Assessing the state of the Barents Sea using indicators: how, when, and where?
Author(s) -
Cecilie Hansen,
Gro van der Meeren,
Harald Loeng,
Morten D. Skogen
Publication year - 2021
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsab053
Subject(s) - representativeness heuristic , environmental resource management , ecological indicator , biomass (ecology) , trophic level , environmental science , ecosystem , ecosystem based management , management by objectives , abundance (ecology) , consistency (knowledge bases) , inclusion (mineral) , ecology , computer science , business , statistics , mathematics , gender studies , marketing , artificial intelligence , sociology , biology
Two end-to-end ecosystem models, NORWECOM.E2E and NoBa Atlantis, have been used to explore a selection of indicators from the Barents Sea Management plans (BSMP). The indicators included in the BSMP are a combination of simple (e.g. temperature, biomass, and abundance) and complex (e.g. trophic level and biomass of functional groups). The abiotic indicators are found to serve more as a tool to report on climate trends rather than being ecological indicators. It is shown that the selected indicators give a good overview of the ecosystem state, but that overarching management targets and lack of connection between indicators and management actions makes it questionable if the indicator system is suitable for direct use in management as such. The lack of socio-economic and economic indicators prevents a holistic view of the system, and an inclusion of these in future management plans is recommended. The evaluated indicators perform well as an assessment of the ecosystem, but consistency and representativeness are extremely dependent on the time and in what area they are sampled. This conclusion strongly supports the inclusion of an observing system simulation experiment in management plans, to make sure that the observations represent the properties that the indicators need.
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