We used an ecosystem-based modeling approach, Ecopath with Ecosim, to explore the relative importance of a top-down biotic management lever (top predator introduction) versus a bottom-up abiotic management lever (alteration of nutrient inputs) in regulating biomass in reservoir food webs. To do so, we modeled three Ohio reservoirs that varied in ecosystem productivity. For each, we simulated five hybrid striped bass (Morone chrysops × Morone saxatilis) (introduced top predator) biomass levels at three nutrient input levels (n = 15 simulations per reservoir). Nutrient inputs influenced the food web more than introduced predators within each reservoir. Further, across all three reservoirs, the impact of stocked hybrid striped bass on the equilibrium biomass of phytoplankton, prey fish (gizzard shad, Dorosoma cepedianum), and native top predators (e.g., largemouth bass, Micropterus salmoides) was <3%, <14%, and <20%, respectively, of the maximum impact of changes in nutrient inputs on these components. Thus, in mesotrophic to hypereutrophic reservoirs that are dominated by omnivorous gizzard shad, manipulating allochthonous inputs of nutrients offers agencies a more powerful means to regulate food web structure than manipulation of top predator biomass.
Proper interpretation of gill-net survey data requires knowledge of gill-net encounter probabilities for target species, including understanding how variation in habitat use and movement rate affects encounter probability. However, few estimates of encounter probability exist. Further, previous studies have hypothesized that gill-net encounter probability is proportional to swimming speed, which increases with fish size. However, potential swimming speed may not be reflective of movement rates and encounter probability due to species-specific biology and behaviors. I used a large telemetry data set consisting of 483,169 fine-scale positions (<5-m resolution) of Walleye Sander vitreus and saugeye (Walleye × Sauger S. canadensis) to simulate daily North American standard gill-net surveys. I tagged and tracked 42 fish (340-614 mm) during both 2013 and 2014 and determined whether each fish position from April to November was within 24.8 m of shore (the length of the North American standard net). I also determined fish movement rate (m/h) during simulated gill-net surveys and whether each fish track during each survey crossed 24.8-m "virtual" gill nets. I then used Bayesian multi-level models to evaluate how nearshore habitat use, movement rate, and gill-net encounter probability varied with fish length, species, and month. Movement rate (m/h) and gill-net encounter probability were greatest for both Walleye and saugeye during April, May, and June, but neither movement rate nor encounter probability increased with fish length during most months. Walleye used nearshore habitats less frequently than saugeye, especially during September and November, resulting in lower gill-net encounter probabilities for Walleye. These results show that gill-net encounter probability varies across species, months, and occasionally fish lengths due to variation in both habitat use and movement rate. These outcomes also indicate that total gill-net selectivity may change throughout the year due to changes in the relationship between fish length and gill-net encounter probability.
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