Literature DB >> 27473106

Biases encountered in long-term monitoring studies of invertebrates and microflora: Australian examples of protocols, personnel, tools and site location.

Penelope Greenslade1,2, Singarayer K Florentine3, Brigita D Hansen4, Peter A Gell3.   

Abstract

Monitoring forms the basis for understanding ecological change. It relies on repeatability of methods to ensure detected changes accurately reflect the effect of environmental drivers. However, operator bias can influence the repeatability of field and laboratory work. We tested this for invertebrates and diatoms in three trials: (1) two operators swept invertebrates from heath vegetation, (2) four operators picked invertebrates from pyrethrum knockdown samples from tree trunk and (3) diatom identifications by eight operators in three laboratories. In each trial, operators were working simultaneously and their training in the field and laboratory was identical. No variation in catch efficiency was found between the two operators of differing experience using a random number of net sweeps to catch invertebrates when sequence, location and size of sweeps were random. Number of individuals and higher taxa collected by four operators from tree trunks varied significantly between operators and with their 'experience ranking'. Diatom identifications made by eight operators were clustered together according to which of three laboratories they belonged. These three tests demonstrated significant potential bias of operators in both field and laboratory. This is the first documented case demonstrating the significant influence of observer bias on results from invertebrate field-based studies. Examples of two long-term trials are also given that illustrate further operator bias. Our results suggest that long-term ecological studies using invertebrates need to be rigorously audited to ensure that operator bias is accounted for during analysis and interpretation. Further, taxonomic harmonisation remains an important step in merging field and laboratory data collected by different operators.

Entities:  

Keywords:  Diatoms; Identification; Long-term monitoring; Pyrethrum knockdown; Sweeping; Tasmanian rainforest

Mesh:

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Year:  2016        PMID: 27473106     DOI: 10.1007/s10661-016-5478-x

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  3 in total

1.  Assessing long-term pH change in an Australian river catchment using monitoring and palaeolimnological data.

Authors:  John Tibby; Michael A Reid; Jennie Fluin; Barry T Hart; A Peter Kershaw
Journal:  Environ Sci Technol       Date:  2003-08-01       Impact factor: 9.028

2.  Using prediction markets to estimate the reproducibility of scientific research.

Authors:  Anna Dreber; Thomas Pfeiffer; Johan Almenberg; Siri Isaksson; Brad Wilson; Yiling Chen; Brian A Nosek; Magnus Johannesson
Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-09       Impact factor: 11.205

3.  Observer bias and the detection of low-density populations.

Authors:  Matthew C Fitzpatrick; Evan L Preisser; Aaron M Ellison; Joseph S Elkinton
Journal:  Ecol Appl       Date:  2009-10       Impact factor: 4.657

  3 in total

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