The increasing pace of land-use change (e.g. deforestation), coupled with a recent focus on reforestation as a climate change mitigation solution (UN decade on Ecosystem Restoration) sets up the 2020s to be a decade of substantial ecosystem modification. In this context, comparing the impacts of land-use change scenarios (e.g. forest to agriculture, or vice versa) on biodiversity and ecosystem services is necessary to minimize damages from ecosystem degradation or maximize returns from conservation. Despite longstanding knowledge that land-use change can affect infectious disease transmission (e.g. deforestation can increase the transmission of malaria, forest fragmentation can increase lyme disease transmission), disease transmission is rarely considered in land-use planning. Here we use a spatially-explicit Who Acquires Infection From Whom (WAIFW) transmission model, parameterized from published literature, to estimate transmission risk (R0) of dengue, malaria, and yellow fever for a series of land allocation strategies (using the “land-sparing” vs “land-sparing” dichotomy to frame our approach). We also explore the relationship between ecosystem services and disease transmission in Brazil where previous work has estimated changes in water quality, carbon sequestration, and biodiversity with either contiguous or patchy reforestation strategies.
Results/Conclusions
We estimate that the R0 of dengue, malaria, and yellow fever can change by as much as 50% across a gradient from a perfectly spatially segregated landscape (i.e. “land-sparing”: forest, farmland, and urbanization separated in space) to a highly heterogeneous landscape (i.e. “land-sharing”: integration of these landscapes). Using single initial seed infections on simulated landscapes, we find negative correlations in the R0 of each pair of diseases. This demonstrates the importance of evaluating, for each disease, both the risk of an initial infection and the cost of an epidemic in order to make an informed land-use decision. Using previously proposed reforestation scenarios in Brazil, we show that when weighting by the magnitude of R0 and scaling by quality-adjusted life-years (QALYs), a land allocation strategy that jointly minimizes edge habitat to reduce Anopheles sp. habitat and spreads out human population density to reduce dengue transmission minimizes overall disease burden. We show that this choice may be suboptimal for water quality but neutral for biodiversity and carbon sequestration. This result highlights that considering land-use effects on disease transmission can change what is the optimal land-use configuration in different ways depending on what services are included and how they are valued.