MODELING GEOGRAPHIC DISTRIBUTION OF ARTEMISIA SIEBERI AND ARTEMISIA AUCHERI USING PRESENCE-ONLY MODELLING METHODS (MAXENT & ENFA)

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KHALASIAHWAZI LEILA; ZARE CHAHOUKI MOHAMMAD ALI; HOSSEINI SEYED ZIAEDIN

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Journal: Journal of Renewable Natural Resources Research Year:2015 | Volume:6 | Issue:1 (SERIAL NUMBER 19) Page(s): 57-73

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Title

MODELING GEOGRAPHIC DISTRIBUTION OF ARTEMISIA SIEBERI AND ARTEMISIA AUCHERI USING PRESENCE-ONLY MODELLING METHODS (MAXENT & ENFA)

Author(s)

KHALASIAHWAZI LEILA | ZARE CHAHOUKI MOHAMMAD ALI | HOSSEINI SEYED ZIAEDIN | Issue Writer Certificate

Keywords

MAXIMUM EENTROPY MODELING TECHNIQUE (MAXENT)Q2

ECOLOGICAL NICHE FACTOR ANALYSIS (ENFA)Q2

JACKKNIFE METHODQ2

AREA UNDER THE CURVEQ2

BOYCE INDEXQ2

Abstract

The main goal of this study was to estimate the geographic distribution of Artemisia sieberi and Artemisia aucheri by models based on occurrence data. Because of widespread use, two methods including Maximum Entropy modeling technique (MaxEnt) and Ecological-niche Factor Analysis (ENFA) selected. For this purpose, a research was conducted in north east rangelands of Semnan. Modeling vegetation data in addition to site condition in formation including topography, climate, geology and soil was prepared. Sampling was done within each unit of sampling parallel transects and 1 vertical transect with 300 m length, each containing 15 quadrates (according to vegetation variations) were established. Quadrate size was determined for each vegetation type using the minimal area method. Soil samples were taken from 0-20 cm and 20-80 cm in starting and ending points of each transect. Soil properties included gravel, texture, organic matter, lime, pH and electrical conductivity were measured. Maps of environmental variables were created by Geographic Information System (GIS) and geostatistics. Then predictive distribution maps of both species were produced using the MaxEnt and ENFA models. Model accuracy in MaxEnt method is evaluated by using the AREA UNDER THE CURVE (AUC). By JACKKNIFE METHOD and response curve, the most important environmental predictor variables were found. By importing the information layers in appropriate model and using necessary statistical analysis in biomapper software, the map of potential habitat has been created. To evaluate the accuracy of the model, BOYCE INDEX has been used and model rectitude in this test was determined as 83.4 percent for A. aucheri but A. sieberi wasn’t achieved sufficient accuracy. In this study, the adequacy of vegetation type mapping was evaluated using kappa statistics and potential habitat map of A. aucheri by MaxEnt method was higher kappa (0.85). Finally, lime 1, gravel 1, lime 2 and slope were significantly affected habitat distribution of A. aucheri, while habitat distribution of A. sieberi affected by elevation, silt 1, and lime 1. MaxEnt, ENFA, and other models based on sampling process to estimate probability of occurrence should be considered as important alternatives for some species distribution models in rangelands.

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APA: Copy

KHALASIAHWAZI, LEILA, ZARE CHAHOUKI, MOHAMMAD ALI, & HOSSEINI, SEYED ZIAEDIN. (2015). MODELING GEOGRAPHIC DISTRIBUTION OF ARTEMISIA SIEBERI AND ARTEMISIA AUCHERI USING PRESENCE-ONLY MODELLING METHODS (MAXENT & ENFA). RENEWABLE NATURAL RESOURCES RESEARCH, 6(1 (SERIAL NUMBER 19)), 57-73. SID. https://sid.ir/paper/212336/en

Vancouver: Copy

KHALASIAHWAZI LEILA, ZARE CHAHOUKI MOHAMMAD ALI, HOSSEINI SEYED ZIAEDIN. MODELING GEOGRAPHIC DISTRIBUTION OF ARTEMISIA SIEBERI AND ARTEMISIA AUCHERI USING PRESENCE-ONLY MODELLING METHODS (MAXENT & ENFA). RENEWABLE NATURAL RESOURCES RESEARCH[Internet]. 2015;6(1 (SERIAL NUMBER 19)):57-73. Available from: https://sid.ir/paper/212336/en

IEEE: Copy

LEILA KHALASIAHWAZI, MOHAMMAD ALI ZARE CHAHOUKI, and SEYED ZIAEDIN HOSSEINI, “MODELING GEOGRAPHIC DISTRIBUTION OF ARTEMISIA SIEBERI AND ARTEMISIA AUCHERI USING PRESENCE-ONLY MODELLING METHODS (MAXENT & ENFA),” RENEWABLE NATURAL RESOURCES RESEARCH, vol. 6, no. 1 (SERIAL NUMBER 19), pp. 57–73, 2015, [Online]. Available: https://sid.ir/paper/212336/en

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