جستجوی مقالات مرتبط با کلیدواژه "مطلوبیت رویشگاه" در نشریات گروه "محیط زیست"

Predicting the effect of climate change on native ecosystems is one of the longstanding goals of ecologists and is essential for their conservation and management. Species distribution models (SDMs) are the most widely used tools to predict the effects of climate change on the geographical range of plants. In this study, two regression techniques (GLM and MARS) and two machine learning techniques (ANN and RF), along with environmental factors were used to predict the distribution of Onobrychis cornuta L. The species response to future climate (2050-2070) was investigated under optimistic (SSP1-2.6), pessimistic (SSP3-7.0) and very pessimistic (SSP5-8.5) emission scenarios of the IPSL-CM6A-LR climatic model from CMIP6 models. Based on results, the ensemble model and then MARS presented the most accurate prediction. ANN had the lowest prediction accuracy with a significant difference from other models (p<0.05). The sensitivity analysis revealed altitude (24.64%), maximum temperature of the warmest month (20.31%), temperature seasonality (16.57%) and diurnal range of mean temperature (16%) as the most effective variables on the distribution. According to the ensemble model, the suitable habitat occupies about 27% of the area, but its distribution will be decrease under the future climate. The SSP5-8.5 scenario will have the greatest impact on the displacement of the species distribution range. The resulting prediction maps provide valuable information for conservation strategies, including identifying suitable places for its reintroduction and cultivation in the framework of rangeland management plans.

Reports on the monitoring of rangelands of the country indicate that the variety of rangelands habitats is declining. In order to restore these ecosystems, it is necessary to study the desirability of habitats for rangeland species and to determine the most important environmental factors affecting their distribution. Hence, the desirability of mountainous habitats of Urmia for the species of Verbascum stachydiforme L. was considered as a valuable medicinal plant using the ecological niche factor analysis model (ENFA). Ecological niche factor analysis is a multivariate analysis method for studying the geographic distribution of species in the scale of presence data as an associated variable and environmental factors as an independent variable. For this purpose, the spatial data of the presence of the Verbascum stachydiforme (actual area) was recorded with GPS and the environmental factors (climate, topography and earth) related to the habitat were measured. By introducing climatological, topographic and earthy information layers and the map of the presence of species into the biomaper software, a potential habitat map was created. The results showed that of 2,220 hectares of studied habitats, 480 hectares (21.6%) are the potential habitat for Verbascum stachydiforme species. In this regard, the accuracy of the model based on the Boys Index and the use of the Medium Algorithm was evaluated 99%. Also, the compliance rate of the map prepared with the actual map of cover, according to Kappa coefficient, was 0.91. The results of this research can be used to identify areas susceptible to range improvments.