EDR_data {ecoregime}

Ecological Dynamic Regime data

Description

Example datasets to characterize and compare EDRs, including abundance data, state, segment, and trajectory dissimilarity matrices for 93 artificial communities belonging to three different EDRs.

Usage

EDR_data

Format

List of four nested sublists. Each element of "EDR1", "EDR2", and "EDR3" is associated with one EDR and includes the following elements:

• abundance: Data table with 15 columns and one row for each community state:

  • EDR: Integer indicating the identifier of the EDR.

  • traj: Integer containing the identifier of the trajectory for each artificial community in the corresponding EDR. Each trajectory represents a different sampling unit.

  • state: Integer indicating the observations or states of each community. The sequence of states of a given community forms a trajectory.

  • ⁠sp1, ..., sp12⁠: Vectors containing species abundances for each community state.

• state_dissim: Object of class dist containing Bray-Curtis dissimilarities between every pair of states in abundance.

• segment_dissim: Object of class dist containing the dissimilarities between every pair of trajectory segments in abundance.

• traj_dissim: Object of class dist containing the dissimilarities between every pair of community trajectories in abundance.

The element EDR3_disturbed represents the dynamics of three disturbed communities originally associated with EDR3. It includes an abundance matrix with 16 columns and one row for each community state. The column disturbed_states is a numeric vector indicating whether the corresponding state represents a state before the disturbance (0), during or immediately after the release of the disturbance (1), or a post-disturbance state (> 1).

Details

Artificial data was generated following the procedure explained in Box 1 in Sánchez-Pinillos et al. (2023). The initial state of each community was defined using a hypothetical environmental space with optimal locations for 12 species. Community dynamics were simulated using a general Lotka-Volterra model.

Abundances for EDR3_disturbed were generated following the procedure explained in Sánchez-Pinillos et al. (2024) for ecological systems affected by pulse disturbances.

State dissimilarities were calculated using the Bray-Curtis metric. Segment and trajectory dissimilarities were calculated using the package 'ecotraj'.

References

Sánchez-Pinillos, M., Kéfi, S., De Cáceres, M., Dakos, V. 2023. Ecological Dynamic Regimes: Identification, characterization, and comparison. Ecological Monographs. doi:10.1002/ecm.1589

Sánchez-Pinillos, M., Dakos, V., Kéfi, S. 2024. Ecological Dynamic Regimes: A key concept for assessing ecological resilience. Biological Conservation. doi:10.1016/j.biocon.2023.110409