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22,597 results for “Regulation”
Plasmodesmata Act as Unconventional Membrane Contact Sites Regulating Inter-Cellular Molecular Exchange in Plants.
<p>This table contains peaks aera values from LC-MS for lipidomic quantification of PIP and PIP2. These data were used for Pérez-Sancho, Jessica and Smokvarska, Marija and Glavier, Marie and Sritharan, Sujith and Dubois, Gwennogan and Dietrich, Victor and Platre, Matthieu and Li, Ziqiang Patrick and Paterlini, Andrea and Moreau, Hortense and Fouillen, Laetitia and Grison, Magali S. and Cana-Quijada, Pepe and Moraes, Tatiana Sousa and Immel, Françoise and Wattelet, Valerie and Ducros, Mathieu and Brocard, Lysiane and Chambaud, Clément and Zabrady, Matej and Luo, Yongming and Busch, Wolfgang and Tilsner, Jens and Helariutta, Yrjö and Russinova, Jenny and Taly, Antoine and Jaillais, Yvon and Bayer, Emmanuelle, Plasmodesmata Act as Unconventional Membrane Contact Sites Regulating Inter-Cellular Molecular Exchange in Plants. </p>
TMEM206 contributes to cancer hallmark functions in colorectal cancer cells and is regulated by p53 in a p21-dependent manner
<p><span>Acid-induced ion flux plays a role in pathologies where tissue acidification is prevalent, including cancer. In 2019, TMEM206 was identified as the molecular component of acid-induced chloride flux. Localizing to the plasma membrane, TMEM206 contributes to cellular processes like acid-induced cell death. Since over 50% of human cancers carry loss of function mutations in the p53 gene, we aimed to analyze how TMEM206 is regulated by p53 and its role in cancer hallmark function and acid-induced cell death in HCT116 colorectal cancer (CRC) cells. We generated p53-deficient HCT116 cells and assessed TMEM206-mediated Cl<sup>-</sup> currents and transcriptional regulation using the patch-clamp and a dual-luciferase reporter assay, respectively. To investigate the contribution of TMEM206 to cancer hallmark functions we performed migration and metabolic activity assays. The role of TMEM206 in p53-mediated acid-induced cell death has been assessed with cell death assays. TMEM206 mRNA level is significantly elevated in human primary CRC tumors. TMEM206 knockout increased acid-induced cell death and reduced proliferation and migration, indicating a role for TMEM206 in these cancer hallmark functions. Furthermore, we observed increased TMEM206 mRNA levels and currents in HCT116 p53 knockout cells. This phenotype can be rescued by transient overexpression of p53, but not by overexpression of dysfunctional p53. In addition, our data suggests that TMEM206 may mediate cancer hallmark functions within p53-associated pathways. TMEM206 promoter activity is not altered by p53 overexpression. Conversely, knockout of p21, a major target gene of p53, increased TMEM206-mediated currents suggesting expression control of TMEM206 by p21 downstream signaling. Our results show that in colorectal cancer cells, TMEM206 expression is elevated, contributes to cancer hallmark functions and its regulation is dependent on p53 through a p21-dependent mechanism.</span></p>
Identification of Genes Regulating Dexamethasone Resistance and Prognostic Model Development in Acute Lymphoblastic Leukemia
<p>This study investigates the mechanisms of dexamethasone resistance in acute lymphoblastic leukemia (ALL) and presents a prognostic model to predict patient outcomes and immunotherapy responses. By analyzing gene expression data, we identified autophagy-related genes associated with dexamethasone resistance, particularly focusing on STK38L’s role in modulating autophagy via ULK1. Our results reveal that high STK38L expression enhances dexamethasone resistance by promoting autophagy markers LC3II/LC3I and beclin-1. This study provides valuable insights into the molecular basis of dexamethasone resistance and highlights STK38L as a potential biomarker and therapeutic target for improving ALL treatment strategies.</p>
Direct molecular evidence for an ancient, conserved developmental toolkit controlling post-transcriptional gene regulation in land plants
<p>In plants, miRNA production is orchestrated by a suite of proteins that control transcription of the pri-miRNA gene, post-transcriptional processing and nuclear export of the mature miRNA. Post-transcriptional processing of miRNAs is controlled by a pair of physically-interacting proteins, HYL1 and DCL1. However, the evolutionary history and structural basis of the HYL1-DCL1 interaction is unknown. Here we use ancestral sequence reconstruction and functional characterization of ancestral HYL1 <em>in vitro</em> and in <em>Arabidopsis thaliana </em>to better understand the origin and evolution of the HYL1-DCL1 interaction and its impact on miRNA production and plant development. We found the ancestral plant HYL1 evolved high affinity for both double-stranded RNA (dsRNA) and its DCL1 partner before the divergence of mosses from seed plants (~500 Ma), and these high-affinity interactions remained largely conserved throughout plant evolutionary history. Structural modeling and molecular binding experiments suggest that the second of two double-stranded RNA-binding motifs (DSRMs) in HYL1 may interact tightly with the first of two C-terminal DCL1 DSRMs to mediate the HYL1-DCL1 physical interaction necessary for efficient miRNA production. Transgenic expression of the nearly 200 Ma-old ancestral flowering-plant HYL1 in <em>A. thaliana</em> was sufficient to rescue many key aspects of plant development disrupted by HYL1<sup>-</sup> knockout and restored near-native miRNA production, suggesting that the functional partnership of HYL1-DCL1 originated very early in and was strongly conserved throughout the evolutionary history of terrestrial plants. Overall, our results are consistent with a model in which miRNA-based gene regulation evolved as part of a conserved plant ‘developmental toolkit’.</p>
Supplementary material for "Learning Boolean controls in regulated metabolic networks: a case-study"
<p>This record contains notebooks and Docker image for reproducing the learning of Boolean controls in regulated metabolic networks, and the case study presented in the CMSB 2021 conference proceeding article "Learning Boolean controls in regulated metabolic networks: a case-study".</p> <p>Visualize notebooks online:</p> <ul> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/5060985/files/CaseStudy-Simulations.ipynb">CaseStudy-Simulations.ipynb</a></li> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/5060985/files/CaseStudy-SearchSpace.ipynb">CaseStudy-SearchSpace.ipynb</a></li> <li><a href="https://nbviewer.jupyter.org/urls/zenodo.org/record/5060985/files/CaseStudy-Inference.ipynb">CaseStudy-Inference.ipynb</a></li> </ul> <p>Notebooks can be executed interactively within the Docker image <code>bioasp/boolean-caspo-flux:cmsb2021 </code>which extends the <a href="http://colomoto.org/notebook">CoLoMoTo Docker</a> version <code>2021-02-01.</code></p> <p>Alternatively, they can be executed without any installation at <a href="https://mybinder.org/v2/zenodo/10.5281/zenodo.5070151/">https://mybinder.org/v2/zenodo/10.5281/zenodo.5070151/</a>.</p> <p>The Docker image can be executed as follows:</p> <pre><code class="language-bash">docker pull bioasp/boolean-caspo-flux:cmsb2021 docker run -it --rm -p 8888:8888 bioasp/boolean-caspo-flux:cmsb2021 </code></pre> <p>then point your browser to <a href="http://127.0.0.1:8888">http://127.0.0.1:8888</a>.</p> <p>The image can be imported using the command <code>docker load</code> with the image file provided in this record:</p> <pre><code>docker load -i image.tar.gz</code></pre> <p>or with the <code>donodo</code> command available at <a href="https://github.com/pauleve/donodo">https://github.com/pauleve/donodo</a>:</p> <pre><code>pip install -U donodo donodo pull 10.5281/zenodo.5070151</code></pre>
Diel-regulated transcriptional cascades of microbial eukaryotes in the North Pacific Subtropical Gyre
<p>Trinity <em>de novo </em>assemblies of 24 poly-A+ selected, combined-replicate metatranscriptomes from HOE-Legacy 2 cruise KM1513 (Jul 24 - Aug 6, 2015). KM1513 cruise information, plots, and associated environmental data for the HOE Legacy II cruise can be found online at <a href="http://hahana.soest.hawaii.edu/hoelegacy/hoelegacy.html">http://hahana.soest.hawaii.edu/hoelegacy/hoelegacy.html</a>. Raw metatranscriptome short-read sequence data is available in the NCBI Sequence Read Archive under BioProject ID PRJNA492142. Code associated with this project is available on Github (<a href="https://github.com/armbrustlab/diel_eukaryotes">https://github.com/armbrustlab/diel_eukaryotes</a>).</p> <p> </p> <p> </p>
Evolution of the recombination regulator PRDM9 in minke whales
<p>This data repository contains data and protocols for the manuscript: Evolution of the recombination regulator PRDM9 in minke whales</p>
Riboswitch-inspired toehold riboregulators for gene regulation in Escherichia coli
<p>This dataset comprises flow cytometry data accompanying a publication on the development of synthetic riboregulators.</p> <p>These riboregulators were inspired by the architecture of naturally occurring riboswitches and toehold-mediated strand displacement. Specifically, we adopt the toehold switch hairpin and inserted regulatory sequences within the loop region of which accessibility can be controlled by toehold-mediated strand displacement. We utilized this design principle to develop toehold translation repressor and toehold transcriptional repressor, which regulate mCherry expression in <em>E. coli </em>in translational and transcriptional levels with certain ON/OFF ratios. Furthermore, we combined these two riboregulators and developed them into a NOR gate switch that can regulate downstream GFP expression in <em>E. coli </em>with different input conditions of trigger RNA. We used flow cytometry to quantify the expression level of the NOR gate switch under different inputs.</p>
Genetic and epigenetic regulation of zebrafish intestinal development
<p>This dataset contains zebrafish (<em>Danio rerio</em>) raw RNA and ChIP (paired-end) sequencing data:</p> <ul> <li>RNA-seq <ul> <li>lane1_BSwt5dpf*: 3 biological replicates of RNA-seq data from 5dpf wild-type (AB background) pooled intestines</li> <li>lane1_BSwt7dpf*: 3 biological replicates of RNA-seq data from 7dpf wild-type (AB background) pooled intestines</li> <li>lane1_BSwt9dpf*: 3 biological replicates of RNA-seq data from 9dpf wild-type (AB background) pooled intestines</li> </ul> </li> <li>ChIP-seq <ul> <li>Cldn-wt-int-5dpf-H3K27me3*: 2 biological replicates of H3K27me3 ChIP-seq data from 5dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-5dpf-H3K4me3*: 2 biological replicates of H3K4me3 ChIP-seq data from 5dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-5dpf-input-12727_R[12].fastq.gz: 1 sample of input ChIP-seq data from 5dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-7dpf-H3K27me3*: 2 biological replicates of H3K27me3 ChIP-seq data from 7dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-7dpf-H3K4me3*: 2 biological replicates of H3K4me3 ChIP-seq data from 7dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-7dpf-input-12727_R[12].fastq.gz: 1 sample of input ChIP-seq data from 7dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-9dpf-H3K27me3*: 2 biological replicates of H3K27me3 ChIP-seq data from 9dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-9dpf-H3K4me3*: 2 biological replicates of H3K4me3 ChIP-seq data from 9dpf wild-type (AB background) pooled intestines</li> <li>Cldn-wt-int-9dpf-input-12727_R[12].fastq.gz: 1 sample of input ChIP-seq data from 9dpf wild-type (AB background) pooled intestines</li> </ul> </li> </ul>
Chromatin activity identifies differential gene regulation across human ancestries
<p>This repository contains data related to:</p> <p>Chromatin activity identifies differential gene regulation across human ancestries</p> <p>Kade P. Pettie, Maxwell Mumbach, Amanda J. Lea, Julien Ayroles, Howard Y. Chang, Maya Kasowski, Hunter B. Fraser</p> <p> </p>
Belgian baseline distribution of invasive alien species of Union concern (Regulation (EU) 1143/2014)
<p><strong>Aims and scope</strong></p> <p>The European Alien Species Information Network team (EASIN, http://easin.jrc.ec.europa.eu) of the Joint Research Centre (JRC) requests the European member states to provide and verify the baseline distribution data of invasive alien species of Union Concern (Tsiamis et al. 2017) as provided by the EASIN mapping system (Katsanevakis et al. 2012). These are species with documented biodiversity impacts sensu the European Union Regulation on the prevention and management of the introduction and spread of Invasive Alien Species in Europe (IAS Regulation No 1143/2014) (European Union 2014). The purpose of this baseline is to set a representative geographic account of the distribution of these species at (i) country and (ii) 10km<sup>2</sup> grid level before the entry into force of the Regulation (and the listing of species through implementing regulations). This distribution provides the baseline for subsequent reporting by the member states as required by the IAS Regulation.</p> <p>The dataset provides a shapefile on the baseline distribution of the invasive species of EU concern in Belgium based on an aggregated dataset (<em>ias_belgium_t0_xxxx</em>). Data were compiled from various datasets holding invasive species observations such as data from research institutes and research projects (76%), citizen science observatories (23%) and a range of other sources (1%) such as governmental agencies, water managers, invasive species control companies, angling and hunting organizations etc. Data were normalized using a custom mapping of the original data files to Darwin Core (Wieczorek et al. 2012) where possible. Species names were mapped to the GBIF Backbone Taxonomy (GBIF 2016) using the species API (http://www.gbif.org/developer/species). Appropriate selection of records was performed based on predefined cut-off dates (see data range) and record content validation (see validation procedure). Data were then joined with GRID10k layer Belgium based on GRID10k cellcodes (ETRS_1989_LAEA).</p> <p><strong>File description</strong></p> <p>The dataset contains two types of data:</p> <ol> <li> <p>Shapefiles (<em>ias_belgium_t0_2016.zip, ias_belgium_t0_2018.zip, ias_belgium_t0_2020.zip and ias_belgium_t0_2023.zip</em>) providing the presence of the species of EU concern at 10km<sup>2</sup> (European Terrestrial Reference System projection - 1989 ETRS_1989_LAEA) level (resp. for 1st, 2nd, 3rd and 4th batch of species added to the Union List). The attributes table field “ACCEPTED” provides coded information on the distribution validation: correct squares (Y) represent data overlapping between the collated baseline data for Belgium and the EASIN maps. Incorrect data (N) can represent records mapped on wrong 10km2 squares, non-validated records or records that fall outside of the date range applied. New squares (New) represent previously unpublished data that were absent from EASIN. The work was supervised and validated by the Belgian national scientific council on invasive alien species, an official consultative structure coordinating scientific input and data aggregation between Belgian regions and institutions with regards to technical implementation of the Regulation No 1143/2014 on invasive alien species.</p> </li> <li> <p>A geojson version of the same shapefiles (<em>ias_belgium_t0_2016.geojson, ias_belgium_t0_2018.geojson, ias_belgium_t0_2020.geojson, ias_belgium_t0_2023.geojson</em>), in WGS84 projection.</p> </li> </ol> <p><strong>Date range</strong></p> <p>The baseline distribution reflects the current status and situation of the IAS of Union concern in Belgium at 10km<sup>2</sup> grid level. Historical records were not taken into consideration for the baseline. The choice of cut-off date was based on an analysis of the relative contribution of a year in defining the total distribution of the species at 1km<sup>2</sup> grid level (calculated as [the sum of unique UTM 1km<sup>2</sup> grid squares year-1/total number of unique UTM 1km<sup>2</sup> grid squares for that species]) based on the complete dataset. </p> <p>The dataset comprises observations of Union List invasive species <strong>from 2000 <em>until the entry into force </em>for every species</strong>, hence between January 2000 (2000-01-01) and February 2016 (2016-01-31) for the species of the first batch (<em>ias_belgium_t0_2016.zip</em>), between January 2000 (2000-01-01) and August 2017 (2017-08-31) for the species of the first update of the Union List (<em>ias_belgium_t0_2018.zip</em>), between January 2000 (2000-01-01) and August 2019 (2019-08-31) for the species of the second update of the Union List (<em>ias_belgium_t0_2020.zip</em>), between January 2000 (2000-01-01) and August 2022 (2022-08-2) for the species of the third update (<em>ias_belgium_t0_2023.zip</em>). For raccoon dog (<em>Nyctereutes procyonoides), </em>included in the second update (<em>ias_belgium_t0_2020.zip</em>) the date cut-off is 01/01/2000 to 31/01/2019. Note that <em>Pistia stratiotes</em>, <em>Xenopus laevis </em>and <em>Fundulus heteroclitus </em>enter into force only as from 2 August 2024, <em>Celastrus orbiculatus </em>on 2 August 2027 because of prolonged transitionary measures. However, these species are already included in the baseline now with a cut-off date set on August 2022. The data include both casual records as well as established populations and also comprise data from eradicated populations for the period 2000-2022.</p> <p><strong>Validation procedure</strong></p> <p>Record validation was performed to exclude dubious records, wrong identifications etc. This was done based on the IdentificationVerificationStatus field (to which validation information from original data were mapped) if available. In general, non-validated data were not considered for ias_belgium_t0_xxxx. Data were validated in the original datasets based on evidence (e.g. pictures), on the observer’s experience, or based on a set of predefined rules (e.g. automated validation based on geographic filtering). Data from research institutes were generally considered validated. A few casual records of EU list species that were clearly planted were discarded manually. When the original dataset did not mention any validation status, records were not considered validated and therefore not taken into account for ias_belgium_t0_xxxx, unless for Chinese mitten crab <em>Eriocheir sinensis</em>, ruddy duck <em>Oxyura jamaicensis</em>, raccoon <em>Procyon lotor</em>, Siberian ground squirrel <em>Tamias sibiricus</em>, sacred ibis <em>Threskiornis aethiopicus</em>, and red-eared slider <em>Trachemys spp</em>. For these species, we assumed all records were correct as they originate from dedicated sampling (<em>E. sinensis</em>) within research projects or represent species that are readily recognizable by people in the field. Likewise, for the second batch species, all records of Egyptian goose <em>Alopochen aegyptiaca, </em>Himalayan balsam <em>Impatiens glandulifera</em>, giant hogweed <em>Heracleum mantegazzianum </em>and muskrat <em>Ondatra zibethicus</em> (mostly derived from public eradication services) were considered validated and taken into account. For the third batch species, records of the widespread tree of heaven <em>Ailanthus altissima </em>and pumpkinseed <em>Lepomis gibbosus </em>were also considered validated. For species with less than 10 records (<em>Salvinia molesta</em>, <em>Acridotheres tristis</em>), every record was manually checked.</p> <p>A visual check was performed on the resulting distribution maps by representatives of the Belgian scientific council on IAS and the Belgian Comittee on IAS, two official bodies created in response to the EU Regulation within the framework of a cooperation agreement between the Belgian regions and the Federal Authority. Data in the distribution maps provided by EASIN but not present in ias_belgium_t0_xxxx were carefully checked and kept/rejected accordingly.</p> <p><strong>Data providers</strong></p> <p>The providers of the invasive species data for this exercise (individuals and their respective organizations) are listed in the "data providers" section of the dataset metadata. Much of the primary occurrence data that formed the basis for this aggregated dataset will be published as open data on the Global Biodiversity Information Facility (GBIF) within the framework of the <strong>Tracking Invasive Alien Species project (TrIAS, https://osf.io/7dpgr/, 2017-2020)</strong>.</p>
Binding site plasticity regulation of the FimH catch-bond mechanism: Molecular Dynamics dataset
<p>Dataset of Molecular Dynamics simulations and analysis scripts used in the article "Binding site plasticity regulation of the FimH catch-bond mechanism" [<a href="https://doi.org/10.1016/j.bpj.2023.05.029">paper</a>][<a href="https://doi.org/10.1101/2022.11.15.516604">bioRxiv</a>].</p> <p>Contains:</p> <ul> <li>Replica Exchange with Solute Scaling (REST2) simulations of the FimH protein lectin domain in its two main allosteric states (Associated and Separated), in presence and absence of its synthetic ligand heptyl α-ᴅ-mannose (input files and trajectories of the unscaled replicas)</li> <li>Replica Exchange Umbrella Sampling (REUS) simulations of the liganted systems along a collective variable (CV) describing binding site opening (input files and trajectories)</li> <li>REUS simulations in presence of a pulling force on the protein-ligand complex.</li> </ul> <p>See the article for more details.</p>
Data for "Detection of large-scale cloud microphysical changes within a major shipping corridor after implementation of the IMO 2020 fuel sulfur regulations"
<p>Processed data used for the manuscript "Detection of large-scale cloud microphysical changes within a major shipping corridor after implementation of the IMO 2020 fuel sulfur regulations".</p> <p>Includes input data for kriging algorithm as "SSF1deg_shipkrige_Terra.nc" and output data files as "Data_Terra_[VAR]_[YEAR]_C_M[MONTH].nc" for [VAR] Acld (overcast albedo) or cer (cloud droplet effective radius), [YEAR] the starting year of a three-year period starting with 2002 and ending at 2020 or "clim" for the 2002-2019 climatology, and [MONTH] 1to12 (annual mean) or 9to11 (austral spring).</p> <p>For the output data, "Obs" is the original data, "Est" is the mean counterfactual field obtained via kriging, "lowEst" and "highEst" are the 2.5th and 97.5th percentiles of the kriged fields for each grid box, "krSims" stores the results of the 5,000 simulated kriged fields, "Semivariance" is the binned empirical variogram values, "pVal" is the raw field significance (not adjusted for multiple testing), "nOut" is the number of individually significant grid boxes, "tran" is the transform applied (none for cer, logit for Acld), "iniPhi" and "iniSigma2" are the initial values for the fitted variogram, "Phi" and "Sigma2" are the fitted values using weighted least squares, and "parSel" is the list of selected regressors for the mean function that minimize the Bayesian information criterion.</p>
Regulation of mature mRNA levels by RNA processing efficiency
<p>Data from the research paper "Regulation of mature mRNA levels by RNA processing efficiency" by Henfrey, C., Murphy, S., and Tellier, M.:</p> <p>-Highest expressed transcript annotation for protein-coding genes, gencode v38.</p> <p>-15 txt (BED) files for chromatin vs nucleoplasm enrichment gene sets: HeLa full gene sets, canonical protein only sets, chromatin RNA seq subsamples, mNET seq subsamples, Raji gene sets.</p> <p>-Proteomics data table</p> <p>-mRNA half-life table</p> <p>-Splicing efficiency for POINT-seq, ChrRNA-seq, NucRNA-seq table</p> <p>-Ser2-P mNET-seq readthrough index data table</p> <p>-Splicing efficiency for siLuc/siEX3 table (ChrRNA-seq, NucRNA-seq)</p> <p>-RMATs output tables for alternative splicing results (siEX3 vs siLuc)</p> <p>-Tables for TSS:TES quantifications (mNET-seq(CTD) vs log2FoldChange, chr/nuc/mnet siEX3 vs siLuc)</p>
Analysis accompanying "Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the Drosophila larval brain"
<p>This repository documents the raw data processing and figure generation for the article “Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the <em>Drosophila </em>larval brain”, doi: 10.1261/rna.079552.122.</p>
The global water resources and use model WaterGAP v2.2e: location and attributes of reservoirs and regulated lakes
<p>This dataset contain the location and attributes of the reservoirs and regulated lakes in WaterGAP v2.2e. This dataset is provided to be transparent how the reservoirs are included in this WaterGAP version and e.g. to check deviations from the locations as provided by ISIMIP (www.isimip.org).</p> <p>Please see the readme.md for furhter details and please consider the license terms from the data sources listed in the readme.md.</p>
D6.1- Fertilizers-PCFs-Contaminants-Regulation (EU) 2019/1009 _some EU Member states regulations
<p>The annex of deliverable D6.1 is a summary of the fertiliser contamination limits in each of the countries participating in the WalNUT project according to the national legislation of each country.</p>
Distribution of invasive alien species of Union concern (Regulation (EU) 1143/2014) in Belgium for the reporting period 2015-2018
<p><strong>Aims and scope</strong></p> <p>Member State authorities are required to report on the distribution in their territory of each of the invasive alien species (IAS) of Union concern. These are species with documented biodiversity impacts sensu the European Union Regulation on the prevention and management of the introduction and spread of Invasive Alien Species in Europe (IAS Regulation No 1143/2014) (European Union 2014). This distribution represents the official reporting under Article 24(1) of R.1143/2014 on invasive alien species for the period 2015–2018. Baseline distribution of these species has previously been reported and published (Adriaens et al. 2018, ).</p> <p>Data were compiled from various datasets holding invasive species observations such as data from research institutes and research projects (9%), citizen science observatories (68%) and a range of other sources (23%) such as governmental agencies, water managers etc. More specifically the dataset includes:</p> <ul> <li>The citizen science recording portals www.waarnemingen.be and www.observation.be which has a specific alert system for IAS where nature volunteers can report their observations (Adriaens et al. 2018);</li> <li>Data from the Research Institute for Nature and Forest (INBO), the Flemish government institute that coordinates N2000, WFD and BIrd Directive and IAS monitoring in the terrestrial, estuarine and freshwater environment;</li> <li>Data from the Flemish Environment Agency which performs management of muskrat and invasive water plants in Flanders, gathered with a dedicated smartphone app since 2015;</li> <li>Data from the Flemish provinces and Rato vzw that manage water plants, muskrat, giant hogweed etc.;</li> <li>Some smaller datasets from cities;</li> <li>Data from the Brussels Capital Region from the Brussels Environment data portal;</li> <li>Plant inventories of the ‘contrats de rivière’ along watercourses in Wallonia, making use of a dedicated application to collect data directly from the field (fulcrum);</li> <li>The government reporting portals for IAS of the ‘Observatoire wallon de la flore, de la faune et des habitats (Service Public de Wallonie)’;</li> <li>Some validated data from specific datasets on gbif (iNaturalist, Natusfera, Naturgucker).</li> </ul> <p>Data were normalized using a custom mapping of the original data files to Darwin Core (Wieczorek et al. 2012) where possible. Species names were mapped to the GBIF Backbone Taxonomy (GBIF 2016) using the species API (http://www.gbif.org/developer/species). The mapping was assisted by dedicated software (SMARTIE) which was specifically written for the purpose of aggregating IAS data from various sources. Appropriate selection of records was performed based on the cut-off dates (see data range) and record content validation (see validation procedure). Data were then joined with GRID10k layer Belgium based on GRID10k cellcodes (ETRS_1989_LAEA). The technical format is in line with the <a href="http://cdr.eionet.europa.eu/help/ias_regulation/material/IAS-species-distribution-user-manual">guidelines</a> provided to the member states for the compilation of reports on Species Distribution (SD) of Invasive Alien Species of Union concern.</p> <p><strong>File description</strong></p> <p>The dataset contains a shapefiles (<em>T1_Belgium_Union_List_Species.shp</em>) with the distribution of the species of Union Concern at 10km<sup>2</sup> (European Terrestrial Reference System projection - 1989 ETRS_1989_LAEA) level. The attributes table contains <em>Cellcode </em>(ETRS<sup> </sup>grid cell code) and <em>Species </em>(scientific name + authority).</p> <p><strong>Date range</strong></p> <p>The data reflects the distribution of the IAS of Union concern in Belgium in the first reporting period for the EU Regulation hence comprises observations of Union List invasive species between January 2015 (2015-01-01) and December 2018 (2018-12-31). </p> <p><strong>Validation procedure</strong></p> <p>Record validation was performed to exclude dubious records, wrong identifications etc. This was done based on the IdentificationVerificationStatus field (to which validation information from original data were mapped) if available. In general, non-validated data were not considered. Data were validated in the original datasets based on evidence (e.g. pictures), on the observer’s experience, or based on a set of predefined rules (e.g. automated validation based on geographic filtering). Data from research institutes were generally considered validated. A few casual records of EU list species that were clearly planted were discarded manually. When the original dataset did not mention any validation status, records were not considered validated and therefore not taken into account unless for Chinese mitten crab <em>Eriocheir sinensis</em>, ruddy duck <em>Oxyura jamaicensis</em>, raccoon <em>Procyon lotor</em>, Siberian ground squirrel <em>Tamias sibiricus</em>, sacred ibis <em>Threskiornis aethiopicus</em>, Egyptian goose <em>Alopochen aegyptiaca, </em>Himalayan balsam <em>Impatiens glandulifera</em>, giant hogweed <em>Heracleum mantegazzianum, </em>muskrat <em>Ondatra zibethicus </em>and red-eared slider <em>Trachemys spp</em>. For these species, it was assumed all records were correct as they originate from dedicated sampling (<em>E. sinensis</em>) within research projects, were gathered by public bodies (e.g. muskrat), or represent species that are readily recognizable by people in the field. Data provided by EASIN in the care package and GBIF data were carefully checked.</p> <p>A visual check was performed on the resulting distribution maps by representatives of the Belgian national scientific council on invasive alien species, an official consultative structure coordinating scientific input and data aggregation between Belgian regions and institutions with regards to technical implementation of the Regulation No 1143/2014 on invasive alien species.</p> <p><strong>Data providers</strong></p> <p>The providers of the invasive species data for this exercise (individuals and their respective organizations) are listed in the "data providers" section of the dataset metadata. Much of the primary occurrence data that formed the basis for this aggregated dataset will be published as open data on the Global Biodiversity Information Facility (GBIF).</p>
Carbon quality regulates the temperature dependence of aquatic ecosystem respiration
Lakes are undergoing a variety of changes that may alter their role in the global carbon cycle. Lake temperatures are increasing at the same time that lakes in many regions are experiencing long-term increases in dissolved organic carbon (DOC) concentrations. The balance between rates of ecosystem respiration (ER) and gross primary production (GPP) is an important determinant of CO2 outgassing from lakes and thus it is important to understand factors regulating ER rates in these systems. Temperature is known to regulate rates of ER, but other factors have the potential to modulate this relationship. One such regulator may be the quality of the dissolved organic matter (DOM) in the system. Theory suggests that ER may increase more with temperature in lakes dominated by allochthonous, refractory material than in systems dominated by more autochthonous DOM. To test this theory, we conducted a mesocosm study where half of the mesocosms received water from a naturally occurring autochthonous DOM source and the other half from an allochthonous DOM source. We monitored water temperature and dissolved oxygen concentrations in each mesocosm using in-situ high frequency DO sensors. After 27 days we used this data to calculate daily ER for each mesocosm. We then related daily ER to mean nighttime temperature and tested whether the relationship was different in the two DOM treatments. Treatments dominated by allochthonous DOM had a greater temperature dependence of respiration than those dominated by autochthonous DOM. These results suggest that as lake temperatures continue to increase, ER will increase more in lakes dominated by allochthonous DOM than those dominated by autochthonous DOM.
Emotion regulation in the Ageing Brain, University of Reading, BBSRC
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