Browsing by Author "Johnston, Carol A"

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Development of Environmental Indicators for the U.S. Great Lakes Basin Using Remote Sensing Technology
(University of Minnesota Duluth, 2006) Niemi, Gerald J; Johnston, Carol A; Wolter, Peter T.
In 2001 we initiated a study of remote sensing technology to complement our development of environmental indicators for the U.S. Great Lakes coastal region. Our objectives were to: 1) quantify land use/land cover (LULC) and change for the U.S. portion of the Great Lakes basin between 1992 and 2001; 2) identify salient LULC change categories that are most likely to affect near-shore ecosystems; 3) recommend landscape indicators to guide managers toward long-term sustainable development; 4) develop methodologies to quantify SAV within near-shore areas of the Great Lakes; and 5) use historically low water levels in Lakes Michigan and Huron to produce a digital elevation model of recently exposed lake bed using radar interferometry to better model coastal wetland inundation events as lake water levels returns to normal. In addition, we completed four focused studies in the Great Lakes basin: 1) two studies to determine the degree of accuracy of Quiclcbird satellite imagery to identify specific vegetation types within a wetland; 2) an examination of 63 years (1940 to 2003) of land use change in a 100 km2 area in western Lake Erie; and 3) a study to test the use of Hyperion hyperspectral satellite imagery for mapping PhragmitesL an invasive plant species in the Great Lakes. All of the objectives were successfully completed, except objective 5 in which we had technical difficulties with the use of radar interferometry because of changes in ice and snow in the region. A total of six peer-reviewed publications have been completed and three additional publications are either in review or in preparation. The land use/land cover map produced for 1992 and 2001 will serve an extremely important baseline for future monitoring of change in the U.S. Great Lakes basin. A special issue of the Journal of Great Lakes Research is in preparation that summarizes additional work on this project. It is scheduled for publication in 2007.
Effects of Disturbance of Water-Quality Functions of Wetlands
(University of Minnesota Duluth, 1991) Johnston, Carol A; Detenbeck, Naomi E; Hagley, Cynthia; Taylor, Debra A; Lima, Ann R; Bamford, Stacey
The following report has been organized into three sections. The first two sections represent rough drafts of manuscripts on 'Temporal and spatial variability of wetland water- quality in The Minneapolis/St. Paul area" and "Effects of physical, chemical, and hydrologic disturbance on wetland water-quality". The third section summarizes work in progress on assessing time trends in wetland water quality function.
Environmental Indicators for the Coastal Region of the U.S. Great Lakes
(University of Minnesota Duluth, 2006) Niemi, Gerald J; Axler, Richard P; Brady, Valerie; Brazner, John; Brown, Terry; Ciborowski, Jan H; Danz, Nicholas P; Hanowski, JoAnn M; Hollenhorst, Thomas; Howe, Robert; Johnson, Lucinda B; Johnston, Carol A; Reavie, Euan D; Simcik, Matthew; Swackhamer, Deborah L.
The goal of this research collaboration was to develop indicators that both estimate environmental condition and suggest plausible causes of ecosystem degradation in the coastal region of the U.S. Great Lakes. The collaboration consisted of 8 broad components, each of which generated different types of environmental responses and characteristics of the coastal region. These indicators included biotic communities of amphibians, birds, diatoms, fish, macroinvertebrates, and wetland plants as well as indicators of polycyclic aromatic hydrocarbon (PAH) photo-induced toxicity and landscape characterization. These components are summarized below and discussed in more detailed in 5 separate reports (Section II). Stress gradients within the U.S. Great Lakes coastal region were defined from 207 variables (e.g., agriculture, atmospheric deposition, land use/land cover, human populations, point source pollution, and shoreline modification) from 19 different data sources that were publicly available for the coastal region. Biotic communities along these gradients were sampled with a stratified, random design among representative ecosystems within the coastal zone. To achieve the sampling across this massive area, the coastal region was subdivided into 2 major ecological provinces and further subdivided into 762 segment sheds. Stress gradients were defined for the major categories of human-induced disturbance in the coastal region and an overall stress index was calculated which represented a combination of all the stress gradients. Investigators of this collaboration have had extensive interactions with the Great Lakes community. For instance, the Lake Erie Lakewide Area Management Plan (LAMP) has adopted many of the stressor measures as integral indicators of the condition of watersheds tributary to Lake Erie. Furthermore, the conceptual approach and applications for development of a generalized stressor gradient have been incorporated into a document defining the tiered aquatic life criteria for defining biological integrity of the nation’s waters. A total of 14 indicators of the U.S. Great Lakes coastal region are presented for potential application. Each indicator is summarized with respect to its use, methodology, spatial context, and diagnosis capability. In general, the results indicate that stress related to agricultural activity and human population density/development had the largest impacts on the biotic community indicators. In contrast, the photoinduced PAH indicator was primarily related to industrial activity in the U.S. Great Lakes, and over half of the sites sampled were potentially at risk of PAH toxicity to larval fish. One of the indicators developed for land use/land change was developed from Landsat imagery for the entire U.S. Great Lakes basin and for the period from 1992 to 2001. This indicator quantified the extensive conversions of both agricultural and forest land to residential area that has occurred during a short 9 year period. Considerable variation in the responses were manifest at different spatial scales and many at surprisingly large scales. Significant advances were made with respect to development of methods for identifying and testing environmental indicators. In addition, many indicators and concepts developed from this project are being incorporated into management plans and U.S. 8 EPA methods documents. Further details, downloadable documents, and updates on these indicators can be found at the GLEI website - http://glei.nrri.umn.edu.
Environmental Indicators for the US. Great Lakes Coastal Region
(University of Minnesota Duluth, 2006) Niemi, Gerald J; Axler, Richard P; Brady, Valerie; Brazner, John; Brown, Terry; Ciborowski, Jan H; Danz, Nicholas P; Hanowski, JoAnn M; Hollenhorst, Thomas; Howe, Robert; Johnson, Lucinda B; Johnston, Carol A; Reavie, Euan D; Simcik, Matthew; Swackhamer, Deborah L.
The goal of this research collaboration was to develop indicators that both estimate environmental condition and suggest plausible causes of ecosystem degradation in the coastal region of the U.S. Great Lakes. The collaboration consisted of 8 broad components, each of which generated different types of environmental responses and characteristics of the coastal region. These indicators included biotic communities of amphibians, birds, diatoms, fish, macroinvertebrates, and wetland plants as well as indicators of polycyclic aromatic hydrocarbon (P AH) photo-induced toxicity and landscape characterization. These components are summarized below and discussed in more detailed in 5 separate reports (Section II). Stress gradients within the U.S. Great Lakes coastal region were defined from 207 variables (e.g., agriculture, atmospheric deposition, land use/land cover, human populations, point source pollution, and shoreline modification) from 19 different data sources that were publicly available for the coastal region. Biotic communities along these gradients were sampled with a stratified, random design among representative ecosystems within the coastal zone. To achieve the sampling across this massive area, the coastal region was subdivided into 2 major ecological provinces and further subdivided into 762 segment sheds. Stress gradients were defined for the major categories of human-induced disturbance in the coastal region and an overall stress index was calculated which represented a combination of all the stress gradients. Investigators of this collaboration have had extensive interactions with the Great Lakes community. For instance, the Lake Erie Lakewide Area Management Plan (LAMP) has adopted many of the stressor measures as integral indicators of the condition of watersheds tributary to Lake Erie. Furthermore, the conceptual approach and applications for development of a generalized stressor gradient have been incorporated into a document defining the tiered aquatic life criteria for defining biological integrity of the nation's waters. A total of 14 indicators of the U.S. Great Lakes coastal region are presented for potential application. Each indicator is summarized with respect to its use, methodology, spatial context, and diagnosis capability. In general, the results indicate that stress related to agricultural activity and human population density/development had the largest impacts on the biotic community indicators. In contrast, the photoinduced P AH indicator was primarily related to industrial activity in the U.S. Great Lakes, and over half of the sites sampled were potentially at risk of P AH toxicity to larval fish. One of the indicators developed for land use/land change was developed from Landsat imagery for the entire U.S. Great Lakes basin and for the period from 1992 to 2001. This indicator quantified the extensive conversions of both agricultural and forest land to residential area that has occurred during a short 9 year period. Considerable variation in the responses were manifest at different spatial scales and many at surprisingly large scales. Significant advances were made with respect to development of methods for identifying and testing environmental indicators. In addition, many indicators and concepts developed from this project are being incorporated into management plans and U.S. EPA methods documents.
A Georeferenced Aerial Video Imaging System Annual Report
(University of Minnesota Duluth, 1994) Johnston, Carol A; Bonde, John
The objective of this project is to develop a system to georeference airborne video Imagery using Global Positioning System (GPS) technology. The system will make it possible for video images taken from an airplane to be used to make maps that could be interfaced with other data layers in a Geographic Information System (GIS). The uniqueness of the proposed system is its real-time georeferencing capability, which greatly accelerates the conversion of video images into a mosaiced, georeferenced digital database.
GIS and Modeling in Ecological Studies: Analysis of Beaver Pond Impacts on Runoff and its Quality
(University of Minnesota Duluth, 1994-02) Nawrocki, Tatiana; Johnston, Carol A; Sales, James
The ARC/INFO GRID module was used to derive watershed variables for input to AGNPS, a cell-based runoff model that estimates water volume, peak flow, eroded and delivered sediment, chemical oxygen demand, and nutrient export from watersheds (Young et al. 1987). The boundary of a 534 ha watershed in Voyageurs National Park was hand-digitized from 1:24,000 topographic maps, and used to clip elevation data from a 7~ minute U.S.G.S. Digital Elevation Model (DEM) with 30 m mesh-point spacing. ARC/INFO GRID was used to generate slope, slope shape, and field slope length for each of the 90x90 m cells used to subdivide the watershed. A surface runoff network was then generated using the FLOWDIRECTION, FLOWACCUMULATION, and STREAMLINE hydrologic modeling tools in ARC/INFO GRID. Each of the 90x90 m cells was uniquely numbered, and receiving cell numbers were derived for each source cell based on FLOWDIRECTION results. A 1:24,000 land cover map (Allen et al. 1993) was digitized and gridded to derive Manning's roughness coefficient, surface condition constant, and chemical oxygen demand factor for each cell. Detailed soil maps have never been made for the wilderness study site used, so land cover classes were coupled with information about soil series from nearby mapped sites to estimate soil texture, soil erodibility factor, and hydrologic group (to derive SCS curve numbers). The drainage area for each beaver impoundment in the watershed was derived from a digital database of subwatersheds. All variables were exported from ARC/INFO into the Microsoft Excel spreadsheet program, which was used to generate a data file in the appropriate format for AGNPS. The methodology was applied to the 534 ha, third order stream watershed to determine the influence of beaver ponds on water quality and quantity. Beavers influence runoff by: 1) constructing dams that retard the flow of water, 2) creating ponds that promote sediment deposition and increase phosphorus retention, and 3) changing forest land cover to water and wetland vegetation. We ran the model for a range of storms with average 24-hour rainfalls equivalent to a 1 yr, 2 yr, 5 yr, 10 yr, 25 yr, 50 yr, and 100 yr storm, based on National Weather Service records for the region. Model runs for the beaver-impounded landscape ("with ponds") were compared with those for the same watershed without the influence of beaver ("no ponds"), based on historical vegetation and adjacent forest types. The ''with ponds" scenario resulted in slightly increased water flow at the mouth of the watershed. This is because, assuming that the pond is full, 100% of the rain that falls onto it will flow off of it. This caused a 10% increase in runoff at the lowest rainfall intensity, but only a 1% difference during the 100 yr storm. The runoff contribution of individual cells changed relatively little between the two scenarios, but there were easily discernable differences in accumulated runoff per cell ii: with distance downstream. Sediment deposition in the beaver ponds also had an effect that accumulated downstream, so that the ''with ponds" scenario yielded 7 to 12% less sediment than the ''no ponds" scenario, an effect that increased with storm intensity. The model predicted a 4% decrease in watershed nitrogen output with ponds for a 1 yr storm, but there was no effect for storms with a 10 to 50 yr frequency, and a net increase for a 100 yr storm. This implies that while beaver ponds may retain N during low-intensity storms, there may be a flushing of that retained N during high-intensity storms. This pattern is visible on GIS maps for "with ponds" scenario with low intensity storm: higher nitrogen concentrations were observed at the locations, where no ponds were situated, and nitrogen content in runoff had remarkable alterations in cells adjacent to ponds. Chemical oxygen demand (COD) showed the largest effect of any of the parameters predicted: the presence of beaver ponds was associated with a 10 to 17% reduction of COD, depending on the storm intensity. This is because a forest has a lot more primary productivity than a pond, and therefore contributes more organic matter (and therefore COD) to the system. This model-based approach provided insight into the landscape scale influence of beaver ponds that could not have been derived using conventional field techniques. The modeling was done at a spatial level of detail that would have been impractical using manual data entry to AGNPS. Automating the derivation and interchange of variables with a GIS made this research possible.
Human Impacts to Minnesota Wetlands
(University of Minnesota Duluth, 1991) Johnston, Carol A
Minnesota’s 3.6 million ha of wetlands have been impacted by a variety of human activities, including agricultural drainage, urbanization, water control, and nonpoint source pollution. More than half of Minnesota's wetlands have been destroyed since the first European settlers arrived, an average loss of about 35,600 ha/yr. Drainage for agriculture is the major cause of wetland loss in Minnesota, particularly in southern Minnesota and the Red River Valley. In addition to impacting wetlands directly, wetland drainage affects downstream areas by increasing flood flows, and releasing sediment and nutrients. Urban development and highway construction affect a smaller proportion of Minnesota’s wetlands, but substantially alter their physical, chemical, and biological properties. Hydrology has a major influence on the structure and function of wetlands, so changes in the frequency, duration, depth, and timing o f wetland flooding can severely impact wetlands. While wetlands can assimilate low levels o f sediment and nutrient enrichment, excessive inputs can be detrimental. Peat harvesting is not currently extensive in Minnesota, but could cause substantial impacts. Cumulative impact, the incremental impact o f an action when added to other past, present, and reasonably foreseeable future actions, is becoming an area of increasing concern.
An Integrated Approach to Assessing Multiple Stressors for Coastal Lake Superior
(2011) Niemi, Gerald J; Reavie, Euan; Peterson, Gregory S; Kelly, John R; Johnston, Carol A; Johnson, Lucinda B; Howe, Robert W; Host, George; Hollenhorst, Thomas; Danz, Nick; Ciborowski, Jan H; Brown, Terry; Brady, Valerie; Axler, Richard P
This peer-reviewed article summarizes research conducted under the Great Lakes Environmental Indicators (GLEI) project initiated by the authors in 2001. The authors assessed the status of Lake Superior’s coastal ecosystem relative to over 200 environmental variables collected from GIS data sets for the enture US Great Lakes basin. These were assessed using gradients including atmosphereic deposition, agriculture, human population and development, land cover, point source pollution, soils and a cumulative stress index. Relationships of biological assemblages of birds, diatoms, fish and invertebrates, wetland plants, soils and stable isotopes to these gradients were then assessed. Key findings are extracted and reproduced below. Biological indicators can be used both to estimate ecological condition and to suggest plausible causes of ecosystem degradation across the U.S. Great Lakes coastal region. Here we use data on breeding bird, diatom, fish, invertebrate, and wetland plant communities to develop robust indicators of ecological condition of the U.S. Lake Superior coastal zone. Sites were selected as part of a larger, stratified random design for the entire U.S. Great Lakes coastal region, covering gradients of anthropogenic stress defined by over 200 stressor variables (e.g. agriculture, altered land cover, human populations, and point source pollution). A total of 89 locations in Lake Superior were sampled between 2001 and 2004 including 31 sites for stable isotope analysis of benthic macroinvertebrates, 62 sites for birds, 35 for diatoms, 32 for fish and macroinvertebrates, and 26 for wetland vegetation. A relationship between watershed disturbance metrics and 15N levels in coastal macroinvertebrates confirmed that watershed-based stressor gradients are expressed across Lake Superior’s coastal ecosystems, increasing confidence in ascribing causes of biological responses to some landscape activities. Several landscape metrics in particular—agriculture, urbanization, human population density, and road density—strongly influenced the responses of indicator species assemblages. Conditions were generally good in Lake Superior, but in some areas watershed stressors produced degraded conditions that were similar to those in the southern and eastern U.S. Great Lakes. The following indicators were developed based on biotic responses to stress in Lake Superior in the context of all the Great Lakes: (1) an index of ecological condition for breeding bird communities, (2) diatom-based nutrient and solids indicators, (3) fish and macroinvertebrate indicators for coastal wetlands, and (4) a non-metric multidimensional scaling for wetland plants corresponding to a cumulative stress index. These biotic measures serve as useful indicators of the ecological condition of the Lake Superior coast; collectively, they provide a baseline assessment of selected biological conditions for the U.S. Lake Superior coastal region and prescribe a means to detect change over time.” Key points: “In general, the U.S. Great Lakes coastal region of Lake Superior shows greater overall stress in the southern regions compared with relatively low overall stress in the northern regions. These patterns are primarily due to agricultural land use, higher human population densities, and point sources in the eastern and western portions on the south shore, while the north shore at the western end of Lake Superior is primarily forested with relatively sparse human population densities. Coastal regions of Lake Superior can be found at each of the extremes of the disturbance gradients. This includes relatively pristine watersheds in the northern regions with low human population densities and little agriculture that contrast with regions of relatively high populations with industrial activity such as Duluth-Superior in Minnesota-Wisconsin and Sault Ste. Marie Michigan at the other end of the gradient. The U.S. Lake Superior coastal region varies widely in the degree of human-related stress; generally, levels of stress decrease from south to north but with considerable variation, especially along the southern shore due to local agricultural activity and the presence of several population and industrial centers. In spite of a lack of latitudinal variation, there is human-induced, watershed scale variability across the Lake Superior coast. Compared to the other Great Lakes, Lake Superior coastal fish communities had more generally intolerant fish and more turbidity intolerant fish. Coastal fish community composition reflected the higher levels of suspended solids associated with human alteration to watersheds. The most disturbed sites on Lake Superior had greater proportions of non-native species and fewer bottom-feeding taxa.
Land Use and Water Resources in the Minnesota North Shore Drainage Basin
(University of Minnesota Duluth, 1991) Johnston, Carol A; Bonde, John; Meysembourg, Paul; Allen, Brian; Sales, James
The major land use change currently occurring in the Lake Superior drainage basin is the increase in deforestation resulting from demand for wood and paper products, which is projected to increase total harvest by 50% between 1988 and 1995 (Minnesota DNR 1989). We know that the extensive pre-settlement logging of the Great Lakes drainage basin affected water quality, as indicated by sediment evidence of increased phosphorus concentrations (Kemp et al. 1972) and diatom production (Stoermer et al. 1985; Schelske et al. 1988), and model predictions of increased phosphorus loading (Chapra 1977). However, we don’t know the magnitude of land affected by more recent clearcutting, nor its effects on water resources. The purpose of this report is to describe these land use changes and other characteristics of the Minnesota North Shore drainage basin that could potentially affect fluxes of sediment and nutrients into Lake Superior.
Literature Pertaining to the Environmental Impacts of Turfgrass Management on Wetlands
(University of Minnesota Duluth, 1990) Johnston, Carol A
This report lists references pertaining to the environmental impact of turfgrass management, in the following categories: General Wetland References, Impacts of Wetland Loss, Construction Impacts to Wetlands, Impacts of Pesticides on Wetlands, Nonpoint Source Pollution from Urbanization, Impacts of Recreation, Cumulative Impacts to Wetlands
Natural Resources of Minnesota Point: Maps and Data in Support of the Minnesota Point Environmental Plan
(University of Minnesota Duluth, 1999) Johnston, Carol A; Trauger, Amy; Meysembourg, Paul; Bonde, John; Hawrot, Rita Y; Walton, Gary B
Includes maps and data regarding ecological subsections of Minnesota, information regarding the distribution and relationships of habitats and birds in the St. Louis River estuary, a map and inventory of open space in Duluth, and a map and data from an aquatic habitat survey (fish monitoring) in the Park Point area.
Productivity of Wet Soils: Biomass of Cultivated and Natural Vegetation
(University of Minnesota Duluth, 1988) Johnston, Carol A
Wet soils, soils which have agronomic limitations because of excess water, comprise 105 million acres of non-federal land in the conterminous United States. Wet soils which support hydrophytic plants are "wetlands", and are some of the most productive natural ecosystems in the world. When both above- and belowground productivity are considered, cattail (Typha latifolia) is the most productive temperate wetland species (26.4 Mg/ha/year). Both cattail and reed (Phragmites australis) have aboveground productivities of about 13 Mg/ha/year. Although average aboveground yields of reed canarygrass (Phalaris arundinacea) are lower (9.5 Mg/ha/year), techniques for its establishment and cultivation are we 11-deve1 oped. Other herbaceous wetland species which show promise as biomass crops include sedge (Carex spp.), river bulrush (Scirpus fluviatilis) and prairie cordgrass (Spart ina pectinata). About 40% of wet soils in the conterminous U.S. are currently cultivated, and they produce one-quarter of the major U.S. crops. Most of this land is artificially drained for crops such as corn, soybeans, and vegetables. U.S. wetlands are drained for agriculture at the rate of 223,000 ha/yr. Paddies flooded with water are used to grow rice, cranberries, and wild rice. Forage and live sphagnum moss IV are products of undrained wetlands. A number of federal and state regulations apply to the draining or irrigation of wetlands, but most do not seriously restrict their use for agriculture.
Relationship Between Development and Condition of Lakes in Minnesota's Northern Lakes and Forests Ecoregion
(University of Minnesota Duluth, 1999) Johnston, Carol A; Shmagin, Boris
Human development in shorelands and watersheds has the potential to impact the condition and sustainability of Minnesota lakes. Shoreland and local zoning ordinances have guided development in recognition of this potential impact, but must be based on scientific evidence of land-lake linkages. The impacts of development must also be distinguished from the effects of lake and watershed characteristics that naturally alter lake condition. The objectives of this project were to: (1) develop classification systems for lakes based on (a) measures of lake condition and (b) measures of shoreland population density, and (2)develop methodologies to assess the cumulative effects of development on lakes by relating indicators of human activity to indicators of lake condition. GIS and statistical analysis techniques were used to relate indicators of lake condition, in particular Secchi transparency, to lake, shoreland and watershed characteristics. Existing lake condition data were obtained from two digital repositories: the Minnesota DNR Fisheries Data Warehouse and EPA's STORET database. Data were analyzed for two time periods, 1977-79 and 1994-96, so as to temporally match lake condition with available GIS land use data. The spatial extent of the study is the Northern Lakes and Forest (NLF) ecoregion, which covers 68,243 km2 in northeastern Minnesota and contains 5,408 lakes >. 10 ha, the majority of which are oligotrophic to mesotrophic. Secchi transparency of 589 lakes sampled in 1994-96 ranged from 0.6 to nearly 12 m. Of the eight clearest lakes, three were abandoned mine pits. Average Secchi transparency was 2.75 m for the 1977-79 time period, but increased to 3.17 m for the 1994-96 time period, a significant increase in lake clarity over time. Highly colored lakes were less transparent, and the correlation between Secchi transparency and lake color (r = -0.480, p = 0.000) was greater than the correlation between Secchi transparency and total P ( r = -0.365, p = 0.014). Multivariate analysis of seven lake condition parameters revealed that 73% of the variance in lake condition was explained by just two lake principal components (LPCs): LPCl was positively related to pH, alkalinity, total dissolved solids, and conductivity, whereas LPC2 was positively related to Secchi transparency and negatively related to chlorophyll A and total P. These principal components were used to classify lakes into four lake condition classes: deep transparency low alkalinity, shallow transparency low alkalinity, shallow transparency high alkalinity, and deep transparency high alkalinity. The area of lakes studied ranged from 5 to 51, 7 48 ha, and maximum lake depth ranged from 1 to 70 m. Average shoreland land cover within a 1000' buffer surrounding each lake was 69% forest and brushland, 11% wetland, 8% water (ie., adjacent lakes), 6% grassland, 5% urban, and less than 1% cultivation and mining. With the exception of mining within the shoreland zone, which was associated with clearer mine pit lakes, there were no significant correlations between individual measures of development and Secchi transparency. Lakes with people living around them were significantly clearer than those without, indicating that people choose to live on clearer lakes. Shoreland population density was grouped into five classes based on the natural breaks method, but the only significant difference in Secchi transparency were between the most populous class (>. 844.4 people/km2), which represented the three lakes with the most extreme urbanization in the ecoregion, and the two classes with intermediate population densities (37.5-361.1 people/lm12). The transparency of the most populous class was not significantly different than the transparency of the least populous class (0-3 7 people/km2). Stepwise multiple regression between Secchi transparency and original environmental variables revealed that maximum lake depth was the single variable that consistently had the greatest influence on Secchi transparency, the deeper the lake the greater the clarity. Maximum lake depth provided 47 to 75% of the explanatory power of the stepwise multiple regressions developed using original variables, much more than any variable related to development. This means that deep lakes are naturally less sensitive to cumulative impacts than are shallow lakes. Stepwise multiple regression between Secchi transparency and principal components derived from environmental variables revealed that the following natural conditions were associated with clearer lakes: watersheds with loamy vadose soils, watersheds with moderately acid soils of very low erodibility, and lakes with other lakes in their shoreland zone. Lakes with more wetlands in their shoreland and watershed were less transparent. Lakes with urban shorelands were less transparent, but lakes in watersheds with private land ownership were clearer than lakes in watersheds with public non-wilderness ownership. Seasonal home development was associated with clearer lakes, but lakes with the most seasonal home development tended to be deep, which may have overridden any negative effects of shoreland development. Cultivated crops in the shoreland were associated with circumneutral soils, which were associated with reduced clarity. Overall, there was little evidence that development was detrimental to Secchi transparency except at the highest levels of population density and urbanization.

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