Everything but the kitchen sink? Combating species extinction using multiple functional traits
The present biodiversity crisis should come as no surprise to conservationists and ecologists alike, but an often unacknowledged aspect of the increasingly rampant number of extinctions– both local and global – is that we are losing different kinds of species. The non-random demise of large-bodied, slow-reproducing apex predators, for example, is well-known, but the ecological information in these terms – ‘large-bodied’ vs. ‘small-bodied,’ ‘slow-reproducing’ vs. ‘fast-reproducing,’ and so on – are not often invoked in biodiversity research. Instead, we simply treat species as equally different, with little regard for the degree of separation between them.
One solution is to actually incorporate information on such ‘functional traits’ in descriptions of biodiversity. So-called ‘functional diversity,’ the component of biodiversity related to the range of roles that organisms can play in communities and ecosystems based on their traits, promises to greatly enhance our understanding of the natural world.
There is a growing desire to apply functional traits to a wide variety of systems and organisms. The roadblock is that many systems and organisms are poorly studied, both in terms of their ecology and natural history. So what’s a researcher to do?
In our comment, published in Environmental Conservation, “Choosing and using multiple traits in functional diversity research,” we outline several strategies for those who wish to use functional traits in their own system. We focus on practical scenarios to supplement existing advice, which often – and frustratingly – assumes an omniscient and pre-existing knowledge of the study organisms. Our recommendations are based on consideration of both philosophical and quantitative questions, and are summarised in the following flowchart:
In some situations, we argue that more is better, in that integrating across multiple traits may actually be able to account for imperfect, coarse, or imprecise knowledge – the ‘safety in numbers’ principle. For example, predictions derived across multiple functional traits have recently been shown to be more accurate than those from any single trait. Measuring multiple traits may also safeguard against changing goals or new priorities, sparing researchers and managers from looking back and saying, “I wish I had…” Finally, casting a wide net can help winnow down traits of particular importance, helping guide future applications.
On the quantitative side, however, we ask researchers to resist the temptation to toss in everything and the kitchen sink. As with any mathematical construct, care should be taken to include only relevant and non-redundant information in calculations of functional diversity. We show that many common functional diversity metrics are sensitive to both the number of and correlations among traits, implying that lots of redundant traits may make it harder to tease apart differences among ecological communities, management regimes, etc. These same metrics have also been shown to misbehave when confronted with gaps in the trait data (i.e., trait values that are missing for some species) so care should be taken to only include traits for which information is actually available. Finally, we highlight some recent examples where trade-offs among individual traits – where some traits are positively related to the response of interest, and others and negatively related – or lots of noisy, uninformative traits, can obscure overall patterns. Thus, we also recommend a thorough investigation of each trait as well as a composite index.
Functional traits have the potential to provide extraordinary insight, but like any tool, they can be misused if one is not careful. We hope that our recommendations will make researchers stop, outline their goals – including any future scenarios – and think critically about how each and every trait will illuminate the overall picture.