The problem of pattern and scale in ecology: what have we learned in 20 years?

Jérôme Chave, early view. Ecology Letters. DOI:10.1111/ele.12048. The problem of pattern and scale in ecology: what have we learned in 20 years?

Below, we give our first impressions of this article. Please comment below, or tweet Will or Lynsey (maybe use #pegejc). Think of this as a journal club discussion group!


Will Pearse

Will Pearse

I am not a field ecologist, and I downed quadrats and upped my laptop because of the two papers Chave repeatedly cites in this paper: Lawton (1999) and Levin (1992). These papers made me see there was a place for biologists who looked across taxa, space, and time, to find general rules in ecology. This paper demonstrates just how far ecology has come in a little over two decades, and left me with an awful lot of hope for the next two. There’s a lot of material in this paper, and (judging by the sections I think I know something about) it’s all been very deeply considered.

Chave’s review almost operates in reverse of Levin’s paper. He starts with the eco-evolutionary problems that Levin left until the end, presumably because what was an exciting possible avenue in 1992 has now become an exciting reality in 2013. I encourage anyone who feels Chave overplays the importance of computing power to go back to Levin’s review; figure 1 is a 10 x 10 degree grid cell model of the world, and the only colour figure (13) pales in comparison to Chave’s (perhaps bafflingly!) complex reprinted figure 3. Whatever you think of the current vogue for ‘big data’ and complex modelling techniques, I don’t think anyone in 1992 would have predicted the changes that increased computer power, in combination with the open source R ecosystem, would bring. We are beginning to tame the complexity Levin hoped we could explore.

Which is why I would have enjoyed a discussion of agent-based models, and (perhaps more explicitly, if I missed the subtext) the importance of emergent properties of systems. Agent-based models are an excellent way of using information on individual-level actions to predict higher-level properties of systems, and I feel (as an outsider) are changing the way we look at species movement and dispersal. I’ve been thinking a lot about abstract properties of different kinds of systems (after re-reading this recently) – to what extent can we find general properties of ecological systems, at higher scales (be they temporal, spatial, or something else) that allow us to better predict changes in those systems? What general rules and patterns can we pull out of analyses conducted across multiple scales?

It is this idea of abstraction that made me particularly enjoy Chave’s section on using compartmental analysis to define the ecological niche. I’m not a bacterial ecologist, but I wish I were, because I think it’s almost impossible to quantify any other kind of ecosystem in this level of detail. Finding repeating units (like these network motifs) and using them to infer process falls right into the category of the emergent property driven analysis I mentioned above, and gives hope for definitions of niche that aren’t dependent on traits, environmental tolerances, or phylogeny. Grouping species along niche axes that derive from properties of their organisation, which are more intangible but arguably more real than things we can measure with a ruler, could be incredibly powerful. Despite the risks and potential pitfalls, measuring the niche according to dimensions of species’ own organisation, not what we decide is important a priori and can measure, sounds exciting to me.


Lynsey McInnes

Lynsey McInnes

This paper has been floating around online, hailed as a forthcoming classic. Perhaps. I have to say I’ve read it at least four times now and it doesn’t get any easier. There is absolutely tons of great and thoughtful stuff in here, but sometimes the typos, the poor sentence structure and some logical leaps made extracting that thoughtful stuff quite difficult (at least for me). Anyway, moving on from these critiques and focusing on what I was able to extract from the paper…

Scale matters! Looking back over the four papers Will & I have chosen so far for PEGE, this paper does indeed seem right up our street – turns out we are both a bit taken by processing operating across a range of temporal and spatial scales and seem drawn to studies addressing scale issues head on. So, at the very least, PEGE is helping us identify our research interests.

It is indeed amazing the progress ‘ecology’ has made in the past twenty years and this does seem largely due to access to more data, more computing power and the development of swankier and swankier methods and models. My fear is that progress on these fronts has been too rapid and that data and methods are thrown at sometimes quite vague questions, ‘just because we can.’ I think I might be biased here as this issue might plague my own field – macroecology – more than others (this certainly seems the case from some of the cool study examples outlined here). But, to sound a general note of caution, aimed mostly at myself, take things slow, think about the interesting questions and pursue their answers with appropriate methods and data (not necessarily the most elaborate methods and data).

One of the main messages I did extract from the paper is that biotic interactions matter in understanding species’ ecologies. Whether this in the form of interaction networks, community dynamics or broad-scale diversity patterns, how species’ interact with conspecifics, congeners, competitors, mutualists or across trophic levels matters. Recognising this and quantifying these interactions is going to be crucial in predicting how species and in turn communities will respond to global change. Sprinkle in the potential for rapid evolutionary responses (mostly likely different speeds for different populations/species) and these predictions sound hellishly difficult, but might still be possible.

The second main message was perhaps that a crucial species’ trait to consider is dispersal ability. Debate still rages on what dispersal is, but in terms of scale-dependent processes, it’s central. It can influence population connectivity, species’ range size, species’ ability to track good abiotic environmental conditions and/or biotic interactions and on longer temporal scales can influence rates of speciation and extinction. In short, getting a better handle on dispersal (ability, evolution, variation) will help unify our understanding of species’ distributions (and more).

Lastly, I really appreciated Chave’s call for more crosstalk among disciplines from geneticists to ecologists to earth system scientists, an understanding of emergent patterns will only be gotten from fusing information, techniques and expertise from disparate disciplines. Easy to say, hard to do, no doubt.

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About will.pearse
Ecology / evolutionary biologist

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