Jamie N. Womble

Key Questions in Marine Megafauna Movement Ecology

It is a golden age for animal movement studies and so an opportune time to assess priorities for future work. We assembled 40 experts to identify key questions in this field, focussing on marine megafauna, which include a broad range of birds, mammals, reptiles, and fish. Research on these taxa has both underpinned many of the recent technical developments and led to fundamental discoveries in the field. We show that the questions have broad applicability to other taxa, including terrestrial animals, flying insects, and swimming invertebrates, and, as such, this exercise provides a useful roadmap for targeted deployments and data syntheses that should advance the field of movement ecology.

Post-Breeding Season Migrations of a Top Predator, the Harbor Seal (Phoca vitulina richardii), from a Marine Protected Area in Alaska

Marine protected areas (MPAs) are increasingly being used as a conservation tool for highly mobile marine vertebrates and the focus is typically on protecting breeding areas where individuals are aggregated seasonally. Yet movements during the non-breeding season can overlap with threats that may be equally as important to population dynamics. Thus understanding habitat use and movements of species during the non-breeding periods is critical for conservation. Glacier Bay National Park, Alaska, is one of the largest marine mammal protected areas in the world and has the only enforceable protection measures for reducing disturbance to harbor seals in the United States. Yet harbor seals have declined by up to 11.5%/year from 1992 to 2009. We used satellite-linked transmitters that were attached to 37 female harbor seals to quantify the post-breeding season migrations of seals and the amount of time that seals spent inside vs. outside of the MPA of Glacier Bay. Harbor seals traveled extensively beyond the boundaries of the MPA of Glacier Bay during the post-breeding season, encompassing an area (25,325 km2) significantly larger than that used by seals during the breeding season (8,125 km2). These movements included the longest migration yet recorded for a harbor seal (3,411 km) and extended use (up to 23 days) of pelagic areas by some seals. Although the collective utilization distribution of harbor seals during the post-breeding season was quite expansive, there was a substantial degree of individual variability in the percentage of days that seals spent in the MPA. Nevertheless, harbor seals demonstrated a high degree of inter-annual site fidelity (93%) to Glacier Bay the following breeding season. Our results highlight the importance of understanding the threats that seals may interact with outside of the boundaries of the MPA of Glacier Bay for understanding population dynamics of seals in Glacier Bay.

An integrated data model to estimate spatiotemporal occupancy, abundance, and colonization dynamics

Ecological invasions and colonizations occur dynamically through space and time. Estimating the distribution and abundance of colonizing species is critical for efficient management or conservation. We describe a statistical framework for simultaneously estimating spatiotemporal occupancy and abundance dynamics of a colonizing species. Our method accounts for several issues that are common when modeling spatiotemporal ecological data including multiple levels of detection probability, multiple data sources, and computational limitations that occur when making fine-scale inference over a large spatiotemporal domain. We apply the model to estimate the colonization dynamics of sea otters (Enhydra lutris) in Glacier Bay, in southeastern Alaska.

Estimating occupancy and abundance using aerial images with imperfect detection

Summary 1.Species distribution and abundance are critical population characteristics for efficient management, conservation, and ecological insight. Point process models are a powerful tool for modeling distribution and abundance, and can incorporate many data types, including count data, presence-absence data, and presence-only data. Aerial photographic images are a natural tool for collecting data to fit point process models, but aerial images do not always capture all animals that are present at a site. Methods for estimating detection probability for aerial surveys usually include collecting auxiliary data to estimate the proportion of time animals are available to be detected. 2.We developed an approach for fitting point process models using an N-mixture model framework to estimate detection probability for aerial occupancy and abundance surveys. Our method uses multiple aerial images taken of animals at the same spatial location to provide temporal replication of sample sites. The intersection of the images provide multiple counts of individuals at different times. We examined this approach using both simulated and real data of sea otters (Enhydra lutris kenyoni) in Glacier Bay National Park, southeastern Alaska. 3.Using our proposed methods, we estimated detection probability of sea otters to be 0.76, the same as visual aerial surveys that have been used in the past. Further, simulations demonstrated that our approach is a promising tool for estimating occupancy, abundance, and detection probability from aerial photographic surveys. 4.Our methods can be readily extended to data collected using unmanned aerial vehicles, as technology and regulations permit. The generality of our methods for other aerial surveys depends on how well surveys can be designed to meet the assumptions of N-mixture models. This article is protected by copyright. All rights reserved.

Quantification and Analysis of Icebergs in a Tidewater Glacier Fjord Using an Object-Based Approach

Tidewater glaciers are glaciers that terminate in, and calve icebergs into, the ocean. In addition to the influence that tidewater glaciers have on physical and chemical oceanography, floating icebergs serve as habitat for marine animals such as harbor seals (Phoca vitulina richardii). The availability and spatial distribution of glacier ice in the fjords is likely a key environmental variable that influences the abundance and distribution of selected marine mammals; however, the amount of ice and the fine-scale characteristics of ice in fjords have not been systematically quantified. Given the predicted changes in glacier habitat, there is a need for the development of methods that could be broadly applied to quantify changes in available ice habitat in tidewater glacier fjords. We present a case study to describe a novel method that uses object-based image analysis (OBIA) to classify floating glacier ice in a tidewater glacier fjord from high-resolution aerial digital imagery. Our objectives were to (i) develop workflows and rule sets to classify high spatial resolution airborne imagery of floating glacier ice; (ii) quantify the amount and fine-scale characteristics of floating glacier ice; (iii) and develop processes for automating the object-based analysis of floating glacier ice for large number of images from a representative survey day during June 2007 in Johns Hopkins Inlet (JHI), a tidewater glacier fjord in Glacier Bay National Park, southeastern Alaska. On 18 June 2007, JHI was comprised of brash ice (x¯ = 45.2%, SD = 41.5%), water (x¯ = 52.7%, SD = 42.3%), and icebergs (x¯ = 2.1%, SD = 1.4%). Average iceberg size per scene was 5.7 m2 (SD = 2.6 m2). We estimate the total area (± uncertainty) of iceberg habitat in the fjord to be 455,400 ± 123,000 m2. The method works well for classifying icebergs across scenes (classification accuracy of 75.6%); the largest classification errors occur in areas with densely-packed ice, low contrast between neighboring ice cover, or dark or sediment-covered ice, where icebergs may be misclassified as brash ice about 20% of the time. OBIA is a powerful image classification tool, and the method we present could be adapted and applied to other ice habitats, such as sea ice, to assess changes in ice characteristics and availability.