pavo 2: New tools for the spectral and spatial analysis of colour in r
Biological coloration presents a canvas for the study of ecological and evolutionary processes. Enduring interest in colour‐based phenotypes has driven, and been driven by, improved techniques for quantifying colour patterns in ever‐more relevant ways, yet the need for flexible, open frameworks for...
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Veröffentlicht in: | Methods in ecology and evolution 2019-07, Vol.10 (7), p.1097-1107 |
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creator | Maia, Rafael Gruson, Hugo Endler, John A. White, Thomas E. O’Hara, Robert B. |
description | Biological coloration presents a canvas for the study of ecological and evolutionary processes. Enduring interest in colour‐based phenotypes has driven, and been driven by, improved techniques for quantifying colour patterns in ever‐more relevant ways, yet the need for flexible, open frameworks for data processing and analysis persists.
Here we introduce pavo 2, the latest iteration of the r package pavo. This release represents the extensive refinement and expansion of existing methods, as well as a suite of new tools for the cohesive analysis of the spectral and (now) spatial structure of colour patterns and perception. At its core, the package retains a broad focus on (a) the organization and processing of spectral and spatial data, and tools for the alternating (b) visualization, and (c) analysis of data. Significantly, pavo 2 introduces image‐analysis capabilities, providing a cohesive workflow for the comprehensive analysis of colour patterns.
We demonstrate the utility of pavo with a brief example centred on mimicry in Heliconius butterflies. Drawing on visual modelling, adjacency, and boundary strength analyses, we show that the combined spectral (colour and luminance) and spatial (pattern element distribution and boundary salience) features of putative models and mimics are closely aligned.
pavo 2 offers a flexible and reproducible environment for the analysis of colour, with renewed potential to assist researchers in answering fundamental questions in sensory ecology and evolution. |
doi_str_mv | 10.1111/2041-210X.13174 |
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Here we introduce pavo 2, the latest iteration of the r package pavo. This release represents the extensive refinement and expansion of existing methods, as well as a suite of new tools for the cohesive analysis of the spectral and (now) spatial structure of colour patterns and perception. At its core, the package retains a broad focus on (a) the organization and processing of spectral and spatial data, and tools for the alternating (b) visualization, and (c) analysis of data. Significantly, pavo 2 introduces image‐analysis capabilities, providing a cohesive workflow for the comprehensive analysis of colour patterns.
We demonstrate the utility of pavo with a brief example centred on mimicry in Heliconius butterflies. Drawing on visual modelling, adjacency, and boundary strength analyses, we show that the combined spectral (colour and luminance) and spatial (pattern element distribution and boundary salience) features of putative models and mimics are closely aligned.
pavo 2 offers a flexible and reproducible environment for the analysis of colour, with renewed potential to assist researchers in answering fundamental questions in sensory ecology and evolution.</description><identifier>ISSN: 2041-210X</identifier><identifier>EISSN: 2041-210X</identifier><identifier>DOI: 10.1111/2041-210X.13174</identifier><language>eng</language><publisher>London: John Wiley & Sons, Inc</publisher><subject>Biodiversity ; Biodiversity and Ecology ; Biological evolution ; Boundary element method ; Butterflies & moths ; Color ; color, perception, animals, workflow ; Coloration ; colour ; colourspace ; Data analysis ; Data processing ; Ecological monitoring ; Ecology, environment ; Environmental Sciences ; Image processing ; Information processing ; Iterative methods ; Life Sciences ; Luminance distribution ; Mimicry ; Phenotypes ; photography ; Populations and Evolution ; reflectance ; sensory ecology ; Spatial analysis ; Spatial data ; Spectra ; spectrometry ; Symbiosis ; vision ; Workflow</subject><ispartof>Methods in ecology and evolution, 2019-07, Vol.10 (7), p.1097-1107</ispartof><rights>2019 The Authors. Methods in Ecology and Evolution © 2019 British Ecological Society</rights><rights>Methods in Ecology and Evolution © 2019 British Ecological Society</rights><rights>Copyright</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3964-e15bf3d0cbeacb02a274e52a722a7534ee7d4b0b565f521f464240e819a2f73</citedby><cites>FETCH-LOGICAL-c3964-e15bf3d0cbeacb02a274e52a722a7534ee7d4b0b565f521f464240e819a2f73</cites><orcidid>0000-0002-7563-9795 ; 0000-0002-4094-1476 ; 0000-0002-7557-7627 ; 0000-0002-3976-1734 ; 0000-0002-0536-6162</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%2F2041-210X.13174$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2F2041-210X.13174$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://hal.science/hal-02063659$$DView record in HAL$$Hfree_for_read</backlink></links><search><contributor>O’Hara, Robert B.</contributor><creatorcontrib>Maia, Rafael</creatorcontrib><creatorcontrib>Gruson, Hugo</creatorcontrib><creatorcontrib>Endler, John A.</creatorcontrib><creatorcontrib>White, Thomas E.</creatorcontrib><creatorcontrib>O’Hara, Robert B.</creatorcontrib><title>pavo 2: New tools for the spectral and spatial analysis of colour in r</title><title>Methods in ecology and evolution</title><description>Biological coloration presents a canvas for the study of ecological and evolutionary processes. Enduring interest in colour‐based phenotypes has driven, and been driven by, improved techniques for quantifying colour patterns in ever‐more relevant ways, yet the need for flexible, open frameworks for data processing and analysis persists.
Here we introduce pavo 2, the latest iteration of the r package pavo. This release represents the extensive refinement and expansion of existing methods, as well as a suite of new tools for the cohesive analysis of the spectral and (now) spatial structure of colour patterns and perception. At its core, the package retains a broad focus on (a) the organization and processing of spectral and spatial data, and tools for the alternating (b) visualization, and (c) analysis of data. Significantly, pavo 2 introduces image‐analysis capabilities, providing a cohesive workflow for the comprehensive analysis of colour patterns.
We demonstrate the utility of pavo with a brief example centred on mimicry in Heliconius butterflies. Drawing on visual modelling, adjacency, and boundary strength analyses, we show that the combined spectral (colour and luminance) and spatial (pattern element distribution and boundary salience) features of putative models and mimics are closely aligned.
pavo 2 offers a flexible and reproducible environment for the analysis of colour, with renewed potential to assist researchers in answering fundamental questions in sensory ecology and evolution.</description><subject>Biodiversity</subject><subject>Biodiversity and Ecology</subject><subject>Biological evolution</subject><subject>Boundary element method</subject><subject>Butterflies & moths</subject><subject>Color</subject><subject>color, perception, animals, workflow</subject><subject>Coloration</subject><subject>colour</subject><subject>colourspace</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Ecological monitoring</subject><subject>Ecology, environment</subject><subject>Environmental Sciences</subject><subject>Image processing</subject><subject>Information processing</subject><subject>Iterative methods</subject><subject>Life Sciences</subject><subject>Luminance distribution</subject><subject>Mimicry</subject><subject>Phenotypes</subject><subject>photography</subject><subject>Populations and Evolution</subject><subject>reflectance</subject><subject>sensory ecology</subject><subject>Spatial analysis</subject><subject>Spatial data</subject><subject>Spectra</subject><subject>spectrometry</subject><subject>Symbiosis</subject><subject>vision</subject><subject>Workflow</subject><issn>2041-210X</issn><issn>2041-210X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqFkE1rAjEQhkNpoWI99xroqYfVZPKxbm8iWgu2PbSH3kJ2TXBla7bJqvjvzbpFeuvAMB887zC8CN1TMqQxRkA4TYCSryFlNOVXqHfZXP_pb9EghA2JwcYZAd5D81rvHYYn_GYOuHGuCtg6j5u1waE2ReN1hfV2FQfdlOdeV8dQBuwsLlzldh6XW-zv0I3VVTCD39pHH_PZ53SRLN-fX6aTZVKwTPLEUJFbtiJFbnSRE9CQciNApxBTMG5MuuI5yYUUVgC1XHLgxIxppsGmrI8eu6trXanal9_aH5XTpVpMlqrdESCSSZHtaWQfOrb27mdnQqM28dn4fVAAPJMpEBCRGnVU4V0I3tjLWUpU66xqvVOtd-rsbFTITnEoK3P8D1evsxnrhCd843fS</recordid><startdate>201907</startdate><enddate>201907</enddate><creator>Maia, Rafael</creator><creator>Gruson, Hugo</creator><creator>Endler, John A.</creator><creator>White, Thomas E.</creator><creator>O’Hara, Robert B.</creator><general>John Wiley & Sons, Inc</general><general>Wiley</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7SN</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0002-7563-9795</orcidid><orcidid>https://orcid.org/0000-0002-4094-1476</orcidid><orcidid>https://orcid.org/0000-0002-7557-7627</orcidid><orcidid>https://orcid.org/0000-0002-3976-1734</orcidid><orcidid>https://orcid.org/0000-0002-0536-6162</orcidid></search><sort><creationdate>201907</creationdate><title>pavo 2: New tools for the spectral and spatial analysis of colour in r</title><author>Maia, Rafael ; Gruson, Hugo ; Endler, John A. ; White, Thomas E. ; O’Hara, Robert B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3964-e15bf3d0cbeacb02a274e52a722a7534ee7d4b0b565f521f464240e819a2f73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Biodiversity</topic><topic>Biodiversity and Ecology</topic><topic>Biological evolution</topic><topic>Boundary element method</topic><topic>Butterflies & moths</topic><topic>Color</topic><topic>color, perception, animals, workflow</topic><topic>Coloration</topic><topic>colour</topic><topic>colourspace</topic><topic>Data analysis</topic><topic>Data processing</topic><topic>Ecological monitoring</topic><topic>Ecology, environment</topic><topic>Environmental Sciences</topic><topic>Image processing</topic><topic>Information processing</topic><topic>Iterative methods</topic><topic>Life Sciences</topic><topic>Luminance distribution</topic><topic>Mimicry</topic><topic>Phenotypes</topic><topic>photography</topic><topic>Populations and Evolution</topic><topic>reflectance</topic><topic>sensory ecology</topic><topic>Spatial analysis</topic><topic>Spatial data</topic><topic>Spectra</topic><topic>spectrometry</topic><topic>Symbiosis</topic><topic>vision</topic><topic>Workflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Maia, Rafael</creatorcontrib><creatorcontrib>Gruson, Hugo</creatorcontrib><creatorcontrib>Endler, John A.</creatorcontrib><creatorcontrib>White, Thomas E.</creatorcontrib><creatorcontrib>O’Hara, Robert B.</creatorcontrib><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Ecology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Methods in ecology and evolution</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Maia, Rafael</au><au>Gruson, Hugo</au><au>Endler, John A.</au><au>White, Thomas E.</au><au>O’Hara, Robert B.</au><au>O’Hara, Robert B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>pavo 2: New tools for the spectral and spatial analysis of colour in r</atitle><jtitle>Methods in ecology and evolution</jtitle><date>2019-07</date><risdate>2019</risdate><volume>10</volume><issue>7</issue><spage>1097</spage><epage>1107</epage><pages>1097-1107</pages><issn>2041-210X</issn><eissn>2041-210X</eissn><abstract>Biological coloration presents a canvas for the study of ecological and evolutionary processes. Enduring interest in colour‐based phenotypes has driven, and been driven by, improved techniques for quantifying colour patterns in ever‐more relevant ways, yet the need for flexible, open frameworks for data processing and analysis persists.
Here we introduce pavo 2, the latest iteration of the r package pavo. This release represents the extensive refinement and expansion of existing methods, as well as a suite of new tools for the cohesive analysis of the spectral and (now) spatial structure of colour patterns and perception. At its core, the package retains a broad focus on (a) the organization and processing of spectral and spatial data, and tools for the alternating (b) visualization, and (c) analysis of data. Significantly, pavo 2 introduces image‐analysis capabilities, providing a cohesive workflow for the comprehensive analysis of colour patterns.
We demonstrate the utility of pavo with a brief example centred on mimicry in Heliconius butterflies. Drawing on visual modelling, adjacency, and boundary strength analyses, we show that the combined spectral (colour and luminance) and spatial (pattern element distribution and boundary salience) features of putative models and mimics are closely aligned.
pavo 2 offers a flexible and reproducible environment for the analysis of colour, with renewed potential to assist researchers in answering fundamental questions in sensory ecology and evolution.</abstract><cop>London</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1111/2041-210X.13174</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-7563-9795</orcidid><orcidid>https://orcid.org/0000-0002-4094-1476</orcidid><orcidid>https://orcid.org/0000-0002-7557-7627</orcidid><orcidid>https://orcid.org/0000-0002-3976-1734</orcidid><orcidid>https://orcid.org/0000-0002-0536-6162</orcidid></addata></record> |
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subjects | Biodiversity Biodiversity and Ecology Biological evolution Boundary element method Butterflies & moths Color color, perception, animals, workflow Coloration colour colourspace Data analysis Data processing Ecological monitoring Ecology, environment Environmental Sciences Image processing Information processing Iterative methods Life Sciences Luminance distribution Mimicry Phenotypes photography Populations and Evolution reflectance sensory ecology Spatial analysis Spatial data Spectra spectrometry Symbiosis vision Workflow |
title | pavo 2: New tools for the spectral and spatial analysis of colour in r |
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