Towards understanding tree root profiles: simulating hydrologically optimal strategies for root distribution

In this modelling study differences in vertical root distributions measured in four contrasting forest locations in the Netherlands were investigated. Root distributions are seen as a reflection of the plant’s optimisation strategy, based on hydrological grounds. The 'optimal' root distribution is defined as the one that maximises the water uptake from the root zone over a period of ten years. The optimal root distributions of four forest locations with completely different soil physical characteristics are calculated using the soil hydrological model SWIF. Two different model configurations for root interactions were tested: the standard model configuration in which one single root profile was used (SWIF-NC), and a model configuration in which two root profiles compete for the same available water (SWIF-C). The root profiles were parameterised with genetic algorithms. The fitness of a certain root profile was defined as the amount of water uptake over a simulation period of ten years. The root profiles of SWIF-C were optimised using an evolutionary game. The results showed clear differences in optimal root distributions between the various sites and also between the two model configurations. Optimisation with SWIF-C resulted in root profiles that were easier to interpret in terms of feasible biological strategies. Preferential water uptake in wetter soil regions was an important factor for interpretation of the simulated root distributions. As the optimised root profiles still showed differences with measured profiles, this analysis is presented, not as the final solution for explaining differences in root profiles of vegetation but as a first step using an optimisation theory to increase understanding of the root profiles of trees.</p> <p style='line-height: 20px;'><b>Keywords:</b> forest hydrology, optimisation, root

Household level modelling in CCAFS and other CRPs: Moving from ideas to action

Across different CGIAR centres there is a strong interest in applying farm household models to evaluate and target adaptation to climate change and variability. The Commonwealth Scientific and Industrial Research Organization (CSIRO), an important research partner for the CGIAR Research Program (CRP) on Climate Change, Agriculture and Food Security (CCAFS), has developed into a top institute in this research area, and has strong interest in strengthening collaboration with CCAFS and other CRPs like Integrated Systems for the Humid Tropics. In recent years CCAFS and Humid Tropics have invested a lot of time and effort in collecting farm household level characterization data and in developing coherent socio-economic scenarios of change in the near future. Given the current interest in household level analyses of adaptation and mitigation options, and the availability of data and resources within CCAFS and other CRPs the aim of the workshop was to develop a community of practice across CGIAR centres and stimulate active CGIAR – CSIRO collaboration, thereby more effectively sharing and further developing the wide range of tools and approaches available in the different institutes. The workshop, besides exchanging information about new results of on-going work and sharing of approaches and methods also produced a flexible and stepwise work plan that could be implemented under different scenarios of available funding

Towards understanding tree root profiles: simulating hydrologically optimal strategies for root distribution

International audienceIn this modelling study differences in vertical root distributions measured in four contrasting forest locations in the Netherlands were investigated. Root distributions are seen as a reflection of the plant's optimisation strategy, based on hydrological grounds. The "optimal" root distribution is defined as the one that maximises the water uptake from the root zone over a period of ten years. The optimal root distributions of four forest locations with completely different soil physical characteristics are calculated using the soil hydrological model SWIF. Two different model configurations for root interactions were tested: the standard model configuration in which one single root profile was used (SWIF-NC), and a model configuration in which two root profiles compete for the same available water (SWIF-C). The root profiles were parameterised with genetic algorithms. The fitness of a certain root profile was defined as the amount of water uptake over a simulation period of ten years. The root profiles of SWIF-C were optimised using an evolutionary game. The results showed clear differences in optimal root distributions between the various sites and also between the two model configurations. Optimisation with SWIF-C resulted in root profiles that were easier to interpret in terms of feasible biological strategies. Preferential water uptake in wetter soil regions was an important factor for interpretation of the simulated root distributions. As the optimised root profiles still showed differences with measured profiles, this analysis is presented, not as the final solution for explaining differences in root profiles of vegetation but as a first step using an optimisation theory to increase understanding of the root profiles of trees. Keywords: forest hydrology, optimisation, root

Optical instruments for measuring leaf area index in low vegetation : application in Arctic ecosystems

Author Posting. © Ecological Society of America, 2005. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 15 (2005): 1462–1470, doi:10.1890/03-5354.Leaf area index (LAI) is a powerful diagnostic of plant productivity. Despite the fact that many methods have been developed to quantify LAI, both directly and indirectly, leaf area index remains difficult to quantify accurately, owing to large spatial and temporal variability. The gap-fraction technique is widely used to estimate the LAI indirectly. However, for low-stature vegetation, the gap-fraction sensor either cannot get totally underneath the plant canopy, thereby missing part of the leaf area present, or is too close to the individual leaves of the canopy, which leads to a large distortion of the LAI estimate. We set out to develop a methodology for easy and accurate nondestructive assessment of the variability of LAI in low-stature vegetation. We developed and tested the methodology in an arctic landscape close to Abisko, Sweden. The LAI of arctic vegetation could be estimated accurately and rapidly by combining field measurements of canopy reflectance (NDVI) and light penetration through the canopy (gap-fraction analysis using a LI-COR LAI-2000). By combining the two methodologies, the limitations of each could be circumvented, and a significantly increased accuracy of the LAI estimates was obtained. The combination of an NDVI sensor for sparser vegetation and a LAI-2000 for denser vegetation could explain 81% of the variance of LAI measured by destructive harvest. We used the method to quantify the spatial variability and the associated uncertainty of leaf area index in a small catchment area.This research was funded by U.S. National Science Foundation grant DEB0087046

How can the Data Revolution contribute to climate action in smallholder agriculture?

In this article, we discuss the ongoing Data Revolution in relation to climate action in agriculture. Data are highly relevant for climate action, as climate change makes current local knowledge increasingly irrelevant and requires smarter management of agricultural systems. We discuss five datarelated concepts and explore how they are linked with agricultural climate action: lean data, crowdsourcing, big data, ubiquitous computing, and information design. We show practical examples for each of these concepts. There are many opportunities for improving agricultural development projects, providing new services to smallholder farmers, and generating better information for policy- and decision-making. Making the Data Revolution work for smallholder farmers’ climate action not only takes further technological development, but also requires careful governance and public investment to avoid a few actors taking over the current innovation space and stifle further development

Scanning for Velocity Anomalies in the Crust and Mantle with Diffractions from the Core-Mantle Boundary

A novel method, based on differential arrival times of diffractions from the core-mantle boundary, swiftly scans for seismic velocity anomalies in the crust and mantle below an array of seismometers. The method is applied to data from the USArray and the large-scale structural features in the western United States are resolved. High lateral resolution is achieved, but structure is averaged over depth. As such, this method is complementary to surface-wave and tomographic body-wave methods, where averaging takes place in the lateral sense. Processing and data-volume requirements involved are minimal. Therefore, this method can be applied during the early stages of array deployment, before the necessary data is acquired to obtain accurate inversion images. The quick scanner can be used to identify features of interest, upon which the array could be refined