Big data help to define climate change challenges for the typical Mediterranean species Cistus ladanifer L.

Abstract

Climate change’s huge impact on Mediterranean species’ habitat suitability and spatial and temporal distribution in the coming decades is expected. The present work aimed to reconstruct rockrose (Cistus ladanifer L.) historical and future spatial distribution, a typically Mediterranean species with abundant occurrence in North Africa, Iberian Peninsula, and Southern France. The R ensemble modeling approach was made using the biomod2 package to assess changes in the spatial distribution of the species in the Last Interglacial (LIG), the Last Glacial Maximum (LGM), and the Middle Holocene (MH), in the present, and in the future (for the years 2050 and 2070), considering two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). The current species potential distribution was modeled using 2,833 occurrences, six bioclimatic variables, and four algorithms, Generalized Linear Model (GLM), MaxEnt, Multivariate Adaptive Regression Splines (MARS), and Artificial Neural Networks (ANN). Two global climate models (GCMs), CCSM4 and MRI-CGCM3, were used to forecast past and future suitability. The potential area of occurrence of the species is equal to 15.8 and 14.1% of the study area for current and LIG conditions, while it decreased to 3.8% in the LGM. The species’ presence diaminished more than half in the RCP 4.5 (to 6.8% in 2050 and 7% in 2070), and a too low figure (2.2%) in the worst-case scenario (RCP 8.5) for 2070. The results suggested that the current climatic conditions are the most suitable for the species’ occurrence and that future changes in environmental conditions may lead to the loss of suitable habitats, especially in the worst-case scenario. The information unfolded by this study will help to understand future predictable desertification in the Mediterranean region and to help policymakers to implement possible measures for biodiversity maintenance and desertification avoidance.

Predicting the habitat suitability and niche dynamics of two Ziziphus species in response to climate change

“…To address collinearity issues among these variables, hierarchical cluster analysis was employed with Pearson's correlation coefficient (with a cutoff set at 0.7) (Gallego-Narbón et al, 2023). This approach was executed using the 'remove collinearity' function in the R package 'virtualspecies' (Leroy et al, 2016;Louppe et al, 2020;Almeida et al, 2023). Ultimately, a total of seven predictors were retained in the model, encompassing isothermality (bio3), maximum temperature of warmest month (bio5), temperature annual range (bio7), mean temperature of wettest quarter (bio8), precipitation seasonality (bio15), precipitation of wettest quarter (bio17), and precipitation of coldest quarter (bio19).…”

Impact of Climate Change on the Potential Geographical Distribution Patterns of Luculia pinceana Hook. f. since the Last Glacial Maximum

“…Since paleoclimate data from WorldClim2. 1 were not yet available, we used Community Climate System Model version 4 (CCSM4) from the WorldClim1.4 dataset, developed by the National Center for Atmospheric Research to better simulate East Asian climate characteristics [49], for predictions during the LGM and the MH periods. We scaled down the temperature layer values to one tenth of their original to maintain consistency with current and future layer units [14].…”

“…Plants possess a certain level of adaptability to their environment, and changes in living conditions brought about by climate change can impact this adaptability [1]. Understanding how plants survive and reproduce under dynamic climatic conditions is crucial.…”

“…Climate change, a focal topic of the 21st century, has wrought a series of impacts through changes in surface temperature, precipitation, heatwave frequency and intensity, forest fires, and pest outbreaks. These factors collectively alter the adaptability of plants to stress, as well as the structure and function of ecosystems [1,2], and consequently modify the geographic distribution patterns of plants. Such alterations can lead to extensive expansions [3], directly or indirectly causing substantial losses in global biodiversity [4].…”