Why most conservation monitoring is, but need not be, a waste of time. J Env Manag

School of GeoSciences, University of Edinburgh, Crew Building, King's Buildings, Mayfield Road, Edinburgh EH9 3JN, Scotland.
Journal of Environmental Management (Impact Factor: 2.72). 02/2006; 78(2):194-9. DOI: 10.1016/j.jenvman.2005.04.016
Source: PubMed


Ecological conservation monitoring programmes abound at various organisational and spatial levels from species to ecosystem. Many of them suffer, however, from the lack of details of goal and hypothesis formulation, survey design, data quality and statistical power at the start. As a result, most programmes are likely to fail to reach the necessary standard of being capable of rejecting a false null hypothesis with reasonable power. Results from inadequate monitoring are misleading for their information quality and are dangerous because they create the illusion that something useful has been done. We propose that conservation agencies and those funding monitoring work should require the demonstration of adequate power at the outset of any new monitoring scheme.

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    • "Quality environmental monitoring goes hand in hand with good survey design (Legg and Nagy [2]), and developing efficient and effective surveys for environmental systems is a fast evolving area of statistics. One principle of survey designs for environmental studies is that a biological characteristic observed in one area is likely to be observed in an adjacent area. "
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    ABSTRACT: Spatially balanced sampling is becoming a popular design for surveys in biological and environmental management. For large scale surveys, where the region of interest is too large to visit every site, a sample is taken from a selection of sites. The process used to select these sites is called the survey design. Spatially balanced designs ensure there is spatial coverage of the entire survey area. The resultant sample should be representative of the population of interest.
    12/2015; 27:6-9. DOI:10.1016/j.proenv.2015.07.108
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    • "Size-at-age samples that are used to estimate growth should be representative of the true extent of the age structure and the true variability in length at each age (Ricker 1975: 205; Walters and Martell 2004: 117). Unfortunately, the assumption of representativeness is often violated in fisheries assessments due to various forms of sampling selectivity (Myers and Hoenig 1997; Walters and Martell 2004) and problems with sampling designs (Peterman 1990; Legg and Nagy 2006), which can result in biased and incorrect statistical outcomes . Differential selectivity emerges for a number of reasons , including spatial variability in habitat selection; gear restrictions (Matthias et al. 2014); size selectivity (Myers and Hoenig 1997; Gwinn et al. 2010); and behavioral selectivity (Bryan and Larkin 1972; Nuhfer and Alexander 1994; Cooke et al. 2007; Philipp et al. 2009). "

    North American Journal of Fisheries Management 11/2015; 35(6):1121-1131. DOI:10.1080/02755947.2015.1079573 · 0.95 Impact Factor
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    • "Conventional wildlife monitoring generally relies on resource intensive fieldwork. With increasing need for data, and generally decreasing resources for monitoring, one of the challenges for natural resource management is to develop more cost-effective approaches to ecological monitoring while ensuring that the data are robust and fit for purpose (Yoccoz et al. 2001; Legg and Nagy 2006). The deployment of camera traps is therefore an attractive tool because of their potential to provide a low cost, non-invasive survey method which (due to the physical absence of an observer) reduces disturbance and does not require the capture and handling of the study animals. "
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    ABSTRACT: The availability of affordable ‘recreational’ camera traps has dramatically increased over the last decade. We present survey results which show that many conservation practitioners use cheaper ‘recreational’ units for research rather than more expensive ‘professional’ equipment. We present our perspective of using two popular models of ‘recreational’ camera trap for ecological field-based studies. The models used (for >2 years) presented us with a range of practical problems at all stages of their use including deployment, operation, and data management, which collectively crippled data collection and limited opportunities for quantification of key issues arising. Our experiences demonstrate that prospective users need to have a sufficient understanding of the limitations camera trap technology poses, dimensions we communicate here. While the merits of different camera traps will be study specific, the performance of more expensive ‘professional’ models may prove more cost-effective in the long-term when using camera traps for research.
    AMBIO A Journal of the Human Environment 11/2015; 44(S4-S4):624-635. DOI:10.1007/s13280-015-0713-1 · 2.29 Impact Factor
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