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We introduce a general procedure to match a stochastic functional-structural tree model (here LIGNUM augmented with stochastic rules) with real tree structures depicted by quantitative structure models (QSMs) based on terrestrial laser scanning. The matching is done by iteratively finding the maximum correspondence between the measured tree structure and the stochastic choices of the algorithm. First, we analyze the match to synthetic data (generated by the model itself), where the target values of the parameters to be estimated are known in advance, and show that the algorithm converges properly. We then carry out the procedure on real data obtaining a realistic model. We thus conclude that the proposed stochastic structure model (SSM) approach is a viable solution for formulating realistic plant models based on data and accounting for the stochastic influences.

We apply quantitative structure modelling to produce detailed information on branch-level metrics in trees. Particularly we are interested in the branch size distribution, by which we mean the total volume of branch parts distributed over the diameter classes of the parts. We investigate the possibility of predicting tree branch size distributions for trees in similar growing conditions. The quantitative structure model enables for the first time the comparisons of structure between a large number of trees. We found that the branch size distribution is similar for trees of different height in similar growing conditions. The results suggest that tree height could be used to estimate branch size distribution in areas with similar growing conditions and topography.

Due to their long lifespan, trees and bushes develop higher order of branches in a perennial manner. In contrast to a tall tree, with a clearly defined main stem and branching order, a bush is shorter and has a less apparent main stem and branching pattern. To address the developmental basis of these two forms, we studied several naturally occurring architectural variants in silver birch (Betula pendula). Using a candidate gene approach, we identified a bushy kanttarelli variant with a loss-of-function mutation in the BpMAX1 gene required for strigolactone (SL) biosynthesis. While kanttarelli is shorter than the wild type (WT), it has the same number of primary branches, whereas the number of secondary branches is increased, contributing to its bush-like phenotype. To confirm that the identified mutation was responsible for the phenotype, we phenocopied kanttarelli in transgenic BpMAX1::RNAi birch lines. SL profiling confirmed that both kanttarelli and the transgenic lines produced very limited amounts of SL. Interestingly, the auxin (IAA) distribution along the main stem differed between WT and BpMAX1::RNAi. In the WT, the auxin concentration formed a gradient, being higher in the uppermost internodes and decreasing toward the basal part of the stem, whereas in the transgenic line, this gradient was not observed. Through modeling, we showed that the different IAA distribution patterns may result from the difference in the number of higher-order branches and plant height. Future studies will determine whether the IAA gradient itself regulates aspects of plant architecture. [ABSTRACT FROM AUTHOR]

This study presents an approach for predicting stand-level forest attributes utilizing mobile laser scanning data collected as a nonprobability sample. Firstly, recordings of stem density were made at point locations every 10th metre along a subjectively chosen mobile laser scanning track in a forest stand. Secondly, kriging was applied to predict stem density values for the centre point of all grid cells in a 5 m x 5 m lattice across the stand. Thirdly, due to nondetectability issues, a correction term was computed based on distance sampling theory. Lastly, the mean stem density at stand level was predicted as the mean of the point-level predictions multiplied with the correction factor, and the corresponding variance was estimated. Many factors contribute to the uncertainty of the stand-level prediction; in the variance estimator, we accounted for the uncertainties due to kriging prediction and due to estimating a detectability model from the laser scanning data. The results from our new approach were found to correspond fairly well to estimates obtained using field measurements from an independent set of 54 circular sample plots. The predicted number of stems in the stand based on the proposed methodology was 1366 with a 12.9% relative standard error. The corresponding estimate based on the field plots was 1677 with a 7.5% relative standard error. Key words: covariogram, detectability function, forest management, model-based inference. Cette etude presente une approche pour predire les attributs forestiers a l'echelle du peuplement en utilisant des donnees de balayage laser mobile recueillies comme un echantillon non probabiliste. Tout d'abord, la densite des tiges a ete notee de facon ponctuelle a tous les decimetres le long d'un transect de balayage laser mobile choisi de maniere subjective dans un peuplement forestier. Deuxiemement, une technique de krigeage a ete appliquee pour predire la valeur de la densite des tiges pour le point central de toutes les cellules d'une grille avec une maille de 5 m x 5 m dans le peuplement. Troisiemement, en raison de problemes de non detection, un terme de correction a ete calcule sur la base de la theorie de l'echantillonnage selon la distance. Enfin, la densite moyenne des tiges a l'echelle du peuplement a ete predite comme etant la moyenne des predictions de chaque point multipliee par le facteur de correction, puis la variance correspondante a ete estimee. De nombreux facteurs contribuent a l'incertitude de la prediction a l'echelle du peuplement; dans l'estimateur de variance, nous avons tenu compte des incertitudes liees a la prediction de krigeage et a l'estimation d'un modele de detectabilite a partir des donnees de balayage laser. Les resultats de notre nouvelle approche correspondent assez bien aux estimations obtenues en utilisant des mesures de terrain a partir d'un ensemble independant de 54 parcelles echantillons circulaires. Sur la base de la methodologie proposee, le nombre de tiges predit dans le peuplement etait de 1366 avec une erreur standard relative de 12,9 %. L'estimation correspondante sur la base des parcelles de terrain etait de 1677 avec une erreur standard relative de 7,5 %. [Traduit par la Redaction] Mots-cles: covariogramme, fonction de detectabilite, gestion des forets, inference fondee sur un modele., Introduction Traditionally, stand-level forest inventories have been based on field surveys where the surveyor allocates sample plots either subjectively or by random sampling to assess key stand characteristics such as [...]

A procedure that speeds up parametric modelling is presented. With the help of manifolds and differential geometry it is possible to use a single mesh for problems corresponding to different parameter values. Index Terms--Differential geometry, optimization, parametric modelling.