DOI: 10.5061/dryad.bzkh189g7
title: Data from: A user-friendly guide to using distance measures to compare time series in ecology

description: Time series are a critical component of ecological analysis, used to track
 changes in biotic and abiotic variables. Information can be extracted from
 the properties of time series for tasks such as classification (e.g.
 assigning species to individual bird calls); clustering (e.g. clustering
 similar responses in population dynamics to abrupt changes in the
 environment or management interventions); prediction (e.g. accuracy of
 model predictions to original time series data); and anomaly detection
 (e.g. detecting possible catastrophic events from population time series).
 These common tasks in ecological research rely on the notion of (dis-)
 similarity, which can be determined using distance measures. A plethora of
 distance measures have been described, predominantly in the computer and
 information sciences, but many have not been introduced to ecologists.
 Furthermore, little is known about how to select appropriate distance
 measures for time-series-related tasks. Therefore, many potential
 applications remain unexplored. Here we describe 16 properties of distance
 measures that are likely to be of importance to a variety of ecological
 questions involving time series. We then test 42 distance measures for
 each property and use the results to develop an objective method to select
 appropriate distance measures for any task and ecological dataset. We
 demonstrate our selection method by applying it to a set of real-world
 data on breeding bird populations in the UK and discuss other potential
 applications for distance measures, along with associated technical issues
 common in ecology. Our real-world population trends exhibit a common
 challenge for time series comparisons: a high level of stochasticity. We
 demonstrate two different ways of overcoming this challenge, first by
 selecting distance measures with properties that make them well-suited to
 comparing noisy time series, and second by applying a smoothing algorithm
 before selecting appropriate distance measures. In both cases, the
 distance measures chosen through our selection method are not only
 fit-for-purpose but are consistent in their rankings of the population
 trends. The results of our study should lead to an improved understanding
 of, and greater scope for, the use of distance measures for comparing
 ecological time series, and help us answer new ecological questions.
description: Distance measure test results were produced using R and can be
 replicated using scripts available on GitHub at https://github.com/shawndove/Trend_compare. Detailed information on wading bird trends can be found in Jellesmark <em>et al</em>. (2021) below. Jellesmark, S., Ausden, M., Blackburn, T. M., Gregory, R. D., Hoffmann, M., Massimino, D., McRae, L., & Visconti, P. (2021). A counterfactual approach to measure the impact of wet grassland conservation on U.K. breeding bird populations. <em>Conservation Biology</em>, <em>35</em>(5), 1575–1585. https://doi.org/10.1111/cobi.13692
description: .RData files can be opened with R .csv files
 can be opened with Excel or a generic text editor.