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Ecological networks: the missing links in biomonitoring science

Gray, Clare; Baird, Donald J.; Baumgartner, Simone; Jacob, Ute; Jenkins, Gareth B.; O'Gorman, Eoin J.; Lu, Xueke; Ma, Athen; Pocock, Michael J.O.; Schuwirth, Nele; Thompson, Murray; Woodward, Guy. 2014 Ecological networks: the missing links in biomonitoring science. Journal of Applied Ecology, 51 (5). 1444-1449. https://doi.org/10.1111/1365-2664.12300

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Abstract/Summary

1. Monitoring anthropogenic impacts is essential for managing and conserving ecosystems, yet current biomonitoring approaches lack the tools required to deal with the effects of stressors on species and their interactions in complex natural systems. 2. Ecological networks (trophic or mutualistic) can offer new insights into ecosystem degradation, adding value to current taxonomically constrained schemes. We highlight some examples to show how new network approaches can be used to interpret ecological responses. 3. Synthesis and applications: Augmenting routine biomonitoring data with interaction data derived from the literature, complemented with ground-truthed data from direct observations where feasible, allows us to begin to characterise large numbers of ecological networks across environmental gradients. This process can be accelerated by adopting emerging technologies and novel analytical approaches, enabling biomonitoring to move beyond simple pass/fail schemes and to address the many ecological responses that can only be understood from a network-based perspective.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1111/1365-2664.12300
CEH Sections/Science Areas: Pywell
ISSN: 0021-8901
Additional Information. Not used in RCUK Gateway to Research.: Open Access paper - Official URL link provides full text
Additional Keywords: anthropogenic stress, climate change, conservation, food web, global warming, mutualism, pollination
NORA Subject Terms: Ecology and Environment
Date made live: 27 Oct 2014 15:12 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/508275

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