Predicting the Viability of Fish Populations in a Modified Riverine Environment (original) (raw)
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Ecological Modelling, 2015
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.
A Simulation Study of Factors Controlling White Sturgeon Recruitment in the Snake River
2000
Five of the nine populations of white sturgeon Acipenser transmontanus, located between dams on the Middle Snake River, have declined from historical levels and are now at risk of extinc- tion. One step towards more effectively protecting and managing these nine populations is ranking factors that influence recruitment in each of these river segments. We developed a model to suggest