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26 results for “climate monitoring”
Vibration-based Monitoring of a Small-scale Wind Turbine Blade Under Varying Climate Conditions. Part I: An Experimental Benchmark
<p>This repository contains all publicly available data related to the experimental part of <a href="https://onlinelibrary.wiley.com/doi/epdf/10.1002/stc.2660">Sonkyo-Benchmark</a>. The data of each experimental case (R, A, B, C, D, E, F, G, H, I, J, K, L) and temperature point (-15, -10, -5, 0, 5, 10, 15, 20, 25, 30, 35, 40) are stored in a zip file named "Case_<em>X</em>_(<em>T</em>)", where <em>X</em> denotes the case label and <em>T</em> refers to the temperature value. Each file "Case_<em>X</em>_(<em>T</em>).zip" contains two folders "Case_<em>X</em>_(<em>T</em>)_1" and "Case_<em>X</em>_(<em>T</em>)_2", wherein the test results from the two sensor layouts are stored. </p>
Data from Yellow Sigatoka monitoring methods in the subtropical climate of southern Brazil
<h2>Description of the data and file structure</h2> <p>In this study four methods of disease monitoring were tested under field conditions: Biological Pre Warning (BPW); Stage of Evolution (SE); youngest Leaf Spotted (YLS); Infection Index (II). The BPW system evaluates the youngest leaves (2, 3, and 4), assigning a value for each type of lesion present, as well as for intensity of the lesion on the leaves (BUREAU et al., 1992). In the dataset is cited as the variable gross sum (points).</p> <p>The SE evaluates more leaves (1, 2, 3, 4, and 5) and scores only the most advanced symptoms of leaf disease, but without considering lesion intensity (GANRY et al., 2008). The SE calculation also corrects the gross sum of the disease according to leaf emission. The leaf emission rate was calculated using the Brun scale, which evaluates cigar leaf growth in decimals from 0.0 to 0.8. In the dataset is cited as the variable corrected gross sum (points).</p> <p>YLS is evaluated as the first leaf that has 10 spots with gray centers (CARLIER et al., 2003). In the dataset is cited as the variable YLS, which means the leaf position counted from the top to the botton of the plant (leaf number 3, leaf number 4...).</p> <p>Sigatoka Infection Index is quantified by assessing the severity of banana leaf disease using the Stover scale, with indexes from 0 to 50%, by means of the following formula: Infection Index =% (IF): [Σn × b / (N- 1) × T] × 100, in which: n = the number of leaves at each Stover scale level; b = degree according to the scale; N = the number of degrees employed in the scale (6); T = the total number of leaves evaluated (CARLIER et al., 2003). In the dataset is cited as the variable Infection index that should be understood like the severity of this leaf disease.</p> <p>In the second phase of the study, two monitoring methods were applied in commercial orchards in order to compare the standard model (Biological Pre-Warning – BPW) with the alternative method selected in the experimental phase (Youngest Leaf Spotted – YLS). The methods were applied, as described before in three sites in Criciúma (site 1) and Siderópolis (sites 2 e 3), municipalities in the southern coast of the state of Santa Catarina, from March 2016 to November 2018. During this period, 37 disease evaluations were performed at each location.</p> <p>Disease data of the experimental area were submitted to descriptive analysis and Pearson correlation at 5% probability of error. Disease progress curves were also plotted. The disease development data in commercial orchards were analyzed by plotting disease progress curves for BPW and by frequency distribution (%) for the YLS variable during all period of the experiment.</p>
Figure 7. The outcomes of the Monitoring and Control of the Greenhouse soil and climate Conditions for tomato crops-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>In the past generation greenhouses it was enough to have one cabled measurement point in<br> the middle to provide the information to the greenhouse automation system. The system itself was<br> usually simple without opportunities to control locally heating, lights, ventilation or some other<br> activity, which was affecting the greenhouse interior climate. The optimal greenhouse climate and<br> soil adjustment can enable us to improve productivity and to achieve remarkable energy savings. In<br> this paper we proposed a multi-agent methodology for integrated management systems in<br> greenhouses. In this regards wireless sensor networks play a vital role to monitor greenhouse and<br> environment parameters. Each controlled process of the greenhouse environment is modeled as an<br> autonomous agent with its own inputs, its own outputs and its own interactions with the other<br> agents. Each agent acts autonomously, as it knows a priori the desired environmental set-points. In<br> this way, any possible conflicting decisions of conventional environmental control methodologies<br> are resolved through negotiations between the agents so that the possible optimal integrated solution<br> is achieved. The developed system is simple, cost effective, and easily installable.</p>
Data, code, and supplementary materials for Pearman P. B., Broennimann, O., et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nature Ecology & Evolution
<p>The repository contains several archives of digital materials that were used and/or produced in the analyses presented in Pearman, P. B. and Broennimann et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. <strong>Nature Ecology & Evolution</strong>, likely 2023. These archives include (1) Supplementary Materials files ; (2) Data and code to generate country-level maps and plots; and (3) data and code to generate all maps of species and joint climate niche marginality, all in G-zipped tar archives. Readme files are available in each archive to guide running of the scripts and identification of objects in the Supplementary Materials. Please see the paper for all co-authors names, and the methods, the results obtained, and discussion of their implications.</p> <p>This work is dedicated to the memory of our friend and colleague Michael Bruford (1963-2023).</p>
Long-term monitoring reveals forest tree community change driven by atmospheric sulfate pollution and contemporary climate change
Aim: Montane environments are sentinels of global change, providing unique opportunities to assess impacts on species diversity. Multiple anthropogenic stressors such as climate change and atmospheric pollution may act concurrently or synergistically in restructuring communities. Thus, a major challenge for conservation is untangling the relative importance of different stressors. Here, we combine long-term monitoring with multivariate community modeling to estimate the anthropogenic drivers shaping forest tree diversity along an elevational gradient. Location: Camels Hump Mountain, Vermont, USA Methods: We used Generalized Dissimilarity Modelling (GDM) to model spatial and temporal turnover in beta diversity along an elevational gradient over a 50-year period, and tested for spatiotemporal shifts in density and elevational distribution of individual species. GDMs were used to predict community turnover as non-linear functions of changes in elevation, climate and atmospheric pollution. Results: We observed significant shifts in elevational range and density of individual species, which contributed to an overall reduction in the elevational gradient in beta diversity through time. GDMs showed the combined effects of sulfate deposition and temperature as drivers of this temporal reduction in beta diversity. Spatiotemporal changes differed among species, with shifts observed both up and downslope. For example, in a reversal of a previous upslope range contraction, red spruce (Picea rubens Sarg.) increased in density and shifted downslope since the 1990's, occupying warmer, drier climates. Main conclusion: Our results demonstrate that global change is impacting the stratification of forest tree diversity along elevational gradients, but the responses of individual species are complex and variable in direction. We suggest abiotic drivers may directly impact individual species while also indirectly altering species interactions along elevational gradients. Our approach modelling the drivers of compositional turnover quantifies the rate and amount of change in beta diversity along environmental gradients, and serves as a powerful complement to studying species-specific responses.
Data from: Evaluating genotyping-in-thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non-invasive and archival samples
<p>Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Though many DNA sequencing approaches still require high quality and quantity of DNA obtained from traditional sources (e.g. blood and tissue), rapid genotyping tools such as Genotyping-in-Thousands by sequencing (GT-seq) have improved our ability to make use of degraded and less concentrated DNA commonly obtained from non-invasive and archival samples. Here, we developed a multi-purpose GT-seq panel (307 single nucleotide polymorphisms) for a climate sentinel mammal (the American pika, <em>Ochotona princeps</em>) for use as a genetic tool for monitoring populations in the Canadian Rocky Mountains. We optimized the panel using contemporary tissue samples (n = 77) and subsequently applied it to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) to evaluate its effectiveness at identifying individuals and sex, estimating relatedness, and inferring population structure. The panel demonstrated high efficacy with contemporary and archival tissue samples (94.7% and 90.5% genotyping success, respectively) and negligible genotyping error (0.001% and 0.0%, respectively). Despite relatively high genotyping success for fecal pellet samples (79.7%), high genotyping error (28.4%) limited its power as a monitoring tool to assess genetic variation using non-invasive samples and highlighted the need for further optimization around sample and data collection.</p>
Changes Monitoring in Hongjiannao Lake from 1987-2023 using Google Earth Engine and Analysis of Climatic and Anthropogenic Forces (Climatic Data)
<p>This dataset presents temporal (1987 to 2023) climatic data for the weather station near Hongjiannao Lake.</p>
King's College Cambridge wildflower meadow monitoring data: biodiversity, climate change and society
<p class="MsoNormal">The biodiversity and climate crises are critical challenges of this century. Wildflower meadows in urban areas could provide important nature-based solutions, addressing the biodiversity and climate crises jointly, and benefitting society in the process. King's College Cambridge (England, UK) established a wildflower meadow over a portion of its iconic Back Lawn in 2019, replacing a fine lawn first laid in 1772.</p> <p class="MsoNormal">We used biodiversity surveys, Wilcoxon signed rank, and ANOVA models to compare species richness, abundance, and composition of plants, spiders, bugs, bats, and nematodes supported by the meadow, and remaining lawn, over three years. We estimated the climate change impact of meadow vs lawn from maintenance emissions, soil carbon sequestration, and reflectance effect. We surveyed members of the university to quantify the societal benefits of, and attitudes towards, increased meadow planting on the collegiate university estate.</p> <p class="MsoNormal">In spite of its small size (0.36 ha), the meadow supported approximately three times more plant species, three times more spider and bug species and individuals, and bats were recorded three times more often over the meadow than the remaining lawn. Terrestrial invertebrate biomass was 25 times higher in the meadow compared with the lawn. Fourteen species with conservation designations were recorded on the meadow (six for lawn), alongside meadow specialist species.</p> <p class="MsoNormal">Reduced maintenance and fertilising associated with meadow reduced emissions by an estimated 1.36 Mg CO<sub>2</sub>-e per hectare per year compared with lawn. Relative reflectance increased by 25-34% for meadow relative to lawn. Soil carbon stocks did not differ between meadow and lawn.</p> <p class="MsoNormal">Respondents thought meadows provided greater aesthetic, educational, and mental well-being services than lawns. In open responses, lawns were associated with undesirable elitism and social exclusion (most colleges in Cambridge restrict lawn access to senior members of the college), and respondents proved overwhelmingly in favour of meadow planting in place of lawns on the collegiate university estate.</p> <p class="MsoNormal">This study demonstrates the substantial benefits of small urban meadows for local biodiversity, cultural ecosystem services, and climate change mitigation, supplied at a lower cost than maintaining conventional lawn.</p>
What Do Firms Say in Reporting on Impacts of Climate Change? An Approach to Monitoring ESG Actions and Environmental Policy
<p>This paper focuses on two research questions arising from the 2010 U.S. Securities and Exchange Commission (SEC) Advisory on climate change reporting: (1) How does the discussion of climate change in SEC filings change after the Advisory? and (2) What are firms talking about when they talk about climate change?<br> Findings were obtained from the 218,000 10-K filings to the SEC during the 2000--2019 period. The study develops and applies text mining methodology based on extracting information from the ``semantic associates'' in the ``neighborhoods'' of indicative terms. On (1) it finds that climate change-related reporting does increase substantially after the SEC guidance. On (2) a nuanced picture emerges. Firms with comparatively larger transition risks tend to discuss climate change comparatively more, focusing on regulation-related topics. Firms exposed to the physical risks of climate change tend to discuss climate change somewhat less, focusing on meteorological topics. The results enrich our understanding regarding environmental policies and firms' behaviors regarding climate change. Theoretical and practical implications are provided.</p>
Data from:Climate-specific dynamics of fall armyworm on maize: Implications for pest monitoring and management
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King's College Cambridge wildflower meadow monitoring data: biodiversity, climate change and society
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Data from: Evaluating genotyping-in-thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non-invasive and archival samples
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Long-term monitoring reveals forest tree community change driven by atmospheric sulfate pollution and contemporary climate change
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Data from: Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru
<p>This is the data from the publication "Monitoring and predictive mapping of floristic biodiversity along a climatic gradient in ENSO's terrestrial core region, NW Peru" (<a href="http://onlinelibrary.wiley.com/doi/10.1111/ecog.05091/abstract">http://onlinelibrary.wiley.com/doi/10.1111/ecog.05091/abstract</a>).</p> <p>The code (including figures, appendices and the manuscript) can be found directly in the <a href="https://github.com/jannes-m/2020-enso-tdf">GitHub repository</a>.</p> <p><strong>Data sources and description</strong></p> <p>Column descriptions for all tables can be found in <em>variable_description.ods. </em>Following tables are stored in <em>tables.gpkg</em>:</p> <ol> <li>plot_species_matrix_2011: Plot species matrix recorded in 2011</li> <li>plot_species_matrix_2012: Plot species matrix recorded in 2012.</li> <li>plot_species_matrix_2016: Plot species matrix recorded in 2016.</li> <li>plot_species_matrix_2017: Plot species matrix recorded in 2017.</li> <li>lifeform: Lifeforms of the recorded species</li> <li>plot_variables: Variables specific to the plots such as height of the first tree layer, cover of dead wood, etc.</li> <li>soil: Edaphic variables.</li> <li>topography: Topographic variables.</li> <li>streets: Streets and dirt tracks in the study area.</li> <li>towns: Polygons displaying the outline of the cities Paita, Piura and Chulucanas.</li> <li>rivers: Lines displaying the major rivers in the study area.</li> <li>study_area: Outline of the study area.</li> <li>peru: Outline of Peru.</li> <li>neighbors: Outline of Peru's neighbors (Bolivia, Brazil, Chile, Colombia, Ecuador).</li> <li>coast: Coastal strip of and close to the study area.</li> <li>precipitation: Precipitation measured at the three climatic stations (Paita, Piura, Chulucanas).</li> <li>experiment_count: species counted per visit (irrigation-fertilization experiment).</li> <li>experiment_irrigation: Rain input by time during the irrigation-fertilization experiment.</li> <li>experiment_cover: Cover of each plant species per visit and per experimental plot (irrigation-fertilization experiment).</li> </ol>
Up in the air: threats to Afromontane biodiversity from climate change and habitat loss revealed by genetic monitoring of the Ethiopian Highlands bat
<p>Whilst climate change is recognised as a major future threat to biodiversity, most species are currently threatened by extensive human-induced habitat loss, fragmentation and degradation. Tropical high altitude alpine and montane forest ecosystems and their biodiversity are particularly sensitive to temperature increases under climate change, but they are also subject to accelerated pressures from land conversion and degradation due to a growing human population. We studied the combined effects of anthropogenic land-use change, past and future climate changes and mountain range isolation on the endemic Ethiopian Highlands long-eared bat, <i>Plecotus balensis</i>, an understudied bat that is restricted to the remnant natural high altitude Afroalpine and Afromontane habitats. We integrated ecological niche modelling, landscape genetics and model-based inference to assess the genetic, geographic and demographic impacts of past and recent environmental changes. We show that mountain range isolation and historic climates shaped population structure and patterns of genetic variation, but recent anthropogenic land-use change and habitat degradation are associated with a severe population decline and loss of genetic diversity. Models predict that the suitable niche of this bat has been progressively shrinking since the last glaciation period. This study highlights threats to Afroalpine and Afromontane biodiversity, squeezed to higher altitudes under climate change while losing genetic diversity and suffering population declines due to anthropogenic land-use change. We conclude that the conservation of tropical montane biodiversity requires a holistic approach, using genetic, ecological and geographic information to understand the effects of environmental changes across temporal scales and simultaneously addressing the impacts of multiple threats.</p>
Changes Monitoring in Hongjiannao Lake from 1987-2023 using Google Earth Engine and Analysis of Climatic and Anthropogenic Forces
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Data and Code for Shriver et al. 2021, Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using range-wide monitoring data
<p>Data and code for demographic analyses in Shriver et al. 2021. See paper and ReadMe for analysis description and further details. </p> <p>Shriver, R.K., C.B. Yackulic, D.M. Bell, J.B. Bradford. (2021)Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using range-wide demographic models. Ecology. <a href="https://doi.org/10.1002/ecy.3425">https://doi.org/10.1002/ecy.3425</a></p> <p> </p>
Bold Park reptile species capture data for: Decadal abundance patterns in an isolated urban reptile assemblage: Monitoring under a changing climate
<p class="MsoNormal"><span>Fenced pitfall trapping in four sampling sites <span>representing different habitats and fire history</span> over the primary reptile activity period for 35 consecutive years with over 17000 individuals captured during 3300 days of sampling; the trapping regime was modified for the last 28 years.</span></p>
EnviroStream: A Stream Reasoning Benchmark for Climate and Ambient Monitoring
<p>Stream Reasoning (SR) focuses on developing advanced approaches for applying inference to dynamic data streams; it has become increasingly relevant in various application scenarios such as IoT, Smart Cities, Emergency Management, and Healthcare, despite being a relatively new field of research.</p> <p>The current lack of standardized formalisms and benchmarks has been hindering the comparison between different SR approaches. <br> We propose a new benchmark, called <em>EnviroStream</em>, for evaluating SR systems on weather and environmental data from two European cities. </p> <p>The benchmark includes queries and datasets of different sizes. We adopt <em>I-DLV-sr</em>, a recently released SR system based on Answer Set Programming, as a baseline experiment. We illustrate how the queries can be modeled via <em>I-DLV-sr</em> input language and report evaluation times. We also assess continuous online reasoning via a web application.</p> <p>############################################################################################</p> <ul> <li>Data can and queries can be also downloaded via the GitHub repository: <a href="https://github.com/DeMaCS-UNICAL/EnviroStream">https://github.com/DeMaCS-UNICAL/EnviroStream</a></li> <li>Real-time data can be visualized via the following link: <a href="https://experiments.demacs.unical.it/">https://experiments.demacs.unical.it/</a></li> </ul>
Up in the air: threats to Afromontane biodiversity from climate change and habitat loss revealed by genetic monitoring of the Ethiopian Highlands bat
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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.