We rarely consider light limitation in ecosystem productivity, yet light limitation is a major constraint on river autotrophy. Because the light that reaches benthic autotrophs must first pass through terrestrial vegetation and an overlying water column that can be loaded with sediments or colored organic material, there is strong selection for river autotrophs to have high light use efficiencies (LUEs), that is, the efficiency at which light energy is converted to biomass. In contrast to prior studies that have estimated river LUE on single days, we calculated continuous LUE over more than 6 full years for 64 free‐flowing rivers across the United States. This dataset represents the largest compilation of continuous estimates of daily rates of gross primary productivity (GPP) and daily light inputs from which we calculated daily estimates of LUE. Early estimates of LUE in rivers found that clearwater springs with stable flows could achieve LUEs of 4%, much higher than LUEs reported for terrestrial plants. We found that 53% of the rivers in our dataset have LUEs that exceed 4% on at least one day of their time series. Because of the high variability in daily LUE, measurements taken on any given day may misrepresent a river ecosystem's annual LUE. Though most rivers share a high potential, the mean annual LUE of all rivers in our dataset is much lower, only 0.5%. We found that rivers with more variable flow regimes had lower annual LUEs, which indicates that LUE is constrained by hydrologic disturbances that remove, bury, or shade autotrophic biomass. Comparisons of LUE across ecosystems allow us to reframe our view of rivers, by recognizing the high efficiency with which they convert light to biomass compared with lentic, marine, and terrestrial ecosystems.
This content will become publicly available on June 23, 2024
Directly observing autotrophic biomass at ecologically relevant frequencies is difficult in many ecosystems, hampering our ability to predict productivity through time. Since disturbances can impart distinct reductions in river productivity through time by modifying underlying standing stocks of biomass, mechanistic models fit to productivity time series can infer underlying biomass dynamics. We incorporated biomass dynamics into a river ecosystem productivity model for six rivers to identify disturbance flow thresholds and understand the resilience of primary producers. The magnitude of flood necessary to disturb biomass and thereby reduce ecosystem productivity was consistently lower than the more commonly used disturbance flow threshold of the flood magnitude necessary to mobilize river bed sediment. The estimated daily maximum percent increase in biomass (a proxy for resilience) ranged from 5% to 42% across rivers. Our latent biomass model improves understanding of disturbance thresholds and recovery patterns of autotrophic biomass within river ecosystems.
more » « less- NSF-PAR ID:
- 10434493
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Ecology Letters
- ISSN:
- 1461-023X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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