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 |
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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 |
format | Article |
fullrecord | <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_02612928v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2384767921</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3668-366d7c5848d9befaaca60f5126dd5d7c4669ac7d4e48e2e9b26df21ab81343393</originalsourceid><addsrcrecordid>eNp1kMFLwzAYxYMoOKcH_4OAJw_dkrRNU29T5iYMFVTwFtL0q82oTU06Zf-9mZV58jvkC3m_PB4PoXNKJjTM9A2KCY0JFwdoRBPOI8Ficbi_s9djdOL9mhCSJikfoflTB9qAx87ougXvsWnxvXV9jWd9o9reaFwZX1_hR2f1Tte21aAaKHGxxZ3qe3DtKTqqVOPh7HeP0cvt_PlmGa0eFnc3s1WkY85FFI4y06lIRJkXUCmlFSdVShkvyzQoIWOudFYmkAhgkBdBqBhVhaBxEsd5PEaXg2-tGtk5867cVlpl5HK2krs3wjhlOROfNLAXA9s5-7EB38u13bg2xJOhkiTjWc7on6N21nsH1d6WErlrVIZG5U-jgZ0O7JdpYPs_KBfz6-HHNy64dd4</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2384767921</pqid></control><display><type>article</type><title>Species richness in North Atlantic fish: Process concealed by pattern</title><source>Wiley Online Library Journals Frontfile Complete</source><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</creator><creatorcontrib>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</creatorcontrib><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><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 & 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 models</subject><subject>temperature</subject><issn>1466-822X</issn><issn>1466-8238</issn><issn>1466-822X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kMFLwzAYxYMoOKcH_4OAJw_dkrRNU29T5iYMFVTwFtL0q82oTU06Zf-9mZV58jvkC3m_PB4PoXNKJjTM9A2KCY0JFwdoRBPOI8Ficbi_s9djdOL9mhCSJikfoflTB9qAx87ougXvsWnxvXV9jWd9o9reaFwZX1_hR2f1Tte21aAaKHGxxZ3qe3DtKTqqVOPh7HeP0cvt_PlmGa0eFnc3s1WkY85FFI4y06lIRJkXUCmlFSdVShkvyzQoIWOudFYmkAhgkBdBqBhVhaBxEsd5PEaXg2-tGtk5867cVlpl5HK2krs3wjhlOROfNLAXA9s5-7EB38u13bg2xJOhkiTjWc7on6N21nsH1d6WErlrVIZG5U-jgZ0O7JdpYPs_KBfz6-HHNy64dd4</recordid><startdate>202005</startdate><enddate>202005</enddate><creator>Gislason, Henrik</creator><creator>Collie, Jeremy</creator><creator>MacKenzie, Brian R.</creator><creator>Nielsen, Anders</creator><creator>Borges, Maria de Fatima</creator><creator>Bottari, Teresa</creator><creator>Chaves, Corina</creator><creator>Dolgov, Andrey V.</creator><creator>Dulčić, Jakov</creator><creator>Duplisea, Daniel</creator><creator>Fock, Heino O.</creator><creator>Gascuel, Didier</creator><creator>Gil de Sola, Luís</creator><creator>Hiddink, Jan Geert</creator><creator>Hofstede, Remment</creator><creator>Isajlović, Igor</creator><creator>Jonasson, Jónas Páll</creator><creator>Jørgensen, Ole</creator><creator>Kristinsson, Kristján</creator><creator>Marteinsdottir, Gudrun</creator><creator>Masski, Hicham</creator><creator>Matić‐Skoko, Sanja</creator><creator>Payne, Mark R.</creator><creator>Peharda, Melita</creator><creator>Reinert, Jakup</creator><creator>Sólmundsson, Jón</creator><creator>Silva, Cristina</creator><creator>Stefansdottir, Lilja</creator><creator>Velasco, Francisco</creator><creator>Vrgoč, Nedo</creator><creator>Tittensor, Derek</creator><general>Wiley Subscription Services, Inc</general><general>Wiley</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7SN</scope><scope>7SS</scope><scope>7ST</scope><scope>7U6</scope><scope>C1K</scope><scope>1XC</scope><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></search><sort><creationdate>202005</creationdate><title>Species richness in North Atlantic fish: Process concealed by pattern</title><author>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</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3668-366d7c5848d9befaaca60f5126dd5d7c4669ac7d4e48e2e9b26df21ab81343393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Abundance</topic><topic>Agricultural sciences</topic><topic>biodiversity</topic><topic>Biological evolution</topic><topic>Catchability</topic><topic>density</topic><topic>Ecology, environment</topic><topic>Environment models</topic><topic>Environmental conditions</topic><topic>Environmental modeling</topic><topic>Finite element method</topic><topic>Fish</topic><topic>Identification methods</topic><topic>Latitude</topic><topic>Life Sciences</topic><topic>Longitude</topic><topic>Marine fish</topic><topic>Mathematical models</topic><topic>Metabolism</topic><topic>Pattern analysis</topic><topic>Primary production</topic><topic>Sampling</topic><topic>Sciences and technics of fishery</topic><topic>Speciation</topic><topic>Species extinction</topic><topic>Species richness</topic><topic>species size</topic><topic>Statistical analysis</topic><topic>Statistical models</topic><topic>temperature</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><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><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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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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