Our Research in the News

Recently, we’ve had a few students whose research has been highlighted in the news.

Laura Koehn’s research on Magellanic penguins with Jeff Hard (NOAA), Elaine Akst (Montgomery College) and P. Dee Boersma (UW Biology) was highlighted by UW Today. Her research looked at natural selection and heritability of body size and other morphological traits in Magellanic Penguins at Punta Tombo, Argentina. This is the first study to look at natural selection in a penguin species over more than 20 years; and only the second for a bird species.

See the UW Today article and video here: http://www.washington.edu/news/2016/09/23/how-natural-selection-acted-on-one-penguin-species-over-the-past-quarter-century/

And for the full research article: http://www.aoucospubs.org/doi/abs/10.1642/AUK-16-50.1

Also, back in May, Kiva Oken’s research (with Tim Essington) on the effects of lingcod fishing strategies on rockfish (lingcod prey), was highlighted by UW Today. See the article here: http://www.washington.edu/news/2016/05/20/lingcod-meet-rockfish-catching-one-improves-chances-for-the-other/

And for the full research article see: http://icesjms.oxfordjournals.org/content/73/9/2267

More updates from the lab, and welcome Elizabeth Ng

We’ve been a little slow in updating work that has been coming out of the lab.

Emma Hodgson’s great paper linking life history, demographics into risk assessment came out in PLoS One :

Hodgson, E. E., T. E. Essington, and I. C. Kaplan. 2016. Extending Vulnerability Assessment to Include Life Stages Considerations. PLoS ONE 11:e0158917.

Kiva’s paper showing where selective removal of piscivores can offset prey bycatch came out in ICES J. of Marine Science

Oken, K. L., and T. E. Essington. 2016. Evaluating the effect of a selective piscivore fishery on rockfish recovery within marine protected areas. ICES Journal of Marine Science

Laura’s paper that looked at the trophic position of forage fish in the california current came out in Ecological Modeling:

Koehn, L. E., T. E. Essington, K. N. Marshall, I. C. Kaplan, W. J. Sydeman, A. I. Szoboszlai, and J. A. Thayer. 2016. Developing a high taxonomic resolution food web model to assess the functional role of forage fish in the California Current ecosystem. Ecological Modelling 335:87-100.

Pam’s groundbreaking paper showing us how to estimate diet fractions is available at Can J. Fish. Aquat. Sci:

Moriarty, P. E., T. E. Essington, and E. J. Ward. 2016. A novel method to estimate prey contributions to predator diets. Canadian Journal of Fisheries and Aquatic Sciences:1-10.

Finally, we welcome Elizabeth Ng to the lab this Autumn!  She joins us from University of Idaho where she received degrees in Fish and Wildlife and in Statistics.  She is beginning the Ph.D. program in Quantitative Ecology and Resource Management (QERM).

Recent Achievements

This Spring quarter, we had many academic achievements in the lab group:

First, Christine Stawitz, Kiva Oken, and Megsie Siple, all passed their general exams this quarter and are now Ph.D. candidates in the School of Aquatic and Fishery Sciences.

Additionally, Halley Froehlich passed her Ph.D. defense and is now Dr. Froehlich. We will miss her greatly, but wish her all the best in her post-doc position at University of California Santa Barbara.

Finally, Dr. Tim Essington was awarded the “Outstanding Researcher” award by the University of Washington College of the Environment.

Congratulations to everyone! Keep up the good work!

 

Does fishing amplify forage fish collapse?

Small pelagic fish (forage fish) play an important role in marine ecosystems by transferring nutrients from lower trophic levels to predators, including fish, seabirds, and marine mammals. They’re also crucial to humans, comprising the largest fisheries in the world and providing services in the form of food, and aquaculture and livestock feed. However, because these species are fast-growing with highly variable recruitment, forage fish populations naturally experience periods of “boom” (very high biomass) and “bust” (very low biomass or “collapse”). Collapses can be devastating for fishing communities, as immortalized in John Steinbeck’s novel Cannery Row, which details the collapse of the California sardine fishery in the 1940’s. California sardines are a hot topic again this month, as federal regulators have decided to close the fishery for more than a year.

Because forage fish populations are both highly important and highly variable, it is important to understand if human activities, like fishing, make forage fish collapses worse or if collapses are entirely caused by natural variability. Our fearless leader Tim led the lab group in a search for the answer to this question. We compiled fishery catch and biomass data for 55 forage fish stocks worldwide and examined collapse frequency and characteristics. A similar recipe led to collapse across stocks: high fishing pressure for several years before collapse, followed by a natural decrease in population productivity and a lagged management response. We additionally found that the magnitude and frequency of forage fish collapses are increased by fishing, but that fishing does not increase a species’ time to recovery from a collapse.

We found that forage fish collapses are not caused by fishing alone, but that managers can potentially reduce the magnitude and frequency of collapse by quickly responding to observed natural drops in productivity. This finding points toward the need for an agile and flexible management framework to deal with scenarios where populations are naturally highly stochastic. We are encouraged to see fishery managers’ proactive closure of the California sardine fishery in response to the current period of low productivity in this stock. Our analysis suggests that proactive closures like this can help reduce the impact of forage fish collapse on marine ecosystems while only slightly reducing fishery yield. A precautionary and swift management response to these natural dips in productivity is key to ensuring long-term sustainability of this vital resource.

You can read the full paper here.

Essington, T.E.; Moriarty, P.E.; Froehlich, H. E.; Hodgson, E.E.; Koehn, L.E.; Oken, K.L.; Siple, M.C.; and Stawitz, C.C. (2015). Fishing amplifies forage fish population collapses. Proceedings of the National Academy of Sciences. In press.

SURF’s Up!

One of the great pleasures of this line of work is the opportunity to work with some really smart and creative people.  As a member of the Lenfest Forage Fish Task Force, I got to meet a number of talented people that I had only known through the literature.  Éva Plagányi , an outstanding ecological modeler at CSIRO was one of these people that I was really happy to finally meet in person.

Not only is Éva a top-notch scientist, she’s a wizard when it comes to paper titles.  Our recent collaboration “When the SURF’s up, forage fish are key” ranks right up there with some of her most clever titles.  Apart from the snazzy title, this paperdescribes a new, easily obtained metric that can be used to flag whether a forage fish (sardine, herring, anchovy) is a “key” forage species.  This distinction turns out to be pretty important.  When you’re dealing with a key forage fish, you need to have extra precaution in your fisheries management, because errors in management not only hurt fish stocks and fisheries, but also  the large fish, birds and mammals that depend upon them.  Recently, the Marine Stewardship Council implemented new seafood certification requirements for  key forage species, that include a lower biomass limit below which fishing is sharply limited, and a maximum allowable fishing rate.

You can find our new paper here.

 

Learning Across Ecosystem Boundaries

I had a somewhat unusual path in my research.  I started studying trout reproductive behavior in small streams, then transitioned to studying food webs and trophic cascades in lakes, and then “smoltified” as a post doc into the marine realm.  Of all of these transitions, the last one was by far the most difficult.  The language, the concepts, the framework for looking at marine systems – particularly from a fish population biology viewpoint – was completely foreign to me.  Needless to say, I finally got my head around it, but that experience was important.  It instilled in me the appreciation that the place in which you work really does affect the way you think about problems, and there is great benefit from looking beyond your own “system” to see how others think about the same issues

For that reason, I was delighted when asked by Steven Cooke to join a team tasked with writing a synthesis and comparison of fisheries management across freshwater and marine realms.  Thanks to Steven’s persistence, this work is now published in Canadian Journal of Fisheries and Aquatic Sciences (presently available as a “Just-IN Article”.  Hope you can check it out.

P-values and the surprising realization: scientists need to think critically

One of the great debates that I have learned about at grad school is the conflict between frequentist statistics and Bayesian statistics (nicely highlighted here by xkcd). Both have their uses, but the longer I have been here, the more criticism I hear about the famous P value and whether it has a place in science. Recently, a number of publications have come out in discussion of this debate, and I indulged myself over spring break by nerding out over a few papers.

I started this task (papers listed at the bottom of this post), with a definite bias in my outlook. In the last year I have learned about likelihood, AIC and Bayesian statistics and found myself embracing these techniques that were not taught in my undergraduate Intro to stats. Notably, as I have learned more about Bayesian statistics, I have been impressed by the types of questions that can be answered that we cannot approach at with frequentist statistics. In particular I am interested in risk assessment – and with Bayesian statistics you can actually ask what the probability of a particular outcome might be – for example, what is the probability that if we fish a population at X rate, that the population will fall below a certain level? Coming from the world of the P value, where all you can do is test against a null hypothesis, I have found this an exciting ‘new’ method. Over the last year and a half, I have heard a number of people in SAFS (including myself) state the limitations of the P-value when one is interested in more complex questions (such as model selection), and as a result expected to come out of these readings with stronger arguments against its use. I expected to scoff the papers which were in support of the P value and embrace those that put it down. However, there is more complexity to the debate than my original thinking presumed.

Although I did not come out of this reading entirely scoffing the P value, I definitely did not have any renewed sense that the P value is a fantastic statistical tool. There is some strong presentation that the P value has some use, albeit in limited settings. Then there are also many strong arguments against it, arguing that there are inherent flaws (Barber and Ogle 2014), demonstrating the superiority of alternative methods – e.g. AIC (Burnham and Anderson 2014) and going so far as to write that ‘P values are flawed and not acceptable as properly quantifying evidence’ (Burnham and Anderson 2014)citing Royal 1997). However, what I noticed more consistently was some of the subtleties behind the debate that do not necessarily have to do with whether or not scientists should be using the P value.

It seemed to me that the more I read, the more authors seemed to be circling around the same type of argument: that scientists need to think critically about their results and the statistical technique that they chose to employ. Repeatedly in the papers defending the P value, the authors address the issue of the binary cut-off value. Rather than using some value, they stress the need for an analysis of what the study actually measured. Or other authors have argued that in fact a cut-off value may be of use, but should be much more conservative than what we have thus far been using (e.g. smaller than 0.05). And even the papers putting down the use of the P value in the first place argue in support of thinking through the type of statistical tool we use and better understanding the results that have been found (which more often then previously thought, may have no significance).

There is a desire to approach statistical analysis with some perfect tool which allows the scientist to be entirely objective, when in reality, no such tool exists. So my take-away from all of this is that we need to learn to embrace the reality that subjectivity comes into play and use the resources we have around us (other scientists) to try to think through the best approach to use.

And so where do I think that leaves us? In fact, I think this leaves us better off. Rather than being free to publish papers where someone blindly uses a statistical technique that shows their results are ‘important’ (and I think this happens more frequently than any of us would like to admit), scientists, or biologists I should say, are required to put consideration into both what statistical tools they are using, but also how they interpret the results.

 

Citations

Barber, J. J., and K. Ogle. 2014. To P or not to P? Ecology 95:621-626.

Burnham, K. P., and D. R. Anderson. 2014. P values are only an index to evidence: 20th- vs. 21st-century statistical science. Ecology 95:627-630.

de Valpine, P. 2014. The common sense of P values. Ecology 95:617-621.

Johnson, V. E. 2013. Revised standards for statistical evidence. Proceedings of the National Academy of Sciences.

Murtaugh, P. A. 2014. In defense of P values. Ecology 95:611-617.

Royall, R.M. 1997. Statistical evidence: a likelihood paradigm. Chapman and Hall, London, UK

Chukchi Sea Food Web Model Published

Congratulations to Andy Whitehouse, whose M.Sc. thesis work has just been published in Polar Biology

Whitehouse, GA, Aydin, K, Essington, TE, Hunt, GL.  A trophic mass balance model of the eastern Chukchi Sea with comparisons to other high-latitude systems.

http://link.springer.com/article/10.1007/s00300-014-1490-1

Can we put a price tag on whales?

Check out interesting Forum in Ecological Applications on market-based tools for conservation – can we put a price tag on whales?

http://www.esajournals.org/doi/full/10.1890/13-1590.1

Congratulations to the two author teams (Gerber et al. and Smith et al.) for their thoughtful contributions.