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Background and Aims: The structure of heterogeneous forests has consequences for their biophysical environment. Variations in the local climate significantly affect tree physiological processes. We hypothesize that forest structure also alters tree root elongation and longevity through temporal and spatial variations in soil temperature and water potential., Methods: We installed rhizotrons in paired vegetation communities of closed forest (tree islands) and open patches (canopy gaps), along a soil temperature gradient (elevations of 1400, 1700 and 2000 m) in a heterogeneous mixed forest. We measured the number of growing tree roots, elongation and mortality every month over 4 years., Key Results: The results showed that the mean daily root elongation rate (RER) was not correlated with soil water potential but was significantly and positively correlated with soil temperature between 0 and 8 °C only. The RER peaked in spring, and a smaller peak was usually observed in the autumn. Root longevity was dependent on altitude and the season in which roots were initiated, and root diameter was a significant factor explaining much of the variability observed. The finest roots usually grew faster and had a higher risk of mortality in gaps than in closed forest. At 2000 m, the finest roots had a higher risk of mortality compared with the lower altitudes., Conclusions: The RER was largely driven by soil temperature and was lower in cold soils. At the treeline, ephemeral fine roots were more numerous, probably in order to compensate for the shorter growing season. Differences in soil climate and root dynamics between gaps and closed forest were marked at 1400 and 1700 m, but not at 2000 m, where canopy cover was more sparse. Therefore, heterogeneous forest structure and situation play a significant role in determining root demography in temperate, montane forests, mostly through impacts on soil temperature.

Background and Aims: Many studies exist in the literature dealing with mathematical representations of root systems, categorized, for example, as pure structure description, partial derivative equations or functional-structural plant models. However, in these studies, root architecture modelling has seldom been carried out at the organ level with the inclusion of environmental influences that can be integrated into a whole plant characterization., Methods: We have conducted a multidisciplinary study on root systems including field observations, architectural analysis, and formal and mathematical modelling. This integrative and coherent approach leads to a generic model (DigR) and its software simulator. Architecture analysis applied to root systems helps at root type classification and architectural unit design for each species. Roots belonging to a particular type share dynamic and morphological characteristics which consist of topological and geometric features. The DigR simulator is integrated into the Xplo environment, with a user interface to input parameter values and make output ready for dynamic 3-D visualization, statistical analysis and saving to standard formats. DigR is simulated in a quasi-parallel computing algorithm and may be used either as a standalone tool or integrated into other simulation platforms. The software is open-source and free to download at http://amapstudio.cirad.fr/soft/xplo/download., Key Results: DigR is based on three key points: (1) a root-system architectural analysis, (2) root type classification and modelling and (3) a restricted set of 23 root type parameters with flexible values indexed in terms of root position. Genericity and botanical accuracy of the model is demonstrated for growth, branching, mortality and reiteration processes, and for different root architectures. Plugin examples demonstrate the model's versatility at simulating plastic responses to environmental constraints. Outputs of the model include diverse root system structures such as tap-root, fasciculate, tuberous, nodulated and clustered root systems., Conclusions: DigR is based on plant architecture analysis which leads to specific root type classification and organization that are directly linked to field measurements. The open source simulator of the model has been included within a friendly user environment. DigR accuracy and versatility are demonstrated for growth simulations of complex root systems for both annual and perennial plants.

Background and Aims In Costa Rica, coffee (Coffea arabica) plants are often grown in agroforests. However, it is not known if shade-inducing trees reduce coffee plant biomass through root competition, and hence alter overall net primary productivity (NPP). We estimated biomass and NPP at the stand level, taking into account deep roots and the position of plants with regard to trees. Methods Stem growth and root biomass, turnover and decomposition were measured in mixed coffee/tree (Erythrina poeppigiana) plantations. Growth ring width and number at the stem base were estimated along with stem basal area on a range of plant sizes. Root biomass and fine root density were measured in trenches to a depth of 4 m. To take into account the below-ground heterogeneity of the agroforestry system, fine root turnover was measured by sequential soil coring (to a depth of 30 cm) over 1 year and at different locations (in full sun or under trees and in rows/inter-rows). Allometric relationships were used to calculate NPP of perennial components, which was then scaled up to the stand level. Key Results Annual ring width at the stem base increased up to 2·5 mm yr-1 with plant age (over a 44-year period). Nearly all (92 %) coffee root biomass was located in the top 1·5 m, and only 8 % from 1·5 m to a depth of 4 m. Perennial woody root biomass was 16 t ha-1 and NPP of perennial roots was 1·3 t ha-1 yr-1. Fine root biomass (0-30 cm) was two-fold higher in the row compared with between rows. Fine root biomass was 2·29 t ha-1 (12 % of total root biomass) and NPP of fine roots was 2·96 t ha-1 yr-1 (69 % of total root NPP). Fine root turnover was 1·3 yr-1 and lifespan was 0·8 years. Conclusions Coffee root systems comprised 49 % of the total plant biomass; such a high ratio is possibly a consequence of shoot pruning. There was no significant effect of trees on coffee fine root biomass, suggesting that coffee root systems are very competitive in the topsoil., (© The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background and Aims: In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m(-2)). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape., Methods: The model comprises three sub-models for predicting: (1) the spatial heterogeneity - RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum - the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile - the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition., Key Results: In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data., Conclusions: The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems., (© The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)