Uncommon Ground


Genetic structure and clonal diversity in an important Chinese grass

Since you’re reading this blog, you must know that I don’t have a lot of time for research these days. My duties as Vice Provost for Graduate Education and Dean of The Graduate School at UConn take up most of my time. I do manage to contribute to some research, so long as other people do the real work and I contribute some ideas or some statistical analyses. Here’s another example of that.

Last fall I was asked about the old C++ program Hickory that I had written to facilitate analysis of Wright’s F-statistics with dominant markers. It was never terribly widely used, and it was difficult to maintain. I gave up about 10 years ago. In the meantime, I realized that there’s an easy way to rewrite Hickory using Stan. After being contacted, I finally bit the bullet and did the rewrite in a combination of Stan and R. I even mentioned the R/Stan implementation last September.

Yesterday, we posted a pre-print on bioRxiv that uses the new version of Hickory as one of a variety of analytical methods that provide some insight into the genetic structure of Leymus chinensis. Here’s the abstract and a link.

Genetic structure in patchy populations of a candidate foundation plant: a case study of Leymus chinensis (Poaceae) using genetic and clonal diversity

Jian Guo, Christina L. Richards, Kent E. Holsinger, Gordon A. Fox, Zhuo Zhang, Chan Zhou

doi: https://doi.org/10.1101/2021.06.12.448174

PREMISE The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species since they create and define ecological communities, contributing disproportionately to ecosystem function.

METHODS We examined the distribution of genetic diversity and clones, which we defined first as unique multi-locus genotypes (MLG), and then by grouping similar MLGs into multi-locus lineages (MLL). We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass Leymus chinensis. We examined the relationship between genetic and clonal diversities, their variation with patch-size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species.

RESULTS Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single MLL. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three.

CONCLUSIONS We found strong genetic structure among patches of L. chinensis. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.

The link between traits and performance in Protea

If you’re reading this, you probably know enough about me to know that my students and I have been working on Protea for the last 10-15 years. Today I am pleased to report that the most recent work, from Kristen Nolting’s PhD dissertation has appeared in Annals of Botany. The advance publication version appeared nearly a year ago, but the paper is officially out in a special issue focusing on intraspecific trait variation in plants. Here’s the abstract and a link.

Intraspecific trait variation influences physiological performance and fitness in the South Africa shrub genus Protea (Proteaceae)

Kristen M Nolting, Rachel Prunier, Guy F Midgley, Kent E Holsinger

Background and Aims

Global plant trait datasets commonly identify trait relationships that are interpreted to reflect fundamental trade-offs associated with plant strategies, but often these trait relationships are not identified when evaluating them at smaller taxonomic and spatial scales. In this study we evaluate trait relationships measured on individual plants for five widespread Protea species in South Africa to determine whether broad-scale patterns of structural trait (e.g. leaf area) and physiological trait (e.g. photosynthetic rates) relationships can be detected within natural populations, and if these traits are themselves related to plant fitness.


We evaluated the variance structure (i.e. the proportional intraspecific trait variation relative to among-species variation) for nine structural traits and six physiological traits measured in wild populations. We used a multivariate path model to evaluate the relationships between structural traits and physiological traits, and the relationship between these traits and plant size and reproductive effort.

Key Results

While intraspecific trait variation is relatively low for structural traits, it accounts for between 50 and 100 % of the variation in physiological traits. Furthermore, we identified few trait associations between any one structural trait and physiological trait, but multivariate regressions revealed clear associations between combinations of structural traits and physiological performance (R2 = 0.37–0.64), and almost all traits had detectable associations with plant fitness.


Intraspecific variation in structural traits leads to predictable differences in individual-level physiological performance in a multivariate framework, even though the relationship of any particular structural trait to physiological performance may be weak or undetectable. Furthermore, intraspecific variation in both structural and physiological traits leads to differences in plant size and fitness. These results demonstrate the importance of considering measurements of multivariate phenotypes on individual plants when evaluating trait relationships and how trait variation influences predictions of ecological and evolutionary outcomes.

Annals of Botany 127:519–531; 2021 https://doi.org/10.1093/aob/mcaa060

Microscale trait-environment associations in Protea

If you follow me (or Nora Mitchell) on Twitter, you saw several weeks ago that a publish before print version of our most recent paper appeared in the American Joiurnal of Botany. This morning I noticed that the full published version is available on the AJB website. Here’s the citation and abstract:

Mitchell, N., and K. E. Holsinger.  2019.  Microscale trait‐environment associations in two closely‐related South African shrubs. American Journal of Botany 106:211-222.  doi: 10.1002/ajb2.1234

Premise of the Study
Plant traits are often associated with the environments in which they occur, but these associations often differ across spatial and phylogenetic scales. Here we study the relationship between microenvironment, microgeographical location, and traits within populations using co‐occurring populations of two closely related evergreen shrubs in the genus Protea.
We measured a suite of functional traits on 147 plants along a single steep mountainside where both species occur, and we used data‐loggers and soil analyses to characterize the environment at 10 microsites spanning the elevational gradient. We used Bayesian path analyses to detect trait‐environment relationships in the field for each species. We used complementary data from greenhouse grown seedlings derived from wild collected seed to determine whether associations detected in the field are the result of genetic differentiation.
Key Results
Microenvironmental variables differed substantially across our study site. We found strong evidence for six trait‐environment associations, although these differed between species. We were unable to detect similar associations in greenhouse‐grown seedlings.
Several leaf traits were associated with temperature and soil variation in the field, but the inability to detect these in the greenhouse suggests that differences in the field are not the result of genetic differentiation.

Saturday afternoon at Trail Wood

OK. This is mildly embarrassing. I moved to Connecticut in 1986, I was one of the co-founders of the Edwin Way Teale Lecture Series on Nature and the Environment in 1996, I’ve read A Naturalist Buys an Old Farm at least half a dozen times, and Trail Wood is less than 30 miles (40 minutes) from my home in Coventry, but it wasn’t until Saturday that I finally visited. It won’t be the last time. I expect to return once or twice a year to the Beaver Pond Trail, to cross Starfield and Firefly Meadow, and to visit the Summerhouse and Writing Cabin.

Black-eyed susan (Rudbeckia hirta) photographed at Trail Wood

A nice patch of black-eyed susan (Rudbeckia hirta) greeted me near the parking area, which is just a short walk from the house at Trail Brook. Rather than following Veery Lane, I turned left and followed the path through Firefly Meadow towards the small pond.

Edwin Way Teale’s writing cabin at Trail Wood

The Writing Cabin is on the southwest shore of the pond. I turned right and followed the northeast shore to Summerhouse. From there I followed a path along the stone wall bordering Woodcock Pasture until it met the Shagbark Hickory Trail.

Spotted wintergreen (Chimaphila maculata) photographed at Trail Wood

I found spotted wintergreen (Chimaphila maculata) along the Shagbark Hickory Trail , which I followed to the Old Colonial Road. From their I followed the Beaver Pond Trail to the edge of the pond.

Beaver Pond at Trail Wood

After sitting for a while on a nice bench at the south end of the pond, I backtracked on the Beaver Pond Trail and followed the Fern Brook trail through Starfield back to the house and then to the parking area. The whole walk was less than a mile and a half, and the total elevation gain was only 55 feet. It was definitely an easy walk, not a hike, but it was very pleasant, and it was nice to spend time on the old farm where Teale spent so much of his time.

So to anyone from UConn (or nearby) who reads this and hasn’t been to Trail Wood yet, take a couple of hours some afternoon, drive to Hampton, and explore. Trail Wood is easy to find, and it’s open from dawn to dusk. It’s a gem in our own backyard. And if you haven’t read A Naturalist Buys an Old Farm, do it now. You’ll enjoy your visit to Trail Wood even more if you do.

Trait-environment relationships in Pelargonium

Almost 15 years ago Wright et al. (Nature 428:821–827; 2004 – doi: 10.1038/nature02403) described the worldwide leaf economics spectrum “a universal spectrum of leaf economics consisting of key chemical, structural and physiological properties.” Since then, an enormous number of articles have been published that examine or refer to it – more than 4000 according to Google Scholar. In the past few years, many authors have pointed out that it may not be as universal as originally presumed. For example, in Mitchell et al. (The American Naturalist 185:525-537; 2015 – http://www.jstor.org/stable/10.1086/680051) we found a negative relationship between an important component of the leaf economics spectrum (leaf mass per area) and mean annual temperature in Pelargonium from the Cape Floristic Region of southwestern South Africa, while the global pattern is for a positive relationship.1

Now Tim Moore and several of my colleagues follow up with a more detailed analysis of trait-environment relationships in Pelargonium. They demonstrate several ways in which the global pattern breaks down in South African samples of this genus. Here’s the abstract and a link to the paper.

  • Functional traits in closely related lineages are expected to vary similarly along common environmental gradients as a result of shared evolutionary and biogeographic history, or legacy effects, and as a result of biophysical tradeoffs in construction. We test these predictions in Pelargonium, a relatively recent evolutionary radiation.
  • Bayesian phylogenetic mixed effects models assessed, at the subclade level, associations between plant height, leaf area, leaf nitrogen content and leaf mass per area (LMA), and five environmental variables capturing temperature and rainfall gradients across the Greater Cape Floristic Region of South Africa. Trait–trait integration was assessed via pairwise correlations within subclades.
  • Of 20 trait–environment associations, 17 differed among subclades. Signs of regression coefficients diverged for height, leaf area and leaf nitrogen content, but not for LMA. Subclades also differed in trait–trait relationships and these differences were modulated by rainfall seasonality. Leave‐one‐out cross‐validation revealed that whether trait variation was better predicted by environmental predictors or trait–trait integration depended on the clade and trait in question.
  • Legacy signals in trait–environment and trait–trait relationships were apparently lost during the earliest diversification of Pelargonium, but then retained during subsequent subclade evolution. Overall, we demonstrate that global‐scale patterns are poor predictors of patterns of trait variation at finer geographic and taxonomic scales.


  1. If you read The American Naturalist paper, you’ll see that we wrote in the Discussion that “We could not detect a relationship between LMA and MAT in Protea….” I wouldn’t write it that way now. Look at Table 2. You’ll see that the posterior mean for the relationship is 0.135 with a 95% credible interval of (-0.078,0.340). I would now write that “We detected a weakly supported positive relationship between LMA and MAT….” Why the difference? I’ve taken to heart Andrew Gelman’s observation that “The difference between significant’ and ‘not significant’ is not itself statistically significant” (blog post; article in The American Statistician). I am training myself to pay less attention to which coefficients in a regression and which aren’t and more to reporting the best guess we have about each relationship (the posterior means) and the amount of confidence we have about them (the credible intervals). I recently learned about hypothesis() in brms, which will provide an estimate of the posterior probability that the you’ve got the sign of the relationship right. I need to investigate that. I suspect that’s what I’ll be using in the future.

Trait-climate evolution in Protea

Protea compacta

If you’re reading this post, you know that my colleagues and I have been studying Protea for more than a decade. A lot of our work has focused on documenting and understanding trait-environment associations. We’ve studied those associations both among populations within species (Protea repens: https://doi.org/10.1093/aob/mcv146), among populations within a small, closely related clade (Protea sect. Exsertae: https://doi.org/10.1111/j.1558-5646.2010.01131.x and https://doi.org/10.1111/j.1420-9101.2012.02548.x), and across the entire genus (https://doi.org/10.1086/680051). But all of those studies look at the relationship between the climate as it is now (as reflected in the South African Atlas of Agrohydrology and Climatology). They haven’t examined how traits have evolved in response to changes in climate.

Our latest paper, begins to address that shortcoming. We use the highly resolved phylogeny of Protea that Nora Mitchell constructed as part of her dissertation (http://darwin.eeb.uconn.edu/uncommon-ground/blog/2017/01/23/a-new-phylogeny-for-protea/ and https://doi.org/10.3732/ajb.1600227), and we reconstruct estimates of how traits changed over evolutionary time in concert (or not) with climates. Our reconstructions depend on particular models of evolutionary change, and we explore several alternatives. Here’s the abstract:

Evolutionary radiations are responsible for much of Earth’s diversity, yet the causes of these radiations are often elusive. Determining the relative roles of adaptation and geographic isolation in diversification is vital to understanding the causes of any radiation, and whether a radiation may be labeled as “adaptive” or not. Across many groups of plants, trait–climate relationships suggest that traits are an important indicator of how plants adapt to different climates. In particular, analyses of plant functional traits in global databases suggest that there is an “economics spectrum” along which combinations of functional traits covary along a fast–slow continuum. We examine evolutionary associations among traits and between trait and climate variables on a strongly supported phylogeny in the iconic plant genus Protea to identify correlated evolution of functional traits and the climatic-niches that species occupy. Results indicate that trait diversification in Protea has climate associations along two axes of variation: correlated evolution of plant size with temperature and leaf investment with rainfall. Evidence suggests that traits and climatic-niches evolve in similar ways, although some of these associations are inconsistent with global patterns on a broader phylogenetic scale. When combined with previous experimental work suggesting that trait–climate associations are adaptive in Protea, the results presented here suggest that trait diversification in this radiation is adaptive.

Mitchell, N., J.E. Carlson, and K.E. Holsinger.  2018.  Correlated evolution between climate and suites of traits along a fast–slow continuum in the radiation of Protea. Ecology and Evolution 8:1853–1866. doi: 10.1002/ece3.3773.

The origin of a bipolar moss (i.e., one that occurs in the far North and the far South)

One of the great pleasures of serving as an associate advisor on PhD committee is that sometimes you contribute enough to the analysis and interpretation of the data that you end up being a co-author on a paper. That’s why I have papers on New Zealand cicadas, deer mice, and tapeworms, among other things. Now I’ve added another group to my list – moss. Lily Lewis finished her PhD at UConn in the spring of 2015 working with Bernard Goffinet. I was a member of her committee, and now a chapter of her dissertation on which I was able to help has appeared in the American Journal of Botany.1 Here’s the title and abstract. You’ll find the DOI and a link to the paper below.

Resolving the northern hemisphere source region for the long-distance dispersal event that gave rise to the South American endemic dung moss Tetraplodon fuegianus.

PREMISE OF THE STUDY: American bipolar plant distributions characterize taxa at various taxonomic ranks but are most common in the bryophytes at infraspecific and infrageneric levels. A previous study on the bipolar disjunction in the dung moss genus Tetraplodon found that direct long-distance dispersal from North to South in the Miocene–Pleistocene accounted for the origin of the Southern American endemic Tetraplodon fuegianus, congruent with other molecular studies on bipolar bryophytes. The previous study, however, remained inconclusive regarding a specific northern hemisphere source region for the transequatorial dispersal event that gave rise to T. fuegianus.
METHODS: To estimate spatial genetic structure and phylogeographic relationships within the bipolar lineage of Tetraplodon, which includes T. fuegianus, we analyzed thousands of restriction-site-associated DNA (RADseq) loci and single nucleotide polymorphisms using Bayesian individual assignment and maximum likelihood and coalescent model based phylogenetic approaches.
KEY RESULTS: Northwestern North America is the most likely source of the recent ancestor to T. fuegianus.
CONCLUSIONS: Tetraplodon fuegianus, which marks the southernmost populations in the bipolar lineage of Tetraplodon, arose following a single long-distance dispersal event involving a T. mnioides lineage that is now rare in the northern hemisphere and potentially restricted to the Pacific Northwest of North America. Furthermore, gene flow between sympatric lineages of Tetraplodon mnioides in the northern hemisphere is limited, possibly due to high rates of selfing or reproductive isolation.

DOI: 10.3732/ajb.1700144

Climate change and Pelargonium in South Africa

For more than a decade my colleagues Margaret Rubega and Bob Wyss have co-taught a course to graduate students in science and engineering and undergraduates in Journalism.1 The purpose of the course is to help science students improve their skills in working with journalists and to help journalist increase their skills in interviewing scientists and developing stories from those interviews. One of the projects in this fall’s edition of the course was for the journalism students to interview one of the science graduate students and produce a short video describing the student’s research. Daniela Doncel interviewed Tanisha Williams, a PhD student in EEB whom I co-advise with Carl Schlichting. In addition to interviewing Tanisha, Daniela also interviewed Cindi Jones and me. She assembled a video that explains Tanisha’s work very well. I think Daniela did a very nice job of weaving the disparate interviews into a compelling story, and I think the video looks very good (even though it has me in it). I hope that you agree.


Plants, People, and the Mother City

Tanisha Williams, Fulbright 2015-2016, South Africa, at Boulders Beach visiting the penguins.

Some of you know that Carl Schlichting and I co-advise Tanisha Williams. If you know that, you almost certainly know that Tanisha spent the 2015-2016 academic year as a Fulbright Fellow in South Africa. She was based at the Cape Peninsula University of Technology, and she used her time not only to collect seeds of Pelargonium and establish experimental gardens at Kirstenbosch Botanical Garden and Rhodes University but also to work with two non-profit environmental organizations. She posted an article about her experience on the blog of the Fulbright Student Program. Here’s an excerpt to whet your appetite:

Among the many experiences I had, I must say the residents from the Khayelitsha township have taken a special place in my heart. This is where I taught girls and young women math, science, computer tutoring, life skills, and female empowerment through a community center program. It was such an impactful experience, as these girls are growing up in a community with high rates of unemployment, violence, and other socioeconomic issues. It was empowering for me to see the curiosity and determination these girls had for learning and changing their community. They thought I was there to teach them from my own experiences being raised in a comparable situation and now working on my doctorate as a scientist, but I know I was the one that gained the most from our time together. I learned what it truly means to have hope and persevere. These lessons, along with the ecological and evolutionary insights from my academic research, will be ones that I always remember.