Volume 17, Issue 1 (5-2023)
مرتع 2023, 17(1): 66-81 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Zare M, Ghorbani A, Moameri M, Piri Sahragard H, Mostafazade R, Hosseini Z et al . Effect of Environmental Factors on Habitat Prediction of Species Dorema ammoniacum D. DON. in Nadoushan Rangelands, Yazd Province. مرتع 2023; 17 (1) :66-81
URL: http://rangelandsrm.ir/article-1-1109-en.html
URL: http://rangelandsrm.ir/article-1-1109-en.html
Mostafa Zare 
, Ardavan Ghorbani , Mehdi Moameri , Hossein Piri Sahragard , Raoof Mostafazade , Zeinolabedin Hosseini , Farid Dadjou
, Ardavan Ghorbani , Mehdi Moameri , Hossein Piri Sahragard , Raoof Mostafazade , Zeinolabedin Hosseini , Farid Dadjou
Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil
Abstract: (3894 Views)
Background and objectives: The conservation and management of endangered medicinal and industrial plants in rangelands are essential for the economic and social benefits they provide. Dorema ammoniacum D. DON. is an important fodder, medicinal, and industrial plant that is threatened due to over-exploitation. This study aimed to predict the potential habitat of D. ammoniacum using logistic regression analysis and to identify the environmental factors that influence its distribution in the Nadoushan rangelands of Yazd province.
Methodology: We collected data on environmental factors, including topography, climate, soil, and vegetation, from the rangelands of Nadushan. Vegetation sampling was conducted in six homogeneous units using the random-systematic method. Soil samples were collected from the beginning and end of each transect at depths of 0-30 and 30-60 cm. We used variogram analysis to investigate the spatial structure between soil factors, and kriging interpolation and inverse distance weighting methods were used to prepare soil characteristic maps. The logistic regression model was used to predict the potential distribution of D. ammoniacum, using presence/absence data and environmental data.
Results: The results showed that the variables of saturated moisture, sodium and calcium percentage of the first soil depth, organic carbon percentage of the second soil depth, and nitrate of the first soil depth were the most important environmental factors affecting the distribution of D. ammoniacum. The presence of D. ammoniacum had a positive relationship with the percentage of saturated moisture and sodium of the first soil depth, organic carbon of the second depth, and calcium of the first soil depth, and a negative relationship with nitrate of the first soil depth. The logistic regression model predicted that 20% of the studied area had excellent suitability and 24% had suitable habitat for D. ammoniacum.
Conclusion: Logistic regression analysis was useful for predicting the potential habitat of D. ammoniacum in the Nadoushan rangelands, and the results can guide conservation efforts and management decisions. The study identified the significant environmental factors that influence the distribution of D. ammoniacum and provided a useful tool for identifying potential areas for sustainable exploitation and restoration of the species.
Methodology: We collected data on environmental factors, including topography, climate, soil, and vegetation, from the rangelands of Nadushan. Vegetation sampling was conducted in six homogeneous units using the random-systematic method. Soil samples were collected from the beginning and end of each transect at depths of 0-30 and 30-60 cm. We used variogram analysis to investigate the spatial structure between soil factors, and kriging interpolation and inverse distance weighting methods were used to prepare soil characteristic maps. The logistic regression model was used to predict the potential distribution of D. ammoniacum, using presence/absence data and environmental data.
Results: The results showed that the variables of saturated moisture, sodium and calcium percentage of the first soil depth, organic carbon percentage of the second soil depth, and nitrate of the first soil depth were the most important environmental factors affecting the distribution of D. ammoniacum. The presence of D. ammoniacum had a positive relationship with the percentage of saturated moisture and sodium of the first soil depth, organic carbon of the second depth, and calcium of the first soil depth, and a negative relationship with nitrate of the first soil depth. The logistic regression model predicted that 20% of the studied area had excellent suitability and 24% had suitable habitat for D. ammoniacum.
Conclusion: Logistic regression analysis was useful for predicting the potential habitat of D. ammoniacum in the Nadoushan rangelands, and the results can guide conservation efforts and management decisions. The study identified the significant environmental factors that influence the distribution of D. ammoniacum and provided a useful tool for identifying potential areas for sustainable exploitation and restoration of the species.
Keywords: Dorema ammoniacum, habitat prediction, logistic regression, species distribution modeling.
Type of Study: Research |
Subject:
Special
Received: 2021/12/19 | Accepted: 2021/12/1 | Published: 2023/05/31
Received: 2021/12/19 | Accepted: 2021/12/1 | Published: 2023/05/31
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
