Spatiotemporal variation in flow-dependent recruitment of long-lived riverine fish: Model development and evaluation
Research output: Contribution to journal › Article › peer-review
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DOI
Natural flow regimes can play a major role as an overarching ecosystem driver in reproduction and recruitment of riverine fishes. Human needs for freshwater however have altered hydrology of many riverine systems worldwide, threatening fish population sustainability. To understand and predict how spatiotemporal dynamics of flow regimes influence reproductive and recruitment variability, and ultimately population sustainability of shovelnose sturgeon (Scaphirhynchus platorynchus), we develop a spatially explicit (1D) individual-based population model that mechanistically (via energetics-based processes) simulates daily activities (dispersal, spawning, foraging, growth, and survival). With field observations of sturgeon and habitat conditions in a major tributary of the Missouri River system (USA), we calibrate and evaluate the model via pattern-oriented modeling. Model simulation experiments using 17-year environmental time series data showed that seasonal and interannual variation in hydrological conditions plays a major role in timing, location, and magnitude of spawning and recruitment success of sturgeon. During droughts, consecutive weak year-classes resulted in a steady population decline. While low flow and subsequent low prey production limited foraging opportunities and slowed gonad development, these conditions were not severe enough for adults to abort the reproductive cycle. Post-settlement larval sturgeon were however unable to feed efficiently to grow out of a size-dependent ‘predation window’, resulting in high mortality. Slow growth and low survival of larval sturgeon thus likely play a larger role in recruitment failures during droughts than low or lack of spawning events.
Keywords
- River, Population dynamics, Energetics, Individual-based models, Spatially explicit models, Shovelnose sturgeon, Conservation
Original language | English |
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Pages (from-to) | 79-92 |
Number of pages | 14 |
Journal | Ecological Modelling |
Volume | 296 |
Early online date | 7 Nov 2014 |
DOIs | |
Publication status | Published - 24 Jan 2015 |
Externally published | Yes |