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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Modelling and testing forest ecosystems condition account.

Adrián G Bruzón1, Patricia Arrogante-Funes1, Fernando Santos-Martín1

  • 1Department of Chemical and Environmental Technology, ESCET, Rey Juan Carlos University, C/Tulipán s/n, Móstoles, 28933, Madrid, Spain.

Journal of Environmental Management
|August 10, 2023
PubMed
Summary
This summary is machine-generated.

A new model maps forest ecosystem condition using the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework. Spanish forests showed a slight condition improvement from 2000-2015, with varied trends across ecosystem types.

Keywords:
ConditionEcosystem accountingForestNatural capitalSEEA-EASpain

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Area of Science:

  • Environmental accounting
  • Ecosystem assessment
  • Forestry science

Background:

  • The United Nations Statistical Commission endorsed the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework in 2021.
  • Monitoring forest ecosystem condition is crucial for conservation and management.
  • A standardized, spatially explicit method for assessing forest condition was lacking.

Purpose of the Study:

  • To develop and apply an automated model for mapping forest ecosystem condition accounts.
  • To test the model's effectiveness nationally in Spain from 2000 to 2015.
  • To provide insights into forest condition status and trends for policy-making.

Main Methods:

  • Developed an application model based on the SEEA-EA framework.
  • Defined forest ecosystem types and selected condition variables (physical, chemical, structural, etc.).
  • Established reference levels, aggregated variables into an index, and rescaled to a 0-1 range.

Main Results:

  • The model successfully generated spatially explicit forest condition accounts for Spain (2000-2015).
  • Overall forest ecosystem condition in Spain slightly increased from 0.56 to 0.58.
  • Distinct trends were observed: mixed Alpine and Macaronesia forests improved, while Mediterranean coniferous forests remained unchanged.

Conclusions:

  • The automated SEEA-EA based model effectively monitors forest condition accounts.
  • Findings highlight the need for tailored conservation strategies based on ecosystem-specific trends.
  • The approach supports evidence-based nature conservation, ecosystem service management, and restoration planning.