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Water Levels and Porewater Temperature data from the Shark River and Taylor River Slough mangrove sites, Everglades National Park (FCE LTER), South Florida, USA: May 2001 - ongoing
Water levels for SRS4 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at Tarpon Bay. Water levels for SRS5 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS6 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for SRS7 are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m at the Shark River Slough. Water levels for TS/Ph6a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 80 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph7a are recorded at 1h intervals. Water level recorder is located in the mangrove forest approximately 60 m inland at the Taylor River Slough. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. Water levels for TS/Ph8 are recorded at 1h intervals. Water level recorder is located in the mangrove forests 40 m inland at the Joe Bay area. Water level recorder is located in between of two 20 by 20 m permanent monitoring plots. All water level data are measured by Florida International University.
Global Climate Change Impacts on the Vegetation and Fauna of Mangrove Forested Ecosystems in Florida (FCE): Nekton Mass from March 2000 to April 2004
Bottomless lift nets are buried within the mangrove forest floor and raised remotely on slack high spring tides to enclose a 6m2 area. As the tide ebbs, fishes retreat into a subtidal refuge cleared when the tide has fallen. Three replicate nets have been sampled at 3 locations along a salinity gradient on Shark River for 4 years. Small resident forage fish and grass shrimp dominate the collections. Exotic species and estuarine transient species that use the estuary as a nursery are rare within the assemblage of fishes that routinely use the flooded forest.
Mangrove Litterfall from the Shark River Slough and Taylor Slough, Everglades National Park (FCE), South Florida, USA, January 2001 - ongoing
Monthly litterfall data is being collected in two mangrove-dominated regions (Shark River and Taylor Slough) in South Florida. Three sites (SRS4, SRS5, SRS6) in the Shark River region and one site (TS/Ph8) in the Joe Bay area region were used to characterize patterns of litterfall production. At each mangrove site 10 litter baskets (0.5 x 0.5 m) were placed in two 20 x 20 m plots (five baskets per plot). Data have been collected since January 2001. Statistical analysis is being performed. See also Shark River mangrove litterfall carbon and nutrients data package knb-lter-fce.1266 (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1266).
Patterns of root biomass, productivity, turnover, and decomposition in riverine and scrub mangroves in the Everglades, Florida, USA, immediate-post-Irma, 2018-2019, and post-Irma, 2023-2024
Mangrove root biomass, productivity, and decomposition in the shallow (0-45 cm depth) root zone were estimated at Florida Coastal Everglades Long Term Ecological Research (FCE-LTER) Program Shark River (SRS4, SRS5, SRS6, SRS7) and Taylor River (TS/Ph6b, TS/Ph7b) mangrove sites during 2018-2019 and 2023-2024 following Hurricane Irma’s impacts in September 2017. Root biomass was estimated at all sites during both immediate-post-Irma (March 2018) and post-Irma (February-May 2023) periods with a PVC coring device (10.2 cm diameter x 45 cm length) using the same sampling protocol previously published for the study area (Castañeda-Moya et al. 2011). After collection, root cores were processed individually and initially rinsed with water through a 1-mm screen mesh to remove soil particles. Roots were separated manually based on their buoyancy, turgor, and color into biomass (live) and necromass (dead) components (Castañeda-Moya et al. 2011; Cormier et al. 2015; Medina-Calderon et al. 2021). Live roots were further sorted into three size diameter classes including fine (<2 mm), small (2-5 mm), and coarse (5-20 mm). Roots greater than 20 mm in diameter were not included in this study due to sampling limitations (i.e., core area). All root samples were oven-dried at 60°C to a constant mass and weighed to estimate root biomass and necromass (g m-2). Root productivity was estimated with the ingrowth core technique (Vogt et al., 1998) during both the immediate-post-Irma and post-Irma periods using the same sampling protocol previously published for the study area (Castañeda-Moya et al. 2011). Ingrowth cores (10.2 cm diameter x 45 cm length) were made of synthetic material (3 mm mesh) and filled with root-free commercial sphagnum peat moss. This material has similar soil properties (i.e., bulk density, organic matter content, total C and N) as mangrove peat in our study sites. Ingrowth cores were installed in each of the cored holes formed during sampling of root biomass. At each
Global Mangrove Watch: Mangrove Habitat Mask
<p>This is the habitat mask used to define the locations where mangroves can be found. It was used during the creation of the Global Mangrove Watch (GMW; <a href="https://www.globalmangrovewatch.org/?map=eyJiYXNlbWFwIjoibGlnaHQiLCJ2aWV3cG9ydCI6eyJsYXRpdHVkZSI6MjAsImxvbmdpdHVkZSI6MCwiem9vbSI6MiwiYmVhcmluZyI6MCwicGl0Y2giOjB9fQ%3D%3D">https://www.globalmangrovewatch.org</a>) extent products. Details of how this layer was originally produced are within Bunting et al., 2018 but it has subsequently been edited with further regions added as the GMW layers have been updated and improved. This is considered a living dataset which is edited, and new versions are produced when missing areas or improvements are identified. New versions will be uploaded here on zenodo.</p> <p><strong>Relevant publications:</strong></p> <p>Bunting, P., Rosenqvist, A., Lucas, R., Rebelo, L.-M., Hilarides, L., Thomas, N., Hardy, A., Itoh, T., Shimada, M., Finlayson, C., 2018. The Global Mangrove Watch—A New 2010 Global Baseline of Mangrove Extent. Remote Sens-basel 10, 1669. <a href="https://doi.org/10.3390/rs10101669" target="_blank" rel="noopener">https://doi.org/10.3390/rs10101669</a></p> <p>Bunting, Pete, Rosenqvist, Ake, Lucas , Richard, Rebelo, Lisa-Maria, Hilarides, Lammert, Thomas, Nathan, Hardy, Andy, Itoh, Takuya, Shimada, Masanobu, & Finlayson, Max. (2019). Global Mangrove Watch (1996 - 2016) Version 2.0 (2.0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.5658808" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.5658808</a></p> <p>Bunting, P., Rosenqvist, A., Hilarides, L., Lucas, R.M., Thomas, N., 2022. Global Mangrove Watch: Updated 2010 Mangrove Forest Extent (v2.5). Remote Sens-basel 14, 1034. <a href="https://doi.org/10.3390/rs14041034" target="_blank" rel="noopener">https://doi.org/10.3390/rs14041034</a></p> <p>Pete Bunting, Ake Rosenqvist, Lammert Hilarides, Richard M. Lucas, & Nathan Thomas. (2022). Global Mangrove Watch 2010 Baseline (v2.5) (2.5) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.5828339" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.5828339</a></p> <p>Bunting, P., Rosenqvist, A., Hilarides, L., Lucas, R.M., Thomas, N., Tadono, T., Worthington, T.A., Spalding, M., Murray, N.J., Rebelo, L.-M., 2022. Global Mangrove Extent Change 1996–2020: Global Mangrove Watch Version 3.0. Remote Sens-basel 14, 3657. <a href="https://doi.org/10.3390/rs14153657" target="_blank" rel="noopener">https://doi.org/10.3390/rs14153657</a></p> <p>Bunting, P., Rosenqvist, A., Hilarides, L., Lucas, R., Thomas, N., Tadono, T., Worthington, T., Spalding, M., Murray, N., Rebelo, L.-M., (2022) Global Mangrove Watch (1996 - 2020) Version 3.0 Dataset. <a href="https://doi.org/10.5281/zenodo.6894273" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.6894273</a></p> <p><br><br> </p>
Global Mangrove Watch 2010 Baseline (v2.5)
<p>This dataset is an updated version of the Global Mangrove Watch (Bunting et al. 2018) 2010 global mangrove baseline. A number of regions have been remapped to improve quality and map regions missed in the older version 2.0 product published in 2018. </p>
Global Mangrove Watch (1996 - 2020) Version 3.0 Dataset
<p>This study has used L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA) for 11 epochs from 1996 to 2020 to develop a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. This approach was applied between all image-date pairs producing 10 maps for each epoch, which were summarised to produce the global mangrove time-series. The resulting mangrove extent maps had an estimated accuracy of 87.4 % (95th conf. int.: 86.2 - 88.6 %), although the accuracies of the individual gain and loss change classes were lower at 58.1 % (52.4 - 63.9 %) and 60.6 % (56.1 - 64.8 %), respectively. Sources of error included a mis-registration in the SAR mosaic datasets, which could only be partially corrected for, but also confusion in fragmented areas of mangroves, such as around aquaculture ponds. Overall, 152,604 km<sup>2</sup> (133,996 - 176,910) of mangroves were identified for 1996, with this decreasing by -5,245 km<sup>2</sup> (-13,587 - 3686) resulting in a total extent of 147,359 km<sup>2</sup> (127,925 - 168,895) in 2020, and representing an estimated loss of 3.4 % over the 24-year time period. The Global Mangrove Watch Version 3.0 represents the most comprehensive record of global mangrove change achieved to date and is expected to support a wide range of activities, including the ongoing monitoring of the global coastal environment, defining and assessments of progress towards conservation targets, protected area planning and risk assessments of mangrove ecosystems worldwide.</p> <p>The paper which goes along with this dataset is available at the following reference:</p> <p>Bunting, P.; Rosenqvist, A.; Hilarides, L.; Lucas, R.M.; Thomas, T.; Tadono, T.; Worthington, T.A.; Spalding, M.; Murray, N.J.; Rebelo, L-M. Global Mangrove Extent Change 1996 – 2020: Global Mangrove Watch Version 3.0. Remote Sensing. 2022</p>
Global mangrove soil carbon data set at 30 m resolution for year 2020 (0-100 cm)
<p>Global soil organic carbon stocks in mangrove forests at 30 m resolution, and predicted for 2020 using spatiotemporal ensemble machine learning. Soil organic carbon stock (t/ha) was derived using predictions of soil organic carbon content and bulk density (BD) to 1 m soil depth, which were then aggregated to calculate soil organic carbon stocks.</p> <p>The "mangroves_tiles_SOC_predictions_2020.zip" file contains predictions of SOC content, Bulk Density (BD) and aggregated SOC stocks (t/ha) for 0—100 cm depth interval. Example of a tile:</p> <ul> <li>089E_21N (89E to 90E, 21N to 22N): <ul> <li>sol_db.od_mangroves.typology_m_30m_s0..100cm_2020_global_v0.1.tif = predicted BD aggregated to 0—100 cm;</li> <li>sol_soc.wpct_mangroves.typology_m_30m_s0..0cm_2020_global_v1.1.tif = predicted SOC content (%) at 0 cm depth (surface soil);</li> <li>sol_soc.wpct_mangroves.typology_m_30m_s0..100cm_2020_global_v1.1.tif = predicted SOC content (%) for 0—100 cm;</li> <li>sol_soc.tha_mangroves.typology_m_30m_s0..100cm_2020_global_v0.1.tif = predicted SOC stocks in t/ha (mean value);</li> <li>sol_soc.tha_mangroves.typology_l.std_30m_s0..100cm_2020_global_v0.1.tif = predicted SOC stocks in t/ha lower 95% probability prediction interval;</li> <li>sol_soc.tha_mangroves.typology_u.std_30m_s0..100cm_2020_global_v0.1.tif = predicted SOC stocks in t/ha upper 95% probability prediction interval;</li> </ul> </li> </ul> <p>Example of a tile:</p> <ul> <li>class : RasterLayer</li> <li>dimensions : 4004, 4004, 16032016 (nrow, ncol, ncell)</li> <li>resolution : 0.00025, 0.00025 (x, y)</li> <li>extent : 88.9995, 90.0005, 20.9995, 22.0005 (xmin, xmax, ymin, ymax)</li> <li>crs : +proj=longlat +datum=WGS84 +no_defs</li> <li>source : sol_db.od_mangroves.typology_m_30m_s0..0cm_2002_global_v0.1.tif</li> </ul> <p>To load global mosaics <strong><strong>Soil Carbon t/ha Maps (0—100cm)</strong></strong> as COGs directly into QGIS or similar, best use:</p> <ul> <li> <p><a href="https://s3.eu-central-1.wasabisys.com/openlandmap/mangroves/sol/soc.tha_tnc.mangroves.typology_m_30m_b0..100cm_2019_2020_go_epsg.4326_v1.2.tif">https://s3.eu-central-1.wasabisys.com/openlandmap/mangroves/sol/soc.tha_tnc.mangroves.typology_m_30m_b0..100cm_2019_2020_go_epsg.4326_v1.2.tif</a></p> </li> <li> <p><a href="https://s3.eu-central-1.wasabisys.com/openlandmap/mangroves/sol/soc.tha_tnc.mangroves.typology_l.std_30m_b0..100cm_2019_2020_go_epsg.4326_v1.2.tif">https://s3.eu-central-1.wasabisys.com/openlandmap/mangroves/sol/soc.tha_tnc.mangroves.typology_l.std_30m_b0..100cm_2019_2020_go_epsg.4326_v1.2.tif</a></p> </li> <li> <p><a href="https://s3.eu-central-1.wasabisys.com/openlandmap/mangroves/sol/soc.tha_tnc.mangroves.typology_u.std_30m_b0..100cm_2019_2020_go_epsg.4326_v1.2.tif">https://s3.eu-central-1.wasabisys.com/openlandmap/mangroves/sol/soc.tha_tnc.mangroves.typology_u.std_30m_b0..100cm_2019_2020_go_epsg.4326_v1.2.tif</a></p> </li> </ul>
Predicted soil organic carbon stock at 30 m in t/ha for 0-100 cm depth global / update of the map of mangrove forest soil carbon
<p>This is the 2nd update of maps produced by <a href="https://doi.org/10.1088/1748-9326/aabe1c">Sanderman et al (2018)</a>. The improvements to the <a href="https://opengeohub.github.io/spatial-prediction-eml/spatiotemporal-prediction-of-soil-organic-carbon.html">3D spatial predictions</a> include:</p> <ul> <li> <p>new updated global mangrove coverage map (contact Thomas Worthington),</p> </li> <li> <p>spatiotemporal predictions to account for differences in spectral reflectance at the time of field work,</p> </li> <li> <p>additional SOC points <a href="https://static-content.springer.com/esm/art%3A10.1038%2Fs41558-018-0162-5/MediaObjects/41558_2018_162_MOESM2_ESM.xlsx">published in Rovai et al. (2018)</a> used in model training (see gpkg file).</p> </li> </ul> <p>To open map in QGIS or similar, drag and drop the *.tif files. You can than add also the gpkg file contain the training points.</p> <p>Production steps (ensemble predictions using SuperLearner) are explained in detail at: </p> <ul> <li>R code: <a href="https://github.com/whrc/Mangrove-Soil-Carbon/">https://github.com/whrc/Mangrove-Soil-Carbon/</a> (see "R_code/GMW_mangroves_SOC_30m.R")</li> <li>Tutorial: <a href="https://envirometrix.github.io/PredictiveSoilMapping/soilmapping-using-mla.html#ensemble-predictions-using-superlearner-package">"Predictive Soil Mapping with R"</a></li> </ul> <p>Produced for the purpose of Mangrove Restoration Potential Map funded by The Nature Conservancy and IUCN. Contact TNC: Emily Landis <<a href="mailto:elandis@TNC.ORG">elandis@TNC.ORG</a>>. Contact IUCN / University of Cambridge: Thomas Worthington <<a href="mailto:taw52@cam.ac.uk">taw52@cam.ac.uk</a>>.</p> <ul> <li>The mangrove restoration potential map is available at: <a href="https://www.researchgate.net/deref/http%3A%2F%2Fmaps.oceanwealth.org%2Fmangrove-restoration%2F">http://maps.oceanwealth.org/mangrove-restoration/</a></li> </ul>
A database of published mangrove articles for coastal Louisiana, USA
Mangroves are being increasingly recognized as natural climate solutions for the range of ecosystem services they provide. In North America, one of the northern range limits of mangroves is found in coastal Louisiana, USA, where in recent decades, mangroves have been expanding into wetlands formerly dominated by salt marsh primarily due to decreases in the frequency and severity of winter freeze events. While reviews focused on mangrove ecology that include coastal Louisiana within a broader geographic scope have been conducted, no systematic review has focused on what is known about mangrove ecology across coastal Louisiana, a region that contains the expansive Mississippi River Delta. To fill this knowledge gap, we conducted a systematic review to highlight the breadth of mangrove research topics that have been studied in coastal Louisiana and identify emerging and future research opportunities. We identified four main research topics: (1) mangrove expansion, (2) freeze tolerance, (3) coastal restoration, and (4) disturbance. We also identified geographic biases in where mangrove research has been conducted, with a focus around the heavily industrialized Port Fourchon/Grand Isle area.
Effect of mangroves on transplanted marsh plants, Port Aransas, Texas: 2013
We transplanted three common species of salt marsh plants (Spartina alterniflora, Batis maritima, Sarcocornia sp.) into eight experimental plots (24 x 42 m) varying in plot-level mangrove cover in Port Aransas, Texas in 2013. We transplanted marsh plants into 3 x 3 m “cells” with one of 3 different vegetation treatments (cleared, mangrove, pneumatophores) in each of the eight plots. Marsh plants were harvested to measure final size.
Mangrove Forest Growth from the Shark River Slough, Everglades National Park (FCE), South Florida, USA, January 1995 - ongoing
All mangrove trees having a diameter at breast height (DBH) greater than 2.5 cm were tagged in two 20 x 20 m plot in stations SRS4-7 and TS/Ph-8. Measurements in Plot Num1 began in 1995; measurements in Plot Num 2 began in 2001. Plot Num1 in TS/Ph-8 was established in 2001. Measurements at SRS-7 began in 2022. DBH has been measured in the period 1995-2023. Mangrove species include Rhizophora mangle, Laguncularia racemosa, Avicennia germinans, Conocarpus erectus.
Physical Hydrologic Data for the National Audubon Society's 16 Research Sites in coastal mangrove transition zone of southern Florida, March 1986 - ongoing
Temperature, salinity and depth were continuously collected using Hydrolab/Hach sensors within the coastal mangrove transition zone at 16 sites from southern Biscayne Bay to Cape Sable. Data were collected at 12 sites within the coastal mangrove zone of Everglades National Park, incorporating the Cape Sable, Taylor River and Panhandle region. Data were collected at 4 sites within the coastal mangrove zone of southern Biscayne Bay, incorporating the Manatee Bay, Barnes Sound, and Card Sound regions. Rainfall, pH, and dissolved oxygen were collected at a number of these sites with varying periods of record.
Abiotic monitoring of physical characteristics in porewaters and surface waters of mangrove forests from the Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), South Florida, USA, December 2000 - ongoing
Data on porewater salinity, temperature, conductivity, pH and redox have been collected to help explain patterns found in porewater nutrient concentrations that were sampled in the same plots. See knb-lter-fce.1171 (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1171) for related porewater-nutrient-concentration data.
Monitoring of nutrient and sulfide concentrations in porewaters of mangrove forests from the Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, December 2000 - ongoing
To monitor soil chemistry in the mangrove sites SRS4, SRS5, SRS6, and SRS7, and TS/Ph6b, TS/Ph7b and TS/Ph8, porewater concentrations of sulfide, PO4, NH4, NO2 and NO3 have been analyzed. See also related porewater-physical-characteristics data package knb-lter-fce.1169 (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1169).
Mangrove soil phosphorus addition experiment from June 2013 to August 2013 at the mangrove peat soil mesocosms (FCE), Key Largo, Florida - Nutrients in Porewater, Soil and Roots
Sea levels in South Florida are conservatively predicted to rise by 0.60 m by 2060. The key mechanisms that maintain coastal peatland elevation against increasing sea level are organic matter accumulation via plant production and mineral sedimentation rates (Smoak et al. 2013). Although coastal mangrove soils are regularly inundated with seawater, little is know about the drivers of carbon sequestration (above or below ground) versus atmospheric efflux under different conditions of salinity and elevated phosphorus (P) associated with sea-level rise and storm surge. A recent study using mangrove peat soils found that seawater inundation reduced soil carbon efflux losses and salinity concentration had little effect on carbon retention or loss pathways. The next logical steps are to understand how plant-soil interactions affect above and below ground carbon processes, as well as how increases in P associated with storm surge from the Gulf of Mexico will influence physical, chemical and biological components of mangrove soils that are associated with above and belowground carbon processes. We will manipulate P in inundated peat soil mesocosms with disturbed and undisturbed red mangrove (Rhizophora mangle) seedlings to identify some of the fundamental mechanisms of soil elevation and carbon cycling given expected increases in seawater-based P availability in South Florida coastal mangroves.
Mangrove soil phosphorus addition experiment from July 2013 to August 2013 at the mangrove peat soil mesocosms (FCE), Key Largo, Florida - Nutrients in Surface Water and Aboveground Biomass
Sea levels in South Florida are conservatively predicted to rise by 0.60 m by 2060. The key mechanisms that maintain coastal peatland elevation against increasing sea level are organic matter accumulation via plant production and mineral sedimentation rates (Smoak et al. 2013). Although coastal mangrove soils are regularly inundated with seawater, little is know about the drivers of carbon sequestration (above or below ground) versus atmospheric efflux under different conditions of salinity and elevated phosphorus (P) associated with sea-level rise and storm surge. A recent study using mangrove peat soils found that seawater inundation reduced soil carbon efflux losses and salinity concentration had little effect on carbon retention or loss pathways. The next logical steps are to understand how plant-soil interactions affect above and below ground carbon processes, as well as how increases in P associated with storm surge from the Gulf of Mexico will influence physical, chemical and biological components of mangrove soils that are associated with above and belowground carbon processes. We will manipulate P in inundated peat soil mesocosms with disturbed and undisturbed red mangrove (Rhizophora mangle) seedlings to identify some of the fundamental mechanisms of soil elevation and carbon cycling given expected increases in seawater-based P availability in South Florida coastal mangroves.
Sediment and nutrient deposition and plant-soil phosphorus interactions associated with Hurricane Irma (2017) in mangroves of the Florida Coastal Everglades (FCE LTER), Florida
We quantified how Hurricane Irma influenced soil nutrient pools, vertical accretion, and plant phosphorus (P) uptake after its passage across the Florida Coastal Everglades in September 2017. Mangrove leaf litter data from three years (2008, 2014, 2018) were selected for each site at Shark River estuary to identify species-specific foliar P responses post-Wilma’s impact in 2005 and immediate post-Irma’s impact in 2017. We also monitored porewater SRP concentrations in the Shark River mangrove sites to evaluate the effect of Hurricane Irma on soil chemistry. The data in this data package were used in the following paper: Castañeda-Moya, E., V.H. Rivera-Monroy, R.M. Chambers, X. Zhao, L. Lamb-Wotton, A. Gorsky, E.E. Gaiser, T.G. Troxler, J.S. Kominoski, and M. Hiatt. 2020. Hurricanes fertilize mangrove forests in the Gulf of Mexico (Florida Everglades, USA). PNAS. In Press.
FCE LTER Taylor Slough/Panhandle-7 Site Scrub Red Mangrove (Rhizophora mangle) Leaf Gas Exchange Data, Florida, USA from January-December 2019
Rates of leaf gas exchange were measured monthly during the 2019 calendar year in a scrub Red mangrove (Rhizophora mangle (L.) L.) forest site (TS/Ph-7) near the mouth of Taylor River in southeastern Florida Everglades. Sampling of green mature leaves was designed to target scrub mangrove tree branches growing on slightly higher elevation mangrove island centers versus permanently inundated island edge habitats. Concurrent measurements of water depth and surface and porewater salinity were collected at each of the mangrove island habitats, with the research objective of assessing the effect of physicochemical variables on rates of leaf gas exchange (i.e., assimilation and stomatal conductance). Leaf gas exchange data were collected using the Li-6800 portable photosynthesis system (Li-COR, Lincoln, NE). Additional data on leaf functional traits and nutrient concentrations and environmental data from the site are included. Data are presented in five datasets (.csv).
Mangrove Leaf Litter Carbon and Nutrients from the Shark River Slough, Everglades National Park (FCE), South Florida, USA, January 2019 - ongoing
Mangrove litterfall dynamics have been monitored in all Shark River sites (SRS-4, SRS-5, SRS-6) since January 2001 using the same collection method stated in Castañeda-Moya et al. 2013 (metadata: knb-lter-fce.1195) and Danielson et al. 2017. Briefly, litterfall was collected monthly at all sites (10 baskets per site) using permanent 0.25 m2 wooden baskets supported approximately 1.3 m above the soil surface and lined with 1 mm mesh screening. Litterfall from each basket was sorted, dried, and weighed by leaf species, reproductive parts by species, and woody material. Leaf litter data from different years (2019, 2020, 2021, 2023) were selected for each site to identify species-specific foliar carbon and nutrient (N and P) content. Monthly leaf litter samples were analyzed separately by species for all years after grinding with a Wiley Mill to pass through a 40-µm mesh screen. Total leaf litter C and N contents were determined with a Carlo-Erba NA-1500 elemental analyzer (Fisons Instruments Inc., Danvers, MA, USA). Total leaf litter P was extracted using an acid-digest (HCl) extraction, and concentrations of SRP were determined by spectrophotometric analysis (Methods 365.4 and 365.2, USA EPA 1983). Litterfall data collection is ongoing every year since 2001, while C and nutrients analyses are performed every other year after 2021. See also Shark River mangrove litterfall data (knb-lter-fce.1195) on the FCE LTER website's data catalog or in the EDI repository (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1195). References: Castañeda-Moya, E., Twilley, R. R., & Rivera-Monroy, V. H. (2013). Allocation of biomass and net primary productivity of mangrove forests along environmental gradients in the Florida Coastal Everglades, USA. Forest Ecology and Management, 307, 226-241. Danielson, T.M., V.H. Rivera-Monroy, E. Castaneda-Moya, H. Briceno, R. Travieso, B.D. Marx, E. Gaiser, and L.M. Farfan. 2017. Assessment of Everglades mangrove forest re
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.