Comparing phenology curves

Packera plattensis, which was found first flowering on April 13 in 2010. 

The timing of flowering is a critical component of the ecology of plants. Flowering during environmentally stressful times or when other plants that utilize the same pollinators can lower a plant’s fecundity if not lead to its extirpation from an ecosystem. As such, the timing of flowering should be under strong selection pressure and be an important component of community assembly. 


Over the past two years, Gene Towne and I (mostly Gene) collected first flowering date (FFD) data on 430 Konza herbaceous species. The last species found to start flowering (a gentian) was found in early October, 189 days after the first herbaceous species--Holosteum umbellatum--was found in late March.


The patterns at Konza are interesting. More on those later. The unexpected find was comparing the patterns with two other predominantly grassland flora. The first was from Chinnor, Oxfordshire. The second, Fargo, ND. 

The y-axis is the fraction of each flora flowering on a given day. x-axis is day of year.


Two things pop out. Relative to Konza, the Chinnor flora has an early tail of species, but not a late tail. Is this because species phenology are all shifted earlier, so that the same species would flower ~50 d earlier there? Or is it just a suite of species that flower earlier are found at Chinnor, but  late-flowering species are not?


And relative to Konza, the Fargo phenology is much more compressed. Again, though, why? Does Fargo not have early- and late- flowering species, or are the phenology of individual species compressed.


Turns out we can begin to answer that and the mechanisms that underly the differences between the pairs differ.


Here are the relationships between FFD between the pairs of sites. Dotted line is 1:1.

Species common to Chinnor and Konza flower on roughly the same day. Hence, one would suspect that the differences in curves between the two sites are due to novel types of species at each site. Yet for Konza and Fargo, early flowering species flower later at Fargo, and late-flowering species flower earlier. Phenology gets compressed for individual species.

Theoretically, I'm still getting up to speed, but comparisons between flora just haven't been done like this. Mid-domain theories are prevalent to test, but each site would support the idea of a mid-domain peak. What's more interesting is why sites differ. Right now, hypotheses about functional novelty/plugging of holes in niche space vs. functional stretching/compression are pretty interesting ones to test here. Flowering is interesting to think about, but the really interesting comparisons (at least for me) will come with comparing functional traits associated with resources, not reproduction.

Konza flowering phenology and functional groups.

In general, we have little understanding of how communities are assembled and the types of interactions that long-term generate evolutionary pressures, extinctions, and radiations. I'm pretty sure that whole-flora analyses are going to be keys to helping us understand these complex systems and there are precious few datasets on the scale necessary to do this.


With that in mind, here's the latest Konza phenology data by functional group. This is through Sept 1. The x-axis is day of year of first flowering for a species. Based on n = 408 species, which represents about 80% of the herbaceous grassland flora for Konza. We'll probably get another 10-20 species flowering before the year is up.

The y-axis is probability of flowering per day over the year for species of each functional group based on a "smooth" fit of the distribution data. Probabilities are standardized across functional groups. I broke out the Cyperaceae because it was the Carex that flowered early, not any C3 grasses. The C3 grasses that flower late in the year are generally woodland grasses.

This is terribly fascinating, though I'm not sure what the story is yet. For example, why are there C3 forbs that flower in August, but not any C3 grasses? And why are there C4 grasses that begin flowering in March, but not any C4 forbs? 

There certainly is an long-term competitive interactions that sort communities and drive selection. It's almost likely a rock-paper-scissors story. If rock (C4 grasses) then no scissors (C3 grasses), but if paper (grazers) then there are less rocks, so can have knife (C3 forbs).  

The C4 forbs are probably the most interesting story. If high temperatures favor C4 over C3, then why are there so many C3 forbs that are active during the hottest months rather than C4 forbs. Konza's C4 forbs are mostly Chamaesyche (Euphorbiaceae) and Amaranthus. Often they are prostrate forbs and/or weedy species keying in on disturbed areas. The C3 forbs that flower during this time are species like Salvia. Are there C4 forbs that fall into the same niches as these C3 forbs. Is there evolutionary constraint here that allows all the mid- to late-summer C3 forbs to persist? 

As we generate more large-scale trait datasets, more of these patterns should come clear. 

Whole-flora analysis: flowering and community assembly

Distribution of first flowering dates for 265 Konza grassland species (as of mid-May). 

There are some ecological analyses that can only be done by analyzing every species in a flora. Statistical inference aside, if we are to understand ecological sorting and community assembly, we need whole-flora analyses.

For example, we've slowly been accumulating data on first flowering for the Konza flora. For each species,  the day of year it first begins to flower is recorded. We're about half-way to having dates for the entire grassland flora. It's a bit biased now as we're still collecting data this year, but that's why this is on a blog...

There seems like there might be pretty strong selection pressures to flower at times when 1) environmental stress is low and 2) there is little competition for pollinators. I'm not sure if there would be selection against synchrony in flowering time for anemophilous species, but we that would be something to test, too. In this case, deciding what the null model is, is the hardest part.

I like the idea of whole-flora analyses. It's a lot of work though.