Developing a Bird-Habitat Decision Support System for the Lower Great Lakes/St. Lawrence Region: Pilot Project for the St. Lawrence Focus Area

FINAL REPORT

Submitted to:

American Bird Conservancy U.S. Fish and Wildlife Service U.S.D.A Forest Service

Submitted by:

Ducks Unlimited, Inc. 1 November 2005 TABLE OF CONTENTS

ACKNOWLEDGEMENTS...... 3 DISCLAIMER...... 3 ABSTRACT ...... 4 1. INTRODUCTION...... 5 1.1 Joint Ventures and Bird Conservation ...... 5 1.2 Great Lakes HEN...... 5 2. PROJECT AREA ...... 6 3. METHODS...... 8 3.1 Existing Data ...... 8 3.1.1 National Inventory (NWI) ...... 8 3.1.2 Coastal Change Analysis Program(C-CAP) ...... 8 3.1.3 St. Lawrence River Valley...... 9 3.1.4 Atlantic Flyway Breeding Waterfowl Plot Survey ...... 9 3.2 Data Development...... 10 3.2.1 Conservation and Recreation Lands ...... 10 3.2.2 Potential Restoration Layer...... 10 3.2.3 Row Crop, Grassland and Pasture/Hay Layer ...... 11 3.2.4 Potential Grassland Layer...... 11 3.2.5 Mallard Distribution Layer ...... 12 3.2.6 Mallard Productivity Layer...... 13 3.3 Waterfowl Priority Areas...... 13 3.4 Decision Support System Tools...... 13 4. RESULTS...... 15 4.1 Conservation and Recreation Lands (CARL)...... 15 4.2 Potential Wetland Restoration Layer ...... 16 4.3 Row Crop, Grassland and Pasture/Hay Layer ...... 17 4.4 Potential Grassland Layer ...... 19 4.5 Mallard Distribution Layer ...... 20 4.6 Mallard Productivity Layer...... 21 4.7 Waterfowl Priority Areas...... 22 4.8 Decision Support System Tools...... 23 6. LITERATURE CITED ...... 24

Ducks Unlimited, Inc. 2 November 2005

ACKNOWLEDGEMENTS

Funding for this project was through a cooperative agreement with the American Bird Conservancy, U.S.D.A. Forest Service, U.S. Fish and Wildlife Service, and Ducks Unlimited, Inc.

The Great Lakes HEN model was used to prioritize breeding waterfowl habitats in the St. Lawrence was developed through cooperative agreements with: EPA Great Lakes National Program Office; Herbert H. and Grace A. Dow Foundation; Indiana Department of Natural Resources; Institute for Wetland and Waterfowl Research of Ducks Unlimited Canada; Kellogg Bird Sanctuary; Michigan Department of Natural Resources; Michigan State University; Ohio Department of Natural Resources; Saginaw Bay Watershed Initiative Network; The Bruning Foundation; The Christel DeHaan Family Foundation; Upper Mississippi River-Great Lakes Joint Venture; USFWS Great Lakes Coastal Program; West Rosendale Hunt Club; Winous Point Conservancy; Wisconsin Department of Natural Resources; and Ducks Unlimited, Inc.

DISCLAIMER

The data and analysis used in this project were developed for landscape level planning and should be used only after careful consideration of the scale, accuracy, and applicability. Ducks Unlimited, Inc. makes no representation or warranty of any kind regarding this material, data and information, including, but not limited to, the accuracy of the material, data and information or its suitability for any purpose. All use of the material, data and information is at the user’s sole risk. By using any of this material, data and information, the user agrees that Ducks Unlimited, Inc. is not responsible for their use of the material, data and information or the results thereof.

For additional information about the project, report, or maps, please contact: Ducks Unlimited, Inc., Great Lakes/Atlantic Regional Office, 331 Metty Drive, Suite 4, Ann Arbor, MI 48103, (734)-623-2000.

Ducks Unlimited, Inc. 3 November 2005 ABSTRACT

The Atlantic Coast Joint Venture is developing a strategic conservation planning effort for priority bird species in Bird Conservation Region 13 (BCR 13). These efforts will include both geographically explicit recommendations on priority sites for conservation action and recommendations on how to effectively manage the habitat needs of a diverse set of priority species over large geographic extents. This pilot project developed the geographic data recommended by the Joint Venture for bird conservation, applied the Great Lakes breeding waterfowl model, and developed an Internet based data viewer for the St. Lawrence Valley Focus Area. The six primary data layers developed were: potential wetlands, existing wetlands, existing grasslands, potential grasslands, conservation lands, and waterfowl distributions. The results of the waterfowl model identified priority areas for protection and wetland restoration for breeding waterfowl. All of the data, including aerial photos and base maps, were incorporated into an Internet map viewer. The data and methods used in this pilot project could be expanded for bird conservation throughout BCR 13.

Ducks Unlimited, Inc. 4 November 2005

1. INTRODUCTION

1.1 Joint Ventures and Bird Conservation

The North American Waterfowl Management Plan (NAWMP) was developed by the United States, Canadian, and Mexican governments during the 1980’s when waterfowl populations plummeted to record lows. Realizing that implementing the NAWMP was beyond the scope of any one organization, regional partnerships were formed to transform the goals of the Plan into on-the-ground action. The regional partnerships are called “joint ventures” and are comprised of individuals, corporations, conservation organizations, and local, state, provincial, and federal agencies.

The Atlantic Coast Joint Venture (ACJV) is one of the original joint ventures and initially focused on protecting and restoring habitat for the American Black Duck and other waterfowl species. While maintaining this strong focus on waterfowl, the ACJV mission has evolved to include the conservation of habitat for all birds. At the regional scale, the ACJV is integrating bird conservation efforts in the eight Bird Conservation Regions (BCRs) partially or wholly within the Joint Venture. Currently, a draft bird conservation plan has been developed for the Lower Great Lakes – St. Lawrence Plain Bird Conservation Region (BCR 13). A number of partner organizations including Audubon New York, Audubon Vermont, New York State Department of Environmental Conservation, U.S. Fish and Wildlife Service, Natural Resource Conservation Service, the Cornell Lab of Ornithology, and Ducks Unlimited are working to better understand the specific distribution and habitat needs of priority species and to determine specific geographic areas for priority grassland, early successional, wetland and forest species in order to focus conservation efforts.

1.2 Great Lakes HEN

The basic scientific information to develop conservation targeting tools for waterfowl habitat program development does not exist on a landscape level within the Great Lakes States. In light of this, Ducks Unlimited (DU) started the planning process for an ambitious three-year research program to identify habitat specific reproductive data for mallards in the spring of 2000. During the planning process of this research, DU realized that it needed a mechanism to translate the results of the Great Lakes Mallard Study into a format that would be usable to both conservation planners and the biologists at the field level. Therefore, HEN, or Habitat Evaluation Network, was developed to turn the results of the research into tools conservation planners and biologists can use to target and identify habitat restoration in the Great Lakes.

Ducks Unlimited, Inc. 5 November 2005 2. PROJECT AREA

The project area for developing a strategic conservation planning effort for priority bird species includes Bird Conservation Region 13 (BCR 13). BCR 13 includes parts of Ohio, Pennsylvania, New York, and Vermont in the United States and parts of Ontario and Quebec in Canada (Figure 1). This pilot project developed the data and methods for the St. Lawrence Valley Focus Area within BCR 13 (Figure 2).

Figure 1. The Bird Conservation Region 13

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Figure 2: The St. Lawrence Valley Focus Area.

Ducks Unlimited, Inc. 7 November 2005 3. METHODS

3.1 Existing Data

3.1.1 National Wetlands Inventory (NWI)

NWI digital data files are records of wetlands location and classification as developed by the U.S. Fish & Wildlife Service. The classification system was adopted as a national classification standard in 1996 by the Federal Geographic Data Committee. This dataset is one of a series available in 7.5 minute by 7.5 minute blocks containing ground planimetric coordinates of wetlands point, line, and polygon features and wetlands attributes. When completed, the series will provide coverage for all of the contiguous United States, Hawaii, Alaska, and U.S. protectorates in the Pacific and Caribbean.

Coverage includes both digital data and hardcopy maps. The NWI maps do not show all wetlands since the maps are derived from aerial photo interpretation with varying limitations due to scale, photo quality, inventory techniques, and other factors. Consequently, the maps tend to show wetlands that are readily photointerpreted given consideration of photo and map scale. In general, the older NWI maps prepared from 1970s-era black and white photography (1:80,000 scale) tend to be very conservative, with many forested and drier-end emergent wetlands (e.g., wet meadows) not mapped. Maps derived from color infrared photography tend to yield more accurate results except when this photography was captured during a dry year, making wetland identification equally difficult. Proper use of NWI maps therefore requires knowledge of the inherent limitations of this mapping. It is suggested that users also consult other information to aid in wetland detection, such as U.S. Department of Agriculture soil survey reports and other wetland maps that may have been produced by state and local governments, and not rely solely on NWI maps.

For this project, the NWI data was downloaded from the US Fish and Wildlife Service’s NWI website (http://www.nwi.fws.gov/) as individual 24k quads. These quads were then merged and the upland class was removed. The data was then selected based on the St. Lawrence pilot study area.

3.1.2 Coastal Change Analysis Program(C-CAP)

This data is the 2000 era or late-date classification done by NOAA Coastal Services Center (http://www.csc.noaa.gov/crs/lca/ccap.html ). This data set consists of about 1 partial Landsat 7 Thematic Mapper scenes which were analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine to improve the understanding of coastal uplands and wetlands, and their linkages with the distribution, abundance, and health of living marine resources. The data were field validated and subsequently mosaicked to produce a land cover inventory for a portion of the US Great Lakes Coastal Zone.

Ducks Unlimited, Inc. 8 November 2005 3.1.3 St. Lawrence River Valley

The boundary for the St. Lawrence pilot study based on the Wetland and Grassland Management District.

3.1.4 Atlantic Flyway Breeding Waterfowl Plot Survey

Prior to 1989, no regional survey of waterfowl breeding populations in the northeast United States existed. In 1989, the Atlantic Flyway Technical Section initiated this breeding waterfowl survey in 11 northeast states from New Hampshire to Virginia. The purpose of this survey was to collect breeding population abundance data that would support effective management of eastern waterfowl breeding populations. Prior to this survey (and Federal breeding waterfowl surveys initiated in 1990 in eastern Canada and Maine) eastern waterfowl populations were managed based on data collected for mid- continent populations. This survey was designed primarily to estimate population sizes of mallards (Anas platyrhynchos platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), however all observed waterfowl are recorded.

During this survey, approximately 1,500 1-km2 plots are surveyed each spring by biologists from participating states. The survey plots are randomly allocated among nearly 20 physiographic strata. Plots are assigned to be surveyed during twilight or mid- day, and surveyed during the same time each year. Sample plots are surveyed in most cases from the ground by either automobile, boat, or on foot. Ducks are counted as pairs, lone drakes, drakes in groups of 2-4 birds, and mixed-sex flocks of 5 or more birds. Canada geese (Branta canadensis) and mute swans (Cygnus olor) are counted as pairs, single birds, and groups of 3 or more birds. From these counts, the numbers of pairs and total birds are estimated for each plot. These estimates are then expanded to provide estimates for the each stratum, the entire study area, strata within states, and entire states.

In 1993, several changes were made to the survey procedures. Prior to 1993 certain plots were checked annually, while others were re-selected each year. In 1993, all plot locations were fixed and plots were surveyed every year. Analyses of survey data indicate that the time of day that a plot is surveyed can significantly affect detection probability. Since 1993, survey participants have been instructed to survey plots consistently during the twilight or daylight periods from year to year. Also in 1993, a stratum was delineated from existing BBS strata, primarily the Coastal Plain stratum. Data are only consistent since 1993 and only data from 1993 to the present are available online.

Users of the data presented here are encouraged to consult Heusmann and Sauer (1997, 2000) for more detailed discussions of survey procedures and analyses.

Count Database: This database records the number of total indicated pairs (IP) and total indicated birds (TIB) at the level of the individual plot, the primary unit on which waterfowl are counted and summarized for this survey. The number of IP and TIB for

Ducks Unlimited, Inc. 9 November 2005 mallards, black ducks, wood ducks, and Canada geese, total counts for other species, and the total number of ducks on the plot are available from 1993 to the present. Starting in 2003, IP and TIB are available for blue-winged and green-winged teal, hooded and common mergansers, and mute swans.

3.2 Data Development

3.2.1 Conservation and Recreation Lands

Information for the St. Lawrence River Valley Conservation and Recreation Lands (CARL) layer came from three primary sources: digital parcel information obtained from the counties, hardcopy maps, and the State of NY Department of Environmental Conservation's ARC IMS site. Jefferson and St. Lawrence counties had existing parcel information in digital format.

All NY taxable parcels are assigned a 3 digit property classification scheme, which was very useful in creating the CARL layer. The classification scheme can be found at http://www.orps.state.ny.us/assessor/manuals/vol6/ref/prclas.htm#PUBLIC%20PARKS . This classification scheme is maintained by the NY Office of Real Property Services. St. Lawrence County parcel data was more recent and more complete the Jefferson County parcel data at the time this CARL layer was created.

Hard copy maps from the Thousand Island Lands Trust, Jefferson County, and numerous state forest/state parks maps were used to create the CARL layer. The boundary delineation from some of these sources was often less accurate than the digital parcel data.

The NY Department of Environmental Conservation's ARC IMS site was also used to create the CARL layer. That site can be found at http://www.dec.state.ny.us/apps/statelands/ . In addition, each CARL record has a "source" attribute that describes where the information was obtained for that record.

3.2.2 Potential Wetland Restoration Layer

The process to create the Potential Wetlands layer was developed to identify areas that could potentially be restored to wetlands. Most wetland restorations in the Great Lakes occur on current or former cultivated lands due to the economics of farming hydric soils and landowner incentives to convert these lands to wetlands from government and private programs. Therefore, those hydric soils with a history of agriculture have potential for conversion to wetlands. However, detailed county level soils data is not available for a large portion of the Great Lakes. Since the surface soil moisture of fallow fields and exposed bare soils can be detected using the thermal and infrared portions of the electromagnetic spectrum, it is possible to classify the soil moisture from satellite imagery (Ducks Unlimited, 2005).

Ducks Unlimited, Inc. 10 November 2005 Landsat 7 ETM scenes for path 15 rows 29 and 30 from April 28, 2001 were mosaicked together. This scene was then masked to remove cities, roads, water, wetlands, existing grassland and to clip it to the St. Lawrence River Valley boundary. After removing as much of the unwanted classes as possible, a series of 220 class unsupervised classifications were run. Each of the classifications removed unwanted classes, leaving only bare soil and crop. The original scene was then masked to produce two separate scenes, one with only bare soil and one with only crop. The bare soil was run through a 100 class unsupervised classification, and the signature file was run through the pixel grouping program CLUSTAR. Using CLUSTAR’s groupings as a guide, the bare soil was classified into five classes; very wet, wet, intermediate, dry and very dry. The very wet, wet and intermediate classes were then merged to create the potential wetland layer. This layer was then converted into a shapefile and all stray polygon clusters smaller then 0.5 acres were deleted.

3.2.3 Row Crop, Grassland and Pasture/Hay Layer

Landsat 7 ETM scenes for path 15 rows 29 and 30 from April 28, 2001 and path 15 row 29 from October 2, 2000 were masked to remove cities, roads, water, wetlands, existing grassland and to clip it to the St. Lawrence River Valley boundary. A series of 100 class unsupervised classifications were run to identify bare soil, grass and pasture/hay. The results of the classifications were then merged using a conditional model.

Once merged, the raster was converted into a shapefile, acreage was calculated, and all polygons under 5 acres were removed. The USDA Farm Service Agency (FSA) had completed a common land unit dataset for Jefferson County. This dataset consists of digitized farm tract and field boundaries. Zonal statistics was run with the soil/grass/hay layer and the common land units. Each field polygon was classified based on the predominant class (majority) as determined by the Landsat classification.

The dataset was then overlaid on digital orthophotos (1994-1997). The data was checked by panning at a scale of 1:24000, and correcting any obvious errors. In addition two datasets from 2005 were also used to help correct errors in the classification. One set covered Jefferson County where land use was field verified at 210 locations as part of grassland bird surveys (Lazazzero, 2005). The other dataset had around 70 locations in the St. Lawrence River Valley where land use was field verified as part of grassland bird surveys (Morgan, 2005).

3.2.4 Potential Grassland Layer

Landsat 7 ETM scenes for path 15 rows 29 and 30 from April 28, 2001 were mosaicked together. This scene was then masked to remove cities, roads, water, wetlands, existing grassland and to clip it to the St. Lawrence River Valley boundary. After removing as much of the unwanted classes as possible, a series of 220 class unsupervised classifications were run. Each of the classifications removed unwanted classes, leaving

Ducks Unlimited, Inc. 11 November 2005 only bare soil and crop. The original scene was then masked to produce two separate scenes, one with only bare soil and one with only crop.

The bare soil was run through a 100 class unsupervised classification, and the signature file was run through the pixel grouping program CLUSTAR. Using CLUSTAR’s groupings as a guide, the bare soil was classified into five classes; very wet, wet, intermediate, dry and very dry.

The crop layer and the dry and very dry classes of bare soil were then merged to create the potential grassland layer. This layer was then converted into a shapefile and all stray polygon clusters smaller then 1.0 acres were deleted.

3.2.5 Mallard Distribution Layer

Mallard survey data from 1993 to 2003 for the state of New York was extracted from the Atlantic Flyway Breeding Waterfowl Plot Survey data. This tabular data was joined to the spatial plot data and all plots without corresponding National Wetlands Inventory (NWI) data were removed. The NWI attribute field was truncated down to class level and the NWI shapefile was clipped to the New York waterfowl plots. The clipped NWI data was then intersected with the New York waterfowl plot data. The area of each NWI wetland class present in each waterfowl survey plot was calculated. This data was then sent to a Ducks Unlimited Canada statistician, where the formula was developed to model average mallard numbers as a function of NWI classes.

Predicted Square-Root of Mallards = 0.4959 + (0.0095 * Lacustrine 1) + (0.0290 * Palustrine Emergent) + (0.0671 * Palustrine Unconsolidated Bottom) + (0.0196 * Palustrine Scrub/Shrub) + (0.0053 * Palustrine Forested) + (0.0023 * Estuarine) + (0.0202 * Riverine) [R-Square .3603]

A grid value field was added to the merged NWI shapefile and calculated as follows: 1 Lacustrine 1 2 Palustrine Emergent 3 Palustrine Unconsolidated Bottom 4 Palustrine Scrub/Shrub 5 Palustrine Forested 6 Estuarine 7 Riverine

All zero values were removed and the shapefile was converted to a 33.3m GRID.

The New York wetlands layer was recoded into 7 individual wetland layers, each having a value of 1 for the desired class and zero for the rest. Focal Sums were run on each of the 7 wetland layers in a 30 x 30 area (the formula is based upon a 1 km square area, 30 – 33.3 cells = @1000m). The 7 focal sum layers were then run through the formula

Ducks Unlimited, Inc. 12 November 2005 [Predicted Square-Root of Mallards = 0.4959 + (0.0095 * Lacustrine 1) + (0.0290 * Palustrine Emergent) + (0.0671 * Palustrine Unconsolidated Bottom) + (0.0196 * Palustrine Scrub/Shrub) + (0.0053 * Palustrine Forested) + (0.0023 * Estuarine) + (0.0202 * Riverine)] to arrive at the predicted mallard distribution. This layer was then clipped to the boundary of the state of New York and further down to the St. Lawrence River Valley boundary.

3.2.6 Mallard Productivity Layer

The Great Lakes Mallard Model (Coluccy, et al.) runs on two input parameters; Nest Success and Fledgling Survival. Both of these parameters are derived from landscape variables based upon research conducted during the Great Lakes Mallard Study. Nest Success is a proportion of crop in an area to the total area (predicted nest success = 0.22281 – (0.1803* Area of Crop/Total Area). The St. Lawrence CCAP crop value (4) was used to calculate the area of crop. Predicted Fledgling Survival is based on the formula; Predicted Fledgling Survival = 0.1440 + (0.5432 * PWWEM) – (0.3800 * Forest) Where PWWEM = (Aquatic Wetland + Scrub-shrub wetland + Emergent wetland + Forested wetland) / (Aquatic Wetland + Scrub-shrub wetland + Emergent wetland + Forested wetland + Open water + Other wetland) And where Forest = (Deciduous forest + Coniferous forest + Mixed forest + Shrubland)/ Total Area. The areas of landcover were derived from the St. Lawrence CCAP dataset. Once the Nest Success and Fledgling Survival layers were completed, their values were run through the Great Lakes Mallard Model to get a lambda (productivity) value.

3.3 Waterfowl Priority Areas

The waterfowl priority areas are square kilometer cells prioritized for either protection or wetland enhancement. The priority is based upon the predicted distribution of mallards and their productivity. The mallard distribution was used to select cells which had a distribution of breeding mallards greater than one pair per square kilometer. The mallard productivity layer was then used to prioritize either protection if populations were stable or increasing, or wetland enhancement if the populations were declining.

3.4 Decision Support System Tools

The map viewer allows anyone with access to the Internet the ability to view and analyze the data created for this project. It can be used as both an analysis tool and data viewer. The map viewer has navigation tools, which allow for zooming (both in and out), panning, and the capability to zoom to the previous extent (the last area viewed). The analysis tools include a measure tool (allows for distance measurements), polygon area tool (can calculate acreage/hectare/square miles/square meters for a digitized polygon), locate address tool (a geocoding tool which finds an address along a road segment), and

Ducks Unlimited, Inc. 13 November 2005 select by location tool. The select by location tool is capable of finding like features by either placing a point, line, or polygon onto the map and buffering the shape (point/line/polygon) by some user defined distance.

Ducks Unlimited, Inc. 14 November 2005

4. RESULTS

4.1 Conservation and Recreation Lands (CARL)

There are approximately 225,950 acres included in the CARL layer (some of which are outside the St. Lawrence River Valley pilot study area). This layer is comprised of digital parcel data, information from other data layers and hard copy maps. Only St. Lawrence and Jefferson counties had digital parcel data available, and some of this data was poorly attributed. It is also likely that there are many easements held by local conservancies as well as enrolled in federal programs that are not represented in this data layer.

Figure 3. Conservation and Recreation Lands (CARL)

Ducks Unlimited, Inc. 15 November 2005 4.2 Potential Wetland Restoration Layer

The potential wetland restoration layer indicates there are approximately 132,300 acres which could be restored to wetland in the St. Lawrence River Valley. It should be noted that this layer was created by classification of a single-date Landsat 7 ETM scene. A classification of wet soil may be the result of local rain events, farming practice (i.e. recent tilling), or even shadow. Also, many wetlands, especially tidal areas and mud flats did not show up in the National Wetland Inventory, but being bare wet soil did get classified as restorable.

Figure 4. Potential Wetland Restoration sites.

Ducks Unlimited, Inc. 16 November 2005 4.3 Row Crop, Grassland and Pasture/Hay Layer This layer shows a snapshot of vegetation types. Row crops and pasture/hay are often used in rotation and can vary from year to year, while grasslands naturally convert to scrub-shrub and eventually to forests. It would have been best if the Landsat scenes used were from the same growing season as opposed to fall one year and the next spring. This would help to insure the fields did not change between growing seasons, a hay field plowed up for row crop for example. Also, the orthophotos used to verify data were from 1994-1997, so change may have also occurred between the Landsat scenes and the photos. Finally, the field site data was from 2005. In order to insure an accurate assessment of what is on the ground at a given time, it would be necessary to use data all from the same growing season.

Figure 5. Row crops, grassland and pasture/hay.

Ducks Unlimited, Inc. 17 November 2005

Figure 6. An example of where the field studies (orange circle and triangle) indicate grassland (2005), whereas the Landsat (2001) scene suggests tilled fields.

Ducks Unlimited, Inc. 18 November 2005 4.4 Potential Grassland Layer

There are approximately 327, 300 acres which could be restored to grassland in the St. Lawrence River Valley. This layer consists mainly of lands which are currently in agriculture, but due to the nature of the classification there are also many areas which are currently mowed grass. In the spring, fields planted with winter wheat will have a very similar spectral signature to lawns, parks and sports fields.

Figure 7. Potential grassland restoration sites.

Ducks Unlimited, Inc. 19 November 2005 4.5 Mallard Distribution Layer

The Mallard Distribution layer is the predicted distribution of breeding mallards based upon waterfowl surveys and wetland type. The waterfowl survey had 20 sites located in the St. Lawrence River Valley. National Wetlands Inventory data was available for the St. Lawrence River Valley area, but there are still many limitations associated with the data, including age and interpretation.

Figure 8. Predicted distribution of breeding mallards.

Ducks Unlimited, Inc. 20 November 2005 4.6 Mallard Productivity Layer

The formulas used to calculate nest success and fledgling survival were developed from data collected during Ducks Unlimited’s Great Lakes Mallard Survey. The Survey included study sites from Michigan, Ohio, Indiana, Illinois and Wisconsin. Though most of the habitat in these areas is similar to the St. Lawrence River Valley, it should be noted that none of the study targeted the area specifically.

Figure 9. Predicted mallard productivity.

Ducks Unlimited, Inc. 21 November 2005 4.7 Waterfowl Priority Areas

According to the Waterfowl Priority Areas layer, there are 245,271 acres which could be protected and another 161,538 acres for wetland enhancement in the St. Lawrence River Valley area. Some of these acres fall just outside the area, as buffered datasets were used to create the layer. Also, there may be some edge effect from the process due to the lack of NWI data for Canada, which would lower the predicted mallard distribution along the St. Lawrence River.

Figure 10. Waterfowl priority areas.

Ducks Unlimited, Inc. 22 November 2005 4.8 Decision Support System Tools

To view the decision support system tools, go to http://glaro.ducks.org and select the St. Lawrence map viewer link. If new to internet mapping sites use the help button on the top tool bar.

Figure 11. Screen capture of the St. Lawrence map viewer.

Ducks Unlimited, Inc. 23 November 2005

6. LITERATURE CITED

Heusmann, H.W. and J.R. Sauer. 1997. A survey for mallard pairs in the Atlantic Flyway. Journal of Wildlife Management 61:1191-1198.

Heusmann, H.W. and J.R. Sauer. 2000. The northeastern states’ breeding waterfowl population survey. Wildlife Society Bulletin 28:355-364.

Lazazzero, S. and C. Norment. 2005. A multi-scale analysis of grassland bird habitat relations in the St. Lawrence River Valley, with a focus on Henslow's Sparrows. Final report prepared for the Nature Conservancy. Department of Environmental Science and Biology, SUNY College at Brockport. 80 pp.

Morgan, Michael R. 2005. Survey of grassland bird abundance, distribution, and habitats in New York. Audubon New York.

Ducks Unlimited. 2005. Development of a Potential Wetland Restoration Layer for Research and Planning in the Great Lakes. Final report submitted to U.S. Fish and Wildlife Service. DU Great Lakes/Atlantic Regional Office, Ann Arbor, MI. 32pp (plus CD).

Coluccy, J.M., T. Yerkes, R. Walling, J.W. Simpson, and L. Armstrong. Population dynamics and sensitivity analyses of breeding mallards in the Great Lakes states. Journal of Wildlife Management. In preparation.

Ducks Unlimited, Inc. 24 November 2005