Clarity or confusion?: problems in attributing large-scale ecological changes to anthropogenic drivers

Ways of reducing the drivers of global biodiversity loss and degradation of ecosystem services are needed more than ever before. Policy options must be based on the best evidence of the role of multiple driving forces. Increasingly, a significant part of the evidence base comes from attributing signals of biological change detected in large-scale analytical surveys to a range of possible causal factors. We highlight a number of subtle difficulties that can beset the challenge of detecting such correlative relationships. These are as follows: (1) The Modifiable Area Unit Problem. (2) Incomplete explanatory variable data. (3) Lack of control over the replication and crossing of driving variables. In most cases these problems can be avoided by more careful specification of the scientific question and application of relatively new analytical techniques. Ignoring them can lead to mis-specification of hypothesised driver–state–impact relationships and flawed conclusions as to the most important causes of change.