Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop mode...Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop models to predict longleaf pine tree diameter at breast height （dbh） and merchantable stem volume （V） using data obtained from field measurements. We used longleaf pine tree data from 3,376 planted trees on 127 permanent plots located in the U.S. Gulf Coastal Plain region to fit equations to predict dbh and V as functions of tree height （H） and crown area （CA）. Prediction of dbh as a function of H improved when CA was added as an additional independent variable. Similarly, predic- tions of V based on H improved when CA was included. Incorporation of additional stand variables such as age, site index, dominant height, and stand density were also evaluated but resulted in only small improvements in model performance. For model testing we used data from planted and naturally-regenerated trees located inside and outside the geographic area used for model fitting. Our results suggest that the models are a robust alternative for dbh and V estimations when H and CA are known on planted stands with potential for naturally-regenerated stands, across a wide range of ages. We discuss the importance of these models for use with metrics derived from remote sensing data.展开更多
目的:探究基于Kano模型下的护理干预对特发性矮小症(idiopathic short stature,ISS)患儿生长发育、骨代谢水平的影响。方法:选取于2022年1—7月九江市妇幼保健院收治的90例ISS患儿作为研究对象,并根据随机数字表法将其分为对照组与干预...目的:探究基于Kano模型下的护理干预对特发性矮小症(idiopathic short stature,ISS)患儿生长发育、骨代谢水平的影响。方法:选取于2022年1—7月九江市妇幼保健院收治的90例ISS患儿作为研究对象,并根据随机数字表法将其分为对照组与干预组,各45例。给予对照组患儿常规干预,给予干预组患儿常规干预+基于Kano模型下的护理干预。分别于干预前、干预6个月后,对比两组血清生长因子、骨代谢水平及体格发育情况。结果:干预后,两组胰岛素样生长因子结合蛋白-3(insulin-like growth factor binding protein-3,IGFBP-3)、胰岛素样生长因子Ⅰ(insulin-like growth factor-Ⅰ,IGF-Ⅰ)、25-羟维生素D_(3)水平均升高,且干预组上述指标水平均显著高于对照组(P<0.05)。干预后,两组身高、体重、骨龄(bone age,BA)及身高标准差积分(height standard deviation score,HtSDS)均升高,其中干预组身高、HtSDS均显著高于对照组(P<0.05),但两组体重、BA对比,差异均无统计学意义(P>0.05)。结论:基于Kano模型下的护理干预应用于ISS,有助于提高患儿IGFBP-3、IGF-Ⅰ及骨代谢水平,改善患儿生长发育相关指标。展开更多
基金supported by the U.S.Department of Defense,through the Strategic Environmental Research and Development Program(SERDP)
文摘Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop models to predict longleaf pine tree diameter at breast height （dbh） and merchantable stem volume （V） using data obtained from field measurements. We used longleaf pine tree data from 3,376 planted trees on 127 permanent plots located in the U.S. Gulf Coastal Plain region to fit equations to predict dbh and V as functions of tree height （H） and crown area （CA）. Prediction of dbh as a function of H improved when CA was added as an additional independent variable. Similarly, predic- tions of V based on H improved when CA was included. Incorporation of additional stand variables such as age, site index, dominant height, and stand density were also evaluated but resulted in only small improvements in model performance. For model testing we used data from planted and naturally-regenerated trees located inside and outside the geographic area used for model fitting. Our results suggest that the models are a robust alternative for dbh and V estimations when H and CA are known on planted stands with potential for naturally-regenerated stands, across a wide range of ages. We discuss the importance of these models for use with metrics derived from remote sensing data.
