Challenges to Sea Otter Recovery and Conservation

Ballachey, Brenda E.; Bodkin, James L.

doi:10.1016/b978-0-12-801402-8.00004-4

Cited by 8 publications

(7 citation statements)

References 113 publications

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“…While sea otter abundance at the scale of WPWS had demonstrated modest increases since 1993, areas most severely impacted by oil-related mortality did not return to pre-spill numbers until 2011 [8]. The numerical recovery of sea otters was supported by improved survival of sea otters after 2009, with a return to rates observed prior to the spill [4,8,55]. The findings for sea otters related to diminished oil exposure and population recovery were consistent with related findings for sea ducks.…”

Section: Discussionsupporting

confidence: 78%

Gene Transcript Profiling in Sea Otters Post-Exxon Valdez Oil Spill: A Tool for Marine Ecosystem Health Assessment

Bowen

Miles

Ballachey

et al. 2016

JMSE

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Using a panel of genes stimulated by oil exposure in a laboratory study, we evaluated gene transcription in blood leukocytes sampled from sea otters captured from 2006-2012 in western Prince William Sound (WPWS), Alaska, 17-23 years after the 1989 Exxon Valdez oil spill (EVOS). We compared WPWS sea otters to reference populations (not affected by the EVOS) from the Alaska Peninsula (2009), Katmai National Park and Preserve (2009), Clam Lagoon at Adak Island (2012), Kodiak Island (2005) and captive sea otters in aquaria. Statistically, sea otter gene transcript profiles separated into three distinct clusters: Cluster 1, Kodiak and WPWS 2006-2008 (higher relative transcription); Cluster 2, Clam Lagoon and WPWS 2010-2012 (lower relative transcription); and Cluster 3, Alaska Peninsula, Katmai and captive sea otters (intermediate relative transcription). The lower transcription of the aryl hydrocarbon receptor (AHR), an established biomarker for hydrocarbon exposure, in WPWS 2010-2012 compared to earlier samples from WPWS is consistent with declining hydrocarbon exposure, but the pattern of overall low levels of transcription seen in WPWS 2010-2012 could be related to other factors, such as food limitation, pathogens or injury, and may indicate an inability to mount effective responses to stressors. Decreased transcriptional response across the entire gene panel precludes the evaluation of whether or not individual sea otters show signs of exposure to lingering oil. However, related studies on sea otter demographics indicate that by 2012, the sea otter population in WPWS had recovered, which indicates diminishing oil exposure.hydrocarbons has the potential to cause not only catastrophic short-term effects, but importantly, often overlooked, long-term damage to individuals, populations or even ecosystems [1,13]. The extent and duration of long-term effects are difficult to assess, as pathophysiological changes within an individual may be significant yet subtle and, consequently, undetectable using classical wildlife diagnostic methods. Alterations in the levels of gene transcription can provide the earliest observable signs of health impairment, discernable prior to clinical manifestation [14][15][16]. The utility of the methodology used in our study relies on the assumption that oil-induced pathology in sea otters is accompanied by predictable and specific changes in gene transcription.In 2008, we sampled sea otters in previously oiled and unoiled areas of WPWS and compared these to samples from reference (i.e., deemed clinically normal) sea otters from the Alaska Peninsula and captive, healthy sea otters from aquaria [6]. We concluded that sea otters in oiled areas had gene transcription patterns consistent with chronic, low-grade exposure to organic compounds. In 2010 and 2012, we resampled sea otters in the same areas of WPWS to evaluate whether gene transcription patterns observed in 2008 persisted. To provide a broader geographic and temporal interpretation for the analysis of WPWS samples collected in

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Section: Discussionsupporting

confidence: 78%

Gene Transcript Profiling in Sea Otters Post-Exxon Valdez Oil Spill: A Tool for Marine Ecosystem Health Assessment

Bowen

Miles

Ballachey

et al. 2016

JMSE

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“…Although a variety of factors can affect sea otter abundance, including harvests, fisheries, oil spills, and predation (Ballachey and Bodkin ), the availability of food resources is recognized as a common factor governing population status (Kenyon , Monson et al. , Monson and Bowen ).…”

Section: Discussionmentioning

confidence: 99%

Detecting and inferring cause of change in an Alaska nearshore marine ecosystem

et al. 2016

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Abstract. Community composition, species abundance, and species distribution are expected to change while monitoring ecosystems over time, and effective management of natural resources requires understanding mechanisms contributing to change. Marine ecosystems in particular can be difficult to monitor, in part due to large, multidimensional spatial scales and complex dynamics. However, within the temperate marine ecosystems, the nearshore food web is reasonably well described. This food web is ecologically and socially important, spatially constrained, and has been the focus of extensive experimental research that describes the underlying mechanisms important to system dynamics. Here, we describe a monitoring program initiated in 2006 that focuses on the nearshore benthic food web in the Gulf of Alaska, whose design anticipates potential causes of ecosystem change to improve rigor, resolution, and confidence in understanding the mechanisms underlying change. We established 15 long-term monitoring sites across more than 1000 km of coastline, including 10 within two national parks and 5 within Prince William Sound, area of the 1989 Exxon Valdez oil spill. The program evaluates six ecological indicators and more than 200 species that range from primary producers to top-level consumers, and is designed to examine both bottom-up and top-down dynamics. Employing a design that allows broad spatial inference and selecting species with direct food-web linkages, we demonstrate the ability of our monitoring program to simultaneously detect change and assess potential mechanisms underlying that change. Detecting change and understanding mechanisms can help guide management and conservation policy. Specifically, we provide an example focusing on the sea otter (Enhydra lutris) that illustrates how (1) analytical methods are used to evaluate changes on various scales and infer potential mechanisms of change, (2) food-web linkages can enhance the understanding of changes and their effects, and (3) data can be used to inform management.

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“…Given that subsistence harvest of sea otters (Raymond et al, 2019) and human activities (e.g., disturbance from vessel traffic; Ballachey and Bodkin, 2015) influence sea otter population dynamics, we added a covariate of cumulative distance to the nearest incorporated city, town, or village. This was the sum of the shortest swimmable paths from each city, town, or village, to any location s.…”

Section: Environmental Covariatesmentioning

confidence: 99%

“…and bivalves Panopea spp.) as well as mortality from subsistence harvest (Ballachey and Bodkin, 2015;Carswell et al, 2015). Indeed, sea otter population growth and spread was remarkable after individuals reached Glacier Bay National Park-the only area in Southeast Alaska where subsistence harvest of sea otters is not permitted-around the mid 1980s (Williams et al, 2019), yet Southeast Alaska encompasses a diverse matrix of marine areas with various types of resource management.…”

Section: Introductionmentioning

confidence: 99%

Diffusion modeling reveals effects of multiple release sites and human activity on a recolonizing apex predator

Eisaguirre

Williams

et al. 2021

Preprint

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Background: Reintroducing predators is a promising conservation tool to help remedy human-caused ecosystem changes. However, the growth and spread of a reintroduced population is a spatiotemporal process that is driven by a suite of factors, such as habitat change, human activity, and prey availability. Sea otters (Enhydra lutris) are apex predators of nearshore marine ecosystems that had declined nearly to extinction across much of their range by the early 20th century. In Southeast Alaska, which is comprised of a diverse matrix of nearshore habitat and managed areas, reintroduction of 413 individuals in the late 1960s initiated the growth and spread of a population that now exceeds 25,000. Methods: Periodic aerial surveys in the region provide a time series of spatially-explicit data to investigate factors influencing this successful and ongoing recovery. We integrated an ecological diffusion model that accounted for spatially-variable motility and density-dependent population growth, as well as multiple population epicenters, into a Bayesian hierarchical framework to help understand the factors influencing the success of this recovery. Results: Our results indicated that sea otters exhibited higher residence time as well as greater equilibrium abundance in Glacier Bay, a protected area, and in areas where there is limited or no commercial fishing. Asymptotic spread rates suggested sea otters colonized Southeast Alaska at rates of 1-8 km/yr with lower rates occurring in areas correlated with higher residence time, which primarily included areas near shore and closed to commercial fishing. Further, we found that the intrinsic growth rate of sea otters may be higher than previous estimates suggested. Conclusions: This study shows how predator recolonization can occur from multiple population epicenters. Additionally, our results suggest spatial heterogeneity in the physical environment as well as human activity and management can influence recolonization processes, both in terms of movement (or motility) and density dependence.

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Challenges to Sea Otter Recovery and Conservation

Cited by 8 publications

References 113 publications

Gene Transcript Profiling in Sea Otters Post-Exxon Valdez Oil Spill: A Tool for Marine Ecosystem Health Assessment

Gene Transcript Profiling in Sea Otters Post-Exxon Valdez Oil Spill: A Tool for Marine Ecosystem Health Assessment

Detecting and inferring cause of change in an Alaska nearshore marine ecosystem

Diffusion modeling reveals effects of multiple release sites and human activity on a recolonizing apex predator

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