This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Nightingale, J. M. Articles by Held, A. A. Search for Related Content Social Bookmarking                         What's this?

Ecosystem process models at multiple scales for mapping tropical forest productivity

Biophysical Remote Sensing Group, School of Geography, Planning and Architecture, University of Queensland, Brisbane, 4072, Australia and Cooperative Research Centre for Greenhouse Accounting, s350141{at}student.uq.edu.au

S. R. Phinn

Biophysical Remote Sensing Group, School of Geography, Planning and Architecture, University of Queensland, Brisbane, 4072, Australia and Cooperative Research Centre for Greenhouse Accounting

A. A. Held

CSIRO Land and Water, Environmental Remote Sensing Group, GPO Box 1666, Canberra ACT, 2601, Australia

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Key Words: carbon cycle • ecosystem process models • remote sensing • scaling carbon fluxes • tropical forests

Progress in Physical Geography, Vol. 28, No. 2, 241-281 (2004)
DOI: 10.1191/0309133304pp411ra


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				S. J. Dark and D. Bram The modifiable areal unit problem (MAUP) in physical geography Progress in Physical Geography, October 1, 2007; 31(5): 471 - 479. [Abstract] [PDF]

				D. F. Levia Jr. and E. E. Frost Variability of throughfall volume and solute inputs in wooded ecosystems Progress in Physical Geography, October 1, 2006; 30(5): 605 - 632. [Abstract] [PDF]

				P. Aplin Remote sensing: ecology Progress in Physical Geography, March 1, 2005; 29(1): 104 - 113. [PDF]