A field test of the distance sampling method using Golden‐cheeked Warblers

ABSTRACT Criteria for delisting Golden‐cheeked Warblers (Dendroica chrysoparia) include protection of sufficient breeding habitat to ensure the continued existence of 1000 to 3000 singing males in each of eight recovery regions for ≥10 consecutive years. Hence, accurate abundance estimation is an integral component in the recovery of this species. I conducted a field test to determine if the distance sampling method provided unbiased abundance estimates for Golden‐cheeked Warblers and develop recommendations to improve the accuracy of estimates by minimizing the effects of violating this method's assumptions. To determine if observers could satisfy the assumptions that birds are detected at the point with certainty and at their initial locations, I compared point‐transect sampling estimates from 2‐, 3‐, 4‐, and 5‐min time intervals to actual abundance determined by intensive territory monitoring. Point‐transect abundance estimates were 15%, 29%, 43%, and 59% greater than actual abundance (N= 156) for the 2‐, 3‐, 4‐, and 5‐min intervals, respectively. Point‐transect sampling produced unbiased estimates of Golden‐cheeked Warbler abundance when counts were limited to 2 min (N= 154–207). Abundance estimates derived from point‐transect sampling were likely greater than actual abundance because observers did not satisfy the assumption that birds were detected at their initial locations due to the frequent movements and large territory sizes of male Golden‐cheeked Warblers. To minimize the effect of movement on abundance estimates, I recommend limiting counts of singing males to 2‐min per point. Counts for other species in similar habitats with similar behavior and movement patterns also should be limited to 2 min when unbiased estimates are important and conducting field tests of the point‐transect distance sampling method is not possible.     

Using time‐of‐detection to evaluate detectability assumptions in temporally replicated aural count indices: an example with Ring‐necked Pheasants

ABSTRACT The validity of treating counts as indices to abundance is based on the assumption that the expected detection probability, E(p), is constant over time or comparison groups or, more realistically, that variation in p is small relative to variation in population size that investigators seek to detect. Unfortunately, reliable estimates of E(p) and var(p) are lacking for most index methods. As a case study, we applied the time‐of‐detection method to temporally replicated (within season) aural counts of crowing male Ring‐necked Pheasants (Phasianus colchicus) at 18 sites in southern Minnesota in 2007 to evaluate the detectability assumptions. More specifically, we used the time‐of‐detection method to estimate E(p) and var(p), and then used these estimates in a Monte Carlo simulation to evaluate bias‐variance tradeoffs associated with adjusting count indices for imperfect detection. The estimated mean detection probability in our case study was 0.533 (SE = 0.030) and estimated spatial variation in E(p) was 0.081 (95% CI: 0.057–0.126). On average, both adjusted (for) and unadjusted counts of crowing males qualitatively described the simulated relationship between pheasant abundance and grassland abundance, but the bias‐variance tradeoff was smaller for adjusted counts (MSE = 0.003 vs. 0.045, respectively). Our case study supports the general recommendation to use, whenever feasible, formal population‐estimation procedures (e.g., mark‐recapture, distance sampling, double sampling) to account for imperfect detection. However, we caution that interpreting estimates of absolute abundance can be complicated, even if formal estimation methods are used. For example, the time‐of‐detection method was useful for evaluating detectability assumptions in our case study and the method could be used to adjust aural count indices for imperfect detection. Conversely, using the time‐of‐detection method to estimate absolute abundances in our case study was problematic because the biological populations and sampling coverage could not be clearly delineated. These estimation and inference challenges may also be important in other avian surveys that involve mobile species (whose home ranges may overlap several sampling sites), temporally replicated counts, and inexact sampling coverage.     

Mite‐y bees: bumble bees (Bombus spp., Hymenoptera: Apidae) host a relatively homogeneous mite (Acari) community,shaped by bee species identity but not by geographic proximity

1. Parasites can affect the communities of their hosts; and hosts, in turn, shape communities of parasites and other symbionts. This makes host–symbiont relationships a key but often overlooked aspect of community ecology. 2. Mites associated with bees have a range of lifestyles; however, little is known about mites associated with wild bees or about factors influencing the make‐up of bee‐associated mite communities. This study investigated how mite communities associated with bumble bees (Bombus spp.) are shaped by the Bombus community and geographic proximity. 3. Bees were collected from 15 sites in Ontario, Canada, and examined for mites. Mite abundance and species richness increased with local bee abundance. Several bee species also differed in mite abundance, species richness, prevalence, and diversity. Locally uncommon species tended to have more mites than other bees. Queen bees had the most mites, and males had more mites than workers. 4. Spatial proximity was not a predictor of mite community composition, despite a strong effect of proximity on bee community similarity. 5. On the 11 Bombus spp. examined, 33 mite species were found. Whereas nearly half of these mite species are obligate associates of bumble bees, none was restricted to particular Bombus species. 6. The best predictor of mite community composition was bee identity. Although many parasite communities show strong geographic patterns, the communities of primarily commensalistic bee‐mites in this study did not. These findings have implications for bumble bee conservation, given that pollen‐feeding commensals might become harmful at high densities or act as disease vectors.     

Evaluation of three methods to estimate density and detectability from roadside point counts

Roadside point counts are often used to estimate trends of bird populations. The use of aural counts of birds without adjustment for detection probability, however, can lead to incorrect population trend estimates. We compared precision of estimates of density and detectability of whistling northern bobwhites (Colinus virginianus) using distance sampling, independent double-observer, and removal methods from roadside surveys. Two observers independently recorded each whistling bird heard, distance from the observer, and time of first detection at 362 call-count stops in Ohio. We examined models that included covariates for year and observer effects for each method and distance from observer effects for the double-observer and removal methods using Akaike's Information Criterion (AIC). The best model of detectability from distance sampling included observer and year effects. The best models from the removal and double-observer techniques included observer and distance effects. All 3 methods provided precise estimates of detection probability (CV = 2.4–4.4%) with a range of detectability of 0.44–0.95 for a 6-min survey. Density estimates from double-observer surveys had the lowest coefficient of variation (2005 = 3.2%, 2006 = 1.7%), but the removal method also provided precise estimates of density (2005 CV = 3.4%, 2006 CV = 4.8%), and density estimates from distance sampling were less precise (2005 CV = 9.6%, 2006 CV = 7.9%). Assumptions of distance sampling were violated in our study because probability of detecting bobwhites near the observer was <1 or the roadside survey points were not randomly distributed with respect to the birds. Distances also were not consistently recorded by individual members of observer pairs. Although double-observer surveys provided more precise estimates, we recommend using the removal method to estimate detectability and abundance of bobwhites. The removal method provided precise estimates of density and detection probability and requires half the personnel time as double-observer surveys. Furthermore, the likelihood of meeting model assumptions is higher for the removal survey than with independent double-observers. © 2011 The Wildlife Society.     

Improving inference for aerial surveys of bears: The importance of assumptions and the cost of unnecessary complexity

Obtaining useful estimates of wildlife abundance or density requires thoughtful attention to potential sources of bias and precision, and it is widely understood that addressing incomplete detection is critical to appropriate inference. When the underlying assumptions of sampling approaches are violated, both increased bias and reduced precision of the population estimator may result. Bear (Ursus spp.) populations can be difficult to sample and are often monitored using mark‐recapture distance sampling (MRDS) methods, although obtaining adequate sample sizes can be cost prohibitive. With the goal of improving inference, we examined the underlying methodological assumptions and estimator efficiency of three datasets collected under an MRDS protocol designed specifically for bears. We analyzed these data using MRDS, conventional distance sampling (CDS), and open‐distance sampling approaches to evaluate the apparent bias‐precision tradeoff relative to the assumptions inherent under each approach. We also evaluated the incorporation of informative priors on detection parameters within a Bayesian context. We found that the CDS estimator had low apparent bias and was more efficient than the more complex MRDS estimator. When combined with informative priors on the detection process, precision was increased by >50% compared to the MRDS approach with little apparent bias. In addition, open‐distance sampling models revealed a serious violation of the assumption that all bears were available to be sampled. Inference is directly related to the underlying assumptions of the survey design and the analytical tools employed. We show that for aerial surveys of bears, avoidance of unnecessary model complexity, use of prior information, and the application of open population models can be used to greatly improve estimator performance and simplify field protocols. Although we focused on distance sampling‐based aerial surveys for bears, the general concepts we addressed apply to a variety of wildlife survey contexts.     

Comparative performance of four survey methods for assessing Lilian’s Lovebird abundance in Liwonde National Park,Malawi

Monitoring abundance of threatened species is important for conservation planning. Lilian’s Lovebird Agapornis lilianae is a near-threatened small parrot found in mopane Colophospermum mopane woodland. Its population has not been investigated in any part of its range. We investigated the abundance and density of the Lilian’s Lovebird in Liwonde National Park, Malawi. Both distance sampling (line and point transects) methods and total counts (waterhole and flyway counts) were applied. The point count method gave very low numbers and was discontinued after the first year. Line transects conducted during the wet season had the highest density estimates of 17 ± 4.8 lovebirds km?2 of mopane woodland. However, number of observations per transect in each year were low. Waterhole counts had the lowest density estimates (10 ± 3.5 lovebirds km?2). Flyway counts gave an intermediate estimate (13 ± 3.0 lovebirds km?2). The total population of Lilian’s Lovebirds in Liwonde National Park is therefore estimated to be about 4 000 individuals. The use of line transect counts at the end of the rainy season is recommended for continued monitoring of Lilian’s Lovebirds abundance in Liwonde National Park.     

Detection Probability and Sources of Variation in White-Tailed Deer Spotlight Surveys

Abstract: As a first step in understanding structure and dynamics of white-tailed deer (Odocoileus virginianus) populations, managers require knowledge of population size. Spotlight counts are widely used to index deer abundance; however, detection probabilities using spotlights have not been formally estimated. Using a closed mark—recapture design, we explored the efficiency of spotlights for detecting deer by operating thermal imagers and spotlights simultaneously. Spotlights detected only 50.6% of the deer detected by thermal imagers. Relative to the thermal imager, spotlights failed to detect 44.2% of deer groups (≥1 deer). Detection probabilities for spotlight observers varied between and within observers, ranging from 0.30 (SE = 0.053) to 0.66 (SE = 0.058). Managers commonly assume that although road counts based on convenience sampling designs are imperfect, observers can gather population-trend information from repeated counts along the same survey route. Our results indicate detection rate varied between and within observers and surveyed transects. If detection probabilities are substantially affected by many variables, and if transect selection is not based on appropriate sampling designs, it may be impractical to correct road spotlight counts for detection probabilities to garner unbiased estimates of population size.     

Total Counts Versus Line Transects for Estimating Abundance of Small Gopher Tortoise Populations

Abstract: Status and trends of gopher tortoise (Gopherus polyphemus) populations are a critical information need for natural resource managers, researchers, and policy makers. Many tortoise populations are small and isolated, which can present challenges for deriving population estimates. Our objective was to compare abundance and density estimates for a small tortoise population derived using a total burrow count versus estimates obtained with line transect distance sampling (LTDS) using repeated surveys. We also compared results of the 2 survey methods using standard burrow-to-tortoise correction factors versus assessing occupancy of all burrows with a camera scope. In addition, we compared LTDS data obtained using a compass and measuring tape to define transects to those obtained using a Global Positioning System (GPS) and Personal Data Assistant (PDA) field computer to navigate transects. Line transect distance sampling with repeated surveys (both with a measuring tape and compass and with a GPS—PDA) yielded sufficient observations of tortoises to calculate population estimates. From 18% to 31% of burrows were occupied by tortoises as determined with the burrow camera. We found 25 burrows during the LTDS survey that we did not find in the total count survey, which demonstrated that the assumption of 100% detection for the total count was not met; hence, density or abundance measurements derived with this method were underestimates. We recommend using GPS—PDA technology, scoping all burrows detected, and using LTDS with repeated surveys to estimate abundance and density for small gopher tortoise populations.     

Local bumble bee decline linked to recovery of honey bees,drought effects on floral resources

Time series of abundances are critical for understanding how abiotic factors and species interactions affect population dynamics, but are rarely linked with experiments and also scarce for bee pollinators. This gap is important given concerns about declines in some bee species. I monitored honey bee (Apis mellifera) and bumble bee (Bombus spp.) foragers in coastal California from 1999, when feral A. mellifera populations were low due to Varroa destructor, until 2014. Apis mellifera increased substantially, except between 2006 and 2011, coinciding with declines in managed populations. Increases in A. mellifera strongly correlated with declines in Bombus and reduced diet overlap between them, suggesting resource competition consistent with past experimental results. Lower Bombus numbers also correlated with diminished floral resources. Declines in floral abundances were associated with drought and reduced spring rainfall. These results illustrate how competition with an introduced species may interact with climate to drive local decline of native pollinators.     

Accounting for imperfect detection of groups and individuals when estimating abundance

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recapture‐distance‐sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under‐counted, but not over‐counted. The estimator combines an MRDS model with an N‐mixture model to account for imperfect detection of individuals. The new MRDS‐Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS‐Nmix model to an MRDS model. Abundance estimates generated by the MRDS‐Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re‐allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.     

An Evaluation of Survey Methods for Estimating Northern Bobwhite Abundance in Southern Texas

Abstract: Distance sampling has been identified as a reliable and well-suited method for estimating northern bobwhite (Colinus virginianus) density. However, distance sampling using walked transects requires intense sampling to obtain precise estimates, thus making the technique impractical for large acreages. Researchers have addressed this limitation by either resorting to the use of indices (e.g., morning covey-call surveys) or incorporating the use of aerial surveys with distance sampling. Both approaches remain relatively untested. Our objectives were to 1) compare density estimates among morning covey-call surveys, helicopter transects, and walked transects; 2) test a critical assumption of distance sampling pertinent to helicopter surveys (i.e., all objects on line are detected); and 3) evaluate the underlying premise of morning covey-call surveys (i.e., that the no. of calling coveys correlates with bobwhite density). Our study was conducted on 3 study sites in Brooks County, Texas, USA, during October to December, 2001 to 2005. Comparisons between walked transects and morning covey-call surveys involved the entire 5-year data set, whereas helicopter transects involved only the latter 2 years. Density estimates obtained from helicopter transects were similar to walked transect estimates for both years. We documented a detection probability on the helicopter transect line of 70 ± 10.2% (% ± SE; n = 20 coveys). Morning covey-call surveys yielded similar density estimates to walked transect estimates during only 2 of 5 years, when walked transect estimates were the least accurate and precise. We detected a positive relationship (R² = 0.51; 95% CI for slope: 29.5–53.1; n = 63 observations) between covey density and number of coveys heard calling. We conclude that helicopter transects appear to be a viable alternative to walked transects for estimating density of bobwhites. Morning covey-call surveys appear to be a poor method to estimate absolute abundance and to depict general population trajectories.     

Comparison of survey methods for wintering grassland birds

ABSTRACT Although investigators have evaluated the efficacy of survey methods for assessing densities of breeding birds, few comparisons have been made of survey methods for wintering birds, especially in grasslands. In winter, social behavior and spatial distributions often differ from those in the breeding season. We evaluated the degree of correspondence between density estimates based on different survey methods. Surveys were conducted during two winters (2001–2002 and 2002–2003) on 16 grassland sites in southwestern Oklahoma. Line‐transect (using a detection function to account for birds present but not detected) and area‐search (where density was based on the total count within a given area) methods were employed. Observations on line transects were also analyzed as strip transects, where density was based on total count within a given strip width and no detection function was used. Savannah Sparrows (Passerculus sandwichensis), LeConte's Sparrows (Ammodramus leconteii), Song Sparrows (Melospiza melodia), Smith's Longspurs (Calcarius pictus), Chestnut‐collared Longspurs (C. ornatus), and Eastern Meadowlarks (Sturnella magna) were sufficiently abundant to allow comparison. Area‐search density estimates tended to be higher than line‐transect estimates for Savannah Sparrows, Song Sparrows, and Eastern Meadowlarks, suggesting that some individuals initially located close to the transect line were not detected on line transects. The area‐search and line‐transect methods gave similar density estimates for Chestnut‐collared and Smith's longspurs. Area‐search estimates of Eastern Meadowlarks were significantly higher in the second year of the study only. For this species, area‐search estimates did not differ from those of strip transects covering an equal area, so the reason for the differing meadowlark estimates is not clear. Higher density estimates using the area‐search method likely resulted from: (1) birds that might escape detection by hiding were more likely detected (flushed) during area searches because of the repeated passes through the area, and (2) birds close to the line in line transects escape detection by hiding, biasing those estimates low. We also evaluated the correspondence of density rankings for the six species as determined by the different survey methods and for the same species across survey sites. Correlations among the six species of the area‐search results with those of line transects and strip transects generally were high, increasing in 2002–2003 when densities of birds were greater. All three methods provided similar density rankings among species. Density rankings within species across sites for the four non‐longspur species generally were concordant for the three methods, suggesting that any of them will adequately reflect among‐site differences, especially when densities vary greatly across sites. Further research is needed to determine the extent to which grassland birds are missed on line transects. We suggest that workers using line transects to study these species give careful consideration and make additional efforts to satisfy the distance‐sampling assumption that all birds on or near the line are detected. If density is measured as a total count in a fixed area, we recommend that observers pass within <10 m of all points in the area.     

Models for Estimating Abundance from Repeated Counts of an Open Metapopulation

Summary Using only spatially and temporally replicated point counts, Royle (2004b, Biometrics 60, 108–115) developed an N ‐mixture model to estimate the abundance of an animal population when individual animal detection probability is unknown. One assumption inherent in this model is that the animal populations at each sampled location are closed with respect to migration, births, and deaths throughout the study. In the past this has been verified solely by biological arguments related to the study design as no statistical verification was available. In this article, we propose a generalization of the N ‐mixture model that can be used to formally test the closure assumption. Additionally, when applied to an open metapopulation, the generalized model provides estimates of population dynamics parameters and yields abundance estimates that account for imperfect detection probability and do not require the closure assumption. A simulation study shows these abundance estimates are less biased than the abundance estimate obtained from the original N ‐mixture model. The proposed model is then applied to two data sets of avian point counts. The first example demonstrates the closure test on a single‐season study of Mallards (Anas platyrhynchos), and the second uses the proposed model to estimate the population dynamics parameters and yearly abundance of American robins (Turdus migratorius) from a multi‐year study.     

Optimizing surveys for marsh songbirds: does timing matter?

Analysis of data from point counts, a common method for monitoring bird population trends, has evolved to produce estimates of various population parameters (e.g., density, abundance, and occupancy) while simultaneously estimating detection probability. An important consideration when designing studies using point counts is to maximize detection probability while minimizing variation in detection probability both within and between counts. Our objectives were to estimate detection probabilities for three marsh songbirds, including Marsh Wrens (Cistothorus palustris), Swamp Sparrows (Melospiza georgiana), and Yellow‐headed Blackbirds (Xanthocephalus xanthocephalus), as a function of weather covariates and to evaluate temporal variability in detection probability of these three species. We conducted paired, unlimited radius, 10‐min point counts during consecutive morning and evening survey periods for our three focal species at 56 wetlands in Iowa from 20 April to 10 July 2010. Mean detection probabilities ranged from 0.272 (SE = 0.042) for Marsh Wrens to 0.365 (SE = 0.052) for Swamp Sparrows. Time of season was positively correlated with detection probability for Swamp Sparrows, but was negatively correlated with detection probability for Yellow‐headed Blackbirds, suggesting that detection probability increased during the breeding season for Swamp Sparrows and was highest early in the breeding season for Yellow‐headed Blackbirds. Understanding how detection probabilities of marsh songbirds vary throughout the breeding season allows targeted survey efforts that maximize detection probabilities for these species. Furthermore, consistent detection probabilities of marsh songbirds during morning and evening survey periods mean that investigators have more time to conduct surveys for these birds, allowing greater flexibility to increase spatial and temporal replication of surveys that could provide more precise estimates of desired population parameters.     

How accurate are single site transect data for monitoring butterfly trends? Spatial and temporal issues identified in monitoring Lasiommata megera

Multiple transect counts following Butterfly Monitoring Scheme (UKBMS) guidelines and Jolly–Seber estimates of population size were used to monitor the abundance of second generation Lasiommata megera on a single site in southern England. The two methods resulted in different patterns of emergence being detected. The proportion of the population (estimated by Jolly–Seber) recorded with transect counts depended on the time of day and weather with afternoon transect counts best recording the trend in abundance over the flight period, but even then counts recorded a variable fraction of the population (6.2–51.3%). Increasing the frequency with which transect counts are carried out per week reduced variation and increased the fit of transect counts to Jolly–Seber generated population estimates. However, indices of abundance generated from randomly selected transect counts for L. megera within sampling weeks varied 4-fold and indices for other butterfly species were also highly variable. For L. megera, transect count variability is attributed to non-representative placement of the transect route and changes in the behaviour and spatial distribution in relation to population size and season. We suggest that transect counts need to be fully validated before the data are used to monitor changes of butterfly populations at individual sites.     

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.     

Improving Aquatic Warbler Population Assessments by Accounting for Imperfect Detection

Monitoring programs designed to assess changes in population size over time need to account for imperfect detection and provide estimates of precision around annual abundance estimates. Especially for species dependent on conservation management, robust monitoring is essential to evaluate the effectiveness of management. Many bird species of temperate grasslands depend on specific conservation management to maintain suitable breeding habitat. One such species is the Aquatic Warbler (Acrocephalus paludicola), which breeds in open fen mires in Central Europe. Aquatic Warbler populations have so far been assessed using a complete survey that aims to enumerate all singing males over a large area. Because this approach provides no estimate of precision and does not account for observation error, detecting moderate population changes is challenging. From 2011 to 2013 we trialled a new line transect sampling monitoring design in the Biebrza valley, Poland, to estimate abundance of singing male Aquatic Warblers. We surveyed Aquatic Warblers repeatedly along 50 randomly placed 1-km transects, and used binomial mixture models to estimate abundances per transect. The repeated line transect sampling required 150 observer days, and thus less effort than the traditional ‘full count’ approach (175 observer days). Aquatic Warbler abundance was highest at intermediate water levels, and detection probability varied between years and was influenced by vegetation height. A power analysis indicated that our line transect sampling design had a power of 68% to detect a 20% population change over 10 years, whereas raw count data had a 9% power to detect the same trend. Thus, by accounting for imperfect detection we increased the power to detect population changes. We recommend to adopt the repeated line transect sampling approach for monitoring Aquatic Warblers in Poland and in other important breeding areas to monitor changes in population size and the effects of habitat management.     

Using distance sampling techniques to estimate bottlenose dolphin (Tursiops truncatus) abundance at Turneffe Atoll,Belize

Reliable abundance estimates are critical for management and conservation of coastal small cetaceans. This is particularly important in developing countries where coastal human populations are increasing, the impacts of anthropogenic activities are often unknown, and the resources necessary to assess coastal cetaceans are limited. We adapted ship‐based line transect methods to small‐boat surveys to estimate the abundance of bottlenose dolphins (Tursiops truncatus) at Turneffe Atoll, Belize. Using a systematic survey design with random start and uniform coverage, 34 dolphin clusters were sighted during small‐boat line transect surveys conducted in 2005–2006. Distance sampling methods estimated abundance at 216 individuals (CV = 27.7%, 95% CI = 126–370). Due to species rarity in the Atoll, small sample size, and potential violations in line transect assumptions, the estimate should be considered preliminary. Nevertheless, it provides up‐to‐date information on the status of a regional population in an area under increasing threat of habitat loss and prey depletion via uncontrolled development and unsustainable fishing. This information will be useful as Belize develops a new conservation initiative to create a comprehensive and resilient marine protected area system. Our study illustrates the application of distance sampling methods to small‐boat surveys to obtain abundance estimates of coastal cetaceans in a region lacking resources.     

Challenges and opportunities for estimating abundance of a low-density moose population

Monitoring large herbivores across their core range has been readily accomplished using aerial surveys and traditional distance sampling. But for peripheral populations, where individuals may occur in patchy, low-density populations, precise estimation of population size and trend remains logistically and statistically challenging. For moose (Alces alces) along their southern range margin in northern New York, USA, we sought robust estimates of moose distribution, abundance, and population trend (2016–2019) using a combination of aerial surveys (line transect distance-sampling), repeated surveys in areas where moose were known to occur to boost the number of detections, and density surface modeling (DSM) with spatial covariates. We achieved a precise estimate of density (95% CI = 0.00–0.29 moose/km²) for this small population (656 moose, 95% CI = 501–859), which was patchily distributed across a large and heavily forested region (the 24,280-km² Adirondack Park). Local moose abundance was positively related to active timber management, elevation, and snow cover, and negatively related to large bodies of water. As expected, moose abundance in this peripheral population was low relative to its core range in other northern forest states. Yet, in areas where abundance was greatest, moose densities in New York approached those where epizootics of winter tick (Dermacentor albipictus) have been reported, underscoring the need for effective and efficient monitoring. By incorporating autocorrelation in observations and landscape covariates, DSM provided spatially explicit estimates of moose density with greater precision and no additional field effort over traditional distance sampling. Combined with repeated surveys of areas with known moose occurrence to achieve viable sample sizes, DSM is a useful tool for effectively monitoring low density and patchy populations.