Research Article

Predicting Cerulean Warbler Habitat Use in theCumberland Mountains of Tennessee

DAVID A. BUEHLER,1 Department of Forestry, Wildlife and Fisheries, University of Tennessee, Knoxville, TN 37996-4563, USA

MELINDA J. WELTON, Franklin, TN 37064, USA

TIFFANY A. BEACHY, Department of Forestry, Wildlife and Fisheries, University of Tennessee, Knoxville, TN 37996-4563, USA

Abstract

We developed a habitat model to predict cerulean warbler (Dendroica cerulea) habitat availability in the Cumberland Mountains of

eastern Tennessee. We used 7 remotely sensed vegetation and topographic landform explanatory variables and known locations of

territorial male cerulean warblers mapped in 2003 as the response variable to develop a Mahalanobis distance statistic model of

potential habitat. We evaluated the accuracy of the model based on field surveys for ceruleans during the 2004 breeding season.

The model performed well with an 80% correct classification of cerulean presence based on the validation data, although

prediction of absence was only 54% correct. We extrapolated from potential habitat to cerulean abundance based on density

estimates from territory mapping on 8 20-ha plots in 2005. Over the 200,000-ha study area, we estimated there were 80,584 ha of

potential habitat, capable of supporting about 36,500 breeding pairs. We applied the model to the 21,609-ha state-owned Royal

Blue Wildlife Management Area to evaluate the potential effects of coal surface mining as one example of a potential conflict

between land use and cerulean warbler conservation. Our models suggest coal surface mining could remove 2,954 ha of cerulean

habitat on Royal Blue Wildlife Management Area and could displace 2,540 breeding pairs (23% of the Royal Blue population). A

comprehensive conservation strategy is needed to address potential and realized habitat loss and degradation on the breeding

grounds, during migration, and on the wintering grounds. (JOURNAL OF WILDLIFE MANAGEMENT 70(6):1763–1769; 2006)

Key wordscerulean warbler, coal mining, Dendroica cerulea, habitat, Mahalanobis distance function, population viability.

Cerulean warblers (Dendroica cerulea) are listed as one of the

top priority species for conservation action by Partners in

Flight for the eastern deciduous forest because of consistent,

long-term population declines (Hamel 2000a,b; Hamel et al.

2004). The cerulean warbler has been petitioned for listing

as a threatened species under the Endangered Species Act.

The United States Fish and Wildlife Service has determined

that listing may be warranted and is conducting a status

review (Federal Register 2002). As a result of these actions,

much attention has been focused on delineating breeding

habitat and identifying factors that influence habitat

availability over time, including forest management and

other forms of resource use, such as coal surface mining. The

Appalachian Bird Conservation Region (BCR; BCR 28) is

considered the heart of the cerulean’s range; approximately

80% of the known population occurs in the region

(Rosenberg et al. 2002). As such, conservation of this

species may be closely tied to the ability to sustain ceruleans

within the Appalachian BCR. Ceruleans use predominantly

mature, deciduous forest throughout their range (Hamel

2000a). Factors influencing the availability of these forests

in the Appalachian BCR may ultimately affect the viability

of cerulean populations.

In the Appalachians, coal surface mining, forest manage-

ment, and human development (residential, commercial,

industrial, and transportation) are large-scale land uses that

may affect cerulean habitat availability. We specifically

analyzed potential coal mining effects on cerulean habitat

and abundance because spatial data on coal reserves werereadily available.

Hardwood timber resources in the region from 1989–1998were growing at rates in excess of extractions (Schweitzer2000a,b). Cerulean habitat on lands managed for timberharvest could still be decreasing, however, if the total acresof suitable habitat are declining, regardless of timber volumeincreases. We lack spatial data on recent timber harvest to beable to model this potential effect. In addition, several large(1,600-ha) residential retirement communities are beingconstructed in the study area. This type of development mayalso contribute to declines in cerulean habitat availability,depending upon changes in forest habitat structure andlandscape configuration.

Given these potential conflicts between ceruleans and landuse, we need to critically assess the sustainability of ceruleanpopulations in the region in light of planned resource use.We answered 3 fundamental questions: 1) can ceruleanwarbler habitat be accurately modeled in the AppalachianBCR based on remotely sensed vegetation and landformdata, 2) how much potential habitat is currently availableand what is the size of the population supported by thishabitat, and 3) what is the likely impact from coal mining oncerulean abundance, distribution, and sustainability?

We conducted this assessment for ceruleans in theCumberland Mountains of eastern Tennessee, the largestdocumented population range-wide for this species (Rosen-berg et al. 2002). Cerulean populations in the CumberlandMountains appear to be declining (Nicholson 2004, Sauer etal. 2005). Recent North American breeding bird survey(BBS) estimates suggest significant declines for the1 E-mail: dbuehler@utk.edu

Buehler et al. � Cerulean Warbler Habitat Model 1763

Cumberland Plateau physiographic province, which includesthe Cumberland Mountains, over recent (�8.48% from1995–2004, P ¼ 0.003) and longer (�4.15% from 1966–2004, P , 0.001) time periods (Sauer et al. 2005).Quantification of potential impacts on cerulean warblerpopulations from various land-use activities is a critical firststep in addressing the issues responsible for the populationdeclines.

Study Area

Our study area encompassed 206,579 ha of the CumberlandMountains in 4 eastern Tennessee counties (Anderson,Campbell, Morgan, and Scott). The Cumberland Moun-tains are a discrete landform extending out of the Cumber-land Plateau physiographic province, located west of theRidge and Valley physiographic province and east of theInterior Low Plateaus physiographic province. Elevationsrange from 250 m to 1,075 m. Greater than 80% of the areawas forested, with about 60% of the total area maturedeciduous forest. Predominant land uses included coalmining, forest management, and recreation, with verylimited agriculture in the valleys. Human development wasgenerally light compared to surrounding areas althoughdevelopment of residential retirement communities wasincreasing. Large public land holdings in the CumberlandMountains included the Big South Fork National Recre-ation Area (50,000 ha), Royal Blue Wildlife ManagementArea (21,000 ha), Sundquist Forest Wildlife ManagementArea (34,000 ha), and Frozen Head State Park (4,400 ha).Private land ownership included several large blocks(.10,000 ha) owned by mining and timber companies.

Twenty-hectare study plots were located on the RoyalBlue Wildlife Management Area and Sundquist ForestWildlife Management Area study sites. Plots were located inareas composed predominantly of cerulean habitat based onthe cerulean model; 4 plots were located on Royal Blue and4 plots were located on Sundquist Forest. Royal Blue andSundquist Forest differed in habitat conditions significantlybecause Royal Blue has had no coal surface mining and verylimited timber harvest since Tennessee Wildlife ResourcesAgency acquired the property in 1991. Sundquist Forest,acquired by the state in 2003, has been actively mined andtimbered through 2005 because timber and mineral rightson Sundquist Forest are privately owned. The Koppers coalreserves underlie the Royal Blue Wildlife Management area,although the Koppers reserves are smaller than Royal Bluein total area. Tennessee Valley Authority (TVA) owns themineral rights on Royal Blue, is considering leasing the coalmining rights within the next 5–10 years, and is currentlyconducting an environmental impact assessment (R. Hor-ton, TVA, personal communication).

Methods

Model DevelopmentIn 2003, we randomly located 12 transects across the studyarea. Each transect traversed from mountaintop to valleyfloor. Transects were variable in length (1–8 km), depending

on the local topography, and occurred on the range of slopesand aspects available in the Cumberland Mountains. Wewalked each transect once between sunrise and 4 hourspostsunrise during the peak of the cerulean breeding seasonin mid-May. We used Garmin Global Positioning Systemequipment (10-m accuracy) to record the locations ofsinging male ceruleans audible from transects. We recorded114 male cerulean locations from these transects, whichserved as the basis for model development.

We used the Mahalanobis distance statistic (D2) as thebasis for the modeling. D2 is a measure of dissimilarity andrepresents the difference in the standard multivariatesquared distance between the ideal cerulean location andother locations on the study area (Clark et al. 1993).Modeling based on D2 was desirable because we couldreadily document singing male cerulean warbler presencewithout investing significant effort to document ceruleanwarbler absence through repeated visits over the extensivestudy area (Dettmers et al. 2002). We selected a suite ofexplanatory variables a priori (Table 1) that were thought tobe biologically relevant for cerulean habitat selection(Dettmers and Bart 1999, Nicholson 2004, Weakland andWood 2005). We used an ArcView (Environmental SystemsResearch Institute, Redlands, California) extension (JennessEnterprises, Flagstaff, Arizona) to develop the model fromthe cerulean locations and calculate D2 for all pixels in thestudy area. We limited the number of explanatory variablesto 7 because the ArcView extension was limited to 7variables. We did not engage in a model selection process toreduce the number of explanatory variables. We felt therewas a limited cost of including additional variables becauseall of these variables were readily available from remotelysensed data. Our goal was to create a model with reasonableaccuracy, as opposed to developing the most parsimoniousmodel. We only used explanatory variables that were notcorrelated (r , 0.75) to reduce redundancy.

Some of the landform data were available from theSouthern Appalachian Assessment database (90-m resolu-tion, Hermann 1996). We developed a coverage of mature(.30 yr old) deciduous forest as an explanatory variablethrough a supervised classification of 2000 LandSat TMsatellite imagery with ERDAS Imagine software (30-mresolution). We did not attempt to update the 2000 imageryfor land use change on the study area because of theextensive size of the area involved. We also obtained1:24,000 digital elevation model data from the United StatesGeological Survey. We used the ArcGIS 9.0 Spatial AnalystSLOPE command to generate a slope coverage in degreesfor the study area. We derived slope position from digitalelevation model data based on Wilds (1996); values rangedfrom 0 (valley floor) to 50 (midslope) to 100 (ridge top). Weresampled the 90-m resolution data in ArcGIS 9.0 so thatall explanatory variables matched the satellite imageryresolution (30 m). After the model was developed, wedetermined a cutoff D2¼ 14.0, such that lesser values weremore similar to the ideal cerulean location, and greatervalues were less similar. We selected the cutoff value as the

1764 The Journal of Wildlife Management � 70(6)

value that maximized the difference in cumulative frequencybetween the cerulean locations and the study area as a whole(Browning et al. 2005; Fig. 1). By setting the cutoff value insuch a manner, we maximized the ability of the model todiscriminate between cerulean habitat and conditionsavailable on the rest of the study area. We recoded theMahalanobis distance model coverage into cerulean habitat(D2 � 14.0) and unsuitable areas (D2 . 14.0) in ArcGIS9.0. We constructed 95% confidence intervals for the meansof explanatory variables for the 2003 cerulean warblerlocations (n ¼ 114). We compared these intervals withmeans for the explanatory variables for the entire study area;we assumed habitat selection occurred (P , 0.05) whencerulean confidence intervals did not contain study areameans, similar to Neu et al. (1974).

We evaluated model accuracy in 2 ways. First, wecalculated the correct classification rate for cerulean presencefrom the 2003 cerulean data used to develop the model.Second, in 2004, we randomly located another 6 transects(3,250–5,000 m long) across the study area that traversedfrom mountaintops to valleys and crossed in and out ofpredicted cerulean habitat. We located sampling points

every 250 m across each transect (13–20/transect). Wewalked each transect once during a morning in mid-May2004. We stopped at each point and recorded ceruleanactivity within 50 m of the point for 3 minutes. We thenplayed a cerulean male song with playback equipment for 2minutes, listened an additional 3 minutes, and recorded anycerulean activity within 50 m. We deemed a point as havingceruleans present if we observed any cerulean activity within50 m during the entire 8-minute monitoring period. Weoverlaid these point locations on the cerulean model inArcView and calculated a correct classification rate for bothcerulean presence and absence. Based on use of tapedplaybacks during capture and banding efforts in 2005, weestimate the detection probability of this protocol to be.90% during this part of the breeding season (Beachy andBuehler, University of Tennessee, unpublished data).

To extend our modeled habitat to predict ceruleanabundance, we spot-mapped cerulean territories during 8visits to 8 20-ha plots in the Cumberlands during May–June2005 using standard spot-mapping methods (Robbins1970). For each plot, we divided the number of observedterritories by the hectares of modeled cerulean habitat forthat plot to estimate cerulean density per hectare of potentialhabitat. We then averaged these densities for Royal Blue (n¼ 4) and Sundquist Forest (n¼ 4) separately. We multipliedthe mean density by modeled habitat hectares for that areato generate an estimate of abundance for each area. Weaveraged the average densities for Royal Blue and SundquistForest and applied this average density to the CumberlandMountains cerulean habitat acreage to generate an estimateof abundance for the entire study area. We estimated that80% of cerulean males were paired based on spot-map andnest-monitoring work in 2005; we decreased the estimatednumber of breeding pairs accordingly.

We did not account for differences in density related tospatial configuration of the habitat. Unlike elsewhere acrossthe range of ceruleans (e.g., lower Mississippi River alluvialvalley; Hamel 2000a, b), cerulean habitat in the CumberlandMountains is contiguous and occurs in a largely forested

Table 1. Explanatory variables used to model cerulean warbler habitat, Cumberland Mountains, Tennessee, USA.

Cerulean warbler locations Study area

Variable x SE 95% CI Range x Range

Average solar exposure (d/yr)a 261.4 7.1 247.2–275.6 101–451 297.1 65–461Distance to nearest stream (m)b 526.5 24.7 477.1–575.9 0–1208 370 0–1775Elevation (m)c 733.1 8.0 717.1–749.1 564–941 558.2 243–1076Relative slope positiond 86.7 2.1 82.5–90.9 0–100 67.5 0–100Slope (degrees)e 22.4 0.6 21.2–23.6 5–38 18.3 0–58Terrain relative moisture indexf 24.6 0.7 23.2–26.0 3–49 25.2 0–60Mature deciduous forestg 90.4% 56.7%

a Calculated from elevation in ArcInfo (Hermann 1996).b Calculated in ArcInfo (Hermann 1996).c United States Geological Survey 1:24,000 digital elevation model data.d Calculated in ArcInfo from elevation (Hermann 1996 based on Wilds 1996).e ArcGIS Spatial Analyst SLOPE command.f Calculated in ArcInfo from elevation, slope, and aspect (based on Parker 1982).g Derived from ERDAS supervised classification of LandSat imagery (2003).

Figure 1. Mahalanobis distance function statistic cumulative frequencydistribution for cerulean warbler model with 2003 cerulean warblerdevelopment data, with 2004 cerulean warbler evaluation data, and forthe entire study area, Cumberland Mountains, eastern Tennessee, USA.

Buehler et al. � Cerulean Warbler Habitat Model 1765

context. Small, isolated cerulean habitat patches ,1.0 ha inextent accounted for ,1% of the cerulean habitat by area.Inclusion (or exclusion) of these small patches did notsignificantly affect our overall estimates of available habitator cerulean abundance; we retained the small patches in theanalysis for convenience.

To evaluate the potential impacts of coal mining in thearea, we overlaid the cerulean habitat layer on a layer of coalreserves obtained from the TVA for the Koppers coalreserves underlying the Royal Blue Wildlife ManagementArea. We extracted the pixels from the cerulean habitat thatfell within the coal reserves (using the EXTRACTcommand, ArcGis 9.0). Additional surface area disturbancewould accompany the area associated with the coal reservesfor haul roads, sediment retention ponds, and spoil areas.TVA personnel estimated this additional surface disturbancewould increase the total impact area by 33%; identificationof where the additional disturbances will occur isn’t possibleuntil actual mining permits are issued (R. Horton, TVA,personal communication). Therefore, we did not try toevaluate coal-mining impacts spatially but simply increasedaffected acreage by 33% to identify potential impacts onavailable cerulean warbler habitat and abundance.

Results

Habitat SelectionMale cerulean warblers selected locations with less averagesolar exposure (d/yr), greater distance to streams, and higherelevations, which occurred more on ridge tops, on upperslopes, and on steeper slopes than what was available, onaverage, in the study area (P , 0.05; Table 1). Ceruleansalso occupied sites that were predominantly maturedeciduous forest (.90% of locations), but mature deciduousforest occurred on only 56.7% of the study area. Ceruleansdid not show any specific selection for terrain moisture (P .

0.05) and occurred on sites with a moisture index similar towhat was available on the study area.

Model PerformanceBased on the 2003 cerulean model development data, 106 of114 cerulean locations (93.0%) were correctly classified ascerulean habitat. Based on the 2004 data, 32 of 40 ceruleanlocations (80%) were correctly classified, although only 33of 61 absences (54%) were correctly classified as unoccupiedby ceruleans.

Model ApplicationPotential cerulean habitat was distributed throughout theCumberland Mountains, generally associated with ridgetops and upper slopes (Fig. 2). The Cumberland Mountainsin Tennessee are estimated to contain over 80,000 ha ofpotential cerulean habitat, composing 39% of the total area(Table 2). Habitat was widely distributed across a range ofpatch sizes, with ,1% of the total area in patches ,1.0 ha.Eighteen patches were .250 ha; the largest patch wasalmost 25,000 ha. We calculated an average breeding densityof 5.67 pairs/10 ha for Royal Blue and Sundquist Forestcombined. Extrapolating this estimate based on available

habitat, the Cumberland Mountains support an estimated36,553 breeding pairs of ceruleans. Royal Blue WildlifeManagement Area contained 12,785 ha of cerulean habitat,with 59% of the area comprised of cerulean habitat, capableof supporting 10,995 breeding pairs (Table 2). SundquistForest Wildlife Management Area also contained a largeamount of cerulean habitat (17,423 ha), although SundquistForest was less suitable overall (50.5% was cerulean habitat)and was estimated to support lower densities and fewer pairs(3,485 breeding pairs).

Coal surface reserves covered 3,133 ha of Royal BlueWildlife Management Area; coal surface mining maydisturb 4,167 ha. Coal reserves and cerulean habitatoccurred in essentially the same area on Royal Blue (Fig.3). Over 70% of the coal disturbance area was ceruleanhabitat. Coal mining would remove habitat for 23.1% of theRoyal Blue cerulean population, displacing an estimated2,540 pairs (Table 2, Fig. 3).

Discussion

Based on model accuracy during evaluation tests anddemonstrated application, we believe we have developed auseful cerulean warbler habitat model for the CumberlandMountains of Tennessee. Cerulean warbler habitat wassuccessfully modeled from remotely sensed vegetation andlandform data, based on the Mahalanobis distance statistic.The modeling approach was appealing because it was basedsolely on presence data; we avoided issues related todetection of ceruleans and identification of locations whereceruleans were absent. As long as the cerulean presences

Figure 2. Potential cerulean warbler habitat, based on Mahalanobisdistance function model, Cumberland Mountains, eastern Tennessee,USA, 2003–2004.

1766 The Journal of Wildlife Management � 70(6)

were representative of the cerulean population, the modelshould accurately predict Cumberland Mountains ceruleanhabitat. Although our model development surveys werelimited to a single visit on each transect during the peak ofthe breeding season, we do not see any reason why theindividuals detected (primarily through singing) would notbe representative of the population at large. Potential biasassociated with this survey approach should have beenaccounted for in our accuracy-assessment results.

Habitat selection in the Cumberland Mountains wassimilar to habitat selection from the Ohio Hills (Dettmersand Bart 1999) and West Virginia (Weakland and Wood2005) in some respects, with ceruleans in the CumberlandMountains using upper slopes on steep sites dominated bymature deciduous forest. Cerulean selection for ridge topsand the presence of a much greater elevation gradient alsohelped delineate habitat in the Cumberland Mountains, butridge tops apparently were not important in the Ohio Hills.Six of 7 variables selected a priori for model developmentshowed significance with a posteriori statistical tests. Terrainrelative moisture index did not differ between ceruleanlocations and available habitat apparently because ceruleansselected rich, mixed mesophytic forests on moist cove sitesas well as oak (Quercus spp.)–hickory (Carya spp.) forests ondrier ridge tops, thus spanning the terrain moisture gradient.

Model accuracy was excellent for predicting ceruleanpresence (80% correct classification of presence sites), basedon the 2004 evaluation data. The model was much lessaccurate in terms of classification of absence (54% correctclassification), suggesting that ceruleans occurred across abroader range of conditions than defined by the model. Thisresult was consistent with field observations in which weoccasionally observed cerulean males singing in relativelyyoung forest (,30 yr old) associated with reforested butunreclaimed strip-mining benches. We do not know pairingstatus or nest success of these individuals; these sites mayconstitute marginal habitat for floaters in the population. Ifwe incorporated model correct classification rates into ourestimate of available habitat, our estimate of 80,584 ha ofcerulean habitat would decrease by 20% to 64,467 habecause of false positives. In addition, the 125,995 ha ofunsuitable habitat would reduce by 46% because of falsenegatives. Thus there would be an additional 57,958 ha ofpotential cerulean habitat. The net effect of incorporatingcorrect classification in the estimates would lead to a final

estimate of 64,467 ha þ 57,958 ha, equaling 122,425 ha ofhabitat. By applying this habitat estimate to our abundanceestimate, the abundance estimate would grow accordingly to35,500 breeding pairs. This estimate represents a 52%increase over our base estimate and may provide an upperlimit on what is present in the Cumberland Mountains.

There also is a source of variability in the populationestimate related to using the density estimate as a multiplierwith modeled acreage. Additional sampling over broaderspatial and temporal scales is necessary to fully capture thevariability associated with the density estimate. A 95%confidence interval developed for the density estimate, basedon the 8 plots measured, was 5.67 6 2.7 pairs/10 ha.Inclusion of this variability in our abundance estimateyielded a 95% confidence interval of 19,147–67,449 pairs.

Our estimates for the Cumberland Mountains suggestthere are 19,000–68,000 pairs in the region. This undoubt-

Table 2. Cerulean warbler potential habitat (ha) and abundance (breeding pairs) in the Cumberland Mountains, Tennessee, USA, 2004.

Cerulean warbler habitat Cerulean population Unsuitable

Area of interest Area (ha) % Pairs/10 ha Breeding pairsa Area (ha) % Total area (ha)

Sundquist Forest 17,423 50.5 2.50 3,485 17,102 49.5 34,525Royal Blue Wildlife Area 12,785 59.2 10.75 10,995 8,824 40.8 21,609Royal Blue coal reservesb 2,221 17.4 10.75 1,910 911 29.1 3,133Royal Blue coal disturbanceb 2,954 23.1 10.75 2,540 1,212 29.1 4,167Cumberland Mountains, Tennessee 80,584 39.0 5.67 36,553 125,995 61.0 206,579

a Breeding pairs assumes 80% pairing success.b Percentages represent percent of cerulean habitat on Royal Blue Wildlife Management Area.

Figure 3. Cerulean warbler habitat and surface coal reserves, RoyalBlue Wildlife Management Area, Cumberland Mountains, Tennessee,USA, 2003–2004.

Buehler et al. � Cerulean Warbler Habitat Model 1767

edly is a large population from a viability point of view, andit represents the largest population documented throughoutthe cerulean range (Rosenberg et al. 2002). The Partners inFlight estimate for the entire cerulean population for 1995was 280,000 breeding pairs (Rich et al. 2004), based onextrapolation of BBS data (Rosenberg and Blancher 2005).Based on a BBS estimated rate of decline of approximately3% range-wide over the last 10 years (J. Sauer, UnitedStates Geological Survey, personal communication), a 2005population estimate would be approximately 200,000breeding pairs. Thus the 2005 Cumberland Mountainspopulation may compose .20% of the range-widepopulation.

Cerulean habitat availability may be limited by cumulativeeffects of coal mining, timber harvest, and human develop-ment. We only modeled coal mining because spatial data oncoal surface reserves were readily available from TVA.Documenting potential cumulative effects from timberharvest and development was difficult because well-docu-mented, long-term forest management or developmentplans were lacking for the region. Our estimate suggeststhat coal mining may displace 23% of the ceruleanpopulation on Royal Blue. Because coal mining is occurringat similar rates elsewhere in the Cumberland Mountains, weexpect about 23% of the overall cerulean population(.8,000 breeding pairs) may be in jeopardy. It is unclearexactly what the displacement of these individuals will meanfor the sustainability of the regional cerulean population.Determining a minimum viable population size is problem-atic (Beissinger and McCollough 2002). In fact, we do noteven know if cerulean populations are limited by breedingground (e.g., habitat quantity and quality), or winteringground events, or both (Rappole and MacDonald 1994).

We did not explicitly analyze landscape configurationvariables (patch size, patch shape, connectivity, etc.) inmodeling cerulean habitat in the Cumberland Mountainsbecause the region is largely composed of large, intercon-nected patches of mature, deciduous forest. Our estimate ofthe impact of coal mining, as a result, ignores the landscape-level effects. Landscape characteristics have been shown tobe important in defining cerulean habitat suitability else-where (Hamel 2000a,b, Weakland and Wood 2005) andmay be important in the Cumberland Mountains as well.Weakland and Wood (2005) specifically documented the

response of ceruleans to coal mining in West Virginia anddemonstrated that impacts extended beyond the edge of themined area. To date, ceruleans nesting in the CumberlandMountains have not experienced negative effects of forestfragmentation; levels of brown-headed cowbird (Molothrusater) parasitism and edge-related nest predation have beenvery low (Nicholson 2004, Beachy and Buehler, Universityof Tennessee, unpublished data). As a result, Cumberlandcerulean populations may serve as a source for supportingpopulations across a broader area. Regardless of the sourceof the disturbance, fragmentation of the Cumberland forestsmay have deleterious effects on cerulean productivity in thefuture.

Management Implications

Various land-use activities have the potential to affectcerulean warbler habitat by either direct loss (quantityeffects) or by reducing productivity or survival in otherwisesuitable areas (quality effects). Although our modeling hasdocumented the potential impact of coal mining on habitatquantity in the Cumberland Mountains of Tennessee,declining cerulean warbler populations may be respondingto an accumulation of effects related to habitat quantity andquality on the breeding grounds, during migration, and onthe wintering grounds. Conservation strategies for ceruleansmust go beyond addressing the easily identified targets (coalmining in this case) and form comprehensive plans thataddress potential limiting factors range-wide.

Acknowledgments

We thank the University of Tennessee Agricultural Experi-ment Station, the Lyndhurst Foundation, the HealingstonesFoundation, and Tennessee Wildlife Heritage Foundationfor project support. We thank Tennessee Wildlife ResourcesAgency, especially S. Stooksbury and J. Elkins, for helpingwith project logistics. We thank Fountain Forestry,especially E. Dennis, for providing information on forestmanagement on the Sundquist Forest. We thank TVA forproviding coal surface coverages. We thank C. Thatcher forhelp with ArcView and ArcGIS 9.0 analyses. We thanknumerous field assistants that helped spot-map ceruleanwarbler census plots in 2005. We thank R. Dettmers, P.Wood, and 2 anonymous reviewers for reviewing earlierversions of the manuscript.

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Associate Editor: Kus.

Buehler et al. � Cerulean Warbler Habitat Model 1769