Package: ecoregime 0.4.1

Martina Sánchez-Pinillos

ecoregime: Analysis of Ecological Dynamic Regimes

A toolbox for implementing the Ecological Dynamic Regime framework, including functions to characterize and compare groups of ecological trajectories (Sánchez-Pinillos et al., 2023 <doi:10.1002/ecm.1589>); assess the ecological resilience of a disturbed system using a reference dynamic regime (Sánchez-Pinillos et al., 2024 <doi:10.1016/j.biocon.2023.110409>); and forecast ecological trajectories from a dynamic regime (Sánchez-Pinillos et al. 2026, <doi:10.1111/2041-210x.70372>). Additional functions are also available for visualizing ecological dynamic regimes, their representative trajectories, as well as predicted trajectories in a multidimensional state space.

Authors:Martina Sánchez-Pinillos [aut, cre, cph]

ecoregime_0.4.1.tar.gz
ecoregime_0.4.1.zip(r-4.7-any)ecoregime_0.4.1.zip(r-4.6-any)ecoregime_0.4.1.zip(r-4.5-any)
ecoregime_0.4.1.tgz(r-4.6-any)ecoregime_0.4.1.tgz(r-4.5-any)
ecoregime_0.4.1.tar.gz(r-4.7-any)ecoregime_0.4.1.tar.gz(r-4.6-any)
ecoregime_0.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ecoregime/json (API)

# Install 'ecoregime' in R:
install.packages('ecoregime', repos = c('https://mspinillos.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mspinillos/ecoregime/issues

Pkgdown/docs site:https://mspinillos.github.io

Datasets:
  • EDR_data - Ecological Dynamic Regime data

On CRAN:

Conda:

6.35 score 10 stars 15 scripts 414 downloads 14 exports 118 dependencies

Last updated from:718cb58c54. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK308
source / vignettesOK242
linux-releaseOK241
macos-releaseOK243
macos-oldrelOK277
windows-develOK288
windows-releaseOK288
windows-oldrelOK280
wasm-releaseOK117

Exports:amplitudedBDdDisdefine_retradEvedist_edrMPDnet_changepetra_edrplot_edrrecoveryresistanceretra_edrstate_to_trajectory

Dependencies:apebackportsbase64encbitbit64bootbroombslibcachemcheckmateclassclicliprclustercodetoolscolorspacecpp11crayondata.tabledigestdoParalleldplyre1071ecotrajellipseevaluatefarverfastmapfontawesomeforcatsforeachforeignFormulafsgdatagenericsggplot2glmnetgluegridExtragtablegtoolshavenhighrHmischmshtmlTablehtmltoolshtmlwidgetsisobanditeratorsjomojquerylibjsonliteknitrlabelinglatticelifecyclelme4magrittrMASSMatrixmemoisemicemimeminqamitmlnlmenloptrnnetnnlsnumDerivordinalpanpillarpkgconfigplotrixpolynomprettyunitsprogressproxypurrrR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreadrreformulasrlangrmarkdownrpartrstudioapiS7sassscalesshapesmacofstringistringrsurvivaltibbletidyrtidyselecttinytextzdbucminfutf8vctrsviridisLitevroomweightswithrwordcloudxfunyaml

Ecological Dynamic Regime framework
1. Introduction | 1.1. Ecological Dynamic Regimes and the EDR framework | 1.2. About this vignette | 2. Trajectory data, state and trajectory spaces | 3. Defining EDRs | 3.1. Identifying EDRs from clustering analyses | 3.2. Defining EDRs based on ecological properties | 4. Representative trajectories | 4.1. Identifying representative trajectories with RETRA-EDR | 4.2. Visualizing representative trajectories in the state space | 4.3. Defining representative trajectories based on trajectory features | 4.4. Variation of ecological properties along representative trajectories | 5. Distribution and heterogeneity of ecological trajectories in EDRs | 5.1. Dynamic dispersion (dDis) | 5.2. Dynamic beta diversity (dBD) | 5.3. Dynamic evenness (dEve) | 6. Comparing EDRs | Acknowledgements

Last update: 2026-08-04
Started: 2023-01-01

Predicting ecological trajectories from ecological dynamic regimes
1. Introduction | 1.1. Predicting ecological trajectories within the EDR framework | 1.2. About this vignette | 2. Artificial data | 3. Understanding petra_edr() | 3.1. The arguments of petra_edr() | 3.2. The outputs of petra_edr() | 4. Forecasting ecological trajectories | 4.1. Preliminary analyses | 4.2. Forecasting ecological trajectories of multiple targets using different conditions | 4.3. Evaluating the predicted trajectories | The k-nearest EDR states | The predicted states | 5. Prediction accuracy | 6. Representing predicted trajectories

Last update: 2026-08-04
Started: 2026-07-21

Ecological resilience to pulse disturbances
1. Introduction | 1.1. Ecological resilience and the EDR framework | 1.2. About this vignette | 2. Disturbed and undisturbed trajectories | 3. Assessing ecological dynamic regimes | 3.1. Identifying the reference ecological dynamic regime | 3.2. Define the main dynamic trends through representative trajectories | 4. Metrics of ecological resilience to pulse disturbances | 4.1. Resistance | 4.2. Amplitude | 4.3. Recovery | 4.4. Net change | 5. Assessing the ecological resilience of systems affected by pulse disturbances | Acknowledgements

Last update: 2026-07-21
Started: 2024-04-04