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Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China
Lianas are an important component of subtropical forests, but the mechanisms underlying their spatial distribution patterns have received relatively little attention. Here, we selected 12 most abundant liana species, constituting up to 96.9% of the total liana stems, in a 20‐ha plot in a subtropical...
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| Published in: | Biotropica 2022-03, Vol.54 (2), p.301-308 |
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| container_title | Biotropica |
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| creator | Bai, Xiao‐Long Liu, Qi Mohandass, Dharmalingam Cao, Min Wen, Han‐Dong Chen, Ya‐Jun Gupta, Sunil Kumar Lin, Lu‐Xiang Zhang, Jiao‐Lin |
| description | Lianas are an important component of subtropical forests, but the mechanisms underlying their spatial distribution patterns have received relatively little attention. Here, we selected 12 most abundant liana species, constituting up to 96.9% of the total liana stems, in a 20‐ha plot in a subtropical evergreen broadleaved forest at 2472–2628 m elevation in SW China. Combining data on topography (convexity, slope, aspect, and elevation) and host trees (density and size) of the plot, we addressed how liana distribution is shaped by host tree properties, topography and spatial autocorrelation by using principal coordinates of neighbor matrices (PCNM) analysis. We found that lianas had an aggregated distribution based on the Ripley's K function. At the community level, PCNM analysis showed that spatial autocorrelation explained 43% variance in liana spatial distribution. Host trees and topography explained 4% and 18% of the variance, but less than 1% variance after taking spatial autocorrelation into consideration. A similar trend was found at the species level. These results indicate that spatial autocorrelation might be the most important factor shaping liana spatial distribution in subtropical forest at high elevation.
We found that lianas had an aggregated distribution based on the Ripley's K function. Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China. |
| doi_str_mv | 10.1111/btp.13043 |
| format | article |
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We found that lianas had an aggregated distribution based on the Ripley's K function. Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China.</description><identifier>ISSN: 0006-3606</identifier><identifier>EISSN: 1744-7429</identifier><identifier>DOI: 10.1111/btp.13043</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc</publisher><subject>Autocorrelation ; climbing mechanism ; Coniferous forests ; Convexity ; dispersal limitation ; Distribution ; Distribution patterns ; Elevation ; Forests ; habitat preference ; Lianas ; Properties ; Spatial analysis ; Spatial distribution ; spatial process ; Topography ; Trees ; Tropical forests ; variation partitioning</subject><ispartof>Biotropica, 2022-03, Vol.54 (2), p.301-308</ispartof><rights>2021 The Association for Tropical Biology and Conservation</rights><rights>Copyright © 2022 Association for Tropical Biology and Conservation Inc</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3323-5e8ee31e7ce3ddeeefd7f5a3870716041f390b8dbcaa4c85dfdb49ec40b9fb0a3</citedby><cites>FETCH-LOGICAL-c3323-5e8ee31e7ce3ddeeefd7f5a3870716041f390b8dbcaa4c85dfdb49ec40b9fb0a3</cites><orcidid>0000-0002-4497-5841 ; 0000-0002-3782-8165 ; 0000-0003-3693-7965</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%2Fbtp.13043$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fbtp.13043$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,786,790,27957,27958,50923,51032</link.rule.ids></links><search><creatorcontrib>Bai, Xiao‐Long</creatorcontrib><creatorcontrib>Liu, Qi</creatorcontrib><creatorcontrib>Mohandass, Dharmalingam</creatorcontrib><creatorcontrib>Cao, Min</creatorcontrib><creatorcontrib>Wen, Han‐Dong</creatorcontrib><creatorcontrib>Chen, Ya‐Jun</creatorcontrib><creatorcontrib>Gupta, Sunil Kumar</creatorcontrib><creatorcontrib>Lin, Lu‐Xiang</creatorcontrib><creatorcontrib>Zhang, Jiao‐Lin</creatorcontrib><title>Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China</title><title>Biotropica</title><description>Lianas are an important component of subtropical forests, but the mechanisms underlying their spatial distribution patterns have received relatively little attention. Here, we selected 12 most abundant liana species, constituting up to 96.9% of the total liana stems, in a 20‐ha plot in a subtropical evergreen broadleaved forest at 2472–2628 m elevation in SW China. Combining data on topography (convexity, slope, aspect, and elevation) and host trees (density and size) of the plot, we addressed how liana distribution is shaped by host tree properties, topography and spatial autocorrelation by using principal coordinates of neighbor matrices (PCNM) analysis. We found that lianas had an aggregated distribution based on the Ripley's K function. At the community level, PCNM analysis showed that spatial autocorrelation explained 43% variance in liana spatial distribution. Host trees and topography explained 4% and 18% of the variance, but less than 1% variance after taking spatial autocorrelation into consideration. A similar trend was found at the species level. These results indicate that spatial autocorrelation might be the most important factor shaping liana spatial distribution in subtropical forest at high elevation.
We found that lianas had an aggregated distribution based on the Ripley's K function. Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China.</description><subject>Autocorrelation</subject><subject>climbing mechanism</subject><subject>Coniferous forests</subject><subject>Convexity</subject><subject>dispersal limitation</subject><subject>Distribution</subject><subject>Distribution patterns</subject><subject>Elevation</subject><subject>Forests</subject><subject>habitat preference</subject><subject>Lianas</subject><subject>Properties</subject><subject>Spatial analysis</subject><subject>Spatial distribution</subject><subject>spatial process</subject><subject>Topography</subject><subject>Trees</subject><subject>Tropical forests</subject><subject>variation partitioning</subject><issn>0006-3606</issn><issn>1744-7429</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kE1PwzAMhiMEEmNw4B9E4sShW7Jk_TjCxJeEBNKGOFZO466ZSlOSdGi_hT9L2Ljii2X78WvrJeSSswmPMVWhn3DBpDgiI55JmWRyVhyTEWMsTUTK0lNy5v0mlsWcyRH5XvYQDLQUhmAr6xy2sbYd9Q306GlroAOqjQ_OqGE_URgCOhoa6GiwvV076JsdhU7TxvpAg0OkvbM9umCihOkoUD-oEFumiqdwi24doSjlLOgWYYua1tZh3I708p0uGtPBOTmpofV48ZfH5O3-brV4TJ5fHp4WN89JJcRMJHPMEQXHrEKhNSLWOqvnIPKMZTxlkteiYCrXqgKQVT7XtVaywEoyVdSKgRiTq4NufPpziE-UGzu4Lp4sZ6lIeZYzOYvU9YGqnPXeYV32znyA25Wclb_el9H7cu99ZKcH9su0uPsfLG9Xr4eNH_X8ixI</recordid><startdate>202203</startdate><enddate>202203</enddate><creator>Bai, Xiao‐Long</creator><creator>Liu, Qi</creator><creator>Mohandass, Dharmalingam</creator><creator>Cao, Min</creator><creator>Wen, Han‐Dong</creator><creator>Chen, Ya‐Jun</creator><creator>Gupta, Sunil Kumar</creator><creator>Lin, Lu‐Xiang</creator><creator>Zhang, Jiao‐Lin</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QG</scope><scope>7QR</scope><scope>7SN</scope><scope>7SS</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H95</scope><scope>L.G</scope><scope>P64</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-4497-5841</orcidid><orcidid>https://orcid.org/0000-0002-3782-8165</orcidid><orcidid>https://orcid.org/0000-0003-3693-7965</orcidid></search><sort><creationdate>202203</creationdate><title>Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China</title><author>Bai, Xiao‐Long ; Liu, Qi ; Mohandass, Dharmalingam ; Cao, Min ; Wen, Han‐Dong ; Chen, Ya‐Jun ; Gupta, Sunil Kumar ; Lin, Lu‐Xiang ; Zhang, Jiao‐Lin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3323-5e8ee31e7ce3ddeeefd7f5a3870716041f390b8dbcaa4c85dfdb49ec40b9fb0a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Autocorrelation</topic><topic>climbing mechanism</topic><topic>Coniferous forests</topic><topic>Convexity</topic><topic>dispersal limitation</topic><topic>Distribution</topic><topic>Distribution patterns</topic><topic>Elevation</topic><topic>Forests</topic><topic>habitat preference</topic><topic>Lianas</topic><topic>Properties</topic><topic>Spatial analysis</topic><topic>Spatial distribution</topic><topic>spatial process</topic><topic>Topography</topic><topic>Trees</topic><topic>Tropical forests</topic><topic>variation partitioning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bai, Xiao‐Long</creatorcontrib><creatorcontrib>Liu, Qi</creatorcontrib><creatorcontrib>Mohandass, Dharmalingam</creatorcontrib><creatorcontrib>Cao, Min</creatorcontrib><creatorcontrib>Wen, Han‐Dong</creatorcontrib><creatorcontrib>Chen, Ya‐Jun</creatorcontrib><creatorcontrib>Gupta, Sunil Kumar</creatorcontrib><creatorcontrib>Lin, Lu‐Xiang</creatorcontrib><creatorcontrib>Zhang, Jiao‐Lin</creatorcontrib><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Biotropica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bai, Xiao‐Long</au><au>Liu, Qi</au><au>Mohandass, Dharmalingam</au><au>Cao, Min</au><au>Wen, Han‐Dong</au><au>Chen, Ya‐Jun</au><au>Gupta, Sunil Kumar</au><au>Lin, Lu‐Xiang</au><au>Zhang, Jiao‐Lin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China</atitle><jtitle>Biotropica</jtitle><date>2022-03</date><risdate>2022</risdate><volume>54</volume><issue>2</issue><spage>301</spage><epage>308</epage><pages>301-308</pages><issn>0006-3606</issn><eissn>1744-7429</eissn><notes>Funding information</notes><notes>Associate Editor: Jennifer Powers</notes><notes>Handling Editor: John Poulsen</notes><notes>Xiao‐Long Bai and Qi Liu made equal contribution to the work.</notes><notes>This study was funded by National Natural Science Foundation of China, Grant/Award Number: 31870385, 31470470; CAS 135 program, Grant/Award Number: 2017XTBG‐F01; CAS "Light of West China” program.</notes><abstract>Lianas are an important component of subtropical forests, but the mechanisms underlying their spatial distribution patterns have received relatively little attention. Here, we selected 12 most abundant liana species, constituting up to 96.9% of the total liana stems, in a 20‐ha plot in a subtropical evergreen broadleaved forest at 2472–2628 m elevation in SW China. Combining data on topography (convexity, slope, aspect, and elevation) and host trees (density and size) of the plot, we addressed how liana distribution is shaped by host tree properties, topography and spatial autocorrelation by using principal coordinates of neighbor matrices (PCNM) analysis. We found that lianas had an aggregated distribution based on the Ripley's K function. At the community level, PCNM analysis showed that spatial autocorrelation explained 43% variance in liana spatial distribution. Host trees and topography explained 4% and 18% of the variance, but less than 1% variance after taking spatial autocorrelation into consideration. A similar trend was found at the species level. These results indicate that spatial autocorrelation might be the most important factor shaping liana spatial distribution in subtropical forest at high elevation.
We found that lianas had an aggregated distribution based on the Ripley's K function. Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/btp.13043</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-4497-5841</orcidid><orcidid>https://orcid.org/0000-0002-3782-8165</orcidid><orcidid>https://orcid.org/0000-0003-3693-7965</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Biotropica, 2022-03, Vol.54 (2), p.301-308 |
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| language | eng |
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| source | Wiley |
| subjects | Autocorrelation climbing mechanism Coniferous forests Convexity dispersal limitation Distribution Distribution patterns Elevation Forests habitat preference Lianas Properties Spatial analysis Spatial distribution spatial process Topography Trees Tropical forests variation partitioning |
| title | Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China |
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