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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1111/gcb.12226
|2 doi
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|a pubmed24n0756.xml
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|a DE-627
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|a eng
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1 |
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|a Pérez-Rodríguez, Antón
|e verfasserin
|4 aut
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| 245 |
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|a Finding the appropriate variables to model the distribution of vector-borne parasites with different environmental preferences
|b climate is not enough
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|c 2013
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Completed 19.05.2014
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| 500 |
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|a Date Revised 14.10.2013
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2013 John Wiley & Sons Ltd.
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|a Understanding how environmental variation influences the distribution of parasite diversity is critical if we are to anticipate disease emergence risks associated with global change. However, choosing the relevant variables for modelling current and future parasite distributions may be difficult: candidate predictors are many, and they seldom are statistically independent. This problem often leads to simplistic models of current and projected future parasite distributions, with climatic variables prioritized over potentially important landscape features or host population attributes. We studied avian blood parasites of the genera Plasmodium, Haemoproteus and Leucocytozoon (which are viewed as potential emergent pathogens) in 37 Iberian blackcap Sylvia atricapilla populations. We used Partial Least Squares regression to assess the relative importance of a wide array of putative determinants of variation in the diversity of these parasites, including climate, landscape features and host population migration. Both prevalence and richness of parasites were predominantly related to climate (an effect which was primarily, but not exclusively driven by variation in temperature), but landscape features and host migration also explained variation in parasite diversity. Remarkably, different models emerged for each parasite genus, although all parasites were studied in the same host species. Our results show that parasite distribution models, which are usually based on climatic variables alone, improve by including other types of predictors. Moreover, closely related parasites may show different relationships to the same environmental influences (both in magnitude and direction). Thus, a model used to develop one parasite distribution can probably not be applied identically even to the most similar host-parasite systems
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Blackcap Sylvia atricapilla
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| 650 |
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|a Haemoproteus
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| 650 |
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|a Leucocytozoon
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| 650 |
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4 |
|a Plasmodium
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| 650 |
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|a avian haemosporidians
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| 650 |
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4 |
|a environmental constrains
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| 650 |
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|a host migration
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| 650 |
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4 |
|a partial least squares regression
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| 650 |
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|a DNA, Protozoan
|2 NLM
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| 700 |
1 |
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|a Fernández-González, Sofía
|e verfasserin
|4 aut
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| 700 |
1 |
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|a de la Hera, Iván
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Pérez-Tris, Javier
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t Global change biology
|d 1999
|g 19(2013), 11 vom: 11. Nov., Seite 3245-53
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnns
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| 773 |
1 |
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|g volume:19
|g year:2013
|g number:11
|g day:11
|g month:11
|g pages:3245-53
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| 856 |
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|u http://dx.doi.org/10.1111/gcb.12226
|3 Volltext
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