Volume 6, Issue 2 (2018)                   IQBQ 2018, 6(2): 139-145 | Back to browse issues page

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Kargar M, Jafarian Z, Tamartash R, Alavi S. Prediction of Spatial Distribution of Plant Species Richness in ‎the Valdarreh Rangelands, Mazandaran by Macroecological ‎Modelling and Stacked Species Distribution Models. IQBQ. 2018; 6 (2) :139-145
URL: http://journals.modares.ac.ir/article-24-16475-en.html
1- Range Management Department, Natural Resource Faculty, Sari Agricultural of Sciences & Natural ‎Resources University, Sari, Iran
2- Range Management Department, Natural Resource Faculty, Sari Agricultural of Sciences & Natural ‎Resources University, Sari, Iran , jafarian79@yahoo.com
3- Forestry Department, Natural Resource Faculty, Tarbiat Modares University, Noor, Iran
Abstract:   (95 Views)
Aims: The information on species richness (SR) can be used to help establish conservation strategies or to predict future patterns of biodiversity under global change. The aim of the present study was the prediction of spatial distribution of plant species richness in the Valdarreh Rangelands, Mazandaran, Iran by Macroecological Modelling (MEM) and Stacked Species Distribution Models (S-SDM).
Materials & Methods: This experimental study was carried out in the Valdarreh rangelands. In the present study compared the direct, macroecological approach for modeling species richness with the more recent approach of stacking predictions from individual species distributions. Both approaches performed in reproducing observed patterns of species richness along an elevation gradient were evaluated. MEM was implemented by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually, assuming a binomial distribution.
Findings: The direct MEM approach yielded nearly unbiased predictions centered around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by The S-SDM approaches. This method also cannot provide any information on species identity and, thus community composition. Predicted SR by S-SDM was correlated by a Spearman p of 0.76 with the observed SR. The MEM-predicted SR achieved a Spearman rank correlation of 0.32 with S-SDM. The species richness along the elevational gradient for MEM and S-SDM were 0.21 and 0.82, respectively.
Conclusion: MEM and S-SDM have complementary strengths and both can be used in combination to obtain better species richness predictions.
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Article Type: مقاله Ø§Ø³ØªØ®Ø±Ø§Ø Ø´Ø¯Ù‡ از پایان نامه |
Received: 2017/10/14 | Accepted: 2018/07/17 | Published: 2018/07/17
* Corresponding Author Address: Range Management Department, Natural Resource Faculty, Sari Agricultural of Sciences & Natural ‎Resources University, Sari, Iran

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