Within crown variation in the relationship between foliage biomass and sapwood area in jack pine

Water, starch, and nuclear behavior in ray parenchyma during heartwood formation of Catalpa bungei 'Jinsi'

Catalpa bungei 'Jinsi', a cultivar of C. bungei C. A. Mey., is valued for its heartwood with good overall mechanical properties, naturally durable and golden-yellow color. Little is known about heartwood formation in C. bungei 'Jinsi' trees. The behavior of starch, water, and nuclei was studied in the xylem tissue of C. bungei 'Jinsi' concerning aging in ray parenchyma cells. Blocks containing heartwood, golden zone, transition zone, and sapwood were collected from the stems of six C. bungei 'Jinsi' trees. The moisture content of the blocks was measured by oven drying. Changes in starch and nuclei in ray parenchyma were investigated in radial profiles from sapwood to heartwood blocks using microscopy and various staining techniques. The nuclear size and starch content gradually decreased to heartwood. While the horizontal distribution of moisture content of C. bungei 'Jinsi' was very varied, with the heartwood and golden zone being lower than sapwood but slightly higher than the transition zone. Starch grains were rare, but nuclei were still present in some ray parenchyma cells in the heartwood and golden zone. The nuclei showed irregular shape and elongation before disintegration. These results suggest that the most apparent change occurs in the transition zone, the critical location involved in forming C. bungei 'Jinsi' heartwood. Water and starch appear to be actively engaged in heartwood formation. The loss of function of ray parenchyma cells results from heartwood formation.

Understanding Effects of Competition and Shade Tolerance on Carbon Allocation with a Carbon Balance Model

A carbon-balance model based on mechanistic and allometric relationships (CroBas) was used to assess the effects of competition in C allocation in jack pine (Pinus banksiana Lamb.), a shade-intolerant species, and black spruce (Picea mariana (Mill.) B.S.P.), a moderately shade-tolerant species. For both species, model efficiencies ranged from 36 to 99%. The average model bias was lower than 11% and 18% for jack pine and black spruce, respectively. For both jack pine and black spruce, the total tree C increased over the years, with greater increases noted for decreasing competition. When considering a C compartment as a ratio of the total tree C, decreasing competition resulted for both species in decreasing stem C and increasing C in branches and foliage. When considering the amount of C in a given compartment, for jack pine, decreasing competition led to greater C stem, branches, foliage, and roots, whereas, for black spruce, it also increased its stem C but lately shifted at about 20 years, following thinning; thus, the changing C allocation over time results from both “passive plasticity”, reflecting environmentally induced variations in growth, and “ontogenetic plasticity”, referring to variations in the ontogenetic trajectory of a trait. Overall, the C allocation to stem and foliage relative to the total tree C generally decreased as competition decreased, supporting the optimal partitioning theory. These C-allocation patterns were related to the species’ shade tolerance and illustrated how jack pine and black spruce maximize their competitive fitness.

Trans-species predictors of tree leaf mass

Tree leaf mass is a small, highly variable, but critical, component of forest ecosystems. Estimating leaf mass on standing trees with models is challenging because leaf mass varies both within and between tree species and at different locations and points in time. Typically, models for estimating tree leaf mass are species specific, empirical models that predict intraspecific variation from stem diameter at breast height (dbh). Such models are highly limited in their application because there are many other factors beyond tree girth and species that cause leaf mass to vary and because such models provide no way to predict leaf mass for species for which data are not available. We conducted destructive sampling of 17 different species in Michigan, covering multiple life history traits and sizes, to investigate the potential for using a single, "trans-species" model for predicting leaf mass for all the trees in our study. Our results show the most important predictors of tree leaf mass are dbh, five-year basal area increment, crown class, and competition index, none of which are species specific. Species-specific variation could be captured by leaf longevity and shade tolerance. Wood specific gravity was a statistically significant, but marginally important predictor. Together, these variables describing tree size, life-history traits, and competitive environment allowed us to develop a generalized leaf mass model applicable to a diverse set of species, without having to develop species-specific equations.

The pipe model theory half a century on: a review

Background

More than a half century ago, Shinozaki et al. (Shinozaki K, Yoda K, Hozumi K, Kira T. 1964a. A quantitative analysis of plant form - the pipe model theory. I. Basic analyses. Japanese Journal of Ecology B: 97-105) proposed an elegant conceptual framework, the pipe model theory (PMT), to interpret the observed linear relationship between the amount of stem tissue and corresponding supported leaves. The PMT brought a satisfactory answer to two vividly debated problems that were unresolved at the moment of its publication: (1) What determines tree form and which rules drive biomass allocation to the foliar versus stem compartments in plants? (2) How can foliar area or mass in an individual plant, in a stand or at even larger scales be estimated? Since its initial formulation, the PMT has been reinterpreted and used in applications, and has undoubtedly become an important milestone in the mathematical interpretation of plant form and functioning.

Scope

This article aims to review the PMT by going back to its initial formulation, stating its explicit and implicit properties and discussing them in the light of current biological knowledge and experimental evidence in order to identify the validity and range of applicability of the theory. We also discuss the use of the theory in tree biomechanics and hydraulics as well as in functional-structural plant modelling.

Conclusions

Scrutinizing the PMT in the light of modern biological knowledge revealed that most of its properties are not valid as a general rule. The hydraulic framework derived from the PMT has attracted much more attention than its mechanical counterpart and implies that only the conductive portion of a stem cross-section should be proportional to the supported foliage amount rather than the whole of it. The facts that this conductive portion is experimentally difficult to measure and varies with environmental conditions and tree ontogeny might cause the commonly reported non-linear relationships between foliage and stem metrics. Nevertheless, the PMT can still be considered as a portfolio of properties providing a unified framework to integrate and analyse functional-structural relationships.

Co-optimal distribution of leaf nitrogen and hydraulic conductance in plant canopies

Leaf properties vary significantly within plant canopies, due to the strong gradient in light availability through the canopy, and the need for plants to use resources efficiently. At high light, photosynthesis is maximized when leaves have a high nitrogen content and water supply, whereas at low light leaves have a lower requirement for both nitrogen and water. Studies of the distribution of leaf nitrogen (N) within canopies have shown that, if water supply is ignored, the optimal distribution is that where N is proportional to light, but that the gradient of N in real canopies is shallower than the optimal distribution. We extend this work by considering the optimal co-allocation of nitrogen and water supply within plant canopies. We developed a simple 'toy' two-leaf canopy model and optimized the distribution of N and hydraulic conductance (K) between the two leaves. We asked whether hydraulic constraints to water supply can explain shallow N gradients in canopies. We found that the optimal N distribution within plant canopies is proportional to the light distribution only if hydraulic conductance, K, is also optimally distributed. The optimal distribution of K is that where K and N are both proportional to incident light, such that optimal K is highest to the upper canopy. If the plant is constrained in its ability to construct higher K to sun-exposed leaves, the optimal N distribution does not follow the gradient in light within canopies, but instead follows a shallower gradient. We therefore hypothesize that measured deviations from the predicted optimal distribution of N could be explained by constraints on the distribution of K within canopies. Further empirical research is required on the extent to which plants can construct optimal K distributions, and whether shallow within-canopy N distributions can be explained by sub-optimal K distributions.