Package: restoptr 1.0.6
restoptr: Ecological Restoration Planning
Flexible framework for ecological restoration planning. It aims to identify priority areas for restoration efforts using optimization algorithms (based on Justeau-Allaire et al. 2021 <doi:10.1111/1365-2664.13803>). Priority areas can be identified by maximizing landscape indices, such as the effective mesh size (Jaeger 2000 <doi:10.1023/A:1008129329289>), or the integral index of connectivity (Pascual-Hortal & Saura 2006 <doi:10.1007/s10980-006-0013-z>). Additionally, constraints can be used to ensure that priority areas exhibit particular characteristics (e.g., ensure that particular places are not selected for restoration, ensure that priority areas form a single contiguous network). Furthermore, multiple near-optimal solutions can be generated to explore multiple options in restoration planning. The package leverages the 'Choco-solver' software to perform optimization using constraint programming (CP) techniques (<https://choco-solver.org/>).
Authors:
restoptr_1.0.6.tar.gz
restoptr_1.0.6.zip(r-4.5)restoptr_1.0.6.zip(r-4.4)restoptr_1.0.6.zip(r-4.3)
restoptr_1.0.6.tgz(r-4.4-any)restoptr_1.0.6.tgz(r-4.3-any)
restoptr_1.0.6.tar.gz(r-4.5-noble)restoptr_1.0.6.tar.gz(r-4.4-noble)
restoptr_1.0.6.tgz(r-4.4-emscripten)restoptr_1.0.6.tgz(r-4.3-emscripten)
restoptr.pdf |restoptr.html✨
restoptr/json (API)
NEWS
# Install 'restoptr' in R: |
install.packages('restoptr', repos = c('https://dimitri-justeau.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dimitri-justeau/restoptr/issues
Last updated 4 months agofrom:f6bf438bbf. Checks:OK: 5 NOTE: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 13 2024 |
R-4.5-win | NOTE | Oct 13 2024 |
R-4.5-linux | NOTE | Oct 13 2024 |
R-4.4-win | OK | Oct 13 2024 |
R-4.4-mac | OK | Oct 13 2024 |
R-4.3-win | OK | Oct 13 2024 |
R-4.3-mac | OK | Oct 13 2024 |
Exports:%>%add_available_areas_constraintadd_compactness_constraintadd_components_constraintadd_connected_constraintadd_locked_out_constraintadd_min_iic_constraintadd_min_mesh_constraintadd_restorable_constraintadd_settingsarea_to_nb_cellscell_areacell_widthget_aggregation_factorget_cell_areaget_constraintsget_existing_habitatget_habitat_thresholdget_locked_out_areasget_metadataget_objectiveget_original_habitatget_restorable_habitatget_settingsinvert_vectoris_java_availablenb_cell_to_areapreprocess_inputrestopt_problemset_max_iic_objectiveset_max_mesh_objectiveset_max_nb_pus_objectiveset_max_restore_objectiveset_min_nb_pus_objectiveset_min_restore_objectiveset_no_objective
Case study: using historical data to set ecological restoration targets
Rendered fromcase_study.Rmd
usingknitr::rmarkdown_notangle
on Oct 13 2024.Last update: 2022-11-07
Started: 2022-09-06
Getting started
Rendered fromrestoptr.Rmd
usingknitr::rmarkdown_notangle
on Oct 13 2024.Last update: 2023-03-08
Started: 2022-02-03