Lake Ontario Biocomplexity Project Research Areas

Research Areas

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Research Areas by Discipline:

Applied mathematics (Pasour)
Aquatic macroinvertebrates (Bain)
Aquatic macrophytes (Johnson)
Ecosystem properties/processes (Bain)
Fish (Arend, Bain, Singkran)
Food web dynamics (Arend)
Forest ecology (Leopold)
Hydrodynamics (Cowen, King, Pasour, Tanaka)
Hydrology (Cowen, Driscoll, Loucks)
Landscape ecology (Gamarra)
Land use change (Abrams, Buck, Morad, Pendall, Wei)
Models: agent-based (Odekon, Pendall, Wei)
Models: ecological, complex systems (Ellner, Gamarra, Pasour, Variano)
Phytoplankton (Doyle-Morin, Hairston)
Turtles (Kaleta)
Water chemistry, water quality (Chen, Driscoll)
Wetland ecology (Distler, Hajek, Hotaling, Kelsall, Leopold)
Zooplankton (Doyle-Morin, Hairston)

Research Areas by Individual:

Joshua Abrams
Kristin Arend
Mark Bain
Crystal Buck
Edwin A. Cowen
Matt Distler
Rebecca Doyle-Morin
Charles Driscoll
Stephen Ellner
Nelson Hairston Jr.
Nicole Hotaling
Robert Johnson
Jenn Kaleta
Nathan Kelsall
Alexandra King
Donald Leopold
Daniel P. Loucks
Virginia Pasour
Rolf Pendall
Nuanchan Singkran
Evan Variano

Joshua Abrams

From Here to There: Building a Regional Movement

Research will involve conducting a series of case studies that look at how actors become motivated to advocate for policy changes in a given community. In particular, the case study will look at three rural communities along the shore of Lake Ontario. In one community, Sodus Point (Sodus Bay) the impetus for change came from a local group. In a second Fairhaven (Little Sodus Bay) the state forced change to happen. In the third, yet to be identified, no actors were vocal in supporting change despite significant environmental problems. Alternatively, the third case study might have both active local and nonlocal actors. These cases are interesting to examine together because actors are showing different responses to similar problems. This cross-comparison will offer us greater insight into the subtleties that encourage or prevent action. This information will also be used in an agent based model that looks at how humans affect water quality and how that water quality affects human decisions.

Kristin Arend
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Importance of variability in local environmental characteristics to aquatic food web structure and dynamics

Research Objectives
The goal of my dissertation research is to explore how environmental characteristics of coastal embayment ecosystems constrain fish community food web structure and function. Coastal embayments are important because they are located at the interface of the watershed and lake and, thus, process and transform watershed-derived nutrients and energy before these materials reach the lake ecosystem. The embayments were selected to vary in physical characteristics such as morphometry and hydrologic connectedness to the watershed. Consequently, these embayments differ in the ratio of pelagic (deep, open-water) to littoral (shallow, usually vegetated) habitat and productivity (e.g., nutrient concentrations). Fish community composition is similar among these embayments, but population size structure and relative abundance varies. The objectives of my research are to combine empirical and modeling approaches to:

Compare fish and prey communities among all eight embayments, and identify correlations between community and environmental characteristics.
Identify food web structure and energy flow in four of the eight embayments.
Identify possible mechanisms underlying effects of food web attributes on fish population relative abundance and size structure.

I hypothesize that observed differences in fish populations reflect constraints of embayment physical characteristics on food web structure and function. More specifically, I anticipate:

The relative amount of benthic and pelagic habitat will determine the amount of material derived from and exchanged between each habitat through food web processes.
Utilization of watershed nutrient and energy inputs to the embayment will increase with hydrologic connectedness to the watershed.
Internal and external energy exchange and nutrient availability in each embayment will influence resource availability to the fish food web.
Resource availability will affect relative abundance and size structure of fish populations through fish growth and predator-prey interactions.

Research findings to date
Fish and benthic invertebrate communities
Fish were collected from all eight embayments using an electrofishing boat during the summers 2001-2003. These data show that fish community composition is similar, but individual species’ population size structure and relative abundance differ. Of 40 species identified across all embayments, 10 species dominated fish community abundance and biomass. Of these species, yellow perch constituted 15-71% (mean 41%) of catch per unit effort in the embayments. Benthic invertebrates were collected from all 8 embayments in 2002 and 2003, and from Sterling, South Colwell, Little Sodus, and South Sandy in 2004 to assess community composition and population relative abundance. Preliminary data suggest differences in benthic invertebrate taxonomic composition and relative abundance among embayments.

Food web structure and energy flow
To intensively study food web structure and energy flow, I have selected to focus on Sterling, South Colwell, Little Sodus, and South Sandy, because they vary in the ratio of littoral:pelagic habitat and watershed inputs. During June and July 2003-2004, up to 30 individuals from the 10 most dominant fish species were collected or processed on site to obtain stomach contents and dorsal muscle tissue samples. During summer 2004, I collected biweekly samples of zooplankton, phytoplankton and periphyton, and monthly samples of benthic invertebrates and macrophyte tissue for stable isotope analysis. Fish stomach contents have been identified and will be used to assign predator-prey relationships in each embayment. Stable isotope analysis of 15N and 13C in the animal and plant tissue is currently underway to identify fish trophic position in the food web (e.g., primary consumer, secondary consumer, etc.) and relative assimilation of benthic and pelagic energy sources, respectively. Preliminary analysis of fish stable isotope ratios suggests that multiple energy sources were incorporated into the Sterling and South Colwell food webs, which likely indicate contributions from benthic and pelagic energy sources (including adjacent wetlands). Only one source, likely planktonic, was incorporated into the South Sandy and Little Sodus food webs. I plan to complete analyses of the remaining fish, invertebrate, algal, and vascular plant samples by December 2005.

Future Work
I have begun to work on an energy budget model for yellow perch, to explore how differences in food web structure (i.e., prey availability and bioenergetics and predation pressure) may result in our observed differences in yellow perch population relative abundance and size structure. I have chosen to focus on yellow perch because they are the dominant fish species, numerically, in most of the study embayments and thus largely determine total fish relative abundance and size structure.

Updated 10/05

Mark Bain
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Pelagic Fishes and Ichthyoplankton

Fish occupying the open water zone of embayments have a high potential to interact with other pelagic food web components, especially through direct effects of zooplankton grazing. As reported for many lentic habitats (Carpenter and Kitchell 1993; Carpenter et al. 1996), the top down effects of piscivorous and planktivorous fishes on lower trophic groups can be pronounced, but we expect such effects to be highly transient in our study waters. Juveniles and adults of open water fishes are mobile and they may enter bay waters from Lake Ontario for short time periods to access available foods, reproductive habitats, or preferred environmental conditions such as specific temperatures. Resident pelagic fishes could have the same effects on pelagic food webs but we would expect such influences to be less variable through time. Larval fish that comprise the ichthyoplankton can also have a strong effect on zooplankton, but these weak swimming fish are commonly distributed by currents. Their appearance is also likely to be sporadic in time and largely related to spawning periods. Using the well documented fish life history data for the Great lakes region (Herdendorf et al. 1981a, b, c), we will be able to confidently determine the source of transient and larval fishes without monitoring all nearby Lake Ontario and stream habitats. We will sample the open water zone of the study sites during summer on the same sampling schedule described above in this section. Multipanel gills nets will be set overnight and during the day to correspond with plankton sampling. Plankton net (505 µm mesh, 0.5 m diameter) tows will be made to capture larval fish, and this sampling will again be paired to plankton samples. Final data series will be the relative (catch per effort) abundance by species, size group, and trophic class for all fish inhabiting open water habitats of the study embayments.

Littoral Fish Fauna
We expect our bay and lagoon study sites could support most of the species found in the Lake Ontario system. Jude and Pappas (1992) contrasted the fish fauna of nine wetland and bay habitats with the open waters of the five Great Lakes. Of the 113 fish species recorded, most (82 species) were either opportunistic (35) or obligate (47) occupants of embayment and wetland habitats. The wetland species were split into two main groups: permanent residents (e.g., brown bullhead Ictalurus nebulosus, mudminnow Umbra lima, longnose gar Lepisosteus osseus) and migratory species. Migratory species included three subgroups: (1) those that spawned in the wetlands and then left (e.g., northern pike Esox lucius, common carp Cyprinus carpio, white sucker Catostomus commersoni, walleye Stizostedion vitreum ), (2) those that used the wetlands as a nursery area (e.g., gizzard shad Dorosoma cepedianum, spottail shiner Notropis hudsonius), and (3) those that migrated into the wetland from other wetlands or a Great Lake for shelter, spawning sites, food, and dispersal of young. Degradation of shallow water habitats by vegetation clearing, dredging, and shoreline breakwall construction reduces the diversity and abundance of fishes leaving local assemblages dominated by habitat generalists and turbidity-tolerant species (Brazner 1997). Finally, fish production has been found to be positively related to the mechanical energy in a habitat (Nixon 1988; Randall et al. 1995), although at very high levels, production would likely be reduced.

Sampling in littoral and wetland habitats will be conducted to obtain a complete assessment of study site species, relative abundances, and size structure. This sampling will be conducted on a 3-season basis to record regular changes in species using embayments for spawning, thermal conditions, and prey. Gill nets, electrofishing, and fish traps will be used in vegetated, shallow water habitats. This combination of gears should yield comprehensive fish faunal data when combined with open water sampling (Knight and Bain 1996).

Crystal Buck

Changes in Agriculture in the Lake Ontario Biocomplexity Study Sites

Based on my research questions pertaining to trends in agriculture I propose the following objectives for the upcoming semester/year:

Question 1: Are farms getting larger? Method:

Using tax parcel data (1996-2001), aggregate parcels according to owner (to account for dispersed parcels owned by the same person).
Identify trends in the size of holdings over time for agriculture properties.
Using the digitized land coverage data for the past 50 years, track the size of agriculture digitized polygons over time. This obviously won’t reflect land ownership, but it may indicate something about field size, crop diversity, and agriculture segmentation. This method needs to be explored further in terms of what the historic digitized data can actually show.

Question 2: What are the potential impacts of the trends in farms size on the watershed? Method:

Conduct a literature review on the impacts of varying sizes of farms on the environment in general and watershed in particular. (See Appendix B for literature list).
Explore the possibility of expanding on the research done by Driscoll and Whitall for the Biocomplexity project on the relationship between Potassium levels as a function of percent of agriculture land use in sampling areas. Specifically, it would be interesting to look at Potassium levels as a function of size and type of agriculture in the sampling areas.

Question 3: What is happening to farms that are unsuccessful? How does success relate to the size of the farm? Method:

Using the sales data, identify agriculture properties that were sold and track the property classification of these properties following the transactions. If the properties remain in agriculture, identify the size of agriculture holdings for the new owner and compare to the size of agriculture holdings for the previous owner.
Using the sales data and the tax parcel data, identify agriculture properties that became vacant or abandoned agriculture properties and properties that became residential. Identify the average size of agriculture parcels that became residential or vacant and compare to the average size of agriculture parcels that remained in agriculture. Determine whether parcels were part of larger holdings and compare size of holding for parcels that became residential or vacant to size of holding for remaining agriculture parcels.

Edwin A. Cowen
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Embayment Hydrodynamics

We hypothesize that internal hydrodynamics play a critical role in local ecological processes, and that the internal hydrodynamics will be to an unknown extent a product of inflowing stream waters and Lake Ontario water levels. Some anticipated internal linkages include water residence time, water clarity through sediment suspension and resuspension, nutrient fluxes to biota, and the relation between bathymetry and water surface elevation. Hydrodynamic linkages extend to and from the physical processes. For example, the biota modify sediment deposition and resuspension rates, and aquatic plants alter water flow conditions and turbulence (Nepf 1999). We intend to develop and use a validated computational model of each study system to test these expectations and include hydrodynamic information with analyses of exogenous variables.

The kernel of the computations will be a hydrodynamic model capable of resolving, in space and time, the velocity and density structure of a water body due to water level variations and dynamically evolving bathymetry. Based on an initial survey of available models, we presently intend to use the unstructured-grid, three-dimensional, shallow water wave equation model recently developed by Casulli and Walters (2000). This model, which has been made available to us, is computationally efficient, allows for variable free-surface heights, wetting and drying of the shore, stream and groundwater flow inputs, as well as unstructured grids. This latter capability is seen as a great advantage in studying water body hydrodynamics as the basin shapes can be much better approximated reducing grid effects on the computation results. Notably the model can be relaxed to a depth integrated two-dimensional model or a standard Cartesian grid-based model should the local environment suggest these simplifications be warranted. Initially the hydrodynamic model will handle the turbulence based on an eddy viscosity approach (Casulli and Walters 2000). When the full model is functioning, the eddy viscosity model will be upgraded to a k –E / algebraic stress model (Rodi 1993), similar to versions currently running for free-surface flows at Cornell (e.g., Lin and Liu 1998). This will allow spatially and temporally variable non-isotropic eddy viscosities that are a function of the wind speed, stratification, velocity, and macrophyte community (Nepf 1999).

The hydrodynamic model will take as inputs the tributary and groundwater flows from the watershed hydrologic simulation model, and allow thermal and wind forced exchange with Lake Ontario. For the particular case of the exchange through permeable sand and gravel shorelines the hydrodynamic model will be coupled to a groundwater flow model that solves for Darcy’s flow making the Dupuit approximation (an analogy to the shallow water approximation in surface water flows; Marsily 1986). Again we will take advantage of an existing model for which we can obtain the source code. The porous media model of Liu and Wen (1997) has been made available to us and is a likely candidate.

Transport equations will be coupled to the water quality data series (see above water quality section) to track the fate of parameters of interest (suspended solids, total phosphorus, total nitrogen, dissolved organic carbon, dissolved oxygen and others). A significant effort will be put forth to understand the cycle of these parameters within the three intensively studied embayments and the cycles will set the number of necessary transport equations. Gross et al. (1999) performed a detailed study of various explicit advection schemes for estuarine salinity transport, which will be taken as a starting point for handling the advection terms for transport.

Hydrodynamic model development will require that a parallel research effort be made in the field to calibrate and verify the model with sound data sets. These data sets will include water velocity information (both mean and turbulent), wind records (interpolated into the hydrodynamic model, Ludwig 1998), temperature structure, suspended sediment and measurements of the POI. We plan on simultaneously monitoring turbidity, wind velocity, free-surface position, and thermal structure to gain insight into the role of surface and internal waves in sediment and nutrient resuspension and their proper parameterization into the model. We will also need to account for the effect of the macrophyte community on flow physics. Nepf (1999) presents models of the physical effects of vegetation on flow (e.g., turbulence generation, drag, diffusivity). We will couple the hydrodynamic model to macrophyte growth and abundance data (below), and proper linking will require use of the hydrodynamic model to assess site favorability for macrophyte growth. Other internal relations will likely need similar integration, and these efforts will yield data for analyses with exogenous variables.

Rebecca Doyle-Morin
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Plankton communities, spatial and temporal scales in embayments. Download a PowerPoint poster about Becky's work.

Matt Distler
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My dissertation work investigates the long-term development of wetlands associated with the Biocomplexity Project study sites and nearby coastal embayments. Through analysis of plant macrofossils in peat cores, I am investigating the long-term stability and variability of wetland plant communities and the role of major disturbances such as fire and flooding in their development. One of the major changes observed in coastal wetlands of Lake Ontario in the last century is the rapid expansion of Typha x glauca (cattail) into formerly diverse graminoid-shrub fen. My research will focus on the long-term and short-term history of Typha dominance in different landscape positions within these wetlands using paleoecological methods and assessment of historical aerial photos. To better characterize the significance of Great Lakes setting and processes on community development, developmental histories and modern flora will be compared between areas of diverse coastal fen and nearby inland fens that are not affected by Great Lakes hydrology.

Major Paleoecological Hypotheses:
1) Historical maintenance of diverse fen communities in coastal wetlands and inland fens historically depended on the stressing effect of low nutrient levels in fens; increased nutrient levels associated with European settlement have allowed much faster expansion of Typha stands in response to periodically favorable hydrologic conditions. Periods of major Typha expansion will be absent from the peat record.
2) Fires during low water level periods have also played a part in maintaining open inland and coastal fens over time.

Field work at two biocomplexity sites, South Sandy Pond and North Sandy Pond, has been aimed at description of modern wetland vegetation, its diversity, and the expansion and ecological effects of Typha in parts of these wetlands. Data from these sites comprise part of a larger dataset aimed at comparing physical, chemical, and vegetative characteristics of four coastal wetlands and four inland wetlands in Oswego County. Data analysis is ongoing for this portion of the project.

Major Hypotheses related to field studies:
1) Typha x glauca growth is associated with increased mineral sedimentation and nutrient enrichment in marginal stream or pond-side areas of coastal fens.
2) Typha-dominated areas (including those recently invaded by Typha) have lower plant species richness and diversity as compared to open graminoid-shrub fen.

To date, we have finished preliminary plant macrofossil analysis of a 7-meter peat core from the deepest area of the peatland at South Sandy Pond and the top meter of a 5 meter peat core from Juniper Pond wetland.
The complete core sequence from South Sandy pond shows a progression from mineral-rich forested wetland characterized by yellow birch (Betula alleghaniensis) and eastern hemlock (Tsuga canadensis) to an alder (Alnus rugosa)-dominated community to a relatively mineral-poor medium fen dominated by (Carex spp.), leatherleaf (Chamaedaphne calyculata), and sweetgale (Myrica gale). Fire appears to have been a relatively common disturbance at South Sandy Pond, especially in the later half of the peatland’s development, and may have contributed to the maintenance of higher water levels and open shrub-graminoid fen.
The first meter of the Juniper Pond core shows a continuous history of shrub dominance, but a change in the species composition suggesting an increase in wetness and minerotrophy in its more recent developmental history. Sand layers in the peat core imply that barrier dune blowouts may be an important disturbance affecting the composition and succession of the wetland plant community at Juniper Pond.
Field investigations show that both open and forested portions of coastal (and inland) fens are diverse and harbor a number of rare species. Areas of Typha latifolia are equally or more diverse than other portions of these fens, but areas invaded by Typha x glauca are significantly less diverse and species-rich.

Updated 11/05

Charles Driscoll
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Water Quality, Water Chemistry

The investigation of water quality dynamics is a critical component of this proposed study. Water quality data will be used to verify results obtained from the watershed simulation modeling system and provide information critical to interpret patterns of phytoplankton, macrophytes, and fish. Investigators have repeatedly demonstrated that mean depth and hydraulic residence time are critical controllers of the retention and loss of materials entering ponded waters (Vollenweider et al. 1969; Dillon and Rigler 1974; Kelly et al. 1987). The loading of nutrients, and subsequent deposition and mineralization of organic carbon have important implications for the oxygen and redox status of embayments.

We will use a mass balance approach to assess the role of watershed loading and hydraulic residence time in the control of water quality of Lake Ontario embayments. Water quality samples will be collected biweekly at the three intensive study embayments and at three-week intervals in the five less intensively studied embayments. For each embayment, samples will be collected at the inlet stream or adjacent to extensive wetlands when streams are absent, at the central deep water station, and in or near the embayment connection with Lake Ontario. Samples will be analyzed for suspended solids, total phosphorus, total dissolved phosphorus, soluble reactive phosphorus, total nitrogen, ammonium and nitrate, and dissolved organic carbon and oxygen using standard methods. At the deep water station, water column profiles will be measured in situ for temperature, suspended solids, turbidity, and dissolved oxygen. In addition to the above analyses, water column depth samples at the intensive study embayments will be analyzed for the redox solutes, including sulfate, sulfide, ferrous iron, manganese, dissolved inorganic carbon and methane. Triplicate sediment traps (Rosa et al. 1991) will be deployed immediately below the thermocline at the intensive study embayments and depositing material will be collected at two week intervals during summer stratification. Depositing material will be analyzed for total organic carbon, total nitrogen and total phosphorus.

With the data collected from this field program, mass balance will be calculated for each of the embayments for suspended solids, and forms of phosphorus and nitrogen. We will use the watershed hydrologic simulation model and bay hydrodynamic model to determine water budgets for the embayment. Water budgets will be used with field water quality data to calculate mass balances. For the three intensive study embayments, hypolimnetic carbon, nitrogen, phosphorus and electron budgets will be developed for the summer stratification period. Water column profiles will be used to calculate sediment release and consumption of solutes within the hypolimnion. The hydrodynamic model will be used to estimate cross thermocline (diapycnal) mixing. Using the approach of Caraco et al. (1991), we will investigate controls on sediment release of phosphorus. Through the development of electron budgets, we will quantify the rate of organic matter mineralization and specific electron acceptors mediating this process (Mattson and Likens 1993). We envision that watershed loading, and mean depth and hydraulic residence time of the embayments will be critical determinants of nutrient deposition and export to Lake Ontario.

Stephen Ellner
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Integrated Analyses

Identifying the importance of exogenous variables for system dynamics falls within the domain of sensitivity analysis. Our "generic" questions are how strongly the variability in exogenous variables (especially those characterizing inflows and lake water exchange) affects means and variances of endogenous variables, and how the magnitudes of these effects change along the gradient of embayment water residence times. Two principal techniques will be used that place sensitivity analysis in a formal statistical framework. The first is the time-dependent Latin Hypercube Sampling/Partial Rank Correlation (LHS/PRC) uncertainty analysis described by Blower and Dowlatabadi (1994), based on methods developed in the field of risk assessment starting with McKay et al. (1979). LHS provides an efficient way of sampling the high-dimensional parameter space of a complex simulation model while taking into account uncertainty of parameter values. The main effects of each parameter or variable are summarized by partial rank correlations with output variables. The efficiency of LHS sampling minimizes the need for multiple runs of computationally intensive models relative to parameter-by-parameter estimates of sensitivity. Having identified the most important variables through LHS/PRC, we will use the Sensitivity Index (SI) methods developed by Sobol and collaborators (Archer et al. 1997, Rabitz et al. 1999, Saltelli et al. 1999). SI methods are formally akin to an ANOVA decomposition of system response to parameter variations into main effects and interactions of various orders. The advantage of SI is that interactive and direct effects are quantified, so that variables whose main role is to enhance or diminish the effect of other variables will be identified as important. The disadvantage is computational effort, because the parameter space is sampled randomly and the "curse of dimensionality" thus creates a computational effort that grows exponentially in the number of parameters. SI will therefore be limited to variables of most interest, either identified a priori or identified by LHS/PRC as key variables.

For our measurement data, we cannot manipulate variables at will, but have to attempt to extract comparable information from the "natural experiments" of measured system responses to measured exogenous variables. A useful framework for these analysis is nonlinear forecasting, an emerging set of concepts and techniques (Tong 1995, Cutler and Kaplan 1997, Kantz and Schreiber 1997), resulting from the recent collision of two distinct traditions of nonlinear dynamic modeling: chaotic dynamics in physical systems (attractor reconstruction and related ideas, e.g. Ott, Sauer, & Yorke 1994), and mainstream statistics and econometrics (e.g. Tong 1990). Concepts and methods originally developed for selecting the order of a univariate time series model (called the embedding dimension in the chaos literature) are equally applicable to the problem of identifying which variables (in a multivariate system) carry useful information for predicting future changes (or current time-derivatives) of other variables. In particular, the Nonlinear Partial Autocorrelation Coefficient (Cheng and Tong 1995), or the prediction r 2 (Ellner et al. 1998, Dixon et al. 1999, Pascual and Ellner in press) can be used to quantify and compare the predictive value of multiple candidate predictor variables with internal system dynamics as the response variables. Resampling methods will allow us to attach standard errors to estimates and to attach significance levels to comparisons between alternate predictor variables (Efron and Tibshirani 1993, Davison and Hinkley 1997, Pascual and Ellner 2000).

Our data sets will be higher-dimensional relative to those to which these methods have been applied in the past, and all of the methods are new enough that each data set brings never-before-seen pitfalls. We will therefore evaluate our methods for quantifying predictability based on output from our simulation models. The models provide an artificial "universe" where we know exactly what the chains of influence are, and we can therefore test our nonlinear forecasting methods by applying them to pseudo-data sets obtained by "sampling" from model output at the frequency and resolution of the real data. In this way, the simulation models will allow us to hone and validate the data analysis methods. Reversing the process, these nonlinear forecasting analyses will provide additional tests of the models. Parallel statistical analyses of real data and model output will give us a series of "probes" into whether the model is a good representation of the actual processes operating in the system. By comparing the apparent cause-and-effect chains in real and simulated data, we can assess whether the models may be getting the right answer for the wrong reasons (because parameters were tuned to make that happen). Thus, our statistical analyses of the data will also inform and influence the development and refinement of the simulation models.

Because our study involves multiple systems along the gradient of water residence time, we avoid the perhaps insoluble problem of determining whether or not a system is truly self-organizing versus externally driven. Instead we have the more straightforward problem of ranking systems from more to less self-organizing (as defined above in terms of nonlinear predictability), which we can then relate to the ranking by hydrologic residence time. This gradient approach also frees us from the artificial need to define a single measure of overall self-organization for the entire biota of each system. For example, retention rates of some community components (e.g. rooted macrophytes) may be far longer than the hydrologic residence time. For such species and food chains built on top of them, community structure and the degree of internal predictability may be similar to those characteristic of systems with longer hydrological retention times.

Nelson Hairston, Jr.
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Phytoplankton, Zooplankton, and Nutrients

These components of the embayments should respond most rapidly both to external forcing by stream inputs or water exchange with Lake Ontario, and to internal ecological interactions. Ideally, they should be sampled at a frequency that permits reliable extrapolation of densities in intervening periods and calculation of realistic rates of change. For periods when population sizes change rapidly, this means sampling at roughly the generation times of the organisms. At the same time, however, we wish to explore the full water retention gradient of embayment types along the Lake Ontario coast. To address these conflicting demands, we propose both intensive and extensive approaches. Three embayments, spanning the gradient of water retention times, will be sampled at weekly intervals when temperatures are warm and biweekly during the ice-free cold months. Sampling will be conducted at a central, deep water station that most accurately reflects water residence time. These sites will be chosen for each embayment based on initial hydrodynamic models. In each of these embayments, monthly samples will also be collected at a site near the connection to Lake Ontario and at a site at the edge of a macrophyte bed where water flow is restricted. Havens (1991a) showed marked differences in zooplankton species composition among sites within a single embayment on Lake Erie with the least temporal change occurring at a site near the main stream channel, a site near the mouth showing a mixture of bay and lake plankton, and a site in a vegetation bed having many littoral species. Thus, sampling at a range of sites within each embayment permits an assessment of spatial variation and how this changes among embayments depending upon water residence times.

Havens (1991b) observed that the plankton community in the bay that he studied was dominated by species with a high potential rate of increase (r), and speculated that this life history was favored by the relatively high flushing rate of the habitat. In bays with long water residence times, we expect that species with longer generation times will also be present providing both a mechanism for the maintenance of greater biodiversity, but also increased complexity of interactions within the plankton community. To test for these patterns, we will sample the remaining five embayments every three weeks. These data will provide information on species diversity differences among the bays as well as a picture of broad temporal patterns within each water body, and hence an ability to evaluate broad patterns of biocomplexity at a regional scale.

Replicate samples will be collected at each sampling site on each collection date. Water samples for phytoplankton will be collected using an integrated water-sampler. Phytoplankton will be preserved in Lugol's solution and counted by the settling method. Zooplankton will be collected with a Clarke-Bumpus quantitative sampler fitted with at 75 µm-mesh net and counted, and identified to species under a dissecting microscope. We have no plans at the moment to assess the planktonic microbial community, but we have the capacity to assess this using a fluorescence compound microscope.

Nicole Hotaling
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Structure and Function of Wetland Communities

I am interested in the structure and function of wetlands associated with the eight study embayments along Lake Ontario. Vegetation surveys were conducted in the summer of 2001 to establish wetland community composition. We (myself and field assistants) recorded stem density and percent cover of each vascular plant species for plots (0.25m2 herbaceous, 5m2 woody) systematically placed along transects and the line-intercept of community types (graminoid herbaceous, non-graminoid herbaceous, shrub, tree, water) along each transect. From these data we tabulated species richness and calculated species relative importance values [(%frequency + %density +%dominance)/3] and the percentages of each community type present on a site. During the summer of 2002 we investigated water level fluctuations, substrate (i.e. peat) depth, and water chemistry (TN, TP, DOC, Ca, Mg) in wetlands at each study embayment as possible factors affecting wetland plant species composition and structure.

At least one of three nitrogen-fixing species, mosquito-fern (Azolla caroliniana), speckled alder (Alnus incana spp. rugosa), and sweetgale (Myrica gale) occurs on six of the eight study sites (only Juniper Pond and Floodwood lacked N-fixing species). Studies have reported N-fixation rates of 37 to 43 kg N/ha/yr for speckled alder in the Adirondacks (Hurd et al. 2001), 35 kg N/ha/yr for sweetgale in Massachusetts (Schwintzer 1983), and 30 to 40 kg N/ha over two weeks for Azolla in the Phillipines (Wagner 1997). Fixation rates of 91 to 614 nmol N/gfw/hr in lab tests have been reported for A. caroliniana (Reddy 1987), but these rates for amount of N fixed per unit of plant tissue can only be translated to amount fixed per unit area if densities of Azolla are known for a given area. I am interested in exploring the ecological role of these species, particularly how much nitrogen is being fixed in wetlands in our study sites and what contribution this fixed nitrogen makes to nitrogen levels in wetland and bay waters. I am also interested in the possibility of using pollen analyses to determine when nitrogen-fixing species first occurred on or dominated these sites (sensu Hu et al. 2001). Other possible directions of investigation include an exploration of wetland connectedness and water movement within the watersheds through GIS analysis with the goal of determining the effect of wetlands on surface water chemistry, and an examination of relationships between species diversity and wetland productivity through correlational and/or manipulative studies.

Robert Johnson
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Aquatic Plants and Littoral Invertebrates

Plants and associated invertebrate taxa of shallow, littoral habitats are expected to vary by season according to normal life cycles. However, we expect these system components to be responsive to water levels, sedimentation dynamics, water quality, and hydrodynamic patterns. Aquatic plants are an important feature of quality lentic habitats supporting high fish production and species diversity (Dibble et al. 1996, Jude and Pappas 1992). The percent of the littoral bottom that is vegetated has been found to be directly related to fish abundance and species richness in Great Lakes coastal bays and waters (Randall et al. 1996). Also, invertebrates are sensitive to organic material availability (plant detritus) from aquatic plants and wetlands, the microhabitat structure provided by plants, sediment characteristics, and fish predation. Aquatic plant production and species richness are expected to peak at intermediate levels of local wave action and water currents as suggested by Keddy (1983). Strong wave action exposes plants to physical damage and unstable sediments (Wilson and Keddy 1986) while very still waters typically have reduced water clarity (Scheffer et al. 1992) and increased sediment deposition on plant surfaces that reduces internal gas diffusion (Wetzel 1992). Consequently, we expect both plant and invertebrate assemblages to be more diverse and abundant when exposed to moderate or weak water currents as suggested by Bailey (1988). Aquatic plants will be seasonally (spring, summer, fall) sampled with grabs for identification, and percent cover measured using line transect observations (Madsen et al. 1996; Madsen 1999). This sampling will provide the extent of aquatic vegetation and the assemblage composition by common species. Invertebrates will be sampled using standardized numbers of sweep nets in vegetated habitats, a pole-mounted Ekman dredge for shallow soft sediment samples, and 0.1 m 2 Van Veen grab for larger taxa and deeper water. All specimens would be identified to lowest practical taxon with the aim of obtaining relative abundance data (numbers per effort) and assemblage composition.

Jenn Kaleta

A Study of Turtle Diversity in the Bays of Lake Ontario

Turtles and amphibians represent the bulk of the biomass in freshwater wetlands (Taylor et al. 1990) and their decline or extirpation can result in important changes in the ecosystem structure and function. Gibbon et al. (2000) illustrate the pattern of reptile declines, and the similarity to the pattern of amphibian declines. In comparison with amphibians, reptiles have lost more species to extinction and have more endangered species. Turtles are the second most affected group of reptiles, and thus their preservation is of concern to conservation biologists. Turtle species depend on the mesic conditions of wetland environments. Thus, the attributes of wetlands determine whether turtle populations exist, thrive, and reproduce within the habitat. The Great Lakes have lost 2/3 of their coastal wetlands since European settlement (Shirose et al. 1995).

This study was proposed as part of a large biocomplexity study being conducted by Cornell University. The study is aiming to characterize the importance of conserving Great Lakes habitat by modeling the complexity of the habitats created by Lake Ontario. Turtle presence had not yet been studied, and literature has shown that turtles contribute largely to ecosystem structure.

Study sites were already being utilized by the Cornell Biocomplexity study. In order for my data to be useful to their efforts, the same bays were used. Eight bays along Lake Ontario were used, including four western sites (Blind Sodus Bay, Little Sodus Bay, Sterling Pond, and Juniper Pond) and four eastern sites (Floodwood Pond, South Colwell Pond, North Sandy Pond, and South Sandy Pond). Due to equipment loss from theft and mammal destruction, only the first seven of the sites were studied. The wetland areas of each bay were chosen for study. Each bay was sampled for one week. Turtle hoop nets were three and a half feet in diameter with one and a half inch square mesh. Three to four nets were placed in the wetland partially submerged in water, baited with one can of sardines, and checked daily for turtles. Turtles trapped were identified by species, sexed, and weighed. Carapaces were measured for length, width, and height; plastrons were measured for length and width. Turtles were checked for markings, deformities, and external parasites. All information was recorded on individual data sheets, along with any behavioral notes and the current water temperature. Before release, turtles were marked with a non-toxic paint pen for purposes of identification if recaptured.

All turtle data was complied and arranged by site. The amount of species present and the number of each individual species per site was then compiled. Finally, diversity was compared by site. Sterling Pond had the highest species richness, with three different species being trapped. Juniper Pond had the lowest species richness with only one species recorded. Most sites were similar in the amount of individuals trapped in one week being about four or five; although some sites remained at only two to three. Sterling Pond stands out as the most diverse in turtle communities, while Juniper Pond showed little diversity.

Nathan Kelsall
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Change of wetland vegetation in two Lake Ontario coastal fens as a result of water depth and fluctuation

To date most models of wetland vegetation, with a few exceptions, have been qualitative rather than quantitative, perhaps limiting their direct application to specific wetlands. Additionally, management scenarios for Lake Ontario water levels in the past have focused on commercial and recreational uses, taking little account of natural communities associated with the lake.

Because of this I decided to study Lake Ontario coastal wetland vegetation change. As part of this study, I am researching the response of wetland plant species to water level fluctuations and depth, both short and long term, in the primary literature. I am then going to create a quantitative spatial model that predicts, regressively the distribution of wetland vegetation types in two coastal wetlands on the eastern shore of Lake Ontario when lake level regulation began, and what the vegetation may be in the future under different management scenarios.

Alexandra King
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The Effects of Macrophyte Growth on the Hydrodynamics of Lake Ontario Embayments

This research project is still in its planning stages. The goal of the project will be to examine the effects of macrophyte growth on the hydrodynamics of Sterling Pond - one of the Biocomplexity study sites on Lake Ontario.

Donald Leopold
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Wetland Plants and Embayment Associated Vegetation

Water level fluctuations in Lake Ontario are natural and this natural variability is important to the development and maintenance of wetland plant communities (Poff et al. 1997, Wilcox and Whillans 1999, Jansson et al. 2000). For example, without occasional natural drawdowns, wetland organic materials accumulate to a degree that substrate elevation rises above the water table, favoring shallow marsh and even upland species. Without the occasional, deep flooding, some wetland species like cattails (Typha spp.) grow so fast that they develop into dense monocultures, replacing deep, emergent marshes and greatly diminishing wetland plant diversity. Since the 1960s, water levels in Lake Ontario have been regulated such that the once natural, extreme highs are lower and extreme lows are higher, which has slowly resulted in changes in wetland plant composition and structure (Roden and Kreutzwiser 1989). Aside from water level changes, human alterations of Great Lakes embayments and wetlands are common, and these disturbances have long-term effects on plant communities (Klarer and Millie 1992; Crowder et al. 1996; Whillians 1996). Wetlands and associated aquatic habitats along the eastern shore of Lake Ontario, including those that are part of the current study, were investigated in the mid 1970s (Geis and Kee 1977). A few years earlier, Geis and Luscombe (1972) noted that over 50 percent of the land along the shoreline to one mile inland in Jefferson County had been converted to agriculture or some other developed land use. Development for seasonal residences, trailer camps, and marinas was actually much higher just along the shoreline. Data collected for the 1974 study are in our possession and include: panchromatic black and white aerial photography, color aerial imagery (color, filtered color, color infrared; at different times during the growing season), and mapping of each wetland and aquatic community type within each pond-marsh complex. Descriptions of these wetland types are detailed enough to allow us to assign type names given in Reschke (1990), which will be used for the proposed present day inventory.

Current wetland and riparian plant community types will be determined by estimating cover of plant species along systematically placed transects extending from upland to aquatic plants. This sampling will be matched with aquatic plant sampling. For communities dominated by woody species, stem densities (all stems over 1 cm dbh) will be measured in 5.0 m 2 plots along the transects. Upland plant communities will be examined similarly. Plant abundance data will be used to place vegetation data into a community type as given in Reschke (1990). Relatively recent historical wetland and upland community types will generally be determined from aerial photographs that are available since the 1930s to present. Longer-term community types will be determined from sediment deposits by examining sediment cores for plant remains.

Daniel P. Loucks
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Watershed Simulation of Water Quality and Quantity

An interactive suite of models (Watershed Information Modeling System [WIMS], Loucks et al. 1985) will be used to predict the quantity and quality of surface and subsurface runoff from watersheds draining into the embayments being studied. The core model of this simulation system (Interactive River-Aquifer Simulation [IRAS], Loucks 1995, Loucks et al. 1996) will enable us to simulate daily runoff as a function of the soil types, land cover, topography, and air temperature in the watersheds. The river-aquifer simulation model will allow us to route those quantities of water and their sediment and chemical constituents as they travel downstream and through wetlands, lakes, and reservoirs, taking into account any surface-groundwater exchanges. These models will be calibrated based on the data sets collected throughout the watersheds, and with the aid of genetic algorithms. Data will be set aside to permit verification, and then incorporated into a more complete calibration data set. Model calibration and verification will be an adaptive process throughout our study. These models will provide the time-series| of inputs from the upstream watersheds to the embayments, and allow us to define the effects of changing land cover and land uses.

Virginia Pasour
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The Effect of Water Retention Time on Embayment Ecosystem Dynamics

This project is focused on modeling biological-physical interactions in marine and aquatic systems. Virginia's work will focus on modeling plankton movement and on channel flow through macrophytes. Download Virginia's research proposal (PDF file).

Rolf Pendall
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Land Use and Human Activity in Study System Watersheds

We will employ new regional science model building methods (Axelrod 1997, Epstein and Axtell 1996) to capture local-scale interactions among landowner and land user agents with a limited set of behavioral rules. This approach has borrowed heavily from work on agent-based models and interacting particle systems models developed by mathematical biologists and mathematicians over the past 20 years. By modifying behavioral rules (e. g., how an agent’s behavior is influenced by other agents), we can conduct experimental numerical simulations to recreate large-scale behavior and land use patterns. Our agent-based modeling will allow us to explicitly assess the ways in which spatial land cover patterns emerge from the collective actions of agents at the time scale of years to decades. At the watershed scale, we intend to model location decisions by households, which are conditioned by developers’ decisions where to build, governments’ decisions where to restrict vs. encourage development, landowners’ decisions whether to sell, and site characteristics (views, open space surroundings) that are themselves affected by previous household and landowner decisions. All these actors are prime examples of economic agents whose local behavior is greatly influenced by observing what other similar agents do, thereby changing the environment in which the aggregate of the agents operate.

In addition to the agent based modeling, we propose to develop a GIS using historic air photos and currently available digital data. The GIS will enable us to model historic to current land-use patterns for the watershed hydrologic and water quality modeling. There have been few attempts at calibrating an agent based model with carefully recorded data and historical spatial data. Furthermore, by bringing together an agent-based model with GIS data, the results of numerical experiments can be compared with actual spatial patterns. Overall, at the watershed scale, our modeling and GIS will provide time-series data at 5- to 10-year intervals on major land cover types (e.g., forest, cultivated cropland, residential, etc.); municipal regulations (zoning, subdivision requirements); and infrastructure networks (roads, public sewer, public water) as exogenous inputs to our study embayments and inputs to watershed hydrologic models for further external data simulation.

Nuanchan Singkran
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Ecotone Formation and Impact on Fish Distribution along Habitat Gradients in Complex Aquatic Systems

A study was undertaken in the summers of 2002 and 2004 to understand the formation and impact of ecotones along habitat gradients of open water–bay–tributaries of Lake Ontario. In the summer of 2002, ecotone studies were conducted along both Sterling and Floodwood gradients. In the summer of 2004, the ecotone study was repeated along the Floodwood gradient using finer scale samplings than those performed in 2002. Turnover rate in fish species composition and changing physical habitat attributes (water depth, current velocity, cover, and substrate) were used to detect ecotone formation in both summers. Responses of fish assemblages to the ecotones were categorized based on abundances observed in the ecotones and adjacent habitats. These categorizations were used to interpret ecotone function.

The results showed that the ecotones present along both Sterling and Floodwood gradients were static in location through the first summer period (June–August 2002). Additionally, the ecotone present in the second summer period (June–August 2004) was detected at the same location on the Floodwood gradient as that of the first summer. Overall, ecotones on the Lake Ontario open water–bay–tributary gradient were stable in location during the summer period. At the same time, changing magnitudes of the studied habitat attributes altered ecotone permeability for fish assemblages entering or migrating across ecotones. Consequently, four functions of the ecotones (aggregator, mediator, soft barrier, and hard barrier) were revealed from the fish species' responses to the ecotones on both study gradients.

Based on the two summer observations along the Floodwood gradient, the ecotone location and its orientation on this gradient were used to separate the gradient into three macrohabitats: downstream, ecotonal, and upstream. Distributions of ten selected fish species in and around the ecotone were then quantitatively predicted using an abundance exchange model (AEM). The model was developed from the fishes’ preferences for five physical habitat attributes (water depth, current velocity, water temperature, substrate, and cover) and their population processes (e.g., natural birth and death rates, and seasonal migration). According to the model simulation, the distribution of the selected fish predicted by the AEM agreed with fish responses to the ecotone and changing physical habitat observed through fieldwork. Because of its flexible structure, the AEM can be applied to other aquatic gradients with different target fish species, geographic areas, and significant habitat variables. Currently, the model is undergoing validation using datasets from different habitat gradients in different water systems.

Updated 12/05

Evan Variano
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Information Theory, Networks, and Trophic Webs

Graduate research will focus on:

Information theory as a potentially useful tool for quantifying aspects of biocomplexity and
universal properties of networks and their relation to trophic webs.

Main interests are in:

Air-water gas transfer and its relation to near-surface turbulence
Information theory as a potentially useful tool for quantifying aspects of biocomplexity
networks, dynamics, and trophic webs