{"id":4662,"date":"2021-02-19T16:11:24","date_gmt":"2021-02-19T15:11:24","guid":{"rendered":"https:\/\/ist.blogs.inrae.fr\/afs\/?p=4662"},"modified":"2021-02-19T16:11:24","modified_gmt":"2021-02-19T15:11:24","slug":"structure-area-curves-in-eastern-hardwoods-implications-for-minimum-plot-sizes-to-capture-spatially-explicit-structure-indices","status":"publish","type":"post","link":"https:\/\/ist.blogs.inrae.fr\/afs\/2021\/02\/19\/structure-area-curves-in-eastern-hardwoods-implications-for-minimum-plot-sizes-to-capture-spatially-explicit-structure-indices\/","title":{"rendered":"Structure area curves in Eastern Hardwoods: implications for minimum plot sizes to capture spatially explicit structure indices"},"content":{"rendered":"<script type='text\/javascript' src='https:\/\/d1bxh8uas1mnw7.cloudfront.net\/assets\/embed.js'><\/script><p><strong><a href=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2021\/02\/Peck-2021.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-4665 alignright\" src=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2021\/02\/Peck-2021-300x214.png\" alt=\"\" width=\"300\" height=\"214\" srcset=\"https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2021\/02\/Peck-2021-300x214.png 300w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2021\/02\/Peck-2021-768x549.png 768w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2021\/02\/Peck-2021-640x457.png 640w, https:\/\/ist.blogs.inrae.fr\/afs\/wp-content\/uploads\/sites\/5\/2021\/02\/Peck-2021.png 816w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a>Key message<\/strong><\/p>\n<p align=\"justify\">Sampling needs differ by forest type for timber inventory and structural complexity metrics. We demonstrate in a typical mixed Eastern Hardwoods forest that optimal sampling of timber inventory metrics and spatially explicit structure indices may be achieved in one large plot plus a cruise for large diameter trees, but accurately capturing inventory metrics may not be possible with sparse large-scale sampling.<\/p>\n<p><strong>Abstract<\/strong><\/p>\n<p align=\"justify\"><strong>Context<\/strong> Managing forest stand structures for multiple objectives require accurate and precise estimates of structural features that may be best estimated at different scales.<br \/>\n<strong>Aims<\/strong> We document minimum necessary plot sizes for structural metrics and spatially explicit indices to characterize structure in a mature North American Eastern hardwoods forest.<br \/>\n<strong>Methods<\/strong> Metrics and indices (Index of Aggregation, Diameter Differentiation Index, Dissimilarity Coefficient, Structural Complexity Index) were calculated within 0.05\u20131.75-ha plots for 1000 iterations of random placement in two 2.0-ha macroplots. Estimation adequacy required (1) precision (varied &lt; 10% among plots) and (2) accuracy (within 10% of the 2.0-ha value at 5th and 95th percentiles).<br \/>\n<strong>Results<\/strong> Minimum single plot sizes to achieve estimation adequacy were 0.25\u20130.75 ha for spatially explicit indices and 0.5\u20132 ha for stand metrics. A minimum of five 0.10-ha subplots would be needed for most indices and 6\u201325 for most metrics, but an untenable 375+\u2009for the density of large diameter trees.<br \/>\n<strong>Conclusion<\/strong> Estimation adequacy for structural complexity requires no greater sampling intensity than for timber metrics, except for density of large trees. A single large plot may be most cost-effective. National inventories in Eastern hardwoods may not estimate structural complexity well due to inadequate sampling intensity.<\/p>\n<p><strong>Keywords<\/strong><br \/>\nSampling; Rarity; Estimation error; Oak; Quercus; Structural complexity<\/p>\n<div class='altmetric-embed' data-badge-type='donut' data-doi='10.1007\/s13595-021-01036-5'  style='float: right; ' ><\/div>\n<p><strong>Publication<\/strong><br \/>\nPeck, J., Zenner, E. Structure area curves in Eastern Hardwoods: implications for minimum plot sizes to capture spatially explicit structure indices. Annals of Forest Science 78, 16 (2021). <a href=\"https:\/\/doi.org\/10.1007\/s13595-021-01036-5\">https:\/\/doi.org\/10.1007\/s13595-021-01036-5<\/a><\/p>\n<p><strong>For the read-only version of the full text<\/strong>:<br \/>\n<a href=\"https:\/\/rdcu.be\/cfvGm\">https:\/\/rdcu.be\/cfvGm<\/a><\/p>\n<p><strong>Data availability<\/strong><br \/>\nThe raw data are available through the Penn State Data Commons at <a href=\"https:\/\/doi.org\/10.26208\/wx8r-fb53\">https:\/\/doi.org\/10.26208\/wx8r-fb53<\/a><\/p>\n<p><strong>Handling Editor<\/strong><br \/>\nAndreas Bolte<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Key message Sampling needs differ by forest type for timber inventory and structural complexity metrics. We demonstrate in a typical mixed Eastern Hardwoods forest that optimal sampling of timber inventory metrics and spatially explicit structure indices may be achieved in one large plot plus a cruise for large diameter trees, but accurately capturing inventory metrics [&hellip;]<\/p>\n","protected":false},"author":109,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14,110,15],"tags":[],"class_list":["post-4662","post","type-post","status-publish","format-standard","hentry","category-article-type","category-data-in-repository","category-research-paper","cat-14-id","cat-110-id","cat-15-id"],"_links":{"self":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/4662","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/users\/109"}],"replies":[{"embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/comments?post=4662"}],"version-history":[{"count":0,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/posts\/4662\/revisions"}],"wp:attachment":[{"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/media?parent=4662"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/categories?post=4662"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ist.blogs.inrae.fr\/afs\/wp-json\/wp\/v2\/tags?post=4662"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}