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243 results for “Coastal area”
Data for 'Global Assessment of Interannual Hazard Variability in Coastal Urban Areas and Ecosystems'
<p>This dataset supports Odériz et al. (2024). 'Global Assessment of Interannual Hazard Variability in Coastal Urban Areas and Ecosystems'</p>
Image 14 in A New Species Of Platylestes Selys (Odonata: Zygoptera: Lestidae) From The Coastal Area Of Kannur District, Kerala, India
Image 14. Type locality of Platylestes kirani sp. nov.
Figure 1 in A New Species Of Platylestes Selys (Odonata: Zygoptera: Lestidae) From The Coastal Area Of Kannur District, Kerala, India
Figure 1. Type locality of Platylestes kirani sp. nov.
GNSS and levelling data to detect ground deformation along the Upper Adriatic Sea coastal area (Italy)
<p>This geodetic dataset includes both Global Navigation Satellite System (GNSS) and levelling data. GNSS measurements were recorded by continuous stations managed by public institutions and private companies, while levelling measurements were obtained by the use of benchmarks managed by ENI S.p.A. </p> <p>This dataset is used in the manuscript entitled "Multi-technique geodetic detection of onshore and offshore subsidence along the Upper Adriatic Sea coasts" to estimate deformation around the littoral area of Ravenna (Italy) (Polcari et al., 2022). The GNSS data, from permanent stations RAVE, PCTA, FIUN and ANGA covers the period from around 1998 to 2018. The files in .csv format contain displacement time series with respect to the Adria-fixed reference frame and for PCTA, FIUN and ANGA also with respect to RAVE GNSS station.</p> <p>The levelling data refer to campaigns that took place in 2002, 2003, 2004, 2005, 2007, 2009, 2011, 2014, and 2017. The file named <em>Original.csv</em> contains the original height measurements for each benchmark, while the file named <em>Ref.RAVE.csv</em> contains the mean velocity and the displacement calculated for all 147 benchmarks. In this last file the data were scaled with respect to the mean velocity of the benchmark located near the RAVE station.</p>
Fig. 1 in Assessment of coastal fish assemblages before the establishment of a new marine protected area in the central Mediterranean: its role in formulating a zoning proposal Abstract
Fig. 1: Map of the study area with indication of sampling sectors around the promontory of Milazzo.
Fig. 2 in Reproductive studies of Anchoa marinii Hildebrand, 1943 (Actinopterygii: Engraulidae) in the nearby-coastal area of Mar Chiquita coastal lagoon, Buenos Aires, Argentina
Fig. 2. Monthly relative frequency (%) of gonad phases for females of Anchoa marinii.
Fig. 5 in Reproductive studies of Anchoa marinii Hildebrand, 1943 (Actinopterygii: Engraulidae) in the nearby-coastal area of Mar Chiquita coastal lagoon, Buenos Aires, Argentina
Fig. 5. Oocyte diameter distribution in spawning capable phase of Anchoa marinii. N= 183.
Fig. 2 in Anomuran and Brachyuran Symbiotic Crabs in Coastal Areas between the Southern Ryukyu arc and the Coral Triangle
Fig. 2. Number (a) and proportion (b) of symbiont identified in the investigation area.
Fig. 5 in Anomuran and Brachyuran Symbiotic Crabs in Coastal Areas between the Southern Ryukyu arc and the Coral Triangle
Fig. 5. Brachyuran crab Trapezia septata living with the host coral Acropora hyacinthus.
Figure 1 in Impact of dike age on biodiversity and functional composition of soil macrofaunal communities in poplar forests in a reclaimed coastal area
Figure 1. Distribution of sample sites on the reclaimed coast.
Figure. Study area (the Sea of Marmara, Türkiye) and the sampling stations. in The length-weight relationship and condition factors of coastal small-sized adult and juvenile fish species following dense mucilage in the Sea of Marmara, Türkiye
Figure. Study area (the Sea of Marmara, Türkiye) and the sampling stations.
Figure 8. A. Scincus mitranus. B. Varanus griseus. C in Reptiles and Amphibians along the Coastal Area of the Eastern Province, Saudi Arabia
Figure 8. A. Scincus mitranus. B. Varanus griseus. C. Diplometopon zarudnyi.
Figure 1 in Reptiles and Amphibians along the Coastal Area of the Eastern Province, Saudi Arabia
Figure 1. Map of the study area showing studied sites.
Fig. 1 in Patterns In Community Structure Of Trawl Catches Along Coastal Area Of The South China Sea
Fig. 1. Map of the study area.
Data from: Ancestral area analyses reveal Pleistocene-influenced evolution in a clade of Coastal Plain endemic plants
<p><strong>AIM:</strong> The North American Coastal Plain is currently recognized as a global biodiversity hotspot. However, the mechanisms driving high levels of species richness in a region with relatively low topographic relief and homogeneous climate are unclear. We investigated the evolutionary processes driving ancestral area evolution and diversification in a biodiversity hotspot from both a systematic and biogeographic context using a clade endemic to the hotspot.</p> <p><strong>LOCATION</strong>: North American Coastal Plain</p> <p><strong>TAXON</strong>: The Scrub Mint clade comprises <em>Dicerandra</em>, <em>Conradina</em>, <em>Piloblephis</em>, <em>Stachydeoma</em>, and four species of <em>Clinopodium</em> (Mentheae; Lamiaceae), almost all of which are endemic to the North American Coastal Plain. </p> <p><strong>METHODS</strong>: We generated a dated phylogeny using a target enrichment/capture dataset and then calculated ancestral area using biogeographic models. We uncovered neo- and paleo-endemism hotspots and inferred ancestral potential ranges at each node based on ancestral niche reconstructions and paleoclimatic data to understand the geographic range evolution of subclades. </p> <p><strong>RESULTS</strong>: Ancestral area for the SMC was inferred to be the Florida Panhandle/Apalachicola River basin. A diversification event likely happened around the mid-Pleistocene Transition. Endemism hotspots were recovered in NE Florida, the Atlantic Coastal Ridge, and along the Lake Wales Ridge. Reconstructions of potential ranges support biogeographic findings, with the ancestor of the SMC likely located in the vicinity of the northeastern Gulf Coast during interglacial and glacial periods.</p> <p><strong>MAIN</strong> <strong>CONCLUSIONS</strong>: The timing of diversification events and colonization of new areas by ancestors of the SMC is consistent with the timing of major geological events in the region. The presence of multiple types of endemism highlights the complexity of evolutionary and ecological processes that foster the large number of endemic taxa found in this region. Efforts to identify hotspots in this region will be critical to preserving the remaining pockets of biodiversity threatened by global change.</p>
Bio-optical observations of the Baltic Sea and coastal areas, 2008-2012
<p>This a dataset of optical-biogeochemical measurement results was collected during 2008-2012 as part of spring and summer cruises with R/V Aranda as well as from flow-through water samples taken with the Ferrybox system on M/S Finnmaid. The majority of observations were made in the Gulf of Finland, Baltic Proper, Archipelago Sea, and Gulf of Bothnia in the Baltic Sea. A number of riverine and inshore observations are also included. The data collection is owned by the Finnish Environment Institute SYKE and made available under a CC-BY-NC licence. </p> <p>Detail on methods and protocols are provided in the following papers </p> <ul> <li>Simis, Stefan GH; Ylöstalo, Pasi; Kallio, Kari Y; Spilling, Kristian; Kutser, Tiitt. 2017. Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea. PLoS One 12(4), e0173357. https://doi.org/10.1371/journal.pone.0173357</li> <li>Ylöstalo, Pasi; Seppälä, Jukka; Kaitala, Seppo; Maunula, Petri; Simis, Stefan. 2016. Loadings of dissolved organic matter and nutrients from the Neva River into the Gulf of Finland–Biogeochemical composition and spatial distribution within the salinity gradient. Marine Chemistry 186, 58-71. https://doi.org/10.1016/j.marchem.2016.07.004</li> </ul> <p>A large number of individuals took part in these bio-optical research cruises over the years. The authors of this dataset are particularly grateful to the contributions by international visitors, students and volunteers taking part in one or more cruises, as well as crew and support staff operating the research vessel and ship-of-opportunity. </p> <p>Variables included in the dataset include: </p> <table> <tbody> <tr> <td>Column name</td> <td>unit/format</td> <td>Description</td> </tr> <tr> <td>Secchi</td> <td>m</td> <td>Secchi disk depth</td> </tr> <tr> <td>AirTemp(38)</td> <td>°C, 01H</td> <td>Air temperature from ship weather channel 38, 1-h average</td> </tr> <tr> <td>SeaTemp(42)</td> <td>°C, 01H</td> <td>Sea temperature from ship weather channel 42, 1-h average</td> </tr> <tr> <td>WindSpeed(92)</td> <td>m/s, 10M</td> <td>Wind speed from ship weather channel 92, 10-min average</td> </tr> <tr> <td>WindDir(96)</td> <td>°, 10M</td> <td>Wind direction from ship weather channel 96, 10-min average</td> </tr> <tr> <td>Salinity(104)</td> <td>PSU, 01H</td> <td>Salinity from ship weather channel 104, 1-h average</td> </tr> <tr> <td>Rel.humid(54)</td> <td>%, 01H</td> <td>Relative humidity from ship weather channel 54, 1-h average</td> </tr> <tr> <td>Chla</td> <td>mg/m3</td> <td>Chlorophyll-a concentration (cold ethanol extraction and calibrated fluorescence)</td> </tr> <tr> <td>TSM_avg</td> <td>mg/L</td> <td>Total Suspended Matter Dry Weight, Average</td> </tr> <tr> <td>OSM_avg</td> <td>mg/L</td> <td>Dry weight of Organic fraction of TSM, Average</td> </tr> <tr> <td>ISM_avg</td> <td>mg/L</td> <td>Dry weight of Inorganic fraction of TSM, Average</td> </tr> <tr> <td>DOC_avg</td> <td>µM</td> <td>Dissolved Organic Carbon concentration, Average</td> </tr> <tr> <td>TDN_avg</td> <td>µM</td> <td>Total Dissolved Nitrogen concentration, Average</td> </tr> <tr> <td>NH4</td> <td>µM</td> <td>Ammonium concentration</td> </tr> <tr> <td>NO32</td> <td>µM</td> <td>Nitrate-Nitrate concentration</td> </tr> <tr> <td>NO2</td> <td>µM</td> <td>Nitrite concentration</td> </tr> <tr> <td>PO4</td> <td>µM</td> <td>Phosphate concentration</td> </tr> <tr> <td>SiO4</td> <td>µM</td> <td>Silicate concentration</td> </tr> <tr> <td>TN</td> <td>µM</td> <td>Total nitrogen concentration</td> </tr> <tr> <td>TP</td> <td>µM</td> <td>Total phosphorous concentration</td> </tr> <tr> <td>pH</td> <td>pH</td> <td>pH value</td> </tr> <tr> <td>Temp_CTD</td> <td>°C</td> <td>Water temperature measured by Seabird CTD on sampling rosette</td> </tr> <tr> <td>Salinity_CTD</td> <td>SSU</td> <td>Salinity measured by Seabird CTD on sampling rosette</td> </tr> <tr> <td>POC</td> <td>µM</td> <td>Particulate Organic Carbon concentration, Average</td> </tr> <tr> <td>PON</td> <td>µM</td> <td>Particulate Organic Nitrogen concentration, Average</td> </tr> <tr> <td>POP</td> <td>µM</td> <td>Particulate Organic Phosphorus concentration, Average (30.973762 g/Mol)</td> </tr> <tr> <td>Turbidity</td> <td>PSU</td> <td>Turbidity</td> </tr> <tr> <td>aCDOM</td> <td>m^-1</td> <td>spectral absorption coefficient of coloured dissolved organic matter</td> </tr> <tr> <td>CloudCover</td> <td>0-1</td> <td>Fraction (0-1) of cloud cover assesed from photos taken in the field.</td> </tr> <tr> <td>Kd</td> <td>m^-1</td> <td>spectral Vertical diffuse downwelling irradiance coefficient</td> </tr> <tr> <td>a_nap</td> <td>m^-1</td> <td>spectral absorption coefficient by non-pigmented fraction of suspended matter</td> </tr> <tr> <td>a_tsm</td> <td>m^-1</td> <td>spectral absorption coefficient by suspened matter</td> </tr> <tr> <td>R0</td> <td>-</td> <td>spectral Subsurface Irradiance Reflectance</td> </tr> <tr> <td>pigments</td> <td>mg/m3</td> <td>Chlorophyll and other pigments extracted and quantified using a combination of calibrated fluorometry and HPLC</td> </tr> </tbody> </table>
Data for "Measurement report: A one-year study to estimate maritime contributions to PM10 in a coastal area in Northern France."
<p>The characterization and the source apportionment of PM10 data have been used for the article "<strong>Measurement report: A one-year study to estimate maritime contributions to PM<sub>10</sub> in a coastal area in Northern France</strong>," which is under revision in the journal <em>Atmospheric Chemistry and Physic</em><em>s. </em></p>
Gulls contribute to olive seed dispersal within and among islands in a Mediterranean coastal area
<p><strong>Aim: </strong>To analyse the role of non-frugivorous birds on seed dispersal, seed dispersal by gulls is expected to be especially instrumental in island ecosystems, as these have a smaller subset of frugivores when compared to the mainland, and because long-distance dispersal is required for plant colonization. Here we investigated the seed dispersal of olives by gulls among ten islands of the same archipelago to reveal if gulls contribute to long-distance seed dispersal including different islands, and how gulls' adaptation to domestic olives and individual differences in foraging activities affect their seed dispersal pattern.</p> <p><strong>Location: </strong>Balearic Islands in the Western Mediterranean Sea, Spain</p> <p><strong>Taxon:</strong> Yellow-legged gulls ( <em>Larus michahellis</em>), Domestic and wild Olives ( <em>Olea europaea</em> and <em>O. europaea var.</em> <em>sylvestris</em>)</p> <p><strong>Methods</strong>: We developed seed dispersal models of the two ecotypes of olives dispersed by gulls across an archipelago, based on GPS tracking data, gut passage time, and seed viability.</p> <p><strong>Results</strong>: Mean dispersal distances were 7.67 (±12.48) km in wild and 12.57 (±13.08) km in domestic olives. Seven-point one percent of wild and 8.5% of domestic olives were dispersed among islands. Among these, 8.2% of domestic seeds were transported from large to small islands where gull colonies are located, whereas wild olives were dispersed in more variable directions. Such dispersal pattern of two olive ecotypes were consistent despite the differences in dispersal distances among individuals.</p> <p><strong>Main conclusions:</strong> Gulls contributed to long-distance olive seed dispersal including different islands. The seed dispersal of domestic olives to longer distances with specific directions may facilitate colonization and expansion of that variant if the conditions of seed deposition sites are suitable. Our findings indicate that gulls are relevant vectors for long-distance dispersal of large fleshy fruits in island ecosystems where specialist large frugivores are absent.</p>
Data from: Efficient wildlife monitoring: Deep learning-based detection and counting of green turtles in coastal areas
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Gulls contribute to olive seed dispersal within and among islands in a Mediterranean coastal area
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