<p>Vegetation responds to environmental change in many ways and at various time scales. For example, increasing atmospheric CO<sub>2</sub> concentrations can reduce stomatal conductance and, hence, transpiration at an hourly scale, whereas adjustments in leaf area, photosynthetic capacity and root distributions follow at the daily to seasonal scale. Evidence for root growth plasticity and adaptation to soil moisture conditions can be found in field and experimental data. However, the time scales at which roots respond to a sudden change in soil moisture are not well documented, and the dynamics of root allocation in response to soil moisture changes at daily time scales is not well understood. In addition, when looking at even longer time scales, shifts in tree density and species composition may happen over decades or centuries only. These responses give rise to feedbacks with soil water resources and atmospheric conditions, affecting the entire soil-vegetation-atmosphere system on a large range of spatio-temporal scales.</p><p>Reliable projections of long-term ecosystem response to environmental change require adequate understanding and quantitative representation of the physical processes and biological trade-offs related to vegetation-environment interactions. This includes answering the following questions:</p><p>1) What is the trade-off between canopy CO<sub>2 </sub>uptake and water loss under given atmospheric conditions?</p><p>2) How much carbon do the plants need to invest into their root system, as well as water transport and storage tissues in order to achieve a certain water and nutrient supply for the canopy?</p><p>3) How quickly can root systems respond to changing conditions?</p><p>4) What are the trade-offs between carbon investments into foliage, stems and roots and returns in terms of carbon uptake by photosynthesis?</p><p>5) Do plants adapt to the environment in an optimal way in order to maximise their net carbon profit, i.e. the carbon uptake minus carbon invested into tissues needed for its uptake?</p><p>6) And finally, can vegetation behaviour be predicted by assuming a community-scale optimal adaptation for maximum net carbon profit?</p><p>Here we present promising results related to Question 6) based on the Vegetation Optimality Model (VOM), which was recently applied and tested along a precipitation gradient in Australia. We also explain the benefits of quantitative answers to Questions 1-4 and point to targeted experiments needed to address these questions, some of which will be presented separately.</p>

<p>The goals of open science include easy reproducibility of research results, transparency of research methods and re-usability of artefacts, e.g. data, code, and graphics. Consequently, open science is expected to foster scientific collaboration and sustainability of research, as it enables building on each others' methods and results for many years and decades to come.</p><p>Here we report about our collective attempts in the last 4-10 years of taking open science to the extreme by using exclusively open formats, open-source software, sharing all stages of our work online and recording workflows and provenance of code and data. Most of our analyses are carried out in Jupyter Notebooks, which are all shared online through gitlab. In these notebooks and our python-analyses, we integrate the python package essm for transparent and easily reproducible mathematical derivations. For more complex analyses, including large model runs, we use the tool Renku of the Swiss Data Science Center in order to record workflows and provenance of code and data.</p><p>Find out where we succeeded, where we failed, what we gained and what we lost in pursuing open science to the extreme. Hear about the views and experiences with open science at the undergraduate, postgraduate, postdoc, engineer and senior researcher level. Eventually, we will also report about what we are still missing for entirely reproducible, verifiable, and reusable open science. We hope we can foster a debate about good open science practices, and how we can remove obstacles that are still in our way.</p>

<p>Plant water uptake is often a limiting factor for above-ground productivity and therefore models of soil-vegetation-atmosphere transfer strongly rely on a precise characterization of the spatial organization of root systems. However, roots display plasticity in morphology and physiology under environmental fluctuations. Plants, in fact, can adjust their root length distribution to soil moisture. The phenomenon of hydropatterning consists of preferential lateral root development in water-rich soil areas and suppression of lateral root growth in dry soil areas. The preferential root growth in wet soil areas was previously observed in large portions of root systems exposed to wet soil patches, including diverse types of roots and both pre-existing and newly grown roots. Here we refer to this phenomenon as “global hydropatterning”. However, the capacity of the root systems to adapt to fluctuating soil water availability at daily time scales, for example after a rainfall event, are less clear.</p><p>We conducted an experiment with the aim to answer the following research questions: (a) can we detect global hydropatterning in response to a water pulse in a hydraulically isolated soil layer, (b) how fast does global hydropatterning occur and (c) does the phenomenon get interrupted in the previously wetted layer and promoted in another layer when a second pulse is applied there?</p><p>We grew maize in 45 cm long cylindrical soil columns organized in four hydraulically isolated soil layers separated by vaseline barriers. After six days of water depletion by the plant, water pulses to reach 15% VWC were injected specifically into selected layers while the remaining layers remained unwatered.</p><p>For quantifying dynamic responses of the root systems to the water pulses, we measured root distribution repeatedly and non-destructively every 48 hours using a Magnetic Resonance Imaging (MRI) for four weeks. Vertical soil moisture distribution was quantified using the Soil Water Profiler (SWaP) [1].</p><p>A preliminary analysis indicates that roots grew preferentially in layers where water pulses had been applied and that allocation to root growth changed dynamically in response to water pulses. Our non-invasive measurements suggest that the global hydropatterning appears in less than 48 hours, and that plants adjust root growth to highly dynamic soil moisture conditions.</p><p>A more detailed analysis of root growth rates in response to water pulses in different soil layers will be presented and will provide insights into the response time of maize root systems to changing soil moisture conditions and in how far allocation of carbon to different portions of the root system is an absolute response to soil moisture or a relative response to soil moisture distribution.</p><p> </p><p>[1] van Dusschoten, D., Kochs, J., Kuppe, C., Sydoruk, V.A., Couvreur, V., Pflugfelder, D., Postma, J.A., 2020. Spatially resolved root water uptake determination using a precise soil water sensor. Plant Physiol. https://doi.org/10.1104/pp.20.00488</p>