Prediction of Spatial Distribution of Plant Species Richness in the Valdarreh Rangelands, Mazandaran by Macroecological Modelling and Stacked Species Distribution Models

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.of CO occurred in summer, and maximum concentration of PM10 was in autumn.