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Fig. 1 in Effect of leaf decomposition stage and water temperature on fragmentation activity of a shredder invertebrate species in lotic ecosystems
Fig. 1. Schematic representation of the eXperimental design of the present study. EXperiment I: nine discs of senescent (S) and nine discs of conditioned senescent (SCD) wastes were used in each aquarium in the absence of shredder invertebrates. EXperiment II: nine discs of senescent (S), nine discs of conditioned senescent (SCD) and nine discs of green detritus (G) were used in each aquarium in the presence of shredded invertebrates (Phylloicus sp.).
Fig. 2 in Effect of leaf decomposition stage and water temperature on fragmentation activity of a shredder invertebrate species in lotic ecosystems
Fig. 2. Mean values and standard error of leaf mass loss (LML) of senescent (senescent plus conditioned senescent, due to the absence of visual distinction by coloration) and green detritus for larval case production by Phylloicus sp. in the different water temperature treatments at Capetinga Stream, Água Limpa Farm, Brasília, Brazil.
Fig. 7. A, C in Latest Cretaceous leaf floras from southern Poland and western Ukraine
Fig. 7. A, C. Eudicot Debeya insignis (Hosius and von der Marck, 1880) Knobloch, 1964. A. Lectotype PBO 1021[−1]; Haldem, Stemweder Berg, upper Campanian. General view (A1), enlargement of the petiolule branching (A2). C. General view of the slab PBO 1021 showing the lectotype (shown in A) and a paralectotype (PBO 1021[−2]) of Debeya insignis as well as two leaflets of Debeya haldemiana (shown in B); Haldem, Stemweder Berg, upper Campanian. B, G. Debeya haldemiana de Saporta and Marion, 1873. B. Fragmentary leaf PBO 1021[−3]; Haldem, Stemweder Berg, upper Campanian. G. Isolated leaflet ZPAL 4/2/2; Bliżów, lower Maastrichtian. D. Eolirion sp., fragmentary leaf ZPAL Pl 4/1/9; Krasbobród, upper Campanian. E. Debeya paulinae sp. nov., fragmentary leaf KrM Pb 1/6 (paratype); Krasnobród, upper Campanian. F. Debeya paulinae sp. nov., paratype KrS 1, enlargement of the petiolule branching (see general view in Fig. 2C). Scale bars 10 mm.
Fig. 10 in Latest Cretaceous leaf floras from southern Poland and western Ukraine
Fig. 10. Reconstructions of leaves of the most characteristic taxa of the late Campanian flora of the studied area (not to scale). A. Eudicot Debeya paulinae sp. nov. B. Dicot Rarytkinia polonica (Karczmarz and Popiel in Malicki et al. 1967) comb. nov. C. Eudicot Debeya haldemiana (Debey ex de Saporta and Marion, 1873) Knobloch, 1964. Drawings by B. Waksmundzki.
Fig. 4. Conifer Cunninghamites squamosus Heer, 1873 in Latest Cretaceous leaf floras from southern Poland and western Ukraine
Fig. 4. Conifer Cunninghamites squamosus Heer, 1873. Single leaf from the specimen MZ VII/32/13, Chełm, Maastrichtian, SEM view.
Fig. 1 in Latest Cretaceous leaf floras from southern Poland and western Ukraine
Fig. 1. Map of central Europe showing the extent of upper Cretaceous deposits (both cropping out and under Quaternary cover; simplified after von Gaertner and Walther 1971). Main studied localities are represented by diamonds.
Cercospora Leaf Spot in Chili Pepper Leaves Image Dataset
<p>A custom dataset consisting of 1,738 preprocessed images of chili pepper leaves affected by Cercospora leaf spot for research purposes related to lesion detection using artificial intelligence algorithms.</p>
Fig. 5. Pleuromeialean lycophyte leaf Mesenteriophyllum serratum Sixtel, 1961 in Macrofossil evidence for pleuromeialean lycophytes from the Triassic of Antarctica
Fig. 5. Pleuromeialean lycophyte leaf Mesenteriophyllum serratum Sixtel, 1961 from the Triassic Madygen Formation, Kyrgyz Republic. Modified from Sixtel (1961). Leaf width up to ~12 mm.
Fig. 4. Pleuromeialean lycophyte leaf Mesenteriophyllum serratum Sixtel, 1961 in Macrofossil evidence for pleuromeialean lycophytes from the Triassic of Antarctica
Fig. 4. Pleuromeialean lycophyte leaf Mesenteriophyllum serratum Sixtel, 1961 from the Upper Triassic of the "Alfie's Elbow" site, central Transantarctic Mountains. A. Two overlying leaf fragments recognizable primarily by the distinct serrate appearance of the leaf margins. B. Detail of A showing serrate appearance of margins. C. Detail of leaf margin with alternating transverse ridges and furrows, and preserved cell pattern. Note longitudinal striae (s), circular holes on central leaf portion (some marked with arrows), and vertical alignment of transversely elongated epidermal cells (e) on leaf margin. D. Detail of leaf margin with cellular preservation, showing transversely elongated cells aligned in vertical rows. E. Detail of longitudinal striae on central leaf portion. F, G. Orthogonal pattern of epidermal cells in central leaf portion, visible only in places where carbonized cuticle layer is lifted off.
Figure 1. Air temperature and rainfall during the study between February 2015 and January 2016 in Intra-annual colonization of Chironomidae on leaf litter in a Brazilian Cerrado stream
Figure 1. Air temperature and rainfall during the study between February 2015 and January 2016 in the Boiadeiro stream, Mucugê, BA, Brazilian Cerrado. Data: http://www.snirh.gov.br/hidroweb/ serieshistoricas (Hidroweb 2020).
Figure 5 in Intra-annual colonization of Chironomidae on leaf litter in a Brazilian Cerrado stream
Figure 5. Non-metric multidimensional scaling (NMDS) of Chironomidae assemblages functional feeding group at leaf litter during inter-annual seasons in Boiadeiro stream, Mucugê, BA, Brazilian Cerrado. RD-Rainy-dry (brown). (D) Dry (red), (DR) Dry-rainy (green), (R) Rainy (blue).
Figures 2–3 in Intra-annual colonization of Chironomidae on leaf litter in a Brazilian Cerrado stream
Figures 2–3. Abundance (2) and richness (3) (mean ± SEM) of Chironomidae assemblages associated at leaf litter on 30, 60, and 90 days during inter-annual seasons in Boiadeiro stream, Mucugê, BA, Brazilian Cerrado.
Figure 4 in Intra-annual colonization of Chironomidae on leaf litter in a Brazilian Cerrado stream
Figure 4. Functional feeding group (FFG) proportion of Chironomidae assemblages associated at leaf litter during inter-annual seasons in Boiadeiro stream, Mucugê, BA, Brazilian Cerrado. (Shr) Shredder, (C-F) Collector-filter, (C-G) Collector-Gatherer, (Scr) Scraper, (Pre) Predator.
supporting files for "What to Choose for Estimating Leaf Water Status - Spectral Reflectance or in vivo Chlorophyll Fluorescence?"
<p><strong><span>Fig. 1 </span></strong><span>Workflow and parameters used for comparative analysis.</span></p> <p><strong><span>Fig. 2</span></strong><span> Representative spectra of diffusive reflectance measured on the adaxial side (R<sub>D</sub>) of fresh (RWC = 98%), partially desiccated (RWC = 52% or 54%) and severely desiccated leaves (RWC = 5%) of tobacco (A) and barley (E). Comparison of R<sub>D</sub> and R<sub>B</sub> (R from the abaxial leaf side) in fresh and severely desiccated leaves of tobacco (B) and barley (F). Water index (WI = R<sub>900</sub>/R<sub>970</sub>) and relative decrease of R in the 800-1100 nm region (ΔR) estimated from R<sub>D</sub> (indexed by "D") and R<sub>B</sub> (indexed by "B") in desiccating leaves of tobacco (C, D) and barley (G, H).</span></p> <p><strong><span>Fig. 3</span></strong><span> Water index (WI<sub>SWIR </sub>= R<sub>1000</sub>/R<sub>1450</sub>) estimated from measurement of directional R from adaxial side of desiccating leaf samples of tobacco (A) and barley (B). </span></p> <p><strong><span>Fig. 4 </span></strong><span>Equivalent water thickness (EWT) during desiccation of tobacco and barley leaf samples within the RWC interval 100-50%.</span></p> <p><strong><span>Fig. 5 </span></strong><span>Normalized difference vegetation index</span><span> </span><span>(NDVI</span><span> </span><span>=</span><span> </span><span>(R<sub>780</sub>-R<sub>630</sub>)/(R<sub>780</sub>+R<sub>630</sub>)) estimated from measurement of diffusive R from the </span><span>abaxial (</span><span>NDVI</span><sub><span>B</span></sub><span>) and </span><span>adaxial side (NDVI</span><sub><span>D</span></sub><span>) of desiccating leaves of tobacco (A) and barley (D). SPAD-value</span><span>s</span><span> of desiccating leaves of tobacco (B) and barley </span><span>(E)</span><span>. Relative SPAD and NDVI</span><span>΄<sub>D</sub> (estimated from measurement of directional R from the adaxial side</span><span>)</span><span> </span><span>of a representative leaf of tobacco </span><span>(C)</span><span> and barley (F) during its desiccation (in % of the value measured immediately after leaf detachment). For selected data points, the time after the leaf detachment is indicated. </span></p> <p><strong><span>Fig. 6</span></strong><span> Chlorophyll fluorescence parameters of desiccating tobacco and barley leaf samples. (A, D) The maximum quantum yield of PSII photochemistry in the dark-adapted state (F<sub>V</sub>/F<sub>M</sub>) and the effective quantum yield of PSII photochemistry in the light-adapted state (ΦPSII<sub>st</sub>). (B, E) The non-photochemical quenching of chlorophyll fluorescence after 1 min of exposure to actinic light (NPQ<sub>1</sub>). (C, F) The non-photochemical quenching of chlorophyll fluorescence at steady state (NPQ<sub>st</sub>).</span></p> <p><strong><span>Fig. 7 </span></strong><span>Coefficient of reliability (<em>CR</em>), coefficient of sensitivity (<em>CS</em>) and coefficient of inaccuracy (<em>CI</em>) of parameters measured in desiccating leaf samples of tobacco and barley within the RWC interval 100-50%. The parameters have been divided into 5 groups according to the type of leaf characteristics they reflect. A horizontal line in <em>CR</em> plot indicates the reliability threshold (<em>CR</em> = 0.4).</span></p> <p><strong><span>Table 1 </span></strong><span>Parameters measured on desiccating tobacco and barley leaves ranked according to the value of their coefficient of reliability (<em>CR</em>) within the RWC interval 100-50% and the corresponding values of the coefficient of determination (<em>R<sup>2</sup></em>).</span></p> <p><strong><span>Fig. S1 </span></strong><span>Decrease in relative water content (RWC) of leaf samples of tobacco and barley with time after their detachment</span></p> <p><strong><span>Fig. S2 </span></strong><span>Micrographs of leaf structure of fresh tobacco (A) and barley (B) leaves.</span></p> <p><strong><span>Fig. S3</span></strong><span> </span><span>WI<sub>SWIR</sub> images </span><span>o</span><span>f representative desiccating tobacco and barley leaf samples</span><strong><span>. </span></strong><span>Numbers above the samples indicate their RWC in %.</span></p> <p><strong><span>Fig. S4 </span></strong><span>(A)</span><strong><span> </span></strong><span>Leaf area (in % of the area of fresh leaves) and (B) equivalent water thickness (EWT) during desiccation of tobacco and barley leaf samples.</span></p> <p><strong><span>Fig. S5 </span></strong><span>Imaging of chlorophyll fluorescence parameters of representative desiccating tobacco and barley leaf samples. The maximum quantum yield of PSII photochemistry (F<sub>V</sub>/F<sub>M</sub>), the effective quantum yield of PSII photochemistry in the light-adapted state (ΦPSII<sub>st</sub>), the non-photochemical quenching of chlorophyll fluorescence after 1 min of exposure to actinic light (NPQ<sub>1</sub>), and the non-photochemical quenching of Chl fluorescence at steady state (NPQ<sub>st</sub>).</span></p> <p><strong><span>Fig. S6</span></strong><span> Dependencies of</span><strong><span> </span></strong><span>measured parameters on RWC (in interval 100-50%) in desiccating tobacco leaves and segments. The parameters are ranked from most to least reliable according to their coefficient of reliability (<em>CR</em>). All parameters are normalized to their mean value (<em>ȳ</em>).</span></p> <p><strong><span>Fig. S7</span></strong><span> Dependencies of</span><strong><span> </span></strong><span>measured parameters on RWC (in interval 100-50%) in desiccating barley leaves and segments. The parameters are ranked from most to least reliable according to their coefficient of reliability (<em>CR</em>). All parameters are normalized to their mean value (<em>ȳ</em>).</span></p> <p><strong><span>Fig. S8 </span></strong><span>Leaf water potential measured by psychrometry </span><span>(Ψ<sub>psy</sub>) and by pressure chamber (Ψ<sub>press</sub>) in desiccating leaves of tobacco (A) and barley (B).</span></p> <p><strong><span>Table S1 </span></strong><span>Parameters measured on desiccating leaf samples ranked according to their coefficient of sensitivity (<em>CS</em>) within the RWC interval 100-50% in tobacco and barley.</span></p> <p><strong><span>Table S2 </span></strong><span>Parameters measured on desiccating leaf samples ranked according to their coefficient of inaccuracy (<em>CI</em>) within the RWC interval 100-50% in tobacco and barley.</span></p> <p><strong><span>Table S3 </span></strong><span>Ranking of measured parameters according to their coefficient of reliability (<em>CR</em>), sensitivity (<em>CS</em>) and inaccuracy (<em>CI</em>) in desiccating leaf samples of tobacco and barley within the RWC interval 100-50%. The parameters have been divided into 5 groups (the first column) according to the type of leaf characteristics they reflect.</span></p> <p><strong><span>Table S4</span></strong><span> Approximate </span><span>time required for the measurement of the parameters used in the study and the destructiveness/non-destructiveness of the measurement. The parameters that were used for the comparison according to their coefficients of reliability (<em>CR</em>), sensitivity (<em>CS</em>) and inaccuracy (<em>CI</em>) are written in bold.</span></p> <p><strong><span>Fig. 2_spectra of diffusive reflectance </span></strong><span>- source data for each panel (A-H) of Fig. 2: </span><span>Representative spectra of diffusive reflectance measured on the adaxial side (R<sub>D</sub>) of fresh (RWC = 98%), partially desiccated (RWC = 52% or 54%) and severely desiccated leaves (RWC = 5%) of tobacco (A) and barley (E). Comparison of R<sub>D</sub> and R<sub>B</sub> (R from the abaxial leaf side) in fresh and severely desiccated leaves of tobacco (B) and barley (F). Water index (WI = R<sub>900</sub>/R<sub>970</sub>) and relative decrease of R in the 800-1100 nm region (ΔR) estimated from R<sub>D</sub> (indexed by "D") and R<sub>B</sub> (indexed by "B") in desiccating leaves of tobacco (C, D) and barley (G, H).</span></p> <p><strong><span>Fig.3_water index WISWIR</span></strong><span> - source data for each panel (A+B) of Fig. 3: Water index (WISWIR = R1000/R1450) estimated from measurement of directional R from adaxial side of desiccating leaf samples of tobacco (A) and barley (B).</span></p> <p><strong><span>Fig.4_equivalent water thickness</span></strong><span> - source data for Fig. 4: Equivalent water thickness (EWT) during desiccation of tobacco and barley leaf samples within the RWC interval 100-50%.</span></p> <p><strong><span>Fig.5_NDVI</span></strong><span> - source data for each panel (A-F) of Fig. 5: Normalized difference vegetation index (NDVI = (R780-R630)/(R780+R630)) estimated from measurement of diffusive R from the abaxial (NDVIB) and adaxial side (NDVID) of desiccating leaves of tobacco (A) and barley (D). SPAD-values of desiccating leaves of tobacco (B) and barley (E). Relative SPAD and NDVI΄D (estimated from measurement of directional R from the adaxial side) of a representative leaf of tobacco (C) and barley (F) during its desiccation (in % of the value measured immediately after leaf detachment).</span></p> <p><strong><span>Fig.6_chlorophyll fluorescence parameters</span></strong><span> - source data for each panel (A-F) of Fig. 6: Chlorophyll fluorescence parameters of desiccating tobacco and barley leaf samples. (A, D) The maximum quantum yield of PSII photochemistry in the dark-adapted state (FV/FM) and the effective quantum yield of PSII photochemistry in the light-adapted state (ΦPSIIst). (B, E) The non-photochemical quenching of chlorophyll fluorescence after 1 min of exposure to actinic light (NPQ1). (C, F) The non-photochemical quenching of chlorophyll fluorescence at steady state (NPQst).</span></p> <p><strong><span>Fig.7_coefficients of reliability, sensitivity, inaccuracy</span></strong><span> - Coefficient of reliability (CR), coefficient of sensitivity (CS) and coefficient of inaccuracy (CI) of parameters measured in desiccating leaf samples of tobacco and barley within the RWC interval 100-50%.</span></p> <p><strong><span>Fig.S1_relative water content</span></strong><span> - source data for supplementary Fig. 1: Relative water content (RWC) of leaf samples of tobacco and barley with time after their detachment.</span></p> <p><strong><span>Fig.S4_leaf area and equivalent water thickness</span></strong><span> - source data for supplementary Fig. 4: Leaf area (A) and equivalent water thickness (EWT; B) during desiccation of tobacco and barley leaf samples.</span></p> <p><strong><span>Fig.S6_dependencies of parameters on RWC in tobacco</span></strong><span> - source data for each panel (A-N) of supplementary Fig.6: Dependencies of measured parameters (water potential, NPQ, NDVI, reflectance, SPAD, Fv/Fm, water indexes) on RWC (in interval 100-50%) in desiccating tobacco leaves and segments.</span></p> <p><strong><span>Fig.S7_dependencies of parameters on RWC in barley</span></strong><span> - source data for each panel (A-N) of supplementary Fig.7: Dependencies of measured parameters (water potential, NPQ, NDVI, reflectance, SPAD, Fv/Fm, water indexes) on RWC (in interval 100-50%) in desiccating barley leaves and segments.</span></p> <p><strong><span>Fig.S8_leaf water potential</span></strong><span> - source data for supplementary Fig. 8: Leaf water potential measured by psychrometry (Ψpsy) and by pressure chamber (Ψpress) in desiccating leaves of tobacco (A) and barley (B).</span></p>
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).
FIGURE 5. Justicia zapoteca. A. Shoot with inflorescence. B. Leaf. C. Inflorescence node with flower. D. Bracteole. E. Bract. F. Calyx. G in New and Reconsidered Mexican Acanthaceae XII
FIGURE 5. Justicia zapoteca. A. Shoot with inflorescence. B. Leaf. C. Inflorescence node with flower. D. Bracteole. E. Bract. F. Calyx. G. Distal portion of stamen with bithecous anther. H. Capsule. I. Seed. (A, C from Daniel et al. 11898; B, H, I from Daniel et al. 11810; D–G from Saynes V. & Elorsa 2741). Drawn by Sean Edgerton.
FIGURE 2. Carlowrightia yucatanensis. A. Shoot with inflorescence. B. Leaf. C in New and Reconsidered Mexican Acanthaceae XII
FIGURE 2. Carlowrightia yucatanensis. A. Shoot with inflorescence. B. Leaf. C. Inflorescence nodes with corolla dehisced (bottom) and corolla present (top) in side-view. D. Magnification of inflorescence rachis. E. Corolla in front-view. F. Distal portion of stamen with bithecous anther, side-view (left) and front-view (right). G. Distal portion of style and stigma. H. Capsule with one seed. I. Magnification showing pubescence on surface of capsule. J. Seed. K. Magnification of seed margin. (A, B from Daniel et al. 10312; C–K from Daniel et al. 10320). Drawn by Amy Whitesides
Figure 4 in Introgression of bacterial leaf blight (BLB) resistant gene, Xa7 into MARDI elite variety, MR219 by marker assisted backcrossing (MABC) approach
Figure 4. PCR-based genetic polymorphism analysis of Xa7 gene closed linked, ID7 marker. Agarose gel profile of backcrossed progenies in 2% (w/v) of 1X TBE agarose gel. Lane L: 100bp DNA ladder. Lanes D and R represent IRBB7 and MR219 respectively. Line 1-22: (1) PB-2-91, (2) PB-2-107, (3) PB-2-156, (4) PB-2-224, (5) PB-2-234, (6) PB-2-238, (7) PB-2-258, (8) PB-2-29, (9) PB-2-77, (10) PB-2-226, (11) PC3-26-2, (12) PC-39-3, (13) PB-2-34, (14) PB-2-35, (15) PB-2-150, (16) PB-2-223, (17) PB-2-252, (18) PC-3-14-3, (19) PC-3-23-1, (20) PB-2-32, (21) PC3-5-2, (22) MR263.
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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.