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Spatially balanced designs for transect-based surveys

Citation

Foster, SD and Hosack, GR and Monk, J and Lawrence, E and Barrett, NS and Williams, A and Przeslawski, R, Spatially balanced designs for transect-based surveys, Methods in Ecology and Evolution, 11, (1) pp. 95-105. ISSN 2041-210X (2019) [Refereed Article]


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DOI: doi:10.1111/2041-210X.13321

Abstract

  1. Many sampling techniques rely on taking measurements along a transect; an example is underwater imagery from towed platforms used for marine ecological studies. Despite transect‐based sampling being commonly used, methods to generate randomized survey designs have not hitherto been developed.
  2. We develop methods to generate random transect designs, which respect the user‐defined probability of sampling each grid cell (the cell inclusion probabilities). We show how to: (a) define transect inclusion probabilities from user‐specified cell inclusion probabilities, which allows particular environments to be sampled more often; (b) alter the cell and transect inclusion probabilities so that when transects are sampled the frequencies of sampling cells approximate the cell inclusion probabilities, and; (c) draw a spatially balanced probability sample of transects.
  3. The spatially balanced transect designs approximately maintain the cell inclusion probabilities. The greatest of the small departures occur near the extreme corners of our convex study region, which are difficult to place transects into. The proposed designs also exhibit superior spatial balance compared to the non‐balanced counterparts. We illustrate the successful application of the method to a towed‐camera survey of deep‐sea (5002,000m depths) seamounts off Tasmania, Australia. This was a challenging application due to the complex topology of the setting, and uneven inclusion probabilities for the property of interest the presence of a stony coral.
  4. Our approach develops the randomization approach to transect‐based surveys, thereby ensuring that transect‐based surveys can enjoy the same benefits as random point‐based surveys. The method approximates the cell inclusion probabilities, and does so while spatially balancing the transects throughout the study area. Practitioners can access the methods through the R‐package MBHdesign, which is available from CRAN. We anticipate that it will act as a cornerstone for transect‐based ecological monitoring programmes.

Item Details

Item Type:Refereed Article
Keywords:marine conservation, protection, management, biodiversity, coastal monitoring, evaluation, balanced acceptance sample, MBH design, quadrat, quasi-random, spatial balance, survey design, transect, unequal probability sample
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Marine and Estuarine Ecology (incl. Marine Ichthyology)
Objective Division:Environment
Objective Group:Flora, Fauna and Biodiversity
Objective Field:Marine Flora, Fauna and Biodiversity
UTAS Author:Monk, J (Dr Jacquomo Monk)
UTAS Author:Barrett, NS (Associate Professor Neville Barrett)
ID Code:136142
Year Published:2019
Web of Science® Times Cited:1
Deposited By:Ecology and Biodiversity
Deposited On:2019-12-02
Last Modified:2020-01-29
Downloads:0

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