09/16/19

Trees we liked this summer

Summer is wrapping up and the Aitken lab is getting back to classes and lab meetings and all the regular routine of fall term. We spent our summer watering trees in the greenhouse, presenting at conferences, trekking around the field, and taking quiet vacations. Where ever we went, we found trees that delighted and soothed us. Here are a few of our favourites –

Susannah –

While wandering around Eves Provincial Park near Duncan, I came across the biggest bigleaf maple I’ve ever seen. The sign claimed it was the biggest maple in all of Canada. I’m not sure about that, but it was very impressive. When trying to verify the claim, I found there are 4 giant bigleaf maples in Stanley Park – practically in my backyard. Guess I know what I’m going to be looking for on my Stanley Park walks this fall! One of the things I love about bigleaf maple are how many epiphytes they support – their bark is just covered with mosses, lichens, liverworts, and ferns.
Bigleaf maple

 

Beth –

Bristlecone pine: wilderness survival expert

This is a Great Basin bristlecone pine tree (Pinus longaeva) from the protected Ancient Bristlecone Pine Forest in the Inyo National Forest of California. The trees in this forest are some of the oldest on the planet; the oldest living tree is estimated to be over 5,000 years old. They achieve these great ages by growing extremely slowly; an inch of diameter growth can take up to 100 years. Their needles can persist for over 40 years (the longest lasting of any plant). As they age, portions of cambium die, leaving only narrow strips of active vascular tissue and bark, leading to their characteristically gnarled growth form.

GB bristlecone pine

Pia –

My favourite neighbourhood tree:  a large multi-stemmed pine on 14th and Trimble. It’s on my way to the swimming pool. Unfortunately, I don’t know the species.

Pine

ID anyone?

Sally –

European yew (Taxus baccata) on Mt. Olympus in Greece. Yews are rare in Greece as they are toxic to livestock and farmers cut them down, but this population survived because it is near a monastery.

Taxus baccata

 

Iain –

This summer took me from Waterton to Jasper and everywhere in between helping complete health surveys of permanent whitebark and limber pine plots. Whitebark and limber pine continue to decline throughout their ranges mainly due to the introduced pathogen Cronartium ribicola causing the disease white pine blister rust, but also from mountain pine beetle, fire suppression and subsequent encroachment of lower elevation species, and climate change. Started in 2003 by Parks Canada, these permanent plots are surveyed every 5 years to assess the condition of whitebark and limber pine in the Canadian Rocky and Columbia Mountains. Lucky for me, I was able to help with the 2019 surveys while working for Parks Canada and travel to remote parts of these mountains to assess the endangered trees. I can safely say it was the most physically exhausting road trip I have been on!

Whitebark pine by Iain Reid

Whitebark pine by Iain Reid

Rafa –

Saying goodbye to my little Douglas-fir babies – this was the last picture I took from my experiment at Totem Field before cutting the plants down two weeks ago for biomass measurements.

It was quite a close and intense interaction with these plants since they were sowed in May 2017. Many and many assessments for phenology, height and cold hardiness.

Doug fir growing at Totem Field

07/7/19

Summer 2019 conferences

Conference season is in full swing and the Aitken lab is travelling near and far to share what we’ve been up to.

Here’s a list of recent and upcoming conference talks by lab members and associates.

Evolution June 21-25

Combining exome capture and pool-seq: Lessons from three conifer species. Brandon Lind.

Evolution of phenology along elevation gradients: insights from different modeling approaches. Ophélie Ronce, Isabelle Chuine, Julie Gauzere, Sylvain Delzon, Luis-Miguel Chevin

Western Forest Genetics Association Conference June 24-26

Phenotypic and genomic patterns of climate adaptation in western larch to assess assisted migration strategies with climate change. Beth Roskilly, Brandon Lind, Mengmeng Lu, Sam Yeaman, Sally N. Aitken

A forest of information: Comparing phenotypic, genomic and climatic data for managing climate adaptation. Colin R. Mahony, Ian R. MacLachlan, Brandon M. Lind, Jeremy B. Yoder, Tongli Wang, Sally N. Aitken

SMBE July 21-25

Patterns of genetic diversity around protein-coding exons and conserved non-coding elements are explained by strong selective sweeps in mice. Tom Booker. Poster session.

Canadian Forest Genetics Association Conference Aug 19-23
Does local adaptation to drought need to be considered in assisted gene flow strategies for Douglas-fir reforestation? Rafael Candido Ribeiro. August 20 5pm poster session.

IUFRO World Congress Sep 29 – Oct 5

Does local adaptation to drought need to be considered in assisted gene flow strategies for Douglas-fir reforestation? Rafael Candido Ribeiro. In session “B2a Trees on the move: range shifts, potential for genetic adaptation and assisted migration”

02/14/19

What will your city be like in 60 years?

When Colin started publishing his papers on calculating climate similarity and novel climates, we wished for

 a tool that lets me plug in coordinates, a year and an emissions scenario and get a map of climate analogs and their associated ecosystems.

Looks like someone else was reading Colin’s papers and thinking along the same lines!

This week, Fitzpatrick and Dunn published an online map that lets you look at cities and their future climate analogues and along with a paper in Nature using the sigma dissimilarity metric that Colin et. al developed.

Be sure to turn on the climate similarity map option when you use Fitzpatrick and Dunn’s tool – it’ll show you how analogous the closest analogue city really is! Seattle is Vancouver’s closest analogue, but it’s not a good one. You’ll have to read this paper by Colin et al. on novel climates in BC forests to find out why!

03/7/18

The Homebrew Series: Inferring demographic history with ABC, by Joane Elleouet and Sally Aitken

Want to know about the history of the populations you’re studying? Joane Elleouet and Sally Aitken see how far Approximate Bayesian Computation (ABC) and your sequencing method of choice can take you in a new paper in Molecular Ecology Resources.

20 years ago, Tavaré et al. used ABC to estimate that the time to coalescence for the human population based on the Y chromosome was about 157,300 years ago (but!) and evolutionary biologists were off to the races. Now ABC is a common tool in the field with many software implementations to choose from. A lot else has happened in the last 20 years – like huge advances in genotyping technology. Even for non-model species, we can now get lots of genomic data for cheaper than ever using reduced representation library sequencing methods like genotyping-by-sequencing and GBS.

But how well does ABC perform with RRL data and different demographic models? What are its limitations? How do you make the best choices for your sequencing efforts? To answer these questions, Jo simulated data sets for 4 kinds of demographic models and 5 types of sequencing efforts and performed ABC on those datasets. She compared different model’s performance with

  • phased and unphased data, (phasing doesn’t help)
  • data from lots of short reads vs fewer, longer sequences (lots of short reads just as good)
  • different times since colonization, (depends on parameter value and demographic model)
  • tradeoffs between number and individuals and sampling depth at different sequencing error rates, (go for more individuals over depth)
  • and compared ABC to an SFS method. (similar)

As far as the different demographic models they consider, they find that ABC can be used with data from reduced representation library sequencing methods to precisely infer very simple demographic models, but not complex ones.

Here’s what Aitken Lab members had to say after reading the paper:

What’s your takeaway from this paper?

Reader 1: This paper provides several rules of thumb for inferring demographic events from incomplete, fragmented genomic data. Demographic models should be kept as simple as possible, and numerous short sequences from many individuals is preferable to fewer long sequences from a small sample of the population.

Reader 2: You’d better know what kind of demographic history your population has before you start trying to estimate parameters!

Reader 3: Estimating demographic parameters with ABC has limitations even with very simple demographic models

What’s the coolest thing about this paper?

R1: Improving techniques to infer the ancient demographic history of any species you like, not just model species.

R2: I didn’t realize how hard inferring demographic history is, even with so much genomic data. The extensive simulations are really impressive and convincing.

R3: Adding a realistic component by testing the effect of sequencing depth and error

What questions are you left with after reading this paper?

R2: How often do researchers know the “right” model of demographic history to try to infer? Whether or not to include migration or how many populations there have been? How do people figure this out?

R3: What if summary statistics lead to a too drastic loss of data? is there a better way to summarize the data while keeping crucial information?