Global Biodiversity Data Influenced by Human Histories

Global biodiversity data used to make major policy and conservation investment decisions reflect legacies of social and political inequities. In a Policy Forum, Melissa Chapman and colleagues highlight this issue and its implications for global conservation policy and planning. The rapid rise of global biodiversity data repositories like the Global Biodiversity Information Facility (GBIF) – a data repository that synthesizes billions of species observations across the globe – has led to unprecedented insight into large-scale biodiversity patterns worldwide. Not only are these data important to ecologists, but they have also become crucial to governments and businesses seeking to create and implement multilateral conservation commitments, global investments, and biodiversity offset markets, which have wide-reaching implications for nature and people. However, according to Chapman et al., the systems that generate biodiversity data are complex, uneven, and ultimately human, capturing patterns of human processes across space and time. Here, the authors show how biodiversity observations in GBIF data do not reflect latitudinal gradients of biodiversity and instead trace social infrastructure like cities, roads, and the rise of biodiversity monitoring technology. Moreover, they also reveal signatures of armed conflict, the legacy effects of racist and/or colonialist policies, economic inequalities, and changes in political regimes at a variety of scales. Chapman et al. discuss the potential impact of the data disparities on global and national biodiversity conservation policies and ways in which their negative effects could be mitigated. The authors note that understanding the histories of biodiversity data is critical to ensuring that policy and practice informed by these data systems do not reproduce and exacerbate inequities. "Without directly addressing and correcting for social and political disparities in data, the conservation community will likely fall into the same traps that other domains do – entrenching the inequities of the past and present in future decision-making through data," write Chapman et al.