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Monthly aggregated GLASS FAPAR V6 (250 m): 50th percentile monthly time-series (2007)
<p><strong>List of Subdatasets:</strong></p> <ul> <li>Long-term data: <a href="https://doi.org/10.5281/zenodo.8381409">2000-2021</a></li> <li>5th percentile (p05) monthly time-series: <a href="https://doi.org/10.5281/zenodo.8408654">2000</a>, <a href="https://doi.org/10.5281/zenodo.8411611">2001</a>, <a href="https://doi.org/10.5281/zenodo.8412712">2002</a>, <a href="https://doi.org/10.5281/zenodo.8413021">2003</a>, <a href="https://doi.org/10.5281/zenodo.8413689">2004</a>, <a href="https://doi.org/10.5281/zenodo.8414639">2005</a>, <a href="https://doi.org/10.5281/zenodo.8411609">2006</a>, <a href="https://doi.org/10.5281/zenodo.8414085">2007</a>, <a href="https://doi.org/10.5281/zenodo.8414960">2008</a>, <a href="https://doi.org/10.5281/zenodo.8415476">2009</a>, <a href="https://doi.org/10.5281/zenodo.8415686">2010</a>, <a href="https://doi.org/10.5281/zenodo.8412154">2011</a>, <a href="https://doi.org/10.5281/zenodo.8414082">2012</a>, <a href="https://doi.org/10.5281/zenodo.8411364">2013</a>, <a href="https://doi.org/10.5281/zenodo.8414933">2014</a>, <a href="https://doi.org/10.5281/zenodo.8415414">2015</a>, <a href="https://doi.org/10.5281/zenodo.8412246">2016</a>, <a href="https://doi.org/10.5281/zenodo.8414083">2017</a>, <a href="https://doi.org/10.5281/zenodo.8411366">2018</a>, <a href="https://doi.org/10.5281/zenodo.8415203">2019</a>, <a href="https://doi.org/10.5281/zenodo.8415549">2020</a>, <a href="https://doi.org/10.5281/zenodo.8387608">2021</a></li> <li>50th percentile (p50) monthly time-series: <a href="https://doi.org/10.5281/zenodo.8408710">2000</a>, <a href="https://doi.org/10.5281/zenodo.8408798">2001</a>, <a href="https://doi.org/10.5281/zenodo.8408866">2002</a>, <a href="https://doi.org/10.5281/zenodo.8415319">2003</a>, <a href="https://doi.org/10.5281/zenodo.8415619">2004</a>, <a href="https://doi.org/10.5281/zenodo.8415878">2005</a>, <a href="https://doi.org/10.5281/zenodo.8416080">2006</a>, <a href="https://doi.org/10.5281/zenodo.8416619">2007</a>, <a href="https://doi.org/10.5281/zenodo.8417164">2008</a>, <a href="https://doi.org/10.5281/zenodo.8417513">2009</a>, <a href="https://doi.org/10.5281/zenodo.8417708">2010</a>, <a href="https://doi.org/10.5281/zenodo.8415669">2011</a>, <a href="https://doi.org/10.5281/zenodo.8416000">2012</a>, <a href="https://doi.org/10.5281/zenodo.8416542">2013</a>, <a href="https://doi.org/10.5281/zenodo.8417055">2014</a>, <a href="https://doi.org/10.5281/zenodo.8417467">2015</a>, <a href="https://doi.org/10.5281/zenodo.8415747">2016</a>, <a href="https://doi.org/10.5281/zenodo.8416333">2017</a>, <a href="https://doi.org/10.5281/zenodo.8416835">2018</a>, <a href="https://doi.org/10.5281/zenodo.8417326">2019</a>, <a href="https://doi.org/10.5281/zenodo.8417589">2020</a>, <a href="https://doi.org/10.5281/zenodo.8388078">2021</a></li> <li>95th percentile (p95) monthly time-series: <a href="https://doi.org/10.5281/zenodo.8408949">2000</a>, <a href="https://doi.org/10.5281/zenodo.8409059">2001</a>, <a href="https://doi.org/10.5281/zenodo.8409154">2002</a>, <a href="https://doi.org/10.5281/zenodo.8409362">2003</a>, <a href="https://doi.org/10.5281/zenodo.8416487">2004</a>, <a href="https://doi.org/10.5281/zenodo.8417029">2005</a>, <a href="https://doi.org/10.5281/zenodo.8417833">2006</a>, <a href="https://doi.org/10.5281/zenodo.8417996">2007</a>, <a href="https://doi.org/10.5281/zenodo.8418308">2008</a>, <a href="https://doi.org/10.5281/zenodo.8418669">2009</a>, <a href="https://doi.org/10.5281/zenodo.8418986">2010</a>, <a href="https://doi.org/10.5281/zenodo.8417649">2011</a>, <a href="https://doi.org/10.5281/zenodo.8417816">2012</a>, <a href="https://doi.org/10.5281/zenodo.8417959">2013</a>, <a href="https://doi.org/10.5281/zenodo.8418253">2014</a>, <a href="https://doi.org/10.5281/zenodo.8418625">2015</a>, <a href="https://doi.org/10.5281/zenodo.8417759">2016</a>, <a href="https://doi.org/10.5281/zenodo.8417898">2017</a>, <a href="https://doi.org/10.5281/zenodo.8418076">2018</a>, <a href="https://doi.org/10.5281/zenodo.8418442">2019</a>, <a href="https://doi.org/10.5281/zenodo.8418751">2020</a>, <a href="https://doi.org/10.5281/zenodo.8392976">2021</a></li> </ul> <p><strong>General Description</strong></p> <p>The <i>monthly aggregated Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</i> dataset is derived from <abbr title="glass.umd.edu/FAPAR/MODIS/250m/">250m 8d GLASS V6 FAPAR</abbr>. The data set is derived from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and LAI data using several other FAPAR products (MODIS Collection 6, GLASS FAPAR V5, and PROBA-V1 FAPAR) to generate a bidirectional long-short-term memory (Bi-LSTM) model to estimate FAPAR. The dataset time spans from March 2000 to December 2021 and provides data that covers the entire globe. The dataset can be used in many applications like land degradation modeling, land productivity mapping, and land potential mapping. The dataset includes:</p> <ul> <li><strong>Long-term:</strong></li> </ul> <p>Derived from monthly time-series. This dataset provides linear trend model for the p95 variable: (1) slope beta mean (p95.beta_m), p-value for beta (p95.beta_pv), intercept alpha mean (p95.alpha_m), p-value for alpha (p95.alpha_pv), and coefficient of determination R<sup>2</sup> (p95.r2_m).</p> <ul> <li><strong>Monthly time-series:</strong></li> </ul> <p>Monthly aggregation with three standard statistics: (1) 5th percentile (p05), median (p50), and 95th percentile (p95). For each month, we aggregate all composites within that month plus one composite each before and after, ending up with 5 to 6 composites for a single month depending on the number of images within that month.</p> <p><strong>Data Details</strong></p> <ul> <li><strong>Time period:</strong> March 2000 – December 2021</li> <li><strong>Type of data:</strong> Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)</li> <li><strong>How the data was collected or derived:</strong> Derived from 250m 8 d GLASS V6 FAPAR using Python running in a local HPC. The time-series analysis were computed using the <a href="https://github.com/scikit-map/scikit-map">Scikit-map</a> Python package.</li> <li><strong>Statistical methods used:</strong> for the long-term, Ordinary Least Square (OLS) of p95 monthly variable; for the monthly time-series, percentiles 05, 50, and 95.</li> <li><strong>Limitations or exclusions in the data:</strong> The dataset does not include data for Antarctica.</li> <li><strong>Coordinate reference system:</strong> EPSG:4326</li> <li><strong>Bounding box (Xmin, Ymin, Xmax, Ymax):</strong> (-180.00000, -62.0008094, 179.9999424, 87.37000)</li> <li><strong>Spatial resolution:</strong> 1/480 d.d. = 0.00208333 (250m)</li> <li><strong>Image size:</strong> 172,800 x 71,698</li> <li><strong>File format:</strong> Cloud Optimized Geotiff (COG) format.</li> </ul> <p><strong>Support</strong></p> <p>If you discover a bug, artifact, or inconsistency, or if you have a question please raise a GitHub issue: <a href="https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues">https://github.com/Open-Earth-Monitor/Global_FAPAR_250m/issues</a></p> <p><strong>Reference</strong></p> <p>Hackländer, J., Parente, L., Ho, Y.-F., Hengl, T., Simoes, R., Consoli, D., Şahin, M., Tian, X., Herold, M., Jung, M., Duveiller, G., Weynants, M., Wheeler, I., (2023?) "Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution", submitted to PeerJ, preprint available at: <a href="https://doi.org/10.21203/rs.3.rs-3415685/v1">https://doi.org/10.21203/rs.3.rs-3415685/v1</a></p> <p><strong>Name convention</strong></p> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:</p> <ol> <li><strong>generic variable name:</strong> fapar = Fraction of Absorbed Photosynthetically Active Radiation</li> <li><strong>variable procedure combination:</strong> essd.lstm = Earth System Science Data with bidirectional long short-term memory (Bi–LSTM)</li> <li><strong>Position in the probability distribution / variable type:</strong> p05/p50/p95 = 5th/50th/95th percentile</li> <li><strong>Spatial support:</strong> 250m</li> <li><strong>Depth reference:</strong> s = surface</li> <li><strong>Time reference begin time:</strong> 20000301 = 2000-03-01</li> <li><strong>Time reference end time:</strong> 20211231 = 2022-12-31</li> <li><strong>Bounding box:</strong> go = global (without Antarctica)</li> <li><strong>EPSG code:</strong> epsg.4326 = EPSG:4326</li> <li><strong>Version code:</strong> v20230628 = 2023-06-28 (creation date)</li> </ol>
Species cover, community biomass, and richness in global grasslands from NutNet (2007–2023): Dominant species predict plant richness and biomass in global grasslands
The Nutrient Network (NutNet) is a globally coordinated research initiative designed to investigate the impacts of human-driven alterations in nutrient availability and consumer presence on grassland ecosystems. Data were collected from over 130 herbaceous-dominated sites worldwide, spanning diverse environmental conditions from desert grasslands to arctic tundra. Standardized methodologies were employed across all sites to enable direct comparisons of productivity, diversity, and ecosystem responses. Experimental treatments included nutrient additions to assess co-limitation of plant growth by multiple nutrients, as well as grazer manipulations to examine their role in regulating biomass, species diversity, and community composition. By compiling these cross-site data, NutNet aims to enhance our understanding of productivity-diversity relationships and provide new insights into the ecological consequences of anthropogenic changes to nutrient cycles and food webs at a global scale.
Insights on global rangeland ecosystem services shaped by grazing and fertilization (2007-2021)
The Nutrient Network (NutNet) is a globally coordinated research initiative aimed at investigating the impacts of human-induced changes in nutrient availability and consumer presence on grassland ecosystems. In this study, we used data from 79 grassland sites participating in NutNet, which includes a factorial experiment involving herbivory exclusion and/or nutrient addition. Standardized methodologies were applied across all sites to facilitate direct comparisons of response variables. We used ecosystem variables to quantify three provisioning ecosystem services (forage quantity, forage chemical quality, and forage physical quality), three supporting services (forage stability, soil fertility, and soil stability), and eight regulating services (erosion control, control of soil acidification, regulation of water quantity and quality, carbon storage, resistance to plant invasion, pest control, and pollination). Additionally, we identified three plant biodiversity variables that are closely related to the provisioning of ecosystem services (alpha richness, beta diversity, and native diversity). Using this data, we quantified key ecosystem services provided by rangelands, assessed both short- and long-term impacts of grazing exclusion and fertilization on these services, and identified synergies and trade-offs between them.
Survey of Alarka Laurel and Rich Mountain Red Spruce (Picea rubens) Overstory, Saplings, and Seedlings in western North Carolina in 2007, 2022, and 2023
In the southern Appalachians, disjunct red spruce (Picea rubens) populations persist at low latitudes at elevations above 1,370 m. However, research on the condition of these disjunct red spruce populations is limited. This study compared baseline health, recruitment, and stand dynamics of two of the southern-most red spruce populations in eastern North America, the Rich Mountain and Alarka Laurel spruce bog basins in Nantahala National Forest, North Carolina. We collected data on overstory (DBH>10 cm), saplings (DBH< 10 cm, and height >2 m), and seedlings (height<10 cm) from Alarka Laurel in 2007 and 2022. Data from Rich Mountain were collected in 2023. We used 10-m wide belt transects noted the species and diameter at breast height (DBH) of overstory species, counted and noted the DBH of red spruce saplings, and counted and noted the height of red spruce seedlings. In 2022 and 2023, we gave a health score from 0-3 for all three categories of trees (overstory, saplings, and seedlings), with 0 being dead and 3 being healthy with little to no signs of disease or stress. Overall, both stands did not yet appear affected by climatic warming, despite the southern latitude and relatively low elevation. Our findings reveal that red spruce is the dominant overstory species, comprising an average of 25.6% of all measured overstory trees, with seedlings and saplings making up 72.8% of the red spruce population, indicating sustainable recruitment. Red spruce basal area declined by 13.9% from 2007 to 2022 in Alarka Laurel, with a concomitant increase in some hardwood species. However, both Alarka Laurel and Rich Mountain showed high levels of sapling and seedling recruitment. Overall, red spruce trees are healthy, particularly seedlings, representing the healthiest age category. Our results suggest the stands are relatively stable and provide essential baseline data for monitoring of forest conditions in the context of intensifying climate change. This research contributes to b
Vegetation indices calculated from reflectance spectra collected at LTER plots at Toolik Lake, Alaska during the 2007-2019 growing seasons.
Vegetation indices calculated from reflectance spectra collected at Arctic LTER experimental plots at Toolik Lake, Alaska during the 2007-2019 growing seasons. Long term experimental plots span several different vegetation types: Heath (HTH89), Moist Acidic Tussock (MAT89 and Low Fert), Moist Non-Acidic Tussock (MNAT), Non-Acidic Non-Tussock (NANT), Shrub (SHB), and Wet Sedge (WSG). Plots are differentiated by their experimental treatment and are located in replicate blocks.Canopy reflectance is measured by hand-held spectrophotometer and several indices of interest (NDVI, EVI, EVI2, PRI, WBI, and Chlorophyll index) are calculated.
Eddy Flux Measurements, Tussock Station, Imnavait Creek, Alaska - 2007
The Biocomplexity Station was established in 2005 to measure landscape-level carbon, water and energy balances at Imnavait Creek, Alaska. The station is now contributing valuable data to the Arctic Observing Network that was established at two nearby stations. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. We will provide a comprehensive description of the state of the regional Arctic system with respect to these variables, its overall regulation and controlling features and its interaction with the global system.
Eddy Flux Measurements, Fen Station, Imnavait Creek, Alaska - 2007
In contribution to the Arctic Observing Network, the researchers have established two observatories of landscape-level carbon, water and energy balances at Imnaviat Creek, Alaska and at Pleistocene Park near Cherskii, Russia. These will form part of a network of observatories with Abisko (Sweden), Zackenburg (Greenland) and a location in the Canadian High Arctic which will provide further data points as part of the International Polar Year. This particular part of the project focuses on simultaneous measurements of carbon, water and energy fluxes of the terrestrial landscape at hourly, daily, seasonal and multi-year time scales. These are the major regulatory drivers of the Arctic climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. We will provide a comprehensive description of the state of the regional Arctic system with respect to these variables, its overall regulation and controlling features and its interaction with the global system. In support of these objectives, a 3m eddy covariance station was established on Imnaviat Creek, Alaska. This station has been continuously monitoring carbon dioxide, water vapor, energy fluxes and various micro-meteorological variables.
Soil nutrient availability from the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016 growing season
This file contains plant-available nitrate (NO3), ammonium (NH4), and phosphate (PO4) in the upper 5-10 cm of organic matter from a burned and unburned site in the southern section of the 2007 Anaktuvuk River fire in northern Alaska. Soil nutrients were assessed using ion-exchange resin membranes incubated in the soil during the growing season of 2016.
Point-frame measurments from a nitrogen (N), phosphorus (P) and N+P fertilization experiment at the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016-2019 growing seasons
This file contains point-frame measurements from a nitrogen (N), phosphorus (P) and N+P fertilization experiment established in the southern section of the 2007 Anaktuvuk River fire in 2016 at a severely burned site and an unburned site. Pin-vegetation contact was recorded using a 0.75 m2 frame with 41 evenly spaced pin-drop points. Data was collected once during the height of the growing season in 2016 (when fertilization began) 2017, 2018 and 2019. This data was used to measure the impact of fertilization and fire on community composition.
Soil nutrient availability from the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2019 growing season
This file contains plant-available nitrate (NO3), ammonium (NH4), phosphate (PO4), and total free primary amines (TFPA )in the upper 5-10cm of organic matter from a burned and unburned site in the southern section of the 2007 Anaktuvuk River fire in northern Alaska. Soil nutrients were assessed using buried resin bags which incubated for 1 month during the peak of the growing season in 2019.
Leaf area index (LAI) recorded from a nitrogen (N), phosphorus (P) and N+P fertilization experiment at the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016-2019 growing seasons
This file contains leaf area index (LAI) measurements from an nitrogen (N), phosphorus (P) and N+P fertilization experiment established in the southern section of the 2007 Anaktuvuk River fire in 2016. LAI was recorded using a handheld plant canopy analyzer (LI-COR 2200C; LI-COR, Lincoln, NE, USA) Data spans 4 years from 2016 (when fertilization began) until 2019. Data was recorded once a year at the peak of each growing season.
Point-frame measurement of maximum canopy height for plant growth forms at the 2007 Anaktuvuk River Fire scar measured in 2019.
This file contains maximum plant heights from point frame measurements made in the southern section of the 2007 Anaktuvuk River fire scar, at a severely burned site and a nearby unburned site. Pin-vegetation contact was recorded using a 0.56 m2 frame with 41 evenly spaced sampling points. Data were collected during peak green in summer 2019. These data were used to examine the impact of post-fire changes in plant community composition and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tussock tundra.
Small mammal captures per 100 trap nights at the 2007 Anaktuvuk River fire scar and nearby unburned site, sampled in 2014, 2017-2019.
Small mammals (rodents and shrews) were sampled 7-12 years following the Anaktuvuk River Fire to examine how post-fire ecological changes influence small mammal abundance. Small mammals were snap-trapped in August 2014, 2017-2019 at the site of the 2007 Anaktuvuk River Fire, and a nearby unburned control site. At each site, 120 traps were set in 3 parallel lines spaced 40m apart. Each trap was spaced 10m apart, baited, and set to rodent sign within one meter of the trap station. Traps were checked the following two mornings with all captures collected and sprung traps reset. Abundance estimates (captures per 100 trap nights) are presented for tundra voles (Microtus oeconomus), red-backed voles (Myodes rutilus) and shrews (Sorex spp.) The goals of the project were to examine the impact of post-fire changes in plant community composition and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tundra.
Eriophorum vaginatum tiller nitrogen content at the 2007 Anaktuvuk River fire scar and nearby unburned tundra measured in 2019.
Tillers from 24 Eriophorum vaginatum individuals were sampled in late July 2019 to examine differences in percent nitrogen between previously burned (Anaktuvuk River Fire) and unburned tussocks at a nearby unburned control site. At the burned site tussocks exhibiting evidence of rodent grazing were also sampled to separate herbivore effects from those of the fire. From each tussock, 3-4 new leaves were sampled (as indicated by lack of brown tips) and dried at 60°C for 24 hours, before being ground and analyzed for percent nitrogen. The goals of the project were to examine the impact of post-fire changes in plant community composition, nutrient quality and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tundra.
Rainfall Stable Isotopes collected at Florida International University-MMC (FCE LTER), Miami, Florida, USA, October 2007 - ongoing
δ18O and δ2H values for precipitation collected at the Modesto A. Maidique Campus of Florida International University (FIU) relative to Vienna Standard Mean Ocean Water. Rainfall was collected from the roof of AHC-1 building (25.75772 ºN, 80.37108 ºW) from October 2007 to November 2022 using an Aerochemitrics wet/dry collector. Since December 2022, rainfall has been collected using a Palmex Rain Collector located in the FIU Organic Garden (25.75490 ºN, 80.37985 ºW). Oxygen and hydrogen isotope ratios were measured on a Los Gatos Research DLT-100 Liquid-Water Isotope Analyzer in the Hydrogeology laboratory at FIU since the project inception.
Environmental data from FCE LTER Caribbean Karstic Region (CKR) study in Yucatan, Belize and Jamaica during Years 2006, 2007 and 2008
Several studies have shown that within the Florida Coastal Everglades, periphyton mat properties, (incuding biomass, nutrient and organic content, and community composition) vary predictably in response to water quality.The Florida Coastal Everglades (FCE) wetland system is very similar with respect to climate, geology, hydrology and vegetation, to wetlands found in Jamaica, the Yucatan region of Mexico and parts of Belize. This study was therefore conducted to ascertain (i) the level of similarity between the periphyton diatom communities from karstic wetland sites in Belize, Mexico, Jamaica and comparable sites within the FCE, (ii) the relationship between periphyton biomass, TP levels and diatom community composition at these sites, and (iii) the feasibility of employing diatoms as indicators of water quality at these sites, using models relating diatom community composition to water quality from comparable sites within the FCE. Multiple wetland sites in Jamaica, the Yucatan region of Mexico and parts of Belize were visited between 2006 and 2008, during wet and dry seasons. At each site physico-chemical data were collected along with periphyton samples. The periphyton samples were processed in accordance with standard methods to obtain biomass, organic content and TP measures, and to identify and enumerate diatom and soft algae species. Various aspects of the diatom communities were then compared to previously compiled data on diatom communities from various parts of the FCE. SIMI analysis was used to determine the level of similarity between the systems and Non-Metric Multidimensional Scaling was used to identify relationships between diatom communities and water quality.
Diatom Species Abundance Data from LTER Caribbean Karstic Region (CKR) study (FCE) in Yucatan, Belize and Jamaica during 2006, 2007, 2008
Several studies have shown that within the Florida Coastal Everglades, periphyton mat properties, (incuding biomass, nutrient and organic content, and community composition) vary predictably in response to water quality.The Florida Coastal Everglades (FCE) wetland system is very similar with respect to climate, geology, hydrology and vegetation, to wetlands found in Jamaica, the Yucatan region of Mexico and parts of Belize. This study was therefore conducted to ascertain (i) the level of similarity between the periphyton diatom communities from karstic wetland sites in Belize, Mexico, Jamaica and comparable sites within the FCE, (ii) the relationship between periphyton biomass, TP levels and diatom community composition at these sites, and (iii) the feasibility of employing diatoms as indicators of water quality at these sites, using models relating diatom community composition to water quality from comparable sites within the FCE. Multiple wetland sites in Jamaica, the Yucatan region of Mexico and parts of Belize were visited between 2006 and 2008, during wet and dry seasons. At each site physico-chemical data were collected along with periphyton samples. The periphyton samples were processed in accordance with standard methods to obtain biomass, organic content and TP measures, and to identify and enumerate diatom and soft algae species. Various aspects of the diatom communities were then compared to previously compiled data on diatom communities from various parts of the FCE. SIMI analysis was used to determine the level of similarity between the systems and Non-Metric Multidimensional Scaling was used to identify relationships between diatom communities and water quality.
Periphyton data from LTER Caribbean Karstic Region (CKR) study in Yucatan, Belize and Jamaica (FCE LTER) during 2006, 2007, 2008
Several studies have shown that within the Florida Coastal Everglades, periphyton mat properties, (incuding biomass, nutrient and organic content, and community composition) vary predictably in response to water quality.The Florida Coastal Everglades (FCE) wetland system is very similar with respect to climate, geology, hydrology and vegetation, to wetlands found in Jamaica, the Yucatan region of Mexico and parts of Belize. This study was therefore conducted to ascertain (i) the level of similarity between the periphyton diatom communities from karstic wetland sites in Belize, Mexico, Jamaica and comparable sites within the FCE, (ii) the relationship between periphyton biomass, TP levels and diatom community composition at these sites, and (iii) the feasibility of employing diatoms as indicators of water quality at these sites, using models relating diatom community composition to water quality from comparable sites within the FCE. Multiple wetland sites in Jamaica, the Yucatan region of Mexico and parts of Belize were visited between 2006 and 2008, during wet and dry seasons. At each site physico-chemical data were collected along with periphyton samples. The periphyton samples were processed in accordance with standard methods to obtain biomass, organic content and TP measures, and to identify and enumerate diatom and soft algae species. Various aspects of the diatom communities were then compared to previously compiled data on diatom communities from various parts of the FCE. SIMI analysis was used to determine the level of similarity between the systems and Non-Metric Multidimensional Scaling was used to identify relationships between diatom communities and water quality.
Biomarker assessment of spatial and temporal changes in the composition of flocculent material (floc) in the subtropical wetland of the Florida Coastal Everglades (FCE) from May 2007 to December 2009
Flocculent material (floc) is an important energy source in wetlands. In the Florida Everglades, floc is present in both freshwater marshes and coastal environments and plays a key role in food webs and nutrient cycling. However, not much is known about its environmental dynamics, in particular its biological sources and bio-reactivity. We analysed floc samples collected from different environments in the Florida Everglades and applied biomarkers and pigment chemotaxonomy to identify spatial and seasonal differences in organic matter sources. An attempt was made to link floc composition with algal and plant productivity. Spatial differences were observed between freshwater marsh and estuarine floc. Freshwater floc receives organic matter inputs from local periphyton mats, as indicated by microbial biomarkers and chlorophyll-a estimates. At the estuarine sites, the floc is dominated by mangrove as well as diatom inputs from the marine end-member. The hydroperiod (duration and depth of inundation) at the freshwater sites influences floc organic matter preservation, where the floc at the short-hydroperiod site is more oxidised likely due to periodic dry-down conditions. Seasonal differences in floc composition were not consistent and the few that were observed are likely linked to the primary productivity of the dominant biomass (periphyton in the freshwater marshes and mangroves in the estuarine zone). Molecular evidence for hydrological transport of floc material from the freshwater marshes to the coastal fringe was also observed. With the on-going restoration of the Florida Everglades, it is important to gain a better understanding of the biogeochemical dynamics of floc, including its sources, transformations and reactivity.
Fall 2007 plant monitoring survey -- shoot height and flowering status of plants in permanent plots at GCE sampling sites 1-10
A quadrat survey was conducted in October 2007 to measure the species and size distribution of plants at 10 GCE LTER sampling sites. The quadrats were established as permanent plots at GCE sampling sites in October 2000 by placing wooden stakes at random locations across two nominal zones at each site, designated based on marsh structure (creekbank and high marsh). Several new plots were also added in October 2001, 2002, 2003 and 2004 to replace those lost due to catastrophic wrack disturbance or creek bank erosion. The plots were visually surveyed and the species, shoot height, and flowering status was recorded individually for each shoot over 10 cm in height present in each plot. Observations from plots exhibiting signs of disturbance were noted in the data set with additional details recorded in GCE data set PLT-GCEM-1801. This survey will be repeated annually to assess changes in plant distribution and biomass in relation to environmental changes documented by other GCE LTER monitoring efforts.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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
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.