Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model
Species distribution modeling was used to determine factors among the large predictor candidate data set that affect the distribution of Muscari latifolium, an endemic bulbous plant species of Turkey, to quantify the relative importance of each factor and make a potential spatial distribution map of...
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description | Species distribution modeling was used to determine factors among the large predictor candidate data set that affect the distribution of Muscari latifolium, an endemic bulbous plant species of Turkey, to quantify the relative importance of each factor and make a potential spatial distribution map of M. latifolium. Models were built using the Boosted Regression Trees method based on 35 presence and 70 absence records obtained through field sampling in the Gönen Dam watershed area of the Kazdağı Mountains in West Anatolia. Large candidate variables of monthly and seasonal climate, fine‐scale land surface, and geologic and biotic variables were simplified using a BRT simplifying procedure. Analyses performed on these resources, direct and indirect variables showed that there were 14 main factors that influence the species’ distribution. Five of the 14 most important variables influencing the distribution of the species are bedrock type, Quercus cerris density, precipitation during the wettest month, Pinus nigra density, and northness. These variables account for approximately 60% of the relative importance for determining the distribution of the species. Prediction performance was assessed by 10 random subsample data sets and gave a maximum the area under a receiver operating characteristic curve (AUC) value of 0.93 and an average AUC value of 0.8. This study provides a significant contribution to the knowledge of the habitat requirements and ecological characteristics of this species. The distribution of this species is explained by a combination of biotic and abiotic factors. Hence, using biotic interaction and fine‐scale land surface variables in species distribution models improved the accuracy and precision of the model. The knowledge of the relationships between distribution patterns and environmental factors and biotic interaction of M. latifolium can help develop a management and conservation strategy for this species.
Muscari latifolium is an endemic bulbous species of Turkey. Factors were determined that affect the distribution on M. latifolium. We used a large environmental variable data set and simplified them with BRTs. We used biotic interactions in the model. The information obtained in the study can be used to support management, conservation, and, if needed, restoration programs for this species. |
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Muscari latifolium is an endemic bulbous species of Turkey. Factors were determined that affect the distribution on M. latifolium. We used a large environmental variable data set and simplified them with BRTs. We used biotic interactions in the model. The information obtained in the study can be used to support management, conservation, and, if needed, restoration programs for this species.</description><identifier>ISSN: 2045-7758</identifier><identifier>EISSN: 2045-7758</identifier><identifier>DOI: 10.1002/ece3.2766</identifier><identifier>PMID: 28303182</identifier><language>eng</language><publisher>England: John Wiley & Sons, Inc</publisher><subject>Abiotic factors ; Bedrock ; biotic factors ; boosted regression modeling ; bulbous plant ; Distribution patterns ; Endemic species ; Environmental factors ; Mecranium latifolium ; Model accuracy ; Mountains ; Muscari ; Original Research ; Pine trees ; Pinus nigra ; Plant species ; Quercus cerris ; Rainfall ; Regression analysis ; Spatial distribution ; Species ; species distribution modeling ; Watersheds ; Wildlife conservation</subject><ispartof>Ecology and evolution, 2017-02, Vol.7 (4), p.1112-1124</ispartof><rights>2017 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2017. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4766-acef6aafc6c9c812383b6ed25300ba0da8bf34c63ce5cdeb058bcbdcd86d994b3</citedby><cites>FETCH-LOGICAL-c4766-acef6aafc6c9c812383b6ed25300ba0da8bf34c63ce5cdeb058bcbdcd86d994b3</cites><orcidid>0000-0002-4614-9447</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306017/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306017/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,865,886,1418,11567,27929,27930,45579,45580,46057,46481,53796,53798</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28303182$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yilmaz, Hatice</creatorcontrib><creatorcontrib>Yilmaz, Osman Yalçın</creatorcontrib><creatorcontrib>Akyüz, Yaşar Feyza</creatorcontrib><title>Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model</title><title>Ecology and evolution</title><addtitle>Ecol Evol</addtitle><description>Species distribution modeling was used to determine factors among the large predictor candidate data set that affect the distribution of Muscari latifolium, an endemic bulbous plant species of Turkey, to quantify the relative importance of each factor and make a potential spatial distribution map of M. latifolium. Models were built using the Boosted Regression Trees method based on 35 presence and 70 absence records obtained through field sampling in the Gönen Dam watershed area of the Kazdağı Mountains in West Anatolia. Large candidate variables of monthly and seasonal climate, fine‐scale land surface, and geologic and biotic variables were simplified using a BRT simplifying procedure. Analyses performed on these resources, direct and indirect variables showed that there were 14 main factors that influence the species’ distribution. Five of the 14 most important variables influencing the distribution of the species are bedrock type, Quercus cerris density, precipitation during the wettest month, Pinus nigra density, and northness. These variables account for approximately 60% of the relative importance for determining the distribution of the species. Prediction performance was assessed by 10 random subsample data sets and gave a maximum the area under a receiver operating characteristic curve (AUC) value of 0.93 and an average AUC value of 0.8. This study provides a significant contribution to the knowledge of the habitat requirements and ecological characteristics of this species. The distribution of this species is explained by a combination of biotic and abiotic factors. Hence, using biotic interaction and fine‐scale land surface variables in species distribution models improved the accuracy and precision of the model. The knowledge of the relationships between distribution patterns and environmental factors and biotic interaction of M. latifolium can help develop a management and conservation strategy for this species.
Muscari latifolium is an endemic bulbous species of Turkey. Factors were determined that affect the distribution on M. latifolium. We used a large environmental variable data set and simplified them with BRTs. We used biotic interactions in the model. The information obtained in the study can be used to support management, conservation, and, if needed, restoration programs for this species.</description><subject>Abiotic factors</subject><subject>Bedrock</subject><subject>biotic factors</subject><subject>boosted regression modeling</subject><subject>bulbous plant</subject><subject>Distribution patterns</subject><subject>Endemic species</subject><subject>Environmental factors</subject><subject>Mecranium latifolium</subject><subject>Model accuracy</subject><subject>Mountains</subject><subject>Muscari</subject><subject>Original Research</subject><subject>Pine trees</subject><subject>Pinus nigra</subject><subject>Plant species</subject><subject>Quercus cerris</subject><subject>Rainfall</subject><subject>Regression analysis</subject><subject>Spatial distribution</subject><subject>Species</subject><subject>species distribution modeling</subject><subject>Watersheds</subject><subject>Wildlife conservation</subject><issn>2045-7758</issn><issn>2045-7758</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNks9uFSEUhydGY5vahS9gSNxo4m0ZmGG4G5Pmev2T1LipawKHQ0udGUZgNPclfGYZb9u0JiaygXC-fHDgV1XPa3pSU8pOEZCfsE6IR9Uho0276rpWPr63PqiOU7qmZQjKGto9rQ6Y5JTXkh1Wv95hxjj40Y-XJF8hcRpyiIlo5xDy7a71KUdv5uzDSIIjn-cEOnrS6-xd6P08vCF6JDhaHDyQqddjXriLOX7D3VKzRJNBT9NiTBOCx_TQOgSL_bPqidN9wuOb-aj6-n57sfm4Ov_y4dPm7HwFTel0pQGd0NqBgDXImnHJjUDLWk6p0dRqaRxvQHDAFiwa2koDxoKVwq7XjeFH1du9d5rNgBZwzFH3aop-0HGngvbqYWX0V-oy_FDlBEHrrghe3Qhi-D5jymrwCbAvjWOYk6plJyVjHVv_D8pk-Zd2sb78C70OcxzLSyhGeSuYFKIu1Os9BTGkFNHd3bumasmEWjKhlkwU9sX9Ru_I2wQU4HQP_PQ97v5tUtvNlv9R_gaFzcQc</recordid><startdate>201702</startdate><enddate>201702</enddate><creator>Yilmaz, Hatice</creator><creator>Yilmaz, Osman Yalçın</creator><creator>Akyüz, Yaşar Feyza</creator><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>WIN</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7SS</scope><scope>7ST</scope><scope>7X2</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>SOI</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-4614-9447</orcidid></search><sort><creationdate>201702</creationdate><title>Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model</title><author>Yilmaz, Hatice ; 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Models were built using the Boosted Regression Trees method based on 35 presence and 70 absence records obtained through field sampling in the Gönen Dam watershed area of the Kazdağı Mountains in West Anatolia. Large candidate variables of monthly and seasonal climate, fine‐scale land surface, and geologic and biotic variables were simplified using a BRT simplifying procedure. Analyses performed on these resources, direct and indirect variables showed that there were 14 main factors that influence the species’ distribution. Five of the 14 most important variables influencing the distribution of the species are bedrock type, Quercus cerris density, precipitation during the wettest month, Pinus nigra density, and northness. These variables account for approximately 60% of the relative importance for determining the distribution of the species. Prediction performance was assessed by 10 random subsample data sets and gave a maximum the area under a receiver operating characteristic curve (AUC) value of 0.93 and an average AUC value of 0.8. This study provides a significant contribution to the knowledge of the habitat requirements and ecological characteristics of this species. The distribution of this species is explained by a combination of biotic and abiotic factors. Hence, using biotic interaction and fine‐scale land surface variables in species distribution models improved the accuracy and precision of the model. The knowledge of the relationships between distribution patterns and environmental factors and biotic interaction of M. latifolium can help develop a management and conservation strategy for this species.
Muscari latifolium is an endemic bulbous species of Turkey. Factors were determined that affect the distribution on M. latifolium. We used a large environmental variable data set and simplified them with BRTs. We used biotic interactions in the model. The information obtained in the study can be used to support management, conservation, and, if needed, restoration programs for this species.</abstract><cop>England</cop><pub>John Wiley & Sons, Inc</pub><pmid>28303182</pmid><doi>10.1002/ece3.2766</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-4614-9447</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Abiotic factors Bedrock biotic factors boosted regression modeling bulbous plant Distribution patterns Endemic species Environmental factors Mecranium latifolium Model accuracy Mountains Muscari Original Research Pine trees Pinus nigra Plant species Quercus cerris Rainfall Regression analysis Spatial distribution Species species distribution modeling Watersheds Wildlife conservation |
title | Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model |
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