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Mountain Plover Population Responses to Black-Tailed Prairie Dogs in Montana

Stephen J. Dinsmore Colorado State University, [email protected]

Gary C. White Colorado State University - Fort Collins, [email protected]

Fritz L. Knopf U.S. Geological Survey

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Dinsmore, Stephen J.; White, Gary C.; and Knopf, Fritz L., "Mountain Plover Population Responses to Black-Tailed Prairie Dogs in Montana" (2005). USGS Staff -- Published Research. 48. https://digitalcommons.unl.edu/usgsstaffpub/48

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Mountain Plover Population Responses to Black-Tailed Prairie Dogs in Montana Author(s): Stephen J. Dinsmore, Gary C. White, Fritz L. Knopf Source: The Journal of Wildlife Management, Vol. 69, No. 4 (Oct., 2005), pp. 1546-1553 Published by: Allen Press Stable URL: http://www.jstor.org/stable/3803514 Accessed: 23/06/2009 00:45

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http://www.jstor.org MOUNTAINPLOVER POPULATION RESPONSES TO BLACK-TAILED PRAIRIEDOGS IN MONTANA

STEPHENJ. DINSMORE,1,2Department of Fisheryand WildlifeBiology, Colorado State University,Fort Collins, CO 80523 USA GARYC. WHITE,Department of Fisheryand WildlifeBiology, Colorado State University,Fort Collins, CO 80523 USA FRITZL. KNOPF,U.S. GeologicalSurvey, Biological Resources Division,Fort Collins Science Center,2150-C CentreAvenue, FortCollins, CO 80525 USA

Abstract:We studied a local population of mountain plovers (Charadriusmontanus) in southern Phillips County, Mon- tana, USA, from 1995 to 2000 to estimate annual rates of recruitment rate (f) and population change (X). We used Pradel models, and we modeled X as a constant across years, as a linear time trend, as year-specific, and with an addi- tive effect of area occupied by prairie dogs (Cynomysludovicianus). We modeled recruitment rate (f) as a function of area occupied by prairie dogs with the remaining model structure identical to the best model used to estimate X. Our results indicated a strong negative effect of area occupied by prairie dogs on both x (slope coefficient on a log scale was -0.11; 95% CI was -0.17, -0.05) andf (slope coefficient on a logit scale was -0.23; 95% CI was -0.36, -0.10). We also found good evidence for a negative time trend on X; this model had substantial weight (wi= 0.31), and the slope coefficient on the linear trend on a log scale was -0.10 (95% CI was -0.15, -0.05). Yearlyestimates of X were >1 in all years except 1999, indicating that the population initially increased and then stabilized in the last year of the study. We found weak evidence for year-specific estimates of X;the best model with year-specific estimates had a low weight (wi = 0.02), although the pattern of yearly estimates of X closely matched those estimated with a linear time trend. In southern Phillips County, the population trend of mountain plovers closely matched the trend in the area occupied by black-tailed prairie dogs. Black-tailed prairie dogs declined sharply in the mid-1990s in response to an outbreak of sylvatic plague, but their numbers have steadily increased since 1996 in concert with increases in plovers. The results of this study (1) increase our understanding of the dynamics of this population and how they relate to the area occupied by prairie dogs, and (2) will be useful for planning plover conservation in a prairie dog ecosystem. JOURNALOF WILDLIFEMANAGEMENT 69(4):1546-1553; 2005

Keyworls: Charadriusmontanus, Cynomys ludovicianus, Montana, mountain plover, population trend, prairie dog, status.

The finite rate of population change, lambda dictors of future trends. Additionally, estimates of (X), is often of fundamental importance to ecol- X from projection matrices may be biased down- ogists interested in assessing population status. ward if there is substantial emigration, particularly Estimates of lambda can show that a population amongjuvenile age classes (Franklin et al. 1996). is increasing (k > 1), stable (k = 1), or declining Pradel (1996) introduced a reparameterization (X < 1) and provide a more formal means of of the Jolly-Seber model to estimate the finite interpreting estimates of population size. Under- rate of population change (X) in addition to standing these rates becomes even more impor- apparent survival (4) and conditional capture tant for rare or declining species that require probability (p). Unlike the Leslie projection immediate intervention to rescue them from fur- matrix, this method directly accounts for internal ther declines or extinction. (reproduction and mortality) and external The traditional method of estimating X has (immigration and emigration) influences on the been with the use of Leslie projection matrices population of interest and is an improvement (Leslie 1945, Caswell 2001). Under this method, because Xis estimated directly from the data. measures of average age-specific survival and Mountain plovers are a local and declining fecundity are used to project population growth shorebird of the western Great Plains (Knopf over a specified period. However, this method 1994). Perceived declines led to a proposal to list has problems. The most important flaw is that the them as a Threatened species in 1999 (U.S. rates that are often used represent averages over Department of the Interior 2002). Rigorous a specified time period, so predicted values of X assessment of plover status and trends at key are also averages and may not be reasonable pre- breeding areas is needed and will provide a better understanding of local population dynamics and future conservation efforts for this 1 Present address: of NaturalResource help species. Department We estimates of annual rates of Ecology and Management,Iowa State University,339 provide popula- Science II, Ames, IA 50011. tion change (X) from 1995 to 1999 for a popula- 2 E-mail:[email protected] tion of mountain plovers in southern Phillips 1546 J. Wildl.Manage. 69(4):2005 MOUNTAINPLOVERS AND PRAIRIE DOGS IN MONTANA* Dinsmoreet al. 1547

County, Montana. Southern Phillips County is thought to contain the largest breeding popula- tion of plovers in Montana and one of the largest in North America (Knopf and Miller 1994). We discuss population trends at this site in light of the total size of this population (Dinsmore et al. 2003) and changes in the area occupied by black- tailed prairie dogs. We then comment on the sta- tus and future outlook for mountain plovers at this key breeding site, and we identify several aspects of their biology needing further study. STUDY AREA We studied mountain plovers on a 3,000-km2area in southern Phillips County in north-central Mon- tana (47040'-47055'N,107"35'-108030'W; Fig. 1). The study area was bounded by the Missouri River to the south, the Sun Prairie and Content roads to the east, Beaver Creek to the north, and Highway 191 to the west. Approximately 2,250 km2 of the study area was in public ownership with the Bureau 0 40 80 Kilometers of Land Management (BLM, Malta Field Office) and the U.S. Fish and Wildlife Service (USFWS, Charles M. Russell National Wildlife Refuge). This Fig. 1. Mapof PhillipsCounty, Montana, USA, showing the dis- area was a with flats tributionin 2000 of black-tailedprairie-dog colonies. The stip- mixed-grass prairie sagebrush pled regionrepresents the study area. bordering the southwestern edge of the Prairie Pothole Region (Knowles et al. 1982, Olson and Edge 1985). Predominant vegetation included big negative impact on some of the smaller prairie-dog sagebrush (Artemisia tridentata), silver sagebrush colonies (Vosburgh and Irby 1998). Prairie dogs (Artemisiacana), greasewood (Sarcobatusvermicula- have rapidly recovered from the last major plague tus), yellow sweetclover (Melilotusofficinalis), green outbreak in 1992-96.Colony areas were reduced by needlegrass (Stipa viridula), and western wheat- about 80% during this outbreak, but they have grass (Agropyronsmithii). Active black-tailedprairie since increased from 1,371 ha in 1995 to 5,071 ha in dog colonies contained variable amounts of bare 2000 (J. Grensten, Bureau of Land Management, ground interspersed with sparse vegetation that personal communication; Fig. 2). Inactive colonies, included fringed sagewort (Artemisia frigida), mostly the result of plague outbreaks, were not plains prickly pear (Opuntia polycantha), blue included in this total because habitat on such grama (Boutelouagracilis), needle-and-thread grass colonies rapidly became unsuitable for plovers, (Stipa comata), and Sandberg bluegrass (Poa often within a matter of a few weeks. secunda), with fewer grasses generally present on the older colonies. Mean annual precipitation METHODS near the center of the study area was 33 cm, most and of which fell from May to July (D. Veseth, Veseth Capture Marking and Veseth Inc., personal communication). Mean We studied mountain plovers from 20 May to 20 elevation was approximately 930 m. July during 6 breeding seasons (1995-2000). We We studied mountain plovers exclusively on or systematicallysearched active prairie-dog colonies adjacent to active black-tailed prairie-dog colonies within the study area >3 times each year. On these because previous research found that mountain searches we slowly drove a vehicle across each plovers preferentially used such sites in Montana colony and periodically stopped to scan for (Knowles et al. 1982, Knowles and Knowles 1984). plovers. We watched individual adult birds from a Prairie-dog numbers fluctuated considerably in distance until they returned to a nest. Once we southern Phillips County, mainly as a result of out- located a nest, we trapped the adult immediately breaks of sylvatic plague, an epizootic (Barnes with a walk-in, wire-mesh trap placed over the 1993), although recreational shooting may have a nest, and we then banded the bird with a unique 1548 MOUNTAINPLOVERS AND PRAIRIE DOGS IN MONTANA* Dinsmoreet al. J. Wildl.Manage. 69(4):2005

6000 - Estimating Population Trends (X) * We estimated the finite rate of population ^ 4000- ~* ~ change (X) and recruitment (J) using the Pradel lambda models (Pradel 1996) in program MARK e (White and Burnham 1999). We estimated annu- < 2000- al apparent survival and population size earlier using the robust design (Dinsmore et al. 2003); 0 , , our focus was only on estimates of X and f Mod- 1995 1996 1997 1998 1999 2000 els to estimate X from a robust Year directly design study have not been developed, so we were Fig. 2. Area occupied by black-tailedprairie dogs in southern forced to slightly modify our approach to esti- PhillipsCounty, Montana, USA, 1995-2000. We calculated mating X and fwith this model. areas from annual Bureau of Land Management surveys; We summarized releases and live of areas from 1998 and 2000 were from cornplete censuses, resightings whileall otherestimates were predictedarea is basedon ann babandedplovers in encounter history format with al countsof 1/3of allknown colonies. 6 encounter occasions, 1 for each year of the study. We only used information from adult plovers, which included all birds first banded as combination of 4 colored leg baneIs and an alu- adults and all juveniles that were subsequently minum, size 3A USFWS numbered leg band. We resighted as adults. Using this approach, we esti- derived color-band combinations frrom 6 possible mated the annual rate of the breeding adult colors (red, orange, yellow, dark blue, green, population change (X) for 5 years (1995-1999) white) that we chose to minimize possible read- and recruitment (f) for 5 years (1996-2000). ing errors. We used ultraviolet (U V) stable Dar- Our general approach to modeling X and ffol- vac leg bands (A. C. Hughes, Lond on) to reduce lowed Lebreton et al. (1992) and Burnham and color fading. We released all plo\ vers within 15 Anderson (2002). We first developed a list of a minutes of capture. We typically banded juvenile priori factors influencing each parameter (4, p, f, plovers as flightless chicks (>10 days old). In July, X), and we then used this information to define a we occasionally trapped and band(ed small num- set of candidate models. bers (<10 per year) of juvenile andI adult plovers The Pradel models allowed the simultaneous at night. We located the birds at roosts with a estimation of apparent survival (+) with capture spotlight, approached them on f oot, and cap- probability (p) and the finite rate of population tured them in a large dip-net. iCapture tech- change (X) or recruitment (/). Because there was niques did not result in any imme.diate mortali- only a single encounter occasion per year, we ties. The Colorado State Universit)y Animal Care could not estimate the recapture probability (c). and Use Committee approved the field methods Under this model, population change was esti- (Protocol 98-134A-01). mated as: for Marked Plovers Surveys +1 We searched all known, active prairie-dog _t=^N NtN colonies within the study area >3 times each year. Searches were divided among 3 secondary sam- where Nt represented the population size at some pling periods (20 May-10 Jun, 11-30 Jun, 1-20 time t. Between times t and t + 1 the population Jul), with a minimum of 1 search per sampling changed as a function of births, deaths, emigra- period. We conducted live recaptures by resight- tion, and immigration. Thus, changes in X were a ing marked plovers. For all plovers, we recorded function of apparent survival, recruitment, and the age (adult orjuvenile) and exact sequence of movement. color bands, if the bird was marked. We trained To estimate X using the Pradel model, we had all individuals involved in resighting plovers prior to model annual apparent survival and initial to fieldwork to minimize possible errors reading capture probability correctly. For mountain color band combinations (Milligan et al. 2003). plovers, we modeled apparent survival (4) as We believe that reading error rates were low year-specific. Because we believed X changed because plovers were approachable, were typical- annually, it made sense to also allow survival to ly detected singly, and were marked with leg vary annually, even though we suspected yearly bands of contrasting colors. differences in adult survival were small (Dins- J. Wildl.Manage. 69(4):2005 MOUNTAINPLOVERS AND PRAIRIEDOGS IN MONTANA* Dinsmoreet al. 1549 more et al. 2003). For comparison, we also ed instead of population trend (k). In this model, included a single model where apparent survival recruitment was a function of the hectares of active was constant across years. prairie-dog colonies and used the same constraints The initial capture of mountain plovers on ) and p that were in the best survival and X occurred by either physical capture (p) or model. Here, f was defined as the number of new resighting (r), and we knew from earlier work animals in the population at time i per animal that that the probability of physical capture was much was in the population at time i - 1 (Franklin 2000). lower than resighting probability (Dinsmore et The relationship between lambda, apparent sur- al. 2003). In an earlier analysis, we showed that vival, and recruitment was simply X = 4 + f There- models where p = r + C, where C was some con- fore, f estimated the portion of apparent survival stant, received the best support (Dinsmore et al. that was due to recruitment. We modeled recruit- 2003). Limitations in the structure of the Pradel ment models on the logit scale, where: model prohibited modeling p and r separately, so we were forced to model all initial with + captures logit(f) )= ln( f-) o , (X), probability p. We considered 2 constraints on cap- ture probability: We let it be constant across years and X represented some variable of interest such [p(.)] and allowed it to vary by year [P(t)].Because as the area occupied by prairie dogs. differences in yearly capture probabilities using With these guidelines, we considered the fol- the robust design were small (Dinsmore et al. lowing 6 models to estimate k and f 2003), we hypothesized that models with constant capture probability would receive better support (1) {(.) p(.) (.) than those with time-specific capture probability, (2) (t) P(.)p (73 but this was somewhat we speculative. Therefore, (3) +(t) p(.) 3(t) considered the use of both of these constraints (4) +(t) P(t) 3(t) on capture probability partly exploratory. (5) (t) P(.) Xprairiedog For lambda 4 from best X (X), we considered constraints. We (6) fprairiedog with and p structure considered 2 models with full time variation where model X varied by year [(t)]; 4 was also year-specific in Goodness-of-fit both models, while p was constant in 1 model and year-specific in the other. We also considered a We used the total chi-square value from Tests 2 model where k had a linear time trend [x()]; ) and 3 in program RELEASE(Burnham et al. 1987) was year-specific, and p was constant. We next con- as a test of goodness-of-fit of our mountain plover sidered a model where x was constant [k (.)], but data to the Pradel lambda model. We checked for only when 4 and p were also constant; a model overdispersion in these data using an estimate of c with constant x and time variation on 0 and p was from RELEASE,that we obtained by dividing the nonsensical. Finally,we considered a model where total chi-square by its degrees of freedom. X was a function of the hectares of active prairie- We computed the ratio of differences in log dog colonies [dprairiedog]. This latter model was an likelihood values as an approximate measure of attempt to solidify the relationship between these the proportion of deviance explained by the best 2 species that we found earlier (Dinsmore et al. model (Skalski et al. 1993). We calculated this 2003). Thus, temporal variation in X was account- quantity as: ed for by recruitment and immigration in the first case and by recruitment, immigration, and appar- Proportion of deviance = [log L (best) ent survivalin the second case. We modeled lamb- - log L (.)]/[log L (global) - log L (.)] da models on a log scale, where: using log likelihoods from the best model, the = log(k) + 1(X), global (4(t) p(t) X (t)) model, and the simplest (((.) p() k (.)) model. Here, the simplest model had 3 and X represented some variable of interest such parameters (), p, and X), and the global model as the area occupied by prairie dogs or a linear had full year-effects on (, p, and X (15 parameters). time trend. Model Selection In an attempt to better understand possible caus- es of annual population trends, we also considered We selected an appropriate model using the a single model where recruitment (J) was estimat- methodology of Burham and Anderson (2002). 1550 MOUNTAINPLOVERS AND PRAIRIEDOGS IN MONTANA* Dinsmoreet a. J. Wildl.Manage. 69(4):2005

First, we ranked the set of R candidate models Akaike weights; parameter estimates from models using Akaike's Information Criterion (AIC; with higher weights received stronger support Akaike 1973). The use of AIC provides a means of than those from models with little or no weight. objectively ranking a set of models and then Using the Akaike weight and estimate of lamb- selecting a best approximating model or models da (X) from each of the R models, we computed for inference (Burnham and Anderson 2002). To a model averaged estimate of X as: correct for small bias, we used possible sample R AICCto rank models. We defined AICCas: xi= L i AICc= -2log L + 2K[n/(n - K- 1)] with sampling variance: where logL was the natural logarithm of the like- lihood function evaluated at the maximum likeli- R 2 hood estimates, K was the number of estimable var(1i)= X wi Ivar( i Mi) + (i- xi)2 parameters, and n was the sample size. Here, the sample size was the total number of releases (new releases plus resightings). The second term in where Mi was the ith model in the candidate set the above equation was a correction for small (Buckland et al. 1997). The 95% confidence sample size. interval for model-averaged estimates of X was: Once we computed AICcvalues for each model, we ranked the R models relative to the model 95%CIL = i - 96[SE(Xi)] with the minimum AICcvalue. We made compar- isons between models AAICC where using values, 95%CIu= i + 1.96 SE(xi ] for each model i: where: AAICc = AIC tAIC- Ci Ci minm SE(Xi)= var(Xi)- The AAICCvalues compared the relative dis- RESULTS tances between the best approximating model (AICc ) and each competing model (AICc). The pooled results from Tests 2 and 3 in pro- Generally, models with AAICc values <2 have gram RELEASE showed there was a good fit to strong support whereas those with hAIC values the Pradel lambda model (4X2,P= 0.41). There >10 have little support (Burnham and Anderson was no evidence of extra binomial variation in 2002). We also computed normalized Akaike these data (c = 1.03). The proportion of deviance weights (wi) for each of the R models as: explained by the best model was 49% of variation. Model-averaged estimates of X showed -that the e _(_) population of mountain plovers in southern Wi R (AAICJ Phillips County, Montana, increased rapidly from 1995-1998 and then to stabilize in 1999 e appeared r=1 (Fig. 3). During the period of increase from 1995 to 1998, the estimates of X were >1, but X could These normalized weights provided another not reliably be judged different from 1 in 1999. means of directly evaluating the strength of evi- We found good evidence supporting an effect of dence for each model and were useful for com- the hectares of active prairie-dog colonies on X, but estimates that reflected model the effect on the scale was puting parameter log negative ([3prairie-o selection uncertainty (Burnham and Anderson = -0.11; 95%CI was -0.17, -0.05). We also found 2002). Parameter estimates in MARKwere maxi- good evidence for a negative linear time trend in mum likelihood estimates with 95% confidence X on the log scale in the third best model (PT = intervals based on a logit or log transformation. -0.09; 95%CI was -0.14, -0.04). This model had Instead of using parameter estimates from a single stronger support (wi = 0.31) than models where X best model, we model averaged (Burnham and was time-specific or constant across time (Table 1). Anderson 2002) parameter estimates across all 5 Using the best lambda and survival model, we candidate models. This procedure weighted the estimated recruitment instead of lambda (Table 1). individual parameter estimates according to their This model received only slightly less support J. Wildl.Manage. 69(4):2005 MOUNTAINPLOVERS AND PRAIRIE DOGS IN MONTANA* Dinsmoreet al. 1551

than the best k model

(AAIC = 0.07, wi= 0.32). 0) The effect of area occu- C 1.5 c- pied by prairie dogs was still strongly negative on I + the logit scale {iaii-og ff 0=c 1 = -0.23; 95%CI was 0 I in this -0.36, -0.10} 0 model. Estimates of f O. o gradually declined from 0.72 in 1996 to 0.38 in 0.5 I I I I 1995 1996 1997 1998 1999 2000 (Table 2). Year DISCUSSION Fig. 3. Model-averagedestimates and 95% confidence intervalsof annual populationtrends (X)for adultmountain plovers in southernPhillips County, Montana, USA, 1995-1999. Interpretation of k Estimates of X are to bias if the size of The model selection results generally agreed with susceptible the area the earlier findings on apparent survival and capture study changed during study (Franklin et al. In our trends probabilities,lending support to estimates of k from 1999). study, population repre- the Pradel model. Earlier,we found that adult sur- sented real trends and were not a reflection of in the size of area studied. The bound- vivalshowed little annual variationand that captCyno- changes aries of the area were fixed for the duration mysludovicianusure probabilities were high with only study of the Within the we slight annual variation (Dinsmore et al. 2003). Pradel 6-year study. study area, to all known colonies models with the same constraints on apparent sur- attempted survey prairie-dog for We missed some small vival and capture probabilityreceived the best sup- plovers. occasionally but seldom these port of the models we considered. Due to limitations colonies, plovers occupied colonies and in the Pradel model that forced capture probabilities (Olson-Edge Edge 1987). Thus, study area was each and to be estimated as a single parameter,these estimates coverage nearly complete year, trends reflected real in the of X should still be interpreted with caution. Improp- population changes numbers of mountain within this area. er modeling of capture probabilitiesmay have result- plovers ed in biased estimates of annual slightly population Prognosis trends. Ultimately, a robust design Pradel model is At the mountain in needed to properly model capture probabilities present, plover population southern to be stable at and generate less biased estimates of X for this Phillips County appears 175 individuals et al. population. approximately (Dinsmore 2003). The viability of such a small population is unknown, although they successfully rebounded Table1. Summaryof modelselection resultsfor the population from estimated population levels below 100 indi- trends of breedingadult mountain plovers in southernPhillips viduals in the mid-1990s. Our results that County, Montana,USA, 1995-2000. Models are ranked by suggest ascending AAICC,wi is the model weight,and K is the number the population increased rapidly from 1995 to of parameters.We modeled apparent survival (+), capture 1998, from in situ but more and the finiterate of possibly reproduction, probability(p), recruitmentrate (f), popu- from a combination of and lationchange (X)to include no time effects (.), a lineartime likely reproduction trend(T), fulltime effects (t), or an effect of area occupied by prairiedogs (prairiedog).a Table2. Model forf) estimates(?SE) of Model Deviance K AICc AAICC wi averaged(except appar- ent survival(4), recruitment(f), and finite rate of population f( P(.) Xprairiedog 2,565.05 8 2,581.24 0.00 0.33 change (x) fromthe Pradelmodel for adult mountain plovers in f(0 P) fprairie-dog 2,565.12 8 2,581.31 0.07 0.32 southernPhillips County, Montana, USA, 1995-2000. f( P(R.)(T) 2,565.21 8 2,581.40 0.17 0.31 Year SE ()) f SE (f) . SE (X) f(, p(.)I(m 2,564.71 11 2,587.06 5.83 0.02 f(, p('( ) 2,581.34 3 2,587.37 6.13 0.02 1995 0.68 0.06 NA NA 1.42 0.10 f(, p(t \(2 2,564.07 15 2,594.71 13.47 0.00 1996 0.69 0.05 0.72 0.08 1.34 0.07 1997 0.63 0.04 0.69 0.07 1.22 0.04 a We computed deviance as -2[loge(L({)) - 2loge(Ls()))], 1998 0.62 0.04 0.57 0.04 1.08 0.04 where representeda maximumlikelihood estimate whose log- 1999 0.63 0.05 0.44 0.04 0.99 0.06 likelihoodwas evaluatedfor the model in question [L(6)]and 2000 NA NA 0.38 0.04 NA NA forthe saturatedmodel [Ls(0)]. 1552 MOUNTAINPLOVERS AND PRAIRIE DOGS IN MONTANA* Dinsmoreet al. J. Wildl.Manage. 69(4):2005 immigration from surrounding areas such as Fort ment of the Interior 2003). With this heightened Belknap Indian Reservation (Dinsmore et al. interest in their conservation, mountain plovers 2003). During 2000-2001, there were signs of will undoubtedly be the subject of various mea- another sylvatic plague outbreak in prairie dog sures designed to reverse their recent declines. populations in southern Phillips County. Because mountain plovers in this region are closely tied to MANAGEMENTIMPLICATIONS black-tailedprairie dog numbers, any future reduc- The patchy distribution, low breeding densities, tions in area occupied by prairie dogs will likely and widespread declines of mountain plovers make negatively impact plovers. Monitoring plovers them a solid candidate for conservation measures. through a sylvatic plague outbreak would be use- Plovers are a highly specialized, endemic bird of ful for noting the timing and magnitude of the western Great Plains and have adapted to a her- declines and recovery and correlating these bivore-driven,arid ecosystem. Threats to their con- changes to the area occupied by prairie dogs. tinued existence are many and include habitat loss We cannot address whether the estimate of 175 on the breeding and wintering grounds, regional breeding adults is sufficient to sustain this popula- changes in grazing practices, declines of a primary tion for an extended period. Recruitment was herbivore (black-tailed prairie dogs), and perhaps high in 1995, but it gradually declined with an threats from agriculture (Knopf and Rupert increase in the area occupied by prairie dogs, a 1996). One of the greatest threats to mountain pattern similar to that exhibited by estimates of plovers in Montana, and possibly elsewhere within annual survival (Table 2). The high estimates of their breeding range, is the continued loss of recruitment relative to estimates of survivalsuggest prairie-dog colonies. Montana has begun work on that recruitment was an important component of a statewide prairie dog management plan (Knowles population growth in this population. This in turn 1999) and there is hope that this will be used to in- suggests that immigration may have played an crease prairie dog numbers in the state. The results important role in this rapid recovery. of this study illustrate that mountain plovers are at We found a strong negative relationship between least partly dependent on black-tailed prairie the area occupied by prairie dogs and both X and dogs within part of their range (Montana), and f Prairie-dog colonies were a preferred habitat for that the conservation of prairie dogs is thus mountain plovers in this region (Olson 1984), so imperative for plovers in that region. we initially expected to find a positive relationship between area occupied by prairie dogs and both ACKNOWLEDGMENTS population growth and recruitment. It is clear that We are grateful to Fort Carson Military Reser- this population is rebounding in concert with an vation (U.S. Department of Defense), the U.S. increase in the area occupied by prairie dogs. If Fish and Wildlife Service (Colorado Fish and the rate of change in the area occupied by prairie Wildlife Management Assistance Office), the Bio- dogs was slower than the rate of change in plover logical Resources Division of the U.S. Geological numbers, then such a negative relationship could Survey, the U.S. Bureau of Land Management result. The result was that plovers may not have (Malta Field Office, Montana, USA), the Denver been able to colonize new prairie dog colonies as Zoological Foundation, and the Fort Belknap fast as they were becoming available. Or, perhaps Tribal Community for financial support. The staff the area occupied by prairie dogs was not the best at Charles M. Russell National Wildlife Refuge measure of plover habitat; colony-specific fea- supplied additional logistical support. J. J. Gren- tures, the spatial arrangement of colonies, or the sten and B. D. Rosenlund assisted with multiple site fidelity of plovers may all be more important, aspects of the study. Field assistance was provided and these factors are not related to the total area by A. Brees, D. C. Ely, T. Hanks, J. G. Jorgensen, occupied by prairie dogs. C. McQueary, and T. Vosburgh. We thank B. This information should provide a more solid Matovitch, D. Robinson, and J. Robinson for foundation on which to build conservation mea- allowing us access to their lands. This is contribu- sures for mountain plovers. Mountain plovers tion number WF193 of the Forest and Wildlife were recently identified as highly imperiled in a Research Center, Mississippi State University. review of North American shorebirds, 1 of 5 shore- bird species receiving this designation (Brown et LITERATURECITED al. A to 2001). petition federally list the species as AKAIKE,H. 1973.Information theory and an extension Threatened was withdrawn in 2003 (U.S. Depart- of the maximumlikelihood principle. Pages 267-281 J. Wildl. Manage. 69(4):2005 MOUNTAIN PLOVERSAND PRAIRIEDOGS IN MONTANA * Dinsmoreet al. 1553

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