Where Z, is the linear combination model of species I (Water Onion) as follows: Z= ß0 + ß1X1 + ß2X2 +…+ ßnXn ß1 = coefficient Xi = independent variables (environment factors) The probability values derived from the regression models range from 0.0-0.1. The higher the value, the greater the likelihood of occupancy of the Water Onion and the lower value suggests an unlikely occurrence. A cut-off value of 0.5 was used for binary classification. Thus, any pixel containing the probability values equal or greater than 0.5 was categorized as presence, otherwise classified as absence. Besides co n tingency t a b l e , the performance of the logistic regression model was assessed by using the area under curve (AUC) of a receiver operating characteristic curve (ROC) (Hosmer and Lemeshow, 2000). 2. Maximum entropy (MaxEnt) which operates by establishing a relationship between a presence-only data and ecological variables within that region and then identifying other suitable areas (Phillips et. al., 2006). Default setting in MaxEnt as outlined in Phillips and Dudik (2008) were used and a 25% random test percentage and f ive cross validate replicated runs were applied. The performance and accuracy of MaxEnt were evaluated similar to the logistic regression model. 2.4 Assessment of conservation status The current conservation status of Water Onion in Thailand was evaluated using the IUCN Red List categories and criteria version 3.1 (criterion Geographic range in the form of B1-predicted extent of occurrence (IUCN, 2001). III. RESULTS 3.1 Distribution of Water Onion The results of the logistic regressions indicated that elevation, NDVI, annual mean Temperature, max Temperature of warmest month, annual precipitation, precipitation of wettest quarter, precipitation of driest quarter, dredging, distance to village and distance to road were significantly related to the distribution of Water Onion as shown below. Z = -56.42 - 0.02 (dem) + 15.74 (NDVI) - 0.30 (bio_1) + 0.42 (bio_5) + 0.02 (bio_12) - 0.04 (bio_16) - 0.12 (bio_17) - 0.00007 (dred) - 0.00032 (village_dist) - 0.00121 (road_dist) Where : dem = elevation (meter) NDVI = normalized difference vegetation Index bio_1 = annual mean temperature bio_5 = max temperature of warmest month bio_12 = annual precipitation bio_16 = precipitation of wettest quarter Fig.1 The area under curve (AUC) for Water Onion from logistic regression 32 Proceedings of the International Conference on Climate Change, Biodiversity and Ecosystem Services for the Sustainable Development Goals (SDGs): Policy and Practice 27-29 June 2016, Cha-am, Phetchaburi, Thailand
Proceedings of International Conference on Climate Change, Biodiversity and Ecosystem Services for the Sustainable Development Goals : Policy and Practice 27-29 June 2016 at the Sirindhorn International Environmental Park, Cha-am, Phetchaburi, Thailand
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