A simple metric for predicting the timing of river phytoplankton blooms

Abstract

In rivers, phytoplankton populations are continuously exported by unidirectional, advective flow. Both transport and growth conditions determine periods of excess phytoplankton growth, or blooms, in a given reach. Phytoplankton abundance, however, has mainly been compared to the state of either growth or transport conditions alone rather than in tandem. Previous studies have not yielded consistent driver–response relationships, limiting our ability to predict the timing of riverine phytoplankton blooms based on environmental factors. Here, we derive a simple joint metric that combines the state of growth and transport conditions, specifically the ratio of temperature and discharge (T/Q$$ T/Q $$). We then compare the metric to biomass abundance data (daily, sensor‐based chlorophyll a [chl a] data) from a mid‐sized Great Plains river (the Kansas). T/Q$$ T/Q $$ was an excellent predictor of low to high biomass, outperforming either variable alone. However, it could not differentiate between very high biomass values, values well above the biomass threshold designating bloom conditions. Our findings of reduced performance at the highest values of T/Q indicated that T/Q$$ T/Q $$ could predict the occurrence (timing) but not magnitude of phytoplankton blooms, and we used T/Q to correctly predict 71% of days when bloom conditions occurred. Analyzing chl a abundance with T/Q$$ T/Q $$ also revealed likely switching from transport and temperature to nutrient control. T/Q$$ T/Q $$ offers a simple tool for (1) predicting the timing of river phytoplankton blooms, (2) forecasting how river ecosystems will respond to surrounding environmental changes, and (3) determining which environmental factors shape phytoplankton blooms at specific locations along a river.

River Control Points for Algal Productivity Revealed by Transport Analysis

“…Algal biomass may be substantially thinned by grazing organisms (e.g., zooplankton and mussels) in rivers (Sellers & Bukaveckas, 2003); in the Illinois River, grazers may also include invasive carp which are common in the lower River (Young, 2015). Even if algal growth persists downstream of a control point, it may only thrive until nutrients have been depleted (Bruns et al., 2022; Valett et al., 2022). Furthermore, as individual algal cells grow and die during transport, the community composition may shift (e.g., from a non‐toxic diatom to a toxic cyanobacteria dominated community; Graham et al., 2012), in part because of transport or seed organisms from upstream.…”

“…In idealized cases, maximum algal biomass production coincides with longer residence times, warm water temperatures, and high water clarity (Turner et al., 2022). Nutrients are known controls on algal growth (Bruns et al., 2022; Glibert, 2017), but might not be limiting in rivers with an abundant nutrient supply (Wehr & Descy, 1998), such as the Illinois River.…”

“…The relation between chl‐ a and algal biomass varies with algal species, temperature, light, and nutrient availability (Geider, 1987), yet chl‐ a has long been used as a proxy for algal biomass (Cloern et al., 1995). For this study, we do not define an algal bloom occurrence by a set chl‐ a concentration threshold as others have done (e.g., 10–50 μg L −1 , World Health Organization, 2003; 30 μg L −1 , Bruns et al., 2022). Instead, we used a network of continuous chl‐ a concentrations and streamflow to quantify the reach‐by‐reach daily components of biomass net growth or loss, upstream advection, and tributary inputs (Table 1 and Figure 1).…”

“…Studies in lowland rivers indicate that streamflow and water temperature drive the formation of planktonic algal blooms as nutrients are in abundant supply (Sellers & Bukaveckas, 2003; Turner et al., 2022). During warm, slow streamflow conditions, for example, an algal bloom may rapidly develop and persist until conditions change; as algae are transported downstream, they may continue to grow, persist without growth, or decay (Bruns et al., 2022; Graham et al., 2012; Otten et al., 2015; Williamson et al., 2018). Conversely during higher streamflow when flushing rates are faster than algal growth rates, algal biomass does not have time to accumulate (Cha et al., 2017; Lucas et al., 2009; Peierls et al., 2012; Søballe & Kimmel, 1987), suggesting that planktonic river algal blooms may follow certain residence time thresholds (Bruns et al., 2022).…”

“…During warm, slow streamflow conditions, for example, an algal bloom may rapidly develop and persist until conditions change; as algae are transported downstream, they may continue to grow, persist without growth, or decay (Bruns et al., 2022; Graham et al., 2012; Otten et al., 2015; Williamson et al., 2018). Conversely during higher streamflow when flushing rates are faster than algal growth rates, algal biomass does not have time to accumulate (Cha et al., 2017; Lucas et al., 2009; Peierls et al., 2012; Søballe & Kimmel, 1987), suggesting that planktonic river algal blooms may follow certain residence time thresholds (Bruns et al., 2022). However, building a robust river algal growth model from local residence times (Kim et al., 2019) could be futile when streamflow, and therefore the amount of underlying transported mass, is rapidly changing.…”