The fine-scale landscape of immunity and parasitism in a wild ungulate population
The fine-scale landscape of immunity and parasitism in a wild ungulate population
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野生有蹄类动物种群免疫和寄生的精细景观
DOI:
10.1101/483073
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发表时间:
2018
期刊:
影响因子:
--
通讯作者:
Albery G
中科院分区:
文献类型:
--
作者:
Albery G
Spatial heterogeneity in susceptibility and exposure to parasites is a common source of confounding variation in disease ecology studies. However, it is not known whether spatial autocorrelation acts on immunity at small scales, within wild animal populations, and whether this predicts spatial patterns in infection. Here we used a well-mixed wild population of individually recognized red deer (Cervus elaphus) inhabiting a heterogeneous landscape to investigate fine-scale spatial patterns of immunity and parasitism. We noninvasively collected 842 fecal samples from 141 females with known ranging behavior over 2 years. We quantified total and helminth-specific mucosal antibodies and counted propagules of three gastrointestinal helminth taxa. These data were analyzed with linear mixed models using the Integrated Nested Laplace Approximation, using a Stochastic Partial Differentiation Equation approach to control for and quantify spatial autocorrelation. We also investigated whether spatial patterns of immunity and parasitism changed seasonally. We discovered substantial spatial heterogeneity in general and helminth-specific antibody levels and parasitism with two helminth taxa, all of which exhibited contrasting seasonal variation in their spatial patterns. Notably,Fasciola hepaticaintensity appeared to be strongly influenced by the presence of wet grazing areas, and antibody hotspots did not correlate with distributions of any parasites. Our results suggest that spatial heterogeneity may be an important factor affecting immunity and parasitism in a wide range of study systems. We discuss these findings with regards to the design of sampling regimes and public health interventions, and suggest that disease ecology studies investigate spatial heterogeneity more regularly to enhance their results, even when examining small geographic areas.
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影响因子:
2.4
作者:
R. Callaby;O. Hanotte;I. V. Wyk;H. Kiara;P. Toye;M. Mbole;A. Jennings;S. Thumbi;J. Coetzer;B. Bronsvoort;S. Knott;M. Woolhouse;L. Kruuk
通讯作者:
L. Kruuk
影响因子:
4.4
作者:
S. Parsons;C. Michael Bull;David M. Gordon
通讯作者:
David M. Gordon
DOI:
--
发表时间:
2004
期刊:
影响因子:
--
作者:
K. Wilson;B. Grenfell;J. Pilkington;H. Boyd;F. Gulland
通讯作者:
F. Gulland
影响因子:
1.8
作者:
S. Bisset;A. Vlassoff;C. Morris;Southey Br;R. L. Baker;A. Parker
通讯作者:
A. Parker
DOI:
10.1073/pnas.1518046113
发表时间:
2016-03-29
影响因子:
11.1
作者:
Huisman, Jisca;Kruuk, Loeske E. B.;Pemberton, Josephine M.
通讯作者:
Pemberton, Josephine M.