Accounting for among-sampler variability improves confidence in fuel moisture content field measurements

Kerryn Little; Laura J. Graham; Nicholas Kettridge

doi:10.1071/WF23078

RESEARCH ARTICLE (Open Access)

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Accounting for among-sampler variability improves confidence in fuel moisture content field measurements

Kerryn Little

^A ^* , Laura J. Graham

^A ^B and Nicholas Kettridge

^A

+ Author Affiliations

- Author Affiliations

^A School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK.

^B Biodiversity, Ecology and Conservation Group, International Institute for Applied Systems Analysis, Vienna, Austria.

^* Correspondence to: k.e.little@bham.ac.uk

International Journal of Wildland Fire 33, WF23078 https://doi.org/10.1071/WF23078

Submitted: 2 December 2022 Accepted: 30 November 2023 Published: 21 December 2023

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY).

Abstract

Background

Direct fuel moisture content measurements are critical for characterising spatio-temporal variations in fuel flammability and for informing fire danger assessments. However, among-sampler variability (systematic differences in measurements between samplers) likely contributes to fuel moisture measurement variability in most field campaigns.

Aims

We assessed the magnitude of among-sampler variability in plot-scale Calluna vulgaris fuel moisture measurements.

Methods

Seventeen individuals collected samples from six fuel layers hourly from 10:00 hours to 18:00 hours. We developed mixed effects models to estimate the among-sampler variability.

Key results

Fuel moisture measurements were highly variable between individuals sampling within the same plot, fuel layer, and time of day. The importance of among-sampler variability in explaining total measured fuel moisture variance was fuel layer dependent. Among-sampler variability explained the greatest amount of measurement variation in litter (58%) and moss (45%) and was more important for live (19%) than dead (4%) Calluna.

Conclusions

Both consideration of samplers within the experimental design and incorporation of sampler metadata during statistical analysis will improve understanding of spatio-temporal fuel moisture dynamics obtained from field-based studies.

Implications

Accounting for among-sampler variability in fuel moisture campaigns opens opportunities to utilise sampling teams and citizen science research to examine fuel moisture dynamics over large spatio-temporal scales.

Keywords: Calluna vulgaris, citizen science, diurnal, ecological field studies, fuel moisture dynamics, heathland, measurement error, mixed effects models, spatiotemporal variation, wildfire.

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