Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
10
datasets available to search
ShareScore release 0.9.0
Dataset results
10 results for “White birch”
Diurnal Patterns of Cavitation in Red Maple, Paper Birch and White Ash at Harvard Forest 2011-2012
Previous work at Harvard Forest has suggested that woody plants cavitate and re-dissolve embolisms in xylem on a daily basis. Here we investigated the common assumption that severing stems and petioles under water preserves the hydraulic continuity in the xylem conduits opened by the cut when the xylem is under tension. In red maple and white ash, higher PLC in the afternoon occurred when the measurement segment was excised under water at native xylem tensions, but not when xylem tensions were relaxed prior to sample excision. Bench drying vulnerability curves in which measurement samples were excised at native versus relaxed tensions showed a dramatic effect of cutting under tension in red maple, a moderate effect in sugar maple, and no effect in paper birch. These results suggest that sampling methods can generate PLC patterns indicative of repair under tension by inducing a degree of embolism that is itself a function of xylem tensions at the moment of sample excision.
Tree-Ring Data for Co-Occurring White Spruce and Paper Birch at an Intermediate Aged Stand in the Bonanza Creek LTER Regional Site Network - 2018
This dataset contains tree ring widths of co-occurring white spruce and Alaska paper birch. The data were published as part of a 2021 article in Journal of Ecology.
Ecoregion and community structure influences on the foliar elemental niche of balsam fir (Abies balsamea (L.) Mill.) and white birch (Betula papyrifera Marshall)
<p><strong><span>Context</span></strong><span>: Changes in foliar elemental niche properties, defined by axes of carbon (C), nitrogen (N), and phosphorus (P) concentrations, reflect how species allocate resources under different environmental conditions. For instance, elemental niches may differ in response to large-scale latitudinal temperature and precipitation regimes that occur between ecoregions and small-scale differences in nutrient dynamics based on species co-occurrences at a community level.</span></p> <p><strong><span>Methods</span></strong><span>: at a species level, we compared foliar elemental niche hypervolumes for balsam fir (<em>Abies balsamea</em> (L.) Mill.) and white birch (<em>Betula papyrifera</em> Marshall) between a northern and southern ecoregion. At a community level, we grouped our focal species using plot data into conspecific (i.e., only one focal species is present) and heterospecific groups (i.e., both focal species are present) and compared their foliar elemental concentrations under these community conditions across, within, and between these ecoregions. Between ecoregions at the species and community level, we expected niche hypervolumes to be different and driven by regional biophysical effects on foliar N and P concentrations. At the community level, we expected niche hypervolume displacement and expansion patterns for fir and birch, respectively – patterns that reflect their resource strategy.</span></p> <p><strong><span>Results</span></strong><span>: at the species level, foliar elemental niche hypervolumes between ecoregions differed significantly for fir (F = 14.591, p-value = 0.001) and birch (F = 75.998, p-value = 0.001) with higher foliar N and P in the northern ecoregion. At the community level, across ecoregions, the foliar elemental niche hypervolume of birch differed significantly between heterospecific and conspecific groups (F = 4.075, p-value = 0.021) but not for fir. However, both species displayed niche expansion patterns, indicated by niche hypervolume increases of 35.49% for fir and 68.92% for birch. Within the northern ecoregion, heterospecific conditions elicited niche expansion responses, indicated by niche hypervolume increases for fir of 29.04% and birch of 66.48%. In the southern ecoregion we observed a contraction response for birch (niche hypervolume decreased by 3.66%), and no changes for fir niche hypervolume. Conspecific niche hypervolume comparisons between ecoregions yielded significant differences for fir and birch (F = 7.581, p-value = 0.005 and F = 8.038, p-value = 0.001) as did heterospecific comparisons (F = 6.943, p-value = 0.004, and F = 68.702, p-value = 0.001, respectively). </span></p> <p><strong><span>Conclusions</span></strong><span>: our results suggest species may exhibit biogeographical specific elemental niches – driven by biophysical differences such as those used to describe ecoregion characteristics. We also demonstrate how a species resource strategy may inform niche shift patterns in response to different community settings. Our study highlights how biogeographical differences may influence foliar elemental traits and how this may link to concepts of ecosystem and landscape functionality.</span></p>
Рис. 1. Географическое поΛожение Норского заповеΑника (А) и картосхема распоΛожения на его территории (Б) учетных пΛощаΑок с фитоценозами (L_1–L_7) на Αвух мониторинговых станциях (I–II). I — МаΛьцевская: L_1 — березняк с участием осины и Λиственницы рябинниковый вейниково-разнотравный; L_2 — осиново-беΛоберезовый рябинниковый вейниково-разнотравный Λес; L_3 — Λиственничник с участием березы пΛоскоΛистной осоково-вейниковый с разнотравьем; L_4 — беΛоберезово-Λиственничный с примесью осины роΑоΑенΑроновый бруснично-осоковый Λес; L_5 — закустаренный, преимущественно тавоΛгой ивоΛистной, разнотравно-вейниковый Λуг. II — Антоновская: L_6 — Λиственничник роΑоΑенΑроново-брусничный; L_7 — Λиственнично-беΛоберезовый с примесью пихты и еΛи закустаренный разнотравно-вейниковый Λес (коΑ типа местообитания соответствуют таковому в табΛ. 1 и 3 и на рис. 2) Fig. 1. Geographical location of the Norsky Nature Reserve (A) and the map (B) of registration sites with phytocenoses (L_1–L_7) at two monitoring stations (I–II). I — Maltsevskaya: L_1 — birch forest with aspen and larch, fieldfare reed-forb; L_2 — aspen-white-birch, fieldfare reed-forb forest; L_3 — larch forest with flat-leaved sedge-reed birch with forbs; L_4 — white-birch-larch with an admixture of aspen rhododendron lingonberry-sedge forest; L_5 — bushy, mostly meadowsweet, forb-reed grass meadow. II — Antonovskaya: L_6 — rhododendron-cowberry larch forest; L_7 — larch-white-birch with fir and spruce, shrubby forb-reed grass forest (the code of the habitat type corresponds to that in Tables 1 and 3 and in Fig. 2) in Structure and dynamics of the taxocenes of shrews in different habitats of the Norsky nature reserve
Рис. 1. Географическое поΛожение Норского заповеΑника (А) и картосхема распоΛожения на его территории (Б) учетных пΛощаΑок с фитоценозами (L_1–L_7) на Αвух мониторинговых станциях (I–II). I — МаΛьцевская: L_1 — березняк с участием осины и Λиственницы рябинниковый вейниково-разнотравный; L_2 — осиново-беΛоберезовый рябинниковый вейниково-разнотравный Λес; L_3 — Λиственничник с участием березы пΛоскоΛистной осоково-вейниковый с разнотравьем; L_4 — беΛоберезово-Λиственничный с примесью осины роΑоΑенΑроновый бруснично-осоковый Λес; L_5 — закустаренный, преимущественно тавоΛгой ивоΛистной, разнотравно-вейниковый Λуг. II — Антоновская: L_6 — Λиственничник роΑоΑенΑроново-брусничный; L_7 — Λиственнично-беΛоберезовый с примесью пихты и еΛи закустаренный разнотравно-вейниковый Λес (коΑ типа местообитания соответствуют таковому в табΛ. 1 и 3 и на рис. 2) Fig. 1. Geographical location of the Norsky Nature Reserve (A) and the map (B) of registration sites with phytocenoses (L_1–L_7) at two monitoring stations (I–II). I — Maltsevskaya: L_1 — birch forest with aspen and larch, fieldfare reed-forb; L_2 — aspen-white-birch, fieldfare reed-forb forest; L_3 — larch forest with flat-leaved sedge-reed birch with forbs; L_4 — white-birch-larch with an admixture of aspen rhododendron lingonberry-sedge forest; L_5 — bushy, mostly meadowsweet, forb-reed grass meadow. II — Antonovskaya: L_6 — rhododendron-cowberry larch forest; L_7 — larch-white-birch with fir and spruce, shrubby forb-reed grass forest (the code of the habitat type corresponds to that in Tables 1 and 3 and in Fig. 2)
Fig. 2 in Effect of tenthredinid leaf miner invasions on growth of Alaska white birch in Anchorage, Alaska, USA, and the interaction with biological control of amber-marked birch leaf miner
Fig. 2. Time series analysis of mean radial growth increments (mm) of Alaska white birch (Betula neoalaskana) in Anchorage, Alaska (n = 99) from 1984 to 2018: (1) pre-amber-marked birch leaf miner (Profenusa thomsoni) outbreak control period (1984–1995) (black dots); (2) amber-marked birch leaf miner outbreak period (1996–2007) (red dots); and (3) the amber-marked birch leaf miner suppression period due to biological control (2008–2018) (green dots). Time Series Mean = 1.7938, Std = 0.3843, N = 35, Zero Mean ADF (Augmented Dickey Fuller test) = −0.9887, Single ADF = −2.8315, Trend ADF = −4.8800.
Fig. 1 in Effect of tenthredinid leaf miner invasions on growth of Alaska white birch in Anchorage, Alaska, USA, and the interaction with biological control of amber-marked birch leaf miner
Fig. 1. Percentage of Alaska white birch (Betula neoalaskana) leaves in Anchorage mined by the amber-marked birch leaf miner (AMBLM on graph) (Profenusa thomsoni) or the late birch leaf edge miner (LEM on graph) (Heterarthrus nemoratus) from 1990 to 2019, from the initial invasion of amber-marked birch leaf miner (around 1991) through its suppression by classical biocontrol (2004– 2015) and the invasion of a second species of leaf miner (H. nemoratus) (around 2008). Data on percentage of birch leaves mined by each species were taken from multiple sources: (1) P. thomsoni: 2006–2011 (Soper et al. 2015); 2015 and 2018 (Wenninger unpublished 2018); and 2019 (Andersen et al. 2021); and (2) H. nemoratus: 2008–2010 (Lundquist et al. 2012); 2011 (Mulvey &Lamb 2012, p. 15); 2015 and 2018 (Wenninger unpublished 2018); and 2019 (Andersen et al. 2021).
Fig. 3 in Effect of tenthredinid leaf miner invasions on growth of Alaska white birch in Anchorage, Alaska, USA, and the interaction with biological control of amber-marked birch leaf miner
Fig. 3. Trends in annual radial growth increment (mm) from Alaska white birch (Betula neoalaskana) in Anchorage, Alaska (n = 99 cores) during each of 3 periods: (A) the pre-amber-marked birch leaf miner (Profenusa thomsoni) outbreak period (1984–1995, (B) the amber-marked birch leaf miner outbreak period (1996– 2007), and (C) the biological control amber-marked birch leaf miner suppression period (2008–2018).
Ecoregion and community structure influences on the foliar elemental niche of balsam fir (Abies balsamea (L.) Mill.) and white birch (Betula papyrifera Marshall)
Open the record for dataset details and reuse information.
Sap Flux and Microclimate Data for Co-Occurring White Spruce and Paper Birch at an Intermediate Aged Stand in the Bonanza Creek LTER Regional Site Network 2013-2018
This dataset contains hourly mean sap flux density and microclimate data for co-occurring white spruce and Alaska paper birch from early June of 2013 to mid-September of 2018. The data were published as part of a 2021 article in Journal of Ecology.
Assessing the Efficacy and Safety of White Birch Sap for Skin Whitening: In Vivo and In Vitro Investigations
<p><strong>Figure S1.</strong> Schematic diagram of fluorescence intensity of neutral-particle fluorescent zebrafish treated with WBS (50, 100 and 200 μg/mL).</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.