Ecological Indicators (Feb 2021)

Determining species diversity and functional traits of beetles for monitoring the effects of environmental change in the New Zealand alpine zone

  • Keely Paler,
  • Adrian Monks,
  • Richard A.B. Leschen,
  • Darren F. Ward

Journal volume & issue
Vol. 121
p. 107100

Abstract

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Alpine invertebrate populations are expected to be highly sensitive to a changing climate because temperature plays an important role in their development, reproduction, and survival. However, high levels of rarity and endemism make it particularly challenging to measure climate effects on this group because interpretation of monitoring data is undermined by high levels of spatial turnover and inter-sample variability. Functional traits may overcome this monitoring challenge by allowing generalisation across taxa based on characters that respond consistently to a changing environment.Here we evaluate whether functional traits respond more consistently and sensitively to changes in environmental conditions at different sites than species diversity metrics. Temperature and physical structure in Chionochloa grassland plots was manipulated using Open-Top-Chamber and fertility treatments, respectively. Pitfall traps were used to sample beetles from four years (2013–2016) during the austral summer at two different altitudes in Takahe Valley, Fiordland.Natural variation between years and sites had a stronger influence on the beetle community compared with temperature and nutrient treatments. The presence of complex interactive effects between treatments, different sites, and different years, indicates that the impact of changes to temperature and nutrient levels are context-specific and that landscape-level variations have a large role on structuring beetle communities.The responses of alpine beetle communities to climate change are likely to be complex, however, trait-based measures may comprise a more sensitive method for detecting generalisable change because they can be pooled over sets of species that appear rarely in the data.

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