Award Abstract # 1717498
Predicting the evolution of vector-borne disease dynamics in a changing world

NSF Org: DEB
Division Of Environmental Biology
Recipient: SMITHSONIAN INSTITUTION
Initial Amendment Date: August 18, 2017
Latest Amendment Date: September 26, 2017
Award Number: 1717498
Award Instrument: Standard Grant
Program Manager: Samuel Scheiner
DEB
 Division Of Environmental Biology
BIO
 Directorate for Biological Sciences
Start Date: September 1, 2017
End Date: November 30, 2019 (Estimated)
Total Intended Award Amount: $2,498,876.00
Total Awarded Amount to Date: $2,498,876.00
Funds Obligated to Date: FY 2017 = $685,168.00
History of Investigator:
  • Dina Fonseca (Principal Investigator)
    Dina.fonseca@rutgers.edu
  • Robert Fleischer (Co-Principal Investigator)
  • Auston Kilpatrick (Co-Principal Investigator)
  • Nina Fefferman (Co-Principal Investigator)
  • Eben Paxton (Co-Principal Investigator)
Recipient Sponsored Research Office: Smithsonian Institution
1000 JEFFERSON DR SW
WASHINGTON
DC  US  20560-0008
(202)633-7110
Sponsor Congressional District: 00
Primary Place of Performance: Smithsonian Institution
3001 Connecticut Ave.
Washington
DC  US  20008-2537
Primary Place of Performance
Congressional District:
00
Unique Entity Identifier (UEI): KQ1KJG78NNS9
Parent UEI: KQ1KJG78NNS9
NSF Program(s): Ecology of Infectious Diseases
Primary Program Source: 01001718DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7242
Program Element Code(s): 724200
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.074

ABSTRACT

This project will advance our understanding of how disease transmission will be affected by and evolve in response to environmental change. Diseases transmitted among hosts by small invertebrates such as mosquitoes or ticks (vectors) are on the rise across the world but our ability to measure and predict risk is lagging. Predicting vector-borne disease risk requires both an understanding of how all the species involved are likely to be affected by environmental change and how those interactions may evolve. The transmission of avian malaria in native and introduced Hawaiian birds is an ideal system to gain this understanding. The project will focus on the Hawaiian honeycreepers, a diverse group that includes many species that are threatened with extinction. Through the use of historical specimens of both the birds and the malaria parasite, the project will be able to document and model the evolution of disease tolerance and resistance over the past 80 years. The model methodology will then be available for broad application into any disease system in which evolution is expected to occur in response to shifting environmental conditions. The results will also be used for management of the bird species in Hawaii. The project will support undergraduate and graduate student training, and participation of local high school students.

The agent of avian malaria in Hawaii is a non-native Haemosporidian parasite, Plasmodium relictum, vectored by mixes of two non-native strains of the mosquito Culex quinquefasciatus. Avian malaria in Hawaii occurs as a series of replicated natural experiments in which vector and parasite prevalence vary along elevational gradients on several islands, and a parallel gradient in tolerance among some bird hosts has been reported. Although P. relictum was previously highly virulent to all of the >50 species of Hawaiian honeycreepers, evolution of tolerance (or resistance) has been observed in at least three species including the amakihi (Chlorodrepanis sp.). Additionally, there is geographic variation within and across islands in host species composition, host tolerance, climate (temperature and precipitation), vector abundance, vector competence, and pathogen fitness. This project will 1) characterize the genomic signatures of parasites, hosts and vectors at different elevations replicated across islands and through time, the latter by using museum specimens; 2) perform common-garden experiments and experimental infections to assess differences in competence or virulence among strains of vectors and parasites, respectively; 3) integrate Aims 1 and 2 in predictive models of the impact of co-evolutionary changes on vector-borne disease transmission under current and future climate scenarios. We will use comparative genomics and transcriptomics at multiple spatial, temporal and experimental scales, and combine Susceptible-Infected-Resistant (SIR) models with evolutionary game theory to capture the reciprocal influence of changing populations.

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