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202 results for “sap”
The asymmetric diurnal latent heat flux in Chi-Lan montane cloud-fog forest: CLM simulations and sap flow observations
<p>Chilan_30min_sap_flow_V_2020JJA.csv recorded the data of sap flow velocity during JJA 2020.</p> <p>CL_CTR.*.nc is the analyzed CTR simulations which consider fog interception as a source of canopy water.</p> <p>CL_EXP.*.nc is the analyzed EXP simulations that do not allow the canopy to hold the water.</p>
Quantification of uncertainties introduced by data-processing procedures of sap flow measurements using the cut-tree method on a large mature tree
<p>Motivation: Sap flow sensors are crucial instruments to understand whole-tree water use. The lack of direct calibration of the available methods on large trees and the application of several data-processing procedures may jeopardize our understanding of water uptake dynamics by increasing the uncertainties around sensor-based estimates. We directly compared the heat ratio method (HRM) sap flow measurements to water uptake measured gravimetrically using the cut-tree method on a large mature aspen tree to quantify those uncertainties for ten consecutive days.</p> <p>Dataset: In this dataset, we provide sap flux density (ten-minutes intervals; g.cm-2.hr-1; corrected for wounding and sapwood thermal diffusivity) obtained from four HRM sap flow sensors installed at 2.5 m high on the focus tree (20 m tall, 60 years old trembling aspen in the boreal mixedwood region of Alberta) between July 18th and August 22nd 2017. We present the code and data (weather data from neighboring weather station) used to calculate whole-tree sap flux (L.hr-1) from each of the individual sensors using different methods of radial integration of sap flux density across the sapwood area estimated via different calculations, as well as different zero-flow corrections used. The cut-tree procedure was applied to the focus tree, and gravimetric measurements of water uptake (ten-minutes intervals) were made using a recording scale. We directly compared the different estimates of hourly, daily and cumulative sap flows obtained with gravimetric measurement of water uptake. We present the code providing the statistical analysis and results reported in the associated publication (Merlin, M., Solarik, K.A., Landhäusser, S.M. Quantification of uncertainties introduced by data-processing procedures of sap flow measurements using the cut-tree method on a large mature tree. 2020. Agricultural and Forest Meteorology, http://dx.doi.org/10.1016/j.agrformet.2020.107926)</p>
Bridging the flux gap: sap flow measurements reveal species-specific patterns of water-use in a tallgrass prairie
<p>Predicting the hydrological consequences following changes in grassland vegetation type (i.e., woody encroachment) requires an understanding of water flux dynamics at high spatiotemporal resolution for predominant species within grassland communities. However, grassland fluxes are typically measured at the leaf or landscape scale, which inhibits our ability to predict how individual species contribute to changing ecosystem fluxes. We used external heat balance sap flow sensors and a hierarchical Bayesian state-space modeling approach to bridge this "flux-gap" and estimate continuous species-level water flux in common tallgrass prairie species. Specifically, we asked: 1) How do diurnal and nocturnal water fluxes differ among woody and herbaceous plants? (2) How sensitive are woody and herbaceous species to environmental drivers of diurnal and nocturnal water flux? We highlight three results: (1) <i>Cornus drummondii</i>, the primary woody encroacher in this grassland, exhibited the greatest canopy-level water loss, (2) nocturnal transpiration was a large component of the water lost in this ecosystem and was driven primarily by C<sub>4</sub> grasses and <i>C. drummondii</i>, and (3) the sensitivity of canopy transpiration to environmental drivers varies among plant functional types and throughout a 24-hour period. Our data reveal important insights regarding the water-use strategies of woody versus herbaceous species in tallgrass prairies, and about the potential hydrological consequences of ongoing woody encroachment. We suggest that the high, static flux rates observed in woody species will likely deplete deep water stores over time, potentially creating hydrological deficits in grasslands experiencing woody encroachment and concomitantly increasing the vulnerability of these ecosystems to drought.</p>
Data from: Single, but not dual, attack by a biotrophic pathogen and sap-sucking insect affects the oak leaf metabolome
<p>Plants interact with a multitude of microorganisms and insects, both belowand above ground, which might influence plant metabolism. Despite this, we lack knowledge of the impact of natural soil communities and multiple aboveground attackers on the metabolic responses of plants, and whether plant metabolic responses to single attack can predict responses to dual attack. We used untargeted metabolic fingerprinting (gas chromatographymass spectrometry, GC-MS) on leaves of the pedunculate oak, <em>Quercus robur</em>, to assess the metabolic response to different soil microbiomes and aboveground single and dual attack by oak powdery mildew (<em>Erysiphe alphitoides</em>) and the common oak aphid (<em>Tuberculatus annulatus</em>). Distinct soil microbiomes were not associated with differences in the metabolic profile of oak seedling leaves. Single attacks by aphids or mildew had pronounced but different effects on the oak leaf metabolome, but we detected no difference between the metabolomes of healthy seedlings and seedlings attacked by both aphids and powdery mildew. Our findings show that aboveground attackers can have species-specific and non-additive effects on the leaf metabolome of oak. The lack of a metabolic signature detected by GC-MS upon dual attack might suggest the existence of a potential negative feedback, and highlights the importance of considering the impacts of multiple attackers to gain mechanistic insights into the ecology and evolution of species interactions and the structure of plant-associated communities, as well as for the development of sustainable strategies to control agricultural pests and diseases and plant breeding.</p>
Processed data supporting the manuscript "Cutting the sap: first molecular phylogeny of twig-girdler longhorn beetles (Coleoptera: Cerambycidae: Lamiinae: Onciderini) suggests shifts in host plant attack behaviors contributed to morphological evolution"
<div><strong>Processed data supporting the manuscript: </strong>Cutting the sap: first molecular phylogeny of twig-girdler longhorn beetles (Coleoptera: Cerambycidae: Lamiinae: Onciderini) suggests shifts in host plant attack behaviors contributed to morphological evolution</div> <div> </div> <div><strong>By:</strong> Diego de S. Souza 1, 2, Rowan L. K. French 3, José O. Silva Júnior 4, Eugenio H. Nearns 5, Luciane Marinoni 4, Ian P. Swift 6, Kelly B. Miller 7, Felix A. H. Sperling 2 & Marcela L. Monné 1</div> <div> </div> <div>1 Department of Entomology, National Museum, Federal University of Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.</div> <div>2 Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.</div> <div>3 Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.</div> <div>4 Department of Zoology, Federal University of Paraná, Curitiba, Paraná, Brazil.</div> <div>5 National Museum of Natural History, Smithsonian Institution, Washington, DC, USA.</div> <div>6 California State Collection of Arthropods, Sacramento, California, USA.</div> <div>7 Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico, USA.</div> <div> </div> <div>Corresponding author: Diego de S. Souza, dsouza@fieldmuseum.org. Current affiliation: Field Museum of Natural History, Chicago, Illinois, USA.</div> <div> </div> <div> </div> <div><strong>List of Contents: </strong></div> <div> </div> <div><strong>Onciderini_concat_matrix.phy</strong></div> <div>Concatenated matrix (cox1, Wg and CPS) used for the phylogenetic analyses of Onciderini (Coleoptera: Cerambycidae: Lamiinae: Onciderini). </div> <div> </div> <div><strong>PartitionFinder_AICc_best_scheme.txt</strong></div> <div>Results from PartitionFinder v2.1.1, containing the best partitioning scheme for the concatenated matrix of Onciderini, identified using the corrected Akaike Information Criterion (AICc), with model definitions for use in the phylogenetic analyses.</div> <div> </div> <div><strong>RAxML_Onciderini_concat_matrix (zip file)</strong></div> <div>- Onciderini_concat_matrix.phy: concatenated matrix (cox1, Wg and CPS) used in the RAxML phylogenetic analyses of Onciderini (Coleoptera: Cerambycidae: Lamiinae: Onciderini).</div> <div>- Partitions_AICc_RAxML.txt: partitioning scheme used in the RAxML analysis as predefined by PartitionFinder v2.1.1 using the corrected Akaike Information Criterion (AICc).</div> <div>- RAxML_bestTree.Onciderini_concat_matrix_ML: best-scoring maximum likelihood tree inferred by RAxML for the concatenated matrix of Onciderini.</div> <div>- RAxML_bipartitions.Onciderini_concat_matrix_final: bipartitions (clades) of the maximum likelihood tree inferred by RAxML with support values estimated from 1,000 pseudoreplicates.</div> <div>- RAxML_bipartitionsBranchLabels.Onciderini_concat_matrix_final: final maximum likelihood tree inferred by RAxML for the concatenated matrix of Onciderini, with labeled branches showing bootstrap support values.</div> <div>- RAxML_bootstrap.Onciderini_concat_matrix_bootstrap: bootstrap trees generated from a non-parametric bootstrap analysis in RAxML based on 1,000 pseudoreplicates.</div> <div>- RAxML_info.Onciderini_concat_matrix_bootstrap: log file containing details of the bootstrap analysis, including the settings and parameters used in the non-parametric bootstrap runs in RAxML.</div> <div>- RAxML_info.Onciderini_concat_matrix_final: log file summarizing the RAxML analysis, including settings and convergence statistics for the final maximum likelihood tree.</div> <div>- RAxML_info.Onciderini_concat_matrix_ML: log file containing details of the maximum likelihood tree search, including the parameters and models applied during the maximum likelihood analysis conducted by RAxML.</div> <div>- RAxML_log.Onciderini_concat_matrix_ML: log file of the maximum likelihood tree search for the concatenated matrix of Onciderini.</div> <div>- RAxML_parsimonyTree.Onciderini_concat_matrix_ML: parsimony starting tree used by RAxML during the maximum likelihood analysis for the concatenated matrix of Onciderini.</div> <div>- RAxML_result.Onciderini_concat_matrix_ML: maximum likelihood tree inferred by RAxML from the concatenated matrix of Onciderini, summarizing the tree topology and likelihood score for the best tree obtained.</div> <div> </div> <div><strong>BI_AICc_Onciderini_concat_matrix (zip file)</strong></div> <div>- BI_AICc_Onciderini_concat_matrix.nex: nexus file containing the concatenated matrix of Onciderini used for Bayesian Inference (BI), including the best-fit model scheme identified by PartitionFinder and MCMC parameters for running the analysis in MrBayes.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex_r1_r2_combined_consensus.tree: consensus tree from two combined independent Bayesian Inference (BI) runs based on the concatenated matrix of Onciderini, after discarding the first 25% of initial generations as burn-in.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex.run1.p: log file containing parameter values and likelihood scores from the first run of the Bayesian Inference (BI) based on the concatenated matrix of Onciderini.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex.run2.p: log file containing parameter values and likelihood scores from the second run of the Bayesian Inference (BI) based on the concatenated matrix of Onciderini.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_lognormal (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_lognormal.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- BEAST2_Onciderini_BD_lognormal_run[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_exponential (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_exponential.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- BEAST2_Onciderini_BD_exponential_[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- TreeAnnotator_Onciderini_BD_exponential_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- TreeAnnotator_Onciderini_BD_exponential_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_uniform (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_uniform.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- BEAST2_Onciderini_BD_uniform_[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- TreeAnnotator_Onciderini_BD_uniform_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- TreeAnnotator_Onciderini_BD_uniform_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>Comparative_analyses (zip file)</strong></div> <div><strong>RawData (folder):</strong> raw morphometric and girdling data, plus tree that was later pruned for downstream comparative analyses; these data were used as input for the OncidHeadDimorphism-DatasetPREP-FINAL.R data cleaning script. </div> <div>- Onciderini_BD_lognormal_run1-run8_consensus.nwk: newick version of TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.tre (outputted as a newick file by importing the .tre file into FigTree and exporting in newick format).</div> <div>- Measurements_Onciderini_Raw_Final.csv: individual-level raw morphometric data for Onciderini.</div> <div>- Behav_Matrix_2_states_trimmed_2022-12-15.csv: species-level data on girdling status for Onciderini species, with all Lochmaeocles species classified as girdlers (2 behavioral states across Onciderini species). </div> <div>- Matrix_3_states_trimmed_final.csv: species-level data on girdling status for Onciderini species, with all Lochmaeocles species classified as facultative girdlers (3 behavioral states across Onciderini species). </div> <div>- Matrix_2_states_trimmed_1LochGirdler_Final.csv: species-level data on girdling status for Onciderini species, with only one Lochmaeocles species (L. tessellatus) classified as a girdler (2 behavioral states across Onciderini species). </div> <div> </div> <div><strong>ProcessedData (folder): </strong>filtered data and pruned trees outputted by the OncidHeadDimorphism-DatasetPREP-FINAL.R script</div> <div>- oncid_f_36spp_clean.csv: dataset of species means and log-ratios for morphometric traits in females, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_m_42spp_clean.csv: dataset of species means and log-ratios for morphometric traits in males, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_sd_35spp_clean.csv: dataset of species means for sexual dimorphism in morphometric traits, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_girdlingbehav_allingroupspp_clean.csv: full dataset of girdling behavior for 56 Onciderini species that are in the phylogenetic tree; includes separate columns for the three alternative girdling classification schemes</div> <div>- oncid_tree_behavfull_56spp.nwk: pruned phylogenetic tree for the full girdling dataset (56 species)</div> <div>- oncid_tree_f_36spp.nwk: pruned phylogenetic tree for the female morphometric dataset (36 species)</div> <div>- oncid_tree_m_42spp.nwk: pruned phylogenetic tree for the male morphometric dataset (42 species)</div> <div>- oncid_tree_mf_43spp.nwk: pruned phylogenetic tree for all species with morphometric data for males or females; used for the stochastic character map next to the heatmap plot (Fig 4)</div> <div>- oncid_tree_sd_35spp.nwk: pruned phylogenetic tree for the sexual dimorphism dataset (35 species)</div> <div> </div> <div><strong>FittedModels (folder): </strong>fitted models (mvgls, model comparison analyses, OUM models, simmaps) outputted by the OncidHeadDimorphism-Analysis-FINAL.R script </div> <div>- MacroModelFits_logRtraits_f_36spp-2024-10-12.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to female morphometric data across 100 stochastic character maps of girdling behavior</div> <div>- MacroModelFits_logRtraits_m_42spp-2024-10-12.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to male morphometric data across 100 stochastic character maps of girdling behavior</div> <div>- MacroModelFits-SDDI-35spp_2024-10-11.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to sexual dimorphism data across 100 stochastic character maps of girdling behavior</div> <div>- mvgls-results-headsize-mf-2024-10-12.Rdata: fitted mvgls regression models for male and female traits (analyzed separately)</div> <div>- mvgls-results-sddi-2024-10-12.Rdata: fitted mvgls regression models for sexual dimorphism</div> <div>- OUM_headtraits_f_36spp-2024-10-12.Rdata: fitted OUM models and summary statistics for female head traits</div> <div>- OUM_headtraits_m_42spp-2024-10-12.Rdata: fitted OUM models and summary statistics for male head traits</div> <div>- OUM-SDDI-35spp-2024-10-12.Rdata: fitted OUM models and summary statistics for sexual dimorphism in head traits</div> <div>- simmaps_ard_full_2state.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with two behavioral states (girdling or non-girdling) - all Lochmaeocles species are classified as girdlers</div> <div>- simmaps_ard_full_3state.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with three behavioral states (girdling, non-girdling, or facultative girdling)</div> <div>- simmaps_ard_full_1Loch.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with two behavioral states (girdling or non-girdling) - only one Lochmaeocles species (L. tessellatus) is classified as a girdler</div> <div>- simmaps_ard_m.RDS: stochastic character map for the 42 species used in the analyses of male morphometric traits</div> <div>- simmaps_ard_f.RDS: stochastic character map for the 36 species used in the analyses of female morphometric traits</div> <div>- simmaps_ard.RDS: stochastic character map for the 35 species used in the sexual dimorphism analyses; 2 behavioral states.</div> <div> </div> <div><strong>Rscripts (folder): </strong>R scripts used to process data and run phylogenetic comparative analyses of head size and girdling behavior.</div> <div>- OncidHeadDimorphism-DatasetPREP-FINAL.R: R script used to filter data and prune trees from the RawData folder for downstream phylogenetic comparative analyses; outputs of this script are in the ProcessedData folder.</div> <div>- OncidHeadDimorphism-Analysis-FINAL.R: R script used to analyze data in the ProcessedData folder to answer questions about the origin and evolution of girdling behavior and the relationship between girdling and head size or head size sexual dimorphism; fitted models outputted by this script are in the FittedModels folder</div> <div>- OncidHeadDimorphism-Plots-FINAL.R: R script used to generate plots for the manuscript<br><br></div>
Enhanced isohydric behavior decoupled the whole-tree sap flux response to leaf transpiration under nitrogen addition in a subtropical forest
<p><span>Anthropogenic nitrogen deposition has the potential to change the leaf water-use strategy in the subtropical region of China. Nevertheless, the whole-tree level response crucial for ecosystem functions has not been well addressed over the past decades. In this study, the stem sap flux density (J<sub>S</sub>) was monitored for the whole-tree water transport capacity in two dominant species (<em>Schima</em> <em>superba</em> and <em>Castanopsis</em> <em>chinensis</em>) in a subtropical forest. To simulate the increased nitrogen deposition, the NH<sub>4</sub>NO<sub>3</sub> solutions were sprayed onto the forest canopy at 25 kg </span><span>ha<sup>-1</sup> year<sup>-1</sup></span><span> (CAN25) and 50 kg ha<sup>-1</sup> year<sup>-1</sup> (CAN50), respectively, since April 2013. The </span><span>J<sub>S</sub></span><span> and microclimate (monitored since January 2014) derived from the whole-tree level </span><span>stomatal conductance </span><span>(G<sub>S</sub>) were used to quantify the stomatal behavior </span><span>(G<sub>S</sub> sensitive to</span><span> vapor pressure deficit</span><span>, G<sub>S-VPD</sub>)</span><span> in response to the added nitrogen. </span><span>The maximum shoot hydraulic conductance (Kshoot-max) was also measured for both species. After one year of monitoring</span><span> in January 2015, the </span><span>mid-day (J<sub>S-mid</sub>) and daily mean (J<sub>S-mean</sub>) sap flux rates did not change under all the nitrogen addition treatments (p > 0.05). A consistent</span><span> decline in the </span><span>G<sub>S-VPD</sub></span><span> indicated an enhanced isohydric behavior for both species. In addition, the G<sub>S-VPD</sub></span><span> in the wet season was much lower than that in the dry season. </span><span><em>S</em>. <em>superba</em> </span><span>had a lower </span><span>G<sub>S-VPD</sub></span><span> and decreased J<sub>S-mid</sub>/J<sub>S-mean</sub>, implying a stronger stomatal control under the fertilization, which might be attributed to the low efficient diffuse-porous conduits and a higher JS. In addition, the G<sub>S</sub> for </span><span><em>S</em>. <em>superba</em></span><span> decreased and the </span><span>G<sub>S-VPD</sub></span><span> increased more under CAN50 than that under CAN25, indicating that the high nitrogen dose restrains the extra nitrogen benefits. Our results indicate</span><span>d</span><span> that the J<sub>S</sub> for both species was decoupled from the leaf transpiration for both species due to an enhanced isohydric behavior, and a xylem anatomy difference and fertilization dose would affect the extent of this decoupling relation.</span></p>
Sap flow in Juglans mandshurica trees during the growing season 2015 (I)
<p>The primary data on the sap flow of Manchurian walnut (Juglans mandshurica) trees under the conditions of introduction are given. The walnut population is located on the territory of the Volga-Kama Reserve. Coordinates N55.883288, E48.730038. The measurements were carried out from May 31 to June 4 year 2015. Using EMS51A instruments (EMS, Brno, Czech Republic). The measurement interval is 5 minutes. The meteorological<br> observations.</p>
Data from: Contrasting sap flow characteristics between pioneer and late-successional tree species in secondary tropical montane forests of Eastern Himalaya, India
Abstract The interactive role of life-history traits and environmental forcing on plant-water relations is crucial for understanding species response to climate change but remains poorly understood in secondary tropical montane forests (TMFs). Comparing contrasting life-history traits (pioneer vs late-successional species) in a biodiverse Eastern Himalayan secondary TMF, we investigated sap flow responses in co-occurring pioneer species, Symplocos racemosa (n=5) and Eurya acuminata (n=5), and late-successional species, Castanopsis hystrix (n=3), using modified Granier's Thermal Dissipation probes. The fast-growing pioneers S. racemosa and E. acuminata) had 2.1- and 1.6-times higher sap flux density than the late-successional C. hystrix, respectively, and exhibited characteristics of long-lived pioneer species. Significant radial and azimuthal variability in sap flow (V) between species was observed and attributed to life history traits and the canopy's access to sunlight. Nocturnal V (1800-0500 hr) was 13.8 % of daily V and is attributed to stem recharge for evening V (1800-2300 hr) and to endogenous stomatal controls for pre-dawn V (0000-0500 hr). Both the shallow-rooted pioneer species exhibited midday depression in V attributed to photosensitivity and diel moisture stress response. In contrast, deep-rooted C. hystrix transpired unaffected across the dry season likely accessing groundwater. Thus, the secondary broadleaved TMFs, with the dominance of shallow-rooted pioneers, are more prone to the negative impacts of drier and warmer winters than primary forests, which are dominated by deep-rooted species. The study provides an empirical understanding of life-history traits and microclimate modulating plant-water use in widely distributed secondary TMFs in Eastern Himalaya and highlights their vulnerability against warmer winters and reduced snowfall due to climate change.
USS Virginia Closed-Loop Versus SAP Therapy for Hypoglycemia Reduction in T1D
ClinicalTrials.gov study NCT02302963. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Chromosome-level genome of the melon thrips yields insights into evolution of a sap-sucking lifestyle and pesticide resistance
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Data from: Contrasting sap flow characteristics between pioneer and late-successional tree species in secondary tropical montane forests of Eastern Himalaya, India
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Quantification of uncertainties introduced by data-processing procedures of sap flow measurements using the cut-tree method on a large mature tree
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Bridging the flux gap: sap flow measurements reveal species-specific patterns of water-use in a tallgrass prairie
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Enhanced isohydric behavior decoupled the whole-tree sap flux response to leaf transpiration under nitrogen addition in a subtropical forest
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Data from: Anatomy of an agricultural antagonist: Feeding complex structure and function of three xylem sap-feeding insects illuminated with synchrotron-based 3D imaging
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Data from: Single, but not dual, attack by a biotrophic pathogen and sap-sucking insect affects the oak leaf metabolome
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SAPFLUXNET: A global database of sap flow measurements
<p><strong>General description</strong></p> <p>SAPFLUXNET contains a global database of sap flow and environmental data, together with metadata at different levels.<br> SAPFLUXNET is a harmonised database, compiled from contributions from researchers worldwide. </p> <p>The SAPFLUXNET version 0.1.5 database harbours 202 globally distributed datasets, from 121 geographical locations. SAPFLUXNET contains sap flow data for 2714 individual plants (1584 angiosperms and 1130 gymnosperms), belonging to 174 species (141 angiosperms and 33 gymnosperms), 95 different genera and 45 different families. More information on the database coverage can be found here: <a href="http://sapfluxnet.creaf.cat/shiny/sfn_progress_dashboard/">http://sapfluxnet.creaf.cat/shiny/sfn_progress_dashboard/</a>. </p> <p><br> The SAPFLUXNET project has been developed by researchers at CREAF and other institutions (<a href="http://sapfluxnet.creaf.cat/team/">http://sapfluxnet.creaf.cat/#team</a>), coordinated by Rafael Poyatos (CREAF, <a href="http://www.creaf.cat/staff/rafael-poyatos-lopez">http://www.creaf.cat/staff/rafael-poyatos-lopez</a>), and funded by two Spanish Young Researcher's Grants (SAPFLUXNET, CGL2014-55883-JIN; DATAFORUSE, RTI2018-095297-J-I00 ) and an Alexander von Humboldt Research Fellowship for Experienced Researchers).</p> <p><strong>Changelog </strong></p> <p>Compared to version 0.1.4, this version includes some changes in the metadata, but all time series data (sap flow, environmental) remain the same. </p> <ul> <li>For all datasets, climate metadata (temperature and precipitation, ‘si_mat’ and ‘si_map’) have been extracted from CHELSA (https://chelsa-climate.org/), replacing the previous climate data obtained with Wordclim. This change has modified the biome classification of the datasets in ‘si_biome’.</li> <li>In ‘species’ metadata, the percentage of basal area with sap flow measurements for each species (‘sp_basal_area_perc’) is now assigned a value of 0 if species are in the understorey. This affects two datasets: AUS_MAR_UBD and AUS_MAR_UBW, where, previously, the sum of species basal area percentages could add up to more than 100%.</li> <li>In ‘species’ metadata, the percentage of basal area with sap flow measurements for each species (‘sp_basal_area_perc’) has been corrected for datasets USA_SIL_OAK_POS, USA_SIL_OAK_1PR, USA_SIL_OAK_2PR.</li> <li>In ‘site’ metadata, the vegetation type (‘si_igbp’) has been changed to SAV for datasets CHN_ARG_GWD and CHN_ARG_GWS.</li> </ul> <p><strong>Variables and units</strong></p> <p>SAPFLUXNET contains whole-plant sap flow and environmental variables at sub-daily temporal resolution. Both sap flow and environmental time series have accompanying flags in a data frame, one for sap flow and another for environmental<br> variables. These flags store quality issues detected during the quality control process and can be used to add further quality flags. </p> <p>Metadata contain relevant variables informing about site conditions, stand characteristics, tree and species attributes, sap flow methodology and details on environmental measurements. The description and units of all data and metadata variables can be found here: <a href="http://sapfluxnet.creaf.cat/sapfluxnetr/articles/metadata-and-data-units.html">Metadata and data units</a>.</p> <p>To learn more about variables, units and data flags please use the functionalities implemented in the sapfluxnetr package (<a href="https://github.com/sapfluxnet/sapfluxnetr">https://github.com/sapfluxnet/sapfluxnetr</a>). In particular, have a look at the package vignettes using R:</p> <pre><code># remotes::install_github( # 'sapfluxnet/sapfluxnetr', # build_opts = c("--no-resave-data", "--no-manual", "--build-vignettes") # ) library(sapfluxnetr) # to list all vignettes vignette(package='sapfluxnetr') # variables and units vignette('metadata-and-data-units', package='sapfluxnetr') # data flags vignette('data-flags', package='sapfluxnetr')</code></pre> <p><strong>Data formats</strong></p> <p>SAPFLUXNET data can be found in two formats: 1) RData files belonging to the custom-built 'sfn_data' class and 2) Text files in .csv format. We recommend using the sfn_data objects together with the sapfluxnetr package, although we also provide the text files for convenience. For each dataset, text files are structured in the same way as the slots of sfn_data objects; if working with text files, we recommend that you check the data structure of 'sfn_data' objects in the <a href="http://sapfluxnet.creaf.cat/sapfluxnetr/articles/sfn-data-classes.html">corresponding vignette</a>.</p> <p><strong>Working with sfn_data files</strong></p> <p>To work with SAPFLUXNET data, first they have to be downloaded from Zenodo, maintaining the folder structure. A first level in the folder hierarchy corresponds to file format, either RData files or csv's. A second level corresponds to how sap flow is expressed: per plant, per sapwood area or per leaf area. Please note that interconversions among the magnitudes have been performed whenever possible. Below this level, data have been organised per dataset. In the case of RData files, each dataset is contained in a sfn_data object, which stores all data and metadata in different slots (see the vignette 'sfn-data-classes'). In the case of csv files, each dataset has 9 individual files, corresponding to metadata (5), sap flow and environmental data (2) and their corresponding data flags (2).</p> <p>After downloading the entire database, the sapfluxnetr package can be used to:<br> - Work with data from a single site: data access, plotting and time aggregation.<br> - Select the subset datasets to work with.<br> - Work with data from multiple sites: data access, plotting and time aggregation.</p> <p>Please check the following package vignettes to learn more about how to work with sfn_data files:</p> <p><a href="http://sapfluxnet.creaf.cat/sapfluxnetr/articles/sapfluxnetr-quick-guide.html">Quick guide</a></p> <p><a href="http://sapfluxnet.creaf.cat/sapfluxnetr/articles/metadata-and-data-units.html">Metadata and data units</a></p> <p><a href="http://sapfluxnet.creaf.cat/sapfluxnetr/articles/sfn-data-classes.html">sfn_data classes</a></p> <p><a href="http://sapfluxnet.creaf.cat/sapfluxnetr/articles/custom-aggregation.html">Custom aggregation</a></p> <p><a href="http://sapfluxnet.creaf.cat/sapfluxnetr/articles/memory-and-parallelization.html">Memory and parallelization</a></p> <p><strong>Working with text files</strong></p> <p>We recommend to work with sfn_data objects using R and the sapfluxnetr package and we do not currently provide code to work with text files. </p> <p><strong>Data issues and reporting</strong></p> <p>Please report any issue you may find in the database by sending us an email: sapfluxnet@creaf.uab.cat.</p> <p>Temporary data fixes, detected but not yet included in released versions will be published in SAPFLUXNET main web page ('Known data errors').</p> <p><strong>Data access, use and citation</strong></p> <p>This version of the SAPFLUXNET database is open access and corresponds to the data paper submitted to Earth System Science Data in August 2020.</p> <p>When using SAPFLUXNET data in an academic work, please cite the data paper, when available, or alternatively, the Zenodo dataset (see the ‘Cite as’ section on the right panels of this web page).</p>
FIGURES 13–23 in New species in the sap beetle genus Soronia Erichson (Coleoptera: Nitidulidae Nitidulinae) from China
FIGURES 13–23. Soronia expansa sp. nov. (13) tegmen, ventral, (14) median lobe, dorsal; Soronia xiangxiyuanica sp. nov. (15) tegmen, ventral, (16) median lobe, dorsal; Soronia grisea (17) tegmen, ventral, (18) median lobe, dorsal; Soronia magnipunctura sp. nov. (19) tegmen, ventral, (20) median lobe, dorsal; Soronia gratiosa (21) tegmen, ventral, (22) median lobe, dorsal; Soronia expansa sp. nov. (23) ovipositor, dorsal.
FIGURES 7–12 in New species in the sap beetle genus Soronia Erichson (Coleoptera: Nitidulidae Nitidulinae) from China
FIGURES 7–12. Soronia xiangxiyuanica sp. nov. (7) male habitus, dorsal, (8) male habitus, ventral; Soronia gratiosa (9) male habitus, dorsal, (10) male habitus, ventral; Soronia grisea (11) male habitus, dorsal, (12) male habitus, ventral.
FIGURES 24–30 in New species in the sap beetle genus Soronia Erichson (Coleoptera: Nitidulidae Nitidulinae) from China
FIGURES 24–30. Soronia expansa sp. nov. (24) male, right antenna, dorsal, (27) male, right protibia, dorsal, (28) female, right protibia, dorsal; Soronia magnipunctura sp. nov. (25) male, right antenna, dorsal, (29) male, right protibia, dorsal; Soronia xiangxiyuanica sp. nov. (26) male, right antenna, dorsal, (30) male, right protibia, dorsal.
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