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7 results for “polar ecosystems”
Indicative distribution map for Ecosystem Functional Group T6.3 Polar tundra and deserts
<p>This archive contains indicative distribution maps and profiles for <strong>T6.3 Polar tundra and deserts</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Observational Data for: Polarized information ecosystems can reorganize social networks via information cascades
<p><strong>General Information</strong></p> <p>This contains the observational data for the publication:</p> <blockquote> <p>Tokita, Guess, and Tarnita (2021). Polarized information ecosystems can reorganize social networks via information cascades. <em>Proceedings of the National Academies of Science of the United States.</em></p> </blockquote> <p>Please see the above peer-reviewed article that resulted from this data for more details.</p> <p>Please see the <em>o</em><em>bservational/ </em>directory in the Github repository <a href="http://%28https//github.com/christokita/information-cascades)">https://github.com/christokita/information-cascades</a> for the code that analyzes the Twitter data and generates derived data. Data directly pertaining to the four news sources of interest are in the <em>data/</em> directory, while data that is related to the 4,000 monitored news followers are in the <em>data_derived/</em> directory.</p> <p>The main data file is in a zipped file. We also included a read me with a description of each directory and subdirectory of the data.</p> <p><strong>Methods</strong></p> <p>For each of our four news sources of interest (CBS News, USA Today, Vox, and the Washington Examiner), we used the Twitter API to sample 3,000 random Twitter users that followed that news source's account. We then used the <em>tweetscores</em> R package to estimate the ideology of each of the 12,000 sampled users.</p> <p>From the original pool of approximately 12,000 sampled users who follow a news outlet of interest, we monitored the follower networks of 1,000 liberal followers of CBS News, 1,000 conservative followers of USA Today, 1,000 liberal followers of Vox, and 1,000 conservative followers of the Washington Examiner. When selecting the 1,000 random users to monitor for a given news outlet, we first conducted filters based on self-reported geolocation and other Twitter profile attributes to reasonably filter down to US-based users who primarily tweet in English. We then pulled the complete follower network of each of our 4,000 monitored users at the beginning and end of a 6-week period from August to September 2020, allowing us to assess who unfollowed these users over this period of time. Finally, using the initial follower networks of each monitored user, we estimated the ideology of up to 50 random followers to create a baseline for the ideological composition of each user’s follower network. </p> <p>Using the initial and final follower networks of each individual, we calculated the rate of unfollows by opposite-ideology users in their follower network. To determine whether an unfollow event was breaking a cross-ideology social tie, users and their unfollowers were classified simply as either liberal (ideology score < 0) or conservative (ideology score > 0). We excluded from analysis unfollowers for whom we could not estimate ideology, either because the account had been suspended, deleted, or made private, or because they did not follow any of the political, news, or cultural accounts needed to do the estimation. We then compared the proportion of unfollowers that were of the opposite ideology (i.e., conservative unfollowers if the focal user is liberal) against the estimated proportion of opposite-ideology followers in the focal user’s initial follower network. This allowed us to account for the fact that many user’s follower networks were not ideologically balanced and set the baseline expectation that if unfollows were random then the proportion of unfollows by opposite-ideology users should match the proportion of followers that were of the opposite ideology.</p> <p> </p> <p><strong>Abstract (for main paper)</strong></p> <p>The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively “unimportant” story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others’ political identities. Observational follow network data collected on Twitter support this prediction:We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be “unimportant” news at the expense of missing out on subjectively “important” news far more frequently. This suggests that “echo chambers”—to the extent that they exist—may not echo so much as silence.</p>
Baltimore Ecosystem Study polar organic contaminant integrative sampler data for pharmaceuticals and personal care products in core sites within Gwynns Falls watershed and reference sites.
An ongoing component of the Baltimore urban long-term ecological research (LTER) project (Baltimore Ecosystem Study, BES) is the use of the watershed approach and monitoring of stream water quality to evaluate the impacts of multiple chemical stressors on urban stream ecosystem functioning within Baltimore. The LTER research has focused on the Gwynns Falls watershed, which spans a gradient from highly urban, urban-residential, and suburban zones. In addition, a forested watershed serves as a reference. The long-term sampling network includes four longitudinal sampling sites along the Gwynns Falls mainstem, as well as several small (40-100 ha) watershed within or near the Gwynns Falls, providing data on water quality in different land use zones of the watersheds. Each study site is continuously monitored for discharge and is sampled weekly for water chemistry. Those data are available elsewhere on the BES website. We are interested in studying the presence and concentrations of pharmaceuticals and personal care products (PPCPs) within urban streams, and then linking these PPCPs with various stream ecosystem functions. To quantify the concentrations of PPCPs in streams, we deploy polar organic contaminant integrative samples (POCIS), which integrate all organic contaminants that pass by them in a stream over a set period of deployment. These POCIS allow us to integrate the total amount of PPCPs within a stream over a set period of time, and then to relate these concentrations with other ecosystem processes. We monitored PPCP concentration in four suburban to urban sites within the Gwynns Falls, as well as one exurban and one forested stream monitoring site. Each POCIS was deployed for two weeks at a stream monitoring site in March 2012. After completion of the sampling period, POCIS were removed from the streams and shipped on ice to the University of Nebraska for extraction and quantification of recovered compounds. This dataset includes all compounds extracted and q
Data from: Microgeography, not just latitude, drives climate overlap on mountains from tropical to polar ecosystems
<p class="CxSpFirst"><span>An extension of the climate variability hypothesis is that relatively stable climate, such as that of the tropics, induces distinct thermal bands across elevation that render dispersal over tropical mountains difficult compared to temperate mountains. Yet, ecosystems are not thermally static in space-time, especially at small scales, which might render some mountains greater thermal isolators than others. Here, we provide an extensive investigation of temperature drivers from fine to coarse scales, and demonstrate that the degree of overlap in temperatures at high and low elevations on mountains is driven by more than just absolute mountain height and latitude. We compiled a database of 29 mountains spanning 6 continents to characterize "thermal overlap" by vertically stratified microhabitats, biomes, and owing to seasonal changes in foliage, demonstrating via mixed-effects modeling that micro- and mesogeography more strongly influence thermal overlap than macrogeography. Impressively, an increase of one meter of vertical microhabitat height generates an increase in overlap equivalent to a 5.26° change in latitude. In addition, forested mountains have reduced overlap – 149% lower – relative to non-forested mountains. We provide evidence in support of a climate hypothesis that emphasizes microgeography as a determinant of dispersal, demographics, and behavior, thereby refining classical theory of macroclimate variability as a prominent driver of biogeography.</span></p> <p class="CxSpMiddle"> </p>
High benthic community respiration and ecosystem response to phytodetrital input in a sub-polar fjord on the West Antarctic Peninsula
<p><span>Glaciomarine fjords dominate the coastal margin of the West Antarctic Peninsula. Studies in similar habitats in the Arctic have shown that benthic biodiversity and ecosystem functioning in inner and middle fjord basins are reduced by turbidity and sedimentation disturbance caused by climate-warming-enhanced glacial melting. In contrast, the inner and middle fjord basins along the West Antarctic Peninsula are characterised as productivity and biodiversity hotspots, but benthic ecosystem functions remain unevaluated.</span> <span>In 2015-2016, we conducted sediment-respiration and <sup>13</sup>C pulse-chase experiments to assess benthic ecosystem functions along a five-station transect at ~500-600 m depths from the inner Andvord Bay fjord, through to Gerlache Strait, and onto the open continental shelf. Incubation samples from the inner and middle basins of Andvord Bay showed peaks in background seafloor respiration, benthic biomass, and uptake of labeled algal biomass compared to more outlying stations; the continental shelf exhibited the lowest levels of these variables, as well as dissolved inorganic carbon production. Macrofaunal community uptake was responsible for most of the C processing in the inner and middle parts of the fjord (>45%) while dissolved inorganic carbon was the dominant repository of processed C near the fjord mouth and on the continental shelf (>80%). The inner parts of Andvord Bay are hotspots of benthic C-cycling and metabolism, in addition to biodiversity. Ongoing climate warming is likely to negatively impact these inner-fjord hotspots by increasing meltwater input and sedimentation disturbance, yielding a reduction in the input and recycling of labile detritus at the seafloor in the inner-middle fjord.</span></p>
Data from: Microgeography, not just latitude, drives climate overlap on mountains from tropical to polar ecosystems
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Figures from: The Cabrières Biota (France) provides insights into Ordovician polar ecosystems
<p>This repository contains high-resolution versions of the figures from the manuscript by Farid Saleh et al., "The Cabrières Biota (France) provides insights into Ordovician polar ecosystems".</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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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.