{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T03:45:11Z","timestamp":1769744711221,"version":"3.49.0"},"reference-count":102,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,1,6]],"date-time":"2020-01-06T00:00:00Z","timestamp":1578268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["CRDPJ462973-14"],"award-info":[{"award-number":["CRDPJ462973-14"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2014-03822"],"award-info":[{"award-number":["RGPIN-2014-03822"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2019-04151"],"award-info":[{"award-number":["RGPIN-2019-04151"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Climate warming has led to an urgent need for improved estimates of carbon accumulation in uneven-aged, mixed temperate forests, where high uncertainty remains. We investigated the feasibility of using LiDAR-derived forest attributes to initialize a growth and yield (G&amp;Y) model in complex stands at the Petawawa Research Forest (PRF) in eastern Ontario, Canada; i.e., can G&amp;Y models based on LiDAR provide accurate predictions of aboveground carbon accumulation in complex forests compared to traditional inventory-based estimates? Applying a local G&amp;Y model, we forecasted aboveground carbon stock (tons\/ha) and accumulation (tons\/ha\/yr) using recurring plot measurements from 2012\u20132016, FVS1. We applied statistical predictors derived from LiDAR to predict stem density (SD), stem diameter distribution (SDD), and basal area distribution (BA_dist). These data, along with measured species abundance, were used to initialize a second model (FVS2). A third model was tested using LiDAR-initialized tree lists and photo-interpreted estimates of species abundance (i.e., FVS3). The carbon stock projections for 2016 from the inventory-based G&amp;Y model) were equivalent to validation carbon stocks measured in 2016 at all size-class levels (p &lt; 0.05), while LiDAR-based G&amp;Y models were not. None of the models were equivalent to validation data for accumulation (p &gt; 0.05). At the plot level, LiDAR-based predictions of carbon accumulation over a nine-year period did not differ when using either inventory or photo-interpreted species (p &lt; 0.05). Using a constant mortality rate, we also found statistical equivalency of inventory and photo-interpreted accumulation models for all size classes \u226517 cm. These results suggest that more precise information is needed on tree characteristics than we could derive from LiDAR, but that plot-level species information is not as critical for predictions of carbon accumulation in mixed-species forests. Further work is needed on the use of LiDAR to quantify stand properties before this technique can be used to replace recurring plot measurements to quantify carbon accumulation.<\/jats:p>","DOI":"10.3390\/rs12010201","type":"journal-article","created":{"date-parts":[[2020,1,6]],"date-time":"2020-01-06T10:34:46Z","timestamp":1578306886000},"page":"201","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Predicting Carbon Accumulation in Temperate Forests of Ontario, Canada Using a LiDAR-Initialized Growth-and-Yield Model"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2216-1142","authenticated-orcid":false,"given":"Paulina T.","family":"Marczak","sequence":"first","affiliation":[{"name":"Department of Geography and Planning, Queen\u2019s University, Kingston, ON K7L 3N6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karin Y.","family":"Van Ewijk","sequence":"additional","affiliation":[{"name":"Department of Geography and Planning, Queen\u2019s University, Kingston, ON K7L 3N6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul M.","family":"Treitz","sequence":"additional","affiliation":[{"name":"Department of Geography and Planning, Queen\u2019s University, Kingston, ON K7L 3N6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neal A.","family":"Scott","sequence":"additional","affiliation":[{"name":"Department of Geography and Planning, Queen\u2019s University, Kingston, ON K7L 3N6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6925-7117","authenticated-orcid":false,"given":"Donald C.E.","family":"Robinson","sequence":"additional","affiliation":[{"name":"ESSA Technologies, Vancouver, BC V6J 5C6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.geoderma.2006.09.003","article-title":"How strongly can forest management influence soil carbon sequestration?","volume":"137","author":"Jandl","year":"2007","journal-title":"Geoderma"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"405","DOI":"10.5194\/essd-10-405-2018","article-title":"Global Carbon Budget 2017","volume":"10","author":"Andrew","year":"2018","journal-title":"Earth Syst. 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