Potential Geographic Distribution Of Species Research Articles

Predicting the response of three common subtropical tree species in China to climate change

IntroductionClimate is crucial factor influencing species distribution, and with global climate change, the potential geographic distribution of species will also alter. In this study, three subtropical tree species (Cunninghamia lanceolata, Pinus taiwanensis, and Quercus glauca) of great ecological values were selected as research objects.MethodsWe applied a maximum entropy (MaxEnt) to predict their potential distributions under different climate scenarios in both present and future conditions based on 37 environmental factors. Jackknife test was used in key factors affecting species distribution. In addition, we explored the key environmental variables that affect their distributions and revealed the evolutionary patterns and migration trends of these tree species under future climate.ResultsThe main findings are as follows: (1) Winter temperature, winter precipitation, and annual temperature range are identified as the key environmental variables affecting the potential geographic distribution of the three tree species; moreover, precipitation-related factors have a greater impact than temperature-related factors; (2) Currently suitable habitats for these three tree species are primarily located in subtropical China with decreasing suitability from south to north; (3) Under future climate conditions, the area of potentially suitable habitat for C. lanceolata continues to expand, while P. taiwanensis and Q. glauca tend to experience a reduction due to increasing greenhouse gas emissions over time; and (4) The centroid of suitable habitat for C. lanceolata shifts northward under future climate change, while the centroid of P. taiwanensis and Q. glauca move southward along with shrinking suitable habitat area.DiscussionOur predictions highlight a high risk of habitat loss of Q. glauca under climate change, recommending management and conservation references for these three commonly used afforestation species under current and future climate change scenarios in China.

Distributional Response of the Rare and Endangered Tree Species Abies chensiensis to Climate Change in East Asia.

Globally, increasing temperatures due to climate change have severely affected natural ecosystems in several regions of the world; however, the impact on the alpine plant may be particularly profound, further raising the risk of extinction for rare and endangered alpine plants. To identify how alpine species have responded to past climate change and to predict the potential geographic distribution of species under future climate change, we investigated the distribution records of A. chensiensis, an endangered alpine plant in the Qinling Mountains listed in the Red List. In this study, the optimized MaxEnt model was used to analyse the key environmental variables related to the distribution of A. chensiensis based on 93 wild distribution records and six environmental variables. The potential distribution areas of A. chensiensis in the last interglacial (LIG), the last glacial maximum (LGM), the current period, and the 2050s and 2070s were simulated. Our results showed that temperature is critical to the distribution of A. chensiensis, with the mean temperature of the coldest quarter being the most important climatic factor affecting the distribution of this species. In addition, ecological niche modeling analysis showed that the A. chensiensis distribution area in the last interglacial experiencing population expansion and, during the last glacial maximum occurring, a population contraction. Under the emission scenarios in the 2050s and 2070s, the suitable distribution area would contract significantly, and the migration routes of the centroids tended to migrate toward the southern high-altitude mountains, suggesting a strong response from the A. chensiensis distribution to climate change. Collectively, the results of this study provide a comprehensive and multidimensional perspective on the geographic distribution pattern and history of population dynamics for the endemic, rare, and endangered species, A. chensiensis, and it underscores the significant impact of geological and climatic changes on the geographic pattern of alpine species populations.

A Model-Based Assessment for the Ability of National Nature Reserves to Conserve the Picea Species in China under Predicted Climate Conditions

Climate change has a profound impact on the conservation and management of the Picea species, and establishing more nature reserves would be an effective way to conserve wild species in general. Based on a novel computational method using ecological niche modeling to predict the potential geographical distribution of species and a spatial decision support system, the planning process could predict the future distribution of the Picea species and thus select appropriate nature reserves. In this research, we utilized systematic conservation planning to define priority conservation areas for the Picea species in China according to future climate predictions. We hypothesized that: (1) the distribution of the Picea species could be changed under predicted climate conditions in China; (2) the current national nature reserves had sufficient capacity to conserve Picea species under predicted climate conditions in China; and (3) there were still deficiencies in the planned conservation for the Picea species based on predicted climate predictions in China. The results of a spatial analysis showed that the predicted climate would have an impact on the area of distribution of the Picea species. Current nature reserves have a strong potential to conserve the Picea species. However, the conservation of the Picea species in the existing nature reserves was not adequate. There were still many Picea specimens outside the reserve that would be threatened. This research systematically improved the research on the Picea species, and it also scientifically identified the suitable growth and conserved areas of the Picea species in China to provide an empirical basis for the conservation and management of the Picea species.

Prediction of the potential geographical distribution of Betula platyphylla Suk. in China under climate change scenarios.

Climate is a dominant factor affecting the potential geographical distribution of species. Understanding the impact of climate change on the potential geographic distribution of species, which is of great significance to the exploitation, utilization, and protection of resources, as well as ecologically sustainable development. Betula platyphylla Suk. is one of the most widely distributed temperate deciduous tree species in East Asia and has important economic and ecological value. Based on 231 species distribution data points of Betula platyphylla Suk. in China and 37 bioclimatic, soil, and topography variables (with correlation coefficients < 0.75), the potential geographical distribution pattern of Betula platyphylla Suk. under Representative Concentration Pathway (RCP) climate change scenarios at present and in the 2050s and 2070s was predicted using the MaxEnt model. We analyzed the main environmental variables affecting the distribution and change of suitable areas and compared the scope and change of suitable areas under different climate scenarios. This study found: (1) At present, the main suitable area for Betula platyphylla Suk. extends from northeastern to southwestern China, with the periphery area showing fragmented distribution. (2) Annual precipitation, precipitation of the warmest quarter, mean temperature of the warmest quarter, annual mean temperature, and precipitation of the driest month are the dominant environmental variables that affect the potential geographical distribution of Betula platyphylla Suk. (3) The suitable area for Betula platyphylla Suk. is expected to expand under global warming scenarios. In recent years, due to the impact of diseases and insect infestation, and environmental damage, the natural Betula platyphylla Suk. forest in China has gradually narrowed. This study accurately predicted the potential geographical distribution of Betula platyphylla Suk. under current and future climate change scenarios, which can provide the scientific basis for the cultivation, management, and sustainable utilization of Betula platyphylla Suk. resources.

A prediction of suitable habitat mapping of Pinus roxburghii sarg. using maxent modeling

Prediction of the potential geographic distribution of species is essential concerning various purposes in protection and conservation. The present study focused on predicting the distribution of Pinus roxburghii Sarg. (chir pine) in Uttarakhand Himalayas using the MaxEnt model. The model produced AUC curve with significant value of 0.882 (± 0.023). The study results showed that 426200 ha (5.91%) cover highly potential habitat area for chir pine. Whereas 833900 ha (11.56%), 1019200 ha (14.13%) and 4936000 ha (68.41%) cover good potential, moderately potential and least potential habitat areas, respectively. Based on the jacknife test, it was observed that temperature seasonality (bio4), precipitation of seasonality (bio15) and precipitation of driest month (bio14) are the significant contributors to the occurrence of chir pine in Uttarakhand Himalayas. This study exemplifies the usefulness of the prediction model of species distribution and offers a more effective way to manage chir pine forest by all means, which is beneficial for both the wildlife and human beings for future prospects.

Identifying prioritized planting areas for medicinal plant Thesium chinense Turcz. under climate change in China

As an important plant resource in China, medicinal plants dominate the Chinese herbal medicine market. The intensified human activities and the deteriorated ecological environment have caused the reduction or even extinction of medicinal plants nationwide. The artificial bionic cultivation of medicinal plants has become an important way for the healthy development of the Chinese medicine industry, given the increasing demand for Chinese medicinal materials. However, the blind introductions of medical plants ignoring the planting area's environmental suitability will waste many human and financial resources. Currently, species distribution models, widely used to predict the potential geographic distribution of species, enable the proper planning of prioritized planting areas with fully considered climatic factors. To scientifically and reasonably determine the best planting area of medicinal materials under current and future climate, we used the MaxEnt model to predict the suitable habitat for Thesium chinense Turcz., and determined the potential migration trends of its suitable areas. In addition, we also evaluated the main environmental variables that affect the distribution of T. chinense. In all the suitable habitat predictions, the training and testing area under the curve (AUC) values were greater than 0.9, indicating the robust performance of our model. Meanwhile, we found that annual mean temperature (Bio1), the maximum temperature of the warmest month (Bio5), annual temperature range (Bio7) and annual precipitation (Bio12) are the main environmental variables determining the T. chinense distribution, with the temperature being the most important factor under bionic cultivation conditions. The potential distribution areas of T. chinense are mainly the provinces along the middle and lower reaches of the Yangtze River. Under the future climate scenario, the highly suitable areas of T. chinense will generally increase, with the distribution ranges extending to higher latitudes. The Yellow River Basin may become another important planting area of T. chinense. Overall, the analysis provided the scientific basis for planning prioritized planting areas and improving bionic cultivation management techniques.

Potential geographical distribution and environmental explanations of rare and endangered plant species through combined modeling: A case study of Northwest Yunnan, China.

In recent decades, due to the effect of climate change and the interference of human activities, the species habitat index has fallen by 2%. Studying on the geographical distribution pattern and predicting the potential geographical distribution of species are of great significance for developing scientific and effective biodiversity conservation strategies. Plenty of rare and endangered species that need immediate conservation are distributed in Northwest Yunnan. In this regard, this research is conducted in the purpose of predicting the potential geographical distribution of 25 rare and endangered plant species in Northwest Yunnan and analyzing the explanation capabilities of various environmental factors on the potential geographical distribution patterns of these species. Initially, the ecological niche model MaxEnt was employed to predict the potential geographical distribution of target species. Following that, the superposition method was applied to obtain the potential geographical distribution pattern of species richness on the spatial scale of the ecological niche model with a resolution of 0.05° × 0.05°. Ultimately, geographically weighted regression (GWR) model was adopted to investigate the explanation capabilities of various environmental parameters on the potential distribution patterns. The research results showed that the average value of the area under the receiver operating curve (AUC) of each species was between 0.80 and 1.00, which indicated that the simulation accuracy of the MaxEnt model for each species was good or excellent. On the whole, the potential distribution area for each species was relatively concentrated and mainly distributed in the central‐western, central‐eastern and northern regions of Northwest Yunnan. In addition, the potential distribution areas of these species were between 826.33 km2 and 44,963.53 km2. In addition, the annual precipitation (Bio12), precipitation of coldest quarter (Bio19), and population density (Pop) made a greater contribution to the species distribution model, and their contribution values were 25.92%, 15.86%, and 17.95%, respectively. Moreover, the goodness‐of‐fit R 2 and AIC value of the water model were 0.88 and 7,703.82, respectively, which indicated the water factor largely influenced the potential distribution of these species. These results would contribute to a more comprehensive understanding of the potential geographical distribution pattern and the distribution of suitable habitats of some rare and endangered plant species in Northwest Yunnan and would be helpful for implementing long‐term conservation and reintroduction for these species.

Assessing the impact of climate change on the distribution of Osmanthus fragrans using Maxent.

Models that evaluate the potential geographic distribution of species can be used with a variety of important applications in conservation biology. Osmanthus fragrans has high ornamental, culinary, and medicinal value, and is widely used in landscaping. However, its preferred habitat and the environmental factors that determine its distribution remain largely unknown; the environmental factors that shape its suitability also require analysis. Based on 89 occurrence records and 30 environmental variables, this study constructed Maxent models for current as well as future appropriate habitats for O. fragrans. The results indicate that UV-B seasonality (19.1%), precipitation seasonality (18.8%), annual temperature range (13.1%), and mean diurnal temperature range (12.5%) were the most important factors used for interpreting the environmental demands for this species. Highly appropriate habitats for O. fragrans were mainly distributed in southwestern Jiangsu, southern Anhui, Shanghai, Zhejiang, Fujian, northern Guangdong, Guangxi, southern Hunan, southern Hubei, Sichuan, and Taiwan. Under climate change scenarios, the spatial extent of the area of suitable distribution will decrease, and the distribution center of O. fragrans will shift to the southwest. The results of this study will help land managers to avoid blindly introducing this species into inappropriate habitat while improving O. fragrans yield and quality.

基于MAXENT模型评估北部湾潮间带中国鲎和圆尾鲎稚鲎的潜在地理分布及种群保育对策

PDF HTML阅读 XML下载 导出引用 引用提醒 基于MAXENT模型评估北部湾潮间带中国鲎和圆尾鲎稚鲎的潜在地理分布及种群保育对策 DOI: 10.5846/stxb201805161079 作者: 作者单位: 1水产科学国家级实验教学示范中心(上海海洋大学) 201306 2海洋生物科学国际联合研究中心(上海海洋大学)，中国科学技术部 201306 3上海水产养殖工程技术研究中心(上海海洋大学) 201306,广西壮族自治区水产科学研究院,天津市一瑞生物工程有限公司,上海海洋大学信息学院,1水产科学国家级实验教学示范中心(上海海洋大学) 201306 2海洋生物科学国际联合研究中心(上海海洋大学)，中国科学技术部 201306 3上海水产养殖工程技术研究中心(上海海洋大学) 201306,1水产科学国家级实验教学示范中心(上海海洋大学) 201306 2海洋生物科学国际联合研究中心(上海海洋大学)，中国科学技术部 201306 3上海水产养殖工程技术研究中心(上海海洋大学) 201306 作者简介: 通讯作者: 中图分类号: 基金项目: 香港海洋公园保育基金（OT03.1617）；2017北海市"十三五"海洋经济创新发展示范项目（Bhsfs006） Prediction of potential distribution areas of Chinese horseshoe crab and mangrove horseshoe crab in the Beibu Gulf of Guangxi based on MAXENT model and their population conservation strategies Author: Affiliation: National Demonstration Center for Experimental Fisheries Science Education,Shanghai Ocean University,Shanghai,,,,National Demonstration Center for Experimental Fisheries Science Education,Shanghai Ocean University,Shanghai,National Demonstration Center for Experimental Fisheries Science Education,Shanghai Ocean University,Shanghai Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:鲎具有极高的经济价值和科研意义。近年来由于过度捕捞和栖息地受损等原因，亚洲鲎种群数量正急剧下降。鲎漫长的生命周期使得鲎资源的保护和增殖迫在眉睫。生态位模型已经广泛应用于物种的潜在地理分布预测。基于实地调研数据和公开发表的北部湾中国海域中国鲎和圆尾鲎地理分布数据，运用MAXENT模型得到中国鲎和圆尾鲎在广西北部湾（中国部分）的栖息地适宜度指数（Habitat suitability index，HSI），确定了这两种稚鲎在北部湾中国海域潜在适生区。模型分析结果表明，潮间带坡度和地形指数是影响中国鲎分布的主要环境因子，而潮间带底质的有机物含量和植被指数是影响圆尾鲎分布的主要环境因子，根据研究结果建议在两种稚鲎适生区建立保护区，进行人工放流稚鲎，加强对海草和红树林的生态建设，进而促进鲎资源种群恢复和发展。 Abstract:Horseshoe crab has high economic and scientific values. In recent years, because of overfishing and habitat degradation, the population of horseshoe crabs in China is decreasing rapidly. However, their long life cycle makes it extremely urgent to protect horseshoe crabs. Ecological niche models have been widely applied to predict the potential geographic distribution of species. The habitat suitability index of the Chinese horseshoe crab Tachypleus tridentatus and mangrove horseshoe crab Carcinoscorpius rotundicauda in the Beibu Gulf (Chinese part) was determined by using the maximum entropy model and the distribution of habitat suitability of the two types of juvenile horseshoe crab in the Beibu Gulf was determined based on field survey data and published data on the geographical distribution of two horseshoe crab species in the Beibu Gulf. The model analysis results showed that the slope of the intertidal zone and topographic index were the main environmental factors affecting the distribution of the Chinese horseshoe crab, while the organic content and vegetation index of intertidal sediment were the main environmental factors affecting the distribution of the mangrove horseshoe crab. According to the results, to promote the recovery and development of horseshoe crab resources, protected areas should be established, artificial release of juvenile horseshoe crabs in habitat suitability areas of horseshoe crab should be conducted, and the ecological construction of seagrasses and mangroves in these areas should be strengthened. 参考文献 相似文献 引证文献

Trends and biases in global scientific literature about ecological niche models.

Recently, ecological niche models have been employed to investigate the potential geographical distribution of species. However, it is necessary to analyze the vast number of publications on this topic to understand the trends and biases of research using ecological niche models (ENMs). Therefore, this study aims to investigate trends in the scientific literature regarding studies on ENMs. For the quantitative analysis of the literature on ENMs, we performed a search in the Thomson ISI (Web of Science) database between 1991 and 2013. The search identified 3042 papers containing preselected keywords in either the title or abstract. The results showed that the number of papers has increased over the years (r=0.77, P<0.001), with a sharp increase in recent years, highlighting the widespread use of the ENMs. There was an increase in the diversity of journals that published papers about ENMs (r=0.97, P<0.001). The research was conducted in different countries, predominantly the United States of America (550 papers), and the most commonly used method was the Maximum Entropy method (312 papers). Regarding the taxonomic group, most research has been conducted on plants (402 papers, or 28.36% of the total). There was no relationship between the modeling method used and the taxonomic group studied (χ2=4.8, P=0.15). Finally, the wide availability of biological, environmental and computational resources has elicited the broad use of tools for ENMs. Despite the conceptual discussions of the ENMs, this method is currently the most effective way to evaluate the potential geographical distribution of species, and to predict the distribution under different environmental conditions (i.e., future or past scenarios).

Climate change effects on the geographic distribution of specialist tree species of the Brazilian tropical dry forests.

The aim of this study was to evaluate the ecological niche models (ENMs) for three specialist trees (Anadenanthera colubrina, Aspidosperma pyrifolium and Myracrodruon urundeuva) in seasonally dry tropical forests (SDTFs) in Brazil, considering present and future pessimist scenarios (2080) of climate change. These three species exhibit typical deciduousness and are widely distributed by SDTF in South America, being important in studies of the historical and evolutionary processes experienced by this ecosystem. The modeling of the potential geographic distribution of species was done by the method of maximum entropy (Maxent).We verified a general expansion of suitable areas for occurrence of the three species in future (c.a., 18%), although there was reduction of areas with high environmental suitability in Caatinga region. Precipitation of wettest quarter and temperature seasonality were the predictor variables that most contributed to our models. Climatic changes can provide more severe and longer dry season with increasing temperature and tree mortality in tropics. On this scenario, areas currently occupied by rainforest and savannas could become more suitable for occurrence of the SDTF specialist trees, whereas regions occupied by Caatinga could not support the future level of unsustainable (e.g., aridity). Long-term multidisciplinary studies are necessary to make reliable predictions of the plant's adaptation strategies and responses to climate changes in dry forest at community level. Based on the high deforestation rate, endemism and threat, public policies to minimize the effects of climate change on the biodiversity found within SDTFs must be undertaken rapidly.