There’s a lot of grist for the mill here – what is the roll of post-publication peer review, do we have an efficient system to conduct it, can we do better, and if so, how (and how can we do it simply instead of having to build some whole new platform)?
Take a gander, and I’d love to hear more of your thoughts about how we can better accelerate the pace of the scientific discussion in an efficient way.
A service that is travelling along similar lines of what I’m interested in for open publishing has launched today. PeerJ is being pitched as a cross between PLoS ONE and arXiv and indeed the company was founded by former PLoS ONE and Mendeley folk. It’s an interesting model where authors signup with a pre-paid plan. $99 gets you unlimited public preprints and 1 peer reviewed paper per year. $169 adds unlimited private preprints and another paper per year. $259 ups you to unlimited publications. And its nice as you can chose to pay once your paper is accepted (see how it works) so an author isn’t just being fleeced. There also appear to be reasonable plans for large numbers of co-authors etc. They also require members to review once per year. Nice.
I’m still reading through all of the materials about it myself, and there’s a lot here to digest and meditate on. It still appears that review is not open – both before and after ‘publication’ – although you can publish the review-trail and previous versions along with the finished product if you’d like. But in general, this is pretty fantastic
SciFund Round 2 is now complete, and it pulled in $100,345 for science! 43% of the projects achieved 100% or more of their goal – almost double of round 1 – and 60% of all funds asked for were secured. Numerous projects that didn’t fully reach their goal were above 80%. A TON of great research is going to come out of this, and I am excited!
Science crowdfunding continues to grow as a viable source of research fund. To explore this further, Jai and I participated in an online hangout for SciLingual and discussed science crowdfunding with Liz Neeley, Jerry Nguyen, and the folk from Microryza. A lot of interesting stuff came up, so I’m posting the video of the even below for you all to checkout. If you’re new to the idea of science crowdfunding, or want to learn some of the nitty-gritty, check it out!
Allright, folk! The final documents have been signed, sealed, and delivered. Looks like I’ll be starting a position as an Assistant Professor in the Department of Biology at UMass Boston in the fall. That’s right, soon the Byrnes Lab is going to become a reality. Get ready, Science, because this is going to be an adventure!
Happy Friday, everyone. To celebrate the end of the week, I leave you with what is hands down my favorite #SciFund video from round 2. And I don’t just say this because it was made by a collaborator of mine of the #SciFund paper that we happen to be editing right this very moment (or, in half an hour or so). I say this because it is a beautiful example of the fusion of (silly) Art and Science. That it is my favorite from a sea of awesome videos also says a lot about how my brain works, but more of that another time.
The project is called Beach of the Goliath Crabs by the ever amazing Dr. Zen Faulkes. The project itself is pretty awesome – looking at environmental and evolutionary drivers of gigantism in the teeny tiny Lepidopa benedicti . It’s a great project with a GREAT video channeling Godzilla and other classic Japanese monster movies. Definitely worth kicking in a few bucks to make this research happen (and it won’t even take very many of those bucks to hit Zen’s goal!)
Awesome, yes? Worth funding just for the video. And you get hot Science to boot!
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.
Results from a meta-analysis showing sensitivity to warming in experiments and what we've observed. Panel a shows all plant species, b is just those that are in both the observed and experimental data sets.
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.
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.
Will losing one or more of these algae matter as much as the rapid rise in global temperature?
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?
What would results from experiments like this one with flumes full of many different combinations of algae tel us about how diversity and the environment both shape primary production?
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.
Changes in primary production as a function of per cent local species loss or the application of an environmental change treatment. The line with the confidence interval around it shows the effect of diversity loss. The think no-CI curve is its mirror image so that we can easily compare effect magnitude to types of environmental change that differ in the sign of their effect. Anything in red is a negative effect on productivity. E.g., drought and diversity loss both have negative effects. Anything in blue is a positive effect. E.g., if you add nitrogen and phosphorous, you boost productivity by quite a bit. Y-axis is in units of log response ratios. Any designers in the house with an even slicker way of presenting this, email me!
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.
Figure S4 from the supplement. All is as it was before in the above figure, but, this data is from experiments that cross changes in number of species with one or more other forms of environmental change.
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!
The working group at our first meeting.
(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.)
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
Woohoo! #SciFund 2 is off to the races! I am in awe of the nearly 70 scientists who have put their work up for your enjoyment. I’ll be featuring a few marine projects in the next few days, but, for now, get on over there, check it out, and help us crowdfund some amazing science!