Species Distribution Modelling predicts habitat suitability and reduction of suitable habitat under future climatic scenario for Sclerophrys perreti: A critically endangered Nigerian endemic toad

Sclerophrys perreti is a critically endangered Nigerian native frog currently imperilled by human activities. A better understanding of its potential distribution and habitat suitability will aid in conservation; however, such knowledge is limited for S. perreti. Herein, we used a species distribution model (SDM) approach with all known occurrence data (n = 22) from our field surveys and primary literature, and environmental variable predictors (19 bioclimatic variables, elevation and land cover) to elucidate habitat suitability and impact of climate change on this species. The SDM showed that temperature and precipitation were the predictors of habitat suitability for S. perreti with precipitation seasonality as the strongest predictor of habitat suitability. The following variable also had a significant effect on habitat suitability: temperature seasonality, temperature annual range, precipitation of driest month, mean temperature of wettest quarter and isothermality. The model predicted current suitable habitat for S. perreti covering an area of 1,115 km². However, this habitat is predicted to experience 60% reduction by 2050 owing to changes in temperature and precipitation. SDM also showed that suitable habitat exists in south-eastern range of the inselberg with predicted low impact of climate change compared to other ranges. Therefore, this study recommends improved conservation measures through collaborations and stakeholder's meeting with local farmers for the management and protection of S. perreti.     

未来气候变化对广布种麻栎地理分布的影响和主导气候因子分析

为了解麻栎（Quercus acutissima）的潜在分布特征及其对未来气候的响应,运用最大熵模型（Maxent）模拟在当前气候条件下麻栎的潜在分布格局,预测未来不同温室气体排放情景下的格局变化,并分析影响其分布的主导因子。结果表明,Maxent模型有较好的预测能力,AUC值大于0.95。当前气候条件下,麻栎广泛分布于我国南方大部分地区和陕西、河南、山西、甘肃、北京、辽宁等北方省市。此外,在日本、朝鲜半岛、老挝、越南、缅甸、尼泊尔、不丹、印度、巴基斯坦等国家和地区亦存在不同程度和范围的麻栎适生区域,麻栎总适生区域面积达11.57×10⁵km²。在RCP2.6和RCP8.5情景下,麻栎适宜分布区域向北和西南方向扩展,新增适生区面积为（2.49~3.02）×10⁵km²;适生区域丧失主要集中在广西南部、广东南部和缅甸东部等地。影响其分布的主导气候因子为最暖季降水量、等温性、最干季均温、最冷月最低温,因子贡献率分别为54.2%、13.7%、8.8%和7.8%。这为麻栎的栽培和保育研究提供了参考依据。     

气候变化下耐旱藓类连轴藓属在新疆的分布模拟

该研究基于耐旱藓类连轴藓属5种53条在新疆的地理分布信息和7个气候变量,利用最大熵模型和ArcGIS 10.2软件,分别模拟现代气候和未来气候情景下连轴藓属在新疆的适生分布区,为探讨气候变化对干旱、半干旱区苔藓植物物种分布的影响提供参考。结果表明:(1)Maxent模型预测连轴藓属在新疆适生区的准确性非常高(AUC=0.957)。(2)年降雨量、最干季度降雨量和最暖季度平均气温是影响连轴藓属分布的主要气候因子。(3)连轴藓属在新疆的适生区主要集中在阿尔泰山和天山沿线,在未来(2061~2080年)气候情景下,连轴藓属分布面积将比现代气候下减少10.39%,其绝大部分现有南部适生区将丧失。     

滇黄精的潜在分布与气候适宜性分析

为了解滇黄精(Polygonatum kingianum)的适宜生长区,运用Maxent模型模拟其潜在分布区,探讨其引种栽培的适宜气候条件。结果表明,预测模型的AUC值为0.974~0.980,表明模型具有良好的预测能力。滇黄精主要适生区位于我国西南地区,适生面积约81.34×10~4 km~2,占全国适生区面积的88.24%。云南的高度适生区面积最大(19.96×10~4 km~2);四川次之(5.49×10~4 km~2)。75%的高度适生区分布于海拔2 492 m以下的地区,3 400 m以上的地区不适宜于滇黄精生长。最冷月最低温度、7月最低温度、5-8月太阳辐射、最干月降水量、4月和9-11月平均降水量是限制滇黄精分布的主要气候变量。因此,海拔1 400~2 100 m的亚热带地区是滇黄精最适宜的生长区。     

Geographic variation in body size and its relationship with environmental gradients in the Oriental Garden Lizard,Calotes versicolor

Patterns of geographic variation in body size are predicted to evolve as adaptations to local environmental gradients. However, many of these clinal patterns in body size, such as Bergmann's rule, are controversial and require further investigation into ectotherms such as reptiles on a regional scale. To examine the environmental variables (temperature, precipitation, topography and primary productivity) that shaped patterns of geographic variation in body size in the reptile Calotes versicolor, we sampled 180 adult specimens (91 males and 89 females) at 40 locations across the species range in China. The MANOVA results suggest significant sexual size dimorphism in C. versicolor (F_23,124 = 11.32, p < .001). Our results showed that C. versicolor failed to fit the Bergmann's rule. We found that the most important predictors of variation in body size of C. versicolor differed for males and females, but mechanisms related to heat balance and water availability hypotheses were involved in both sexes. Temperature seasonality, precipitation of the driest month, precipitation seasonality, and precipitation of the driest quarter were the most important predictors of variation in body size in males, whereas mean precipitation of the warmest quarter, mean temperature of the wettest quarter, precipitation seasonality, and precipitation of the wettest month were most important for body size variation in females. The discrepancy between patterns of association between the sexes suggested that different selection pressures may be acting in males and females.     

基于Maxent模型的假臭草潜在分布区预测

为有效开展假臭草的防除工作,运用最大熵值模型(Maxent)和地理信息技术(GIS)对假臭草(Praxelis clematidea)在中国的潜在分布区和影响其分布的主导环境变量进行预测。运用AUC法对预测精度进行评价,达到"优秀"水平。结果表明,Maxent模型预测结果具有较高的可信度。假臭草在中国的潜在适生面积为785985km2,占总国土面积的8.19%,主要分布在华南及东南区域,其中福建、广东、海南和广西省为假臭草的中高适生区。福建省的假臭草分布最为广泛,61.98%的福建区域适合假臭草的生长,其中闽南沿海为假臭草的高适生区,而闽北区域假臭草的种群密度较低。2月最低温可能是限制假臭草分布的主要气候变量,贡献率为61.70%;最干季度降水量、9月最高温对假臭草的分布具有一定的影响。假臭草的分布预测为早期监测和预警提供理论依据和技术支持,防止假臭草的进一步扩散蔓延。     

Habitat suitability of Gymnocladus assamicus - A critically endangered plant of Arunachal Pradesh,India using machine learning and statistical modeling

The present study sought to identify the potential distribution range of critically endangered Gymnocladus assamicus in Arunachal Pradesh based on published data and field collection. We used the Maxent model to estimate the range of distribution and the result was then compared with three other models, i.e., the Generalized Linear Model (GLM), the Bioclim and the Random Forest model to assess the species' habitat suitability. A total of 23 different environmental variables were used, including bioclimatic ones, monthly minimum and maximum temperature, monthly precipitation and elevation data. The Maxent output listed 12 variables explaining 99.9% variation in the model. In comparison, Maxent showed the maximum region under habitat suitability criteria (1884.48 km²), followed by Random Forest (70.73 km²) and Bioclim (11.62 km²) model. Except for the Maxent model, suitable habitats predicted by other models are highly restricted within and across the study species' current distribution range. The average model prediction shows an expanded distribution range for the species up to Tawang which is the closest district of currently known distribution of the species in the state. Thus, the present study recognizes the importance of the geographic range of G. assamicus, a critically endangered species with very limited spatial distribution range and also provides some specific details to explore possible habitats for the species in new areas of potential occurrence in Arunachal Pradesh, India.     

Using macroclimatic models to estimate the distribution ranges of taxonomically challenging taxa,an example with Macromitrium cavaleriei Cardot & Thér. (Orthotrichaceae)

An expanded taxonomic study of the narrowly understood Macromitrium cavaleriei Cardot & Thér. identified four new synonyms, M. cancellatum Y.X.Xiong, M. giraldii var. acrophylloides Müll.Hal., M. handelii Broth. and M. rigbyanum Dixon. With the discovery of the new synonyms, the range of M. cavaleriei is extended to India, Nepal, South Korea and Vietnam. To determine the potential distribution range of the species, we described its macroclimatic niche from its extant distribution with the maximum entropy algorithm modelling program (Maxent), contrasting the impact of different geographic backgrounds on the models. We found that the potential range of the species included central, southern, southwestern China to northern Vietnam, Myanmar, Bhutan, Nepal and India, and northwards to Japan and the Korean Peninsula. This estimation of the potential distribution range is largely confirmed by the herbarium specimens. The predicted climate suitability for M. cavaleriei is higher in the areas where the annual temperature range is about 26°C and precipitation during the warmest quarter, wettest quarter and month, and driest month are 500–600 mm, 500 mm, 200–210 mm, and 50 mm, respectively.     

Past distribution of epiphyllous liverworts in China: The usability of historical data

Epiphyllous liverworts form a special group of bryophytes that primarily grow on the leaves of understory vascular plants in tropical and subtropical evergreen broadleaf forests. Being sensitive to moisture and temperature changes, epiphyllous liverworts are often considered to be good indicators of climate change and forest degradation. However, they are a poorly collected and taxonomically complicated group, with an only partly identified distribution pattern. In this study, we built four models based on 24 environmental variables at four different spatial resolutions (i.e., 1 km, 5 km, 10 km, and 15 km) to predict the past distribution of epiphyllous liverworts in China, using Maxent model and 63 historical location records (i.e., presence‐only data). Both area under the curve of the receiver operating characteristic (AUC) and true skill statistic (TSS) methods are used to assess the model performance. Results showed that the model with the predictors at a 15‐km resolution achieved the highest predictive accuracy (AUC=0.946; TSS=0.880), although there was no statistically significant difference between the four models (p > 0.05). The most significant environmental variables included aridity, annual precipitation, precipitation of wettest month, precipitation of wettest quarter, and precipitation of warmest quarter, annual mean NDVI, and minimum NDVI. The predicted suitable areas for epiphyllous liverworts were mainly located in the south of Yangtze River and seldom exceed 35°N, which were consistent with the museum and herbarium records, as well as the historical records in scientific literatures. Our study further demonstrated the value of historical data to ecological and evolutionary studies.     

Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

Climate change poses a serious threat to biodiversity. Predicting the effects of climate change on the distribution of a species' habitat can help humans address the potential threats which may change the scope and distribution of species. Pterocarya stenoptera is a common fast‐growing tree species often used in the ecological restoration of riverbanks and alpine forests in central and eastern China. Until now, the characteristics of the distribution of this species' habitat are poorly known as are the environmental factors that influence its preferred habitat. In the present study, the Maximum Entropy Modeling (Maxent) algorithm and the Genetic Algorithm for Ruleset Production (GARP) were used to establish the models for the potential distribution of this species by selecting 236 sites with known occurrences and 14 environmental variables. The results indicate that both models have good predictive power. Minimum temperature of coldest month (Bio6), mean temperature of warmest quarter (Bio10), annual precipitation (Bio12), and precipitation of driest month (Bio14) were important environmental variables influencing the prediction of the Maxent model. According to the models, the temperate and subtropical regions of eastern China had high environmental suitability for this species, where the species had been recorded. Under each climate change scenario, climatic suitability of the existing range of this species increased, and its climatic niche expanded geographically to the north and higher elevation. GARP predicted a more conservative expansion. The projected spatial and temporal patterns of P. stenoptera can provide reference for the development of forest management and protection strategies.     

气候变化背景下紫楠在中国的适宜分布区模拟

为了解气候对紫楠(Phoebe sheareri)分布的影响,应用Maxent和GARP模型模拟了紫楠在当前气候下的中国适宜分布区,分析了影响其分布的主要环境因子,并预测了未来气候情境下其分布区的变化。结果表明,紫楠适宜分布在长江中下游及以南的各省区。影响紫楠分布的主要环境因子有年降雨量、最干季均温、降雨的季节性、相对湿度和6-8月的日照时数,这5个因子的累积贡献率达84.3%。在未来气候情境下,广东、云南、广西和海南等地区的适生区面积会显著锐减,而陕西中部、河南南部、安徽东部和江苏北部适生区面积会大幅度增加。因此,在未来气候变化背景下,紫楠的适宜分布区有向北扩张的趋势。     

Using maximum entropy to predict the potential distribution of an invasive freshwater snail

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Using Species Distribution Model to Estimate the Wintering Population Size of the Endangered Scaly-Sided Merganser in China

Scaly-sided Merganser is a globally endangered species restricted to eastern Asia. Estimating its population is difficult and considerable gap exists between populations at its breeding grounds and wintering sites. In this study, we built a species distribution model (SDM) using Maxent with presence-only data to predict the potential wintering habitat for Scaly-sided Merganser in China. Area under the receiver operating characteristic curve (AUC) method suggests high predictive power of the model (training and testing AUC were 0.97 and 0.96 respectively). The most significant environmental variables included annual mean temperature, mean temperature of coldest quarter, minimum temperature of coldest month and precipitation of driest quarter. Suitable conditions for Scaly-sided Merganser are predicted in the middle and lower reaches of the Yangtze River, especially in Jiangxi, Hunan and Hubei Provinces. The predicted suitable habitat embraces 6,984 km of river. Based on survey results from three consecutive winters (2010–2012) and previous studies, we estimated that the entire wintering population of Scaly-sided Merganser in China to be 3,561 ± 478 individuals, which is consistent with estimate in its breeding ground.     

Habitat invasion risk assessment based on Landsat 5 data,exemplified by the shrub Rosa rubiginosa in southern Argentina

Prediction of invasive species spread helps to plan management actions. We performed a risk assessment by quantifying habitat invasibility, predicted the potential distribution of an invasive species using the Maxent modelling program and confirmed patterns using detailed field studies. Our study was conducted in southern Argentina, Patagonia, where large areas are already invaded by the European shrub Rosa rubiginosa. A total of 163 R. rubiginosa locations served as ground truth data, and predictors were obtained from the spaceborne sensor Landsat 5. Based on the Maxent Method (area under the receiver operating characteristic curve 0.8), the habitat invasibility map covered about 5000 km². Our model revealed that R. rubiginosa has the potential to invade 36% of the area along a steep precipitation gradient (target region 600–1400 mm per year). The Tasseled Cap brightness index and the normalized vegetation index explained most of the variance in our model, followed by the Tasseled Cap greenness and wetness indices, which can be interpreted as indicators of disturbance. Highest levels of invasibility were predicted for urban areas, along roads and rivers, on pastures, in Austrocedrus chilensis forests and inside Nothofagus dombeyi forest gaps. Detailed field assessments of rose cover performed in seven habitat types supported these results: rose cover significantly decreased with increasing tree cover (P < 0.01). Our data revealed that the occurrence of R. rubiginosa is not connected to a certain habitat type, but that it thrives in open patches following habitat disturbance. Our approach is a widely applicable, cost‐free remote sensing method that can serve as a risk assessment tool for alien plant species invasion of habitats.     

Spatial ecology and conservation of the microendemic ovenbird Cipo Cinclodes (Cinclodes espinhacensis) from the Brazilian highlands

Birds in the genus Cinclodes are habitat specialists, with most restricted to the highlands of South America. The recently described Cipo Cinclodes (C. espinhacensis) is isolated in the southern Espinhaço Range of Brazil and is considered Endangered in Brazil and Near Threatened by the IUCN, but as a subspecies of Long‐tailed Cinclodes (C. pabsti). We examined the population and spatial ecology of Cipo Cinclodes at two geographic scales to improve our understanding of their basic biology and conservation status. We monitored 30 birds at Serra do Breu and found relatively large home ranges (mean = 9.3 ha), a density of paired adults of 0.09/ha, a male‐skewed adult sex ratio (males/total adults = 0.57) due to territories occupied by unpaired males, and long‐term site fidelity. Cipo Cinclodes used all habitat types available in our study area, including rocky outcrops, grasslands, and riparian areas, but habitat selection analyses revealed the importance of riparian areas for foraging and rocky outcrops for nesting. At the species distribution scale, we compiled known and novel recorded occurrence points and used them to calculate the extent of occurrence (EOO) and the area of occupancy (AOO). We used a Maxent species distribution model to generate a binary map to estimate upper limits for EOO (EOO around the model predicted area) and AOO (comprised by the model predicted area within the EOO). We obtained 41 locations, resulting in an EOO of 890.7 km² (up to 1748.7 km²) and an AOO of 100 km² (up to 327.5 km²). The global population is estimated to be between 880 and 2882 birds, which is concerning because small populations are at risk of extinction due to demographic stochasticity, genetic drift, and the interaction of these factors. As such, our results support the designation of Cipo Cinclodes as Endangered on the Brazilian red list.     

Ecological analysis and environmental niche modelling of Dactylorhiza hatagirea (D. Don) Soo: A conservation approach for critically endangered medicinal orchid

The natural populations of Dactylorhiza hatagirea have been greatly affected due to incessant exploitation. As such, studies on its population attributes together with habitat suitability and environmental factors affecting its distribution are needed to be undertaken for its conservation in nature. Present study aimed at accessing an impact of anthropogenic pressure on population structure and locate suitable habitats for the conservation of this critically endangered orchid. Considerable changes in the phytosociological attributes were observed on account of the changing magnitude and extent of anthropogenic threat in their natural abode. The distribution pattern of species indicated that more than 90% of the populations exhibit substantially aggregated spatial distribution. Maximum Entropy (MaxEnt) distribution modelling algorithm was used to predict suitable habitat and potential area for its cultivation and reintroduction. Twenty-seven occurrence records, nineteen bioclimatic variables, altitude, and slope were used. MaxEnt map output gave the habitat suitability for this species and predicted its distribution in the North-Western Himalayas of India for approximately 616 km². Jackknifing indicated that maximum temperature of warmest month, annual mean temperature, mean temperature of the driest quarter, and mean temperature of the wettest quarter were the governing factors for its distribution and hence, presented a higher gain with respect to other variables. According to permutation importance, precipitation seasonality and mean temperature of wettest quarter shows the prominent impact on the habitat distribution. Results of AUC (area under curve) were statistically significant (0.940) and the line of predicted omission falls very close to an omission on training samples, validating a better run of the model. Response curves revealed a probable increase in the occurrence of D. hatagirea with an increase in mean temperature of the wettest quarter and maximum temperature of the warmest month contributed more than 50% to predicted habitat suitability. Direct field observations concurrent with predicted habitat suitability and google-earth images represent greater model thresholds for successful inception of the species. Together, the study proposes that the species can be conserved in or near its present-day natural habitats and is equally effective in determining the possible habitats for its cultivation and reintroduction.     

新疆千里光Senecio jacobaea在中国的适生区预测

【背景】菊科植物新疆千里光原产于欧亚大陆,在北美和澳洲为入侵植物,目前在中国只有新疆有分布记录。新疆千里光一旦成为入侵植物,将对农业、畜牧业和人类健康都可能产生危害,所以需要评估其在中国的扩散趋势。【方法】搜集新疆千里光在中国和世界其他地区的分布记录,结合当前和未来(2050年)气候条件下19种生物气候变量,应用Maxent模型和Diva Gis软件,定量预测新疆千里光在中国目前和未来的潜在分布区域;并通过接受者操作特征曲线(ROC)分析法对模型进行精度检验。另外,通过Maxent给出新疆千里光在欧洲(原产地)、北美洲和大洋洲(入侵地)以及中国等4个分布区的年均温度和年均降水量的气候阈值。【结果】用中国和全球分布的数据预测的结果有些差异。前者结果表明除了新疆地区,其他省份几乎没有新疆千里光的适生区;而后者显示在中国其他几个省份也有可能分布,且在甘肃四川交界处有较高适生性。前者模型精确度较高,但2个结果都显示新疆千里光在中国目前和未来的分布区大部分还是在新疆地区。中国分布区年均温度和年均降水量的阈值比其他2个地区都低。【结论与意义】新疆千里光在当前和未来气候条件下在中国未来的扩散趋势较弱,基本局限于新疆地区。用中国分布数据预测优于全球分布数据预测结果,新疆千里光不同分布区的气候阈值的差异揭示分布于中国的新疆千里光与其他地区的种群的生态位有所不同,可能是一个新的亚种,希望未来能进行进一步的研究。     

Evidence of niche shift and global invasion potential of the Tawny Crazy ant,Nylanderia fulva

Analysis of an invasive species' niche shift between native and introduced ranges, along with potential distribution maps, can provide valuable information about its invasive potential. The tawny crazy ant, Nylanderia fulva, is a rapidly emerging and economically important invasive species in the southern United States. It is originally from east‐central South America and has also invaded Colombia and the Caribbean Islands. Our objectives were to generate a global potential distribution map for N. fulva, identify important climatic drivers associated with its current distribution, and test whether N. fulva's realized climatic niche has shifted across its invasive range. We used MaxEnt niche model to map the potential distribution of N. fulva using its native and invaded range occurrences and climatic variables. We used principal component analysis methods for investigating potential shifts in the realized climatic niche of N. fulva during invasion. We found strong evidence for a shift in the realized climatic niche of N. fulva across its invasive range. Our models predicted potentially suitable habitat for N. fulva in the United States and other parts of the world. Our analyses suggest that the majority of observed occurrences of N. fulva in the United States represent stabilizing populations. Mean diurnal range in temperature, degree days at ≥10°C, and precipitation of driest quarter were the most important variables associated with N. fulva distribution. The climatic niche expansion demonstrated in our study may suggest significant plasticity in the ability of N. fulva to survive in areas with diverse temperature ranges shown by its tolerance for environmental conditions in the southern United States, Caribbean Islands, and Colombia. The risk maps produced in this study can be useful in preventing N. fulva's future spread, and in managing and monitoring currently infested areas.     

Modelling potential impacts of climate change on the bioclimatic envelope and conservation of the Maned Wolf (Chrysocyon brachyurus)

Forecasting the influence of climatic changes on the distribution of the Maned Wolf (Chrysocyon brachyurus) is important for the conservation of the species. We explored the environmental characteristics than best explain the current distribution of the species, modelled the past and present distribution, projected the niche model into the future, and identified suitable areas for conservation. Niche modelling was performed using Maxent and 21 environmental variables. For past conditions, we considered the Last Glacial Maximum (LGM) and the mid-Holocene (MH) climates. For future conditions, we used the A2a greenhouse gas emission scenario for 2050. Four General Circulation Models (FGOALS 1.0, HADCM3, IPSL-CM4 and MIROC 3.2) were used. The resulting niche model (AUC = 0.89 ± 0.02) predicts maximum probability of presence at precipitation of 106 mm during the coldest quarter, of 396 mm during the warmest quarter, and in totally flat areas. The suitable area for the Maned Wolf currently covers 4,320,364 km². For the LGM, there were inter-model differences in predicted areas (from 819,324 km² to 6,395,886 km²) and in geographic location. The MH models showed drastic changes with respect to the present and considerable inter-model variation. Predictions for 2050 show significant (at least 33%) reductions in distribution. Only a minor fraction (39%) of the current distribution can be considered stable for the period LGM-2050. The FGOALS model was the best option for projecting species occurrence into the future because it included the three localities known for the Maned Wolf from the late Pleistocene and predicts stable areas that coincide with spatial patterns of genetic diversity. The FGOALS projection for 2050 predicts a 33% reduction in suitable habitats, indicating some stable areas (central South America) that will probably be key sites for the conservation of the species.     

基于MAXENT和ZONATION的加拿大一枝黄花入侵重点监控区确定

外来入侵植物对本地生态系统及其生物多样性构成严重的威胁,要有效地控制外来植物入侵,首先应该明确植物入侵的高度风险区.以加拿大一枝黄花(Solidago canadensis)为对象,以其广泛发生的安徽、江苏、浙江和上海华东3省1市为研究区域,综合考虑了土地利用变化、人类活动干扰、土壤性质、气候和地形等影响因子,采用MAXENT模型预测其潜在分布及其对主要影响因子的响应,并结合空间优化软件ZONATION识别出需要重点布控的入侵风险区。结果表明:1)影响加拿大一枝黄花分布的主要环境因子及其百分比贡献率分别为:距主要道路距离(29.4%)、土地利用变化(16.9%)、降水的季节性变异(15.9%)、人口密度(9.5%)与最干季均温(6.2%)。2)从影响因子的响应曲线分析得出,加拿大一枝黄花的发生概率随着距主要道路距离的增大而迅速减小;在耕地转化成的城乡居民点及工矿用地、水域转化成的草地、城乡居民点及工矿用地转化成的林地、草地与城乡居民点及工矿用地相互转换频繁的区域和城乡居民点及工矿用地保持不变的区域,其发生概率明显较高;其发生概率随着降水季节性变异的增大而快速减小至0.4,之后缓慢减小;随着人口密度的增大,其发生概率起初急剧升高,人口密度超过4千人/km~2后又缓慢地小幅下降;随着最干季均温的增大,其发生概率逐渐减小,在2.4℃附近达最小,之后逐渐增大。3)加拿大一枝黄花的入侵风险区面积为130433 km~2。其中,一级风险区主要分布在太湖流域、沿杭州湾地区、浙江沿海以及内陆地势较低的耕地及居民点区域;二级风险区主要分布在一级风险区的外缘,尤其是江苏南部的长江沿岸地区。三级风险区则广泛分布在江苏的南部和东部,安徽的中东部,浙江的北部和东部。