Find research datasets worth reusing

opencc-by-4.0Mar 2014View details →

Figure 1 in Seasonal distribution of Trachurus mediterraneus (Steindachner, 1868) in the Golden Horn Estuary, İstanbul

Figure 1. Map of Golden Horn Estuary and sampling locations.

Figure 11 in Brackish water snails from Qi'ao-Dan'gan Island in the Pearl River estuary, China

Figure 11. Melanoides tuberculata. Radular teeth.

Figure 4. Sphaerassiminea brevicula. A. front view B in Brackish water snails from Qi'ao-Dan'gan Island in the Pearl River estuary, China

Figure 4. Sphaerassiminea brevicula. A. front view B. back view. Scale bar = 1 mm.

Figure 2. Assiminea estuarina. A. front view B in Brackish water snails from Qi'ao-Dan'gan Island in the Pearl River estuary, China

Figure 2. Assiminea estuarina. A. front view B. back view. Scale bar = 1 mm.

Figure 16. I in Brackish water snails from Qi'ao-Dan'gan Island in the Pearl River estuary, China

Figure 16. I. (Fairbankia) cochinchinensis. Radular teeth.

opencc-by-4.0Dec 2021View details →

Figure 1 in Studies on the free-living protozoan fauna of estuaries in the coastal zone of Tamil Nadu, India

Figure 1. Map showing the localities of various estuaries studied for protozoan fauna.

opencc-by-4.0May 2019View details →

Fig. 1 in Cossura yacy sp. nov. (Cossuridae, Annelida) from a tropical Brazilian estuary

Fig. 1. Collection sites in the São Luís do Maranhão port complex, Northeastern Brazil.

opencc-by-4.0Jun 2016View details →

Fig. 2 in Fishers' ecological knowledge of smalleye hammerhead, Sphyrna tudes , in a tropical estuary

Fig. 2. Fishing gear used to catch Sphyrna tudes in Cassurubá Extractive Reserve, eastern Brazil.

opencc-by-4.0Sep 2024View details →

Cryptic diversity patterns of subterranean estuaries

Data and results used in the analyses for the article: Calderón-Gutiérrez F, Labonté JM, Gonzalez B, Iliffe TM, Mejía‐Ortíz LM, Borda E. 2024. Cryptic diversity patterns of subterranean estuaries. Proceedings of the Royal Society B: Biological Sciences. (doi: 10.1098/rspb.2024.1483)

opencc-by-4.0Oct 2024View details →

Data from: Surfing the tidal wave: use of transiently-aquatic habitat by juvenile Pacific salmon and other fishes in estuaries

Tide and species count data used in the note "Surfing the tidal wave: use of transiently-aquatic habitat by juvenile Pacific salmon and other fishes in estuaries."

opencc-zeroDec 2006View details →

FIG. 5 in On some rare and new species of rotifers (Digononta, Bdelloida; Monogononta, Ploima and Flosculariaceae) in the Kaw River estuary (French Guiana)

FIG. 5. — Testudinella haueriensis Gillard, 1967. Scale bar: 50 µm.

opencc-by-4.0Dec 2010View details →

Fig. 1 in Reproductive biology of Plagioscion magdalenae (Teleostei: Sciaenidae) (Steindachner, 1878) in the bay of Marajo, Amazon Estuary, Brazil

Fig. 1. Study area. Bay of Marajo in theAmazon Estuary, Brazil.

opencc-by-4.0Oct 2021View details →

Scripts for post-processing Delft3d output data and figures for manuscript 'Longitudinal scour-bar pattern in estuaries'

The 7z file contains two folders, one named 'mat' contains the matlab scripts for post-processing Delft3D output data and plotting, the other named 'Figures' contains main outputs for the manuscript 'Longitudinal scour-bar pattern in estuaries'.

opencc-by-4.0Sep 2022View details →

Assessing a megadiverse but poorly known community of fishes in a tropical mangrove estuary through environmental DNA (eDNA) metabarcoding

Biodiversity surveys are crucial for monitoring the status of threatened aquatic ecosystems, such as tropical estuaries and mangroves. Conventional monitoring methods are intrusive, time-consuming, substantially expensive, and often provide only rough estimates in complex habitats. An advanced monitoring approach, environmental DNA (eDNA) metabarcoding, is promising, although only few applications in tropical mangrove estuaries have been reported. In this study, we explore the advantages and limitations of an eDNA metabarcoding survey on the fish community of the Merbok Estuary (Peninsular Malaysia). COI and 12S eDNA metabarcoding assays collectively detected 178 species from 127 genera, 68 families, and 25 orders. Using this approach, significantly more species have been detected in the Merbok Estuary over the past decade (2010–2019) than in conventional surveys, including several species of conservation importance. However, we highlight three limitations: (1) in the absence of a comprehensive reference database the identities of several species are unresolved; (2) some of the previously documented specimen-based diversity was not captured by the current method, perhaps as a consequence of PCR primer specificity, and (3) the detection of non-resident species—stenohaline freshwater taxa (e.g., cyprinids, channids, osphronemids) and marine coral reef taxa (e.g., holocentrids, some syngnathids and sharks), not known to frequent estuaries, leading to the supposition that their DNA have drifted into the estuary through water movements. The community analysis revealed that fish diversity along the Merbok Estuary is not homogenous, with the upstream more diverse than further downstream. This could be due to the different landscapes or degree of anthropogenic influences along the estuary. In summary, we demonstrated the practicality of eDNA metabarcoding in assessing fish community and structure within a complex and rich tropical environment within a short sampling period. However, some limitations need to be considered and addressed to fully exploit the efficacy of this approach.

opencc-by-4.0Feb 2023View details →

High Resolution Phragmites Australis Classification in Delaware Estuaries

This dataset provides a high resolution (1-m) land cover map for Estuarine wetlands in the State of Delaware in the United States of America during the summer of 2017. This dataset was created to identify populations of the invasive marsh species Phragmites australis. Input data: This classification is derived from National Agriculture Imagery Program (NAIP) 1-m aerial imagery captured in the State of Delaware during June of 2017. NAIP imagery includes a blue, green, red, and near infrared band. To improve classification accuracy, a Normalized Difference Vegetation Index (NDVI) was calculated from NAIP imagery using the near infrared and red bands. A principal component analysis (PCA) was used on the four NAIP bands and the NDVI band to create five new PCA bands. The five PCA bands were used as input into a random forest classification. NDVI = (Near infrared - Red) / (Near infrared + Red) Classification methods: We classified the input data using a Random Forest classifier with 100 trees. Data was classified into three coded land cover classes: 1 - Phragmites 2 - Other Vegetation 3 - Open Water 1,050 land cover reference points were collected with 70% used to train and 30% to test the classifier. Accuracy: Measures of accuracy including overall accuracy and per class user’s (UA) and producer’s accuracy (PA) of the random forest classifier were calculated. Overall accuracy: 95% Kappa: .92 Phragmites: UA = 97% PA = 95% Other vegetation: UA = 92% PA = 96% Open water: UA = 100% PA = 95% Code link: The Google Earth Engine code used in this analysis is publicly available. https://github.com/mattswalter/Phragmites_Classification Data for download: The following zipped file is available for download:        1. Delaware_Phragmites_Classification.zip Contains a GEOTIFF titled "Phrag_DE_5PC" with the classified image for 2017.

opencc-by-4.0May 2013View details →

Fig. 2 in Observations on the bloom-forming jellyfish Crambionella stuhlmanni (Chun, 1896) in the St Lucia Estuary, South Africa

Fig. 2. Map of the St Lucia estuarine lake, showing the main basins and stations within the system.

opencc-zeroApr 2023View details →

Global methane and nitrous oxide emissions from inland waters and estuaries

Inland waters (rivers, reservoirs, lakes, ponds, streams) and estuaries are globally significant emitters of methane (CH4) and nitrous oxide (N2O) to the atmosphere, while global estimates of these emissions have been hampered due to the lack of a worldwide comprehensive dataset with the collection of complete CH4and N2O flux components. Here, we synthesize 2,997 in-situ flux or concentration measurements of CH4 and N2O from 277 peer-reviewed publications to explore the role of inland waters and estuaries in shaping climate change. We estimate that inland waters including rivers, reservoirs, lakes, and streams together release 95.18 Tg CH4 yr-1 (ebullition plus diffusion) and 1.48 Tg N2O yr-1 (diffusion) to the atmosphere, yielding an overall CO2-equivalent emission total of 3.06 Pg CO2 yr-1, representing roughly 60% of CO2 emissions (5.13 Pg CO2 yr-1) from these four inland aquatic systems, among which lakes act as the largest emitter for both CH4and N2O. Ebullition is noticed as a dominant flux component of CH4, contributing up to 62–84% of total CH4fluxes across all inland waters. Chamber-derived CH4 emission rates are significantly greater than those determined by diffusion model-based methods for commonly capturing both diffusive and ebullitive fluxes. Water dissolved oxygen (DO) showed as a dominant factor among all variables to influence both CH4(diffusive and ebullitive) and N2O fluxes from inland waters. Our study reveals a major oversight in regional and global CH4budgets from inland waters, caused by neglect of the dominant role of ebullition pathways in those emissions. The indirect N2O EF5 values established in this study generally suggest a downward revision is required in current IPCC default EF5 values for inland waters and estuaries. Our findings further indicate that a comprehensive understanding of the magnitude and patterns of CH4 and N2O emissions from inland waters and estuaries is essential in defining how these aquatic systems will shape our climate.

opencc-zeroApr 2023View details →

Data for: Integrated multi-trophic aquaculture with sugar kelp and oysters in a shallow coastal salt pond and open estuary site

The data set includes environmental data as well as kelp and oyster data from an integrated multi-trophic aquaculture study where sugar kelp was planted on four established oyster farms in Rhode Island, USA over 2 growing seasons (Year 1 = 2017-2018; Year 2 = 2018-2019). At each site, we planted to 60 m kelp lines (denoted as Line 1 and Line 2) approximately three weeks apart to determine optimal planting time. Kelp blade length and width was recorded at periodic intervals, and tissues were collected for carbon, nitrogen, δ15N, and δ13C analyses. Oyster growth data was collected from the same sites across the same timespans. Environmental data includes data collected on monthly farm visits with a YSI Sonde, as well as dissolved nutrients in the seawater. In addition, temperatures were logged on kelp lines every 15 minutes during each growing season.

opencc-zeroMay 2023View details →

Data from: Environmental and climate variability drive population size of annual penaeid shrimp in a large lagoonal estuary

Species with short life spans frequently show a close relationship between population abundance and environmental variation making these organisms potential indicator species of climatic variability. White (Penaeus setiferus), brown (P. aztecus), and pink (P. duorarum) penaeid shrimp typically have an annual life history and are of enormous ecological, cultural, and economic value to the southeastern United States and Gulf of Mexico. Within North Carolina, all three species rely on the Pamlico Sound, a large estuarine system that straddles Cape Hatteras, one of the most significant climate and biogeographic breaks in the world, as a nursery area. These characteristics make penaeid species within the Pamlico Sound a critical species-habitat complex for assessing climate impacts on fisheries. However, a comprehensive analysis of the influence of the environmental conditions that influence penaeid shrimp populations has been lacking in North Carolina. In this study, we used more than 30 years of data from two fishery-independent trawl surveys in the Pamlico Sound to examine the spatial distribution and abundance of adult brown, white, and pink shrimp and the environmental drivers associated with adult shrimp abundance and juvenile brown shrimp recruitment using numerical models. Brown shrimp recruitment models demonstrate that years with higher temperature, salinity, offshore windstress, and North Atlantic Oscillation phase predict increased abundance of juveniles. Additionally, models predicting adult brown, white, and pink shrimp abundance illustrate the importance of winter temperatures, windstress, salinity, the North Atlantic Oscillation index, and the abundance of spawning adult populations from the previous year on shrimp abundance. Our findings show a high degree of variability in shrimp abundance is explained by climate and environmental variation and indicate the importance of understanding these relationships in order to predict the impact of climate variability within ecosystems and develop climate-based adaptive management strategies for marine populations.