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Plant genetics predicts intra-annual variation in phytochemistry and arthropod community structure.

Identifieur interne : 003A96 ( Main/Exploration ); précédent : 003A95; suivant : 003A97

Plant genetics predicts intra-annual variation in phytochemistry and arthropod community structure.

Auteurs : G M Wimp [États-Unis] ; S. Wooley ; R K Bangert ; W P Young ; G D Martinsen ; P. Keim ; B. Rehill ; R L Lindroth ; T G Whitham

Source :

RBID : pubmed:17927708

Descripteurs français

English descriptors

Abstract

With the emerging field of community genetics, it is important to quantify the key mechanisms that link genetics and community structure. We studied cottonwoods in common gardens and in natural stands and examined the potential for plant chemistry to be a primary mechanism linking plant genetics and arthropod communities. If plant chemistry drives the relationship between plant genetics and arthropod community structure, then several predictions followed. We would find (i) the strongest correlation between plant genetic composition and chemical composition; (ii) an intermediate correlation between plant chemical composition and arthropod community composition; and (iii) the weakest relationship between plant genetic composition and arthropod community composition. Our results supported our first prediction: plant genetics and chemistry had the strongest correlation in the common garden and the wild. Our results largely supported our second prediction, but varied across space, seasonally, and according to arthropod feeding group. Plant chemistry played a larger role in structuring common garden arthropod communities relative to wild communities, free-living arthropods relative to leaf and stem modifiers, and early-season relative to late-season arthropods. Our results did not support our last prediction, as host plant genetics was at least as tightly linked to arthropod community structure as plant chemistry, if not more so. Our results demonstrate the consistency of the relationship between plant genetics and biodiversity. Additionally, plant chemistry can be an important mechanism by which plant genetics affects arthropod community composition, but other genetic-based factors are likely involved that remain to be measured.

DOI: 10.1111/j.1365-294X.2007.03544.x
PubMed: 17927708


Affiliations:


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Le document en format XML

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<div type="abstract" xml:lang="en">With the emerging field of community genetics, it is important to quantify the key mechanisms that link genetics and community structure. We studied cottonwoods in common gardens and in natural stands and examined the potential for plant chemistry to be a primary mechanism linking plant genetics and arthropod communities. If plant chemistry drives the relationship between plant genetics and arthropod community structure, then several predictions followed. We would find (i) the strongest correlation between plant genetic composition and chemical composition; (ii) an intermediate correlation between plant chemical composition and arthropod community composition; and (iii) the weakest relationship between plant genetic composition and arthropod community composition. Our results supported our first prediction: plant genetics and chemistry had the strongest correlation in the common garden and the wild. Our results largely supported our second prediction, but varied across space, seasonally, and according to arthropod feeding group. Plant chemistry played a larger role in structuring common garden arthropod communities relative to wild communities, free-living arthropods relative to leaf and stem modifiers, and early-season relative to late-season arthropods. Our results did not support our last prediction, as host plant genetics was at least as tightly linked to arthropod community structure as plant chemistry, if not more so. Our results demonstrate the consistency of the relationship between plant genetics and biodiversity. Additionally, plant chemistry can be an important mechanism by which plant genetics affects arthropod community composition, but other genetic-based factors are likely involved that remain to be measured.</div>
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