Determination of the Potential Habitat of Range Plant Species Using Maximum Entropy Method (original) (raw)
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Determination of Potential Habitat of Range Plant Species Using Maximum Entropy Method
This study aimed to identify the most important physical variables affecting the distribution of four range plant species (Tamarix aphylla, Calligonum comosum, Prosopis spicigera and Salsola rigida) habitats and to prepare potential habitat map of the species using Maximum Entropy (MaxEnt) method in rangelands of Jiroft city, Kerman province, Iran. To this end, sampling of vegetation including species type and percent cover was conducted with a randomized-systematic method in 2015. Sample size was determined as 60 plots with a quadrat size of 25-100 m 2. For soil sampling, eight profiles were dug in each habitat and samples were taken at two depths, i.e., 0-30 and 30-60 cm. Results indicated that the classification accuracy of the model was acceptable and soil variables including EC, percentage of lime, organic matter, moisture content and texture had the greatest effect on the distribution of the studied plant species habitats. Correlations between the actual and predicted maps for Tamarix aphylla and Calligonum comosum habitats were at a very good level, Kappa= 0.81 and 0.79, respectively; for Prosopis spicigera habitat, it was at a good level, Kappa= 0.75, and finally for Salsola rigida, it was at a moderate level, Kappa = 0.53. These results indicate that the MaxEnt method can provide valuable information about the physical conditions of plant habitats in arid rangeland. Knowledge on physical characteristics of plant habitats can be useful in determination of potential habitats and rangeland improvement projects.
This study aimed to predict geographical distribution of Tamarix ramosissima, Seidlitzia rosmarinus and Cornulaca monocantha in Poshtkouh rangelands and to find the influential variables in the distribution of these species in desert rangelands of central Iran. Eleven environmental factors used to explore the effective environmental variables on given species distribution. Maps of the environmental variables were generated using GIS and Geostatistics facilities. Predictive maps of distribution were produced with maximum entropy method (MaxEnt). Accuracy of model output was assessed by using area under the curve (AUC) and withholding 25 per cent of the data. The agreement of predictive map with actual map was checked by calculating Kappa coefficient. The results indicated that vegetation distribution pattern was mainly related to soil characteristics such as EC, available moisture (AW), lime, organic matter (OM) and elevation. AUC values indicated the high power of MaxEnt to create habitat distribution maps of plant species except C. monocantha (S. Rosmarinus = 0.98, T. ramosissima = 0.99, and C. monocantha = 0.78). Correspondence of actual map with predictive map for S. rosmarinus, C. monocantha and T. ramosissima was assessed at very satisfactory (Kappa=0.76), good (Kappa= 0.61) and poor (Kappa= 0.31) level, respectively.
The quantification of complex relationships between environmental variables and plant habitat distribution is difficult and crucial. The present study employed Logistic Regression (LR), Maximum Entropy (MaxEnt) and Artificial Neural Network (ANN) methods to model plant habitat distribution and identifies the most appropriate modeling approach. The study was conducted in Poshtkouh rangelands, Yazd Province, central Iran. Vegetation was sampled using randomize-systematic sampling method. Soil samples were taken from 0-30 and 30-80 cm depths. The highest values of Kappa index (0.57) belonged to the ANN. Average Kappa values for the MaxEnt and LR were 0.56 and 0.48, respectively. The performance of LR model was higher for species with high marginality and low tolerance, e.g. Cornulaca monacantha, and lower for species with low marginality and high tolerance, e.g. Artemisia sieberi. The ANN and MaxEnt provided better models for species with complex distribution patterns such as widespread species. In fact, differences in the optimal ecological range of plant species, could affect the accuracy of predictive distribution models.
Journal of Arid Environments, 2004
The objective of this research was to study the relationships between environmental factors and vegetation in order to find the most effective factors in the separation of the vegetation types in Poshtkou rangelands of Yazd province. Sampling of soil and vegetation were performed with randomized-systematic method. Vegetation data including density and cover percentage were estimated quantitatively within each quadrat, and using the two-way indicator species analysis (TWINSPAN), and vegetation was classified into different groups. The topographic conditions were recorded in quadrat locations. Soil samples were taken in 0-30 and 30-60 cm depths in each quadrat. The measured soil variables included texture, lime, saturation moisture, gypsum, acidity (pH), electrical conductivity, sodium absorption ratio, and soluble ions (Na + , K + , Mg 2+ , Cl À , CO 3 2À , HCO 3 À and SO 4 2À). Multivariate techniques including principal component analysis (PCA) and canonical correspondence analysis (CCA) were used to analyse the collected data. The results showed that the vegetation distribution pattern was mainly related to soil characteristics such as salinity, texture, soluble potassium, gypsum, and lime. Totally, considering the habitat conditions, ecological needs and tolerance range each plant species has a significant relation with soil properties.
Journal of Rangeland Science, 2017
There is less published research on ecosystems of forested rangeland in Iran. This research was conducted to investigate the forested rangeland area based on legal definition via comparison of indices species richness, diversity, and morphology of the trees and shrubs in Sabzkouh watershed, Chaharmahal Bakhtiari province, Iran. Quantitative characteristics of trees and shrubs were measured by 56 transects using the 'sample line with the fixed tree' method in 2016. In each transect five plots were thrown to measure understory factors. The data was divided into two categories, less and more than 1% and 5%, according to legal definitions of tree canopy cover percentage. In addition, timber volume was divided into two categories, less and more than 20 (m3/ha). Two independent sample analyses (U test and T test) were used to compare between communities and Kappa index method were used check the maps accuracy. In this study, no significant differences were observed in structural c...
Mountainous rangelands play a pivotal role in providing forage resources for livestock, particularly in summer, and maintaining ecological balance. This study aimed to identify environmental variables affecting range plant species distribution, ecological analysis of the relationship between these variables and the distribution of plants, and to model and map the plant habitats suitability by the Random Forest Method (RFM) in rangelands of the Taftan Mountain, Sistan and Baluchestan Province, southeastern Iran. In order to determine the environmental variables and estimate the potential distribution of plant species, the presence points of plants were recorded by using systematic random sampling method (90 points of presence) and soils were sampled in 5 habitats by random method in 0-30 and 30-60 cm depths. The layers of environmental variables were prepared using the Kriging interpolation method and Geographic Information System facilities. The distribution of the plant habitats was finally modelled and mapped by the RFM. Continuous maps of the habitat suitability were converted to binary maps using Youden Index () in order to evaluate the accuracy of the RFM in estimation of the distribution of species potential habitat. Based on the values of the area under curve (AUC) statistics, accuracy of predictive models of all habitats was in good level. Investigating the agreement between the predicted map, generated by each model, and actual maps, generated from fieldmeasured data, of the plant habitats, was at a high level for all habitats, except for Amygdalus scoparia habitat. This study concluded that the RFM is a robust model to analyze the relationships between the distribution of plant species and environmental variables as well as to prepare potential distribution maps of plant habitats that are of higher priority for conservation on the local scale in arid mountainous rangelands.
Potential habitat modeling for reintroduction of three native plant species in central Iran
Journal of Arid Land, 2014
Potential habitat modeling of endemic species is an appropriate method to maintain biodiversity, ecosystem function and rehabilitation of rangeland ecosystems. Astragalus caragana, A. cyclophyllon and A. podolobus are endemic in Iran's rangelands and some neighboring countries. The three native species could endure environmental stresses due to their distinctive ecophysiological characteristics. They play important roles in sustainable pastures production, recreation and improvement. They suffer severe threat from many factors including; grazing, agriculture and invasive exotic species. We analyzed the potential habitat of three native plant species in central Iran basing on the grid map with the resolution of 1-km. We used inventory records from field surveys, herbarium collections and 22 environmental factors to explore the environmental influences on given species distribution by Maximum entropy (Maxent) model. Maxent is a species distribution model that uses species occurrence and environmental data for predicting potential species. The results of our study indicated species occurrence has strong correlation with environmental factors such as mean temperature of wettest season, elevation and precipitation of coldest season. We evaluated the model accuracy by AUC (area under the receiver operating characteristic curve) based on an independent test data set. AUC values indicated the high power of Maxent to create potential habitat map (AUC A. caragana =0.988, AUC A. cyclophyllon =0.927, AUC A. podolobus =0.923). It is important to consider that AUC values tend to be lower for species that have broad distribution scope, such as A. podolobus distribution. Most suitable potential habitat distributions of the three species were predicted in the western and southwestern parts of rangelands in Isfahan province. Visual comparisons of the actual distribution map of the three species with produced Maxent maps represent a good agreement. In general, the model demonstrated that the occurrence of the given species is highly probable when the elevation is between 2,200 and 3,000 m and mean temperature of wettest season less than 3°C. This model, therefore, can be applied to recognize potential sites for rangeland reclamation projects.
The main objective of this study was to investigate the relationship between some index plants of drylands a nd some different soil and environmental variables in Shahriyar rangelands, Iran. Principal Component Analysis (PCA) and SHAZAM 10 package were implied to determine the most effective soil parameters controlling the distribution of vegetation type and finding the logical relationship between each plant species and environmental variables. Analysis with PCA suggesting that there is a relatively high correspondence between vegetation and soil factors that explain 97% of the total variance in data set. PCA results showed that soil texture, salinity, effective soil depth, available nitrogen, potassium, organic matter, lime and soil moisture criteria were the major soil factors responsible for variations in the pattern of vegetation. Besides, results show that for P. aucheri sand in both depth, for Z. eurypterum saturated moisture in both depth, for A. sieberi lime and available water in the first depth and for A. spinosa effective soil depth in the second depth and organic matter in the first depth have the most important role in plant presence and absence probability.
Analele Universitatii din …
A major scientific challenge in plant ecology is to identify and quantify the strength of environmental factors that are responsible for the distribution and abundance of plant species within and among ecosystems. Hence, this study is focused on relation between plant communities and environmental variables in Khezrabad region of Iran. Based on field surveys, eight vegetation types including Artemisia sieberi-Acantholimon erinaceum, Artemisia sieberi-Hertia angustifolia, Artemisia sieberi-Launea acanthodes, Artemisia sieberi-Salsola tomentosa, Artemisia sieberi-Zygophyllum atriplicoides, Artemisia aucheri-Astrgalus albispinus, Artemisia sieberi-Fortuynia bungei, Haloxylon aphyllum were identified. With respecting to the present variance between vegetation and environmental factors, four samples were established in each vegetation type in 0-30 cm depth. The studied soil variables affecting plant communities were texture, EC, pH, Na + , k + , Cl -, Ca 2+ , Mg 2+ , SP, O.M, CaCO3, HCO3and CEC. Among the topographic conditions, elevation was recorded in sampling regions as well. Data matrix of environmental factors and vegetation type was made using the windows (ver. 4.17) of PC-ORD. Results according to PCA showed that in the study area, among different environmental factors, the distribution of vegetation types was most strongly correlated with some agents such as soil texture, salinity and sodicity. In fact, soil texture controls distribution of plant species by affecting moisture availability, ventilation and distribution of plant roots. Beside, soil salinity and sodicity because of habitat condition, plant ecological needs and tolerance range can have negative affect on plant diversity. In addition, results indicated that increasing of elevation had negative effect on plant distribution. However, soil characteristics have more influence on vegetation separation than to the elevation in this study.
Journal of Environmental Science and Management, 2017
The necessary recommendations for environmental management can be provided by measuring diversity and distribution of plant species. The relationship between species diversity and environmental variables affecting Furg rangelands, in the East of Iran was examined. A systematic-random approach was employed to sample vegetation and soil characteristics. Vegetation sampling was conducted using a 10×10 m quadrate (10 quadrate per vegetation type). According to the rooting depth of plants, soil samples were taken from 0-30 cm depth and analyzed through standard laboratory approaches to determine physical and chemical properties. Species diversity was measured using the indices Simpson, Shannon-Wiener and Fisher's alpha. To determine factors affecting species diversity, the Canonical Corresponding Analysis (CCA) and Principal Component Analysis (PCA) were utilized. The vegetation type Ar.au-Ac.sp (type III) had the highest diversity, which was mainly located on the soils with higher quantities of EC, Ca, Na, Gypsum and sand content. The vegetation type Ar.au-La.or-Co.er (type I) with the lowest diversity was mainly placed on the soils where sand content was higher and soil pH, moisture content, TNV, silt content and slope were lower, as compared with those in other vegetation types. Generally, it could be established that in the studied region, the species diversity of plants was more impacted by soil properties, as compared with topographic characteristics.