Research overview: reporting bias and underreporting in conflict data

This overview examines the pervasive problem of biased and incomplete data in human-big cat conflict research, which can distort understanding and management. It synthesises evidence that incidents are underreported where compensation is absent or claiming is burdensome, overreported where payments incentivise claims, and misattributed across predator species or between depredation and other causes of death. The literature discusses how such biases skew hotspot maps, trend analyses, and program evaluations, and methods to detect and correct them. The survey frames data integrity as a foundational but underappreciated concern, arguing that conclusions about where conflict occurs, whether it is rising, and what works depend critically on the quality and representativeness of the underlying incident records.