Intraspecific variation of thermal tolerance in freshwater insects along elevational gradients: the case of a widespread diving beetle
Pallares, S.; Carbonell, J. A.; Picazo, F.; Bilton, D. T.; Millan, A.; Abellan, P.
Show abstract
Species distributed along wide elevational gradients are likely to experience local adaptation and exhibit high plasticity of thermal tolerance traits, as these gradients are characterised by steep environmental changes over short geographic distances (i.e., strong selection differentials). However, the prevalence of adaptive clinal intraspecific variation in thermal tolerance with elevation remains unclear, and this aspect has been poorly studied in freshwater insects. We explored variation in upper (heat coma temperature) and lower (supercooling point) thermal limits and acclimation capacity among Iberian populations of the widespread aquatic beetle Agabus bipustulatus (fam. Dytiscidae) across a 2,000-m elevational gradient, from lowland to alpine areas. As minimum, maximum and mean temperatures decline with elevation, we predicted that higher elevation populations will show lower heat tolerances and higher cold tolerances. We also explored whether acclimation capacity is positively related with climatic variability across different elevations. We found significant variation in upper and lower thermal limits among populations of A. bipustulatus, but no evidence of local adaptation to different thermal conditions along the altitudinal gradient, as relationships between thermal limits and elevation or climatic variables were in general not significant. Plasticity of upper and lower thermal limits was overall and consistently low in all populations. These results suggest conservatism of the thermal niche, which might be the result of gene flow counteracting the effects of divergent selection, or adaptations in other traits that buffer the exposure of populations to climate extremes. The limited adaptive potential and plasticity of thermal tolerance found here for A. bipustulatus imply that even generalist species, distributed along wide environmental gradients, may have little resilience to global warming.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Thermal biology of two sympatric Lacertids lizards (Lacerta diplochondrodes and Parvilacerta parva) from Western Anatolia 94%
- Long-term evolution experiments fully reveal the potential for thermal adaptation 94%
- The effect of elevated aestivation temperatures on the behaviour of Bogong Moths (Agrotis infusa) 94%
Similar papers in this journal
- Acclimation Capacity to Global Warming of Amphibians and Freshwater Fishes: Drivers, Patterns, and Data Limitations 96%
- Temperature-dependence of metabolic rate in tropical and temperate aquatic insects: support for the Climate Variability Hypothesis in mayflies but not stoneflies. 96%
- Recurrent extreme climatic events are driving gorgonian populations to local extinction: low adaptive potential to marine heatwaves. 95%
Similar papers in this journal
- Warming undermines emergence success in a threatened alpine stonefly: a multi-trait perspective on vulnerability to climate change 96%
- Sexual selection moderates heat stress response in males and females 94%
- Multigenerational exposure to elevated temperatures leads to a reduction in standard metabolic rate in the wild 93%
Similar papers in this journal
- Landscape genetics across the Andes Mountains: Environmental variation drives genetic divergence in the leaf-cutting ant Atta cephalotes 93%
- Whole genome analyses reveal weak signatures of population structure and environmentally associated local adaptation in an important North American pollinator, the bumble bee Bombus vosnesenskii 93%
- Macrogenetics reveals multifaceted influences of environmental variation on vertebrate population genetic diversity across the Americas 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.