Assessing the suitability of diversity metrics to detect biodiversity change
Introduction
In a period of rapid global change, monitoring biodiversity changes is key to detect early warning signals of decline, infer the causes of such decline, and develop effective conservation strategies to mitigate it (Ash et al., 2009, Balmford et al., 2003, Balmford et al., 2005, Buckland et al., 2005, Butchart et al., 2010, Gregory et al., 2005, Nichols and Williams, 2006, Tittensor et al., 2014). The multifaceted nature of biodiversity (Gaston, 1996, Purvis and Hector, 2000) is studied through a large number of metrics. Different metrics measure different components of biodiversity such as species richness, abundance, evolutionary history (i.e. phylogenetic diversity; Faith, 1992), and functional traits (Mason et al., 2005). However, as no single metric captures all relevant aspects of biodiversity, none of them taken individually can provide a full picture of the patterns of change. Further, metrics can even be misleading if considered individually. For instance, the geometric mean abundance can increase if rare species increase in abundance, while total abundance is decreasing (Schipper et al., 2016). Similarly, invasive species can increase species richness or functional and phylogenetic diversity, while having negative impacts on the abundances of native species (Thomas, 2013, Winter et al., 2009). The rate and direction of change in a metric may also depend on idiosyncrasies in the state of the initial community, and/or natural ecological succession. Moreover, in addition to directional changes in biodiversity, species relative abundances may fluctuate over shorter time frames due to demographic stochasticity or competitive and predator-prey dynamics. This “noise” can confound the signal of interest (i.e. directional change in response to a specific driver).
The choice and response of biodiversity metrics may strongly affect our interpretation of biodiversity change and, hence, prioritization of resources for conservation (Gaston and Spicer, 2004, Purvis and Hector, 2000). Thus, it is crucial to understand how alternative metrics respond to specific changes, which metrics are the most sensitive in order to detect early signals of biodiversity decline, and which ones respond consistently to changes. Empirical datasets allow investigating how metrics change in space and time, but have several limitations. These include the limited number of possible scenarios and communities represented, and the lack of control on the underlying cause of change, the likely co-existence of several mechanisms of decline (e.g., decline of habitat specialists due to the loss of their habitat type and decline of large species due to overexploitation). This complicates the attempts to link the behaviour of a diversity metric to a definite mechanism of biodiversity change. Virtual datasets allow full control of both the community composition and the mechanism of decline, and thus allow the comparison of the relative responses of the diversity metrics (Zurell et al., 2010) by simulating ecological processes under alternative scenarios (Dornelas, 2010, Lamb et al., 2009, Münkemüller and Gallien, 2015, Olden and Poff, 2003, Supp and Ernest, 2014).
In this study, we explored the behaviour of a set of diversity metrics under different scenarios of biodiversity change. To this end, we generated synthetic communities and simulated changes in their composition to investigate the responses of the metrics. We recorded how metrics changed over time under each scenario, and identified those that were most sensitive to these community changes and showed a consistent response irrespective of the state of the original community. We also assessed non-linearity in metrics responses, and their effect on our ability to detect early warning signals of biodiversity change. Finally, we measured the signal-to-noise ratio (SNR) of the metrics under each scenario to compare the metrics' ability to detect directional changes in biological communities.
Section snippets
Virtual dataset
We assumed a landscape area of 10,000 km2 consisting of two habitats, one dominant and one secondary. For convenience we will refer to these habitats as forest and grassland, respectively. The size of the landscape was chosen such that it was large enough to allow each species to form a population from ~ 15 to > 50,000 individuals. Forest covered a random proportion between 0.7 and 0.9 of the entire landscape.
We generated 150 species, and randomly assigned to each a diet, body mass, population
Metric behaviour under alternative scenarios
The diversity metrics exhibited different temporal trends under the nine scenarios of biodiversity change (Fig. 2, Fig. 3, Fig. A1, Fig. A2, Fig. A3, Fig. A4, Fig. A5, Fig. A6, Fig. A7, Fig. A8). Under the “Uniform decline” scenario, where all species decreased by the same number of individuals and rare species went extinct first, all metrics showed a decrease, especially species richness, functional richness and functional dispersion (Fig. 2). The “Proportional decline” scenario, where all
Discussion
Simulating biodiversity change through time allowed us to explore the behaviour of a set of biodiversity metrics and assess their suitability for monitoring biodiversity change, including declines in species' abundances that can be of conservation concern. Richness-based metrics require presence data, which is less time-consuming and costly to collect than abundance data (Costello et al., submitted for publication). Knowing which species are present, particularly those that are ecologically
Acknowledgements
We thank R D Gregory and another anonymous reviewer for providing constructive comments on earlier versions of the manuscript. This article is based upon work from COST Action ES1101 “Harmonising Global Biodiversity Modelling” (Harmbio), supported by COST (European Cooperation in Science and Technology).
References (69)
- et al.
Measuring the changing state of nature
Trends Ecol. Evol.
(2003) Conservation evaluation and phylogenetic diversity
Biol. Conserv.
(1992)- et al.
Commonness, population depletion and conservation biology
Trends Ecol. Evol.
(2008) - et al.
Indices for monitoring biodiversity change: are some more effective than others?
Ecol. Indic.
(2009) - et al.
Mapping habitats in a marine reserve showed how a 30-year trophic cascade altered ecosystem structure
Biol. Conserv.
(2012) Opposite trends in response for the Shannon and Simpson indices of landscape diversity
Appl. Geogr.
(2002)- et al.
Monitoring for conservation
Trends Ecol. Evol.
(2006) - et al.
Desirable mathematical properties of indicators for biodiversity change
Ecol. Indic.
(2012) - et al.
Biodiversity variables for prioritization and monitoring of conservation areas
Biol. Conserv.
(2016) - et al.
bioDISCOVERY: assessing, monitoring and predicting biodiversity
The Convention on Biological Diversity's 2010 target
Science
A critical assessment of the form of the interspecific relationship between abundance and body size in animals
J. Anim. Ecol.
Consumer-resource body-size relationships in natural food webs
Ecology
Toward a metabolic theory of ecology
Ecology
Monitoring change in biodiversity through composite indices
Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci.
The geometric mean of relative abundance indices: a biodiversity measure with a difference
Ecosphere
Global biodiversity: indicators of recent declines
Science
Multiple causes of high extinction risk in large mammal species
Science
Strategic Plan for Biodiversity 2011–2020. Montreal
Amphipod fauna of the sponges Halichondria panicea and Hymeniacidon perleve in Lough Hyne, Ireland
Mar. Ecol. Prog. Ser.
Distinguishing essential and fundamental biodiversity variables
Biol. Conserv.
Rarity value and species extinction: the anthropogenic allee effect
PLoS Biol.
Interspecific allometry of population density in mammals and other animals: the independence of body mass and population energy-use
Biol. J. Linn. Soc.
Disturbance and change in biodiversity
Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci.
Assemblage time series reveal biodiversity change but not systematic loss
Science
Trophic downgrading of planet Earth
Science
Biodiversity: A Biology of Numbers and Difference
Biodiversity: An Introduction
Minimum viable populations: processes of species extinction
A general coefficient of similarity and some of its properties
Biometrics
Wild bird indicators: using composite population trends of birds as measures of environmental health
Ornithol. Sci.
Developing indicators for European birds
Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci.
The impact of conservation on the status of the world's vertebrates
Science
The Unified Neutral Theory of Biodiversity and Biogeography
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