Species Distribution Modelling under Climate Change Scenarios for Maritime Pine (Pinus pinaster Aiton) in Portugal

To date, a variety of species potential distribution mapping approaches have been used, and the agreement in maps produced with different methodological approaches should be assessed. The aims of this study were: (1) to model Maritime pine potential distributions for the present and for the future under two climate change scenarios using the machine learning Maximum Entropy algorithm (MaxEnt); (2) to update the species ecological envelope maps using the same environmental data set and climate change scenarios; and (3) to perform an agreement analysis for the species distribution maps produced with both methodological approaches. The species distribution maps produced by each of the methodological approaches under study were reclassified into presence-absence binary maps of species to perform the agreement analysis. The results showed that the MaxEnt-predicted map for the present matched well the species' current distribution, but the species ecological envelope map, also for the present, was closer to the species' empiric potential distribution. Climate change impacts on the species' future distributions maps using the MaxEnt were moderate, but areas were relocated. The 47.3% suitability area (regular-medium-high), in the present, increased in future climate change scenarios to 48.7%-48.3%. Conversely, the impacts in species ecological envelopes maps were higher and with greater future losses than the latter. The 76.5% suitability area (regular-favourable-optimum), in the present, decreased in future climate change scenarios to 58.2%-51.6%. The two approaches combination resulted in a 44% concordance for the species occupancy in the present, decreasing around 30%-35% in the future under the climate change scenarios. Both methodologies proved to be complementary to set species' best suitability areas, which are key as support decision tools for planning afforestation and forest management to attain fire-resilient landscapes, enhanced forest ecosystems biodiversity, functionality and productivity.

Automated summary

This study modeled the potential distribution of Maritime pine using the MaxEnt algorithm under current and future climate change scenarios. It updated the species ecological envelope map and assessed the agreement between the maps produced by different methodological approaches. The MaxEnt-predicted map matched well with the species' current distribution, while the ecological envelope map was closer to the species' empirical potential distribution. Climate change had moderate impacts on the species' future distributions using MaxEnt, but higher and more severe impacts on the ecological envelope map. Combining both approaches resulted in a decrease in species occupancy in the future under climate change scenarios.