Ecology. 2017 Apr 26. doi: 10.1002/ecy.1876. [Epub ahead of print]
- 1
- Department of Ecology, Evolution and Natural Resources, Rutgers University, New Brunswick, New Jersey, USA, 08901.
- 2
- Department of Biological Sciences, University of Calgary, Calgary, AB, Canada, T2N 1N4.
- 3
- Department of Entomology and Nematology, University of California, Davis, California, USA, 95616.
- 4
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, California, USA, 94720.
- 5
- Department of Biological Science, National University of Singapore, Singapore, 117543.
- 6
- Department of Entomology, University of Manitoba, Winnipeg, MB, Canada, R3T 2N2.
Abstract
The
relationship between biodiversity and the stability of ecosystem
function is a fundamental question in community ecology, and hundreds of
experiments have shown a positive relationship between species richness
and the stability of ecosystem function. However, these experiments
have rarely accounted for common ecological patterns, most notably
skewed species abundance distributions and non-random extinction risks,
making it difficult to know whether experimental results can be scaled
up to larger, less manipulated systems. In contrast with the prolific
body of experimental research, few studies have examined how species
richness affects the stability of ecosystem services at more realistic,
landscape scales. The paucity of these studies is due in part to a lack
of analytical methods that are suitable for the correlative structure of
ecological data. A recently developed method, based on the Price
equation from evolutionary biology, helps resolve this knowledge gap by
partitioning the effect of biodiversity into three components: richness,
composition, and abundance. Here, we build on previous work and present
the first derivation of the Price equation suitable for analyzing
temporal variance of ecosystem services. We applied our new derivation
to understand the temporal variance of crop pollination services in two
study systems (watermelon and blueberry) in the mid-Atlantic United
States. In both systems-but especially in the watermelon system-the
stronger driver of temporal variance of ecosystem services was
fluctuations in the abundance of common bee species, which were present
at nearly all sites regardless of species richness. In contrast,
temporal variance of ecosystem services was less affected by differences
in species richness, because lost and gained species were rare. Thus,
the findings from our more realistic landscapes differ qualitatively
from the findings of biodiversity-stability experiments. This article is
protected by copyright. All rights reserved.
This article is protected by copyright. All rights reserved.
KEYWORDS:
Price equation; abundance; biodiversity; composition; ecosystem services; richness; variance
