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Volume 13, Issue 9 e4232
Open Access

Spatial drivers of wetland bird occupancy within an urbanized matrix in the Upper Midwestern United States

Anastasia A. Rahlin

Corresponding Author

Anastasia A. Rahlin

Illinois Natural History Survey, Prairie Research Institute, University of Illinois Urbana-Champaign, Urbana, Illinois, USA

Department of Natural Resources and Environmental Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois, USA


Anastasia A. Rahlin

Email: [email protected]

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Sarah P. Saunders

Sarah P. Saunders

National Audubon Society, New York, New York, USA

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Stephanie Beilke

Stephanie Beilke

Audubon Great Lakes, Chicago, Illinois, USA

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First published: 07 September 2022
Citations: 1
Handling Editor: Brooke Maslo
Funding information Illinois State Toll Highway Authority contract, Grant/Award Number: 1-594662-375002-191100-A00


Wetland birds are undergoing severe population declines in North America, with habitat degradation and wetland loss considered two of the primary causes. Due to the cryptic nature of many wetland bird species, the ecological conditions (e.g., matrix composition) that influence bird occupancy, and the relevant spatial scales at which to measure bird responses, remain unclear but may affect inference about wetland use and suitability. We conducted wetland bird surveys at 477 points across northeastern Illinois and northwestern Indiana within the highly urbanized landscape surrounding Chicago. Using remotely sensed land cover data, we built occupancy models for 10 wetland bird species (American Coot Fulica americana, Black-crowned Night-Heron Nycticorax nycticorax, Blue-winged Teal Anas discors, Common Gallinule Gallinula galeata, Least Bittern Ixobrychus exilis, Marsh Wren Cistothorus palustris, Pied-billed Grebe Podilymbus podiceps, Sora Porzana carolina, Swamp Sparrow Melospiza georgiana, and Virginia Rail Rallus limicola) to quantify their responses to wetland cover types (emergent wetland, forested wetland, riverine wetland, and freshwater pond) and urbanization at four spatial scales (200-, 400-, 800-, and 2000-m radial distances). We also included the distance to Lake Michigan as a covariate in occupancy models to account for ecological differences between coastal and inland wetlands. We found that relationships between land cover types and occupancy differed by species, as did the spatial scale of support. Generally, the presence of emergent wetlands or ponds at immediate (200 m) and local (400 m) spatial scales within the surrounding matrix was positively associated with wetland bird occupancy. Contrary to expectations, we did not find support for a negative relationship between urbanization and occupancy for most focal species, indicating that birds are using available wetland habitats despite surrounding development. While future research should evaluate management strategies at the watershed scale, our findings suggest that wetland conservation planning at immediate and local scales is likely to promote bird habitat use within highly modified landscapes of the Upper Midwestern United States.


Wetland birds in North America have experienced population declines of approximately 22% since 1970 (Rosenberg et al., 2019). Within the Great Lakes region, both the North American Breeding Bird Survey and Birds Canada's Great Lakes Marsh Monitoring Program document similar declines across multiple species, including Least Bittern (Ixobrychus exilis), Sora (Porzana carolina), and Virginia Rail (Rallus limicola; Sauer et al., 2017; Tozer, 2016). King Rail populations (Rallus elegans) have also declined in the Midwestern United States (Bolenbaugh et al., 2012), and a long-term study (1980–2005) of northeastern Illinois wetland birds revealed approximately 8%, 12%, 15%, and 19% population declines of Blue-winged Teal (Anas discors), Black Tern (Chlidonias niger), American Coot (Fulica americana), and Common Gallinule (Gallinula galeata), respectively (Ward et al., 2010). The causes of wetland bird declines are multifaceted and have been linked to wetland loss, fragmentation, and degradation following agriculture conversion and urbanization throughout the United States, especially in the Midwest (Brazner et al., 2007; Ward et al., 2010).

Urbanization poses unique challenges for wetland birds. Buildings, impervious surfaces, and roads fragment wetlands and alter the surrounding matrix, reducing the availability of high-quality habitats for breeding and foraging (Aronson et al., 2014). Wetland loss and fragmentation also decrease wetland bird reproductive success, particularly for area-dependent species such as Least Bittern and Common Gallinule, which require a minimum of ~7 ha of contiguous habitat to breed (Tozer et al., 2010). Surrounding development can increase silt and pollution runoff into nearby wetlands, decreasing species richness of common food sources for wetland birds, such as invertebrates, amphibians, and fish (Sievers et al., 2018; Ward et al., 2010). As native prey availability declines, wetland birds can exploit anthropogenic food subsidies (Evans & Gawlik, 2020), but urban subsidies may be of poor nutritional quality and thus can lead to lower fitness (Shochat et al., 2010). Despite these challenges, wetland birds may continue to persist in wetland habitats within highly modified landscapes, provided that species-specific resource needs (e.g., food availability and vegetation structure) are met. Given the increasing pace of urbanization and the growing need to manage wetlands in the context of human population growth (Zhang & Ouyang, 2019), more information on the conditions influencing species-specific persistence in urban wetlands is needed.

Due to the diversity of habitat requirements, life history strategies, and food sources of wetland birds, it is likely that individual species will respond to landscape characteristics across a variety of spatial scales, thereby impacting multispecies conservation strategies. For example, species that are known to nest and forage in open water, such as Pied-billed Grebe (Podilymbus podiceps) and Common Gallinule, have been shown to occupy areas with larger and more abundant ponds, and less emergent vegetation (Saunders et al., 2019; Tozer et al., 2010). By contrast, occupancy of some species, such as the Virginia Rail and Sora, remains invariant to increases in landscape-level wetland cover. Species such as rails that exhibit especially secretive behaviors and rely on dense, emergent vegetation for nesting may be more limited by fine-scale habitat characteristics than by wetland availability at larger spatial scales (Tozer et al., 2010). Although several studies have documented species- and scale-specific responses to certain land cover types for several wetland birds (e.g., Saunders et al., 2019; Tozer et al., 2010), these surveys were not concentrated within urban areas. Without understanding how species respond across disturbance and habitat availability gradients, we cannot effectively manage or conserve wetland birds in a rapidly urbanizing world.

Here, we assess relationships between wetland and urban land cover types measured at multiple spatial scales (200-, 400-, 800-, and 2000-m radial distances) with wetland bird occupancy in the Chicago Wilderness region of northeastern Illinois and northwestern Indiana, USA. We address the following questions: (1) Which wetland bird species are using urbanized habitats during the breeding season? (2) Which wetland cover types have the strongest associations with species-specific occupancy probabilities across our suite of focal species? And (3) at which spatial scales do wetland cover types and urbanization impact breeding wetland birds? The purpose of our study was to assess the value of urban wetlands for multiple species of conservation concern to inform land management decisions and pinpoint further avenues of research.


Study sites and wetland selection

We surveyed a suite of 60 wetland complexes in northeastern Illinois and northwestern Indiana, including marshes, lake and pond edges, wet meadows, emergent wetlands, and bogs (Figure 1). Following Conway (2011), we created fixed, permanent survey points within wetlands on public lands. Wetlands were chosen based on accessibility, as well as existing partnerships with landowners as part of ongoing wetland management and threatened species work in Cook, Lake, and McHenry Counties in Illinois and Lake, Porter, and LaPorte Counties in Indiana. Though a subset of wetlands that we surveyed were coastal, 45 of 60 (75%) wetland complexes in our study were not hydrologically connected to Lake Michigan. Thus, water levels at these sites would not be responsive to fluctuating Great Lakes water levels, which have been shown to impact wetland bird abundance (Gnass Giese et al., 2018; Timmermans et al., 2008). For wetland bird surveys, up to 14 survey points within a wetland unit were located at least 200 m apart and together comprised a survey route. Survey points were initially determined using the center points within a 200  × $$ \times $$  200 m grid for small wetlands (<40 ha) or a 400 × $$ \times $$  400 m grid for large wetlands (>40 ha); survey point selection was then adjusted and finalized on site using GPS coordinates to ensure accessibility and that each point sampled emergent marsh habitat. A total of 477 unique points along 60 routes were surveyed during the combined 2017–2019 breeding seasons, with surveys at 53 points repeated between years. Surveyors consisted of a mix of professionals and volunteers; all surveyors were trained in wetland bird monitoring protocols and tested on their identification abilities prior to surveying.

Details are in the caption following the image
Map of wetland bird survey locations within the Chicago Wilderness region. Survey points are colored to illustrate the range of urbanization: not urbanized to slightly (0%–14%) urbanized wetlands in blue (i.e., low urbanization); moderately (14%–32%) urbanized wetlands in yellow (i.e., medium urbanization); and severely (32%–66%) urbanized wetlands in dark orange (i.e., high urbanization), as measured by the percentage of urbanized/impervious surfaces within a 2000-m buffer around each survey location.

Survey design and focal species

Wetland bird surveys followed the North American Wetland Bird Monitoring Protocol (Conway, 2011). All survey locations were visited three times between 1 May and 15 June during 2017–2019, with a single surveyor collecting data from 30 min before sunrise to ~3 h after sunrise. Surveys were not conducted during high winds, sustained rain, or heavy fog. All surveys began with a passive 5-min point count of unlimited radius, followed immediately by a 60-s sequence comprised of 30 s of wetland bird broadcasts and 30 s of silence for five primary focal species, for a total of 10 min of survey time. We also noted occurrences of 12 additional secondary species for which we did not use playback calls because these species are known to call consistently without the use of playback or are otherwise easily detected. The majority of surveyed species are of special conservation concern in the Chicago Wilderness region and are state-threatened or endangered in Illinois and Indiana.

During each survey, observers estimated the number of individuals for each of the 17 species detected by sight or sound. Observers estimated the distance from the survey point to each individual to the nearest 5 m for all primary focal species and estimated binned distances of <50, 50–100, and >100 m for secondary focal species. For this analysis, we truncated species detections to those within a 200 m radius from the survey point, the distance at which many calling wetland birds can be heard (Allen et al., 2004; Johnson et al., 2009). Of the 17 total species included in this survey effort, 10 had sufficient sample sizes for occupancy analysis (i.e., ≥25 total detections): American Coot, Black-crowned Night-Heron, Blue-winged Teal, Common Gallinule, Least Bittern, Marsh Wren, Pied-billed Grebe, Sora, Swamp Sparrow, and Virginia Rail. Overall, the species selected for occupancy modeling vary in their wetland habitat requirements, as well as their potential sensitivity to urbanization. We controlled for species-specific habitat preferences by building separate models for each of the 10 focal species.

Land cover data

We quantified the amount of wetland and urbanized land cover types surrounding survey points at four spatial scales (i.e., radial distances from each survey point): immediate (200 m), local (400 m), intermediate (800 m), and landscape (2000 m). We based spatial scales on our detection cutoff of birds within 200 m of each survey point, as well as a review of focal species' home range sizes (Allen et al., 2004; Johnson et al., 2009). Additionally, the first three radial distances increase in area by a factor of four (i.e., 12.6, 50.3, and 201.2 ha), and the landscape-scale designation (1256 ha) captures potential regional habitat associations.

We used National Wetland Inventory (NWI) data to calculate the proportion of wetland cover types unique to each survey point's radial buffer distances. We accessed NWI data through US Fish and Wildlife Service, using Illinois and Indiana NWI data updated in May 2020. Using ArcGIS 10.7.1 (Environmental Systems Resource Institute, 2019), we retained cover classes of wetland types most associated with habitats used by our focal species (Glisson et al., 2017; Lor & Malecki, 2002), including emergent wetland (EmWet), forested/shrub wetland (ForWet), and riverine wetland (RivWet), as separate covariates to represent relevant wetland availability. We also calculated the proportion of freshwater ponds (Pond) within each survey point's buffer distances as some focal species preferentially nest over or forage in open water (e.g., Pied-billed Grebe).

Surveyed wetlands contained a mixture of open water at the wetland center, with emergent vegetation comprised of invasive hybrid cattail (Typha × glauca) and common reed (Phragmites australis). Native species, such as pickerel weed (Pontederia cordata), common bur-reed (Sparganium eurycarpum), and sedges, often fringed ponds, and floating vegetation dominated pond centers. While most riverine wetlands were broad channels edged with emergent vegetation, others were narrow channels surrounded by invasive reed canary grass (Phalaris arundinacea) and stands of purple loosestrife (Lythrum salicaria). Emergent wetlands included wet meadows, which usually contained multiple native sedges, rushes, and aquatic perennials such as arrowheads (Sagittaria spp.). Emergent flora in remnant swale and dune wetlands was similar to that in inland wetlands, and adjacent dunes were typically forested.

To estimate the influence of anthropogenic development on wetland use by our focal species, we used the Global Urban Footprint (GUF) (Esch et al., 2017) layer to calculate the proportion of land cover around each survey point (at each of the four spatial scales) classified as urbanized/impervious surface (Urban; Figure 2; Appendix S1: Table S1). The GUF layer is a fine-scale, binary, thematic raster (12-m resolution) with values for “built-up” and “non-built-up” areas, where “built-up” is defined as a region featuring man-made structures with a vertical component. We calculated proportional cover of the five land cover groups (three wetland types, freshwater ponds, and urbanized habitat) within the nested set of four buffers surrounding each survey point, yielding 20 land cover covariates for inclusion: emergent wetland (EmWet200, EmWet400, EmWet800, and EmWet2000), forested wetland (ForWet200, ForWet400, ForWet800, and ForWet2000), riverine wetland (RivWet200, RivWet400, RivWet800, and RivWet2000), freshwater ponds (Pond200, Pond400, Pond800, and Pond2000), and urbanized habitat (Urban200, Urban400, Urban800, and Urban2000). Lastly, we included a covariate that represented distance to Lake Michigan (DistLake), given that the ecology of Great Lakes coastal wetlands (e.g., vegetation and soil composition) is markedly different than that of inland wetlands (Albert et al., 2005).

Details are in the caption following the image
Google Earth images depicting low (row a), medium (row b), and high urbanization (row c) around survey locations, as measured by the percentage of urbanized/impervious surfaces within a 2000-m buffer around each survey location.

Statistical analyses

We estimated occupancy ( ψ $$ \uppsi $$ ) and detection probability ( p $$ p $$ ) parameters for focal species with the unmarked package in R, version 3.6.1 (Fiske & Chandler, 2011; R Development Core Team, 2020). We estimated species-specific occupancy using the likelihood-based method (MacKenzie et al., 2002) and developed separate models for each species based on stacking data from repeated survey visits within years. Thus, our “effective sites” were derived from three survey visits at each survey point annually. We treated year as a site-specific covariate in all models because only about 40% of survey points were visited in all years (Linden et al., 2017).

Under this occupancy model parameterization, the area within 200 m of the survey point was considered closed to changes in occupancy within years (MacKenzie et al., 2002). Our occupancy response variable ( ψ $$ \uppsi $$ ) can be considered “use” (sensu MacKenzie, 2005; Mackenzie et al., 2006) because birds may be temporarily, but not permanently, absent from a given survey point at random times. In this context, our estimate of occupancy describes the proportion of survey points ever occupied, rather than the survey points that are permanently occupied (Kéry & Schaub, 2012). We retain the term “occupancy” to maintain the terminology used in this modeling approach (e.g., Glisson et al., 2017). For comparison across species, we also estimated parametric bootstrapped distributions of finite-sample occupancy probabilities ( ψ FS $$ {\uppsi}_{\mathrm{FS}} $$ ) and associated 95% confidence intervals (CIs), which we defined as the proportion of occupied survey points (Kéry & Royle, 2016).

Model selection and goodness of fit—Occupancy modeling followed a multistep process adapted from Glisson et al. (2017) and Saunders et al. (2019). In our initial step, we examined the influence of survey-specific covariates on detection probability p $$ p $$ , while holding occupancy probability ψ $$ \uppsi $$ constant. We were interested in accounting for two processes known to influence the detection probability and availability of wetland birds during surveys (Conway, 2011; Tozer, 2016): time of day (Time; 24 h) and time of year (Date; ordinal date). Both continuous explanatory variables were standardized to have a mean of zero and a standard deviation (SD) of 1. We used the Akaike information criterion (AIC) to compare among nine detection models: a null (intercept-only) model, three models with only linear terms (Date, Time, and Date + Time), and five models with linear and quadratic terms (Date + Date2, Time + Time2, Date + Date2 + Time, Time + Time2 + Date, and Date + Date2 + Time + Time2). We incorporated the model with the lowest AIC into all subsequent occupancy models for each species.

After we developed detection models with appropriate covariates, we used a multistep modeling approach to examine the influence of emergent wetland cover, forested wetland cover, riverine wetland cover, freshwater ponds, urbanized habitat, and distance to Lake Michigan on wetland bird occupancy. Given potential correlations between the same land cover type measured across scales, we first evaluated which spatial scale was most supported for each of the five land cover covariate categories independently (EmWet, ForWet, RivWet, Pond, and Urban) using AIC to compare among scale-specific covariates on occupancy. Hence, we compared separate occupancy models for each species to determine the spatial scale of support for each land cover variable. Of the four covariates within each land cover category (e.g., EmWet200, EmWet400, EmWet800, and EmWet2000), we retained the one that led to the greatest reduction in AIC relative to the null model, which included only year as a site-specific covariate on occupancy. If none of the four covariates were supported for a given land cover type (i.e., did not reduce AIC relative to the null model), we omitted that land cover category in subsequent steps. We then incorporated the retained informative variables (i.e., as additive terms) individually in multiple regression occupancy models and used AIC to compare models within subsets. If the inclusion of a given variable improved upon the base model by >2 AIC , $$ \Delta \mathrm{AIC}, $$ we considered that variable informative and retained it for the next step. We used Pearson's correlation coefficient ( r $$ r $$ ) to examine correlations among informative variables that we identified via this process. If two informative variables were highly correlated (| r $$ r $$ | ≥ 0.5), we retained the variable with the lower AIC value. If the linear term for a given covariate was supported, we also considered the quadratic term (e.g., Urban4002). When additional covariates no longer led to a reduction in AIC, we retained the top-ranking model from the previous step as the best-supported model. Occupancy models for all species included a year effect to account for possible differences in survey effort and sites visited annually. We did not include interactions among explanatory variables on occupancy because we started with a large number of covariates and wanted to avoid overfitting, maintain a manageable number of candidate models, and preserve biological interpretability.

We assessed goodness of fit of the best-supported, species-specific occupancy models using the goodness-of-fit test (Pearson's χ2 test) by MacKenzie and Bailey (2004), implemented with the mb.gof.test function in the R package AICmodavg (Mazerolle, 2015), and bootstrapped 500 times to obtain a p value. We also calculated c-hat, the overdispersion ratio, to ensure that all c-hat values were close to 1 (all c-hat values were 0.95 ≥ c-hat ≤ 1.07); in cases where c-hat was >1 (Pied-billed Grebe only), we adjusted standard errors and CIs by the overdispersion ratio when illustrating model-based predictions (sensu Kéry & Royle, 2016).


Species-specific occupancy and detection probabilities

Of the 10 wetland bird species included in occupancy modeling, Sora had the greatest finite-sample occupancy, on average, followed by Marsh Wren, Swamp Sparrow, Black-crowned Night-Heron, American Coot, Blue-winged Teal, and Virginia Rail with ≥30% occupancy at survey points (Table 1). Least Bittern, Pied-billed Grebe, and Common Gallinule occupied <30% of survey points (Table 1). Overall, we found no substantial differences in annual mean occupancy estimates for any species among years during 2017–2019 (i.e., overlapping 95% CIs), although Common Gallinule, Sora, and Virginia Rail had a positive trend in mean occupancy over the three-year period (Appendix S1: Figure S1). Mean occupancy of Blue-winged Teal, Least Bittern, Marsh Wren, Pied-billed Grebe, and Swamp Sparrow was relatively stable during 2017–2019. Variables included in the best-supported occupancy models differed among species (Table 2), but relationships with survey-specific variables were generally consistent with expectations. For example, detection probabilities ( p $$ p $$ ) of four species (American Coot, Blue-winged Teal, Common Gallinule, and Sora) had strongly negative associations with date, indicating that these species were more likely to be detected early in the breeding season (Appendix S1: Table S2). Marsh Wren detection probability had a quadratic relationship with time of day, indicating higher detection at both dawn and dusk (Appendix S1: Table S2). There were no significant effects of survey date or time on detection of Black-crowned Night-Heron, Least Bittern, Pied-billed Grebe, or Virginia Rail.

TABLE 1. Number of survey points at which each species was observed (out of 530 total points) and the estimated proportion of survey points occupied ( ψ FS $$ {\uppsi}_{\mathrm{FS}} $$ ), based on top-ranking models, along with 95% confidence intervals (95% CIs) estimated from parametric bootstrapping.
Species No. points with observations Estimated proportion of points occupied (95% CI)
Sora 210 0.56 (0.49–0.64)
Marsh Wren 253 0.51 (0.47–0.56)
Swamp Sparrow 163 0.38 (0.34–0.42)
Black-crowned Night-Heron 83 0.34 (0.25–0.48)
American Coot 64 0.33 (0.25–0.45)
Blue-winged Teal 68 0.32 (0.22–0.53)
Virginia Rail 123 0.31 (0.26–0.35)
Least Bittern 34 0.28 (0.12–0.63)
Pied-billed Grebe 86 0.23 (0.18–0.28)
Common Gallinule 50 0.19 (0.15–0.24)
  • Note: Species are listed in order of decreasing probability of occupancy.
TABLE 2. Explanatory variables included in top-ranking occupancy models for 10 wetland bird species in Illinois during 2017–2019.
Species Emergent wetland Forested wetland Riverine wetland Freshwater pond Urbanized habitat Distance to Lake Michigan
American Coot RivWet2000 (+) Pond200 (q)
Black-crowned Night-Heron RivWet2000 (q) Pond400 (+) DistLake (−)
Blue-winged Teal Pond400 (+)
Common Gallinule EmWet200 (+) RivWet2000 (q) DistLake (−)
Least Bittern EmWet800 (+)
Marsh Wren EmWet200 (+) Pond400 (q) DistLake (−)
Pied-billed Grebe EmWet2000 (−) Urban200 (−) DistLake (−)
Sora EmWet200 (+) RivWet200 (−)
Swamp Sparrow EmWet400 (q) RivWet2000 (q) Urban200 (−)
Virginia Rail EmWet200 (+)
  • Note: Variables evaluated on occupancy ψ $$ \uppsi $$ include proportion of emergent wetland cover (EmWet), distance to Lake Michigan (DistLake), proportion of forested wetland (ForWet), proportion of freshwater pond cover (Pond), proportion of riverine wetland (RivWet), and proportion of urbanized habitat (Urban). Year was included as a site-specific variable in all models. EmWet, ForWet, Pond, RivWet, and Urban were measured at four spatial scales (200, 400, 800, and 2000-m radial distance buffers), indicated by subscripts. Directions of relationships are shown in parentheses, with + indicating a positive relationship, − indicating a negative relationship, and q indicating a quadratic relationship with the predictor. See Appendix S1: Table S2 for parameter estimates.

Species–land cover relationships

The expected occupancy of six species exhibited a strong positive association with the proportion of emergent wetland cover at a given spatial scale (p < 0.05; Figure 3; Appendix S1: Table S2). Pied-billed Grebe occupancy, however, was negatively related to proportion of emergent wetland at the landscape scale (i.e., 2000-m radial distance). Best-supported occupancy models included a quadratic effect of the proportion of riverine wetland cover for Black-crowned Night-Heron, Common Gallinule, and Swamp Sparrow at the landscape scale (Figure 4; Appendix S1: Table S2). American Coot occupancy was also related to landscape-scale riverine wetland availability, although the relationship was linear and positive, whereas Sora occupancy was negatively associated with riverine wetland cover at the smallest spatial scale (i.e., 200-m radial distance; Figure 4; Appendix S1: Table S2). American Coot, Black-crowned Night-Heron, Blue-winged Teal, and Marsh Wren occupancy rates were positively related to proportion of freshwater ponds at finer spatial scales (i.e., immediate and local, 200–400 m; Appendix S1: Table S2, Figure S2). Best-supported models for two of these species (Black-crowned Night-Heron and Marsh Wren) also included negative effects of distance to Lake Michigan on occupancy (Appendix S1: Figure S3). Similarly, Common Gallinule and Pied-billed Grebe occupancy rates were negatively related to distance to the lake (Appendix S1: Figure S3). The expected occupancy probabilities of only two species, Pied-billed Grebe and Swamp Sparrow, were negatively influenced by the proportion of urbanized habitat in the immediate vicinity (i.e., 200-m radial distance; Figure 5; Appendix S1: Table S1). The proportion of forested wetlands was not a strong predictor of occupancy for any of the 10 focal species at any of the four spatial scales evaluated.

Details are in the caption following the image
Estimates of the expected occupancy probability for Common Gallinule, Least Bittern, Marsh Wren, Pied-billed Grebe, Sora, Swamp Sparrow, and Virginia Rail as a function of the proportion of emergent wetland cover (EmWet) around survey points in the Chicago Wilderness region during 2017–2019 breeding seasons. EmWet is measured at the immediate (200-m radial distance) scale for Common Gallinule, Marsh Wren, Sora, and Virginia Rail; at the local (400 m) scale for Swamp Sparrow; at the intermediate (800 m) scale for Least Bittern; and at the landscape (2000 m) scale for Pied-billed Grebe. All other covariates in top-ranking models were held at mean values (year = 2019). Shading represents 95% CIs. Graphs include 95% of the observed range of variation in covariates.
Details are in the caption following the image
Estimates of the expected occupancy probability for American Coot, Black-crowned Night-Heron, Common Gallinule, Sora, and Swamp Sparrow as a function of the proportion of riverine wetland cover (RivWet) around survey points in the Chicago Wilderness region during 2017–2019 breeding seasons. RivWet is measured at the landscape (2000-m radial distance) scale for all species except Sora (200-m radial distance). All other covariates in top-ranking models were held at mean values (year = 2019). Shading represents 95% CIs. Graphs include 95% of the observed range of variation in covariates.
Details are in the caption following the image
Estimates of the expected occupancy probability for Pied-billed Grebe and Swamp Sparrow as a function of the proportion of urbanized habitat (Urban) around survey points in the Chicago Wilderness region during 2017–2019 breeding seasons. Urban is measured at the immediate (200-m radial distance) scale for both species. All other covariates in top-ranking models were held at mean values (year = 2019). Shading represents 95% CIs. Graphs include 95% of the observed range of variation in covariate.


Wetland cover associations at scale

By combining wetland bird survey datasets collected across the Chicago Wilderness region with remotely sensed data describing wetland habitat availability and urbanization, we found that wetland bird occupancy was related to multiple land cover characteristics at several spatial scales. The presence of emergent wetlands from immediate to intermediate scales (200–800 m) and freshwater ponds at immediate and local scales (200–400 m) increased the occupancy of 9 of 10 focal species. At the immediate (200 m) scale, the presence of emergent wetlands increased occupancy of Common Gallinule, Marsh Wren, Sora, and Virginia Rail, suggesting that fine-scale features of emergent vegetation likely provide critical habitat for these species. The positive relationship between Least Bittern and Swamp Sparrow occupancy probability with emergent wetland habitat, and between Common Gallinule occupancy and riverine habitat at larger (400–2000 m) scales, suggests that these species are more area-sensitive. Thus, their occupancy probability may only increase if there is sufficient habitat availability (i.e., large wetland complexes) at the landscape scale. Other studies have shown that Swamp Sparrow has a positive association with wetland density and the presence of wetland edge habitat (Fairbairn & Dinsmore, 2001; Harms & Dinsmore, 2015), corroborating our results. The management of Swamp Sparrow would likely benefit from increasing the number of small wetlands distributed across the landscape. Alternatively, previous research has shown that Least Bittern has a minimum wetland area requirement to breed; therefore, both Least Bittern and Common Gallinule may require larger tracts of intact wetlands to maintain their populations (Tozer et al., 2010).

As in Bolenbaugh et al. (2011), forested wetland cover was not a strong predictor of occupancy for any of our focal species, indicating restoration of this wetland type would be unlikely to increase the occupancy of wetland-breeding birds. Indeed, forested wetlands are likely to harbor predators of our focal species, such as raptors, corvids, and raccoons, which are likely to target nests and young (Jobin & Picman, 1997). However, land managers seeking to increase populations of wetland-breeding birds should not ignore forested wetland restoration as forested wetlands eventually turn over to emergent wetlands through a cycle of disturbance and succession (Welsch et al., 1995) and can benefit species that require consistent water depths during nesting (e.g., Virginia Rail) by acting as spillover sites during flooding events (Acreman & Holden, 2013). Overall, the management of diverse wetland habitat types in varying degrees of succession is ideal for supporting wetland bird diversity (Lor & Malecki, 2006).

Wetland bird persistence in urbanized regions

Urbanization did not significantly affect occupancy of most focal species during our study period, with the exception of Pied-billed Grebe and Swamp Sparrow, which showed negative effects at the immediate (200 m) scale. Likewise, several studies have shown declines in Swamp Sparrow populations with increasing urbanization (Smith & Chow-Fraser, 2010). However, studies of Pied-billed Grebe are generally lacking, so their responses to urban wetlands remain largely unknown (Routhier et al., 2014). Range-wide studies are needed to further elucidate the possible consequences of urbanization on the abundance and demographic rates of Pied-billed Grebe (Harms & Dinsmore, 2015; Ward et al., 2010).

This study was conducted during years (2017–2019) when Lake Michigan water levels were high, which may have impacted wetland water depth and thus wetland bird occupancy in our study area. It is possible that during lower water years, species may exhibit greater sensitivity to urbanization. Our inferences on occupancy–urbanization relationships may differ under these circumstances (i.e., due to nonstationarity of covariate effects; Rollinson et al., 2021). Nevertheless, 75% of wetlands we surveyed were not hydrologically connected to Lake Michigan, so the potentially negative effects of urbanization on wetland bird occupancy would not have been confounded by high lake water levels. Rather, the lack of urbanization as a significant covariate influencing American Coot, Blue-winged Teal, Least Bittern, Sora, and Virginia Rail occupancy suggests that these species opportunistically use urban wetland habitats provided that minimum habitat requirements—sufficient emergent vegetation, the presence of open water and riverine wetlands, and availability of deep water for overwater nesting species—are met (Fournier et al., 2021).

A prior study conducted in the Great Lakes region found that American Bittern, Black-crowned Night-Heron, Blue-winged Teal, Least Bittern, and Swamp Sparrow occurrences were not significantly associated with the percentage of impervious surfaces compared with wetland type, water level, and Phragmites presence (Grand et al., 2020). Likewise, we found that Black-crowned Night-Heron, Blue-winged Teal, and Least Bittern occupancy was not related to urbanization in our study area. Rather, occupancy of multiple wetland bird species primarily depended on the presence of emergent wetlands and ponds at immediate and local (200–400 m) scales, suggesting wetland birds likely take advantage of high-quality wetland habitat even in small, urbanized wetlands. Similarly, McKinney et al. (2011) noted increased dependence of birds on wetlands with increasing urbanization regardless of wetland size, while Baldwin (2004) found increased complexity and higher plant diversity in a restored urban wetland relative to multiple reference wetlands. Both studies highlight the importance of urban wetland restoration, though Tozer (2016) and Tozer et al. (2020) argue for increasing marsh connectivity and minimizing development-bordering marshes. Based on the results of our study, these two goals need not be mutually exclusive; restoring emergent wetland at immediate spatial scales and pond restoration at local (200 m) scales will both improve wetland connectivity and help increase wetland bird occupancy in urban and rural wetlands throughout the Chicago Wilderness region.

Management implications

The results of this study emphasize that even small, urban wetlands can be managed for a variety of wetland bird species of concern. A critical component of wetland restoration is the removal of invasive monocultures (Hazelton et al., 2014; Tozer & Mackenzie, 2019). Thus, in areas that already have high occupancy of wetland birds and dominance of invasive emergent vegetation, we recommend managers take steps to pair the removal of invasives with the planting of native, emergent vegetation. Managers should also consider leaving several stands of cattail, given that certain species (e.g., Marsh Wren) benefit from the structure these patches of taller emergent vegetation provide (Kroodsma & Verner, 2020). Because our study indicated that Least Bittern, Swamp Sparrow, and Common Gallinule may be area-sensitive, we recommend that managers seek opportunities to increase wetland connectivity and “defragment” wetlands (Meng et al., 2020). Greater connectivity may increase breeding opportunities for these species.

Since many wetlands in the Chicago Wilderness region have been hydrologically disconnected from other waterbodies (Environmental Protection Agency, 2021), the implementation of water control structures can also be used to enhance small urban wetlands in highly urbanized areas. When feasible, we recommend that land managers use water level control as an artificial way of lowering and raising water levels, as this method can re-create dynamic water levels in an otherwise fragmented or stagnant wetland (Ma et al., 2009). Artificial water level control can also be used to control invasive species through raising the water level, while lowering the water level can allow new plantings to germinate (Casanova & Brock, 2000; Hazelton et al., 2014). Wetlands in less developed coastal zones would likely benefit from hydrologic reconnection to enhance their water level regulation by seasonal fluctuations in lake levels.

The findings of this study are currently being applied to wetland restoration efforts across the Chicago Wilderness region in a regional effort to boost declining wetland bird populations. For example, in 2021, Audubon Great Lakes launched the Marsh Bird Monitoring Hub (Audubon Great Lakes, 2022), a set of interactive data visualization tools used by land managers to make science-informed management decisions while evaluating restoration impacts on birds. With this tool, land managers can visualize bird activity at specific locations within sites and compare changes in occupancy to management actions, such as improving wetland hydrology, creating openings within dominant invasive emergent vegetation, and planting native emergent vegetation. Thus, the results of wetland bird data collection fuel an adaptive management process that continually provides feedback to land managers over the long term (Ma et al., 2009; Saunders et al., 2021).

Future studies

Given that the relationships between wetland bird occupancy and wetland cover types may vary with particularly high or low Great Lakes water levels (Gnass Giese et al., 2018; Timmermans et al., 2008), continued monitoring will help reveal how wetland bird occupancy varies temporally as a function of landscape-level water availability. Additionally, future analyses should focus on parsing out wetland vegetation cover into ecologically relevant proportions of specific plant communities (e.g., cattail, Phragmites, native rushes, and sedges) at appropriate spatial scales to evaluate associations with wetland bird species, serving to provide more detailed guidance to managers during wetland restorations.

Finally, few studies link restoration actions to wetland bird occupancy or population trends (Bradshaw et al., 2020). Audubon's Marsh Bird Monitoring Hub offers a promising approach for compiling site-specific management data with the goal of evaluating the effects of different restoration techniques on wetland bird occupancy and diversity across watershed-level scales. Future iterations of the Marsh Bird Monitoring Hub will track how habitat quality (as a function of bird occupancy and vegetation characteristics) changes over time with restoration activities. Overall, this approach will assist researchers and managers with conserving multiple state-endangered, declining, and cryptic wetland bird species in the highly urbanized landscape of the Upper Midwest.


We thank the following individuals and organizations for assistance with fieldwork: Matt Beatty, Donnai Casillas, Carly Conley, Joe Drexler, Victor Duda, Kim Ehn, Cookie Ferguson, Jessica Gomez, Carol Goodall, Lindsay Grossman, Gregory Hejnar, Aqsa Junagadhwala, Libby Keyes, Sammi King, Travis Kuntzelman, Paul Labus, Vera Leopold, Emma Lord, Dan Lory, Barb Lucas, Walter Marcisz, Shari McCollough, Michael McNamee, Lauren Nassef, Dick Niemi, Joel Perez, Michael Topp, Alison Világ, Edward Warden, Kristian Wielunski, Ken Wilson, Dunes-Calumet Audubon Society, Indiana Audubon Society, Illinois Department of Natural Resources, Indiana Department of Natural Resources, Indiana University Northwest, Shirley Heinze Land Trust, South Bend-Elkhart Audubon Society, and The Nature Conservancy. Anastasia A. Rahlin was supported by the funding from the Illinois State Toll Highway Authority under Bryan Wagner. Funders had no input into the content of the manuscript and did not require approval of this manuscript before submission or publication. Illinois wetland bird surveys were conducted under permits granted by the Chicago Park District, Forest Preserves of Cook, Lake, McHenry, and DuPage County, Illinois Department of Natural Resources, Northeastern University, and the Illinois Nature Preserves Commission. Illinois wetland bird surveys were conducted under University of Illinois-approved IACUC Protocols (number 18191). Indiana wetland bird surveys were conducted under permit NP20-08 issued by the Indiana Department of Natural Resources and permit INDU-2017-SCI-0025 issued by the US Department of the Interior National Park Service, Indiana Dunes.


    The authors declare no conflict of interest.


    Data and code (Rahlin et al., 2022) are available from the University of Illinois Databank: