Towards the fully automated monitoring of ecological communities.

Journal: Ecology letters
Published Date:

Abstract

High-resolution monitoring is fundamental to understand ecosystems dynamics in an era of global change and biodiversity declines. While real-time and automated monitoring of abiotic components has been possible for some time, monitoring biotic components-for example, individual behaviours and traits, and species abundance and distribution-is far more challenging. Recent technological advancements offer potential solutions to achieve this through: (i) increasingly affordable high-throughput recording hardware, which can collect rich multidimensional data, and (ii) increasingly accessible artificial intelligence approaches, which can extract ecological knowledge from large datasets. However, automating the monitoring of facets of ecological communities via such technologies has primarily been achieved at low spatiotemporal resolutions within limited steps of the monitoring workflow. Here, we review existing technologies for data recording and processing that enable automated monitoring of ecological communities. We then present novel frameworks that combine such technologies, forming fully automated pipelines to detect, track, classify and count multiple species, and record behavioural and morphological traits, at resolutions which have previously been impossible to achieve. Based on these rapidly developing technologies, we illustrate a solution to one of the greatest challenges in ecology: the ability to rapidly generate high-resolution, multidimensional and standardised data across complex ecologies.

Authors

  • Marc Besson
    School of Biological Sciences, University of Bristol, Bristol, UK.
  • Jamie Alison
    Department of Ecoscience, Aarhus University, Aarhus, Denmark.
  • Kim Bjerge
    School of Engineering, Aarhus University, DK-8200 Aarhus N, Denmark.
  • Thomas E Gorochowski
    School of Biological Sciences, University of Bristol, Life Sciences Building Tyndall Avenue, Bristol BS8 1TQ, UK; BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK. Electronic address: thomas.gorochowski@bristol.ac.uk.
  • Toke T Høye
    Department of Bioscience, Aarhus University, DK-8410 Rønde, Denmark; tth@bios.au.dk.
  • Tommaso Jucker
    School of Biological Sciences, University of Bristol, Bristol, UK.
  • Hjalte M R Mann
    Department of Bioscience, Aarhus University, DK-8410 Rønde, Denmark.
  • Christopher F Clements
    School of Biological Sciences, University of Bristol, Bristol, UK.