GIS modeling of introduction zones in Sochi
Автор: Annenkova Irina Vladimirovna
Журнал: Hortus Botanicus @hortbot
Статья в выпуске: 9, 2014 года.
MaxEnt method calculated the probability distribution of three groups of resistance of plants species to Sochi climate based on the results of the introduction of the 1950 – 1975. Geographical coordinates locations of plants taken from the Global Database on Biodiversity (GBIF), the climatic data of high resolution (30 arc-seconds) - from the global data set Bioclim for 1950-2000. Modeling was performed on all global land areas using training data set from 50% of the GBIF records, in a 4 replicates. For the criterion of habitat suitability of the territory was used the 10% training presence logistic threshold because of the data is likely to have some errors. The Maxent model had an AUC of 0.936, 0.952 and 0.972 for I, II и III groups of resistance to climate meaning the model fit the presence data well. The internal jackknife test of variable importance showed that ‘Mean Temperature of Coldest Quarter’, ‘Annual Mean Temperature’ and ‘Min Temperature of Coldest Month’ were the three most important predictors of habitat distribution. Maps of probabilities of three groups of resistance of plants for the region of Sochi have been merged into a multi-channel raster in ArcGIS. With the tools module Spatial Analysis was performed cluster analysis and constructed clustering dendrogram. Clusters are merged hierarchically into seven climatic zones suitable for growing exotic species. Defined the mean monthly temperature and precipitation for each zone. The diagram shows the dependence of the probability distribution of the three groups resistance from the mean annual temperature and mean annual precipitation. Describes the climatic conditions of the zones.
Arcgis, bioclim, gbif, maxent, spatial analysis, gis, group of resistance of plants species, dendrogram, zones introduction of plants., climatic conditions zones, species distribution modeling, sochi, izocluster
Короткий адрес: https://sciup.org/14748429