Linking ice accretion and crown structure: towards a model of the effect of freezing rain on tree canopies.

BACKGROUND AND AIMS: Despite a longstanding interest in variation in tree species vulnerability to ice storm damage, quantitative analyses of the influence of crown structure on within-crown variation in ice accretion are rare. In particular, the effect of prior interception by higher branches on lower branch accumulation remains unstudied. The aim of this study was to test the hypothesis that intra-crown ice accretion can be predicted by a measure of the degree of sheltering by neighbouring branches. METHODS: Freezing rain was artificially applied to Acer platanoides L., and in situ branch-ice thickness was measured directly and from LiDAR point clouds. Two models of freezing rain interception were developed: 'IceCube', which uses point clouds to relate ice accretion to a voxel-based index (sheltering factor; SF) of the sheltering effect of branch elements above a measurement point; and 'IceTree', a simulation model for in silico evaluation of the interception pattern of freezing rain in virtual tree crowns. KEY RESULTS: Intra-crown radial ice accretion varied strongly, declining from the tips to the bases of branches and from the top to the base of the crown. SF for branches varied strongly within the crown, and differences among branches were consistent for a range of model parameters. Intra-crown variation in ice accretion on branches was related to SF (R(2) = 0·46), with in silico results from IceTree supporting empirical relationships from IceCube. CONCLUSIONS: Empirical results and simulations confirmed a key role for crown architecture in determining intra-crown patterns of ice accretion. As suspected, the concentration of freezing rain droplets is attenuated by passage through the upper crown, and thus higher branches accumulate more ice than lower branches. This is the first step in developing a model that can provide a quantitative basis for investigating intra-crown and inter-specific variation in freezing rain damage.

Assessing the potential of low-cost 3D cameras for the rapid measurement of plant woody structure.

Detailed 3D plant architectural data have numerous applications in plant science, but many existing approaches for 3D data collection are time-consuming and/or require costly equipment. Recently, there has been rapid growth in the availability of low-cost, 3D cameras and related open source software applications. 3D cameras may provide measurements of key components of plant architecture such as stem diameters and lengths, however, few tests of 3D cameras for the measurement of plant architecture have been conducted. Here, we measured Salix branch segments ranging from 2-13 mm in diameter with an Asus Xtion camera to quantify the limits and accuracy of branch diameter measurement with a 3D camera. By scanning at a variety of distances we also quantified the effect of scanning distance. In addition, we also test the sensitivity of the program KinFu for continuous 3D object scanning and modeling as well as other similar software to accurately record stem diameters and capture plant form (<3 m in height). Given its ability to accurately capture the diameter of branches >6 mm, Asus Xtion may provide a novel method for the collection of 3D data on the branching architecture of woody plants. Improvements in camera measurement accuracy and available software are likely to further improve the utility of 3D cameras for plant sciences in the future.

Deciphering the developmental plasticity of walnut saplings in relation to climatic factors and light environment.

Developmental plasticity, the acclimation of plants to their local environment, is known to be crucial for the fitness of perennial organisms such as trees. However, deciphering the many possible developmental and environmental influences involved in such plasticity in natural conditions requires dedicated statistical models integrating developmental phases, environmental factors, and interindividual heterogeneity. These models should be able to analyse retrospective data (number of leaves or length of annual shoots along the main stem in the present case). In this study Markov switching linear mixed models were applied to the analysis of the developmental plasticity of walnut saplings during the establishment phase in a mixed Mediterranean forest. In the Markov switching linear mixed models estimated from walnut data sets, the underlying Markov chain represents both the succession and lengths of growth phases, while the linear mixed models represent both the influence of climatic factors and interindividual heterogeneity within each growth phase. On the basis of these integrative statistical models, it is shown that walnut saplings have an opportunistic mode of development that is primarily driven by the changing light environment. In particular, light availability explains the ability of a tree to reach a phase of strong growth where the first branches can appear. It is also shown that growth fluctuation amplitudes in response to climatic factors increased while interindividual heterogeneity decreased during tree development.