GIS-based landslide susceptibility model considering effective contributing area for drainage time

This study employed GIS modelling to ascertain landslide susceptibility on Mt. Umyeon, south of Seoul, South Korea. In this study, an effective contributing area (ECA) for certain drainage time was purposed as a temporal causative factor and then used for modelling in combination with spatial causative factors such as elevation, slope, plan curvature, drainage proximity, forest type, soil type and geology. Landslide inventory map of 163 landslide locations was prepared using aerial photographic interpretation and field verifications after that digitized using GIS environment in 1:5000 scale. A presence-only-based maximum entropy model was used to establish and analyse the relationship between landslides and causative factors. Before final modelling, a jackknife test was performed to measure the variable contributions, which showed that the slope was the most significant spatial causative factor, and ECA with a drainage time of 12 h was the most significant temporal causative factor. The performances of the final models, with and without significant ECA, were assessed by plotting a receiver operating characteristic curve to be 75.5 and 81.2%, respectively.     

Mapping the stray domestic cat (Felis catus) population in New Zealand: Species distribution modelling with a climate change scenario and implications for protected areas

Species distribution models of stray cats were developed using two types of occurrence data: (i) a combined dataset of stray cats and cat colonies in Auckland and projected to the wider New Zealand area; and (ii) population density as an analogue for country-wide stray cat occurrence. These occurrence data, together with sets of environmental variables were used as input to the Maxent modelling tool to produce maps of suitability for the species. Environmental variables used in the models consist of current bioclimatic conditions, and a future climate scenario (RCP8.5 for year 2070 CCSM model). Commonly occurring bias in the modelling process due to latitude, the area for selecting background points in model evaluation, inherent spatial autocorrelation of occurrence points, and correlated bioclimatic variables were explicitly addressed. Results show that the North Island consistently provide more suitable areas for stray cats with increased suitability in a high emission climate change condition. Key protected areas at risk from the increased suitability to stray cats are also presented.     

Habitat suitability and protection status of four species of amphibians in the Dominican Republic

Hispaniola Island has both a high level of amphibian endemism, and a high level of habitat degradation due to agriculture, infrastructure development, and extractive industries. The objective of this work was to evaluate the capacity of Dominican Republic's current network of protection to maintain the habitat of four species of amphibians endemic to Hispaniola (Osteopilus pulchrilineatus, Osteopilus vastus, Hypsiboas heilprini, and Eleutherodactylus flavescens). Spatial analysis was performed to relate observations of the target species to environmental factors using a maximum entropy algorithm (Maxent). Results of this analysis produced maps of probability of occurrence for each species. Analysis of habitat degradation was based on a change analysis of vegetation, by evaluating trends in the normalized difference vegetation index (NDVI) between 2000 and 2011. Results show that forest loss and species habitat loss within protected areas are smaller but similar to those extracted for the country as a whole, suggesting that the current protected area network is not effective for the maintenance of the habitat of the amphibians analyzed. Enforcement of established protection and restoration within current protected areas could facilitate the protection of up to 25.7% of target amphibian habitat. The methodologies presented here can be applied to measure biodiversity offset effectiveness.     

Biogeography and conservation of viperids from North-West Africa: An application of ecological niche-based models and GIS

North-West Africa is an outstanding region to study biogeographic patterns in biodiversity distribution. This study identifies biogeographic affinities and areas of probable occurrence for seven viperid snakes through the combination of high resolution presence data and environmental factors. Vipers exhibited distinct biogeographical affinities: Bitis arietans was mostly found along savannahs, Echis leucogaster along the Sahel/savannahs, Cerastes cerastes and C. vipera throughout most desertic areas, Daboia mauritanica in coastal and hilly regions and Vipera latastei and V. monticola in almost only mountains. Suitable habitats were predicted for B. arietans in southern Senegal and Mali, and coastal southern Morocco, for E. leucogaster in southern Mauritania, Senegal, Mali, and fragmented habitats in Saharan mountains and south-western Morocco, for C. cerastes from the Atlantic coast to northern Algeria, for C. vipera in the central region, for D. mauritanica in northern-western Morocco and northern Algeria, for V. latastei in the Rif, Middle Atlas and coastal Morocco, and for V. monticola in the High Atlas. In potential sympatric areas, competition is probably limiting distribution, resulting in parapatric ranges. Northern Saharan populations of B. arietans and E. leucogaster are isolated. Saharan mountains and coastal south-western Morocco constitute isolated suitable areas for sub-Saharan relicts.     

Predicting Potential Geographic Distribution of Tibetan Incarvillea younghusbandii Using the Maxent Model

Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau. It is important to study spatial distribution patterns of the plant in order to develop effective protection measures. Based on field survey work and environmental data, the potential geographic distribution of Incarvillea younghusbandii was delineated using a Maximum Entropy (Maxent) model with 28 environmental variables that screened for climate, topography, human activity and biological factors. Our results showed that the main geographic range of Incarvillea younghusbandii included the valley between the Yarlung Zangbo river and the Duoxiong Zangbo river, the valley in the middle section of the Himalaya Mountains, and the area between the north side of the east section of the Himalayas and the south bank of the middle reach of the Yarlung Zangbo river. Distribution may spread to parts of the eastern Himalayas. The Jackknife test indicated that soil types, ratio of precipitation to air temperature, extreme atmospheric pressure differences and annual precipitation were the most important predictive factors for the model, while other variables made relatively small contributions.     

Predictive habitat modelling of humpback (Megaptera novaeangliae) and Antarctic minke (Balaenoptera bonaerensis) whales in the Southern Ocean as a planning tool for seismic surveys

Seismic surveys are frequently a matter of concern regarding their potentially negative impacts on marine mammals. In the Southern Ocean, which provides a critical habitat for several endangered cetacean species, seismic research activities are undertaken at a circumpolar scale. In order to minimize impacts of these surveys, pre-cruise planning requires detailed, spatio-temporally resolved knowledge on the likelihood of encountering these species in the survey area. In this publication we present predictive habitat modelling as a potential tool to support decisions for survey planning. We associated opportunistic sightings (2005–2011) of humpback (Megaptera novaeangliae, N=93) and Antarctic minke whales (Balaenoptera bonaerensis, N=139) with a range of static and dynamic environmental variables. A maximum entropy algorithm (Maxent) was used to develop habitat models and to calculate daily basinwide/circumpolar prediction maps to evaluate how species-specific habitat conditions evolved throughout the spring and summer months. For both species, prediction maps revealed considerable changes in habitat suitability throughout the season. Suitable humpback whale habitat occurred predominantly in ice-free areas, expanding southwards with the retreating sea ice edge, whereas suitable Antarctic minke whale habitat was consistently predicted within sea ice covered areas. Daily, large-scale prediction maps provide a valuable tool to design layout and timing of seismic surveys as they allow the identification and consideration of potential spatio-temporal hotspots to minimize potential impacts of seismic surveys on Antarctic cetacean species.     

金沙江流域滑坡易发性空间预报分析

灾害易发性预报是提高灾害防控能力的第一步。针对位于云南省内的金沙江流域因地势险峻、生态环境脆弱,加之近年来人为活动增多已成为地质灾害高发区的现状,本文以金沙江德钦至华坪段滑坡灾害为例,运用Maxent和随机森林两种机器学习模型对滑坡空间分布作归因与预测,并对两者之间的差异进行对比分析。试验结果表明,随机森林模型的预测精度高于Maxent模型,AUC值为0.72。