The Common Redstart is used as a model species to develop sustainable planning for urban green infrastructures. The model estimates optimal densities for environmental variable in the city of La Chaux-de-Fonds, Switzerland. It identifies priority areas of conservation concern, for any urban area, as long as the input data are available. We expect however that the prediction of the model makes more sense in similarly structures urbanized areas like in La Chaux-de-Fonds. In cities with breeding populations of Common Redstart, we recommend censusing the territories and to compare the predicted preferences with the true distribution. We provide here an improved and better automated version of the model presented in: Droz, B.; Arnoux, R.; Bohnenstengel, T.; Laesser, J.; Spaar, R.; Ayé, R.; Randin, C. F., Moderately urbanized areas as a conservation opportunity for an endangered songbird. Landscape Urban Plann. 2019, 181, 1-9. https://doi.org/10.1016/j.landurbplan.2018.09.011
The production of predicting variables and the model-Redstart is provided by a series of scripts. Its source code is primarily written in the R language version 4.0.3 or under version 3.5.0. Some parts of the coding are supported by GRASS v.7 (https://grass.osgeo.org), Java Runtime Environment 64-bit 8.0-build-271 (http://www.filehippo.com/download_jre_64/) and Maxent version 3.3.3k (https://biodiversityinformatics.amnh.org/open_source/maxent/) which should be installed before starting. Please see the tutorial section Implementation of the workflow for more details.
- Copy the folder Redstart-model
- Follow the instructions on the tutorial
Droz, Boris, Laesser, Jacques, & Spaar, Reto. (2022). Species distribution models (SDMs) of Common Redstart (Phoenicurus phoenicurus) – workflow and tutorial. V.0.1. Zenodo. https://doi.org/10.5281/zenodo.5817737
Laesser, Jacques, Droz, Boris, & Spaar, Reto. (2022). Identification des quartiers verts d'importance pour la biodiversité – Modèle d'habitat du rougequeue à front blanc en milieux urbanisés à l'intention des gestionnaires. Zenodo. https://doi.org/10.5281/zenodo.5949033
The folder "evaluate_prediction" contain script to evaluate the performance of the prediction compare to the calibration area.