Comparison of density estimates derived from strip transect and distance sampling for underwater visual censuses: a case study of Chaetodontidae and Pomacanthidae

Abstract Inferences based on counts adjusted for detectability represent a marked improvement over unadjusted counts, which provide no information about true population density and rely on untestable and unrealistic assumptions about constant detectability for inferring differences in density over time or space. Distance sampling is a widely used method to estimate detectability and therefore density. In the standard method, we model the probability of detecting a bird as a function of distance alone. Here, we describe methods that allow us to model probability of detection as a function of additional covariates—an approach available in DISTANCE, version 5.0 (Thomas et al. 2005) but still not widely applied. The main use of these methods is to increase the reliability of density estimates made on subsets of the whole data (e.g., estimates for different habitats, treatments, periods, or species), to increase precision of density estimates or to allow inferences about the covariates themselves. We present a case study of the use of multiple covariates in an analysis of a point-transect survey of Hawaii Amakihi (Hemignathus virens). Amélioration des estimations de densité d’oiseaux par l’utilisation de l’échantillonnage par la distance avec covariables multiples

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Estimating western ringtail possum (Pseudocheirus occidentalis) density using distance sampling

Australian Mammalogy ◽

10.1071/am09037 ◽

2010 ◽

Vol 32 (2) ◽

pp. 197 ◽

Cited By ~ 1

Author(s):

G. R. Finlayson ◽

A. N. Diment ◽

P. Mitrovski ◽

G. G. Thompson ◽

S. A. Thompson

Keyword(s):

Urban Development ◽

Population Size ◽

Western Australia ◽

Distance Sampling ◽

Reliable Estimate ◽

Population Estimates ◽

Density Estimates ◽

The Subject ◽

Ringtail Possum

A reliable estimate of population size is of paramount importance for making management decisions on species of conservation significance that may be impacted during development. The western ringtail possum (Pseudocheirus occidentalis) is regularly encountered during urban development and is the subject of numerous surveys to estimate its abundance. A variety of techniques have been used for this species with mixed results. This paper reports on a case study using distance sampling to estimate density of P. occidentalis in a small habitat remnant near Busselton, Western Australia. Density estimates obtained were within the range of previous studies of this species and we suggest that this technique should be employed in future surveys to improve the accuracy of population estimates for this species before development.

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Conventional distance sampling versus strip transects and abundance indices for estimating abundance of greater gliders (Petauroides volans) and eastern ringtail possums (Pseudocheirus peregrinus)

Wildlife Research ◽

10.1071/wr18155 ◽

2019 ◽

Vol 46 (6) ◽

pp. 518

Author(s):

Luke D. Emerson ◽

Guy-Anthony Ballard ◽

Karl Vernes

Keyword(s):

Distance Sampling ◽

Probability Of Detection ◽

Density Estimate ◽

Imperfect Detection ◽

Density Estimates ◽

Transect Line ◽

Eucalypt Forest ◽

Arboreal Marsupials ◽

Abundance Indices ◽

Strip Transect

Abstract ContextAccurate estimates of abundance are extremely useful for wildlife management and conservation. Estimates generated from distance sampling are typically considered superior to strip transects and abundance indices, as the latter do not account for probability of detection, thereby risking significant error. AimTo compare density estimates generated from conventional distance sampling (CDS) of arboreal marsupials with strip transect density estimates and abundance indices. MethodsOff-track CDS and strip transects were used to estimate densities of P. volans and P. peregrinus across ~2.6km2 of remnant eucalypt forest at Mt Duval in north-eastern New South Wales. Key resultsCDS density estimates for P. volans (1.36ha−1, 95% confidence interval (CI) of 1.07–1.72ha−1) and P. peregrinus (0.28ha−1, 95% CI 0.22–0.35ha−1) were consistent with densities reported in other studies conducted in open eucalypt forests. A strip transect width of 40m for P. volans resulted in a collective set of values for density (1.35ha−1), error (s.e.±0.14), precision (cv 0.10) and 95% CI (1.07–1.62ha−1) closest to those associated with the CDS-generated density estimate (1.36ha−1, s.e.±0.15, cv 0.10, 95% CI 1.07–1.72ha−1). Strip widths of 10 to 40m resulted in density estimates for P. peregrinus closest to those generated through CDS, but much less precise. ConclusionsAlthough a 40-m wide strip transect provided a robust density estimate for P. volans at Mt Duval, this is unlikely to be consistent across different study areas. Strip transects provided less precise density estimates, or underestimated P. peregrinus density at Mt Duval, when compared with CDS density estimates. CDS should be favoured over strip transects or abundance indices for estimating P. volans and P. peregrinus abundance, because it is capable of providing more meaningful and robust abundance estimates by accounting for the probability of detection from the transect line across different habitats. ImplicationsResearchers, conservation managers and decision makers should be aware that common methods for assessing arboreal marsupial abundance have serious potential weaknesses. Thus, it would be prudent to invest in studies that address imperfect detection to improve the quality of monitoring data.

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Evaluating Alternative Flight Plans in Thermal Drone Wildlife Surveys—Simulation Study

Remote Sensing ◽

10.3390/rs13061102 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1102

Author(s):

Julia Witczuk ◽

Stanisław Pagacz

Keyword(s):

Computer Simulations ◽

Survey Design ◽

Distance Sampling ◽

Line Of Sight ◽

Density Estimates ◽

Accuracy And Precision ◽

Survey Costs ◽

Random Survey ◽

Density Population

The rapidly developing technology of unmanned aerial vehicles (drones) extends to the availability of aerial surveys for wildlife research and management. However, regulations limiting drone operations to visual line of sight (VLOS) seriously affect the design of surveys, as flight paths must be concentrated within small sampling blocks. Such a design is inferior to spatially unrestricted randomized designs available if operations beyond visual line of sight (BVLOS) are allowed. We used computer simulations to assess whether the VLOS rule affects the accuracy and precision of wildlife density estimates derived from drone collected data. We tested two alternative flight plans (VLOS vs. BVLOS) in simulated surveys of low-, medium- and high-density populations of a hypothetical ungulate species with three levels of effort (one to three repetitions). The population density was estimated using the ratio estimate and distance sampling method. The observed differences in the accuracy and precision of estimates from the VLOS and BVLOS surveys were relatively small and negligible. Only in the case of the low-density population (2 ind./100 ha) surveyed once was the VLOS design inferior to BVLOS, delivering biased and less precise estimates. These results show that while the VLOS regulations complicate survey logistics and interfere with random survey design, the quality of derived estimates does not have to be compromised. We advise testing alternative survey variants with the aid of computer simulations to achieve reliable estimates while minimizing survey costs.

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Problems with Avian Point Counts for Estimating Density of Northern Bobwhite—A Case Study

Journal of Fish and Wildlife Management ◽

10.3996/092010-jfwm-033 ◽

2011 ◽

Vol 2 (1) ◽

pp. 117-121 ◽

Cited By ~ 2

Author(s):

Roger D. Applegate ◽

Robert E. Kissell ◽

E. Daniel Moss ◽

Edward L. Warr ◽

Michael L. Kennedy

Keyword(s):

Count Data ◽

Distance Sampling ◽

Bird Species ◽

Northern Bobwhite ◽

Model Fit ◽

Point Count ◽

Point Counts ◽

Occupancy Estimation ◽

Detection Probabilities

Abstract Point count data are used increasingly to provide density estimates of bird species. A favored approach to analyze point count data uses distance sampling theory where model selection and model fit are important considerations. We used uniform and half normal models and assessed model fit using χ2 analysis. We were unsuccessful in fitting models to 635 northern bobwhite Colinus virginianus observations from 85 avian point locations spanning 6 y (P ≤ 0.05). Most observations (74%) occurred in the outermost (>100-m) distance radius. Our results violated the assumptions that all observations at the point are detected. The assumption that birds were assigned to the correct distance interval also was probably violated. We caution managers in implementing avian point counts with distance sampling when estimating northern bobwhite population density. We recommend exploring other approaches such as occupancy-estimation and modeling for estimating detection probabilities.

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A Comparison of White-Winged Dove Zenaida asiatica Densities Estimated During Morning and Evening Surveys

Journal of Fish and Wildlife Management ◽

10.3996/092011-jfwm-059 ◽

2012 ◽

Vol 3 (1) ◽

pp. 158-163 ◽

Cited By ~ 1

Author(s):

Michael F. Small ◽

Joseph A. Veech ◽

John T. Baccus

Keyword(s):

Distance Sampling ◽

Visual Observation ◽

Probability Of Detection ◽

Reasonable Assumption ◽

Zenaida Asiatica ◽

Density Estimates ◽

Bird Populations ◽

Game Birds ◽

Population Sizes ◽

Cost Efficient

Abstract Surveying bird populations through visual observation is generally limited to morning. The focus on morning surveys is based on the reasonable assumption that detection is more likely when birds are most active. However, population surveys could become more time- and cost-efficient if both morning and evening sampling were equally effective, particularly for game birds, such as white-winged dove Zenaida asiatica. Texas Parks and Wildlife Department has recently implemented distance sampling to estimate population sizes and monitor an ongoing range expansion of this species. We compared morning vs. evening density estimates for white-winged doves sampled in Mason, Texas, on six separate occasions during summer 2006. Program DISTANCE (version 5.0) calculated similar detection probabilities and density estimates between paired morning and evening sampling periods. Probability of detection ranged from 0.27 to 0.46 for both morning and evening samples. Densities, in individuals/ha, ranged from 2.54 to 4.02 for morning sampling and 2.48 to 4.31 for evening sampling. In addition, variables (number of observations, cluster size, distance to cluster) used by DISTANCE did not vary substantially between morning and evening surveys. Our results suggest evening surveys are as effective as the conventional protocol of surveying white-winged doves only in the morning. Additional studies, using Program DISTANCE, should be conducted to similarly evaluate other species.

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Landbird Counting Techniques: Current Practices and an Alternative

The Auk ◽

10.1093/auk/119.1.46 ◽

2002 ◽

Vol 119 (1) ◽

pp. 46-53 ◽

Cited By ~ 45

Author(s):

Steven S. Rosenstock ◽

David R. Anderson ◽

Kenneth M. Giesen ◽

Tony Leukering ◽

Michael F. Carter

Keyword(s):

Distance Sampling ◽

Field Studies ◽

Empirical Models ◽

Viable Alternative ◽

Density Estimates ◽

Abundance Index ◽

Point Counts ◽

Density Index ◽

Conceptual Overview ◽

Current Practices

AbstractCounting techniques are widely used to study and monitor terrestrial birds. To assess current applications of counting techniques, we reviewed landbird studies published 1989–1998 in nine major journals and one symposium. Commonly used techniques fell into two groups: procedures that used counts of bird detections as an index to abundance (index counts), and procedures that used empirical models of detectability to estimate density. Index counts rely upon assumptions concerning detectability that are difficult or impossible to meet in most field studies, but nonetheless remain the technique of choice among ornithologists; 95% of studies we reviewed relied upon point counts, strip transects, or other index procedures. Detectability-based density estimates were rarely used and deserve wider application in landbird studies. Distance sampling is a comprehensive extension of earlier detectability-based procedures (variable-width transects, variable circular plots) and a viable alternative to index counts. We provide a conceptual overview of distance sampling, specific recommendations for applying this technique to studies of landbirds, and an introduction to analysis of distance sampling data using the program DISTANCE.

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An Evaluation of the Strip Transect Method for Censusing Bird Communities in Forests

Wildlife Research ◽

10.1071/wr9860203 ◽

1986 ◽

Vol 13 (2) ◽

pp. 203 ◽

Cited By ~ 6

Author(s):

RH Harden ◽

RJ Muir ◽

DR Milledge

Keyword(s):

New South ◽

Bird Communities ◽

Density Estimate ◽

Density Estimates ◽

Number Of Species ◽

South Wales ◽

Sclerophyll Forest ◽

Transect Counts ◽

Estimate Number ◽

Strip Transect

The effects of varying transect width and census duration on the number of birds counted, the density estimate, number of species detected and the percentage of unidentified birds were examined in rainforest and wet sclerophyll forest at Mount Nardi in northern New South Wales. The nine combinations of three strip widths (40, 60 and 80 m) and three durations of census (24, 18 and 12 min) were compared in 200-m-long transects in each forest. The census of birds was more sensitive to changes in census duration than in strip width, and the effects were greater in the rainforest than the wet sclerophyll forest. Both the precision of the density estimates and the number of species detected were highest for the narrowest strips censused for the longest time. The bias of the density estimate varied with the treatments both within and between forests, and thus the strip transect could not be used to compare them. We suggest that variation in bias between sites may be a problem common to all transect counts of birds.

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Development of a species distribution model for fin whales (Balaenoptera physalus) within a Bayesian hierarchical framework: Implications for uncertainty

10.7287/peerj.preprints.27424 ◽

2018 ◽

Author(s):

Douglas B Sigourney ◽

Samuel Chavez-Rosales ◽

Paul Conn ◽

Lance Garrison ◽

Elizabeth Josephson ◽

...

Keyword(s):

Species Distribution ◽

Species Distribution Model ◽

Distance Sampling ◽

Distribution Model ◽

Balaenoptera Physalus ◽

Density Estimates ◽

Bayesian Hierarchical ◽

Hierarchical Framework ◽

Final Density ◽

Fin Whales

Species distribution models (SDMs) have proven to be an integral tool in the conservation and management of cetaceans. Many applications have adopted a two-step approach where a detection function is estimated using conventional distance sampling in the first step and subsequently used as an offset to a density-habitat model in the second step. A drawback to this approach, hereafter referred to as the conventional species distribution model (CSDM), is the difficulty in propagating the uncertainty from the first step to the final density estimates. We describe a Bayesian hierarchical species distribution model (BHSDM) which has the advantage of simultaneously propagating multiple sources of uncertainty. Our framework includes 1) a mark-recapture distance sampling observation model that can accommodate two team line transect data, 2) an informed prior for surface availability 3) spatial smoothers using spline-like bases and 4) a compound Poisson-gamma likelihood which is a special case of the Tweedie distribution. We compare our approach to the CSDM method using a simulation study and a case study of fin whales (Balaenoptera physalus) off the East Coast of the USA. Simulations showed that the BHSDM method produced estimates with lower precision but with confidence interval coverage closer to the nominal 95% rate (94% for the BSHDM vs 85% for the CSDM). Results from the fin whale analysis showed that density estimates and predicted distribution patterns were largely similar among methods. Abundance estimates were also similar though modestly higher for the CSDM (4700, CV=0.13) than the BHSDM (4526, CV=0.26). Estimated sampling error differed substantially among the two methods where the average CV for density estimates from BHSDM method was approximately 3.5 times greater than estimates from the CSDM method. Successful wildlife management hinges on the ability to properly quantify uncertainty. Underestimates of uncertainty can result in ill-informed management decisions. Our results highlight the additional sampling uncertainty that is propagated in a hierarchical framework. Future applications of SDMs should consider techniques that allow all sources of error to be fully represented in final density predictions.

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First estimates of primate density and abundance in Siberut National Park, Mentawai Islands, Indonesia

Oryx ◽

10.1017/s0030605314001185 ◽

2015 ◽

Vol 50 (2) ◽

pp. 364-367

Author(s):

Marcel C. Quinten ◽

Fifin Nopiansyah ◽

J. Keith Hodges

Keyword(s):

National Park ◽

Total Population ◽

Distance Sampling ◽

Primate Species ◽

Density Estimates ◽

Mentawai Islands ◽

Major Significance ◽

West Sumatra ◽

Simias Concolor ◽

Primate Density

AbstractIn 2011 we carried out the first systematic survey to determine the density and abundance of endemic forest primates in Siberut National Park, in the Mentawai Islands of West Sumatra, Indonesia. Distance sampling was employed to survey 18 transects located systematically throughout the Park, yielding a total survey effort of 192 km and 285 observations of primates for data analysis. From density estimates for the four resident primate species, the Siberut langur Presbytis siberu, the pig-tailed snub-nosed langur Simias concolor, Kloss's gibbon Hylobates klossii and the Siberut macaque Macaca siberu, we extrapolated a total population of c. 51,000 primates within the Park. We conclude that Siberut National Park is of major significance for the continued survival of Siberut's endemic primates, and provide recommendations to help ensure that it will continue to function as a refuge for primates.

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