Prediction of Dry Dipterocarp Forest Distribution Using Ecological Niche Model in Ping Basin of Northern Thailand

DDF （dry dipterocarp forest） is importantly deciduous forest type in Thailand since it consists of important tree species for timber products and non-timber products. So, people would like to come to use these products for daily uses in this forest type. The main aim of this study is to evaluate significant biophysical factors for DDF distribution using factor analysis and to model DDF distribution using ENFA （ecological niche factor analysis）. In this study, 13 watersheds of Ping Basin in northern Thailand were selected as the study site based on availability of forest inventory data in 2007 from DNP （Department of National Parks, Wildlife and Plant Conservation）. Basic biophysical data for data analysis included forest inventory data （179 DDF plots）, 10 climatic data, three topographic data, and one soil data. For identification and evaluation of biophysical factors for DDF distribution using factor analysis, the first three factors, namely DDF-1, DDF-2 and DDF-3, had been extracted with 95.35% of total variance. These three components were used to predict DDF distribution based on HS （habitat suitability） with ENFA. In practice, the results were validated with AVI （absolute validation index） and CVI （contrast validation index） with validated forest inventory dataset. This evaluation shows that DDF-2 model is the best HS data consisting of four physical factors （mean annually temperature, mean monthly maximum temperature, mean monthly minimum temperature, and elevation）, which is able to effectively used for habitat suitability for DDF distribution prediction. It was found that habitat suitability for DDF distribution can be classified into four classes including high suitable habitat, moderate suitable habitat, low suitable habitat, and unsuitable habitat. As a result, DDF distributions with high suitable habitat are highly related with DDF forest inventory plots of DNP. Thus, the obtained output can be further used for DDF rehabilitation according to climate and topographic factors.

Predicting Potential Distribution of Gaur （Bos gaurus） in Tadoba-Andhari Tiger Reserve, Central India

The rapid pace of development of GIS （geographical information system） has assisted in identification of conservation priority sites by delineating species distribution using models on habitat suitability. Gaur, Bos gaurus, is categorized as ＂Vulnerable＂ in the IUCN Red List of Threatened Species, 2009. The study has used ENFA （ecological niche factor analysis） to understand the distribution status of Gaur in TATR （Tadoba-Andhari Tiger Reserve）, Central India. TATR was sampled using stratified random sampling strategy. A total of 21 continuous variables were used, categorised under 4 environmental descriptors categories viz. habitat, anthropogenic, topographic and hydrological variables. All the variables were tested for the correlation and one of the variable among strongly correlated （r 〉 0.7） variables was discarded to avoid redundancy. A total of 14 variables were retained. The model resulted in marginality of 0.56 and specialization of 2.608. Presence of Gaur showed the positive association with canopy density classes （〈 30% ＆ 40-60%） and open forest. However, it was negatively associated with elevation, non-forest, riparian forest, scrub and teak forest. The study has delineated the areas where appropriate habitat conditions exist to sustain Gaur populations vital for planning strategies for conservation of this megaherbivore species in tropical forests.

The failed invasion of Harmonia axyridis in the Azores, Portugal: Climatic restriction or wrong population origin?

We tested two questions:(i)whether the climatic conditions of the Azorean Islands in Portugal may have restricted the invasion of Harmonia axyridis across this archipelago and(ii)determine what population of this species could have a higher probability of invading the islands.We used MaxEnt to project the climate requirements of different H.axyridis populations from three regions of the world,and the potential global niche of the species in the Azorean islands.Then we assessed the suitability of the islands for each of the three H.axyridis populations and global potential niche through histograms analysis,Principal Component Analysis(PCA)of climate variables,and a variable-by-variable assessment of the suitability response curves compared with the climatic conditions of the Azores.Climatic conditions of the Azores are less suitable for the U.S.and native Asian populations of H.axyridis,and more suitable for European populations and the global potential niche.The PCA showed that the climatic conditions of the islands differed from the climatic requirements of H.axyridis.This difference is mainly explained by precipitation of the wettest month,isothermality,and the minimum temperature of the coldest month.We concluded that the climatic conditions of the Azores could have influenced the establishment and spread of H.axyridis on these islands from Europe.Our results showed that abiotic resistance represented by the climate of the potentially colonizable zones could hinder the establishment of invasive insects,but it could vary depending of the origin of the colonizing population.

Habitat suitability modeling of amphibian species in southern and central China:environmental correlates and potential richness mapping

Successful wildlife management must take into account suitable habitat areas. Information on the correlation between distribution ranges and environmental conditions would, therefore, improve the efficacy of in-situ conservation of wildlife. In this contribution, correlations between environmental factors and the distribution of 51 amphibians in southern and central China were investigated. Ecological niche factor analysis （ENFA） at a spatial resolution of 1°latitudexllongitude identified a mixture of climatic and habitat factors as important predictors of the occurrence of individual species. The aims of the present work were （i） to evaluate potential distributions of amphibians based on the suitability of areas; （ii） to identify the major environmental descriptors upon which they depend; and （iii） to identify areas of potential high richness that have been overlooked in available inventories. Most of the predicted species ranges of species covered the majority of southern and central China. Six richness hotspots were predicted, of which four have been described previously, but two overlooked （SE Fujian and SE Qinghai）. The prediction model was considered to be relatively accurate and it is recommended that these two new potential hotspots should be subjected to further evaluation and sampling efforts. Amphibians have high ecological preference for high humidity and precipitation, and low annual frost days. ENFA is a useful tool in wildlife conservation assessment because it is able to identify potential hotspots where studies on the correlations between environmental descriptors and the occurrence of particular species could be focused.

Quantifying landscape linkages among giant panda subpopulations in regional scale conservation

Understanding habitat requirements and identifying landscape linkages are essential for the survival of isolat­ed populations of endangered species.Currently,some of the giant panda populations are isolated,which threat­ens their long-term survival,particularly in the Xiaoxiangling mountains.In the present study,we quantified niche requirements and then identified potential linkages of giant panda subpopulations in the most isolated re­gion,using ecological niche factor analysis and a least-cost path model.Giant pandas preferred habitat with co­nifer forest and gentle slopes(>20 to≤30°).Based on spatial distribution of suitable habitat,linkages were iden­tified for the Yele subpopulation to 4 other subpopulations(Liziping,Matou,Xinmin and Wanba).Their lengths ranged from 15 to 54 km.The accumulated cost ranged from 693 to 3166 and conifer forest covered over 31%.However,a variety of features(e.g.major roads,human settlements and large unforested areas)might act as barriers along the linkages for giant panda dispersal.Our analysis quantified giant panda subpopulation connec­tivity to ensure long-term survival.