Find research datasets worth reusing

opencc-by-4.0Nov 2019View details →

Dataset: Open access potential and uptake in the context of Plan S - a partial gap analysis

Dataset belonging to the report: <a href="https://doi.org/10.5281/zenodo.3543000">Open access potential and uptake  in the context of Plan S  - a partial gap analysis</a>   On the report:  The analysis presented in the report, carried out by Utrecht University Library, aims to provide cOAlition S, an international group of research funding organizations, with initial quantitative and descriptive data on the availability and usage of various open access options in different fields and subdisciplines, and, as far as possible, their compliance with Plan S requirements. Plan S, launched in September 2018, aims to accelerate a transition to full and immediate Open Access. In the guidance to implementation, released in November 2018 and updated in May 2019, a gap analysis of Open Access journals/platforms was announced. Its goal was to inform Coalition S funders on the Open Access options per field and identify fields where there is a need to increase the share of Open Access journals/platforms.  The report should be seen as a first step: an exploration in methodology as much as in results. Subsequent interpretation (e.g. on fields where funder investment/action is needed) and decisions on next steps (e.g. on more complete and longitudinal monitoring of Plan S-compliant venues) is intentionally left to cOAlition S and its members.    This work was commissioned on behalf of cOAlition S by the Dutch Research Council (NWO), a member of cOAlition S. Bianca Kramer and Jeroen Bosman of Utrecht University Library were appointed to lead the project.

opencc-by-4.0Oct 2024View details →

Toward a Generalizable Machine-Learned Potential for Metal-Organic Frameworks

<ul> <li>This repository contains the dataset used in the publication   `Toward Generalizable Machine Learned Potential for Metal-Organic Frameworks` Yue Yifei, Saad Aldin Mohammed, Loh Duane*, Jiang Jianwen*      Please each the README.md within each subfolder. For brevity, the data is organized into three sections      1. The dataset in DATASET       - The training and testing dataset, including structures of MOFs in extxyz format          2. The training output files and logs in NEQUIP-TRAIN       - The conda environment details, training scripts and logs       - Also Training and testing metrics in csv files      - This is split into two zip files NEQUIP-TRAIN1 and NEQUIP-TRAIN2 due to their size         3. Examples of using the developed models in MD simulations       - Including LAMMPS scripts, data file and environment details used in our scalability tests       - The complied Nequip-patched LAMMPS version is also provided       - Details on how to use our models - we used a default model that is slower but more accurate in our study but faster models are also developed.</li> </ul>

opencc-by-4.0Aug 2021View details →

The Potential of Fragipans in Sustaining Pearl Millet during Drought Periods in North-Central Namiba (dataset)

Abstract Sandy soils with fragipans are usually considered poorly suited for agriculture. However, these soils are cultivated in north-central Namibia as they can secure a minimum harvest during droughts. To understand the hydrological influence of fragipans in these soils, Ehenge, and what makes them valuable, their soil moisture content was measured over a time span of four months. These data were then compared to a deep soil without fragipan, Omutunda, which is more productive during normal years, but less productive during droughts. The results illustrate that the combination of sandy topsoil and shallow fragipan has beneficial effects on plant available water during dry periods, because of three reasons: (i) The high infiltration rate in the sandy topsoil, (ii) the prevention of deep drainage of water by the fragipan, and (iii) the limited evaporation losses through the capillary rise in the sand. The results also confirm the disadvantages of Ehenge during wet periods. Description of Dataset The dataset comprises a .pdf-file with a detailed data description, seven .csv-files (relevant datasets), and two txt-files with the R-code to produce the relevant Figures 4 and 5 from the paper “The Potential of Fragipans in Sustaining Pearl Millet during Drought Periods in North-Central Namibia” by Prudat et al. 2021. File description Rainfall.csv: daily rainfall in mm at two locations (Omutunda & Ehenge) NDOB13_ehenge.csv/ NDOB13_omutunda.csv: soil temperature and soil moisture per minute NDOB13_ehenge_daily.csv/ NDOB13_omutunda_daily.csv: soil temperature and volumetric soil moisture content (θTDR) aggregated per day using the arithmetic mean NDOB13_ehenge_RASW_daily.csv/ NDOB13_omutunda_RASW_daily.csv: The relative available soil water (RASW) was calculated based on the measured plant available water, Scripts (1) RASW_rainfall_daily: Script to calculate and plot the relative available soil water (RASW) at the two stations and the rainfall (2) Max_soil_surface_temperature: Script to calculate and plot the maximum soil surface temperature at the two stations   References Cobos, D., Campbell, C., 2007. Correcting temperature sensitivity of ECH2O soil moisture sensors. Decagon Devices Pullman WA. Hillel, D., 1998. Environmental soil physics: Fundamentals, applications, and environmental considerations. Academic press.

opencc-by-4.0Mar 2023View details →

Environmental and economic potential of decentralised electrocatalytic ammonia synthesis powered by solar energy

Dataset associated with the publication "Environmental and economic potential of decentralised electrocatalytic ammonia synthesis powered by solar energy" by Sebastiano C. D'Angelo, Antonio J. Martín, Selene Cobo, Diego Freire-Ordóñez, Gonzalo Guillén-Gosálbez, and Javier Pérez-Ramírez, available at <a href="https://doi.org/10.1039/D2EE02683J">https://doi.org/10.1039/D2EE02683J</a>. The dataset includes the numeric data required to plot all the figures embedded in the main manuscript and in the Electronic Supplementary Information (ESI). The structure of the dataset is here elucidated sheet by sheet: <ul> <li>GeneralParameters: numerical values for the scaled functional unit used in the study, the world population value adopted, and the three voltage efficiencies assumed in different parts of the study.</li> <li>AL_BaseCase_SensECE: numerical values associated with the results for the ammonia leaf scenarios adopting a voltage efficiency of 63% (base case) and a Faradaic efficiency varying from 1% to 100%; highest, average, and lowest capacity factors for the solar power production were here used. The ammonia leaf configuration here assessed is the one including solar panels, electrolyzer, and fuel cell as key components. The results report all the ReCiPe 2016 (hierarchical approach) midpoints and endpoints and the values for the assessed planetary boundaries; the levelised cost of ammonia (LCOA) is reported, as well.</li> <li>AL_EtaV75_SensECE: this sheet has the structure as the previous one, but includes the results for the ammonia leaf scenario using 75% voltage efficiency, instead of 63%. The remaining assumptions do not deviate from the base case.</li> <li>AL_Eta100_SensECE: this sheet has the structure as the previous one, but includes the results for the ammonia leaf scenario using 100% voltage efficiency, instead of 63%. The remaining assumptions do not deviate from the base case.</li> <li>AL_NoFC_H2Vented_SensECE: this sheet has the same structure as the sheet "AL_BaseCase_SensECE", but includes the ammonia leaf scenario using a configuration with no fuel cell. The hydrogen by-product was here considered vented to the air. The remaining assumptions do not deviate from the base case.</li> <li>AL_NoFC_H2Subst_SensECE: this sheet has the same structure as the sheet "AL_BaseCase_SensECE", but includes the ammonia leaf scenario using a configuration with no fuel cell. The hydrogen by-product was here considered substituting the production of an equivalent quantity from a water electrolyzer deployed in the same location as the ammonia leaf. The remaining assumptions do not deviate from the base case.</li> <li>AL_BaseCase_SpatAnal_BreakFEff: numerical results for the ammonia leaf base case scenario stemming from the spatial analysis performed on a global grid of 1140 points. The yearly average capacity factors for the solar panels at each location are included, and the results portraying the breakeven Faradaic efficiency for the indicators climate change - CO2 concentration, global warming, human health, and levelised cost of ammonia were included. The assumptions for the voltage efficiency and the other parameters correspond to the base case.</li> <li>AL_BaseCase_SpatAnal_AbsValues: numerical results for the ammonia leaf scenarios using the base case state-of-the-art (34%) and 100% Faradaic efficiency, as well as the base case voltage efficiency of 63%. The same metrics as the previous sheet are reported. The structure of the sheet is the same as the previous one.</li> <li>AL_BaseCase_Breakdowns: breakdown of the same four indicators as the previous sheet for the best and worst combination of Faradaic efficiency and solar panels capacity factors, i.e., 34% Faradaic efficiency and 6% capacity factor on one side and 100% Faradaic efficiency and 26% capacity factor on the other side. The breakdown is divided into solar panels, electrolyser, fuel cell, and other elements. A further breakdown of the levelised cost of ammonia (LCOA) into capital expenditure (CAPEX) and operating expenditure (OPEX) is provided, as well. The voltage efficiency is the same as the base case, as well as the other parameters.</li> <li>AL_BaseCase_CAPEXSens: numerical results for the levelised cost of ammonia (LCOA) in dependence of the sensitivity on the capital expenditure (CAPEX) for the ammonia leaf configuration assessed in the base case. Two cases assuming state-of-the-art (34%) and 100% Faradaic efficiency were assumed, and lowest, average, and highest capacity factor are included. The remaining parameters do not deviate from the base case configuration.</li> <li>AL_gHB_BestMap: numerical results to produce the map showing the best technology between ammonia leaf (AL) and green Haber-Bosch (gHB) in the category climate change - CO2 concentration for all the assessed locations. column D shows the share of safe operating space (%SOS) for each location, while column E shows which technology was selected, where 1 is ammonia leaf and 2 is green HB.</li> <li>AL_BaseCase_Sensitivity: percentual variation of the results obtained assuming the base configuration ammonia leaf for a state-of-the-art Faradaic efficiency and an average capacity factor for the solar panels. The varied parameters include the voltage efficiency (columns C-D-E), the levelised cost of electricity (columns G-H-I), the electrolyser cost (columns K-L-M), the fuel cell cost (columns O-P-Q), the electrolyser environmental impact (columns S-T-U), and the fuel cell environmental impact (columns W-X-Y).</li> <li>CompTech_BaseCase: environmental and economic metrics characterizing the assessed Haber-Bosch scenarios (business as usual, BAU; blue Haber-Bosch; green Haber-Bosch for lowest, average, and highest solar panels capacity factor; BAU assuming natural gas spot prices in Europe in August 2022). The reported metrics are the ReCiPe 2016 (hierarchical approach) midpoints and endpoints, the planetary boundaries, and the levelised cost of ammonia (LCOA).</li> <li>CompTech_EtaV75: this sheet has the same structure as the previous one, but the hydrogen electrolyser used for the green Haber-Bosch scenarios was assumed to have a 10% stack efficiency improvement. The remaining parameters are the same.</li> <li>CompTech_EtaV100:  this sheet has the same structure as the previous one, but the hydrogen electrolyser used for the green Haber-Bosch scenarios was assumed to have a 100% stack efficiency. The remaining parameters are the same.</li> <li>CompValues_Fig1: numerical values for yearly global warming impacts of a selection of countries, as well as for the yearly human health impacts of selected diseases and catastrophic events.</li> </ul>

opencc-by-4.0Dec 2022View details →

Current and future global distribution of potential biomes under climate change scenarios

Probability and uncertainty maps showing the potential current and future natural vegetation on a global scale under three different climate change scenarios (RCP 2.6, RCP 4.5 and RCP 8.5) predicted using ensemble machine learning. Current (2022 - 2023)   conditions are calculated on historical long term averages (1979 - 2013), while future projections cover two different epochs: 2040 - 2060 and 2061 - 2080. Files are named according to the following naming convention, e.g.: <ul> <li>biomes_graminoid.and.forb.tundra.rcp85_p_1km_a_20610101_20801231_go_epsg.4326_v20230410</li> </ul> with the following fields: <ul> <li>generic theme: biomes,</li> <li>variable name: graminoid.and.forb.tundra.rcp85,</li> <li>variable type, e.g. probability ("p"), hard class ("c"), model deviation ("md")</li> <li>spatial resolution: 1km,</li> <li>depth reference, e.g. below ("b"), above ("a") ground or at surface ("s"),</li> <li>begin time (YYYYMMDD): 20610101,</li> <li>end time: 20801231,</li> <li>bounding box, e.g. global land without Antarctica ("go"),</li> <li>EPSG code: epsg.4326,</li> <li>version code, e.g. creation date: v20230410.</li> </ul> We provide probability and hard class layers using a revised classification system of the <a href="https://www.jstor.org/stable/2846196">BIOME 6000 project</a> explained in the work of <a href="https://doi.org/10.7717/peerj.5457">Hengl et al. (2018)</a>. The 20 classes from this classification system have then been aggregated in 6 biome classes following the <a href="https://global-ecosystems.org/page/typology">IUCN Global Ecosystem Typology</a> classification system. For probability layers, the uncertainty (model deviation: md) is calculated as the standard deviation of the predicted values of the base learners of the ensemble model. The higher the standard deviation the more uncertain the model is regarding the right value to assign to the pixel. For hard class layers the uncertainty is calculated using the margin of victory (<a href="https://doi.org/10.1016/j.rse.2020.112148">Calderón-Loor et al., 2021</a>) defined as the difference between the first and the second highest class probability value in a given pixel. High values would be measures of low uncertainty, while low values would indicate a high uncertainty. It is highly recommended to use the md layers to properly interpret the results of the map. Styling files are provided in both .SLD and .QML format; two different styling files are provided for the uncertainty of the probability layers and the hard classes due to the different interpretation of the chosen uncertainty metrics. The R scripts and a tutorial will be uploaded to the <a href="https://github.com/Envirometrix/PNVmaps">PNVmaps Github repository</a>, where previous versions of the biomes maps from <a href="https://doi.org/10.7717/peerj.5457">Hengl et al. (2018)</a> is currently hosted. To cite the maps and the methodology, it is possible to refer to the scientific publication: Bonannella C, Hengl T, Parente L, de Bruin S. 2023. Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation. PeerJ 11:e15593 <a href="https://doi.org/10.7717/peerj.15593">https://doi.org/10.7717/peerj.15593</a>

opencc-by-4.0Jul 2023View details →

Raw data for the article "Unwrap Them First: Operando Potential-induced Activation Is Required when Using PVP-Capped Ag Nanocubes as Catalysts of CO₂ Electroreduction"

Raw data for the article "Unwrap Them First: Operando Potential-induced Activation Is Required when Using PVP-Capped Ag Nanocubes as Catalysts of CO₂ Electroreduction'', published in Chimia 2021 75:163, doi: <a href="http://doi.org/10.2533/chimia.2021.163">10.2533/chimia.2021.163</a> Folder names describe the type of data content.

Optimized structures of the stationary points on the potential energy surface of the OH(2Π) + C2H4 reaction

This Zip file contains the cartesian coordinates of optimized stationary points of the OH(2Π) + C2H4 potential energy surface published in our article “OH(2Π) + C2H4 Reaction: A Combined Crossed Molecular Beam and Theoretical Study” (Phys. Chem. A 2023, 127, 21, 4609–4623), that can be found in <a href="https://doi.org/10.1021/acs.jpca.2c08662">https://doi.org/10.1021/acs.jpca.2c08662</a>. All calculations have been performed with  Gaussian 09, Revision D.01. All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.

Optimized structures of the stationary points on the potential energy surface of the O(3P, 1D) + HCCCN(X1Σ+) reaction

This Zip file contains the cartesian coordinates of optimized stationary points of the O(3P, 1D) + HCCCN(X1Σ+) potential energy surface published in our article “Reactions O(3P, 1D) + HCCCN(X1Σ+) (Cyanoacetylene): Crossed-Beam and Theoretical Studies and Implications for the Chemistry of Extraterrestrial Environments” (J. Phys. Chem. A 2023, 127, 3, 685–703), that can be found in <a href="https://doi.org/10.1021/acs.jpca.2c07708">https://doi.org/10.1021/acs.jpca.2c07708</a>. All calculations have been performed with  Gaussian 09, Revision D.01. All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.

Adsorption free energies and potentials of mean-force for interactions between amino acids, lipid fragments, and nanoparticles

This dataset contains tabulated potentials of mean force (PMFs) and associated adsorption (binding) free energies for interactions of amino acids side chain analogues and lipid fragments (LF) with a range of materials: titanium dioxide, iron oxide, amorphous silica, quartz, and a range of carbon-based materials including amorphous carbon, graphene and carbon nanotubes both in a pristine form and functionalized by certain chemical groups. All data were computed from atomistic molecular dynamics simulations as a part of the SmartNanoTox project 2016-2020. Version 2 of the dataset includes additional materials: zink oxide, zink sulfate in pristine and PMMA-coated forms computed within NanoSolveIt project (2019-2023). The data are intended to be used in coarse-grained models describing interactions of nanomaterials with nanoparticles, for the prediction of the binding affinity of proteins and lipids to nanoparticles, and as biological "fingerprints" of nanomaterials characterizing behavior of the nanomaterials in biological environments.

Optimized structures of the stationary points on the potential energy surface of the dissociation of the CH3OH˙+ cation

This Zip file contains the optimized stationary points structures of the potential energy surface (PES) for the dissociation of the  CH3OH˙+ cation. The PES has been published in our paper “Fragmentation of interstellar methanol by collisions with He˙+: an experimental and computational study” (Phys. Chem. Chem. Phys., 2022, 24, 22437-22452), that can be found in https://doi.org/10.1039/D2CP02458F . All calculations have been performed with Gaussian 09, Revision D.01 and the structures were optimized at ωB97X-D/aug-cc-pVTZ level of theory.

openCC (other)Jan 2026View details →

Missouri reservoir profile data including depth, temperature, oxygen, photopigments, conductivity, pH, turbidity, and oxidative-reductive potential starting in 2023

This dataset of annual limnological profiles starts in 2023 and is from reservoirs in the state of Missouri (MO) in the USA collected by the University of Missouri Limnology Lab. Physical parameters derived from sensors include temperature and oxygen with depth. Sondes used were Yellow Springs Instruments (YSI) EXO3s; profiles include a range of physical, chemical, and biological parameters including depth, conductivity, pH, oxidative-reductive potential (ORP), chlorophyll a, phycocyanin (PC), and turbidity. After May 2024, the turbidity sensor was replaced with a phycoerythrin (PE) sensor. Most of the profiles were collected during the summer months (May-September) when the reservoirs were thermally stratified, but a few were taken during the rest of the year (October-April). The majority of profiles were taken at the deepest point in the reservoir directly up-reservoir of the dam. Sampling was conducted from a boat. The bulk of the data come from the Statewide Lake Assessment Project (SLAP), funded by the Missouri Department of Natural Resources. The profiles are divided into single files for each year. This data has been quality controlled for basic errors and any data outside of normal factory issued sensor ranges.

openCC0Mar 2025View details →

Salt marsh redox potential at sites with runnel remediation in SE Massachusetts, 2020-2022

Natural disturbances, sea level rise, and historic human impacts to salt marshes have increased impounded water on marsh surfaces, resulting in vegetation loss and the associated loss of important ecosystem services such as carbon storage. Runnels are a climate adaptation technique designed to restore salt marsh habitat by reestablishing a tidal connection between impounded water and a nearby drainage feature. While runnels can drain impounded water and promote revegetation, the unintended effects of altering redox conditions remain unknown. Draining sediment and increasing redox potential could stimulate decomposition. We measured redox potential in two marshes in SE Massachusetts (Little Bay in Fairhaven, and Ocean View Farm in Dartmouth) prior to runnel restoration, and two years post restoration. We measured redox potential using three spatial distinctions: in the center of the panne, landward of the panne, and seaward of the panne. This was done every 2-3 weeks over a growing season.

openCC (other)Dec 2025View details →

Analyzing fish leaping and movement potential at a migratory barriers: Michigan 2022-2025

The enclosed Matlab scripts and supporting files are used for fish passage assessments at small migratory barriers with complex geometry. Building upon a 2-D ballistic trajectory mathematical model, the model incorporates field-derived behavioral parameters and simulated flow data to evaluate the likelihood of successful leaping attempts. The model integrates stochastic variation in key fish characteristics—such as body length, launch speed, and leap origin—to simulate a range of realistic leaping scenarios. These are coupled with three-dimensional, CFD-derived inputs for local water velocity and depth, enabling a spatially detailed assessment of hydraulic conditions that are most conducive to successful passage. This integrated approach provides a more comprehensive and biologically informed evaluation of passage potential at migratory barriers. To demonstrate its utility, the model is applied in a case study examining the influence of complex barrier geometry on fish passage outcomes, highlighting its potential to inform engineering design decisions that either facilitate or limit fish movement based on management objectives. The enclosed files are associated with steelhead passage at a arc-labyrinth and low-flow weir at the FishPass project, located on the Boardman/Ottaway River, MI, USA.

openCC0Feb 2023View details →

Lots for greening: Identification of metropolitan vacant land and its potential use for cooling and agriculture in Phoenix, Arizona, USA

This project provides the first systematic assessment of non-governmental vacant parcels for potential greening (VPPG) the Phoenix metropolitan area—land parcels that are or can be privately owned but which contain no buildings, are unpaved, have no apparent use, and are potential candidates for urban greening. To achieve the data, a new method for the identification of vacant lands was employed that combines remote sensing techniques and cadastral data and trains the computer to distinguish different forms of vacant land. The classification result proved to be an effective approach for open land identification and identified approximately 19500 ha of open land in the metro area. The model achieved an average accuracy of 90.67%. This dataset only includes VPPG and does not include other vacant land determined to be inappropriate for potential greening (developed/abandoned or impervious surface). (Overall accuracy for all classes was 87.20%).

openCC (other)Mar 2022View details →

Counts of potential nest predators from Black-throated Blue Warbler territories, Hubbard Brook Experimental Forest, 1997 – 2019

This dataset provides counts of potential nest predators recorded on surveys conducted in black-throated blue warbler territories at the Hubbard Brook Experimental Forest. Surveys occurred on three gridded study plots at the HBEF: low elevation (250-350 m; 85 ha), middle elevation (450-600 m; 65 ha), and high elevation (750-850 m; 35 ha). See Rodenhouse et al. 2003 for plot details. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.

openCC (other)Feb 2022View details →

Hubbard Brook Experimental Forest: Droughtnet soil moisture, temperature and soil water potential

The forest drought experiment prototype at Hubbard Brook was constructed in 2015, as part of the International Drought Experiment (IDE) coordinated by the DroughtNet Research Coordination Network. The throughfall exclusion experiment was designed to simulate a 1-in-100-year drought during an average precipitation year by diverting ~50% of forest throughfall from each treatment plot starting in May 2015 (Asbjornsen et al., 2018). Throughfall was intercepted by reinforced polyethylene troughs and diverted passively to the downslope side of each plot. Each throughfall exclusion plot was 15 x 15 meters in area. TFE plots were designated with the labels 7 and 8 to avoid any confusion with the nearby CCASE plots (which are labeled 1-6). Plots were not trenched to isolate them from the surrounding soil. In May 2019 throughfall removal was increased to approximately 95% (i.e. full coverage but with stemflow not fully excluded). Throughfall exclusion treatments ended in February 2020. Recovery and return to baseline conditions were monitored during 2020 (when a natural drought occurred) and 2021 (a more normal year). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.

openCC (other)Mar 2022View details →

MCR LTER: Coral Reef: Distinguishing the molecular diversity, nutrient content, and energetic potential of exometabolomes produced by macroalgae and reef-building corals; data for Kelly et al., 2022 PNAS

Metabolites exuded by primary producers comprise a significant fraction of marine dissolved organic matter, a poorly characterized, heterogenous mixture that dictates microbial metabolism and biogeochemical cycling. We present a foundational untargeted molecular analysis of exudates released by coral reef primary producers using liquid chromatography–tandem mass spectrometry to examine compounds produced by two coral species and three types of algae (macroalgae, turfing microalgae, and crustose coralline algae [CCA]) from Mo’orea, French Polynesia. Of 10,568 distinct ion features recovered from reef and mesocosm waters, 1,667 were exuded by producers; the majority (86%) were organism specific, reflecting a clear divide between coral and algal exometabolomes. These data allowed us to examine two tenets of coral reef ecology at the molecular level. First, stoichiometric analyses show a significantly reduced nominal carbon oxidation state of algal exometabolites than coral exometabolites, illustrating one ecological mechanism by which algal phase shifts engender fundamental changes in the biogeochemistry of reef biomes. Second, coral and algal exometabolomes were differentially enriched in organic macronutrients, revealing a mechanism for reef nutrient-recycling. Coral exometabolomes were enriched in diverse sources of nitrogen and phosphorus, including tyrosine derivatives, oleoyl-taurines, and acyl carnitines. Exometabolites of CCA and turf algae were significantly enriched in nitrogen with distinct signals from polyketide macrolactams and alkaloids, respectively. Macroalgal exometabolomes were dominated by nonnitrogenous compounds, including diverse prenol lipids and steroids. This study provides molecular-level insights into biogeochemical cycling on coral reefs and illustrates how changing benthic cover on reefs influences reef water chemistry with implications for microbial metabolism. This material is based upon work supported by the U.S. National Science Founda