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The Impact of Climate Change on Habitat Suitability for Artemisia sieberi and Artemisia aucheri (Asteraceae) : a Modeling Approach

Mousaei Sanjerehei M., Rundel P. W.

Polish Journal of Ecology

2017

Vol. 65, nr 1

97--109

We determined the current potential distribution of Artemisia sieberi and A. aucheri, two important widespread rangeland shrub species in Iran, using bioclimatic variables with and without the addition of elevation (E) to the MaxEnt model. The impact of climate change on the habitat suitability of the Artemisia species was modeled for mid century under the projected climate change of GFDL-ESM2G (RCP2.6) model, a warmer and slightly wetter condition, and CCSM4 (RCP4.5) model, a warmer and drier condition. The results showed that annual precipitation (AP) and temperature annual range (TAR) were the most important drivers of A. aucheri distribution at a regional scale. With the addition of E to the model, we found that E and AP were the most significant factors in determining the habitat suitability of this species. The most significant factors influencing A. sieberi distribution were AP and annual mean temperature (AMT). E was not identified as the important variable influencing A. sieberi distribution when was added to the model in spite of its high correlation to AMT (|r| > 0.8), while AP was the most important, indicating that A. sieberi is less dependent on elevation than A. aucheri. A. aucheri is regarded as a high elevation species (E > 2500 m) which can be distributed in colder and wetter areas as compared to A. sieberi, a mid-elevation species (E < 2500 m). The projected climate change using both models has a much more impact on A. aucheri, potentially driving more losses and fewer gains in climatically suitable habitat of this species as compared to A. sieberi suggesting the adaptation of the later to a wider range of climatic conditions than A. aucheri. The results of the current and future distribution modeling of the Artemisia species is significant in managing susceptible habitats of these species for climate change and for habitat restoration.

Effects of Sample Size, Sample Accuracy and Environmental Variables on Predictive Performance of MaxEnt Model

Li Y., Ding C.

Polish Journal of Ecology

2016

Vol. 64, nr 3

303--312

The availability of sample data, together with detailed environmental factors, has fueled a rapid increase in predictive modeling of species geographic distributions and environmental requirements. We founded that MaxEnt model has provided different descriptions of potential distributions based on different sample size, sample accuracy and environmental background. We used six combinations based on three sample data set and two kinds of environmental variables to estimate the potentially suitable areas of Brown Eared Pheasant (Crossoptilon mantchuricum) in MaxEnt model. The results show that the complex variables provided the higher AUC value and accurate potential distribution than simple variables based on the same size of samples. Complicated environmental factors combined with moderate size and accurate sample, can predict better results. The model results were scabrous based on simple environmental factors. Furthermore, big sample size and simple prediction environmental factors will reduce the prediction accuracy, whereas small samples provided a conservative description of ecological niche. Here, we highlighted that considering the big size and high accuracy of sample and many environmental factors of a species to minimize error when attempting to infer potential distributions from current data in MaxEnt model.