Background:Digital hemispherical photography(DHP)is widely used to estimate the leaf area index(LAI)of forest plots due to its advantages of high efficiency and low cost.A crucial step in the LAI estimation of forest ...Background:Digital hemispherical photography(DHP)is widely used to estimate the leaf area index(LAI)of forest plots due to its advantages of high efficiency and low cost.A crucial step in the LAI estimation of forest plots via DHP is choosing a sampling scheme.However,various sampling schemes involving DHP have been used for the LAI estimation of forest plots.To date,the impact of sampling schemes on LAI estimation from DHP has not been comprehensively investigated.Methods:In this study,13 commonly used sampling schemes which belong to five sampling types(i.e.dispersed,square,cross,transect and circle)were adopted in the LAI estimation of five Larix principis-rupprechtii plots(25m×25 m).An additional sampling scheme(with a sample size of 89)was generated on the basis of all the sample points of the 13 sampling schemes.Three typical inversion models and four canopy element clumping index(Ωe)algorithms were involved in the LAI estimation.The impacts of the sampling schemes on four variables,including gap fraction,Ωe,effective plant area index(PAIe)and LAI estimation from DHP were analysed.The LAI estimates obtained with different sampling schemes were then compared with those obtained from litter collection measurements.Results:Large differences were observed for all four variable estimates(i.e.gap fraction,Ωe,PAIe and LAI)under different sampling schemes.The differences in impact of sampling schemes on LAI estimation were not obvious for the three inversion models,if the fourΩe algorithms,except for the traditional gap-size analysis algorithm were adopted in the estimation.The accuracy of LAI estimation was not always improved with an increase in sample size.Moreover,results indicated that with the appropriate inversion model,Ωe algorithm and sampling scheme,the maximum estimation error of DHP-estimated LAI at elementary sampling unit can be less than 20%,which is required by the global climate observing system,except in forest plots with extremely large LAI values(~>6.0).However,obtaining an LAI from DHP with an estimation error lower than 5%is impossible regardless of which combination of inversion model,Ωe algorithm and sampling scheme is used.Conclusion:The LAI estimation of L.principis-rupprechtii forests from DHP was largely affected by the sampling schemes adopted in the estimation.Thus,the sampling scheme should be seriously considered in the LAI estimation.One square and two transect sampling schemes(with sample sizes ranging from 3 to 9)were recommended to be used to estimate the LAI of L.principis-rupprechtii forests with the smallest mean relative error(MRE).By contrast,three cross and one dispersed sampling schemes were identified to provide LAI estimates with relatively large MREs.展开更多
基于自主开发的智能手机App(LAISmart)对针阔混交林、阔叶林和农作物3种植被类型的叶面积指数(leaf area index,LAI)进行测量,并以数字半球摄影(digital hemispherical photography,DHP)的测量结果作为参考值进行对比分析.结果表明,虽然...基于自主开发的智能手机App(LAISmart)对针阔混交林、阔叶林和农作物3种植被类型的叶面积指数(leaf area index,LAI)进行测量,并以数字半球摄影(digital hemispherical photography,DHP)的测量结果作为参考值进行对比分析.结果表明,虽然LAISmart与DHP的LAI值总体上具有高度一致性(R2=0.95,RMSE=0.68),但是,LAISmart的性能受到植被叶片密集程度的影响.研究发现:LAI>3.9时,LAISmart的测量结果会明显低于DHP的测量结果;智能手机成像传感器的自动曝光模式,是引起LAISmart在测量LAI高值区域估值偏低的重要影响因素;当对LAI高值区域的LAISmart图像进行降低曝光度处理后,LAISmart和DHP的测量结果偏差得到进一步降低,且LAISmart测量结果的精度可以提高49%左右.此外,LAISmart的较窄视场角几乎不会对其测量结果产生影响,若能在调节智能手机曝光度的条件下使用LAISmart,则具有更高效率和更低成本优势的LAISmart可以成为替代DHP的有效方法.展开更多
利用光学仪器法能够快速、高效地测定森林生态系统的叶面积指数(leaf area index,LAI)。然而,评估该方法测定针阔混交林LAI季节动态准确性的研究较少。该研究基于凋落物法测定了小兴安岭地区阔叶红松(Pinus koraiensis)林LAI的季节动态...利用光学仪器法能够快速、高效地测定森林生态系统的叶面积指数(leaf area index,LAI)。然而,评估该方法测定针阔混交林LAI季节动态准确性的研究较少。该研究基于凋落物法测定了小兴安岭地区阔叶红松(Pinus koraiensis)林LAI的季节动态,其结果可代表真实的LAI。参考真实的LAI,对半球摄影法(digital hemispherical photography,DHP)和LAI-2000植物冠层分析仪测定的有效叶面积指数(effective LAI,Le)进行了评估。首先对DHP测定LAI过程中采用的不合理曝光模式(自动曝光)进行了系统校正。同时,测定了光学仪器法估测LAI的主要影响因素(包括木质比例(woody-to-total area ratio,α)、集聚指数(clumping index,E)和针簇比(needle-to-shoot area ratio,γE))的季节变化。结果表明:3种不同方法测定的LAI均表现为单峰型的季节变化,8月初达到峰值。从5月至11月,DHP测定的Le比真实的LAI低估50%–59%,平均低估55%;而LAI-2000植物冠层分析仪测定的Le比真实的LAI低估19%–35%,平均低估27%。DHP测定的Le经过自动曝光,α、E和γE校正后,精度明显提高,但仍比真实的LAI低估6%–15%,平均低估9%;相对而言,LAI-2000植物冠层分析仪测定的Le经过α、E和γE校正后,精度明显提高,各时期与真实的LAI的差异均小于9%。研究结果表明,考虑木质部和集聚效应对光学仪器法的影响后,DHP和LAI-2000植物冠层分析仪均能相对准确地测定针阔混交林LAI的季节动态,其中,DHP的测定精度高于85%,而LAI-2000植物冠层分析仪的测定精度高于91%。展开更多
Aims Most biodiversity-ecosystem functioning research has been carried out in grassland ecosystems,and little is known about whether forest ecosystems,in particular outside the temperate zone,respond similarly.Here,we...Aims Most biodiversity-ecosystem functioning research has been carried out in grassland ecosystems,and little is known about whether forest ecosystems,in particular outside the temperate zone,respond similarly.Here,we tested whether productivity,assessed as leaf area index(LAI),increases with species richness in young experimental stands of subtropical trees,whether this response is similar for early-season leaf area(which is dominated by evergreens)and seasonal leaf area increase(which is dominated by deciduous species),and whether responses saturate at high species richness.Methods We used a planted tree biodiversity experiment in south-east China to test our hypotheses.LAI was determined three times by digital hemispheric photography in 144 plots that had been planted with 400 trees each,forming communities with 1,2,4,8 or 16 tree species.Important Findings LAI increased significantly with tree species richness in the fifth year of stand establishment.Similar,but weaker,statistically non-significant trends were observed 1 year before.We did not observe leaf area overyielding and the presence of particularly productive and unproductive species explained large amounts of variation in leaf area,suggesting that selection-type effects contributed substantially to the biodiversity effects we found in this early phase of stand establishment.Effects sizes were moderate to large and comparable in magnitude to the ones reported for grassland ecosystems.Subtropical(and tropical)forests harbor substantial parts of global net primary production and are critical for the Earth’s carbon and hydrological cycle,and our results suggest that tree diversity critically supports these ecosystem services.展开更多
基金the National Science Foundation of China(Grant Nos.41871233,41371330 , 41001203).
文摘Background:Digital hemispherical photography(DHP)is widely used to estimate the leaf area index(LAI)of forest plots due to its advantages of high efficiency and low cost.A crucial step in the LAI estimation of forest plots via DHP is choosing a sampling scheme.However,various sampling schemes involving DHP have been used for the LAI estimation of forest plots.To date,the impact of sampling schemes on LAI estimation from DHP has not been comprehensively investigated.Methods:In this study,13 commonly used sampling schemes which belong to five sampling types(i.e.dispersed,square,cross,transect and circle)were adopted in the LAI estimation of five Larix principis-rupprechtii plots(25m×25 m).An additional sampling scheme(with a sample size of 89)was generated on the basis of all the sample points of the 13 sampling schemes.Three typical inversion models and four canopy element clumping index(Ωe)algorithms were involved in the LAI estimation.The impacts of the sampling schemes on four variables,including gap fraction,Ωe,effective plant area index(PAIe)and LAI estimation from DHP were analysed.The LAI estimates obtained with different sampling schemes were then compared with those obtained from litter collection measurements.Results:Large differences were observed for all four variable estimates(i.e.gap fraction,Ωe,PAIe and LAI)under different sampling schemes.The differences in impact of sampling schemes on LAI estimation were not obvious for the three inversion models,if the fourΩe algorithms,except for the traditional gap-size analysis algorithm were adopted in the estimation.The accuracy of LAI estimation was not always improved with an increase in sample size.Moreover,results indicated that with the appropriate inversion model,Ωe algorithm and sampling scheme,the maximum estimation error of DHP-estimated LAI at elementary sampling unit can be less than 20%,which is required by the global climate observing system,except in forest plots with extremely large LAI values(~>6.0).However,obtaining an LAI from DHP with an estimation error lower than 5%is impossible regardless of which combination of inversion model,Ωe algorithm and sampling scheme is used.Conclusion:The LAI estimation of L.principis-rupprechtii forests from DHP was largely affected by the sampling schemes adopted in the estimation.Thus,the sampling scheme should be seriously considered in the LAI estimation.One square and two transect sampling schemes(with sample sizes ranging from 3 to 9)were recommended to be used to estimate the LAI of L.principis-rupprechtii forests with the smallest mean relative error(MRE).By contrast,three cross and one dispersed sampling schemes were identified to provide LAI estimates with relatively large MREs.
文摘基于自主开发的智能手机App(LAISmart)对针阔混交林、阔叶林和农作物3种植被类型的叶面积指数(leaf area index,LAI)进行测量,并以数字半球摄影(digital hemispherical photography,DHP)的测量结果作为参考值进行对比分析.结果表明,虽然LAISmart与DHP的LAI值总体上具有高度一致性(R2=0.95,RMSE=0.68),但是,LAISmart的性能受到植被叶片密集程度的影响.研究发现:LAI>3.9时,LAISmart的测量结果会明显低于DHP的测量结果;智能手机成像传感器的自动曝光模式,是引起LAISmart在测量LAI高值区域估值偏低的重要影响因素;当对LAI高值区域的LAISmart图像进行降低曝光度处理后,LAISmart和DHP的测量结果偏差得到进一步降低,且LAISmart测量结果的精度可以提高49%左右.此外,LAISmart的较窄视场角几乎不会对其测量结果产生影响,若能在调节智能手机曝光度的条件下使用LAISmart,则具有更高效率和更低成本优势的LAISmart可以成为替代DHP的有效方法.
文摘利用光学仪器法能够快速、高效地测定森林生态系统的叶面积指数(leaf area index,LAI)。然而,评估该方法测定针阔混交林LAI季节动态准确性的研究较少。该研究基于凋落物法测定了小兴安岭地区阔叶红松(Pinus koraiensis)林LAI的季节动态,其结果可代表真实的LAI。参考真实的LAI,对半球摄影法(digital hemispherical photography,DHP)和LAI-2000植物冠层分析仪测定的有效叶面积指数(effective LAI,Le)进行了评估。首先对DHP测定LAI过程中采用的不合理曝光模式(自动曝光)进行了系统校正。同时,测定了光学仪器法估测LAI的主要影响因素(包括木质比例(woody-to-total area ratio,α)、集聚指数(clumping index,E)和针簇比(needle-to-shoot area ratio,γE))的季节变化。结果表明:3种不同方法测定的LAI均表现为单峰型的季节变化,8月初达到峰值。从5月至11月,DHP测定的Le比真实的LAI低估50%–59%,平均低估55%;而LAI-2000植物冠层分析仪测定的Le比真实的LAI低估19%–35%,平均低估27%。DHP测定的Le经过自动曝光,α、E和γE校正后,精度明显提高,但仍比真实的LAI低估6%–15%,平均低估9%;相对而言,LAI-2000植物冠层分析仪测定的Le经过α、E和γE校正后,精度明显提高,各时期与真实的LAI的差异均小于9%。研究结果表明,考虑木质部和集聚效应对光学仪器法的影响后,DHP和LAI-2000植物冠层分析仪均能相对准确地测定针阔混交林LAI的季节动态,其中,DHP的测定精度高于85%,而LAI-2000植物冠层分析仪的测定精度高于91%。
基金German Research Foundation grant(FOR 891)the University of Zürich.
文摘Aims Most biodiversity-ecosystem functioning research has been carried out in grassland ecosystems,and little is known about whether forest ecosystems,in particular outside the temperate zone,respond similarly.Here,we tested whether productivity,assessed as leaf area index(LAI),increases with species richness in young experimental stands of subtropical trees,whether this response is similar for early-season leaf area(which is dominated by evergreens)and seasonal leaf area increase(which is dominated by deciduous species),and whether responses saturate at high species richness.Methods We used a planted tree biodiversity experiment in south-east China to test our hypotheses.LAI was determined three times by digital hemispheric photography in 144 plots that had been planted with 400 trees each,forming communities with 1,2,4,8 or 16 tree species.Important Findings LAI increased significantly with tree species richness in the fifth year of stand establishment.Similar,but weaker,statistically non-significant trends were observed 1 year before.We did not observe leaf area overyielding and the presence of particularly productive and unproductive species explained large amounts of variation in leaf area,suggesting that selection-type effects contributed substantially to the biodiversity effects we found in this early phase of stand establishment.Effects sizes were moderate to large and comparable in magnitude to the ones reported for grassland ecosystems.Subtropical(and tropical)forests harbor substantial parts of global net primary production and are critical for the Earth’s carbon and hydrological cycle,and our results suggest that tree diversity critically supports these ecosystem services.
