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Climate change is speeding up the timing of plants growing & flowering. It’s an old trope we’re all used to hearing by now. Spring warms up earlier, and plants shift their timing – their phenology. This shift in phenology is going to have big consequences for things like agricultural production, the ability for wildlife to find food, the ski season, etc. Important, right? Something we might want to predict. So, we’ve been running experiments for years, looking at climate change scenarios, and finding out how much earlier plants will do their thing, and we’ve gotten some pretty good results.

Or have we.

New work published online in Nature by Lizzie Wolkovich and colleagues (go-go NCEAS working group headed by a former postdoc!) shows that…ah, hell, I think I can summarize it with their figure 2.

Basically, after collecting an enormous database of changes in leafing and flowering times in both experiments and what has been observed out in the world, we’ve found that experiments UNDERPREDICT how sensitive plants are to climate change.

That’s right. Something has moved these plants to leaf and flower ever EARLIER than predicted. Climate change’s effects on plans are even STRONGER than we’d predict from simple warming experiments.

To me, this suggests a whole lot of interesting directions – why are things moving even earlier? What indirect effects is warming having on the Natural world that might speed up plant timing? What crazy interactions are there that we’re missing when we try and isolate out just one signal of climate change?

It’s a little disheartening – we canot predict climate impacts on Life on Earth from changes in one or two simple variables – and a little scary – we have only begun to understand the impacts of climate change. But I think it’s fascinating in that it suggests we really need to understand the how the complex system of nature is going to be affected by climate change to alter even the most basic properties of the world around us.

Wolkovich, E., Cook, B., Allen, J., Crimmins, T., Betancourt, J., Travers, S., Pau, S., Regetz, J., Davies, T., Kraft, N., Ault, T., Bolmgren, K., Mazer, S., McCabe, G., McGill, B., Parmesan, C., Salamin, N., Schwartz, M., & Cleland, E. (2012). Warming experiments underpredict plant phenological responses to climate change Nature DOI: 10.1038/nature11014

Just over a year and a half ago, I was lucky enough to be in a room with some of the world’s top authorities on the consequences of species loss at the National Center for Ecological Analysis and Synthesis. We were worried. When Brad Cardinale asked, “So, where does diversity loss rank? As important as climate change? Rampant nutrient runoff from agriculture? I mean, come on, how important is it, really?”, none of us knew the answer.

But now we do.

As our group has just published in Nature, species loss matters quite a bit – as much as many of the major drivers of environmental change.

Let me back up. As species continue to go extinct across the globe, one has to ask – will there be any consequences? We’ve spent the last 15 years answering this question, and it is, yes. Losing species, at the bare minimum, reduces the ability of fields of plants or algae to most efficiently turn sunlight and nutrients into new production. Losing some of the myriad of species responsible for munching their way through dead detrital material will slow that whole process down. More questions remain, but diversity loss seems to be altering a wide variety of ecosystem properties.

But how important is that loss, really? In the grand scheme of climate change, pollution, and other forms of environmental change, is losing species important? Or is it just the icing on the cake of environmental degradation?

Realizing that there was no good answer to this, we sat down, rolled up our digital sleeves, and got to work. Led by the ever steady Dave Hooper and always insightful Carol Adair, we began to dig into the literature – to see what information was out there about the impacts of these different forms of environmental change. We were armed with the hugely revised and updated version of Brad’s monster database (in no small part due to the Epic efforts of the unflappable Kristin Matulich at UC Irvine) documenting nearly every experiment that has measured the consequences of diversity loss ever conducted. Most of the data was from experiments describing changes to plant or algal productivity & decomposition. So we had a starting point.

How will diversity loss compare to the plethora of other forms of environmental change in altering these basic processes?

The answer came from what we called the Meta-Meta. (Come on, say it 10 times fast). We assembled a huge database of meta-analyses – statistical summaries of previous experimental results much like our own diversity set – that examined the effect of, say, nutrient addition or warming on plant productivity and decomposition. Carol then did some statistical wizardry, calculating bootstrapped effect sizes of each from these previous meta-analyses. Hence, we had Meta-Meta-Analytic results that we could compare with our own meta-analytic results. There was a lot of meta.

But we had a problem. The measurements in our diversity experiment database looked at the consequences of having 1 species versus many species in a plot for productivity. That number of ‘many’ species varied from experiment to experiment. And, besides, what’s the right diversity loss scenario to compare to climate change. 10% species loss? 50%? 95%? Only 1 last species left, clinging tenaciously to the earth?

We actually argued about this for a long time as only scientists can when they want to get something dead-on right. But the solution ended up being delightfully elegant.

Why not look at the whole range of species loss scenarios. Bruce Hungate, Carol, Dave and I figured out a way to look at slices of the data that simulate some relevant range of species loss and applied a nonlinear model shown to fit species loss data quite well to generate a loss-productivity curve. The curve showed that, if you lose a few species, meh! Some productivity is lost, but no big whoop. But as you start losing more and more, the problem of species loss starts to compound. Like the interest rate from hell, more species lost means exponentially more plant production lost.

We still struggled with visualization (hey, infographics people, any ideas), but the figure that we ended up producing I think gets the point across nicely.

So, now you can compare the effect of some environmental change to some percentage of species loss. For example, ~50% species loss has an equivalent impact to dousing a plot in acid rain.

Of all of the types of environmental change out there, a lot of them are roughly equivalent to between 30-70% species loss for production and decomposition. And, some additional review work we did showed that predictions of local extinctions (i.e., within a plot) range pretty widely, but, the upper end of that range is ~41-60% – so, right in our range of observations.

“Oh-ho!”, I hear some of you saying (and some in the group said – I’m looking at you, Lars). “Aren’t the effects of environmental change in your Meta-Meta actually including any loss of species in experiments? I want a cleaner result!”

Well, we thought of that.

Kristin, Dave, and I did some data-sorting kung-fu on the diversity experiment data set, and turned up several studies that not only manipulated species number, but also crossed that with a manipulation of some form of environmental change – things like drought, nutrient enrichment, and more. This was a much smaller set of data, and a smaller set of environmental change manipulations. But, the results are compelling, and show that we’ve got the story right.

Those careful factorial crossed experiments show that once the diversity signal is taken out, the size of many of those environmental effects gets smaller relative to diversity. For example, the average effect of a CO₂ increase is of the same magnitude as 20% species loss (although opposite in sign). The effect of drought, one of the biggest from the Meta-Meta, drops waaaay back as well – although for both of these, the confidence intervals overlap 0 due to low sample sizes (and the 2 or the three drought datapoints come from mosses, so, more factorial experiments are needed!). Still, it’s pretty darned suggestive that there are some interesting indirect effects hidden in the meta-meta.

At the very least, the experimental data pretty clearly backs up the conclusion that loss of species appears to have effects on primary productivity that is similar to other sources of environmental change. And more intriguingly, it suggests that if environmental change ALSO causes loss of species, ecosystem functions like productivity are going to get hit with a 1-2 punch.

The team noted a few caveats and open questions to this. When multiple kinds of environmental change were present – say, multiple kinds of fertilizers – the effects are way stronger than diversity loss. But we don’t have a great handle on those kinds of synergistic effects overall. We also don’t know how they’ll affect diversity and then indirectly alter function. Also, because we were working with meta-analyses, we don’t have, say, the ability to compare 30% species loss to a 30% increase in temperature, or something comparable. It would be awesome to be able to compare two continuous curves, but we’re not there yet. Our results (deep inside the supplement) also show that composition – which species go extinct – can matter a great deal. But that was ancillary to our overall question of diversity loss. And there’s all sorts of ancillary questions about scaling and interaction between diversity loss and environmental change – but that’s work that Andy Gonzalez and Mary O’Connor are following up on in a massive multilevel modeling extravaganza.

Overall, we felt like this told a pretty tight story. Sure, as we came up with question after question, we accumulated a lot of figures and explanatory materials that made their way into the supplementary material, but the big story was pretty clear and compelling. In working group meeting 3, we really shaped this sucker, and then bounced revisions back and forth, wrenching the text back and forth. I’ve never been part of such a large collaboration (save for our earlier first paper), so it was an inspiring process to see big ideas hashed out, thrown aside, revised, and made into clearer cleanly crafted pieces all on the screen of my word processor.

I’m pretty psyched that the paper is now out, and I hope you all enjoy it as well. There’s more to come from the working group, so stay tuned!

(Oh, and, final note – to anyone who wants to look at this data, or for R-nerds who want to see how we created these awesome figures, it’s all available here.)

References
Cardinale, Bradley J.; Matulich, Kristin L.; Hooper, David U.; Byrnes, Jarrett E.; Duffy, Emmett; Gamfeldt, Lars; Balvanera, Patricia; O’Connor, Mary I.; Gonzalez, Andrew. 2011. The functional role of producer diversity in ecosystems. American Journal of Botany. 98:572-592. 10.3732/ajb.1000364

Hooper, David U., Adair, E. Carol, Cardinale, Bradley J., Byrnes, Jarrett E.K., Hungate, Bruce A., Matulich, Kristin L., Gonzalez, Andrew, Duffy, J.E., Gamfeldt, Lars, O’Connor, Mary I. 2012. Biodiversity loss ranks as a major driver of ecosystem change. Nature. 10.1038/nature11118