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  • Tippecanoe Soundscape Studies, Indiana
  • Life Story Interviews and Social Networks Along Climate Gradients of Mt. Kenya, Kenya
  • Muskegon River Watershed Mega Model Ecosystem Project
  • Tipping Points of Land Use on Ecosystem Integrity
  • NSF Chicago ULTRA Project - Balancing Ecosystem Services in Urban Areas
  • NSF Climate-Land Interaction Project (CLIP) in East Africa (Mt. Kilimanjaro)
  • USGS Fish Habitat Assessment Project - Assessing Impacts of Climate Change and Land Use Change on Nation's Fisheries
  • NSF III-XT: Tropical Soundscapes, Land Use and Biodiversity La Selva, Costa Rica
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NOAA Tipping Point Project (2010-2014)

 

Ed Rutherford, NOAA-GLERL
Bryan Pijanowski, Purdue University
Brian Miller, Illinois-Indiana Sea Grant
Mike Wiley, University of Michigan
R. Jan Stevenson, Michigan State University
Joan Rose, Michigan State University
David Hyndman, Michigan State University

 

Changes in land use are known to cause considerable problems to the environment, and in the Great Lakes basin, impacts to water quality and aquatic natural resources are broad and at time severe.    These can lead not only to impairment of functioning aquatic ecosystems but also significant public health risks.  Degradation to ecosystem services requires considerable resources to restore and return these ecosystems to states that provide necessary services to residents of the Great Lakes.  However, we lack the necessary tools that provide planners and managers with specific targets (i.e., tipping points) that should never be exceeded.  The amount of impervious surface or forest cover are two well established tipping point metrics that are used nationally by planners when decisions regarding new developments or new conservation efforts are being planned.  It is also known that universal targets do not exist because ecosystem processes vary considerably from region to region.

 

Task 1. Identify Land Use Indicators.  Work will be performed by IISG extension specialists and a CILER fellow (located at Purdue University and co advised by NOAA researchers) to engage university faculty and other Great Lakes researchers in development of two new SOLEC indicator suites for Land Use Change and Agricultural Lands. These indicators will be based on scientific analysis of past and ongoing work (see tasks 2-6) to more completely assess the impact of coastal land and watershed impacts on both the nearshore and open waters of the Great Lakes. Development of the needed indicator suites will occur via consultation with researchers at universities in the Great Lakes and government agencies (including EPA team members involved in the SOLEC process). Leading land use and agriculture researchers will be convened in a workshop setting at GLERL and /or in Chicago to further refine indicators that are reasonable and feasible and would best allow an assessment of Great Lakes ecosystem health. Funding will be provided for travel to workshops  and funds for subsequent indicator refinement that is identified in the workshops will be awarded to participating researchers via subcontracts; these researchers will also become part of the SOLEC process by assessing the indicators every three years for SOLEC reporting.  These indicators will help decision makers to more completely assess the impact of coastal land and watershed impacts on both the nearshore and open waters of the Great Lakes and to make decisions that improve nearshore and open water conditions and ecosystems.

 

Task 2. Develop and apply Causal statistical models, mechanistic individual based models and CART Model to identify tipping points.  The UM team (Wiley, Riseng) will develop causal models (e.g., Structural Equation Models) to identify land use tipping points by relating land use indicators to hydrology, water quality, macroinvertebrates and fishes in Grand Traverse Bay, Grand River, St. Joseph River and (time permitting) Green Bay watersheds. The UM team also will work with Tyler to link land use indicators (phosphorus loadings) to invertebrate prey dynamics and water quality as components of agent-based models to identify tipping points for steelhead and Chinook salmon. Tyler will develop a model of fish growth rate potential (a measure of habitat quality) which can be applied at coarse spatial scales over several watersheds. The model will allow prediction of changes in habitat quality for several fish species based on land use changes 
The PU, UM, MSU teams and Tyler will use the CART model (developed in 2010), the causal models and the fish models to analyze tipping point indicators for the Grand Traverse Bay area watersheds and Grand River watershed) and (time permitting) the Green Bay watershed. The models will demonstrate how land use change impacts a key aquatic natural resource (runoff, nutrient loading, fish diversity, fish habitat).
Because the data are assembled already and several of the team members have used CART models (Pijanowski, Wiley and Riseng), we anticipate that this will be completed by June 1, 2012.


Task 3. Compare output from CART model, causal model, mechanistic coupled model.The PU, MSU, UM teams and Tyler will compare predictions of land-use tipping points from coarse-scale CART and causal models with predictions from a calibrated, highly-mechanistic fish model and a static growth rate potential model for the Grand River, the St. Joseph River and Grand Traverse Bay watersheds. Multiple land use scenarios will be evaluated with both models including varying rates of urban change, forest regeneration rates, riparian setbacks, and water recharge protection areas. We anticipate this task will be completed by June 30, 2012.


Task 4. Extend the Hierarchical Tipping Point Models to Include Bacterial Contaminants.  The MSU group (Dr. Joan Rose, Dr. David Hyndman) along with Dr. Bryan Pijanowski (Purdue) will develop maps of septic tank use and water quality violations for specific watersheds including the Grand River watershed, the Grand Traverse Bay watersheds, the St. Joseph River watershed, and (if time permits) the Green Bay watersheds. For these watersheds, Hyndman and Rose will use hydrology and groundwater models to predict E. coli occurrence and transfer from septic tanks to reported TMDLs and water quality variations.


Dr. Rose will work with the UM group to compare hierarchical model predictions of invertebrate biomass and species composition to E. coli contamination. We hypothesize that the land use variables that impact invertebrate communities are the same variables that impact E. coli contamination.


Task 5. Apply regression and multivariate statistical models to evaluate land use tipping points for multiple nearshore areas in the Lake Michigan basinDr. Sara Adlerstein-Gonzalez (UM) will perform a retrospective study to quantify responses in nearshore Great Lakes ecosystems to land use tipping points through statistical analyses of long-term data. The data, collected by state and federal agencies, include measurements of nutrient loadings, watershed land cover, physical and chemical characteristics (eg. dissolved oxygen, temperature, conductivity, turbidity) and biota (phytoplankton, zooplankton, benthos, fish, birds) in Green Bay Wisconsin, Muskegon Lake and nearshore Lake Michigan, near St. Joseph and Grand Haven. She will implement multivariate and generalized linear/additive models to characterize changes in community structure, distribution and abundance with land use indicators. This analysis will be complete by Sept. 30, 2012.

 

Task 6. Integrate and compare predictions from the hierarchical, statistical and simulation models to predictions by other GLRI projects on biological outcomes from land use scenarios.  We will integrate the hierarchical models (land use, hydrology, fisheries and contaminants) for a select number of locations including Grand River watershed, the Grand Traverse Bay and St. Joseph watersheds, and perhaps the Green Bay, Wisconsin watersheds.  We anticipate being able to integrate these models and/or have the ability to predict biological/contaminant outcomes from land use scenarios by June 1, 2012. We will compare biological outcomes from our suite of models with coincident sampling and modeling of phosphorus loadings and algal blooms in Michigan’s nearshore waters by Drs. Stevenson and Hyndman.

 

Task 7.  Identify specific land use tipping points that change biological and/or contaminant outcomes.  We will begin to develop a web-based GIS decision support data layer that can be used by land use decision makers to determine where they are relative to these tipping points.  We will initiate development of additional materials to help decision makers determine their options if they are nearing or exceeding tipping points and users will be directed to potential policies and management practices that could improve these conditions.   

 

Task 8. Conduct a Demonstration of Use.  We will travel to several locations and work directly with planners and natural resource managers in these pilot communities to demonstrate the tipping point tool.  This demonstration will include a presentation and discussion regarding specific targets (i.e., tipping points) that should guide planning for their community.  We intend to hold this/these meeting(s) from March through Aug 2012.  Feedback gained from pilot communities will be used to improve the decision support tool and associated support materials.

 

 

Last updated March 6, 2011