Live-trapping capture-recapture studies of animal populations with fixed trap locations inevitably have a spatial component: animals close to traps are more likely to be caught than those far away. This is not addressed in conventional closed-population estimates of abundance and without the spatial component, rigorous estimates of density cannot be obtained. We propose new, flexible capture-recapture models that use the capture locations to estimate animal locations and spatially referenced capture probability. The models are likelihood-based and hence allow use of Akaike's information criterion or other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its dependence on spatial or temporal covariates is therefore straightforward. Additional (nonspatial) variation in capture probability may be modeled as in conventional capture-recapture. The method is tested by simulation, using a model in which capture probability depends only on location relative to traps. Point estimators are found to be unbiased and standard error estimators almost unbiased. The method is used to estimate the density of Red-eyed Vireos (Vireo olivaceus) from mist-netting data from the Patuxent Research Refuge, Maryland, U.S.A. Estimates agree well with those from an existing spatially explicit method based on inverse prediction. A variety of additional spatially explicit models are fitted; these include models with temporal stratification, behavioral response, and heterogeneous animal home ranges.

Summary 1.The status of small cetaceans in the North Sea and adjacent waters has been of concern for many years. Shipboard and aerial line transect surveys were conducted to provide accurate and precise estimates of abundance as a basis for conservation strategy in European waters. 2. The survey, known as SCANS (Small Cetacean Abundance in the North Sea), was conducted in summer 1994 and designed to generate precise and unbiased abundance estimates. Thus the intensity of survey was high, and data collection and analysis methods allowed for the probability of detection of animals on the transect line being less than unity and, for shipboard surveys, also allowed for animal movement in response to the survey platform. 3. Shipboard transects covered 20 000 km in an area of 890 000 km 2 . Aerial transects covered 7000 km in an area of 150 000 km 2 . 4. Three species dominated the data. Harbour porpoise Phocoena phocoena were encountered throughout the survey area except in the Channel and the southern North Sea. Whitebeaked dolphin Lagenorhynchus albirostris and minke whale Balaenoptera acutorostrata were found mainly in the north-western North Sea. 5. Phocoena phocoena abundance for the entire survey area was estimated as 341 366 [coefficient of variation (CV) = 0·14; 95% confidence interval (CI) = 260 000-449 000]. The estimated number of B. acutorostrata was 8445 (CV = 0·24; 95% CI 5000-13 500). The estimate for L. albirostris based on confirmed sightings of this species was 7856 (CV = 0·30; 95% CI = 4000 -13 000). When Atlantic whitesided dolphin Lagenorhynchus acutus and Lagenorhynchus spp. sightings were included, this estimate increased to 11 760 (CV = 0·26; 95% CI 5900-18 500). 6. Shortbeaked common dolphin Delphinus delphis were found almost exclusively in the Celtic Sea. Abundance was estimated as 75 450 (CV = 0·67; 95% CI = 23 000 -149 000). 7. Current assessments and recommendations by international fora concerning the impact on P. phocoena of bycatch in gillnet fisheries in the North Sea and adjacent waters are based on these estimates.

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Summary1. Accurate and precise estimates of abundance are required for the development of management regimes for deer populations. In woodland areas, indirect dung count methods, such as the clearance plot and standing crop methods, are currently the preferred procedures to estimate deer abundance. The use of line transect methodology is likely to provide a cost-effective alternative to these methods. 2. We outline a methodology based on line transect surveys of deer dung that can be used to obtain deer abundance estimates by geographical block and habitat type. Variance estimation procedures are also described. 3.As an example, we applied the method to estimate sika deer Cervus nippon abundance in south Scotland. Estimates of deer defecation and length of time to dung decay were used to convert pellet group density to deer density by geographical block and habitat type. The results obtained agreed with knowledge from cull and sightings data, and the precision of the estimates was generally high. 4. Relatively high sika deer densities observed in moorland areas up to 300 m from the forest edge indicated the need to encompass those areas in future surveys to avoid an underestimate of deer abundance in the region of interest. 5. It is unlikely that a single method for estimating deer abundance will prove to be better under all circumstances. Direct comparisons between methods are required to evaluate thoroughly the relative merits of each of them. 6. Line transect surveys of dung are becoming a widely used tool to aid management and conservation of a wide range of species. The survey methodology we outline is readily adaptable to other vertebrates that are amenable to dung survey methodology.

Abstract. The density of a closed population of animals occupying stable home ranges may be estimated from detections of individuals on an array of detectors, using newly developed methods for spatially explicit capture-recapture. Likelihood-based methods provide estimates for data from multi-catch traps or from devices that record presence without restricting animal movement (''proximity'' detectors such as camera traps and hair snags). As originally proposed, these methods require multiple sampling intervals. We show that equally precise and unbiased estimates may be obtained from a single sampling interval, using only the spatial pattern of detections. This considerably extends the range of possible applications, and we illustrate the potential by estimating density from simulated detections of bird vocalizations on a microphone array. Acoustic detection can be defined as occurring when received signal strength exceeds a threshold. We suggest detection models for binary acoustic data, and for continuous data comprising measurements of all signals above the threshold. While binary data are often sufficient for density estimation, modeling signal strength improves precision when the microphone array is small.

Mark-recapture models applied to double-observer distance sampling data neglect the information on relative detectability of objects contained in the distribution of observed distances. A difference between the observed distribution and that predicted by the mark-recapture model is symptomatic of a failure of the assumption of zero correlation between detection probabilities implicit in the mark-recapture model. We develop a mark-recapture-based model that uses the observed distribution to relax this assumption to zero correlation at only one distance. We demonstrate its usefulness in coping with unmodeled heterogeneity using data from an aerial survey of crabeater seals in the Antarctic.

Summary1. Acoustic monitoring can be an efficient, cheap, non-invasive alternative to physical trapping of individuals. Spatially explicit capture-recapture (SECR) methods have been proposed to estimate calling animal abundance and density from data collected by a fixed array of microphones. However, these methods make some assumptions that are unlikely to hold in many situations, and the consequences of violating these are yet to be investigated. 2. We generalize existing acoustic SECR methodology, enabling these methods to be used in a much wider variety of situations. We incorporate time-of-arrival (TOA) data collected by the microphone array, increasing the precision of calling animal density estimates. We use our method to estimate calling male density of the Cape Peninsula Moss Frog Arthroleptella lightfooti. 3. Our method gives rise to an estimator of calling animal density that has negligible bias, and 95% confidence intervals with appropriate coverage. We show that using TOA information can substantially improve estimate precision. 4. Our analysis of the A. lightfooti data provides the first statistically rigorous estimate of calling male density for an anuran population using a microphone array. This method fills a methodological gap in the monitoring of frog populations and is applicable to acoustic monitoring of other species that call or vocalize.