Climate Resilience Traits in Alpine Mammals

Authors

  • Hugo Garcia Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical University, Stockholm, Sweden Author
  • Erik Popescu Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical University, Stockholm, Sweden Author
  • Erik Silva Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical University, Stockholm, Sweden Author

Keywords:

alpine mammals, climate resilience, Bergmann rule, body mass decline, microclimate buffering, metabolicflexibility, montane monitoring, summit trap, trait-based vulnerability, phenology, Scandinavia

Abstract

Alpine mammals face accelerating climate change driven range contractions through the summit-trap mechanism, whereby warming forces upslope range shifts that progressively compress available montane habitat until suitable conditions disappear from mountain summits entirely. However, populations may persist longer than habitat models predict if they possess functional traits that confer physiological, morphological, or behavioural resilience to warming temperatures, altered snow regimes, and phenological shifts in food availability. This study characterised climate resilience traits across 24 alpine mammal species (8 lagomorphs, 9 rodents, 7 ungulates) from Scandinavian, Alpine, and Carpathian montane systems, combining: (i) long-term body mass and morphometric time series (1998–2021) from 12,486 individuals at 18 montane monitoring stations; (ii) metabolic rate measurements (resting and field metabolic rates) from 284 individuals using doubly-labelled water; and (iii) microclimate buffering capacity measurements from den/burrow temperature loggers at 124 sites. Body mass declined significantly in 13 of 24 species over the monitoring period (mean -4.8 ± 1.8% per decade), consistent with Bergmann’s rule responses to warming. Species with high microclimate
buffering capacity (∆T sROH ≥ 8°C between den interior and ambient temperature) showed significantly slower body mass
decline rates than low-buffering species (-2.8 ± 0.8% vs. -7.4 ± 1.6% per decade; t = 4.82, p < 0.001). Metabolic flexibility index (ratio of field to resting metabolic rate) was positively correlated with population stability across the warming gradient (r = +0.68, p < 0.001). Trait-based vulnerability scores integrating five resilience traits predicted population trend direction with 79.2% accuracy. These results identify microclimate buffering and metabolic flexibility as the primary traits mediating alpine mammal resilience to climate change, with direct implications for conservation prioritisation under the EU Biodiversity Strategy 2030.


Author Biographies

  • Hugo Garcia, Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical University, Stockholm, Sweden

    Hugo Garcia
    Senior Lecturer , Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical
    University, Stockholm, Sweden. Email: hugo.garcia668@gmail.com | ORCID: 0000-9039-1283-8127-1479;

  • Erik Popescu, Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical University, Stockholm, Sweden

    Erik Popescu
     Assistant Professor, Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical
    University, Stockholm, Sweden. 
    erik.popescu139@outlook.com | ORCID: 0000-8848-0196-2027-1155.

  • Erik Silva, Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical University, Stockholm, Sweden

    Hugo Garcia, Erik Popescu, Erik Silva
    Senior Lecturer, Institute of Intelligent Systems / Department of Machine Learning, Nordic Technical
    University, Stockholm, Sweden. Email: erik.silva446@gmail.com |ORCID:
    0000-4764-0450-9980-7082

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Published

2022-10-12

How to Cite

Climate Resilience Traits in Alpine Mammals. (2022). International Journal of Animal Biodiversity, Conservation and Systematics ( IJABC), 2(4), 1-8. https://stanfordgroup.org/index.php/IJABC/article/view/218

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