TY - JOUR
T1 - Species richness in North Atlantic fish
T2 - Process concealed by pattern
AU - Gislason, Henrik
AU - Collie, Jeremy
AU - MacKenzie, Brian R.
AU - Nielsen, Anders
AU - Borges, Maria de Fatima
AU - Bottari, Teresa
AU - Chaves, Corina
AU - Dolgov, Andrey V.
AU - Dulčić, Jakov
AU - Duplisea, Daniel
AU - Fock, Heino O.
AU - Gascuel, Didier
AU - Gil de Sola, Luís
AU - Hiddink, Jan Geert
AU - ter Hofstede, Remment
AU - Isajlović, Igor
AU - Jonasson, Jónas Páll
AU - Jørgensen, Ole
AU - Kristinsson, Kristján
AU - Marteinsdottir, Gudrun
AU - Masski, Hicham
AU - Matić-Skoko, Sanja
AU - Payne, Mark R.
AU - Peharda, Melita
AU - Reinert, Jakup
AU - Sólmundsson, Jón
AU - Silva, Cristina
AU - Stefansdottir, L
AU - Velasco, Francisco
AU - Vrgoč, Nedo
N1 - Publisher Copyright:
© 2020 John Wiley & Sons Ltd
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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 speciation and extinction rates.
AB - 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 speciation and extinction rates.
KW - abundance
KW - biodiversity
KW - density
KW - marine fish
KW - species size
KW - temperature
UR - http://www.scopus.com/inward/record.url?scp=85078681412&partnerID=8YFLogxK
U2 - 10.1111/geb.13068
DO - 10.1111/geb.13068
M3 - Article
AN - SCOPUS:85078681412
SN - 1466-822X
VL - 29
SP - 842
EP - 856
JO - Global Ecology and Biogeography
JF - Global Ecology and Biogeography
IS - 5
ER -