High landscape-scale forest cover favors cold-adapted plant communities in agriculture-forest mosaics
This repo contains the raw dataset and the code used in the study "High landscape-scale forest cover favors cold-adapted plant communities in agriculture-forest mosaics" published in GEB
DOI: https://doi.org/10.1111/geb.13676
You can clone this R project to reproduce the Analysis, the results and the figures, we advise you to use R studio and its Git connection.
tutorial to getting stated with R studio and git :https://jennybc.github.io/2014-05-12-ubc/ubc-r/session03_git.html
The dataset contains all of the French Forest Inventory (new version: 2005-2019), which is freely distributed by the institute for geographic and forest information (IGN) at https://inventaire-forestier.ign.fr/
We included subsets of the rasters in order to reproduce the figures
The analysis was run using R 4.1.1, and we checked for reproducibility with R 3.6.2
Aim: The ongoing climate warming is expected to reshuffle understory plant-community composition by increasing the occurrence of warm-adapted species at the expense of cold-adapted species. Previous studies have evidenced a warming Community Temperature Index (CTI) over time. However, data indicate that the local tree canopy can partly explain an observed lag between understory plant CTI and climate warming rates, though landscape-scale forest cover effects have not yet been investigated. Here, we test the hypothesis that the amount of forest cover in the landscape lowers local CTI.
Location: France, European temperate mixed forest
Time period: 2005 - 2019
Major taxa studied: Forest vascular plants.
Methods: We compared 2,012 pairs of neighboring French forest inventory plots with contrasting percentages of forest cover within a 1-km radius area (landscape forest cover). We computed the difference in the CTI of the understory communities for each pair and tested the contribution of the landscape-scale forest cover, local canopy cover, and soil conditions to the differences in CTI.
Results: Plots located in highly forested areas (>80% in the 1km area) had an average CTI 0.26 °C lower (0.81°C s.d.) than plots in sparsely forested areas (<30% in a 1km area). Fifty percent of this difference was explained by landscape-scale forest cover. Bioindicated soil conditions such as pH and available nutrients, which correlated with cold-adapted species preferences, explained the remaining 50%.
Main conclusions: Highly forested landscapes allow colder-adapted species to survive in given macroclimatic conditions. These landscapes meet cold-adapted species soil requirements and may cool the regional climate. Further microclimatic studies are needed to confirm the cooling capacity of landscape-scale forest cover.