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253 results for “regional level”
Data from: Numbers and distribution of the Great Cormorant in Iceland: limitation at the regional and metapopulation level
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Patch-level facilitation fosters high-Andean plant diversity at regional scales
<p>Survey of the alpine vegetation in seven mountains of the Patagonian Andes from January to March of 2017 and 2018. On each mountain, we established one study site at each of three elevations (1600, 1800 and 2000 m). Accordingly, we sampled a total of 21 alpine plant communities (i.e., seven mountains x three elevations) dominated by cushion plants. At each community, 50 individual cushion plants were haphazardly selected within an area of approx. 0.5 ha, pairing each cushion with an adjacent non-cushion or open area 50 cm away in a random direction. In order to sample a similar surface in the surrounding open area, a wire hoop was shaped to match the size of the sampled cushion that was then placed on the ground. The number and identity of all plant species were recorded at both cushion and open area plots. Given that cushion plants are roughly elliptical, microsites were defined as elliptical plots, and thus, the longer and shorter axes of each cushion were measured as an approximate estimation of its area. In total, we sampled 2100 plots (1050 cushion plants and 1050 open area plots).</p>
Figure 2 from: Al-Nadaf AH, Awadallah A (2020) Evaluation for the level of knowledge about herbal medicine use within people and university students in Mutah region. Pharmacia 67(4): 397-403. https://doi.org/10.3897/pharmacia.67.e59319
Figure 2 Illnesses for which herbal drugs are used among participants. Participants answer for open-ended question: Illnesses for which herbs are used other than mentioned in the questionnaire.
Figure 1 from: Al-Nadaf AH, Awadallah A (2020) Evaluation for the level of knowledge about herbal medicine use within people and university students in Mutah region. Pharmacia 67(4): 397-403. https://doi.org/10.3897/pharmacia.67.e59319
Figure 1 Source of herbal information. The chart shows the sources of information about way and recipes to herbal drugs.
Data from: Meta-analysis reveals enhanced growth of marine harmful algae from temperate regions with warming and elevated CO2 levels
Elevated pCO2 and warming may promote algal growth and toxin production, and thereby possibly support the proliferation and toxicity of HABs. Here, we tested whether empirical data supports this hypothesis using a meta-analytic approach and investigated the responses of growth rate and toxin content or toxicity of numerous marine and estuarine HAB species to elevated pCO2 and warming. Most of the available data on HAB responses towards the two tested climate change variables concerns dinoflagellates, as many members of this phytoplankton group are known to cause HAB outbreaks. Toxin content and toxicity did not reveal a consistent response towards both tested climate change variables, while growth rate increased consistently with elevated pCO2 . Warming also led to higher growth rates, but only for species isolated at higher latitudes. The observed gradient in temperature growth responses shows the potential for enhanced development of HABs at higher latitudes. Increases in growth rates with more CO2 may present an additional competitive advantage for HAB species, particularly as CO2 was not shown to enhance growth rate of other non-HAB phytoplankton species. However, this may also be related to the difference in representation of dinoflagellate and diatom species in the respective HAB and non-HAB phytoplankton groups. Since the proliferation of HAB species may strongly depend on their growth rates, our results warn for a greater potential of dinoflagellate HAB development in future coastal waters, particularly in temperate regions.
Distribution of economic damages due to climate-driven sea-level rise across European regions and sectors
<p>The datasets generated during and/or analysed during the study</p>
Comment on Krüger (2023): Decreasing Trends of Chinstrap Penguin Breeding Colonies in a Region of Major and Ongoing Rapid Environmental Changes Suggest Population Level Vulnerability. Diversity 2023, 15, 327
<p>Data and analyis scripts for:</p> <p><strong>Comment on Krüger (2023): Decreasing Trends of Chinstrap Penguin Breeding Colonies in a Region of Major and Ongoing Rapid Environmental Changes Suggest Population Level Vulnerability. Diversity 2023, 15, 327</strong></p> <p>W. Chris Oosthuizen, Murray Christian, Mzabalazo Ngwenya</p> <p>Centre for Statistics in Ecology, Environment and Conservation, Department of Statistical Sciences, University of Cape Town, Cape Town, 7701, South Africa</p> <p><strong>Abstract</strong></p> <p>Historical data on chinstrap penguin (<em>Pygoscelis antarctica</em>) breeding population sizes are sparse and sometimes highly uncertain, making it hard to estimate true population trajectories. Yet, information on population trends is desirable as changes in population size can help inform conservation assessments. Krüger (2023) (<em>Diversity</em> 2023, 15, 327) used chinstrap penguin nest count data to predict breeding colony size trends between 1960 and 2020, to estimate whether the level of population change within three generations exceeded IUCN Red List Criteria for "Vulnerable" populations. Chinstrap penguin population trends are an important research topic, but we caution that Krüger (2023)’s statistical analyses (intended to form the foundation for drawing valid, evidence-based inferences from sparse data) contain fundamental errors that invalidate that paper's findings. We discuss these oversights to help others detect and avoid some of the pitfalls associated with estimating population trends with mixed models. While we do not address all challenges, we also show through reanalysis that improved statistical modelling can yield better predictions of chinstrap penguin population trends, at least within the range of observed data. This case study highlights (1) the profound influence that seemingly minor differences in modelling procedures (both unintentional errors and other decisions) can have on predictions of population trends, and (2) the substantial inherent uncertainty in population trend predictions derived from sparse, heterogenous data.</p> <p> Keywords: Antarctic Peninsula, IUCN red list criteria, Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD), population assessment, population trend, <em>Pygoscelis antarctica, </em>reproducible research</p>
Enhancing Regional Quasi-Geoid Refinement Precision: An Analytical Approach Employing ADS80 Tri-linear Array Stereoscopic Imagery for Aerial Triangulation Densification and GNSS Gravity-Potential Leveling
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FluView National, Regional, and State Level Outpatient Illness and Viral Surveillance 2017-2018 (archived by MIDAS-ISG)
<p>Description from the FluView Interactive web application (from which these files were downloaded):</p> <p>Viral Surveillance — Data collection from both the U.S. World Health Organization (WHO) Collaborating Laboratories and National Respiratory and Enteric Virus Surveillance System (NREVSS) laboratories began during the 1997-98 season. The volume of tested specimens has greatly increased during this time due to increased participation and increased testing. During the 1997-98 season 43 state public health laboratories participated in surveillance, and by the 2004-05 season all state public health laboratories were participating in surveillance. The addition of NREVSS data during the 1997-98 season roughly doubled the amount of virologic data reported each week. </p> <p>The number of specimens tested and % positive rate vary by region and season based on different testing practices including triaging of specimens by the reporting labs, therefore it is not appropriate to compare the magnitude of positivity rates or the number of positive specimens between regions or seasons. </p> <p>The U.S. WHO and NREVSS collaborating laboratories report the total number of respiratory specimens tested and the number positive for influenza types A and B each week to CDC. Most of the U.S. WHO collaborating laboratories also report the influenza A subtype (H1 or H3) of the viruses they have isolated, but the majority of NREVSS laboratories do not report the influenza A subtype. </p> <p>For more information on virologic surveillance please visit:http://www.cdc.gov/flu/weekly/overview.htm#Viral</p> <p>Outpatient Illness Surveillance — Information on patient visits to health care providers for influenza-like illness is collected through the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). This collaborative effort between CDC, state and local health departments, and health care providers started during the 1997-98 influenza season when approximately 250 providers were enrolled. Enrollment in the system has increased over time and there were >3,000 providers enrolled during the 2010-11 season.</p> <p>The number and percent of patients presenting with ILI each week will vary by region and season due to many factors, including having different provider type mixes (children present with higher rates of ILI than adults, and therefore regions with a higher percentage of pediatric practices will have higher numbers of cases). Therefore it is not appropriate to compare the magnitude of the percent of visits due to ILI between regions and seasons.</p> <p>Baseline levels are calculated both nationally and for each region. Percentages at or above the baseline level are considered to be elevated.</p> <p>For more information on ILI surveillance and baselines please visit:http://www.cdc.gov/flu/weekly/overview.htm#Outpatient</p>
FluView National, Regional, and State Level Outpatient Illness and Viral Surveillance 2016-2017 (archived by MIDAS-ISG)
<p>Description from the FluView Interactive web application (from which these files were downloaded):</p> <p>Viral Surveillance — Data collection from both the U.S. World Health Organization (WHO) Collaborating Laboratories and National Respiratory and Enteric Virus Surveillance System (NREVSS) laboratories began during the 1997-98 season. The volume of tested specimens has greatly increased during this time due to increased participation and increased testing. During the 1997-98 season 43 state public health laboratories participated in surveillance, and by the 2004-05 season all state public health laboratories were participating in surveillance. The addition of NREVSS data during the 1997-98 season roughly doubled the amount of virologic data reported each week. </p> <p>The number of specimens tested and % positive rate vary by region and season based on different testing practices including triaging of specimens by the reporting labs, therefore it is not appropriate to compare the magnitude of positivity rates or the number of positive specimens between regions or seasons. </p> <p>The U.S. WHO and NREVSS collaborating laboratories report the total number of respiratory specimens tested and the number positive for influenza types A and B each week to CDC. Most of the U.S. WHO collaborating laboratories also report the influenza A subtype (H1 or H3) of the viruses they have isolated, but the majority of NREVSS laboratories do not report the influenza A subtype. </p> <p>For more information on virologic surveillance please visit:http://www.cdc.gov/flu/weekly/overview.htm#Viral</p> <p>Outpatient Illness Surveillance — Information on patient visits to health care providers for influenza-like illness is collected through the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). This collaborative effort between CDC, state and local health departments, and health care providers started during the 1997-98 influenza season when approximately 250 providers were enrolled. Enrollment in the system has increased over time and there were >3,000 providers enrolled during the 2010-11 season.</p> <p>The number and percent of patients presenting with ILI each week will vary by region and season due to many factors, including having different provider type mixes (children present with higher rates of ILI than adults, and therefore regions with a higher percentage of pediatric practices will have higher numbers of cases). Therefore it is not appropriate to compare the magnitude of the percent of visits due to ILI between regions and seasons.</p> <p>Baseline levels are calculated both nationally and for each region. Percentages at or above the baseline level are considered to be elevated.</p> <p>For more information on ILI surveillance and baselines please visit:http://www.cdc.gov/flu/weekly/overview.htm#Outpatient</p>
FluView National, Regional, and State Level Outpatient Illness and Viral Surveillance 2015-2016 (archived by MIDAS-ISG)
<p>Description from the FluView Interactive web application (from which these files were downloaded):</p> <p>Viral Surveillance — Data collection from both the U.S. World Health Organization (WHO) Collaborating Laboratories and National Respiratory and Enteric Virus Surveillance System (NREVSS) laboratories began during the 1997-98 season. The volume of tested specimens has greatly increased during this time due to increased participation and increased testing. During the 1997-98 season 43 state public health laboratories participated in surveillance, and by the 2004-05 season all state public health laboratories were participating in surveillance. The addition of NREVSS data during the 1997-98 season roughly doubled the amount of virologic data reported each week. </p> <p>The number of specimens tested and % positive rate vary by region and season based on different testing practices including triaging of specimens by the reporting labs, therefore it is not appropriate to compare the magnitude of positivity rates or the number of positive specimens between regions or seasons. </p> <p>The U.S. WHO and NREVSS collaborating laboratories report the total number of respiratory specimens tested and the number positive for influenza types A and B each week to CDC. Most of the U.S. WHO collaborating laboratories also report the influenza A subtype (H1 or H3) of the viruses they have isolated, but the majority of NREVSS laboratories do not report the influenza A subtype. </p> <p>For more information on virologic surveillance please visit:http://www.cdc.gov/flu/weekly/overview.htm#Viral</p> <p>Outpatient Illness Surveillance — Information on patient visits to health care providers for influenza-like illness is collected through the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). This collaborative effort between CDC, state and local health departments, and health care providers started during the 1997-98 influenza season when approximately 250 providers were enrolled. Enrollment in the system has increased over time and there were >3,000 providers enrolled during the 2010-11 season.</p> <p>The number and percent of patients presenting with ILI each week will vary by region and season due to many factors, including having different provider type mixes (children present with higher rates of ILI than adults, and therefore regions with a higher percentage of pediatric practices will have higher numbers of cases). Therefore it is not appropriate to compare the magnitude of the percent of visits due to ILI between regions and seasons.</p> <p>Baseline levels are calculated both nationally and for each region. Percentages at or above the baseline level are considered to be elevated.</p> <p>For more information on ILI surveillance and baselines please visit:http://www.cdc.gov/flu/weekly/overview.htm#Outpatient</p>
Figure 11 in Epilithic biofilms of the Eastern Caspian (Aktau region, Kazakhstan) under conditions of falling sea level
Figure 11. Fibrous brown biofilms that grow in narrow low areas of the landscape of the middle and upper pseudolittoral in presence of water flow. General view of biofilms in a thin layer of water flowing to the sea (a) and fragments of diatom microfouling on the surface of Enteromorpha sp. (b, c). Designations: csh - colonial settlements of Halamphora borealis, ad – araphid diatoms, e.g. Tabularia fasciculata. Scale bar: a - 5 cm, b – 100 µm, c- 10 µm. Photos by Philipp Sapozhnikov, Olga Kalinina.
Figure 8 in Epilithic biofilms of the Eastern Caspian (Aktau region, Kazakhstan) under conditions of falling sea level
Figure 8. Biofilm on clay soil in the "lagoon" (location 1, April 2023). General view of the community in the pseudolittoral landscape (a) and its fragment when assembled x400 (b). Designations: h — cells of different Halamphora species. Scale bar: a - 5 cm, b - 20 µm. Photos by Philipp Sapozhnikov.
Figure 5 in Epilithic biofilms of the Eastern Caspian (Aktau region, Kazakhstan) under conditions of falling sea level
Figure 5. Fragments of biofilms lining the bottom of cauldrons and washout furrows on the tops of sheer cliffs in October 2022. Designations: lm - Lyngbya cf. major, br - Berkeleya rutilans. Scale bar: 20 µm. Photos by Philipp Sapozhnikov.
Figure 4 in Epilithic biofilms of the Eastern Caspian (Aktau region, Kazakhstan) under conditions of falling sea level
Figure 4. Fragments of a black biofilm formed on rocks in the surf zone: a — October 2022, b — April 2023. Scale bar: 20 μm. Designations: gc - Gloeocapsa crepidinum, cg - Calothrix geitonos, cm - Calothrix micromeres, br - Berkeleya rutilans. Photos by Philipp Sapozhnikov.
Figure 7 in Epilithic biofilms of the Eastern Caspian (Aktau region, Kazakhstan) under conditions of falling sea level
Figure 7. Algal-bacterial mat (a) formed in longitudinal puddles (marl folds) on the upper pseudolittoral by mid-April 2023 (location 5). A fragment of the mat at x400 magnification (b), the structural basis is formed by mucous colonies of the smallest cyanobacteria. Designations: np – Navicymbula pusilla, chl – Chroococcus limneticus, lpo - Leptolyngbya ochridana, gl – Gomphosphaeria aponina. Scale bar: a — 5 cm, b — 20 µm. Photos by Philipp Sapozhnikov.
Figure 6 in Epilithic biofilms of the Eastern Caspian (Aktau region, Kazakhstan) under conditions of falling sea level
Figure 6. Fragments of biofilms that covered the bottom of puddles in marl folds on the upper pseudolittoral: a — filamentous green algae; b — microfouling (microepiphyton) on the surface of the thallus of Rhizoclunium sp. Designations: c – Cladophora sp., rh – Rhizoclunium sp., tw - Tabularia waernii, chq - Chroococcus quaternarius. Scale bar: a – 50 µm, b – 20 µm. Photos by Philipp Sapozhnikov.
Figure 2 in Epilithic biofilms of the Eastern Caspian (Aktau region, Kazakhstan) under conditions of falling sea level
Figure 2. Examples of biotops at the newly dry coast of the Caspian Sea in the City of Aktau: a, b - sheer cliffs irrigated by surf; c, d - folded marl forming flat areas of the pseudolittoral. Photos by Philipp Sapozhnikov.
Gas Temperature and Plasma Discharge Region Temperature at Different Input Power Levels
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FIGURE 30A–B in The water mite family Mideopsidae (Acari: Hydrachnidia): a contribution to the diversity in the Afrotropical region and taxonomic changes above species level
FIGURE 30A–B. Djeboa nzia sp. nov. male: A = idiosoma, ventral view; B = palp.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.