Claims that tropical forests are declining cannot be backed up by hard evidence, according to new research from the University of Leeds.
This major challenge to conventional thinking is the surprising finding of a study published today in the Proceedings of the US National Academy of Sciences by Dr Alan Grainger, Senior Lecturer in Geography and one of the world’s leading experts on tropical deforestation.
In the first attempt for many years to chart the long-term trend in tropical forest area, he spent more than three years going through all available United Nations data with a fine toothcomb – and found some serious problems.
Read the entire EurekAlert write up here.
Philip Stott also has a good write up here.
The abstract from the paper is below:
Difficulties in tracking the long-term global trend in tropical forest area
School of Geography, University of Leeds, Leeds LS2 9JT, United Kingdom
Edited by B. L. Turner II, Clark University, Worcester, MA, and approved December 3, 2007 (received for review April 3, 2007)
The long-term trend in tropical forest area receives less scrutiny than the tropical deforestation rate. We show that constructing a reliable trend is difficult and evidence for decline is unclear, within the limits of errors involved in making global estimates. A time series for all tropical forest area, using data from Forest Resources Assessments (FRAs) of the United Nations Food and Agriculture Organization, is dominated by three successively corrected declining trends. Inconsistencies between these trends raise questions about their reliability, especially because differences seem to result as much from errors as from changes in statistical design and use of new data. A second time series for tropical moist forest area shows no apparent decline. The latter may be masked by the errors involved, but a “forest return” effect may also be operating, in which forest regeneration in some areas offsets deforestation (but not biodiversity loss) elsewhere. A better monitoring program is needed to give a more reliable trend. Scientists who use FRA data should check how the accuracy of their findings depends on errors in the data.