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Inter-observer variation in habitat survey data: investigating the consequences for professional practice
Authors:Andrew Cherrill
Institution:Crop and Environment Sciences, Harper Adams University, Edgmond TF10 8NB, United Kingdom
Abstract:Environmental assessments and land-use planning require reliable information on the botanical composition and distribution of habitats. There have been numerous academic studies of inter-observer variation in species-inventory and habitat mapping, but studies addressing the prevalence of inter-observer variation and consequences of poor quality data in professional practice are lacking. This paper addresses these questions via a questionnaire survey of environmental professionals, using the standard Phase 1 and National Vegetation Classification (NVC) survey methods in the United Kingdom. The survey revealed that misidentification of habitat types within survey reports was relatively common (approximating to 20% of all reports seen by respondents over the previous five years). Approximately 40% of respondents who had encountered erroneous reports stated that these had led to inaccurate initial site ecological assessments. Additional field surveys and discussions with surveyors were commonly used to resolve these issues, but for Phase 1 and NVC 26% and 34% of respondents, respectively, had encountered one or more cases where errors resulted in negative consequences for clients commissioning surveys (in terms of extra costs and project delays). Net loss of biodiversity arising from inaccurate reports was reported in at least one instance by 32% and 38% of respondents for Phase 1 and NVC surveys, respectively – results that may contribute to the attrition of natural capital within the UK. The study highlights the need to extend studies of inter-observer variation to consider impacts on environmental assessments and decision-making in professional practice. The potential benefits of introducing an accreditation scheme (favoured by the majority of respondents to the questionnaire) are discussed.
Keywords:observer bias  data error  vegetation mapping  environmental assessment
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