Modeling habitat suitability of range plant species using random forest method in arid mountainous rangelands

Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method(RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method(90 points of presence) and soils were sampled in 5 habitats by random method in 0–30 and 30–60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index(?) in order to evaluate the accuracy of the RFM in estimation of the distribution of species potentialhabitat. Based on the values of the area under curve(AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.

Assessing habitat quality of the mountain nyala Tragelaphus buxtoni in the Bale Mountains, Ethiopia

Populations of the endangered mountain nyala Tragelaphus buxtoni are significantly threatened by the loss of critical habitat. Population estimates are tentative, and information on the species＇ distribution and available habitat is required for for-mulating immediate management and conservation strategies. To support management decisions and conservation priorities, we integrated information from a number of small-scale observational studies, interviews and reports from multiple sources to define habitat parameters and create a habitat quality model for mountain nyala in the Bale Mountains. For our analysis, we used the FunConn model, an expertise-based model that considers spatial relationships （i.e., patch size, distance） between the species and vegetation type, topography and disturbance to create a habitat quality surface. The habitat quality model showed that approxi- mately 18,610 km^2 （82.7% of our study area） is unsuitable or poor habitat for the mountain nyala, while 2,857 km^2 （12.7%） and 1,026 km^2 （4.6%） was ranked as good or optimal habitat, respectively. Our results not only reflected human induced habitat deg-radation, but also revealed an extensive area of intact habitat on the remote slopes of the Bale Mountain＇s southern and southeast- ern escarpments. This study provides an example of the roles that expert knowledge can still play in modem geospatial modeling of wildlife habitat. New geospatial tools, such as the FunConn model, are readily available to wildlife managers and allow them to perform spatial analyses with minimal software, data and training requirements. This approach may be especially useful for species that are obscure to science or when field surveys are not practical .

A web-based, component-oriented application for spatial modelling of habitat suitability of mosquito vectors

This paper proposes a web-enabled computational environment for the spatial modelling of habitat suitability of mosquito vectors.Under a component-based architecture and implemented using an object-oriented data model,we integrate database interfaces,Web feature services(WFS)based on the open GIS consortium(OGC)protocols,and the data-mining tool WEKA,coupled through Java servlet scripts(JSP).The prototype,based exclusively on freely available libraries and software components,provides basic dynamic spatial simulation capabilities using logistic regression to end-users engaged in local and regional health administration and planning but who lack access to specific software and/or detailed knowledge of spatial modelling techniques.The component-based approach facilitates system maintenance and future expansion of functionality,and guarantees the reusability of developed modules in new spatial modelling applications of health and environmental-related phenomena.Functionality of the WWW-application was validated in a study of habitat suitability mapping of the Malaria vector Anopheles darlingi,in an area surrounding the Manso River hydropower plant,Central Brazil.