Lake Erie has undergone a substantial amount of ecosystem changes over the past century; including cultural eutrophication and several invasions by industrious exotic species. Simple mass balance models for phosphorus have been useful in guiding policy decisions that led to reduced eutrophication, but new, confounding threats to the ecological health of Lake Erie continue to appear and lake managers continue to need useful tools to better understand the lake. As more complex ecological questions are asked to guide future management decisions, more complex ecological models are developed in an effort to provide some clues. The walleye fishery in Lake Erie is economically very important. Walleye recruitment has been highly variable from year to year since the 1990s. Modelling zooplankton is desired as a diagnostic tool for elucidating the quality of habitat – spatially and temporally – that is available to walleye in their vulnerable larval state. ELCOM-CAEDYM (or ELCD) is a 3-dimensional, coupled hydrodynamic and ecological model, which has been successfully applied to Lake Erie to model the nutrients and phytoplankton. The objectives of this study were to better understand the ELCOM-CAEDYM model of Lake Erie through a sensitivity analysis (SA), which has not been done before, and to explicitly simulate zooplankton in this model. An SA is important for determining which of the uncertain parameters have the greatest impact on the output variables. Due to the complexity of the CAEDYM model and the highly interdependent functions and variables modelled, a local SA (comparing changes in output by perturbing parameters one-at-a-time from some baseline configuration) was not desirable. Local SA’s ignore the possibility of a parameter’s effects being correlated to the status of other parameters. However, quantitative global methods are enormously computationally expensive for a complex model. The Lake Erie ELCD model simulates temperature, mixing, nutrient cycles, and phytoplankton dynamics. Phytoplankton are represented by 5 functional groups. With the explicit inclusion of 2 functional groups of zooplankton (copepods and cladocerans), the model uses over 300 function parameters in addition to requiring meteorological data and river inflow characteristics throughout the simulation. The model is set up with a 2-km grid over 40 layers with a 5-minute timestep from April 11 to September 1. This full simulation takes 6 days to complete. A quantitative global method to evaluate all parameters potentially significant to zooplankton would be impossible. The Morris method was selected for its streamlined global sampling procedure combined with the manageable computational demands of a one-at-a-time analysis. This method provides the relative sensitivity of diagnostic outputs to perturbed parameters. Ninety-one parameters were selected to be evaluated in 3680 simulations for the Morris SA. The selection of which parameters to evaluate and their assigned ranges are critical components in any SA. The ranges for parameters that represent a measurable quantity were assessed based on observed values in Lake Erie and other relevant studies. For some parameters, a measured realistic range was unknown. In these cases, values from relevant published models or judgements based on experience with the ELCD-Erie model were used to choose a suitable range. To assess the sensitivity of CAEDYM variables to parameters, DYRESM was substituted for ELCOM to vastly decrease the computation time of a single run. DYRESM is not suitable to model the entire lake due to the large size and irregular shape of the entire lake. Therefore, only the West Basin was modelled and analysed using DYCD. The West Basin was of special interest for a sensitivity analysis of CAEDYM parameters with respect to zooplankton because it is an important area for walleye larval development. DYCD output profiles for temperature, total chlorophyll a (TChla as a surrogate for total phytoplankton concentration) were similar in magnitudes and seasonal dynamics compared to ELCD outputs in deep West Basin stations. The sensitivity of zooplankton, TChla and TP to each parameter was assessed using two single value diagnostics: the simulated seasonal maximum and the simulated day on which peak maximum was reached. Zooplankton were sensitive to almost all of the zooplankton parameters perturbed in the analysis. This may indicate that modelling zooplankton is extremely complex, relying on many dynamic processes, or that evaluated ranges were not constrained well enough. An example of sensitivity to a poorly known parameter is the messy feeding coefficient. Reducing the uncertainty of this parameter would improve the confidence in the zooplankton assimilation submodel. Other parameters that stood out for being especially significant to zooplankton were: the respiration rate, mortality rate, internal phosphorus to carbon ratio, the temperature multiplier and standard temperature for feeding dynamics, and the half saturation constant. Most of these are easily explained as they directly aid or impede growth or they directly affect zooplankton losses. The most significant phytoplankton parameters on TChla and zooplankton outputs were, not surprisingly, the maximum growth rate and the mortality and respiration coefficient. Some particulate matter parameters proved to be important to outputs as well. More than 2500 of the 3680 parameter configurations resulted in unrealistic zooplankton simulations: peak values that did not much exceed initial conditions on the first day of the simulation. The SA exercise pinpointed a few configurations that resulted in reasonable peak zooplankton values and timing; these runs were used as a starting point for calibrating the ELCD model. Parameters were further manually adjusted by quickly checking their impacts on DYCD before applying them to ELCD. Post SA and minor calibration, the modelled zooplankton results were dramatically better than initial modelling attempts prior to the SA. Zooplankton concentrations throughout the lake were close to measured ranges and in some parts of the lake seasonal patterns were also similar to measured patterns. Modelled zooplankton results were least consistent with observations in the south west area of the lake: zooplankton were overestimated in late June-early July and they subsequently crashed and were underestimated in late July-August. It is supposed that this is due to higher grazing pressure from fish larvae in that area of the lake, which is not explicitly modelled. Although it is not anticipated that the south west seasonal zooplankton patterns will improve through parameter calibration (since predator effects are uniformly characterized throughout the lake by the same mortality factor) , further calibration is needed to improve results in the rest of the lake since copepods are generally overestimated and cladocerans generally underestimated. Phytoplankton groups must also be calibrated simultaneously to ensure that they are still operating within reasonable concentrations given more successful zooplankton simulations.

Abstract There are 22 species of chaetognaths belonging 11 genera and 4 families found in coastal waters around the Kaohsiung and Liuchiu Yu Island from March 1997 to February 1998. The average abundance of chaetognaths was 2527 ¡Ó1659 ind./100m3. The 5 most dominant species were Flaccisagitta enflata, Aidanosagitta crassa, Sagitta bipuncata, Ferosagitta ferox and Serratosagitta pacifica, and comprised > 95% of total chaetognaths. Fl. efnlata was the most common and abundance species, its number occupied 70% of total chaetognaths and occurred in every station. These dominant species showed significant seasonal succession, in that, Fl. Enflata could be found in all seasons, while S. bipuncata was found only in fall and winter. Most of chaetognaths found in this study were pelagic, tropical and temperate species, and most of them are widely distributed in the Pacific, the Atlantic and the Indian ocean (50% of total species), and in the Indian and the Pacific ocean (41% of total species). In terms of ecological distribution patterns, warm euryhaline species (i.e. Fl. Enflata and Fe. ferox), and warm hyperhaline species (i.e. S. bipuncata and Se. pacifica) dominated in this study areas. The abundance of chaetognaths was higher in fall (4721 ¡Ó8435 ind./100m3) and the lower in spring (1077 ¡Ó995 ind./100m3). The horizontal distribution of chaetognaths was apparently influenced by the runoff of Kaohsiung Habor and Kaoping River, and the peak abundance was usually found in the front of Kaoping river plume. Most chaetognaths (over 60% of total amount) were found in the surface waters (0-5 m), and its abundance abruptly decreased with depth. The scales of day/night vertical migration of chaetognaths were small (generally less than 50 m). Three types of vertical migration were distinguished in this study: Nocturnal migration (i.e. Fl. Enflata and Se. pacifica). Reverse migration (i.e. S. bipuncata ), and Non-migration (i.e. Fe. ferox). The vertical distribution and the distance of vertical migration of most chaetognaths, however, varied seasonally.

Project (B.S.)--James Madison University, 2009. / Includes bibliographical references.

Thesis (Ph. D.)--Massacnusetts Institute of Technology and Woods Hole Oceanographic Institution, 1977. / Includes bibliographical references (leaves 201-220).

The global movement of aquatic non-indigenous species can have severe ecological, environmental and economic impacts emphasizing the need to identify potential invaders and transport pathways. Initial transport is arguably the most important stage of the invasion process owing to its role in selectively determining potential invasion candidates. This study characterizes a well defined human-mediated dispersal mechanism, ballast water transport, as a vector for the introduction of non-indigenous zooplankton. Ballast water exchange in the open ocean is the most widely adopted practice for reducing the threat of aquatic invasions and is mandatory for most foreign vessels intending to release ballast in Canadian waters. Ships entering Canadian ports are categorized into the following three shipping classes based on current regulations: overseas vessels carrying exchanged ballast water, intra-coastal vessels carrying exchanged ballast water or intra-coastal vessels carrying un-exchanged ballast water. This study characterizes zooplankton communities associated with each of these shipping classes sampled from ports on Canada’s Pacific coast, Atlantic coast and the Great Lakes Basin. Ballast water samples were collected and analyzed from 77 vessels between 2006 - 2007. The ballast water environment was found to be diverse, with over 193 zooplankton taxa, 71 of which were non-indigenous to their receiving environments. Intracoastal vessels containing un-exchanged coastal water transported the greatest density of non-indigenous zooplankton into Canadian ports. Total zooplankton density was found to be negatively correlated with ballast water age The absence of mandatory ballast water exchange and the younger ballast water age of coastal un-exchanged vessels is likely responsible for the higher density of non-indigenous zooplankton in intracoastal un-exchanged vessels. Propagule pressure, invasion history and environmental suitability are all useful in evaluating invasion potential and all suggest that intracoastal un-exchanged vessels pose the greatest invasion threat to Canadian aquatic ecosystems. In conclusion, although the risk of primary introductions from overseas ports may have been reduced through open-ocean exchange of ballast water, secondary introductions from previously invaded ports in North America may be the primary threat to Canadian aquatic ecosystems via this transport vector.

While much evidence suggests that ecosystem functioning is closely related to biodiversity, present rates of biodiversity loss are high. With the emergence of the metacommunity concept ecologists have become increasingly aware that both local processes (e.g. competition, predation), and regional processes (e.g. dispersal and regional heterogeneity) affect ecological communities at multiple spatial scales. I experimentally investigated the effects of habitat connectivity and regional heterogeneity on biodiversity, community composition, and ecosystem functioning of artificial pond metacommunities of freshwater invertebrates at the local (α), among-community (β), and regional (γ) spatial levels. There was a significant effect of habitat connectivity on mean local richness, but mean local Simpson diversity, mean local functional diversity (FD), and all the three indices of ecosystem functioning investigated (regional abundance, invertebrate biomass, and chlorophyll a concentration) were unaffected by connectivity levels. Regional heterogeneity had no effect on local diversity, but enhanced both among-community richness and among-community Simpson diversity. Conversely, connectivity reduced among-community Simpson diversity. All indices of regional diversity were unaffected by either connectivity or heterogeneity. Despite expectations that there would be strong interactions between the effects of connectivity and heterogeneity on species richness, there were no interactions for any index of biodiversity at any spatial scale. Invertebrate community composition was unaffected by either connectivity or heterogeneity, though there was a significant effect of heterogeneity on its variance. Neither connectivity nor heterogeneity had significant effects on any index of ecosystem functioning, nor among-community coefficients of variation of ecosystem functioning. Connectivity appears to act mainly as a force homogenizing habitat patches in a region, as opposed to having strong effects in and of itself on communities. Conversely, heterogeneity acts largely as a diversifying force, maintaining differences between communities within a region, but, similar to connectivity, it does not have clear effects on communities at the local scale. Despite the different processes expected to act in homogeneous and heterogeneous regions, it does not appear that connectivity and heterogeneity interact strongly. / Thesis (Master, Biology) -- Queen's University, 2008-10-16 09:06:33.103

No description available.

Filter-feeding macrozooplankton were collected from 24 lakes in south-central Ontario to examine relationships between environmental factors and methyl mercury accumulation. Zooplankton methyl mercury levels ranged from 19 to 448 ng$ rm cdot g sp{-1}$ dry weight in the study lakes and were highest in zooplankton from acidic brownwater lakes. Water color and lake water pH were the best predictors of methyl mercury levels in zooplankton explaining 73% of the variation. Methyl mercury concentrations were positively correlated with water color and inversely correlated with lake water pH. Water color explained a greater portion of the overall variance in methyl mercury levels, indicating that the supply of mercury from the drainage basin plays a key role in determining methyl mercury concentrations in the lacustrine biota. Zooplankton methyl mercury levels were well correlated with mercury concentrations in smallmouth bass (Micropterus dolomieui) and largemouth bass (Micropterus salmoides) from 11 of the study lakes showing zooplankton to be good indicators of the relative bioavailability of mercury at the base of the food chain.

Lake Erie has undergone a substantial amount of ecosystem changes over the past century; including cultural eutrophication and several invasions by industrious exotic species. Simple mass balance models for phosphorus have been useful in guiding policy decisions that led to reduced eutrophication, but new, confounding threats to the ecological health of Lake Erie continue to appear and lake managers continue to need useful tools to better understand the lake. As more complex ecological questions are asked to guide future management decisions, more complex ecological models are developed in an effort to provide some clues. The walleye fishery in Lake Erie is economically very important. Walleye recruitment has been highly variable from year to year since the 1990s. Modelling zooplankton is desired as a diagnostic tool for elucidating the quality of habitat – spatially and temporally – that is available to walleye in their vulnerable larval state. ELCOM-CAEDYM (or ELCD) is a 3-dimensional, coupled hydrodynamic and ecological model, which has been successfully applied to Lake Erie to model the nutrients and phytoplankton. The objectives of this study were to better understand the ELCOM-CAEDYM model of Lake Erie through a sensitivity analysis (SA), which has not been done before, and to explicitly simulate zooplankton in this model. An SA is important for determining which of the uncertain parameters have the greatest impact on the output variables. Due to the complexity of the CAEDYM model and the highly interdependent functions and variables modelled, a local SA (comparing changes in output by perturbing parameters one-at-a-time from some baseline configuration) was not desirable. Local SA’s ignore the possibility of a parameter’s effects being correlated to the status of other parameters. However, quantitative global methods are enormously computationally expensive for a complex model. The Lake Erie ELCD model simulates temperature, mixing, nutrient cycles, and phytoplankton dynamics. Phytoplankton are represented by 5 functional groups. With the explicit inclusion of 2 functional groups of zooplankton (copepods and cladocerans), the model uses over 300 function parameters in addition to requiring meteorological data and river inflow characteristics throughout the simulation. The model is set up with a 2-km grid over 40 layers with a 5-minute timestep from April 11 to September 1. This full simulation takes 6 days to complete. A quantitative global method to evaluate all parameters potentially significant to zooplankton would be impossible. The Morris method was selected for its streamlined global sampling procedure combined with the manageable computational demands of a one-at-a-time analysis. This method provides the relative sensitivity of diagnostic outputs to perturbed parameters. Ninety-one parameters were selected to be evaluated in 3680 simulations for the Morris SA. The selection of which parameters to evaluate and their assigned ranges are critical components in any SA. The ranges for parameters that represent a measurable quantity were assessed based on observed values in Lake Erie and other relevant studies. For some parameters, a measured realistic range was unknown. In these cases, values from relevant published models or judgements based on experience with the ELCD-Erie model were used to choose a suitable range. To assess the sensitivity of CAEDYM variables to parameters, DYRESM was substituted for ELCOM to vastly decrease the computation time of a single run. DYRESM is not suitable to model the entire lake due to the large size and irregular shape of the entire lake. Therefore, only the West Basin was modelled and analysed using DYCD. The West Basin was of special interest for a sensitivity analysis of CAEDYM parameters with respect to zooplankton because it is an important area for walleye larval development. DYCD output profiles for temperature, total chlorophyll a (TChla as a surrogate for total phytoplankton concentration) were similar in magnitudes and seasonal dynamics compared to ELCD outputs in deep West Basin stations. The sensitivity of zooplankton, TChla and TP to each parameter was assessed using two single value diagnostics: the simulated seasonal maximum and the simulated day on which peak maximum was reached. Zooplankton were sensitive to almost all of the zooplankton parameters perturbed in the analysis. This may indicate that modelling zooplankton is extremely complex, relying on many dynamic processes, or that evaluated ranges were not constrained well enough. An example of sensitivity to a poorly known parameter is the messy feeding coefficient. Reducing the uncertainty of this parameter would improve the confidence in the zooplankton assimilation submodel. Other parameters that stood out for being especially significant to zooplankton were: the respiration rate, mortality rate, internal phosphorus to carbon ratio, the temperature multiplier and standard temperature for feeding dynamics, and the half saturation constant. Most of these are easily explained as they directly aid or impede growth or they directly affect zooplankton losses. The most significant phytoplankton parameters on TChla and zooplankton outputs were, not surprisingly, the maximum growth rate and the mortality and respiration coefficient. Some particulate matter parameters proved to be important to outputs as well. More than 2500 of the 3680 parameter configurations resulted in unrealistic zooplankton simulations: peak values that did not much exceed initial conditions on the first day of the simulation. The SA exercise pinpointed a few configurations that resulted in reasonable peak zooplankton values and timing; these runs were used as a starting point for calibrating the ELCD model. Parameters were further manually adjusted by quickly checking their impacts on DYCD before applying them to ELCD. Post SA and minor calibration, the modelled zooplankton results were dramatically better than initial modelling attempts prior to the SA. Zooplankton concentrations throughout the lake were close to measured ranges and in some parts of the lake seasonal patterns were also similar to measured patterns. Modelled zooplankton results were least consistent with observations in the south west area of the lake: zooplankton were overestimated in late June-early July and they subsequently crashed and were underestimated in late July-August. It is supposed that this is due to higher grazing pressure from fish larvae in that area of the lake, which is not explicitly modelled. Although it is not anticipated that the south west seasonal zooplankton patterns will improve through parameter calibration (since predator effects are uniformly characterized throughout the lake by the same mortality factor) , further calibration is needed to improve results in the rest of the lake since copepods are generally overestimated and cladocerans generally underestimated. Phytoplankton groups must also be calibrated simultaneously to ensure that they are still operating within reasonable concentrations given more successful zooplankton simulations.

No description available.