Public preferences of the Great Lakes Environment : a Lake Michigan pilot study

The Great Lakes watershed is home to over 40 million people, and the health of the Great Lakes ecosystem is vital to the overall economic, societal, and environmental health of the U.S. and Canada. However, environmental issues related to them are sometimes overlooked. Policymakers and the public face the challenges of balancing economic benefits with the need to conserve and/or replenish regional natural resources to ensure long term prosperity. From the literature review, nine critical stressors of ecological services were delineated, which include pollution and contamination, agricultural erosion, non-native species, degraded recreational resources, loss of wetlands habitat, climate change, risk of clean water shortage, vanishing sand dunes, and population overcrowding; this list was validated through a series of stakeholder discussions and focus groups in Grand Rapids. Focus groups were conducted in Grand Rapids to examine the awareness of, concern with, and willingness to expend resources on these stressors. Stressors that the respondents have direct contact with tend to be the most important. The focus group results show that concern related to pollution and contamination is much higher than for any of the other stressors. Low responses to climate change result in recommendations for outreach programs.

Patch selection by wintering white-tailed deer : consequences for eastern hemlock regeneration at local and landscape scales

Tsuga canadensis (eastern hemlock) is a highly shade-tolerant, late-successional, and long-lived conifer species found throughout eastern North America. It is most often found in pure or nearly pure stands, because highly acidic and nutrient poor forest floor conditions are thought to favor T. canadensis regeneration while simultaneously limiting the establishment of some hardwood species with greater nutrient requirements. Once a common species, T. canadensis is currently experiencing widescale declines across its range. The hemlock woolly adelgid (Adelges tsugae) is decimating the population across its eastern distribution. Across the Upper Great Lakes region, where the adelgid is currently being held at bay by cold winter temperatures, T. canadensis has been experiencing failures in regeneration attributed, in part, to herbivory by white-tailed deer (Odocoileus virginianus). Deer utilize T. canadensis stands as winter habitat in areas of high snow depth. Tsuga canadensis, once a major component of these forests, currently exists at just a fraction of its pre-settlement abundance due to historic logging and contemporary forest management practices, and what remains is found in small remnant patches surrounded by second- and third-growth deciduous forests. The deer population across the region, however, is likely double that of pre-European settlement times. In this dissertation I explore the relationship between white-tailed deer use of T. canadensis as winter habitat and the effect this use is having on regeneration and forest succession. For this research I quantified stand composition and structure and abiotic variables of elevation and snow depth in 39 randomly selected T. canadensis stands from across the western Upper Peninsula of Michigan. I also quantified composition and the configuration of the landscapes surrounding these stands. I measured relative deer use of T. canadensis stands as pellet group piles deposited in each stand during each of three consecutive winters, 2005-06, 2006-07, and 2007-08. The results of this research suggest that deer use of T. canadensis stands as winter habitat is influenced primarily by snow depth, elevation, and the composition and configuration of the greater landscapes surrounding these stands. Specifically, stands with more heterogeneous landscapes surrounding them (i.e., a patchy mosaic of conifer, deciduous, and open cover) had higher relative deer use than stands surrounded by homogenous deciduous forest cover. Additionally, the intensity of use and the number of stands used was greater in years with higher average snow depth. Tsuga canadensis regeneration in these stands was negatively associated with deer use and Acer saccharum (sugar maple) basal area. Of the 39 stands, 17 and 22 stands had no T. canadensis regeneration in small and large sapling categories, respectively. Acer saccharum was the most common understory tree species, and the importance of A. saccharum in the understory (stems < 10 cm dbh) of the stands was positively associated with overstory A. saccharum dominance. Tsuga canadensis establishment was associated with high-decay coarse woody debris and moss, and deciduous leaf litter inputs in these stands may be limiting access to these important microsites. Furthermore, A. saccharum is more tolerant to the effects of deer herbivory than T. canadensis, giving A. saccharum a competitive advantage in stands being utilized as winter habitat by deer. My research suggests that limited microsite availability, in conjunction with deer herbivory, may be leading to an erosion in T. canadensis patch stability and an altered successional trajectory toward one of A. saccharum dominance, an alternately stable climax species.

Open top chambers and infrared lamps : a comparison of heating efficacy and CO₂/CH₄ dynamics in a Lake Superior coastal peatland

Experimental warming provides a method to determine how an ecosystem will respond to increased temperatures. Northern peatland ecosystems, sensitive to changing climates, provide an excellent setting for experimental warming. Storing great quantities of carbon, northern peatlands play a critical role in regulating global temperatures. Two of the most common methods of experimental warming include open top chambers (OTCs) and infrared (IR) lamps. These warming systems have been used in many ecosystems throughout the world, yet their efficacy to create a warmer environment is variable and has not been widely studied. To date, there has not been a direct, experimentally controlled comparison of OTCs and IR lamps. As a result, a factorial study was implemented to compare the warming efficacy of OTCs and IR lamps and to examine the resulting carbon dioxide (CO2) and methane (CH4) flux rates in a Lake Superior peatland. IR lamps warmed the ecosystem on average by 1-2 #°C, with the majority of warming occurring during nighttime hours. OTC's did not provide any long-term warming above control plots, which is contrary to similar OTC studies at high latitudes. By investigating diurnal heating patterns and micrometeorological variables, we were able to conclude that OTCs were not achieving strong daytime heating peaks and were often cooler than control plots during nighttime hours. Temperate day-length, cloudy and humid conditions, and latent heat loss were factors that inhibited OTC warming. There were no changes in CO2 flux between warming treatments in lawn plots. Gross ecosystem production was significantly greater in IR lamp-hummock plots, while ecosystem respiration was not affected. CH4 flux was not significantly affected by warming treatment. Minimal daytime heating differences, high ambient temperatures, decay resistant substrate, as well as other factors suppressed significant gas flux responses from warming treatments.

Mechanisms contributing to the deep chlorophyll maximum in Lake Superior

The seasonal appearance of a deep chlorophyll maximum (DCM) in Lake Superior is a striking phenomenon that is widely observed; however its mechanisms of formation and maintenance are not well understood. As this phenomenon may be the reflection of an ecological driver, or a driver itself, a lack of understanding its driving forces limits the ability to accurately predict and manage changes in this ecosystem. Key mechanisms generally associated with DCM dynamics (i.e. ecological, physiological and physical phenomena) are examined individually and in concert to establish their role. First the prevailing paradigm, “the DCM is a great place to live”, is analyzed through an integration of the results of laboratory experiments and field measurements. The analysis indicates that growth at this depth is severely restricted and thus not able to explain the full magnitude of this phenomenon. Additional contributing mechanisms like photoadaptation, settling and grazing are reviewed with a one-dimensional mathematical model of chlorophyll and particulate organic carbon. Settling has the strongest impact on the formation and maintenance of the DCM, transporting biomass to the metalimnion and resulting in the accumulation of algae, i.e. a peak in the particulate organic carbon profile. Subsequently, shade adaptation becomes manifest as a chlorophyll maximum deeper in the water column where light conditions particularly favor the process. Shade adaptation mediates the magnitude, shape and vertical position of the chlorophyll peak. Growth at DCM depth shows only a marginal contribution, while grazing has an adverse effect on the extent of the DCM. The observed separation of the carbon biomass and chlorophyll maximum should caution scientists to equate the DCM with a large nutrient pool that is available to higher trophic levels. The ecological significance of the DCM should not be separated from the underlying carbon dynamics. When evaluated in its entirety, the DCM becomes the projected image of a structure that remains elusive to measure but represents the foundation of all higher trophic levels. These results also offer guidance in examine ecosystem perturbations such as climate change. For example, warming would be expected to prolong the period of thermal stratification, extending the late summer period of suboptimal (phosphorus-limited) growth and attendant transport of phytoplankton to the metalimnion. This reduction in epilimnetic algal production would decrease the supply of algae to the metalimnion, possibly reducing the supply of prey to the grazer community. This work demonstrates the value of modeling to challenge and advance our understanding of ecosystem dynamics, steps vital to reliable testing of management alternatives.

Critical evaluation of diameter increment modelling in the Great Lakes region

Simulations of forest stand dynamics in a modelling framework including Forest Vegetation Simulator (FVS) are diameter driven, thus the diameter or basal area increment model needs a special attention. This dissertation critically evaluates diameter or basal area increment models and modelling approaches in the context of the Great Lakes region of the United States and Canada. A set of related studies are presented that critically evaluate the sub-model for change in individual tree basal diameter used in the Forest Vegetation Simulator (FVS), a dominant forestry model in the Great Lakes region. Various historical implementations of the STEMS (Stand and Tree Evaluation and Modeling System) family of diameter increment models, including the current public release of the Lake States variant of FVS (LS-FVS), were tested for the 30 most common tree species using data from the Michigan Forest Inventory and Analysis (FIA) program. The results showed that current public release of the LS-FVS diameter increment model over-predicts 10-year diameter increment by 17% on average. Also the study affirms that a simple adjustment factor as a function of a single predictor, dbh (diameter at breast height) used in the past versions, provides an inadequate correction of model prediction bias. In order to re-engineer the basal diameter increment model, the historical, conceptual and philosophical differences among the individual tree increment model families and their modelling approaches were analyzed and discussed. Two underlying conceptual approaches toward diameter or basal area increment modelling have been often used: the potential-modifier (POTMOD) and composite (COMP) approaches, which are exemplified by the STEMS/TWIGS and Prognosis models, respectively. It is argued that both approaches essentially use a similar base function and neither is conceptually different from a biological perspective, even though they look different in their model forms. No matter what modelling approach is used, the base function is the foundation of an increment model. Two base functions – gamma and Box-Lucas – were identified as candidate base functions for forestry applications. The results of a comparative analysis of empirical fits showed that quality of fit is essentially similar, and both are sufficiently detailed and flexible for forestry applications. The choice of either base function in order to model diameter or basal area increment is dependent upon personal preference; however, the gamma base function may be preferred over the Box-Lucas, as it fits the periodic increment data in both a linear and nonlinear composite model form. Finally, the utility of site index as a predictor variable has been criticized, as it has been widely used in models for complex, mixed species forest stands though not well suited for this purpose. An alternative to site index in an increment model was explored, using site index and a combination of climate variables and Forest Ecosystem Classification (FEC) ecosites and data from the Province of Ontario, Canada. The results showed that a combination of climate and FEC ecosites variables can replace site index in the diameter increment model.

Applications of LiDAR remote sensing of forest structure in the Upper Great Lakes region, USA

We used active remote sensing technology to characterize forest structure in a northern temperate forest on a landscape- and local-level in the Upper Peninsula of Michigan. Specifically, we used a form of active remote sensing called light detection and ranging (e.g., LiDAR) to aid in the depiction of current forest structural stages and total canopy gap area estimation. On a landscape-level, LiDAR data are shown not only to be a useful tool in characterizing forest structure, in both coniferous and deciduous forest cover types, but also as an effective basis for data-driven surrogates for classification of forest structure. On a local-level, LiDAR data are shown to be a benchmark reference point to evaluate field-based canopy gap area estimations, due to the highly accurate nature of such remotely sensed data. The application of LiDAR remote sensed data can help facilitate current and future sustainable forest management.

INTEGRATED ASSESSMENT OF ANTHROPOGENIC, CLIMATE, AND POLICY INDUCED CHANGES OF PHOSPHORUS EXPORT IN THE UNITED STATES LAURENTIAN GREAT LAKES WATERSHEDS

Anthropogenic activities have increased phosphorus (P) loading in tributaries to the Laurentian Great Lakes resulting in eutrophication in small bays to most notably, Lake Erie. Changes to surface water quality from P loading have resulted in billions of dollars in damage and threaten the health of the world’s largest freshwater resource. To understand the factors affecting P delivery with projected increasing urban lands and biofuels expansion, two spatially explicit models were coupled. The coupled models predict that the majority of the basin will experience a significant increase in urban area P sources while the agriculture intensity and forest sources of P will decrease. Changes in P loading across the basin will be highly variable spatially. Additionally, the impacts of climate change on high precipitation events across the Great Lakes were examined. Using historical regression relationships on phosphorus concentrations, key Great Lakes tributaries were found to have future changes including decreasing total loads and increases to high-flow loading events. The urbanized Cuyahoga watersheds exhibits the most vulnerability to these climate-induced changes with increases in total loading and storm loading , while the forested Au Sable watershed exhibits greater resilience. Finally, the monitoring network currently in place for sampling the amount of phosphorus entering the U.S. Great Lakes was examined with a focus on the challenges to monitoring. Based on these interviews, the research identified three issues that policy makers interested in maintaining an effective phosphorus monitoring network in the Great Lakes should consider: first, that the policy objectives driving different monitoring programs vary, which results in different patterns of sampling design and frequency; second, that these differences complicate efforts to encourage collaboration; and third, that methods of funding sampling programs vary from agency to agency, further complicating efforts to generate sufficient long-term data to improve our understanding of phosphorus into the Great Lakes. The dissertation combines these three areas of research to present the potential future impacts of P loading in the Great Lakes as anthropogenic activities, climate and monitoring changes. These manuscripts report new experimental data for future sources, loading and climate impacts on phosphorus.

Study of particle movement in the nearshore region of Lake Superior with radioisotope tracers

Biogeochemical processes in the coastal region, including the coastal area of the Great Lakes, are of great importance due to the complex physical, chemical and biological characteristics that differ from those on either the adjoining land or open water systems. Particle-reactive radioisotopes, both naturally occurring (210Pb, 210Po and 7Be) and man-made (137Cs), have proven to be useful tracers for these processes in many systems. However, a systematic isotope study on the northwest coast of the Keweenaw Peninsula in Lake Superior has not yet been performed. In this dissertation research, field sampling, laboratory measurements and numerical modeling were conducted to understand the biogeochemistry of the radioisotope tracers and some particulate-related coastal processes. In the first part of the dissertation, radioisotope activities of 210Po and 210Pb in a variability of samples (dissolved, suspended particle, sediment trap materials, surficial sediment) were measured. A completed picture of the distribution and disequilibrium of this pair of isotopes was drawn. The application of a simple box model utilizing these field observations reveals short isotope residence times in the water column and a significant contribution of sediment resuspension (for both particles and isotopes). The results imply a highly dynamic coastal region. In the second part of this dissertation, this conclusion is examined further. Based on intensive sediment coring, the spatial distribution of isotope inventories (mainly 210Pb, 137Cs and 7Be) in the nearshore region was determined. Isotope-based focusing factors categorized most of the sampling sites as non- or temporary depositional zones. A twodimensional steady-state box-in-series model was developed and applied to individual transects with the 210Pb inventories as model input. The modeling framework included both water column and upper sediments down to the depth of unsupported 210Pb penetration. The model was used to predict isotope residence times and cross-margin fluxes of sediments and isotopes at different locations along each transect. The time scale for sediment focusing from the nearshore to offshore regions of the transect was on the order of 10 years. The possibility of sediment longshore movement was indicated by high inventory ratios of 137Cs: 210Pb. Local deposition of fine particles, including fresh organic carbon, may explain the observed distribution of benthic organisms such as Diporeia. In the last part of this dissertation, isotope tracers, 210Pb and 210Po, were coupled into a hydrodynamic model for Lake Superior. The model was modified from an existing 2-D finite difference physical-biological model which has previously been successfully applied on Lake Superior. Using the field results from part one of this dissertation as initial conditions, the model was used to predict the isotope distribution in the water column; reasonable results were achieved. The modeling experiments demonstrated the potential for using a hydrodynamic model to study radioisotope biogeochemistry in the lake, although further refinements are necessary.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

SYSTEM DYNAMICS MODELING AS A QUANTITATIVE-QUALITATIVE FRAMEWORK FOR SUSTAINABLE WATER RESOURCES MANAGEMENT: INSIGHTS FOR WATER QUALITY POLICY IN THE GREAT LAKES REGION

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

FACTORS AFFECTING DIPOREIA GROWTH RATES IN LAKE SUPERIOR

An ability to predict population dynamics of the amphipod Diporeia is important in understanding how energy pathways in the Lake Superior food web might be altered by disturbances to the ecosystem. Estimating growth rates for this prominent prey item for fish requires information on the physiological effects of changes to its environment. These effects have been investigated for Diporeia in other Great Lakes, but little is known about Lake Superior populations. The primary objective of this study is to obtain quantitative data for rates of Diporeia respiration and consumption that can be incorporated into a bioenergetics model for Lake Superior. Benthic communities in Lake Superior were sampled bimonthly from April through September during 2011 and 2012 to investigate spatial and temporal trends of Diporeia abundances as well as size class structures of the population. Additional samples of Diporeia were collected and kept alive in natural sediment for laboratory experiments. Respiration rates for Diporeia were measured by monitoring dissolved oxygen concentrations in microcosoms using microelectrodes. Additionally, a series of experiments to estimate consumption rates based on food availability were conducted using 14C-labeled algae (Selenastrum capricornutum). Amphipod population densities are highest between 30-110 m (slope) compared to 0-30 m (shelf) or >110 m (profundal) regions in Lake Superior. This heterogeneous distribution of Diporeia in Lake Superior is an important component to quantifying lake-wide biomass. Rates of oxygen consumption by Diporeia range from 32.0 to 44.7 mgO2*gDW-1*d-1, and do not vary significantly with body size per individual. The predicted consumption rate corresponding to average Lake Superior algal carbon fluxes was 0.08 ± SE mgC*gDW-1*d-1. Data on Lake Superior Diporeia biomass and bioenergetics found in this study can be incorporated in a model used to estimate the viability of this population under potential future environmental stressors.

Development of measurement and modeling techniques to quantify atmospheric deposition of persistent, bioaccumulative and toxic chemicals in the Great Lakes

Measurement and modeling techniques were developed to improve over-water gaseous air-water exchange measurements for persistent bioaccumulative and toxic chemicals (PBTs). Analytical methods were applied to atmospheric measurements of hexachlorobenzene (HCB), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs). Additionally, the sampling and analytical methods are well suited to study semivolatile organic compounds (SOCs) in air with applications related to secondary organic aerosol formation, urban, and indoor air quality. A novel gas-phase cleanup method is described for use with thermal desorption methods for analysis of atmospheric SOCs using multicapillary denuders. The cleanup selectively removed hydrogen-bonding chemicals from samples, including much of the background matrix of oxidized organic compounds in ambient air, and thereby improved precision and method detection limits for nonpolar analytes. A model is presented that predicts gas collection efficiency and particle collection artifact for SOCs in multicapillary denuders using polydimethylsiloxane (PDMS) sorbent. An approach is presented to estimate the equilibrium PDMS-gas partition coefficient (Kpdms) from an Abraham solvation parameter model for any SOC. A high flow rate (300 L min-1) multicapillary denuder was designed for measurement of trace atmospheric SOCs. Overall method precision and detection limits were determined using field duplicates and compared to the conventional high-volume sampler method. The high-flow denuder is an alternative to high-volume or passive samplers when separation of gas and particle-associated SOCs upstream of a filter and short sample collection time are advantageous. A Lagrangian internal boundary layer transport exchange (IBLTE) Model is described. The model predicts the near-surface variation in several quantities with fetch in coastal, offshore flow: 1) modification in potential temperature and gas mixing ratio, 2) surface fluxes of sensible heat, water vapor, and trace gases using the NOAA COARE Bulk Algorithm and Gas Transfer Model, 3) vertical gradients in potential temperature and mixing ratio. The model was applied to interpret micrometeorological measurements of air-water exchange flux of HCB and several PCB congeners in Lake Superior. The IBLTE Model can be applied to any scalar, including water vapor, carbon dioxide, dimethyl sulfide, and other scalar quantities of interest with respect to hydrology, climate, and ecosystem science.