Ecosystem vulnerability to ocean warming

Analysis of the temperature ranges occupied by marine species finds that the vulnerability of ecological communities to global warming may depend more on organismal physiology than on the magnitude of change. See Article p.88

Human communities have already begun to develop and execute plans for adapting to climate change1. Ecological communities are equally vulnerable, and human intervention is required to alleviate pressures and minimize the risks of biodiversity loss and species extinction. Much of our attention so far has focused on predicting the responses of individual species. But is it possible to anticipate how entire ecosystems will respond and reconfigure as the land and oceans warm? In this issue, Stuart-Smith et al.2 (page 88) construct a metric of community vulnerability for marine environments that is based on the physiology of individual species as well as on external environmental conditions. Their findings challenge previous assumptions that the magnitude or rate of warming is the best predictor of ecological change.

All species have a thermal niche — the temperature range in which they can survive. But, in reality, most do not occupy all sites within this range because other constraints, such as competition and food availability, limit them further. The range of temperatures over which a species actually lives is its 'realized' thermal niche. Stuart-Smith et al. use two large species-occurrence databases to construct realized thermal niches for almost 4,000 reef fish and marine macroinvertebrate species, by comparing observations of the animals' occurrence with data on sea surface temperature at those locations.

Each realized thermal niche has a midpoint, and the mean of these midpoints for all individuals in an ecological community is called the community thermal index (CTI; Fig. 1). Although the CTI is not a new concept (see ref. 3, for example), Stuart-Smith et al. calculate it across a global range of marine communities. They then compare it with observed temperatures to determine a 'thermal bias' — the discrepancy between the CTI and the mean annual sea surface temperature. This indicates whether a community is weighted towards species adapted to warmer environments (a positive bias) or to cooler ones.

Figure 1: Community thermal indices.

Each species has a realized thermal niche — the range of temperatures over which it can live in a given community. The community thermal index (CTI) is the mean midpoint of these thermal niches for all individuals in a community. Stuart-Smith et al.2 have extended this metric to the CTImax, which is a measure of the mean of the upper end (95th percentile) of the realized thermal limits of the species in the community. The CTImax allows calculation of a vulnerability metric — the proportion of species in a community that has an upper thermal limit lower than a given summer sea surface temperature. In this example, if the future summer sea surface temperature is 25 °C, the vulnerability metric will be 0.33, because one of the three species in the community (species 3) has an upper thermal limit below that temperature.

The authors find that most communities are associated with a thermal bias. This is perhaps unsurprising, but Stuart-Smith et al. also detect an intriguing large-scale biogeographical pattern, with the thermal bias not randomly scattered around ocean temperature (see Fig. 1 of the paper2). Moving from CTIs to examining the thermal-niche midpoints that underpin them, the authors find that most species are associated with either a temperate or tropical midpoint, with noticeably fewer species having midpoints at subtropical temperatures (there is also a third group of invertebrates that have a subpolar midpoint). Such faunal clustering is responsible for the nonlinear distribution in thermal bias observed in these marine communities. This pattern awaits testing for consistency in other taxa, and the potential mechanisms that establish it require further exploration. The assumption that a species is 'optimized' for its thermal midpoint also needs further experimental or empirical verification, although the authors provide evidence to support it.

Of course, a thermal bias in a community may not represent anything more than an assortment of species with wide thermal ranges, indicating low susceptibility to warming. To move beyond an index of bias and towards an estimate of vulnerability, a measure that accounts for the upper limit of each organism's temperature tolerance must instead be determined. Stuart-Smith et al. define the upper limit as the 95th percentile of its thermal distribution; thus, for a species with a 95th percentile of 28 °C, 95% of individuals would be found below this temperature. The authors then define a measure for each community, called the CTImax, as the mean of the 95th percentile of each species in the community (Fig. 1).

Sites with a CTImax close to the summer water temperature are likely to contain many species living perilously close to their thermal limits. The authors encapsulate this in a vulnerability metric, which is defined as the proportion of species at each site that have an upper thermal limit lower than the mean summer water temperature. Projecting temperatures forward 100 years to 2115 using climate models from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC)4, they predict that one-third of surveyed ecoregions will have all species living at temperatures greater than their upper thermal limits — a stark indication that these individuals must move, adapt or perish.

Will all individuals of those species in these ecoregions die? Not necessarily. Just as correlation does not imply causation, vulnerability does not imply extinction. Many species may have greater plasticity or ability to respond to change than we anticipate. Stuart-Smith and colleagues' study also does not take into account the complex interactions between species, perturbations of which may propagate in unpredictable and complex ways. Other potential biasing factors include the authors' use of the IPCC's most-extreme climate scenario (RCP8.5), and the fact that some other anthropogenic impacts will act synergistically. And as communities reorganize, species may move in as well as out and total species richness thus be unaffected — or even increased.

Nonetheless, the CTImax takes into account organismal physiology rather than just levels or rates of environmental warming, and as such may move us a step closer towards understanding the effects of warming on entire assemblages. Indeed, Stuart-Smith et al. find that the sites projected to lose the most species are those with a more negative thermal bias, rather than those with a high magnitude of warming. This suggests that using environmentally based metrics of warming (see ref. 5, for example), without taking species characteristics into account, may be insufficient for characterizing vulnerability. An obvious next step is to test Stuart-Smith and colleagues' approach with other taxa to see whether similar patterns emerge. However, under-sampling of species ranges could give the impression of an artificially narrow niche. The picture provided is only as good as the data underlying it, which may limit broader application of this metric.

The response of ecological communities to climate change is undeniably more complex than any single value can reveal. Suites of metrics are used by international policymakers to track the status of biological communities in response to anthropogenic change6, and metrics that encompass biological traits may add valuable information. In conjunction with modelling efforts that incorporate species interactions (see, for example, refs 7 and 8), a scaffolding of understanding, or at least plausibility, can be constructed. Stuart-Smith et al. have contributed a tool that could help us to reach this goal. But in a world in which marine and terrestrial ecosystems face accelerating pressures9, our ability to respond, protect and sustain remains precarious.Footnote 1


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Correspondence to Derek P. Tittensor.

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Tittensor, D. Ecosystem vulnerability to ocean warming. Nature 528, 43–44 (2015).

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