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907 results for “Pines”
Short-term effects of biochar on soil CO2 efflux in boreal Scots pine forests
<p>This dataset includes all the data we collected at the first summer after biochar application in boreal forests. Our paper“ the effect of biochar on soil CO<sub>2</sub> efflux in boreal forests“ now is under review in Annals of Forest Science. Biochar prepared at two reaction temperatures was applied at three rates (including non-amended controls). During the first year after treatment, efflux increased with higher rates of biochar, but the reaction temperature had no effect. o explain char effects on efflux, soil moisture and temperature were also added to the model testing treatment effects. These environmental variables explained more of the variation in efflux and caused treatment to no longer have a significant effect. Based on this result, we concluded that soil temperature explains the effect of char on efflux.</p>
Species co-occurrences from EuPMC articles related to pines
<p>A dataset containing info on matches from full text searches by ContentMine tools, that can be mapped to Wikidata. See README.md.</p>
Data from: Mechanical soil disturbance in a pine savanna has multi-year effects on plant species composition
<p>Data used in the manuscript Mechanical soil disturbance in a pine savanna has multi-year effects on plant species composition accepted for publication in Ecosphere. Data included are species lists for all plots and years, percent cover of species in each plot in 2021, and life-history characteristics (life span, dispersal mechanism, seed bank persistence) of all species. See manuscript for site description and data collection methodology. </p>
Food and social cues modulate reproductive development but not migratory behavior in a nomadic songbird, the Pine Siskin (Pinus spinus)
<p>Many animals rely on photoperiodic and non-photoperiodic environmental cues to gather information and appropriately time life history stages across the annual cycle, such as reproduction, molt, and migration. Here, we experimentally demonstrate that the reproductive physiology, but not migratory behavior, of captive Pine Siskins responds to both food and social cues during the spring migratory-breeding period. Pine Siskins are a nomadic finch with a highly flexible breeding schedule and, in the spring, free-living Pine Siskins can wander large geographic areas and opportunistically breed. To understand the importance of non-photoperiodic cues to the migratory-breeding transition, we maintained individually housed birds on either a standard or enriched diet in the presence of group-housed heterospecifics or conspecifics experiencing either the standard or enriched diet type. We measured body condition and reproductive development of all Pine Siskins and, among individually housed Pine Siskins, quantified nocturnal migratory restlessness. In group-housed birds, the enriched diet caused increases in body condition and, among females, promoted reproductive development. Among individually housed birds, female reproductive development differed between treatment groups whereas male reproductive development did not. Specifically, individually housed females showed greater reproductive development when presented with conspecifics compared to heterospecifics. The highest rate of female reproductive development, however, was observed amongst individually housed females provided the enriched diet and maintained with group-housed conspecifics on an enriched diet. Changes in nocturnal migratory restlessness did not vary by treatment group or sex. By manipulating both the physical and social environment, this study demonstrates how multiple environmental cues can affect the timing of transitions between life history stages with differential responses between sexes and between migratory and reproductive systems.</p>
Abiotic factors modify ponderosa pine regeneration outcomes after high-severity fire
<p>Large high-severity burn patches are increasingly common in southwestern US dry conifer forests. Seed-obligate conifers often fail to quickly regenerate large patches because their seeds rarely travel the distances required to reach the core patch area. Abiotic factors may further alter the distance seeds can travel to regenerate a patch, which would change expected post-fire regeneration patterns. We used the presence and density of ponderosa pine regeneration as a proxy for seed dispersal to quantify the effect of abiotic factors on seed dispersal into high-severity patches. We established 45 transects in burn patches across the Gila National Forest, NM, USA to measure regeneration density in areas that varied by aspect, slope, and prevailing wind direction relative to intact forest. We modeled the effect of abiotic features on regeneration presence and density, comparing density estimates against a distance-only model to assess differences in model performance and expected regeneration density. We found the highest regeneration densities on north-facing aspects that were near, downwind, and downslope of intact forest, which decreased in density and likelihood as conditions for seed dispersal became less favorable. Accounting for abiotic factors improved model performance and increased regeneration density estimates compared to the distance-only model. Our findings indicate that regeneration presence and density vary as a function of the interaction between abiotic factors and distance to the primary seed source, which is determined by patch characteristics. Therefore, abiotic factors will have a smaller effect on regeneration outcomes in large, simple patches, which have more area further from the patch edge.</p>
Fig. 1 in Spider community responds to litter complexity: insights from a small-scale experiment in an exotic pine stand
Fig. 1. Mean density of individuals (A, individuals.g-1 of dry litter) and morphospecies (B, species.g-1 of dry litter adults only) ± standard error of hunting and web-building spiders in simple and complex substrate treatments in a pine stand in Minas do Leão, Southern Brazil.
Fig. 2 in Spider community responds to litter complexity: insights from a small-scale experiment in an exotic pine stand
Fig. 2. Individual-based rarefaction (interpolation, solid lines) and extrapolation (dashed line) from eight experimental units (90 x 60 cm) of simple and complex substrate in a pine stand in Minas do LeÃo, Southern Brazil, under multinomial model, with 95% unconditional confidence intervals (shaded area, bootstrap with 1,000 replications) (based on COLWELL et al. 2012). In parenthesis, the number of individuals and morphospecies observed and estimated (extrapolation) respectively in each treatment.
EXPLO. Lin 3. Supplementary material for Yermokhin et al., 2025, Dendroarchaeology at Lake Ohrid: Pine Tree-Ring Chronology and 5th Millennium BCE Palisades from the Pile-Dwelling Settlement of Lin 3, Albania
<p>Supplementary data for the article "Dendroarchaeology at Lake Ohrid: Pine Tree-Ring Chronology and 5th Millennium BCE Palisades from the Pile-Dwelling Settlement of Lin 3, Albania, by Maxim Yermokhin, Andrej Maczkowski, Matthias Bolliger, John Francuz, Adrian Anastasi, Krist Anastasi, Ariane Ballmer, Ilirjan Gjipali, Mirco Brunner, Tryfon Giagkoulis, Martin Hinz, Marco Hostettler, Johannes Reich, Sönke Szidat, Albert Hafner submited in Dendrochronologia.</p>
Fig. 1 in Biogeography and evolution of the screw-pine genus Benstonea Callm. & Buerki (Pandanaceae)
Fig. 1. – Bayesian half-compatible consensus tree of Pandanaceae inferred from six plastid DNA regions. Bayesian posterior probabilities (BPP) and bootstrap support (BS) values are displayed at nodes. See main text for the discussion of the clades within Benstonea Callm. & Buerki.
Fig. 5 in Benstonea Callm. & Buerki (Pandanaceae): characterization, circumscription, and distribution of a new genus of screw-pines, with a synopsis of accepted species
Fig. 5. – Infructescences and details of stigmas of species of Benstonea Callm. & Buerki. A. Benstonea parva (Ridl.) Callm. & Buerki; B. Benstonea pectinata (Martelli) Callm. & Buerki; C. Benstonea rupestris (. C. Stone) Callm. & Buerki; D. Benstonea thomissophylla (. C. Stone) Callm. & Buerki. [Photos: M. W. Callmander]
Fig. 6 in Benstonea Callm. & Buerki (Pandanaceae): characterization, circumscription, and distribution of a new genus of screw-pines, with a synopsis of accepted species
Fig. 6. – Infructescence of Benstonea thurstonii (C. H. Wright) Callm. & Buerki with details of stigmas in frame. [Photo: M. W. Callmander]
Fig. 2 in Benstonea Callm. & Buerki (Pandanaceae): characterization, circumscription, and distribution of a new genus of screw-pines, with a synopsis of accepted species
Fig. 2. – Plastid maximum likelihood phylogenetic tree of Pandanaceae inferred using RAxML and based on matK, trnL-trnF and trnQ-rps16. Bootstrap support values are represented below branches. This figure is adapted from the figure S1 in BUERKI & al. (2012).
Fig. 1 in Benstonea Callm. & Buerki (Pandanaceae): characterization, circumscription, and distribution of a new genus of screw-pines, with a synopsis of accepted species
Fig. 1. – General habit, infructescences and details of stigmas of species of Pandanus sect. Epiphytica Martelli (A-B) and Pseudoacrostigma B. C. Stone (C-D). A-B. Pandanus epiphyticus Martelli; C. Pandanus platystigma Martelli; D. Pandanus pugnax B. C. Stone. [Photos: M. W. Callmander]
Fig. 3 in Benstonea Callm. & Buerki (Pandanaceae): characterization, circumscription, and distribution of a new genus of screw-pines, with a synopsis of accepted species
Fig. 3. – Distribution map of Benstonea Callm. & Buerki showing the number of species and the level of endemicity per geographical region.
Quantitative magnetic resonance imaging of Scots pine seeds and the assessment of germination potential
<p>This dataset contains all the raw source data and MATLAB analysis functions that comprise the study:</p> <p><strong>Quantitative magnetic resonance imaging of Scots pine seeds and the assessment of germination potential</strong></p> <p>Canadian Journal of Forest Research | DOI: 10.1139/cjfr-2021-0273.</p> <p>Tuomainen, TV (1), Himanen, K (2), Helenius, P (2), Kettunen, MI (3), Nissi, MJ (1,4)*<br> 1. University of Eastern Finland, Department of Applied Physics, Kuopio, Finland<br> 2. Natural Resources Institute Finland, Suonenjoki Unit, Suonenjoki, Finland.<br> 3. University of Eastern Finland, Kuopio Biomedical Imaging Unit, A.I. Virtanen Institute for Molecular Sciences, Kuopio, Finland <br> 4. University of Oulu, Research Unit of Medical Imaging, Physics and Technology, Oulu, Finland</p> <p>*Corresponding author:<br> Mikko J. Nissi<br> Department of Applied Physics,<br> University of Eastern Finland<br> POB 1627<br> FI-70211, Kuopio, Finland<br> mikko.nissi@uef.fi<br> +358-50-5955517</p> <p>Keywords: Pinus sylvestris, seed germination, MRI, radiography, relaxation time mapping</p> <p> </p> <p><strong>Study and data description</strong></p> <p>Altogether 90 Scots pine (Pinus sylvestris L.) seeds were MR imaged using RAREVTR, MSME, MGE and ZTE pulse sequences with reference radiograph from each seed.</p> <p>The data includes MR images and relaxation time data as well as individual X ray radiographs of Scots pine seeds. </p> <p>The data includes all data ('fid' and '2dseq' for MRI, and .jpeg/.png for radiographs), metadata (acquisition and reconstruction MRI parameters), figures of manuscript, and calculated relaxation time maps (in MATLAB MAT-file format).</p> <p> </p> <p>Included folders and files in the zenodo_repo_scotspine_MRI_zip_20012022 are:</p> <ul> <li><strong>additional_info_scotspine</strong>: Information on the seed batches, their germination and structure in .xlsx file format. Translated into English from Finnish on 06.10.2021.</li> <li><strong>manuscript_figures:</strong> Figures in .eps vector file format (fig1.eps-fig7.eps)</li> <li><strong>matlab_scripts:</strong> Contains MATLAB functions and scripts for data analysis of the MRI data, processed together with 'aedes' GUI (aedes.uef.fi/, redirects to github.com).</li> <li><strong>mri_scotspine</strong>: Contains the MRI data using 5 mm and 10 mm RF coils at 11.7 T (Bruker). The folders 'discard_folder/' contain ZTE data that are not processed with carbon_collector.m MATLAB script (i.e. processed separately).</li> <li><strong>radiography_scotspine: </strong>Contains radiographs of invidual seeds in two folders: old (lower resolution, Faxitron MX-20, Faxitron Bioptics LLC, <em>Tucson, Az, USA</em>) and new (higher resolution, Faxitron MultiFocus, Faxitron Bioptics LLC, <em>Tucson, Az, USA</em>).</li> <li><strong>readme.txt: </strong>More information on the file and folder structure and datatypes.</li> </ul> <p> </p> <p>Please see the included readme.txt for further details.</p> <p> </p> <p>(Teemu Tuomainen, Jan 25, 2022)</p>
Data supporting "Solar radiation drives methane emissions from the shoots of Scots pine"
<p>Data supporting our New Phytologist publication "Solar radiation drives methane emissions from the shoots of Scots pine". </p>
T a b l e 5 in Month-To-Month Variations In Densities And Dominance Of Birds Breeding In An Extensive Pine Forest
T a b l e 5. Recommended and highly recommended months for counting birds by means of line transect method in pine forests
Data of microbiological decomposition monitoring of pine coniferous litter in the soils at the Moscow region by the ICP IM method
<p>Данные мониторинга микробиологического разложения хвойного опада сосны в почвах Московской области по методу ICP IM</p> <p>Data of microbiological decomposition monitoring of pine coniferous litter in the soils at the Moscow region by the ICP IM method</p> <p> </p> <p>Исследования проведены на базе двух особо охраняемых природных территориях (далее ООПТ) в Московской области и г. Москве, расположенных на расстоянии 90 км друг от друга. На обеих ООПТ работы проводились на постоянных пробных площадках (ППП) площадью 1 га.</p> <p>Эталон – Приокско-Террасный государственный природных биосферный заповедник. В заповеднике заложены 4 ППП, расположенные в бассейне малой реки Тоденка, большая часть бассейна которой находится в границах Заповедника. ППП расположены не далее 2 км от русла реки, в преобладающих по площади в ООПТ типах лесах: сосняке сложном (две ППП), березняке сложном широкотравном и дубраве широкотравной. В сосняках Заповедника были заложены 2 ППП, различающиеся по увлажнению и месторасположению, на террасе и на коренном берегу.</p> <p>Модельная находится под более высокой антропогенной нагрузкой в г. Москве с лесопарковая часть природно-исторического парка «Кузьминки-Люблино» (далее – Лесопарк), имеющая также схожий с Заповедником рельеф и породный состав лесов. Территории Заповедника и Лесопарка имеют сходство физико-географических условий формирования: обе ООПТ расположены на надпойменных террасах крупных рек Волжского бассейна (рек Оки и Москвы соответственно), на обеих территориях формируются слабо дифференцированные дерново-подзолистые почвы ржавоземы на флювиогляциальных песках (Brunic Arenosols) под сосновыми и березовыми лесами. Основные физико-химические свойства почв Лесопарка соответствуют естественным аналогам.</p> <p><strong>Метод изучения скорости разложения опада.</strong> Методической основой проводимых измерений скорости биоразложения опада является метод подпрограммы «MB Microbial decomposition» программы ICP IM [https://www.syke.fi/en-US/Research__development/Nature/Monitoring/Integrated_Monitoring/Manual_for_Integrated_Monitoring] с некоторыми изменениями.</p> <p>Изменения методики касались срока экспозиции. Мы использовали стандартный срок экспозиции в 1 год и отказались от экспозиции иголок более 1 года, как рекомендовано в методике ICP IM. Такая модификация метода позволила существенно сократить трудозатраты при получении сравнимых результатов.</p> <p>Измерение разложения опада проводились методом закладки конвертов из нейлоновой сетки 8 на 8 см с ячеей 1 мм с упакованными в них пробами на срок 1 год. Конверты запечатывались металлическими скобами. Пробы закладывались и снимались в последней декаде октября – начале ноября. В таблицах и тексте год указывается по году снятия образца, соответственно, пробы, заложенные в 2013 г. и собранные в 2014 г. относятся к 2014 г.</p> <p>Согласно методике, в экспериментах по изучению разложения опада использовались иголки сосны обыкновенной (<em>Pinus</em> <em>sylvestris</em> L.), которые собирались с ветвей невысоких деревьев (10–20 лет) в одном и том же квартале Заповедника и только пожелтевшие, перед их массовым опадом (обычно в начале октября). Предварительно все пробы высушивались до абсолютно сухого веса при 85 <sup>0</sup>С и взвешивались перед упаковкой в конверты. Взвешивание осуществлялось с точностью до 0.001 г, вес проб соснового опада 1 г.</p> <p>Конверты каждый год раскладывались на каждой ППП размерами 100×100 м возле углов и в центре пробных площадей в пределах квадрата 3×3 м в фиксированных точках. Конверты располагались в верхних 5 см почвы, под углом в 15<sup>0</sup>, под моховым покровом (при его наличии) или подстилкой и привязывались леской для удобства поиска. Не допускалось размещение конверта в приствольном круге деревьев. После экспозиции в течение 12 месяцев (350–380 суток) конверты снимались, а содержимое проб аккуратно с использованием пинцета промывалось дистиллированной водой от твердых частиц субстрата и мицелия грибов до остатков иголок и высушивалось до абсолютно сухого веса. Измерение потери массы каждой пробы проводилось методом взвешивания с точностью 0.001 г. Ежегодно закладывалось по 5 проб на каждой ППП в сосняке и березняке, но через год не всегда удавалось найти все заложенные конверты, так как происходили ветровалы и иные нарушения. На ППП в дубняке закладывалось по 10 конвертов.</p>
A low-dimensional, mechanistic water balance model for piñon pine-juniper woodlands in southern Nevada, USA
<p>This is a low-dimensional water balance model developed for pinon pine-juniper woodlands in southern Nevada. It may require extensive revision for use in other similar or dissimilar woodland ecosystems. The model will require parameterization before use in any capacity.</p> <p>This model is mechanistic, but is driven from randomized precipitation. This framework allows the user to estimate the mean and standard deviation of water balance variables by simulating the same average meteorological year 1000s of times, each with randomized precipitation. This technique approximates a normal distribution of precipitation, and will need to be modified for locations/sites that have a non-normal precipitation distribution. It is not recommended to use the model in any other way without first testing and validating its output.</p> <p>I have provided documentation throughout the wrapper, model and parameter files to assist with your use of the model. You are encouraged to learn from, build on, and improve this model. You will need to set your own pathways and build your own meteorological inputs and site parameterizations. You may need to update, revise and add/remove different submodules depending on your intended use.</p>
Data from: Pyrophilic plants respond to post-fire soil conditions in a frequently burned longleaf pine savanna
<p class="RealLife">Fire-plant feedbacks engineer recurrent fires in pyrophilic ecosystems like savannas. The mechanisms sustaining these feedbacks may be related to plant adaptations that trigger rapid responses to fire's effects on soil. Plants adapted for high fire frequencies should quickly regrow, flower, and produce seeds that mature rapidly and disperse post-fire. We hypothesized that offspring of such plants would germinate and grow rapidly, responding to fire-generated changes in soil nutrients and biota. We conducted an experiment using longleaf pine savanna plants that were paired based on differences in reproduction and survival under annual ("more" pyrophilic) vs. less frequent ("less" pyrophilic) fire regimes. Seeds were planted in different soil inoculations from experimental fires of varying severity. The "more" pyrophilic species displayed high germination rates followed by species specific, rapid growth responses to soil location and fire severity effects on soils. In contrast, the "less" pyrophilic species had lower germination rates that were not responsive to soil treatments. This suggests that rapid germination and growth constitute adaptations to frequent fires, and that plants respond differently to fire severity effects on soil abiotic factors and microbes. Further, variable plant responses to post-fire soils may influence plant community diversity and fire-fuel feedbacks in pyrophilic ecosystems.</p>
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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.