cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14986683
title: Data and code to run the DCA and GLMM analyses in the study described in the article "Language change in multidimensional space: New methods for modelling linguistic coherence", by Xia Hua, Felicity Meakins, Cassandra Algy and Lindell Bromham, published in Language Dynamics and Change (2021).

description: These are the supplementary materials for an article published in Language Dynamics and Change, entitled 'Language change in multidimensional space: New methods for modelling linguistic coherence', by Xia Hua, Felicity Meakins, Cassandra Algy and Lindell Bromham, with DOI: 10.1163/22105832-bja10015. Linguistic coherence – the co-variation of language variants within speaker repertoires – has been proposed as a key process driving the divergence of language dialects. Previous studies on coherence have been often limited by dataset sizes and analyses. We analyze the use of 185 variables across 78 speakers from the Gurindji community in Australia. We use two multivariate statistical approaches to test whether clusters of variables co-vary with generation, family, household, exposure to Gurindji language speakers and education. Using Discriminant Correspondence Analysis, we find generation is the strongest grouping factor of speakers and co-varies with clusters of variants. Using the Generalized Linear Mixed Model, we find these clusters of variants not only represent a gradual loss of Gurindji language use across generations, but also contribute to distinct patterns of language usage in the different generations. Our study demonstrates the use of multivariate analyses on big datasets to identify sociolects, an important step in linking the ‘micro-level’ processes to the ‘macro-level’ outcomes.These datasets contain the input data and codes to run the DCA and GLMM analyses in this study.
DOI: 10.6084/m9.figshare.14986683.v1
title: Data and code to run the DCA and GLMM analyses in the study described in the article "Language change in multidimensional space: New methods for modelling linguistic coherence", by Xia Hua, Felicity Meakins, Cassandra Algy and Lindell Bromham, published in Language Dynamics and Change (2021).

description: These are the supplementary materials for an article published in Language Dynamics and Change, entitled 'Language change in multidimensional space: New methods for modelling linguistic coherence', by Xia Hua, Felicity Meakins, Cassandra Algy and Lindell Bromham, with DOI: 10.1163/22105832-bja10015. Linguistic coherence – the co-variation of language variants within speaker repertoires – has been proposed as a key process driving the divergence of language dialects. Previous studies on coherence have been often limited by dataset sizes and analyses. We analyze the use of 185 variables across 78 speakers from the Gurindji community in Australia. We use two multivariate statistical approaches to test whether clusters of variables co-vary with generation, family, household, exposure to Gurindji language speakers and education. Using Discriminant Correspondence Analysis, we find generation is the strongest grouping factor of speakers and co-varies with clusters of variants. Using the Generalized Linear Mixed Model, we find these clusters of variants not only represent a gradual loss of Gurindji language use across generations, but also contribute to distinct patterns of language usage in the different generations. Our study demonstrates the use of multivariate analyses on big datasets to identify sociolects, an important step in linking the ‘micro-level’ processes to the ‘macro-level’ outcomes.These datasets contain the input data and codes to run the DCA and GLMM analyses in this study.
DOI: 10.6084/m9.figshare.13369460.v1
title: Rapid tufa deposition and bryophyte growth rates in Irish petrifying springs

description: Rates of deposition of tufa in petrifying springs are complex and highly variable, and the growth rates of associated bryophytes are poorly known. Tufa deposition and bryophyte growth rates were measured using novel methods at six petrifying spring sites in Ireland, north-western Europe. Tufa height was measured at 293 point locations, from 2011 to 2013, using fixed bars mounted above actively growing deposits. Most samples were bryophyte-dominated and the height increments of individual species were measured. Environmental factors were recorded and the chemical composition of spring water was analysed. Tufa deposits increased in height by 20.5 ± 1.1 mm.yr<sup>−1</sup> on average. The pleurocarpous moss <i>Palustriella commutata</i>, in particular, was associated with rapid deposition. Mixed effects modelling revealed a significant interaction between <i>P. commutata</i> and the presence of surface water: together, they increased annual deposition of tufa by 5.7 ± 1.9 mm. The mean height increment for bare, unvegetated tufa was only 16.5 ± 3.0 mm.yr<sup>−1</sup>. <i>Palustriella commutata</i> can outgrow the mean rate of tufa deposition, with a mean annual increment of 27.6 ± 1.9 mm in depth of sward. The smaller acrocarpous mosses <i>Didymodon tophaceus</i> and <i>Eucladium verticillatum</i> grew in height by only 9.1 ± 1.6 mm.yr<sup>−1</sup> and 9.5 ± 1.3 mm.yr<sup>−1</sup> respectively; these two species cannot, therefore, contend with the most rapid rates of tufa deposition. A colonisation cycle was observed, involving competitive displacement of the smaller species by <i>P. commutata</i>. Non-intrusive methods enabled rapid deposition rates to be detected.
DOI: 10.6084/m9.figshare.13369460
title: Rapid tufa deposition and bryophyte growth rates in Irish petrifying springs

description: Rates of deposition of tufa in petrifying springs are complex and highly variable, and the growth rates of associated bryophytes are poorly known. Tufa deposition and bryophyte growth rates were measured using novel methods at six petrifying spring sites in Ireland, north-western Europe. Tufa height was measured at 293 point locations, from 2011 to 2013, using fixed bars mounted above actively growing deposits. Most samples were bryophyte-dominated and the height increments of individual species were measured. Environmental factors were recorded and the chemical composition of spring water was analysed. Tufa deposits increased in height by 20.5 ± 1.1 mm.yr<sup>−1</sup> on average. The pleurocarpous moss <i>Palustriella commutata</i>, in particular, was associated with rapid deposition. Mixed effects modelling revealed a significant interaction between <i>P. commutata</i> and the presence of surface water: together, they increased annual deposition of tufa by 5.7 ± 1.9 mm. The mean height increment for bare, unvegetated tufa was only 16.5 ± 3.0 mm.yr<sup>−1</sup>. <i>Palustriella commutata</i> can outgrow the mean rate of tufa deposition, with a mean annual increment of 27.6 ± 1.9 mm in depth of sward. The smaller acrocarpous mosses <i>Didymodon tophaceus</i> and <i>Eucladium verticillatum</i> grew in height by only 9.1 ± 1.6 mm.yr<sup>−1</sup> and 9.5 ± 1.3 mm.yr<sup>−1</sup> respectively; these two species cannot, therefore, contend with the most rapid rates of tufa deposition. A colonisation cycle was observed, involving competitive displacement of the smaller species by <i>P. commutata</i>. Non-intrusive methods enabled rapid deposition rates to be detected.
DOI: 10.5281/zenodo.4719836
title: WPuQ

description: Electric load of 38 households measured in a small village in Lower Saxony, Germany. Data is available for voltage, reactive power and active power. Seperate measurements are available for each total household load, for each heat pump and at the local power transformer. Different temporal and spatial aggregations are available for conveniance.
DOI: 10.6073/pasta/ac5e46822d54c85f24fc3a72e65238c8
title: Assessing Plant Phenological Patterns in the Eastern United States Over the Last 120 Years

description: Phenology is a key biological trait of an organism’s success and is one of the best indicators of its response to recent climate change. Plants are among the most well-studied organisms in this regard, but observational data bearing on this topic are largely restricted to woody species of the northern hemisphere, mostly from ca. the last three decades. Recent research has demonstrated that mobilized online herbarium specimens provide important, albeit mostly neglected, information on plant phenology. Here, we use the web tool CrowdCurio to crowdsource phenological data from more than 10,000 herbarium specimens representing 30 flowering plant species broadly distributed across the eastern United States. Our results, spanning 120 years and generated from over 2,000 crowdsourcers, clarify numerous aspects of plant phenology. First, they reveal that plant reproductive phenology is significantly advancing in response to warming, which is consistent with previous studies. Second, among those species with broad latitudinal ranges, populations from more southern latitudes are significantly more phenologically sensitive to temperature than those from northern populations. Last, contrary to some recent findings, plants in warmer, less variable climates may be much more dynamic, on average, in their phenological sensitivity. Our results are robust to a variety of confounding factors and span large phylogenetic distances and myriad life histories. These may represent more global trends in the latitudinal gradient of phenological response with myriad potential ecological and evolutionary consequences, and leads us to hypothesize that phenological sensitivity across species' ranges is driven by adaptation to local climates.
DOI: 10.26078/7rvg-k921
title: TDIM ionospheric model TEC maps of the high-latitude northern hemisphere, used in the paper titled "Hemispherical Shifted Symmetry in Polar Cap F-Region Patch Occurrence: A Survey of GPS TEC data from 2015 to 2018"

description: TDIM ionospheric model was run for the year 2018 at 10-day intervals and 2-hr intervals in UT.
DOI: 10.6073/pasta/06b60295395ff9116fcd0a85ba3caad6
title: Ants of the CTFS-ForestGEO Plot at Harvard Forest 2018

description: Foundation species in forests are hypothesized to control the diversity of associated organisms and modulate core ecosystem processes. At Harvard Forest, eastern hemlock (Tsuga canadensis) is a foundation species, but its relationship to local biodiversity has not been explored in detail. This project examined co-occurrence relationships (using codispersion statistics) between forest trees and ants in the 35-hectare Forest Dynamics Plot in the Prospect Hill tract at Harvard Forest ("megaplot"), in which more than 100,000 woody stems have been identified, mapped, and measured.
DOI: 10.6073/pasta/8b8e905abab157af3fbeb19b9b015e63
title: Understory Removal Experiment at Harvard Forest 1956-2018

description: In 1956, Ernie Gould and colleagues established an experiment to test whether removing understory trees will accelerate the growth of the residual overstory. The motivation for the experiment was the suggestion that the understory uses growth materials that would otherwise be available for the main canopy crop trees, and that if the understory were removed the development of the crop trees would be accelerated. In Tom Swamp Compartment I, a 300’ by 400’ rectangular plot was established in a closed-canopy hardwood forest, and every tree &gt;2 inches dbh was mapped, measured and assigned to the overstory or understory. In half of the plot, all understory trees and woody shrubs were cut. Wood and brush were removed from the study area. Sprouts that emerged were killed by spraying with 2-4-5-T and kerosene in 1956 and 1958. Diameter growth measurements of the remaining trees (overstory in the treated area; overstory and understory in the control) were repeated in 1960, 1966, 1969, and 1975 as part of the original experiment. The control portion of the plot was measured in 2003 and 2018. This data set contains tree measurements from the control portion of the site for 1956, 1969, 1975, 2003, and 2018. Additional measurements are available on paper data sheets in the Harvard Forest Document Archives (Research File HF 1956-03). Results of the understory removal experiment are reported in Kelty and Gould (1987).
DOI: 10.26078/z079-5m22
title: Social media use and preferences of visitors to Crater Lake National Park: Data from a 2014 on-site survey

description: These data describe the use, and preferences for, social media among visitors to Crater Lake National Park (Oregon, USA)
DOI: 10.6084/m9.figshare.15091221
title: RSCM temperatures of 14 North Pyrenean samples located in Figure 3. Extension and early orogenic inversion along the basal detachment of a hyper-extended rifted margin: an example from the Central Pyrenees (France)

description: Supplementary Table 1: RSCM temperatures of 14 North Pyrenean samples located in Figure 3.
DOI: 10.6084/m9.figshare.15091221.v1
title: RSCM temperatures of 14 North Pyrenean samples located in Figure 3. Extension and early orogenic inversion along the basal detachment of a hyper-extended rifted margin: an example from the Central Pyrenees (France)

description: Supplementary Table 1: RSCM temperatures of 14 North Pyrenean samples located in Figure 3.
DOI: 10.6084/m9.figshare.15078417.v1
title: Sawyer Mill Dam Removal Bellamy River Reservoir Response Training Polygons, Test Polygons, and Updated Accuracy Assessment Points

description: These are the training & testing polygons as well as the updated accuracy assessment points made from the test polygons for the Evans et al. Sawyer Mill dam removal Bellamy River Reservoir (Dover, New Hampshire, USA) response manuscript. These polygons were used to train and test machine learning classifiers for mapping vegetation structure in a drained reservoir environment pre-/post-dam removal. For more information on these shapefiles and how they were created and used in the SfM/ML classification workflow, please see the Evans et al. manuscript. The study name and sample date (written mddyyyy) are noted in the file name, as well as whether the file contains test polygons, training polygons, or accuracy assessment points.<br>Note: The train/test polygon sets have varying projections depending on the sampling date. In hindsight, this was due to some of the polygons being drawn in different/earlier preliminary work. The polygons here, as is, were fed into the relevant ArcGIS Pro tools along with the GE raster datasets in WGS 1984 in the classification workflow, and it appears that ArcGIS Pro was able to reconcile these differences during processing based on the classification results. When the polygons here are overlaid with the corresponding orthomosaics in WGS 1984 in ArcGIS, upon visual inspection they designate the areas of cover correctly. This breakaway from keeping projections consistent across spatial data files was unnoticed until the data was being prepared for publication, and it was assumed to not have impacted the results in any meaningful way.<br>These materials were made using resources from an NSF EPSCoR funded project “RII Track-2 FEC: Strengthening the scientific basis for decision-making about dams: Multi-scale, coupled-systems research on ecological, social, and economic trade-offs” (a.k.a. "Future of Dams"). Support for this project is provided by the National Science Foundation’s Research Infrastructure Improvement NSF #IIA-1539071. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.<br>
DOI: 10.6084/m9.figshare.15078417
title: Sawyer Mill Dam Removal Bellamy River Reservoir Response Training Polygons, Test Polygons, and Updated Accuracy Assessment Points

description: These are the training & testing polygons as well as the updated accuracy assessment points made from the test polygons for the Evans et al. Sawyer Mill dam removal Bellamy River Reservoir (Dover, New Hampshire, USA) response manuscript. These polygons were used to train and test machine learning classifiers for mapping vegetation structure in a drained reservoir environment pre-/post-dam removal. For more information on these shapefiles and how they were created and used in the SfM/ML classification workflow, please see the Evans et al. manuscript. The study name and sample date (written mddyyyy) are noted in the file name, as well as whether the file contains test polygons, training polygons, or accuracy assessment points.<br>Note: The train/test polygon sets have varying projections depending on the sampling date. In hindsight, this was due to some of the polygons being drawn in different/earlier preliminary work. The polygons here, as is, were fed into the relevant ArcGIS Pro tools along with the GE raster datasets in WGS 1984 in the classification workflow, and it appears that ArcGIS Pro was able to reconcile these differences during processing based on the classification results. When the polygons here are overlaid with the corresponding orthomosaics in WGS 1984 in ArcGIS, upon visual inspection they designate the areas of cover correctly. This breakaway from keeping projections consistent across spatial data files was unnoticed until the data was being prepared for publication, and it was assumed to not have impacted the results in any meaningful way.<br>These materials were made using resources from an NSF EPSCoR funded project “RII Track-2 FEC: Strengthening the scientific basis for decision-making about dams: Multi-scale, coupled-systems research on ecological, social, and economic trade-offs” (a.k.a. "Future of Dams"). Support for this project is provided by the National Science Foundation’s Research Infrastructure Improvement NSF #IIA-1539071. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.<br>
DOI: 10.26078/catv-bm75
title: Automated Narrative Analysis

description: The accuracy of four Machine Learning methods in predicting narrative macrostructure scores was compared to scores obtained by human raters utilizing a criterion-referenced progress monitoring rubric. The machine learning methods that were explored covered methods that utilized hand-engineered features, as well as those that learn directly from the raw text. The predictive models were trained on a corpus of 414 narratives from a normative sample of school-aged children (5;0-9;11) who were given a standardized measure of narrative proficiency. Performance was measured using Quadratic Weighted Kappa, a metric of inter-rater reliability. The results indicated that one model, BERT, not only achieved significantly higher scoring accuracy than the other methods, but was consistent with scores obtained by human raters using a valid and reliable rubric. The findings from this study suggest that a machine learning method, specifically, BERT, shows promise as a way to automate the scoring of narrative macrostructure for potential use in clinical practice.
DOI: 10.6073/pasta/4bc6498314937247287ac4c97b9d2331
title: Conservation and Economic Data for New England Towns 1990-2010

description: Land protection, whether public or private, is often controversial at the local level because residents worry about lost economic activity. We used panel data and a quasi-experimental impact-evaluation approach to determine how key economic indicators were related to the percentage of land protected. Specifically, we estimated the impacts of public and private land protection based on local area employment and housing permits data from 5 periods spanning 1990-2015 for all major towns and cities in New England. To generate rigorous impact estimates, we modeled economic outcomes as a function of the percentage of land protected in the prior period, conditional on town fixed effects, metro-region trends, and controls for period and neighboring protection. Contrary to narratives that conservation depresses economic growth, land protection was associated with a modest increase in the number of people employed and in the labor force and did not affect new housing permits, population, or median income. Public and private protection led to different patterns of positive employment impacts at distances close to and far from cities, indicating the importance of investing in both types of land protection to increase local opportunities. The greatest magnitude of employment impacts were due to protection in more rural areas, where opportunities for both visitation and amenity-related economic growth may be greatest. Overall, we provide novel evidence that land protection can be compatible with local economic growth and illustrate a method that can be broadly applied to assess the net economic impacts of protection.
DOI: 10.26078/815h-aa49
title: Open/Closed Boundary and Energy Cutoff Latitude Data for Papers 1 and 2

description: Abstract for Paper 1
The open-closed boundary (OCB) defines a region of significant transformation in Earth's protective magnetic shield. Principle among these changes is the transition of magnetic field lines from having two foot points, one in each hemisphere, to one foot point at Earth, the other mapping to the solar wind (SW). Charged particles in the SW are able to follow these open field lines into Earth's upper atmosphere. The OCB also defines the polar cap boundary (PCB). Being able to identify and track the OCB allows study of several components of the geomagnetic system. Among them are the electrodynamics of the geomagnetic field and the reconnection balance between the dayside and nightside of the geomagnetic field. Furthermore, the OCB can provide interesting insights into the precipitation of energetic protons into the ionosphere. Using the Tsyganenko model of the geomagnetic field we demonstrate a diurnal fluctuation which we call the Universal Time (UT) effect of the OCB. This UT effect is independent of all other inputs. We anticipate this UT effect to have important consequences in modeling the OCB and other polar cap-associated structures, especially polar cap absorption (PCA) events which adversely affect high frequency radio wave propagation in polar regions. 

Abstract for Paper 2: 
The first well-documented polar cap absorption event occurred on 23 February 1956. Since that time much has been learned and explored regarding these events and their effect on high-frequency radio wave propagation in earth's polar regions. An important boundary when considering geomagnetic field topology and polar cap absorption events is commonly referred to as the cutoff latitude or energy cutoff latitude. The cutoff latitude is dependent on several factors, including solar wind parameters and proton energy. There exists an extensive body of research involving the cutoff latitude. One common approach in finding the cutoff latitude is to use a model of the geomagnetic field and trace proton trajectories through the field. Using this approach and the 1996 version of the Tsyganenko model, we demonstrate a unique method to organize three cutoff latitude boundary dependencies. The first, which we call a Universal Time or UT effect, is independent of proton energy and is based on geomagnetic alignment. The second, a local time or LT effect, exhibits an energy-dependent modulation as well as solar wind dependence. The third, a longitudinal effect, is also energy-dependent. Together, these effects can significantly alter the solar proton energy cutoff latitude, especially in the energy regime most responsible for polar cap absorption events.