4.2 Article

Butterfly abundance in a warming climate: patterns in space and time are not congruent

期刊

JOURNAL OF INSECT CONSERVATION
卷 15, 期 1-2, 页码 233-240

出版社

SPRINGER
DOI: 10.1007/s10841-010-9340-0

关键词

Biotic homogenisation; Butterflies; Climate change; Climate envelope; Mixed models; Niche; Space-for-time substitution; UK butterfly monitoring scheme

资金

  1. NERC [NE/D009448/2]
  2. European Commission (EC)
  3. multi-agency consortium led by Defra
  4. CCW
  5. JNCC
  6. FC
  7. NE
  8. NERC
  9. NIEA
  10. SNH
  11. Natural Environment Research Council [CEH010021, NE/D009448/2, NE/G001901/1] Funding Source: researchfish
  12. NERC [NE/D009448/2, NE/G001901/1] Funding Source: UKRI

向作者/读者索取更多资源

We present a model of butterfly abundance on transects in England. The model indicates a significant role for climate, but the direction of association is counter to expectation: butterfly population density is higher on sites with a cooler climate. However, the effect is highly heterogeneous, with one in five species displaying a net positive association. We use this model to project the population-level effects of climate warming for the year 2080, using a medium emissions scenario. The results suggest that most populations and species will decline markedly, but that the total number of butterflies will increase as communities become dominated by a few common species. In particular, Maniola jurtina is predicted to make up nearly half of all butterflies on UK Butterfly Monitoring Scheme (UKBMS) transects by 2080. These results contradict the accepted wisdom that most insect populations will grow as the climate becomes warmer. Indeed, our predictions contrast strongly with those derived from inter-annual variation in abundance, emphasizing that we lack a mechanistic understanding about the factors driving butterfly population dynamics over large spatial and temporal scales. Our study underscores the difficulty of predicting future population trends and reveals the naivety of simple space-for-time substitutions, which our projections share with species distribution modelling.

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