# The Morning Algal IDs

When it’s wavy out…

Coffee, laptop, scope, and a red alga that looks pretty much like every other red alga in the tank…time for some IDs.

SCIENCE!

# Day 1: Back in the field!

Well, today was it. After a 2 year hiatus behind my computer screen, my skin now softer and more delicate from its soothing rays, I hopped back in the water FOR SCIENCE! Not only that, but it was my return to dry suit diving. Oh, dry suit diving. I really didn’t miss you and your weird buoyancy tricks (note to self, get ankle weights, as old ones have desintegrated).

It was a great day, despite feeling kinda like the first day back at school. Ted (lab manager) and I came out to SML to work with a fantastic undergrad I’m advising for the summer, as well as do some site scouting of our own. The weather report said that things would turn awful in the afternoon/early evening (and was right), so, a morning dive on the backside of Appledore was just the thing.

This truck is loaded WITH SCIENCE!

We were there to help Sarah census the invasive Heterosiphonia japonica to look at its distribution with respect to a depth and exposure gradient (see also this kick butt paper by Christine Newton et al.). And the backside of Appledore is quite exposed. The transects we were sampling are next to a spot in the intertidal that got wiped bare by this winter’s storms.

Photo by Ted of Sarah (L) and I about to plop down our first transect.

What intrigued me about the transects was two things. I remember this area being super-kelpy. Indeed, the wave exposure limited Codium back when that alga was the big bad (I’ve heard it’s quite rare here, and in a quick checkout at The Cribs, I only saw 3 individuals). But now…well, there are some kelps, but, mostly, it’s red and brown filamentous algae. A lot of Desmerestia viridis to be sure, but a lot of red and brown puffiness. That, and a lot more Chondrus. I mean, we were fairly shallow, but, still. Interesting.

Photo by Sarah of one of her transects

Not a lot of Heterosiphonia, though. It’s going to be interesting to see how Sarah’s project turns out. Some sites have been heavy with it, some light.

I’m just glad to be back in, and seeing how the place has changed. Steneck’s Flips & Locks paper was an interesting update on how this system is doing. I’m going to be curious to browse around and try and take the big whole community perspective I honed at the SBC LTER and see what there is to see here.

A great photo by Sarah of a school I totally missed.

# True Facts About Marine Life

Because there hasn’t been enough ocean silliness lately…

I’ve long been a fan of Ze Frank. But who knew that one of the next places he’d be turning his razor sharp with was on the natural world. And not only that, but, he’d make sure everything is pretty much scientifically kosher. So, I give you three things that nearly made me laugh so hard I was almost glad I wasn’t in a drysuit (because tight neck seals and laughing = no fun?), in escalating order of hilarity. Note, some of this is not so SFW in a mild manner, but certainly always SFDSN.

# Living a Dream: Back to SML

So, today, I’m going to catch a ferry out to the Shoals Marine Lab. I’m just going to be out for a day to meet with the undergrad intern I’m mentoring. I’ll be back later this summer to work with her and setup some permanent monitoring transects.

I have to be honest, this is one of those moments in my life where I am watching a dream come through. I went to SML in the summer of 1999 to take some classes. It changed everything for me. I cannot recount the number of paths that opened up due to that summer than I have run down, higgledy-piggledy. To return now as a mentor and researcher? To have the chance to really learn the secrets of the sea around the Isles of Shoals? To come back with new eyes after a decade of developing as a scientist? I’m having a hard time expressing my excitement and joy.

Rather than kvell any more about the place and my excitement, here’s a video from the participants of the Underwater Research Course at SML (which, also, totally formative to who I am as a scientist – thanks, Jim!) I think it conveys a lot of what I could say, but in images and video that’s much more telling.

# Best Peer Review Experience Ever

So, I recently submitted a piece regarding the future of scholarly publishing in Ecology & Evolutionary Biology. Simultaneous to posting, I put up a preprint in PeerJ Preprints and also put it on Google Docs for line by line commentary (which you are welcome to give!). I asked in both places that commenters identify themselves, unless they felt deeply uncomfortable.

OMG the experience has been amazing!

At PeerJ you can comment on the main page of the article, and others can rate it – which is fantastic – and I’ve gotten some wonderful feedback there (thanks Lars!)

The Google Doc experience has been even more fascinating, given the ability to put in line by line comments.

One of our reviewers is using the Google Doc for their comments. It has made it easy to see what they are saying, respond to things that I think are relevant (or I’ll just change some of the text in the next draft for bigger changes), and have an interactive experience with the reviewer. It absolutely fabulous.

I’ve been really fascinated by the idea of how collaboration can improve peer review ever since reading Leek et al.’s 2011 piece Cooperation between Referees and Authors Increases Peer Review Accuracy. I’m delighted that one of our reviewers has embraced that ethos, and in so doing, I can see how this will really help with future publications if not just Ross Mounce, but everyone embraced this model. Very cool!

# A Preprint Experiment: Four Pillars and a Foundation for the Future of Scholarly Publishing

x-post from the OpenPub Project blog

So, we got together, had two working group meetings to discuss the future of scholarly publishing in Ecology, Evolutionary Biology, and the Earth and Ocean Sciences. What were were thinking that entire time?

We’ve just submitted a piece that brings together our broad ideas (some of which have been seen before), but, simultaneous to publication, we’ve also decided to put up a preprint. Why? Simply put, immediate access is one of our four pillars of the future of scholarly publication. Once you feel something is ready for public consumption, put it out there! We’ve been delighted to watch the evolution of PeerJ Preprints, so we’ve placed our piece there.

Byrnes et al. (2013) The four pillars of scholarly publishing: The future and a foundation. PeerJ PrePrints 1:e11 http://dx.doi.org/10.7287/peerj.preprints.11

This immediate access to the piece goes hand in hand with another of our four pillars. Open Review. We want to know what you think. And now. We hope you give us feedback over at the preprint. Or, if you want to give us more detailed annotated comment, we’ve put it in a comment-open Google doc. Highlight something you disagree with. Argue with us. We welcome it! We’d ask that you put your name with the comment. We want a discussion, as discussion will improve this manuscript and help us shape our argument rather than just one-way commenting. This will also allow *you* to get full recognition for your comments, and we will include this in future acknowledgements.

So, enjoy the piece – our commentary is not a straight experiment-analysis-discussion piece, but rather part of a broader ecosystem of scholarly products that we feel are important to get out there. We look forward to hearing what you think of the piece!

# Favorite Wave Sensor?

So, Internet, I’m setting up a number of monitoring sites this summer. I’m hoping to get good wave height measurements from them to look at disturbance. I have yet to find something like the CDIP swell height model for the Gulf of Maine (although, I’d love to hear that this is due to a failure of my google-fu). So, I’m casting about for some good wave height sensors.

The problem I face is that I’d like to deploy a lot of them, and in some highly variable conditions, secured to subtidal transects. Possibly for 6 months. Or maybe even up to a year. So, I’m trying to see if a lower cost smaller profile solution is available. Something like a tidbit for wave heights.

I’ve found a few that kinda sorta fit the bill, although not quite. There’s the venerable SeaBird, products from RBR, the SEAGUARD tide and wave recorder, and the MIDAS from Valeport.

I’m a little worried that this might be too large or expensive given the conditions I’m deploying in. Or I might be asking for a pipe dream.

Internet – any thoughts, recommendations, or experiences you’d care to share? Am I being ridiculous?

# More on Bacteria and Groups

Continuing with bacterial group-a-palooza

I followed Ed’s suggestions and tried both a binomial distribution and a Poisson distribution for abundance such that the probability of a density of one species s in one group g in one plot r where there are S_g species in group gis

$A_rgs ~ Poisson(\frac{A_rg}{S_g})$

In the analysis I’m doing, interesting, the results do change a bit such that the original network only results are confirmed.

I am having one funny thing, though, which I can’t lock down. Namely, the no-group option always has the lowest AIC once I include abundances – and this is true both for binomial and Poisson distributions. Not sure what that is about. I’ve put the code for all of this here and made a sample script below. This doesn’t reproduce the behavior, but, still. Not quite sure what this blip is about.

For the sample script, we have five species and three possible grouping structures. It looks like this, where red nodes are species or groups and blue nodes are sites:

And the data looks like this

  low med high  1   2   3
1   1   1    1 50   0   0
2   2   1    1 45   0   0
3   3   2    2  0 100   1
4   4   2    2  0 112   7
5   5   3    2  0  12 110


So, here’s the code:

And the results:

> aicdf
k LLNet LLBinomNet  LLPoisNet   AICpois  AICbinom AICnet
low  5     0    0.00000  -20.54409  71.08818  60.00000     30
med  3     0  -18.68966  -23.54655  65.09310  73.37931     18
high 2     0 -253.52264 -170.73361 353.46723 531.04527     12


We see that the two different estimations disagree, with the binomial favorint disaggregation and poisson favoring moderate aggregation. Interesting. Also, the naive network only approach favors complete aggregation. Interesting. Thoughts?