Multiple Covariate Distance Sampling Research Articles

Acoustic density estimates of beaked whales off the mid-Atlantic coast of the USA in winter and spring

Increasing amounts of noise have been introduced into the marine environment by commercial, military and recreational activities over recent decades. Ziphiids (beaked whales in the Family Ziphiidae) are particularly sensitive to anthropogenic noise, which can lead to behavioural and physiological changes that may cause death in extreme cases. Despite these concerns, there are significant gaps in our knowledge of ziphiid distribution and density in areas exposed to noise. This study presents data from acoustic and visual vessel surveys conducted across the Outer Continental Shelf of North and South Carolina and southern Virginia in the USA (NOAA permits 14,809-03 and 16,473) with the aim of addressing data gaps for this region in spring and winter. Echolocation click trains were attributed to either Cuvier's (Ziphius cavirostris) or Gervais' (Mesoplodon europaeus) beaked whales based on peak frequency, 3 dB and 10 dB bandwidths, and inter-click interval. Estimates of click depth were used to correct estimates of perpendicular distance and improve detection functions used in Multiple Covariate Distance Sampling. Availability bias was quantified using tag data from other regions modified with local dive data. Swell height and sea surface temperature were found to affect the detection function and were therefore included in the final model. Incorporating cruise identity (winter vs. spring), candidate species (Cuvier's vs. Gervais' beaked whale) and/or cluster size did not improve model fit, suggesting there was no discernible seasonal effect, variation in detectability by species or increased probability of detection for larger groups. Design-based estimates of global beaked whale density (1.64 individuals per 100 km2: CI 0.88–3.03) and abundance (2963: CI 1597-5497) were then made incorporating a g(0) estimate of 0.43. These represent the first abundance estimates made for ziphiids using a towed hydrophone array off the USA's eastern seaboard. A Density Surface Model suggested slope and Sea Surface Temperature may influence ziphiid density in the region. This study provides seasonal data on deep diving beaked whales that can be used to inform management decisions regarding anthropogenic activities in this region.

Use of aerial distance sampling to estimate abundance of tule elk across a gradient of canopy cover and comparison to a concurrent fecal DNA spatial capture-recapture survey

Historically, aerial surveys have been used widely to monitor abundance of large mammals in the western United States. In California, such surveys have typically served as minimum count indices rather than true abundance estimates. Here, we evaluated the utility of aerial multiple covariate distance sampling (MCDS) to estimate abundance of three populations of tule elk (Cervus canadensis nannodes) in northern California. We also compared estimates and costs with published results from a concurrent fecal DNA spatial capture-recapture (SCR) survey. During December 2018 and 2019, we flew line transects for distance sampling of tule elk in Colusa and Lake counties. We modeled detection functions and evaluated effects of group size, canopy cover, and survey year. We averaged the top models comprising ≥0.95 of Akaike Model Weight and estimated abundance of both total and discrete populations. Detection probability increased with increasing group size and decreasing canopy cover. We estimated a two-year average total population size of N̂ = 674 elk (90% CI = 501–907) in our survey area which was similar to N̂ = 653 elk (90% CI = 573–745) from SCR estimates. Overall precision was greater (CV = 0.08; range = 0.11–0.30 by population) for SCR than for MCDS (CV = 0.18; range = 0.22–0.43 by population). Although estimates differed somewhat between methods for the individual populations, the combined estimate across the study region compared favorably. Total cost of SCR and MCDS surveys was $98,326 and $147,324, respectively. While SCR efforts were more precise and less expensive overall, our MCDS approach reduced staff time by 64% (587 person-hours) and the number of survey days by 87% (64 days). Our results suggest MCDS methods can produce reliable abundance estimates across a gradient of canopy cover, particularly when observations can be pooled across populations to decrease variance. We recommend future research to assess use of hybrid models, such as mark-recapture distance sampling or hierarchical distance sampling, to improve precision and estimation of detection probability.

Habitat selection and density of common pheasant (Phasianus colchicus) in Northern Italy: effects of land use cover and landscape configuration

Knowing the ecology of game species is important to define sustainable hunting pressure and to plan management actions aimed to maintain viable populations. Common pheasant (Phasianus colchicus) is one of the main gamebird species in Europe and North America, despite its native range extending from the Caucasus to Eastern China. This research aimed to define the environmental variables shaping the spatial distribution of male pheasants and to estimate their breeding density in an agroecosystem of northern Italy. During the breeding season, 2015, we carried out 372 point counts with unlimited distances, randomly placed following a stratified sampling survey design. The habitat requirements of the pheasant were evaluated following a presence vs. availability approach, using environmental variables related to land use cover and landscape configuration. We built generalized linear models with a binary distribution, selecting variables following an information-theoretic approach. Densities were estimated through both conventional and multiple-covariate distance sampling. We estimated a density of 1.45 males/km2, with 4.26 males/km2 in suitable areas and 0.91 males/km2 in unsuitable ones. We found pheasants in areas with meadows and tree plantations, which were used to find food and refuges from predators and bad weather conditions. Similarly, woodlands have a positive effect on species occurrence, whereas arable lands were avoided, specifically maize and paddy fields. We found little evidence that landscape configuration affects pheasant occurrence. We found pheasants to be negatively affected by the length of edges between woodlands and arable lands, whereas edges between woodlands and grasslands seem to be beneficial for the species. These findings could help landscape and wildlife managers to plan habitat improvement actions useful to maintain self-sustaining populations of this species, by increasing cover of woodlands, meadows, and tree plantations.

Cautious considerations for using multiple covariate distance sampling and seafloor terrain for improved estimates of rockfish density

Distance sampling is one of the most widely used methods for adjusting fish counts for detectability, which allows the estimation of absolute density. Further, abundance can be estimated spatially beyond the transect width with density surface models. The present study used a density surface modelling approach with survey data from line transects and terrain metrics from multibeam acoustic bathymetry data, integrated with a Geographic Information System, to estimate the population density of Pacific Ocean perchSebastes alutus(POP) within 6 sampling areas in the Gulf of Alaska (GOA) at 2 sampling scales: local and landscape. For adult POP, the final density model included depth as a significant predictor for density estimation at both the local and landscape scale. Additional factors included sponge coverage (local scale), aspect eastness and seafloor slope (landscape scale). Predicted densities of adult POP are highest on low (<5°) eastern-facing slopes with high sponge coverage (>75%), at depths of 100 to 200 m. By using habitat-based density models with data collected from line transect distance sampling and multibeam acoustic seafloor mapping surveys, we provide an alternative method for estimating rockfish abundance in untrawlable areas, which may help improve rockfish stock assessments and essential fish habitat descriptions and maps.

Estimating forest antelope population densities using distance sampling with camera traps

AbstractTraditional transect survey methods for forest antelopes often underestimate density for common species and do not provide sufficient data for rarer species. The use of camera trapping as a survey tool for medium and large terrestrial mammals has become increasingly common, especially in forest habitats. Here, we applied the distance sampling method to images generated from camera-trap surveys in Dja Faunal Reserve, Cameroon, and used an estimate of the proportion of time animals are active to correct for negative bias in the density estimates from the 24-hour camera-trap survey datasets. We also used multiple covariate distance sampling with body weight as a covariate to estimate detection probabilities and densities of rarer species. These methods provide an effective tool for monitoring the status of individual species or a community of forest antelope species, information urgently needed for conservation planning and action.

Mark‐Recapture Distance Sampling for Aerial Surveys of Ungulates on Rangelands

ABSTRACTAerial surveys are an efficient technique for counting animals over large geographic areas such as rangelands. In southwestern rangelands, aerial surveys are routinely conducted for ungulates, with the implicit understanding that abundance estimates represent an undercount. Distance sampling can correct for visibility bias, but assumes perfect detection on the survey line, a condition often violated in aerial surveys of ungulates. The incorporation of mark‐resight methods into the distance‐sampling framework, termed mark‐recapture distance sampling (MRDS), corrects for both visibility bias and imperfect detection on the survey line. However, the use of MRDS introduces logistical and technical constraints that may not be practical for aerial surveys. We conducted aerial surveys of ungulates on rangelands in south Texas, USA, to evaluate the feasibility and performance of MRDS relative to conventional distance sampling (CDS) and multiple covariate distance sampling (MCDS). We conducted surveys prior to and after leaf‐fall in 2013–2015 to test the hypothesis that distance sampling corrected for changes in visibility bias. We surveyed white‐tailed deer (Odocoileus virginianus), nilgai (Boselaphus tragocamelus), collared peccary (Pecari tajacu), and feral swine (Sus scrofa) on 4 sites. Each site was surveyed seasonally for 2 years; twice both prior to (Nov) and after leaf‐fall (Feb). Probability of detection on survey lines for each species was high (range = 0.82–0.97) and the average for each species was similar between seasons (0.89 and 0.92 during pre and post leaf‐fall, respectively). The MRDS density estimates often were only ~10% greater than CDS and MCDS estimates; all population estimates had overlapping 95% confidence intervals. Further, CDS and MCDS estimates were similar indicating that measured covariates (seat position, vegetation type, and cluster size) contributed little towards detection probabilities. Despite similar average probability of detection for all species before and after leaf‐fall (0.47 and 0.51, respectively), deer and nilgai population estimates were 22–59% lower during fall surveys than winter surveys. The discrepancy between consistent probability of detections with different population estimates suggests that availability bias, which cannot be addressed with distance sampling, was an issue. Overall, the MRDS technique addressed imperfect detection on the survey line and generated probabilities of detection in the survey area consistent with previous studies done in Texas. However, the extra costs (~US$13,000) and logistical hurdles to preserve observer independence for a small increase in precision of population estimates may not be justifiable. © 2020 The Wildlife Society.

Detection function, cluster size, density, and population size of Black Crowned Crane Balearica pavonina ceciliae in the upper Blue Nile River, Lake Tana area

The aim of the study was to investigate the abundance, density and cluster size of Black Crowned Cranes. Seventy four and 56 transects were examined in 14,764 ha of land in 2015 (wet season) and 2016 (dry season), respectively. Multiple Covariate Distance Sampling model was employed. The encounter rate, detection probability, expected cluster size and density were parameters for estimation. Hazard rate key (σ=0.3), detection function g(x)=1-exp[-(x/σ) ^(-β)], x≤w was selected for analysis. Cluster analysis based on exact sizes was computed by regression of log(s(i)) on g(x(i)). The minimum Akaike Information Criterion was chosen during estimator selection. The result showed that the cluster size of cranes during the wet season in wetland and farmland habitats regression estimate were Cwi=0.73+0.16*xi; and Cfi=0.52+-0.21*xi, respectively. Similarly, in 2016, the regression estimate of wetland and farmland were Cwi=0.16+0.56*xi and Cfi=0.20+-0.34*xi, respectively. During the wet season in 2015, in the wetland habitat, the crane density was estimated 0.21768±0.82 per hectare, and the total population (N) was estimated to be 1472±554.62. Whereas in the farmland, crane density was estimated 0.79921 E-01±0.13370E-01 per hectare, and the total population (N) was estimated to be 639. The total density and abundance of Black Crowned Cranes during the wet season in 2015 was estimated. The wet season pooled density estimate was 14.304 cranes per 100 hectares with (% CV = 26.75, df = 50.2, 95%CI= 0.84355E-01=CI = 0.24254) and the population size was estimated to be 2112 cranes with (% CV = 26.75, df = 50.2, 95%CI = 1245=CI = 3581). During the dry season, in 2016, the crane density was estimated 0.3625±0.6958E-01 per hectare, and the total population (N) was estimated to be 2452±470.65. In the farmland, the cranes density was estimated 0.13904±0.14809E-01 per hectare, and the total population (N) was estimated to be 1112±118.44. The dry season pooled density estimate was 24.142 cranes per 100 hectares with (%CV=13.62, df = 164.02, 95%CI = 0.18473=CI= 0.31550) and the population was estimated to be 3564 cranes with (%CV=13.62, df = 164.02, 95%CI = 2727=CI = 4658). In conclusion, the cluster size of cranes in wetland and farmland habitat during the dry season showed that the species consisted of a small number of cranes per family. However, the wetland habitat was more suitable than the farmland in consisting of larger cluster size and overall population of cranes. Wetland degradation is a threat for cranes.

Modelling the effect of covariates on the detectability and density of native blackbucks and invasive feral-horse using Multiple Covariate Distance Sampling at Point Calimere Wildlife Sanctuary, Southern India

Reliable estimates of population size and a knowledge of determinants of detectability and density estimates are crucial for effective conservation of species. Using Multiple Covariate Distance Sampling (MCDS), we modelled the influence of covariates on detection probability and density estimates of native blackbuck Antilope cervicapra and the invasive feral-horse Equus caballus at Point Calimere Wildlife Sanctuary. Grids of 1 × 1 km size were overlaid on the study area with a 1-km line transect in alternate grid cells. Sixteen transects were walked four times each, which detected 199 blackbuck and 152 feral-horse clusters. On each sighting, the climatic, habitat and anthropogenic covariates were recorded, which are likely to affect detection probability. At first, exploratory analyses were made using Conventional Distance Sampling (CDS) to arrive at estimates. Later, in Multiple Covariate Distance Sampling (MCDS), key models were fit into the dataset after selecting the potential covariates that had a significant effect on detection distances obtained from FAMD/PCA, and the best one was selected based on AIC. The MCDS analysis in blackbuck included covariates, viz., distance to water in the best model (29 individuals/km2; CI 22–36; detection probability = 0.58), followed by distance to feral-horse, sampling time and principal diet. The covariate distance to water emerged as the best model for feral-horse as well (13 individuals/km2; CI 9–18; detection probability = 0.36), followed by distance to cattle and principal diet. While the MCDS approach outperformed the CDS global and survey-strata estimates in blackbuck, both the approaches had a marginal difference in feral-horse. Post-stratification analysis showed that blackbuck density increased significantly with distance to water and feral-horse, but insignificantly with the absence of principal diet; whereas, the density of the feral-horse increased significantly with distance to water and cattle in the presence of principal diet. These findings suggest the ability of feral-horse to keep the blackbuck away from optimal areas, where the principal diet is abundant. Our study, thus, illustrates the need for the use of MCDS approach that ascertained (i) reliable population density estimates, (ii) spatiotemporal constraint on large herbivores caused by overabundance of water during the wet season, and (iii) competitive interaction of the invasive feral-horse with the native blackbuck and its likely effect on the latter keeping away from the former and the principal diet to overcome competition. Thus, the study highlights the impact of feral-horse on the native species and suggests measures for the long-term conservation of the blackbuck.

Population Change of Red Kites Milvus milvus in Central Southern England between 2011 and 2016 Derived from Line Transect Surveys and Multiple Covariate Distance Sampling

Successful reintroduction programmes are usually defined by an increase in size and extent of the new population after a given period of time. Among studies of birds, these population estimates are often focused on the monitoring of nesting attempts and productivity. For many raptors, however, this approach can overlook a large number of non-breeding adults and immature birds leading to underestimation of population size and reproductive potential. A more thorough approach is to generate assessments of total population size. In this study we used a line transect survey methodology and multiple covariate distance sampling to assess the change in population size of a reintroduced raptor species, Red Kite Milvus milvus, across a 2600 km2 area of central southern England. Surveys were performed in spring and autumn between 2011 and 2016 in an area 45 km to the south of the initial English reintroduction project which started 25 years previously. Survey routes avoided using roads where possible to counter the potential attraction that such landscape features may have (e.g. increased food availability, perches etc.). The use of roads was unavoidable in some instances; however, we found no evidence of Red Kite attraction to these landscape features when comparing distances of observations from stretches along roads with 5000 randomly-generated locations. Distance of detection was influenced by bird activity (greatest when the bird was on the ground or interacting with other birds) and extent of woodland but not by time of day, seasonality or when comparing between years. During the five years, estimated population size doubled from approximately 490 to 1100 individuals; a density of one Red Kite per 2.5–3.5 km2. This suggests an increase in the breeding population in the study area from c. 95 to 174 pairs. During the study, rate of population growth was not uniform; rapid growth was recorded in years two and three followed by a slowing over the last two years of the study. While an overall increase in population and availability of suitable nesting habitat across south-eastern England indicates that there is still potential for expansion of the Red Kite breeding population, other factors are potentially limiting this growth.

Abundance estimates of six species of Delphinidae cetaceans off the Pacific coast of Japan between 1985 and 2015

AbstractThe abundances of six delphinids off the Pacific coast of Japan were estimated using line transect survey data collected in 1985, 1992, 2006, 2007, 2014, and 2015. A multiple covariate distance sampling method was used to estimate a detection function. Because of unsurveyed blocks in 2006, 2007, and 2015, total abundance was estimated only in 1985, 1992, and 2014, when the estimated abundances were for the 3 yr respectively 3,626 (coefficient of variation = 0.74), 2,085 (0.85), and 5,029 (1.24) for rough‐toothed dolphins; 72,762 (0.48), 37,513 (0.54), and 44,529 (0.57) for common bottlenose dolphins; 59,727 (0.46), 60,014 (0.62), and 130,718 (0.43), for pantropical spotted dolphins; 71,983 (0.36), 6,972 (1.03), and 144,163 (0.69) for Risso's dolphins; 38,966 (0.41), 20,507 (0.57), and 31,569 (0.65) for short‐finned pilot whales; and 8,135 (1.23), 5,051 (1.70), and 56,522 (0.56) for melon‐headed whales. To deal with measurement error due to distance and angle, we additionally estimated error‐corrected abundance using data from distance and angle experiments. These new abundance estimates and time series will update 20‐yr‐old estimates and provide a baseline to facilitate dolphin conservation and management around Japan.

R2MCDS: An R package for the analysis of multi-species datasets collected using distance sampling

We present R2MCDS, an R package that provides tools to call the multiple-covariate distance sampling (MCDS) engine from the Distance 6.2 software in the R environment. We built R2MCDS for the analysis of line transects data collected using distance intervals. Based on the user inputs, the package writes a command file, runs the MCDS engine and re-imports the resulting statistics file as an R object. The package is particularly useful when the user wants to repeat the same distance analysis, as in multi-species surveys. We demonstrate the applicability of the package for multi-species surveys using data from the Eastern Canada Seabirds at Sea (ECSAS) database.

Double-observer evaluation of pronghorn aerial line-transect surveys

Context Distance sampling is used to estimate abundance for several taxa, including pronghorn (Antilocapra americana). Comparisons between population estimates derived from quadrat sampling and distance sampling suggest that distance sampling underestimates pronghorn density, likely owing to violations of the critical assumption of distance sampling that all pronghorn within the innermost distance band (A band; nearest to the aircraft) are detected. Aims We sought to rigorously test the assumption that all pronghorn clusters are detected within the innermost distance band by applying a double-observer approach to an established pronghorn aerial-survey protocol. Additionally, we evaluated potential effects of cluster size, landscape composition and seat position (front seat versus rear) on the probability of detection. Methods We conducted aerial line-transect distance-sampling surveys using independent, paired observers and modelled the probability of detection with mark–recapture distance-sampling (MRDS) analysis techniques that explicitly estimate the probability of detection for pronghorn clusters in the innermost distance band. We compared density estimates produced by the MRDS analysis with those produced by multiple-covariate distance sampling (MCDS), a method that assumes complete detection for clusters on the transect line. Key results We identified violations of the assumption that all clusters within the innermost distance band were detected, which would contribute to proportional biases in density estimates for analysis techniques that assume complete detection. The frequency of missed clusters was modest from the front-seat position, with 45 of the 47 (96%) clusters in the A band detected. In contrast, the frequency of missed clusters was more substantial for the rear position, from which 37 of 47 (79%) clusters in the A band were detected. Further, our analysis showed that cluster size and landscape composition were important factors for pronghorn sightability. Conclusions When implementing standard survey methodologies, pronghorn aerial-line transect surveys underestimated population densities. A double-observer survey configuration allowed us to quantify and correct for the bias caused by the failure of observers to detect all pronghorn clusters within the innermost distance band. Implications Population monitoring programs should incorporate double-observer validation trials to quantify the extent of bias owing to undetected clusters within the innermost distance band realised under typical survey conditions. Wildlife managers can improve the precision of pronghorn aerial line-transect surveys by incorporating cluster size and measures of landscape composition and complexity into detection models without incurring additional survey costs.

How many are there? Multiple-covariate distance sampling for monitoring pampas deer in Corrientes, Argentina

Context The pampas deer (Ozotoceros bezoarticus) is an endangered species in Argentina. Scarce information exists about one of the four last populations that survive in Corrientes province, where direct counts estimated a population of <500 individuals. Aims To evaluate the status of the pampas deer population in Corrientes by applying a standardised methodology and to develop methodological recommendations for future deer monitoring. Methods We conducted six population censuses between 2007 and 2010, using line transects placed on roads throughout 1200 km2 of grasslands in the Aguapey region, Corrientes, Argentina. From a moving vehicle, we counted every pampas deer group observed along transects. We used Distance 6.0 and its multiple-covariate distance sampling engine to estimate deer density, while exploring the potential effect of roads, habitat type, hour, season, observer experience and survey effort on deer occurrence and density estimation. Key results The occurrence of pampas deer was irrespective of transect location (minor or major road) but a greater number of animals was detected over transects in minor roads and in areas covered by grasslands with young pine plantations. We estimated a density of 1.17 individuals km–2 (s.e. = 0.52), and habitat type was the most important covariate for density estimation. We estimated a total population of 1495 deer (95% CI = 951–2351, CV = 23.27%) for the Aguapey region in Argentina. Conclusions Corrientes hosts one of the largest populations of pampas deer in Argentina, with ~1000 individuals. The fact that we estimated a larger population than did previous studies could be explained either by actual population growth during the past 10 years, or by the use of more exhaustive and sophisticated sampling design and data analysis. Implications Population surveys using covariate distance sampling on ground line transects can provide more realistic population estimates than do other simpler methods. Our population estimates and methods can be used as a baseline for future monitoring of this population, as long as factors such as sampling effort, type of roads for locating transects, and habitat type are considered in future analysis.

Improving distance sampling: accounting for covariates and non‐independency between sampled sites

Summary There is currently much interest in replacing the design‐based component of conventional distance sampling methods by a modelling approach where animal densities are related to environmental covariates. These models allow identification of relationships between density and covariates. One of the uses of such models is to assess the effects of some intervention on numbers for species of conservation interest in designed distance sampling experiments. In this context, we use an integrated likelihood approach for modelling sample counts, adopting a Poisson model and allowing imperfect detectability on the sample plots. We use the method of Royle, Dawson & Bates (2004, Ecology, 85, 1591), extended to model heterogeneity in detection probabilities using either multiple covariate distance sampling methods or stratification. Moreover, we include a random effect for site in the plot abundance model to accommodate correlation in repeat counts at a single site. These developments were motivated by a large‐scale experimental study to assess the effects of establishing conservation buffers along field margins on indigo buntings in several US states. We analyse the data using an integrated likelihood and include model selection for both the Poisson rate of counts and detection probabilities. We assess model performance by comparing our results with those using a two‐stage approach (Buckland et al. 2009, Journal of Agricultural, Biological, and Environmental Statistics, 14, 432) which we extended by including a random effect for site in the plot abundance model. The two methods led to the same selected models and gave similar results for parameters, which revealed significant beneficial effects of buffers on indigo bunting densities. Densities on buffered fields were on average 35% higher than on unbuffered fields. Using a detection function stratified by state captured some of the heterogeneity in detection probabilities between the nine states included in the analyses. Synthesis and applications. We develop and compare two methods for analysing data from large‐scale distance sampling experiments with imbalanced repeat measures. By including a random site effect in the plot abundance model, we relax the assumption of independent sample counts which is generally made for distance sampling methods, and we allow inference to be drawn for the wider region that the sites represent.

Estimating Western Scrub-Jay Density in California by Multiple-Covariate Distance Sampling

Using multiple-covariate distance sampling with seasonal point transects, we surveyed for the Western Scrub-Jay (Aphelocoma californica californica group) over a substantial portion of its range in California . Our goals were to produce seasonal and habitat-specific estimates of the scrub-jay's regional density and abundance in 2008 and to demonstrate how the concurrent collection and analysis of covariate data may be useful in improving estimates of bird density. Density and abundance estimates implied a significant 38% increase over 2008, from a low of 24 jays km-2 (2.3 × 106 jays) in February to a high of 78 jays km-2 (7.5 × 106 jays) in November. Density was greatest in agricultural habitats (98 jays km-2) and least in rural habitats (38 jays km-2). Averaged over the study, abundance was greatest in agricultural habitats (2.6 × 106 jays) and least in urban habitats (3.6 ×105 jays). Inclusion of covariates such as habitat type, observer, weather, and time of day often increased the precision of density estimates, and it significantly improved model results in one case. As detailed in this study, the techniques of multiple-covariate distance sampling may have application as effective and noninvasive methods for obtaining more precise estimates of bird density and monitoring the density and abundance of species across broad habitats.

Abundance, Distribution, and Group Composition of Indian River Lagoon Bottlenose Dolphins (Tursiops truncatus)

Information on the abundance and distribution of cetaceans is essential to management and conservation and necessary to assess mortality trends and anthropogenic impacts for stock assessment. Linetransect aerial surveys (n = 45) were conducted to assess bottlenose dolphin (Tursiops truncatus) abundance, distribution, and group composition in the Indian River Lagoon (IRL) estuary system, Florida, from 2002 to 2004. Calves composed 9.41% of all known age class animals sighted. Multiple covariate distance sampling was used to estimate abundance. Abundance estimates varied seasonally, ranging between 362 (95% CI = 192 to 622; summer 2003) and 1,316 dolphins (95% CI = 795 to 2,061; winter 2002-2003), with a mean abundance of 662 dolphins (95% CI = 544 to 842). Abundance estimates for the Mosquito Lagoon sub-basin exhibited the greatest seasonal variability. Seasonal differences in abundance within strata suggest seasonal movement patterns. This study provides the first abundance estimate for IRL dolphins in over 30 y. Further studies that investigate evidence of influx/efflux are needed to better understand the population biology of IRL dolphins.

Distance software: design and analysis of distance sampling surveys for estimating population size

Summary 1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built‐in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple‐covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state‐of‐the‐art software that implements these methods is described that makes the methods accessible to practising ecologists.

Abundance, trends and distribution of baleen whales off Western Alaska and the central Aleutian Islands

Large whales were extensively hunted in coastal waters off Alaska, but current distribution, population sizes and trends are poorly known. Line transect surveys were conducted in coastal waters of the Aleutian Islands and the Alaska Peninsula in the summer of 2001–2003. Abundances of three species were estimated by conventional and multiple covariate distance sampling (MCDS) methods. Time series of abundance estimates were used to derive rates of increase for fin whales ( Balaenoptera physalus) and humpback whales ( Megaptera novaeangliae). Fin whales occurred primarily from the Kenai Peninsula to the Shumagin Islands, but were abundant only near the Semidi Islands and Kodiak. Humpback whales were found from the Kenai Peninsula to Umnak Island and were more abundant near Kodiak, the Shumagin Islands and north of Unimak Pass. Minke whales ( B. acutorostrata) occurred primarily in the Aleutian Islands, with a few sightings south of the Alaska Peninsula and near Kodiak Island. Humpback whales were observed in large numbers in their former whaling grounds. In contrast, high densities of fin whales were not observed around the eastern Aleutian Islands, where whaling occurred. Average abundance estimates (95% CI) for fin, humpback and minke whales were 1652 (1142–2389), 2644 (1899–3680), and 1233 (656–2315), respectively. Annual rates of increase were estimated at 4.8% (95% CI=4.1–5.4%) for fin and 6.6% (5.2–8.6%) for humpback whales. This study provides the first estimate of the rate of increase of fin whales in the North Pacific Ocean. The estimated trends are consistent with those of other recovering baleen whales. There were no sightings of blue or North Pacific right whales, indicating the continued depleted status of these species.

Estimating abundance of killer whales in the nearshore waters of the Gulf of Alaska and Aleutian Islands using line-transect sampling

Killer whale (Orcinus orca Linnaeus, 1758) abundance in the North PaciWc is known only for a few populations for which extensive longitudinal data are available, with little quantitative data from more remote regions. Line-transect ship surveys were con- ducted in July and August of 2001-2003 in coastal waters of the western Gulf of Alaska and the Aleutian Islands. Conventional and Multiple Covariate Distance Sampling methods were used to estimate the abun- dance of diVerent killer whale ecotypes, which were distinguished based upon morphological and genetic data. Abundance was calculated separately for two data sets that diVered in the method by which killer whale group size data were obtained. Initial group size (IGS) data corresponded to estimates of group size at the time of Wrst sighting, and post-encounter group size (PEGS) corresponded to estimates made after closely approach- ing sighted groups. 'Resident'-type (Wsh-eating) killer whales were more abundant than the 'transient'-type (mammal-eating). Abundance estimates of resident killer whales (991 (95% CI = 379-2,585) (IGS) and 1,587 (95% CI = 608-4,140) (PEGS)), were at least four times greater than those of the transient killer whales (200 (95% CI = 81-488) (IGS) and 251 (95% CI = 97-644) whales (PEGS)). The IGS estimate of abundance is preferred for resident killer whales because the estimate based on PEGS data may show an upward bias. The PEGS estimate of abundance is likely more accurate for transients. Residents were most abundant near Kodiak Island in the northern Gulf of Alaska, around Umnak and Unalaska Islands in the eastern Aleutians, and in Seguam Pass in the central Aleutians. This ecotype was not observed between 156 and 164°W, south of the Alaska Peninsula. In contrast, transient killer whale sightings were found at higher densities south of the Alaska Peninsula between the Shumagin Islands and the eastern Aleutians. Only two sightings of 'oVshore'-type killer whales were recorded during the surveys, one northeast of Unalaska Island and the other south of Kodiak Island. These are the Wrst estimates of abundance of killer whale ecotypes in the Aleutian Islands and Alaska Peninsula area and provide a baseline for quantifying the role of these top predators in their ecosystem.