Abstract
The identification of geographical distribution of a plant species is crucial for understanding the importance of environmental variables affecting plant habitat. In the present study, the spatial potential distribution of Astragalus fasciculifolius Boiss. as a key specie was mapped using maximum entropy (Maxent) as data mining technique and bivariate statistical model (FR: frequency ratio) in marl soils of southern Zagros, Iran. The A. fasciculifolius locations were identified and recorded by intensive field campaigns. Then, localities points were randomly split into a 70% training dataset and 30% for validation. Two climatic, four topographic, and eight edaphic variables were used to model the A. fasciculifolius distribution and its habitat potential. Maps of environmental variables were generated using Geographic Information System (GIS). Next, the habitat suitability index (HSI) maps were produced and classified by means of Maxent and FR approaches. Finally, the area under the receiver operating characteristic (AUC-ROC) curve was used to compare the performance of maps produced by Maxent and FR models. The interpretation of environmental variables revealed that the climatic and topographic parameters had less impact compared to edaphic variables in habitat distribution of A. fasciculifolius. The results showed that bulk density, nitrogen, acidity (pH), sand, and electrical conductivity (EC) of soil are the most significant variables that affect distribution of A. fasciculifolius. The validation of results showed that AUC values of Maxent and FR models are 0.83 and 0.76, respectively. The habitat suitability map by the better model (Maxent) showed that areas with high and very high suitable classes cover approximately 22% of the study area. Generally, the habitat suitability map produced using Maxent model could provide important information for conservation planning and a reclamation project of the degraded habitat of intended plant species. The distribution of the plants identifies the water, soil, and nutrient resources and affects the fauna distribution, and this is why it is relevant to research and to understand the plant distribution to properly improve the management and to achieve a sustainable management.
Highlights
Spatial and temporal distribution of species is affected by the quality and quantity of habitats [1,2]
Among the 14 variables selected for the model development, A. fasciculifolius habitat was mainly influenced by soil parameters including bulk density, nitrogen content, electrical conductivity, acidity, and clay percent
The habitat suitability maps produced using Frequency ratio (FR) and maximum entropy (Maxent) approach were classified into four classes including very high, high, moderate, and low
Summary
Spatial and temporal distribution of species is affected by the quality and quantity of habitats [1,2]. Species distribution models (SDMs) are generally used to predict the habitat potential and spatial distribution of a species according to the occurrence data and different environmental variables [3,4,5]. These models have been widely used for many different purposes in ecological and conservation studies to evaluate the relationship between species occurrence and environmental variables [6,7,8]. Among different species distribution models, Maxent has been proven suitable to predict the habitat potential of plant species based on presence-only occurrence data [5,6,18,20,21]. Among the mentioned models, the FR algorithm mainly has been used for predicting the natural hazard such as landslide [22,23,24,25], its application in species distribution modeling has not been well documented
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