Accuracy assessment and error analysis for diameter at breast height measurement of trees obtained using a novel backpack LiDAR system

Background: The LiBackpack is a recently developed backpack light detection and ranging(LiDAR) system that combines the flexibility of human walking with the nearby measurement in all directions to provide a novel and efficient approach to LiDAR remote sensing, especially useful for forest structure inventory. However, the measurement accuracy and error sources have not been systematically explored for this system.Method: In this study, we used the LiBackpack D-50 system to measure the diameter at breast height(DBH) for a Pinus sylvestris tree population in the Saihanba National Forest Park of China, and estimated the accuracy of LiBackpack measurements of DBH based on comparisons with manually measured DBH values in the field. We determined the optimal vertical slice thickness of the point cloud sample for achieving the most stable and accurate LiBackpack measurements of DBH for this tree species, and explored the effects of different factors on the measurement error.Result: 1) A vertical thickness of 30 cm for the point cloud sample slice provided the highest fitting accuracy(adjusted R2= 0.89, Root Mean Squared Error(RMSE) = 20.85 mm);2) the point cloud density had a significant negative, logarithmic relationship with measurement error of DBH and it explained 35.1% of the measurement error;3) the LiBackpack measurements of DBH were generally smaller than the manually measured values, and the corresponding measurement errors increased for larger trees;and 4) by considering the effect of the point cloud density correction, a transitional model can be fitted to approximate field measured DBH using LiBackpackscanned value with satisfactory accuracy(adjusted R2= 0.920;RMSE = 14.77 mm), and decrease the predicting error by 29.2%. Our study confirmed the reliability of the novel LiBackpack system in accurate forestry inventory, set up a useful transitional model between scanning data and the traditional manual-measured data specifically for P.sylvestris, and implied the applicable substitution of this new approach for more species, with necessary parameter calibration.

Different Patterns of Changes in the Dry Season Diameter at Breast Height of Dominant and Evergreen Tree Species in a Mature Subtropical Forest in South China

Information on changes in diameter at breast height （DBH） is important for net primary production （NPP） estimates, timing of forest inventory, and forest management. In the present study, patterns of DBH change were measured under field conditions during the dry season for three dominant and native tree species in a monsoon evergreen broad-leaved forest in the Dinghushan Biosphere Reserve. For each tree species, different patterns of DBH change were observed. In the case of the fast-growing tree species Castanopsis chinensis Hance, large diurnal fluctuations occur, with a peak DBH in the early morning （around 05：00 h） that decreases to a minimum by about 14：00 h. Both Schima superba Gardn. et Chemp and Cryptocarya chinensis （Hance） Hemsh exhibited less diurnal swelling and shrinkage. Diurnal fluctuations for these species were observed on a few occasions over the period of observation. Graphical comparisons and statistical analysis of changes in DBH with meteorological variables indicate that for different trees, the different changes in DBH observed responded to different meteorological variables. Large stem changes were found to occur for Ca. chinensis trees that were associated with variations in solar radiation. However, both S. superba and Cr. chinensis were found to be less sensitive to solar radiation. Changes in the DBH of these two species were found to be controlled mainly by soil temperature and soil moisture. During the later dry season, with a lower soil temperature and soil moisture, all three tree species stopped growing and only negligible shrinkage, expansion, or fluctuation occurred, suggesting that the optimum time to measure tree growth in the Dinghushan Biosphere Reserve is the later dry season.

Alternative expressions for stand diameter in complex forests

Quadratic mean diameter is the most frequently reported descriptor of the diameter distribution of forests.As such,it is often used as an indicator of forest stand structure,developmental stage,and ecological and economic potential.However,quadratic mean diameter can be heavily influenced by the presence or absence of large numbers of small stems in lower canopy strata,and it is also sensitive to left-truncation of the diameter distribution,making its interpretation across inventories with different protocols challenging.Here,we examine three alternative expressions of stand diameter:the arithmetic and quadratic mean diameter of the thickest 100 trees per hectare,and the basal area-weighted mean diameter.Using data from the United States Forest Inventory and Analysis program for New York and New England,these alternative expressions showed closer correlation with multiple stand structural variables than did quadratic mean diameter,including merchantable cubic and board foot volume per hectare,aboveground live tree carbon per hectare,and total number of live and dead standing trees greater than 40 cm diameter at breast height per hectare(previously proposed as an index of old-growth structure).Arithmetic and quadratic mean diameter of the thickest 100 trees per hectare showed nearly identical performance,and the strongest correlations across the board.We develop closed-form expressions for these variables when the diameter distribution is a Weibull,and illustrate their behavior relative to quadratic mean diameter for that situation.While the reasons for prevalence of quadratic mean diameter as an indicator remain valid,we suggest that these alternative measures should be more widely reported and analyzed to give a more informative depiction of stand structure and development in complex forests.

Relationship between species diversity and tree size in natural forests around the Tropic of Cancer

Although numerous hypotheses have been proposed to explain the patterns of species diversity of forests at local and landscape levels,it is still difficult to predict the alpha diversity of species,especially in tropical and subtropical natural forests where trees of different sizes and shapes are highly mixed.Size might characterize species diversity,and the possible correlation between these variables may contribute to the development of easy-to-use growth indicators to predict diversity and to understand the status of trees within a stand.In this study,diameter classes were divided using the equal diameter class(EDC)and minimum measured diameter(MMD)methods,and five species diversity indices were calculated for each diameter class of 14 permanent plots in five national nature reserves surrounding the Tropic of Cancer(23.5°),southwest China.The results show that species richness,abundance,and spatial diversity indices decreased in a typical inverted J-shape pattern with increasing diameter class and MMD,and could be easily modeled by a negative exponential function.The ShannonWiener index showed a linear decrease while Pielou’s evenness index displayed a linear increase,with a small degree of instability.The results suggest that species diversity in subtropical forests is closely related to tree size,and the relationship is possibly independent of habitat.Measuring DBH of some trees in a stand could be informative regarding species diversity and contribute to the investigation and assessment of biodiversity.

Biomass Estimation Models for Cocoa (Theobroma cacao) Plantations in Ghana, West Africa

The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Development of aboveground biomass (AGB) models for cocoa plantations is crucial for accurate estimation of carbon stocks in the cocoa systems, however, allometric models for estimating AGB for cocoa plantations remain a challenge for cocoa producing countries in Sub-Saharan Africa especially Ghana. The aim of this study is to develop allometric model that can be used for the estimation of AGB for cocoa plantations in Ghana, as well as West Africa. Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R2), index of agreement (IA), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AICC) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as;AGB = 0.7217ρ(D2)0.921. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. This study is significant because it has provided a model to estimate AGB for the cocoa plantations in Ghana which is very important for the Ghana Cocoa-Forest REDD+ Programme and also can be used by other West African cocoa producing countries.

New indices to balanceα-diversity against tree size inequality

The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large variations in tree size among species and individu-als of the same species,which result in differences in eco-logical processes and ecosystem functions.However,tree size inequality(TSI)has been largely neglected in studies using the available diversity indices.The TSI in the diameter at breast height(DBH)data for each of 99920 m×20 m forest census quadrats was quantified using the Gini index(GI),a measure of the inequality of size distribution.The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat.We also examined the relationships ofα-diversity indices with the GI using correlation tests.The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions,with most root-mean-square errors(990 out of 999 quadrats)being<0.0030.There were significant positive correlations between each of threeα-diversity indices(i.e.,R,D,and H’)and the GI.Nevertheless,the total abundance of trees in each quadrat did not significantly influence the GI.This means that the TSI increased with increasing spe-cies diversity.Thus,two new indices are proposed that can balanceα-diversity against the extent of TSI in the com-munity:(1−GI)×D,and(1−GI)×H’.These new indices were significantly correlated with the original D and H΄,and did not increase the extent of variation within each group of indices.This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities,especially in the face of cumulative species loss under global climate change.

Vitality variation and population structure of a riparian forest in the lower reaches of the Tarim River,NW China

Since 2000, the Chinese government has implemented emergency water diversion measures to restore the damaged riparian forest ecosystem with dominant tree species Euphrat poplar(Populus euphratica Oliv.)at the lower reaches of the Tarim River. In the present study, comparative analysis of variations in the vitality of P. euphratica trees were made using 2005 and 2010 data to illustrate the revitalization process of riparian forest. Poplar trees within 300 m of the riverbed were positively revitalized, while the vitality of trees farther than 300 m from the river decreased. Population structure was studied to demonstrate the development of poplar community. In the first belt, the class structure for the diameter at breast height(DBH) of P. euphratica fit a logistic model, and the 2nd, 3rd and 4th belt curve fittings were close to a Gaussian model; in other plots they were bimodal. Cluster analysis of the composition of the DBH class of poplar trees demonstrated that those within 16–36 cm DBH were the most abundant(58.49% of total) in study area, under 16 cm of DBH were second(31.36%), and trees >40 cm DBH were the least abundant(10.15%). More than 80% of the trees were young and medium-sized, which means that the poplar forest community in the vicinity of the lower Tarim River is at a stable developmental stage. The abundance of juvenile trees of P. euphratica in the first and second measuring belts was 12.13% in 2005 and increased to 25.52% in 2010, which means that the emergency water transfer had a positive impact on the generation of young P. euphratica trees in the vicinity of the river.

Heartwood, sapwood and bark content of teak trees grown in Karnataka, India

We evaluated heartwood, sapwood and bark content in teak trees. A total of 27 sample plots were laid out in teak plantations raised by State Forest Department in Kamataka covering different age groups （11-36 years）, density （516-2061 trees/ha） and sites. From these planta- tions, a total of 130 trees were felled for estimating the yield and bark content in relation to diameter at breast height （DBH）, age and density. Bark content ranged from 22.2%-54.3%. Heartwood and sapwood con- tent were analyzed by sampling five trees each from two different planta- tions, one 30 years old at 553 trees.ha-1 and the other 32 years old at 911 trees.ha-1. The highest heartwood proportion of stem wood volume （over-bark） was 56.3% and the lowest was 37.1%.

Selective harvesting at rational intervals promotes carbon sequestration in temperate coniferous and broad-leaved mixed forests in China

Evidence-based selective cutting at prescribed intervals as part of good forest management can enhance the carbon sequestration capacity of the forest.The effect of forest management on carbon sequestration has,however,not been quantified.Thus,carbon content of various organs was measured for 323 tree species,247 shrub species,and233 herb species in seven temperate coniferous and broadleaved mixed forests that were subjected to selective cutting with restoration durations of 100,55,45,36,25,14,and6 years to explore dynamic changes in carbon storage.The results showed that biomass carbon allocation in different organs followed a pattern:trunk>root>branch>leaf for all forests.With longer restoration durations,more carbon accumulated in different organs and in soils.Interestingly,when the restoration duration exceeded 50 years,carbon storage in ecosystem was larger than that in primary forests with 100-year cutting intervals,suggesting that a reasonable selective cutting interval can increase forest carbon sequestration.Mean diameter at breast height(DBH)and forest carbon storage were significantly positively correlated,and carbon storage of selectively cut forests exceeded that of primary forests when the stand mean DBH exceeded 15.66 cm.Therefore,mean DBH of forests can be an indicator for combining sustainable forest management and forest carbon sequestration.Additionally,the classic coefficients of 0.45 and 0.50 used to estimate carbon sequestration underestimated values by 2.65%and overestimated by 8.16%,respectively,in comparison with the measured carbon content from different plant organs.

Allometric relationships between primary size measures and sapwood area for six common tree species in snow-dependent ecosystems in the Southwest United States

High-elevation,snow-dependent,semiarid ecosystems across southwestern United States are expected to be vulnerable to climate change,including drought and fi re,with implications for various aspects of the water cycle.To that end,much less is known about the dynamics of transpiration,an important component of the water cycle across this region.At the individual-tree scale,transpiration is estimated by scaling mean sap fl ux density by the hydroactive sapwood area(SA).SA also remains a key factor in eff ectively scaling individual tree water-use to stand level.SA across large spatial scales is normally established by relating SA of a few trees to primary size measures,e.g.,diameter at breast height(DBH),tree height(H),or canopy diameter(CD).Considering the importance of SA in scaling transpiration,the primary objective of this study was therefore to establish six species-specifi c(aspen,maple,white fi r,ponderosa pine,Douglas fi r,Englemann spruce)allometric relationships between SA and three primary size measures(DBH,CD,or H)across two high-elevation,snow-dependent,semiarid ecosystems in New Mexico and Arizona.Based on multiple statistical criteria(coeffi cient of determination,index of agreement,Nash–Sutcliff e effi-ciency)and ease of measurement in the forest,we identifi ed DBH as the primary independent variable for estimating SA across all sites.Based on group regression analysis,we found allometric relationships to be signifi cantly(p<0.05)diff erent for the same species(ponderosa pine,Douglas-fi r)across diff erent sites.Overall,our allometric relationships provide a valuable database for estimating transpiration at diff erent spatial scales from sap fl ow data in some of our most vulnerable ecosystems.

Allometric models for estimating aboveground biomass in the tropical woodlands of Ghana, West Africa

Background: Modelling aboveground biomass(AGB) in forest and woodland ecosystems is critical for accurate estimation of carbon stocks. However, scarcity of allometric models for predicting AGB remains an issue that has not been adequately addressed in Africa. In particular, locally developed models for estimating AGB in the tropical woodlands of Ghana have received little attention. In the absence of locally developed allometric models, Ghana will continue to use Tier 1 biomass data through the application of pantropic models. Without local allometric models it is not certain how Ghana would achieve Tier 2 and 3 levels under the United Nations programme for reducing emissions from deforestation and forest degradation. The objective of this study is to develop a mixedspecies allometric model for use in estimating AGB for the tropical woodlands in Ghana. Destructive sampling was carried out on 745 trees(as part of charcoal production) for the development of allometric equations. Diameter at breast height(dbh, i.e. 1.3 m above ground level), total tree height(H) and wood density(ρ) were used as predictors for the models. Seven models were compared and the best model selected based on model efficiency,bias(%) and corrected Akaike Information Criterion. The best model was validated by comparing its results with those of the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) using equivalence test and conventional paired t-test.Results: The results revealed that the best model for estimating AGB in the tropical woodlands is AGB =0.0580ρ((dbh)2 H)0.999. The equivalence test showed that this model and the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) were equivalent within ±10% of their mean predictions(p-values <0.0001 for one-tailed t-tests for both lower and upper bounds at 5% significant level), while the paired t-test revealed that the mean(181.44 ± 18.25 kg) of the model predictions of the best model of this study was significantly(n = 745, mean diff. = 16.50 ± 2.45 kg;S.E. = 1.25 kg;p < 0.001) greater than that(164.94 ± 15.82 kg) of the pantropic model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014).Conclusion: The model developed in this study fills a critical gap in estimating AGB in tropical woodlands in Ghana and other West African countries with similar ecological conditions. Despite the equivalence with the pantropic model it remains superior to the model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014) for the estimation of AGB in local tropical woodlands. It is a relevant tool for the attainment of Tier 2 and 3 levels for REDD+. The model is recommended for use in the tropical woodlands in Ghana and other West African countries in place of the use of pantropic models.

High-throughput phenotyping of two plant-size traits of Eucalyptus species using neural networks

In forest modeling to estimate the volume of wood,artificial intelligence has been shown to be quite effi-cient,especially using artificial neural networks(ANNs).Here we tested whether diameter at breast height(DBH)and the total plant height(Ht)of eucalyptus can be pre-dicted at the stand level using spectral bands measured by an unmanned aerial vehicle(UAV)multispectral sensor and vegetation indices.To do so,using the data obtained by the UAV as input variables,we tested different configurations(number of hidden layers and number of neurons in each layer)of ANNs for predicting DBH and Ht at stand level for different Eucalyptus species.The experimental design was randomized blocks with four replicates,with 20 trees in each experimental plot.The treatments comprised five Eucalyptus species(E.camaldulensis,E.uroplylla,E.saligna,E.gran-dis,and E.urograndis)and Corymbria citriodora.DBH and Ht for each plot at the stand level were measured seven times in separate overflights by the UAV,so that the multispectral sensor could obtain spectral bands to calculate vegetation indices(VIs).ANNs were then constructed using spectral bands and VIs as input layers,in addition to the categorical variable (species), to predict DBH and Ht at the stand level simultaneously. This report represents one of the first appli-cations of high-throughput phenotyping for plant size traits in Eucalyptus species. In general, ANNs containing three hidden layers gave better statistical performance (higher esti-mated r, lower estimated root mean squared error-RMSE) due to their greater capacity for self-learning. Among these ANNs, the best contained eight neurons in the first layer, seven in the second, and five in the third (8 − 7 − 5). The results reported here reveal the potential of using the gener-ated models to perform accurate forest inventories based on spectral bands and VIs obtained with a UAV multispectral sensor and ANNs, reducing labor and time.

Estimating Stem Volume Using QuickBird Imagery and Allometric Relationships for Open Populus xiaohei Plantations

There has been a great deal of interest in studying the crown of trees using remote sensing data. In this study, crown width was extracted from high-resolution QuickBird images for open Populus xiaohei plantations. Regression models for predicting the individual stem volumes of Populus xiaohei were established using extracted crown width, as well as estimated tree parameters （i.e. diameter at breast height [DBH] and tree height） as predictors. Our results indicated that crown width could be accurately extracted from QuickBird images using a multi-scale segmentation approach with a mean relative error of 5.74%, especially for wide-spacing stands. Using either extracted crown width alone or with estimated DBH and tree height can successfully estimate individual stem volume of Populus xiaohei with the R2 value ranging from 0.87 to 0.92 depending on different model forms. In particular, the two second-order polynomial models （model 2 and model 6）, based on QuickBird image-derived crown widths and estimated DBH and tree heights, respectively, were the best at describing the relationship between stem volume and tree characteristics.

Comparing independent climate-sensitive models of aboveground biomass and diame ter grow th with their compatible simultaneous model system for three larch species in China

Accurate estimate of tree biomass is essential for forest management.In recent years,several climate-sensitive allometric biomass models with diameter at breast height(D)as a predictor have been proposed for various tree species and climate zones to estimate tree aboveground biomass(AGB).But the allometric models only account for the potential effects of climate on tree biomass and do not simultaneously explain the influence of climate on D growth.In this study,based on the AGB data from 256 destructively sampled trees of three larch species randomly distributed across the five secondary climate zones in northeastern and northern China,we first developed a climate-sensitive AGB base model and a climate-sensitive D growth base model using a nonlinear least square regression separately.A compatible simultaneous model system was then developed with the climate-sensitive AGB and D growth models using a nonlinear seemingly unrelated regression.The potential effects of several temperature and precipitation variables on AGB and D growth were evaluated.The fitting results of climatic sensitive base models were compared against those of their compatible simultaneous model system.It was found that a decreased isothermality([mean of monthly(maximum temperatureminimum temperature)]/(Maximum temperature of the warmest month-Minimum temperature of the coldest month))and total growing season precipitation,and increased annual precipitation significantly increased the values of AGB;an increase of temperature seasonality(a standard deviation of the mean monthly temperature)and precipitation seasonality(a standard deviation of the mean monthly precipitation)could lead to the increase of D.The differences of the model fitting results between the compatible simultaneous system with the consideration of climate effects on both AGB and D growth and its corresponding climate-sensitive AGB and D growth base models were very small and insignificant(p>0.05).Compared to the base models,the inhere nt correlation of AGB with D was taken into account effectively by the proposed compatible model system developed with the climate-sensitive AGB and D grow th models.In addition,the compatible properties of the estimated AGB and D were also addressed substantially in the proposed model system.

Carbon concentrations of components of trees in lO-year-old Populus davidiana stands within the Desertification Combating Program of Northern China

Most studies do not consider the potential variation in carbon concentration among the different tree components of the same species in regional scale. This study examined the carbon concentrations of the compo- nents （i.e., foliage, branch, stem, and root） in a 10-year-old poplar species （Populus davidiana Dode） from the Desertification Combating Program of Northern China. The highest and lowest carbon concentrations were found in the stem and foliage, respectively. There was a significant difference in carbon concentrations among the different tree components. All of the observed carbon concentrations of tree components were lower than those predicted using the conversion factor of 0.5 applied to component biomass. Stem carbon made up 59.7% of the total tree biomass carbon. The power equation estimating proportion of tree biomass carbon against the independent variable of diameter at breast height explained more than 90% of the variability in allocation of carbon among tree components. Tree height, as a second independent variable is also discussed. Our results suggest that the difference in organic carbon concentration among tree components should be incorporated into accurately develop forest carbon budget. Moreover, further investigations on how the diameter at breast height equation developed in the present study performs across broader scales are required.