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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
Author(s) -
Van DIJK ALBERT I. J. M.,
Van NOORDWIJK MEINE,
CALDER IAN R.,
BRUIJNZEEL SAMPURNO L. A.,
SCHELLEKENS JAAP,
CHAPPELL NICK A.
Publication year - 2009
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/j.1365-2486.2008.01708.x
Subject(s) - flood myth , spurious relationship , deforestation (computer science) , flooding (psychology) , geography , population , land cover , land use , physical geography , ecology , demography , statistics , sociology , archaeology , psychology , mathematics , computer science , psychotherapist , biology , programming language
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.