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36 results for “large scale experiments”
Nutrient amendment effects on phytoplankton, water chemistry, and cyanotoxins in the 2018 Large-Scale Mesocosm Experiment at the University of Kansas Field Station
This dataset includes water physicochemical parameters, phytoplankton community composition, and cyanobacteria metabolites collected during a 21-day nutrient amendment experiment conducted from 23 July to 13 August 2018 at the University of Kansas Biological Station, Lawrence, KS, United States (39.049674°N, 95.190777°W). The experiment was performed using 18 large-scale, closed-bottom fiberglass tanks (volume: 11,000 L; height: 1.25 m; diameter: 3 m). Three tanks served as ambient controls (CON), while the others received one of the following nutrient treatments: nitrogen only (280 µM) as either ammonium chloride (NH4) or sodium nitrate (NO3); nitrogen (280 µM) plus phosphorus (200 µM) as either ammonium chloride + dipotassium phosphate (NHP) or sodium nitrate + dipotassium phosphate (NOP); and phosphorus only (200 µM) as dipotassium phosphate (P). Each tank received an initial nutrient dose on Day 0.5, followed by weekly additions of 20% of the initial amendment to maintain treatment conditions. All data were quality controlled to correct basic errors and to remove measurements outside the manufacturer’s standard operational ranges.
Road-deposited sediment wash-off experiments on a large-scale laboratory
<p><span>This dataset includes raw and processed data from a series of large-scale laboratory tests that were conducted to assess and study the wash-off process of RDS (Road deposited sediments) considering variations in rainfall intensity, for two scenarios: 30 mm/h and 50 mm/h; and modifying RDS loads applied on BLOCK for three scenarios: 100 g/m<sup>2</sup>, 150 g/m<sup>2</sup>, 200 g/m<sup>2</sup>. First, the hydraulic was detailly characterized including rainfall intensity maps, water flows, surface water depths and surface water velocities for both rainfall intensities tested. A synthetic granulometric of RDS was homogeneously distributed on the physical model surface and then washed-off by the simulated rainfall. A total of 31 water samples were collected at the manhole discharge per each experiment. Total RDS mass that remain on the surface and inside the gully was collected by a wet vacuum after the rainfall event. A mass balance considering the initial RDS applied and the total RDS recollected in the three samples locations, was calculated. TUR (Turbidity), EC (Conductivity), TS (Total Solids), TSS (Total suspended solids), TDS (Total dissolved solids), RDS mass by flow, and RDS mass flow variables were measured for the RDS samples recollected in the Manhole discharge. The behaviour of each RDS fraction was also analysed through laser diffraction (</span>Beckman Coulter LS 13 320, Aqueous Liquids Module<span>). This work is part of a Transnational Access developed by the Universidad Distrital Francisco José de Caldas (Colombia) and Universidade da Coruña (Spain) within the scope of Co-UDlabs project. Data may be used to increase knowledge on road-deposited sediment wash-off process, allowing also for calibrating, developing, and validating new and existing urban wash-off models.</span></p>
Data from a Large-Scale Experiment to Evaluate the Effects of Trapping to Control Muskrats (Ondatra zibethicus) in The Netherlands
<p>This data set supports the publication 'A Large-Scale Experiment to Evaluate the Effects of Trapping to Control Muskrats (Ondatra zibethicus) in The Netherlands' by Daan Bos, Emiel van Loon, Erik Klop and Ron Ydenberg. (the paper was accepted for publication in Wildlife Society Bulletin in 2020)</p> <p>The Muskrat is an invasive species in Europe and in the Netherlands muskrat burrowing can compromise the integrity of dykes and hence poses a public safety threat. For that reason a control programme has been in effect since the arrival of the species in 1941. To investigate the relation between catch and effort and enhance prediction models, a large randomized controlled experiment was designed and conducted from 2013 till 2016. The publication by Bos et al. (2020) analyses the experimental results and here we present and document the experimental data. See the readme.md file for further information.</p>
WALOWA (WAve LOads on WAlls) - Large-scale Experiments in the Delta Flume on Overtopping Wave Loads on Vertical Walls
<p>Coasts of low lying countries are often comprised of a gentle foreshore and shallow waters, followed by a dike and a promenade. At the end of the promenade buildings or storm walls are constructed. This setting makes it possible for waves to overtop the dike and impact on the storm wall or building. Especially during storm season the overtopping waves induce large loads on these structures. New scenarios for climate change and sea level rise make it worthwhile to invest in research regarding overtopping wave loads.</p> <p>Within the European project 'Wave Loads on Walls' (WaLoWa) model tests in the Delta flume (The Netherlands) were conducted. It is the aim to study overtopping wave loads on storm walls and buildings. The project is coordinated by Ghent University (Belgium), in cooperation with TU Delft (The Netherlands), RWTH Aachen (Germany), University of Bari, University of L'Aquila, University of Calabria and University of Florence (Italy) and Flanders Hydraulics Research (Belgium). The project is financed by a grant by Hydralab+ in the framework of the EC Horizon 2020 program.</p> <p>A model geometry comprised of a sandy beach, a sloping dike, promenade and wall structure was built into the Delta flume. The beach alone consists of 1000m³ sand material and was an essential part of the structure, to obtain the broken wave conditions similar to reality. Waves representing a storm with a 1000 year return period and an additional water level to account for sea level rise result in the tested superstorm conditions.</p> <p>Measurements of the water surface elevation were taken close to the paddle, along the mildly sloping foreshore and at the dike toe location by resistance type wave gauges mounted to the flume side wall. The bathymetry of the sandy foreshore was measured by a mechanical profiler before and after the test. The overtopping flow properties thickness and velocity were measured by resistance type wave gauges, ultra-sonic distance sensors, paddle wheels and an electro-magnetic current meter installed along the promenade. Finally, the impact forces and pressures on the wall were measured by compression load cells and pressure sensors respectively. The data-set was complemented by a number of synoptic measurements, such as laser scan profiles, GoPro images, High-speed camera images, Digital camera images. Due to its large storage size, these data are provided on request.</p>
2018 NSF Large Scale Experiment Workshop on Volcanic Blasts
<p><em><strong>A collection of datasets which were recorded at the 2018 NSF Large Scale Experiment Multiblast workshop on volcanic hazards</strong></em>. The workshop aimed to facilitate interdisciplinary collaboration and improve field-scale testing of monitoring methods and models. The workshop had 47 participants from US-based and international institutions. <a href="https://doi.org/10.1029/2018EO109237">Read some more details in this EOS article</a> or a <a href="https://doi.org/10.31223/X55W4F">full manuscript which is currently in review</a>.</p> <p><strong>attention</strong>: This dataset is UNDER CONSTRUCTION. It is close to, but not absolutely complete. We will publish version 1.0 once the accompanying JGR manuscript has been approved for publication.</p> <p>All data is provided in several zip archives, and small files containing metadata and descriptions. Large data chunks are separated into 'pads' (1–4), which refer to the four experiments that were performed. The archives contain a folder structure, which should allow for compatible extractions, so that archives can be downloaded to a common local folder (e.g. using a script) and extracted there without running into file name conflicts.</p> <p>Several teams collaborated to come up with this dataset. Below we list the teams from which data was used and is part of the current version of the dataset. More data may be published in the future and added in a later version. The teams collaborated to varying degrees for different tasks.</p> <p><strong>Teams</strong> in <em>alphabetical</em> order:</p> <ul> <li>Baylor<br> Baylor University<br> Lead by Kenneth Befus</li> <li>BYU<br> Brigham Young University<br> Lead by Neilsen<br> Contributors: TODO</li> <li>INGV<br> Istituto Nazionale di Geofisica e Vulcanologia, Rome<br> Lead by Taddeucci<br> Contributors: Ricci</li> <li>LDEO<br> Lamont Doherty Earth Observatory, Columbia University<br> Lead by Lev, Oppenheimer</li> <li>MTU<br> Michigan Tech University<br> Lead by Waite<br> Contributors: TODO</li> <li>UB<br> University at Buffalo<br> Lead by Sonder, Valentine<br> Contributors: David Hyman, Kayley DiemKaye, Norman Yu</li> <li>UCSB<br> University of California Santa Barbara<br> Lead by Matoza<br> Contributors: Sean Maher, Richard Sanderson</li> <li>UMKC<br> University of Missouri, Kansas City<br> Lead by Graettinger<br> Contributors: Kadie Bennis</li> <li>Yamagata<br> Yamagata University<br> Lead by Kae Tsunematsu</li> </ul> <p><strong>Parts of This Dataset</strong></p> <ul> <li><em>Coordinates & Positions:</em><br> Lead by the UB team.<br> Coordinates and Locations of Blast Charges, Sensors etc.</li> <li> <p><em>Elevation Data of Craters:</em><br> Lead by the UMKC and LDEO teams (Graettinger, Lev).<br> Elevation data were created from photographs taken right after charge detonations. The 3D-data was derived in a standard photogrammetry software (Metashape™). This data was then rasterized and imported into ArcGIS™, and is provided here. Fine adjustments were made to better match reference locations of the available site coordinate system.</p> </li> <li> <p><em>Ejecta Data:</em><br> Lead by the UMKC team.<br> Spatial distribution of ejected material.<br> The <code>.csv</code> files contain the same information as the Excel sheet, but do not contain any graphs.</p> </li> <li> <p><em>Airborne Pressure Data:</em><br> Lead by the BYU team.<br> Archive files: <code>buy_pad[i].zip</code>.<br> Data is arranged in four zip-archives, one for each blast sequence ("Pad"). Each file contains time and pressure arrays and some metadata of one microphone channel. Individual sensor locations are in the <code>positions.zip</code>.</p> <ul> <li>Format: Matlab <code>.mat</code></li> <li>File name patterns after unpacking:<br> <code>data/BYU Acoustics/Data/Aligned with Infra peaks/Pad [i]/TimeSyncPad[i]Ch[k].mat</code><br> <code>[i]</code>: Pad number (1 ... 4)<br> <code>[k]</code>: Channel number.</li> </ul> </li> <li> <p><em>Seismo-Acoustic Data:</em><br> Lead by two teams, UCSB and MTU, who deployed horizontally distributed (UCSB) and vertically distributed (MTU) seismometer stations, and infrasound sensors. MTU also provided a geophone chain. Some of the UCSB sensors were combined with the rapid BYU provided microphones to record a very wide frequency spectrum in ground and atmosphere.</p> <ul> <li> <p>UCSB data structure:<br> Data archives are provided in sensor groups for all experiments (pads). Archive file names are <code>ucsb_[sensor_type]_[sensor_gid].zip</code>. <code>[sensor_type]</code> is one of <code>inf</code> or <code>seis</code>. <code>[sensor_gid]</code> is an identifier for the sensor group (may also be a single sensor) the archive contains. E.g. <code>inf_nyi1</code> contains infrasound data of sensors <code>NYI1.1</code>, <code>NYI1.2</code> and <code>NYI1.3</code>. Use the preview window above to look into the archives. The <code>position</code> archive contains the sensor locations.</p> </li> <li> <p>MTU data structure:<br> Data archives (<code>mtu_seis-infr_pad[i].zip</code>) are organized in 'pads' 1 ... 4 and contain all sensors (infrasound, seismometer, geophones).</p> </li> </ul> </li> <li> <p><em>Video Material:</em><br> No leading team here. Cameras were contributed teams by INGV, LDEO, Yamagata, UB.<br> A drone was deployed for a map-view. Six or more cameras for each pad. Read the <code>video_readme.pdf</code> for details about camera locations and types.</p> </li> </ul> <p><strong>Changes</strong></p> <ul> <li>v0.5:<br> Added the <code>drone2</code> videos from Baylor. (All video zips were updated!)</li> <li>v0.4:<br> Added analysis pack 1 (<code>multiblast_analysis-pack1.zip</code>) code that produced figures and tables of the ms in review. This code is also available on <a href="https://gitlab.com/isonder/2018_blasts">gitlab.com/isonder/2018_blasts</a>.</li> <li>v0.3:<br> Added <code>mtu_seis_infr_metadata.zip</code>. Metadata for the MTU dataset.</li> <li>v0.2:<br> Second batch of main data. >90% complete, I guess.</li> <li>v0.1:<br> First batch of main data.</li> </ul>
Ripple Complex Experiments data set at CIEM large scale wave flume within Hydralab + project.
<p>The RIPCOM experiments (RIPple COMplex experiments) are presented in order to study the ripple growth conditions on large wave flume tests under fine unimodal, coarse unimodal and mixed sands conditions. The main objectives of the experiments is to improve and understand the protocols to perform mixed sediment experiments within the ripple regime and use/improve the equipment developed at Task 9.1 of the COMPLEX Joint Research Activity within Hydralab+. The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona.</p> <p>The experimental plan is divided in three steps:</p> <p>1. Find the optimum wave conditions that ensure ripples (based on measured velocities and previous literature studies) on the study area. Test the targeted waves with unimodal fine sediment (d 50 =0.250 mm) and measure the obtained ripples under the tested conditions. From the obtained measurements, the waves to be used on the next two steps are selected in order to fix the best conditions to produce ripples within the experimental constrains.</p> <p>2. The 13 upper cm of the fine sediment is removed and replaced by the coarser sediment (d 50 =0.545 mm). Once that is done the selected waves to be tested are reproduced and the bottom bedforms are measured.</p> <p>3. Mix both sediments fine and coarser sand homogeneously in order to repeat the selected wave conditions and measure the ripples growth and evolution under mixed sediment conditions.</p> <p>Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.</p>
Large scale experiments for an alternative erosion control measure using sand-filled geosystems. Data set produced at the CIEM flume, Hydralab+
<p>Sand-filled geosystems have the potential to mimic aspects of natural and nature-based features that can enhance the resilience of coastal areas challenged by climate, with additional (structural) reinforcement.</p> <p>Knowledge gaps can be identified. For instance, (i) the sediment transport mechanisms around the geosystem; (ii) the amount of erosion in the leeside when the system is overtopped; (iii) quantitative contribution the geosystem for the wave overtopping reduction; and (iv) failure mechanisms of the geosystem under extreme conditions. Specific tests are proposed in order to fill the defined knowledge gap and answer the following research questions:</p> <ol> <li>How do nearshore coastal processes (wave transformation, sediment transport) and wave structure interactions during extreme events differ from those during more usual big storm conditions for situations with and without the geosystem?</li> <li>How do feedbacks between the hydrodynamics and morphology of natural and nature-based features affect flooding, erosion, and recovery of coastal areas when erosion is limited by the 'geosystem'?</li> <li>How to conceive a dynamic coastal protection that can easily adapt to climate change in areas experiencing coastal squeeze (i.e. dense urban environment and human infrastructure with sea encroaching land) and vulnerable to coastal erosion and flooding risks?</li> </ol> <p>The set of experiments, done at the large wave Flume (CIEM) in Barcelona, are here described in order to answer the previous questions. These experiments started on October 2018 and ended at the end of November 2018. These tests include different configurations:<br>an initial benchmark tests in order to test the wave conditions were no geosystem protection is used, a second layout with a geotube used as a geosystem protection and finally a third layout were geobags are used as a protection.</p>
Large scale experiments for an alternative erosion control measure using sand-filled geosystems. Data set produced at the CIEM flume, Hydralab+
<p>Sand-filled geosystems have the potential to mimic aspects of natural and nature-based features that can enhance the resilience of coastal areas challenged by climate, with additional (structural) reinforcement.</p> <p>Knowledge gaps can be identified. For instance, (i) the sediment transport mechanisms around the geosystem; (ii) the amount of erosion in the leeside when the system is overtopped; (iii) quantitative contribution the geosystem for the wave overtopping reduction; and (iv) failure mechanisms of the geosystem under extreme conditions. Specific tests are proposed in order to fill the defined knowledge gap and answer the following research questions:</p> <ol> <li>How do nearshore coastal processes (wave transformation, sediment transport) and wave structure interactions during extreme events differ from those during more usual big storm conditions for situations with and without the geosystem?</li> <li>How do feedbacks between the hydrodynamics and morphology of natural and nature-based features affect flooding, erosion, and recovery of coastal areas when<br> erosion is limited by the 'geosystem'?</li> <li>How to conceive a dynamic coastal protection that can easily adapt to climate change in areas experiencing coastal squeeze (i.e. dense urban environment and human infrastructure with sea encroaching land) and vulnerable to coastal erosion and flooding risks?</li> </ol> <p>The set of experiments, done at the large wave Flume (CIEM) in Barcelona, are here described in order to answer the previous questions. These experiments started on October 2018 and ended at the end of November 2018. These tests include different configurations: an initial benchmark tests in order to test the wave conditions were no geosystem protection is used, a second layout with a geotube used as a geosystem protection and finally a third layout were geobags are used as a protection.</p>
Large scale experiments to improve monopile scour protection design adapted to climate change
<p>Offshore wind farms contribute significantly to contemporary renewable energy production. By installing these offshore structures, new technical design challenges arise, such as foundation optimisation. Present LCoE (Levelized Cost of Electricity) of offshore wind turbines amounts up to 170 Euro/MWh (Crown Estate, 2015), but the ambition is to reduce this by 2020 to 90 Euro/MWh (EY, 2015). Offshore wind turbine foundation costs are 20 % of the total costs in the case of a monopile (NREL, 2014). An important part of those costs is related to the foundation's scour protection. Therefore, optimisations in the design of the scour protection are indispensable.<br>Another promising track to reduce the costs of offshore wind turbines is their lifetime extension. Recent studies (Crown Estate, 2015) show that a 5 year lifetime extension can reduce the cost per kWh by 6 %. To check the feasibility of a lifetime extension, it will be necessary to diagnose or inspect the conditions of several core parts of the turbines, notably its foundation and scour protection. Therefore, more fundamental insight into the (longer term damage) behaviour of the scour protection around the monopile is needed.<br>Beside the interest in design optimisation and lifetime extension, the influence of climate change needs to be investigated in more detail. Climate change will increase the design storm conditions and influence the scour protection stability. Therefore, research towards a risk-based design will help to evaluate the functionality of scour protection already installed and improve the design of future scour protections adapted to climate change.<br>Based on the above motivations, the main research objective is to establish a basic benchmark dataset on the stability of scour protection around monopile foundations to serve as a basis for model tests in other flumes in the future (rather than to carry out a traditional sensitivity study with a fine resolution for all governing parameters). <br>To achieve the goals, scour researchers from several institutions are set to start work on a collaborative project at HR Wallingford's Fast Flow Facility (FFF) as part of PROTEUS, an EU-funded Hydralab+ project. Hydralab+ which is funded by the EU's Horizon 2020 Research and Innovation Programme brings together facilities and researchers in experimental hydraulic and hydrodynamics.<br>The research project aims to improve the design of scour protection around offshore wind turbine monopiles, as well as future-proofing them against the impacts of climate change. <br>PROTEUS, which stands for the 'PRotection of Offshore wind Turbine monopilEs against Scouring' will facilitate the conducting of a series of large scale experiments over a seven week period in the FFF flume at HR Wallingford's UK physical modelling facilities.<br>Partners involved in PROTEUS are: Department of Civil Engineering at Ghent University, HR Wallingford (UK), the Ludwig-Franzius Institute for Hydraulic, Estuarine and Coastal Engineering at the University of Hannover, the Faculty of Engineering at the University of Porto, the Geotechnics division of the Belgian Department of Mobility and Public Works, and International Marine and Dredging Consultants (IMDC nv).</p>
Linked collectors and determiners for: Bumble bees collected in a large-scale field experiment in power line clearings, southeast Norway.
Natural history specimen data linked to collectors and determiners held within, "Bumble bees collected in a large-scale field experiment in power line clearings, southeast Norway". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/78822c79-7646-448d-aac2-35700498c147">https://bionomia.net/dataset/78822c79-7646-448d-aac2-35700498c147</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/78822c79-7646-448d-aac2-35700498c147">https://gbif.org/dataset/78822c79-7646-448d-aac2-35700498c147</a>. Formatted as a Frictionless Data package.
Data for - Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics
<p><strong>Large-scale Corynebacterium glutamicum data set with Segmentation and Tracking Annotation</strong></p> <p>We provide five time-lapse sequences with manually corrected segmentation and tracking annotations of growing <strong><em>C. glutamicum</em></strong> cultivations. The dataset contains more than 1.4 million cell observations in 29k cell tracks and 14k cell divisions. We provide videos of the annotations (videos.zip) and the dataset in <a href="http://celltrackingchallenge.net/datasets/">Cell Tracking Challenge</a> format (ctc_format.zip). In the videos, cell contours are rendered in yellow, cell links between frames are colored red and cell divisions, and their links are colored in blue.</p> <p><strong>Data Acquisition</strong></p> <p><strong><em>Corynebacterium glutamicum</em></strong> ATCC 13032 was cultivated in BHI-medium at 30°C in this study. From and overnight preculture, the main culture was inoculated the next day with a starting OD600 of 0.05 and grown at 120 rpm to a OD600 of 0.25. A chip was fabricated, according to <a href="https://doi.org/10.1039/D0LC00711K">(Täuber et al., 2020)</a>, and fixed to the microscope’s holder. The main culture cells were transferred to monolayer growth chambers (height = 720 nm) on the microfluidic chip. Flow through the microfluidic device was mediated by pressure driven pumps with a pressure of 100 mbar on the medium reservoir.</p> <p>The time-lapse phase contrast images of five monolayer growth chambers were taken every minute using an inverted microscope (Nikon Eclipse Ti2) with a 100x oil emersion objective and a DS-QI2 camera (Nikon) at 15 % relative DIA-illumination intensity and 100 ms exposure time. The spatial image resolution is 0.072 μm/px.</p>
Data for: Zebra finch song ecology: monitoring of breeding, observational transects, focal and year-round acoustic recordings, and a large-scale simultaneous playback experiment
<p class="MsoNormal">Male songbirds sing to establish territories and to attract mates. However, increasing reports of singing in non-reproductive contexts and by females show that song use is more diverse than previously considered. Therefore, alternative functions of song, such as social cohesion and synchronisation of breeding, by and large were overlooked even in such well-studied species as the zebra finch (<em>Taeniopygia guttata</em>). In these social songbirds only the males sing and pairs breed synchronously in loose colonies following aseasonal rain events in their arid habitat. As males are not territorial, and pairs form long-term monogamous bonds early in life, conventional theory predicts that zebra finches should not sing much at all; yet they do and their song is the focus of hundreds of lab-based studies. We hypothesise that zebra finch song functions to maintain social cohesion and to synchronise breeding. Here we test this idea using data from five years of field studies, including observational transects, focal and year-round audio recordings, and a large-scale playback experiment. We show that zebra finches frequently sing while in groups, that breeding status influences song output at the nest and at aggregations, that they sing year-round, and that they predominantly sing when with their partner, suggesting that song remains important after pair formation. Our playback reveals that song actively features in social aggregations as it attracts conspecifics. Together, these results demonstrate that birdsong has important functions beyond territoriality and mate choice, illustrating its importance in coordination and cohesion of social units within larger societies.</p>
Data for: Zebra finch song ecology: monitoring of breeding, observational transects, focal and year-round acoustic recordings, and a large-scale simultaneous playback experiment
Open the record for dataset details and reuse information.
Rapid adaptive evolution to drought in a subset of plant traits in a large-scale climate change experiment
<p>Rapid evolution of traits and of plasticity may enable adaptation to climate change, yet solid experimental evidence under natural conditions is scarce. Here, we imposed rainfall manipulations (+30%, control, -30%) for ten years on entire natural plant communities in two Eastern Mediterranean sites. Additional sites along a natural rainfall gradient and selection analyses in a greenhouse assessed whether potential responses were adaptive. In both sites, our annual target species <i>Biscutella didyma</i> consistently evolved earlier phenology and higher reproductive allocation under drought. Multiple arguments suggest that this response was adaptive: it aligned with theory, corresponding trait shifts along the natural rainfall gradient, and selection analyses under differential watering in the greenhouse. However, another seven candidate traits did not evolve, and there was little support for evolution of plasticity. Our results provide compelling evidence for rapid adaptive evolution under climate change. Yet, several non-evolving traits may indicate potential constraints to full adaptation.</p>
Replication package for: The real effects of monetary expansions: evidence from a large-scale historical experiment
<p>The replication materials contain a README file, STATA datasets and do-files. This replication package for Palma (2021) constructs the entire analysis from the data sources described in the published paper, using STATA. The replicator should expect the code to run for less than 10 minutes.</p> <p>Palma, N. (2021). The real effects of monetary expansions: evidence from a large-scale historical experiment. Review of Economic Studies, forthcoming</p> <p> </p>
Throughfall exclusion and fertilization effects on tropical dry forest tree plantations, a large-scale experiment
<p>Across tropical ecosystems, global environmental change is causing drier climatic conditions and increased nutrient deposition. Such changes represent large uncertainties due to unknown interactions between drought and nutrient availability in controlling ecosystem net primary productivity (NPP). Using a large-scale manipulative experiment, we studied for 4 years whether nutrient availability affects the individual and integrated responses of aboveground and belowground ecosystem processes to throughfall exclusion in 30-year-old mixed plantations of tropical dry forest tree species in Guanacaste, Costa Rica. We used a factorial design with four treatments: control, fertilization (F), drought (D), and drought + fertilization (D + F). While we found that a 13 %–15 % reduction in soil moisture only led to weak effects in the studied ecosystem processes, NPP increased as a function of F and D + F. The relative contribution of each biomass flux to NPP varied depending on the treatment, with woody biomass being more important for F and root biomass for D + F and D. Moreover, the F treatment showed modest increases in maximum canopy cover. Plant functional type (i.e., N fixation or deciduousness) and not the experimental manipulations was the main source of variation in tree growth. Belowground processes also responded to experimental treatments, as we found a decrease in nodulation for F plots and an increase in microbial carbon use efficiency 25 for F and D plots. Our results emphasize that nutrient availability, more so than modest reductions in soil moisture, limits ecosystem processes in tropical dry forests and that soil fertility interactions with other aspects of drought intensity (e.g., vapor pressure deficit) are yet to be explored.</p>
1D-1V Vlasov-Poisson Simulations of Mutual Impedance Experiments in the presence of small-scale and large-scale plasma inhomogeneities - PART 3
<p>PART 1 IS FOUND AT <strong>https://doi.org/10.5281/zenodo.8118023</strong></p> <p>PART 2 IS FOUND AT <strong> https://doi.org/10.5281/zenodo.8119090</strong></p> <p> </p> <p>=====================================================================================================<br> Author : L. Bucciantini<br> Date : 05/07/2023<br> Laboratory : CNRS-LPC2E, Orléans (France)<br> =====================================================================================================</p> <p>Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will<br> find in it.</p> <p>In case you need help with using the dataset, or if you are interested in mutual impedance experiments,<br> do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu)</p> <p>=====================================================================================================<br> Topic:<br> This dataset contains the outputs of numerical simulations performed to assess<br> the impact of plasma inhomogeneities on the diagnostic performance<br> of mutual impedance experiments.</p> <p><br> Numerical model:<br> The outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson<br> system of equations. The scheme used to solve the model is the one developed<br> by Mangeney et al. (2002), A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071).<br> The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson<br> simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind,<br> Journal of Geophysical Research (Space Physics), 115, 6106 (2010)<br> -----------------------------------------------------------------------------------------------------<br> What is inside the dataset:</p> <p>The dataset is composed of 7 different mutual impedance measurements, each corresponding to one<br> directory (see below). The measurements (i.e. directory) correspond to small-scale plasma inhomogeneities at different<br> positions with respect to the mutual impedance antennas, or to a large-scale plasma inhomogeneity.</p> <p>Each directory contains a number of folders. Each folder corresponds to the emission of a signal at<br> different frequency.<br> -----------------------------------------------------------------------------------------------------<br> List of directories:</p> <p>(Note : each directory corresponds to one mutual impedance measurement)</p> <p>L : These outputs correspond to one mutual impedance measurement in<br> small antenna emission amplitude, which corresponds to a linear<br> plasma response to the emission.</p> <p>s_xx : Each of these outputs corresponds to one mutual impedance measurement in correspondance of<br> a small-scale plasma inhomogeneity at xx Debye lengths of distance from the emitting antenna<br> </p> <p>-----------------------------------------------------------------------------------------------------<br> List of folders inside the directories:</p> <p>Folders begin with the name "000" and have increasing index. Inside the same directory, each folder<br> represents a different simulation used to build the same mutual impedance measurement.</p> <p>------------------------------------------------------------------------------------------------------<br> List of files inside the folders:</p> <p>density_e.npz : electron density inside the box, in function of time (tempo)</p> <p>density_p.npz : ion density inside the box, in function of time (tempo)</p> <p>E.npz : electric field in the box, in function of time (tempo)</p> <p>qrho.npz : electric potential in the box, in function of time (tempo)</p> <p>qrho_imposed.npz : electric charge imposed at the emitting antennas, in function of time (tempo)</p> <p>tempo.npz : time-vector for density, electric field, electric potential and charge vectors</p> <p>TEST_Luca.dat : parameters describing the characteristics of the simulated plasma box</p> <p><br> [<br> Note : the previous files can be opened as follows</p> <p>import numpy as np</p> <p>vector_file_name = np.load('file_name.npz') # Use these for the .npz files<br> characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1)</p> <p>]</p> <p><br> -------------------------------------------------------------------------------------------------------<br> Characteristics of the simulated plasma box (TEST_Luca.dat)</p> <p>nx : amount of spatial grid points</p> <p>xl : physical size of the spatial box, expressed in Debye length</p> <p>tt_w : time resolution for ion and electron density, electric field, electric potential and charge</p> <p>rap_m : ion-to-electron mass ratio</p> <p>R_p : ion-to-electron temperature ratio</p> <p>dt : time step used to evolve in time the numerical simulation</p> <p>emission : emission frequency</p> <p>power : amplitude of the electric charge imposed at the emitting antennas</p> <p><br> (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional<br> functionalities of the model. For the use of this dataset, they can be discarded.)</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Throughfall exclusion and fertilization effects on tropical dry forest tree plantations, a large-scale experiment
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Rapid adaptive evolution to drought in a subset of plant traits in a large-scale climate change experiment
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Ecosystem functions of plant diversity: Comparisons from a large-scale marsh restoration experiment in California, USA
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