946 resultados para Archaeological predictive models
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- Aberdeen University (1)
- Abertay Research Collections - Abertay University’s repository (1)
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- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (12)
- Aston University Research Archive (12)
- Avian Conservation and Ecology - Eletronic Cientific Hournal - Écologie et conservation des oiseaux: (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (14)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (145)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (1)
- Biodiversity Heritage Library, United States (10)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (13)
- Brock University, Canada (1)
- CentAUR: Central Archive University of Reading - UK (32)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (6)
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- Digital Commons - Michigan Tech (6)
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- Duke University (3)
- Galway Mayo Institute of Technology, Ireland (1)
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- Instituto Nacional de Saúde de Portugal (1)
- Instituto Politécnico do Porto, Portugal (33)
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- Laboratório Nacional de Energia e Geologia - Portugal (1)
- Martin Luther Universitat Halle Wittenberg, Germany (14)
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- Portal de Revistas Científicas Complutenses - Espanha (1)
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- Repositório digital da Fundação Getúlio Vargas - FGV (4)
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- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (72)
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- Université de Lausanne, Switzerland (51)
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- University of Queensland eSpace - Australia (171)
- University of Southampton, United Kingdom (2)
- University of Washington (3)
Resumo:
Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown