Sea otter populations in Southeast Alaska, USA, have increased dramatically from just over 400 translocated animals in the late 1960s to >8,000 by 2003. The recovery of sea otters to ecosystems from which they had been absent has affected coastal food webs, including commercially important fisheries, and thus information on expected growth and equilibrium abundances can help inform resource management. We compile available survey data for Southeast Alaska and fit a Bayesian state‐space model to estimate past trends and current abundance. Our model improves upon previous analyses by partitioning and quantifying sources of estimation error, accounting for over‐dispersion of aerial count data, and providing realistic measurements of uncertainty around point estimates of abundance at multiple spatial scales. We also provide estimates of carrying capacity (K) for Southeast Alaska, at regional and sub‐regional scales, and analyze growth rates, current population status and expected future trends. At the regional scale, the population increased from 13,221 otters in 2003 to 25,584 otters in 2011. The average annual growth rate in southern Southeast Alaska (7.8%) was higher than northern Southeast Alaska (2.7%); however, growth varied at the sub‐regional scale and there was a negative relationship between growth rates and the number of years sea otters were present in an area. Local populations vary in terms of current densities and expected future growth; the mean estimated density at K was 4.2 ± 1.58 sea otters/km2 of habitat (i.e., the sub‐tidal benthos between 0 m and 40 m depth) and current densities correspond on average to 50% of projected equilibrium values (range = 1–97%) with the earliest‐colonized sub‐regions tending to be closer to K. Assuming a similar range of equilibrium densities for currently un‐occupied habitats, the projected value of K for all of Southeast Alaska is 74,650 sea otters. Future analyses can improve upon the precision of K estimates by employing more frequent surveys at index sites and incorporating environmental covariates into the process model to generate more accurate, location‐specific estimates of equilibrium density. © 2019 The Authors. The Journal of Wildlife Management Published by Wiley Periodicals, Inc.
The Kittlitz's Murrelet (Brachyramphus brevirostris) is a rare, non-colonial seabird often associated with tidewater glaciers and a recent candidate for listing under the Endangered Species Act. We estimated abundance of Kittlitz's Murrelets across space and time from at-sea surveys along the coast of Alaska (USA) and then used these data to develop spatial models to describe abundance patterns and identify environmental factors affecting abundance. Over a five-week period in the summer of 2005, we recorded 794 Kittlitz's Murrelets, 16 Marbled Murrelets (B. marmoratus), and 70 unidentified murrelets. The overall population estimate (N, mean +/- SE) during the peak period (3-9 July) was 1317 +/- 294 birds, decreasing to 68 +/- 37 by the last survey period (31 July-6 August). Density of Kittlitz's Murrelets was highest in pelagic waters of Taan Fjord (18.6 +/- 7.8 birds/km2, mean +/- SE) during 10-16 July. Spatial models identified consistent "hotspots" of Kittlitz's Murrelets, including several small areas where high densities of murrelets were found throughout the survey period. Of the explanatory variables that we evaluated, tidal current strength influenced murrelet abundance most consistently, with higher abundance associated with strong tidal currents. Simulations based on the empirically derived estimates of variation demonstrated that spatial variation strongly influenced power to detect trend, although power changed little across the threefold difference in the coefficient of variation on detection probability. We include recommendations for monitoring Kittlitz's Murrelets (or other marine species) when there is a high degree of uncertainty about factors affecting abundance, especially spatial variability.
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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