In a recent study, published in the journal Global Ecology and Biogeography, we investigate the evolution of leaf morphologies and climatic niches in the Proteaceae family. Proteaceae is a Southern Hemisphere family famous especially in Australia and South Africa for their impressive flowers and leaves. They are also tasty – the macademia nut belongs to the Proteaceae as well. Species in the Proteaceae family occur in all kinds of habitats, from montane forests to dry heathlands to tropical rainforests. During their evolution over millions of years, they managed to adapt to these variable and extreme habitats and climates, and their leaves may have helped them doing so. In this study we test whether open (e.g. mediterranean) and closed (e.g. tropical rainforest) habitats have selected for divergent leaf designs. We also show that the combination of certain leaf traits (e.g. small, sclerophyllous leaves with many teeth) in interaction with certain climatic niches (e.g. warm, dry, mediterranean) may increase diversification rates. This could explain some of the spectacular radiations within the family, for example in genus Banksia in Australia, or the Protea in Africa. Last, we show that there is more stochastic evolution of traits and niches in open habitats, which may explain some of the extreme forms and ‘misfits’ we find here. This “disparification” maybe even led to the process of reproductive isolation and speciation, via ecological divergence, and the ~1700 species of Proteaceae we find on Earth.
Onstein, R.E., Jordan, G.J., Sauquet, H., Weston, P.H., Bouchenak-Khelladi, Y., Carpenter, R.J., Linder, H.P. (2016). “Evolutionary radiations of Proteaceae are triggered by the interaction between traits and climates in open habitats.” Global Ecology and Biogeography 25 (10):1239–1251. doi: 10.1111/geb.12481
Pyrops candelaria in Borneo
New video on rain forest evolution – and why we need the field of evolutionary biology to understand (and possibly change) their fate. Current threat by humans is increasing – but we don’t know how species will adapt, move, evolve. To have a better idea, we need to know which processes have influenced their evolution in the past. Using (phylo)genetics, ecology, functional traits and species distribution modelling we may better understand this.
Tarsius bancanus in Borneo
If selected, this video will be shown at the Evolution meeting in Austin, Texas, this June – I won’t be there, but please vote if you are! Thanks!
Watch the video here.
Yaowu Xing and colleagues (Maria A. Gandolfo, Renske E. Onstein, David J. Cantrill, Bonnie F. Jacobs, Gregory J. Jordan, Daphne E. Lee, Svetlana Popova, Rashmi Srivastava,Tao Su, Sergei V. Vikulin, Atsushi Yabe, and H. Peter Linder) just published an article presenting the CAD (Cenozoic Angiosperm Database): Testing the Biases in the Rich Cenozoic Angiosperm Macrofossil Record in International Journal of Plant Sciences. The database is available from http://www.fossil-cad.net/.
The angiosperms currently have approximately 350,000 species, but how have angiosperms achieved such a high diversity? This question has bothered evolutionary biologists for centuries. The fossil database allows us to understand diversity changes in the past. Especially for angiosperms little is known about the temporal dynamics of species, lineage diversification and richness. It is structured by site (geographical information for each fossil assemblage), geology (name, age, epoch and stages of the formation), taxon (identification reliability and nearest living relatives of each taxon) and taxonomy. We hope that researchers will use the database to understand macro-evolutionary processes in angiosperms – possibly combining data from the database with inferences made from molecular phylogenetics.
For any questions concerning the database, contact Yaowu: yxing (at) fieldmuseum.org.
Wageningen University, credit: JD Santillana-Ortiz
Last week I traveled back to my scientific roots (Wageningen University) to participate in a course on Structural Equation Modeling (SEM) given by Bill Shipley (he is particularly well known from his book on ‘Cause and Correlation in Biology‘). Structural Equation Models can be used to evaluate the sequence of variables affecting each other, and whether the underlying data supports such a sequence of events (also called path-models). For example – ecosystem functions (e.g. productivity and decomposition) can be affected by the biomass of the vegetation, and this can be affected again by the age of the plot (e.g. during succession) (Lohbeck et al. 2015).
As an evolutionary ecologist I was a bit of a misfit in the group. The group was dominated by Dutch PhD students and professors working in ecology (e.g. functional ecology, community assembly, soil science). They often collect data from plots; data which fit perfectly well in a structural equation model. My data did not – for a couple of reasons. My ‘plots’ are fossil assemblages (species richness = count data, problem 1), collected during the Cenozoic (different time scales, problem 2) and the variables we have are often not assemblage-specific but biased by time, and not normally distributed (e.g. CO2 concentration, temperature, latitude). On the positive side – I have a large sample size (N=666), which is necessary to have enough power to run these SEMs. So how can I test what factors directly and indirectly affect biodiversity (species richness)?
The solution. There is a solution. If your data is spatially, or phylogenetically biased, if your variables are not normally distributed, if you deal with binary/categorical/count data, if you have a nested design… The solution is the d-separation test. (d-sep cannot deal with ‘latent’ variables, e.g. unmeasured variables which may be important for the model).
d-separation in 6 steps:
- your hypothetical model (DAG: “Directed Acyclic Graph” avoid feedback loops in the model!) (for simplicity: A<- B <- C)
- write down each pair not connected by an arrow (in our example only AC)
- causal parents of these? (i.e. causal parent of A = B and of B = C. In our example of AC there is just one causal parent: B)
- run a suitable linear model/generalized linear model/PGLS/mixed model in which you test the effect of your pair variables, conditioned on the parent variables, in our example, of C on A conditioned on B (A ~ B + C)
- sum the probabilities (p values) of the slope coefficients of the regressions (in this case only one regression model was run, and we asses the coefficient of C and it’s p-value)
- calculate the C-statistic: -2 * ln (the sum calculated in step 5) and compare this to a Chi-square distribution. The degrees of freedom are calculated by 2* the number of regressions run (in our case 2 degrees of freedom). If p>0.05, you cannot reject you hypothesized model. If p<0.05 your data do not support the model.
All analyses can be performed in R using packages ggm and lavaan. credit: JD Santillana-Ortiz
Thanks to the d-separation test we, evolutionary biologist, can still test for causal relationships in our data, even if these data are far from ‘perfect’ or complete. It provides great potential for the field of phylogenetic comparative methods. But how exactly I’m not sure yet….
Madelon Lohbeck, Lourens Poorter, Miguel Martínez-Ramos, and Frans Bongers 2015. Biomass is the main driver of changes in ecosystem process rates during tropical forest succession. Ecology 96:1242–1252. http://dx.doi.org/10.1890/14-0472.1
The research team (left to right, top to bottom): Jeisin Jumian, Renske Onstein, Hervé Sauquet, Thomas Couvreur, Postar Miun, Joel Dawat, Tawadong Tangah, Aloysius Laim
To study and collect fruits, flowers and leaves of Magnoliales species, Hervé Sauquet, Thomas Couvreur, and I traveled to Sabah, Borneo. We just came back from a very successful trip in which we were amazed by the diversity of Magnoliales in the (mainly lowland) rainforests, and in particular the diversity of flowers and fruits of species belonging to the Annonaceae and Myristicaceae families. These collections wouldn’t have been possible without the help and expertise of our local team from the Forest Research Center (Sabah Forestry Department) in Sepilok.
For a short (informative and entertaining) summary of this trip, watch the video I made.
frugivory in the Atlantic rainforest, Brazil
I am currently doing a postdoc in the Sauquet lab at the Université Paris-Sud. In collaboration with Daniel Kissling, Hélène Morlon, Thomas Couvreur, Lars Chatrou and Hervé Sauquet, I study “Frugivory, functional traits and the diversification of a tropical angiosperm family: Annonaceae (Magnoliales)”.
For a 1 minute summary of the project- watch this video.
In short –
Frugivory (i.e. fruit-eating and seed dispersal by animals) is ubiquitous in tropical ecosystems, but the role that frugivores have played in the macroevolution of species-rich tropical plant families remains largely unexplored. This project will investigate how plant traits relevant to frugivory (e.g. fruit size, fruit color, fruit shape, understory/canopy growth form, etc.) are distributed within the angiosperm family of custard apples (Annonaceae), how this relates to diversification rates, and whether and how it coincides with the global biogeographic distribution of vertebrate frugivores (birds, bats, primates, other frugivorous mammals) and their ecological traits (e.g. diet specialization, body size, flight ability, etc.). Annonaceae are particularly suitable because they are well studied, species-rich (ca. 2400 species), characteristic in all tropical rainforests, and dispersed by most groups of vertebrate seed dispersers. Using a phylogenetic framework and functional trait and species distribution data we will test (i) how fruit trait variability relates to phylogeny and other aspects of plant morphology (e.g. leaf size, plant height, growth form, floral traits) and animal dispersers and their traits, (ii) to what extent interaction-relevant plant traits are related to diversification rates, and (iii) whether geographic variability in fruit traits correlates with the biogeographic distribution of animal dispersers and their traits.