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[Ecosystem productivity process model for landscape based on remote sensing and surface data].

Na Zhang1, Guirui Yu, Shidong Zhao

  • 1College of Earth Sciences, Graduate School, Chinese Academy of Sciences, Beijing 100039, China. zhangna@gscas.ac.cn

Ying Yong Sheng Tai Xue Bao = the Journal of Applied Ecology
|August 20, 2003
PubMed
Summary

This study introduces the Ecosystem Productivity Process Model for Landscape (EPPML) to simulate vegetation productivity and carbon cycles. The model accurately estimates Net Primary Productivity (NPP) in the Changbai Mountain Natural Reserve, showing peak productivity in mixed forests.

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Area of Science:

  • Ecological modeling
  • Biogeochemical cycles
  • Remote sensing applications

Context:

  • Vegetation productivity and carbon/water cycles are crucial ecosystem components.
  • Scaling ecological studies from small to landscape levels presents challenges.
  • Integrating remote sensing and GIS data enhances spatial ecological analysis.

Purpose:

  • To describe and discuss the Ecosystem Productivity Process Model for Landscape (EPPML).
  • To simulate spatial and temporal dynamics of Net Primary Productivity (NPP) and evapotranspiration.
  • To extend physiological ecology studies to a larger scale using remote sensing and GIS.

Summary:

  • The EPPML model utilizes Leaf Area Index (LAI) from remote sensing to simulate NPP and evapotranspiration.

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  • Simulations in Changbai Mountain Natural Reserve (1995) showed EPPML accurately models vegetation NPP.
  • Estimated NPP was 0.680 kg C m⁻² yr⁻¹, with highest values in mixed broad-leaved/Korean pine forests.

    • Impact:

    • EPPML provides a robust tool for landscape-scale ecological productivity assessment.
    • The study demonstrates the successful application of integrated remote sensing and GIS in ecological modeling.
    • Findings offer valuable data for understanding carbon sequestration and forest management in the region.