Parasites and Vectors (2015) 8 (367) - Identifying biotic ...

Nick Golding, Miles A. Nunn and Bethan V. Purse (2015)
Identifying biotic interactions which drive the spatial distribution of a mosquito community
Parasites and Vectors 8 (367)
Abstract:
Background
Spatial variation in the risk of many mosquito-borne pathogens is strongly influenced by the distribution of communities of suitable vector mosquitoes. The spatial distributions of such communities have been linked to the abiotic habitat requirements of each constituent mosquito species, but the biotic interactions between mosquitoes and other species are less well understood. Determining which fauna restrict the presence and abundance of key mosquito species in vector communities may identify species which could be employed as natural biological control agents. Whilst biotic interactions have been studied in the laboratory, a lack of appropriate statistical methods has prohibited the identification of key interactions which influence mosquito distributions in the field. Joint species distribution models (JSDMs) have recently been developed to identify biotic interactions influencing the distributions of species from empirical data.
Methods
We apply a JSDM to field data on the spatial distribution of mosquitoes in a UK wetland to identify both abiotic factors and biotic interactions driving the composition of the community.
Results
As expected, mosquito larval distributions in this wetland habitat are strongly driven by environmental covariates including water depth, temperature and oxidation-reduction potential. By factoring out these environmental variables, we are able to identify species (ditch shrimp of the genus Palaemonetes and fish) as predators which appear to restrict mosquito distributions.
Conclusions
JSDMs offer vector ecologists a way to identify potentially important biotic interactions influencing the distributions of disease vectors from widely available field data. This information is crucial to understand the likely effects of habitat management for vector control and to identify species with the potential for use in biological control programmes. We provide an R package BayesComm to enable the wider application of these models.
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Full text of article
Database assignments for author(s): Bethan Purse

Research topic(s) for pests/diseases/weeds:
environment - cropping system/rotation

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Pest and/or beneficial records:

Beneficial	Pest/Disease/Weed	Crop/Product	Country	Quarant.
	Culex pipiens		United Kingdom
	Culex modestus		United Kingdom
	Anopheles maculipennis		United Kingdom
	Culiseta annulata		United Kingdom