorical times across various cultures. Due to the reliance on natural populations of C. asiatica and the impacts of environmental factors on its yield and centelloside production, there is a need to identify suitable cultivation areas for this species. We employed ecological niche modelling with bioclimatic and soil variables to evaluate the suitability of cultivation under current and future climatic scenarios. Our results identified suitable areas for cultivating C. asiatica worldwide, indicating its potential for global commercial cultivation. However, the niche reconstruction of highly concentrated centelloside was restricted to South and Southeast Asia due to the lack of available data. When we projected the modelled niche of centelloside in these regions, we observed a lower occurrence probability in some areas, suggesting potential challenges in cost-effectiveness. Nevertheless, our results suggest a consistent future distribution for this species when we projected the modelled niche under future climates based on various socio-economic scenarios. This study not only identifies suitable areas to develop commercial cultivation for C. asiatica with highly concentrated centelloside, but also provides supporting evidence of the consistency of these areas, which can increase its sustainability.

A greater negative impact of future climate change on vegetation in Central Asia: Evidence from trajectory/pattern analysis

In the context of global warming, vegetation changes exhibit various patterns, yet previous studies have focused primarily on monotonic changes, often overlooking the complexity and diversity of multiple change processes. Therefore, it is crucial to further explore vegetation dynamics and diverse change trajectories in this region under future climate scenarios to obtain a more comprehensive understanding of local ecosystem evolution. In this study, we established an integrated machine learning prediction framework and a vegetation change trajectory recognition framework to predict the dynamics of vegetation in Central Asia under future climate change scenarios and identify its change trajectories, thus revealing the potential impacts of future climate change on vegetation in the region. The findings suggest that various future climate scenarios will negatively affect most vegetation in Central Asia, with vegetation change intensity increasing with increasing emission trajectories. Analyses of different time scales and trend variations consistently revealed more pronounced downward trends. Vegetation change trajectory analysis revealed that most vegetation has undergone nonlinear and dramatic changes, with negative changes outnumbering positive changes and curve changes outnumbering abrupt changes. Under the highest emission scenario (SSP5-8.5), the abrupt vegetation changes and curve changes are 1.7 times and 1.3 times greater, respectively, than those under the SSP1-2.6 scenario. When transitioning from lower emission pathways (SSP1-2.6, SSP2-4.5) to higher emission pathways (SSP3-7.0, SSP5-8.5), the vegetation change trajectories shift from neutral and negative curve changes to abrupt negative changes. Across climate scenarios, the key climate factors influencing vegetation changes are mostly evapotranspiration and soil moisture, with temperature and relative humidity exerting relatively minor effects. Our study reveals the negative response of vegetation in Central Asia to climate change from the perspective of vegetation dynamics and change trajectories, providing a scientific basis for the development of effective ecological protection and climate adaptation strategies.