Correcting for Incomplete Sighting in Aerial Surveys of Kangaroos

Barnes, A.; Hill, Gordon A.; Wilson, George R.

doi:10.1071/wr9860339

Cited by 15 publications

(2 citation statements)

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“…1981; Caughley & Grice 1982). Most unfortunately, these proposed techniques are impractical and expensive (Barnes, Hill & Wilson 1986). The only application that is practically feasible and theoretically sound is the double‐count technique.…”

Section: Introductionmentioning

confidence: 99%

Comparison of aerial counts with ground counts for large African herbivores

Jachmann¹

2002

Journal of Applied Ecology

159

150

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Summary 1.Over the past 50 years, aerial counts have been widely used in African wildlife management; however, the accuracy of the resulting estimates has rarely been questioned. The reliability of aerial counts of large African herbivores was examined by comparing the results of a series of systematic aerial sample counts with those from a series of line transect foot counts conducted in the Lupande Game Management Area in Zambia. 2. For most large herbivore species, the estimates from the aerial counts were considerably lower than those from the ground counts. The data pointed to undercounting as a major problem of aerial surveys. During the aerial counts, significant numbers of animals were missed on the transects, first due to the low probability of spotting single animals, small groups of animals and less conspicuous ones (sighting probability bias), and secondly because part of the population was concealed by obstructions and therefore not visible to the observers (visibility bias). 3. The main factors that influence visibility of large herbivores from the air are the animals' reactions to an over-flying aircraft, dispersion, body size and colour. Animals that move in response to an aircraft are more likely to be seen than static ones; dark-coloured animals are easier to spot than light-coloured ones against a light background; large herds are easier to detect than small ones; and large animals are more easily seen than small ones. Body size is important while trying to spot grazers and mixed feeders from the air, while colour is important for spotting browsers. This is mainly due to the differences in habitat use, with browsers being confined to the thicker habitat. 4. To minimize undercounting bias, both conventional aerial counts and aerial line transect counts should be restricted to large conspicuous grazers and mixed feeders in medium to large group sizes, such as elephant Loxodonta africana africana , buffalo Sincerus caffer , zebra Equus burchell , wildebeest Connochaetes and lechwe Kobus leche . Operational factors, such as height, speed and strip width, should be kept within reasonable limits for conventional aerial counts. Only one species should be counted at a time, always applying the double-count technique. For aerial line transect counts, the use of a helicopter is a prerequisite to obtaining accurate estimates. Other important considerations are observer experience and flight duration.

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Section: Introductionmentioning

confidence: 99%

Comparison of aerial counts with ground counts for large African herbivores

Jachmann¹

2002

Journal of Applied Ecology

159

150

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“…Although light aircraft have been used since the mid-1950's to census wildlife on the African continent, the accuracy of aerial counts has been overestimated (Jachmann 2001;Redfern et al 2002). A variety of techniques have been suggested to correct bias in aerial counts (Caughley & Goddard 1972;Cook & Jacobson 1979), but these techniques are generally impractical and expensive (Barnes et al 1986). The only theoretically sound and practical method is the double count technique based on the concept of the mark-recapture model (Caughley 1974), usually incorporating an adaptation of the Petersen estimate (Caughley & Sinclair 1994).…”

Section: Introductionmentioning

confidence: 99%

Conducting animal censuses amongst abrupt topography; aGIS‐based alternative toDistance

2014

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Management often bases decisions on estimates of animal density and population size. Aerial sampling is expensive whilst current ground methods, noticeably Distance sampling, assume a single detection function for each habitat and that visibility in a given habitat type declines in a smooth, increasing manner with distance from the observer. If the visibility within a habitat varies widely or is suddenly cut off, as amongst abrupt topography, these assumptions are invalidated. We present an affordable, accessible and accurate method for conducting repeated annual censuses on large herbivores in such terrain.We used a GIS habitat-based approach. Monthly, over a two year period, we conducted repeated road transects in Ithala Game Reserve, South Africa, using GPS to record the geographic position of each sighting.These records (n = 8742) were then imported into a GIS and overlaid onto an existing habitat-type GIS layer.With the sampled area thus defined as an irregular polygon in the GIS encompassing all records, we calculated densities of each herbivore species by habitat type and extrapolated total population size estimates. Estimates of maximum population size for wildebeest and zebra correlated (±15%) with management's estimates based on aerial surveys, walked transects and experience.White rhino are individually counted in the reserve and our estimates (year 1: 52; year 2: 57) matched these known numbers (year 1: 50; year 2: 53). Our method also yielded realistic numbers for impala, but unrealistic numbers for kudu and warthog. Our GIS-based census technique produced realistic maximum population estimates for abundant grazing and mixed-feeder mesoherbivores and for scarce, but highly visible, megaherbivores, but not for cryptic species.With the increasing availability of GIS data, the technique is recommended to those working in abrupt terrain frustrated by the inability of current ground census techniques, principally Distance sampling, to produce realistic population estimates.

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Window Sensitivity Functions for Line Transect Sampling

Crain

1998

Environmental Management

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/ The estimation of animal or plant abundance by the line or belt transect sampling method has been investigated by many authors, including biologists, statisticians, biometricians, wildlife scientists, and fisheries and forestry specialists. The method has reached wide acceptance over the last 30 years, and the theoretical development has continued to expand, both from a parametric and a nonparametric point of view. This article examines the line transect sampling method from a slightly different perspective. If the line transect region is regarded as a rectangle with length L and width 2w, then by a selection of viewing window is meant a choice of w, with the intent being to search for optimal viewing windows, with the goal in mind of improving variances of estimators of population density, reducing sampling effort, while maintaining the property of unbiasedness. The notions of increasing window sensitivity (IWS) and decreasing window sensitivity (DWS) are introduced, and a method of deriving confidence intervals is discussed.KEY WORDS: Line transection sampling; Population estimation; Probability detection function; Window sensitivity function; Strip census.

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Correcting for Incomplete Sighting in Aerial Surveys of Kangaroos

Cited by 15 publications

References 0 publications

Comparison of aerial counts with ground counts for large African herbivores

Comparison of aerial counts with ground counts for large African herbivores

Conducting animal censuses amongst abrupt topography; aGIS‐based alternative toDistance

Window Sensitivity Functions for Line Transect Sampling

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