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Keywords:

  • energy availability;
  • sampling effects;
  • spatial turnover;
  • species richness;
  • temperature;
  • temporal turnover

Summary

  • 1
    The spatial scale of analysis may influence the nature, strength and underlying drivers of macroecological patterns, one of the most frequently discussed of which is the relationship between species richness and environmental energy availability.
  • 2
    It has been suggested that species–energy relationships are hump-shaped at fine spatial grains and consistently positive at larger regional grains. The exact nature of this scale dependency is, however, the subject of much debate as relatively few studies have investigated species–energy relationships for the same assemblage across a range of spatial grains. Here, we contrast species–energy relationships for the British breeding avifauna at spatial grains of 1 km × 1 km, 2 km × 2 km and 10 km × 10 km plots, while maintaining a constant spatial extent.
  • 3
    Analyses were principally conducted using data on observed species richness. While survey work may fail to detect some species, observed species richness and that estimated using nonparametric techniques were strongly positively correlated with each other, and thus exhibit very similar spatial patterns. Moreover, the forms of species–energy relationships using observed and estimated species richness were statistically indistinguishable from each other.
  • 4
    Positive decelerating species–energy relationships arise at all three spatial grains. There is little evidence that the explanatory power of these relationships varies with spatial scale. However, ratios of regional (large-scale) to local (small-scale) species richness decrease with increasing energy availability, indicating that local richness responds to energy with a steeper gradient than does regional richness. Local assemblages thus sample a greater proportion of regional richness at higher energy levels, suggesting that spatial turnover of species richness is lower in high-energy regions. Similarly, a crude measure of temporal turnover, the ratio of cumulative species richness over a 4-year period to species richness in a single year, is lower in high-energy regions. These negative relationships between turnover and energy appear to be causal as both total and mean occupancy per species increases with energy.
  • 5
    While total density in 1 km × 1 km plots correlates positively with energy availability, such relationships are very weak for mean density per species. This suggests that the observed association between total abundance and species richness may not be mediated by population extinction rates, as predicted by the more individuals hypothesis.
  • 6
    The sampling mechanism suggests that species–energy relationships arise as high-energy areas support a greater number of individuals, and that random allocation of these individuals to local areas from a regional assemblage will generate species–energy relationships. While randomized local species–energy relationships are linear and positive, predicted richness is consistently greater than that observed. The mismatch between the observed and randomized species–energy relationships probably arises as a consequence of the aggregated nature of species distributions. The sampling mechanism, together with species spatial aggregation driven by limited habitat availability, may thus explain the species–energy relationship observed at this spatial scale.