Forest–flood relation still tenuous – comment on 'Global evidence that deforestation amplifies flood risk and severity in the developing world' by C. J. A. Bradshaw, N.S. Sodi, K. S.-H. Peh and B.W. Brook |
| |
Authors: | ALBERT I J M van DIJK MEINE van NOORDWIJK † IAN R CALDER‡ SAMPURNO L A BRUIJNZEEL§ JAAP SCHELLEKENS¶ NICK A CHAPPELL |
| |
Institution: | CSIRO Land and Water, Canberra, 2601 ACT, Australia,;World Agroforestry Center, Bogor, Indonesia,;Centre for Land Use and Water Resources Research, Newcastle University, UK,;Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam, The Netherlands,;WL|Delft Hydraulics, Delft, The Netherlands,;Lancaster Environment Centre, Lancaster University, UK |
| |
Abstract: | In a recent paper in this journal, Bradshaw and colleagues analyse country statistics on flood characteristics, land cover and land cover change, and conclude that deforestation amplifies flood risk and severity in the developing world. The study addresses an important and long-standing question, but we identify important flaws. Principal among these are difficulties in interpreting country statistics and the correlation between population and floods. We review current knowledge, which suggests that the removal of trees does not affect large flood events, although associated landscape changes can under some circumstances. Reanalysis of the data analysed by Bradshaw and colleagues shows that population density alone already explains up to 83% of the variation in reported flood occurrences, considerably more than forest cover or deforestation (<10%). Feasible explanations for this statistical finding – whether spurious or causative – are not difficult to conceive. We, therefore, consider the conclusion of Bradshaw and colleagues to be unsupported. However, their study is a valuable first step to show how these or similar flood data might be used to further explore the relationship between land cover and flooding. |
| |
Keywords: | conservation damage flooding events forest loss generalized linear mixed-effects models generalized linear models human displacement projected costs rainfall |
|
|