Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modeling approaches used in the large European project VECTORS
|Author(s)||Peck Myron A.1, Arvanitidis Christos2, Butenschon Momme3, Canu Donata Melaku4, Chatzinikolaou Eva2, Cucco Andrea5, Domenici Paolo5, Fernandes Jose A.3, Gasche Loic6, Huebert Klaus B.1, 15, Hufnagl Marc1, Jones Miranda C.7, 16, Kempf Alexander8, Keyl Friedemann8, Maar Marie9, Mahevas Stephanie6, Marchal Paul10, Nicolas Deiphine11, Pinnegar John K.7, Rivot Etienne12, Rochette Sebastien13, Sell Anne F.8, Sinerchia Matteo5, Solidoro Cosimo4, Somerfield Paul J.3, Teal Lorna R.14, Travers-Trolet Morgane10, Van De Wolfshaar Karen E.14|
|Affiliation(s)||1 : Univ Hamburg, Inst Hydrobiol & Fisheries Sci, Olbersweg 24, D-22767 Hamburg, Germany.
2 : Inst Marine Biol Biotechnol & Aquaculture, Hellen Ctr Marine Res, POB 2214, Iraklion 71003, Crete, Greece.
3 : Plymouth Marine Lab, Prospect Pl, Plymouth PL13 DH, Devon, England.
4 : OGS Ist Nazl Oceanog & Geofis Sperimentale, Borgo Grotta Gigante 42-C, I-34010 Sgonico, TS, Italy.
5 : IAMC, CNR, Loc Sa Mardini, I-09170 Torregrande, Italy.
6 : IFREMER, Unite Ecol & Modeles Halieut, Rue Lile Yeu,BP21105, F-44311 Nantes, France.
7 : Ctr Environm Fisheries & Aquaculture Sci, Lowestoft NR33 0HT, Suffolk, England.
8 : Inst Sea Fisheries, Thunen Inst, Palmaille 9, D-22767 Hamburg, Germany.
9 : Univ Aarhus, Dept Biosci, Frederiksbotgvej 399,POB 358, DK-4000 Roskilde, Denmark.
10 : IFREMER, Lab Fishery Resources, 150 Quai Gambetta,BP 699, F-62321 Boulogne Sur Mer, France.
11 : SAHIFOS, Lab, Citadel Hill, Plymouth PL1 2PB, Devon, England.
12 : ESE Ecol & Ecosystem Hlth, UMR 985, Agrocampus Ouest, F-35042 Rennes, France.
13 : IFREMER, Unite Dynam Environm Cotier, Lab Applicat Geomat, BP 70, F-29280 Plouzane, France.
14 : Inst Marine Resources & Ecosyst Studies, Haringkade 1, Ijmuiden, Netherlands.
15 : Univ Maryland, Ctr Environm Sci, Horn Point Lab, POB 775, Cambridge, MD 21613 USA.
16 : Univ British Columbia, Fisheries Ctr, Vancouver, BC, Canada.
|Source||Estuarine Coastal And Shelf Science (0272-7714) (Academic Press Ltd- Elsevier Science Ltd), 2018-02 , Vol. 201 , P. 40-55|
|WOS© Times Cited||15|
|Keyword(s)||Distribution, Modelling, Habitat, Resources, Man-induced effects|
|Abstract||We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.|