Recommended snapshot length for acoustic point-transect surveys of intermittently available Cuvier's beaked whales.

Acoustic point-transect distance-sampling surveys have recently been used to estimate the density of beaked whales. Typically, the fraction of short time "snapshots" with detected beaked whales is used in this calculation. Beaked whale echolocation pulses are only intermittently available, which may affect the best choice of snapshot length. The effect of snapshot length on density estimation for Cuvier's beaked whale (Ziphius cavirostris) is investigated by sub-setting continuous recordings from drifting hydrophones deployed off southern and central California. Snapshot lengths from 20 s to 20 min are superimposed on the time series of detected beaked whale echolocation pulses, and the components of the density estimation equation are estimated for each snapshot length. The fraction of snapshots with detections, the effective area surveyed, and the snapshot detection probability all increase with snapshot length. Due to compensatory changes in these three components, density estimates show very little dependence on snapshot length. Within the range we examined, 1-2 min snapshots are recommended to avoid the potential bias caused by animal movement during the snapshot period and to maximize the sample size for estimating the effective area surveyed.

Detection and classification of narrow-band high frequency echolocation clicks from drifting recorders.

In the California Current off the United States West Coast, there are three offshore cetacean species that produce narrow-band high frequency (NBHF) echolocation pulses: Dall's porpoise (Phocoenoides dalli) and two species of Kogia. NBHF pulses exist in a highly specialized acoustic niche thought to be outside the hearing range of killer whales and other potential mammal-eating odontocetes. Very little is known about the dwarf and pygmy sperm whales (K. sima and K. breviceps), including their NBHF pulse characteristics. This paper presents a multivariate clustering method using data from unmanned drifting acoustic recorders and visually verified porpoise recordings to discriminate between probable porpoise and Kogia clicks. Using density clustering, this study finds three distinct clusters whose geographic distributions are consistent with the known habitat range for Kogia and Dall's porpoise. A Random Forest classification model correctly assigned 97% of the clicks to their cluster. Visually verified Dall's porpoise clicks from towed hydrophones were strongly associated with one of the clusters, while a second cluster tended to be outside the geographic range of Dall's porpoise and unlike the Dall's porpoise cluster. These clicks, presumed to be made by Kogia, exhibited greater spectral variance than previous Kogia echolocation studies. It is possible that the structure of Kogia NBHF pulses may not be as stereotypical as previously described.

Integrating population dynamics models and distance sampling data: a spatial hierarchical state-space approach.

Stochastic versions of Gompertz, Ricker, and various other dynamics models play a fundamental role in quantifying strength of density dependence and studying long-term dynamics of wildlife populations. These models are frequently estimated using time series of abundance estimates that are inevitably subject to observation error and missing data. This issue can be addressed with a state-space modeling framework that jointly estimates the observed data model and the underlying stochastic population dynamics (SPD) model. In cases where abundance data are from multiple locations with a smaller spatial resolution (e.g., from mark-recapture and distance sampling studies), models are conventionally fitted to spatially pooled estimates of yearly abundances. Here, we demonstrate that a spatial version of SPD models can be directly estimated from short time series of spatially referenced distance sampling data in a unified hierarchical state-space modeling framework that also allows for spatial variance (covariance) in population growth. We also show that a full range of likelihood based inference, including estimability diagnostics and model selection, is feasible in this class of models using a data cloning algorithm. We further show through simulation experiments that the hierarchical state-space framework introduced herein efficiently captures the underlying dynamical parameters and spatial abundance distribution. We apply our methodology by analyzing a time series of line-transect distance sampling data for fin whales (Balaenoptera physalus) off the U.S. west coast. Although there were only seven surveys conducted during the study time frame, 1991-2014, our analysis detected presence of strong density regulation and provided reliable estimates of fin whale densities. In summary, we show that the integrative framework developed herein allows ecologists to better infer key population characteristics such as presence of density regulation and spatial variability in a population's intrinsic growth potential.

Improved estimation of intrinsic growth r(max) for long-lived species: integrating matrix models and allometry.

Intrinsic population growth rate (r(max)) is an important parameter for many ecological applications, such as population risk assessment and harvest management. However, r(max) can be a difficult parameter to estimate, particularly for long-lived species, for which appropriate life table data or abundance time series are typically not obtainable. We describe a method for improving estimates of r(max) for long-lived species by integrating life-history theory (allometric models) and population-specific demographic data (life table models). Broad allometric relationships, such as those between life history traits and body size, have long been recognized by ecologists. These relationships are useful for deriving theoretical expectations for r(max), but r(max) for real populations may vary from simple allometric estimators for "archetypical" species of a given taxa or body mass. Meanwhile, life table approaches can provide population-specific estimates of r(max) from empirical data, but these may have poor precision from imprecise and missing vital rate parameter estimates. Our method borrows strength from both approaches to provide estimates that are consistent with both life-history theory and population-specific empirical data, and are likely to be more robust than estimates provided by either method alone. Our method uses an' allometric constant: the product of r(max) and the associated generation time for a stable-age population growing at this rate. We conducted a meta-analysis to estimate the mean and variance of this allometric constant across well-studied populations from three vertebrate taxa (birds, mammals, and elasmobranchs) and found that the mean was approximately 1.0 for each taxon. We used these as informative Bayesian priors that determine how much to "shrink" imprecise vital rate estimates for a data-limited population toward the allometric expectation. The approach ultimately provides estimates of r(max) (and other vital rates) that reflect a balance of information from the individual studied population, theoretical expectation, and meta-analysis of other populations. We applied the method specifically to an archetypical petrel (representing the genus Procellaria) and to white sharks (Carcharodon carcharias) in the context of estimating sustainable-fishery bycatch limits.

Estimating Limit Reference Points for Western Pacific Leatherback Turtles (Dermochelys coriacea) in the U.S. West Coast EEZ.

Biological limit reference points (LRPs) for fisheries catch represent upper bounds that avoid undesirable population states. LRPs can support consistent management evaluation among species and regions, and can advance ecosystem-based fisheries management. For transboundary species, LRPs prorated by local abundance can inform local management decisions when international coordination is lacking. We estimated LRPs for western Pacific leatherbacks in the U.S. West Coast Exclusive Economic Zone (WCEEZ) using three approaches with different types of information on local abundance. For the current application, the best-informed LRP used a local abundance estimate derived from nest counts, vital rate information, satellite tag data, and fishery observer data, and was calculated with a Potential Biological Removal estimator. Management strategy evaluation was used to set tuning parameters of the LRP estimators to satisfy risk tolerances for falling below population thresholds, and to evaluate sensitivity of population outcomes to bias in key inputs. We estimated local LRPs consistent with three hypothetical management objectives: allowing the population to rebuild to its maximum net productivity level (4.7 turtles per five years), limiting delay of population rebuilding (0.8 turtles per five years), or only preventing further decline (7.7 turtles per five years). These LRPs pertain to all human-caused removals and represent the WCEEZ contribution to meeting population management objectives within a broader international cooperative framework. We present multi-year estimates, because at low LRP values, annual assessments are prone to substantial error that can lead to volatile and costly management without providing further conservation benefit. The novel approach and the performance criteria used here are not a direct expression of the "jeopardy" standard of the U.S. Endangered Species Act, but they provide useful assessment information and could help guide international management frameworks. Given the range of abundance data scenarios addressed, LRPs should be estimable for many other areas, populations, and taxa.

Bayesian inference and assessment for rare-event bycatch in marine fisheries: a drift gillnet fishery case study.

Fisheries bycatch is a global threat to marine megafauna. Environmental laws require bycatch assessment for protected species, but this is difficult when bycatch is rare. Low bycatch rates, combined with low observer coverage, may lead to biased, imprecise estimates when using standard ratio estimators. Bayesian model-based approaches incorporate uncertainty, produce less volatile estimates, and enable probabilistic evaluation of estimates relative to management thresholds. Here, we demonstrate a pragmatic decision-making process that uses Bayesian model-based inferences to estimate the probability of exceeding management thresholds for bycatch in fisheries with < 100% observer coverage. Using the California drift gillnet fishery as a case study, we (1) model rates of rare-event bycatch and mortality using Bayesian Markov chain Monte Carlo estimation methods and 20 years of observer data; (2) predict unobserved counts of bycatch and mortality; (3) infer expected annual mortality; (4) determine probabilities of mortality exceeding regulatory thresholds; and (5) classify the fishery as having low, medium, or high bycatch impact using those probabilities. We focused on leatherback sea turtles (Dermochelys coriacea) and humpback whales (Megaptera novaeangliae). Candidate models included Poisson or zero-inflated Poisson likelihood, fishing effort, and a bycatch rate that varied with area, time, or regulatory regime. Regulatory regime had the strongest effect on leatherback bycatch, with the highest levels occurring prior to a regulatory change. Area had the strongest effect on humpback bycatch. Cumulative bycatch estimates for the 20-year period were 104-242 leatherbacks (52-153 deaths) and 6-50 humpbacks (0-21 deaths). The probability of exceeding a regulatory threshold under the U.S. Marine Mammal Protection Act (Potential Biological Removal, PBR) of 0.113 humpback deaths was 0.58, warranting a "medium bycatch impact" classification of the fishery. No PBR thresholds exist for leatherbacks, but the probability of exceeding an anticipated level of two deaths per year, stated as part of a U.S. Endangered Species Act assessment process, was 0.0007. The approach demonstrated here would allow managers to objectively and probabilistically classify fisheries with respect to bycatch impacts on species that have population-relevant mortality reference points, and declare with a stipulated level of certainty that bycatch did or did not exceed estimated upper bounds.

Global patterns of marine mammal, seabird, and sea turtle bycatch reveal taxa-specific and cumulative megafauna hotspots.

Recent research on ocean health has found large predator abundance to be a key element of ocean condition. Fisheries can impact large predator abundance directly through targeted capture and indirectly through incidental capture of nontarget species or bycatch. However, measures of the global nature of bycatch are lacking for air-breathing megafauna. We fill this knowledge gap and present a synoptic global assessment of the distribution and intensity of bycatch of seabirds, marine mammals, and sea turtles based on empirical data from the three most commonly used types of fishing gears worldwide. We identify taxa-specific hotspots of bycatch intensity and find evidence of cumulative impacts across fishing fleets and gears. This global map of bycatch illustrates where data are particularly scarce--in coastal and small-scale fisheries and ocean regions that support developed industrial fisheries and millions of small-scale fishers--and identifies fishing areas where, given the evidence of cumulative hotspots across gear and taxa, traditional species or gear-specific bycatch management and mitigation efforts may be necessary but not sufficient. Given the global distribution of bycatch and the mitigation success achieved by some fleets, the reduction of air-breathing megafauna bycatch is both an urgent and achievable conservation priority.

Declining abundance of beaked whales (family Ziphiidae) in the California Current large marine ecosystem.

Beaked whales are among the most diverse yet least understood groups of marine mammals. A diverse set of mostly anthropogenic threats necessitates improvement in our ability to assess population status for this cryptic group. The Southwest Fisheries Science Center (NOAA) conducted six ship line-transect cetacean abundance surveys in the California Current off the contiguous western United States between 1991 and 2008. We used a Bayesian hidden-process modeling approach to estimate abundance and population trends of beaked whales using sightings data from these surveys. We also compiled records of beaked whale stranding events (3 genera, at least 8 species) on adjacent beaches from 1900 to 2012, to help assess population status of beaked whales in the northern part of the California Current. Bayesian posterior summaries for trend parameters provide strong evidence of declining beaked whale abundance in the study area. The probability of negative trend for Cuvier's beaked whale (Ziphius cavirostris) during 1991-2008 was 0.84, with 1991 and 2008 estimates of 10771 (CV = 0.51) and ≈7550 (CV = 0.55), respectively. The probability of decline for Mesoplodon spp. (pooled across species) was 0.96, with 1991 and 2008 estimates of 2206 (CV = 0.46) and 811 (CV = 0.65). The mean posterior estimates for average rate of decline were 2.9% and 7.0% per year. There was no evidence of abundance trend for Baird's beaked whale (Berardius bairdii), for which annual abundance estimates in the survey area ranged from ≈900 to 1300 (CV≈1.3). Stranding data were consistent with the survey results. Causes of apparent declines are unknown. Direct impacts of fisheries (bycatch) can be ruled out, but impacts of anthropogenic sound (e.g., naval active sonar) and ecosystem change are plausible hypotheses that merit investigation.

Dynamic habitat models: using telemetry data to project fisheries bycatch.

Fisheries bycatch is a recognized threat to marine megafauna. Addressing bycatch of pelagic species however is challenging owing to the dynamic nature of marine environments and vagility of these organisms. In order to assess the potential for species to overlap with fisheries, we propose applying dynamic habitat models to determine relative probabilities of species occurrence for specific oceanographic conditions. We demonstrate this approach by modelling habitats for Laysan (Phoebastria immutabilis) and black-footed albatrosses (Phoebastria nigripes) using telemetry data and relating their occurrence probabilities to observations of Hawaii-based longline fisheries in 1997-2000. We found that modelled habitat preference probabilities of black-footed albatrosses were high within some areas of the fishing range of the Hawaiian fleet and such preferences were important in explaining bycatch occurrence. Conversely, modelled habitats of Laysan albatrosses overlapped little with Hawaii-based longline fisheries and did little to explain the bycatch of this species. Estimated patterns of albatross habitat overlap with the Hawaiian fleet corresponded to bycatch observations: black-footed albatrosses were more frequently caught in this fishery despite being 10 times less abundant than Laysan albatrosses. This case study demonstrates that dynamic habitat models based on telemetry data may help to project interactions with pelagic animals relative to environmental features and that such an approach can serve as a tool to guide conservation and management decisions.

Fire drives transcontinental variation in tree birch defense against browsing by snowshoe hares.

Fire has been the dominant disturbance in boreal America since the Pleistocene, resulting in a spatial mosaic in which the most fire occurs in the continental northwest. Spatial variation in snowshoe hare (Lepus americanus) density reflects the fire mosaic. Because fire initiates secondary forest succession, a fire mosaic creates variation in the abundance of early successional plants that snowshoe hares eat in winter, leading to geographic variation in hare density. We hypothesize that fire is the template for a geographic mosaic of natural selection: where fire is greatest and hares are most abundant, hare browsing has most strongly selected juvenile-phase woody plants for defense. We tested the hypothesis at multiple spatial scales using Alaska birch (Betula neoalaskana) and white birch (Betula papyrifera). We also examined five alternative hypotheses for geographic variation in antibrowsing defense. The fire-hare-defense hypothesis was supported at transcontinental, regional, and local scales; alternative hypotheses were rejected. Our results link transcontinental variation in species interactions to an abiotic environmental driver, fire. Intakes of defense toxins by Alaskan hares exceed those by Wisconsin hares, suggesting that the proposed selection mosaic may coincide with a geographic mosaic of coevolution.

Modeling loggerhead turtle movement in the Mediterranean: importance of body size and oceanography.

Adapting state-space models (SSMs) to telemetry data has been helpful for dealing with location error and for modeling animal movements. We used a combination of two hierarchical Bayesian SSMs to estimate movement pathways from Argos satellite-tag data for 15 juvenile loggerhead turtles (Caretta caretta) in the western Mediterranean Sea, and to probabilistically assign locations to one of two behavioral movement types and relate those behaviors to environmental features. A Monte Carlo procedure helped propagate location uncertainty from the first SSM into the estimation of behavioral states and environment--behavior relationships in the second SSM. Turtles using oceanic habitats of the Balearic Sea (n = 9 turtles) within the western Mediterranean were more likely to exhibit "intensive search" behavior as might occur during foraging, but only larger turtles responded to variations in sea-surface height. This suggests that they were better able than smaller turtles to cue on environmental features that concentrate prey resources or were more dependent on high-quality feeding areas. These findings stress the importance of individual heterogeneity in the analysis of movement behavior and, taken in concert with descriptive studies of Pacific loggerheads, suggest that directed movements toward patchy ephemeral resources may be a general property of larger juvenile loggerheads in different populations. We discovered size-based variation in loggerhead distribution and documented use of the western Mediterranean Sea by turtles larger than previously thought to occur there. With one exception, only individuals > 57 cm curved carapace length used the most westerly basin in the Mediterranean (western Alborán Sea). These observations shed new light on loggerhead migration phenology.

A Bayesian uncertainty analysis of cetacean demography and bycatch mortality using age-at-death data.

Wildlife ecologists and managers are challenged to make the most of sparse information for understanding demography of many species, especially those that are long lived and difficult to observe. For many odontocete (dolphin, porpoise, toothed whale) populations, only fertility and age-at-death data are feasibly obtainable. We describe a Bayesian approach for using fertilities and two types of age-at-death data (i.e., age structure of deaths from all mortality sources and age structure of anthropogenic mortalities only) to estimate rate of increase, mortality rates, and impacts of anthropogenic mortality on those rates for a population assumed to be in a stable age structure. We used strandings data from 1977 to 1993 (n = 96) and observer bycatch data from 1989 to 1993 (n = 233) for the Gulf of Maine, USA, and Bay of Fundy, Canada, harbor porpoise (Phocoena phocoena) population as a case study. Our method combines mortality risk functions to estimate parameters describing age-specific natural and bycatch mortality rates. Separate functions are simultaneously fit to bycatch and strandings data, the latter of which are described as a mixture of natural and bycatch mortalities. Euler-Lotka equations and an estimate of longevity were used to constrain parameter estimates, and we included a parameter to account for unequal probabilities of natural vs. bycatch deaths occurring in a sample. We fit models under two scenarios intended to correct for possible data bias due to indirect bycatch of calves (i.e., death following bycatch mortality of mothers) being underrepresented in the bycatch sample. Results from the two scenarios were "model averaged" by sampling from both Markov Chain Monte Carlo (MCMC) chains with uniform probability. The median estimate for potential population growth (r(nat)) was 0.046 (90% credible interval [CRI] = 0.004-0.116). The median for actual growth (r) was -0.030 (90% CRI = -0.192 to +0.065). The probability of population decline due to added fisheries mortality, prior to management to reduce bycatch, was 0.690. Our approach takes into account multiple sources of uncertainty in data and process, and it provides posterior distributions for a rich set of demographic rate parameters that are unknown for most cetaceans. This method should be easily adaptable to other taxa for which fertility and age-at-death data are available.

Determinants of seed removal distance by scatter-hoarding rodents in deciduous forests.

Scatter-hoarding rodents should space food caches to maximize cache recovery rate (to minimize loss to pilferers) relative to the energetic cost of carrying food items greater distances. Optimization models of cache spacing make two predictions. First, spacing of caches should be greater for food items with greater energy content. Second, the mean distance between caches should increase with food abundance. However, the latter prediction fails to account for the effect of food abundance on the behavior of potential pilferers or on the ability of caching individuals to acquire food by means other than recovering their own caches. When considering these factors, shorter cache distances may be predicted in conditions of higher food abundance. We predicted that seed caching distances would be greater for food items of higher energy content and during lower ambient food abundance and that the effect of seed type on cache distance variation would be lower during higher food abundance. We recorded distances moved for 8636 seeds of five seed types at 15 locations in three forested sites in Pennsylvania, USA, and 29 forest fragments in Indiana, U.S.A., across five different years. Seed production was poor in three years and high in two years. Consistent with previous studies, seeds with greater energy content were moved farther than less profitable food items. Seeds were dispersed less far in seed-rich years than in seed-poor years, contrary to predictions of conventional models. Interactions were important, with seed type effects more evident in seed-poor years. These results suggest that, when food is superabundant, optimal cache distances are more strongly determined by minimizing energy cost of caching than by minimizing pilfering rates and that cache loss rates may be more strongly density-dependent in times of low seed abundance.

Toward ecologically explicit null models of nestedness.

A community is "nested" when species assemblages in less rich sites form nonrandom subsets of those at richer sites. Conventional null models used to test for statistically nonrandom nestedness are under- or over-restrictive because they do not sufficiently isolate ecological processes of interest, which hinders ecological inference. We propose a class of null models that are ecologically explicit and interpretable. Expected values of species richness and incidence, rather than observed values, are used to create random presence-absence matrices for hypothesis testing. In our examples, based on six datasets, expected values were derived either by using an individually based random placement model or by fitting empirical models to richness data as a function of environmental covariates. We describe an algorithm for constructing unbiased null matrices, which permitted valid testing of our null models. Our approach avoids the problem of building too much structure into the null model, and enabled us to explicitly test whether observed communities were more nested than would be expected for a system structured solely by species-abundance and species-area or similar relationships. We argue that this test or similar tests are better determinants of whether a system is truly nested; a nested system should contain unique pattern not already predicted by more fundamental ecological principles such as species-area relationships. Most species assemblages we studied were not nested under these null models. Our results suggest that nestedness, beyond that which is explained by passive sampling processes, may not be as widespread as currently believed. These findings may help to improve the utility of nestedness as an ecological concept and conservation tool.

Importance of fragmentation-tolerant species as seed dispersers in disturbed landscapes.

Forest fragmentation can negatively affect plants if animal seed-dispersers become locally extinct in fragments. We conducted a 2-year experiment to evaluate the importance of tree squirrels (Sciurus) as seed dispersers for Quercus, Carya, and Juglans, and to assess dispersal consequences in patches where fragmentation-sensitive eastern gray squirrels (Sciurus carolinensis) are absent. We accounted for fates of approximately 15,700 seeds from five tree species in four exclosure treatments at 18 fragments during a high (2003-2004) and low seed (2004-2005) year. Two treatments excluded Sciurus to mimic disperser loss. We sampled nut-tree seedling density at 259 sites across eight watersheds, half of which were too fragmented to support S. carolinensis, but supported fragmentation-tolerant fox squirrels (Sciurus niger). Autumn-to-spring seed survival was low ( approximately 1%) for all species during low seed production. During high seed production, survival was higher for Juglans nigra (20%) and Carya ovata (16%) than for three Quercus species ( approximately 4% for Quercus palustris and Quercus rubra in two exclosure types; approximately 1% for Quercus alba in all treatments). Survival of J. nigra, C. ovata, and Q. rubra was >or=2.1-7.7 times higher for seeds in exclosures that Sciurus could access. Seed displacement distance was higher in the low seed than the seed-rich year, but the proportion of seeds surviving to greater distances was higher in seed-rich years for all seed types except Q. rubra. This affirms the importance of masting to seed survival and dispersal, but also suggests an advantage to trees of producing seed in non-mast years. Seedling densities were comparable in watersheds with and without S. carolinensis. These results demonstrate the importance of tree squirrels as dispersers of nut-bearing trees, but suggest that fragmentation may not disrupt dispersal of certain species if losing S. carolinensis from disturbed landscapes is compensated for by fragmentation-tolerant fox squirrels (S. niger).