Incorporating biodiversity responses to land use change scenarios for preventing emerging zoonotic diseases in areas of unknown host-pathogen interactions

Front Vet Sci. 2023 Nov 9:10:1229676. doi: 10.3389/fvets.2023.1229676. eCollection 2023.

Abstract

The need to reconcile food production, the safeguarding of nature, and the protection of public health is imperative in a world of continuing global change, particularly in the context of risks of emerging zoonotic disease (EZD). In this paper, we explored potential land use strategies to reduce EZD risks using a landscape approach. We focused on strategies for cases where the dynamics of pathogen transmission among species were poorly known and the ideas of "land-use induced spillover" and "landscape immunity" could be used very broadly. We first modeled three different land-use change scenarios in a region of transition between the Cerrado and the Atlantic Forest biodiversity hotspots. The land-use strategies used to build our scenarios reflected different proportions of native vegetation cover, as a proxy of habitat availability. We then evaluated the effects of the proportion of native vegetation cover on the occupancy probability of a group of mammal species and analyzed how the different land-use scenarios might affect the distribution of species in the landscape and thus the risk of EZD. We demonstrate that these approaches can help identify potential future EZD risks, and can thus be used as decision-making tools by stakeholders, with direct implications for improving both environmental and socio-economic outcomes.

Keywords: COVID-19 pandemic; Cerrado; LCLUC; agriculture; land-use planning; zoonosis.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. We are grateful for grants and financial support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Fundação de Amparo à Pesquisa de Mato Grosso do Sul (Fundect) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). This work was partially funded by the Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq (to AVN, 150102/2023-2 and 160547/2023-7).