Evaluating the impact of sampling schemes on leaf area index measurements from digital hemispherical photography in Larix principis-rupprechtii forest plots

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.

Segmentation and focus-point location based on boundary analysis in forest canopy hemispherical photography

Analysis of forest canopy hemisphere images is one of the most important methods for measuring forest canopy structure parameters. In this study, our main focus was on using circular image region segmentation, which is the basis of forest canopy hemispherical photography. The boundary of a forest canopy hemisphere image was analyzed via histogram, rectangle, and Fourier descriptors. The image boundary characteristics were defined and obtained based on the following：（1） an edge model that contains three parts, i.e., step, ramp, and roof;（2） boundary points of discontinuity;（3） an edge that has a linear distribution of scattering points. On this basis, we proposed a segmentation method for the circular region in a forest canopy hemisphere image, fitting the circular boundary and computing the center and radius by the least squares method. The method was unrelated to the parameters of the image acquisition device. Hence, this study lays a foundation for automatically adjusting the parameters of high-performance image acquisition devices used in forest canopy hemispherical photography.

Leaf area increases with species richness in young experimental stands of subtropical trees

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.