For the past few years I’ve been involved in a collaboration to put together a broad-coverage life history database for mammals, reptiles, and birds. The project started because my collaborator, Nathan Myhrvold, and I both had projects we were interested in that involved comparing life history traits of reptiles, mammals, and birds, and only mammals had easily accessible life history databases with broad taxonomic coverage. So, we decided to work together to fix this. To save others the hassle of redoing what we were doing, we decided to make the dataset available to the scientific community. While this post started out as a standard “Hey, check out this new publication from our group” post (Here it is, by the way: Myhrvold, N.P., †E. Baldridge, B. Chan, D. Sivam, D.L. Freeman, S.K.M. Ernest. 2015. An Amniote Life-history Database to Perform Comparative Analyses with Birds, Mammals, and Reptiles. Ecology 96:3109), I’ve realized that there’s something more important that needs to be discussed: what is the future of trait databases?
Trait databases are all the rage these days, for good reason. Traits are interesting from evolutionary and ecological perspectives: How and why do species differ in traits, how do traits evolve, how quickly do traits change in response to changing environment, and what impacts do these differences have on community assembly and ecosystem function. They have the potential to link individual performance with local, regional, and even global processes. There’s lots of trait data out there, but most of it has been buried in papers, books, theses, gray literature, field guides, etc. This has led to the explosion of compendiums compiling trait data. Some of these are published as Data Papers (e.g.: Mammals: Jones et al 2009 , Plankton: Kremer et al 2014) or on-line databases (e.g. AnAge, FishBase), which are open for everyone to use. Many of these open datasets are generated by a small number of scientists to address some particular question. Some are quasi-open/quasi-private resources generated by consortiums of scientists (TRY).
There are a variety of issues regarding these trait compendiums, not least of which is these trait compendiums pull data from numerous sources, but how do data generators get credit and what type of credit is reasonable? This is a doozy that I don’t have an answer to. Instead, my focus today is on the eventual endgame of trait databases. No trait database currently being produced has all the trait data of interest for every species. This means we have a bunch of incomplete data products running around. So, every few years, a bigger – more complete, but still incomplete – trait dataset is produced for some group of species. Sometimes the bigger dataset replicates the effort of the smaller one, sometimes it incorporates the smaller compilation whole-cloth, sometimes they have little overlap in sources whatsoever. Data compilations vary in the ease of use and accessibility. Some databases are widely known, some are known only to a few insiders. I could keep going. Clearly this state of affairs is less than optimal for rapid progress in studying traits.
So what’s the end game here? What should we be doing? In my opinion, what we need is a centralized trait database where people can contribute trait data and where that data is easily accessible by anyone who wants to use it for research (not just to the contributing members of the database). It would also be nice if people who contribute significant amounts of data (no, I’m not going to define that here) could get specific credit for that contribution – maybe as a Data Paper or E-Publication. To encourage people to not just download data, add to it, and then sit on the expanded dataset, embargoes could be put in place to allow people to add their data to the dataset but have the data protected for a limited period of time to allow that researcher to get first crack at the publications using that entry. It’d be really nice if people who use the database could easily download all the references for the data they used so it can be easily incorporated into a literature cited section. The central database could get credit (let’s face it, it needs to be able to justify the funding that such an endeavor would require) by having people register papers published using data from the database. They could then keep track of numbers of pubs and citations to those pubs to help track the database’s impact.
Right about now, my Paleo brethren may be thinking “this sounds suspiciously familiar”. I’ve pretty much lifted this list right off of the Paleobiology Database website (https://paleobiodb.org/#/faq). While ecologists have been running our every database for itself experiment on Trait Databases, the Paleobiologists have been experimenting with collaborative open databases for fossil records. I’m an outsider, so I don’t really know how the database is perceived within the paleo community, but from the outside I have been a big fan of the database, the work that has emerged from its existence, and the community that surrounds it. Which is why I’ve wondered if ecology could some something similar.
But if we’re going to do this, I think we need to copy something else from the Paleobiology Database: a focus on individual records. Currently, many trait databases focus on a species-level value; what is the average number of offspring per litter? Seed Mass? Average body size? This is a logical place to start building a database if many of the questions are focused on comparing central tendencies across species. But our understanding of traits and the questions we want to ask have evolved. Having any info is still better than no info, but often we need info on variability across individuals within a species or we want to know how the trait might vary with changes in the environment. For this, we need record-level data. By this, I mean that instead of pooling observations to obtain an average for a species, we now often want to know that the average litter size for a species at location X is 3 but 8 at location Y. For some species, traits are especially sensitive to temperature or some other environmental variable – so knowing if the body size was measured at 28C or 32C can be important. This data could then be summarized in whatever way the user needed (species-averages, region-specific averages, etc). This, of course, is the hard part, because while we have an increasing number of trait compilations, they have either jettisoned the record information, or little of the record info is associated with the datapoint except maybe the citation name (I say this knowing I’m guilty of this). It also involves doing some form of georeferencing if we want the location info to be useable (like they’ve been doing for museum records). This means we would need to basically uncompile the compilations – find the original citations, extract as much info as we can from them, and then re-enter them as part of a more sophisticated database. This is an extraordinary amount of work that (to be clear) I am not volunteering for.
There are undoubtedly some in the trait community who are about to explode because they’ve been thinking “but we’re doing what you are talking about!”. There are indeed already some bigger initiatives out there (AnAge, FishBase, TRY) but they are either not community-based (i.e. run by a closed group), taxon-centric, or a nightmare of open and closed policies that make extracting data needlessly burdensome, or some unfortunate combo of the above. The one that seems closest to the Paleobiology Database model is TraitBank at the Enyclopedia of Life. Its goal, however, is different from the record-based trait database that I outlined above. Its goal is to have a webpage (and trait data) for every species on the planet, so this still seems to be a species average approach. As I mentioned before, some info is better than no info, so this alone would be a huge benefit to trait research, but still carries the restrictions of species-average values. On the plus side, data in the database is available for everyone to use and each data entry has the specific reference listed with it. But I don’t think it’s had broad buy-in from the trait community. TraitBank only lists 50 data sources and 327 “content partners” (websites/databases that have agreed to share their data via Encyclopedia of Life pages). Admittedly, these sources are some of the biggest data aggregations around, but it’s inconceivable that they cover the wide array of trait info for all of life. Without broad buy-in from the trait community, both using it for research and contributing their data to it, I don’t see this working in the way I’ve outlined above.
So where does this leave us? Well, things are currently in a muddle with respect to trait data, but there’s also tremendous opportunity for someone who can envision the type of database the field needs, sell broad swaths of the trait data community on its importance, and figure out how to build both the database and the community to support and use it. This may involve better community buy-in with TraitBank and/or some new initiative working on a record-level product that would allow a finer-level of question to be asked. The question is how does this happen and is there enough will in the trait community to give up on the current idiosyncratic ad hoc approach and contribute to something with broad trait and taxonomic coverage with an open data policy?