Community ecology of aquatic insects in forested headwater streams in the southern Appalachians

dc.contributor.authorSokol, Eric R.en
dc.contributor.committeechairBenfield, Ernest F.en
dc.contributor.committeememberBelden, Lisa K.en
dc.contributor.committeememberValett, H. Mauriceen
dc.contributor.committeememberJones, Robert H.en
dc.contributor.committeememberVoshell, J. Reese Jr.en
dc.contributor.departmentBiologyen
dc.date.accessioned2014-03-14T20:16:49Zen
dc.date.adate2009-10-13en
dc.date.available2014-03-14T20:16:49Zen
dc.date.issued2009-09-04en
dc.date.rdate2013-05-20en
dc.date.sdate2009-09-26en
dc.description.abstractCompeting paradigms of community assembly emphasize different mechanisms for predicting patterns in biogeography. Niche assembly emphasizes the role of environmental gradients as filters that organize a metacommunity by locally selecting colonizers with similar functional traits, whereas dispersal assembly emphasizes the importance of source pool characteristics and dispersal limitation in organizing a metacommunity. In this study, I developed a framework that uses spatially explicit patterns in taxonomic and functional measures of community composition as diagnostics for community assembly processes for benthic macroinvertebrates in headwater streams in the southern Appalachians. Distance decay in taxonomic and functional similarity was used to determine the scales at which taxonomic turnover occurred within functional niches. Trait-neutral models of community composition were used as null models to assess which functional traits were the best candidates to explain how community composition was influenced by environmental gradients: an assessment of niche-based community assembly. Regional scale patterns suggested that niche-based community assembly was the dominant mechanism organizing community composition in headwater streams at local scales (<30km). Therefore, I compared how well trait-neutral models identified functional traits as relevant to community sorting against how well observed trait distributions correlated with environmental variation at a local scale, in the Ray Branch catchment (<10km study extent). Functional traits exhibiting non-random distributions within the Ray Branch watershed were most strongly correlated with environmental variation. Lastly, I assessed how the influences of niche and dispersal assembly on benthic macroinvertebrate community composition were affected by disturbance (shelterwood logging). Environmental variables defining the habitat template, and macroinvertebrate community composition, were measured before and after the disturbance; and path analysis was used to quantify the disturbance effect. The relationship between environmental variation and functional composition increased following logging, indicating disturbance augmented the influence of environmental filters, and consequently, the importance of niche-based community assembly. My dissertation provides the framework for a novel assessment of taxonomic and functional community composition data to infer the types of ecological dynamics that organize communities in the landscape. Additionally, this work provides a theoretical basis for assessing how dominant ecological processes change, in predictable ways, in response to changes in the habitat template.en
dc.description.degreePh. D.en
dc.identifier.otheretd-09262009-191937en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-09262009-191937/en
dc.identifier.urihttp://hdl.handle.net/10919/29110en
dc.publisherVirginia Techen
dc.relation.haspartSokol_ER_D_2009.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectcommunity assemblyen
dc.subjectnicheen
dc.subjectstreamsen
dc.subjectneutralen
dc.subjectdisturbanceen
dc.subjectbenthic macroinvertebratesen
dc.titleCommunity ecology of aquatic insects in forested headwater streams in the southern Appalachiansen
dc.typeDissertationen
thesis.degree.disciplineBiologyen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en
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