The isolated Erebia pandrose Apennine population is genetically unique and endangered by climate change-Reference-Cited by-同舟云学术

The isolated Erebia pandrose Apennine population is genetically unique and endangered by climate change

Published:2021-10-26 Issue:1 Volume:15 Page:136-148
ISSN:1752-458X
Container-title:Insect Conservation and Diversity
language:en
Short-container-title:Insect Conserv Diversity

Author:

Sistri Ginevra¹,Menchetti Mattia²,Santini Luca³,Pasquali Lorenzo¹,Sapienti Sofia¹,Cini Alessandro¹⁴^ORCID,Platania Leonardo²⁵^ORCID,Balletto Emilio⁶,Barbero Francesca⁶^ORCID,Bonelli Simona⁶,Casacci Luca Pietro⁶^ORCID,Dincă Vlad⁷⁸^ORCID,Vila Roger²^ORCID,Mantoni Cristina⁹,Fattorini Simone⁹^ORCID,Dapporto Leonardo¹^ORCID

Affiliation:

1. ZEN Lab, Dipartimento di Biologia dell'Università di Firenze Sesto Fiorentino Italy

2. Institut de Biologia Evolutiva (CSIC ‐ Universitat Pompeu Fabra) Barcelona, Catalonia Spain

3. Department of Biology and Biotechnologies “Charles Darwin” Sapienza University of Rome Rome Italy

4. Centre for Biodiversity & Environment Research University College London London UK

5. Institut Botànic de Barcelona (IBB, CSIC ‐ Ajuntament de Barcelona) Barcelona Catalonia Spain

6. Dipartimento di Scienze della Vita e Biologia dei Sistemi Università degli Studi di Torino Turin Italy

7. Ecology and Genetics Research Unit University of Oulu Oulu Finland

8. Research Institute of the University of Bucharest (ICUB) University of Bucharest Bucharest Romania

9. Department of Life, Health and Environmental Sciences University of L'Aquila L'Aquila Italy

Funder

Universitatea din București

Academy of Finland

“la Caixa” Foundation

Publisher

Wiley

Subject

Insect Science,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/icad.12538

Reference84 articles.

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2. spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models

3. Multicollinearity

4. A suite of global, cross-scale topographic variables for environmental and biodiversity modeling

5. Ensemble forecasting of species distributions

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