Line S. Cordes

Behavioral responses associated with a human-mediated predator shelter

Human activities in protected areas can affect wildlife populations in a similar manner to predation risk, causing increases in movement and vigilance, shifts in habitat use and changes in group size. Nevertheless, recent evidence indicates that in certain situations ungulate species may actually utilize areas associated with higher levels of human presence as a potential refuge from disturbance-sensitive predators. We now use four-years of behavioral activity budget data collected from pronghorn (Antilocapra americana) and elk (Cervus elephus) in Grand Teton National Park, USA to test whether predictable patterns of human presence can provide a shelter from predatory risk. Daily behavioral scans were conducted along two parallel sections of road that differed in traffic volume - with the main Teton Park Road experiencing vehicle use that was approximately thirty-fold greater than the River Road. At the busier Teton Park Road, both species of ungulate engaged in higher levels of feeding (27% increase in the proportion of pronghorn feeding and 21% increase for elk), lower levels of alert behavior (18% decrease for pronghorn and 9% decrease for elk) and formed smaller groups. These responses are commonly associated with reduced predatory threat. Pronghorn also exhibited a 30% increase in the proportion of individuals moving at the River Road as would be expected under greater exposure to predation risk. Our findings concur with the ‘predator shelter hypothesis’, suggesting that ungulates in GTNP use human presence as a potential refuge from predation risk, adjusting their behavior accordingly. Human activity has the potential to alter predator-prey interactions and drive trophic-mediated effects that could ultimately impact ecosystem function and biodiversity.

Variation in breeding phenology provides insights into drivers of long-term population change in harbour seals

Phenological trends provide important indicators of environmental change and population dynamics. However, the use of untested population-level measures can lead to incorrect conclusions about phenological trends, particularly when changes in population structure or density are ignored. We used individual-based estimates of birth date and lactation duration of harbour seals (Phoca vitulina) to investigate energetic consequences of changes in pupping phenology. Using generalized linear mixed models, we first demonstrate annual variation in pupping phenology. Second, we show a negative relationship between lactation duration and the timing of pupping, indicating that females who pup early nurse their pups longer, thereby highlighting lactation duration as a useful proxy of female condition and resource availability. Third, individual-based data were used to derive a population-level proxy that demonstrated an advance in pupping date over the last 25 years, co-incident with a reduction in population abundance that resulted from fisheries-related shootings. These findings demonstrate that phenological studies examining the impacts of climate change on mammal populations must carefully control for changes in population density and highlight how joint investigations of phenological and demographic change provide insights into the drivers of population declines.

Band reporting rates of waterfowl: does individual heterogeneity bias estimated survival rates?

In capture–recapture studies, the estimation accuracy of demographic parameters is essential to the efficacy of management of hunted animal populations. Dead recovery models based upon the reporting of rings or bands are often used for estimating survival of waterfowl and other harvested species. However, distance from the ringing site or condition of the bird may introduce substantial individual heterogeneity in the conditional band reporting rates (r), which could cause bias in estimated survival rates (S) or suggest nonexistent individual heterogeneity in S. To explore these hypotheses, we ran two sets of simulations (n = 1000) in MARK using Sebers dead recovery model, allowing time variation on both S and r. This included a series of heterogeneity models, allowing substantial variation on logit(r), and control models with no heterogeneity. We conducted simulations using two different values of S: S = 0.60, which would be typical of dabbling ducks such as mallards (Anas platyrhynchos), and S = 0.80, which would be more typical of sea ducks or geese. We chose a mean reporting rate on the logit scale of −1.9459 with SD = 1.5 for the heterogeneity models (producing a back-transformed mean of 0.196 with SD = 0.196, median = 0.125) and a constant reporting rate for the control models of 0.196. Within these sets of simulations, estimation models where σS = 0 and σS > 0 (σS is SD of individual survival rates on the logit scale) were incorporated to investigate whether real heterogeneity in r would induce apparent individual heterogeneity in S. Models where σS = 0 were selected approximately 91% of the time over models where σS > 0. Simulation results showed < 0.05% relative bias in estimating survival rates except for models estimating σS > 0 when true S = 0.8, where relative bias was a modest 0.5%. These results indicate that considerable variation in reporting rates does not cause major bias in estimated survival rates of waterfowl, further highlighting the robust nature of dead recovery models that are being used for the management of harvested species.

Mark-resight estimates of seasonal variation in harbor seal abundance and site fidelity

Monitoring trends in abundance of pinnipeds typically involves counting seals at terrestrial haul-out sites during the breeding season. Counts of seals made at other times of the year are typically lower; however, it is often unknown whether this is because fewer animals are present or whether lower counts simply reflect a reduction in haul-out probability. Here we illustrate how photo-identification data from an individual-based study of harbor seals (Phoca vitulina) can be used to estimate seasonal variation in abundance and site fidelity. Monthly data collected over a two-year period were analyzed using a mark-recapture mark-resight model accounting for individuals transitioning between observable and unobservable states. Levels of site fidelity were high throughout the year and abundance estimates showed no seasonal pattern. This suggests that individual seals used haul-out sites to the same extent throughout the year, and that peaks in counts during the breeding season are a result of seasonal changes in haul-out probability. The results of this study have implications for understanding population sub-structuring, gene flow and disease spread.

Surreptitious sympatry: Exploring the ecological and genetic separation of two sibling species

Abstract Climate change is having profound impacts on animal populations, and shifts in geographic range are predicted in response. Shifts that result in range overlap between previously allopatric congeneric species may have consequences for biodiversity through interspecific competition, hybridization, and genetic introgression. Harbor seals (Phoca vitulina) and spotted seals (Phoca largha) are parapatric sibling species and areas of co‐occurrence at the edges of their range, such as Bristol Bay, Alaska, offer a unique opportunity to explore ecological separation and discuss potential consequences of increased range overlap resulting from retreating sea ice. Using telemetry and genetic data from 14 harbor seals and six spotted seals, we explored the ecological and genetic separation of the two species by comparing their utilization distributions, distance from haul‐out, dive behavior (e.g., depth, duration, focus), and evidence of hybridization. Firstly, we show that harbor and spotted seals, which cannot be visually distinguished definitively in all cases, haul‐out together side by side in Bristol Bay from late summer to early winter. Secondly, we observed subtle rather than pronounced differences in ranging patterns and dive behavior during this period. Thirdly, most spotted seals in this study remained close to shore in contrast to what is known of the species in more northern areas, and lastly, we did not find any evidence of hybridization. The lack of distinct ecological separation in this area of sympatry suggests that interspecific competition could play an important role in the persistence of these species, particularly if range overlap will increase as a result of climate‐induced range shifts and loss of spotted seal pagophilic breeding habitat. Our results also highlight the added complexities in monitoring these species in areas of suspected overlap, as they cannot easily be distinguished without genetic analysis. Predicted climate‐induced environmental change will likely influence the spatial and temporal extent of overlap in these two sibling species. Ultimately, this may alter the balance between current isolating mechanisms with consequences for species integrity and fitness.

The importance of developing modeling frameworks to inform conservation decisions: a response to Lonergan.

Hopefully, this approach represents a process that leads to open and constructive debate, to progress towards a better scientific understanding and to improvements in our ability to manage wildlife. Lonergan has examined our modeling in detail, and his critique raises a series of specific points and also some general questions about how data and expert opinion should be integrated into statistical and modeling frameworks with the aim of advising on conservation methods. we agree with several of Lonergan’s dictums, such as the need for open dialogue between the field biologists collecting data and the modelers subsequently using these data. Indeed, several of his specific points could have been resolved through such dialogue. For example, he queries the lack of data on harbor seal pups after mid-July, but this situation arises because pups cannot be reliably distinguished from juveniles after this time (thompson and Rothery 1987). similarly, detailed evaluation of previous studies from the moray Firth (e.g. thompson et al. 2007) would also call into question Lonergan’s assertion that shooting is the sole driver of historical declines in this population. Lonergan highlights his concerns about the performance and sensitivity of our model to specific assumptions and priors. these are important questions. we hope that in our publication, prior justification was explicit (pp. 155–158), prior sensitivity methodology was described in detail (supplement 3) and the implications of our modeling on our predictions were discussed in full (our points 1–5, pp. 158–159; points 1, 2, p 160). work continues, and our aim is to improve and simplify our modeling—for example, by considering seasonal variation in haulout probability. we are also exploring a question about the mis-match between one datum (2009 population estimate) and model predictions. the sensitivity of our results to these two issues was In his critique of our recent paper (matthiopoulos et al. 2014) on the population dynamics of harbor seals, Lonergan (2014a) argues that although our state–space modeling approach represents an interesting academic exercise, it nevertheless risks misleading those attempting to understand and manage observed declines of this species in UK waters. we argue that approaches like ours need not be misleading as long as information is provided on the assumptions and simplifications used. when such information is available, all assumptions (such as the shape and parameters of prior distributions in a Bayesian analysis) can then be subjected to scrutiny [such as that performed by Lonergan (2014a)], inevitably leading to future improvements.