Root system markup language: toward an unified root architecture description language

The number of image analysis tools supporting the extraction of architectural features of root systems has increased over the last years. These tools offer a handy set of complementary facilities, yet it is widely accepted that none of these software tool is able to extract in an efficient way growing array of static and dynamic features for different types of images and species. We describe the Root System Markup Language (RSML) that has been designed to overcome two major challenges: (i) to enable portability of root architecture data between different software tools in an easy and interoperable manner allowing seamless collaborative work, and (ii) to provide a standard format upon which to base central repositories which will soon arise following the expanding worldwide root phenotyping effort. RSML follows the XML standard to store 2D or 3D image metadata, plant and root properties and geometries, continuous functions along individual root paths and a suite of annotations at the image, plant or root scales, at one or several time points. Plant ontologies are used to describe botanical entities that are relevant at the scale of root system architecture. An xml-schema describes the features and constraints of RSML and open-source packages have been developed in several languages (R, Excel, Java, Python, C#) to enable researchers to integrate RSML files into popular research workflow

Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2)

Terrestrial biosphere models (TBMs) are invaluable tools for studying plant-atmosphere interactions at multiple spatial and temporal scales, as well as how global change impacts ecosystems. Yet, TBM projections suffer from large uncertainties that limit their usefulness. Forest structure drives a significant part of TBM uncertainty as it regulates key processes such as the transfer of carbon, energy, and water between the land and the atmosphere, but it remains challenging to observe and reliably represent. The poor representation of forest structure in TBMs might actually result in simulations that reproduce observed land fluxes but fail to capture carbon pools, forest composition, and demography. Recent advances in terrestrial laser scanning (TLS) offer new opportunities to capture the three-dimensional structure of the ecosystem and to transfer this information to TBMs in order to increase their accuracy. In this study, we quantified the impacts of prescribing initial conditions (tree size distribution), constraining key model parameters with observations, as well as imposing structural observations of individual trees (namely tree height, leaf area, woody biomass, and crown area) derived from TLS on the state-of-the-art Ecosystem Demography model (ED2.2) of a temperate forest site (Wytham Woods, UK). We assessed the relative contributions of initial conditions, model structure, and parameters to the overall output uncertainty by running ensemble simulations with multiple model configurations. We show that forest demography and ecosystem functions as modelled by ED2.2 are sensitive to the imposed initial state, the model parameters, and the choice of key model processes. In particular, we show that: Parameter uncertainty drove the overall model uncertainty, with a mean contribution of 63 % to the overall variance of simulated gross primary production. Model uncertainty in the gross primary production was reduced fourfold when both TLS and trait data were integrated into the model configuration. Land fluxes and ecosystem composition could be simultaneously and accurately simulated with physically realistic parameters when appropriate constraints were applied to critical parameters and processes. We conclude that integrating TLS data can inform TBMs of the most adequate model structure, constrain critical parameters, and prescribe representative initial conditions. Our study also confirms the need for simultaneous observations of plant traits, structure, and state variables if we seek to improve the robustness of TBMs and reduce their overall uncertainties.Peer reviewe

Causes and consequences of pronounced variation in the isotope composition of plant xylem water

Stable isotopologues of water are widely used to derive relative root water uptake (RWU) profiles and average RWU depth in lignified plants. Uniform isotope composition of plant xylem water (delta(xyl)) along the stem length of woody plants is a central assumption of the isotope tracing approach which has never been properly evaluated.Here we evaluate whether strong variation in delta(xyl) within woody plants exists using empirical field observations from French Guiana, northwestern China, and Germany. In addition, supported by a mechanistic plant hydraulic model, we test hypotheses on how variation in delta(xyl) can develop through the effects of diurnal variation in RWU, sap flux density, diffusion, and various other soil and plant parameters on the delta(xyl) of woody plants.The hydrogen and oxygen isotope composition of plant xylem water shows strong temporal (i.e., sub-daily) and spatial (i.e., along the stem) variation ranging up to 25.2 parts per thousand and 6.8 parts per thousand for delta H-2 and delta O-18, respectively, greatly exceeding the measurement error range in all evaluated datasets. Model explorations predict that significant delta(xyl) variation could arise from diurnal RWU fluctuations and vertical soil water heterogeneity. Moreover, significant differences in delta(xyl) emerge between individuals that differ only in sap flux densities or are monitored at different times or heights.This work shows a complex pattern of delta(xyl) transport in the soil-root-xylem system which can be related to the dynamics of RWU by plants. These dynamics complicate the assessment of RWU when using stable water isotopologues but also open new opportunities to study drought responses to environmental drivers. We propose including the monitoring of sap flow and soil matric potential for more robust estimates of average RWU depth and expansion of attainable insights in plant drought strategies and responses

Connecting the dots between computational tools to analyse soil-root water relations

In recent years, many computational tools, such as image analysis, data management, process-based simulation, and upscaling tools, have been developed to help quantify and understand water flow in the soil-root system, at multiple scales (tissue, organ, plant, and population). Several of these tools work together or at least are compatible. However, for the uninformed researcher, they might seem disconnected, forming an unclear and disorganized succession of tools. In this article, we show how different studies can be further developed by connecting them to analyse soil-root water relations in a comprehensive and structured network. This 'explicit network of soil-root computational tools' informs readers about existing tools and helps them understand how their data (past and future) might fit within the network. We also demonstrate the novel possibilities of scale-consistent parameterizations made possible by the network with a set of case studies from the literature. Finally, we discuss existing gaps in the network and how we can move forward to fill them.status: publishe

Loïc Pagès, founding scientist in root ecology and modelling

International audienc

Development and analysis of the Soil Water Infiltration Global database

© Author(s) 2018. In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (∼76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76ĝ€% of the experimental sites with agricultural land use as the dominant type (∼40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in ∗.xlsx and ∗.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.status: publishe