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1.
Climate is an important factor that affects the livability of a region. The climate suitability of a region’s environment for human settlement profoundly affects the regional socio-economic development and the population distribution. Tibet is an area that is sensitive to climate change. Given the impact of global climate change, the climate suitability of Tibet has undergone significant changes. In this study, the temperature humidity index (THI) values for Tibet were calculated, and the relationships between the population distribution and the THI were analyzed quantitatively. In this way, the zoning standards for climate suitability in Tibet were determined such that the climate suitability could be evaluated. The results show that the average annual temperature in the southeast of Tibet, where the population was densely distributed, was relatively high. The mean annual relative humidity showed a trend of gradually decreasing from south to north. Regions with a suitable climate, including the high suitability areas (HSAs), the moderately suitable areas (MSAs) and the low suitability areas (LSAs), accounted for only 7.90% of the total area but accommodated over 40% of the total population. The critically suitable areas (CSAs) accounted for 37.81% of the land area and 48.24% of the total population. Non-suitable areas (NSAs) were widely distributed in Tibet and accounted for 54.29% of the total area and 11.33% of the total population. The results of this study may provide a reference for guiding the reasonable distribution of population and promoting the optimization of the spatial planning in Tibet. 相似文献
2.
甘达基河流域(Gandaki River Basin,GRB)是喜马拉雅中部地区的一部分,该地区栖息着许多珍稀的野生动物。由于气候和人类活动的影响,许多珍稀保护物种的生境处于危险之中。本研究基于最大熵(MaxEnt)模型,运用生物气候、土地覆被和DEM数据,分析各环境要素对棕尾虹雉(Lophophorusimpejanus)的生境适宜性的影响,评估棕尾虹雉现在状况和未来栖息地分布的变化。研究表明,目前棕尾虹雉的高度适宜栖息地面积约为749 km^2,主要分布在流域北部、东部和西部,尤其是郎塘国家公园、马纳斯卢峰自然保护区和安纳布尔纳峰自然保护区等保护区内。到2050年,棕尾虹雉的高度适宜栖息地面积将减少至561 km^2,主要在流域北部和西北部(即Chhyo,Tatopani,Humde和Chame地区)。未来环境变化的模拟表明,由于适宜栖息地面积的减少,棕尾虹雉面临的生存风险将增加。 相似文献
3.
An Evaluation of the Tourist Potential of the Climate in Catalonia (Spain): A Regional Study 总被引：2，自引：0，他引：2
The many links that exist between tourism and the atmospheric elements point to the need to evaluate the potential of the climate as a resource. This study of the spatial and temporal variations of the climate—tourist potential in Catalonia (Spain) is based on the classification of daily weather situations according to the main combinations of climatic variables in the study area, and is adjusted to reflect bioclimatic criteria and tourist perceptions. The results of the study reveal major differences in the climate—tourist aptitudes of the region and, in general, a high tourist potential. However, given that the climate is not the sole factor intervening in the temporal and spatial distribution of tourist activities in Catalonia, it is apparent that the tourist aptitudes of the Catalan climates are not fully exploited by planning in this sector; thus, the periods of the year and areas identified as being climatically suitable for recreational activities are greater than the actual periods and area dedicated to tourism. 相似文献
4.
秃鹫提供了宝贵的生态系统服务,在生态系统平衡中发挥着重要作用,但印度本土秃鹫数量在过去几年有所下降。掌握秃鹫栖息地的分布现状对于管理和防止秃鹫数量继续下降至关重要。可以预见,目前的气候危机可能会进一步导致秃鹫生境适宜性的变化,并影响现存的秃鹫种群。因此,本研究利用物种分布模型,对印度中部一个秃鹫栖息地的短期和长期变化进行预测,并以统计和图形的方式呈现数据。选择MaxEnt软件进行预测,是因为它与其他模型相比具有一定的优势,如只使用现有数据,在数据不完整、样本量小、样本间隙小等情况下表现良好。采用全球气候模式集成学习算法(CCSM4、Had GEM2AO和MIROC5)以获得更好的预测结果。14个稳健模型(AUC 0.864–0.892)是利用7个秃鹫种群(长喙、白臀、红头、银灰色、埃及秃鹫、喜马拉雅和欧亚狮鹫)在两个季节共1000多个地点的数据建立的。选定的气候(温度和降水)和环境变量(NDVI、海拔和土地利用/土地覆盖)被用于预测当前栖息地,未来的预测只基于气候变量。影响秃鹫栖息地分布的最重要变量是降水量(bio 15,bio 18,bio19)和温度(bio 3,bio 5)。在目前的预测中,森林和水体是影响土地利用的主要因素。在较小尺度上,随着时间的推移,极端适宜的栖息地面积减少,高度适宜的栖息地面积增加,总适宜栖息地面积在2050年略有增加,但到2070年有所减少。在更大的尺度上考虑,2050年适宜栖息地的净损失为5%,2070年为7.17%(RCP4.5)。相似的,在RCP8.5下,2050年适宜栖息地的净损失为6%,2070年为7.3%。研究结果可用于制定秃鹫的保护规划和管理,从而保护其免受未来的气候变化等威胁。 相似文献
5.
Modelling patterned ground distribution in Finnish Lapland:
an integration of topographical, ground and remote sensing information 总被引：3，自引：1，他引：3
New data technologies and modelling methods have gained more attention in the field of periglacial geomorphology during the last decade. In this paper we present a new modelling approach that integrates topographical, ground and remote sensing information in predictive geomorphological mapping using generalized additive modelling (GAM) . First, we explored the roles of different environmental variable groups in determining the occurrence of non‐sorted and sorted patterned ground in a fell region of 100 km2 at the resolution of 1 ha in northern Finland. Second, we compared the predictive accuracy of ground‐topography‐ and remote‐sensing‐based models. The results indicate that non‐sorted patterned ground is more common at lower altitudes where the ground moisture and vegetation abundance is relatively high, whereas sorted patterned ground is dominant at higher altitudes with relatively high slope angle and sparse vegetation cover. All modelling results were from good to excellent in model evaluation data using the area under the curve (AUC) values, derived from receiver operating characteristic (ROC) plots. Generally, models built with remotely sensed data were better than ground‐topography‐based models and combination of all environmental variables improved the predictive ability of the models. This paper confirms the potential utility of remote sensing information for modelling patterned ground distribution in subarctic landscapes. 相似文献
6.
Evaluation of current statistical approaches for predictive geomorphological mapping 总被引：5，自引：3，他引：5
Predictive models are increasingly used in geomorphology, but systematic evaluations of novel statistical techniques are still limited. The aim of this study was to compare the accuracy of generalized linear models (GLM), generalized additive models (GAM), classification tree analysis (CTA), neural networks (ANN) and multiple adaptive regression splines (MARS) in predictive geomorphological modelling. Five different distribution models both for non-sorted and sorted patterned ground were constructed on the basis of four terrain parameters and four soil variables. To evaluate the models, the original data set of 9997 squares of 1 ha in size was randomly divided into model training (70%, n=6998) and model evaluation sets (30%, n=2999).In general, active sorted patterned ground is clearly defined in upper fell areas with high slope angle and till soils. Active non-sorted patterned ground is more common in valleys with higher soil moisture and fine-scale concave topography. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC) and the Kappa value. The relatively high discrimination capacity of all models, AUC=0.85–0.88 and Kappa=0.49–0.56, implies that the model's predictions provide an acceptable index of sorted and non-sorted patterned ground occurrence. The best performance for model calibration data for both data sets was achieved by the CTA. However, when the predictive mapping ability was explored through the evaluation data set, the model accuracies of CTA decreased clearly compared to the other modelling techniques. For model evaluation data MARS performed marginally best.Our results show that the digital elevation model and soil data can be used to predict relatively robustly the activity of patterned ground in fine scale in a subarctic landscape. This indicates that predictive geomorphological modelling has the advantage of providing relevant and useful information on earth surface processes over extensive areas, such data being unavailable through more conventional survey methods. 相似文献
7.
Raju RAI ZHANG Yili LIU Linshan Paras Bikram SINGH Basanta PAUDEL Bipin Kumar ACHARYA Narendra Raj KHANAL 《资源与生态学报(英文版)》2022,13(2):173-185
Gandaki River Basin (GRB) is an important part of the central Himalayan region, which provides habitat for numerous wild species. However, climatic changes are making the habitat in this basin more vulnerable. This paper aims to assess the potential impacts of climate change on the spatial distributions of habitat changes for two vulnerable species, Himalayan black bear (Ursus thibetanus laniger) and common leopard (Panthera pardus fusca), using the maximum entropy (MaxEnt) species distribution model. Species occurrence locations were used along with several bioclimatic and topographic variables (elevation, slope and aspect) to fit the model and predict the potential distributions (current and future) of the species. The results show that the highly suitable area of Himalayan black bear within the GRB currently encompasses around 1642 km2 (5.01% area of the basin), which is predicted to increase by 51 km2 in the future (2050). Similarly, the habitat of common leopard is estimated as 3999 km2 (12.19% of the GRB area), which is likely to increase to 4806 km2 in 2050. Spatially, the habitat of Himalayan black bear is predicted to increase in the eastern part (Baseri, Tatopani and north from Bhainse) and to decrease in the eastern (Somdang, Chhekampar), western (Burtibang and Bobang) and northern (Sangboche, Manang, Chhekampar) parts of the study area. Similarly, the habitat of common leopard is projected to decrease particularly in the eastern, western and southern parts of the basin, although it is estimated to be extended in the southeastern (Bhainse), western (Harichaur and northern Sandhikhark) and north-western (Sangboche) parts of the basin. To determine the habitat impact, the environmental variables such as elevation, Bio 15 (precipitation seasonality) and Bio 16 (precipitation of wettest quarter) highly contribute to habitat change of Himalayan black bear; while Bio 13 (precipitation of wettest month) and Bio 15 are the main contributors for common leopard. Overall, this study predicted that the suitable habitat areas of both species are likely to be impacted by climate change at different altitudes in the future, and these are the areas that need more attention in order to protect these species. 相似文献
8.
气候变化和人类活动通过改变物种生境而影响物种多样性。小白额雁是长江流域中下游的一种具有较高生态价值的食草型濒危候鸟,受气候变化和人类活动威胁。本文以小白额雁为代表性物种,定量分析了气候变化对长江流域中下游候鸟潜在生境及适宜性空间分布格局的影响。采用Maxent模型模拟了当前情景和全球环流模型(GCMs)气候场景下小白额雁潜在生境及其适宜性分布。研究结果表明,小白额雁分布特征与其栖息地周边植物分布呈显著相关关系;运用Maxent模型模拟小白额雁六种主要食源植物的分布特征,并将其结果作为环境变量,将显著改善小白额雁潜在生境及其适宜性模型的模拟性能;在两种典型浓度情景(RCP 2.6和RCP8.5)下,2070年小白额雁潜在生境适宜性面积将下降。为应对气候变化对小白额雁的影响,应采取更加合理的管理措施和保护政策,包括调整保护区的大小、形状和用途。 相似文献
9.
10.
T. L. Lei 《International journal of geographical information science》2013,27(2):283-304
Seabed sediment textural parameters such as mud, sand and gravel content can be useful surrogates for predicting patterns of benthic biodiversity. Multibeam sonar mapping can provide near-complete spatial coverage of high-resolution bathymetry and backscatter data that are useful in predicting sediment parameters. Multibeam acoustic data collected across a ～1000 km2 area of the Carnarvon Shelf, Western Australia, were used in a predictive modelling approach to map eight seabed sediment parameters. Four machine learning models were used for the predictive modelling: boosted decision tree, random forest decision tree, support vector machine and generalised regression neural network. The results indicate overall satisfactory statistical performance, especially for %Mud, %Sand, Sorting, Skewness and Mean Grain Size. The study also demonstrates that predictive modelling using the combination of machine learning models has provided the ability to generate prediction uncertainty maps. However, the single models were shown to have overall better prediction performance than the combined models. Another important finding was that choosing an appropriate set of explanatory variables, through a manual feature selection process, was a critical step for optimising model performance. In addition, machine learning models were able to identify important explanatory variables, which are useful in identifying underlying environmental processes and checking predictions against the existing knowledge of the study area. The sediment prediction maps obtained in this study provide reliable coverage of key physical variables that will be incorporated into the analysis of covariance of physical and biological data for this area. 相似文献
11.
清代西南地区森林空间格局网格化重建 总被引：1，自引：0，他引：1
基于遥感土地利用数据和全球潜在植被数据,确定了中国西南地区土地垦殖前森林植被可能的分布范围,并通过量化地形（海拔、坡度）和气候生产潜力（光照、温度、水分）与农林地分布间的关系,构建了土地宜垦性评估模型和历史森林面积网格化分配模型,重建了清代西南地区5个时点、分辨率为10 km×10 km的森林空间格局。结果表明：①本文设计的森林空间格局网格化重建方法具有一定的可行性,其结果能较好地反映森林变迁历史过程的基本特征;②西南地区森林覆被率从雍正二年（1724年）的54.7%下降至宣统三年（1911年）的27.8%,其减少地区主要分布在四川盆地、云南中南部以及贵州大部;③从网格占比的变化趋势看,1724-1911年,西南地区森林覆被率小于10%的网格占比上升了约31个百分点,而覆被率大于80%的网格占比则下降了约13个百分点。 相似文献
12.
清代西南地区森林空间格局网格化重建简 总被引：1，自引：0，他引：1
基于遥感土地利用数据和全球潜在植被数据,确定了中国西南地区土地垦殖前森林植被可能的分布范围,并通过量化地形（海拔、坡度）和气候生产潜力（光照、温度、水分）与农林地分布间的关系,构建了土地宜垦性评估模型和历史森林面积网格化分配模型,重建了清代西南地区5个时点、分辨率为10 km×10 km的森林空间格局。结果表明：①本文设计的森林空间格局网格化重建方法具有一定的可行性,其结果能较好地反映森林变迁历史过程的基本特征;②西南地区森林覆被率从雍正二年（1724年）的54.7%下降至宣统三年（1911年）的27.8%,其减少地区主要分布在四川盆地、云南中南部以及贵州大部;③从网格占比的变化趋势看,1724-1911年,西南地区森林覆被率小于10%的网格占比上升了约31个百分点,而覆被率大于80%的网格占比则下降了约13个百分点。 相似文献
13.
飞蝗Locusta migratoria (Linnaeus)系斑翅蝗科Oedipodidae飞蝗属Locusta Linnaeus洲际性农业重大害虫,在我国主要包括东亚飞蝗L.migratoria manilensis (Meyen)、亚洲飞蝗[WTBX]L.migratoria[WTBZ] (Linnaeus)和西藏飞蝗L.migratoria tibetensis Chen。掌控飞蝗灾害的地理空间分布并预测起潜在的适宜分布区,对于我国飞蝗灾害的综合防控具有重要意义。结合三种中国飞蝗灾害记录地理信息和生物环境环境因子参数,应用最大熵模型(MaxEnt) 和地理信息技术(GIS) ,在3 km×3 km尺度上对三种飞蝗灾害在中国的地理分布空间格局梯度、灾害风险概率和风险等级进行了模拟预测与分析,并对影响分布的关键生物气候环境因子进行了分析。结果显示,蝗灾害风险区的地理分布模拟结果与历史记录完全符合,ROC检验表明MaxEnt 模型预测可靠性极高。三种飞蝗东亚飞蝗、亚洲飞蝗和西藏飞蝗在中国的灾害风险区总面积依次分别为315.87×104 km2、395.80×104 km2和125.00×104 km2,分别占国土面积的33.43%、41.96% 和13.25%。东亚飞蝗和亚洲飞蝗的灾害风险区存在75.8×104 km2的空间重叠,主要分布于我国农牧交错区及以南区域。三种飞蝗灾害风险区的地理梯度与分布格局与中国三大自然地理区高度吻合,其地理分布格局表现出显著的经度和纬度空间梯度异质性。刀切法检测（Jackknife test）表明,三种飞蝗灾害的主导生物—气候影响因子的不同导致了其地理分布格局的显著差异,表明蝗灾爆发概率同时受到各自不同飞蝗物种对气候环境的适应性与地理空间隔离作用的共同制约。研究结果可为我国飞蝗灾害的跨界联合全程防控、区域联网监测联控和综合治理提供参考依据。 相似文献
14.
Given species' vulnerability to climate change, land use change, and habitat loss, it is pertinent to examine how the distribution of a particular species is related to those factors. We assessed the use of climate, habitat, and topography data for modeling the distributions of 14 central European wetland birds, and compared the relative importance of these factors among bird groups with differing latitudinal distributions in Europe. We used the Third Atlas of Breeding Birds in the Czech Republic as a source of species distribution data. Variables were derived from Corine Land Cover, WorldClim, and Shuttle Radar Topography Mission (SRTM) data. Hierarchical partitioning and multiple logistic models identified climatic, topographical, and habitat predictors as important determinants of distribution for each of the species under study. However, the relative contributions of particular variables differed among the species. Climatic, topographical, and habitat factor groups also differed in their importance to latitudinal species groups. Our results indicated that wetland birds with range margins close to the Czech Republic were potentially limited by two different factors: climate conditions impact the southerly distributed species and the availability of suitable habitat affects the northerly distributed species. The accuracy of the study models varied from fair to high (the area under curve values was 0.60–0.89) and revealed negative correlations with the relative occurrence area. In this study, we propose that any difference in model performance is more attributable to data characteristics than to a species' geographical characteristics. 相似文献
15.
《Journal of Arid Environments》1997,35(1):3-16
An information survey of the recent climate of the United Arab Emirates (UAE) was conducted and existing data were used in order to compile a sound and brief introduction to the countries' climates, which are little described in detail.Generally the climate of the UAE is classified as hyperarid. Within the country there are different bioclimatic zones. In the north-eastern areas there are higher mean precipitation rates, and lower temperatures, in comparison with the southern and the western region. The climates of the UAE are similar to those of other areas in Arabia, with low mean precipitation rates, whereas the mean annual temperatures increase along a north–south gradient from Kuwait and Riyadh towards Dibba and Muscat. 相似文献
16.
This paper uses Landsat TM images, GIS technology, Digital Elevation and Habitat Assessment Models to assess the habitat suitability of the endangered plant Tetraena mongolica in western Ordos Plateau of China by selecting terrain, soil, climate, and human activity factors as assessment indices. The results are as follows: natural factors such as climate and terrain are not restrictive factors for the survival and development of T. mongolica in the research region, whereas human activity causes habitat quality of T. mongolica to change intensively in quantity and distribution. The area of less suitable habitat increased by 23.87 km2 compared to potential habitat suitability. Thus, in some areas, human activity may be a key factor causing the endangerment of T. mongolica. There were obvious differences of potential and practical habitat suitability between different habitat regions in the study area. The habitat quality was better in Wujiamiao, Dishan and Qipanjing regions, and worse in Wuda and Qianlishan regions. 相似文献
17.
气候变暖背景下中原腹地冬小麦气候适宜度变化 总被引：6，自引：0，他引：6
通过构建冬小麦光照、温度、降水及综合气候适宜度计算模型,探讨气候变化对冬小麦气候适宜性的影响。结果表明:冬小麦全生育期温度、光照、降水及综合气候适宜度均值分别为0.54、0.64、0.37及0.50;冬小麦对光照适宜性较好,降水是限制冬小麦生长发育的主要因子;温度和降水适宜度以0.001·a-1线性趋势下降,光照适宜度以0.002·a-1线性趋势下降,气候因子匹配效果变差对冬小麦的生长不利。冬前生长阶段温度、光照和降水适宜性较弱,各气候因子匹配效果较差。出苗-拔节期降水适宜性较强,各气候因子组合效果较差;拔节-抽穗期和抽穗-乳熟期温度与光照适宜性较强,水分胁迫较大,气候因子组合效果趋好。乳熟-成熟期光照和降水适宜性较强,综合气候适宜性变差。光照、温度和降水适宜度在全生育期的中后期与冬小麦产量的相关性比较显著。 相似文献
18.
气候变化情景下油茶生长的适宜性特征 总被引：1，自引：0，他引：1
基于气候情景数据与油茶标本,运用MaxEnt模型分析全新世中期、当代与未来阶段油茶生长的气候适宜性特征,将概率分布结果由不适宜到最适宜分为4个等级,分析了各时段空间分布变化与最适宜区北界变化、几何中心变化及位移情况。结果如下：1）MaxEnt模型的AUC值为0.848,评估结果达到“好”的标准,说明该模型可用;年降水量、最湿季降水量、最暖季平均温、温度季节性变化的标准差、最干月降水量、最湿季平均温和最冷季平均温等是7个主要环境因子。2）中国油茶主要适宜生长于长江以南、云贵高原以东,经纬度范围为30°N以南、107°E以东地区;适宜及以上等级占研究区面积的34.9%~61%;适宜性变化,空间上西南地区波动明显,面积上稳定和降低类占比较高。3）油茶最适宜区北界位于亚热带中部,不同年代、不同地区北界各异,长江中下游地区变化较小,而秦岭、渝、贵和桂等地变动较大,整体趋势为全新世中期至1980s向南推移,未来情景下2050s和2070s缓慢向北推移;几何中心在全新世中期时位于湖南郴州,至1980s时向东南方位移至广东韶关,至2050s时向东北位移至江西吉安,并相对稳定。4）基于气候情景数据和MaxEnt物种分布模型分析中国南方地区油茶气候适宜性时空分布与变化特征结果可靠。 相似文献
19.
我国夏玉米潜在种植分布区的气候适宜性研究 总被引：9，自引：0，他引：9
根据我国188 个夏玉米农业气象观测站资料与1971-2000 年10 km×10 km空间分辨率的气候资料,结合国家层次和年尺度筛选出的影响我国玉米种植分布的潜在气候指标,利用最大熵(MaxEnt) 模型和ArcGIS空间分析技术,构建了我国夏玉米潜在种植分布与气候因子关系模型,研究了影响我国夏玉米潜在种植分布的主导气候因子及其气候适宜性。结果表明,影响我国夏玉米潜在种植分布的主导气候因子有：无霜期、年平均温度、≥ 10 oC积温持续天数、≥ 0 oC积温、≥ 10 oC积温、最冷月平均温度、最热月平均温度、年降水;采用夏玉米存在概率这一综合反映各主导因子作用的指标,将我国夏玉米潜在种植分布区划分为4 个等级：最适宜区、适宜区、次适宜区和不适宜区,并阐述了各气候适宜区的气候特征。研究结果可为夏玉米种植的科学布局及制定应对气候变化政策提供参考。 相似文献
20.
基于GIS的云南烤烟种植气候动态分区评估 总被引：2，自引：0，他引：2
基于气象、烟叶化学成分含量的大样本数据,通过完善烤烟种植气候适宜性定量评价指标体系,构建气象条件对烟叶品质影响的定量评判标准,在精细化模拟推算基本气象要素地理空间分布的基础上,应用GIS技术实现了烤烟种植气候的动态分区评估。以云南省两个典型气候年份为例,在GIS平台下将统计模型推算与空间插值技术方法有机结合,尝试突破传... 相似文献