|Abstract or Summary
- After three decades of active research coupling hydrology and stream ecology, the connection among solute transport, metabolism and processing is still unresolved. These knowledge gaps obscure the functioning of stream ecosystems and how those ecosystems interact with other landscape processes. We must resolve these challenges to wisely manage water resources, because there is a need to understand controls on stream ecosystems at local, regional and continental scales, and because we need to predict in-stream biogeochemical processes in environments and conditions that do not have supporting data. More robust methods are required to deconvolve signal imprints of solute transport, metabolism and processing, thus allowing the development and implementation of improved decision-making approaches for stream management. Recognizing that uncertainty and equifinality are ubiquitous issues in hydrologic problems, this dissertation focuses on the development of parsimonious methods to couple solute transport, metabolism and processing in stream ecosystems. These methods consist of scaling and predicting relationships for solute transport, efficient modeling frameworks to estimate processing rates in streams, and the use of the smart tracer resazurin to estimate stream metabolism at different spatial scales. This dissertation is the result of lab and field experiments, meta-analyses, and mathematical, statistical and computational modeling. The most significant contributions of this dissertation to the hydrological and biogeosciences are: (1) there are scaling relationships in stream solute transport. We found that the coefficient of skewness (CSK) of conservative tracer breakthrough curves is statistically constant over time and this result can be used to predict solute transport. (2) The CSK of all commonly used solute transport models decreases over time. This shows that current theory is inconsistent with experimental data and suggests that a revised theory of solute transport is needed. (3) Simple algebraic relationships can be used to estimate processing rates in streams. This eliminates the need to calibrate highly uncertain (and intermediate) parameters. (4) Under some common stream transport conditions dispersion does not play an important role in the estimation of processing rates and, therefore, can be neglected. Under such conditions, no computer modeling is needed to estimate processing rates. (5) Even if the reactions of target and proxy tracers happen in exactly the same locations at rates that are linearly proportional, the exact relationship between the two volume-averaged rates can be nonlinear and a function of transport conditions. However, the uncertainty in the estimation of the target processing rate is linearly proportional to the proxy-tracer processing rate. (6) The transformation of resazurin is nearly perfectly, positively correlated with aerobic microbial respiration. Therefore, resazurin can be used as a surrogate to measure respiration in situ and in vivo at different spatial scales (this is an extension of (5)). (7) Community respiration rates in streams may not need to be "corrected" for temperature between daytime and nighttime, because even when photosynthetically active radiation and stream water temperature are different, respiration rates might not be different across nighttime and daytime conditions.