Species richness in North Atlantic fish: Process concealed by pattern.

• Published in: Global Ecology and Biogeography
• Main Authors: Gislason, H., Collie, J., MacKenzie, B.R. (Brian R.), Nielsen, Anders, Borges, M.F. (María de Fátima), Bottari, Teresa, Chaves, Corina, Dolgov, Andrey V., Dulčić, J. (Jakov), Duplisea, Daniel, Fock, H.O. (Heino), Gascuel, D. (Didier), Gil-de-Sola-Simarro, L. (Luis), Hiddink, J.G. (Jan Geert), Ter Hofstede, Remment, Payne, Mark R., Sólmundsson, J. (Jon), Stefansdottir, Lilja, Velasco, F. (Francisco), Vrgoc, N. (Nedo)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: abundance; biodiversity; density; marine fish; species size; temperature; North Atlantic
• Online Access: http://hdl.handle.net/10508/14885; https://backend.orbit.dtu.dk/ws/files/205806713/Gislason_et_al._2020_Species_richness_Post_print.pdf; https://doi.org/10.1111/geb.13068

Aim: Previous analyses of marine fish species richness based on presence-absence data have shown changes with latitude and average species size, but little is known about the underlying processes. To elucidate these processes we use metabolic, neutral and descriptive statistical models to analyse how richness responds to maximum species length, fish abundance, temperature, primary production, depth, latitude and longitude, while accounting for differences in species catchability, sampling effort and mesh size. Data: Results from 53,382 bottom trawl hauls representing 50 fish assemblages. Location: The northern Atlantic from Nova Scotia to Guinea. Time period: 1977–2013. Methods: A descriptive generalized additive model was used to identify functional relationships between species richness and potential drivers, after which nonlinear estimation techniques were used to parameterize: (a) a ‘best’ fitting model of species richness built on the functional relationships, (b) an environmental model based on latitude, longitude and depth, and mechanistic models based on (c) metabolic and (d) neutral theory. Results: In the ‘best’ model the number of species observed is a lognormal function of maximum species length. It increases significantly with temperature, primary production, sampling effort, and abundance, and declines with depth and, for small species, with the mesh size in the trawl. The ‘best’ model explains close to 90% of the deviance and the neutral, metabolic and environmental models 89%. In all four models, maximum species length and either temperature or latitude account for more than half of the deviance explained. Main conclusions: The two mechanistic models explain the patterns in demersal fish species richness in the northern Atlantic almost equally well. A better understanding of the underlying drivers is likely to require development of dynamic mechanistic models of richness and size evolution, fit not only to extant distributions, but also to historical environmental conditions and to past ...