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1,455 results for “Coastal ecosystems”
How is copepod functional diversity shaped by 2015-2016 El Niño and seasonal water masses in a coastal ecosystem of Southwest Atlantic?
<p>Figure S1: a) El Niño-Southern Oscillation episodes. Index values (Oceanic Niño Index - ONI) of +0.5 or higher indicate El Niño; values of -0.5 or lower indicate La Niña (dotted line). Transparent gray shade represents the period of interest (2014-2016), b) Pixel contour plots show satellite-based sea surface temperature monthly means in the Arvoredo MPA surroundings. Data visualization standard plots from the zooplankton time series adopted by SCOR WG125 (Mackas et al., 2012) and performed at http://www.st.nmfs.noaa.gov/copepod/.</p><p>Table S1 – Taxa code and functional traits of copepod species during the summer and winter of 2014, 2015, and 2016 in the Arvoredo MPA surroundings.</p><p>Table S2 – Total and mean abundance (ind. m-3), standard deviation (SD), relative abundance (RA %), and frequency of occurrence (FO %) of copepod species during the summer and winter of 2014, 2015, and 2016 in the Arvoredo MPA surroundings.</p><p> </p>
Beagle kelp maps from: One of the least disturbed marine coastal ecosystems on Earth: Spatial and temporal persistence of Darwin's sub-Antarctic giant kelp forests
<p>Aim: Marine habitats and their dynamics are difficult to systematically monitor, particularly those in remote locations. This is the case with the sub-Antarctic ecosystem of the giant kelp <i>Macrocystis pyrifera</i>, which was already noted by Charles Darwin in his accounts on the <i>Voyage of the Beagle</i> and recorded on the nautical charts made during that expedition. We combined these and other nautical charts from the 19th and early 20th centuries with surveys conducted in the 1970s and 1980s and satellite detection algorithms from 1984 to 2019, to analyse kelp distribution through time and the factors that correlate with it.</p> <p>Location: Marine ecoregions of Channels and Fjords of Southern Chile, Falkland Islands (Malvinas), and the island of South Georgia.</p> <p>Taxon: <i>Macrocystis pyrifera</i>.</p> <p>Methods: We characterised 309 giant kelp forests by their coastal geospatial attributes. Statistically significant variables were included in a conditional inference tree to predict kelp forest size. Sea surface temperature (SST) records were analysed to confirm temperature ranges over the last four decades. Nautical charts, historical surveys, aerial photogrammetry, unmanned aerial vehicle (UAV) surveys and satellite imagery were overlaid to assess spatial distribution of kelp forest canopies, spanning the period 1829–2020.</p> <p>Results: Considering the extensive natural and human caused changes over the last two centuries, this diverse kelp ecosystem is remarkably persistent. We found that the ocean currents and wave exposure, combined with the geomorphological settings of the coastline are the most critical factors predicting the extent of the kelp forests.</p> <p>Main conclusions: We have described the long-term ecological persistence of the kelp forests in this vastly under-studied region that offers a conceptual biogeographical model supporting the global importance proposed by Charles Darwin 200 years ago (Darwin, 1845). In the current context of global change, the need for conservation of this persistent and well-preserved marine ecosystem has never been more important.</p>
Effects of time since invasion and control actions on a coastal ecosystem invaded by non-native pine trees
<p><span>Invasive non-native trees cause structural and functional changes in plant communities, which tend to </span><span>increase over time since invasion. Native vegetation responses after control operations provide important information for restoration.</span></p> <p><span>We evaluated the effects of time since invasion and of pine control on plant community structure and on functional traits in a </span><span>coastal open ecosystem in southern Brazil</span><span>. We compared richness, diversity, abundance and cover of woody and non-woody native plant species, as well as species composition and community-weighted means (CWM)</span> <span>based on functional traits (</span><span>dispersal syndrome, fruit type, maximum height, and shade tolerance) of plant communities</span><span>, in four conditions: a non-invaded area, an area where pines were controlled (managed area), an area of recent invasion, and an area invaded longer ago.</span></p> <p><span>Woody species abundance, richness and diversity declined over time since invasion. However, while abundance recovered to the point of not differing from the non-invaded condition in areas where pines were controlled, species diversity and richness were lower in the managed area than in the area that was never invaded. The effects of pine invasion on richness and diversity of non-woody plants did not increase over time, but plant cover progressively diminished. </span></p> <p><span>Woody and non-woody species composition varied between the four conditions. Species composition similarity was lower between conditions for non-woody than for woody species. CWM differed between the older invasion and the other conditions, determined especially by native plant height and shade tolerance. Taller plants and m</span><span>ore shade tolerant native species were exclusively sampled in the older invasion.</span></p> <p><span>Synthesis and application. Pine invasion reduced species abundance, plant cover, richness, and diversity, altering the composition of plant community. The escalation of negative temporal effects of pine invasion was observed on the composition of woody and non-woody species and on functional traits. Although pine control favored the natural regeneration of non-woody species, diversity of woody species in the area submitted to pine control was lower than in the non-invaded condition. Restoration activities are therefore required to increase woody species diversity. These results provide relevant guidance for the restoration of coastal ecosystems following invasive pine control. </span></p>
Supplementary material 1 from: Sogawa S, Tsuchiya K, Nagai S, Shimode S, Kuwahara VS (2022) Annual dynamics of eukaryotic and bacterial communities revealed by 18S and 16S rRNA metabarcoding in the coastal ecosystem of Sagami Bay, Japan. Metabarcoding and Metagenomics 6: e78181. https://doi.org/10.3897/mbmg.6.78181
Figures S1–S8
Supplementary material 2 from: Gacutan J, Lal KK, Herath S, Lantz C, Taylor MD, Milligan BM (2022) Using Ocean Accounting towards an integrated assessment of ecosystem services and benefits within a coastal lake. One Ecosystem 7: e81855. https://doi.org/10.3897/oneeco.7.e81855
Ecosystem service assessment methods
Supplementary material 3 from: Gacutan J, Lal KK, Herath S, Lantz C, Taylor MD, Milligan BM (2022) Using Ocean Accounting towards an integrated assessment of ecosystem services and benefits within a coastal lake. One Ecosystem 7: e81855. https://doi.org/10.3897/oneeco.7.e81855
Fisheries - stable isotope calculations
Supplementary material 1 from: Gacutan J, Lal KK, Herath S, Lantz C, Taylor MD, Milligan BM (2022) Using Ocean Accounting towards an integrated assessment of ecosystem services and benefits within a coastal lake. One Ecosystem 7: e81855. https://doi.org/10.3897/oneeco.7.e81855
Definitions and data sources used
Supplementary material 4 from: Garcia Rodrigues J, Conides A, Rivero Rodriguez S, Raicevich S, Pita P, Kleisner K, Pita C, Lopes P, Alonso Roldán V, Ramos S, Klaoudatos D, Outeiro L, Armstrong C, Teneva L, Stefanski S, Böhnke-Henrichs A, Kruse M, Lillebø A, Bennett E, Belgrano A, Murillas A, Sousa Pinto I, Burkhard B, Villasante S (2017) Marine and Coastal Cultural Ecosystem Services: knowledge gaps and research priorities. One Ecosystem 2: e12290. https://doi.org/10.3897/oneeco.2.e12290
Overview of the methods and indicators used to assess marine and coastal CES
Supplementary material 3 from: Garcia Rodrigues J, Conides A, Rivero Rodriguez S, Raicevich S, Pita P, Kleisner K, Pita C, Lopes P, Alonso Roldán V, Ramos S, Klaoudatos D, Outeiro L, Armstrong C, Teneva L, Stefanski S, Böhnke-Henrichs A, Kruse M, Lillebø A, Bennett E, Belgrano A, Murillas A, Sousa Pinto I, Burkhard B, Villasante S (2017) Marine and Coastal Cultural Ecosystem Services: knowledge gaps and research priorities. One Ecosystem 2: e12290. https://doi.org/10.3897/oneeco.2.e12290
List of papers included in the literature synthesis
Supplementary material 1 from: Garcia Rodrigues J, Conides A, Rivero Rodriguez S, Raicevich S, Pita P, Kleisner K, Pita C, Lopes P, Alonso Roldán V, Ramos S, Klaoudatos D, Outeiro L, Armstrong C, Teneva L, Stefanski S, Böhnke-Henrichs A, Kruse M, Lillebø A, Bennett E, Belgrano A, Murillas A, Sousa Pinto I, Burkhard B, Villasante S (2017) Marine and Coastal Cultural Ecosystem Services: knowledge gaps and research priorities. One Ecosystem 2: e12290. https://doi.org/10.3897/oneeco.2.e12290
PRISMA checklist
Figure 3 in Biological diversity and seasonal variation of mesozooplankton in the southeastern Black Sea coastal ecosystem
Figure 3. The variation in total mesozooplankton abundance and temperature with respect to years (SST: sea surface temperature).
Data and Code Supporting Hagy et al. Quantifying coastal ecosystem condition and a trophic state index with a Bayesian analytical framework
<p>The code includes several R markdown files and an associated file containing R functions. The main body of code <em>coastal_TSI_ts.Rmd</em> loads the function file located in the functions folder. Raw data is included as .csv files in the raw directory and various data sets created as intermediate products are in the data folder. Variable definitions are included in a data dictionary.</p> <p>The code has been used to generate the analysis reported in</p> <p>Hagy, JD, B. Kreakie, M. Pelletier, F. Nojavan, J. Kiddon, and A. Oczkowski. Quantifying coastal ecosystem condition and a trophic state index with a Bayesian analytical framework</p> <p>This file contains a zip of a github repository, https://github.com/USEPA/-cTSI</p>
Quantifying the Interaction of Oceanic and Riverine processes on Phytoplankton Dynamics in a Highly Dynamic Coastal Ecosystem
<p>The dataset lists the data in Figure 3, S1 and S7.</p>
Supplementary material 2 from: Gomez Cardona CJ, Moreno JY, Contreras A, Sanchez-Nuñez DA, Arciniegas Moreno N, Guerrero D, Viloria Maestre EA, Lopez Navarro J (2023) Accounting of marine and coastal ecosystems at the Ramsar Site, Estuarine Delta System of the Magdalena River, Ciénaga Grande de Santa Marta, Colombia. One Ecosystem 8: e98852. https://doi.org/10.3897/oneeco.8.e98852
Ecosystem type change matrix (ha) in the CGSM Ramsar site for the period 2012-2018
Supplementary material 1 from: Gomez Cardona CJ, Moreno JY, Contreras A, Sanchez-Nuñez DA, Arciniegas Moreno N, Guerrero D, Viloria Maestre EA, Lopez Navarro J (2023) Accounting of marine and coastal ecosystems at the Ramsar Site, Estuarine Delta System of the Magdalena River, Ciénaga Grande de Santa Marta, Colombia. One Ecosystem 8: e98852. https://doi.org/10.3897/oneeco.8.e98852
Ecosystem extent account (ha) in the CGSM Ramsar Site for the 2012-2018 accounting period
Supplementary material 1 from: Shaffer JA, Parks D, Campbell K, Moragne A, Hueske B, Adams P, Bauman JM (2023) Coastal beaver, Chinook, coho, chum salmon and trout response to nearshore changes resulting from diking and large-scale dam removals: synergistic ecosystem engineering and restoration in the coastal zone. Nature Conservation 53: 61-83. https://doi.org/10.3897/natureconservation.53.85421
Mean woody plant abundance surveyed from the riparian and shrub-emergent marsh vegetation
Assessing the Interaction of Oceanic and Riverine Processes on Phytoplankton Dynamics in a Highly Dynamic Coastal Ecosystem of the East China Sea
<p>The dataset lists the data in all Figures.</p>
Data from: How habitat-modifying organisms structure the food web of two coastal ecosystems
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Data from: Possible adverse impact of contaminants on Atlantic cod population dynamics in coastal ecosystems
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Effects of time since invasion and control actions on a coastal ecosystem invaded by non-native pine trees
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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
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.