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51 results for “transitional communities”
Dataset for greenhouse gas modelling in diesel dependent communities transitioning to bioenergy
<p>The data presented here are from the research article entitled "Greenhouse gas mitigation potential of replacing diesel fuel with wood-based bioenergy in an arctic Indigenous community: A pilot study in Fort McPherson, Canada". Based on a pilot study realized in Northern Canada and life cycle assessment, we provide a set of key parameters and operational data gathered along the biomass supply chain to build a GHG mitigation scenario and compute the quantity and timing of GHG savings in the off-grid community of Fort McPherson, NWT. Given that GHG mitigation scenarios are often assessed against a relative fossil-fuel reference scenario, we are providing two categories of data; 1) data for the reference fossil fuel scenario and; 2) data along the upstream operations of biomass supply chains. Both categories contain data related to the operational processes as well as forest growth or decomposition of unused feedstock. Although the data presented are mostly derived from the boreal forest, they could help guide other communities beyond the boreal to develop a renewable bioenergy system and assess their GHG mitigation options.</p>
PICASO 3.0 Atmospheric Models of WASP-39 b for the JWST Transiting Exoplanet Community Early Release Science Program
<p><strong>OVERVIEW</strong></p> <p>The exoplanetary atmospheric models used in the recent <a href="https://www.nature.com/articles/s41586-022-05269-w">discovery of CO<sub>2 </sub>in WASP- 39 b's atmosphere</a> by the JWST transiting exoplanet community early release science program are presented here. These models are also being used to analyze multiple observations of WASP 39-b obtained using various JWST instruments and observational modes by the transiting exoplanet ERS team. The 1D Radiative-Convective-Thermochemical Equilibrium (RCTE) atmospheric models were computed using the open-source 1D climate model <a href="https://natashabatalha.github.io/picaso/">PICASO 3.0</a> (<a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>). These atmospheric models were then post-processed with condensation clouds using the open-source cloud model <a href="https://natashabatalha.github.io/virga/">VIRGA</a> (<a href="https://ui.adsabs.harvard.edu/abs/2022ApJ...925...33R/abstract">Rooney et al. (2022)</a>). The atmospheric models were also post-processed with the 1D photochemical network code <a href="https://github.com/exoclime/VULCAN">VULCAN</a> (<a href="https://arxiv.org/abs/2108.01790">Tsai et al. (2021)</a>) to explore photochemistry in WASP-39 b's atmosphere.</p> <p><strong>1D RCTE CLOUD-FREE MODELS</strong></p> <p>The base 1D RCTE grid includes atmospheric metallicity points at 0.1, 0.3, 1.0, 3.0, 10.0, 30.0, 50.0, and 100.0x solar values. The Carbon-to-Oxygen (C/O) ratio value is varied between four values - 0.23, 0.46, 0.69, and 0.92. The intrinsic temperature of the planet has been varied across 100, 200, and 300 K, whereas two values of the heat redistribution factor - 0.4 and 0.5 are included. A heat redistribution factor of 0.5 corresponds to the case of full heat redistribution. With these grid points, the grid includes a total of 8x4x3x2= 192 different models.</p> <p>These models are in the "RCTE_cloud_free.zip" folder. The naming scheme of these files is "profile_eq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_.nc" where [T_int] represents the intrinsic temperature of the planet, [MH] is the log<sub>10 </sub>of the atmospheric metallicity relative to solar, [CtoO] is the C/O ratio relative to solar, and [rfacv] is the heat-redistribution factor. So, a metallicity value of 0.3xsolar will have a [MH] value of -0.5, and a C/O 0.46 is considered 1xsolar and will correspond to [CtoO]=1. [T_int] and [rfacv] can assume values described in the previous paragraph.</p> <p><strong>1D RCTE CLOUDY MODELS</strong></p> <p>The base 1D RCTE cloud-free models were post-processed to include condensation cloud species Na<sub>2</sub>S, MnS, and MgSiO<sub>3</sub>. The cloud structure and optical property calculations were performed using the VIRGA model where the sedimentation efficiency <em>f<sub>sed </sub></em>and the vertical eddy diffusion coefficient (<em>K<sub>zz</sub></em>) are free parameters. For the cloudy models, 5 <em>f<sub>sed </sub></em> values - 0.6, 1, 3, 6, and 10 were used along with 3 different values of log<sub>10</sub><em>K<sub>zz </sub></em>- 5, 7, 9, and 11, where <em>K<sub>zz </sub></em>is in cm<sup>2</sup>/s. These models are included in the "RCTE_cloudy.zip" folder following the naming structure "profile_eq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_kzz_1e[log10Kzz]_fsed_[fsed].cld.nc" where two other variables are added in the name - [log10Kzz] and [fsed]. Both of these variables can take values listed here.</p> <p><strong>PHOTOCHEMICAL CLOUD-FREE MODELS</strong></p> <p>A much smaller subset of the base 1D RCTE models were post-processed with the 1D photochemical network code VULCAN to simulate the effects of vertical mixing and photochemistry in WASP-39 b's atmosphere. log<sub>10</sub><em>K<sub>zz </sub></em>was varied again between the 5, 7, 9, and 11 for this purpose. These files are named as "profile_diseq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_kzz_1e[log10Kzz].nc" and can be found in the "photochem_cloud_free.zip" folder.<br> <br> <strong>PHOTOCHEMICAL CLOUDY MODELS</strong></p> <p>The photochemical models were post-processed with clouds to simulate a cloudy atmosphere with disequilibrium chemistry. The <em>f<sub>sed </sub></em> and log<sub>10</sub><em>K<sub>zz </sub></em> grid system for the RCTE cloudy models has been used again for these models as well. These files are in the "photochem_cloudy.zip" folder and are named according to the format "profile_diseq_planet_[T_int]_grav_4.5_mh_[MH]_CO_[CtoO]_sm_0.0486_v_[rfacv]_kzz_1e[log10Kzz]_fsed_[fsed].cld.nc".</p> <p><strong>FILE FORMATTING AND USAGE</strong></p> <p>All the files are released in the <a href="https://docs.xarray.dev/en/stable/">xarray</a> format. Each model has one single xarray file containing all metadata of that model. This metadata includes the input parameters used to compute the model, for example, the metallicity, C/O ratio, and intrinsic temperature. The temperature-pressure (<em>T(P)</em>) profile and the volume mixing ratio profiles of all the different gases in each model is also included in the metadata. The computed transmission spectrum of the model planet from 0.3-6 microns is included in the same file as well. The spectrum is calculated with resampled opacities at a spectral resolution of 60,000, but they should be re-binned at a spectral resolution of 3000 or less for comparison with observed data. For cloudy models, the wavelength dependant optical depth, asymmetry parameter, and single scattering albedo for each atmospheric layer are included in these xarray files.</p> <p>We refer to this <a href="https://natashabatalha.github.io/picaso/notebooks/codehelp/data_uniformity_tutorial.html#Reading/interpreting-an-xarray-file">PICASO tutorial</a> for reading/writing these xarray files. The spectrum from these xarray files can be easily extracted using the following code.</p> <pre><code class="language-python">import xarray as xr path = "path/to/files" ds_sm = xr.open_dataset(path+"profile_eq_planet_300_grav_4.5_mh_+2.0_CO_2.0_sm_0.0486_v_0.5_.nc") # for spectrum wavelength = ds_sm['wavelength'].values transit_depth = ds_sm['transit_depth'].values # for T(P) profile temperature = ds_sm['temperature'].values pressure = ds_sm['pressure'].values</code></pre> <p><a href="https://github.com/natashabatalha/picaso/blob/master/docs/notebooks/fitdata/GridSearch.ipynb">This tutorial</a> shows how to use these models to analyze the NIRSpec Prism observations of WASP-39 b, which led to <a href="http://www.nature.com/articles/s41586-022-05269-w">CO<sub>2 </sub>detection</a>. Please note that the folders must be unzipped before using them with this notebook.</p> <p><strong>CREDITS</strong></p> <p>If you use these modeling products in your work, please cite this zenodo repository along with the following papers depending on the part of the grid being used:</p> <p>1) RCTE_cloud_free.zip</p> <p> <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a> </p> <p>2) RCTE_cloudy.zip</p> <p><a href="https://ui.adsabs.harvard.edu/abs/2022ApJ...925...33R/abstract">Rooney et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a> </p> <p>3) photochem_cloud_free.zip</p> <p> <a href="https://arxiv.org/abs/2108.01790">Tsai et al. (2021)</a> , <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a> </p> <p>4) photochem_cloudy.zip</p> <p> <a href="https://arxiv.org/abs/2108.01790">Tsai et al. (2021)</a> , <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2022ApJ...925...33R/abstract">Rooney et al. (2022)</a></p> <p> </p>
Dataset for greenhouse gas modelling in diesel dependent communities transitioning to bioenergy
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Data from: Tropical biome switching: Ant communities transition from savanna to rainforest following cessation of burning
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Supporting Information - Estimating thermal energy loads in remote and northern communities to facilitate a net-zero transition
<p>This file accompanies "A method for estimating thermal energy loads in Canada’s remote and northern communities" by Ian Maynard and Ahmed Abdulla.</p> <p>This supporting information contains:</p> <ul> <li>Calculations and thermal loads of 40 communities discussed in the above paper</li> <li>Heating Degree Hour (HDH) distribution calculations</li> <li>Diagnostics and dataset used for developing a model for predicting annual and monthly thermal loads using ordinary least squares regression</li> </ul>
Climate driven disruption of transitional alpine bumble bee communities
<p>Pollinators at high elevations face multiple threats from climate change including heat stress, failure to phenological match advancing flower resources and competitive pressure from range-expanding species of lower elevations. We conducted long-term multi-site surveys of alpine bumble bees to determine how phenology of range-stable and range-expanding species is responding to climate change. We ask whether bumble bee responses generate mismatches with floral resources, and whether these mismatches in turn promote community disruption and potential species replacement.</p> <p>In alpine environments of the central Rocky Mountains, range-stable and range-expanding bumble bees exhibit phenological mismatches with flowering host plants due to earlier flowering of preferred resources under warmer spring temperatures. However, workers of range-stable species are more canalised in their foraging schedules, exploiting a relatively narrow portion of the flowering season. Specifically, range-stable species show less variance in phenology in response to temporally and spatially changing conditions than range-expanding ones. Because flowering duration drives the seasonal abundance of floral resources at the landscape scale, we hypothesize that canalisation of phenology in alpine bumble bees could reduce their access to earlier or later season flowers.</p> <p>Warmer conditions are decreasing abundances of range-stable alpine bumble bees above the timberline, increasing abundance of range-expanding species, and facilitating a novel and more species-diverse bumble bee community. However, this trend is not explained by greater phenological mismatch of range-stable bees. Results suggest that conversion of historic habitats for cold-adapted alpine bumble bee species into refugia for more heat-tolerant congeners is disrupting bumble bee communities at high elevations, though the precise mechanisms accounting for these changes are not yet known. If warming continues, we predict that the transient increase in diversity due to colonization by historically low-elevation species will likely give way to declines of alpine bumble bees in the central Rocky Mountains.</p>
Available Community Energy Transition Plan Data
<p>This is the extracted data for 186 communities that have made a pledge to be 100% renewable. A Systematic online search was conducted to find current plans and assess the gaps in community energy transitions. Please cite and reference the manuscript "<strong>Ready or not, here it comes: Assessing the gaps in community plans for renewable energy transitions</strong><strong> within the United States" </strong>published in Energy Research and Social Science </p>
Community Health Worker-Led Transition Support for Persons Living With Dementia and Caregivers
ClinicalTrials.gov study NCT06831318. IPD Sharing: YES. Countries: 1. Publications: 1.
A Transition of Care Model From Hospital to Community for Hispanic/Latino Adult Patients With Diabetes.
ClinicalTrials.gov study NCT04864639. IPD Sharing: YES. Countries: 1. Publications: 1.
Our Peers - Empowerment and Navigational Support - Community Living: Remote Peer Navigator Intervention for Adults With Newly Acquired Disabilities Transitioning to Community Living (OP-ENS -CL)
ClinicalTrials.gov study NCT06941233. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Climate driven disruption of transitional alpine bumble bee communities
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Multi-decadal shifts in fish community diversity across a dynamic biogeographic transition zone
<p><b><span>Aim: </span></b><span>A 21-year fisheries-independent monitoring dataset was used to explore fish community diversity across a latitudinal gradient to quantify how diversity has changed and relate those changes in diversity to changes in the abiotic environment. Additionally, this study spans a biogeographic transition zone, providing insight into future species assemblages across regions of relatively high species diversity.</span></p> <p><b><span>Location: </span></b><span>Indian River Lagoon, Florida, USA</span></p> <p><b><span>Methods: </span></b><span>Spatial and temporal beta diversity<b> </b>was quantified latitudinally with "best derived breaks" determined by using chronological cluster analyses. Multiple indices of alpha diversity were quantified, including species richness, Shannon diversity, Simpson diversity, and Pielou's evenness. AIC model selection and environmental fit tests were performed to link patterns of diversity and species assemblages with the abiotic environment. </span></p> <p><b><span>Results: </span></b><span>Evidence of a biogeographic transition zone was supported by data spanning the entire study period; the largest break in species assemblage occurred near 28</span><span>°</span><span>N. Fine scale analyses using small and large seine catches were noisier than broad analyses but indicated a northern shift in location of the biogeographic transition zone. Beta-diversity was generally dominated by species turnover/balance versus nestedness/gradient components, implying that changes were driven by species sorting associated with the physical environment. Excluding the summation of all environmental variables, temperature and dissolved oxygen best describe patterns of diversity and species composition. </span></p> <p><b><span>Main Conclusions: </span></b><span>Over years less affected by disturbances, large and small seine catch data suggest the fish community assemblage and location of the biogeographic transition zone has shifted 9 km and 21 km to the north. If the trends observed in these years were to continue from 1999 until the year 2100, a 111 km to 243 km shift in fish communities could be expected. Variation in rates of movement based on gear type suggest novel species assemblages could ensue.</span></p>
Data from: Bacterial communities within Phengaris (Maculinea) alcon caterpillars are shifted following transition from solitary living to social parasitism of Myrmica ant colonies
Bacterial symbionts are known to facilitate a wide range of physiological processes and ecological interactions for their hosts. In spite of this, caterpillars with highly diverse life histories appear to lack resident microbiota. Gut physiology, endogenous digestive enzymes, and limited social interactions may contribute to this pattern, but the consequences of shifts in social activity and diet on caterpillar microbiota are largely unknown. Phengaris alcon caterpillars undergo particularly dramatic social and dietary shifts when they parasitize Myrmica ant colonies, rapidly transitioning from solitary herbivory to ant tending (i.e., receiving protein‐rich regurgitations through trophallaxis). This unique life history provides a model for studying interactions between social living, diet, and caterpillar microbiota. Here, we characterized and compared bacterial communities within P. alcon caterpillars before and after their association with ants, using 16S rRNA amplicon sequencing and quantitative PCR. After being adopted by ants, bacterial communities within P. alcon caterpillars shifted substantially, with a significant increase in alpha diversity and greater consistency in bacterial community composition in terms of beta dissimilarity. We also characterized the bacterial communities within their host ants (Myrmica schencki), food plant (Gentiana cruciata), and soil from ant nest chambers. These data indicated that the aforementioned patterns were influenced by bacteria derived from caterpillars' surrounding environments, rather than through transfers from ants. Thus, while bacterial communities are substantially reorganized over the life cycle of P. alcon caterpillars, it appears that they do not rely on transfers of bacteria from host ants to complete their development.
Fig. 2 in Diversity and biogeographical makeup of the dung beetle communities inhabiting two mountains in the Mexican Transition Zone
Fig. 2 Relationship between the decrease (circles and black squares) and the accumulation (circles and open squares) of genera and species with increasing elevation in Los Tuxtlas and La Chinantla
Figure 5 in Seasonal community structure of the molluscan macrofauna at the marine-lagoonal environmental transition at Kalloni solar saltworks (Lesvos Island, NE Aegean Sea, Greece)
Figure 5. Environmental gradients and the corresponding variations of molluscan community descriptors in the study area.
Figure 4 in Seasonal community structure of the molluscan macrofauna at the marine-lagoonal environmental transition at Kalloni solar saltworks (Lesvos Island, NE Aegean Sea, Greece)
Figure 4. Cluster analysis dendrogram and nMDS ordination plot of the sampling sites (1, gulf; 2, channel; 3, pond1; 4, pond2) in each season (WI, winter; SP, spring; SU, summer; AU, autumn).
Figure 2 in Seasonal community structure of the molluscan macrofauna at the marine-lagoonal environmental transition at Kalloni solar saltworks (Lesvos Island, NE Aegean Sea, Greece)
Figure 2. Spatial and seasonal variations of the proportions of the trophic types of the dominant molluscan species. HER, herbivorous; DS, surface deposit feeders; SU, suspension feeders.
Diversity patterns and community structure of the macrofauna along the beach-inland transition zone of small tropical islands: supporting raw data and code
<p>Biodiversity follows distinct and observable patterns. Where to systems meet, biodiversity is often increased, due to overlapping occurrence ranges and the presence of specialized species that can tolerate the dynamic conditions of the transition zones. One of the most pronounced transition zones occurs at shores, where oceans and terrestrial habitat collide, forming the shore-inland transition zone. The relevance of this transition zone in shaping a system's community structure is particularly pronounced on small islands due to their high shore-to-inland-area ratio. However, the community structure of insular faunas along this transition zone is unknown. Here, we investigated the diversity patterns along the beach-inland transition zone of small islands and tested the hypothesis that species diversity increases towards the transition zone where beach and interior habitat meet. By measuring environmental parameters, resource availability, and macrofauna diversity along transects running across the beach-inland transition zone, we show that a gradual change in species composition from beach to the inland exists, but neither taxa richness, Shannon diversity, nor overall abundance change significantly. These findings give important insight into insular community structure at the transition zone from sea to land that are relevant to better understand the dynamic and unique characteristics of insular ecosystems.</p>
Community Assets Supporting Transitions (CAST)
ClinicalTrials.gov study NCT03157999. IPD Sharing: NO. Countries: 1. Publications: 4.
Trauma-informed Intervention to Reduce Substance Use and to Support Community Transition
ClinicalTrials.gov study NCT06651528. IPD Sharing: NO. Countries: 1. Publications: 0.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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