Center for Water
and the Environment
Lucinda Johnson, Ph.D., CWE Center Director and Senior Research Associate
Position and Focus
Areas of interest include bioindicators, amphibians and watersheds. Research projects include: effects of multiple stressors on aquatic communities; testing indicators of coastal ecosystem integrity using fish and macroinvertebrates; protocols for selecting classification systems and reference conditions: a comparison of methods.
Ph.D., Zoology, Michigan State University, 1999
M.S., Environmental Science and Forestry, State University of New York, 1984
B.A., Duke University, 1976
Herb, W R, Johnson, L B Jacobson, P C & Stefan, H G. 2014. Projecting cold-water fish habitat in lakes of the glacial lakes region under changing land use and climate regimes. Canadian Journal of Fisheries and Aquatic Sciences 71(September):1334--1348.
Johnson, L B. 2014. Lake Superior North Shore Brook Trout - How Will They Respond to Climate Change?. Lake Superior Angler 21--25.
Kovalenko, K E, Brady, V J, Brown, T N, Ciborowski, J J H, Danz, N P, Gathman, J P, Host, G E, Howe, R W, Johnson, L B Niemi, G J & Reavie, E D. 2014. Congruence of community thresholds in response to anthropogenic stress in Great Lakes coastal wetlands. Freshwater Science 33(September):958--971.
Kovalenko, K E, Brady, V J, Ciborowski, J J H Ilyushkin, S & Johnson, L B. 2014. Functional changes in littoral macroinvertebrate communities in response to watershed-level anthropogenic stress. PLoS ONE 9(January):e101499.
Peterson, A C Niemi, G J & Johnson, D H. 2014. Patterns in diurnal airspace use by migratory landbirds along an ecological barrier. Ecological Applications In press
to view complete publication list.
Project list for Lucinda Johnson :
(A link will go to the project's current report, an arrow will take you to a project's home page)
Collaborative Research: Climatic and Anthropogenic Forcing of Wetland Landscape Connectivity in the Great Plains
This collaborative project brings together hydrological modelers, ecologists, and spatial scientists from five universities to establish links among climatic and land use drivers affecting habitat connectivity for wildlife in current and projected wetland landscapes. Building on a theoretical framework of well-established landscape ecological principles regarding effects of land cover and connectivity, this work will examine patterns and processes that interact across local to continental scales and incorporate Land Cover/Land Use Change (LCLUC) projections in predicting habitat suitability and landscape connectivity for wetland-dependent species.
The objective of the overall project is to assess the influence of climatic drivers of wetland landscape habitat connectivity in the Great Plains, incorporating sophisticated hydrologic modeling with projected climate change and LCLUC to predict impacts on amphibians and waterbirds under a range of likely future scenarios.
Landscape ecologists at NRRI will be working on the amphibian modeling portion of this project, with the sub-objective to model the effects of climate and land use/land cover change on wetland habitat availability and connectivity at local and landscape scales using amphibians (anurans and salamanders) as a focal group with low vagility.
Woolpert-NOAA ELOHA Modeling (External Sales)
Spatial Conservation and Investment Portfolios to Manage Climate-Related Risk
This project brings together economists and spatial scientists in landscape ecology to carry out important developments in the science of risk management tools from financial portfolio theory that exploits information about spatial covariances in projected ecological conditions, and show how policy makers and conservation agents can apply those tools to spatial targeting of mitigation, restoration, and adaptation investments.
The objectives of the overall project are to develop sets of conservation-outcome forecasts from multiple possible climate scenarios for: 1) wetlands in the Prairie Pothole Region, 2) Eastern Birds, and 3) Appalachian salamanders which can be used to quantify and test hypotheses about the drivers of spatial patterns in ecological uncertainty and construct spatially explicit data sets suitable for MPT analysis. These data will be used for MPT analysis, including evaluation of performance, identifying the kinds of problems this methodology is most useful, identifying when and how iterated portfolio analysis can best be done in absence of data from a large number of climate scenarios, developing a method to guide investment allocation (land purchases and stewardship activities), and identifying potential for multi-objective portfolio analysis methodologies in conservation planning.
Landscape ecologists at NRRI will be developing spatial data on ecological returns and risk from conservation investments in varied sub-regions of the Prairie Pothole Region and providing data and support to the ecologists and economists from University of Illinois to complete the rest of the objectives.
Managing the Nation`s Fish Habitat at Multiple Spatial Scales
1) To refine empirical and mechanistic models for predicting extent of cold water fish habitat under current land use and climate regimes. Predict oxythermal habitat for coldwater fish species using an empirical model incorporating existing land use, lake morphometry, and climate data.
2) Predict future extents of cold water fish habitat in lakes of the Glacial Lakes region under future climate and land use scenarios. Predict future oxythermal habitat in lakes under changing land use and climate for a large set of regional coldwater lakes using empirical models. Predict future oxythermal habitat for individual lakes under changing land use and climate for distinct lake classes and/or geographic regions using a mechanistic model.
Great Lakes Coastal Wetland Monitoring
To assess the biotic condition of all the major coastal wetlands of the Great Lakes, United States and Canadian shorelines.
A Comprehensive Stressor-Response Model to Inform Ecosystem Restorations Across the Great Lakes Basin
Two maps depicting anthropogenic stresses across the Great Lakes Basin will be merged into a composite map that spans the entire basin.
Great Lakes Coastal Database and Classification Framework
To develop a habitat classification system that focuses on the nearshore and coastal systems of the Great Lakes to provide a data framework that will guide future restoration and management objectives.
Improving Hydrology Predictions with LiDAR
Use newly available soils and topographic data to update predictions of peak and base flow in MN`s north shore streams.