cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19470107
title: Assessing the potential of invertebrate natural enemies of insect pests inhabiting <i>Miscanthus</i> x <i>giganteus</i> shelterbelts in pasture

description: <i>Miscanthus</i> x <i>giganteus</i> (<i>Miscanthus</i>) grass shelterbelts can deliver multiple ecosystem services on New Zealand commercial dairy farms. However, there has been little investigation into how these shelterbelts contribute to insect pest management. Here, on a Canterbury dairy farm, we investigated what generalist surface-dwelling invertebrate natural enemies of insect pests inhabit three separate <i>Miscanthus</i> shelterbelts compared to three unmanipulated field margin plots. The potential contribution of these natural enemy assemblages to future biological control was also investigated. To measure this, live moth egg baits with associated pitfall trapping were deployed in autumn, winter and spring of 2015. <i>Miscanthus</i> and the field margin plots were found to have similar potential natural enemy richness but differed in their community composition. The potential predation rate of pests in <i>Miscanthus</i> was 85% higher than in the field margin. Infrared video and Sanger sequencing confirmed that the harvestman <i>Phalangium opilio</i> and the slug <i>Deroceras reticulatum</i> consumed the egg baits in <i>Miscanthus</i>. Conversely, no bait-consuming invertebrates were identified in the field margin. These preliminary results indicate potential natural enemies inhabit <i>Miscanthus</i> and may consume insect pest eggs on the soil-surface. However, to achieve anyinsect pest suppression, further habitat manipulation would be required.
DOI: 10.6084/m9.figshare.19442804
title: Growth dynamics and nutrient uptake of panicum maximum under nitrogen fertilisation

description: We investigated the effects of nitrogen (N) fertilisation levels on structural, productive and morphogenetic traits, chlorophyll content, tiller number (TN) and macronutrient uptake capacity of three <i>Panicum maximum</i> cultivars (BRS Zuri, BRS Quênia and BRS Tamani). The experiment was laid out in a completely randomised design with five N doses (0, 50, 100, 200, and 400 mg dm<sup>−3</sup>). The concentration of chlorophyll increase linearly with increasing N doses in BRS Zuri. There was a significant interaction effect between cultivars and N doses on forage mass (FM), forage yield (FY), TN and the uptakes of nitrogen, potassium, phosphorus, calcium, magnesium and sulfur. The BRS Zuri had the highest FY and FM independent of the applied N dose. In the dose range of 200 and 400 mg dm<sup>−3</sup> of N, there was no increase in the productive performance of BRS Tamani and BRS Quênia, which were similar to each other. N fertilisation increased TN. Higher N doses in the soil translated into greater N uptake by the grasses. Nitrogen application to the soil can increase the production and structural indices of <i>Panicum maximum</i> cultivars and increases grass growth, but its concentration must consider the productive capacity of the plant for this nutrient.
DOI: 10.6084/m9.figshare.19442804.v1
title: Growth dynamics and nutrient uptake of panicum maximum under nitrogen fertilisation

description: We investigated the effects of nitrogen (N) fertilisation levels on structural, productive and morphogenetic traits, chlorophyll content, tiller number (TN) and macronutrient uptake capacity of three <i>Panicum maximum</i> cultivars (BRS Zuri, BRS Quênia and BRS Tamani). The experiment was laid out in a completely randomised design with five N doses (0, 50, 100, 200, and 400 mg dm<sup>−3</sup>). The concentration of chlorophyll increase linearly with increasing N doses in BRS Zuri. There was a significant interaction effect between cultivars and N doses on forage mass (FM), forage yield (FY), TN and the uptakes of nitrogen, potassium, phosphorus, calcium, magnesium and sulfur. The BRS Zuri had the highest FY and FM independent of the applied N dose. In the dose range of 200 and 400 mg dm<sup>−3</sup> of N, there was no increase in the productive performance of BRS Tamani and BRS Quênia, which were similar to each other. N fertilisation increased TN. Higher N doses in the soil translated into greater N uptake by the grasses. Nitrogen application to the soil can increase the production and structural indices of <i>Panicum maximum</i> cultivars and increases grass growth, but its concentration must consider the productive capacity of the plant for this nutrient.
DOI: 10.6084/m9.figshare.19470107.v1
title: Assessing the potential of invertebrate natural enemies of insect pests inhabiting <i>Miscanthus</i> x <i>giganteus</i> shelterbelts in pasture

description: <i>Miscanthus</i> x <i>giganteus</i> (<i>Miscanthus</i>) grass shelterbelts can deliver multiple ecosystem services on New Zealand commercial dairy farms. However, there has been little investigation into how these shelterbelts contribute to insect pest management. Here, on a Canterbury dairy farm, we investigated what generalist surface-dwelling invertebrate natural enemies of insect pests inhabit three separate <i>Miscanthus</i> shelterbelts compared to three unmanipulated field margin plots. The potential contribution of these natural enemy assemblages to future biological control was also investigated. To measure this, live moth egg baits with associated pitfall trapping were deployed in autumn, winter and spring of 2015. <i>Miscanthus</i> and the field margin plots were found to have similar potential natural enemy richness but differed in their community composition. The potential predation rate of pests in <i>Miscanthus</i> was 85% higher than in the field margin. Infrared video and Sanger sequencing confirmed that the harvestman <i>Phalangium opilio</i> and the slug <i>Deroceras reticulatum</i> consumed the egg baits in <i>Miscanthus</i>. Conversely, no bait-consuming invertebrates were identified in the field margin. These preliminary results indicate potential natural enemies inhabit <i>Miscanthus</i> and may consume insect pest eggs on the soil-surface. However, to achieve anyinsect pest suppression, further habitat manipulation would be required.
DOI: 10.26179/nsab-r108
title: Surveys at Davis Station for the Australian Antarctic Division's Davis Aerodrome Project 5097 2019-20
DOI: 10.25582/data.2022-05.2524214/1910312
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524679/1910320
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524616/1910323
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524208/1910346
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524620/1910356
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524622/1910361
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524630/1910364
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524629/1910372
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524619/1910386
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524631/1910406
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524621/1910412
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524209/1910424
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524614/1910436
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524641/1910462
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524215/1910466
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524632/1910470
title: Data for EMSL Project 51134 from May 2022
DOI: 10.25582/data.2022-05.2524946/1925450
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524754/1925451
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524780/1925452
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524812/1925453
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524817/1925454
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524813/1925455
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524865/1925458
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524765/1925459
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524776/1925460
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524750/1925461
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524887/1925463
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524759/1925464
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524760/1925465
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524848/1925466
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524826/1925467
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524864/1925473
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524753/1925474
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524945/1925475
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524846/1925476
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524751/1925477
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524881/1925478
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524847/1925479
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524747/1925480
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524741/1925482
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524749/1925483
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524755/1925485
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524797/1925486
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524777/1925487
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524778/1925489
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524827/1925491
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524849/1925492
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524884/1925493
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524744/1925494
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524815/1925496
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524850/1925499
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524840/1925500
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524775/1925501
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524766/1925503
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524779/1925506
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524947/1925507
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524828/1925508
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524800/1925510
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524851/1925511
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524761/1925512
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524839/1925516
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524763/1925518
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524767/1925519
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524743/1925521
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524866/1925522
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524838/1925523
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524752/1925524
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524742/1925525
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524814/1925526
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524798/1925527
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524764/1925528
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524740/1925529
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524816/1925531
title: Data for EMSL Project 50220 from May 2022
DOI: 10.25582/data.2022-05.2524269/1931909
title: Data for EMSL Project 51575 from May 2022
DOI: 10.25582/data.2022-06.2526426/1932897
title: Data for EMSL Project 51612 from June 2022
DOI: 10.25582/data.2022-06.2526371/1933676
title: Data for EMSL Project 51575 from June 2022
DOI: 10.6084/m9.figshare.23272772
title: How Psychiatrists Learn To Think.xlsx

description: Study used a survey of psychiatrists both in and out of training at two different institutions. Survey asking the simple question "What do all providers need to know about psychiatry?" Thematic analysis was conducted, sorting responses into categories based on subject matter and secondarily into meta-categories denoting "Content," "Process," or "Other." The “Content” meta-theme is comprised of topics pertaining to objective information, such as clinical pearls, diagnosis, pharmacology. “Process” describes topics pertaining to treatment delivery, the patient-physician relationship, and therapeutic techniques. “Other” describes responses that were neither focused on the content or process of the practice of psychiatry but are still pertinent to the field. In total, there were 60 attending responses by email, 41 responses from an attending group brainstorming, and 129 resident answers via formal survey.
DOI: 10.6084/m9.figshare.23272772.v1
title: How Psychiatrists Learn To Think.xlsx

description: Study used a survey of psychiatrists both in and out of training at two different institutions. Survey asking the simple question "What do all providers need to know about psychiatry?" Thematic analysis was conducted, sorting responses into categories based on subject matter and secondarily into meta-categories denoting "Content," "Process," or "Other." The “Content” meta-theme is comprised of topics pertaining to objective information, such as clinical pearls, diagnosis, pharmacology. “Process” describes topics pertaining to treatment delivery, the patient-physician relationship, and therapeutic techniques. “Other” describes responses that were neither focused on the content or process of the practice of psychiatry but are still pertinent to the field. In total, there were 60 attending responses by email, 41 responses from an attending group brainstorming, and 129 resident answers via formal survey.
DOI: 10.13139/olcf/1975494
title: OLCF Frontier Supercomputer 2023-04-29 HPL Power Data used for Top500/Green500 Submission

description: OLCF Frontier Supercomputer 2023-04-29 HPL Power Data used for Top500/Green500 Submission This dataset provides the scripts used to derive the data for submission at [https://www.top500.org/lists/top500/2023/06/](https://www.top500.org/lists/top500/2023/06/) plus the primary data is included in the dataset. Additional information is available in the README.md.
DOI: 10.25582/data.2022-06.2526605/1975568
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2525668/1975569
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526544/1975570
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2525671/1975571
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526607/1975572
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526588/1975573
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526617/1975574
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526546/1975575
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526610/1975576
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526560/1975577
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526554/1975578
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526547/1975579
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526599/1975580
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526556/1975581
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526558/1975582
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526576/1975583
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526559/1975584
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526557/1975585
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526608/1975586
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526555/1975587
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526609/1975588
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526552/1975589
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526572/1975590
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526589/1975591
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526590/1975592
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526553/1975593
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2525628/1975594
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526591/1975595
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2525663/1975596
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2526573/1975597
title: Data for EMSL Project 51461 from June 2022
DOI: 10.25582/data.2022-06.2525623/1975598
title: Data for EMSL Project 51461 from June 2022
DOI: 10.5281/zenodo.7992684
title: Processed data for TransRR

description: Processed data for TransRR
DOI: 10.5281/zenodo.7992683
title: Processed data for TransRR

description: Processed data for TransRR
DOI: 10.6073/pasta/3b2cc6c6f9d2b4dd3a497b58119e234c
title: Assessing change in ecosystem processes twenty four years after the 1988 Yellowstone Wildfires, 2013

description: The extent of young postfire conifer forests is growing throughout western North America as the frequency and size of high-severity fires increase, making it important to understand ecosystem structure and function in early seral forests. Understanding nitrogen (N) dynamics during postfire stand development is especially important because northern conifers are often N limited. We re-sampled lodgepole pine (Pinus contorta var. latifolia) stands that regenerated naturally after the 1988 fires in Yellowstone National Park (Wyoming, USA) to ask: (1) How have N pools and fluxes changed over a decade (15 to 25 years postfire) of very rapid forest growth? (2) At postfire year 25, how do N pools and fluxes vary with lodgepole pine density and productivity? Lodgepole pine foliage, litter (annual litterfall, forest-floor litter), and mineral soils were sampled in 14 plots (0.25-ha) that varied in postfire lodgepole pine density (1,500 to 344,000 stems ha-1) and aboveground net primary production (ANPP; 1.4 to 16.1 Mg ha-1 yr-1). Previous data collected 15 and 17 years postfire (i.e., 2003 and 2005) provided a reference for assessing change in ecosystem process rates over time. At that time, lodgepole pine foliar nitrogen (N) concentrations had not yet suggested N limitation, and tree density and net primary production strongly influenced ecosystem carbon (C) and N stocks. These data were collected in 2012 and 2013 and are associated with the following publication: Turner, M. G., T. G. Whitby, and W. H. Romme. 2019. Feast not famine: Nitrogen pools recover rapidly in 25-yr old postfire lodgepole pine. Ecology (In press).
DOI: 10.5281/zenodo.8041858
title: test——again

description: test
DOI: 10.5281/zenodo.8041857
title: test——again

description: test
DOI: 10.6084/m9.figshare.16892707
title: Ecological stoichiometry and fungal community turnover reveal variation among mycorrhizal partners in their responses to warming and drought

description: dataset about carbon, nitrogen, and phosphorus concentration in the mycelium of arbuscular mycorrhizal fungi under warming and drought
DOI: 10.6084/m9.figshare.23531523
title: mxene275

description: https://cmr.fysik.dtu.dk/c2db/c2db.html
DOI: 10.6084/m9.figshare.23531523.v1
title: mxene275

description: https://cmr.fysik.dtu.dk/c2db/c2db.html
DOI: 10.24396/ordar-119
title: The LNAPL fate in soil under fluctuating groundwater levels: experimental data

description: Experiments carried out on a 2m3 lysimetric column containing a model soil (coarse sandy soil) contaminated with 50L of commercial diesel (LNAPL) and subjected to a scenario of controlled rainfalls and variations in groundwater level.
DOI: 10.5281/zenodo.8046791
title: Processed EKE from FESOM-SO3

description: EKE datasets calculated from FESOM model output on the SO3 mesh and interpolated to a regular grid. Data processing is described in https://doi.org/10.5281/zenodo.8046783.
DOI: 10.34740/kaggle/dsv/5947742
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.8046254
title: SESMG Model Results: "Potential-Risk and No-Regret Options for Urban Energy System Design - A Sensitivity Analysis"

description: Each of the folders contains SESMG results for a sensitivity analysis of the study "Potential-Risk and No-Regret Options for Urban Energy System Design - A Sensitivity Analysis". More information can be found in this publication. Each folder contains two subfolders. The "cost-minimum" subfolder contains the results for financially optimized systems, and the "emission-minimum" subfolder contains the results for GHG emission-optimized systems. Within these subfolders, the results for different gradations of the respective sensitivity parameters are stored in separate sub-subfolders. The 01_reference_total_ghg_emissions folder has a slightly different structure. Since the results are not separated into financially and emissions-optimized scenarios, the results of different gradations are stored directly in the main folder of this sensitivity analysis.
DOI: 10.5281/zenodo.8046253
title: SESMG Model Results: "Potential-Risk and No-Regret Options for Urban Energy System Design - A Sensitivity Analysis"

description: Each of the folders contains SESMG results for a sensitivity analysis of the study "Potential-Risk and No-Regret Options for Urban Energy System Design - A Sensitivity Analysis". More information can be found in this publication. Each folder contains two subfolders. The "cost-minimum" subfolder contains the results for financially optimized systems, and the "emission-minimum" subfolder contains the results for GHG emission-optimized systems. Within these subfolders, the results for different gradations of the respective sensitivity parameters are stored in separate sub-subfolders. The 01_reference_total_ghg_emissions folder has a slightly different structure. Since the results are not separated into financially and emissions-optimized scenarios, the results of different gradations are stored directly in the main folder of this sensitivity analysis.
DOI: 10.34740/kaggle/dsv/5947740
title: YouTube Trending Video Dataset (updated daily)