Bird use of wetlands in a Midwestern metropolitan area in relation to adjacent land cover.
In the U.S., at least 80% of the human population now lives in areas classified as urban (Adams et al., 2006). Because the U.S. population also continues to grow (U.S. Census Bureau, 2011), the absolute number of people in cities is increasing. As U.S. cities gain people, their structure tends to sprawl geographically; metropolitan regions now encompass as much as 20% of land area in the U.S. (Adams et al., 2006). This combination of trends represents an important challenge for those who desire to protect natural landscapes and the biota they harbor (McDonnell and Pickett, 1990).
Most wildlife research is not conducted in urban environments, but the number of urban focused studies is increasing. In particular, several studies of birds have investigated population sizes and community attributes in relation to variation in land cover attributes. For example, bird species diversity generally has been found to be greater in rural than in urban settings (e.g., Beissinger and Osborne, 1982; Clergeau et al., 1998; Chapman and Reich, 2007), but most of these studies were performed in upland habitats. To our knowledge, little attention has been given to wetland bird-land cover relationships in urban settings. This is an unfortunate omission since some urban landscapes possess potentially important wetland habitats at high densities. Wetlands often are biologically diverse and provide a wide array of other environmental benefits related to water quality and hydrology (Novitzki et al., 1996), yet they are often lost to commercial or residential development. Moreover, upland environments near wetlands may be important to the biological composition and function of the wetlands themselves. We surveyed birds in wetlands in the Minneapolis and St. Paul (MSP), Minnesota (USA) metropolitan area to assess relationships among metrics describing the birds in the wetlands and the land cover types near these wetlands.
STUDY AREA AND METHODS
Wetlands encompass nearly 15% of the total area of the seven-county MSP metropolitan area (Minnesota DNR, 201la). We used a combination of on-the-ground visits and examination of aerial photography to choose six palustrine emergent marshes (sensu Cowardin et al., 1979) in northern MSP suburbs. This is a predominant wetland type in the upper midwestern U.S. (Tiner, 1984), and in the MSP area, these marshes number >5/[km.sup.2] (U.S. Fish and Wildlife Service, 2011b). In addition to selecting wetlands of the same type, we used wetlands that afforded access, were similar in size (9.5-19.9 ha), had similar configurations of open water and emergent vegetation, had surrounding land cover that represented a gradient from sparse to more extensive natural cover, and were sufficiently distant from one another so as not to overlap with regard to land cover analysis or bird surveys. To determine wetland boundaries, one observer walked the perimeter of each wetland with a global positioning system receiver. We superimposed waypoint data on 1 m resolution aerial photography and used ArcGIS 9.2 to digitize the boundaries and calculate area. The six wetlands averaged 16 [+ or -] 2 (SE) ha.
We surveyed birds from mid-Aug, through late Sept. 2007. Documenting bird use and habitat relationships at this time of year is important because both birds that use the wetlands during the nesting season and birds that nest in other habitats likely use the wetlands in late summer to feed young and to prepare for fall migration. During our survey period, we visited each wetland four times. During each visit, we conducted a 5-min point count at each of two locations along the wetland boundary; after the first visit to a particular wetland, we used the same two locations in all subsequent point counts. We selected point count locations so as to position the observer at the wetland boundary, afford a clear view of the wetland and be sufficiently distant ([greater than or equal to] 250 m) from each other to avoid double counting. We conducted all counts between sunrise and 1000 h; we did no counts during periods of rain, fog, or winds exceeding 4.5 m/s. The same observer conducted all counts. During counts, we recorded all birds seen or heard within the wetland boundary; we did not record birds outside of the wetland boundary. Birds flying above the wetland were counted only if they could be judged clearly not to be incidental flyovers [e.g., tree swallows (Tachyaneta bicolor) foraging in flight above a wetland were counted]. Thus, the survey data represented only birds using the wetlands, and the bird-land cover relationships discussed below result from and apply to these birds only.
We calculated the following metrics: bird species richness (the average number of bird species recorded during the two, 5-min counts that comprised a wetland visit); the total number of birds detected during the two combined 5-min counts of a wetland visit; and Shannon diversity (calculated for each wetland visit from the species and individuals recorded during the two combined 5-min counts). We averaged each metric for each wetland over the four visits so that, for a given metric, each wetland was represented by only one value in any subsequent analyses.
We used 1 m resolution aerial photography in conjunction with ArcGIS to quantify land cover around each wetland. The aerial photographs were taken in 2003. We established land cover categories that were easily identifiable from the photographs, accounted for substantial proportions of the area around the wetlands and seemed to have the greatest potential to be associated with the bird metrics we estimated. These categories were trees; nontree vegetation (e.g., meadows, pastures, prairie plots, shrubby areas); nonnatural vegetation (primarily lawns and playing fields); agricultural crop fields; open water; pavement; and building footprints. To ensure that our land cover analyses accurately represented conditions at the time of the bird surveys, we superimposed a 100-m graticule on each photo, selected 50 graticule points near each wetland, and compared the 2003 photos with 2008 photos (which became available after our work was completed). Only five of 300 points (<2%) so examined were classified differently from 2008 photos as compared to the 2003 photos. We thus concluded that the 2003 photos were an accurate representation of conditions at the time of the bird surveys.
We used ArcGIS to buffer each wetland boundary at distances of 25, 50, 100, 150, 200, 300, 400, and 500 m. We then used the buffers to quantify land cover in progressively broader areas around each wetland; within each buffer, all land cover polygons in each category were totaled and the sum expressed as a percentage of the total area of the buffer. This approach enabled us to examine the minimum distance from the wetland within which a particular land cover effect might become evident and also the greater distance beyond which an effect might diminish or disappear.
We calculated Pearson product moment correlation coefficients to analyze the strength of relationships among bird metrics and land cover percentages. We set statistical significance at P [less than or equal to] 0.05. We also examined scatterplots of nonsignificant relationships to search for potentially meaningful nonlinear patterns.
We recorded 24 species during the study; five were recorded on all six wetlands and eight on only one wetland (Table 1). Although none of the species was nesting at the time of our study, all of them are known to nest in Minnesota (Minnesota DNR, 2011b). The maximum number of species recorded during the study on any wetland (all four visits combined) was 16; the minimum was eight. Four species [bald eagle (Haliaeetus leucocephalus), mourning dove (Zenaida macroura), downy woodpecker (Picoides pubescens), song sparrow (Melospiza melodia)] were detected only once in the study.
Mean estimates of species richness per point count and total detections per wetland visit varied nearly two-fold among the six wetlands, and the mean Shannon diversity values varied 30% from least to greatest (Table 2). The wetland with greatest species richness also had the greatest Shannon diversity and the greatest number of bird detections, but the wetland with the lowest values for species richness and diversity had the second greatest number of detections.
None of the bird metrics was significantly associated with wetland area: the correlation coefficients describing these relationships did not exceed 0.32 (P = 0.54). Nor were any of the land cover variables significantly related to wetland area. Thus, it is unlikely that wetland area confounded any of the land cover-bird relationships reported below.
We found no significant relationships among bird metrics and nonnatural vegetation, agricultural crop fields, or open water. Those categories were therefore omitted from further consideration, and the subsequent land cover analysis focused on trees, nontree vegetation, buildings, and pavement. These four land cover categories together comprised 52%-82% of the land within 500 m of the six wetlands (Fig. 1).
Within the 100 m of land closest to the wetlands, none of the bird metrics was significantly related to tree cover (Table 3). In fact, total bird detections were not significantly associated with any aspect of vegetative cover around the wetlands. However, bird species richness was correlated with tree cover within all buffers [greater than or equal to] 150 m wide. Similarly, diversity was positively associated with tree cover within all buffers [greater than or equal to] 300 m. The cover of nontree vegetation, by itself, was not related to any bird metric, but cover of nontree vegetation combined with tree cover was significantly associated with bird species richness within all buffer widths [less than or equal to] 300 m and with diversity in all buffers [greater than or equal to] 200 m wide (Table 3).
The cover of building footprints was negatively correlated with bird species richness within all terrestrial buffers [greater than or equal to] 50 m wide (Table 4). Diversity was negatively associated with cover of building footprints within buffers 150-400 m wide. The cover of pavement, by itself, was not significantly related to any of the bird metrics, but cover of pavement in combination with cover of building footprints was negatively associated with diversity within the 200-m buffer (Table 4). Similarly, total bird detections were negatively associated with the combination of pavement and buildings. This relationship was strongest very near the wetlands (Table 4) but nonsignificant within buffer widths >150 m.
Clearly, bird species richness and diversity in these suburban wetlands were positively associated with the cover of trees and nontree vegetation within a few hundred meters of the wetland boundaries, whereas richness, diversity and total detections were negatively associated with human constructed aspects of land cover. These results are generally consistent with those of other urban focused studies of bird diversity and abundance (e.g., Germaine et al., 1998; Green and Baker, 2003; Pennington et al., 2008). However, some studies have shown that avian diversity along urban-rural gradients may not be greatest in the settings of greatest natural cover but instead may peak in suburban or exurban regions with intermediate levels of disturbance (Blair, 1996; Crooks et al., 2004; Bock et al., 2008). This pattern has been attributed to the greater habitat diversity and complexity (including natural habitats, buildings, gardens, other plantings, feeders, and nest boxes), which sometimes characterize suburban developments. Further, the common use of artificial watering and fertilizers may increase the overall productivity of such environments, thereby enhancing local bird diversity (Chapman and Reich, 2007). At least some of the enhanced diversity may be due to nonnative species, which have adapted well to human dominated settings (McKinney, 2002).
Although bird metrics in the wetlands in our study were related to aspects of adjacent land cover, those relationships varied in strength with distance from the wetland boundary. In particular, bird-tree and bird-building relationships within 50 m of wetland boundaries were generally weak. Given that we only surveyed birds within wetland boundaries, it is somewhat surprising that land cover closest to the wetlands seemingly had less influence on bird metrics than that within the 500-m buffer as a whole. Moreover, landscape and natural habitat features outside the wetlands, where trees seemed especially important, were very unlike those within the wetlands themselves, where hydrophytic herbaceous vegetation and open water dominated. These birds may have selected these marshes on a scale much broader than that of the individual wetland and its immediately adjacent shoreline environment (Morrison et al., 1992).
None of the species recorded in our study is threatened or endangered (U.S. Fish and Wildlife Service, 2011a), but four of the 24 [great blue heron (Ardea herodias), mourning dove, common yellowthroat (Geothlypis trichas), red-winged blackbird (Agelaius phoeniceus)] have shown evidence of declines in Minnesota over the past half-century (Sauer et al., 2011). Also, we recorded wetland use by birds that are not typically regarded as wetland species [e.g., black-capped chickadee (Poecile atricapillus)]; thus, wetlands may be valuable not only for 'wetland' birds during and after the nesting season but also for species that breed in other habitats yet use the wetlands opportunistically at various times of year.
Wetland losses that are mitigated through restorations are helpful, but further loss of natural urban and suburban wetlands must be minimized. If bird diversity and abundance are management goals for wetlands, they can be enhanced within wetlands if the surrounding landscape contains more of the elements that attract birds and fewer that deter them. In new housing or commercial developments that are being planned but are not yet established, astute implementation of local zoning ordinances and environmentally friendly design principles can be used to minimize roads and buildings. In existing developments it is unrealistic to suppose that already established buildings, roads, and other pavement can be reduced. However, emphasis can be placed on the establishment of trees and other natural vegetative elements.
Acknowledgments.--We are grateful to the leadership of Bethel University and to the faculty of the Department of Biological Sciences for material support and for cultivating a receptive environment for this research. We thank L. Kristen Page and two anonymous reviewers for critiquing an earlier draft of this paper.
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KENNETH L. PETERSEN, Department of Biological Sciences, Bethel University, St. Paul, Minnesota 55112; and AMY S. WESTMARK, 7415 Girard Avenue North, Brooklyn Park, Minnesota 55444. Submitted 23 November 2010; accepted 11 May 2012.
TABLE 1.--Bird species detected during point counts in six Minneapolis and St. Paul, Minnesota wetlands in Aug. and Sept., 2007 (a) Family Species Dayton Springbrook Ardeidae Great blue heron (Ardea 0.8 (0.5) 1.2 (0.6) herodias) Great egret (Ardea alb') 0 0 Green heron (Butorides 0 0.2 (0.2) virescens) Anatidae Canada goose (Branta 4.2 (1.9) 6.5 (2.2) canadensis) Wood duck (Aix sponsa) 0 4.5 (1.9) Mallard (Anal 3.0 (0.9) 1.8 (1.2) platyrhynchos) Pandionidae Osprey (Pandion haliaetus) 0 0 Accipitridae Bald eagle (Haliaeetus 0 0 leucocephalus) Cooper's hawk (Accipiter 0 0.5 (0.5) cooperii) Charadriidae Killdeer (Charadrius 0 0 vociferus) Columbidae Mourning dove (Zmaida 0 0 macroura) Trochilidae Ruby-throated hummingbird 1.8 (1.2) 0 (Archilochus colubris) Picidae Downy woodpecker (Picoides 0 0 pubescens) Tyrannidae Eastern phoebe (Sayornis 1.0 (0.7) 0 phoebe) Corvidae Blue jay (Cyanocitta 0 1.5 (1.5) cristata) American crow (Corvus 0.5 (0.5) 2.5 (2.5) brachyrhynchos) Hirundinidae Tree swallow (Tachycineta 5.5 (2.5) 2.2 (1.4) bicolor) Paridae Black-capped chickadee 4.8 (3.0) 0.2 (0.2) (Poecile atricapillus) Troglodytidae Marsh wren (Cistothorus 0.8 (0.2) 0.8 (0.5) palustris) Parulidae Common yellowthroat 3.8 (2.2) 3.0 (3.0) (Geothlypis trichas) Emberizidae Song sparrow (Melospiza 0 0.2 (0.2) melodia) Swamp sparrow (Melospiza 1.5 (0.6) 6.8 (2.7) georgiana) Cardinalidae Northern cardinal 0 0.5 (0.5) (Cardinalis cardinalis) Icteridae Red-winEed blackbird 14.0 (5.8) 4.8 (2.8) (Azelaius phoeniceus) Family Species Lexington White Bear Ardeidae Great blue heron (Ardea 0.2 (0.2) 0.2 (0.2) herodias) Great egret (Ardea alb') 0.5 (0.5) 3.2 (3.2) Green heron (Butorides 0 0.5 (0.3) virescens) Anatidae Canada goose (Branta 7.0 (4.7) 0.5 (0.5) canadensis) Wood duck (Aix sponsa) 11.0 (3.7) 0.5 (0.5) Mallard (Anal 2.8 (1.1) 0 platyrhynchos) Pandionidae Osprey (Pandion haliaetus) 0.8 (0.5) 0 Accipitridae Bald eagle (Haliaeetus 0.2 (0.2) 0 leucocephalus) Cooper's hawk (Accipiter 0 0 cooperii) Charadriidae Killdeer (Charadrius 0.2 (0.2) 0.2 (0.2) vociferus) Columbidae Mourning dove (Zmaida 0 0.2 (0.2) macroura) Trochilidae Ruby-throated hummingbird 0 0 (Archilochus colubris) Picidae Downy woodpecker (Picoides 0 0.2 (0.2) pubescens) Tyrannidae Eastern phoebe (Sayornis 0 0 phoebe) Corvidae Blue jay (Cyanocitta 0 0 cristata) American crow (Corvus 0 0 brachyrhynchos) Hirundinidae Tree swallow (Tachycineta 6.2 (3.2) 2.5 (1.6) bicolor) Paridae Black-capped chickadee 0.2 (0.2) 4.2 (2.1) (Poecile atricapillus) Troglodytidae Marsh wren (Cistothorus 0 0.2 (0.2) palustris) Parulidae Common yellowthroat 0.8 (0.8) 1.5 (1.2) (Geothlypis trichas) Emberizidae Song sparrow (Melospiza 0 0 melodia) Swamp sparrow (Melospiza 0 0.5 (0.5) georgiana) Cardinalidae Northern cardinal 0 0.2 (0.2) (Cardinalis cardinalis) Icteridae Red-winEed blackbird 4.5 (0.3) 5.8 (4.2) (Azelaius phoeniceus) Maple Family Species Grove Anoka Ardeidae Great blue heron (Ardea 0 0 herodias) Great egret (Ardea alb') 0.8 (0.5) 0 Green heron (Butorides 0 0 virescens) Anatidae Canada goose (Branta 3.5 (2.1) 3.0 (3.0) canadensis) Wood duck (Aix sponsa) 0.2 (0.2) 3.2 (3.2) Mallard (Anal 3.0 (1.6) 10.8 (6.3) platyrhynchos) Pandionidae Osprey (Pandion haliaetus) 0 0 Accipitridae Bald eagle (Haliaeetus 0 0 leucocephalus) Cooper's hawk (Accipiter 0 0 cooperii) Charadriidae Killdeer (Charadrius 0 0 vociferus) Columbidae Mourning dove (Zmaida 0 0 macroura) Trochilidae Ruby-throated hummingbird 0.2 (0.2) 0 (Archilochus colubris) Picidae Downy woodpecker (Picoides 0 0 pubescens) Tyrannidae Eastern phoebe (Sayornis 0 0 phoebe) Corvidae Blue jay (Cyanocitta 0 0 cristata) American crow (Corvus 0 0 brachyrhynchos) Hirundinidae Tree swallow (Tachycineta 5.0 (2.6) 6.0 (2.3) bicolor) Paridae Black-capped chickadee 3.8 (2.4) 2.2 (1.4) (Poecile atricapillus) Troglodytidae Marsh wren (Cistothorus 0.2 (0.2) 0.8 (0.2) palustris) Parulidae Common yellowthroat 0.2 (0.2) 3.8 (2.5) (Geothlypis trichas) Emberizidae Song sparrow (Melospiza 0 0 melodia) Swamp sparrow (Melospiza 0 0 georgiana) Cardinalidae Northern cardinal 0 0 (Cardinalis cardinalis) Icteridae Red-winEed blackbird 3.0 (1.8) 10.2 (5.5) (Azelaius phoeniceus) (a) Values are means (one standard error) of total detections per wetland visit (two 5-min point counts at different locations) derived from four visits to each wetland TABLE 2.--Bird metrics in six Minneapolis and St. Paul, Minnesota wetlands in Aug. and Sept. 2007 (a) Wetland Bird species Shaimon Detections richness (b) diversity (c) (d) Anoka 3.5 (0.2) 1.38 (0.11) 40 (8) Maple Grove 3.8 (0.7) 1.44 (0.20) 22 (3) White Bear 4.1 (0.6) 1.45 (0.20) 23 (4) Lexington 5.4 (0.5) 1.43 (0.03) 34 (5) Springbrook 5.8 (0.5) 1.77 (0.09) 39 (5) Dayton 6.8 (1.0) 1.80 (0.24) 44 (4) (a) Values are means (one standard error) derived from four visits to each wetland (b) Bird species detected per 5-min point count (c) Shannon index of diversity calculated from all data in one wetland visit (two 5-min point counts at different locations) (d) Total birds detected in one wetland visit (two 5-min point counts at different locations); means include 0-3 detections per wetland of birds that were unidentified TABLE 3.--Pearson product-moment correlation coefficients describing relationships among wetland bird metrics vs. vegetative aspects of land cover adjacent to six Minneapolis and St. Paul, Minnesota wetlands in Aug. and Sept. 2007 Bsr (a) H (b) Detections (c) Width of terrestrial Trees + Trees + Trees + buffer (m) Trees ntv (d) Trees ntv Trees ntv 25 0.12 0.84 * -0.18 0.58 0.51 0.64 50 0.51 0.89 * 0.15 0.66 0.56 0.45 100 0.76 0.86 * 0.48 0.72 0.52 0.35 150 0.80 * 0.87 * 0.60 0.79 0.56 0.40 200 0.83 * 0.86 * 0.70 0.86 * 0.56 0.40 300 0.88 * 0.83 * 0.81 * 0.90 * 0.54 0.32 400 0.88 * 0.74 0.86 * 0.89 * 0.47 0.20 500 0.86 * 0.67 0.82 * 0.81 * 0.36 0.07 (a) Bird species richness per 5-min point count (b) Shannon index of diversity calculated from all data in one wetland visit (two 5-min point counts at different locations) (c) Total birds detected in one wetland visit (two 5-min point counts at different locations) (d) Trees plus nontree vegetation * P [less than or equal to] 0.05 TABLE 4.--Pearson product moment correlation coefficients describing relationships among wetland bird metrics vs. human constructed aspects of land cover adjacent to six Minneapolis and St. Paul, Minnesota wetlands in Aug. and Sept. 2007 Bsr (a) H (b) Detections (c) Width of terrestrial Bldgs Bldgs + Bldgs + Bldgs + buffer (m) (d) pvmt (e) Bldgs pvmt Bldgs pvmt 25 -0.74 -0.67 -0.53 -0.59 -0.58 -0.96 * 50 -0.84 * -0.77 -0.63 -0.72 -0.61 -0.90 * 100 -0.90 * -0.79 -0.71 -0.79 -0.77 -0.85 * 150 -0.92 * -0.75 -0.81 * -0.77 -0.67 -0.81 * 200 -0.94 * -0.78 -0.88 * -0.82 * -0.63 -0.77 300 -0.95 * -0.77 -0.90 * -0.79 -0.60 -0.64 400 -0.87 * -0.72 -0.87 * -0.72 -0.61 -0.53 500 -0.82 * -0.66 -0.79 -0.62 -0.51 -0.38 (a) Bird species richness per 5-min point count (b) Shannon index of diversity calculated from all data in one wetland visit (two 5-min point counts at different locations) (c) Total birds detected in one wetland visit (two 5-min point counts at different locations) (d) Building footprints (e) Buildings plus pavement * P [less than or equal to] 0.05
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|Title Annotation:||Notes and Discussion|
|Publication:||The American Midland Naturalist|
|Date:||Jan 1, 2013|
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