1.Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance.2.We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use.3.Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated.4.A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance.5.All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap.6.Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software.7.Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of-the-art software that implements these methods is described that makes the methods accessible to practising ecologists.

Within their circumpolar range, polar bears (Ursus maritimus) are not subject to absolute barriers. However, physiographic features do cause discontinuities in their movements. These discontinuities in distribution can be used to delineate population units. Based on satellite telemetry of the movements of female polar bears carried out in 1989–1998, we used cluster analysis to identify 6 regions within the Canadian and western Greenland Arctic in which movements appear to be restricted enough to identify distinct populations. These regions generally correspond to management units that have been previously identified as Viscount Melville Sound, Lancaster Sound, Norwegian Bay, Kane Basin, Baffin Bay, and Davis Strait. A north–south substructure was identified for the Baffin Bay population, but it was weaker than the structure identified for the 6 primary units. The 6 units were consistent with genetic information, except for the Baffin Bay – Kane Basin separation, and with mark–recapture observations and the traditional knowledge of Inuit hunters. Only 2 of 65 bears that provided telemetry information for more than 1 year were classified in different populations in different years. However, annual rates of exchange, measured as the percentage of locations outside the population boundary, ranged from 0.4 to 8.9%. Analysis of mark–recapture movements indicated no difference in large-scale movements between the sexes or long-term movements with age. Although our validation criteria for demographic closure were satisfied, the observed rates of exchange between adjacent populations suggest that population dynamics in adjacent populations may not be completely independent.

Pitcher. 2011. Cohort effects and spatial variation in age-specific survival of Steller sea lions from southeastern Alaska.Ecosphere 2(10):111. doi:10.1890/ES11-00215.1Abstract. Information concerning mechanistic processes underlying changes in vital rates and ultimately population growth rate is required to monitor impacts of environmental change on wildlife. We estimated age-specific survival and examined factors influencing survival for a threatened population of Steller sea lions (Eumetopias jubatus) in southeastern Alaska. We used mark-recapture models and data from 1,995 individuals marked at approximately one month of age at four of five rookeries in southeastern Alaska, and resighted from Oregon to the Bering Sea. Average annual survival probability for females was 0.64 for pups and 0.77 for yearlings, and increased from 0.91 to 0.96 from age 3-7 yrs. Annual survival probability of males averaged 0.60 for pups and 0.88 by 7 yrs, resulting in probability of survival to age 7, 33% lower for males compared to females. Pups from northern southeastern Alaska (including an area of low summer population size but rapid growth) were twice as likely to survive to age 7 compared to pups from southern rookeries (including a large, historical, stable rookery). Effects of early conditions on future fitness were observed as (1) environmental conditions in the birth year equally affected first-and secondyear survival, and (2) effects of body mass at approximately one month of age were still apparent at 7 yrs. Survival from 0-2 yrs varied among five cohorts by a maximum absolute difference of 0.12. We observed survival costs for long-distance dispersal for males, particularly as juveniles. However, survival was higher for non-pups that dispersed to northern southeastern Alaska, suggesting that moving to an area with greater productivity, greater safety, or lower population size may alleviate a poor start and provide a mechanism for spatial structure for sea lion populations.

Summary 1.We describe an open-source R package, marked, for analysis of mark-recapture data to estimate survival and animal abundance. 2. Currently, marked is capable of fitting Cormack-Jolly-Seber (CJS) and Jolly-Seber models with maximum likelihood estimation (MLE) and CJS models with Bayesian Markov Chain Monte Carlo methods. The CJS models can be fitted with MLE using optimization code in R or with Automatic Differentiation Model Builder. The latter allows incorporation of random effects. 3. Some package features include: (i) individual-specific time intervals between sampling occasions, (ii) generation of optimization starting values from generalized linear model approximations and (iii) prediction of demographic parameters associated with unique combinations of individual and time-specific covariates. 4. We demonstrate marked with a commonly analysed European dipper (Cinclus cinclus) data set. 5. The package will be most useful to ecologists with large mark-recapture data sets and many individual covariates.

ABSTRACT. We estimated demographic parameters and harvest risks for a population of polar bears (Ursus maritimus) inhabiting Baffin Bay, Canada and Greenland, from 1974 to 1997. Our demographic analysis included a detailed assessment of age-and sex-specific survival and recruitment from 1221 marked polar bears, which used information contained within the standing age distribution of captures and mark-recapture analysis performed with Program MARK. Unharvested (natural) survival rates for females (± 1 SE) from mark-recapture analysis were 0.620 ± 0.095 (cubs), 0.938 ± 0.042 (ages 1 -4), 0.953 ± 0.020 (ages 5 -20), and 0.919 ± 0.046 (ages 21+). Total (harvested) survival rates for females were reduced to 0.600 ± 0.096 (cubs), 0.901 ± 0.045 (ages 1 -4), 0.940 ± 0.021 (ages 5-20), and 0.913 ± 0.047 (ages 21+). Mean litter size was 1.59 ± 0.07 cubs, with a mean reproductive interval of 2.5 ± 0.01 years. By age 5, on average 0.88 ± 0.40 of females were producing litters. We estimated the geometric means (± bootstrapped SDs) for population growth rates at stable age distribution as 1.055 ± 0.011 (unharvested) and 1.019 ± 0.015 (harvested). The model-averaged, mark-recapture estimate of mean abundance (± 1 SE) for years 1994 -97 was 2074 ± 266 bears, which included 1017 ± 192 females and 1057 ± 124 males. We incorporated demographic parameters and their error terms into a harvest risk analysis designed to consider demographic, process, and sampling uncertainty in generating likelihoods of persistence (i.e., a stochastic, harvest-explicit population viability analysis). Using our estimated harvest of polar bears in Baffin Bay (88 bears/yr), the probability that the population would decline no more than could be recovered in five years was 0.95, suggesting that the current hunt is sustainable.Key words: demography, harvest, mark-recapture, polar bear, Ursus maritimus, population viability analysis, program MARK, recruitment, survival RÉSUMÉ. De 1974 à 1997, on a évalué les paramètres démographiques d'une population d'ours polaires (Ursus maritimus) habitant la baie de Baffin (Canada et Groenland), ainsi que les risques associés à leur prélèvement. Notre analyse démographique comprenait un bilan détaillé de la survie et du recrutement par âge et par sexe, bilan mené sur 1221 ours polaires étiquetés et qui faisait appel à l'information contenue dans les limites de la structure d'âge des captures à un moment précis, ainsi que des analyses de marquage-recapture réalisées avec le logiciel MARK. Les taux de survie sans prélèvements (c'est-à-dire naturels) des femelles (± 1 erreur-type) tirés de l'analyse de marquage-recapture étaient les suivants: 0,620 ± 0,095 (oursons), 0,938 ± 0,042 (1 -4 ans), 0,953 ± 0,020 (5-20 ans) et 0,919 ± 0,046 (21 ans et plus). Les taux de survie globaux (avec prélèvements) des femelles diminuaient à: 0,600 ± 0,096 (oursons), 0,901 ± 0,045 (1 -4 ans), 0,940 ± 0,021 (5-20 ans) et 0,913 ± 0,047 (21 ans et plus). La taille moyenne des portées était de 1,59 ± 0,07 ourson avec des intervalles moyens de r...

S Su ur rv ve ey ys s o of f b be el lu ug ga as s a an nd d n na ar rw wh ha al ls s i in n t th he e C Ca an na ad di ia an n H Hi ig gh h A Ar rc ct ti ic c i in n 1 19 99 96 6 A AB BS ST TR RA AC CT TThe summer range of belugas (Delphinapterus leucas) and narwhals (Monodon monoceros) in Prince Regent Inlet, Barrow Strait and Peel Sound in the Canadian High Arctic was surveyed from 31 July to 3 August 1996 with a visual aerial survey of offshore areas and photographic aerial surveys of concentration areas. The visual survey estimate based on the number of belugas visible to the observers using systematic line transect methods was 10,347 (cv = 0.28). This included corrections for whales that were missed by the observers, observations without distance measurements and an estimate of 1,949 (cv=0.22) belugas from a photographic survey in southern Peel Sound. Using data from belugas tagged with satellite-linked time-depth recorders, the estimate was adjusted for individuals that were diving during the survey which resulted in an estimate of 18,930 belugas (cv = 0.28). Finally, counts of belugas in estuaries, corrected for estuarine surface time, were added to provide a complete estimate of 21,213 belugas (95% CI 10,985 to 32,619). The estimated number of narwhals corrected for sightings that were missed by observers was 16,364 (cv = 0.24). Adjusting this for sightings without distance information and correcting for whales that were submerged produced an estimate of 45,358 narwhals (95% CI 23,397 to 87,932).

Mark–recapture and line-transect sampling procedures both provide estimators for visibility bias in aerial surveys, and have coexisted in the literature for decades. Mark–recapture estimators of abundance tend to be negatively biased in this context as a result of unmodelled heterogeneity. Line-transect sampling can also be negatively biased if detection probability on the line is less than 1.0. Numerous papers have described hybrid approaches using mark–recapture and line transect methods but there have been some subtle but important differences that may not be apparent to the practitioner. We have used wild horse survey data collected in south-eastern Australia and some imaginary data to highlight these subtle differences. We demonstrate the advantage of using the hybrid approach, which uses the strengths of both mark–recapture and line-transect procedures by fitting a detection function (with p(0) = 1) to the line-transect data to estimate the shape of the detection function, and uses a separate detection function for the mark–recapture data to estimate the intercept (p(0)).

Polar bear (Ursus maritimus) numbers in M'Clintock Channel, Nunavut, Canada have decreased significantly since 1972. We used mark–recapture and recovery data collected from 348 marked polar bears from 1972 to 2000 to estimate demographic characteristics and harvest risks of the M'Clintock Channel polar bear population. Total (harvested) survival rates (±1 SE) from mark–recapture analysis were: 0.62 (±0.15) for cubs of the year, 0.90 (±0.04) for subadults (ages 1–4 yr), 0.90 (±0.04) for adult (age ≤5 yr) females, and 0.88 (± 0.04) for adult males. Mean litter size was 1.68 ± 0.15 cubs with a mean reproductive interval of 2.8 ± 0.2 years. By 6 years of age, on average 0.29 ± 0.47 females were producing litters; mean litter production rate for females aged >6 years was 0.93 ± 0.33. We estimated total abundance to average 284 ± 59.3 bears, of which 166.9 ± 35.4 individuals were female and 117.2 ± 26.4 were male. We incorporated our standing age and mark–recapture demographic parameters as input into a harvest risk analysis designed to account for demographic, environmental, and sampling uncertainty. Population growth rate was 0.946 ± 0.038 for the period 1993–1999. A harvest quota not exceeding 3 bears/year is required if the population is to increase in the short term. Slightly higher quota options are available if increased risk and recovery times are accepted by stakeholders.