Factors affecting detectability of river otters during sign surveys

Sign surveys are commonly used to study and monitor wildlife species but may be flawed when surveys are conducted only once and cover short distances, which can lead to a lack of accountability for false absences. Multiple observers surveyed for river otter (Lontra canadensis) scat and tracks along stream and reservoir shorelines at 110 randomly selected sites in eastern Kansas from January to April 2008 and 2009 to determine if detection probability differed among substrates, sign types, observers, survey lengths, and near access points. We estimated detection probabilities (p) of river otters using occupancy models in Program PRESENCE. Mean detection probability for a 400-m survey was highest in mud substrates (p = 0.60) and lowest in snow (p = 0.18) and leaf litter substrates (p = 0.27). Scat had a higher detection probability (p = 0.53) than tracks (p = 0.18), and experienced observers had higher detection probabilities (p > 0.71) than novice observers (p < 0.55). Detection probabilities increased almost 3-fold as survey length increased from 200 m to 1,000 m, and otter sign was not concentrated near access points. After accounting for imperfect detection, our estimates of otter site occupancy based on a 400-m survey increased >3-fold, providing further evidence of the potential negative bias that can occur in estimates from sign surveys when imperfect detection is not addressed. Our study identifies areas for improvement in sign survey methodologies and results are applicable for sign surveys commonly used for many species across a range of habitats. © 2010 The Wildlife Society     

AN ESTIMATION OF CARRYING CAPACITY FOR SEA OTTERS ALONG THE CALIFORNIA COAST

Carrying capacity (K) for the California sea otter ( Enhydra lutris nereis ) was estimated as a product of the density of sea otters at equilibrium within a portion of their existing range and the total area of available habitat. Equilibrium densities were determined using the number of sea otters observed during spring surveys in 1994, 1995, and 1996 in each of three habitat types where sea otters currently exist. Potential sea otter habitat was defined as from the California coastline to the 40-m isobath and classified as rocky, sandy, or mixed habitat according to the amount of kelp and rocky substrate in the area. The amount of habitat available to sea otters in California was estimated using a Geographic Information Systems (GIS) program. The estimated mean number of sea otters that could be supported by the marine environment to a depth of 40 m in California was 15,941 (95% CI 13,538–18,577). The GIS-based approach incorporated detailed bathymetric contours, produced repeatable and accurate estimates, and served as an innovative method of measuring sea otter habitat. We believe the approach described in this paper represents the best available information on how a sea otter population at equilibrium would be distributed along the California coast.     

Evaluating the current condition of a threatened marine mammal population: Estimating northern sea otter (Enhydra lutris kenyoni) abundance in southwest Alaska

We estimated density and abundance of the threatened southwest Alaska distinct population segment of northern sea otters (Enhydra lutris kenyoni) in two management units. We conducted aerial surveys in Bristol Bay and South Alaska Peninsula management units in 2016, and modeled sea otter density and abundance with Bayesian hierarchical distance sampling models and spatial environmental covariates (depth, distance to shore, depth × distance to shore). Spatial environmental covariates substantially impacted sea otter group density in both management units, but effects sizes differed between the two management units. Abundance (9,733 otters, 95% CrI 6,412–17,819) and density (0.82 otters/km², 95% CrI 0.54–1.49) estimates for Bristol Bay indicated a moderate population size. In contrast, abundance (546 otters, 95% CrI 322–879) and density (0.06 otters/km², 95% CrI 0.03–0.09) estimates indicated a relatively low population size in South Alaska Peninsula. Overall, our results highlight the importance of accounting for the detection process in monitoring at-risk species to reduce the uncertainty associated with making conclusions about population declines.     

A Sightability Model for Mountain Goats

ABSTRACT Unbiased estimates of mountain goat (Oreamnos americanus) populations are key to meeting diverse harvest management and conservation objectives. We developed logistic regression models of factors influencing sightability of mountain goat groups during helicopter surveys throughout the Cascades and Olympic Ranges in western Washington during summers, 2004–2007. We conducted 205 trials of the ability of aerial survey crews to detect groups of mountain goats whose presence was known based on simultaneous direct observation from the ground (n = 84), Global Positioning System (GPS) telemetry (n = 115), or both (n = 6). Aerial survey crews detected 77% and 79% of all groups known to be present based on ground observers and GPS collars, respectively. The best models indicated that sightability of mountain goat groups was a function of the number of mountain goats in a group, presence of terrain obstruction, and extent of overstory vegetation. Aerial counts of mountain goats within groups did not differ greatly from known group sizes, indicating that under-counting bias within detected groups of mountain goats was small. We applied Horvitz-Thompson-like sightability adjustments to 1,139 groups of mountain goats observed in the Cascade and Olympic ranges, Washington, USA, from 2004 to 2007. Estimated mean sightability of individual animals was 85% but ranged 0.75–0.91 in areas with low and high sightability, respectively. Simulations of mountain goat surveys indicated that precision of population estimates adjusted for sightability biases increased with population size and number of replicate surveys, providing general guidance for the design of future surveys. Because survey conditions, group sizes, and habitat occupied by goats vary among surveys, we recommend using sightability correction methods to decrease bias in population estimates from aerial surveys of mountain goats.     

Detection Probabilities for Ground-Based Breeding Waterfowl Surveys

ABSTRACT Current methods for conducting ground-based surveys of breeding waterfowl pairs make the unlikely assumption that detection probabilities are constant and approach 100%. To test this assumption, we conducted independent double-observer pair surveys in North Dakota, USA, to evaluate sources of variation in detection probabilities for 8 common species of prairie-nesting ducks. An experienced observer had 0.911 detection probability averaged over all 8 species (range = 0.866-0.944) versus 0.790 (range = 0.537-0.890) for a novice observer. Detection probabilities also varied substantially among species, but patterns were not consistent between observers. Detection probabilities declined as number of ducks per wetland increased, presumably due to difficulty in identifying large numbers of flushing ducks. Other covariates affecting detection probabilities included size of social groups, precipitation, survey methodology (roadside vs. walk-up), cloud cover, time of day, and amount of wetland vegetation, but these covariates only affected detection probabilities by 2–5%. Our results demonstrated that the assumption of 100% detection probabilities for ground-based waterfowl counts was clearly false and surveys based on this erroneous assumption underestimated population size by 10–29%. We recommend that future investigators measure detection probabilities explicitly by using double-observer methodologies.     

POTENTIAL IMPACT OF OIL SPILLS ON CALIFORNIA SEA OTTERS: IMPLICATIONS OF THE EXXON VALDEZ SPILL IN ALASKA

Based on the survival of sea otters held at rehabilitation centers during the 1989 Exxon Valdez oil spill in Alaska, we built two models of otter mortality. One was based on the relationship between mortality and distance from spill origin, the other was based on the relationship between mortality and time from the spill origin. These models are simplistic and are meant as first steps in arriving at realistic risk estimates and in providing a conceptual framework for relating oil spills and sea otter mortality. Using the distance model, we simulated the impact of an Exxon Valdez event occurring at different locations along the California coast. A spill at the Monterey Peninsula had the greatest impact, exposing 90% of the California sea otter population to oil and killing at least 50% of the individuals. The time model was used to predict the mortality of otters exposed to oil of various ages and for various periods of time. It suggested that efforts to rehabilitate otters should be discontinued 20-30 d after a spill. The limitations of the data available from the Exxon Valdez spill emphasize the importance of being prepared to conduct appropriate research during the next oil spill in sea otter habitat.     

MORTALITY OF SEA OTTERS IN PRINCE WILLIAM SOUND FOLLOWING THE EXXON VALDEZ OIL SPILL

Abstract: This paper presents an estimate of the total number of sea otters that died as a direct consequence of the oil spill that occurred when the T/V Exxon Valdez grounded in Prince William Sound, Alaska on 24 March 1989. We compared sea otter counts conducted from small boats throughout the Sound during the summers of 1984 and 1985 to counts made after the spill during the summer of 1989. We used ratio estimators, corrected for sighting probability, to calculate otter densities and population estimates for portions of the Sound affected by the oil spill. We estimated the otter population in the portion of Prince William Sound affected by the oil was 6,546 at the time of the spill and that the post-spill population in the summer of 1989 was 3,898, yielding a loss estimate of approximately 2,650. Bootstrapping techniques were used to approximate confidence limits on the loss estimate of about 500–5,000 otters. The wide confidence limits are a result of the complex scheme required to estimate losses and limitations of the data. Despite the uncertainty of the loss estimate it is clear that a significant fraction of the otters in the spill zone survived. We observed otters persisting in relatively clean embayments throughout the oil spill zone suggesting that the highly convoluted coastline of Prince William Sound produced refuges that allowed some sea otters in the oil spill area to survive.     

Using soundscape recordings to estimate bird species abundance, richness, and composition

ABSTRACT Point counts are the most frequently used technique for sampling bird populations and communities, but have well‐known limitations such as inter‐ and intraobserver errors and limited availability of expert field observers. The use of acoustic recordings to survey birds offers solutions to these limitations. We designed a Soundscape Recording System (SRS) that combines a four‐channel, discrete microphone system with a quadraphonic playback system for surveying bird communities. We compared the effectiveness of SRS and point counts for estimating species abundance, richness, and composition of riparian breeding birds in California by comparing data collected simultaneously using both methods. We used the temporal‐removal method to estimate individual bird detection probabilities and species abundances using the program MARK. Akaike's Information Criterion provided strong evidence that detection probabilities differed between the two survey methods and among the 10 most common species. The probability of detecting birds was higher when listening to SRS recordings in the laboratory than during the field survey. Additionally, SRS data demonstrated a better fit to the temporal‐removal model assumptions and yielded more reliable estimates of detection probability and abundance than point‐count data. Our results demonstrate how the perceptual constraints of observers can affect temporal detection patterns during point counts and thus influence abundance estimates derived from time‐of‐detection approaches. We used a closed‐population capture–recapture approach to calculate jackknife estimates of species richness and average species detection probabilities for SRS and point counts using the program CAPTURE. SRS and point counts had similar species richness and detection probabilities. However, the methods differed in the composition of species detected based on Jaccard's similarity index. Most individuals (83%) detected during point counts vocalized at least once during the survey period and were available for detection using a purely acoustic technique, such as SRS. SRS provides an effective method for surveying bird communities, particularly when most species are detected by sound. SRS can eliminate or minimize observer biases, produce permanent records of surveys, and resolve problems associated with the limited availability of expert field observers.     

Assessing Risks to Sea Otters and the Exxon Valdez Oil Spill: New Scenarios,Attributable Risk,and Recovery

The Exxon Valdez oil spill occurred more than two decades ago, and the Prince William Sound ecosystem has essentially recovered. Nevertheless, discussion continues on whether or not localized effects persist on sea otters (Enhydra lutris) at northern Knight Island (NKI) and, if so, what are the associated attributable risks. A recent study estimated new rates of sea otter encounters with subsurface oil residues (SSOR) from the oil spill. We previously demonstrated that a potential pathway existed for exposures to polycyclic aromatic hydrocarbons (PAHs) and conducted a quantitative ecological risk assessment using an individual-based model that simulated this and other plausible exposure pathways. Here we quantitatively update the potential for this exposure pathway to constitute an ongoing risk to sea otters using the new estimates of SSOR encounters. Our conservative model predicted that the assimilated doses of PAHs to the 1-in-1000th most-exposed sea otters would remain 1–2 orders of magnitude below the chronic effects thresholds. We re-examine the baseline estimates, post-spill surveys, recovery status, and attributable risks for this subpopulation. We conclude that the new estimated frequencies of encountering SSOR do not constitute a plausible risk for sea otters at NKI and these sea otters have fully recovered from the oil spill.     

A systematic re-sampling approach to assess the probability of detecting otters Lutra lutra using spraint surveys on small lowland rivers

Assessing and monitoring populations of elusive species frequently rely on the identification of indirect signs such as faeces. The absence of signs does not necessarily denote the absence of a species, thus, the ability to determine the presence/absence is susceptible to false negative results. The probability of detection is central to the interpretation and utility of data from field sign surveys. A low probability of detection may introduce considerable error into distribution patterns, resulting in inaccurate ecological conclusions.We used a systematic resampling approach, based on sequential spatial replication of spraint surveys, to investigate the probability of detecting Eurasian otters (Lutra lutra L.) with different survey designs. This included the standard otter transect survey methodology, which is widely used in conservation and scientific studies. In particular, we focus on the impact of applying broad scale population assessment techniques at smaller spatial scales. Fortnightly catchment-level otter surveys were undertaken on four lowland rivers in South Wales, over a period of two years. GIS was used to construct binary vectors for each survey, denoting the presence (1) or absence (0) of otters at each 50 m section of river. Vectors from all study rivers were pooled and resampled to test the different survey designs. The mean probability of detecting otters based on the standard protocol of a single 600 m transect survey was very low (0.26 ± 0.01 SE). The best way of obtaining a detection probability of 0.8 was to undertake three repeat surveys at two separate sites, using a transect of 800–1000 m.We demonstrate how sequentially collected spatial data can be analysed to determine the reliability of field sign surveys. Increasing the number of visits and study sites was a more efficient means of improving detection power than increasing transect length alone. The study emphasises the importance of determining detection probabilities and designing field sign surveys according to study scale and objectives. Our findings question the value of survey designs that aim to provide an instantaneous assessment of species presence/absence.     

Comparing direct and indirect methods to estimate detection rates and site use of a cryptic semi-aquatic carnivore

Monitoring animal populations can be challenging, particularly when working with species that are cryptic, rare, or occur at low densities. The northern river otter (Lontra canadensis) is a cryptic, semi-aquatic carnivore that has been intensively studied in recent decades, yet much of what is known about its ecology is a result of studies that have employed indirect methods of detection and monitoring. These indirect methods, such as latrine or other sign surveys, have been the primary approach used for studying distribution, abundance, and habitat use of otters, with minimal representation of direct methods. In this study, we compared direct (camera traps) and indirect (scat count surveys) methods of evaluating detection probabilities and site use patterns of otters at latrines. We found that the direct method produced a significantly greater monthly detection probability than the indirect method and that camera surveys resulted in fewer occurrences of false negatives than scat surveys. However, the number of scats deposited at a site was positively correlated with number of visits by otters at a site (Tau-b = 0.675). Thus, while cameras outperformed scat counts in terms of detection, the two methods were comparable in determining intensity of site use. We conclude that, depending on the parameter of interest, scat counts may be an acceptable surrogate for more direct methods of monitoring otters and other cryptic species. We caution, however, that in the absence of comparative methodological data, direct methods such as camera trapping should be preferred when making inferences about animal distribution, abundance, or habitat use.     

DIET AND FORAGING BEHAVIOR OF SEA OTTERS IN SOUTHEAST ALASKA

Abstract: Direct observations of feeding sea otters ( Enhydra lutris ) at 11 sites in southeast Alaska showed infaunal clams to be the primary prey utilized by otters throughout the region. Foraging dive times associated with clam and sea urchin prey were significantly longer than those for more easily captured prey (crabs and mussels). Dive times and surface intervals were also generally correlated with water depth or apparent difficulty in obtaining buried prey. Male otters, which fed more extensively on clams than females, made significantly longer foraging dives than females. Foraging success remained high, even at sites where prey numbers were found to be very low during a related study. The very deeply burrowing geoduck clam ( Panope abrupta ), while common at several otter feeding sites, was rarely captured by otters. These results, combined with those of a companion study on prey numbers, indicate that butter clams ( Saxidomus giganteus ) account for the majority of the sea otter diet in southeast Alaska, and that sea urchins may represent relatively short-term prey in comparison to infaunal bivalves in regions where both prey types co-exist. Furthermore, the importance of butter clams in the sea otter diet and the tendency for this bivalve to retain chronically high levels of paralytic shellfish poisoning toxins in southeast Alaska increases the probability that toxic phytoplankton blooms influence sea otter distribution in this region.     

An unusual genotype of Toxoplasma gondii is common in California sea otters (Enhydra lutris nereis) and is a cause of mortality

Toxoplasma gondii-associated meningoencephalitis is a significant disease of California sea otters (Enhydra lutris nereis), responsible for 16% of total mortality in fresh, beachcast carcasses. Toxoplasma gondii isolates were obtained from 35 California otters necropsied between 1998 and 2002. Based on multi-locus PCR-restriction fragment length polymorphism and DNA sequencing at conserved genes (18S rDNA, ITS-1) and polymorphic genes (B1, SAG1, SAG3 and GRA6), two distinct genotypes were identified: type II and a novel genotype, here called type x, that possessed distinct alleles at three of the four polymorphic loci sequenced. The majority (60%) of sea otter T. gondii infections were of genotype x, with the remaining 40% being of genotype II. No type I or III genotypes were identified. Epidemiological methods were used to examine the relationship between isolated T. gondii genotype(s) and spatial and demographic risk factors, such as otter stranding location and sex, as well as specific outcomes related to pathogenicity, such as severity of brain inflammation on histopathology and T. gondii-associated mortality. Differences were identified with respect to T. gondii genotype and sea otter sex and stranding location along the California coast. Localised spatial clustering was detected for both type II (centred within Monterey Bay) and x (centred near Morro Bay)-infected otters. The Morro Bay cluster of type x-infected otters overlaps previously reported high-risk areas for sea otter infection and mortality due to T. gondii. Nine of the 12 otters that had T. gondii-associated meningoencephalitis as a primary cause of death were infected with type x parasites.     

SEA OTTERS AND BENTHIC PREY COMMUNITIES IN WASHINGTON STATE

An August 1987 benthic survey of otter-free and otter-occupied areas along the outer coast of Washington State's Olympic Peninsula confirms that this area has been as profoundly influenced by sea otters as other rocky, nearshore communities studied in California, Canada, and Alaska. Prey density, size, and biomass were found to be negatively correlated with sea otter abundance, suggesting that the re-introduction of sea otters to this area in 1969–1970 has profoundly affected invertebrate prey abundance and distribution, particularly that of the red sea urchin, Strongylocentrotus franciscanus. Red urchin distribution appears to influence algal groups differently and in a manner consistent with current otter/urchin/kelp theory. Foliose red algal abundance was negatively related to urchin numbers and coralline crusts were positively correlated. Aerial photographs of Macrocystis integrifolia cover at Cape Alava suggest an increase since the introduction of sea otters. Given the present distribution of prey along the Olympic Peninsula coast, we conclude that as the sea otter population continues to grow, range expansion is more likely to occur to the north, which may also lead to possible conflicts with an increasing sea urchin fishery and Native American set net activity.     

Estimating Carrying Capacity for Sea Otters in British Columbia

ABSTRACT We estimated carrying capacity for sea otters (Enhydra lutris) in the coastal waters of British Columbia, Canada, by characterizing habitat according to the complexity of nearshore intertidal and sub-tidal contours. We modeled the total area of complex habitat on the west coast of Vancouver Island by first calculating the complexity of the Checleset Bay-Kyuquot Sound (CB-KS) region, where sea otters have been at equilibrium since the mid-1990s. We then identified similarly complex areas on the west coast of Vancouver Island (WCVI model), and adapted the model to identify areas of similar complexity along the entire British Columbia coast (BC model). Using survey data from the CB-KS region, we calculated otter densities for the habitat predicted by the 2 models. The density estimates for CB-KS were 3.93 otters/km² and 2.53 otters/km² for the WCVI and BC models, respectively, and the resulting 2 estimates of west coast of Vancouver Island complex habitat carrying capacity were not significantly different (WCVI model: 5,123, 95% CI = 3,337–7,104; BC model: 4,883, 95% CI = 3,223–6,832). The BC model identified the region presently occupied by otters on the central British Columbia coast, but the amount of coast-wide habitat it predicted (5,862 km²) was relatively small, and the associated carrying capacity estimate (14,831, 95% CI = 9,790–20,751) was low compared to historical accounts. We suggest that our model captured a type of high-quality or optimum habitat prevalent on the west coast of Vancouver Island, typified by the CB-KS region, and that suitable sea otter habitat elsewhere on the coast must include other habitat characteristics. We therefore calculated a linear, coast-wide carrying capacity of 52,459 sea otters (95% CI = 34,264–73,489)—a more realistic upper limit to sea otters in British Columbia. Our carrying capacity estimates are helping set population recovery targets for sea otters in Canada, and our habitat predictions represent a first step in Critical Habitat identification. This habitat-based approach to estimating carrying capacity is likely suitable for other nonmigratory, density-dependent species.     

A Quantitative Ecological Risk Assessment of the Toxicological Risks from Exxon Valdez Subsurface Oil Residues to Sea Otters at Northern Knight Island,Prince William Sound,Alaska

A comprehensive, quantitative risk assessment is presented of the toxicological risks from buried Exxon Valdez subsurface oil residues (SSOR) to a subpopulation of sea otters (Enhydra lutris) at Northern Knight Island (NKI) in Prince William Sound, Alaska, as it has been asserted that this subpopulation of sea otters may be experiencing adverse effects from the SSOR. The central questions in this study are: could the risk to NKI sea otters from exposure to polycyclic aromatic hydrocarbons (PAHs) in SSOR, as characterized in 2001–2003, result in individual health effects, and, if so, could that exposure cause subpopulation-level effects? We follow the U.S. Environmental Protection Agency (USEPA) risk paradigm by: (a) identifying potential routes of exposure to PAHs from SSOR; (b) developing a quantitative simulation model of exposures using the best available scientific information; (c) developing scenarios based on calculated probabilities of sea otter exposures to SSOR; (d) simulating exposures for 500,000 modeled sea otters and extracting the 99.9% quantile most highly exposed individuals; and (e) comparing projected exposures to chronic toxicity reference values. Results indicate that, even under conservative assumptions in the model, maximum-exposed sea otters would not receive a dose of PAHs sufficient to cause any health effects; consequently, no plausible toxicological risk exists from SSOR to the sea otter subpopulation at NKI.     

Status,trends, and equilibrium abundance estimates of the translocated sea otter population in Washington State

Sea otters (Enhydra lutris kenyoni) historically occurred in Washington State, USA, until their local extinction in the early 1900s as a result of the maritime fur trade. Following their extirpation, 59 sea otters were translocated from Amchitka Island, Alaska, USA, to the coast of Washington, with 29 released at Point Grenville in 1969 and 30 released at La Push in 1970. The Washington Department of Fish and Wildlife has outlined 2 main objectives for sea otter recovery: a target population level and a target geographic distribution. Recovery criteria are based on estimates of population abundance, equilibrium abundance (K), and geographic distribution; therefore, estimates of these parameters have important management implications. We compiled available survey data for sea otters in Washington State since their translocation (1977–2019) and fit a Bayesian state-space model to estimate past and current abundance, and equilibrium abundance at multiple spatial scales. We then used forward projections of population dynamics to explore potential scenarios of range recolonization and as the basis of a sensitivity analysis to evaluate the relative influence of movement behavior, frontal wave speed, intrinsic growth, and equilibrium density on future population recovery potential. Our model improves upon previous analyses of sea otter population dynamics in Washington by partitioning and quantifying sources of estimation error to estimate population dynamics, by providing robust estimates of K, and by simulating long-term population growth and range expansion under a range of realistic parameter values. Our model resulted in predictions of population abundance that closely matched observed counts. At the range-wide scale, the population size in our model increased from an average of 21 independent sea otters (95% CI = 13–29) in 1977 to 2,336 independent sea otters (95% CI = 1,467–3,359) in 2019. The average estimated annual growth rate was 12.42% and varied at a sub-regional scale from 6.42–14.92%. The overall estimated mean K density of sea otters in Washington was 1.71 ± 0.90 (SD) independent sea otters/km² of habitat (1.96 ± 1.04 sea otters/km², including pups), and estimated densities within the current range correspond on average to 87% of mean sub-regional equilibrium values (range = 66–111%). The projected value of K for all of Washington was 5,287 independent sea otters (95% CI = 2,488–8,086) and 6,080 sea otters including pups (95% CI = 2,861–9,300), assuming a similar range of equilibrium densities in currently un-occupied habitats. Sensitivity analysis of simulations of sea otter population growth and range expansion suggested that mean K density estimates in currently occupied sub-regions had the largest impact on predicted future population growth (r² = 0.52), followed by the rate of southward range expansion (r² = 0.26) and the mean K density estimate of currently unoccupied sub-regions to the south of the current range (r² = 0.04). Our estimates of abundance and sensitivity analysis of simulations of future population abundance and geographic range help determine population status in relation to population recovery targets and identify the most influential parameters affecting future population growth and range expansion for sea otters in Washington State.     

Trends and Carrying Capacity of Sea Otters in Southeast Alaska

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.     

Lessons from the use of non-invasive genetic sampling as a way to estimate Eurasian otter population size and sex ratio

Given the difficulties in establishing population parameters of elusive animals in the wild by traditional methods, such as trapping, much attention has been given in recent years to non-invasive genetic sampling. Our work compared estimates of population size and sex ratio derived from genetic sampling with the known number and sex of animals released during an otter reintroduction and reports on the pitfalls and opportunities that may be encountered in studies of this kind. This study makes use of 121 samples of otter spraints (faeces) collected over 7 months during a reintroduction in the Upper Thames (UK) where a total of 17 otters was released in two consecutive phases. Spraints were processed with a multiple tubes approach and seven microsatellites were used. Of all collected samples, 19 % were complete for at least five loci, the minimum required for discrimination between individuals. Six out of nine of the otters that were released in the first phase were detected, four males and two females, while none of the otters released in the second phase was detected probably due to a combination of sampling pitfalls and otter behaviour. In particular, the specific sex (mostly females) and dominance composition (lower) of the individuals in the second release group may explain our failure to detect individuals in this group. Taken together, our results add further evidence that genetic sampling approaches represent a potentially accurate and non-invasive route to census populations of otters but that the sampling design should take into account factors like the sex ratio and dominance composition of the population in order to maximise detection and minimise error.     

A Double-Observer Method to Estimate Detection Rate During Aerial Waterfowl Surveys

Abstract We evaluated double-observer methods for aerial surveys as a means to adjust counts of waterfowl for incomplete detection. We conducted our study in eastern Canada and the northeast United States utilizing 3 aerial-survey crews flying 3 different types of fixed-wing aircraft. We reconciled counts of front- and rear-seat observers immediately following an observation by the rear-seat observer (i.e., on-the-fly reconciliation). We evaluated 6 a priori models containing a combination of several factors thought to influence detection probability including observer, seat position, aircraft type, and group size. We analyzed data for American black ducks (Anas rubripes) and mallards (A. platyrhynchos), which are among the most abundant duck species in this region. The best-supported model for both black ducks and mallards included observer effects. Sample sizes of black ducks were sufficient to estimate observer-specific detection rates for each crew. Estimated detection rates for black ducks were 0.62 (SE = 0.10), 0.63 (SE = 0.06), and 0.74 (SE = 0.07) for pilot-observers, 0.61 (SE = 0.08), 0.62 (SE = 0.06), and 0.81 (SE = 0.07) for other front-seat observers, and 0.43 (SE = 0.05), 0.58 (SE = 0.06), and 0.73 (SE = 0.04) for rear-seat observers. For mallards, sample sizes were adequate to generate stable maximum-likelihood estimates of observer-specific detection rates for only one aerial crew. Estimated observer-specific detection rates for that crew were 0.84 (SE = 0.04) for the pilot-observer, 0.74 (SE = 0.05) for the other front-seat observer, and 0.47 (SE = 0.03) for the rear-seat observer. Estimated observer detection rates were confounded by the position of the seat occupied by an observer, because observers did not switch seats, and by land-cover because vegetation and landform varied among crew areas. Double-observer methods with on-the-fly reconciliation, although not without challenges, offer one viable option to account for detection bias in aerial waterfowl surveys where birds are distributed at low density in remote areas that are inaccessible by ground crews. Double-observer methods, however, estimate only detection rate of animals that are potentially observable given the survey method applied. Auxiliary data and methods must be considered to estimate overall detection rate.