Climate projections predict major changes in alpine environments by the end of the 21st century. To avoid climate-induced maladaptation and extinction, many animal populations will either need to move to more suitable habitats or adapt in situ to novel conditions. Since populations of a species exhibit genetic variation related to local adaptation, it is important to incorporate this variation into predictive models to help assess the ability of the species to survive climate change. Here, we evaluate how the adaptive genetic variation of a mountain ungulate-the Northern chamois (Rupicapra rupicapra)-could be impacted by future global warming. Based on genotype-environment association analyses of 429 chamois using a ddRAD sequencing approach, we identified genetic variation associated with climatic gradients across the European Alps. We then delineated adaptive genetic units and projected the optimal distribution of these adaptive groups in the future. Our results suggest the presence of local adaptation to climate in Northern chamois with similar genetic adaptive responses in geographically distant but climatically similar populations. Furthermore, our results predict that future climatic changes will modify the Northern chamois adaptive landscape considerably, with various degrees of maladaptation risk

Hoste, A.; Capblancq, T.; Broquet, T.; Denoyelle, L.; Perrier, C.; Buzan, E.; Šprem, N.; Corlatti, L.; Crestanello, B.; Hauffe, H.C.; Pellissier, L.; Yannic, G. (9999-12-11). Projection of current and future distribution of adaptive genetic units in an alpine ungulate. HEREDITY. doi: 10.1038/s41437-023-00661-2 handle: https://hdl.handle.net/10449/83424

Projection of current and future distribution of adaptive genetic units in an alpine ungulate

Crestanello, Barbara;Hauffe, Heidi Christine;
In corso di stampa

Abstract

Climate projections predict major changes in alpine environments by the end of the 21st century. To avoid climate-induced maladaptation and extinction, many animal populations will either need to move to more suitable habitats or adapt in situ to novel conditions. Since populations of a species exhibit genetic variation related to local adaptation, it is important to incorporate this variation into predictive models to help assess the ability of the species to survive climate change. Here, we evaluate how the adaptive genetic variation of a mountain ungulate-the Northern chamois (Rupicapra rupicapra)-could be impacted by future global warming. Based on genotype-environment association analyses of 429 chamois using a ddRAD sequencing approach, we identified genetic variation associated with climatic gradients across the European Alps. We then delineated adaptive genetic units and projected the optimal distribution of these adaptive groups in the future. Our results suggest the presence of local adaptation to climate in Northern chamois with similar genetic adaptive responses in geographically distant but climatically similar populations. Furthermore, our results predict that future climatic changes will modify the Northern chamois adaptive landscape considerably, with various degrees of maladaptation risk
Settore BIO/05 - ZOOLOGIA
In corso di stampa
Hoste, A.; Capblancq, T.; Broquet, T.; Denoyelle, L.; Perrier, C.; Buzan, E.; Šprem, N.; Corlatti, L.; Crestanello, B.; Hauffe, H.C.; Pellissier, L.; Yannic, G. (9999-12-11). Projection of current and future distribution of adaptive genetic units in an alpine ungulate. HEREDITY. doi: 10.1038/s41437-023-00661-2 handle: https://hdl.handle.net/10449/83424
File in questo prodotto:
File Dimensione Formato  
2023 H Hauffe.pdf

accesso aperto

Tipologia: Altro materiale allegato (Other attachments)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 3 MB
Formato Adobe PDF
3 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10449/83424
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact