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7,081 results for “Habitats”
Occurrences records of Herichthys labridens (Cichliformes: Cichlidae), with associated habitat information, in the Media Luna spring, San Luis Potosí, Mexico
<h2><strong>Introduction</strong></h2> <blockquote> <p>Occurrence records of the endemic cichlid <em>Herichthys labridens</em>, by adult and juvenile life stages, during three summer events (years of 1999, 2009, and 2019), in the Media Luna spring, San Luis Potosí Mexico. </p> </blockquote> <h2><strong>Material and Methods </strong></h2> <blockquote> <p>The occurrence records, ordered by adult and juvenile life stages, were obtained from two sources. For the summer of 1999, data were downloaded from the literature (Palacio-Núñez et al., 2010). For subsequent events, we recorded new data from 66 underwater transects distributed among 14 sectors (S1 to S14) in the Media Luna spring. We followed the method of Palacio-Núñez (2007), which maintained the transect location and sector boundaries of the summer of 1999 (Fig. 1a). The 20 m² transects were placed transversely to the current, from the edge to the central part of the canal (Fig. 1b). This sampling design was selected to meet two basic assumptions for studies of spatial distribution and habitat suitability: (1) the observations within the area are true and, (2) these observations delimit the initial position of the recorded individuals (Buckland & Elston, 1993). The analysis of the spatial information of the sectors, the underwater transects, and the delimitation of the water surface was performed using the QGIS® software version 3.4.8 (Menke, 2019).</p> <p> </p> <p><strong>Figure 1</strong>. <a href="https://zenodo.org/api/records/14231104/draft/files/Sector%20boundary_Transect%20location%20and%20sampling_Media%20Luna%20spring.jpeg/content" target="_blank" rel="noopener noreferrer">Sector boundary_Transect location and sampling_Media Luna spring.jpeg</a>. (a) Location of the transects in the Media Luna spring, Mexico. (b) Design scheme of the sampling transect; a CPVC pipe was used to give width to the edges of the transect and a nylon rope was attached to each side of the pipes to demarcate the length of the transect. Floating rubber buoys were added to the transects (at the edge towards the center of the canal) to prevent them from sinking into the sediment and to locate them among the vegetation. Transect scheme: Jorge Palacio-Núñez.</p> <p><br>In the summer events where we worked in field, we recorded the spatial location (i.e., GPS coordinates) of each individual and its life stage by direct observation with snorkel equipment and using a Garmin etrex device. The recorded information included the data of water depth and related underwater coverage. It is important to mention that, to prevent a repeat observation of the same organism or to ommit any individual, the transect was swaped slowly and in one direction only (i.e., from the center of the canal to the shore). We also used underwater cameras to validate the information. In adittion, the characterization of <em>H. labridens</em> individuals by life stage was performed by approximate size. For this purpose, previous studies on the life history and biology of the species were reviewed (Miller et al., 2005; De La Maza-Benignos & Lozano-Vilano, 2013). It is worth mentioning that, during fieldwork, we avoided manipulation, damage, or unnecessary capture of the fish (e.g., Prchalová et al., 2009).</p> <p><br>The databases by life stage were organized for each summer event, where, each observation record was included along with the associated habitat conditions. Subsequently, we depurated each database to remove atypical spatial data, data without information, incomplete data, or data with duplicate coordinates (García-Roselló et al., 2014). Then, we performed spatial filtering of the remaining records to validate those that were within the study area, and to prevent that two or more points were within 0.1 m of each other. These steps of our analysis were performed using the software Qgis® version 3.28.4 and Rstudio® (Rstudio team, 2020). Subsequently, with the data set that included fish records, water depth, and underwater coverage variables, we performed a final environmental filter to rule out atypical records. This exploration was performed in Rstudio ® using the outliers function, starting from the lowest and highest quantiles.</p> </blockquote> <h2><strong>Results</strong></h2> <blockquote> <p>The final filtered databases were organized by life stage and summer event:</p> <p><strong>Adult: </strong></p> <table> <tbody> <tr> <td>Summer event</td> <td>Database</td> </tr> <tr> <td>1999</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Adult_1999_Palacio-N%C3%BA%C3%B1ez%20et%20al.,%202010.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Adult_1999_Palacio-Núñez et al., 2010.csv</a></td> </tr> <tr> <td>2009</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Adult_2009_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Adult_2009_Field work.csv</a></td> </tr> <tr> <td>2019</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Adult_2019_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Adult_2019_Field work.csv</a></td> </tr> </tbody> </table> <p><strong> Juvenile:</strong></p> <table> <tbody> <tr> <td>Summer event</td> <td>Database</td> </tr> <tr> <td>1999</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Juvenile_1999_Palacio-N%C3%BA%C3%B1ez%20et%20al.,%202010.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Juvenile_1999_Palacio-Núñez et al., 2010.csv</a></td> </tr> <tr> <td>2009</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Juvenile_2009_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Juvenile_2009_Field work.csv</a></td> </tr> <tr> <td>2019</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Juvenile_2019_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Juvenile_2019_Field work.csv</a></td> </tr> </tbody> </table> </blockquote> <p> </p> <blockquote> <p>These occurrence records for <em>H. labridens </em>are ready to be used in ecological niche modeling and spatial distribution studies. Also, these records can be used for other ecological and spatial studies, because each record (i.e., individual) included geoespatial coordinates, sector, location, and transect number. Also, we recorded information about the conditions of underwater coverage and water depth, which were asociated to each ocurrence record.</p> <p>For more information about several R codes where the previous databases can be used, visit the following repository URL: <a href="https://doi.org/10.5281/zenodo.7603557">https://doi.org/10.5281/zenodo.7603557</a>.</p> <p>Also, to download the UC and WDp variables to run the spatial and ecological modeling, visit the following repository URL: <a href="https://doi.org/10.5281/zenodo.7603890">https://doi.org/10.5281/zenodo.7603890</a>.</p> </blockquote>
Distribution and habitat suitability maps for Central European steppe plants
<p>This dataset contains distribution maps for Central European steppe plants and coordinates of species occurrence points used by Divíšek et al. (2022) to calibrate habitat suitability models. These models were projected onto past climates and the resulting habitat suitability maps for 10 periods since the Last Glacial Maximum (LGM) are also included. These maps were further used as input data for simulations of species migration from climatically suitable areas in the LGM to identify those that may have served as a source for colonisation of the species' current ranges. For each species, we present maps of climatically suitable areas during the LGM and mid-Holocene (for the latter period, only areas accessible from the LGM are shown), as well as maps of the "source areas" from which the species may have colonised the regions occupied today.</p>
GRTS master sample for habitat monitoring in Flanders
<p>Spatially balanced sample for the whole of Flanders and the Brussels Capital Region based on the Generalized Random-Tessellation Stratified (GRTS) method (Stevens and Olsen, 2004). The sample consists of a grid of 32 meter x 32 meter cells, each having a unique ranking number. This so-called master sample is used as a basis to draw samples for different Natura 2000 habitat types in Flanders. A sample with sample size <em>n</em> for a certain habitat type is selected as follows: (1) select all grid cells of the master sample that overlap with the sampling frame of the target habitat type and (2) select the <em>n</em> grid cells with the lowest ranking number.</p>
GRTSmh_base4frac: the raster data source GRTSmaster_habitats converted to base 4 fractions
<p>The data source file is a monolayered GeoTIFF in the <code>FLT8S</code> datatype. In <code>GRTSmh_base4frac</code>, the decimal (i.e. base 10) integer values from the raster data source <code>GRTSmaster_habitats</code> (<a href="https://doi.org/10.5281/zenodo.2682323">link</a>) have been converted into base 4 fractions, using a precision of 13 digits behind the decimal mark (as needed to cope with the range of values). For example, the integer <code>16</code> (<code>= 4^2</code>) has been converted into <code>0.0000000000100</code> and <code>4^12</code> has been converted into <code>0.1000000000000</code>.</p> <p>Long base 4 fractions seem to be handled and stored easier than long (base 4) integers. This approach follows the one of Stevens & Olsen (2004) to represent the reverse hierarchical order in a GRTS sample as base-4-fraction addresses.</p> <p>See R-code in the GitHub repository <a href="https://github.com/inbo/n2khab-preprocessing/tree/ecadaf54d4a5aa662d0d18fbfe59788732bb7182/src/generate_GRTS_10_GRTSmh_base4frac">'n2khab-preprocessing' at commit ecadaf5</a> for the creation from the <code>GRTSmaster_habitats</code> data source.</p> <p>A reading function to return the data source in a standardized way into the R environment is provided by the R-package <a href="https://inbo.github.io/n2khab/">n2khab</a>.</p> <p>Beware that not all GRTS ranking numbers are present in the data source, as the original GRTS raster has been clipped with the Flemish outer borders (i.e., not excluding the Brussels Capital Region).</p>
Habitat characteristics and species abundances of reptiles in northern Israel
<p>Data and auxiliary information collected in a field survey of reptile assemblages in northern Israel, conducted in the spring seasons from 2016 to 2018. Data were collected in 272 Mediterranean woodland and shrubland sites, exposed to different types of human land uses. Sites are located along a geo-climatic gradient of 120 km, with elevations between 50 m and 1,570 m above sea level. Species data contains the abundances of 15 lizards, six snakes and one tortoise. The species included in the data are:</p> <p><em>Mediodactylus orientalis, Ptyodactylus puiseuxi, Chamaeleo chamaeleon, Phoenicolacerta kulzeri, Phoenicolacerta laevis, Lacerta media, Ophisops elegans, Ablepharus rueppellii, Chalcides guentheri, Heremites vittate, Pseudopus apodus, Dolichophis jugularis, Hemorrhois nummifer, Platyceps collaris, Malpolon insignitus, Daboia palaestinae, Testudo graeca, Ptyodactylus guttatus, Laudakia stellio, Chalcides ocellatus, Eumeces schneideri, Psammophis schokari, </em>and<em> </em>unidentified lizard species.</p> <p>Data columns are:</p> <p>Sample = sample site code</p> <p>Date = sampling date</p> <p>Region = name of sub region in northern Israel</p> <p>Locality = sampling site name</p> <p>T_min = average minimum annual temperature from 1970 to 2000</p> <p>T_max = average maximum annual temperature from 1970 to 2000</p> <p>Precipitation = mean annual rainfal (mm) from 1970 to 2000</p> <p>Lat_sample = latitude of the centroid of the sampling site (m, ITM coordinate system)</p> <p>Lon_sample = longitude of the centroid of the sampling site (m, ITM cooridnate system)</p> <p>Elev_MEAN = elevation above sea level (m)</p> <p>EgrtPredPress = an estimate of predation pressure by cattle egrets (based on distance to nearest colony and colony size)</p> <p>Closeness = a visual estimate of vegetation cover</p> <p>Barrenness = a visual estimate of the amount of non-vegetated cover</p> <p>DISTURB = a visual estimate of the amount of anthropogenic disturbance to the site</p> <p>CATTLE = a visual estimate of cattle grazing pressure</p> <p>GOATS = a visual estimate of goat grazing pressure</p> <p>Shannon_LC = Shannon's index of habitat diversity</p> <p>Ndvi_MEAN = mean value of the normalized difference vegetation index captured by Landsat satellite imagery in August 2020</p> <p>Ndvi_STD = standard deviation of the values of the normalized difference vegetation index captured by Landsat satellite imagery in August 2020</p> <p>PreyLizAbun = total abundance of reptile species identified as cattle egret prey</p> <p>HerpAbun = total reptile abundance</p> <p>SpeciesRich = total species richness</p> <p>Columns 23 - 46: abundances of individual reptile species</p>
Standardized map of habitat types and regionally important biotopes in Flanders
<p>The <code>habitatmap_stdized.gpkg</code> file is a processed version of the <a href="https://www.vlaanderen.be/datavindplaats/catalogus/biologische-waarderingskaart-en-natura-2000-habitatkaart-toestand-2023">Natura 2000 habitat map of Flanders</a> (De Saeger et al., 2023; see also De Saeger et al. 2017). It contains all polygons with Natura 2000 habitat types or regional important biotopes (RIB). This file is used as a basis for designing monitoring schemes in Flanders. </p> <p>In the original habitat map, every polygon can consist of maximum 5 different types (habitat (sub)types and regionally important biotopes). This information is stored in the columns <code>HAB1</code>, <code>HAB2</code>,..., <code>HAB5</code> of the attribute table. The fraction of each type within the polygons is stored in the columns <code>PHAB1</code>, <code>PHAB2</code>, ..., <code>PHAB5</code>.</p> <p>The <code>habitatmap_stdized.gpkg</code> file is a GeoPackage that contains:</p> <ul> <li><code>habitatmap_polygons</code>: a spatial layer with every habitat map polygon that contains a Natura 2000 habitat or RIB type.</li> <li><code>habitatmap_types</code>: a table with information on the habitat and RIB types (HAB1, HAB2,..., HAB5) that occur within each polygon of <code>habitatmap_polygons.</code></li> </ul> <p>The processing of the habitatmap_types table included following adjustments:</p> <ul> <li>For some polygons the type is uncertain, and the type code in the raw habitatmap data source consists of 2 or 3 possible types, separated with a ','. The different possible types are split up and one row is created for each of them, with <code>phab</code> for each new row simply set to the original value of <code>phab</code>. The variable <code>certain</code> will be <code>FALSE</code> if the original type code consists of 2 or 3 possible types, and <code>TRUE</code> if only one type is provided.</li> <li>Some polygons contain both a standing water habitat type and <code>rbbmr</code>: <ul> <li><code>3130_rbbmr</code>,</li> <li><code>3140_rbbmr</code>,</li> <li><code>3150_rbbmr</code>, and</li> <li><code>3160_rbbmr</code>.</li> </ul> </li> <li>Since <code>habitatmap_stdized_2020_v1</code>, the two types <code>31xx</code> and <code>rbbmr</code> are split up and one row is created for each of them, with <code>phab</code> for each new row simply set to the original value of <code>phab</code>. The variable certain in this case will be <code>TRUE</code> for both types.</li> <li>After those steps, a given polygon could contain the same type with the same value for <code>certain</code> repeated several times, e.g. when <code>31xx_rbbmr</code> is present with <code>phab</code> = yy% and <code>31xx</code> is present with <code>phab</code> = zz%. In that case the rows with the same <code>polygon_id</code>, <code>type</code> and <code>certain</code> were gathered into one row and the respective phab values were added up.</li> </ul> <p>The R-code for creating the <code>habitatmap_stdized</code> data source can be found in the GitHub repository <a href="https://github.com/inbo/n2khab-preprocessing/tree/abf596e/src/generate_habitatmap_stdized">'n2khab-preprocessing' at commit abf596e</a>.</p> <p>A reading function to return the data source in a standardized way into the R environment is provided by the R-package <a href="https://github.com/inbo/n2khab">n2khab</a>.</p> <p>Attributes of <code>habitatmap_polygons</code>:</p> <ul> <li><code>polygon_id</code></li> <li><code>description_orig</code>: polygon description based on the original type codes in the raw habitatmap </li> </ul> <p>Attributes of <code>habitatmap_types</code>:</p> <ul> <li><code>polygon_id</code></li> <li><code>type</code>: the interpreted habitat or RIB type</li> <li><code>certain</code>: <code>TRUE</code> when type is certain and <code>FALSE</code> when type is uncertain</li> <li><code>code_orig</code>: original type code in raw habitatmap</li> <li><code>phab</code>: proportion of polygon covered by type, as a percentage.</li> </ul> <p>Since version <code>habitatmap_stdized_2020_v1</code>, rows are unique only by the combination of the <code>polygon_id</code>, <code>type</code> and <code>certain</code> columns.</p>
Functional redundancy of non-volant small mammals increases in human-modified habitats
<p>This repository hosts all R codes, data and output supporting the findings of the study "Functional redundancy of non-volant small mammals increases in human-modified habitats", by André L. Luza (UFRGS, BR), Catherine H. Graham (WSL, CH), Sandra M. Hartz (UFRGS, BR), and Dirk, N. Karger (WSL, CH).</p> <p>The only data that are not here are the Ecoregions of WWF. These data can be found in the webpage of WWF.</p>
Population genomics reveals differences in genetic structure between two endemic arboreal rodent species in threatened cloud forest habitat
<p>SNPs obtained by UNEAK pipeline for <em>Habromys schmidlyi </em>and <em>Reithrodontomys microdon</em>. </p> <p>Pleae cite as: </p> <p>Colunga-Salas P., T Marines-Macías, G Hernández-Canchola, S Barbosa, C Ramírez, JB Searle, L León-Paniagua. 2022. <strong>Population genomics reveals differences in genetic structure between two endemic arboreal rodent species in threatened cloud forest habitat</strong>. Mammalian Reasearch. Doi: 10.1007/s13364-022-00667-x</p>
Common Raven (Corvus corax) Occupancy Survey and Habitat Selection Data in Cliff Habitat of the Central Appalachian Region, USA, 2009-2010
We identified 24 cliff sites across four states of the Central Appalachian Region of the eastern USA (Kentucky, North Carolina, Virginia, and West Virginia) with known raven occupancy at which to perform occupancy surveys for estimating detection probability and the effects of covariates. We surveyed each cliff site 2-4 times in either 2009 or 2010 and recorded time-to-first detection and time to confirmed cliff occupancy during a two-hour survey. Daily surveys were completed between 06:00 and local solar noon. During each survey, we recorded covariates, including air temperature at survey start time, cloud cover, wind speed, and day of year. We also calculated the distance of the observation point from the cliff being surveyed and the forest cover around the cliff. We also collected data thought to be pertinent for habitat selection by ravens on 26 cliffs occupied by ravens and 26 cliffs deemed unoccupied by ravens in 2010. For each cliff, we measured cliff physiographic characteristics, such as cliff length, cliff height, and occlusion by vegetation, and landscape characteristics, including percent forest and urban cover around the cliff and distances from the cliff to the nearest road and human habitation.
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.
Monitoring of Microtus ochrogaster and Microtus pennsylvanicus populations in three different habitats in east-central Illinois, 1972 to 1997.
Populations of 2 species of arvicoline rodents, the prairie vole (Microtus ochrogaster) and meadow vole (Microtus pennsylvanicus), were monitored monthly from 1972-1997 in three distinct habitats: restored tallgrass prairie, bluegrass (Poa pratensis) and alfalfa (Medicago sativa). The study sites were located in the University of Illinois Biological Research Area (Phillips Tract) and Trelease Prairie. Tallgrass prairie was the original habitat of both species in Illinois. Bluegrass, an introduced species, represents the more common habitat in which the two species can be found today in Illinois. Alfalfa, an atypical habitat, provides an abundant source of high-quality food for both species. At each station, one wooden multiple-capture live-trap was placed. Every month, a two-day period of prebaiting was followed by a 3-day trapping session. The data include the species, individual identification, grid station, sex, reproductive status and body mass. Over the span of 25 years, three trapping sessions monthly were conducted to cover the three habitats, dedicating three weeks each month. Several papers have been based on these data.
Consumption rates of tethered live and dead pinfish and dried squid in mudflat and seagrass habitats in the Upper Laguna Madre in 2018.
These data were recorded during surveys of a tethering experiment conducted on June 7, 2018, during which 180 tethered prey were deployed in two habitat types (seagrass and mudflat) in the Upper Laguna Madre, Texas, USA (27.544006, -97.285912). In each habitat, the following prey types were deployed: squidpops (1 cm2 discs of dried squid (Duffy et al. 2015) attached to 5 cm tethers, n=50), live (n=20) and dead (n=20) pinfish (Lagodon rhomboides, 4 cm fork length, attached to 20 cm tethers) at midday in each habitat. The presence/absence of tethered prey on each stake was observed and recorded after 1 hour and 24 hours. The rate of decay (i.e., disappearance or consumption rate of tethered prey over time) was calculated as the slope of an exponential model fit to discrete observations of the presence/absence of tethered prey over time. Additional environmental variables (temperature, salinity) were also recorded at the site.
Influence of cockle bioturbation on microphytobenthic primary producers: habitat and density-dependent effect
The purpose of this study was to better understand the non-trophic interactions of benthic macrofauna, especially through their bioturbation activity, on microphytobenthos (MPB), which remain poorly studied and understood. For this purpose, a mesocosm experiment was performed, using the common cockles Cerastoderma edule. This species plays a key role in coastal ecosystem, especially impacting sediment characteristics and biogeochemistry through their bioturbation, including sediment reworking and bioirrigation. For the first time, bioturbation rates, biogeochemical fluxes at the sediment-water interface and MPB biomass and photosynthetic variables were measured at the same time. The effect of cockles density and sediment type were also investigated. This mesocosm experiment took place at the marine station of Arcachon. Experimental units consisted of PVC tubes filled with 2 types of sediment (medium sand or fine sand; samples in Arachon Bay and Baie des Veys in France). Then, 4 density of cockles were added in triplicate (0, 288, 720 and 1,297 ind. m-2), for each sediment type. The whole design was repeated twice, because in one of them luminophores were added at the top to measure sediment reworking, and could interfere with fluorescence measurement of MPB variables. All experimental units were incubated 6 days into a big tank, with artificial tide and light. Dissolved tracers were added into the natural seawater (close system) to measure bioirrigation rates of cockles. After 6 days, regarding experimental units with luminophores, they were slices and porewater was extracted to quantify bioturbation rates. Regarding units without luminophores, surface biomass and photosynthetic parameters of MPB were first measured in all unit with an IMAGING PAM. Then, oxygen and nutrient fluxes at the sediment water interface were measured using incubations. And finally, the first centimeter was sliced to measure total MPB biomass. This study demonstrated that bioturbation intens
CBP01 Variable distance line-transect sampling of bird population numbers in different habitats on Konza Prairie (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-knz/26/11. The abstract below was extracted from the Level 0 data package and is included for context: Records of bird species based on line transect sampling, giving perpendicular distance of sighting from the transect line on 16 separate transects. Bird surveys were conducted 2-4 times per year in January, April, June, and October for a 29-year period from 1981 to 2009. Transects were designed to determine bird communities and population numbers associated with tallgrass prairie habitats with different experimental treatments (fire frequency, grazed by bison vs. ungrazed), riparian habitats on forest edge, and gallery forests dominated by oak woodland.
Greenhouse gas fluxes and concentrations and associated habitat data in western Dane County, Wisconsin, USA, streams during the 2018 growing season
Streams are often sources of carbon dioxide (CO2) and methane (CH4), particularly in agricultural regions where sediment and organic matter inputs can be substantial. Floods are occurring more often and more intensely in southern Wisconsin, one such agricultural region, due to climate change and few studies have investigated how floods impact stream CO2 and CH4 fluxes and concentrations. I compared concentrations and fluxes of CO2 and CH4 with greater than 30 variables representing in-stream and watershed attributes at 10 sites in mixed agricultural and suburban locations in southern Wisconsin. Sampling was conducted 10 times at each site during the growing season (May-November) in 2018
Salmonid habitat use monitoring used to determine effectiveness of habitat improvement projects in the Sacramento River, CA
Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains five datasets. Enclosure Study – Growth Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Fish growth was tracked for approximately 6.5 weeks. Annual reports summarize the survey findings. Enclosure Study – Gut Contents Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Enclosures remained in the river for approximately 6.5 weeks. At the end of the study, fish were euthanized, and we dissected their guts and enumerated the taxa found. Annual reports summarize the survey findings. Microhabitat Use Data This dataset covers salmonid microhabitat use conducted in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Surveys are conducted roughly monthly and include pre-project sites, constructed habitat project sites, and control sites where no treatment is planned. Based upon habitat inventory data, annually identify which habitat units within each side channel will be selected for the collectio
Habitat use, consumption, and growth by slimy sculpin (Cottus cognatus) held under different levels of temperature at Toolik Field Station 2019
We tested effects of temperature (12 and 19.3 degrees C; 27 days) on habitat use, consumption, and growth of slimy sculpin (Cottus cognatus). To measure temperature selection by sculpin, we connected two 5.7 L tanks with a PVC pipe that was passable by sculpin (n = 12 tanks). We heated one side of the tank to 12 °C and the other to 19.3 °C using aquarium heaters.
Coweeta Synoptic Data from 49 sampling sites in the Upper Little Tennessee River Basin from 2009 to 2010 (mesoscale habitat data)
This data was generated as part of synoptic sampling conducted at the Coweeta LTER between June 2009 and May 2010. 49 wadeable streams with low levels of development were sampled throughout the Upper Little Tennessee River Basin in the Southern Appalachians. Effects of riparian vegetative conditions on a suite of channel morphological variables were investigated: active channel width, variability of width within a reach, large wood frequency, mesoscale habitat distributions, median particle size, and percent fines. Stream mesoscale habitat areas for each 150 m stream reach were recorded in this particular dataset. At each site, a uniform 150 meter section of stream was surveyed. Observers kept a running tally of the areas associated with various mesoscale habitat units including, cascades, riffles, pools, alcoves, pocket water, runs, glides, and obstructions.
AFLP and MS-AFLP data for Spartina alterniflora and Borrichia frutescens collected from three habitats (i.e. low, medium, and high salt) within five sites, respectively, on Sapelo Island, GA in May 2011
Using amplified fragment length polymorphism (AFLP) and methylation sensitive (MS)-AFLP we assessed genetic and epigenetic variation in two salt marsh perennials, Spartina alterniflora and Borrichia frutescens, in Sapelo Island, Georgia. We sampled Apex (A), Cabretta (C), Hunt Camp (H), Lighthouse (L), and Marsh Landing (M) for S. alterniflora, and C, H, L, M, and Shell Hammock for B. frutescens due to site specific differences in species among the sites. We tested the hypothesis that populatation structure at the habitat level would be due to epigenetic loci and not genetic. The presence and absence AFLP bands and MS-AFLP methylation respresents a genome-wide snapsnot of variation within individuals. We used hierarchical AMOVAs, permutational MANOVA, Bayesian clustering (genetic only), Mantel and partial Mantel tests, and generalized linear models to assess the spatial structure of genetic and epigenetic variation among our two study organisms across five sites for each organism. (Note: genetic and habitat distance tables were normalized for database compatibility. These data must be formatted as a square dissimilarity matrix for input to the code files.)
May to July 2018 ground control points GPS coordinates of tidal marsh and tidal forest plant species to be used as ground control points in habitat mapping.
We collected field data from sites distributed in habitats along the salinity axis of the Altamaha River estuary and the Duplin River to be used as ground control points (GCP) and ground reference data for habitat mapping. GCPs for tidal marsh (salt, brackish, tidal fresh) and tidal fresh forest vegetation species were acquired. A real time kinematic (RTK) GPS survey of GPS coordinates and ground elevations for tidal marsh vegetation was carried out in May of June of 2018. A handheld GPS was used to collect GPS coordinates for tidal forest plant species in July of 2018. A total of 101 GCPs were collected in tidal habitats, with 26 in salt, 28 in brackish and 29 in tidal fresh marsh, and another 18 in tidal fresh forest. These observations will be used to create habitat maps from aerial photographs of the Altamaha River estuary, GA taken following Hurricane Irma to better understand how the storm surge affected tidal vegetation and to examine any shifts in vegetation type.
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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.