This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.ecolind.2022.109117. This is version 1 of this Preprint.
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Abstract
Temporal trends in species occupancy or abundance are a fundamental source of information for ecology and conservation. Model-based uncertainty in these trends is often communicated as frequentist confidence or Bayesian credible intervals; however, these are often misinterpreted in various ways, even by scientists. Research from the science of information visualisation indicates that line ensemble approaches that depict multiple outcomes compatible with a fitted model or data may be superior for the clear communication of model-based uncertainty. The discretisation of continuous probability information into frequency bins has also been shown to be useful for communicating with non-specialists. We present a simple and widely applicable approach that combines these two ideas, and which can be used to clearly communicate model-based uncertainty in species trends (or composite indicators) to stakeholders. We also show how broader ontological uncertainty can also be communicated via trend plots using risk-of-bias visualisation approaches developed in other disciplines. The techniques are demonstrated using the example of long-term plant distributional change in Britain, but are applicable to any temporal data consisting of averages and associated uncertainty measures. Our approach supports calls for full transparency in the scientific process by clearly displaying the multiple sources of uncertainty that can be estimated by researchers.
DOI
https://doi.org/10.32942/osf.io/zfht8
Subjects
Biodiversity, Life Sciences
Keywords
Bayesian model, bootstrap, Environmental monitoring, information visualisation, line ensembles, model-based inference, risk-of-bias, stakeholder communication
Dates
Published: 2022-04-21 22:13
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