Assessing the sensitivity of wetland bird communities to hydrologic change in the eastern Great Lakes region

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Assessing the sensitivity of wetland bird communities to hydrologic change in the eastern Great Lakes region
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  605 WETLANDS, Vol. 26, No. 2, June 2006, pp. 605–611  2006, The Society of Wetland Scientists NOTEASSESSING THE SENSITIVITY OF WETLAND BIRD COMMUNITIES TOHYDROLOGIC CHANGE IN THE EASTERN GREAT LAKES REGION David A. Steen 1,3 , James P. Gibbs 1 , and Steven T. A. Timmermans 21 State University of New York College of Environmental Science and Forestry350 Illick Hall, 1 Forestry DriveSyracuse, New York, USA 13210 2  Bird Studies CanadaP.O. Box 160Port Rowan, Ontario, Canada, N0E 1M0 3 Present address: Joseph W. Jones Ecological Research Center  Route 2, Box 2324 Newton, Georgia, USA 39870 E-mail: David.Steen@jonesctr.org  Abstract: Uncertainty about the effects of ongoing natural and anthropogenic changes to Great Lakes eco-systems, such as managed stabilized water levels, coupled with widespread public interest regarding statusof wetland birds prompted us to evaluate sensitivity of regional wetland birds to hydrologic changes. Wereviewed published literature to determine preferred habitat of 30 wetland birds in the region, emphasizingvegetation required for foraging and nesting during the breeding season. Species were subsequently assignedto one of three risk categories based on association with vegetation types sensitive to water-level stabilization,as well as nesting height above water. Notably, of the bird species designated as low, moderate, and highrisk, 25%, 33%, and 63%, respectively, have been regionally declining based on Bird Studies Canada’sMarsh Monitoring Program. This evaluation may be useful to regional biologists, planners, and managersconcerned with predicting how particular species might be affected by future hydrologic changes in this andrelated systems. Key Words: bird populations, Great Lakes, habitat loss, hydrology, Lake Ontario, waterbirds, water levelmanagement INTRODUCTIONRelatively little is known regarding the biology of wetland-associated birds. These birds include some of the most unique species (e.g., grebes and bitterns) andsome of the most abundant species (e.g., Red-wingedBlackbird; see Table 1 for scientific names), as wellas many charismatic and endangered species (e.g.,Black Tern). Numbers of many wetland bird speciesare decreasing in North America (Eddleman et al.1988, Conway and Eddleman 1994), including in theGreat Lakes region (Timmermans et al. 2004). Theprimary factor for these declines is likely habitat lossand degradation, including wetland habitat alterationcaused by anthropogenic manipulation of hydrologiccycles.Diversity of wetland bird communities is widelyconsidered to be associated with the diversity of wet-land flora, as well as spatial complexity of their jux-taposition with one another on the landscape (Gibbs etal. 1991). Consequently, any ecological processes thattend to simplify or homogenize wetland habitats willlikely do so to the detriment of wetland-associated birdcommunities. Stabilizing water levels or managingthem outside the range of historic fluctuations elimi-nates the dynamic patterns that allow a diversity of wetland species and communities to thrive (Bedford1990). Such is the case in the Great Lakes region,where one consequence of decades of water-level man-agement on Lake Ontario has been a tendency forfringing wetlands to become more densely vegetatedand dominated by cattail ( Typha spp.) and invasivespecies such as purple loosestrife, (  Lythrum salicaria  606 WETLANDS, Volume 26, No. 2, 2006 Table 1. Habitat preferences and nest heights of Lake Ontario wetland birds. Citations upon which this synthesis is based are availablefrom the authors.SpeciesNest Height(m) Foraging Habitats 2 Nesting Habitats Population Trend 3  High Risk  1 Pied-billed Grebe Podilymbus podiceps Linnaeus  1 OW; SV; EV OW; SV; EV DecreaseAmerican Coot Fulica americana Gmelin  1 OW; SV OW; EV N/ACommon Moorhen Gallinula chloropus Linnaeus  1 SV; EV EV; SV DecreaseBlack Tern Chlidonias niger  Linnaeus  1 OW; EV OW, EV DecreaseCaspian Tern Sternia caspia Pallas  1 OW SDG IncreaseVirginia Rail  Rallus limicola Vieillot  1 OW; EV EV IncreaseMarsh Wren Cistothorus palustris Wilson  1 EV EV DecreaseLeast Bittern  Ixobrychus exilis Gmelin  1 EV EV DecreaseSora Porzana carolina Linnaeus  1 EV; SS; MF EV; SS Increase  Moderate Risk  Belted Kingfisher Ceryle alcyon Linnaeus Variable OW B DecreaseRed-winged Blackbird  Agelaius phoeniceus Linnaeus Variable EV EV; SS; MF; OT IncreaseNorthern Shoveler  Anas clypeata Linnaeus  1 OW; SV MF N/ASwamp Sparrow  Melospiza georgiana Latham  1 OW; EV; SS; S EV; SS; S IncreaseBlue-winged Teal  Anas discors Linnaeus  1 SV; EV; SS EV; SS; MF IncreaseGadwall  Anas strepera Linnaeus Variable SV SS; S IncreaseGreen-winged Teal  Anas crecca Linnaeus  1 SV; EV SS; MF N/AAmerican Bittern  Botaurus lentiginosus Rackett  1 EV; SS; S EV; MF; SS DecreaseCommon Snipe Gallinago gallinago Linnaeus  1 SS; EV OW; SS; S N/A  Low Risk  Great Blue Heron  Ardea herodias Linnaeus  1 OW; MF, SV, EV OT IncreaseBlack-crowned Night Heron  Nycticorax nycticorax Linnaeus  1 OW; SV; EV EV; SS; S; OT Decrease  Steen et al. , BIRDS AND GREAT LAKES HYDROLOGY 607 Table 1. Continued.SpeciesNest Height(m) Foraging Habitats 2 Nesting Habitats Population Trend 3 American Wigeon  Anas americana Gmelin  1 SV; EV; MF S; MF N/ACanada Goose  Branta canadensis Linnaeus  1 SV; MF EV; MF IncreaseMallard  Anas platyrhynchos Linnaeus  1 EV; MF EV; SS; MF IncreaseGreen Heron  Butorides striatus Linnaeus  1 EV S; OT IncreaseSedge Wren Cistothorus palustris Wilson  1 SS; S; MF SS; S; MF N/AAlder Flycatcher  Empidonax alnorum Brewster  1 S; MF; OT S; OT IncreaseAmerican Black Duck   Anas rubripes Brewster Variable SV; EV; SS EV; S; OT N/AWillow Flycatcher  Empidonax traillii Audubon  1 EV, S S; OT IncreaseCommon Grackle Quiscalus quiscula Linnaeus  1 MF OT DecreaseNorthern Harrier Circus cyaneus Linnaeus  1 MF MF N/A 1 Risk levels corresponded to a species’ potential response to stabilized water levels based on microhabitats and vegetation used for nesting and foragingduring their breeding season. 2 Habitat Codes: OW: Open Water; SV: Submergent Vegetation; EV: Emergent Vegetation; SDG: Sand/Dirt/Gravel; B: Banks; MF: Meadow/Field; OT:Open Timber; SS: Scrub/Sedge; S: Shrub. 3 Population trends were based on data collected in Lake Ontario coastal marshes. L.) and/or common reed, ( Phragmites australis (Cav.)Trin. ex Steud., (Wilcox 1990, Wilcox 1993, Wilcoxet al. 1993, Hudon 1997, Beland 2003, Farrell et al.2004), a tendency that runs counter to the maintenanceof ‘‘hemi-marsh’’ situations that benefit most wetlandbirds species (Gibbs et al. 1991). Water-level manage-ment in Lake Ontario, initiated with operation of theSt. Lawrence Seaways, has reduced water-level fluc-tuations from about 2 m to approximately 0.9 m since1976 (Wilcox 1993) and has eliminated year-to-yearvariation (Wilcox and Whillans 1999).Artificially minimizing water-level fluctuations maynegatively affect wetland bird populations adapted toaquatic microhabitats. This would likely be achievedthrough direct loss of microhabitats most closely as-sociated with wetlands, such as submergent vegetation.Birds that rely on these microhabitats for foraging andnesting would likely be at greater risk to water levelmanagement. To assess how water-level stabilizationmight influence the wetland bird community in theGreat Lakes region, we reviewed the published liter-ature to identify local- and landscape-scale linkagesbetween wetland characteristics and wetland bird di-versity. We related this information to ongoing popu-lation trends of wetland birds in the region to deter-mine if the species that should be most susceptible towater-level regulation are the species actually declin-ing. Such information is important to synthesize sothat ramifications of various water level regulation sce-narios, as mediated by changes in wetland vegetation,can be evaluated for the significant wetland bird com-munities that occupy the region.SELECTION OF SPECIES AND METHODS OFLITERATURE REVIEWWe chose species for our study that were native,wetland obligates and those relatively common inLake Ontario wetlands (percent occurrence on BirdStudies Canada’s Marsh Monitoring Program countsfrom 1995 to 2002 at 107 points on Lake Ontariomarshes of   1%), or those that were rare (occurrence  1%), but nevertheless of conservation concern be-cause of dependence on wetland habitat, importance  608 WETLANDS, Volume 26, No. 2, 2006as game species, or have experienced population de-clines (Timmermans et al. 2004). Of all species de-tected in Lake Ontario marshes during this period, 30met these criteria (Table 1). We assembled literatureby searching computerized databases using CambridgeScientific Abstracts—Biological Science, BiblioLine’sWildlife Worldwide and The Birds of North Ameri-ca—Life Histories for the 21st Century series.CLASSIFICATION OF SPECIES INTORISK CATEGORIESBased on the literature survey of individual specieshabitat associations (summarized in Table 1), we di-vided the 30 bird species into three categories: low,moderate, and high risk. These risk levels correspond-ed to a species’ potential response to stabilized waterlevels based on microhabitats and vegetation used fornesting and foraging during their breeding season. Aspecies was classified as being at ‘‘low risk’’ if it tend-ed to nest in vegetation over one meter in height inwetlands or in upland habitat at any height, such asmeadow or open timber. Low risk species also foragedeither exclusively in habitat unlikely to be directly af-fected by water-level stabilization or in several typesof habitat. For example, the Great Blue Heron quali-fied as a low risk species according to our criteria be-cause it nests in timber 30 m or more above groundand feeds in a wide variety of habitats.Bird species were classified as being at ‘‘moderaterisk’’ if they foraged in habitat sensitive to water-levelstabilization but either nest exclusively in vegetationover one meter in height in wetlands or in upland hab-itat. For example, Northern Shovelers are consideredmoderate risk because they forage primarily in openwater but are also known to associate closely with sub-mergent vegetation; such microhabitats are likely to beinfluenced by water level and displacement of sub-mergent vegetation by persistent emergents such ascattail. Although a ground nester, the Northern Shov-eler prefers vegetation associated with meadow andfield habitats, such as grass and nettles.A ‘‘high risk’’ species nested  1m above the waterexclusively in wetland habitats. These species foragedon vegetation that could be adversely affected by hu-man-controlled water levels. An example of a high risk species is the Pied-billed Grebe, which nests on float-ing vegetation among and occasionally anchored toemergent vegetation and is highly dependent on float-ing-leaved and submergent vegetation for foraging.The Pied-billed Grebe’s nesting and foraging habitsare sufficient to categorize it as high risk.CONTRASTING PREDICTED SENSITIVITYWITH POPULATION TRENDWe used data collected by Bird Studies Canada’sMarsh Monitoring Program volunteer participants,who surveyed bird abundance and occurrence through-out coastal marsh habitats of Lake Ontario between1995 and 2002. Prior to their first survey season (May–July), participants were given training kits that includ-ed survey protocol instructions, data forms, instruc-tional cassette tapes with examples of songs and callsof common wetland birds, and a call-broadcast tapethat was used during surveys to elicit vocal responsesfrom Virginia Rail, Sora, American Bittern, Least Bit-tern, Common Moorhen, American Coot, and Pied-billed Grebe (Weeber and Vallianatos 2000).After reviewing survey protocol and completing aself-training exercise, participants established surveyroutes in wetlands  1 ha in size. Depending on wet-land size, survey routes consisted of from one to eight(maximum) different survey stations. Survey stationswere defined as 100-m-radius semicircles that con-tained  50% coverage of emergent vegetation wherebirds were counted each year. The center of each sur-vey station was the focal point from which observersrecorded bird counts; these were permanently markedwith a stake and metal tag to ensure relocation in sub-sequent visits within and among years. Each stationwas  250 m from another, which minimized dupli-cate counts of individual birds within routes. Mostroutes were established at the ecotone between wetlandand drier upland habitats, but some participants alsosurveyed routes in wetland interiors.Bird surveys were conducted twice annually at eachstation between 20 May and 5 July, and survey visitswere temporally spaced by at least 10 days. Surveyswere conducted after 1800 hours EST on days whenthere was no precipitation, the temperature exceeded16  C, and wind speed was less than 20 km·hr  1 (3on the Beaufort scale). Birds were counted for 10 min-utes during each survey station visit in the followingmanner. At each focal point, volunteers played a 5-minute call broadcast tape (each species call listedabove separated by 30 seconds of silence) and record-ed all birds heard and/or seen within each survey sta-tion during the call playback period and a 5-minutesilent listening period immediately following the play-back period. Birds flying up to a height of 100 m oversurvey stations were also recorded.Bird abundance indices for Lake Ontario coastalwetlands were calculated in the following manner.First, species count data for stations within routes weresummarized to provide one value for each species de-tected on each route. We used Generalized LinearModels with a Poisson error distribution (PROC GEN-  Steen et al. , BIRDS AND GREAT LAKES HYDROLOGY 609MOD; SAS Institute Inc. 1990) to generate annualabundance indices for each species. These ‘‘route-re-gression’’ models were designated as Species Count(Y)  Year (class), Route (class). We ran 1,000 iter-ations of each model to stabilize variances and to de-rive mean annual abundance estimates for each spe-cies. These values were scaled to correct for possibleoverdispersion before transforming into abundance in-dices for trend analyses (PROC GENMOD, PSCALEoption; SAS Institute Inc. 1990). Annual estimatedspecies counts (i.e., class coefficients) were convertedinto abundance indices using the following formula: A  M Abundance Index  e (1)where e  2.7183 which is the base of the natural logarithmA  annual estimated species count (i.e., class coef-ficients) from route-regression modelsM  mean number of individuals counted on all routesin the final survey year.This transformation allowed us to determine relative(percent) annual differences in bird abundance indicesscaled to the average value for the most recent surveyyear.Species-specific relative abundance trends for birdscounted in Lake Ontario coastal wetlands during the1995–2002 study period were calculated and evaluatedfor biological significance and statistical reliability us-ing Generalized Linear Models (PROC GENMOD;SAS Institute Inc. 1990). The same input data, errordistribution, and regression modeling structures andprocedures as described above for calculating abun-dance indices were used for these analyses, except that‘‘Year’’ was included as a continuous variable to pro-vide a linear estimated rate of change (i.e., trend) ineach species’ abundance through time. Species-specif-ic slope estimates (corrected for overdispersion) fromroute-regression models were converted into relativeindices of change (abundance trends) by using the fol-lowing formula:  Abundance trend  100  ( e  1) (2)where e  2.7183 which is the base of the naturallogarithm   Year coefficient from species-specificroute-regression models.This transformation allowed us to determine percentannual change in bird abundance indices during 1995–2002. Likelihood ratio tests were used to calculate theprobability that year effects (slopes) differed fromzero. To do this, differences in model deviance be-tween those with and without year effects were cal-culated; those differences (based on 1 error degree of freedom) were used to obtain probabilities from a chi-squared distribution, which were subsequently con-verted (1—chi-square probability) into P-values (Col-lett 1994).To determine whether our risk classifications cor-responded with the status of species in the Lake On-tario basin, we contrasted the assigned risk with cur-rent species population trends at coastal wetlands of Lake Ontario, which were available for 22 of the 30birds included in the risk designation analysis (T. 2).Birds for which trend data were not available includedAmerican Wigeon, Green-winged Teal, AmericanBlack Duck, Sedge Wren, Common Snipe, NorthernShoveler, Northern Harrier, and American Coot. Datawere considered reliable for a species if it was ob-served at over 10 sites. Seven species were only re-corded at five to nine sites (Table 2).Of the bird species designated as low, moderate, andhigh risk in this study, we found 25%, 33%, and 63%,respectively, to be decreasing according to the MarshMonitoring Program (not including birds for whichthere were no trend data available). While not statis-tically significant, likely due to small sample size,these results suggest a strong relationship between vul-nerability to hydrologic changes as estimated from ourreviews of these species’ natural history and ongoingchanges in their populations in the region.SYNTHESISAlthough many factors influence population statusof these species in the region, including coastal de-velopment, environmental contamination, erosion, andpredation (Wires and Cuthbert 2001), the corrobora-tion we observed between assigned risk and wetlandbirds abundance suggest indirectly that regional hy-drologic change could be an important driver of con-temporary population trends in these species. Birdpopulations dependent on microhabitats that are likelymost affected by stabilizing water levels are those ev-idently declining in the Great Lakes region. These de-clines may be due to the management history of LakeOntario, which has resulted in wetland degradation dueto water-level change divergent from that resultingfrom natural processes (Wilcox 1990, Wilcox 1993,Hudon 1997). While there are disadvantages associ-ated with fluctuating water levels, such as increasedrisk of nest loss and susceptibility to predation, recent,anthropogenic alterations of the water cycle likely in-fluence wetland-associated bird populations on a largerscale than these natural sources of mortality, as pop-ulations have not had the necessary time to adapt tothese changes. Further research may be required to de-
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