High frequency population ecology using pairs of chlorophyll a sensors on a Great Plains river

Abstract:

Longitudinal phytoplankton patterns in rivers result from population accumulation in water parcels as they move downstream. In this study we ask 2 related questions: 1) Can the spatial patterns of chlorophyll a (chl-a) in rivers reflect population dynamics of phytoplankton during river transit? 2) What can be inferred about population dynamics using stationary, spatial, water quality parameters gathered for ecosystem monitoring? To answer these questions, we characterize relationships in a 3-year USGS dataset of daily chl-a measurements across 3 sites down the mainstem of the Kansas River, a mid-sized American Great Plains river (mean discharge 222 cms). We follow a ‘pseudo-Lagrangian’ approach, similar to 2-site metabolism techniques, assessing patterns across upstream-downstream pairs of fixed site measurements while using temporal offsets to account for transit time. We found that for several (2-3) weeks-long periods annually, chl-a in the Kansas River would rise to stable, elevated concentrations that were spatially persistent across the full 180 km spanned by our 3 study sites. The onset and offset of these bloom events always corresponded with changes in either water temperature or discharge. There also appeared to be density dependence: large downstream increases in chl-a occurred, but such increases did not occur when upstream concentrations were elevated. Further, high chl-a periods corresponded with consistently low daily nitrate measurements, suggesting the density dependence on growth rates may be caused by phytoplankton uptake drawing down nutrients to limiting concentrations. These precise observations of temporal and spatial patterns across the full range of annual conditions create an opportunity to characterize phytoplankton net growth dynamics and evaluate the variety of potential controls on their accumulation in rivers.