Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience
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Abstract
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.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience |
| Series title | Ecology Letters |
| DOI | 10.1111/ele.14269 |
| Volume | 26 |
| Issue | 9 |
| Year Published | 2023 |
| Language | English |
| Publisher | Wiley |
| Contributing office(s) | Southwest Biological Science Center |
| Description | 23 p. |
| First page | 1510 |
| Last page | 1522 |
| Google Analytic Metrics | Metrics page |