A Practical Look at the Variable Area Transect

Dobrowski, Solomon Z.; Murphy, Shannon

doi:10.1890/0012-9658(2006)87[1856:aplatv]2.0.co;2

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…PCQM methods with g ≥ 3 are often impractical in the field. This is because of the difficulty of determining which individual is the g th (Dobrowski, Murphy 2006). In this research, g = 2 was the best.…”

Section: Sampling Methods (Topsis Algorithm)mentioning

confidence: 76%

“…The low RBIAS of VAT sampling is the most important reason for choosing this method. Engeman and Sugihara (1998) and Dobrowski and Murphy (2006) found that the VAT method was robust and more efficient. Kiani et al (2013) showed that the VAT method was the best sampling method in all patterns in terms of RBIAS and time together.…”

Section: Sampling Methods (Accuracy Precision Bias)mentioning

confidence: 99%

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Evaluation of distance methods for estimating population density in Populus euphratica Olivier natural stands (case study: Maroon riparian forests, Iran)

Basiri¹,

Moradi²,

Kiani³

et al. 2018

J. For. Sci.

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Basiri R., Moradi M., Kiani B., Maasumi Babaarabi M. (2018): Evaluation of distance methods for estimating population density in Populus euphratica Olivier natural stands (case study: Maroon riparian forests, Iran). J. For. Sci., 64: 230-244.The aim of this study was to determine the performance of distance methods in terms of accuracy, precision, bias, consumed time and sampling efficiency in the Maroon riparian forests, Iran. 40 estimators were used to evaluate the density of Populus euphratica Olivier trees in pure and mixed stands. Fifty quadrates (30 × 30 m) were established in each stand. To evaluate the accuracy, precision, bias, consumed time and efficiency of sampling techniques, relative root mean square error -RRMSE (%), coefficient of variation -CV (%), relative bias -RBIAS (%), t × RBIAS 2 , t × E 2 , where t is study time and E (%) is sampling error at a confidence level of 95%, and efficiency ratio between method j and k (Ef jk ) were used. A compound of three basic distance estimators sampling method and n-tree were the best in both stands according to all criteria for density estimation. Moreover, variable area transect by Parker (g = 3) and quadrat method were the best methods for density estimation only in pure stand, while the angle order-point-centred quarter method was superior in mixed stand. Regarding to the results, we recommend the use of compound of three basic distances (BDAV3) and basic distance-nearest neighbour (BDNN2) for density estimation of P. euphratica stands in riparian forests.

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Section: Sampling Methods (Topsis Algorithm)mentioning

confidence: 76%

Section: Sampling Methods (Accuracy Precision Bias)mentioning

confidence: 99%

Evaluation of distance methods for estimating population density in Populus euphratica Olivier natural stands (case study: Maroon riparian forests, Iran)

Basiri¹,

Moradi²,

Kiani³

et al. 2018

J. For. Sci.

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“…The method suggested by Borders et al [4] of sampling a fixed number of trees along a variable section of a plantation row may be similar in principle to a variable-length transect. Several simulation studies indicated positive results from variable area transect sampling ( [31][32][33]). However, variable area transects were found to have significant bias towards a clustered spatial distribution by Engman et al [34].…”

Section: Introductionmentioning

confidence: 99%

Design-Unbiased Estimation and Alternatives for Sampling Trees on Plantation Rows

Lynch

Hamlin²,

Ducey

et al. 2018

Forests

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square errors but these were slightly higher than some of the other methods. In contrast to the other methods tested, the NG-MR and G-RM methods were both substantially biased on a simulated row population containing large gaps which might occur due to mortality or thinning. The estimators which had good performance in simulations-Ducey's method, G-MR, NG-RM, and fixed-length row sampling-are viable alternatives to traditional methods of sampling plantations, such as Bitterlich sampling and fixed-size plot sampling, if accurate plantation row lengths can be measured.

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“…They fall within the family of plotless sampling techniques and have as main advantage their speed of application (Parker ; Engeman et al. ; Dobrowski & Murphy ). These techniques are used mainly in forestry to measure the density of tree stems (overall, per species, per size class, etc.).…”

Section: Introductionmentioning

confidence: 99%

Integral occurrence probability: combining cover and relative shoot frequencies based on bounded point‐to‐plant distances

Calster

Damgaard

2017

J Vegetation Science

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Abbreviations CDF = cumulative distribution function; IOP = integral occurrence probability; PDF = probability density function.Nomenclature Lambinon et al. (1998) for vascular plants AbstractAims: To introduce a new distance-based field method for (herbaceous, terrestrial) plant species that relates cover to relative shoot frequency as a continuous process of occurrence probabilities and to explain how these data can be analysed. Methods:We propose to measure shortest distances from a sample of sampling points to the nearest above-ground part of plant species (up to a maximum search distance). We show how, after appropriate transformation of the pointto-plant distances to a 0-1 interval scale, cover as well as relative shoot frequency at any area up to the searched area can be read from the same curve. This leads to the notion of an integral occurrence probability, which we propose as a new species abundance measure. For estimation and regression modelling we make use of the zero-and-one inflated beta distribution. We supply all code required for these analyses.Results: Simulations of plant distribution patterns showed that the integral occurrence probability is able to differentiate between plant abundance patterns that differed in terms of relative cover, density and type of spatial distribution pattern. It is more sensitive to these differences than either cover or relative shoot frequency alone. The method allows summing occurrence probabilities over species to predict expected species richness as a function of the area searched. Aggregation across species, while accounting for overlap in species spatial distributions, is a simple matter of taking the minimum among the pointto-plant distances at each sampling point. The latter was demonstrated with data from a field trial in Nardetea grassland. Conclusions:The method could be a viable alternative for currently employed field methods, such as visual cover estimates, point-intercept sampling and recording the frequency of plant species in equal-area plots. Applications include, but are not limited to, conservation management monitoring and ground-truthing of remote sensing data.

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A Practical Look at the Variable Area Transect

Cited by 8 publications

References 12 publications

Evaluation of distance methods for estimating population density in Populus euphratica Olivier natural stands (case study: Maroon riparian forests, Iran)

Evaluation of distance methods for estimating population density in Populus euphratica Olivier natural stands (case study: Maroon riparian forests, Iran)

Design-Unbiased Estimation and Alternatives for Sampling Trees on Plantation Rows

Integral occurrence probability: combining cover and relative shoot frequencies based on bounded point‐to‐plant distances

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