10.5061/DRYAD.5X69P8D1G
Strauss, Alexander
0000-0003-0633-8443
University of Georgia
Henning, Jeremiah
University of South Alabama
Porath-Krause, Anita
University of Minnesota
Asmus, Ashley
University of Minnesota
Shaw, Allison
University of Minnesota
Borer, Elizabeth
University of Minnesota
Seabloom, Eric
University of Minnesota
Data and code from: Vector demography, dispersal, and the spread of
disease: Experimental epidemics under elevated resource supply
Dryad
dataset
2020
FOS: Biological sciences
barley/cereal yellow dwarf virus
Disease ecology
spatial
transmission
vector
NSF DEB *
1556649
NSF IOS *
1556674
NSF DEB
1556649
NSF IOS
1556674
2020-09-04T00:00:00Z
2020-09-04T00:00:00Z
en
193554 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1. The spread of many diseases depends on the demography and dispersal of
arthropod vectors. Classic epidemiological theory typically ignores vector
dynamics and instead makes the simplifying assumption of
frequency-dependent transmission. Yet vector ecology may be critical for
understanding the spread of disease over space and time and how disease
dynamics respond to environmental change. 2. Here, we ask how
environmental change shapes vector demography and dispersal, and how these
traits of vectors govern the spatiotemporal spread of disease. 3. We
developed disease models parameterized by traits of vectors and fit them
to experimental epidemics. The experiment featured a viral pathogen
(CYDV-RPV) vectored by aphids (Rhopalosiphum padi) among populations of
grass hosts (Avena sativa) under two rates of environmental resource
supply (i.e., fertilization of the host). We compared a non-spatial model
that ignores vector movement, a lagged dispersal model that emphasizes the
delay between vector reproduction and dispersal, and a travelling wave
model that generates waves of infections across space and time. 4.
Resource supply altered both vector demography and dispersal. The lagged
dispersal model fit best, indicating that vectors first reproduced and
then dispersed among hosts in the experiment. Elevated resources decreased
vector population growth rates, nearly doubled their carrying capacity per
host, increased dispersal rates when vectors carried the virus, and
homogenized disease risk across space. 5. Together, the models and
experiment show how environmental eutrophication can shape spatial disease
dynamics – for example, homogenizing disease risk across space – by
altering the demography and behavior of vectors.
see readme file