Effects of road network on Asian elephant habitat and connectivity between the nature reserves in Xishuangbanna,Southwest China

Evaluating road effects on the ecological status and landscape connectivity is critical for animal corridor design. Taking the fragmented nature reserves in Xishuangbanna as a case, road impacts on Asian elephant habitats were determined based on a suitability analysis. Potential corridors between different sub-reserves were located using “least-cost” method as a systematic way incorporating remote sensing (RS) and geographic information system (GIS). Our results revealed that road networks, especially high-level roads (expressway, national road and city-county city road), had the largest effects on the suitability according to the sensitivity analysis. Suitability ( > 40) area will increase about 40% if there were no high-level roads. In total, seven potential linkages were located and found to be capable of connecting the habitats of the four sub-reserves. We suggested the Menglun reserve could serve as a stepping-stone for elephant migration. Four further conservation priorities were also identified between the Menglun reserve and the Mengla reserve where the road impacts were intensive. Our study provided information for the development of an efficient reserve network for elephant conservation between existing nature reserves in China and neighboring provinces in Lao PDR.     

Predicting potential impacts of climate change on freshwater fish in Korea

Climate change is expected to have profound effects on the distribution and phenology of species and the productivity of aquatic ecosystem. In this study, we projected the impacts of climate change on the distributions of 22 endemic fish species in Korea with climatic and geographical variables by using species distribution models (SDMs). Six different SDMs – linear discriminant analysis, generalized linear model, classification and regression trees, random forest, support vector machine, and multivariate adaptive regression splines – were implemented for the prediction, and compared for their prediction capacity. The results showed that the random forest displayed the highest predictive power for the prediction of current species distributions. Therefore, the random forest was used to assess the potential impacts of climate change on the distributions of 22 endemic fish species. The results revealed that five species (Acheilognathus yamatsutae, Sarcocheilichthys variegatus wakiyae, Squalidus japonicus coreanus, Microphysogobio longidorsalis, and Liobagrus andersoni) have a high probability of becoming extinct in their respective habitable sub-watersheds by the 2080s due to climate change. The sensitivity analysis of the model showed that geo-hydrological variables such as stream order and altitude and temperature-related variables such as mean temperature in January and difference between the minimum and maximum temperatures exhibited relatively higher importance in their contributions for the prediction of species occurrence than that other variables. The decline of endemic fish species richness, and their occurrence probability due to climate change, would lead to poleward and upward shifts, as well as extinctions of species. Finally, we believe that our projections are useful for understanding how climate change affects the distribution range of endemic species in Korea, while also providing the necessary information to develop preservation and conservation strategies for maintaining endemic fish.     

Identifying potential conservation areas in the Cuitzeo Lake basin,Mexico by multitemporal analysis of landscape connectivity

Lake Cuitzeo basin is an important ecological area subjected to strong human pressure on forest covers that are key elements for the long-term support of biodiversity. We studied landscape connectivity changes for the years 1975, 1996, 2000, 2003 and 2008 to identify potential conservation areas in the basin. We modeled potential distributions of the Mexican bobcat (Lynx rufus escuinapae) and the ringtail (Bassariscus astutus) – two terrestrial mammal focal species with contrasting dispersal capacities – and we determined their habitat availability and suitability in the basin. We then identified their optimal habitat patches and produced landscape cumulative resistance maps, estimated least-cost paths (graph theory approach), and elaborated current flow maps (circuit theory approach). For evaluation of landscape connectivity, we applied an integral index of connectivity (IIC) to each study period, and determined individual habitat patch contribution to the overall landscape connectivity. The IIC index had very low values associated with reduced availability of focal species habitat. However, our study showed the conservation importance of the surface of optimal habitat patch areas. The combined application of a graph-based approach and current flow mapping were useful, and complementary both in terms of estimating potential dispersal corridors and identifying high probability dispersal areas. This indicated that landscape connectivity analysis is a useful tool for identification of potential conservation areas and for local landscape planning.     

Predicting the impacts of climate change on the distribution of threatened forest‐restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo‐presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real‐presence data with forest layer are better predictors than those from pseudo‐presence data. Using real‐presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.     

Potential impacts of climate change on habitat suitability of Fagus sylvatica L. forests in spain

Abstract

Fagus sylvatica forests are considered to be of Community interest according to Directive 92/43/EEC. Climate change predictions for Spain point to a warming scenario, coupled with decreasing rainfall, which may have an impact on their future distribution particularly at the extremes of its distribution area. Species distribution models incorporating bioclimatic, topographic and phytogeographic variables were used as predictors to assess their habitat suitability under current conditions and a climate change projection. Ten single models were generated and an ensemble-forecasting model was subsequently built by computing a consensus of single-model projections. The results revealed that ombrothermic indices are the main factors controlling the distribution of Spanish beech forests. They are highly vulnerable to climate change and could suffer a decline in their habitat suitability if climate trends observed are maintained in the future. The least favoured areas for them will be located close to the limit between the Temperate and Mediterranean climates, where they could suffer a loss of habitat suitability. Conversely, suitable new areas could be found mainly in western areas of the Cantabrian Range and in the Central Pyrenees.     

Predicting global change impacts on plant species’ distributions: Future challenges

Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species’ range shifts, changes in phenology and species’ extinctions, accurate projections of species’ responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species’ responses to future environmental changes.

There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species’ distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the “trailing edge” of shifting populations, species’ interactions and the interaction between the effects of climate and land-use.

In this review, we propose two main avenues to progress the understanding and prediction of the different processes occurring on the leading and trailing edge of the species’ distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species’ migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species’ distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world.     

Forecasting climate change impacts on the distribution of wetland habitat in the Midwestern United states

Shifting precipitation patterns brought on by climate change threaten to alter the future distribution of wetlands. We developed a set of models to understand the role climate plays in determining wetland formation on a landscape scale and to forecast changes in wetland distribution for the Midwestern United States. These models combined 35 climate variables with 21 geographic and anthropogenic factors thought to encapsulate other major drivers of wetland distribution for the Midwest. All models successfully recreated a majority of the variation in current wetland area within the Midwest, and showed that wetland area was significantly associated with climate, even when controlling for landscape context. Inferential (linear) models identified a consistent negative association between wetland area and isothermality. This is likely the result of regular inundation in areas where precipitation accumulates as snow, then melts faster than drainage capacity. Moisture index seasonality was identified as a key factor distinguishing between emergent and forested wetland types, where forested wetland area at the landscape scale is associated with a greater seasonal variation in water table depth. Forecasting models (neural networks) predicted an increase in potential wetland area in the coming century, with areas conducive to forested wetland formation expanding more rapidly than areas conducive to emergent wetlands. Local cluster analyses identified Iowa and Northeastern Missouri as areas of anticipated wetland expansion, indicating both a risk to crop production within the Midwest Corn Belt and an opportunity for wetland conservation, while Northern Minnesota and Michigan are potentially at risk of wetland losses under a future climate.     

Anthropogenic impact on habitat connectivity: A multidimensional human footprint index evaluated in a highly biodiverse landscape of Mexico

Evaluating the cumulative effects of the human footprint on landscape connectivity is crucial for implementing policies for the appropriate management and conservation of landscapes. We present an adjusted multidimensional spatial human footprint index (SHFI) to analyze the effects of landscape transformation on the remnant habitat connectivity for 40 terrestrial mammal species representative of the Trans-Mexican Volcanic System in Michoacán (TMVS_Mich), in western central Mexico. We adjusted the SHFI by adding fragmentation and habitat loss to its original three components: land use intensity, time of human landscape intervention, and biophysical vulnerability. The adjusted SHFI was applied to four scenarios: one grouping all species and three grouping several species by habitat spatial requirements. Using the SHFI as a dispersal resistance surface and applying a circuit theory based approach, we analyzed the effects of cumulative human impact on habitat connectivity in the different scenarios. For evaluating the relationship between habitat loss and connectivity, we applied graph theory-based equivalent connected area (ECA) index. Results show over 60% of the TMVS_Mich has high SHFI values, considerably lowering current flow for all species. Nevertheless, the effect on connectivity of human impact is higher for species with limited dispersal capacity (100–500 m). Our approach provides a new form of evaluating human impact on habitat connectivity that can be applied to different scales and landscapes. Furthermore, the approach is useful for guiding discussions and implementing future biodiversity conservation initiatives that promote landscape connectivity as an adaptive strategy for climate change.     

基于模糊数学的秦岭地区山茱萸生境适宜性评价

山茱萸(Cornus officinalis)是我国传统常用药材,本文采用模糊数学分析方法,对采自秦岭地区的山茱萸中马钱苷含量与21个评价因子的隶属函数进行拟合,同时采用最大信息熵模型确定各个评价因子的权重,利用ArcGIS 10空间分析模块模拟研究区域适宜山茱萸生长的潜在分布生境。结果表明,在山茱萸生境的21个评价因子中,主要影响因子为气候,其次是土壤和地形因子;所有评价因子中,土壤质地(TTEX)的权重最大,其次是果实生长期降水量(PG)、年降水量(AP)和降水季节性变化(PS)。研究区内山茱萸高适宜区面积占总面积的19.94%,主要分布在甘肃东南部、陕西南部和河南西部,这些区域温度适中、气候湿润、光照充足,适宜山茱萸生长;适宜区面积占总面积的11.85%,低适宜区面积占总面积的16.31%,不适宜区面积占总面积的51.90%。本研究基于GIS与模糊数学的生境适宜性评价模型,对秦岭地区山茱萸生境适宜性做出了科学划分,同时量化了不同生境区的评价因子对山茱萸的影响,可为山茱萸的管理和保护以及人工种植提供科学依据。     

Spatio-temporal analysis of Egyptian flower mantis Blepharopsis mendica (order: mantodea), with notes of its future status under climate change

Egyptian flower mantis Blepharopsis mendica (Order: Mantodea) is a widespread mantis species throughout the southwest Palearctic region. The ecological and geographical distribution of such interesting species is rarely known. So, through this work, habitat suitability models for its distribution through Egyptian territory were created using MaxEnt software from 90 occurrence records. One topographic (altitude) and eleven bioclimatic variables influencing the species distribution were selected to generate the models. The predicted distribution in Egypt was focused on the Delta, South Sinai, the north-eastern part of the country, and some areas in the west including Siwa Oasis. Temporal analysis between the two periods (1900–1961) and (1961–2017) show current reduction of this species distribution through Delta and its surrounding areas, may be due to urbanization. On the other hand, it increases in newly protected areas of South Sinai. Under the future climate change scenario, the MaxEnt model predicted the habitat gains for B. mendica in RCP 2.6 for 2070 and loss of habitat in RCP 8.5 for the same year. Our results can be used as a basis for conserving this species not only in Egypt, but also throughout the whole of its range, also, it show how the using of geo-information could help in studying animal ecology.     

Bayesian analysis of climate change impacts in phenology

The identification of changes in observational data relating to the climate change hypothesis remains a topic of paramount importance. In particular, scientifically sound and rigorous methods for detecting changes are urgently needed. In this paper, we develop a Bayesian approach to nonparametric function estimation. The method is applied to blossom time series of Prunus avium L., Galanthus nivalis L. and Tilia platyphyllos SCOP. The functional behavior of these series is represented by three different models: the constant model, the linear model and the one change point model. The one change point model turns out to be the preferred one in all three data sets with considerable discrimination of the other alternatives. In addition to the functional behavior, rates of change in terms of days per year were also calculated. We obtain also uncertainty margins for both function estimates and rates of change. Our results provide a quantitative representation of what was previously inferred from the same data by less involved methods.     

Predicting how adaptation to climate change could affect ecological conservation: secondary impacts of shifting agricultural suitability

Aim:  Ecosystems face numerous well‐documented threats from climate change. The well‐being of people also is threatened by climate change, most prominently by reduced food security. Human adaptation to food scarcity, including shifting agricultural zones, will create new threats for natural ecosystems. We investigated how shifts in crop suitability because of climate change may overlap currently protected areas (PAs) and priority sites for PA expansion in South Africa. Predicting the locations of suitable climate conditions for crop growth will assist conservationists and decision‐makers in planning for climate change. Location:  South Africa. Methods:  We modelled climatic suitability in 2055 for maize and wheat cultivation, two extensively planted, staple crops, and overlaid projected changes with PAs and PA expansion priorities. Results:  Changes in winter climate could make an additional 2 million ha of land suitable for wheat cultivation, while changes in summer climate could expand maize suitability by up to 3.5 million ha. Conversely, 3 million ha of lands currently suitable for wheat production are predicted to become climatically unsuitable, along with 13 million ha for maize. At least 328 of 834 (39%) PAs are projected to be affected by altered wheat or maize suitability in their buffer zones. Main conclusions:  Reduced crop suitability and food scarcity in subsistence areas may lead to the exploitation of PAs for food and fuel. However, if reduced crop suitability leads to agricultural abandonment, this may afford opportunities for ecological restoration. Expanded crop suitability in PA buffer zones could lead to additional isolation of PAs if portions of newly suitable land are converted to agriculture. These results suggest that altered crop suitability will be widespread throughout South Africa, including within and around lands identified as conservation priorities. Assessing how climate change will affect crop suitability near PAs is a first step towards proactively identifying potential conflicts between human adaptation and conservation planning.     

Predicting the cumulative effect of multiple disturbances on seagrass connectivity

The rate of exchange, or connectivity, among populations effects their ability to recover after disturbance events. However, there is limited information on the extent to which populations are connected or how multiple disturbances affect connectivity, especially in coastal and marine ecosystems. We used network analysis and the outputs of a biophysical model to measure potential functional connectivity and predict the impact of multiple disturbances on seagrasses in the central Great Barrier Reef World Heritage Area (GBRWHA), Australia. The seagrass networks were densely connected, indicating that seagrasses are resilient to the random loss of meadows. Our analysis identified discrete meadows that are important sources of seagrass propagules and that serve as stepping stones connecting various different parts of the network. Several of these meadows were close to urban areas or ports and likely to be at risk from coastal development. Deep water meadows were highly connected to coastal meadows and may function as a refuge, but only for non‐foundation species. We evaluated changes to the structure and functioning of the seagrass networks when one or more discrete meadows were removed due to multiple disturbance events. The scale of disturbance required to disconnect the seagrass networks into two or more components was on average >245 km, about half the length of the metapopulation. The densely connected seagrass meadows of the central GBRWHA are not limited by the supply of propagules; therefore, management should focus on improving environmental conditions that support natural seagrass recruitment and recovery processes. Our study provides a new framework for assessing the impact of global change on the connectivity and persistence of coastal and marine ecosystems. Without this knowledge, management actions, including coastal restoration, may prove unnecessary and be unsuccessful.     

基于电路理论的滇金丝猴生境景观连通性分析

景观连通性对生态系统服务、动植物基因交流的保护以及景观规划等都具有重要影响作用。以滇金丝猴活动区域为研究对象,基于电路理论建立滇金丝猴栖息地的连接度模型,分析滇金丝猴栖息地间的连通性,对于连通性较好的区域,识别出了重点保护与恢复区域;对于连通性较差的区域,通过电路理论连接度模型确定了影响今后廊道建设的重点保护与恢复区域。结果表明:各区域内部猴群栖息地连通性较好,其中中部地区最优,其次是北部,最差为南部。G3和G4栖息地斑块作为对连接各区域猴群生境斑块起到关键作用的"踏脚石"斑块是今后重点保护与恢复的区域,保护和恢复南部与中部猴群栖息地间"空白区域"的植被对于整个滇金丝猴活动区域的猴群基因交流也尤为重要。方法上,相较于图论得到的单一路径,电路理论得到的多路径更具有现势性。研究方法及研究成果可为濒危物种保护和区域生态廊道设计提供重要参考价值。     

Mapping the habitat suitability of Ottelia species in Africa

Understanding the influence of environmental covariates on plant distribution is critical, especially for aquatic plant species. Climate change is likely to alter the distribution of aquatic species. However, knowledge of this change on the burden of aquatic macroorganisms is often fraught with difficulty. Ottelia, a model genus for studying the evolution of the aquatic family Hydrocharitaceae, is mainly distributed in slow-flowing creeks, rivers, or lakes throughout pantropical regions in the world. Due to recent rapid climate changes, natural Ottelia populations have declined significantly. By modeling the effects of climate change on the distribution of Ottelia species and assessing the degree of niche similarity, we sought to identify high suitability regions and help formulate conservation strategies. The models use known background points to determine how environmental covariates vary spatially and produce continental maps of the distribution of the Ottelia species in Africa. Additionally, we estimated the possible influences of the optimistic and extreme pessimistic representative concentration pathways scenarios RCP 4.5 and RCP 8.5 for the 2050s. Our results show that the distinct distribution patterns of studied Ottelia species were influenced by topography (elevation) and climate (e.g., mean temperature of driest quarter, annual precipitation, and precipitation of the driest month). While there is a lack of accord in defining the limiting factors for the distribution of Ottelia species, it is clear that water-temperature conditions have promising effects when kept within optimal ranges. We also note that climate change will impact Ottelia by accelerating fragmentation and habitat loss. The assessment of niche overlap revealed that Ottelia cylindrica and O. verdickii had slightly more similar niches than the other Ottelia species. The present findings identify the need to enhance conservation efforts to safeguard natural Ottelia populations and provide a theoretical basis for the distribution of various Ottelia species in Africa.     

Determining climate change impacts on ecosystems: the role of palaeontology

Climate change is projected to change the ecosystems on land and in the sea at rates that are unprecedented for millions of years. The most commonly used approach to derive projections of how ecosystems will look in the future are experiments on living organisms. By their nature, experiments are unlike the real world and cannot capture the ability of organisms to migrate, select and evolve. They are often limited to a select few species and drivers of environmental change and hence cannot represent the complexity of interactions in ‘real’ ecosystems. The fossil record is an archive of responses to climate change at a global ecosystem scale. If, and only if, fossil assemblage variation is combined with independent information of environmental changes, sensitives of species or higher taxa to a specific magnitude of change of an environmental driver can be determined and used to inform future vulnerabilities of this species to the same driver. While records are often fragmented, there are time intervals which, when thoroughly analysed with quantitative data, can provide valuable insights into the future of biodiversity on this planet. This review provides an overview of projected impacts on marine ecosystems including: (1) the range of neontological methods, observations and their challenges; and (2) the complementary information that palaeontologists can contribution to this global challenge. I advocate that, in collaborations with other disciplines, we should aim for a strong visibility of our field and the knowledge it can provide for policy relevant assessments of the future.     

Projected impacts of climate change on snow leopard habitat in Qinghai Province,China

Assessing species’ vulnerability to climate change is a prerequisite for developing effective strategies to reduce emerging climate‐related threats. We used the maximum entropy algorithm (MaxEnt model) to assess potential changes in suitable snow leopard (Panthera uncia) habitat in Qinghai Province, China, under a mild climate change scenario. Our results showed that the area of suitable snow leopard habitat in Qinghai Province was 302,821 km² under current conditions and 228,997 km² under the 2050s climatic scenario, with a mean upward shift in elevation of 90 m. At present, nature reserves protect 38.78% of currently suitable habitat and will protect 42.56% of future suitable habitat. Current areas of climate refugia amounted to 212,341 km² and are mainly distributed in the Sanjiangyuan region, Qilian mountains, and surrounding areas. Our results provide valuable information for formulating strategies to meet future conservation challenges brought on by climate stress. We suggest that conservation efforts in Qinghai Province should focus on protecting areas of climate refugia and on maintaining or building corridors when planning for future species management.     

Effect of climate change on the occurrence of overwintered moths of orchards in South Korea

According to the Intergovernmental Panel on Climate Change (IPCC), the global mean surface temperature increased by 0.74°C between 1906 and 2005, and is expected to continue rising. In Korea, the temperature increased rapidly by 1.8°C between 1912 and 2010. The effect of global warming are expected to cause phenological changes in exothermic organisms such as insect pests which are highly dependent on temperature. In present study, we estimated the emergence time of three lepidopteran pests (Carposina sasakii, Grapholita molesta, and Phyllonorycter ringoniella) in apple orchards during 2000, 2020s, 2050s, and 2090s, by means of Representative Concentration Pathway (RCP) 8.5 climate change scenario. In comparison with 2000, the emergence of C. sasakii is predicted to occur 5.5 ± 0.49 days earlier in 2020s, 14.9 ± 0.40 days earlier in 2050s, and 40.0 ± 0.75 days earlier in 2090s; the emergence of G. molesta is predicted to occur 8.2 ± 0.36 days earlier in 2020s, 16.9 ± 0.40 days earlier in 2050s, and 49.7 ± 0.61 days earlier in 2090s; and the emergence of P. ringoniella is predicted to occur 9.0 ± 0.34 days earlier in 2020s, 20.5 ± 0.58 days earlier in 2050s, and 52.5 ± 0.63 days earlier in 2090s. The number of generations a year is expected to increase by 0.5–2.8 generations in 2050s, 1.3–6.7 in 2090s. Our predictions provide basic data for the development of insect pest management strategies in spring under conditions of global warming.     

Predicting the impacts of climate change on the evolutionary adaptations of polar fish

The recognition of the important role of the polar habitats in global climate changes has awakened great interest in the evolutionary biology of the organisms that live there, as well as the increasing threat of loss of biological diversity and depletion of marine fisheries. These organisms are exposed to strong environmental constraints, and it is important to understand how they have adapted to cope with these challenges and to what extent adaptations may be upset by current climate changes. Adaptations of the dominant group of Antarctic fish, the suborder Notothenioidei, have been thoroughly investigated by several teams. Considering the amount of information available on cold adaptation, the study of fish adapted to the extreme conditions of the polar seas will allow us to gain invaluable clues on the development, impact and consequences of climate and anthropogenic challenges, with powerful implications for the future of the Earth.     

Evaluation of the spatial distribution of Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae) in South Korea combining climate and host plant distribution

Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae), a global forest pest, has a potential to damage forests in South Korea, requiring an effective tool for evaluating its potential distribution. This study aimed to evaluate the spatial distribution of A. glabripennis in South Korea by simultaneously considering climate and host plants. Climatic suitability was firstly evaluated using a CLIMEX model; then, it was combined with the areal distribution of host plants using a simple mathematical formulation. We finally projected the spatial distribution of A. glabripennis onto the map of administrative districts to identify hazardous areas to watch. As a result, the developed model predicted that over 40% of areas in South Korea could be exposed to A. glabripennis damage, and most of them were located in mountainous areas with abundant host plants. In addition, climatic suitability was higher in coastal areas, which was different than a previous record of A. glabripennis occurrence, while the prediction by a comprehensive model was consistent with the record. In conclusion, the model including both climate and host plant occurrence was more reliable than the model which only included climate, and could provide useful data for determining areas for monitoring and control.