Electronic Thesis and Dissertation Repository

Degree

Doctor of Philosophy

Program

Geography

Supervisor

Yates, Adam G.

2nd Supervisor

Branfireun, Brian

Co-Supervisor

Abstract

Anthropogenic activities continue to expand and intensify resulting in vast areas of the globe being dominated by human land uses. Effective land management and conservation decisions depend on our ability to understand and predict biological response to further disturbance in already stressed ecosystems. Moreover, insight into biological response to ecological stressors may be advanced by using trait and functional community measures in combination with taxonomy. My dissertation goal was to describe patterns and drivers of variation in benthic macroinvertebrate communities (BMIC) taxonomic composition and function in streams in an agriculturally dominated landscape. I achieved my goal by conducting three related studies. First, a reciprocal transfer experiment assessed changes in taxonomic and trait modality composition and taxon-specific and community biomass spectrums associated with a change in agricultural land cover. Second, associations between the BMIC and land cover and habitat data were analyzed and the BMIC was assessed for potential as bioindicators of further land use modification in an already intensely modified landscape. Third, beta diversity and its two components, turnover and nestedness, were used to describe patterns and drivers of taxonomic and functional beta diversity within an agriculturally dominated landscape. Results indicated that agricultural land cover is not a strong predictor of the BMIC. However, individual taxa and traits and the community biomass size spectrum have potential as indicators of agricultural stress. Furthermore, habitat and distance variables are the strongest predictors of the BMIC. Functional descriptions of BMIC exhibited less variation and have more predictive power than taxonomic descriptors. These results indicate that detecting further community changes due to increased agriculture in a background of extensive agricultural cover may be difficult. Moreover, land management decisions based on the BMIC may need to be scaled to reduce spatial effects. I also recommend maintaining and restoring habitat heterogeneity over the entire management area may be the best option to promote beta diversity in ecosystems where conservation is of prime importance. Finally, concurrent application of trait and functional measures of the BMIC provide valuable additional information that can aid in making informed land management and conservation decisions.

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