The potential range of Agrilus planipennis according to current and future climate conditions

This dataset is associated to the following reference:

Jean-Pierre Rossi, Raphaëlle Mouttet, Pascal Rousse and Jean-Claude Streito (2024) Modelling the potential range of Agrilus planipennis in Europe according to current and future climate conditions. In press. Trees, Forests and People. https://doi.org/10.1016/j.tfp.2024.100559

The files correspond to rasters saved as geotiff files. They can be used in geographical information systems.

Current climate conditions: 2001-2018. The maps correspond to the whole world.

CS_2001-2018_Bart.tif

Climate suitability for Agrilus planipennis modelled using the BART algorithm and the reference conditions (2001-2018). The climate suitability ranges from 0 (unsuitable) to 1 (suitable).

CS_2001-2018_Brt.tif

Climate suitability for Agrilus planipennis modelled using the BRT algorithm and the reference conditions (2001-2018). The climate suitability ranges from 0 (unsuitable) to 1 (suitable).

CS_2001-2018_Rf.tif

Climate suitability for Agrilus planipennis modelled using the RF algorithm and the reference conditions (2001-2018). The climate suitability ranges from 0 (unsuitable) to 1 (suitable).

CS_2001-2018_Bart_pres_abs.tif

Reclassified climate suitability maps for Agrilus planipennis modelled using the algorithm BART and the reference conditions (2001-2018). The raster contains 2 classes: suitable conditions (raster value = 1) and unsuitable conditions (raster value = 0).

CS_2001-2018_Brt_pres_abs.tif

Reclassified climate suitability maps for Agrilus planipennis modelled using the algorithm BRT and the reference conditions (2001-2018). The raster contains 2 classes: suitable conditions (raster value = 1) and unsuitable conditions (raster value = 0).

CS_2001-2018_Rf_pres_abs.tif

Reclassified climate suitability maps for Agrilus planipennis modelled using the algorithm RF and the reference conditions (2001-2018). The raster contains 2 classes: suitable conditions (raster value = 1) and unsuitable conditions (raster value = 0).

CS_2001-2018_committee.tif

Map showing the percentage of algorithms indicating suitable climate conditions for Agrilus planipennis. The algorithms (BART, BRT and RF) are projected using the current climate conditions (2001-2018).

Future climate conditions: 2041-2060. The maps correspond to Europe.

 CS_2041-2060_SSP1-2.6_committee.tif

Map showing the percentage of algorithms indicating suitable climate conditions for Agrilus planipennis. The algorithms (BART, BRT and RF) are projected using the climate data associated with 11 GCMs for the period 2041-2060 and the SSP1-2.6.

 CS_2041-2060_SSP2-4.5_committee.tif

Map showing the percentage of algorithms indicating suitable climate conditions for Agrilus planipennis. The algorithms (BART, BRT and RF) are projected using the climate data associated with 11 GCMs for the period 2041-2060 and the SSP2-4.5.

 CS_2041-2060_SSP3-7.0_committee.tif

Map showing the percentage of algorithms indicating suitable climate conditions for Agrilus planipennis. The algorithms (BART, BRT and RF) are projected using the climate data associated with 11 GCMs for the period 2041-2060 and the SSP3-7.0.

 CS_2041-2060_SSP5-8.5_committee.tif

Map showing the percentage of algorithms indicating suitable climate conditions for Agrilus planipennis. The algorithms (BART, BRT and RF) are projected using the climate data associated with 11 GCMs for the period 2041-2060 and the SSP5-8.5.

BART: Bayesian Additive Regression Trees

BRT: Boosted Regression Trees

RF: Random Forest