EFDM

EFDM projects future forest resource dynamics under user-defined management and disturbance scenarios to support scenario-based strategic planning and policy analysis.


Key Features:

  • Area-Based Matrix Model: EFDM operates as an area-based matrix model that integrates protection schemes, forest-management alterations, and threats such as pests, wind, and drought.
  • Scenario Simulation: The model simulates large-scale impacts by combining transitions (for example, from even-aged forestry to continuous cover forestry), land-use changes, and tree species changes into comprehensive scenarios.
  • Input Flexibility: EFDM accepts an initial forest state and models for management activities such as thinning, felling, and other silvicultural treatments.
  • Customizable Outputs: The tool produces user-defined outputs including wood volumes, extent of old forests, dead wood, carbon storage, and harvest income.

Scientific Applications:

  • Strategic Planning and Policy Support: EFDM provides projections of potential future forest states under alternative management strategies to inform strategic planning and policy analysis.
  • Optimization Systems Integration: EFDM can be used as a component within optimization systems aimed at evaluating and improving forestry practices.
  • Climate Change Impact Studies: The model can be integrated with other models to assess the impacts of climate change on forests and to explore adaptive management strategies.

Methodology:

EFDM employs an area-based matrix approach to model forest dynamics and simulates future scenarios by applying management-activity models (thinning, felling, silvicultural treatments) and disturbance factors to an initial forest state.

Topics

Details

License:
GPL-2.0
Cost:
Free of charge
Tool Type:
library
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R
Added:
10/9/2022
Last Updated:
11/24/2024

Operations

Publications

Räty M, Kuronen M. efdm–An R package offering a scenario tool beyond forestry. PLOS ONE. 2022;17(8):e0264380. doi:10.1371/journal.pone.0264380. PMID:35969582. PMCID:PMC9377579.

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