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Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1\% of the total number of all species described, and more than 1\% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts.
L. N. Hudson;T. Newbold;S. Contu;S. L. L. Hill;I. Lysenko;A. De Palma;H. R. P. Phillips;R. A. Senior;D. J. Bennett;H. Booth;A. Choimes;D. L. P. Correia;J. Day;S. Echeverría-Londoño;M. Garon;M. L. K. Harrison;D. J. Ingram;M. Jung;V. Kemp;L. Kirkpatrick;C. D. Martin;Y. Pan;H. J. White;J. Aben;S. Abrahamczyk;G. B. Adum;V. Aguilar-Barquero;M. A. Aizen;M. Ancrenaz;E. Arbeláez-Cortés;I. Armbrecht;B. Azhar;A. B. Azpiroz;L. Baeten;A. Báldi;J. E. Banks;J. Barlow;P. Batáry;A. J. Bates;E. M. Bayne;P. Beja;Å. Berg;N. J. Berry;J. E. Bicknell;J. H. Bihn;K. Böhning-Gaese;T. Boekhout;C. Boutin;J. Bouyer;F. Q. Brearley;I. Brito;J. Brunet;G. Buczkowski;E. Buscardo;J. Cabra-García;M. Calviño-Cancela;S. A. Cameron;E. M. Cancello;T. F. Carrijo;A. L. Carvalho;H. Castro;A. A. Castro-Luna;R. Cerda;A. Cerezo;M. Chauvat;F. M. Clarke;D. F. R. Cleary;S. P. Connop;B. D'Aniello;P. G. da Silva;B. Darvill;J. Dauber;A. Dejean;T. Diekötter;Y. Dominguez-Haydar;C. F. Dormann;B. Dumont;S. G. Dures;M. Dynesius;L. Edenius;Z. Elek;M. H. Entling;N. Farwig;T. M. Fayle;A. Felicioli;A. M. Felton;G. F. Ficetola;B. K. C. Filgueiras;S. J. Fonte;L. H. Fraser;D. Fukuda;D. Furlani;J. U. Ganzhorn;J. G. Garden;C. Gheler-Costa;P. Giordani;S. Giordano;M. S. Gottschalk;D. Goulson;A. D. Gove;J. Grogan;M. E. Hanley;T. Hanson;N. R. Hashim;J. E. Hawes;C. Hébert;A. J. Helden;J. Henden;L. Hernández;F. Herzog;D. Higuera-Diaz;B. Hilje;F. G. Horgan;R. Horváth;K. Hylander;P. Isaacs-Cubides;M. Ishitani;C. T. Jacobs;V. J. Jaramillo;B. Jauker;M. Jonsell;T. S. Jung;V. Kapoor;V. Kati;E. Katovai;M. Kessler;E. Knop;A. Kolb;Á. Kőrösi;T. Lachat;V. Lantschner;V. L. Féon;G. LeBuhn;J. Légaré;S. G. Letcher;N. A. Littlewood;C. A. López-Quintero;M. Louhaichi;G. L. Lövei;M. E. Lucas-Borja;V. H. Luja;K. Maeto;T. Magura;N. A. Mallari;E. Marin-Spiotta;E. J. P. Marshall;E. Martínez;M. M. Mayfield;G. Mikusinski;J. C. Milder;J. R. Miller;C. L. Morales;M. N. Muchane;M. Muchane;R. Naidoo;A. Nakamura;S. Naoe;G. Nates-Parra;D. A. Navarrete;E. L. Neuschulz;N. Noreika;O. Norfolk;J. A. Noriega;N. M. Nöske;N. O'Dea;W. Oduro;C. Ofori-Boateng;C. O. Oke;L. M. Osgathorpe;J. Paritsis;A. Parra-H;N. Pelegrin;C. A. Peres;A. S. Persson;T. Petanidou;B. Phalan;T. K. Philips;K. Poveda;E. F. Power;S. J. Presley;V. Proença;M. Quaranta;C. Quintero;N. A. Redpath-Downing;J. L. Reid;Y. T. Reis;D. B. Ribeiro;B. A. Richardson;M. J. Richardson;C. A. Robles;J. Römbke;L. P. Romero-Duque;L. Rosselli;S. J. Rossiter;T. H. Roulston;L. Rousseau;J. P. Sadler;S. Sáfián;R. A. Saldaña-Vázquez;U. Samnegård;C. Schüepp;O. Schweiger;J. L. Sedlock;G. Shahabuddin;D. Sheil;F. A. B. Silva;E. M. Slade;A. H. Smith-Pardo;N. S. Sodhi;E. J. Somarriba;R. A. Sosa;J. C. Stout;M. J. Struebig;Y. Sung;C. G. Threlfall;R. Tonietto;B. Tóthmérész;T. Tscharntke;E. C. Turner;J. M. Tylianakis;A. J. Vanbergen;K. Vassilev;H. A. F. Verboven;C. H. Vergara;P. M. Vergara;J. Verhulst;T. R. Walker;Y. Wang;J. I. Watling;K. Wells;C. D. Williams;M. R. Willig;J. C. Z. Woinarski;J. H. D. Wolf;B. A. Woodcock;D. W. Yu;A. S. Zaitsev;B. Collen;R. M. Ewers;G. M. Mace;D. W. Purves;J. P. W. Scharlemann;A. Purvis
2014-01-01
Abstract
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1\% of the total number of all species described, and more than 1\% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/775174
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.