Global demography in the animal kingdom

Today the paper that introduces the COMADRE Animal Matrix Database was published in Journal of Animal Ecology (Salguero-Gómez et al. 2016). This is an international effort in collaboration with ca. 10 other institutions. Our main goal was to replicate the impact that its sister database, the COMPADRE Plant Matrix Database (Salguero-Gómez et al. 2015) has had for plant ecology and evolution, but in the rich animal kingdom. Open access to the database itself can be gained from the COMADRE website.

comadre logo

Matrix population models have become one of the most widely used demographic tools among ecologists and evolutionary biologists. Indeed, a matrix model has the capacity to pack rich information (e.g. stage-specific rates of survival, ageing/growth/development and reproduction for various populations, years, treatments and species) into a simple, tractable array of numbers, from which one can relatively easily to track back to the life cycle of the species of interest. Matrix models have “exploded” in the animal ecology literature. A proof of this is that I receive an average of five new publications containing matrix models every week in the automatic search engine alerts that I use to incorporate new information into COMADRE. I argue that this growth is primarily due to two reasons: (i) their versatility and ease of computation for informative biological output, which has resulted in studies exploring questions as diverse as the role of density dependence on population dynamics of grey wolves (Miller et al. 2002), estimation of individual fitness (McGraw & Caswell 1996), or estimation of risk of extinction (Morris & Doak 2002); and (ii) the push for new methods (Caswell 2001) and analytical packages (See this MEE blog by Satu Ramula), which have further encouraged the non-formal demographer to approach these tools with open arms. Indeed, matrix population models exist for all sorts of species, such as roundworms, American black bears, northern pike peregrine falcons, or even for us humans.

Imagine how powerful it would be to have all that information at the reach of your fingertips… ah, and free of license agreements! With information of this type, researchers could provide some potentially very interesting insights into how past and future climatic projections have affected and may affect population viability of major groups currently in peril of extinction (e.g. amphibians), or test how proximity to human settlements may disrupt population dynamics worldwide, to mention a few. The potential is undeniably high, but the limitation to date was the fact that the data remained dispersed throughout dusty library shelves (e.g. MSc and PhD theses), journals, books and scientific reports.

Big data without organization and cross validation is worth nothing. Under this premise, during the last five years I have led a team of diligent researchers and student helpers at the Max Planck Institute for Demographic Research. The task at hand has been (and continues to be) to find, digitize, error-check and supplement the demographic information contained in matrix population models with additional information regarding the biogeography, taxonomy and ecology of the study species. We refer to them as the “compadrinos”, and they are the true rockstars making first COMPADRE and now COMADRE happen.

 

team

The compadrino team

 

In its first version, COMADRE v 1.0.0 contains 1,625 matrix population models from 345 taxonomically accepted animal species, sourced from 402 studies. But COMADRE is way more than just the actual matrix models. For each study, we have carefully supplemented the demographic information with ecological aspects of the species, its life cycle, its corrected taxonomy, and information about the biogeography of the studied populations. It is our belief that by providing such a rich context, the users will be able to address broad, timely macroecological and comparative questions in the animal kingdom.

Naturally, there are more matrix models in the literature, and we will be releasing more open access information from what “we have got in store”. The remaining information has not yet been released because it needs to be error-checked, or supplemented with ancillary information, or because it has been given to us under an embargo agreement by the authors. Users are welcome to take a sneak peek at what we currently have in store for COMADRE. If they find that a study is missing from that list, they are welcome to send it to us at compadre-contact@demogr.mpg.de.

Authors in Journal of Animal Ecology have provided some fundamental insights to the amazing world of animal population dynamics, and many of these works have been facilitated by matrix population models, including work on common stern (Szostek et al. 2014), ring ouzel (Sim et al. 2011), Canada lynx (Row et al. 2014), or stoat (Wittmer et al. 2007). However, I argue that we need to broaden our taxonomic and geographic outlook (below) to improve our understanding of what makes up and shapes animal life histories and their population dynamics. The data in COMADRE have been entered with no priority, and they thus represent an objective sample of the state of the art in animal demography. The number of studies that focus on mammals, birds, amphibians and reptiles is truly overwhelming, as it is the strong bias for field sites in North America, Europe, Kenya and Australia.

Pie chart croped

Proportion of taxonomic groups represented in the database

Many of these studies have provided important insights to the demographic characteristic of those groups and regions. However, the animal kingdom is more than four-legged species based in developed countries. For instance, it is particularly interesting to me that, even though matrix models lend themselves particularly useful for life cycles with discrete stages, as it is the case in insects, and despite the large taxonomic diversity of this group, only a handful of insects exist for which matrix models have been parameterized (but see Radchuk et al. 2013). The same is true for sessile, marine organisms such as corals and sponges. I’d like to take this opportunity to encourage researchers who may not have a preference in the type of organism they choose to address their demographically-related questions to choose an underrepresented taxonomic group. Think invertebrate, possibly slimy, and you’ll be on the right track to make an important contribution to our current understanding of animal demography!

Map_croped

Number of population matrix models per country

I must also make a call for caution against the blind usage of these data. Although my team and I have done significant amounts of (yep, rather tedious) error-checking, the data are likely not free of errors. Users are encouraged to contact us at compadre-contact@demogr.mpg.de to report potential typos and errors.

Future versions will be released periodically at www.comadre-db.org, and more R functions will continue to be developed in our GitHub repository. Buen provecho!

Dr Rob Salguero-Gómez
DECRA fellow of the Australian Research Council
Guest visitor of the Max Planck Institute for Demographic Research
Associate editor of Journal of Ecology

References

Caswell H. 2001. Matrix population models: construction, analysis and interpretation. Sinauer Associates.

McGraw JB, Caswell H. 1996. Estimation of individual fitness from life-history data. The American Naturalist 147, 47-64.

Miller DH, Jensen AL, Hammill JH. 2002. Density dependent matrix model for gray wolf population projection. Ecological Modeling 151, 271-278.

Morris WF, Doak DF. 2002. Quantitative conservation biology: theory and practice of population viability analysis. Sinauer Associates.

Radchuk V, Turlure C, Schtickzelle N. 2013. Each life stage matters: the importance of assessing the response to climate change over the complete life cycle of butterflies. Journal of Animal Ecology 82, 275–285.

Row JR, Wilson PJ, Murray DL. 2014. Anatomy of a population cycle: the role of density dependence and demographic variability on numerical instability and periodicity. Journal of Animal Ecology 83, 800-812.

Salguero-Gómez R, Jones OR, Archer CA, Buckley YM, Che-Castaldo J, Caswell C, Scheuerlein A, Conde DA, Baudisch A, Brinks E, de Buhr H, Farack C, Gottschalk F, Hartmann A, Henning A, Hoppe G, Römer G, Runge J, Ruoff T, Wille J, Zeh S, Vieregg D, Altwegg R, Colchero F, Dong M, Hodgson D, de Kroon H, Lebreton J-D, Metcalf CJE, Neel M, Parker I, Takada T, Valverde T, Vélez-Espino LA, Wardle GM, Franco M & Vaupel JW. 2015 The COMPADRE Plant Matrix Database: an online repository for plant population dynamics. Journal of Ecology 103, 202-218.

Salguero-Gómez R, Jones OR, Archer CA, Bein C, de Buhr H, Farack C, Gottschalk F, Hartmann A, Henning A, Hoppe G, Römer G, Ruoff T, Sommer V, Wille J, Zeh S, Vieregg D, Buckley YM, Che-Castaldo J, Hodgson D, Scheuerlein A, Caswell H, Vaupel JW. 2016. COMADRE: a global database of animal demography. Journal of Animal Ecology DOI: 10.1111/1365-2656.12482.

Sim IM, Rebecca GW, Ludwig SC, Grant MC, Reid JM. 2011. Characterizing demographic variation and contributions to population growth rate in a declining population. Journal of Animal Ecology 80, 159-170.

Szostek KL, Schaub M, Becker PH. 2014. Immigrants are attracted by local pre-breeders and recruits in a seabird colony. Journal of Animal Ecology 83, 1015-1024.

Wittmer HU, Powell RA, King CM. 2007. Understanding contributions of cohort effects to growth rates of fluctuating populations. Journal of Animal Ecology 76, 946-956.

Advertisements

One thought on “Global demography in the animal kingdom

  1. Pingback: Demography Beyond the Population | Animal Ecology In Focus

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s