{"id":1154,"date":"2025-03-03T20:38:09","date_gmt":"2025-03-04T03:38:09","guid":{"rendered":"https:\/\/richardson-lab.nau.edu\/?p=1154"},"modified":"2025-03-03T20:54:31","modified_gmt":"2025-03-04T03:54:31","slug":"new-papers-out","status":"publish","type":"post","link":"https:\/\/richardson-lab.nau.edu\/?p=1154","title":{"rendered":"New papers out!"},"content":{"rendered":"\n

We’ve got some new papers to report:<\/p>\n\n\n\n

First, postdoc Yujie’s paper on using the XGBoost machine learning algorithm for gap filling<\/a> CO2<\/sub> flux data is now out in Agricultural and Forest Meteorology.<\/em> A highlight is that the algorithm is particularly good at filling long gaps that can’t be filled using conventional methods. Additionally, XGBoost is flexible enough to make incorporating new drivers (such as phenological information from satellites or phenocams) very easy! <\/p>\n\n\n\n

Second, the paper “Recommendations for developing, documenting, and distributing data products derived from NEON data<\/a>“, has been published in Ecosphere<\/em>. The paper emerged from the July 2023 NEON Data Products Workshop<\/a>, which was organized by Andrew and other members of the first cohort of NEON Ambassadors<\/a>. Thanks to Jeff Atkins for his leadership and seeing the manuscript through to publication, and to all the early career scientist coauthors for their contributions.<\/p>\n\n\n\n

Third, the paper “Predicting end\u2011of\u2011season timing across diverse North American grasslands<\/a>“, by former postdoc Alison Post, is now out in Oecologia<\/em>. The paper develops and evaluates a wide range of models for senescence in grassland ecosystems across the US, using PhenoCam Network data products as a primary resource. <\/p>\n\n\n\n

Fourth, collaborator Roberto Silvestro’s paper, “From Roots to Leaves: Tree Growth Phenology in Forest Ecosystems<\/a>“, is now out in Current Forestry Reports. <\/em> Andrew wrote the PhenoCam section, and former postdoc Tim Rademacher also contributed.<\/p>\n\n\n\n

Finally, collaborator Yunpeng Luo’s paper, “Internal physiological drivers of leaf development in trees: Understanding the relationship between non-\u00adstructural carbohydrates and leaf phenology<\/a>“, is now out in Functional Ecology. Yunpeng previously visited the lab for a week after the AGU fall meeting 5 or 6 y ago. <\/p>\n","protected":false},"excerpt":{"rendered":"

We’ve got some new papers to report: First, postdoc Yujie’s paper on using the XGBoost machine learning algorithm for gap filling CO2 flux data is now out in Agricultural and Forest Meteorology. A highlight is that the algorithm is particularly good at filling long gaps that can’t be filled using conventional methods. Additionally, XGBoost is … <\/p>\n

Continue reading “New papers out!”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1154","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\nNew papers out! - The Richardson Lab<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/richardson-lab.nau.edu\/?p=1154\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New papers out! - The Richardson Lab\" \/>\n<meta property=\"og:description\" content=\"We’ve got some new papers to report: First, postdoc Yujie’s paper on using the XGBoost machine learning algorithm for gap filling CO2 flux data is now out in Agricultural and Forest Meteorology. 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