Fluctuation of the ecological niche of Moringa peregrina (Forssk.) Fiori with topoclimatic heterogeneity in southern Iran

Abstract

Heterogeneity can be studied for any dynamic or fixed environmental factors over time. However, determining the extent of heterogeneity occurrence in terms of habitat suitability, variability of dynamic and fixed factors, as well as landform role is an issue that has received less attention. This study aimed to investigate the distribution of Moringa peregrina at two climate change scenarios, to identify the Region of High Heterogenetic (ROHH) of the habitats in those scenarios and to ascertain the heterogeneity of habitat variables of the species in southern Iran. The current and potential distributions of the species in mild and severe climate change scenarios of 2050 and 2070, respectively, were modeled through the Ensemble technique using the climatic and topographic (topoclimatic) variables. The current distribution with four predictions of mild to severe Representative Concentration Pathways (RCP2.5, RCP4.5, RCP6.0 and RCP8.5) were entered into the principal component analysis (PCA) each year to achieve the heterogeneity of distribution. Then, the ROHH was calculated for areas with fluctuations of more than 50%. The topoclimatic variables in the ROHH were compared with the value of each variable in the current distribution in different landforms. The climatic variables of temperature seasonality and mean diurnal range had the greatest impact on M. peregrina distribution. There was more than 90% spatial agreement between the species current and potential distributions under different climate change scenarios (minimum Kappa = 0.9). In climate change scenarios, increase in species distribution is mainly limited by reduced rainfall, high temperature and altitude. The heterogeneity of habitat variables varied greatly in the ROHH and current presence points, indicating the species attempt to occupy new ecological niches. The highest distribution of the species was in the canyons and mountain tops, and the species seeks to occupy these areas in the ROHH. The magnitude of fluctuations of habitat variables at the presence points and the ROHH was different, indicating the species crossing the current niche range to establish in new niche. The mean diurnal range (Bio2) and annual precipitation (Bio12) variables had the lowest heterogeneity in 2050 and 2070 scenarios. This study reports that the fluctuation of habitat variables in areas with high heterogeneity was different from the current distribution range of M. peregrina. No significant fluctuation was found in the distribution range of the species in climate change scenarios.

Spatiotemporal analysis of seasonal trends in land surface temperature within the distribution range of Moringa peregrina (Forssk.) in Southern and Southeastern Iran

“…Investigating the impact of climate changes on the distribution of M . peregrina using climate variables indicated that the mean monthly temperature ranges had less fluctuation in climate change scenarios [ 46 ]. Thus, LST changes are different from predicting scenarios for climate changes.…”

“…Ensemble habitat suitability modeling for M . peregrina was conducted according to the literature [ 46 ]. Modeling was conducted using 61 presence points and 120 pseudo-absence points.…”

“…The ensemble model was created through combining the outputs of several models, including classification and regression tree (CART), random forest (RF), generalized paths seeker (GPS), multiple additive regression (mars), and logistic regression (LR). Since a binary map is required to study the impact of temperature changes on habitat suitability [ 46 ], a threshold value of the true skill statistic (TSS) was used to convert the habitat suitability map into a binary map. The threshold was computed using presence and pseudo-absence points in SPSS v16.…”

“…These topographic structures, by affecting key parameters such as elevation and humidity, can impact habitat suitability and dispersal for species with limited mobility [ 45 ]. In other words, spatial heterogeneity in environmental conditions, resulting from topographic features and climatic factors, plays a significant role in constraining the distribution ranges of species [ 46 ]. However, the distribution of plant and animal species across different landforms, and its relationship with changes in LST and habitat suitability have received less attention [ 47 ].…”

Monitoring spatiotemporal impacts of changes in land surface temperature on near eastern fire salamander (Salamandra infraimmaculata) in the Middle East

“…The eSDM was prepared in R 4.3.1 from the models of maximum entropy (MAXENT), classification tree analysis (CTA), multivariate adaptive regression splines (MARS), generalized linear model (GLM), generalized boosting models (GBM), generalized additive models (GAM), artificial neural networks (ANN), and random forests (RF) in SSDM package [ 54 ]. A total of 1000 pseudo absence points were created randomly across the entire study area [ 55 ]. 70% of the data were allocated to training and 30% to testing.…”