### 1 WETLANDS, Vol. 21, No. 1, March 2001, pp. 1–172001, The Society of Wetland Scientists



## A LANDSCAPE APPROACH TO CONSERVING WETLAND BIRD HABITAT IN THE PRAIRIE POTHOLE REGION OF EASTERN SOUTH DAKOTA1



### David E. Naugle College of Natural Resources University of Wisconsin Stevens Point, Wisconsin, USA 54481

Rex R. Johnson North American Waterfowl and Wetlands Office Patuxent Wildlife Research Center Laurel, Maryland, USA 20708

Michael E. Estey U.S. Fish and Wildlife Service Habitat and Population Evaluation Team Bismarck, North Dakota, USA 58501

Kenneth F. Higgins South Dakota Cooperative Fish and Wildlife Research Unit U.S. Geological Survey South Dakota State University Brookings, South Dakota, USA 57007

Abstract: Resource managers confronted with preserving ecosystems for prairie wetland birds in fragmented landscapes require landscape studies that direct conservation efforts over broad geographic regions. We investigated the role of local and landscape factors affecting habitat suitability by integrating remotely sensed wetland and land-cover data with wetland bird habitat models. We linked habitat models with locations of easement and fee-title wetlands to evaluate spatial location and extent of protected, suitable habitat. We also simulated impacts of the loss of small wetlands on suitability of larger wetlands for mobile species that use multiple wetlands. Lastly, we evaluated the efficacy of waterfowl habitat programs in preserving suitablehabitat for nongame wetland bird species to recommend strategies for maximizing regional landscape connectivity. Regional databases constructed for this study indicate that easement and fee-title tracts encompass 13.9% (1.2 million ha) of land area and protect 19.8% of the wetlands in eastern South Dakota, USA. Proportion of protected wetlands is highest for semi-permanent (32.3%), intermediate for seasonal (25.6%), and lowest for temporary wetlands (15.8%). A stratified, two-stage cluster sample was used to randomly select 834 semi-permanent and seasonal wetlands that were surveyed for birds in 1995 and 1996. Logistic analyses indicate that habitat suitability for some species (e.g., Virginia rail, pied-billed grebe) is related to local vegetation conditions within wetlands, while suitability for others (e.g., northern pintail, black tern) is related to landscape structure at larger scales. As a result, unfragmented prairie wetland landscapes (i.e., areas with wetland complexes embedded within upland grasslands) provide habitat for more species than isolated wetlands in tillage fields. Models developed from survey wetlands were used to classify habitat suitability for all semi-permanent and seasonal wetlands in eastern South Dakota. Small wetlands are critical components of the surrounding landscape that influence habitat suitability of larger wetlands. Models used to reclassify suitability of larger remaining wetlands after small wetlands (0.5 ha) were removed indicate that species most vulnerable to loss of small wetlands are vagile species that exploit resources over broad spatial scales. Number of wetlands suitable for northern pintails, a mobile species that uses multiple wetlands within a season, decreased 20.7% when wetlands 0.5 ha were removed. Historic paradigms dictating waterfowl habitat protection efforts also have conserved habitat for nongame bird species. Modern paradigms that acknowledge the importance of small shallow wetlands to breeding waterfowl have shifted the focus of protection towards preserving habitat for species that occupy more abundant seasonal wetlands. Cessation of protection efforts would result in further fragmentation of regional wetland landscapes. We recommend that wetlands be acquired not only to consolidate suitable habitat within protected core areas but also to ensure that core areas coalesce to preserve connectivity among regional wetland landscapes.

Key Words: habitat fragmentation, landscapes, nongame, Prairie Pothole Region, small wetlands, South Dakota, waterfowl, wetland birds, wetland protection

1 This manuscript was previously published in Volume 20, No. 4; however, a printer error resulted in failure to include color figures necessary to illustrate results properly. The Editor-in-Chief made the decision to reprint the paper in this issue in its intended form.

### 2 WETLANDS, Volume 21, No. 1, 2001

Figure 1. Remotely sensed wetland and land cover data and easement and fee-title tracts were combined with habitat suitability models for 20 prairie wetland bird species in a GIS to evaluate the location and extent of protected, suitable wetland habitat. 

### INTRODUCTION

Local vegetation structure has long been known to affect habitat use by prairie wetland birds (e.g., Weller and Spatcher 1965, Kaminski and Prince 1981,1984, Murkin et al. 1997), whereas more recent research has indicated that landscape attributes also may influence local species abundance and diversity (e.g., Pearson 1993, Koopowitz et al. 1994, Vos and Stumpel 1995). In a little over a century, the Prairie Pothole Region (PPR) of North America has been transformed from a contiguous expanse of wetlands and grasslands into a highly fragmented agricultural landscape. Wetland ecosystems provide principal breeding and foraging habitats for about one quarter of the regional avifauna,most of which are nongame species. Resource managers confronted with preserving ecosystems for prairie wetland birds require large-scale studies that direct wetland conservation over broad geographic regions to complement what has been learned at local scales (Flather and Sauer 1996, Haig et al. 1998). Managers continue to extrapolate recommendations from local studies to regional conservation planning because few studies have taken a landscape approach to evaluation. Recent advances in geographic information systems(GIS) and remote sensing technologies now enable researchers to use sampling strategies that result in inferences over larger landscapes. Landscape-level research, which is lacking in wetland ecosystems, is used in forested ecosystems to direct conservation efforts and design reserve systems (e.g., Askins et al. 1987, Robbins et al. 1989, Hansson and Angelstam 1991,Pearson 1993, Flather and Sauer 1996). Pioneering research by Brown and Dinsmore (1986), involving 30 marshes in northwest Iowa, demonstrated that wetland bird species richness was related to wetland area and isolation. Although Johnson and Grier (1988) found that waterfowl settling patterns were related to specieslife history characteristics and regional wetland conditions, additional research is needed to identify how prairie wetland birds relate to habitat variability across local and landscape scales. In this study, we investigated the role of local and landscape attributes in predicting habitat suitability for 20 wetland bird species by integrating remotely sensed wetland and land-cover data with models of habitat suitability (Figure 1). Habitat models were linked with locations of easement and fee-title lands to evaluatelocation and extent of protected, suitable wetland habitat. We also simulated impacts of the loss of small wetlands on suitability of larger wetlands for mobilespecies that exploit wetland resources over broad spatial scales. Lastly, we evaluated the efficacy of waterfowl habitat programs in preserving suitable habitat for nongame wetland bird species to recommend strategies for maximizing regional landscape connectivity.

STUDY AREA The study area encompassed eastern South Dakota, USA from the Minnesota border west to the Missouri River. We divided the region into 3 domains, PrairieCoteau (28.7%), Central Lowlands (44.3%), and Missouri Coteau (27.0%), based on similarity of wetlandcharacteristics (Figure 2). The Prairie Coteau is characterized by an abundance of semi-permanent and permanent wetlands. The Central Lowlands, a low relieflandscape, has an abundance of seasonal and temporary wetlands. The Missouri Coteau has numerous sea-

### Naugle et al., WETLAND BIRD HABITAT 3

Figure 2. A delineation of the 3 domains (Missouri Coteau, Central Lowlands, Prairie Coteau) defined for surveyingwetlands in eastern South Dakota. Domains are modifications of 6 major physiographic regions that were previously delineated using soil characteristics (Johnson et al. 1995). Shaded area in the lower left corner depicts the full extent of the Prairie Pothole Region in the USA. 

### sonal wetlands in the northeast and fluviatile wetlands throughout the south and west. Johnson and Higgins (1997) provide a comprehensive characterization of wetland habitats in eastern South Dakota. Variable wet-dry cycles (Winter 1989) in the PPR make wetland conditions inherently unpredictable.Wet hydrologic conditions in the study area kept seasonal and semi-permanent wetlands inundatedthroughout the breeding season. Remaining native upland vegetation throughout eastern South Dakota is tall-grass/mixed-grass prairie (Westin and Malo 1978). Abundance of native and non-native grasslands (e.g.,Conservation Reserve Program [CRP] fields) varies regionally. Native sod is most abundant in the Missouri Coteau and in northerly portions of the Prairie Coteau. Farming is intensive in the remainder of the Prairie Coteau and throughout the Central Lowlands wheresmall grains and row crops have replaced native upland vegetation.

METHODS Creation of GIS Data Layers Wetland Coverages. We used National Wetlands Inventory (NWI) maps and converted wetlands to wetland basins using techniques described by Cowardinet al. (1995) and Johnson and Higgins (1997). Polygons defining adjacent wetlands were combined to delineate contiguous wetland basins. Basins were classified as temporary, seasonal, semi-permanent, or permanent by the water regime of the most permanent wetland they contained. Polygons labeled as excavated semi-permanent wetlands were reclassified according to the most permanent water regime of the surroundingnatural wetland to ensure that our findings would reflect wetland bird habitat use of natural depressions. Isolated excavated and impounded semi-permanentwetlands were excluded from analyses. Linear wetlands (e.g., drainage ditches) were eliminated from the GIS to minimize bias in estimated wetland density (Johnson et al. 1999). We compared log-transformed densities of temporary, seasonal, semi-permanent, and permanent wetlands among 3 physiographic domains(Figure 2) using analysis-of-variance. Multiple comparisons were performed using Tukey’s pairwise mean comparisons.

Easement and Fee-title Tracts. We manually transferred map boundaries for waterfowl production areas, perpetual wetland easements, national wildlife refuges acquired by the U.S. Fish and Wildlife Service (USFWS) (1:21,120 scale), and game production areas acquired by South Dakota Department of Game, Fish and Parks (1:63,360 scale) before 30 September 1994 to copies of NWI maps (1:24,000 scale) (Estey 1998). We then digitized tract boundaries to create wetlandprotection coverages encompassing eastern South Dakota. Land-Cover Data. Landsat Thematic Mapper imagery from 8 scenes covering eastern South Dakota wereused to classify uplands into tilled and untilled vegetation classes. Untilled lands were permanent pastures, CRP grasslands, and alfalfa. We used imagery newer than 1990 (April and May 1991 and 1992 scenes) toensure that changes in CRP enrollment were incorporated into land-use classifications. Trees, which constituted 1% of area in eastern South Dakota, were not distinguished from untilled herbaceous grassland cover types. Crops and annually fallowed areas were considered tilled lands. Naugle et al. (1999) provide descriptions of methods used to process imagery and assess accuracy of classifications. Overall, per-pixel classification accuracy for the map was 97%.

Wetland Selection Process A grid comprised of
 3,800 25.9-km2 

### cells was overlayed onto wetlands. A cell size of 25.9 km2 

### was

### 4 WETLANDS, Volume 21, No. 1, 2001

Figure 3. Four landscape types used to characterize the wetland complex surrounding surveyed wetlands. Solid polygons depict semi-permanent wetlands while hatched polygons are seasonal wetlands. Each cell is 25.9 km2 in

area. 

### selected to maximize between-cell variability (Stoms 1992) and minimize bias associated with estimatingnumber of wetlands using quadrats (Johnson and Higgins 1998). The center of wetlands was used to assignthem to a single cell. Wetland area encompassed within a cell was used to estimate total wetland area. Median values of the frequency distributions for wetland densities (110 wetlands) and areas (124 ha) per cellwere used to classify cells within domains into 4 Landscape Types (Figure 3): Landscape Type a cells were low in wetland density and area, Type b cells were high in density and low in area, Type c cells were low in density and high in area, and Type d cells were high in density and in area. We randomly selected 216 cellsallocated equally across landscape types within domains in 1995 and 1996 (Figure 4). In 1996, 7 more cells of Landscape Type a were randomly selected from each domain to ensure an adequate sample of semi-permanent wetlands. Alternate wetlands replaced those that were dry, farmed, burned, or mowed.

Bird Surveys

Two seasonal and 2 semi-permanent wetlands were randomly selected within each cell. After obtainingpermission to access wetlands on private lands, we surveyed 416 semi-permanent and 418 seasonal wetlands from 5 May to 10 July in 1995 and 1996. Surveys were conducted when birds were most active (sunrise to 1000 hr and 1800 hr to sunset [Verner and Ritter 1986]). Surveys were not conducted during rainy or windy ( 24 km/h) days. Before entering a wetland, open water was observed from a vantage point, and all birds seen or heard were recorded. Next, we visited a set of predetermined points where tape-recorded calls of Virginia rail ( Rallus limicola Vieillot), sora (Porzana carolina L.), least bittern ( Ixobrychus exilis Gmelin), and American bittern ( Botaurus lentiginosus Rackett) were played to elicit responses from these secretive species (Johnson and Dinsmore 1986, Gibbsand Melvin 1993, 1997). Number of points in a wetland varied with wetland area: 1 point in wetlands 0.5 ha; 2 points in wetlands 0.5–5 ha; 3 points in 5– 10 ha wetlands; and 4 points in wetlands  10 ha (VanRees-Siewert and Dinsmore 1996, Naugle et al. 1999). We visited each point for 8 minutes and began 3 minutes of taped calling during the third minute. We walked the perimeter of each wetland after walking through the emergent vegetation zone to ensure that all species present were detected. Naugle et al. (1999) contains an accuracy assessment of methods used in this study. Bird species were classified as present if we observed adults, active nests, or young. Local Vegetation Variables Percent vegetated wetland area was estimated into the following class intervals using a modification of the Daubenmire scale (Bailey and Poulton 1968): 1) 1%, 2) 1–5%, 3) 6–25%, 4) 26–50%, 5) 51–75%, 6) 76–95%, and 7)  95%. Pattern of emergent vegetation was recorded using the 4 cover-type classifications of Stewart and Kantrud (1971). Grazing intensitywithin wetlands was visually estimated as light, moderate, or heavy. Wetlands were lightly grazed when there was little or no evidence that cattle had beenpresent within the wetland, whereas emergent vegetation in moderately grazed wetlands showed signs of trampling and consumption. Emergent vegetation in heavily grazed wetlands was severely impacted by the presence of cattle. Grazing intensity was estimated onnatural shorelines by visual inspection of residual vegetation and current year’s growth. Shorelines ranged from idled (i.e., 1%) to heavily grazed (i.e.,  95%). Percent of the wetland perimeter occupied by woody vegetation (i.e., willow [Salix spp.] and cottonwood [Populus deltoides Marsh]) was recorded into class in-

### Naugle et al., WETLAND BIRD HABITAT 5

Figure 4. Distribution of 25.9 km2 cells used to evaluate prairie wetland bird use of semi-permanent and seasonal wetlands in the Missouri Coteau, Central Lowlands, and Prairie Coteau domains of eastern South Dakota. Table 1. Description of local and landscape variables used to evaluate habitat suitability for 20 wetland bird species in eastern South Dakota. Acronyms in text are shown in parentheses.

Local variables quantified within or immediately adjacent to the wetland Percent vegetated wetland area (COVER) a Index to grazing intensity on shorelines adjacent to wetlands

(GRAZE)a Proportion of wetland perimeter encompassed by trees (TREES) a Variable indicating whether dominant hydrophytes are thick- or

thin-stemmed (STEM)a Number of dominant hydrophytes comprising 10% of vegetated wetland area (NUMB)a Wetland area (AREA) Wetland perimetera Cover type classification b Index to grazing intensity within wetlands Landscape attributes quantified within 25.9 km2 cells surrounding surveyed wetlands Grassland area (GRASS)a Total temporary wetland area (TEMP) a Total seasonal wetland areas (SEAS) a Total semi-permanent wetland area (SEMI)a Total permanent wetland area (PERM)a Number of temporary wetlands Number of seasonal wetlands Number of semi-permanent wetlands Number of permanent wetlands

a Variable included in analyses.

b Cover type classifications (Stewart and Kantrud 1971) describe the distribution of emergent vegetation within wetlands. 

### tervals. Land use adjacent to surveyed wetlands was recorded as tilled or untilled. Class-interval mid-points were used to analyze categorical data. Number of dominant emergent vegetation types comprising  10% of the vegetated wetland area wasrecorded as an index to wetland vegetation heterogeneity. Emergent cover also was used to categorize wetlands into 2 classes of nesting substrates for wetlandbirds. Class 1 substrates were dominated by thickstemmed emergent vegetation types (e.g., cattail [ Typha spp.]) that were capable of supporting the weight of a bird nest. Class 2 substrates were dominated by thin-stemmed emergent vegetation types (e.g., spike rush [Eleocharis spp.] and sedges [Cyperaceae]) whose weaker stems are less capable of supporting a nest.

Landscape Variables Landscape variables calculated using the wetland GIS were total wetland area and density for each of 4 water regimes (temporary, seasonal, semi-permanent, permanent [Stewart and Kantrud 1971]) (Table 1). Data were log-transformed to approximate normality.Area (ha) and shoreline length (m) of the wetland surveyed also were estimated using the wetland GIS. We used land-cover data to estimate area of untilled upland within 25.9-km2 

### cells. Proportion of untilled area was defined as the sum of untilled area divided by thesum of non-wetland area. Percentage data were squareroot transformed to approximate normality. Eleven local and landscape variables were used in analyses (seeTable 1) after others were eliminated to reduce collinearity.

Logistic Regression Habitat Analyses Forward stepwise logistic regression analyses (Cox1970, Wilkinson 1997) were used to evaluate relationships between local and landscape variables and the probability of individual bird species occurrences. McFadden’s Rho-squared statistic, which was used to evaluate model fit, is a transformation of the likelihood ratio statistic intended to mimic R 2 

### values in logistic regression. Rho-squared values normally are lower than R 2 

### values. Rho-squared values  0.20 imply goodmodel fit (Hensher and Johnson 1981). Variables entering the stepwise procedure at P 0.15 were retained when P 0.01. Bird occurrences in seasonal

### 6 WETLANDS, Volume 21, No. 1, 2001

Table 2. Number and area (ha) of wetlands by water regime in the Missouri Coteau, Central Lowlands, and Prairie Coteau domains (modified from Johnson and Higgins 1997).

Domain

Water Regime Missouri Coteau

No. Hectares %a Central Lowlands

No. Hectares % Prairie Coteau

No. Hectares % Temporary Seasonal Semi-permanent b Permanent Total 95,459 81,001 18,443 421 195,324 28,299 59,843 67,477 19,960 175,579 1.2 2.6 2.9 0.6 7.3 328,464 167,925 29,504 452 526,345 100,106 120,523 116,100 38,399 375,128 2.5 3.1 2.9 1.0 9.5 93,232 84,020 25,689 607 203,548 29,333 43,000 106,421 57,066 235,820 1.2 1.7 4.3 2.3 9.5

a Percent of total domain area.

b Includes natural, excavated, and impounded semi-permanent wetlands.



### and semi-permanent wetlands were analyzed separately.

Identifying Suitable Wetlands Using Landscape VariablesWe selected 4 wetland-obligate bird species for further study (mallard [ Anas platyrhynchos L.], northern pintail [ Anas acuta L.], black tern [ Chlidonias niger L.], and eared grebe [Podiceps nigricollis L.]) that differed in their sensitivity to landscape-level variation. We hypothesized that our species-specific approach to evaluating habitat suitability would reveal contrasting perspectives of landscape structure among bird species (Pearson et al. 1996). Forward stepwise discriminantfunction analyses (Wilkinson 1997) was used to classify wetland suitability. Preliminary evaluations indicated that discriminant analyses provided correct classification rates that were
 10% higher than those from logistic analyses. Only landscape variables encoded in the GIS were included in analyses so that functionscould be used to classify suitability of all semi-permanent and seasonal wetlands  0.20 ha in easternSouth Dakota. Jackknife classification rates (Wilkinson 1997) were used as one method of cross-validating our ability to predict potential wetland bird habitat. We also cross-validated our predictive capability using bird survey information collected in 1997 from 75semi-permanent wetlands on the Prairie Coteau domain that were not used in model construction.We classified wetlands in the GIS as suitable or unsuitable according to the largest value of the classification functions for each of the selected species. We calculated the number of suitable wetlands within 25.9-km2 

### cells using the GIS. The easement and feetitle lands coverage was overlayed on wetlands to estimate proportion of suitable wetlands under federal or state protection. We classified wetlands as protected when they were 90% encompassed by an easement or fee-title tract. Effect of Removing Small Wetlands from the LandscapeTwo simulations were conducted to evaluate the potential effect of loss of small wetlands on suitability of larger remaining wetlands. In the first simulation, only unprotected wetlands 0.50 ha were removed, whereas in the second simulation, all wetlands 0.50 ha, regardless of protected status, were removed. Data from the remaining wetland area in cells were used toreclassify wetland suitability for species (northern pintail, black tern) whose presence was related to the totalwetland area in the landscape. We calculated the percent decline in number of suitable wetlands within size categories for each simulation.

RESULTS

Characteristics of Eastern South Dakota WetlandsSummary data indicate that 932,795 wetlands comprised 861,462 ha or 9.4% of eastern South Dakota. Of this number, 925,217 (99.2%) comprising 786,527ha occurred within the 3 study domains (Table 2). Natural semi-permanent wetlands comprised 31.5% of all semi-permanent wetlands. An additional 50.7% wereshallower wetlands containing dugouts or other excavations imparting a semi-permanent water regime, and15.1% were impoundments. Median area of all wetlands was 0.16 ha. Median sizes were 0.92 ha for semipermanent and 0.20 ha for seasonal wetlands. Number of temporary ( F  581.67, df  2, 3245, P 0.001), seasonal (F  29.25, df  2, 3245, P 0.001), semi-permanent ( F  116.98, df  2, 3245, P
0.001), and permanent ( F  19.77, df  2, 3245, P 0.001) wetlands differed among domains (Table 2). Number of temporary ( P 0.001) and seasonal ( P
0.001) wetlands was greater in the Central Lowlands than in the Prairie Coteau and Missouri Coteau, where numbers were similar ( P  0.20). Number of semipermanent and permanent wetlands was greater in the

### Naugle et al., WETLAND BIRD HABITAT 7

Figure 5. Distribution of easement and fee-title tracts encompassing protected wetlands in the Missouri Coteau, Central Lowlands, and Prairie Coteau domains of eastern South Dakota.



### Prairie Coteau than in other domains ( P 0.002). Number of semi-permanent wetlands was greater in the Central Lowlands than in the Missouri Coteau ( P
0.001); however, number of permanent wetlands was greater in the Missouri Coteau than in the Central Lowlands ( P  0.002).

Distribution and Abundance of Protected Tracts We identified 14,840 easement and fee-title tracts encompassing 13.9% (1,271,085 ha) of eastern SouthDakota (Figure 5). Easement and fee-title tracts protected 19.8% (158,139) of all wetlands in eastern South Dakota (Table 3). Protected wetlands comprised22.0% (127,324 ha) of temporary, seasonal, and semipermanent wetland area (Table 3). Easements encompassed 1,138,648 ha and protected 141,242 ha of wetland (Table 4). Federal and state fee-title tracts encompassed 132,440 ha of wetland and upland habitat (Table 4). Proportion of protected wetlands differed amongtemporary (15.8%), seasonal (25.6%), and semi-permanent (32.3%) water regimes (2 

###  6.083, df  2, P

 0.048) (Table 3). Among domains, proportion of protected wetlands of all water regimes was greatestin the Missouri Coteau and least in the Central Lowlands (2 

###  6.091, df  2, P  0.048) (Table 3). Agreater proportion of protected wetlands had semi-permanent water regimes in the Prairie Coteau than in theMissouri Coteau, where a greater proportion had temporary and seasonal regimes (2 

###  7.674, df  2, P 0.022). Proportion of protected wetlands by water regime in the Central Lowlands was similar to proportions in the Missouri Coteau (2 

###  1.559, df  2, P

 0.459) and Prairie Coteau (2 

###  2.421, df  2, P

 0.298) (Table 3). Size structure of protected wetlands by water regime was representative of the sizestructure of the wetland universe (Figure 6). The greatest number of unprotected wetlands had temporary and seasonal water regimes and were 0.50 ha (Figure 7).

Bird-Habitat RelationshipsWe surveyed larger areas of larger wetlands to obtain a complete census of the bird community. We expected larger wetlands to contain more species than smaller wetlands because larger wetlands provide more surface area in which birds may randomly settle during migration. Although bird use of wetlands in this study is a direct reflection of current bird distributionand abundance, we do not interpret AREA relationships (e.g., a species area-sensitivity) because bird use of small wetlands may fluctuate in response to changesin species settling patterns and regional population sizes. AREA was allowed to step into models to accountfor variation explained by area of the surveyed wetland. With AREA included in models, percent vegetated wetland area (COVER) was the most commonvariable related to species’ occurrences in semi-permanent and seasonal wetlands (Tables 5 and 6). For those species where percent vegetated wetland area was a predictor of occurrence, presence of waterfowl species was negative, whereas presence of nongamespecies was positive to COVER (Tables 5 and 6). Total wetland (SEMI or SEAS) and/or total grassland habitat (GRASS) within cells was positively related to the occurrence of 9 bird species.

Classifying Wetland Suitability Using Landscape Attributes Using the discriminant functions, we identified semi-permanent (SEMI) and seasonal (SEAS) wetland area and grassland habitat (GRASS) within cells asuseful in classifying habitat suitability for selected species (i.e., mallard, northern pintail, black tern, eared grebe; Table 7) ( P 0.005 for each function). Allmodel coefficients were positive, indicating that species were positively associated with total wetland and grassland habitat area in the surrounding landscape.Classification rates indicated that discriminant functions correctly classified 75–88% of unsuitable semipermanent and 79–81% of unsuitable seasonal wet-

### 8 WETLANDS, Volume 21, No. 1, 2001

Table 3. Number and area of protected wetlands by water regime within the Missouri Coteau, Central Lowlands and Prairie Coteau domains of eastern South Dakota.

Domain Water Regime Protected

Number % Area % Unprotected

Number Area

Missouri Coteau Temporary Seasonal Semi-permanent 21604 27738

1053 24.6 36.0 27.4 11417 22358

7870 23.3 36.4 31.4 66068 49315

2792 37481 39105

8245

Central Lowlands Temporary Seasonal Semi-permanent 44956 25694

2014 14.5 19.4 23.0 19066 22639

9920 14.2 20.5 22.2 265558 106603

6740 115446 87663 34793

Prairie Coteau Temporary Seasonal Semi-permanent 9988 18849 6243 11.4 25.7 38.5 4501 6719 22826 11.5 18.7 29.3 77307 54411

9988 34549 29098 55197 Domains combined Temporary Seasonal Semi-permanent 76548 72281

9310 15.8 25.6 32.3 34984 51716 40624 15.7 24.9 27.5 408933 210329

19520 187476 155866 98235

Table 4. Land area (ha) and percent (%) of total land area within easement and fee-title tracts in the Missouri Coteau, Central Lowlands and Prairie Coteau domains of eastern South Dakota. Fee-title tracts include federal and state-owned property. Percent (%) total wetland area indicates proportion of wetland area protected from drainage on easement tracts.

Domain Fee-title Tracts

Land Area (ha) Protected % Total Land Area Easement Tracts

Land Area (ha) Protected % Total Land Area Wetland Area (ha) Protected % Total Wetland

Area

Missouri Coteau Central Lowlands Prairie Coteau 28351 44628 59461 1.2 1.0 1.2 416452 468270 253926 19.1 11.8 12.6 43887 59675 37680 36.6 21.8 27.7 

### lands that were used in model construction (Table 7).Calculations from a sample of 75 semi-permanent wetlands that were not used to construct discriminantfunctions indicated that, except for mallards, classification rates from the test data set were as high as apparent and jackknifed rates for unoccupied wetlands (Table 7).Discriminant functions were used in the GIS to classify habitat suitability of 24,083 semi-permanent and 159,524 seasonal wetlands in eastern South Dakota that were 0.2 ha. Proportion of seasonal wetlands 10 ha that provided suitable habitat for mallards andnorthern pintails was greater than that of semi-permanent wetlands of the same size (Table 8). Number of wetlands classified as suitable habitat for mallards, northern pintails, black terns, and eared grebes was summarized within 25.9-km2 

### cells into 4 classes: 1) 0, 2) 1–2, 3) 3–9, 4)  9 suitable wetlands (Figure 8). Results indicated that suitable mallard habitat wasabundant and widespread throughout all domains (Figure 8). Although northern pintail habitat also was widespread, extent of the most abundant habitat wasmore restricted in all domains. Among wetlands suitable for mallards, 51.7% of semi-permanent and 74.8% of seasonal wetlands also were suitable for northern pintails. Suitable habitat for black terns, which only nested in semi-permanent wetlands, was most abundant in the northern Prairie Coteau and an isolated portion of the northeastern Missouri Coteau. Eared grebe habitat was primarily confined to northernreaches of the Prairie Coteau. Semi-permanent wetlands that were suitable for mallards also providedhabitat for nongame species with more restrictive habitat requirements. Among semi-permanent wetlands suitable for mallards, 92.6% also were suitable for black terns, and 27.0% were suitable for eared grebes.

Effect of Removing Small Wetlands from the Landscape Proportion of wetlands  0.5 ha that were classified as suitable habitat decreased when smaller wetlands were removed from the surrounding landscape (Table 9). For example, removal of all small wetlands (0.5 ha), regardless of their protection status, resulted in an overall 20.7% decrease in number of wetlands  0.5

### Naugle et al., WETLAND BIRD HABITAT 9

Figure 6. Percentage of temporary, seasonal, and semi-permanent wetlands that are protected within easement and feetitle tracts in eastern South Dakota. Solid bars represent % of the total number of wetlands and shaded bars are totalnumber of protected wetlands within size classes. Size classes (ha) are 1) 0–0.2, 2) 0.3–0.5, 3) 0.6–1.0, 4) 1.1–2.0, 5) 2.1–5.0, and 6)  5.0. Figure 7. Number of unprotected temporary, seasonal, andsemi-permanent wetlands in eastern South Dakota. Size classes (ha) are 1) 0–0.2, 2) 0.3–0.5, 3) 0.6–1.0, 4) 1.1–2.0, 5) 2.1–5.0, and 6)  5.0.



### ha that had been previously classified as suitable habitat for northern pintails. Decreases in number of suitable wetlands were highest in smaller size classes (Table 9). Removal of only unprotected small wetlands resulted in a 70.4% decrease in previously suitable 1.0–2.0 ha wetlands compared to a decrease of 80.2% when all small wetlands were removed. Protection of wetlands 0.5 ha has preserved the suitability of 9.8% of 1.0–2.0 ha wetlands (Table 9). DISCUSSION Scale-dependent Perspectives of Habitat SuitabilityLandscapes differ in their potential to provide habitat for wetland birds because species have contrasting life histories that influence the way that each interacts with the landscape. Habitat suitability for some species (e.g., Virginia rail, marsh wren [Cistothorus palustris Wilson]) is related to local vegetative attributes within wetlands, while others (e.g., northern pintail, black tern) relate to landscape attributes at larger spatialscales. Prairie landscapes containing wetland complexes that are embedded within upland grasslands likelyprovide habitat for more species than depauperate wetland landscapes that have been impacted by agricultural tillage. High classification rates for habitats in which black terns, northern pintails, and eared grebes were absent indicated that landscape characteristics (i.e., attributesof the wetland complex and surrounding upland matrix) provide a coarse filter for assessing habitat suitability at a landscape scale. Identification of landscape characteristics related to habitat suitability is critical because a wetland embedded within an unsuitable landscape may not provide habitat despite favorable local vegetative conditions. Lower classification rates for occupied wetlands indicated that suitability also is dependent on local factors in wetlands located withina favorable landscape context (only landscape characteristics available in the GIS were used in models). For example, black terns vacated wetlands occupied in

### 10 WETLANDS, Volume 21, No. 1, 2001

Table 5. Habitat models using stepwise logistic regression analyses for 20 bird species in semi-permanent wetlands. Habitat variables entered regressions at P  0.15 and were retained in the model when P  0.01. Variables are listed in order of entry into equations.

Species Habitat Model Number of Occurrences McFadden’s Rho-squared Dabbling Ducks

Mallard Blue-winged Teal Gadwall Northern Pintail Northern Shoveler  COVER  AREA

 COVER  AREA AREA  GRASS AREA  SEAS AREA

 TREES 198 246 146 76 92 0.20 0.18 0.16 0.15 0.13 Diving Ducksa

Redhead Lesser Scaup Ruddy Duck AREA  SEMI  GRASS

 COVER  AREA AREA 82 50 68 0.20 0.20 0.18 Nongame Birdsa

Eared Grebe Black Tern American Bittern Wilson’s Phalarope Marsh Wren Pied-billed Grebe AREA

 STEM AREA  SEMI  GRASS COVER  AREA AREA

 STEM  NUMB  GRASS COVER  AREA  STEM AREA 18 106 34 58 119 120 0.41 0.24 0.21 0.21 0.20 0.19 Common Yellowthroat American Coot Yellow-headed Blackbird Sora Virginia Rail Red-winged Blackbird COVER  AREA  SEMI  STEM AREA  STEM COVER  AREA  STEM COVER

 GRAZE

 SEMI  NUMB COVER  AREA  STEM

 TREES  STEM 150 206 250 179 89 358 0.17 0.17 0.17 0.13 0.13 0.06

a Scientific names of species in table that are not provided in text: Redhead ( Aythya americana Eyton), Lesser Scaup ( Aythya affinis Eyton), Ruddy Duck (Oxyura jamaicensis Gmelin), Pied-billed Grebe (Podilymbus podiceps L.), Common Yellowthroat (Geothlypis trichas L.), American Coot (Fulica americana Gmelin), Yellow-headed Blackbird ( Xanthocephalus xanthocephalus Bonaparte), Red-winged Blackbird ( Agelaius phoeniceus L.).

Table 6. Habitat models using stepwise logistic regression analyses for 14 bird species in seasonal wetlands. Habitat variables entered regressions at P  0.15 and were retained in the model when P  0.01. Variables are listed in order of entry into equations.

Speciesa Habitat Model Number of Occurrences McFadden’s Rho-squared Dabbling Ducks

Mallard Blue-winged Teal Gadwall Northern Pintail Northern Shoveler  COVER  AREA AREA

 COVER  SEMI  SEAS AREA  GRASS AREA

 STEM AREA

 COVER 132 206

95 57 56 0.11 0.23 0.07 0.14 0.16 Nongame Birds

Wilson’s Phalarope Marsh Wren Pied-billed Grebe Common Yellowthroat American Coot Yellow-headed Blackbird Sora Virginia Rail Red-winged Blackbird AREA

 STEM STEM  COVER

 GRAZE  AREA AREA STEM  COVER

 GRAZE AREA  SEAS AREA  STEM COVER STEM  COVER STEM  COVER

 TREES 51 50 28 87 81 102 142 38 365 0.13 0.19 0.11 0.14 0.07 0.18 0.08 0.09 0.13

a Diving ducks, eared grebe, black tern, and American bittern were excluded from analyses due to their minimal use of seasonal wetlands.

### Naugle et al., WETLAND BIRD HABITAT 11

Table 7. Coefficients of variables used in discriminant functions to classify suitability of semi-permanent wetlands as habitat for 4 species that differ in their sensitivity to landscape structure.

Classification Function Coefficients by Species Constant Wetland Area Semipermanent Area (25.9 km2) Seasonal Wetland

Area (25.9 km2) Grassland Index Classification Rate (%)

Apparent Jackknifed True Semi-permanent wetlands

Mallard

unsuitable suitable  14.575

 17.540 1.291 2.325 38.367 40.505 82 63 80 63 45 76 Northern Pintail

unsuitable suitable  18.911

 23.275 1.128 2.087 8.804 9.455 75 61 75 61 95 33 Black Tern

unsuitable suitable  16.490

 23.403 1.862 2.888 0.854 1.127 39.670 45.528 76 78 76 78 100 22 Semi-permanent wetlands

Eared Grebe

unsuitable suitable  1.765

 7.442 1.538 3.860 88 94 88 94 100 0

Seasonal wetlands

Mallard

unsuitable suitable  1.230

 2.138 1.949 3.198 79 48 79 48 Northern Pintail

unsuitable suitable  1.356

 2.908 2.190 4.004 81 58 81 58

Table 8. Proportion of the number of wetlands classified as suitable habitat. Variables used in discriminant functions to classify suitability are in Table 7.

Wetland Size (ha)

0.2–0.5 0.5–1.0 1.0–2.0 2.0–5.0 5.0–10.0  10.0 Semi-permanent wetlands

Total # of wetlands

Black Tern Mallard Northern Pintail Eared Grebe 4034 38.0 4157 39.4 4660 43.9 11.9

1.7 5638 56.8 60.1 23.9 2720 80.7 89.9 76.2 2874 97.0 100.0 98.7 94.5

Seasonal wetlands

Total # of wetlands

Mallard Northern Pintail 63835 42735 30049 88.2 49.9 17653 100.0 41.8 3832 100.0 37.1 1420 100.0 34.2 

### previous years when height and density of emergent vegetation no longer provided adequate nesting sites (Naugle et al. 2000).

Preserving Long-term Avian Habitat SuitabilityIn the PPR, an ecosystem with inherently unpredictable hydrologic cycles, wetland bird settling patterns are largely dictated by wetland conditions and the number of ponded wetlands. Pulses in wetland birdproduction typically occur during wet hydrologic conditions when seasonal wetlands remain inundated throughout the breeding season (e.g., Kantrud andStewart 1977, 1984). Unfortunately, peaks in waterfowl production during ideal hydrologic conditions when dry years are followed by series of wet years (i.e., 3 or more) have occurred rarely in the past 50 years (Higgins et al. 1992). Thus, for the future of

### 12 WETLANDS, Volume 21, No. 1, 2001

Table 9. Declines in previously suitable semi-permanent wetlands that were reclassified as unsuitable using discriminant functions (Table 7) after small wetlands were removed from the landscape. Habitat suitability for species whose occurrence was related to surrounding wetland area was reclassified once after only unprotected wetlands 0.50 ha were removed, and again after all wetlands 0.50 ha, regardless of their protection status, were removed.

Semipermanent Wetland Area (ha)

0.2–0.5 0.5–1.0 1.0–2.0 2.0–5.0 5.0–10.0  10.0

Total number of wetlands 4034 4157 4660 5638 2720 2874

Number of suitable wetlands before small

wetland removal

Northern Pintail Black Tern 0 1533 3 1638 81 2045 1345 3200 2073 2196 2838 2787

Number of suitable wetlands after removal

of unprotected wetlands 0.5 ha

Northern Pintail Black Tern 0 1365 0 1552 24 1924 828 3043 1753 2139 2767 2775

% loss in number of suitable wetlands after

removal of unprotected wetlands 0.5 ha

Northern Pintail Black Tern 0 11.0 100.0 5.3 70.4 5.9 38.4 4.9 15.4 2.6 2.5 0.4

Number of suitable wetlands after removal

of wetlands 0.5 ha

Northern Pintail Black Tern 0 0 0 1550 16 1921 714 3041 1578 2139 2720 2783

% Loss in number of suitable wetlands after removal of all wetlands 0.5 ha

Northern Pintail Black Tern 0 100.0 100.0 5.4 80.2 6.1 46.9 5.0 23.9 2.6 4.2 0.4



### wetland bird production, as many wetlands as possible should be protected to maintain the pulse potential of wetland landscapes.Numerous species in this study (e.g., Wilson’s phalarope [Steganopus tricolor Vieillot], black tern, gadwall [ Anas strepera L.]) were more likely to inhabit wetlands within landscapes where 50% of the upland matrix was tilled. Average proportion of grasslands within cells was 10.4% higher near semi-permanent wetlands in which dabbling duck species richness was at a maximum compared to wetlands that were devoid of dabbling ducks. Greenwood et al. (1995) reportedthat dabbling duck nest success was correlated positively with the proportion of grassland in their study sites in southern Canada. Recent advances in the fieldof landscape ecology (Turner 1989, Turner and Gardner 1991, Forman 1995, Bissonette 1997) indicate that the matrix (e.g., adjacent uplands) often influenceslandscape function by altering within-patch (e.g., wetland) dynamics. In northern prairie ecosystems, pesticide and fertilizer runoff and siltation from agricultural lands alter wetland vegetation composition (Kantrud 1986, Freeland et al. 1999) and reduce invertebrate abundance (Novak 1992, Dunn and Agro 1995). We used grassland abundance in this study as a surrogate measure reflecting the negative impacts of agricultural activities on wetland habitats. Findings from Beintema(1997), which indicate that agricultural tillage decreases diversity of invertebrate forage available to wetland avifauna, reinforce our contention that human-inducedmodifications in upland habitats are related to processes within wetland complexes. Management designed to increase habitat suitability for waterfowl andnongame species should include continued establishment and maintenance of grassland cover. Future research concerning the role of grasslands should address the influences of grassland patch size, grassland structure within patches, and configuration of multiple grassland patches on wetland bird use and productivity (i.e., source/sink dynamics) (e.g., van Horne 1983, Pulliam 1988).

The Value of Small Wetlands Resource specialists acknowledge the current lack of empirical evidence needed to rebut opponents who

### Naugle et al., WETLAND BIRD HABITAT 13

Figure 8. Distribution of the number of suitable semi-permanent and seasonal wetlands for A) mallards, B) northern pintails, C) black terns, and D) eared grebes in eastern South Dakota. Wetland area and various landscape-level attributes were used in discriminant functions to classify wetland suitability for species A-D that differed in their sensitivity to landscape variation. Colors indicate the number of suitable wetlands within 25.9 km2 cells.

### 14 WETLANDS, Volume 21, No. 1, 2001

Table 10. Percentage of suitable wetlands protected within easement and fee-title tracts. Wetlands were classified as suitable using discriminant functions (Table 7) for selected species.

Wetland Area (ha)

0.2–0.5 0.5–1.0 1.0–2.0 2.0–5.0 5.0–10.0  10.0 Semi-permanent Wetlands

Total # of wetlands

Black Tern Mallard Northern Pintail Eared Grebe 4034 51.9 4157 50.7 4660 49.2 50.5 34.6 5638 43.1 40.6 41.8 2720 38.8 35.8 37.1 2874 34.6 34.0 34.2 33.9

Seasonal Wetlands

Total # of wetlands

Mallard Northern Pintail 63835 42735 30049 28.0 27.9 17653 28.1 28.1 3832 25.1 25.1 1420 17.8 17.8



### question the value of small wetlands (Gibbs 1993,Haig et al. 1998, Semlitsch and Bodie 1998). A heightened awareness of the value of small wetlands is critical in the PPR because most unprotected wetlands aresmall (Figure 7). We previously estimated that the deregulation of small wetlands (0.4 ha) in agricultural fields could result in drainage of up to 49% of the remaining wetlands in eastern South Dakota (Johnsonet al. 1996). Opponents viewing wetlands as individual, disjunct patches quickly devalue the importance of small wetlands as suitable habitat because a single large wetland typically contains more species than one of a smaller size. When viewed as components of a larger landscape, however, small wetlands are critical landscape elements that influence the suitability of larger wetlands. Discriminant functions that were used to reclassify the suitability of larger remaining wetlands after small wetlands (0.5 ha) had been removed from the landscape indicated that species most vulnerable to the lossof small wetlands are vagile species that exploit resources over broader spatial scales. Using the same wetland sites surveyed for this study, Naugle et al.(1999) found that black terns occupied wetlands located in high-density wetland landscapes (landscape type d; Figure 3) more frequently than those in low wetland density landscapes (landscape type a) where potential food sources are spread over large distances. In this study, decreases in the number of previously suitable wetlands were greatest in smaller size classes(0.5–5.0 ha; Table 9) because black terns become increasingly dependent on characteristics of the surrounding landscape as wetland size decreases. Similarly, number of wetlands suitable for northern pintails, a vagile species that uses multiple wetlands within a season, decreased 20.7% when small wetlands wereremoved from the landscape. Suitability of larger wetlands probably decreased when small wetlands were removed because northern pintails breed near small,shallow temporary and seasonal wetlands before moving their broods to larger, more permanent wetland habitats.To further quantify the importance of small wetlands, we also used discriminant functions to reclassify wetland habitat suitability after only unprotected small wetlands, rather than all small wetlands regardless oftheir protection status, were removed from the surrounding landscape. The 9.8% increase in proportionof suitable 1–2 ha wetlands when protected small wetlands remained intact further attests to the importance of small wetlands to northern pintails. Perhaps more importantly, these results also indicate that, despite similarities in proportions of protected wetlands acrosssize classes (Figure 6), the greatest number of unprotected wetlands are still those that are the smallest (Figure 7).

Conserving Habitat for Nongame Wetland Birds Using Waterfowl Paradigms

Advances in waterfowl and wetland research continually shape and change our current understandingof what constitutes suitable wetland bird habitat. Resource managers operating under prevailing habitat paradigms dictate policy and guidelines for wetlands preservation. Initial paradigms (circa 1960s) dictated that waterfowl managers acquire large semi-permanent wetlands to provide pair and brood-rearing habitat.Our results indicate that acquisition of large semi-permanent wetlands for breeding waterfowl also have resulted in preservation of wetland habitats for many nongame bird species. Results from this study further indicate that efforts intended to protect wetland habitat for waterfowl have protected 45% of suitable wetlands for nesting and foraging black terns (Table 10). More recent recognition of the value of smaller, sea-

### Naugle et al., WETLAND BIRD HABITAT 15

sonal wetlands for waterfowl pairs during pre-laying and laying periods resulted in a paradigm shift (circa 1980s) that redirected protection efforts towards highdensity landscapes dominated by complexes of semipermanent and seasonal wetlands. This second paradigm shift initiated preservation of the more extensivesuitable habitat for nongame species that relate to surrounding landscape structure (e.g., northern pintail and black tern on the northeastern Missouri Coteau; Figure8). Occupancy rates that were an average of 15% higher in seasonal wetlands compared to semi-permanent wetlands for northern pintails, blue-winged teal [ Anas discors L.], and northern shoveler [ Anas clypeata L.] indicate that small seasonal wetlands provide extensive breeding habitat for dabbling ducks. Small seasonal wetlands, which are  6 times as abundant as semipermanent wetlands in eastern South Dakota, also provide habitat for species like Wilson’s phalaropes and Virginia rails. Wilson’s phalaropes and Virginia rails in this study were most abundant in small seasonalwetlands that met their nesting and foraging requirements (Johnson and Dinsmore 1986, Colwell and Jehl 1994). In retrospect, shifting habitat paradigms among resource managers have resulted in preservation of suitable habitat for nongame species that use largesemi-permanent wetlands and are now preserving habitat for species that occupy the far more abundant seasonal wetlands.

Strategies for Future Habitat Preservation

Easement and fee-title lands in eastern South Dakota protect 34–52% of semi-permanent and 18–28% of seasonal wetlands suitable for a representative group of species (black tern, mallard, northern pintail, and eared grebe; Table 10) whose habitat needs differ markedly across local and landscape scales (Tables 5and 6). Cessation of protection efforts would ultimately result in further fragmentation of the regional wetland landscape after drainage and expansion of tillage agriculture. Current distribution of protected tracts(Figure 5) most closely mimics distribution of landscapes with large numbers of wetlands that are suitable for northern pintails (Figure 8), a species that reached all-time population lows in the 1980s and is a species of special concern to waterfowl managers (Hestbeck 1996). Protection of additional wetlands will increaseconnectivity of protected tracts and reduce the potential extent of fragmentation. The largest gap in distribution of protected tracts exists in the middle Central Lowlands domain of eastern South Dakota (Figure 5). Wetlands in the Central Lowlands are among those atgreatest risk of drainage because 84% are small, unprotected temporary and seasonal wetlands (Table 3; Figure 7) located within agricultural fields (Johnson et al. 1996). Our results indicate that 9 species of nongame wetland birds (Table 6) nest in and around small seasonal wetlands. Wetland acquisitions in the Central Lowlands would preserve landscapes where seasonal wetland densities commonly exceed 180 wetlands/ 25.9-km2 

### (Johnson and Higgins 1997) and would link the Prairie Coteau and Missouri Coteau into a more highly connected, regional wetland complex (Figure 5).

Importance of Temporary WetlandsBird surveys were not conducted in temporary wetlands, the most abundant wetland type in all domains,because the brief duration of ponding in spring precludes breeding by wetland bird species in most years.Readers should not devalue the importance of temporary wetlands, however, because these wetlands areintegral components of wetland landscapes. The importance of temporary wetlands as pair habitat for early nesting duck species (e.g., mallard and northern pintail) (Drewien 1968, Dzubin 1969, Krapu 1974, Duebbert et al. 1983) is well known. Temporary wetlands in agricultural landscapes also provide foraging habitat for migrating waterfowl (LaGrange and Dinsmore1989) and shorebirds (Skagen and Knopf 1994). Migrating pectoral sandpipers (Calidris melanotos Vieillot) reduced energetic costs by foraging in landscapes containing multiple closely spaced temporary wetlands(Farmer and Parent 1997). Additional landscape studies are necessary to gain a comprehensive understanding of the spatial and temporal dynamics of temporary wetlands.

ACKNOWLEDGMENTS Primary project funding was provided by Federal Aid to Wildlife Restoration (W-107-R, Job No. 8) viathe South Dakota Cooperative Fish and Wildlife Research Unit, in cooperation with South Dakota Department of Game, Fish and Parks, U.S. Geological Survey, South Dakota State University, U.S. Fish andWildlife Service, and the Wildlife Management Institute. We thank C. A. Lively, Coordinator of the Prairie Pothole Joint Venture, North American Waterfowl Management Plan, for funding to cover publication and distribution costs. This study benefited greatlyfrom conversations with C. R. Madsen and C. R. Elliott of the USFWS. J. R. Sauer, F. A. Johnson, C. S. Robbins, G. R. Guntenspergen, J. A. Dubovsky, J. A. Royle, M. R. Koneff, and J. S. Wortham provided helpful comments on an earlier draft. USFWS Divisionof Realty Office in Denver, CO, USFWS Wetland Acquisition Offices in Huron and Aberdeen, SD, and South Dakota Department of Game, Fish and Parks

### 16 WETLANDS, Volume 21, No. 1, 2001

provided invaluable technical assistance. We thank M. J. Kjellsen for help in interpreting National WetlandInventory data and in acquiring digital wetland protection information. We also thank L. D. Flake and Z. W. Wicks III for comments during conceptual phasesof this project. R. E. Reynolds and D. Cohan developed techniques used in GIS wetland basin construction. J. A. Jenks and D. M. Dateo (South Dakota State University) and J. E. Vogelmann (EROS Data Center, U. S. Geological Survey) provided technical support and computer facilities during production of the digital land use cover. Land-cover was produced as part of the South Dakota GAP Analysis Project funded byU.S. Geological Survey-Biological Resources Division. F. R. Quamen, K. K. Bakker, S. A. Stolz, J. W. Bauer, B. L. Kopplin, and M. S. Wilsdon assisted with field work.

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