Quantifying habitat quality of larval bay anchovy (Anchoa mitchilli) in Chesapeake Bay by linking an individual-based model with spatially-detailed field data

Larval bay anchovy (Anchoa mitchilli) habitat quality in Chesapeake Bay was predicted using an individual-based model applied to spatially-detailed field data from Rilling and Houde (1999). Habitat quality was predicted using the ratio of instantaneous mortality rate to instantaneous growth rate. Model predictions of habitat quality were compared to field estimates of habitat quality derived from the spatially-detailed field data. Three sets of one-day simulations were performed to estimate larval growth and mortality rates throughout Chesapeake Bay during June and during July 1993. Field-based simulations used field data to estimate the model inputs of water temperature, zooplankton densities, and the densities and sizes of bay anchovy larvae and gelatinous predators (Mnemiopsis leidyi and Chrysaora quinquecirrha). Standardized larvae simulations used the same field data, but standardized larval sizes and densities throughout the Bay. A third set of simulations was performed to determine the relative importance of six factors in determining the bay-wide spatial variation in predicted growth and mortality rates. Model predictions from the field-based simulations produced spatial patterns of habitat quality in the Bay that sometimes conflicted with the otolith-based predictions of Rilling and Houde. Field estimates of anchovy egg and larvae abundances were generally high in regions predicted to have low M/G ratios, but low in regions with low otolith-estimated M/G ratios. The standardized larvae simulations generally supported the conclusions of the field-based simulations. The effect of habitat quality on larval production was evaluated using the predicted mortality rates from the two sets of simulations. Initial larval abundances dominated the percent of survivors projected 20-days into the future that a region would produce, but when larvae were standardized across the bay, differences in habitat quality among regions was important in determining the relative contributions of survivors by region. Initial larval length and zooplankton densities were the most important factors determining the spatial variation in growth rate, while predator density was most important for mortality rate. Future research should focus on field and laboratory data collection to resolve the discrepancy between model-predicted and otolith-estimated M/G ratios

Predicting water quality effects on bay anchovy (Anchoa mitchilli) growth and production in Chesapeake Bay: linking water quality and individual-based fish models

Water quality in the Chesapeake Bay and the Patuxent River has decreased since the 1950s due to an increase in nutrient loadings. Increased nutrient loads have caused an increase in the extent and duration of hypoxic conditions. Restoration via large-scale reductions in nutrient loadings is now underway. How reducing nutrient loadings will affect water quality is well predicted; however the effect on fish is generally unknown as most water quality models do not include trophic levels higher than zooplankton. I combined two water quality models with bay anchovy models (Anchoa mitchilli) to examine the effects of changes in nutrient loadings on anchovy survival and growth. An individual-based predation model was statically linked to Patuxent River watershed land-use and water quality models, and used to simulate the effects of changes in watershed land-use, Chesapeake Bay boundary condition nutrient loadings, and water year types on the summertime survival of daily anchovy egg and larval cohorts. I found that changes in Patuxent watershed land-use had little effect on egg and larval survival, while reduced nutrient loadings at the Chesapeake Bay boundary condition increased egg survival but reduced larval survival in June. The second analysis dynamically coupled a spatially-explicit, individual-based population dynamics model of juvenile and adult anchovy to the 3-dimensional Chesapeake Bay water quality model. Growth rates of individual anchovy within water quality model cells were calculated using a bioenergetics equation. Zooplankton densities from the water quality model provided prey for anchovy consumption, and anchovy consumption was an additional mortality term on zooplankton. Anchovy mortality was size-dependent. Anchovy movement depended on water temperature, dissolved oxygen, and zooplankton concentrations. Multi-year simulations with fixed annual recruitment were performed under decreased, baseline, and increased nutrient loadings scenarios. Increasing nutrient loadings had small effects on survival, but increased anchovy growth and therefore biomass. Anchovy growth exhibited compensatory density dependence. The results of both analyses showed that anchovy responses to changed nutrient loadings were complex and depended on life stage. Full-life cycle, spatially-explicit population models that are dynamically coupled to water quality models are needed to truly predict the effects of changes in nutrient loadings on fish populations