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Time series methods for the analysis of soundscapes and other cyclical ecological data

Yoh, Natalie, Haley, Charlotte L., Burivalova, Zuzana (2024) Time series methods for the analysis of soundscapes and other cyclical ecological data. Methods in Ecology and Evolution, 15 (7). pp. 1158-1176. E-ISSN 2041-210X. (doi:10.1111/2041-210x.14361) (KAR id:106239)

Abstract

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near‐continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near‐continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

Item Type: Article
DOI/Identification number: 10.1111/2041-210x.14361
Uncontrolled keywords: phenology, power spectrum estimation, ecoacoustics, passive acoustic monitoring, bioacoustics, coherence, multitaper principal component analysis, tropical forest
Subjects: G Geography. Anthropology. Recreation
G Geography. Anthropology. Recreation > GE Environmental Sciences
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology)
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 12 Jun 2024 12:50 UTC
Last Modified: 11 Jul 2024 10:51 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/106239 (The current URI for this page, for reference purposes)

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