Nest Site Selection of the Black Tern in Western New York

JEANNE M. HICKEY1•2 AND RICHARD A. MALECKI

USGS, New York Cooperative Fish and Wildlife Research Unit. Fernow Hall , Cornell University, 11.haca, NY 14853 USA

'Present address: 210 Euclid Avenue. Ridgway, PA '15853 USA

21nternet: jmhickey@ncentral.com

Abstract.-Black Tern ( Chlidonias niger) nest site selection and habitat availability were investigated in 1994 and 1995 at the Iroquois National Wildlife Refuge and acljoining Tonawanda and Oak Orchard State Wildlife Manage­ment Areas in western New York. Nest site selection was evaluated with a logistic regression model using habitat va1i­ables collected in 26 12-m radius ci1·cular nest plolS and 31 random non-nest plots. Significant model variables were vegetation density, horizontal cover 0.5 m above the water, cover:water· ratio. and water level. The model correctly classified 77.2% of all plots. Most nests (84.6%) were in sparse to moderately dense vegetation. Horizontal cover 0.5 m above the water level was g)()% in 84.6% of nest plots as compared to 58.l % or random plolS. Cover:""ater ratio was medium (40%-60% cover) in 65.4% of nest plots, while random plots were evenly distributed among the low, medium, and high cover:water ratio categories. Mean w<1ter level at nests was 48.2 cm and 42. l cm in 1994 and 1995, respectively, similar to random plots. More than 80% of the nests were in bur-reed (Sparganium spp.) in both years. Habitat availability was evaluated by classifying all emergent vegetation within the study area into 4 habit.al quality categories. Highly Favorable Habitat (HFH) was habitat in which the model predicted ~0.50 probabilit:y of a nest site and suitable nest mats were available. Only 7.5% of the 101al available emergent vegetation in the study area was c;lassified as Highly Favorable. Black Terns selected nest si tes in HFH more than expected and used 72.5% of the total area of HFH in nesting marshes and 51.4% oftl1e total area of MFH in all marshes within the study site in 1995. Muskrat ( Ondatra zibethicus) structures were the most frequently used nesting substrate in both years. HFH could become limiting if the size of this breeding colony increases or if nest site selection is influt:nced by social su·ucture of the colony, habitat patch size and isolation, nesting density. or substrate avai lability.

Key words.-Black Tern, Chlidonias niger, habitat availability, lo1:,ris1ic regression, nest habitat, nest site selection, New York.

The Black Tern ( Chilidonias niger) nests within the cattails ( Typha spp.) and reeds as­sociated with freshwater wetlands, rivers, lakes, and sloughs (Novak 1992). Nests are typically found in emergent vegetation that is interspersed with open water <2 m deep (Bent 1921, Pittman 1927, Provost 1947, Cuthbert 1954, Goodwin 1960, Weller and Spatcher 1965, Novak J 992). Nests are buil t on mats or substrates found within the vege­tation and include: floating logs and boards, cattail rootstalks, mats of floating vegetation, muskral feeding platforms and old, inactive muskrat houses (Bent 1921, Goodwin 1960, Weller and Spatcher 1965, Bergman et al. 1970) .

The North American Breeding Bird Sur­vey (NABBS) has documented a 71.8% pop­ulation decline for this species in its breeding range since 1966 (Novak 1992, NABBS 1995). A period of significant de-

Colonial Waterbirds 20(3): 582-595, 1997

cline occurred between 1966-1979. Current­ly, the Black Tern is considered a migratory non-game bird of management concern by the U.S. Fish and Wild life Service Office of Migrato1y Bird Management (Novak 1992). In New York, the species is listed as special concern and is proposed for endangered sta­tus (R. Miller, New York State Department of Environmental Conservation, pers. comm.). The historic population size of the Black Tern in New York is unknown, but estimates of at least 1,000 nesting pairs were made in the late 1950s at the Montezuma National Wildlife Refuge (NWR) in central New York (Novak 1992). Today, the statewide popula­tion averages <300 breeding pairs per year (Carroll 1988, Mazzocchi and Muller 1995) .

Direct loss of wetland habitat is often cit­ed as the most sign ificant factor affecting the viability of Black Tern populations (Novak 1992). Since the late l 700s, major wet.land

582

SL~CJ( TERN NJ:.STINC: I IABrr,1 T 58~

losses have occurred in North Ame rica, ex· ceeding 50% in Lhe con1.erm inous Uni ted States (Mitsc h a nd Cosselink J993). While 1101. all we Lland losses constitu te Black 1crn breeding habitat , palusLrine emergent we1-lands, charaneristic of breeding habitat, dis­appeared at the ra te of 7% per d ecade between the mid-1950s to the mid-1970s ( Mitsch a nd Cosselink 1993). Breeding hab­itat suita bi lity rnay also be affected adversely by successional change. invasion of non-in­digenous plants, management practices, and degradation of water quality (Novak 1992).

Relatively low reproductive ompm has been documented at many Blac k Tern nest· illgsitcs (Novak 1992, Dunn and Agro 1995). Nest and chick losses were often a ttributed w weather. predati on, a nd disturbance. T he reasons for low recruitment a nd their impact on the present popula tion status of this spe­cies remain uncertain. Knowledge of nest ing h abitat requirements is necessary to ade­qu ate ly assess e nviro nmental impacts on rt~ productive success and managem ent options avai lable lo protect and main tain suitable breeding habiLaL for Black Terns.

Early q uali1a1ive d escrip tions of Black Tern nesting habitat have provided a 1ralu­ablc historical perspect:ive for the more re­cent aucmpts to further quantify nesling h abi1a1 and re productive success (Cuthbcn 1954; Goodwin 1960; Weller and Spatcher 1965; Berg1rn111 et al 1970; Chapman Mosher 1986; Eins1l'eiler l988; Knutson 199 1; Dele­hant)' and Svedarsky 1993; Maxson 1993, 1994; Linz et al. 1994). In their classic swcly on habitat and marsh bird abundance, Wel ler and Spatcher ( 1965) recorded peak Black Tern populations when there 11<a.5 a good interspersion of Miler a nd e mergents.

Th e objective of this stud)• was to develop a model to examine nesl si1e selection of Black Terns nesting in western Nf"w York. H abitat models can be useful tools for ev-~ lu­

ating habitat features associated with nest site sclecuon and standardizing habitat eval­uation techniques ( Ma11ly et al 1993). Mod­e ls are also useful 10 test hypotheses in th e field, predicl responses to change. a nd un­derstand nest si te/habitat rela tionships and related influences o n reproductive success.

S'l l ll)Y ARf..;\ AN[) ME11 lt>OS

This ~tud)' was Cc)1lduccc..·tl in wes1t~rn New \'ork on;, 7,96:'.\.-ha \\'eLland complex loa.ued \vithiu the l roquoi~

National Wildlife Rtfuge ( INWR) a nd "djoining Tonowanda (nVMA) and Oak Orchard (OOWMA) Stale Wildlile Management Areas. Thi.; complex is 32 km south of Lake Ontario and 48 km ea.~n of Ltkc Erk (•13°0i'N, ilr'22'\V) .1llC complex consis1$. nf nt11neroulll: m~\l~-madc.: i1np0l1ndmcnt~ wilh MltcrcontroJ s1rutturc~ chat arc managed primarily for Muerfowl produnion and ptO\'idl;" re:-<ting and feeding area~ ror M:Hcrfowl dur­ing rnigr:nion. Aboul f1'J% of1he 1m:i1 area was flooded a nd "'as dominated by llooded Limber (26%). cmergcnl marsh (1 7%), open W'1cr (12%1 •nd scrub/shrub marsh (5%) (S. Lor, l!'IWR, pe". comm.). On ave,;1ge. 30 pairs of Black Terns nest annually at tills :mid)' .silc: (No"1k 1990; Adam, 1990: Seyler 1991, 1993: Hicke) 1992).

Ncsl Site Selection and Model Dcvclopmen1

N~sl sit.._· habitat dau• "'ere collec1ctl in 26 nesl plolS and 31 r-lllclom no11-11e~t plolS withjn 6 impouncl1nc11cs used b)' nestin g 6L'1ck Tern, in 1994. The sampling p lot was a 12 .. m radius circular plot with a +m radiu~ subp101~ ~est ~weas "'ere ol»crvcd <tnd 1><>te1uial nest siles were mapped prior t•> n(.·:,t ~carchc:.. Thl:. l'nalJlcd u~ to loc:ue r'lc~s.t.." rnpidly and accuraLClv and h'<ixe uit. confidcnct that nC'arlyall lhc.: ne~b i1\itiate<I during 1lw habi1a1 ~mp1ing }>t:dvcl were found. A rcpresentath'c sample or nests \\•as obt~:iincd by sampliug at lc:ast 1 ne:sL within each small subgroup of nests locaLCd togclher in si1ni1,1r vegetation. Me~m <:.cnge of inruhation ~t 1he lime of neM sampling was 6.9 (SE :0.74) da)'< it1 19\14 a nd 5.3 da\'< (SE e 1.03) in 199£">, as determined by egg floatation ( I-lays aJ1d LcC:roy I 97 I), R<mdorn plotS " ere selected ll'Qm a giid overlaid on 1:12000 scale aerial photograph> using a r,·H'ldom 11 umbN'~ iahlt! .tnd loc-oued in lhe field. Ran· dom plots. located within acti"e Black Tern uc:s1 colc>­nic:s, i1\ 11n"eg<"1,ated open w;uer: odn areas not lloodcd, were excluded from an(llysis. Plots were sainplc.:d fiom 31M<1yto17June J!J<J'I.

Logi:>Lic regression w·J.~ us .. ·d to dC\e1op 1he habit:'tt model (Hosmcrnnd l.cnleshow 1989.Manll'etn/. 1993). The re~p<>r"l~e (clep<>11dcnt) vari~hle was plot cypc (ncs1 or non-nest) and the prcdktor ( in<lcpendcnt) vari~blt-~ \\'t•re the habiiat features measured in each plol (Hid:.l.')' 1 ~97). D~ita Cc>lit"Ctc:d wi1hin d'e 12-rn radius plot were cover t)'pc (Gn'PE) - open water, cmcrgcnl. scrub/ shrub. 0 1 foreslcd (Cowardin rt nl l9i9)~ dominant veg· eiation (SPECIES), "cgtt<Hion d<"n<ity (OENSITY), an<! pcrcem rover:water r.uio (C:\\') (se~ Table l for funhcr mcthodologico-.1 defini1ions). Oata coHec:ted at 4 carcH· na1 pc>inb and m·eraged witl1in tJ1c 4-m radius plol were "~getation height (I IEIGHT). hc\rlzom.al c:ovc::r at 0.2 m (HCOV2), 0.5 m (HCOV~). and J.0 m (HCOVI) ~bol'e the 1;;1lcr le"cl (Table I), ~nd ""'"' depth (WATER) measured with a graduated rod to nearest ccnt.imeLer. All v:u·iabl~. t:xcept water, were c:ategotized by \'isual cs-­ti mate. Visu:ll cstirn:.-ttion errors \\'c:re minimiz.cd by pl"acticing in 1he fielc1 m maimam cons:isl{·ncy among oh~cn·crs, using measurcmcnl tool.i 1l101t dearly defi ned category levels, using \•huaJ comparcnors as guide:-. when a\'ailable (I lays rt 11l 1981 ), and by using mea!>ul'cment k\•c)s in cate~oritts \\tide Cr\ough to minimize error ef­fec1 or $111311 \""ariation.s among ObM!l"\'ers.

58·1 COL.ONtAL \V,\Tl:.RBIRDS

Table 1. Percent of Black Tern nest plots and random plots in each habitat variable category in weste.ro New York (WI'\~ in 1994 a:nd Black Tern ncsc plots in western Ne"· York and northern New York (NNY) in 1995.

1!194 1995

\\l'~'Y llCS.l plOt'i \\rNY nmdo1n plots WNY nest plO!S Ni\-Y nest plots

N 2G !IL 24 25

Habital \'ariable

Oominam v(-getation1

bur-rccclt 88.5 48.4 83.3 24.0 cattail" l l.5 :~8.7 16.7 20.0 pickerelweecF 0.0 1).0 0.0 16.0 sw·amp loQ~es1Jif ei 0.0 0.0 0.0 16.0 other" 0.0 12.9 0.0 24.0

Vege1.ation densiry• \"Cl)' dense 15.4 38.7 12.5 28.0 mocler,ue :~.5 16.1 79.2 44.0 sparse 46. 1 15.2 8.3 28.0

Cover:wmer ratio(%}' low 7.i 3;,_;, 1.2 ~0.fl

medit1m 65.4 32.3 54.2 68.0 high 26.9 32.3 41.7 12.0

Vege1a1io11 height (cm)'; S25 3.8 16.1 12.5 28.0 26-50 GL.5 41.9 37.5 72.0 ;,1. 100 30.S 19.4 ·15.8 0.0 >LOO 3.~ 22.6 4.2 0.0

l"lorizonial coverai 0.2 111 (%)' <21 19.2 35.5 8.3 52.0 2t-i>O 26.9 19.4 2: •. 0 w.o [,l-i9 42.3 22.G 29.2 0.0 >79 11.5 22.6 37.5 28.0

Horh·.ont4il cover at 0.5 m (%)'' <21 46.2 51.6 625 BS.O 21-50 38.5 1;,;, 29.2 12.0 51-79 11.5 32.3 8.3 o.o >79 3.8 9.7 o.o 0.0

1-lo1i.z.011rnl covea· ;u 1.0 m (<}6f' <21 100.0 67.7 100.0 96.0 !!l-..:;O 0.0 \).7 0.0 4 .0

1Dmnioaot \'<!gCtation (SPECIE.$) - standing tin : ,·e~ecation with greal.C!'st pe1·cem cover. ' Bur·rted (S/J«'1(«11i«111 spp.). <•tt;.1il ( Tjfilm spp.) , picke1·elweed (Po111,,1n;u rortlaln). SMllllJ> loosesirife (J)HoJ011

t1erticillatus). '1nclud<~s: arn::iw-anun (P,,/tmu/rQ virgmi.m). smarl,,·ced (Polygon um spp.), grass. sedge. spike1'\1sh (Cjpfft1tf<~)

dogwood I Cttmus spp.) , or ash \Fmxirw; spp.). ~vegetation dc11sity (DENSLTY) · dcosityor dorni1'Hlmspecies whcl'e: ( 1) • \1errdensc -ca11no1 see wa1er 1hrough

stein baS("s; (2) = moclc;1'"Jldv dt"n:,~ ·stems c1ose1· thao spa.~c a11d water' stil1 \'isiblc 1h rou~h Sle111 bases. and (3) ==

spal"~~ - stems wi:dcly scattered with watc:r \'isiblc 1Jirough s1cm bases. ~ccwcr:w:ncr r~1tio (C:W) · ratio of percent of surface :ln.·a in sla11ding \'C)(t::tation CO\'CI" to open wa1er c:uegori1ed

as: (I)~ low (10:9(}.30:70), (2) - medium (40:6(}.60:40), anti (:I) • high (70:30-90:10). 'Vegetation l1eighc ( HEIGHT)- mosl con1mon hcigh1 c)f domioan1 standing Jive ''C~caatio11 categofited as: (I)

: $25 cm. (2) ~ 26-50 cm , (3) ~ 51-100 cm. and (4) ~ >100 cm. 'Ho1izomal COl'cr 0.2 m (l IC0\'2). 0.5 m (I ICOV5). :u>d 1.0 rn (HC0\11) - percent o f hlack and white d<nsi1y

board obscured by \'CJ:tCHltion at the various heights ~1bo\'e the walCI' level cstima1ed 10 ncaresc 20% (I lay~ et al. 1981) and catel(ori,ed as: \1) ~ <21 %. (2) e 21-50%. (~) ~ fi l -79%. and (4) Q >79%.

B~ICK TERN NESTING Hl18rTAT 585

13ble I. (continued) Percent of Black Te.rn nest plors and random plots in each habita1 variable category in wesu.~rn New York (WNY) in 1994 and Slack Te ro n est plots in western New York and northern Kew York (1'NY) in 1995.

l!J9<1 1995

\V!'\f')' ne:n plot~ WNY random plots WlW nest plots NNY nes1 plo1.s

N 26

I labirat variahle

:il·i9 0.0 >i9 0.0

The calego1-v le\·cl~ ()r 1 he independent \>ariables were coded as 0 or 1 inclic:.itor variablc.~s. This mane 1heir relatjoll$hip wi~h the logi1 of the response \'ariablc (ncst/ non·m:st) lirH:ar aud ;_-1llO\\ed for easier interp1-e­ralion of 1.he coefficients and odds ra1ios ( Hosmer ;tnd LemcshO\\ W89). \<\':ucr was a con1.inuou~ variahle in both models. The independent variables in the (hml model ,\·er-=: st:lected by comparing 1 he significance of each variable in a sc1ic.sorru11 ~md rtduccd models. 111« nu~al fnodel h'a~ sc.:lected by romparing 1he difference in thc·2 LOG l..s1a1btics between rnodt:'.hwith :lnd withOLll the independent variables based on a Chi-square distri· bution (Hosmer and l.cmeshow 1989), coinp..iri11g the clas~ifica1ion tables. which assessed U1c predicti\'C ability of each 1'110(1~1. and considering the biological signifi· cancc of each variable.

Additional data collected in each plot. but nol used in the model. were distances tO ru.:arest habital feau.1rcs which induclcd: small water pool (open water ~3 111 in diameter intersec1ir1g l 2;n radius plot~ large w·.itt:r pool (seasonally pcmlancm open wawr 20.-1 ha): major s1-:indiog '"Cgesation CO\rer ch:mgc: pemlanenL marsh edge; nest or random plot: ,.('gCC1Hion from edge' or 11est bowl: and number of side) nest su1Toundcd by \'Cgem­tion within l m. ~rhc..-sc: chua pl'O\'ided an addilional eval­u:uion of Lhc location of n.:s1 ':.\it~s. Nest subMr.Uc~ w<.·rc idcnLihed for e:~ch ne1.:t site.

Model Pctfon'Hanre::

1ne predicch·e ability of the model w;u lCsted in 1995 by s;tmpling 24 nt'SlS at lhe study area aod 25 nests out.side it. Nc~t~ ouL'>iclc the studv area were located at 1he 2 largesc colc)nics in New York. Pc1'Ch River (WMA) (44°()4'N, 75°56'\\') (N = 20) and Wilson Bay mar.;h (<M0 0!i'N. 76°20"W) (N • 5).J«IT<rson Count)" in north· crn Ne\\' York. Tht'Se coloniC'S. loca1cd neat c~a~1t'n1 Lake Ont;trio. are 290 km eas1 of the TonawJnda/ lro­quois/ Oak Orchard complex. Nests were sampled from 25 Mai to 16 .June 1995. TI1c proJ>Ortion of sampled nc~L' accur-dl.Cly p1·cdic1cd b)' she model \\'a~ deter~ mined.

Habiu'\L A\'ailability

Jn J9'J5, habita1 awilabilit)' was evaluated by classify ... ing all 1,354 ha ( 17% of the complex) of <'t11erge1H "<g· et-;,Hion wi1hi1"I the sn,1d)' area into 4 habitat quaHtr categories. Because of chc large area hwoh·cd, 2 levcls of a$.$essme111 "ere used to dassify the available h;1bltaL Tin• firsL IC\~<:l was a co~trsc. vkilml assessment in late \ 1.ay to classify all a\·.tilablc hilbil..'\l into cwo inilial c-4'1cgo1ies:

31 24 25

l!J.4 0.0 0.0 3.2 o.o 0.0

U nfa,·orablc HabitaL {UM) or favornhle t\v,.ilable nest· i1'lg I labi1a1 (FAH). From our habit~u data collcclcd in 1994 and oilier g:enernl descrip1ions, we ch:.1mc1erizcd FAH as ha,ing a 50:50 vegetation cu,·t·r to ''"-'t.r:r ratio. sparse to moc.lcr..-11ely dense CO\'Cr, and vcgcL1lion hdght of <I m. UH was all emergent \'Cgct;,tion th=-1 did 1'101 rncel 1hesc- cri1cria. TI1e .;;econci lewd was a fine assC'SS"' mcnt using the habitat modd 10 classify ::di F'AH into the 4 habimt quality c:ttego1ies: Mighly fa\'orablc Habitat (I IHI)· model prcdic1ed <!0.5-0 1>robabili1yora ncs1 si1c being pr~eni with ~uiiablc nesL substrdles a\'ailable; F:i· \'Orable I lahi1a1 (Fl I) - model preciictcd ;,0.50 p robabil· iLy of a nes1 site being present with no suilable;: nest s11l.>Strates available; Unfavorable Mabirn1 (UM) - model prcdic-tcd <0.50 probabili1y of a nc.)t site being ptcsc111 \\•ith suit-able nest subs1.ratcs ~wailablc: and Highly L'nfa­\'Orablc 1-labitat (!JUI I)· model predicted <lJ50 prob .. biliry of a nest site being present whJ1 no suitabk ne;.·Sl substrate~ a\'ailable. follo,\ing 1he habiu11 sampling methodology used to develop the model. 2% of tilt 188 h:l of f'Al-i tnapped i1l the lir~t le\'cl, coarse assessment was sampled \\1it1l 72 random uon-ncst plou~ and 24 nest plms. Random ploi.s were sampled only if they were nocxled and had ~~0% Standing \'t!gc;r;uiw C'O\'er. lo marsh uniL'> with several FAH patches. al least t'HlC·lialf of the 1ot.d art:a off AH within each unil '''tli sampled. The proportion C•f sampled plots in each of the 4 C3ttg<wicS was used 10 clctcl'lnint' th~ 1oml area of FN-1 in each cac­egory for aH habitat patches. All sarnpling \V"ot\S <:omplc•· eel hy 20 June 1995. A Ch i-square gooclnt>;-of·fit test (Neu '' "'· 197") \\';.-t.:t used to deter"rninc ir Black Tel'n.c; "'""re selecting B fH in proponion Lo ils avallabilitv.

RESULTS

Nest Site Selection and Model Development

Black Terns used 6 impoundments wi th­in rJ1e complex for 50 nest anempts (nest found with a t least 1 egg including renests), in 1994 and 4 impoundments for 55 nest a t­tempts in 1995. i\11 sampled plots were in nooded areas. In 1994, all the nests sampled were in emergem vegetation, 23 (88.5%) in bur-reed and 3 (11.5%) in cattai l (lllb le I ). Twenty-nine of the 31 random ploLS were also in emergen1 vege1ation, howe\'er. 15

586 COLONIAL WA'fERlllRDS

(48.4%) were in bur-reed, 12 (38.7%) in cat­tail (Table I). Of 50 nests in 1994, 25 (50.0%) were built on o ld muskrat houses and 12 (24.0%) on muskrat feeding plat­forms !Or a total muskrat structtu-e use of 74.0%. l ligh use of mtL~krat smictures pre­vailed in 1995 for 81.1 % of 55 nests.

The best predictors for the presence of a nest site with in a nesting marsh were density of dominant vegetation (DENSI1Y), horizon­tal cover 0.5 m above the water (HCOV5), vegetation cover to water ratio (C:W) , and wa­ter depth (WATER) (Table 2), and the final model was:

logit(i>) = 0.8 143-2.8089(DENSITY I) + 0.51 12(DENSITY2) + 0.9856(HCOV51) +2.2550(HC0V52)- l.37 13(MCOV53) - S.2 105(C :W I) - 2.4380(C:W2) + 0.0302(\V ATER}

where the probability (p) of a nest plot was calcula led as:

(p) e'tog ;,Pl

I + e(log 11pl

Here, logit (p) is the estimated logit of the probabilit)' of an "event" (nesL). The proba· bility (p) is the predicted probability the ''event" (nest) occurs for specific values of 1he predicto.- habitat variables entered. A re­sponse with a predicted probability <!:0.50 was classified as a nest p lot. Using Lhis prob­ability. the model adequately distinguished the exu-emes (e.g., too dense/sparse) in veg­etation slructure, yet allowed for some Vdria­lion. The combined effects of these va1·iablcs were significant (P = 0.0024). The final mod­el correctly classified 80.8% of the nest plots and 74.2% of the random ploLS sampled, a nd overall, correcrJy classified 77.2% of all plots sampled.

The SPECIES variable was purposely ex­cluded Lo develop a model based o n the structural features of lhe dominant vegeta­tion, regardless of species. Density o f domi· nant vege ta1ion (OENSl1Y) was sparse to moderately dense in 84.6% of the nest p lots, while random p lots wert' more often in sparse (45.2%) and very dense (38.7%) veg­et.a1.ion (Table J ). The odds of encountering

a nest site in moderate vegetation d ensity [= OENSITY(2) in Table 2] were 1.7 times high­er than at a site with sparse density and 1.6 Limes higher than at a site with very dense vegetation (Table 2). Mean horizon tal cover 0.5 m above rJ1e water (HCOV5) was greater in random ploL~ 1han in nest ploLS indicating nest sites were located in more open areas of vegetation (Table 1). Although , a large pro­portion (58.1 % ) of random plots were also in S50% HCOV5, more (4 1.9%) of the ran­dom plots were in HCOV5 >50%. The odds of encountering a nest al a site with 2 1-50% llCOV5 l= HCOV5(2) in Table 2] were 9.5 times higher thau at a site with HCOV5 of >79% (Table 2). Likewise, the odds of en­coun1e1·ing a nest at a site with <2 1 % H COV5 [= HCOV5(1) in Table 21 were 2.7 limes higher rJ1an at a site with HCOV5 of >79%.

Nest plots were more frequently (65.4%) in the medium vegetation cover:wa ter (C:W) ca tegory (T'able 1). The frequency of ran­dom ploLS was more evenly distributed across al l C:W categories. Random plots in bur-reed occurred most frequenrJy (25.8%) in low C:W ($ 30:70%), while nest plots in bur-reed occurred most frequently (61.5%) in medi­um C:W (Hickey. unpubl. data) . In random ploLS, 32.3% of the plots wi th sparse vegeta­tion density also had low C:'..V. However, nest plots in sparse vege tation density were more often (42.3%) in medium C:W. Although the water depth (WATER) was not a stalis1ically signi ficam predictor vai;able. ii was kept in the model because it can influence tl1e otl1er vegetation variables and it is useful in marsh managemen t. Mean water depth in nest p lot.s (48.2 cm, SE= 2.8) was nol significantly different from random p loLS (42.6 cm, SE = 3.0) (W = 854.0. P = 0.11, Mann-Whiu1cy) (Table 3) . Most nests were in 40-60 cm of wa­ter, and this was consistent when compared with Lhe 01her habitat variables. In random plots, water depth tended to be lower in plots with low horizontal cover at 0.2 rn and 0.5 m, sparse vegetation density. a nd low­moderate C:W ratios (Hickcy. unpubl. data).

Analysis of the variables excluded from the final model showed that nearly two­thi rds of the nesLS were in bur-recd, 26-50 cm tall , while few nests were in vegetation <26

Table 2. Parameter estimates and associated statistics for the logistic regression rnodel developed for Black Tern nest plots (N = 26) and random plots (N :: 31) in 1994 in western New York.

Analysis of maximum likelihood estiJnates

Habitat Va1·iable1 Parnmecer Estimate 95%CI Standard Error Wald Chi-square Probabili ty> Chi-square Odds Racio 95% Cl

Imercept 0.8143 DENSilY(l ) -2.8089 DENSITY(2) 0.5 112 HCOV5( 1) 0.9856 HCOV5(2) 2.2550 HCOV5(3) -1.3713 C:W(l) -5.2105 C:W(2) -2.4380 WATER 0.0302

Ci-iteda for assessing model fie.

Chi-square for cmoariates df P-value

-2 log likelihood

28.424 8 0.0004

-3.3056, 4.9342 -5.9874. 0.3696 -1.7385, 2.7609 -3.1 506. 5.1218 -1.5678, 6.0778 -4 .5518. l.8092 -8.9272, -1.4937 -5.5845, 0.7086 --0.0255, 0.0859

Score

23.928 8 0.0024

2.1020 J.6217 1.1478 2.1103 1.9504 1.6227 1.8963 1.6051 0.0284

0.1501 2.9999 0.1983 0.218 1 1 3368 0.7142 7.5499 2.3064 1.1273

0.6985 0.0833 0.060 0.6561 l .667 0.6405 2.679 0.2476 9.536 0.3981 0.254 0.0060 0005 0.1288 0.087 0.2884 1.031

Classification table summary

Overall correct

Sensitivity Specifici ty' False positive• False negative'

77.2%

80.8% 74.2% 27.6% 17.9%

0.0025. 1.4472 0. 1758, 15.8139 0.0428. 167.6348 0.2085, 436.0618 0.0105, 6.1055 0.0001 , () 2245 0.0038, 2.0311 0.9748, 1.0896

'Vadable name and (category level) -All categories for each variable (except water) were coded as 0 or l indic<1tor va1iables which resulted in k-1 category levels, where k wa.~ the odginal number of category levels. For example, DENSl"IY( I) "' density- very dense. Water was kept as a continuous covariate.

1Proportion of nest ploL~ predicted as nest plots. ' Proportion (If random plots predicted as random plots. 'Proponion of plots predicted as nest ploL~ observed as random plots. ''Proportion or ple>ts predicted as r.mdom plots observed a.~ nest plots.

;:l ~

" " ""' '< - c_h--:-' (,/} ti£' :iQ' :!. =· ::::'! ::n "' " ,, ,, ;:i ;:i t::.. t::.. '< '< Q. Q.

5 5

.......... - ..... -~ <.O t.C f.D <O<O<J::<O {,)'t 01 iA. ~ ::l :::3 ;J :;, ('; <t - t'b V:V:-'VI ~ ~ Q. ~ -0-0 0-0 - - :::s -0 0 ...; 0 (;! (;! "O :;; ::;· ::;· 0 ::;· ?-; ~ ~- ~

-0

~ ~ -0 ...

~ ;;! jl. <:I' -·ti' :.~ ~ 3: Ut ~

!;O ~ ii>;. ,., ;:l .,,. jl.

~!;!

!)) 0 I/\ IV n n 0 0-0-~-.Ji;_i o.o ~~oo,...o-.-. "' ..., ~ ~ a·-< "O g'e5 :..:.ic.;:,::i o- Cil ;;:;P..00 ~9-: < - · ~ '{f3. ' n ~ 0 - - cCilib o~..o c ~ o..

'<"'Po> n. ll' "' t""t - ...... ~ ,,, ("'J

~ 0:: ~ Cil *'....;

-· N) -0. 0 ~ ..... o ...... ~ n ::i<.0 03 ::. (.0 ....., 0

g ~ ~ 0. ,.... """"' V'J (t n ::I,... -("') , \JJ ... .

S': 0 0. !:!. '"O n ..., O' 8 i»

< :;: 'U ,... ro n ,... v ...,..."'O n ~ r\!l "" p.) ~ :::; p.) -· n cr"O n (b p.) - ::i- "' 0. ~ ............. - 0 ::c: N) ;:5. 3 (b (b 0- ::i ii) 0 !') 3

(Jq "' 0 (b .... CIQ p.; 0 (") 0 < - · . ~ ..., "' 0 "' ,... ~ n/\~ ::l noo o ,...nn~~on.-.<A"' ::i-~ 0 l>!o· O.. C'b~-. --"~'"':>;" ~ ...... e "OC'bt:::~,...o-. c . . ;;;· ~ ' ~ ~ '-.., '<: ~ (l) .... ,.J =· - . ::r 0 o <.11 ~ 8 V> i;;l o ,_.'U - -:.<:;: ("),...-' ~ S- ~:;;;:; n • ~ 0 3 !:? ::I :E ~ 0. q> v ~ ...... ,- -· 0 0 (b :» ,..., 3 0 ~- Sn~n§gN>· ::5&<:3-;i:;:s;o~oo ;:;,. :» <'1> -i ~ _, ;:;;> ,_.. ,...,. _, "O N> ..i.. n ll' :» o. ii" Cil n COO. ~~ ~ '-'~ ~ ~o.r;y,... VO"' ::I _, o. -· o- '-"' . '-' - c ...,... c -· f\ ', -· - n .....:r '::I ,... ..., ._, ::::;· ~ (b h'.i :;:;.' ;::;- e: ~ ,... -::- o- qq N) 0 E n ..., c.o _, ., :» ::

to ~ ~ ~ ...., r:1

~ z l"l

~ z Cl ::c 6; ::i ~

\J\ 00 ..:r

(]I 00 00

588 COLONIAL WATERBIRDS

cm or >100 cm in height (Table 1). In com­parison, more random plots were located in both the tallest and the shortest vegetation classes. Random plots were more frequently in <21 % or >79% horizontal cover 0.2 m above the water (HCOV2), compared with nest plots (Table l). Most nest plots (65.4%) were in medium C:W regardless of the amount of HCOV2. Random plots (32.3%) with HCOV2 <21 % also had low C:W, and 22.3% with high HCOV2 had high C:W (Hickey, unpubl. data). Mean horizontal cover at 1 rn (HCOVl) was similar between plot types, but more random plots had HCOVl >21 % (Table 1). Nest plot:s were >100 m from large open water and farther than random plots from a permanent marsh edge (Table 4). Mean distance between near­est nest:s was 75.2 m, significantly closer than the distance between the closest random plots. Mean distance to nearest vegetation was <0.5 m, and nest:s were surrounded witJ1 vegetation within 1 m on 3 out of 4 sides.

Model Performance

The model accurately predicted 87.5% (21 / 24) of nest sites sampled in western New York in 1995. In 1995, 83.3% of the nest sites were dominated by bur-reed. Three nests not predicted accurately, although dominat­ed by bur-reed, showed the extremes in veg-etation structure. These nests had ~70%:30% , dense cover:water, or $;30%:70%, sparse cover:water. Differences observed in nest frequencies among the vari­ables between years were not statistically sig-

nifican t, except for vegetation density (Table 1). Mean water level in 1995 was sligh tJy low­er than 1994 (Table 3).

The model accurately predicted 64.0% (16/ 25) of nest sites sampled in northern New York in 1995, 70.0% (14/ 20) of nest sites at Perch River WMA, and only 40.0% (2/ 5) of nest sites at Wilson Bay marsh. Perch River WMA nest sites were dominated by bur-reed (30.0%), pickerelweed (Pontede­ria cordata) (30.0%) , and cattail (25.0%). Nest sites at Wilson Bay were dominated by swamp loosestrife (Decodon verticillatus) (80.0%) and arrow-arum (Peltandra virgini­ca) (20.0%). Comparison of the habitat model variables between western and norili­ern New York nest sites showed a greater pro­portion (20.0%) of northern New York nests in low C:W, and fewer in high C:W (P = 0.039, Fisher's Exact Test; Table l). Mean wa­ter level at nest sites in northern New York was deeper than at nest sites in western New York in 1994 and 1995 (Table 3). Nests in northern New York were most frequently ( 44%) in moderately dense vegetation, simi­lar to western New York (P = 0.049, Fisher's Exact Test) , but more often were in either sparse or dense vegetation in 1995 (Table 1). More nests (88.0%) in northern New York were in HCOV5 <21 % (P = 0.073; Table 1). All nests in northern New York were in vege­tation s;50 cm tall, while 50% of the nests in western New York were in vegetation >50 cm tall (P = 0.0001; Table 1). Nests in northern New York were more frequently (72.0%) in $;50% HCOV2 compared to nests (33.3%) in western New York (P = 0.0008; Table l).

Table 3. Mean and median water levels in 1994 Black Tern nest plots and random plots in western New York (WNY) and in 1995 Black Tern nest plots in western New York and northern New York (NNY).

Water level (cm)

Plot cype N x SE Median

1994 nest plots in WNY 26 48.2 2.8 45.51

1994 rnndom plots in WNY 31 42.6 3.0 42.0 1995 nest plots in WNY 24 42.l 2.8 40.52

1995 nest plots in NNY 25 62.6 2.0 61.0'"

1Significantlydiffere m for 1994 nest plots in WNYvs. 1995 nest plot~ in NNY (W = 437.5, P = 0.0000, Mann-Whit­ney) .

~Significantly different for 1995 nesL plolS in WNY vs. 1995 nest plots in NNY (W = 364.5, P = 0.0000, Mann-Whit­ney) .

BLACK TERN NESTJNC HABITAT 589

Table 4. Mean and median estimated distance (m) or (cm) from plot center to nearest habitat features at Black Tern nest plots and random plots in western New York in 1994.

1994 nest plots 1994 random plots

Variable N x SE Median N x SE Median

Small water pool' 36 8.9 1.2 8.0 24 10.4 3.5 4.0 Large water pool2 26 125.8 17.7 100.7 31 141.0 23.6 79.0 Cover changes 26 57.6 9.9 4l.5 31 36.3 6.0 23.0 Marsh edge• 26 87.9 10.6 9l.O* 31 65.5 11.0 37.0* Nest/ Random 26 75.2 12.3 52.7* 31. 156.3 18.5 134.0* Vegetation (cm)3 42 32.4 4.0 24.0 30 24.0 4.2 14.5 No. of sicles6 12 3.2 0.17 4.0 26 2.7 0.3] 3.5

*Significantly different for nest vs. random plots (W > 555, P < 0.05, for both comparisons, Mann-Whitney). 'Open water~ m in diameter intersecting 12-m radius plot. 2Seasonally permanent open water ;e:0.4 ha. 3Major standing vegetation cover change. •pern1anent marsh edge (e.g., upland or dike) . ~Clump of vegetation from edge of nest bowl. 6Number of sides nest surrounded by vegetation within l m.

HCOVl was not different between sites (P"" 1.0).

Habitat Availability

Only 188 ha (13.9%) of all available emergent marsh was classified as favorable Black Tern nesting habitat (FAI-l) from the first level, coarse evaluation. The remaining l, 166 ha of emergent marsh was classified as available, but unfavorable habitat (UH). Black Terns used 57 ha for nesting in 1995, representing only 0.72% of the entire com­plex, 4.2% of the total emergent marsh cover type, and 30.3% of the 188 ha ofFAH initial­ly mapped.

Within the 3 nesting marshes. 57 / 79.4 ha or 71.6% of the total area ofFAH was used in 1995 (Table 5). In 2 marshes, Paddy II and Windmill, >84% of the total area ofFAH was used. The total area of FAH in nesting marshes was >10 ha in each unit and ranged from 25.5%-47.2% of the total size of each unit. Conversely, in marshes not used for nesting, all but 2 of the FAH areas were <6 ha and in most cases, represented <10% of the total area of each unit. The second level, fine evaluation using the habitat model, showed that Black Terns used 72.5% (52.1/71.9 ha) of the total area of HFH in nesting marshes and 51.4% (52.1/ 101.3 ha) of the total area of HFH in all marshes sampled (Table 5) .

Nest densities ranged from 0.43 nests/ ha to 2.6 nests/ha with a mean density of l.l nests/ha (SE= 0.23) (Hickey 1997). In non­nesting marshes, very little (29.4 ha) of the emergent vegetation initially considered fa. vorable, was classified as HFH using the model. Black Terns did not select habitat in proportion to itS availability and selected nest sites in HFH more than expected and Unfavorable Habitat (which included all other habitat classes) less than expected (X2,

= 3.84, p < 0.0001) .

DISCUSSION

Jo this study, Black Tero nests sampled during the first 2 weeks in June were in sparse to moderately dense bur-reed, 26-50 cm tall. Nests were in areas with a 40%-60% cover to water ratio and in 40-60 cm of water. Few Black Terns nested in areas of tall, dense vegetation or in areas of little or no vegeta­tion. These findings were consistent with other general descriptions given throughout the breeding range, using a variety of meth­ods (Dunn 1979, Mossman 1981 , Tilghman 1980, Rabenold 1987, Mossman et al. 1988, Dulin 1990, Knutson 1991, Brewer 1992). In British Columbia, Black Terns nested in reed canarygrass (Phalaris arundinacea) and a wa­ter horsetail (Equiseturn jluviatile), beaked sedge ( Carex rostrata) mix in areas with 25%

Table 5. Swnmary of habitat availability and use by nesting Black Terns in western New York in 1995. (Arca in hectares).

--UniL name Unit size ToLal FAH' % unit area Area used" % ofFAH HFHS

Nest Marshes

Paddy II 21.6 10.2 47.2 8.6 84.3 9.6 Cayuga 142.4 38.6 27.1 20.2 52.3 32.7 Windmill 120.0 3Q.6 25.5 28.2 92.2 29.6 Subtotal 284.0 79.4 57.07 71.9

Non-nest Marshes

Feeder 110.0 5.9 5.4 1.5 Klossen 86.0 0.3 0.3 0.0 Cinnamon 152.0 1.2 0.8 0.6 Meadville 42.0 4.1 9.8 0.9 Sprout 56.0 4.1 7.3 0.0 Ruddy 138.0 4.1 3.0 3.3 Paddy Ill 18.7 3.2 17.J 2.5 Mohawk 518.0 39.5 7.2 19.9 Knowlesville 18.4 2.7 14.7 0.7 Oxbow 56.0 13.5 77.7 0.0 Subtotal 1225.1 108.6 29.4 Grand Tota l 1509.l 188.0 57.0 101.3

'Total favorable available habitat (FAH) deLermined from firsL level, coarse survey and mapping, including cur-rem nesting area. 1Area encompassing each Black Tern nesting group within a marsh. ~Highly Favorable H abitat (HFH) - Model predicted ;e:0.50 probabiliLy of a nest site and suirable substrates wer·e available. 'Favorable Habitat (FH) - Moclel predicted ;:::0.50 probability of a nest site but suitable substrates were unavailable. 'Unfavorable Habitat (UH ) - Model predicted <0.50 probability of a nest site bm suitable substrates were available. 6Highly Unfavorable HabitaL (HUH) - Model predicted <0.50 probability of a nesL site and suitable substrates were unavailable. 70f 57.0 ha used, 52. 1 ha were HFM, while 4.9 were UH.

FH4 uw

0.0 0.6 0.0 5.9 0.0 0.5 0.0 7.0

2.9 l.5 0.0 0.3 0.0 0.6 0.9 2.3 2.7 0.7 o.o 0.0 0.0 0.7 6.2 8.5 0.0 2.0 6.2 12.4

18.9 29.0 18.9 36.0

HUH6

0.0 o.o 0.5 0.5

0.0 0.0 0.0 0.0 0.7 0.8 0.0 4.9 0.0

24.9 31.3 31.8

(,]\

<D 0

(') 0 r 0 z ~ ~ ~ t"1

~

~ V>

BtACK TERN NF.STING HABffAT 591

standing vegetation , 42% matted floating vegeLation, and 33% open water (Chapman Mosher 1986). In MinnesoLa, while the ma­jority of nest sites and random plot.s were in cattail, nest sites were in areas with shorter vegetation, g reater visibi lity (a measure of vegetation density), deeper water, and closer to open water when compared to ra ndom sites (Maxson 1993, 1994). Black Tern nest sires in Vermont were closer to open water and bur-reed, bu t farther from upland than random sites, suggesting a tendency for Black Terns to nest toM1rd the center or marshes (Shambaugh 1995). In this study, bur-reed was considered an important spe­cies because it wa.~ o ne of the earlier emer­gerllS available to terns in May (Shambaugh 1995). These findings snppon the idea that life form of the vegetation is more imporrant in determining key structural features than the actual species ('Neller and Spatchcr 1965).

All of the above studies suggesL that Black Terns seem to select nest si tes in marshes with a 50:50 vegetation cover:water ratio that is well-interspersed with water. This pattern is typical of the regenerating and degenerat­ing stages o f the marsh life cycle in northern prairie wet lands (Weller and Spatther 1965, Weller and Fredrickson 1973, van der Valk and Davis 1978). These stages can occur af­ter drought (natural or artificial) when the vegeiation responds to the alternating wel and dry periods and changes in water levels. Other disrnrbances, such as lire and herbi· cides, can also reduce exis1ing vegetative bio­mass stimulating rege11eratio11.

Since l 989, .Black Terns nesiing at the Tonawanda/ Iroquois/ Oak Orchard wetland complex colonized <lll average of 5 im­poundments each year. Five impoundments consistently used over this period were: Ca­yuga ( INWR), Windmill (OOWMA), Wood (lWMA), Paddy II (TWMA), and Meadville (TWMA). Two of these, Cayuga and Wind­mill, were used 6 ou1 of 7 years. Review of management ac1ions indicated a consistent pattern of response by nesting Black Terns. In nearly every case, afier an intentional or natura l drawdown (removal of w·ater from the impoundmcnt for one or more seasons).

Black Terns colonized impoundments 1.he year following re flooding and peak numbers occurred in the second and t11ird years after drawdown. In t11e firs1 year following re­flooding, vegeiation responded, muskrat populalions grew, and Black Tern ncs1ing was probably limited by lack of suitable nest­ing substrates. Tn the second and third )'Cars, muskrat reeding and house-building activi­ties removed vegetaiion improving the inte r­spersion of vegetation LO water and providing nesting substrates. Similar pat· terns of wetland colonization by Black Terns have been documemed (Delehamy and Sve­darsky 1993, Lim: et al 1994). In one wetland restored 5 years after being drained, Black Terns immedialc ly returned the fo llowing year, and peak populations occurred in the second and tl1ird years (Dclehamy and Sve­darsky 1993). McNicholl (1975) suggesled a high level of g roup adherence combined with moderately low site tenacity would e n­able larids, such as Black Terns, to rapidly colonize newly available habitats a nd recolo­nize pre,fousl)• used habitats when suitable.

The habiiat model was a useful tool to distinguish among the variations in habital struc111 re. In wesicrn New York. the observed differences in habitat features a t nest sites between years may have been related to veg­etation responses w sligh tly higher w;ucr lev­e ls, higher prec1p1tation, and cooler 1emperarures observed in 1994 compared w 1995. The standardized data collection methods enabled comparison of several nesting colonies within New York State. Nest si tes in northern New York were typically more open than nest sites in western New York. This may be related to the relatively highe r water levels in the northern New York colonies and may partly explain why the model predicted only 64.0% of the nesl sites overall.

Poor model perfonnance may reflecr in­adequate model assumptions, va1;alions in local habitat conditions, and othet- factors not associated with the habitat feamres mea­sured (Anderson ;rnd Gutzwiller 1994). lm­ponant habitat fealltres may occur at different temporal or spatial scales. Further. social strucwre of the colony, group adher·

592 COLONIAi. WA'rERBIKOS

ence, and site tenacity likely play a role in sc­leclion of a marsh and individual site for nesting. To better unders1and the microhab­itat and macrohabitat fea1ures imporrant in nes1 site selection, habitat should be evalua1-ed at multiple scales and other fac1.ors, such as food availabil ity and beha,~oral aspects, should be identified.

Habitat Availability

Little of the total emergem vegetation in the western New York s1udy area was classi­fied as favorable Black Tern nesting habitat. TI1e 46 pairs of Black Terns utilized an ex­tremely small pan of to tal emergent vegeta­tion available, but used a significant porcion of tl1e I l ighly Favorable Habital. for nesting. Although tl1ere was unoccupied HFH a l the Tonawanda/ Iroquois/ Oak Orchard wetland complex, much of it was found in small patches scanered over several impound­menl.$. HFH cottld become limiting if the breeding population increases or if nest site selection is influenced by social strncture of the colony, habitat patch size and isolation, and nesiing subsirate availability.

The definition of available habitat may be confounded by limits in nesting densities. The mean internest distance of 75.2 m in this ~tudy was greater than the typical in­ternesr distance of <30 m reported in o ther studies (Cuthbert 1954, Bai ley 1977, Dunn 1979, Chapman Mosher 1986). Black Terns may be able to nest in higher densities in the study area. Considered only partly colonial (Cuthbert 1954), a Black Tern colony within a single m11rsh will form groups of I 0 or few­er nests scanered from 3 to 25 m apan (Pro­vost 1917. Baggennan et al 1956. Weller and Sp11tcher 1965, Railey 1977, Dunn 1979). This pattern of coloniality and nest spacing is probably l reason Black Terns are more commo nly found in larger wetlands and con· sidered an area-dependent species (Brown and Dinsmore 1986). Because these birds tend to spread out to nest, available sui1able habitat may be limited for a g iven area (Van Horne 1983).

Marsh or vegetation patch size and isola­lion may a lso limit habitat availabi lity. In

l\rown and Dinsmore's ( 1986) swdy on marsh size and isolation, Black Terns did not occur in marshes <5 ha and occurred mos1 frequently in marshes >20 ha. Jn marshes 5-20 ha, tems occurred more often when the marshes " 'ere pan of a larger wetland cont­plex (Brown and Dinsmore 1986). The size of the vegetation patches within a marsh may be just as important as the size of Lhe marsh itself. For example. at Lhe swdy area in western New York, no nesting or non-nesting imp0tu1d­ments sampled in the study area were <5 ha and nearly all were >20 ha. The tom I favorable avai lable habitat (FAH) in nesting marshes from the coarse assessment was >to ha, but made up <50% of the total size of the tiniL, a reflection of the large size of the units. In con­u-ast, total FAH in non-nesting marshes was <6 ha in all but 2 uniL~, represented <I 0% of to­tal size of tl1e unit, and in many cases was b ro­ken up in10 small vegetatio n patches. Black Terns may seek an opdmum dis1.ance from botl1 t1·1e water edge a nd the upland edge. V.'here relatively small ' 'egetalion patches oc­cur, terns might be forced to nest near edges. In dense vegetation, terns may select the edg­es which would likely remain sparse through the brood-rearing period, essential for easy mobili ty of chicks seeking refuge. Wind and w·Jve action from the \\'ll.ter edge and preda­tors from both edges could have significamly greater impact.sin colo nies where terns must nest near either type of edge. Thus, wetland habitaL or pa1ch fragmemalion and increased edge might negatively influence reproductive success in a similar "oay foresl fragmentation and edge effect has been implicated in Lhc de­cl ine of some intedor-dependem forest birds (Askins el al. 1990).

There may also be a problem of percep­tion. Habitat might appear suitable for nesl­ing when acwally unsui ia ble. ln non-nesting marshes in this study, very liule (29.4 ha) of the emergent vegetation was classified as HFH using tl1e model. .For example, al­though Oxbow Marsh had a high proportion (77.0%) of tl1e total unit area considered as FAH o n Lhe first level, coarse assessment, wit e n fine-tuned by the model , most of i1 was classified as unfavorable because of poor veg­etation struc ture and lack of nest subsirates.

Bl.AC" Tt'Rl'I =-:t.STl'IG HAllrTAT 59:~

l:sing lhe habitat model 10 asse<;.s the qualit}' of available habitat assumed that the nesting habitat at this complex was of high quality. Quality measured only in temis of nest density may be misleading and should also be measured in terms of reprocluc1i,·e success (\'an I lome 1983). DuringthisslUd). few significant relationships were found be­tween nest fate and ne't sile habitat features (Hickey 1997). 01hc1 swdics hm·e found a few relationships IX:l\\l'Cn nes1 / chick fate and specific nesting habitat features (Cha1>­man :\loshcr 1986; Firs1enccl 1987; Faber 1992; Maxson 1993, 1994), bu1 na1nral mri­ability in reproductive mte~ makes it hard 10 identify trends. Habitat cau indirectly influ­euce the primary dTects of weather and prc­d;ition on nes t/chick fate, but the relationship between hahirnt chararteris1 ics and re productive success may be complex.

Muskrat su·ucturcs we re used heavily as nesting s11hsm1tcs m thi~ Sindy sitc and oth· e rs (Cuthbert 1954; Weller and Sp:ucher 1965: Bergman et al. 1970; Adams 1990; Sey­ler 199 1, 1993; aml llickC)' 1992). In Iowa, 72% of 156 Black lcrn nests were built on muskra1 houses and a general po~iti,•e rela­tionship between the number of muskra1 houses and the percent use of homes b) Black Tern~ was obsef\ed (Weller and Spatcher 1965). Some mtdies ha,·e reported low use of muskrat strur1urc' (Bailey 1977, Dunn 1979).

Nest substrate fonnation and availabilitv may influence nest site selectio n. The a\'ail­ability and use of musl..rat 51rucrures may re· llect the ' egetation l)pc and processes that foster nest substrate fonnation. Floating ' 'eg­eta1.ion mats and roo1SLalks may form more often in marshes dominatc-d hy pcrsistem emergents, such as en trails and hulrushes (Sdtpu.s spp.), as a result of snow accumula­tion, wind and ice aniun. In marshes with less persistent c inergems, 11 cst substrate fo1c mation may depend o n 111uskra1 activities.

In a northern 111arsh in Sask:uchcwan, muskrats preferred burrows whe n popula­tions were smal l, while ho nscs were u,, cd as alternative dwellings at high population le'' els (Messier and Virgl 1992). Ho uses were more likely abandoned in the winter than

burrows. Houses collapsed rapidh in late April and earl)' May after spring thaw. From a managemc-111 perspeclive, :\lessier and Vir­gl ( 1992) suggested that conslll.1ction o f is­lands within marshes 10 enhance \\'ate1 fowl nest success might attract muskrats to bur­row in the islands, reducing the ex1ent mW>k· rats \\'Ould open up ,·egeiation tluough 1hei1 house-building and feeding acti\'ities. This could also result in a tack of nesting sub­s1ra1es available for Black Tems. Muskrats are an important feature in the ecology of nesting Black Terns in some areas.

AOK.'10\\1.WG~IF.'ITI)

Sp~cial thanks to the perwnnel "-'' the New Yo 1-k St.Ale ()epanmcm1 of En\ironment...tl f'.i0n1Jcn,,11011 (:\YSDEC). l\u rcau of Wildlife. Region 8 ;rnd Jlw 11·0-quois Nntional Wildlife Refuge. both locatctl in J\J,,. barn:.. ~ewYork. 0 . Seyler. S. Kno,\lton, T. Lo1·en10, ancl numerous interns and \'Oluntccr'! pro\'idcd v~tlu.1ble

field aMi~Vtncc. lethnical ('td\·ice, guidance, .md '!up­pon were generously offetcd by R. A. Malecki, O. Win­kler. S. Sheaffer. and P. Cunis. G. Churchill of the 81omc1rics Unit at Cornell Uuivtl"'ii1v 'or.ts t'~pt"n.tlly hrlpful with lhe statistical anal)ses. Tiianks 10 ll Ill<»><') and G. Lint for their r('\'ic:\\~ or the oliginal the~1-s .md C:.. \\'e.seloh and R.. Morri5; for Lhdr helpful comment< on the rnar'IUsc:ripl. Special llrn11Ls 10 I. Mau occhi. f\"'S­DEC Region 6, for her coopcraU\1:: sp1ril and ~h~lrcd t .. n­chus1asm i11 stud) lng Black Tem..s. Thb research \\.l'I

funded b\ R<gion 5 of the lJ .S. Fhh •nd II ildlofe l><·r· V1CC, the ~on-Game and Habital Llnil and Region R of the !\"t'SDEC. and the N<·w York Coop<>r:tll\\> h<h ~nd \\'ildlite Research Umt at Conu·U Un1vemt\.

RFFl'R.E.'<U..S crrrn

\dams. O.J. 1990. Populaoon >LllUS .ind brccd11111 ecol­ogy of th<' Black Tern (Ch/ido1110J mgn) al 1hr Im· quois/Tonawanda/ Oak Orchard complc•. 19~10. fot•I r<-pon. Saint john fi>her College. Roche,i.r, Xew\'ork.

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Me~<ocr I' ;ndj. A Virgl l9'J2. 0 1ftur111i<1l <L-.e ofb:rnl. bunO\'i'\ ;,nd ltxtgr' m mu ... L.r;lt\. Ondntra W>rlhuw. m .l nonhc.-rn mar~h t•11\110nmt'nt~ C.otnad1an Jour· n.11 of lool<>K' 74~ I IAA-1181

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\l0»mJ11 , \l J..A. f l cchlo" Ill , l.J Ziebell,'-· \\' ~IJ1-le'><>n and K. J rru1h t'lMll. 'lr<ung guu, and terns of Winnc·b.,go Pool .md Rmh l..tL<'. Wi~<n1'.in. Pa ... >engcr l~g,...,n 50: 107·117.

NAllB.~ [Th,· 'ollh Amrn<an llr<edmg Sird Sun~'). 19% lJn11cd St.ti<"\ t o<h .md 111ldlile &n·icc and ca. 11.ldian W1ldhfc St•1Y1«.·. l ntemet addre~: http:. ""'·w.irn.nl».go, / bb< • I l /2/ 9-,.

Neu. C. IV., C. R. ll1<· r~ ,ondj M. Peel. 1 97~. A wch-111ri11~ fo1 ;m.tl) ''' of utih1dtl()n~av;oh-tbi1i1) d:ua.

J•>urn.11 of \ \ftldllk Man.1gc.·mcn1 38: 5-11·545. 'lov.1k, I' C. 19\10. l'opltl.111011Ma ll"1ll 1lw 1ll.1ck Tern in

~(·wY()rlSr . .it(' .. 198!J. Fitml 1c:ron. Dhi-,ic)n of Fi~h

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Pittm.111 , II II 1927. Tht• Bl.1<1. rcrn">f $,hl.atehr""'"· C'A>rldor 2'). 140. H3.

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