cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1403072
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJmL maize

description: This is model output from LPJmL for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set. The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019). References: Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015 Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017 Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403077
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJmL groundnut

description: This is model output from LPJmL for groundnut as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set. The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019). References: Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015 Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017 Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403083
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJmL field pea

description: This is model output from LPJmL for field pea as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set. The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019). References: Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015 Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017 Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403085
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJmL cassava

description: This is model output from LPJmL for cassava as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set. The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019). References: Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015 Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017 Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403082
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJmL field pea

description: This is model output from LPJmL for field pea as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set. The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019). References: Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015 Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017 Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403084
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJmL cassava

description: This is model output from LPJmL for cassava as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set. The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019). References: Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015 Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017 Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403012
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJmL wheat

description: This is model output from LPJmL for wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set. The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019). References: Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015 Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017 Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.6826512
title: Eocene-Oligocene Southwest Pacific Ocean paleoceanography: New insights from foraminifera chemistry (DSDP Site 277, Campbell Plateau)

description: Supplementary material for Eocene-Oligocene Southwest Pacific Ocean paleoceanography: New insights from foraminifera chemistry (DSDP Site 277, Campbell Plateau) by Hodel et al. 1 - Geochemical data 2 - Age model for Site 277
DOI: 10.5281/zenodo.6826511
title: Eocene-Oligocene Southwest Pacific Ocean paleoceanography: New insights from foraminifera chemistry (DSDP Site 277, Campbell Plateau)

description: Supplementary material for Eocene-Oligocene Southwest Pacific Ocean paleoceanography: New insights from foraminifera chemistry (DSDP Site 277, Campbell Plateau) by Hodel et al. 1 - Geochemical data 2 - Age model for Site 277
DOI: 10.5281/zenodo.3688439
title: Reference Windfarm database PDk 0

description: Dataset for TotalControl reference windfarm database simulation of a pressure-driven high Reynolds number boundary layer flow with 0 degree inflow wind direction angle (Casename PDk 0) Included Python files for loading and visualizing the data. Use the plot_*.py files. Further information, including description of the case and dataset can be found in the deliverable report at: https://cordis.europa.eu/project/id/727680/results "Database for reference wind farms part 2: windfarm simulations"
DOI: 10.21227/zvvw-at47
title: Semantic network as a means of ensuring data quality - the Bridge of Knowledge platform example

description: Our poster is essential for understanding the process of creating a community of practice in the context of Open Science. Building such a community and at the same time being part of the culture change that offers openness in science is challenging. No single researcher or librarian would be able to achieve those results alone. Gdańsk Tech Library’s strategy to popularise and practice Open Science requires many actions supported by a team of people with different competencies
DOI: 10.5517/ccdc.csd.cc25ms3q
title: CCDC 2015003: Experimental Crystal Structure Determination

description: Related Article: Rahul Dev Jana, Biswarup Chakraborty, Sayantan Paria, Takehiro Ohta, Reena Singh, Sourav Mandal, Satadal Paul, Shinobu Itoh, Tapan Kanti Paine|2022|Inorg.Chem.|61|10461|doi:10.1021/acs.inorgchem.2c01308
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25ms4r
title: CCDC 2015004: Experimental Crystal Structure Determination

description: Related Article: Rahul Dev Jana, Biswarup Chakraborty, Sayantan Paria, Takehiro Ohta, Reena Singh, Sourav Mandal, Satadal Paul, Shinobu Itoh, Tapan Kanti Paine|2022|Inorg.Chem.|61|10461|doi:10.1021/acs.inorgchem.2c01308
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25msl6
title: CCDC 2015018: Experimental Crystal Structure Determination

description: Related Article: Rahul Dev Jana, Biswarup Chakraborty, Sayantan Paria, Takehiro Ohta, Reena Singh, Sourav Mandal, Satadal Paul, Shinobu Itoh, Tapan Kanti Paine|2022|Inorg.Chem.|61|10461|doi:10.1021/acs.inorgchem.2c01308
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25mrzk
title: CCDC 2014999: Experimental Crystal Structure Determination

description: Related Article: Rahul Dev Jana, Biswarup Chakraborty, Sayantan Paria, Takehiro Ohta, Reena Singh, Sourav Mandal, Satadal Paul, Shinobu Itoh, Tapan Kanti Paine|2022|Inorg.Chem.|61|10461|doi:10.1021/acs.inorgchem.2c01308
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25ms5s
title: CCDC 2015005: Experimental Crystal Structure Determination

description: Related Article: Rahul Dev Jana, Biswarup Chakraborty, Sayantan Paria, Takehiro Ohta, Reena Singh, Sourav Mandal, Satadal Paul, Shinobu Itoh, Tapan Kanti Paine|2022|Inorg.Chem.|61|10461|doi:10.1021/acs.inorgchem.2c01308
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27x2gq
title: CCDC 2082563: Experimental Crystal Structure Determination

description: Related Article: Wedad Al Garadi, Yusuf Sert, Mohamed El Hafi, Brahim El Ibrahimi, Youssef Ramli, Joel T. Mague, Lhoussaine El Ghayati, Nada Kheira Sebbar, El Mokhtar Essassi|2022|J.Heterocycl.Chem.|59|1213|doi:10.1002/jhet.4461
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc286dpl
title: CCDC 2091529: Experimental Crystal Structure Determination

description: Related Article: Rahul Dev Jana, Biswarup Chakraborty, Sayantan Paria, Takehiro Ohta, Reena Singh, Sourav Mandal, Satadal Paul, Shinobu Itoh, Tapan Kanti Paine|2022|Inorg.Chem.|61|10461|doi:10.1021/acs.inorgchem.2c01308
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.3886/e108503v1-123140
title: Optical Coherence Tomography Image Retinal Database

description: An open source Optical Coherence Tomography Image Database containing different retinal OCT images with different pathological conditions. Please use the following citation if you use the database: Peyman Gholami, Priyanka Roy, Mohana Kuppuswamy Parthasarathy, Vasudevan Lakshminarayanan, "OCTID: Optical Coherence Tomography Image Database", arXiv preprint arXiv:1812.07056, (2018). For more information and details about the database see: https://arxiv.org/abs/1812.07056
DOI: 10.5522/04/20285871
title: Participant Information Sheet from IFS study

description: Participation Information Sheet for ethics approved reflection in medical education study (IFS)
DOI: 10.5522/04/20285871.v1
title: Participant Information Sheet from IFS study

description: Participation Information Sheet for ethics approved reflection in medical education study (IFS)
DOI: 10.5522/04/20285937
title: Focus group transcript for Reflective Practice study

description: Focus group transcript for IFS ethics approved reflective practice study
DOI: 10.34740/kaggle/dsv/3937668
title: YouTube Daily
DOI: 10.22008/fk2/o33yhp/wyqrzb
title: T3b_Status and development of shale gas and shale oil in Europe_070417_final.pdf

description: :unav
DOI: 10.22008/fk2/o33yhp
title: Overview of the current status and development of shale gas and shale oil in Europe

description: This report is prepared by Karen L. Anthonsen, Niels Schovsbo and Peter Britze, Geological Survey of Denmark and Greenland (GEUS) in October 2016, as part of the EUOGA study (EU Unconventional Oil and Gas Assessment) commissioned by JRC-IET. The report is based on information from European National Geological Surveys received in the period from September 2015 until September 2016.
DOI: 10.6084/m9.figshare.20052164
title: Genomic diversity of genus Limosilactobacillus

description: The Supplementary Material associated with the article "Genomic diversity of genus <em>Limosilactobacillus</em>" as published in <em>Microbial Genomics</em>.
DOI: 10.6084/m9.figshare.20052164.v1
title: Genomic diversity of genus Limosilactobacillus

description: The Supplementary Material associated with the article "Genomic diversity of genus <em>Limosilactobacillus</em>" as published in <em>Microbial Genomics</em>.
DOI: 10.5281/zenodo.3540858
title: metadata [IO Islamic 2669] تاریخ طبری

description: IO Islamic 2669 Persian rendering of al-Ṭabarī by Abū ʻAlī Muḥammad ibn Muḥammad Balʻamī. METADATA
description: This upload provides the metadata in Libre office format.
DOI: 10.5281/zenodo.3540857
title: metadata [IO Islamic 2669] تاریخ طبری

description: IO Islamic 2669 Persian rendering of al-Ṭabarī by Abū ʻAlī Muḥammad ibn Muḥammad Balʻamī. METADATA
description: This upload provides the metadata in Libre office format.
DOI: 10.17028/rd.lboro.20297226
title: Supplementary information files for Back to the future: Exploring riverine macroinvertebrate communities' invasibility

description: Supplementary information files for article Back to the future: Exploring riverine macroinvertebrate communities' invasibility Abstract Riverine communities have been subject to numerous biological invasion events, with crustaceans among the most successful group of invasive animals worldwide. Understanding what makes a river system prone to invasion is of considerable interest to environmental regulators, resource managers, scientists and wider society globally. The Ponto-Caspian amphipod, <em>Dikerogammarus haemobaphes</em> (Crustacea: Gammaridae), is a hyper-successful invasive species that was first recorded in the UK in 2012. The use of contemporary distribution data for <em>D. haemobaphes</em> (2009–2020) from England provided a unique opportunity to study faunal community patterns and differences between sites that experienced invasion compared to those that have not. Macroinvertebrate community taxonomic, functional and phylogenetic features, as well as the presence of co-occurrent invaders and abiotic features of the river systems, were examined from sites before the invasion and compared to control sites that were not invaded during the study period. Sites that would later experience invasion by <em>D. haemobaphes</em> were characterized by higher abundances of other invaders (e.g., especially Ponto Caspian taxa), lower abundances of crustaceans and typically had greater channel width and water depth. These basic characteristics may help identify sites at risk of future invasion by <em>D. haemobaphes</em>. Most biomonitoring tools examined displayed no difference between control and pre-invaded samples, while both taxonomic and functional richness displayed higher values at sites that were subsequently invaded, questioning classic biological invasion hypotheses. Recognizing specific community characteristics that may be a precondition for subsequent invasion is essential for understanding and better predicting their future trajectories of change. <br>