Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data:a case study in the Sierra Nevada Mountains,California

Improved monitoring and understanding of tree growth and its responses to controlling factors are important for tree growth modeling.Airborne Laser Scanning(ALS)can be used to enhance the efficiency and accuracy of large-scale forest surveys in delineating three-dimensional forest structures and under-canopy terrains.This study proposed an ALSbased framework to quantify tree growth and competition.Bi-temporal ALS data were used to quantify tree growth in height(ΔH),crown area(ΔA),crown volume(ΔV),and tree competition for 114,000 individual trees in two conifer-dominant Sierra Nevada forests.We analyzed the correlations between tree growth attributes and controlling factors(i.e.tree sizes,competition,forest structure,and topographic parameters)at multiple levels.At the individual tree level,ΔH had no consistent correlations with controlling factors,ΔA andΔV were positively related to original tree sizes(R>0.3)and negatively related to competition indices(R<−0.3).At the forest-stand level,ΔH andΔA were highly correlated to topographic wetness index(|R|>0.7),ΔV was positively related to original tree sizes(|R|>0.8).Multivariate regression models were simulated at individual tree level forΔH,ΔA,andΔV with the R2 ranged from 0.1 to 0.43.The ALS-based tree height estimation and growth analysis results were consistent with field measurements.

Group planting of cherry (Prunus avium L.) fosters growth and tree quality is superior to conventional row planting in Germany

Wild cherry trees produce high-quality timber and provide multiple ecosystem services. However, planting and tending cherry stands in conventional rows are too costly. Therefore, low density group planting was trialled as an alternative to row planting. The mortality, growth, and quality of planted cherry trees were compared between the group and row planting. The influence of neighbourhood competition and light availability on growth and quality was studied. The group and row planting of cherry trees were established at a wind-thrown site in southwestern Germany in the year 2000. In group planting, five cherry seedlings and seven lime seedlings （Tilia cordata Mill.） were planted with a 1 x 1 m spacing. In total, 60 groups were planted per hectare with a 13 × 13 m spacing. In contrast, 3300 seedlings （2475 cherries and 825 limes） were planted per hectare in row planting with a 3 × 1 m spacing. Ten groups and plots （10 × 10 m） were randomly established in group and row planting stand, respectively. The survival rate, stability （height to diameter ratio）, diameter, and height growth were significantly higher in group planting. In the group plantings,40.5% of cherry trees had straight stems and 13.5% had a monopodial crown compared with 15% with straight stems and 2% with a monopodial crown in row planting. The proportion of dominant cherry trees in canopy was 49% in groups compared with 22% in rows. The length of branch free bole was significantly higher in cherries planted in groups than those grown in rows. Intra- and interspecific competition reduced the growth and stability of cherry trees in row planting, but not in group planting. Light availability did not cause any significant effects on growth and quality between group and row planting. This first study on cherry group planting indicates that the survival rate, growth, and tree quality were higher in groups than in rows at this early development stage. The competition by naturally born seedlings was an important reason for the difference in performance between group and row planting. This study will encourage forest practitioners to establish more cherry group planting trials on multiple sites to test the effectiveness of this alternative technique as a tool of regeneration and restoration silviculture.

Estimating tree and stand sapwood area in spatially heterogeneous southeastern Australian forests

Aims Natural and anthropogenic changes in forests can have important influences on transpiration and water production.Understanding the effects of increasing disturbances,due for example to climate change and forest harvesting,requires detailed information on how forest density and structural attributes relate to transpiration.Mean annual transpiration of eucalypt forest communities is often strongly correlated with total cross-sectional sapwood area.Our aim was to test an efficient method for estimating sapwood area at_(1.3)m height(SA_(1.3))in a large number of trees to understand the spatial heterogeneity of tree and stand sapwood area within and between forest communities,and develop allometric relationships that predict SA_(1.3)with forest inventory data.We also apply tree competition models to determine the degree to which the relationship between SA_(1.3)and tree basal area at_(1.3)m height(BABA_(1.3))is influenced by competition.Methods We visited 25 recently harvested southeastern Australian forest sites consisting of 1379 trees and 5 Eucalyptus species to evaluate a new efficient data collection method for estimating SA_(1.3)with tree taper and stump dimensions data using mixed effects models.The locations of 784 stumps within one 5-ha site were accurately mapped using an unmanned aerial vehicle(UAV),and four distance-dependent tree competition models were applied across the site to explain within-stand variation in the ratio of SA_(1.3)to BABA_(1.3).Data from 24 additional sites,consisting of ten 15 m radial plots per site,were used to analyse within-site variation in R_(Ha)(the ratio of stand sapwood area SA_(Ha)to stand basal area BABA_(Ha)).The radial plots were merged within each site to evaluate between-site variations in R_(Ha)across the landscape.For predicting SA_(Ha)with forest inventory data,we computed the relationship between SA_(Ha)and a new index of total stem perimeter per hectare,defined as√BA_(Ha)N_(T),where N_(T)is tree stocking density.Important Findings Our 1379 measured stems represent the most comprehensive measure of sapwood area,surpassing the 757 measured stems in native eucalypt forests published in literature.The species-specific R_(Ha) varied considerably across sites and therefore extrapolating SA_(Ha)with spatially distributed BABA_(Ha)maps and a generalized R_(Ha) would introduce local uncertainty.We found that the species-specific stem perimeter index was more effective at capturing variability in SA_(Ha)across the landscape using forest composition,structure and density data(R^(2):0.72–0.77).The strong correlation between tree SA_(1.3)and BABA_(1.3)improved slightly using tree competition models(R^(2)increased from 0.86 to 0.88).Relating SA_(Ha)to routinely measured forest inventory attributes within permanent plots and Light Detection and Ranging(LiDAR)data may provide opportunities to map forest water use in time and space across large areas disturbed by wildfire and logging.