30 research outputs found
Exploring the Potential to Improve the Estimation of Boreal Tree Structural Attributes with Simple Height- and Distance-Based Competition Index
In many cases, the traditional ground-based estimates of competition between trees are not directly applicable with modern aerial inventories, due to incompatible measurements. Moreover, many former studies of competition consider extreme stand densities, hence the effect of competition under the density range in managed stands remains less explored. Here we explored the utility of a simple tree height- and distance-based competition index that provides compatibility with data produced by modern inventory methods. The index was used for the prediction of structural tree attributes in three boreal tree species growing in low to moderate densities within mixed stands. In silver birch, allometric models predicting tree diameter, crown height, and branch length all showed improvement when the effect of between-tree competition was included. A similar but non-significant trend was also present in a proxy for branch biomass. In Siberian larch, only the prediction of branch length was affected. In Scots pine, there was no improvement. The results suggest that quantification of competitive interactions based on individual tree heights and locations alone has potential to improve the prediction of tree attributes, although the outcomes can be species-specific.Peer reviewe
Multi-objective optimization shapes ecological variation
Ecological systems contain a huge amount of quantitative variation between and within species and locations, which makes it difficult to obtain unambiguous verification of theoretical predictions. Ordinary experiments consider just a few explanatory factors and are prone to providing oversimplified answers because they ignore the complexity of the factors that underlie variation. We used multi-objective optimization (MO) for a mechanistic analysis of the potential ecological and evolutionary causes and consequences of variation in the life-history traits of a species of moth. Optimal life-history solutions were sought for environmental conditions where different life stages of the moth were subject to predation and other known fitness-reducing factors in a manner that was dependent on the duration of these life stages and on variable mortality rates. We found that multi-objective optimal solutions to these conditions that the moths regularly experience explained most of the life-history variation within this species. Our results demonstrate that variation can have a causal interpretation even for organisms under steady conditions. The results suggest that weather and species interactions can act as underlying causes of variation, and MO acts as a corresponding adaptive mechanism that maintains variation in the traits of organisms
How to Derive Biological Information from the Value of the Normalization Constant in Allometric Equations
Peer reviewe
Power-law estimation of branch growth
We demonstrate the efficacy of power-law models in the analysis of tree branch growth. The models can be interpreted as allometric equations, which incorporate multiple driving variables in a single scaling relationship to predict the amount of growth within a branch. We first used model selection criteria to identify the variables that most influenced (1) the length of individual elongating annual shoots and (2) the total length of all elongating annual shoots in the individual branches of silver birch (Betula pendula Roth). We then applied the two resulting power-law equations as dynamic models to predict the trajectories of crown profile development and accumulation of branch biomass during tree growth, using total branch length as a proxy for biomass. In spite of the wide size range and geographical distribution of the study trees, the models successfully reproduced the dynamic characteristics of crown development and branch biomass accumulation. Applying the model to predict long-term growth of a single branch that was initiated at the crown top generated a realistic crown profile and produced a final basal branch size that was well within the range of field observations. The models also predicted a set of more subtle and non-trivial features of crown formation, including the increased rate of growth towards the tree apex, decrease in growth towards the lowest branches, the effect of branching order on the amount of elongation, and the higher vigour of thick branches when the effect of branch height was controlled. In contrast, a simple allometric model of the form Y = aX(b) was incapable of capturing all the variability in growth of individual branches and of predicting the features of crown shape and branch size that are associated with the slowing-down of growth towards the crown base. We conclude that power-law models where the parameter a is refined to include spatial information on branch features shows good potential for identifying and incorporating actual crown construction processes in dynamic models that utilize the structural features of tree crowns.Peer reviewe
Extension of the Li\`ege Intranuclear-Cascade model to reactions induced by light nuclei
The purpose of this paper is twofold. First, we present the extension of the
Li\`ege Intranuclear Cascade model to reactions induced by light ions. Second,
we describe the C++ version of the code, which it is physics-wise equivalent to
the legacy version, is available in Geant4 and will serve as the basis for all
future development of the model. We describe the ideas upon which we built our
treatment of nucleus-nucleus reactions and we compare the model predictions
against a vast set of heterogeneous experimental data. In spite of the
discussed limitations of the intranuclear-cascade scheme, we find that our
model yields valid predictions for a number of observables and positions itself
as one of the most attractive alternatives available to Geant4 users for the
simulation of light-ion-induced reactions.Comment: Submitted to Phys. Rev.
Computational analysis of the effects of light gradients and neighbouring species on foliar nitrogen
Foliar nitrogen is one of the key traits determining the photosynthetic capacity of trees. It is influenced by many environmental factors that are often confounded with the photosynthetic photon flux density (PPFD), which alone strongly modifies the nitrogen content and other foliar traits. We combined field measurements and computational estimates of light transmittance in 3D stands with different combinations of Scots pine (Pinus sylvestris) and silver birch (Betula pendula) to decouple the effect of PPFD from other potential effects exerted by the species of neighbouring trees on the leaf nitrogen content per unit leaf area (Narea) and leaf mass per area (LMA). Independent of the level of PPFD, silver birch had a significantly lower Narea and LMA when Scots pine was abundant in its neighbourhood compared with the presence of conspecific neighbours. In Scots pine, Narea and LMA were only dependent on PPFD and the branching order of shoots. In both species, the relationships between PPFD and Narea or LMA were nonlinear, especially at intermediate levels of PPFD. The levels of PPFD did not show any dependence on the species of the neighbouring trees. The responses of silver birch suggest that the species composition of the surrounding stand can influence foliar nitrogen, independent of the level of PPFD within the canopy.Foliar nitrogen is one of the key traits determining the photosynthetic capacity of trees. It is influenced by many environmental factors that are often confounded with the photosynthetic photon flux density (PPFD), which alone strongly modifies the nitrogen content and other foliar traits. We combined field measurements and computational estimates of light transmittance in 3D stands with different combinations of Scots pine (Pinus sylvestris) and silver birch (Betula pendula) to decouple the effect of PPFD from other potential effects exerted by the species of neighbouring trees on the leaf nitrogen content per unit leaf area (Narea) and leaf mass per area (LMA). Independent of the level of PPFD, silver birch had a significantly lower Narea and LMA when Scots pine was abundant in its neighbourhood compared with the presence of conspecific neighbours. In Scots pine, Narea and LMA were only dependent on PPFD and the branching order of shoots. In both species, the relationships between PPFD and Narea or LMA were nonlinear, especially at intermediate levels of PPFD. The levels of PPFD did not show any dependence on the species of the neighbouring trees. The responses of silver birch suggest that the species composition of the surrounding stand can influence foliar nitrogen, independent of the level of PPFD within the canopy.Foliar nitrogen is one of the key traits determining the photosynthetic capacity of trees. It is influenced by many environmental factors that are often confounded with the photosynthetic photon flux density (PPFD), which alone strongly modifies the nitrogen content and other foliar traits. We combined field measurements and computational estimates of light transmittance in 3D stands with different combinations of Scots pine (Pinus sylvestris) and silver birch (Betula pendula) to decouple the effect of PPFD from other potential effects exerted by the species of neighbouring trees on the leaf nitrogen content per unit leaf area (Narea) and leaf mass per area (LMA). Independent of the level of PPFD, silver birch had a significantly lower Narea and LMA when Scots pine was abundant in its neighbourhood compared with the presence of conspecific neighbours. In Scots pine, Narea and LMA were only dependent on PPFD and the branching order of shoots. In both species, the relationships between PPFD and Narea or LMA were nonlinear, especially at intermediate levels of PPFD. The levels of PPFD did not show any dependence on the species of the neighbouring trees. The responses of silver birch suggest that the species composition of the surrounding stand can influence foliar nitrogen, independent of the level of PPFD within the canopy.Peer reviewe
A study of crown development mechanisms using a shoot-based tree model and segmented terrestrial laser scanning data
Background and Aims: Functional-structural plant models (FSPMs) allow simulation of tree crown development as the sum of modular (e.g. shoot-level) responses triggered by the local environmental conditions. The actual process of space filling by the crowns can be studied. Although the FSPM simulations are at organ scale, the data for their validation have usually been at more aggregated levels (whole-crown or whole-tree). Measurements made by terrestrial laser scanning (TLS) that have been segmented into elementary units (internodes) offer a phenotyping tool to validate the FSPM predictions at levels comparable with their detail. We demonstrate the testing of different formulations of crown development of Scots pine trees in the LIGNUM model using segmented TLS data. Methods: We made TLS measurements from four sample trees growing in a forest on a relatively poor soil from sapling size to mature stage. The TLS data were segmented into intenodes. The segmentation also produced information on whether needles were present in the internode. We applied different formulations of crown development (flushing of buds and length of growth of new internodes) in LIGNUM. We optimized the parameter values of each formulation using genetic algorithms to observe the best fit of LIGNUM simulations to the measured trees. The fitness function in the estimation combined both tree-level characteristics (e.g. tree height and crown length) and measures of crown shape (e.g. spatial distribution of needle area). Key Results: Comparison of different formulations against the data indicates that the Extended Borchert- Honda model for shoot elongation works best within LIGNUM. Control of growth by local density in the crown was important for all shoot elongation formulations. Modifying the number of lateral buds as a function of local density in the crown was the best way to accomplish density control. Conclusions: It was demonstrated how segmented TLS data can be used in the context of a shoot-based model to select model components.Peer reviewe
The effect of sample size and data range on the values of the normalization constant.
<p>The normalization constant <i>b</i> was estimated by nonlinear regression for sets of allometric data generated with the function <i>Y = 2r<sub>c</sub><sup>1.5</sup>X<sup>0.75</sup></i> , where <i>2r<sub>c</sub><sup>1.5</sup></i> = <i>b</i> and where random variation was added to both <i>Y</i> and <i>X</i>. Nonlinear regression was then used to estimate the value of <i>b</i> from the data generated either by assuming a constant exponent <i>a</i> = 0.75 (<i>b</i><sub>a = 0.75</sub>) or by allowing the value of <i>a</i> to be estimated by regression (producing <i>b</i><sub>a = estimated</sub>). For each value of <i>r<sub>c</sub></i>, the graphs show 600 instances of normalization constants estimated using data with either N = 20 or N = 120, and with a range approaching 3-fold, 10-fold or 25-fold differences in the values of <i>X</i>. Each instance is shown as a ‘+’ sign.</p