1. A population′s maximal growth rate (rm) depends on the survivorship, development, and reproduction of its individuals. In ectotherms, these (functional) traits respond predictably to temperature, which provides a basis for predicting how climatic warming could affect natural populations, including disease vectors and the diseases they transmit. 2. Such predictions generally arise from mathematical models that incorporate the temperature–dependence of traits (thermal performance curves) measured under laboratory conditions. Therefore, the accuracy of these predictions depends on the relevance of lab-measured trait thermal performance curves to natural conditions. However, the joint effect of temperature and resource availability—another key limiting environmental factor in nature—on traits is largely unknown. 3. We investigated how larval competition for ecologically–realistic depleting resources affects the thermal performance of rm and its underlying life history traits in the disease vector in Aedes aegypti. We show that competition at food concentrations below a certain threshold drastically depresses rm across the entire temperature range, causes it to peak at a lower temperature, and narrows the breadth of temperatures over which rm is positive (the thermal niche breath). 4. This resource-dependence of the thermal performance curve of rm is driven primarily by the fact that competition delays development and increases juvenile mortality. This is compounded by reduced size at maturity, which in turn decreases adult lifespan and fecundity. 5. These results show that intensified larval competition in depleting resource environments can significantly affect the temperature–dependence of rm by modulating the thermal responses of underlying traits in a predictable way. This has important implications for forecasting the effects of climate change on population dynamics in the field of not just disease vectors, but holometabolous insects in general.
Changes in land-use and the associated shifts in environmental conditions can have large effects on the transmission and emergence of disease. Mosquito-borne disease are particularly sensitive to these changes because mosquito growth, reproduction, survival and susceptibility to infection are all thermally sensitive traits, and land use change dramatically alters local microclimate. Predicting disease transmission under environmental change is increasingly critical for targeting mosquito-borne disease control and for identifying hotspots of disease emergence. Mechanistic models offer a powerful tool for improving these predications. However, these approaches are limited by the quality and scale of temperature data and the thermal response curves that underlie predictions. Here, we used fine-scale temperature monitoring and a combination of empirical, laboratory and temperature-dependent estimates to estimate the vectorial capacity of Aedes albopictus mosquitoes across a tropical forest – oil palm plantation conversion gradient in Malaysian Borneo. We found that fine-scale differences in temperature between logged forest and oil palm plantation sites were not sufficient to produce differences in temperature-dependent trait estimates using published thermal performance curves. However, when measured under field conditions a key parameter, adult abundance, differed significantly between land-use types, resulting in estimates of vectorial capacity that were 1.5 times higher in plantations than in forests. The prediction that oil palm plantations would support mosquito populations with higher vectorial capacity was robust to uncertainties in our adult survival estimates. These results provide a mechanistic basis for understanding the effects of forest conversion on mosquito-borne disease risk, and a framework for interpreting emergent relationships between land-use and disease transmission. As rising demand for palm oil products drives continued expansion of plantations, these findings have important implications for conservation, land management and public health policy at the global scale.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.