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

Genotypes exhibit no variation in precision foraging in mycorrhizal Norway spruce seedlings

Aims Fine roots, that comprise the adjustable part of the root system, are important in spatially heterogeneous boreal forest soils. We investigated the soil exploring patterns of Norway spruce (Picea abies) seedlings of equal height belonging to families representing two contrasting growth phenotypes that have shown fast and slow growth rates in long-term experiments. We hypothesised that seedlings of the fast-growing phenotype would show a more explorative root growth strategy, intense branching, and root proliferation in response to the nutrient patch, and that slow-growing phenotypes would be more tolerant to drought stress. Methods Seedlings were grown in flat Perspex microcosms with a clod of humus placed in the mid-bottom part of each microcosm for eight months. The order-based and functional classification, branching topology, and size of seedling root systems were studied with WinRHIZO (TM) image-analysis software and root exploration patterns with LIGNUM-model simulations. In addition, transpiration, stomatal conductance, net assimilation rate responses were measured. Results No differences were found in the early foraging of roots for the humus clod nor net assimilation rate and transpiration between the phenotype groups. Seedlings were favouring exploitation over exploration in the early phases of development regardless of growth phenotype group. However, in fast-growing phenotypes, the main roots were longer, and the lateral root pool favoured long and bifurcated laterals that formed larger absorptive root area. Conclusions Our results indicate that in nutrient-poor conditions, better growth of lateral roots precedes future differences in the aboveground growth rate of Norway spruce.Peer reviewe

Evaluating CENTURY and Yasso soil carbon models for CO2 emissions and organic carbon stocks of boreal forest soil with Bayesian multi-model inference

We can curb climate change by improved management decisions for the most important terrestrial carbon pool, soil organic carbon stock (SOC). However, we need to be confident we can obtain the correct representation of the simultanous effect of the input of plant litter, soil temperature and water (which could be altered by climate or management) on the decomposition of soil organic matter. In this research, we used regression and Bayesian statistics for testing process-based models (Yasso07, Yasso15 and CENTURY) with soil heterotrophic respiration (Rh) and SOC, measured at four sites in Finland during 2015 and 2016. We extracted climate modifiers for calibration with Rh. The Rh values of Yasso07, Yasso15 and CENTURY models estimated with default parameterization correlated with measured monthly heterotrophic respiration. Despite a significant correlation, models on average underestimated measured soil respiration by 43%. After the Bayesian calibration, the fitted climate modifier of the Yasso07 model outperformed the Yasso15 and CENTURY models. The Yasso07 model had smaller residual mean square errors and temperature and water functions with fewer, thus more efficient, parameters than the other models. After calibration, there was a small overestimate of Rh by the models that used monotonic moisture functions and a small generic underestimate in autumn. The mismatch between measured and modelled Rh indicates that the Yasso and CENTURY models should be improved by adjusting climate modifiers of decomposition or by accounting for missing controls in, for example, microbial growth.Peer reviewe

Temporal Trends in Vertebral Size and Shape from Medieval to Modern-Day

Human lumbar vertebrae support the weight of the upper body. Loads lifted and carried by the upper extremities cause significant loading stress to the vertebral bodies. It is well established that trauma-induced vertebral fractures are common especially among elderly people. The aim of this study was to investigate the morphological factors that could have affected the prevalence of trauma-related vertebral fractures from medieval times to the present day. To determine if morphological differences existed in the size and shape of the vertebral body between medieval times and the present day, the vertebral body size and shape was measured from the 4th lumbar vertebra using magnetic resonance imaging (MRI) and standard osteometric calipers. The modern samples consisted of modern Finns and the medieval samples were from archaeological collections in Sweden and Britain. The results show that the shape and size of the 4th lumbar vertebra has changed significantly from medieval times in a way that markedly affects the biomechanical characteristics of the lumbar vertebral column. These changes may have influenced the incidence of trauma- induced spinal fractures in modern populations