About

This repository contains the code, data and analysis of the manuscript submitted to Drones.

CRediT¹ Statment (Contributor Roles Taxonomy)²:

• Antonio J. Pérez-Luque : Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, and Writing - review & editing.

• Maria Eugenia Ramos Font :: Conceptualization, Investigation, Methodology, and Writing - review & editing.

• Mauro J. Tognetti Barbieri: Data curation, Methodology, Validation, and Writing - review & editing.

• Carlos Tarragona Pérez: Data curation, Methodology, and Validation.

• Guillermo Calvo Renta: Data curation, Methodology, and Validation.

• Ana Belén Robles Cruz: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, and Writing - review & editing.

We used R version 4.2.1 (R Core Team 2022a) and the following R packages: datasets v. 4.2.1 (R Core Team 2022b), DT v. 0.25 (Xie, Cheng, and Tan 2022), ggparty v. 1.0.0 (Borkovec and Madin 2019), ggpmisc v. 0.5.1 (Aphalo 2022a), ggpp v. 0.4.5 (Aphalo 2022b), ggpubr v. 0.4.0 (Kassambara 2020), ggtext v. 0.1.2 (Wilke and Wiernik 2022), graphics v. 4.2.1 (R Core Team 2022c), grateful v. 0.1.11 (Rodríguez-Sánchez, Jackson, and Hutchins 2022), grDevices v. 4.2.1 (R Core Team 2022d), grid v. 4.2.1 (R Core Team 2022e), here v. 1.0.1 (Müller 2020), kableExtra v. 1.3.4 (Zhu 2021), KernSmooth v. 2.23.20 (Wand 2021), knitr v. 1.40 (Xie 2014, 2015, 2022), lattice v. 0.20.45 (Sarkar 2008), libcoin v. 1.0.9 (Hothorn 2021), methods v. 4.2.1 (R Core Team 2022f), Metrics v. 0.1.4 (Hamner and Frasco 2018), modeltools v. 0.2.23 (Hothorn, Leisch, and Zeileis 2020), MPV v. 1.59 (Braun and MacQueen 2022), mvtnorm v. 1.1.3 (Genz and Bretz 2009; Genz et al. 2021), party v. 1.3.11 (Hothorn, Hornik, and Zeileis 2006a; Hothorn et al. 2006; Strobl et al. 2007, 2008; Zeileis, Hothorn, and Hornik 2008a), partykit v. 1.2.16 (Hothorn, Hornik, and Zeileis 2006b; Zeileis, Hothorn, and Hornik 2008b; Hothorn and Zeileis 2015), patchwork v. 1.1.2 (Pedersen 2022), plotrix v. 3.8.2 (J 2006), rgbif v. 3.7.3 (Chamberlain and Boettiger 2017; Chamberlain et al. 2022), rpart v. 4.1.16 (Therneau and Atkinson 2022), sandwich v. 3.0.2 (Zeileis 2004, 2006b; Zeileis, Köll, and Graham 2020), stats v. 4.2.1 (R Core Team 2022g), stats4 v. 4.2.1 (R Core Team 2022h), strucchange v. 1.5.3 (Zeileis et al. 2002, 2003; Zeileis 2006a), tenzing v. 0.2.0 (Kovacs et al. 2020; Holcombe et al. 2020), tidyverse v. 1.3.2 (Wickham et al. 2019), utils v. 4.2.1 (R Core Team 2022i), zoo v. 1.8.11 (Zeileis and Grothendieck 2005).

References

Aphalo, Pedro J. 2022a. Ggpmisc: Miscellaneous Extensions to ’Ggplot2’. https://CRAN.R-project.org/package=ggpmisc.

———. 2022b. Ggpp: Grammar Extensions to ’Ggplot2’. https://CRAN.R-project.org/package=ggpp.

Borkovec, Martin, and Niyaz Madin. 2019. Ggparty: ’Ggplot’ Visualizations for the ’Partykit’ Package. https://CRAN.R-project.org/package=ggparty.

Braun, W. J., and S. MacQueen. 2022. MPV: Data Sets from Montgomery, Peck and Vining. https://CRAN.R-project.org/package=MPV.

Chamberlain, Scott, Vijay Barve, Dan Mcglinn, Damiano Oldoni, Peter Desmet, Laurens Geffert, and Karthik Ram. 2022. Rgbif: Interface to the Global Biodiversity Information Facility API. https://CRAN.R-project.org/package=rgbif.

Chamberlain, Scott, and Carl Boettiger. 2017. “R Python, and Ruby Clients for GBIF Species Occurrence Data.” PeerJ PrePrints. https://doi.org/10.7287/peerj.preprints.3304v1.

Genz, Alan, and Frank Bretz. 2009. Computation of Multivariate Normal and t Probabilities. Lecture Notes in Statistics. Heidelberg: Springer-Verlag.

Genz, Alan, Frank Bretz, Tetsuhisa Miwa, Xuefei Mi, Friedrich Leisch, Fabian Scheipl, and Torsten Hothorn. 2021. mvtnorm: Multivariate Normal and t Distributions. https://CRAN.R-project.org/package=mvtnorm.

Hamner, Ben, and Michael Frasco. 2018. Metrics: Evaluation Metrics for Machine Learning. https://CRAN.R-project.org/package=Metrics.

Holcombe, Alex O., Marton Kovacs, Fredrik Aust, and Balazs Aczel. 2020. “tenzing: A Web App to Document Contributorship with CRediT.” MetaArXiv. https://doi.org/10.31222/osf.io/b6ywe.

Hothorn, Torsten. 2021. Libcoin: Linear Test Statistics for Permutation Inference. https://CRAN.R-project.org/package=libcoin.

Hothorn, Torsten, Peter Buehlmann, Sandrine Dudoit, Annette Molinaro, and Mark Van Der Laan. 2006. “Survival Ensembles.” Biostatistics 7 (3): 355–73.

Hothorn, Torsten, Kurt Hornik, and Achim Zeileis. 2006a. “Unbiased Recursive Partitioning: A Conditional Inference Framework.” Journal of Computational and Graphical Statistics 15 (3): 651–74.

———. 2006b. “Unbiased Recursive Partitioning: A Conditional Inference Framework.” Journal of Computational and Graphical Statistics 15 (3): 651–74. https://doi.org/10.1198/106186006X133933.

Hothorn, Torsten, Friedrich Leisch, and Achim Zeileis. 2020. Modeltools: Tools and Classes for Statistical Models. https://CRAN.R-project.org/package=modeltools.

Hothorn, Torsten, and Achim Zeileis. 2015. “partykit: A Modular Toolkit for Recursive Partytioning in R.” Journal of Machine Learning Research 16: 3905–9. https://jmlr.org/papers/v16/hothorn15a.html.

J, Lemon. 2006. “Plotrix: A Package in the Red Light District of r.” R-News 6 (4): 8–12.

Kassambara, Alboukadel. 2020. Ggpubr: ’Ggplot2’ Based Publication Ready Plots. https://CRAN.R-project.org/package=ggpubr.

Kovacs, Marton, Fredrik Aust, Alex O. Holcombe, and Balazs Aczel. 2020. “tenzing: Documenting Contributions to Scientific Scholarly Output with CRediT.” https://github.com/marton-balazs-kovacs/tenzing.

Müller, Kirill. 2020. Here: A Simpler Way to Find Your Files. https://CRAN.R-project.org/package=here.

Pedersen, Thomas Lin. 2022. Patchwork: The Composer of Plots. https://CRAN.R-project.org/package=patchwork.

R Core Team. 2022a. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022b. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022c. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022d. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022e. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022f. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022g. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022h. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

———. 2022i. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Rodríguez-Sánchez, Francisco, Connor P. Jackson, and Shaurita D. Hutchins. 2022. Grateful: Facilitate Citation of r Packages. https://github.com/Pakillo/grateful.

Sarkar, Deepayan. 2008. Lattice: Multivariate Data Visualization with r. New York: Springer. http://lmdvr.r-forge.r-project.org.

Strobl, Carolin, Anne-Laure Boulesteix, Thomas Kneib, Thomas Augustin, and Achim Zeileis. 2008. “Conditional Variable Importance for Random Forests.” BMC Bioinformatics 9 (307). https://doi.org/10.1186/1471-2105-9-307.

Strobl, Carolin, Anne-Laure Boulesteix, Achim Zeileis, and Torsten Hothorn. 2007. “Bias in Random Forest Variable Importance Measures: Illustrations, Sources and a Solution.” BMC Bioinformatics 8 (25). https://doi.org/10.1186/1471-2105-8-25.

Therneau, Terry, and Beth Atkinson. 2022. Rpart: Recursive Partitioning and Regression Trees. https://CRAN.R-project.org/package=rpart.

Wand, Matt. 2021. KernSmooth: Functions for Kernel Smoothing Supporting Wand & Jones (1995). https://CRAN.R-project.org/package=KernSmooth.

Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.

Wilke, Claus O., and Brenton M. Wiernik. 2022. Ggtext: Improved Text Rendering Support for ’Ggplot2’. https://CRAN.R-project.org/package=ggtext.

Xie, Yihui. 2014. “Knitr: A Comprehensive Tool for Reproducible Research in R.” In Implementing Reproducible Computational Research, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC. http://www.crcpress.com/product/isbn/9781466561595.

———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.

———. 2022. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.

Xie, Yihui, Joe Cheng, and Xianying Tan. 2022. DT: A Wrapper of the JavaScript Library ’DataTables’. https://CRAN.R-project.org/package=DT.

Zeileis, Achim. 2004. “Econometric Computing with HC and HAC Covariance Matrix Estimators.” Journal of Statistical Software 11 (10): 1–17. https://doi.org/10.18637/jss.v011.i10.

———. 2006a. “Implementing a Class of Structural Change Tests: An Econometric Computing Approach.” Computational Statistics & Data Analysis 50 (11): 2987–3008. https://doi.org/10.1016/j.csda.2005.07.001.

———. 2006b. “Object-Oriented Computation of Sandwich Estimators.” Journal of Statistical Software 16 (9): 1–16. https://doi.org/10.18637/jss.v016.i09.

Zeileis, Achim, and Gabor Grothendieck. 2005. “Zoo: S3 Infrastructure for Regular and Irregular Time Series.” Journal of Statistical Software 14 (6): 1–27. https://doi.org/10.18637/jss.v014.i06.

Zeileis, Achim, Torsten Hothorn, and Kurt Hornik. 2008a. “Model-Based Recursive Partitioning.” Journal of Computational and Graphical Statistics 17 (2): 492–514.

———. 2008b. “Model-Based Recursive Partitioning.” Journal of Computational and Graphical Statistics 17 (2): 492–514. https://doi.org/10.1198/106186008X319331.

Zeileis, Achim, Christian Kleiber, Walter Krämer, and Kurt Hornik. 2003. “Testing and Dating of Structural Changes in Practice.” Computational Statistics & Data Analysis 44 (1–2): 109–23. https://doi.org/10.1016/S0167-9473(03)00030-6.

Zeileis, Achim, Susanne Köll, and Nathaniel Graham. 2020. “Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R.” Journal of Statistical Software 95 (1): 1–36. https://doi.org/10.18637/jss.v095.i01.

Zeileis, Achim, Friedrich Leisch, Kurt Hornik, and Christian Kleiber. 2002. “Strucchange: An r Package for Testing for Structural Change in Linear Regression Models.” Journal of Statistical Software 7 (2): 1–38. https://doi.org/10.18637/jss.v007.i02.

Zhu, Hao. 2021. kableExtra: Construct Complex Table with ’Kable’ and Pipe Syntax. https://CRAN.R-project.org/package=kableExtra.

Footnotes

1. CRedIT is a high-level taxonomy, including 14 roles, that indicate some of the roles played by contributors to scientific scholarly output. The roles describe each contributor’s specific contribution to the scholarly output.

2. We used the package tenzing to generate the CRediT taxonomy.