Biotic and abiotic effects on biogeochemical fluxes across multiple spatial scales in a prairie stream network

• Main Author: Trentman, Matthew T.
• Language: en_US
• Published: Kansas State University 2015
• Subjects: Konza Prairie Biological Station; Biogeochemistry; Biogeochemistry (0425); Ecology (0329)
• Online Access: http://hdl.handle.net/2097/19750

Master of Science === Division of Biology === Walter K. Dodds === Understanding the variability of ecological processes across spatial scales is a central issue in ecology, because increasing scale is often associated with increasing complexity. In streams, measurements of biogeochemical fluxes are important for determining ecosystem health and the downstream delivery of nutrients, but are often collected at scales with benthic areas measured in spatial areas from ~10 cm[superscript]2 to ~100 m[superscript]2 (referred to here as patch and reach, respectively), which are smaller than the scale that management decisions are made. Both biotic and abiotic factors will be important when attempting to predict (i.e. scale) biogeochemical rates, but few studies have simultaneously measured rates and their primary drivers at different spatial scales. In the first chapter, I used a conceptual scaling framework to evaluate the ability to additively scale biogeochemical rates by comparing measurements of ecosystem respiration (ER) and gross primary production (GPP) from patch to reach-scales across multiple sites over a two-year period in a prairie stream. Patch-scale measurements with and without fish (biotic factors) and abiotic factors measured simultaneously with metabolic rates suggest that abiotic conditions are stronger drivers of these rates. Patch-scale rates significantly overestimated reach rates for ER and GPP after corrections for habitat heterogeneity, temperature and light, and a variety of stream substrata compartments. I show the importance of determining abiotic and biotic drivers, which can be determined through observational or experimental measurements, when building models for scaling biogeochemical rates. In the second chapter, I further examined patch-scale abiotic and biotic drivers of multiple biogeochemical rates (ER, GPP, and ammonium uptake) using path analyses and data from chapter 2. Total model-explained variance was highest for ER (65% as R[superscript]2) and lowest for GPP and ammonium uptake (38%). Fish removal directly increased ammonium uptake, while all rates were indirectly affected by fish removal through changes in either FBOM and /or algal biomass. Significant paths of abiotic factors varied with each model. Large-scale processes (i.e. climate change and direct anthropogenic disturbances), and local biotic and abiotic drivers should all be considered when attempting to predict stream biogeochemical fluxes at varying spatial scales.