Find research datasets worth reusing

openCC0Sep 2024View details →

Seasonal and annual vegetation surveys of wetlands along the Salt River in and near the greater metropolitan area of Phoenix, Arizona

The Salt River Biodiversity Project collects vegetation data in several urban wetlands across the Phoenix area (Arizona) along the historic channel of the Salt River. This study, along with bird and reptile monitoring (Bateman and Childers 2022, Bateman and Warren 2022), began in 2012. These biodiversity monitoring initiatives help understand how community composition, biodiversity, and ecosystem structure are changing as a result of pressures such as urbanization, climate change, and land management decisions. This dataset contains vegetation assessments from 2012 as well as a reassessment ten years later (2022 and 2023). Bateman, H. and D. Childers. 2022. Long-term monitoring of herpetofauna along the Salt and Gila Rivers in and near the greater Phoenix metropolitan area, ongoing since 2012 ver 8. Environmental Data Initiative. <https://doi.org/10.6073/pasta/3cc81cce91185cdeeded320c4a3528df> Accessed 2024-09-11. Bateman, H. and P. Warren. 2022. Point-count bird censusing: long-term monitoring of bird abundance and diversity along the Salt River in the greater Phoenix metropolitan area, ongoing since 2013 ver 8. Environmental Data Initiative. <https://doi.org/10.6073/pasta/070c0bec46e1336684c534f9a4034334> Accessed 2024-09-11.

openCC (other)Feb 2024View details →

Examination of protein-like fluorophores in chromophoric dissolved organic matter (CDOM) in a wetland and coastal environment for the wet and dry seasons of the years 2002 and 2003 (FCE)

Water samples are collected at the end of the dry and the wet season from all LTER sites and stored on ice until return to the lab. They are pre-filtered through pre-combusted GF/F filters and ultrafiltered and concentrated with a Pellicon 2 Mini tangential flow ultrafiltration system.Concentrated samples were then analyzed using fluorescence and SEC-HPLC. This CDOM optical study revealed the presence of two classes of compounds associated with the protein-like peak (peak T; excitation/emission (Ex/Em) maxima at around 280 nm/325 nm), which have very different chemical structures and ecological roles. In addition to proteins, we propose phenolic compounds as possible origins of peak T in coastal and wetland environments. In this study, natural water samples were obtained from subtropical rivers and estuarine environments within the Florida Coastal Everglades (FCE) ecosystem. The samples were ultra-filtered and excitation-emission fluorescence matrices (EEMs) were obtained. The EEMs showed the presence of four peaks with Ex/Em maxima at around 280 nm/325 nm (T), less than 260 nm/460 nm (A), 300 nm/412nm (M), and 350 nm/470 nm (C). To better understand the nature of peak T, the components originating this peak were separated using size exclusion chromatography (SEC) and detected by fluorescence emission at Ex/Em = 280 nm/325 nm. The elution curves revealed the presence of two elution peaks at a molecular weight of greater than 50K (void volume; T1) and around 7.6K (T2). This result suggested the need of cautious interpretation in the use of peak T as a proxy for the detection of proteinaceous materials in wetland and estuarine environments, since significant amounts of potentially interfering phenolic compounds are leached from senescent biomass in wetland and coastal ecosystems. As such EEM spectra of gallic acid an important component of hydrolysable tannins, and condensed tannins extracted from red mangroves (Rhizophora mangle) showed the presence of a peak maxima

openCC (other)Feb 2024View details →

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.

openCC (other)Feb 2022View details →

The dataset and model code pertinent to the Everglades Peat Elevation Model (EvPEM): The salinity and inundation mesocosm experiment in freshwater and brackish water sawgrass wetlands in Florida Coastal Everglades (2015-2017).

This is an assembled data and Everglades Peat Elevation Model (EvPEMv1.0) Stella code used to estimate and simulate net ecosystem carbon balance (NECB) and peat elevation change in response to saltwater intrusion and level of inundations. Data from several studies were combined for the estimation of NECB, model parameterization, and calibration (Wilson, 2018; Wilson et al., 2018, 2019; Charles et al., 2019; Servais et al., 2020). The reported data includes aboveground net primary productivity (ANPP), belowground net primary productivity (BNPP), peat elevation change, and decomposition rates that were collected from outdoor laboratory mesocosm experiments conducted at the Florida Bay Interagency Science Center in Key Largo, Florida during 2015-17. The plant-soil monoliths were obtained from a freshwater peat and a brackish water peat marsh located within the Florida Coastal Everglades and transported to the Key Largo facility for the experimental manipulations. In experiments focused on the brackish water marsh, three experiments were carried out reflecting the combined effect of salinity, inundation, and peat exposure to air. The brackish water experiments characterized submerged (SUB), exposed (EXP), and extended depth of exposure of peat surface (EXTEXP) conditions, as we varied water depth relative to the peat surface. Each experiment was subjected to two salinity manipulations: (1) ambient (~10 ppt) porewater salinity (AMB) and (2) elevated (~20 ppt) salinity (SALT). The experimental design included six (2 X 3) treatments: (1) submerged ambient salinity (AMB.SUB), (2) submerged elevated salinity (SALT.SUB.), (3) exposed ambient salinity (AMB.EXP), (4) exposed elevated salinity (SALT.EXP), (5) exposed with extended exposure/dry-down ambient salinity (AMB.EXTEXP), and (6) exposed with extended exposure/dry-down elevated salinity (SALT.EXTEXP). The water level was kept 4 cm above the peat surface for the brackish water SUB treatments. Exposure for the EXP treatment

opencc-by-4.0Aug 2024View details →

US Atlantic and Gulf Coast Annual Wetland Land Cover and Change Maps, 1985 to 2022

<h3>This dataset is associated with the following article published in Remote Sensing Applications: Society and Environment, which can be accessed here: https://doi.org/10.1016/j.rsase.2024.101392</h3> Shortly after publishing version 2, errors in the map projections were identified and corrected. Please use version 3 instead of version 2. Updates to version 2 were as follows: <ul> <li>Includes watersheds in Texas that were not included in Version 1.</li> <li>A color map (using ArcPro) was added for improved interpretation.</li> <li>A sub-pixel scale offset in the change type map, related to map projection errors, was corrected.</li> </ul> <h2>Mapping Coastal Wetland Changes from 1985 to 2022 in the US Atlantic and Gulf Coasts using Landsat Time Series and National Wetland Inventories</h2> Courtney A. Di Vittorio1, Melita Wiles2, Yasin W. Rabby2, Saeed Movahedi2, Jacob Louie1, Lily Hezrony1, Esteban Coyoy Cifuentes1, Wes Hinchman1, Alex Schluter1 1Department of Engineering, Wake Forest University, Winston-Salem, North Carolina, USA. 2Department of Statistics, Wake Forest University, Winston-Salem, North Carolina, USA. <h3>Abstract</h3> The areal extent of coastal wetlands is declining rapidly worldwide, and scientists and land managers need land cover maps that show the magnitude and severity of changes over time to assess impacts and develop effective conservation strategies. Within the United States (US), the widely-used, continental-scale wetland land cover data products are either static in time (The National Wetlands Inventory) or have a course temporal resolution, and do not distinguish between different types of change (the NOAA Coastal Change Analysis Program, C-CAP). This study presents a new coastal wetland geospatial data product that leverages the Landsat database and maps annual land cover across the US Atlantic and Gulf Coasts from 1985 to 2022. The algorithm was trained on the existing US wetland inventories to make the final maps compatible with products that are used in operational management. A multi-stage classification approach was designed that uses Google Earth Engine and the Continuous Change Detection and Classification (CCDC) algorithm to characterize time series of remote sensing imagery with fitted harmonic functions and identify when changes likely occurred. The fitted time series models are then input into a random forest classifier to make a class prediction. An annual-scale random forest classification is performed in parallel, and results from both algorithms are combined and analysed to detect both gradual and abrupt changes and to identify transitional time series segments. A time series smoothing procedure is subsequently applied to ensure class transitions are logical and consistent and extract a summative change characterization map that shows the severity and spatial density of change. The final maps distinguish between four homogenous classes and six mixed classes, representing areas that are transitioning between classes and where the boundaries between classes are unstable. The average overall accuracy of the algorithm is 93.7%, and the average class omission and commission errors are 6.7% and 6.4%, respectively. A variety of change detection comparisons were performed, using the existing wetland inventory that employed a fundamentally different change detection approach, and a more comparable annual-scale, Landsat-derived product that estimated changes across the Northeastern Atlantic Coast. These comparisons show that the magnitude of severe changes matches that of the existing inventory and the magnitude of the moderate changes matches that of the more comparable product. The 2019 Wetland Status and Trends Report estimated that net loss rates in emergent wetlands from 2010 to 2019 amount to 1.7%, and the new maps show an equivalent loss rate of 1.6%, again showing close agreement.

opencc-by-4.0Oct 2023View details →

Hydrodynamic field data near Galveston, Texas wetland edges to help assess storm impacts and erosion

Water free surface elevation measurements via submerged pressure transducers along transects near Galveston Bay wetland edges

opencc-by-4.0Feb 2024View details →

Urban Riparian Wetland Hydrology Dataset_Stormwater Capture in Beaver-mediated Wetlands along Walnut Creek, Raleigh, North Carolina, USA

This is the initial release of a hydrology dataset pertaining to the riparian floodplain wetlands alongside Walnut Creek in Raleigh, North Carolina USA.  Walnut Creek is the main drainage channel in an urbanized watershed (HUC-12: 030202011101) in central North Carolina.  There are several riparian floodplain wetlands along the creek which are largely supplied by urban stormwater runoff including directed storm sewer flows and regular overbank flooding events. In many of these wetlands local water retention and residence time in the surface ponds is mediated by the damming activity of North American beavers (Castor canadensis).  This dataset contains data specific to the hydrology of Walnut Creek, and the surface ponds and groundwater at the Walnut Creek Wetland Park which is actively influenced by resident beavers.  The period of this dataset is from January 22, 2023 through January 30, 2024.  The core of the dataset is water stage measured in five surface pond sites and six groundwater monitoring wells within Walnut Creek Wetland Park.  This data was collected using synchronized Solinst Levelogger pressure transducer sensors at 15-minute intervals, compensated with corrections for barometric pressure measured locally using a Solinst Barologger sensor. In addition to this data collected by the authors, this dataset also includes publicly available stream stage and precipitation data obtained from the US Geological Survey, and weather and soils data from the North Carolina State Climate Office. In total, this dataset aims to provide a comprehensive view of surface and subsurface hydrology in the studied wetlands as it connects with precipitation events, antecedent moisture conditions, directed stormwater flows and overbank flood events.  This hydrology dataset is intended to accompany the separate water quality dataset published on Zenodo at URL: <a href="https://doi.org/10.5281/zenodo.10888463">https://doi.org/10.5281/zenodo.10888463</a>. Together, these datasets are meant to support an improved understanding of the water availability and water quality found in connection with beaver-mediated stormwater capture in an urbanized watershed in the North Carolina Piedmont. This dataset resulted from research supported with a Graduate Student Research Grant awarded by the North Carolina Water Resources Research Institute (WRRI), under Project Number 23-10-W: "Stormwater Diversion, Storage, and Treatment by Beaver-enhanced Floodplain Wetlands in Piedmont Urban Watersheds".   This material is based upon work supported by the National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) under Grant No. (DGE 2137100). Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation. Special thanks to Raleigh Parks and Walnut Creek Wetland Park for making this work possible.

opencc-by-4.0Mar 2024View details →

A map selection of wigeon stopover sites (core areas) based on wetland expert knowledge

Stopover areas (core areas only) along the migration route of wigeons tracked with GPS transmitters were selected when they exhibited forests on more than 50% of their total surface or had less than 50% cover by water and/or wetland on the ESA’s global land cover map. We created a sample of 5,630 regions of interest (3,403 for training and 2,227 for validation), delineated with polygons assigned to land classes listed in the Table 1. We used archives of Google Earth, ESRI, and BING satellites for the photointerpretation of the land classes as described in Table 1. The classification was performed with a Sentinel-2 MultiSpectral Instrument, Level-2A image collection in Google Earth Engine (GEE) through the R-package Rgee to create a batch process applying the GEE Random forest classifier to each selected core home range. The cloudless (maximum 3%) images were selected within the period from 01/06/2021 to 30/09/2021. The optimal number of trees was estimated at 100 for an out of bag error of 14%. The overall accuracy on the validation sample was 82 %.

opencc-by-4.0Jul 2021View details →

Indicative distribution map for Ecosystem Functional Group F2.9 Geothermal pools and wetlands

This archive contains indicative distribution maps and profiles for F2.9 Geothermal pools and wetlands, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith et al. (2020) for details. The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).

opencc-by-4.0Jul 2021View details →

Indicative distribution map for Ecosystem Functional Group F3.2 Constructed lacustrine wetlands

This archive contains indicative distribution maps and profiles for F3.2 Constructed lacustrine wetlands, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith et al. (2020) for details. The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).

opencc-by-4.0Jul 2021View details →

Indicative distribution map for Ecosystem Functional Group TF1.2 Subtropical/temperate forested wetlands

This archive contains indicative distribution maps and profiles for TF1.2 Subtropical/temperate forested wetlands, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith et al. (2020) for details. The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).

openCC0Jul 2017View details →

Freshwater connectivity clusters for lakes, wetlands, and streams at the Hydrologic Unit 12 scale in the Midwest and Northeast U.S.A. – freshwater metric variables and K-means cluster assignment

This dataset includes freshwater connectivity cluster output and principal component scores for lakes, wetlands, and streams measured at the Hydrologic Unit 12 (HU12) scale in 17 U.S. states in the Midwest and Northeast regions (appr. 1,800,000 km2). The intent of the cluster analysis is to characterize the macroscale patterns of freshwater connectivity attributes. We define freshwater connectivity as the permanent surface hydrologic connections that link lakes, wetlands, and streams and measure connectivity as the landscape position of systems within stream networks. Geographic data used in the analysis are in LAGOS-NE-GEO database v. 1.03 (Lake multi-scaled geospatial and temporal database), an integrated, multi-thematic geographic database (Soranno et al. 2015). Freshwater connectivity clusters were created separately for lakes, wetlands, and streams through a multi-step process as follows: 1) we quantified multiple freshwater connectivity metrics, 2) we performed principal components analysis (PCA) on the connectivity metric values for each freshwater type to reduce collinearity, and 3) we performed k-means cluster analysis to group spatial units with similar freshwater connectivity characteristics. The resulting freshwater clusters are representations of the macroscale patterns of lake, wetland, and stream connectivity in the landscape.

openCC (other)Mar 2023View details →

Data Source: Synergistic effects of precipitation and groundwater extraction on freshwater wetland inundation

Wetlands provide essential ecosystem services, including nutrient cycling, flood protection, and biodiversity support, that are sensitive to changes in wetland hydrology. Wetland hydrological inputs come from precipitation, groundwater discharge, and surface run-off. Changes to these inputs via climate variation, groundwater extraction, and land development may alter the timing and magnitude of wetland inundation. Data were compiled for 152 wetlands in west-central Florida over 14 years to investigate the response of wetland inundation to the interactive effects of precipitation, groundwater extraction, surrounding land development, basin geomorphology, and wetland vegetation class. Further methods are defined in the Methods section of the journal article associated with this dataset (Synergistic effects of precipitation and groundwater extraction on freshwater wetland inundation, published in the Journal of Environmental Management, 2023).

openCC (other)Jun 2023View details →

Data from: Heterogeneity in habitat and nutrient availability facilitate the co-occurrence of N2 fixation and denitrification across wetland - stream - lake ecotones of Lakes Superior and Huron

Great Lakes coastlines are mosaics of wetland, stream, and lake habitats, characterized by a high degree of spatial heterogeneity that may facilitate the co-occurrence of seemingly incompatible biogeochemical processes due to variation in environmental factors that favor each process. We measured nutrient limitation and rates of N2 fixation and denitrification along transects in 5 wetland - stream - lake ecotones with different nutrient loading in Lakes Superior and Huron and hypothesized that rates of both processes would be related to nutrient limitation status, habitat type, and environmental characteristics including temperature, nutrient concentrations, and organic matter quality. This data package includes information on sampling sites, dates and locations; rates of N fixation and denitrification measured at each site, date and transect location; and biomass information from nutrient diffusing substrates deployed on the study transects.

openCC (other)Oct 2024View details →

Water-soluble organic matter and nutrients from stormwater control measure and urban wetland soils

Water-soluble organic matter (WSOM) represents organic matter that has the potential to be readily released from soils. WSOM has been understudied in urban, engineered soils relative to natural soils. To understand the potential for organic matter and nutrient release, we extracted WSOM from the soils of stormwater control measures (SCM) and urban wetlands. In February 2022, we sampled soils from 20 SCMs and natural wetlands in the Rappahannock River watershed of the mid-Atlantic United States. The SCMs reflected a variety of design configurations including bioretention, rain gardens, wet ponds, and swales. We also sampled naturally occurring floodplain wetlands that are located in this urban watershed. Soils were sampled to a depth of approximately 40 cm. If there was standing water present in the SCMs and wetlands at the time of sampling, we also collected surface water samples. If present, grab samples of leaf litter or biomass were collected. Soil characteristics, such as pH, bulk density, soil moisture, soil organic matter, and cation exchange capacity were also determined for each site. WSOM was extracted from soils and biomass in the laboratory and analyzed for organic matter concentration (dissolved organic carbon) and composition (absorbance and fluorescence metrics), along with dissolved nutrient concentrations (total dissolved nitrogen, total dissolved phosphorus, nitrate, ammonium, and orthophosphate). In addition to the 20 sites in the Rappahannock watershed, soils from 2 additional bioretention SCMs on the Virginia Tech campus were sampled on a monthly basis from February 2022 to February 2023 to explore temporal variability in WSOM. To characterize changes in soil hydrologic conditions during monthly SCM sampling, we applied a Thornthwaite-type monthly water balance model. Finally, we performed a simple scaling exercise to WSOM results based on SCM area, sample depth, and soil bulk density to estimate potential SCM contributions of organic matter.

openCC (other)Apr 2025View details →

Fish Restoration Program Tidal Wetland Restoration Monitoring in Upper San Francisco Estuary, 2015-ongoing

The Fish Restoration Program Monitoring Team assesses the biological effectiveness of 8,000+ acres of tidal wetland restoration in the Upper San Francisco Estuary (Sacramento-San Joaquin Delta and Suisun Marsh) through a contract with the CA Department of Water Resources. The restoration is pursuant to requirements in the 2008/2009 and 2019 Biological Opinions for state and federal water project operations. Data on fish and invertebrate abundance on or near these sites was collected as baseline monitoring data and to determine the most efficient methods for monitoring wetlands. Understanding how invertebrate, fish, and phytoplankton communities change pre- to post-restoration is essential to evaluating the benefits of tidal wetlands to native fish species. Invertebrate data was collected using sweep nets, benthic cores, neuston nets, and zooplankton trawls. Fish data was collected using otter trawls, lampara nets, and beach seines. For each method, the team recorded the catch of fish, invertebrates, and other organisms, length of selected organisms, and a suite of environmental information, including: dissolved oxygen, water temperature, pH, specific conductance, turbidity, chlorophyll a, phycocyanin, and dissolved organic carbon. Additional water quality samples, processed for Chlorophyll a, Dissolved Ammonia, Dissolved Nitrite + Nitrate, Dissolved Organic Carbon, Dissolved Organic Nitrogen, Dissolved Ortho-phosphate, Pheophytin a, Total Kjeldahl Nitrogen, Total Organic Carbon, Total Phosphorus, and Total Suspended Solids, were collected at a subset of sampling sites. Data are collected before and after restoration at project and reference sites (Before-After-Control-Impact-design), as well as at adjacent water bodies.

openCC (other)Aug 2025View details →

UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Fish Abundance and Species Richness

These data describe the annual estimates of density of wetland fish (all species combined) and the species richness (as the number of unique species) in six main channel and six tidal creek locations at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity. This study began in 2012 in the San Dieguito Wetland in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Tijuana Estuary in San Diego County was added in 2013. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.

openCC (other)Jun 2025View details →

UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Bird Abundance and Species Richness

These data describe the annual estimates of bird density and richness (as a species density) in twenty plots at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.

openCC (other)Jun 2025View details →

UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Bird Food Chain Support

These data describe annual estimates of the density of feeding birds at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in food chain support provided to birds. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Point Mugu Lagoon in Ventura County. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.