Optimising the stream habitat assessment for the Bay of Plenty Regional Council : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Conservation Biology at Massey University, Palmerston North, New Zealand
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Date
2021
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Massey University
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Abstract
Multiple stream habitat attributes are evaluated using qualitative and quantitative assessment methods during the current Bay of Plenty Natural Environmental Monitoring Network (BOP NERMN) stream habitat survey. These assessments are carried out by a team of different students each summer. Because qualitative assessments typically require less time (shorter in-field assessment duration) than quantitative measurements, using only qualitative assessment methods are likely to be more economical. However, the results of qualitative assessments are thought to be more subjective. Therefore, the year-to-year change of the surveying team (inter-annual observer variability) could influence the BOP NERMN stream habitat monitoring results. In this thesis, I aimed to determine whether omitting quantitative metrics and using only qualitative metrics could be an appropriate option for creating a more economical BOP NERMN stream habitat survey, considering the metrics’ in-field assessment duration and inter-annual observer variability. First, I investigated whether qualitative and quantitative metrics captured stream habitat attributes similarly by assessing the relationship between the two approaches through Spearman rank correlation tests. The Spearman rank correlation analyses revealed that all qualitative metrics, apart from the ‘RHA riparian shade’, were significantly correlated to at least one quantitative metric. Furthermore, I timed the in-field assessment duration of qualitative and quantitative metrics, with the result that, on average per site, all qualitative metrics were evaluated within 9 minutes, and all quantitative metrics were measured in 17 minutes. I investigated inter-annual observer variability by comparing each metric’s percent coefficient of variation (CV) through Bayesian hierarchical linear models and found that data from most metrics (69%) had high levels of inter-annual observer variability (CV estimate > 30%), regardless of whether metrics were quantitative or qualitative. Lastly, I applied value models to evaluate the performance trade-offs between infield-assessment duration and inter-annual observer variability of qualitative and quantitative metrics. More than half (56%) of all metrics performed relatively equally in relation to their in-field assessment duration and inter-annual observer variability, regardless of whether metrics were qualitative or quantitative. These results suggest there is currently no clear reason to favour qualitative metrics in the BOP NERMN stream habitat survey. Overall, this research suggests the existing BOP NERMN stream habitat assessment protocol requires further refinement to reduce inter-annual observer variability.