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Abstract

  1. Top of page
  2. Abstract
  3. Acknowledgements
  4. References
Thumbnail image of graphical abstract

Slopes of the diversity spectrum for all of the world's coastal large marine ecosystems for which sufficient data exist. From this, it is possible both to relate the diversity spectrum to environmental parameters (e.g. temperature) and to make regional predictions of unmeasured quantities, such as the diversity of small-bodied species.

In Focus: Reuman, D.C., Gislason, H, Barnes, C., Mélin, F. & Jennings, S. (2014) The marine diversity spectrum. Journal of Animal Ecology, 83, 963979.

How do we begin to extract order from the elegant chaos of natural ecosystems? In a landmark new paper published in this issue, Reuman et al. (2014) go back to first principles, combining a range of established body size- and species-centred ecological theories with empirically well-supported relationships to construct a model that enables them to predict key features using only remarkably simple biological and environmental measurements. They test this model using widely available data on the communities living in all of the world's coastal seas. Here, I discuss the key features of their model, and especially how the general patterns they document can lead to further, empirically driven tests of theory across multiple ecosystems.

‘Ecology would be easy were it not for all the ecosystems – vastly complex and variable as they are’. So stated a recent Nature editorial (Anon 2014), drawing on John Lawton's classic depiction of the middle ground of ecology – the domain of community ecology – as ‘a mess’, lacking both the simple generalities that we can extract from the dynamics of single species and the broad, repeatable patterns that emerge at global scales (Lawton 1999). Untangling this complexity is, of course, the challenge and the fascination of ecology; but what if there were a shortcut, a simple means to collapse the elegant chaos of ecosystems into something much more ordered?

The most promising lead in this search for a simplifying principle is the role that body size plays in structuring ecological communities, especially in aquatic systems. From simple observations – for example that most organisms are small, and that large organisms typically eat smaller organisms – an impressive array of conceptual, theoretical and empirical size-based approaches have been employed to address both fundamental and applied problems in marine ecology (e.g. Andersen & Beyer 2006; Jennings et al. 2008; Rossberg 2013; Blanchard et al. 2014). A first step in many such size-based studies is to classify all individuals in a community by body size alone, regardless of species. This allows the construction of the size spectrum, the negative, typically linear relationship between (logged) individual body size and the (logged) frequency of individuals of that size across all species. Increasingly, such ataxonomic size-based approaches are finding applications in other ecosystem types too (e.g. Yvon-Durocher et al. 2011; Trebilco et al. 2013), but the challenge of unifying these with classic species-based community ecology remains significant.

In a groundbreaking study published in this issue, Reuman et al. (2014) take up this challenge, presenting an explanatory model of relationships between body mass and species diversity across all taxa occurring in the world's continental seas. Reuman et al. (2014) introduce a species-level analogue of the size spectrum, the diversity spectrum, defined as the frequency distribution of species of different asymptotic (maximum) sizes. As for size spectra, both axes are logged to linearise the relationship. This link between the sizes of individuals (size spectrum), and species-level sizes and diversity (diversity spectrum) goes a long way towards unifying the species-based approach typical of terrestrial macroecology with the size-structured approaches often applied to marine systems (Webb et al. 2011; Webb 2012).

Reuman et al. (2014) achieve all this by using a series of well-supported allometries, as well as empirical descriptions of size distributions, and by borrowing from an implementation of neutral theory (Etienne & Olff 2004). This enables them to build from first principles a model that predicts key features of marine communities, including the relationship between diversity and body mass, and how this is affected by environmental variables such as sea surface temperature (SST). This technical tour de force requires a lengthy and meticulous model exposition both in the paper itself and in extensive supplementary materials, which would be a significant achievement in itself. Yet Reuman et al. (2014) go still further, confronting their model with global-scale empirical data, showing that they can reproduce the expected gross properties of marine communities. More than this, they demonstrate too the potential of their model to predict unknown quantities of potential use for establishing baselines for conservation and monitoring efforts. For instance, whereas previous models have predicted how many individual large fish there ought to be in a marine ecosystem in the absence of fishing pressure (e.g. Jennings & Blanchard 2004), this new model further predicts how these individuals should be divided between species, an important baseline against which to compare observed diversity.

The biggest criticisms of this model are likely to come from empiricists questioning some of its assumptions. For example, how robust are the relationships between temperature, body mass, larval duration and dispersal distances, that are integral to parameterising the model? Certainly, the larval duration—dispersal relationship is not clear-cut (e.g. Weersing & Toonen 2009; Selkoe & Toonen 2011), and equally robust environmental correlates of larval duration are scarce (e.g. Leis et al. 2013). Likewise, how accurately do the regional species lists and observed maximum lengths used to test the model reflect the actual richness of species and their true asymptotic sizes? How much error is introduced by the use of a single length-weight conversion across species? Or by the focus in the empirical tests on fish, rather than all pelagic species? Reuman et al. (2014) discuss many of these limitations; but in my view to focus on them is entirely to miss the significance of their work which, using only data that is readily available from existing global datasets, both tests existing questions about the environmental dependence of marine diversity patterns, and poses new ones. Rather than quibble over approximations used in the model formulation, empiricists should welcome the generalities proposed here and take up the challenge of confronting the new predictions with data.

For instance, Reuman et al. (2014) show how their model, parameterised only using data on fish with maximum sizes in the range c. 1–1000 kg, can be used to derive predictions of the number of species in much smaller size classes. For the North Sea, they predict 431 species with maximum sizes between 1 and 10 g. This is at the upper end of sizes of the mesozooplankton comprehensively sampled by the Continuous Plankton Recorder survey (www.sahfos.ac.uk), with typical body masses of planktonic Decapod and Euphausid crustacea around 1–2 g and major groups such as planktonic Copepoda considerably smaller (in the 1–100 mg range; wet weights of selected zooplankton taxa taken from Kiørboe 2013). Nonetheless, it is illustrative to consider the total number of distinct taxonomic entities (N = 173; D. Johns, pers. comm.) recorded by the CPR survey from the North Sea. Note that this includes several groups not identified to species level and so is certainly an underestimate of the actual number of sampled species (which in turn will be an underestimate of the species present, the extensive temporal and spatial scale of the CPR survey notwithstanding). The fact that this empirical estimate is on the same order of magnitude as Reuman et al.'s (2014) prediction (N = 431) is certainly encouraging.

Perhaps the most exciting thing about Reuman et al.'s (2014) study is the potential for future development. Already, their model mechanistically explains a third of variation in diversity spectrum properties across marine ecosystems using only gross properties – indeed, gross simplifications of gross properties – of their environmental characteristics. This is impressive indeed; but of course, it means that two-thirds of the variation remains, so plenty of Lawton's (1999) ‘mess’ is still to be explained through consideration of more detailed or idiosyncratic variables. Several other avenues for progress are also identified, including studying how fishing – which we know affects size spectra – changes diversity spectra. Still more tantalising is the authors’ conclusion that ‘it may be possible to generalise [the] theory to… other ecosystems’ (Reuman et al. 2014), a cross-realm effort that is sorely needed (Webb 2012). Achieving this would be progress indeed towards extracting order from the elegant chaos of Earth's ecosystems.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Acknowledgements
  4. References

TJW is a Royal Society University Research Fellow.

References

  1. Top of page
  2. Abstract
  3. Acknowledgements
  4. References