Estimation of In-Water Density and Abundance of Harbor Seals

Ecologists and managers require accurate population estimates of marine mammals to assess potential anthropogenic threats to these animals. We present estimates of in-water density and abundance of a distinct stock of harbor seals (Phoca vitulina richardii) in Hood Canal, Washington, USA. We used aerial line-transect survey data collected from 2013 to 2016 to directly estimate harbor seal density and abundance in the waters of Hood Canal, a deep-water fjord in the Salish Sea. We estimated a correction factor for trackline detection probability from dive and surface time data gathered from regional seal tagging studies, and applied this factor to correct for seals missed on the trackline during surveys. We applied conventional and multiple covariate line-transect approaches in the analysis. The resulting best estimate of in-water density of harbor seals in the Hood Canal study region was 5.80 seals/km², with an estimated abundance of 2,009 seals. We did not derive a correction factor to account for the number of seals on land (i.e., hauled out). Therefore, these estimates do not reflect total stock size but provide a starting point to evaluate potential influences of anthropogenic activities, particularly those involving underwater noise, on this marine mammal stock. © 2021 The Wildlife Society.     

Methods of estimating marine mammal diets: A review of validation experiments and sources of bias and uncertainty

Diet estimation in marine mammals relies on indirect methods including recovery of prey hard parts from stomachs and feces, quantitative fatty acid signature analysis (QFASA), stable isotope mixing models, and identification of prey DNA in stomach contents and feces. Experimental evidence (9 species/13 studies) shows that digestion strongly influences the proportion and size of otoliths that can be recovered in feces. Number correction factors (NCF) and digestion coefficients have been experimentally determined to reduce the biases in fecal analysis. Correction factors and coefficients have not been determined for diet estimated from stomach contents. QFASA estimates which prey species and amounts must have been eaten to account for the fatty acid composition of the predator. Experimental studies on mammals and seabirds (9 species/10 studies) indicate that accurate estimates of diet can be determined using QFASA. Stable isotope mixing models provide rather coarse taxonomic resolution of diet composition. Prey DNA analysis shows promise as a method to estimate the species composition of diet, but further development and testing is needed to validate its use. Obtaining a representative sample from marine mammal populations is a significant challenge. Therefore, the use of complementary methods is recommended to obtain the most informative results.     

Influence of root structure on root survivorship: an analysis of 18 tree species using a minirhizotron method

Fine root survivorship is an important aspect of root ecology and is known to be influenced by a suite of covariates. However, the relative importance of each covariate on root survivorship is not clear. Here, we used minirhizotron-based data from 18 woody species to evaluate the relative strength of influence on root survivorship by root diameter, branch order, soil depth, and season of root birth, and to examine how the relationship between each covariate and root survivorship differed across species. We extracted hazard ratio estimates for 16 species from published studies that performed Cox proportional hazards regression analysis, and from our own unpublished data for two Chinese temperate tree species. The mean change in hazard ratio (CHR) and corresponding coefficient of variation for each factor were calculated across species. On average, root diameter and season of root birth had stronger effects on root survivorship than branch order and soil depth. However, the effects of season varied with species and were stronger in temperate forests, whereas the influence of diameter and order were relatively consistent across species. These results suggest that root structures such as diameter and branch order should be carefully considered in root classification and sampling, and adding season of birth (particularly in temperate forests) as a covariate in root survivorship analysis should further enhance our ability in achieving a better understanding of root demography and more accurate estimates of root turnover in forests of different climate zones.     

The effect of inappropriate calibration: three case studies in molecular ecology

Time-scales estimated from sequence data play an important role in molecular ecology. They can be used to draw correlations between evolutionary and palaeoclimatic events, to measure the tempo of speciation, and to study the demographic history of an endangered species. In all of these studies, it is paramount to have accurate estimates of time-scales and substitution rates. Molecular ecological studies typically focus on intraspecific data that have evolved on genealogical scales, but often these studies inappropriately employ deep fossil calibrations or canonical substitution rates (e.g., 1% per million years for birds and mammals) for calibrating estimates of divergence times. These approaches can yield misleading estimates of molecular time-scales, with significant impacts on subsequent evolutionary and ecological inferences. We illustrate this calibration problem using three case studies: avian speciation in the late Pleistocene, the demographic history of bowhead whales, and the Pleistocene biogeography of brown bears. For each data set, we compare the date estimates that are obtained using internal and external calibration points. In all three cases, the conclusions are significantly altered by the application of revised, internally-calibrated substitution rates. Collectively, the results emphasise the importance of judicious selection of calibrations for analyses of recent evolutionary events.     

Abundance estimation of long-diving animals using line transect methods

Line transect sampling is one of the most widely used methods for estimating the size of wild animal populations. An assumption in standard line transect sampling is that all the animals on the trackline are detected without fail. This assumption tends to be violated for marine mammals with surfacing/diving behaviors. The detection probability on the trackline is estimated using duplicate sightings from double-platform line transect methods. The double-platform methods, however, are insufficient to estimate the abundance of long-diving animals because these animals can be completely missed while the observers pass. We developed a more flexible hazard probability model that incorporates information on surfacing/diving patterns obtained from telemetry data. The model is based on a stochastic point process and is statistically tractable. A simulation study showed that the new model provides near-unbiased abundance estimates, whereas the traditional hazard rate and hazard probability models produce considerably biased estimates. As an illustration, we applied the model to data on the Baird's beaked whale (Berardius bairdii) in the western North Pacific.     

The adequacy of aging techniques in vertebrates for rapid estimation of population mortality rates from age distributions

As a key parameter in population dynamics, mortality rates are frequently estimated using mark–recapture data, which requires extensive, long‐term data sets. As a potential rapid alternative, we can measure variables correlated to age, allowing the compilation of population age distributions, from which mortality rates can be derived. However, most studies employing such techniques have ignored their inherent inaccuracy and have thereby failed to provide reliable mortality estimates. In this study, we present a general statistical model linking birth rate, mortality rate, and population age distributions. We next assessed the reliability and data needs (i.e., sample size) for estimating mortality rate of eight different aging techniques. The results revealed that for half of the aging techniques, correlations with age varied considerably, translating into highly variable accuracies when used to estimate mortality rate from age distributions. Telomere length is generally not sufficiently correlated to age to provide reliable mortality rate estimates. DNA methylation, signal‐joint T‐cell recombination excision circle (sjTREC), and racemization are generally more promising techniques to ultimately estimate mortality rate, if a sufficiently high sample size is available. Otolith ring counts, otolithometry, and age‐length keys in fish, and skeletochronology in reptiles, mammals, and amphibians, outperformed all other aging techniques and generated relatively accurate mortality rate estimation with a sample size that can be feasibly obtained. Provided the method chosen is minimizing and estimating the error in age estimation, it is possible to accurately estimate mortality rates from age distributions. The method therewith has the potential to estimate a critical, population dynamic parameter to inform conservation efforts within a limited time frame as opposed to mark–recapture analyses.     

neogen: A tool to predict genetic effective population size (Ne) for species with generational overlap and to assist empirical Ne study design

Molecular genetic estimates of population effective size (N_e) lose accuracy and precision when insufficient numbers of samples or loci are used. Ideally, researchers would like to forecast the necessary power when planning their project. neogen (genetic N_e for Overlapping Generations) enables estimates of precision and accuracy in advance of empirical investigation and allows exploration of the power available in different user‐specified age‐structured sampling schemes. neogen provides a population simulation and genetic power analysis framework that simulates the demographics, genetic composition, and N_e, from species‐specific life history, mortality, population size, and genetic priors. neogen guides the user to establish a tractable sampling regime and to determine the numbers of samples and microsatellite or SNP loci required for accurate and precise genetic N_e estimates when sampling a natural population. neogen is useful at multiple stages of a study's life cycle: when budgeting, as sampling and locus development progresses, and for corroboration when empirical N_e estimates are available. The underlying model is applicable to a wide variety of iteroparous species with overlapping generations (e.g., mammals, birds, reptiles, long‐lived fishes). In this paper, we describe the neogen model, detail the workflow for the point‐and‐click software, and explain the graphical results. We demonstrate the use of neogen with empirical Australian east coast zebra shark (Stegostoma fasciatum) data. For researchers wishing to make accurate and precise genetic N_e estimates for overlapping generations species, neogen facilitates planning for sample and locus acquisition, and with existing empirical genetic N_e estimates neogen can corroborate population demographic and life history properties.     

The effects of demographic stochasticity and parameter uncertainty on predicting the establishment of introduced species

Invasive species are a serious threat to biodiversity worldwide and predicting whether an introduced species will first establish and then become invasive can be useful to preserve ecosystem services. Establishment is influenced by multiple factors, such as the interactions between the introduced individuals and the resident community, and demographic and environmental stochasticity. Field observations are often incomplete or biased. This, together with an imperfect knowledge of the ecological traits of the introduced species, makes the prediction of establishment challenging. Methods that consider the combined effects of these factors on our ability to predict the establishment of an introduced species are currently lacking. We develop an inference framework to assess the combined effects of demographic stochasticity and parameter uncertainty on our ability to predict the probability of establishment following the introduction of a small number of individuals. We find that even moderate levels of demographic stochasticity influence both the probability of establishment, and, crucially, our ability to correctly predict that probability. We also find that estimation of the demographic parameters of an introduced species is fundamental to obtain precise estimates of the interaction parameters. For typical values of demographic stochasticity, the drop in our ability to predict an establishment can be 30% when having priors on the demographic parameters compared to having their accurate values. The results from our study illustrate how demographic stochasticity may bias the prediction of the probability of establishment. Our method can be applied to estimate probability of establishment of introduced species in field scenarios, where time series data and prior information on the demographic traits of the introduced species are available.     

Population density and genetic diversity are positively correlated in wild felids globally

Aim

Insights into the biological and evolutionary traits of species, and their ability to cope with global changes, can be gained by studying genetic diversity within species. A cornerstone hypothesis in evolutionary and conservation biology suggests that genetic diversity decreases with decreasing population size, however, population size is difficult to estimate in threatened species with large distribution ranges, and evidence for this is limited to few species. To address this gap, we tested this hypothesis across multiple closely related species at a global scale using population density which is a more accessible measure.

Location

Global.

Time Period

Contemporary.

Major Taxa Studied

Wild felids in their natural habitats.

Methods

We obtained data from published estimates of population density assessed via camera trap and within-population genetic diversity generated from microsatellite markers on 18 felid species across 41 countries from 354 studies. We propose a novel method to standardize population density estimates and to spatially join data using K-means clustering. Linear mixed-effect modelling was applied to account for confounding factors such as body mass, generation length and sample size used for the genetic estimates.

Results

We found a significant positive correlation between population density and genetic diversity, particularly observed heterozygosity and allelic richness. While the confounding factors did not affect the main results, long generation length and large sample size were significantly associated with high genetic diversity. Body mass had no effect on genetic diversity, likely because large-bodied species were over-represented in our data sets.

Main Conclusions

Our study emphasizes how recent demographic processes shape neutral genetic diversity in threatened and small populations where extinction vortex is a risk. Although caution is needed when interpreting the small population density effect in our findings, our methodological framework shows promising potential to identify which populations require actions to conserve maximal genetic variation.     

Using sample aerial surveys to estimate the abundance of the endangered Grevy’s zebra in northern Kenya

The effective management of endangered mammals requires reliable estimates of population size. This is challenging for species such as Grevy’s zebra (Equus grevyi) that are distributed over large areas at low densities. Less than 2500 Grevy’s zebra remain in the wild, scattered across 85,000 km² of savannah in northern Kenya and Ethiopia. An efficient, accurate and repeatable survey method is required to guide conservation planning for the species. Currently, total aerial counts are used to census endangered species within Kenya, but are costly in terms of resources. In this study, we evaluated the suitability of sample survey methods for Grevy’s zebra. We estimated population size using sample aerial counts for a known population of Grevy’s zebra in Lewa Wildlife Conservancy (LWC), providing the opportunity to test the accuracy of sample methods, while comparing resource costs with total count methods. We sampled one‐third of LWC using parallel 500‐ m strip transects at 1500‐ m intervals. The population estimate was comparable to the known population size and was less than half as expensive as the equivalent total count survey. Our results suggest sample aerial surveys provide an accurate and cost‐effective means of monitoring Grevy’s zebra and other endangered species in open habitats.     

Combining capture–recapture data and known ages allows estimation of age‐dependent survival rates

In many animal populations, demographic parameters such as survival and recruitment vary markedly with age, as do parameters related to sampling, such as capture probability. Failing to account for such variation can result in biased estimates of population‐level rates. However, estimating age‐dependent survival rates can be challenging because ages of individuals are rarely known unless tagging is done at birth. For many species, it is possible to infer age based on size. In capture–recapture studies of such species, it is possible to use a growth model to infer the age at first capture of individuals. We show how to build estimates of age‐dependent survival into a capture–mark–recapture model based on data obtained in a capture–recapture study. We first show how estimates of age based on length increments closely match those based on definitive aging methods. In simulated analyses, we show that both individual ages and age‐dependent survival rates estimated from simulated data closely match true values. With our approach, we are able to estimate the age‐specific apparent survival rates of Murray and trout cod in the Murray River, Australia. Our model structure provides a flexible framework within which to investigate various aspects of how survival varies with age and will have extensions within a wide range of ecological studies of animals where age can be estimated based on size.     

Calculation of longevity and life expectancy in captive elephants

The concepts of longevity (longest lived) and life expectancy (typical age at death) are common demographic parameters that provide insight into a population. Defined as the longest lived individual, longevity is easily calculated but is not representative, as only one individual will live to this extreme. Longevity records for North American Asian elephants (Elephas maximus) and African elephants (Loxodonta africana) have not yet been set, as the oldest individuals (77 and 53 years, respectively) are still alive. One Asian elephant lived to 86 years in the Taipei Zoo. This is comparable to the maximum (though not typical) longevity estimated in wild populations. Calculation of life expectancy, however, must use statistics that are appropriate for the data available, the distribution of the data, and the species' biology. Using a simple arithmetic mean to describe the non‐normally distributed age at death for elephant populations underestimates life expectancy. Use of life‐table analysis to estimate median survivorship or survival analysis to estimate average survivorship are more appropriate for the species' biology and the data available, and provide more accurate estimates. Using a life‐table, the median life expectancy for female Asian elephants (Lx=0.50) is 35.9 years in North America and 41.9 years in Europe. Survival analysis estimates of average life expectancy for Asian elephants are 47.6 years in Europe and 44.8 years in North America. Survival analysis estimates for African elephants are less robust due to less data. Currently the African elephant average life expectancy estimate in North America is 33.0 years, but this is likely to increase with more data, as it has over the past 10 years. Zoo Biol 23:365–373, 2004. © 2004 Wiley‐Liss, Inc.     

Runs of homozygosity have utility in mammalian conservation and evolutionary studies

Runs of homozygosity (ROHs) arise due the transmission from parents to offspring of segments that are either identical by decent (IBD) or identical by state (IBS). The former is due to consanguineous matings whereas the latter is due to demographic processes. ROHs reduce individual nucleotide diversity (θ) as a function of homozygosity, and thus ROH distributions and θ are expected to vary among species because inbreeding levels, recombination rates, and demographic histories vary widely. To help interpret genetic diversity within and among species, we utilized genome sequence data from 78 mammalian species to compare θ and ROH burden (i.e., number and length of ROHs in the genome) among groups of mammals to assess genomic signatures of inbreeding. We compared θ and ROHs: (i) among threatened and non-threatened mammals to determine the significance of contemporary conservation status; (ii) among carnivorous and non-carnivorous mammals to determine the relevance of trophic effects; (iii) relative to body size because mutation rates generally vary with body mass; and (iv) across mammals from different latitudes to test for gradients in genomic diversity (e.g., due to effects of historic climatic regimes). Our results illustrate the considerable variance in genomic diversity across mammals, and that trophic level, body mass, and latitude have significant effects on θ and ROH burden. However, conservation status was not a reliable indicator of genomic diversity. We argue that genetic or genomic diversity should be an explicit component of conservation status, as such diversity is critical to the long-term sustainability of populations, and anticipate that ROHs will become more commonly used to estimate inbreeding in wild animals.     

Effects of Telemetry Location Error on Space-Use Estimates Using a Fixed-Kernel Density Estimator

ABSTRACT Fixed-kernel density estimates using radiotelemetry locations are frequently used to quantify home ranges of animals, interactions, and resource selection. However, all telemetry data have location error and no studies have reported the effects of error on utilization distribution and area estimates using fixed-kernel density estimators. We simulated different home range sizes and shapes by mixing bivariate-normal distributions and then drawing random samples of various sizes from these distributions. We compared fixed-kernel density estimates with and without error to the true underlying distributions. The effects of telemetry error on fixed-kernel density estimates were related to sample size, distribution complexity, and ratio of median Circular Error Probable to home range size. We suggest a metric to assess the adequacy of the telemetry system being used to estimate an animal's space use before a study is undertaken. Telemetry location error is unlikely to significantly affect fixed-kernel density estimates for most wildlife telemetry studies with adequate sample sizes.     

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.     

Do Insect Populations Die at Constant Rates as They Become Older? Contrasting Demographic Failure Kinetics with Respect to Temperature According to the Weibull Model

Temperature implies contrasting biological causes of demographic aging in poikilotherms. In this work, we used the reliability theory to describe the consistency of mortality with age in moth populations and to show that differentiation in hazard rates is related to extrinsic environmental causes such as temperature. Moreover, experiments that manipulate extrinsic mortality were used to distinguish temperature-related death rates and the pertinence of the Weibull aging model. The Newton-Raphson optimization method was applied to calculate parameters for small samples of ages at death by estimating the maximum likelihoods surfaces using scored gradient vectors and the Hessian matrix. The study reveals for the first time that the Weibull function is able to describe contrasting biological causes of demographic aging for moth populations maintained at different temperature regimes. We demonstrate that at favourable conditions the insect death rate accelerates as age advances, in contrast to the extreme temperatures in which each individual drifts toward death in a linear fashion and has a constant chance of passing away. Moreover, slope of hazard rates shifts towards a constant initial rate which is a pattern demonstrated by systems which are not wearing out (e.g. non-aging) since the failure, or death, is a random event independent of time. This finding may appear surprising, because, traditionally, it was mostly thought as rule that in aging population force of mortality increases exponentially until all individuals have died. Moreover, in relation to other studies, we have not observed any typical decelerating aging patterns at late life (mortality leveling-off), but rather, accelerated hazard rates at optimum temperatures and a stabilized increase at the extremes.In most cases, the increase in aging-related mortality was simulated reasonably well according to the Weibull survivorship model that is applied. Moreover, semi log- probability hazard rate model illustrations and maximum likelihoods may be usefully in defining periods of mortality leveling off and provide clear evidence that environmental variability may affect parameter estimates and insect population failure rate. From a reliability theory standpoint, failure rates vary according to a linear function of age at the extremes indicating that the life system (i.e., population) is able to eliminate earlier failure and/or to keep later failure rates constant. The applied model was able to identify the major correlates of extended longevity and to suggest new ideas for using demographic concepts in both basic and applied population biology and aging.     

Assessing the impact of bycatch on dolphin populations: the case of the common dolphin in the eastern North Atlantic

Fisheries interactions have been implicated in the decline of many marine vertebrates worldwide. In the eastern North Atlantic, at least 1000 common dolphins (Delphinus delphis) are bycaught each year, particularly in pelagic pair-trawls. We have assessed the resulting impact of bycatch on this population using a demographic modeling approach. We relied on a sample of females stranded along the French Atlantic and western Channel coasts. Strandings represent an extensive source of demographic information to monitor our study population. Necropsy analysis provided an estimate of individual age and reproductive state. Then we estimated effective survivorship (including natural and human-induced mortality), age at first reproduction and pregnancy rates. Reproductive parameters were consistent with literature, but effective survivorship was unexpectedly low. Demographic parameters were then used as inputs in two models. A constant parameter matrix proposed an effective growth rate of -5.5±0.5%, corresponding to the current situation (including bycatch mortality). Subsequently, deterministic projections suggested that the population would be reduced to 20% of its current size in 30 years and would be extinct in 100 years. The demographic invariant model suggested a maximum growth rate of +4.5±0.09%, corresponding to the optimal demographic situation. Then, a risk analysis incorporating Potential Biological Removal (PBR), based on two plausible scenarii for stock structure suggested that bycatch level was unsustainable for the neritic population of the Bay of Biscay under a two-stock scenario. In depth assessment of stock structure and improved observer programs to provide scientifically robust bycatch estimates are needed. Effective conservation measures would be reducing bycatch to less than 50% of the current level in the neritic stock to reach PBR. Our approach provided indicators of the status and trajectory of the common dolphin population in the eastern North Atlantic and therefore proved to be a valuable tool for management, applicable to other dolphin populations.     

Estimating the spatial position of marine mammals based on digital camera recordings

Estimating the spatial position of organisms is essential to quantify interactions between the organism and the characteristics of its surroundings, for example, predator–prey interactions, habitat selection, and social associations. Because marine mammals spend most of their time under water and may appear at the surface only briefly, determining their exact geographic location can be challenging. Here, we developed a photogrammetric method to accurately estimate the spatial position of marine mammals or birds at the sea surface. Digital recordings containing landscape features with known geographic coordinates can be used to estimate the distance and bearing of each sighting relative to the observation point. The method can correct for frame rotation, estimates pixel size based on the reference points, and can be applied to scenarios with and without a visible horizon. A set of R functions was written to process the images and obtain accurate geographic coordinates for each sighting. The method is applied to estimate the spatiotemporal fine‐scale distribution of harbour porpoises in a tidal inlet. Video recordings of harbour porpoises were made from land, using a standard digital single‐lens reflex (DSLR) camera, positioned at a height of 9.59 m above mean sea level. Porpoises were detected up to a distance of ~3136 m (mean 596 m), with a mean location error of 12 m. The method presented here allows for multiple detections of different individuals within a single video frame and for tracking movements of individuals based on repeated sightings. In comparison with traditional methods, this method only requires a digital camera to provide accurate location estimates. It especially has great potential in regions with ample data on local (a)biotic conditions, to help resolve functional mechanisms underlying habitat selection and other behaviors in marine mammals in coastal areas.     

A simulation approach to assessing environmental risk of sound exposure to marine mammals

Intense underwater sounds caused by military sonar, seismic surveys, and pile driving can harm acoustically sensitive marine mammals. Many jurisdictions require such activities to undergo marine mammal impact assessments to guide mitigation. However, the ability to assess impacts in a rigorous, quantitative way is hindered by large knowledge gaps concerning hearing ability, sensitivity, and behavioral responses to noise exposure. We describe a simulation‐based framework, called SAFESIMM (Statistical Algorithms For Estimating the Sonar Influence on Marine Megafauna), that can be used to calculate the numbers of agents (animals) likely to be affected by intense underwater sounds. We illustrate the simulation framework using two species that are likely to be affected by marine renewable energy developments in UK waters: gray seal (Halichoerus grypus) and harbor porpoise (Phocoena phocoena). We investigate three sources of uncertainty: How sound energy is perceived by agents with differing hearing abilities; how agents move in response to noise (i.e., the strength and directionality of their evasive movements); and the way in which these responses may interact with longer term constraints on agent movement. The estimate of received sound exposure level (SEL) is influenced most strongly by the weighting function used to account for the specie's presumed hearing ability. Strongly directional movement away from the sound source can cause modest reductions (~5 dB) in SEL over the short term (periods of less than 10 days). Beyond 10 days, the way in which agents respond to noise exposure has little or no effect on SEL, unless their movements are constrained by natural boundaries. Most experimental studies of noise impacts have been short‐term. However, data are needed on long‐term effects because uncertainty about predicted SELs accumulates over time. Synthesis and applications. Simulation frameworks offer a powerful way to explore, understand, and estimate effects of cumulative sound exposure on marine mammals and to quantify associated levels of uncertainty. However, they can often require subjective decisions that have important consequences for management recommendations, and the basis for these decisions must be clearly described.