Abstract
An integrated temporal study of a long-term ecological research and monitoring database of the St. Lawrence River was carried out. A long and mostly uninterrupted high temporal resolution record of fluorometric data from 2014 to 2018 was used to examine phytoplankton fluorometric variables at several scales and to identify temporal patterns and their main environmental drivers. Sets of temporal eigenvectors were used as modulating variables in a multiscale codependence analysis to relate the fluorometric variables and various environmental variables at different temporal scales. Fluorometric patterns of phytoplankton biomass in the St. Lawrence River are characterized by large, yearly-scale patterns driven by seasonal changes in water temperature, and to a lesser extent water discharge, over which finer-scale temporal patterns related to colored dissolved organic matter and weather variables can be discerned at shorter time scales. The results suggest that such an approach to characterize phytoplankton biomass in large rivers may be useful for processing large data sets from remote sensing efforts for detecting subtle large-scale changes in water quality due to land use practices and climate change.
Highlights
Scale becomes an important factor for ecological studies, and for management purposes, as management projects can fail if they use information based on small-scale patterns to modify larger-scale patterns when there is a disconnect between the two
No clear structure was observed in the direction of the wind
Both chlorophyll a and phycocyanin fluorescence showed discernable yearly patterns. These patterns are most likely related to yearly cycles in phytoplankton populations associated with annual variations in drivers of phytoplankton communities between the seasons in this temperate climate zone. This was especially true for phycocyanin, which showed a stronger yearly pattern than chlorophyll a
Summary
Increased knowledge of the patterns of water quality and its main drivers is valuable for the assessment and management of priority resources such as fish populations. To this end, detection of tributary and point-source inputs that result in nutrient enrichment and fecal bacterial contamination (Bramburger et al, 2015), mercury mobilization from changing water levels (Brahmstedt et al, 2019), and harmful cyanobacterial blooms with related taste and odor issues (Watson et al, 2008), are necessary. Scale becomes an important factor for ecological studies, and for management purposes, as management projects can fail if they use information based on small-scale patterns to modify larger-scale patterns when there is a disconnect between the two. If the variables affecting daily variation are different than those affecting yearly variation, considering them to develop programs at the yearly scale will possibly lead to failure
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