Comparing methods for mapping global parasite diversity

Aim Parasites are a major component of global ecosystems, yet spatial variation in parasite diversity is poorly known, largely because their occurrence data are limited and thus difficult to interpret. Using a recently compiled database of parasite occurrences, we compare different models which we u...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Global ecology and biogeography 2020-01, Vol.29 (1), p.182-193
Hauptverfasser: Pappalardo, Paula, Morales‐Castilla, Ignacio, Park, Andrew W., Huang, Shan, Schmidt, John P., Stephens, Patrick R., Jordan, Greg
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 193
container_issue 1
container_start_page 182
container_title Global ecology and biogeography
container_volume 29
creator Pappalardo, Paula
Morales‐Castilla, Ignacio
Park, Andrew W.
Huang, Shan
Schmidt, John P.
Stephens, Patrick R.
Jordan, Greg
description Aim Parasites are a major component of global ecosystems, yet spatial variation in parasite diversity is poorly known, largely because their occurrence data are limited and thus difficult to interpret. Using a recently compiled database of parasite occurrences, we compare different models which we use to infer parasite geographic ranges and parasite species richness across the globe. Innovation To date, most studies exploring spatial patterns of parasite diversity assumed, with little validation, that the geographic range of a parasite species can be represented by the collective geographic range of its host species. Our study compares this assumption with a suite of other methods to infer parasite distribution from parasite occurrence data (e.g., based on data density, ecoregions and climatic conditions). We highlight diversity hotspots identified by the various methods and compare the effects of sampling intensities in different regions, a crucial factor determining observed parasite diversity. Main conclusions The type of model used to infer parasite distributions affects estimates of both total species richness and spatial patterns of hotspots of parasite richness. Overall, the models based on reported occurrences share similar areas of high parasite richness that tend to be biased towards areas of high sampling effort. In contrast, the model based on host distributions showed hotspots of parasite diversity that are biased towards areas of high host species richness. Accounting for sampling effort could only help to reconcile the outcome from the different models in some regions. Further, the non‐saturated species accumulation curves even for the best studied regions of the world such as Europe and North America serve as a call for further sampling effort and development of effective analytic tools that can provide robust accounts of global parasite diversity.
doi_str_mv 10.1111/geb.13008
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2321187737</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2321187737</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2978-a4911146356cc17589e5d23ee65748ae6ef5d49c07fe65c9de6f40ecc60809993</originalsourceid><addsrcrecordid>eNp1kEtLw0AUhQdRsFYX_oOAKxdpZzLvpZZahYIbBXfDdHITU5JOnGmV_HunRtx5N_dw-O6Dg9A1wTOSal7DZkYoxuoETQgTIlcFVad_ung7RxcxbjHGnHExQXLhu96GZldnHezffRmzyoess31_9OrWb2ybJcLGZg9Z2XxCSGq4RGeVbSNc_fYpen1Yviwe8_Xz6mlxt85doaXKLdPpKyYoF84RyZUGXhYUQHDJlAUBFS-ZdlhWyXK6BFExDM4JrLDWmk7Rzbi3D_7jAHFvtv4QdumkKWhBiJKSykTdjpQLPsYAlelD09kwGILNMReTcjE_uSR2PrJfTQvD_6BZLe_HiW9wXmMO</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2321187737</pqid></control><display><type>article</type><title>Comparing methods for mapping global parasite diversity</title><source>Access via Wiley Online Library</source><creator>Pappalardo, Paula ; Morales‐Castilla, Ignacio ; Park, Andrew W. ; Huang, Shan ; Schmidt, John P. ; Stephens, Patrick R. ; Jordan, Greg</creator><contributor>Jordan, Greg</contributor><creatorcontrib>Pappalardo, Paula ; Morales‐Castilla, Ignacio ; Park, Andrew W. ; Huang, Shan ; Schmidt, John P. ; Stephens, Patrick R. ; Jordan, Greg ; Jordan, Greg</creatorcontrib><description>Aim Parasites are a major component of global ecosystems, yet spatial variation in parasite diversity is poorly known, largely because their occurrence data are limited and thus difficult to interpret. Using a recently compiled database of parasite occurrences, we compare different models which we use to infer parasite geographic ranges and parasite species richness across the globe. Innovation To date, most studies exploring spatial patterns of parasite diversity assumed, with little validation, that the geographic range of a parasite species can be represented by the collective geographic range of its host species. Our study compares this assumption with a suite of other methods to infer parasite distribution from parasite occurrence data (e.g., based on data density, ecoregions and climatic conditions). We highlight diversity hotspots identified by the various methods and compare the effects of sampling intensities in different regions, a crucial factor determining observed parasite diversity. Main conclusions The type of model used to infer parasite distributions affects estimates of both total species richness and spatial patterns of hotspots of parasite richness. Overall, the models based on reported occurrences share similar areas of high parasite richness that tend to be biased towards areas of high sampling effort. In contrast, the model based on host distributions showed hotspots of parasite diversity that are biased towards areas of high host species richness. Accounting for sampling effort could only help to reconcile the outcome from the different models in some regions. Further, the non‐saturated species accumulation curves even for the best studied regions of the world such as Europe and North America serve as a call for further sampling effort and development of effective analytic tools that can provide robust accounts of global parasite diversity.</description><identifier>ISSN: 1466-822X</identifier><identifier>EISSN: 1466-8238</identifier><identifier>DOI: 10.1111/geb.13008</identifier><language>eng</language><publisher>Oxford: Wiley Subscription Services, Inc</publisher><subject>biodiversity ; cartography ; Climatic conditions ; geographic range ; Identification methods ; infectious disease ; mammalian host ; Mapping ; parasite ; Parasites ; pathogen ; Sampling ; Spatial variations ; Species diversity ; Species richness</subject><ispartof>Global ecology and biogeography, 2020-01, Vol.29 (1), p.182-193</ispartof><rights>2019 John Wiley &amp; Sons Ltd</rights><rights>2020 John Wiley &amp; Sons Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2978-a4911146356cc17589e5d23ee65748ae6ef5d49c07fe65c9de6f40ecc60809993</citedby><cites>FETCH-LOGICAL-c2978-a4911146356cc17589e5d23ee65748ae6ef5d49c07fe65c9de6f40ecc60809993</cites><orcidid>0000-0002-5055-1308 ; 0000-0003-1995-5715 ; 0000-0001-8549-0587 ; 0000-0002-8570-9312 ; 0000-0003-4080-7274 ; 0000-0003-0853-7681</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.13008$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fgeb.13008$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><contributor>Jordan, Greg</contributor><creatorcontrib>Pappalardo, Paula</creatorcontrib><creatorcontrib>Morales‐Castilla, Ignacio</creatorcontrib><creatorcontrib>Park, Andrew W.</creatorcontrib><creatorcontrib>Huang, Shan</creatorcontrib><creatorcontrib>Schmidt, John P.</creatorcontrib><creatorcontrib>Stephens, Patrick R.</creatorcontrib><creatorcontrib>Jordan, Greg</creatorcontrib><title>Comparing methods for mapping global parasite diversity</title><title>Global ecology and biogeography</title><description>Aim Parasites are a major component of global ecosystems, yet spatial variation in parasite diversity is poorly known, largely because their occurrence data are limited and thus difficult to interpret. Using a recently compiled database of parasite occurrences, we compare different models which we use to infer parasite geographic ranges and parasite species richness across the globe. Innovation To date, most studies exploring spatial patterns of parasite diversity assumed, with little validation, that the geographic range of a parasite species can be represented by the collective geographic range of its host species. Our study compares this assumption with a suite of other methods to infer parasite distribution from parasite occurrence data (e.g., based on data density, ecoregions and climatic conditions). We highlight diversity hotspots identified by the various methods and compare the effects of sampling intensities in different regions, a crucial factor determining observed parasite diversity. Main conclusions The type of model used to infer parasite distributions affects estimates of both total species richness and spatial patterns of hotspots of parasite richness. Overall, the models based on reported occurrences share similar areas of high parasite richness that tend to be biased towards areas of high sampling effort. In contrast, the model based on host distributions showed hotspots of parasite diversity that are biased towards areas of high host species richness. Accounting for sampling effort could only help to reconcile the outcome from the different models in some regions. Further, the non‐saturated species accumulation curves even for the best studied regions of the world such as Europe and North America serve as a call for further sampling effort and development of effective analytic tools that can provide robust accounts of global parasite diversity.</description><subject>biodiversity</subject><subject>cartography</subject><subject>Climatic conditions</subject><subject>geographic range</subject><subject>Identification methods</subject><subject>infectious disease</subject><subject>mammalian host</subject><subject>Mapping</subject><subject>parasite</subject><subject>Parasites</subject><subject>pathogen</subject><subject>Sampling</subject><subject>Spatial variations</subject><subject>Species diversity</subject><subject>Species richness</subject><issn>1466-822X</issn><issn>1466-8238</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kEtLw0AUhQdRsFYX_oOAKxdpZzLvpZZahYIbBXfDdHITU5JOnGmV_HunRtx5N_dw-O6Dg9A1wTOSal7DZkYoxuoETQgTIlcFVad_ung7RxcxbjHGnHExQXLhu96GZldnHezffRmzyoess31_9OrWb2ybJcLGZg9Z2XxCSGq4RGeVbSNc_fYpen1Yviwe8_Xz6mlxt85doaXKLdPpKyYoF84RyZUGXhYUQHDJlAUBFS-ZdlhWyXK6BFExDM4JrLDWmk7Rzbi3D_7jAHFvtv4QdumkKWhBiJKSykTdjpQLPsYAlelD09kwGILNMReTcjE_uSR2PrJfTQvD_6BZLe_HiW9wXmMO</recordid><startdate>202001</startdate><enddate>202001</enddate><creator>Pappalardo, Paula</creator><creator>Morales‐Castilla, Ignacio</creator><creator>Park, Andrew W.</creator><creator>Huang, Shan</creator><creator>Schmidt, John P.</creator><creator>Stephens, Patrick R.</creator><creator>Jordan, Greg</creator><general>Wiley Subscription Services, Inc</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><orcidid>https://orcid.org/0000-0002-5055-1308</orcidid><orcidid>https://orcid.org/0000-0003-1995-5715</orcidid><orcidid>https://orcid.org/0000-0001-8549-0587</orcidid><orcidid>https://orcid.org/0000-0002-8570-9312</orcidid><orcidid>https://orcid.org/0000-0003-4080-7274</orcidid><orcidid>https://orcid.org/0000-0003-0853-7681</orcidid></search><sort><creationdate>202001</creationdate><title>Comparing methods for mapping global parasite diversity</title><author>Pappalardo, Paula ; Morales‐Castilla, Ignacio ; Park, Andrew W. ; Huang, Shan ; Schmidt, John P. ; Stephens, Patrick R. ; Jordan, Greg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2978-a4911146356cc17589e5d23ee65748ae6ef5d49c07fe65c9de6f40ecc60809993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>biodiversity</topic><topic>cartography</topic><topic>Climatic conditions</topic><topic>geographic range</topic><topic>Identification methods</topic><topic>infectious disease</topic><topic>mammalian host</topic><topic>Mapping</topic><topic>parasite</topic><topic>Parasites</topic><topic>pathogen</topic><topic>Sampling</topic><topic>Spatial variations</topic><topic>Species diversity</topic><topic>Species richness</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pappalardo, Paula</creatorcontrib><creatorcontrib>Morales‐Castilla, Ignacio</creatorcontrib><creatorcontrib>Park, Andrew W.</creatorcontrib><creatorcontrib>Huang, Shan</creatorcontrib><creatorcontrib>Schmidt, John P.</creatorcontrib><creatorcontrib>Stephens, Patrick R.</creatorcontrib><creatorcontrib>Jordan, Greg</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><jtitle>Global ecology and biogeography</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pappalardo, Paula</au><au>Morales‐Castilla, Ignacio</au><au>Park, Andrew W.</au><au>Huang, Shan</au><au>Schmidt, John P.</au><au>Stephens, Patrick R.</au><au>Jordan, Greg</au><au>Jordan, Greg</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparing methods for mapping global parasite diversity</atitle><jtitle>Global ecology and biogeography</jtitle><date>2020-01</date><risdate>2020</risdate><volume>29</volume><issue>1</issue><spage>182</spage><epage>193</epage><pages>182-193</pages><issn>1466-822X</issn><eissn>1466-8238</eissn><abstract>Aim Parasites are a major component of global ecosystems, yet spatial variation in parasite diversity is poorly known, largely because their occurrence data are limited and thus difficult to interpret. Using a recently compiled database of parasite occurrences, we compare different models which we use to infer parasite geographic ranges and parasite species richness across the globe. Innovation To date, most studies exploring spatial patterns of parasite diversity assumed, with little validation, that the geographic range of a parasite species can be represented by the collective geographic range of its host species. Our study compares this assumption with a suite of other methods to infer parasite distribution from parasite occurrence data (e.g., based on data density, ecoregions and climatic conditions). We highlight diversity hotspots identified by the various methods and compare the effects of sampling intensities in different regions, a crucial factor determining observed parasite diversity. Main conclusions The type of model used to infer parasite distributions affects estimates of both total species richness and spatial patterns of hotspots of parasite richness. Overall, the models based on reported occurrences share similar areas of high parasite richness that tend to be biased towards areas of high sampling effort. In contrast, the model based on host distributions showed hotspots of parasite diversity that are biased towards areas of high host species richness. Accounting for sampling effort could only help to reconcile the outcome from the different models in some regions. Further, the non‐saturated species accumulation curves even for the best studied regions of the world such as Europe and North America serve as a call for further sampling effort and development of effective analytic tools that can provide robust accounts of global parasite diversity.</abstract><cop>Oxford</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/geb.13008</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-5055-1308</orcidid><orcidid>https://orcid.org/0000-0003-1995-5715</orcidid><orcidid>https://orcid.org/0000-0001-8549-0587</orcidid><orcidid>https://orcid.org/0000-0002-8570-9312</orcidid><orcidid>https://orcid.org/0000-0003-4080-7274</orcidid><orcidid>https://orcid.org/0000-0003-0853-7681</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1466-822X
ispartof Global ecology and biogeography, 2020-01, Vol.29 (1), p.182-193
issn 1466-822X
1466-8238
language eng
recordid cdi_proquest_journals_2321187737
source Access via Wiley Online Library
subjects biodiversity
cartography
Climatic conditions
geographic range
Identification methods
infectious disease
mammalian host
Mapping
parasite
Parasites
pathogen
Sampling
Spatial variations
Species diversity
Species richness
title Comparing methods for mapping global parasite diversity
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T22%3A23%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Comparing%20methods%20for%20mapping%20global%20parasite%20diversity&rft.jtitle=Global%20ecology%20and%20biogeography&rft.au=Pappalardo,%20Paula&rft.date=2020-01&rft.volume=29&rft.issue=1&rft.spage=182&rft.epage=193&rft.pages=182-193&rft.issn=1466-822X&rft.eissn=1466-8238&rft_id=info:doi/10.1111/geb.13008&rft_dat=%3Cproquest_cross%3E2321187737%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2321187737&rft_id=info:pmid/&rfr_iscdi=true