2021
DOI: 10.1186/s40663-021-00346-4
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Effect of thinning intensity on the stem CO2 efflux of Larix principis-rupprechtii Mayr

Abstract: Background Stem CO2 efflux (ES) plays a critical role in the carbon budget of forest ecosystems. Thinning is a core practice for sustainable management of plantations. It is therefore necessary and urgent to study the effect and mechanism of thinning intensity (TI) on ES. Methods In this study, five TIs were applied in Larix principis-rupprechtii Mayr 21-, 25-, and 41-year-old stands in North China in 2010. Portable infrared gas analyzer (Li-8100 A… Show more

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Cited by 4 publications
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“…The characteristics and health of the crown are important indicators of tree vigor, biomass accumulation, and distribution within different organs [14][15][16][17][18]. Reviewing the literature shows that crown research can be categorized into four types: (1) crown structure and visualization simulation [19][20][21][22][23]; (2) the crown and forest productivity relationship [18,[24][25][26][27][28][29]; (3) forest health evaluation [19,30]; and (4) crown and forest physiological and ecological process [31,32]. Several studies have shown that adding crown indicators into the biomass models can improve model accuracy [28,29,33,34] and increase the biological explanatory ability of the models [35].…”
Section: Introductionmentioning
confidence: 99%
“…The characteristics and health of the crown are important indicators of tree vigor, biomass accumulation, and distribution within different organs [14][15][16][17][18]. Reviewing the literature shows that crown research can be categorized into four types: (1) crown structure and visualization simulation [19][20][21][22][23]; (2) the crown and forest productivity relationship [18,[24][25][26][27][28][29]; (3) forest health evaluation [19,30]; and (4) crown and forest physiological and ecological process [31,32]. Several studies have shown that adding crown indicators into the biomass models can improve model accuracy [28,29,33,34] and increase the biological explanatory ability of the models [35].…”
Section: Introductionmentioning
confidence: 99%