Methodological advances for hypothesis‐driven ethnobiology

Ethnobiology as a discipline has evolved recently to increasingly embrace theory-inspired and hypothesis driven approaches to study why and how local people choose plants and animals they interact with and use for their livelihood. However, testing complex hypotheses or a network of ethnobiological hypotheses is challenging, particularly for datasets with non-independent observations due to species phylogenetic relatedness or socio-relational links between participants. Further, to fully account for the dynamics of local ecological knowledge, it is important to account for the spatially explicit distribution of knowledge, the changes in knowledge, knowledge transmission and use. To promote the use of advanced statistical modeling approaches that address these limitations, we synthesize methodological advances for hypothesis-driven research in ethnobiology while highlighting the need for more figures than tables and more tables than text in ethnobiological literature. We present the ethn...