ABSTRACT Climate warming is expected to substantially impact the global landscape of mosquito‐borne disease, but these impacts will vary across disease systems and regions. Understanding which diseases, and where within their distributions, these impacts are most likely to occur is critical for preparing public health interventions. While research has centered on potential warming‐driven expansions in vector transmission, less is known about the potential for vectors to experience warming‐driven stress or even local extirpations. In conservation biology, species risk from climate warming is often quantified through vulnerability indices such as thermal safety margins—the difference between an organism's upper thermal limit and its habitat temperature. Here, we estimated thermal safety margins for 8 mosquito species that are the vectors of malaria, dengue, chikungunya, Zika, West Nile and other major arboviruses, across their known ranges to investigate which mosquitoes and regions are most and least vulnerable to climate warming. We find that several of the most medically important mosquito vector species, includingAe. aegyptiandAn. gambiae, have positive thermal safety margins across the majority of their ranges when realistic assumptions of mosquito behavioral thermoregulation are incorporated. On average, the lowest climate vulnerability, in terms of both the magnitude and duration of thermal safety, was just south of the equator and at northern temperate range edges, and the highest climate vulnerability was in the subtropics. Mosquitoes living in regions including the Middle East, the western Sahara, and southeastern Australia, which are largely comprised of desert and xeric shrubland biomes, have the highest climate vulnerability across vector species.
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Temperature dependence of mosquitoes: Comparing mechanistic and machine learning approaches
Mosquito vectors of pathogens (e.g.,Aedes,Anopheles, andCulexspp. which transmit dengue, Zika, chikungunya, West Nile, malaria, and others) are of increasing concern for global public health. These vectors are geographically shifting under climate and other anthropogenic changes. As small-bodied ectotherms, mosquitoes are strongly affected by temperature, which causes unimodal responses in mosquito life history traits (e.g., biting rate, adult mortality rate, mosquito development rate, and probability of egg-to-adult survival) that exhibit upper and lower thermal limits and intermediate thermal optima in laboratory studies. However, it remains unknown how mosquito thermal responses measured in laboratory experiments relate to the realized thermal responses of mosquitoes in the field. To address this gap, we leverage thousands of global mosquito occurrences and geospatial satellite data at high spatial resolution to construct machine-learning based species distribution models, from which vector thermal responses are estimated. We apply methods to restrict models to the relevant mosquito activity season and to conduct ecologically plausible spatial background sampling centered around ecoregions for comparison to mosquito occurrence records. We found that thermal minima estimated from laboratory studies were highly correlated with those from the species distributions (r = 0.87). The thermal optima were less strongly correlated (r = 0.69). For most species, we did not detect thermal maxima from their observed distributions so were unable to compare to laboratory-based estimates. The results suggest that laboratory studies have the potential to be highly transportable to predicting lower thermal limits and thermal optima of mosquitoes in the field. At the same time, lab-based models likely capture physiological limits on mosquito persistence at high temperatures that are not apparent from field-based observational studies but may critically determine mosquito responses to climate warming. Our results indicate that lab-based and field-based studies are highly complementary; performing the analyses in concert can help to more comprehensively understand vector response to climate change.
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- Award ID(s):
- 2011147
- PAR ID:
- 10630487
- Editor(s):
- Mireji, Paul O
- Publisher / Repository:
- PLoS
- Date Published:
- Journal Name:
- PLOS Neglected Tropical Diseases
- Volume:
- 18
- Issue:
- 9
- ISSN:
- 1935-2735
- Page Range / eLocation ID:
- e0012488
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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