1 resultado para Sentiment Analysis, Opinion Mining, Twitter
em eResearch Archive - Queensland Department of Agriculture
Filtro por publicador
- Aberdeen University (7)
- Aberystwyth University Repository - Reino Unido (2)
- Academic Archive On-line (Mid Sweden University; Sweden) (1)
- Academic Research Repository at Institute of Developing Economies (1)
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (5)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (19)
- Aquatic Commons (1)
- Archive of European Integration (5)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (3)
- Aston University Research Archive (38)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (4)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (2)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (3)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (12)
- Boston University Digital Common (2)
- Brock University, Canada (3)
- Brunel University (1)
- Bucknell University Digital Commons - Pensilvania - USA (2)
- Bulgarian Digital Mathematics Library at IMI-BAS (6)
- CaltechTHESIS (1)
- Cambridge University Engineering Department Publications Database (7)
- CentAUR: Central Archive University of Reading - UK (49)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (1)
- Cochin University of Science & Technology (CUSAT), India (5)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (4)
- CUNY Academic Works (1)
- Dalarna University College Electronic Archive (2)
- Deakin Research Online - Australia (82)
- Digital Archives@Colby (1)
- Digital Commons - Michigan Tech (4)
- Digital Commons - Montana Tech (1)
- Digital Commons at Florida International University (14)
- Digital Peer Publishing (4)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (3)
- Duke University (6)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (1)
- Greenwich Academic Literature Archive - UK (1)
- Helda - Digital Repository of University of Helsinki (6)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (4)
- Indian Institute of Science - Bangalore - Índia (14)
- INSTITUTO DE PESQUISAS ENERGÉTICAS E NUCLEARES (IPEN) - Repositório Digital da Produção Técnico Científica - BibliotecaTerezine Arantes Ferra (1)
- Instituto Politécnico do Porto, Portugal (6)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (1)
- Martin Luther Universitat Halle Wittenberg, Germany (1)
- Massachusetts Institute of Technology (1)
- Memorial University Research Repository (1)
- Nottingham eTheses (2)
- Open University Netherlands (2)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (2)
- Portal de Revistas Científicas Complutenses - Espanha (10)
- Publishing Network for Geoscientific & Environmental Data (2)
- QSpace: Queen's University - Canada (3)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (20)
- Queensland University of Technology - ePrints Archive (252)
- RDBU - Repositório Digital da Biblioteca da Unisinos (6)
- Repositorio Académico de la Universidad Nacional de Costa Rica (1)
- Repositório Científico da Universidade de Évora - Portugal (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (2)
- Repositorio de la Universidad de Cuenca (2)
- Repositório digital da Fundação Getúlio Vargas - FGV (6)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional da Universidade Tecnológica Federal do Paraná (RIUT) (1)
- Repositorio Institucional de la Universidad de La Laguna (1)
- Repositorio Institucional de la Universidad de Málaga (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (21)
- Research Open Access Repository of the University of East London. (1)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (7)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- Scielo Uruguai (1)
- Universidad de Alicante (36)
- Universidad del Rosario, Colombia (5)
- Universidad Politécnica de Madrid (29)
- Universidade Complutense de Madrid (1)
- Universidade de Lisboa - Repositório Aberto (2)
- Universidade Federal de Uberlândia (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (5)
- Universidade Metodista de São Paulo (2)
- Universitat de Girona, Spain (2)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (5)
- Université de Montréal (2)
- Université de Montréal, Canada (18)
- Université Laval Mémoires et thèses électroniques (1)
- University of Connecticut - USA (1)
- University of Michigan (9)
- University of Queensland eSpace - Australia (27)
- University of Southampton, United Kingdom (5)
- University of Washington (4)
- WestminsterResearch - UK (3)
- Worcester Research and Publications - Worcester Research and Publications - UK (1)
Resumo:
Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species.