Line-transect versus point-transect sampling: the effects of survey area and survey effort on method efficiency for Geoffroy’s spider monkeys

2021 ◽  
Author(s):  
Anja Hutschenreiter ◽  
Gabriel Ramos-Fernández ◽  
Filippo Aureli
Keyword(s):  
Line Transect ◽  
Spider Monkeys ◽  
Survey Area ◽  
Transect Sampling ◽  
Point Transect Sampling ◽  
Point Transect ◽  
Survey Effort

scholarly journals Point transect sampling with traps or lures

2006 ◽  
Vol 43 (2) ◽  
pp. 377-384 ◽  
Author(s):  
STEPHEN T. BUCKLAND ◽  
RON W. SUMMERS ◽  
DAVID L. BORCHERS ◽  
LEN THOMAS
Keyword(s):  
Transect Sampling ◽  
Point Transect Sampling ◽  
Point Transect

scholarly journals Point-Transect Surveys for Songbirds: Robust Methodologies

The Auk ◽  
2006 ◽  
Vol 123 (2) ◽  
pp. 345-357 ◽  
Author(s):  
Stephen T. Buckland
Keyword(s):  
Sampling Methods ◽  
Bird Species ◽  
Single Species ◽  
Line Transect ◽  
Line Transect Sampling ◽  
Point Sampling ◽  
Transect Sampling ◽  
Single Location ◽  
Point Transect ◽  
Generally True

Abstract Point-transect sampling is widely used for monitoring trends in abundance of songbirds. It is conceptualized as a “snapshot” method in which birds are “frozen” at a single location. With conventional methods, an observer records birds detected from a point for several minutes, during which birds may move around. This generates upward bias in the density estimate. I compared this conventional approach with two other approaches: in one, the observer records locations of detected birds at a snapshot moment; in the other, distances to detected cues (songbursts), rather than birds, are recorded. I implemented all three approaches, together with line-transect sampling and territory mapping in a survey of four bird species. The conventional method gave a biased estimate of density for one species. The snapshot method was found to be the most efficient of the point-sampling methods. Line-transect sampling proved more efficient than the point-sampling methods for all four species. This is likely to be generally true, provided that terrain and habitat allow easy use of a design with random transect lines. I concluded that the snapshot method is more appropriate than the conventional timed-count method for surveying songbirds. Although precision was rather poor with the cue-based method (partly because too few resources were devoted to cue rate estimation), it may be particularly useful for some single-species surveys. In addition, it is the only valid method for estimating abundance from surveys in which acoustic equipment is used to detect birds. Muestreos en Transectos Puntuales para Aves Canoras: Metodologías Robustas

Point Transect Sampling Along Linear Features

Biometrics ◽  
2010 ◽  
Vol 66 (4) ◽  
pp. 1247-1255 ◽  
Author(s):  
T. A. Marques ◽  
S. T. Buckland ◽  
D. L. Borchers ◽  
D. Tosh ◽  
R. A. McDonald
Keyword(s):  
Linear Features ◽  
Transect Sampling ◽  
Point Transect Sampling ◽  
Point Transect

Kernel Methods in Line and Point Transect Sampling

Biometrics ◽  
1998 ◽  
Vol 54 (2) ◽  
pp. 606 ◽  
Author(s):  
Y. P. Mack ◽  
Pham X. Quang
Keyword(s):  
Kernel Methods ◽  
Transect Sampling ◽  
Point Transect Sampling ◽  
Point Transect

scholarly journals Estimating a resource selection function with line transect sampling

2002 ◽  
Vol 6 (4) ◽  
pp. 213-228 ◽  
Author(s):  
Bryan F. J. Manly
Keyword(s):  
Resource Selection ◽  
Probability Function ◽  
Resource Selection Function ◽  
Line Transect ◽  
Selection Function ◽  
Line Transect Sampling ◽  
Selection Probability ◽  
Transect Sampling ◽  
Conditional Maximum ◽  
Habitat Variables

A resource selection probability function is a function that gives the prob- ability that a resource unit (e.g., a plot of land) that is described by a set of habitat variables X1 to Xp will be used by an animal or group of animals in a certain period of time. The estimation of a resource selection function is usually based on the comparison of a sample of resource units used by an animal with a sample of the resource units that were available for use, with both samples being assumed to be effectively randomly selected from the relevant populations. In this paper the possibility of using a modified sampling scheme is examined, with the used units obtained by line transect sampling. A logistic regression type of model is proposed, with estimation by conditional maximum likelihood. A simulation study indicates that the proposed method should be useful in practice.

Population structure, density and biomass of large herbivores in the tropical forests of Nagarahole, India

1992 ◽  
Vol 8 (01) ◽  
pp. 21-35 ◽  
Author(s):  
K. Ullas Karanth ◽  
Melvin E. Sunquist
Keyword(s):  
Population Structure ◽  
Tropical Forests ◽  
Primate Species ◽  
Line Transect ◽  
Large Herbivore ◽  
Large Herbivores ◽  
Transect Sampling ◽  
Structure Density ◽  
Density And Biomass ◽  
Turn Over

ABSTRACTWe studied the population structure, density and biomass of seven ungulate and two primate species in the tropical forests of Nagarahole, southern India, using line transect sampling and roadside/platform counts, during 1986–87. The estimated ecological densities of large herbivore species in the study area are: 4.2 muntjac km−2, 50.6 chital km−2, 5.5 sambar km−2, 0.8 four-horned antelope km−2, 9.6 gaur km−2, 4.2 wild pig km−2, 3.3 elephant km−2, 23.8 hanuman langur km−2and 0.6 bonnet macaque km−2. Most ungulates have female-biased adult sex ratios. Among common ungulate species, yearlings and young of the year comprise about a third of the population, suggesting relatively high turn-over rates. Three species (muntjac, sambar and four-horned antelope) are solitary, while others form groups. The study area supports a wild herbivore biomass density of 14,744 kg km−2. Among the three habitat types within the study area, biomass is lower in dry deciduous forests when compared with moist deciduous or teak plantation dominant forests. Using our results, we have examined the factors that may contribute towards maintenance of high ungulate biomass in tropical forests.

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