Species richness in North Atlantic fish: Process concealed by pattern

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...

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Veröffentlicht in:Global ecology and biogeography 2020-05, Vol.29 (5), p.842-856
Hauptverfasser: Gislason, Henrik, Collie, Jeremy, MacKenzie, Brian R., Nielsen, Anders, Borges, Maria de Fatima, Bottari, Teresa, Chaves, Corina, Dolgov, Andrey V., Dulčić, Jakov, Duplisea, Daniel, Fock, Heino O., Gascuel, Didier, Gil de Sola, Luís, Hiddink, Jan Geert, Hofstede, Remment, Isajlović, Igor, Jonasson, Jónas Páll, Jørgensen, Ole, Kristinsson, Kristján, Marteinsdottir, Gudrun, Masski, Hicham, Matić‐Skoko, Sanja, Payne, Mark R., Peharda, Melita, Reinert, Jakup, Sólmundsson, Jón, Silva, Cristina, Stefansdottir, Lilja, Velasco, Francisco, Vrgoč, Nedo, Tittensor, Derek
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container_issue 5
container_start_page 842
container_title Global ecology and biogeography
container_volume 29
creator Gislason, Henrik
Collie, Jeremy
MacKenzie, Brian R.
Nielsen, Anders
Borges, Maria de Fatima
Bottari, Teresa
Chaves, Corina
Dolgov, Andrey V.
Dulčić, Jakov
Duplisea, Daniel
Fock, Heino O.
Gascuel, Didier
Gil de Sola, Luís
Hiddink, Jan Geert
Hofstede, Remment
Isajlović, Igor
Jonasson, Jónas Páll
Jørgensen, Ole
Kristinsson, Kristján
Marteinsdottir, Gudrun
Masski, Hicham
Matić‐Skoko, Sanja
Payne, Mark R.
Peharda, Melita
Reinert, Jakup
Sólmundsson, Jón
Silva, Cristina
Stefansdottir, Lilja
Velasco, Francisco
Vrgoč, Nedo
Tittensor, Derek
description 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.
doi_str_mv 10.1111/geb.13068
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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.</description><identifier>ISSN: 1466-822X</identifier><identifier>EISSN: 1466-8238</identifier><identifier>EISSN: 1466-822X</identifier><identifier>DOI: 10.1111/geb.13068</identifier><language>eng</language><publisher>Oxford: Wiley Subscription Services, Inc</publisher><subject>Abundance ; Agricultural sciences ; biodiversity ; Biological evolution ; Catchability ; density ; Ecology, environment ; Environment models ; Environmental conditions ; Environmental modeling ; Finite element method ; Fish ; Identification methods ; Latitude ; Life Sciences ; Longitude ; Marine fish ; Mathematical models ; Metabolism ; Pattern analysis ; Primary production ; Sampling ; Sciences and technics of fishery ; Speciation ; Species extinction ; Species richness ; species size ; Statistical analysis ; Statistical models ; temperature</subject><ispartof>Global ecology and biogeography, 2020-05, Vol.29 (5), p.842-856</ispartof><rights>2020 John Wiley &amp; Sons Ltd</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3668-366d7c5848d9befaaca60f5126dd5d7c4669ac7d4e48e2e9b26df21ab81343393</citedby><cites>FETCH-LOGICAL-c3668-366d7c5848d9befaaca60f5126dd5d7c4669ac7d4e48e2e9b26df21ab81343393</cites><orcidid>0000-0003-0242-3333 ; 0000-0002-0495-3955 ; 0000-0001-5447-6977</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fgeb.13068$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fgeb.13068$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://institut-agro-rennes-angers.hal.science/hal-02612928$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Gislason, Henrik</creatorcontrib><creatorcontrib>Collie, Jeremy</creatorcontrib><creatorcontrib>MacKenzie, Brian R.</creatorcontrib><creatorcontrib>Nielsen, Anders</creatorcontrib><creatorcontrib>Borges, Maria de Fatima</creatorcontrib><creatorcontrib>Bottari, Teresa</creatorcontrib><creatorcontrib>Chaves, Corina</creatorcontrib><creatorcontrib>Dolgov, Andrey V.</creatorcontrib><creatorcontrib>Dulčić, Jakov</creatorcontrib><creatorcontrib>Duplisea, Daniel</creatorcontrib><creatorcontrib>Fock, Heino O.</creatorcontrib><creatorcontrib>Gascuel, Didier</creatorcontrib><creatorcontrib>Gil de Sola, Luís</creatorcontrib><creatorcontrib>Hiddink, Jan Geert</creatorcontrib><creatorcontrib>Hofstede, Remment</creatorcontrib><creatorcontrib>Isajlović, Igor</creatorcontrib><creatorcontrib>Jonasson, Jónas Páll</creatorcontrib><creatorcontrib>Jørgensen, Ole</creatorcontrib><creatorcontrib>Kristinsson, Kristján</creatorcontrib><creatorcontrib>Marteinsdottir, Gudrun</creatorcontrib><creatorcontrib>Masski, Hicham</creatorcontrib><creatorcontrib>Matić‐Skoko, Sanja</creatorcontrib><creatorcontrib>Payne, Mark R.</creatorcontrib><creatorcontrib>Peharda, Melita</creatorcontrib><creatorcontrib>Reinert, Jakup</creatorcontrib><creatorcontrib>Sólmundsson, Jón</creatorcontrib><creatorcontrib>Silva, Cristina</creatorcontrib><creatorcontrib>Stefansdottir, Lilja</creatorcontrib><creatorcontrib>Velasco, Francisco</creatorcontrib><creatorcontrib>Vrgoč, Nedo</creatorcontrib><creatorcontrib>Tittensor, Derek</creatorcontrib><title>Species richness in North Atlantic fish: Process concealed by pattern</title><title>Global ecology and biogeography</title><description>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.</description><subject>Abundance</subject><subject>Agricultural sciences</subject><subject>biodiversity</subject><subject>Biological evolution</subject><subject>Catchability</subject><subject>density</subject><subject>Ecology, environment</subject><subject>Environment models</subject><subject>Environmental conditions</subject><subject>Environmental modeling</subject><subject>Finite element method</subject><subject>Fish</subject><subject>Identification methods</subject><subject>Latitude</subject><subject>Life Sciences</subject><subject>Longitude</subject><subject>Marine fish</subject><subject>Mathematical models</subject><subject>Metabolism</subject><subject>Pattern analysis</subject><subject>Primary production</subject><subject>Sampling</subject><subject>Sciences and technics of fishery</subject><subject>Speciation</subject><subject>Species extinction</subject><subject>Species richness</subject><subject>species size</subject><subject>Statistical analysis</subject><subject>Statistical 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Derek</creatorcontrib><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Global ecology and biogeography</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gislason, Henrik</au><au>Collie, Jeremy</au><au>MacKenzie, Brian R.</au><au>Nielsen, Anders</au><au>Borges, Maria de Fatima</au><au>Bottari, Teresa</au><au>Chaves, Corina</au><au>Dolgov, Andrey V.</au><au>Dulčić, Jakov</au><au>Duplisea, Daniel</au><au>Fock, Heino O.</au><au>Gascuel, Didier</au><au>Gil de Sola, Luís</au><au>Hiddink, Jan Geert</au><au>Hofstede, Remment</au><au>Isajlović, Igor</au><au>Jonasson, Jónas Páll</au><au>Jørgensen, Ole</au><au>Kristinsson, Kristján</au><au>Marteinsdottir, Gudrun</au><au>Masski, Hicham</au><au>Matić‐Skoko, Sanja</au><au>Payne, Mark R.</au><au>Peharda, Melita</au><au>Reinert, Jakup</au><au>Sólmundsson, Jón</au><au>Silva, Cristina</au><au>Stefansdottir, Lilja</au><au>Velasco, Francisco</au><au>Vrgoč, Nedo</au><au>Tittensor, Derek</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Species richness in North Atlantic fish: Process concealed by pattern</atitle><jtitle>Global ecology and biogeography</jtitle><date>2020-05</date><risdate>2020</risdate><volume>29</volume><issue>5</issue><spage>842</spage><epage>856</epage><pages>842-856</pages><issn>1466-822X</issn><eissn>1466-8238</eissn><eissn>1466-822X</eissn><abstract>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.</abstract><cop>Oxford</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/geb.13068</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-0242-3333</orcidid><orcidid>https://orcid.org/0000-0002-0495-3955</orcidid><orcidid>https://orcid.org/0000-0001-5447-6977</orcidid><oa>free_for_read</oa></addata></record>
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source Wiley Online Library Journals Frontfile Complete
subjects Abundance
Agricultural sciences
biodiversity
Biological evolution
Catchability
density
Ecology, environment
Environment models
Environmental conditions
Environmental modeling
Finite element method
Fish
Identification methods
Latitude
Life Sciences
Longitude
Marine fish
Mathematical models
Metabolism
Pattern analysis
Primary production
Sampling
Sciences and technics of fishery
Speciation
Species extinction
Species richness
species size
Statistical analysis
Statistical models
temperature
title Species richness in North Atlantic fish: Process concealed by pattern
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