Survey Techniques for Determining Occupancy of Isolated Wetlands by Round-tailed Muskrats

SOUTHEASTERN NATURALIST2005 4(4):745–756

Survey Techniques for Determining Occupancyof Isolated Wetlands by Round-tailed Muskrats

ROBERT L. SCHOOLEY1,2,* AND LYN C. BRANCH

1

Abstract - Neofiber alleni (round-tailed muskrat) is a wetland-associated species ofconservation concern restricted to the southeastern United States. This species isrelatively unstudied and no standardized procedures exist for determining its distri-bution. We evaluated a survey technique for assessing presence-absence of round-tailed muskrats in small, isolated, freshwater marshes in central Florida. We con-clude that ≥ 2 trained persons searching adjacent belt transects on foot for ≤ 30 minduring fall–early winter can reliably determine occupancy for muskrats based onpresence of their distinctive lodges. Resurveys of unoccupied wetlands did not revealany false absences from our initial survey, and an investigation of lodge persistenceindicated that false presences were unlikely. Broad-scale studies of distributionalpatterns and temporal trends in occupancy of the round-tailed muskrat are needed toassess its conservation status and threats.

Introduction

Neofiber alleni True (round-tailed muskrat) represents a monotypicgenus endemic to the lower coastal plain of the southeastern United Statesand is dependent on isolated wetland habitats in Florida and southernGeorgia (Bergstrom et al. 2000, Lefebvre and Tilmant 1992). Round-tailedmuskrats are semi-aquatic, herbivorous, nocturnal, secretive, and possiblynon-territorial and colonial (Birkenholz 1963, 1972; Lefebvre and Tilmant1992). The Florida Committee on Rare and Endangered Plants and Ani-mals proposed the round-tailed muskrat as a Species of Special Concernbecause of presumed statewide population declines due to wetland losses(Lefebvre and Tilmant 1992), and it is listed as a threatened species inGeorgia (Bergstrom et al. 2000).

Given the conservation status of round-tailed muskrats, efficient andreliable protocols are needed to determine current distributional patterns atbroad spatial scales and to monitor temporal trends at specific sites. Unfortu-nately, round-tailed muskrats are difficult to livetrap (Bergstrom et al. 2000;Birkenholz 1963; Schooley and Branch, in press). For elusive species, anapproach that is practical for landscape-scale studies is to determine presence-absence at sites based on sign (Bright et al. 1994, Fedriani et al. 2002, Walkeret al. 2003). Occupancy data not only are valuable for documenting distribu-tional patterns and developing predictive habitat models (Carroll et al. 1999,Gibson et al. 2004, Reunanen et al. 2002), but also they can provide critical

1Department of Wildlife Ecology and Conservation, University of Florida,Gainesville, FL 32611. 2Current address - Department of Natural Resources andEnvironmental Sciences, University of Illinois at Urbana–Champaign, Urbana, IL61801. *Corresponding author - [email protected].

Southeastern Naturalist Vol. 4, No. 4746

insights into spatial dynamics that may be key to conservation strategies(Hanski 1999). However, imperfect detection of a species can result inunderestimates of site occupancy, biased estimates of local extinction andcolonization rates (MacKenzie et al. 2002, 2003; Moilanen 2002), and dis-torted inferences from wildlife-habitat models (Gu and Swihart 2004). Ifdetection probabilities are low for surveys and “false absences” are common,then special habitat modeling approaches based on presence-only data may berequired (Brotons et al. 2004, Hirzel et al. 2002). Previous studies have usedpresence of sign to measure wetland occupancy (Franz et al. 1998) andtemporal trends (Bergstrom et al. 2000) for round-tailed muskrats, but suchprocedures have not been evaluated for potential biases.

As part of a larger project on vertebrate use of small, isolated wetlands,we investigated patch occupancy and spatial dynamics of round-tailedmuskrats. Key results from that project will be published elsewhere. Here,our objective was to evaluate the survey protocol used to determine pres-ence-absence of muskrats in freshwater marshes based on sign. Specifi-cally, we determined the amount of search time required to find sign,assessed potential effects of number of searchers and survey order onestimates of wetland occupancy, and evaluated the likelihood of falseabsences and false presences.

Our results indicate that distributional patterns of muskrats among wet-lands can be determined reliably from sign. Our procedures involving walk-ing surveys are suitable for typical wetland habitats within the core of thegeographic range for the species, which consist of small, isolated, seasonalfreshwater marshes. This technique might be less suitable for other regionsin which habitat of round-tailed muskrats is substantially different. Forinstance, Bergstrom et al. (2000) used airboat and helicopter surveys ofround-tailed muskrat lodges for several large (340–2400 ha) Carolina baysin Georgia.

Study Area

We conducted our research on a 19,500-ha area in the southern por-tion of Avon Park Air Force Range (APAFR, 15 km east of Avon Park,Highlands County) in central Florida from 2002 to 2004. Suitable habitatfor round-tailed muskrats consists of isolated marshes that are distinctpatches surrounded by a terrestrial matrix that includes dry prairie, pineflatwoods (Pinus palustris Miller, P. elliottii Engelm.), pine plantations(P. elliottii), and oak scrub (Quercus spp.). Most of the marshes are small(median = 0.9 ha), but wetland area is variable (0.04–73.81 ha). Theseseasonal wetlands dry out for some period during the spring (March–May) and then are refilled mainly by summer rains (June–September).The marshes typically are shallow (water depth < 50 cm), which is apreferred condition for round-tailed muskrats (Birkenholz 1963, Lefebvreand Tilmant 1992). Plant zones within the marshes typically are domi-nated by Panicum hemitomon Schultes (maidencane), Pontederia cordata

R.L. Schooley and L.C. Branch2005 747

L. (pickerelweed), or Hypericum fasciculatum Lam. (St. John’s wort).Other common plants include Juncus effusus L., Spartina bakeri Merr.,Rhynchospora inundata (Oakes) Fernald, Sagittaria lancifolia L.,Aristida palustris (Chapm.) Vasey, Andropogon virginicus L., andEriocaulon decangulare L..

Muskrat lodges in the study area are constructed of tightly woven vegeta-tion, especially maidencane, and usually are built upon a base of flattenedplant material just above water level (Birkenholz 1963). Lodges are spheri-cal to dome-shaped, have an average diameter of 30 cm (18–61 cm;Birkenholz 1963, 1972), and characteristically contain two plunge holes thatlead from the interior chamber to the water below. Oryzomys palustrisHarlan (marsh rice rats) also occupy the wetlands, but they build nests thatare distinguishable from muskrat lodges. Rice rat nests are smaller (Wolfe1982), have a single and less conspicuous exit hole located on the top or side,and may be built in vegetation < 50 cm above water level.

Methods

Survey proceduresIndividual searchers walked adjacent belt transects within wetlands and

searched for sign of round-tailed muskrats. Transects were oriented parallelto the long axis of the wetland. Spacing between searchers (ca. 2–6 m) wasdictated by vegetation thickness; searchers maintained a distance that al-lowed for a thorough inspection of the entire area between them. We initi-ated searches in central vegetation zones dominated by emergent grasses andforbs (especially maidencane), instead of in outer zones usually dominatedby shrubby St. John’s wort, because preliminary sampling indicated thesecentral zones were most likely to contain sign.

Occupancy of wetlands by round-tailed muskrats was determined by thepresence of their distinctive lodges (Bergstrom et al. 2000, Birkenholz 1963,Franz et al. 1998). We restricted our sampling to a period after summer rainshad recharged wetlands and when muskrats needed to build lodges to inhabitthe marshes. That is, we avoided sampling during the dry season whenmuskrats abandon lodges and switch to living in burrows (Birkenholz 1963;Schooley and Branch, in press). Although presence of muskrats in recentlydried wetlands might be indicated by presence of freshly excavated burrows(Birkenholz 1963, Lefebvre and Tilmant 1992), the reliability of this ap-proach has not been established.

We classified muskrat lodges as currently either “active” or “inactive.”Active lodges primarily were defined by a solid structure and by a well-formed interior chamber, which we examined if classification based solely onexternal condition was uncertain. Active lodges also typically had one or moreof these traits: fresh vegetation woven into the outside, fresh plant clippingswithin the chamber, or nearby feeding platforms. These platforms (10–15 cmlong) consisted of a pad of vegetation at the water level and are used forfeeding and defecation (Birkenholz 1963, 1972). We initially assumed that the


presence of any muskrat lodge (active or inactive) represented wetlandoccupancy sometime during the current “hydrologic year” (June–May), butthen we evaluated this assumption (see Lodge persistence).

Search timeBecause it is inefficient to search wetlands beyond a point in which

detection of sign becomes unlikely, we established the amount of timeneeded to detect a lodge, given that one would be found during a survey. Thesame two people conducted total searches of 84 wetlands between 7 Augustand 23 October 2002 and recorded the search time (min) until the firstmuskrat lodge was encountered. These wetlands were a representativesample of wetlands at the study area. We used the distribution of searchtimes to construct a one-sided, upper tolerance limit (PROC CAPABILITY,SAS 2002) that included 99% of search times with 99% confidence. We alsotested whether the time required to find the first lodge was related to wetlandarea. This determination allowed us to conduct partial searches of largerwetlands while maintaining a high probability of detecting any sign present.

Number of searchers and survey orderWe surveyed 457 wetlands (with total and partial searches) in each of

two years. These wetlands included all of the marshes in the study area thatwere identified from low-altitude aerial photographs (1:4800) and groundreconnaissance. The total number of surveys was 914. In 2002–2003, thewetland surveys were conducted from 3 July to 15 February, but most (86%)were carried out after 30 September. In 2003–2004, surveys were conductedfrom 30 September to 22 January. We determined the order in which wet-lands were surveyed in a quasi-random manner (with one exception, seebelow). Strictly random sampling was not feasible due to constraints frommilitary activities at the site. The number of searchers per survey ranged upto 6, but was 2–4 for most surveys (85%, n = 914). We varied the number ofsearchers because it was more efficient to use only 2 people for smallerwetlands that could be completely searched in ≤ 30 min, but to use moresearchers for larger wetlands. We also used ≥ 4 searchers on wetlands ofvarious sizes during an initial training period of assistants each year. Weusually restricted our surveys to ≤ 30 min based on our evaluation of searchtime required for two people reliably to find sign (see Results). This timelimit resulted in partial searches for wetlands classified as unoccupied for16% of the surveys in 2002–2003 and for 22% in 2003–2004. We extendedthe search time beyond 30 min for 84 surveys because either we were stillsearching for sign of marsh rice rats for a concurrent study, or we wanted todouble-check that 30-min searches were adequate for detecting presence ofmuskrats in larger wetlands.

We used logistic regression to evaluate potential effects of number ofsearchers and survey order (1–457) on the probability of detecting thepresence of round-tailed muskrats during wetland surveys. We started witha base model that included two explanatory variables, wetland area and


habitat quality, which were positively related to occupancy (Branch andSchooley 2005). Habitat quality of wetlands was an index of cover anddensity of maidencane-dominated zones that ranged from 0 to 1 (Branchand Schooley 2005). We then added the sampling covariates (number ofsearchers, survey order) to these base models individually and in combina-tion. We examined potential linear, quadratic, and cubic effects of surveyorder. For 2003–2004, we removed the first two weeks of surveys fromanalysis because during this period we intentionally selected wetlands witha high probability of being occupied to facilitate training of assistants.Inclusion of these initial surveys would have created a false, negative ordereffect. To examine whether number of searchers was a more importantcovariate for large wetlands, we created four additional models that in-cluded an area x searchers interaction term. A positive interaction wouldsupport our a priori expectation. In total, we evaluated 12 candidate mod-els. We used a model-selection procedure based on Akaike InformationCriterion (AIC) to select the best model and rank the others (Burnham andAnderson 2002). We present results as AIC differences (Δi = AICi - [mini-mum AIC]) so that the best model has Δi = 0. Models with Δi ≤ 2 areconsidered competitive models (Burnham and Anderson 2002). We alsoreport Akaike weights (wi) that are normalized relative likelihoods thatmodel i is the best model.

Revisits and false absencesOur approach for evaluating the potential problem of false absences was

to resurvey a number of sites that were initially classified as empty, in mostcases using an increased sampling effort the second time (Moilanen 2002).The proportion of sites unoccupied in the initial survey but occupied duringthe revisit served as an estimate of the probability of false absences. Weresurveyed 30 wetlands from 10 to 14 February 2004 that were classified asvacant during the first visit. These wetlands were a random sample ofunoccupied wetlands that were initially surveyed < 2 months earlier toreduce the chance that they had been colonized by muskrats during theintervening time. Hence, presences during the second visit indicated falseabsences from the initial survey and not real changes in occupancy. Duringboth visits, seven larger wetlands were partially surveyed by four people,which was the maximum number of trained observers available. Of theremaining 23 wetlands, all were totally searched in ≤ 30 min and ≥ 4searchers were used more often during the revisits (69.9%) compared to theinitial visits (34.8%).

Lodge persistenceWe examined lodge persistence between survey periods to evaluate the

assumption that all lodges encountered during our fall–winter surveys repre-sented muskrat occupancy from the current hydrological year. We selected atotal of 50 lodges (a total sample of 17 from one wetland, and a randomsample of 33 from another). These lodges were active at the end of the


survey period in 2004 (mid-January to mid-February). Each lodge wasflagged and its spatial coordinates recorded with a Global Positioning Sys-tem (accuracy ≤ 2 m). A single observer then classified the status of eachlodge during resurveys as “active”, “inactive”, or “absent.” This final cat-egory included old lodge material that was compressed or under water andno longer discernible as a muskrat lodge. Resurveys were completed on 19May, 1 July, 19 August, and 17 September 2004.

Results

Search timeWe detected sign of round-tailed muskrats in 19 of 84 (22.6%) wetlands

in which two people conducted total searches. The search time until the firstdiscovered lodge was ≤ 15 min in the 19 wetlands with detected sign (mean= 6.7 min, SD = 4.3). The upper tolerance limit was 23.6 min, whichindicates that we can be 99% confident that ≥ 99% of required search timesshould be < 24 min. The amount of search time required until sign wasdiscovered was unrelated to wetland area (rs = 0.15, P = 0.548, n = 19).

Based on these results, we set a typical time limit of 30 min (uppertolerance limit plus 6 min cushion) for most (90%) of the subsequent occu-pancy surveys. For surveys extended beyond 30 min, search time averaged46 min (SD = 13, max. = 106, n = 84). We found sign of round-tailedmuskrats during the extended time and not during the first 30 min at only onewetland (1.2%).

Number of searchers and survey orderIn both years, the best logistic regression model of occupancy included

only wetland area and habitat quality (Table 1). Models that also includedeither number of searchers or survey order (linear effect) were competitive

Table 1. AIC-based selection of logistic regression models of wetland occupancy for round-tailed muskrats. Explanatory variables included wetland area, habitat quality, number ofsearchers, and survey order. K = the number of explanatory variables plus 1, Δi = AICi -(minimum AIC), and wi are Akaike weights. The top five models are presented for eachyear (Δi = 0 for best model).

Year AIC

Model K Log-likelihood Δi wi

2002–2003 Area, quality 3 -208.60 0.00 0.206 Area, quality, searchers 4 -207.89 0.58 0.154 Area, quality, searchers, area x searchers 5 -207.04 0.88 0.133 Area, quality, order (linear) 4 -208.31 1.42 0.101 Area, quality, order (linear), searchers 5 -207.47 1.74 0.086

2003–2004 Area, quality 3 -178.74 0.00 0.351 Area, quality, searchers 4 -178.28 1.08 0.205 Area, quality, order (linear) 4 -178.73 1.98 0.130 Area, quality, order (quadratic) 5 -177.94 2.40 0.106 Area, quality, order (linear), searchers 5 -178.26 3.04 0.077


Figure 1. Relationship between estimated wetland occupancy by round-tailed muskratsand (A) number of searchers, and (B) survey order. Each bar includes an upper 95% CI.


models, but these three-variable models differed by a single variable and hadsimilar log-likelihoods compared to the best model (Table 1), which indi-cates that the larger models were not supported (Burnham and Anderson2002). For 2002–2003, a model that included an area x searcher interactionwas ranked third best (Table 1), but the coefficient for the interaction termwas negative (-0.107) and the effect was weak (Wald 95% CI: -0.270,0.055). All models that included the sampling covariates (number of search-ers, survey order) explained approximately the same amount of variance(< 0.5% increase) as the base model with only wetland area and habitatquality (2002–2003, R2 = 30%; 2003–2004, R2 = 29%). Overall, we foundlittle support that the sampling covariates had measurable effects on esti-mates of wetland occupancy (Fig. 1).

Revisits and false absencesWe detected no sign of round-tailed muskrats during our revisits to the

random sample of 30 wetlands previously classified as unoccupied. Thisresult suggests that unoccupied wetlands generally do not represent falseabsences and that a single visit within a year is adequate to determine thedistributional patterns of round-tailed muskrats.

Lodge persistenceBy May 2004, wetlands were drying out, muskrats were shifting to

burrow use, and most (84%) of the sample of 50 lodges judged active in

Figure 2. Persistence of 50 lodges of round-tailed muskrats classified as active inJanuary–February 2004 and resurveyed by a single observer during months shown.Lodge activity definitions and exact survey dates are provided in the text.


January–February were identifiable but inactive (Fig. 2). By July, waterlevels still were only 0–30 cm in the wetlands due to a late arrival of summerrains. At that time, most (68%) of the 50 lodges still were inactive, but 30%were absent. By August, water levels were 20–50 cm, most lodges (72%)were absent, and none was active (Fig. 2). By September, water levels were40–55 cm and most lodges (96%) were absent.

Discussion

Our field assessment indicated that presence of sign could be useddependably to measure occupancy patterns of round-tailed muskrats in iso-lated, freshwater wetlands typical of our study area. This positive result waspartly due to the obviousness of the sign—basketball-sized lodges—that,unlike the nocturnal animals that created them, did not move and were easilydetected visually. The reliability of our survey technique allows one to treatthe results as presence-absence data and apply an approach such as logisticregression to model habitat relationships, which is more accurate than meth-ods developed for presence-only data (Brotons et al. 2004).

Potential problems with occupancy surveys can result from false ab-sences and false presences. Of these, false absences are more likely and cancause serious estimation biases for occupancy rates and for key parametersof spatially explicit metapopulation models (MacKenzie et al. 2002, 2003;Moilanen 2002). We reduced the chance of false absences in our muskratsurveys in several ways. First, we conducted surveys during the period whenwetlands were inundated and muskrats typically were using lodges, so thatlack of lodges should indicate absence of muskrats. This is a reasonableassumption but one that is difficult to verify in the field because no otherreliable techniques are available for determining presence of muskrats (e.g.,livetrapping is not dependable). We recommend that surveys be conductedin central Florida during fall–early winter when water levels in wetlandshave stabilized somewhat. Our field observations suggest that muskratsmight build and use fewer lodges during the initial summer recharge periodwhen water levels fluctuate rapidly and repeated flooding of lodges ispossible. Densities of muskrats also might be lower in summer compared tofall–winter (Birkenholz 1963). Second, in our initial surveys in 2002–2003we determined the amount of time required by two trained searchers to find alodge (24 min), given that one would be found, and then typically conductedsubsequent surveys for ≤ 30 min with ≥ 2 people. Required search time wasunrelated to wetland size, in part, because we initiated searches always invegetative zones that muskrats were known to prefer. This standard searchtime should be reevaluated in other areas with different wetland sizes orvegetation structure. Third, we conducted revisits of marshes recorded asunoccupied (Moilanen 2002) to estimate directly the probability of falseabsences. For future studies, we recommend that researchers initially deter-mine detection probabilities with a pilot study following the frameworkprovided by MacKenzie et al. (2002).


False presences are considered to occur relatively infrequently in occu-pancy studies because misidentification of species by trained observersshould be minimal. In fact, the approach of MacKenzie et al. (2002) forestimating occupancy rates with imperfect detection probabilities assumesthere are no false presences. For studies in which animal sign is used todetermine presence, however, false presences could arise if sign outlasts theindividuals that produced the sign. In such instances, sign would indicatepast occupancy of a site instead of current occupancy. In our surveys, activelodges clearly represented current occupancy because lodges consistentlybecame inactive during the spring dry season (Fig. 2). Some inactive lodgespersisted into the summer, but nearly all of these disappeared by September.Hence, if surveys are conducted in fall–early winter, then all lodges can beused to indicate presences for the current hydrological year. Over two years,93% of our surveys were conducted after 29 September. For other areaswhere lodges might be built in places in which they could persist longer,such as on floating vegetation mats (Bergstrom et al. 2000), it might be saferto use only active lodges to indicate occupancy unless a site-specific studyof lodge persistence was conducted.

Researchers might be tempted to use counts of lodges as an index ofpopulation size for round-tailed muskrats as the two measures are probablycorrelated. The actual association between number of lodges and populationsize is unknown, however, and this relationship might vary with environ-mental conditions. Birkenholz (1963) concluded that there were approxi-mately two lodges for each muskrat present in a wetland, and this rule-of-thumb has been used to estimate population densities (Bergstrom et al. 2000,Franz et al. 1998). Subsequent studies of space use via radio telemetryindicate that the number of lodges used by individuals is variable, ranges upto 10, and probably averages > 2 (Bergstrom et al. 2000; Schooley andBranch, in press). Importantly, the number of structures used by individualsmight vary with population density (Van Horne et al. 1997), which wouldmean such indices would be insensitive to changes in density over space andtime. Unless lodge counts can be substantiated as an index to population sizethrough comparisons to direct estimates from concurrent mark-recapturestudies (Van Horne et al. 1997), we suggest studies should focus on occu-pancy patterns.

Research in other parts of the geographic range of the round-tailedmuskrat is necessary to determine the true conservation status of this speciesand how it is responding to ongoing modification of wetland habitat. Moni-toring for temporal changes in occupancy rates should be adequate fordetecting strong population trends at landscape scales. Although our surveytechnique was designed and evaluated for relatively small and isolatedmarshes, this technique could be applied with some modification to otherwetland systems in which walking surveys are practical.


Acknowledgments

We are grateful to Scott Cardiff, James Christopoulos, Bob Gilbreath, MollyMcDermott, Alex Pries, Laurinda Showen, Matt Shumar, and Coral Wolf for assis-tance with fieldwork. We also thank John Bridges, Paul Ebersbach, Peg Margosian,and Steve Orzell for facilitating our study at APAFR. Brad Bergstrom provided manyhelpful comments on the manuscript. Our research was funded by a grant from theDepartment of Defense through the Environmental Flight at APAFR. This is FloridaAgricultural Journal Series No. R-10857.

Literature Cited

Bergstrom, B.J., T. Farley, H.L. Hill, Jr., and T. Hon. 2000. Ecology and conserva-tion of a frontier population of the round-tailed muskrat (Neofiber alleni). Occa-sional Papers of the North Carolina Museum of Natural Sciences 12:74–82.

Birkenholz, D.E. 1963. A study of the life history and ecology of the round-tailedmuskrat (Neofiber alleni True) in north-central Florida. Ecological Monographs33:255–280.

Birkenholz, D.E. 1972. Neofiber alleni. Mammalian Species 15:1–4.Branch, L.C., and R.L. Schooley. 2005. Wetlands assessment in a landscape context

on Avon Park Air Force Range: Surveys for wading birds and round-tailedmuskrats (Neofiber alleni). Final Report. Department of Defense, Avon Park, FL.191 pp.

Bright, P.W., P. Mitchell, and P.A. Morris. 1994. Dormouse distribution: Surveytechniques, insular ecology, and selection of sites for conservation. Journal ofApplied Ecology 31:329–339.

Brotons, L., W. Thuiller, M.B. Araújo, and A.H. Hirzel. 2004. Presence-absenceversus presence-only modelling methods for predicting bird habitat suitability.Ecography 27:437–448.

Burnham, K.P., and D.R. Anderson. 2002. Model Selection and Multimodel Infer-ence: A Practical Information-Theoretic Approach. Springer-Verlag, New York,NY. 488 pp.

Carroll, C., W.J. Zielinski, and R.F. Noss. 1999. Using presence-absence data tobuild and test spatial habitat models for the fisher in the Klamath Region, USA.Conservation Biology 13:1344–1359.

Fedriani, J.M., M. Delibes, P. Ferreras, and J. Roman. 2002. Local and landscapehabitat determinants of water vole distribution in a patchy Mediterranean envi-ronment. Ecoscience 9:12–19.

Franz, R., D. Maehr, A. Kinlaw, C. O’Brien, and R.D. Owen. 1998. Distribution andabundance of sensitive wildlife species at Avon Park Air Force Range. FinalReport. Department of Defense, Avon Park, FL. 90 pp.

Gibson, L.A., B.A. Wilson, D.M. Cahill, and J. Hill. 2004. Modelling habitatsuitability of the swamp antechinus (Antechinus minimus maritimus) in thecoastal heathlands of southern Victoria, Australia. Biological Conservation117:143–150.

Gu, W., and R.K. Swihart. 2004. Absent or undetected? Effects of non-detection ofspecies occurrence on wildlife-habitat models. Biological Conservation116:195–203.

Hanski, I. 1999. Metapopulation Ecology. Oxford University Press, Oxford, UK.313 pp.


Hirzel, A.H., J. Hausser, D. Chessel, and N. Perrin. 2002. Ecological-niche factoranalysis: How to compute habitat-suitability maps without absence data? Ecol-ogy 83:2027–2036.

Lefebvre, L.W., and J.T. Tilmant. 1992. Round-tailed muskrat (Neofiber alleni). Pp.276–286, In S.R. Humphrey (Ed.). Rare and Endangered Biota of Florida. Vol-ume I. Mammals. University Press of Florida, Gainesville, FL. 392 pp.

MacKenzie, D.I., J.D. Nichols, G.B. Lachman, S. Droege, J.A. Royle, and C.A.Langtimm. 2002. Estimating site occupancy rates when detection probabilitiesare less than one. Ecology 83:2248–2255.

MacKenzie, D.I., J.D. Nichols, J.E. Hines, M.G. Knutson, and A.B. Franklin. 2003.Estimating site occupancy, colonization, and local extinction when a species isdetected imperfectly. Ecology 84:2200–2207.

Moilanen, A. 2002. Implications of empirical data quality to metapopulation modelparameter estimation and application. Oikos 96:516–530.

Reunanen, P., A. Nikula, M. Mönkkönen, E. Hurme, and V. Nivala. 2002. Predictingoccupancy for the Siberian flying squirrel in old-growth forest patches. Ecologi-cal Applications 12:1188–1198.

SAS. 2002. SAS for Windows, Version 9.0. SAS Institute Inc., Cary, NC.Schooley, R.L., and L.C. Branch. In press. Space use by round-tailed muskrats in

isolated wetlands. Journal of Mammalogy.Van Horne, B., R.L. Schooley, S.T. Knick, G.S. Olson, and K.P. Burnham. 1997.

Use of burrow entrances to indicate densities of Townsend’s ground squirrels.Journal of Wildlife Management 61:93–102.

Walker, R.S., A.J. Novaro, and L.C. Branch. 2003. Effects of patch attributes,barriers, and distance between patches on the distribution of a rock-dwellingrodent (Lagidium visacia). Landscape Ecology 18:187–194.

Wolfe, J.L. 1982. Oryzomys palustris. Mammalian Species 176:1–5.

Documents

Survey Techniques for Determining Occupancy of Isolated Wetlands by Round-tailed Muskrats