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1,071 results for “mangrove”
Field survey of mangrove regeneration, porewater variables, and light in mangrove forests in Everglades National Park, Florida, USA, July 2020 - August 2022
This dataset package encompasses measurements from field surveys of mangrove regeneration, porewater variables, and light conditions across six mangrove sites in the coastal Everglades. The goal of this project was to quantify mangrove regeneration of seedlings and saplings in mid- and downstream locations within three estuaries in Everglades National Park, Florida, USA. We assessed the effects of porewater variables and light conditions on the observed regeneration patterns. The package includes seven datasets: FCE1268_Porewater: Contains measurements of porewater salinity, sulfide, ammonia, nitrite, orthophosphate, and nitrate at a 30 cm depth. Porewater surveys were conducted biannually from 09-10-2020 to 05-17-2022. See also similar porewater data for Florida Coastal Everglades (FCE) long-term sites in data packages knb-lter-fce.1169 and knb-lter-fce.1171, which contain data for SRS-5 and SRS-6, available in the FCE LTER website's data catalog or the EDI repository. FCE1268_Foliar_Nutrient_Content dataset, collected in August 2022, includes measurements of foliar nutrient content (total carbon, total nitrogen, and total phosphorus) for three mangrove species (A. germinans, L. racemosa, R. mangle) of two life stages—seedlings (height < 1 m) and saplings (height ≥ 1 m and Diameter at Breast Height (DBH) < 2.5 cm). FCE1268_Light contains light intensity (foot-candle) measurements taken at 1-hour intervals from 09-18-2020 to 08-29-2022 at mangrove sites and converted photosynthetic active radiation values from an outdoor mesocosm experiment. FCE1268_Sapling_Density provides biannual count measurements of individuals at the sapling plot level (4 m^-2) within each site from 07-09-2020 to 08-29-2022. FCE1268_Seedling_Density contains biannual count measurements of individuals at the seedling plot level (m^-2) within each site from 07-07-2020 to 08-29-2022. FCE1268_Sapling_Regeneration contains height, crown area, and stem elongation measurements of tagged sapling indiv
Root productivity of riverine and scrub mangroves from the Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, March 2024 - April 2024
Root productivity of riverine and scrub mangroves in the Florida Everglades: Mangrove root productivity in the shallow root zone (0-45 cm depth) was estimated at all Shark River (SRS-4, SRS-5, SRS-6, SRS-7) and Taylor River (TS/Ph-6, TS/Ph-7) sites in March-April 2024. Root productivity was estimated with the ingrowth core technique 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 as previously reported by Castañeda-Moya et al. (2011). Ingrowth cores were installed in holes made out with a PVC coring device (10.2 cm diameter x 45 cm length). At each site, 8 ingrowth cores were deployed vertically into the soil to a depth of 45 cm and retrieved one year later (March-April 2024). After collection, ingrowth cores were processed individually and initially rinsed with water through a 1-mm screen mesh to remove soil particles and peat moss material. Live roots were separated manually based on their buoyancy, turgor, and color (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. Root growth within each ingrowth core following one year of incubation was used to estimate annual root productivity (g m⁻² yr⁻¹) in the shallow root zone across all mangrove sites. All data collection and processing were funded by FCE-LTER. Data collection is complete. References: Castañeda-Moya, E., R.R. Twilley, V.H. Rivera-
Scrub Mangrove Annual Leaf Net Primary Production Data in Taylor River Slough, Florida Everglades, Florida, USA (FCE LTER): 2012-2021
Foliar Net Primary Productivity (NPPF) of monospecific Rhizophora mangle scrub mangroves (tree height <2.5m) was assessed using modified leaf-tagging techniques (direct count, ring tracking) in the lower Everglades Taylor Slough (FCE-LTER sites: TS/Ph6b and TS/Ph7b). Rings made with plastic zip ties were used to mark and track new and old leaves twice yearly (dry vs. wet season). During each sampling period, total old and new leaves were counted in previously selected branches in vegetated areas inside 20 x 20 m plots (replicates) in each site. Data collection is complete. This data set is analyzed and discussed in the publication Rivera-Monroy et al. Linking Scrub Mangroves Long-Term (2012-2021) Foliar Net Primary Productivity and Spatial Distribution in the Everglades (Florida, USA): A Leaf Tagging Approach
Root biomass, productivity, and turnover of riverine and scrub mangroves in the Everglades, Florida, USA, 2000-2006
Mangrove root biomass and productivity in the shallow (0-45 cm depth) and deeper (45-90 cm) root zones were estimated at Florida Coastal Everglades Long Term Ecological Research (FCE-LTER) Program Shark River (SRS4, SRS5, SRS6) and Taylor River (TS/Ph6b, TS/Ph7b, TS/Ph8) mangrove sites during 2000-2006. Root biomass was estimated at all sites using a PVC coring device (10.2 cm diameter x 45 cm length). After collection, root cores from each zone were processed individually and initially rinsed with water through a 1-mm screen mesh to remove soil particles. Live roots were separated manually based on their buoyancy, turgor, and color. 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 (g m-2). Root productivity was estimated with the ingrowth core technique (Vogt et al., 1998). 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 site, ingrowth cores were deployed vertically into the soil and retrieved at one- and three-year intervals, and the subsequent root growth within the ingrowth core was used to estimate annual root production (g m-2 yr-1) in the shallow and deeper root zones across all mangrove sites. After collection, ingrowth cores were processed individually using the same protocol as for root biomass. Root turnover rate in the shallow root zone was calculated as root productivity divided by root biomass of each root size class at all site
Mangrove soil biogeochemistry and geomorphology data from Biscayne National Park, Florida, USA, 2011 - 2024
We quantified long-term changes in tidal hydrology and surface soil elevation (2011-2024) across two representative fringe mangrove forest sites (BISC-1, BISC-2) in Biscayne National Park (Florida, USA). We measured the spatiotemporal variation of monthly wrack deposition, litter breakdown rates, soil organic carbon, and stable isotope δ13C and δ15N content along landward transects in Biscayne National Park (Florida, USA) from 2022 to 2024. We surveyed marine wrack deposition biovolume monthly using a quadrat in plots along our transects. At each marine wrack survey plot, we collected soil cores seasonally to measure soil physicochemistry. Finally, we deployed leaf litter decomposition mesh bags with Rhizophora mangle leaf litter, Thalassia testudinum leaf litter, and teabag standards to quantify breakdown rates on the soil surface of each marine wrack survey plot. Data collection is complete.
Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures
<p>To whom concerned,</p> <p>This dataset is the supplementary dataset for the publication in <em>Environmental Research Letters</em> entitled '<a href="https://dx.doi.org/10.1088/1748-9326/abc122"><em>Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures</em></a>' authored by Danghan Xie, et al. in 2020. The publication can be freely downloaded here: <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abc122">https://iopscience.iop.org/article/10.1088/1748-9326/abc122</a>. The dataset consists of both model results and corresponding codes that one can easily reproduce figures either in the manuscript or the supplementary document. </p> <p>To use the code, one needs to pre-install the Matlab (R2017a) and changes the pre-set route (in the code) to the directory where the dataset is stored. The figure shapes may vary with the size of the user's monitor so output figures may be either squeezed or extended in unpredictable ways, but the window size of the figure can be adjusted to match the shape and the results will not be affected.</p> <p>The author is appreciated that any potential concerns or questions regarding our research from any party or person, so please contact me through the email: <a href="mailto:d.xie@uu.nl">d.xie@uu.nl</a> or <a href="mailto:xiedanghan@gmail.com">xiedanghan@gmail.com</a>. To know more about my research, you can also follow the <a href="https://www.researchgate.net/profile/Danghan_Xie">ResearchGate</a>.</p> <p>With Kind Regards,</p> <p>Danghan</p> <p>11th of November, 2020</p>
Root phytohormone levels of mangrove seedlings grown in soils of low and high bulk density
<p>These data contain information on root traits and concentrations of multiple hormones in root tissue of two mangrove species grown under low and high soil bulk density conditions. Inhibitors were used to assess the role of the phytohormone ethylene.</p> <h2>Description of the data and file structure</h2> <p>The root trait file contains total root length (cm), mean root length (cm), root dry weight (g), and root number data for two mangrove species (Avicennia marina, Rhizophora stylosa) grown under two different soil bulk densities: 0.2 and 1.0 g cm^-3. Treatment refers to the application of ethylene inhibitors (CoCl2: cobalt chloride, AIB: aminoisobutyric acid, control).</p> <p>The phytohormone file contains the root tissue concentrations (all in ng g^-1) for multiple hormones (ABA: abscisic acid, ACC: 1-aminocyclopropane-1-carboxylic acid, GAx: gibberellins, IAA: indole-3-acetic acid, iP: isopentenyl adenine, JA: jasmonic acid, SA: salicylic acid, tZ: cytokinin <em>trans</em>-zeatin) of two mangrove species (Avicennia marina, Rhizophora stylosa) grown under two different soil bulk densities: 0.2 and 1.0 g cm^-3. Treatment refers to the application of ethylene inhibitors (CoCl2: cobalt chloride, AIB: aminoisobutyric acid, control).</p> <p> </p> <p> </p>
Mangrove terrestrial laser scanning (TLS) point clouds and quantitative structural models (QSMs)
<p>Datasets for a publication entitled, "Terrestrial laser scanning for the estimation of above ground biomass of mangrove roots by modelling them as inverted trees."</p> <p>See the file "Data dictionary for Mangrove terrestrial laser scanning.pdf" for a description of the datasets included in the zipped folder. </p>
Data from: Saltmarsh vegetation and secured woody debris facilitate mangrove re-colonization
<p>Does the presence of saltmarsh vegetation affect the long-term regeneration of the pioneer mangrove species <em>Avicennia germinans</em> in a degraded dwarf forest? Does immobilized coarse woody debris (CWD) affect regeneration similarly? Do larger trees suppress or facilitate intraspecific saplings? The study was conducted in a dwarf mangrove forest in the high intertidal zone on Bragança peninsula in northern Brazil. The spatial patterns of <em>A. germinans</em>, the herbaceous halophyte <em>Sesuvium portulacastrum</em>, and CWD were mapped in three sample plots (each 400 m<sup>2</sup>) during two consecutive vegetation surveys, conducted in 2011 and 2014. Inhomogeneous Poisson and Thomas point-process models were used to assess the distribution of <em>A. germinans</em> life-history stages (seedlings, saplings, and adult dwarf trees), conditioned on the presence of <em>S. portulacastrum</em> and CWD. In addition, intraspecific interactions between trees and regeneration were assessed based on crown projection mapping. Bivariate point pattern analyses were used to assess the dependence of advance regeneration on dwarf <em>A. germinans</em> trees and <em>S. portulacastrum</em>. <em>A. germinans</em> saplings and trees were positively associated with <em>S. portulacastrum</em> and CWD, whereas seedlings were located around tree crowns. The density of fruit-bearing trees was positively associated with sapling density, indicating that regeneration relied on locally dispersed propagules. Herbaceous vegetation and CWD have an important ecological function in degraded mangroves by retaining tidally dispersed propagules. Here, we show that herbaceous vegetation does not suppress the growth of seedlings but facilitates mangrove recolonization. Due to limited tidal dispersal, regeneration relies on local propagule supply. In addition to hydrological restoration, the observed vegetation patterns suggest that, in the absence of propagule-retaining vegetation, restoration of high-intertidal mangroves can be facilitated by establishing nuclei of planted trees and installing secured logs.</p>
Global Mangrove Watch: Annual Mangrove Extent
<p>To improve the resolution and local relevance of the Global Mangrove Watch (GMW) baseline, a new layer has been created for 2020. Using Copernicus Sentinel-2 satellite imagery, processed to a pixel resolution of 10 m, the mangrove extent has been completely remapped and revised with many areas which were not previously mapped now included within the new map. This has increased the spatial resolution of the mapping from a pixel resolution of 25 m to 10 m, allowing finer features to be mapped, such as fringing and riverine mangroves.</p> <p><span>Using the same pre-processed Sentinel-2 data as used for the ESA WorldCover 2020 map (Zanaga et al., 2021), over 30,000 machine learning models were trained to classify mangroves using over 5 million reference points for mangrove and non-mangrove classes. The reference points were generated using the existing CoastTrain reference dataset (Murray et al., 2022), sampling from the GMW v3.0 mangrove extent layers, user feedback and extensive quality assurance and refinement during the production of the classification. </span></p>
Mangroves in the lagoon of the protected Aldabra Atoll: a dataset on species, structure, biomass and the environment
<p>Mangroves are vital for climate change mitigation since they store vast quantities of carbon as biomass and in the soil. Global mangrove biomass estimates are derived from climate-based relationships of mangroves with precipitation and temperature. However, the carbon stored locally is highly variable depending on environmental conditions. This uncertainty highlights the importance of local mangrove surveys and the need to explore factors that regulate forest structure and, therefore, carbon storage. In this study, we investigate the mangrove forest structure, seedling growth, species composition, aboveground biomass, soil organic carbon, and local environmental factors related to variation in mangrove carbon in the lagoonal mangroves on the protected Aldabra Atoll, Seychelles. We present a database from an extensive field survey of Aldabra's mangrove ecosystem using 54 plots of 5 m x 5 m along a mangrove coverage gradient. From November 2019 to November 2020, we measured the structural attributes and identified six mangrove species from >750 adult mangrove trees on Aldabra. We used the height and diameter of adult trees to derive aboveground biomass and carbon from a tropical allometric equation. We measured the height of 59 mangrove seedlings over three sampling periods. In addition, environmental factors were recorded for each plot. We measured soil salinity repeatedly along the soil column. From 90 soil samples, we measured the physical and chemical properties of the soil, including soil organic carbon and elemental concentrations for >20 elements. Autonomous measures of the water level, temperature and conductivity were made every 10 minutes over 1 year in a subset of 36 plots. The database provides 60% more information that is currently available for Seychelles regarding mangrove forest structure and biomass and is essential for research on several globally threatened and endemic species that depend on the mangroves on Aldabra. Furthermore, the database allows the incorporation of data and insights for the Western Indian Ocean and lagoonal mangroves, where few studies have been conducted on mangrove aboveground biomass and soil organic carbon. No copyright restrictions apply to the use of this data set. Please cite this data paper when using the current data in publications.</p>
Mangrove Crab Sampling Data in Dongzhaigang National Nature Reserve, Haikou, Hainan Province, China
<p>This dataset contains the results of a study on mangrove crabs conducted in four seasons (Summer, SU; Autumn, AU; Winter, WI; Spring, SP) of 2020 and 2021. The samples were collected in the Dongzhaigang National Nature Reserve, Haikou, Hainan Province, China, at five sites: Sanjiang (SJ), Tashi (TS), Shanweitou (SWT), Luodou (LD), and Puqian (PQ). The primary focus is on crab species belonging to the superfamilies Ocypodoidea (ghost crabs), Grapsoidea (square crabs), and Portunoidea (swimming crabs).</p> <p>Sampling was conducted using net trapping, with three replicate plots set up for each habitat type at each site. Each plot was sampled continuously for three days. Vegetation information was recorded using dominant species as representatives, and water environmental information was collected using a WTW instrument. The parameters measured include total dissolved solids (TDS) (mg/L), dissolved oxygen (DO) (mg/L), salinity (SAL) (‰), water temperature (T) (℃), and pH. Finally, the longitude and latitude in the WGS84 coordinate system and Cartesian coordinates for each plot were recorded.</p> <p>The dataset fields are as follows:</p> <ul> <li>date: Date of sampling</li> <li>year: Year of sampling</li> <li>month: Month of sampling</li> <li>day: Day of sampling</li> <li>site: Sampling location, including TS, SJ, SWT, LD, PQ</li> <li>habitat: Habitat type, including tidal channels, tidal flats, and several vegetation types represented by mangrove trees such as Avicennia marina, Rhizophora stylosa, Bruguiera sexangular, Sonneratia apetala, and Ceriops tagal.</li> <li>plotname: Plot name</li> <li>species: Species name, as per the World Register of Marine Species (<a href="https://www.marinespecies.org/">https://www.marinespecies.org</a>)</li> <li>superfamily: Superfamily, as per the World Register of Marine Species (<a href="https://www.marinespecies.org/">https://www.marinespecies.org</a>)</li> <li>season: Season, including Summer (SU), Autumn (AU), Winter (WI), and Spring (SP)</li> <li>cname: Plot division by season, site, and habitat</li> <li>fullname: Plot division by season, site, habitat, and plot sequence number</li> <li>pname: Plot division by site, habitat, and plot sequence number</li> <li>TDS: Water total dissolved solids (mg/L)</li> <li>pH: Water pH</li> <li>DO: Water dissolved oxygen (mg/L)</li> <li>T: Water temperature (℃)</li> <li>SAL: Water salinity (‰)</li> <li>longitude: Longitude in WGS84 coordinate system</li> <li>latitude: Latitude in WGS84 coordinate system</li> <li>x: Cartesian coordinate x</li> <li>y: Cartesian coordinate y</li> </ul> <p>We thank Chengpu Jiang, Liangjun Wei and other colleagues for their assistance during the field samplings. Thanks also for the experimental conditions and sampling support provided by Hainan Dongzhaigang National Nature Reserve Authority.</p>
A global biophysical typology of mangroves version 3
<p>This dataset in an updated version of:</p> <p>Worthington, T. A. et al. A global biophysical typology of mangroves and its relevance for ecosystem structure and deforestation. Sci. Rep. 10, 14652 (2020)</p> <p>which delineates the world’s mangroves into geomorphic units based on their biophysical setting. Each unit consists of one or more patches of mangrove, grouped based on their proximity to macroscale coastal features, with these features determining their geomorphic class – deltaic, estuarine, lagoonal, and open coast.</p> <p> </p> <p>With the development of an updated mangrove extent timeseries (Global Mangrove Watch (GMW) v3.12), we updated the mangrove biophysical typology<sup>1</sup> to match this new extent. We firstly created an overlay between GMW v3.12 (all years combined to produce a 24-year composite extent) and the mangrove typology (v2.2) and identified those patches that were present in both. These patches were assigned to the same geomorphic class and individual geomorphic unit as the mangrove typology and provided the basis for the updated version. The patches present in the typology v2.2 but not in GMW v3.12 were deleted as they were no longer being mapped as mangrove in the GMW dataset.</p> <p> </p> <p>The patches now being mapped as mangrove in GMW v3.12 but had not been identified as such in the previous extent used to create the typology were then assigned to a geomorphic type and individual geomorphic unit using an iterative approach. Firstly, we identified patches that intersected with a single geomorphic unit and merged those patches to that unit, creating an enlarged unit extent. We repeated this procedure with the enlarged units, again enlarging their extent with patches only intersecting a single unit.</p> <p> </p> <p>We then used a series of distance buffers to identify unassigned patches that were within a certain distance of a single unit. After each step patches that were within the buffer distance of a single geomorphic unit were merged with that unit, and then the buffer was recalculated. The buffer distances were 1000m, 1000m, 1000m, 500m, 250m and 100m. Following the buffer, for the remaining unassigned patches we split them into those whose centroid was ≤ 10,000m from a geomorphic unit and those whose centroid was >10,000m for a geomorphic unit. As some of the patches were close (≤ 10,000m) from multiple geomorphic units, they were manually assessed and their assignment was corrected where necessary.</p> <p> </p> <p>The remaining patches (>10,000m from a geomorphic unit) were then visually assessed and can be split into three groups, 1) those part of large existing geomorphic units (only deltas, estuaries and lagoons) that were merged with that unit, 2) patches near deltas, estuaries and lagoons not mapped in the original GMW dataset, and 3) areas of open coast. The patches near deltas, estuaries and lagoons not mapped in the original GMW dataset resulted in the creation of 81 new geomorphic units. The open coast patches were aggregated into 268 clusters using a distance of 10,000m. Thirty-eight of the clusters were within 10,000m of an original open coast geomorphic unit and were merged with that unit. The remaining 230 were designated as new geomorphic units.</p> <p> </p> <p>We then undertook a process to merge open coast geomorphic units, by finding those small (<1km<sup>2</sup>) open coast geomorphic units that were within 10,000m of a larger one. Repeating the procedure to merge small open coast geomorphic units that were within 10,000m of another small open coast geomorphic unit. The final step was to do a visual assessment of all the units to remove errors. This was based around merging neighbouring geomorphic units of the same class if they represent the same system (e.g., one contiguous estuary or lagoon unit), assessed using high resolution imagery and the fluvial boundaries of the Hydrosheds basins<sup>2</sup>. Manually editing errors at unit boundaries where patches of one unit were surrounded by another unit. Splitting open coast units that overlapped another class of geomorphic unit e.g., an open coast unit with an estuary in the middle of it. Merging open coast units into large extents, particular those of the same section or aspect of the coast, using a distance of 10,000m as an approximate guide and trying not to create extents >100km<sup>2</sup>.</p> <p> </p> <p>A final publication version of the GMW dataset<sup>3</sup> (v3.14) was released <a href="https://zenodo.org/record/6894273">https://zenodo.org/record/6894273</a>, which differed slightly from v3.12. Firstly, a number of small areas of mangrove were removed at the edges of polygons, these were also removed from the typology. Secondly, additional areas of mangrove were mapped in the Persian Gulf, these new areas were merged with existing geomorphic units. These steps resulted in a final dataset ‘Mangrove Typology v3’ consisting of 3983 geomorphic units.</p> <p> </p> <p>1. Worthington, T. A. <em>et al.</em> A global biophysical typology of mangroves and its relevance for ecosystem structure and deforestation. <em>Sci. Rep.</em> <strong>10</strong>, 14652 (2020).</p> <p>2. Lehner, B. & Grill, G. Global river hydrography and network routing: Baseline data and new approaches to study the world’s large river systems. <em>Hydrol. Process.</em> <strong>27</strong>, 2171–2186 (2013).</p> <p>3. Bunting, P. <em>et al.</em> Global mangrove extent change 1996-2020: Global Mangrove Watch version 3.0. <em>Remote Sens.</em> <strong>14</strong>, 3657 (2022).</p> <p> </p>
A hurricane alters the relationship between mangrove cover and marine subsidies in Texas, USA: 2014-2019
We experimentally manipulated black mangrove (Avicennia germinans) cover in ten large plots and over five years (2014-2019) quantified the effects of mangrove cover on subsidies of floating organic material (wrack) into coastal wetlands. We hypothesized that the change from salt marsh to mangrove vegetation would alter the permeability of the intertidal habitat, and thus alter the nature of subsidies from marine to intertidal habitats. Data from field surveys of wrack distribution showed that as mangrove cover increased from zero to 100%, wrack cover and thickness decreased by ~60%, the distance that wrack penetrated into the plots decreased by ~70%, and the percentage of the wrack trapped in the first six m of the plot tripled. Data from wrack samples indicated that wrack samples collected from the fringe were ~3 times heavier than those from the interior of plots. Animals were ~40% more abundant in samples from the interior than from the fringe of plots, but this trend was not statistically significant due to low replication of interior samples. Data from a wrack experiment revealed that animal abundance and species composition varied between the fringe and interior of the plots, and between microhabitats dominated by salt marsh versus mangrove vegetation. Increasing mangrove cover decreased the relative importance of marine subsidies into the intertidal at the plot level, but concentrated subsidies at the front edge of the mangrove stand. Storms, however, may temporarily override mangrove attenuation of wrack inputs.
Stratified Vegetation Survey Data from an Experimental Mangrove Site in Port Aransas, Texas: 2019
We visually surveyed the vegetation at the front and back of ten large experimental plots located in a large stand of mangroves near Port Aransas, Texas on November 28th, 2019. The ten experimental plots had been thinned using a 3 x 3 m grid in 2012 to create a gradient in plot-level mangrove cover from 0 to 100 percent. We estimated percent cover in six “mangrove” and six “cleared” cells at the front and back of each plot.
Patterns of root biomass, productivity, and turnover in riverine and scrub mangroves post-Hurricane Wilma in the Everglades, Florida, USA, 2012-2013
Mangrove root biomass, productivity, and turnover 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) and Taylor River (TS/Ph6b, TS/Ph7b) mangrove sites during 2012-2013 following Hurricane Wilma’s impacts in October 2005. Root biomass was estimated at all sites in May 2012 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. Live roots were separated manually based on their buoyancy, turgor, and color (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 (g m-2). Root productivity was estimated with the ingrowth core technique (Vogt et al., 1998) 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 site, ingrowth cores were deployed vertically into the soil to a depth of 45 cm and retrieved one year later (June 2013). Root growth within the ingrowth core was used to estimate annual root production (g m-2 yr-1) in
FIG. 1 in Beyond shells: first detailed morphological description of the mangrove-associated gastropod Haminoea cf. fusca (A. Adams, 1850) (Cephalaspidea, Haminoeidae), with a COI phylogenetic analysis
FIG. 1. — Bayesian phylogenetic tree based on partial sequences of the COI gene. Figures on nodes are posterior probabilities, scale bar refer to branch lengths. Coloured squares refer to species that are Indo West Pacific in origin, whereas grey squares to Atlantic and eastern Pacific species. PP, 1. The specimen here used from the Philippines is depicted in Gosliner et al. 2015: 30, lower right.
Effects of tidal influence on the structure and function of prokaryotic communities in the sediments of a pristine Brazilian mangrove
<p>Mangrove forests are ecosystems that constitute a large portion of the world's coastline and span tidal zones below, between, and above the waterline, while the ecosystem as a whole is defined by the health of these tidal microhabitats. However, we are only beginning to understand tidal zone microbial biodiversity and the role of these microbiomes in nutrient cycling. While extensive research has characterized microbiomes in pristine versus anthropogenically impacted mangroves these have, largely, overlooked differences in tidal microhabitats (sublittoral, intertidal, and supralittoral). Unfortunately, the small number of studies that have sought to characterize mangrove tidal zones have occurred in impacted biomes, making interpretation of the results difficult. Here, we characterized prokaryotic populations and their involvement in nutrient cycling across the tidal zones of a pristine mangrove within a Brazilian Environmental Protection Area of the Atlantic Forest. We hypothesized that the tidal zones in pristine mangroves are distinct microhabitats, which we defined as distinct regions that present spatial variations in the water regime and other environmental factors, and as such, these are composed of different prokaryotic communities with distinct functional profiles. Samples were collected in triplicate from zones below, between, and above the tidal waterline. Using 16S rRNA gene amplicon sequencing, we found distinct prokaryotic communities with significantly diverse nutrient cycling functions, as well as specific taxa with varying contribution to functional abundances between zones. Where previous research from anthropogenically impacted mangroves found the intertidal zone to have high prokaryotic diversity and functionally enriched in nitrogen cycling, we find that the intertidal zone from pristine mangroves have the lowest diversity and no functional enrichment, relative to the other tidal zones. The main bacterial phyla in all samples were Firmicutes, Proteobacteria and Chloroflexi while the main archaeal phyla were Crenarchaeota and Thaumarchaeota. Our results differ slightly from other studies where Proteobacteria is the main phyla in mangrove sediments and Firmicutes make up for only a small percentage of the communities. Salinity and organic matter were the most relevant environmental factors influencing these communities. Bacillaceae was the most abundant family at each tidal zone and showed potential to drive a large proportion of the cycling of carbon, nitrogen, phosphorus and sulfur. Our findings suggest that some aspects of mangrove tidal zonation may be compromised by human activity, especially in the intertidal zone.</p>
An Excel spreadsheet including eddy covariance, meteorological, and tidal data measured at Yunxiao mangrove flux tower.
<p>An Excel spreadsheet including eddy covariance, meteorological, and tidal data at Yunxiao mangrove flux tower required to reproduce key findings in Figures 4-9 in the main text (each figure corresponds to a single sheet). Contact Xudong Zhu at Xiamen University (xdzhu@xmu.edu.cn) if you have any question.</p>
Figs. 1-3. Hebrus murphyi, new species. 1 in Hebrus Murphyi, New Species (Heteroptera: Hebridae) From An Intertidal Mangrove Habitat In Burias Island, Philippines
Figs. 1-3. Hebrus murphyi, new species. 1. Habitus of male, dorsal aspect. 2. Head, lateral aspect. 3. Left paramere of male, lateral aspect.
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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
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