RESUMEN
The North American Great Lakes have been experiencing dramatic change during the past half-century, highlighting the need for holistic, ecosystem-based approaches to management. To assess interest in ecosystem-based management (EBM), including the value of a comprehensive public database that could serve as a repository for the numerous physical, chemical, and biological monitoring Great Lakes datasets that exist, a two-day workshop was organized, which was attended by 40+ Great Lakes researchers, managers, and stakeholders. While we learned during the workshop that EBM is not an explicit mission of many of the participating research, monitoring, and management agencies, most have been conducting research or monitoring activities that can support EBM. These contributions have ranged from single-resource (-sector) management to considering the ecosystem holistically in a decision-making framework. Workshop participants also identified impediments to implementing EBM, including: 1) high anticipated costs; 2) a lack of EBM success stories to garner agency buy-in; and 3) difficulty in establishing common objectives among groups with different mandates (e.g., water quality vs. fisheries production). We discussed as a group solutions to overcome these impediments, including construction of a comprehensive, research-ready database, a prototype of which was presented at the workshop. We collectively felt that such a database would offer a cost-effective means to support EBM approaches by facilitating research that could help identify useful ecosystem indicators and management targets and allow for management strategy evaluations that account for risk and uncertainty when contemplating future decision-making.
RESUMEN
Agent-based, spatially-explicit models that incorporate movement rules are used across ecological disciplines for a variety of applications. However, appropriate movement rules may be difficult to implement due to the complexity of an individual's response to both proximate and ultimate cues, as well as the difficulty in directly assessing how organisms choose to move across their environment. Environmental cues may be complex and dynamic, and therefore, movement responses may require tradeoffs between preferred levels of different environmental variables (e.g., temperature, light level, and prey availability). Here, we present an approach to determine appropriate movement rules by setting them as heritable traits in an eco-genetic modeling framework and allowing movement rules to evolve during the model rather than setting them a priori. We modeled yellow perch, Perca flavescens, movement in a simulated environment and allowed perch to move in response to high-resolution vertical gradients in temperature, dissolved oxygen, light, predators, and prey. Evolving movement rules ultimately increased fish growth and survival over generations in our model, indicating that evolving movement rules led to improved individual performance. We found that emergent movement rules were consistent across trials, with evolved movement rules incorporating different weights of these environmental factors and the most rapid selection on temperature preference. This case study presents a flexible method using eco-genetic modeling to determine appropriate movement rules that can be applied to diverse scenarios in spatially-explicit ecological modeling.
Asunto(s)
Ritmo Circadiano/genética , Ecosistema , Modelos Genéticos , Movimiento , Animales , Simulación por Computador , Percas/fisiologíaRESUMEN
Due to cultural eutrophication and global climate change, an exponential increase in the number and extent of hypoxic zones in marine and freshwater ecosystems has been observed in the last few decades. Hypoxia, or low dissolved oxygen (DO) concentrations, can produce strong negative ecological impacts and, therefore, is a management concern. We measured biomass and densities of Dreissena in Lake Erie, as well as bottom DO in 2014 using 19 high frequency data loggers distributed throughout the central basin to validate a three-dimensional hydrodynamic-ecological lake model. We found that a deep, offshore hypoxic zone was formed by early August, restricting the Dreissena population to shallow areas of the central basin. Deeper than 20 m, where bottom hypoxia routinely develops, only young of the year mussels were found in small numbers, indicating restricted recruitment and survival of young Dreissena. We suggest that monitoring Dreissena distribution can be an effective tool for mapping the extent and frequency of hypoxia in freshwater. In addition, our results suggest that an anticipated decrease in the spatial extent of hypoxia resulting from nutrient management has the potential to increase the spatial extent of profundal habitat in the central basin available for Dreissena expansion.
RESUMEN
It is well documented that the introduction of dreissenid bivalves in eutrophic lakes is usually associated with decreases in turbidity and total phosphorus concentrations in the water column, concomitant increases in water clarity, as well as other physical changes to habitat that may have cascading effects on other species in the invaded waterbody. In contrast, there is a paucity of data on the ecological ramifications of the elimination or decline of dreissenids due to pollution, bottom hypoxia, or other mechanisms. Using data collected by the U.S. Environmental Protection Agency Great Lakes National Program Office's Long-Term Biology and Water Quality Monitoring Programs, we analyzed the impacts of the hypoxia-induced declines in Dreissena densities in the central basin of Lake Erie on major water chemistry and physical parameters. Our analysis revealed that the decline in Dreissena density in the central basin was concomitant with a decrease in spring dissolved silica concentrations and an increase in total phosphorus and near bottom turbidity not seen in the western or eastern basins. In contrast, opposite patterns in water quality were observed in the eastern basin, which was characterized by a high and relatively stable Dreissena population. We are the first to report that dreissenid-related shifts in water quality of invaded waterbodies are reversible by documenting that the sharp decline of Dreissena in the central basin of Lake Erie was concomitant with a shift from clear to turbid water.
RESUMEN
To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.
RESUMEN
Nutrient loading from the Maumee River watershed is a significant reason for the harmful algal blooms (HABs) problem in Lake Erie. The nutrient loading from urban areas needs to be reduced with the installation of green infrastructure (GI) practices. The Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model was used to explore the influences of land use (LU) and climate change on water quantity and quality in Spy Run Creek watershed (SRCW) (part of Maumee River watershed), decide whether and where excess phosphorus loading existed, identify critical areas to understand where the greatest amount of runoff/pollutants originated, and optimally implement GI practices to obtain maximum environmental benefits with the lowest costs. Both LU/climate changes increased runoff/pollutants generated from the watershed. Areas with the highest runoff/pollutant amount per area, or critical areas, differed for various environmental concerns, land uses (LUs), and climates. Compared to optimization considering all areas, optimization conducted only in critical areas can provide similar cost-effective results with decreased computational time for low levels of runoff/pollutant reductions, but critical area optimization results were not as cost-effective for higher levels of runoff/pollutant reductions. Runoff/pollutants for 2011/2050 LUs/climates could be reduced to amounts of 2001 LU/climate by installation of GI practices with annual expenditures of $0.34 to $2.05 million. The optimization scenarios that were able to obtain the 2001 runoff level in 2011/2050, can also reduce all pollutants to 2001 levels in this watershed.