Structured Decision Making Course

As part of the EDG/CEED Leadership Program, CEED was kind enough to give each represented node $3000 to host an event that would help us improve our leadership skills. This is a broader brief than it sounds as the concept of ‘leadership’ as defined on the course includes everything from self leadership, to networking, to influencing others (see blogs from the leadership cohort who explore this more). Therefore, after much deliberation we decided to run a workshop on Structured Decision Making. Now this usually costs you tens of thousands of dollars but the University of Melbourne is lucky to have three resident experts in structured decision making; Libby Rumpff, Kelly de Bie and Prue Addison and they were willing to teach us. I should say that $3000 did not nearly cover their wages for the time they put in to preparing and running the two day workshop but they saw this as an opportunity to refine their skills (I hear that they may consider offering similar Structured Decision Making Courses in the future). Around 30 students, post docs and government and NGO employees attended the course. Most of these people attended in person at the University of Melbourne but we also streamed the lecture components of the workshop live to a number of interstate and overseas participants.

The workshop was designed to progress in the same way that you would approach a structured decision making problem. Structured Decision Making is made up of 6 steps (although some steps may be done multiple times depending on the concept: 1) creating a problem statement, 2) delineating objectives, 3) cataloguing alternatives, 4) determining the consequences of the alternatives, 5) comparing the different alternatives and, 6) deciding on an action. The workshop took us through each of these steps and we simultaneously learned about the steps and implemented them using a toy decision problem (deciding on a correct course of action in Victorian Mountain Ash forests).

Throughout the workshop our facilitators gave us examples of how they have used structured decision making for everything from choosing a house to protecting the Great Barrier Reef. By the end of the workshop I felt like I had the knowledge and skills to implement a Structured Decision Making process, though it might be easier to implement Structured Decision Making in a group context after some facilitation training.

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My Epic Trip to America

I just recently returned from my first solo overseas conference trip and want to chronicle all of the amazing places I saw and people I met so that the details wont get lost in the sand of time. Feel free to read on if you want to hear about some amazing people and a little bit about my adventure.

I am not a big traveller so I tried not to think of all the scary possibilities when I submitted and abstract to attend the ESA (America). After I was accepted I resorted to denial and avoidance and finally I spent the last month or so freaking out about it and obsessively organising every single detail. I decided that I wanted to make the very most of the experience and get as much bang for my carbon buck as I could. So I searched online for people who might be able to give me insights into my research. Unfortunately, my research is a little hard to describe so my success was a little bit hit and miss. Regardless, I think I made a lot of connections which will be very valuable.

Here’s the plan I came up with:

Fly to New York, see some of New York city and meet with Justin Bledin, a linguist from Johns Hopkins University

Catch the train to Princeton University meet with Matthieu Barbie, Simon Levin and the other ecologists at Princeton

Catch the train to Baltimore to attend ESA and network with the people there

Fly to LAX and travel to Riverside to meet with Helen Regan and visit UC Riverside

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America Trip: Princeton

After the chaos of New York I cant even begin to describe how relieved I was to be in Princeton. It felt like Stars Hollow (from Gilmore Girls… which I totally dont watch) except that everyone was rich and well educated. Trees lined the streets, squirrels and birds abounded and it was a critical 5 degrees cooler than New York which had felt like being inside an oven. I imagine the Princeton is a little less idyllic when it isn’t holidays, what with drunken students stumbling around everywhere but I’d still go back.

When I got into town I dropped my bags off at the AirBnB place I was staying at (which was completely lovely and reasonably priced) and headed in to Princeton University to meet Matthieu Barbier who had graciously organised a schedule of meetings for me during my stay. I’ll briefly describe each of the people I met.

Matthieu Barbier

Matthieu is a bit of an enigma, he works in the Levin Lab which focuses broadly in ecology and evolution but his expertise is in linguistics and physics. He was my point of contact at Princeton (because of his cross disciplinary expertise and the possibility that he could advise me on linguistic grounds). He is interested in introducing more qualitative methods to hard sciences and more quantitative methods to fields like linguistics. The main project he is working on at the moment is to do with bringing a qualitative emphasis to ecology by studying generalisable rules about how people make ecological choices.

Simon Levin

Simon Levin has been one of my research heroes for a long time so it was fantastic to get some career advice from him. He says that for your first post-doc you should look for a job where you can

  • Do something new
  • Take ownership over a project
  • Diversify your skills and expertise
  • Work in large labs where you can benefit from collaboration

Some funding schemes that he suggested for me and might be relevant for other QAECOlogists and allies are:

SESYNC: The National Socio-Environmental Synthesis Centre, where they use science to inform conservation policy. They have lots of post-doc opportunities but usually you dont work in a large groups so it might be a bit isolating

NatureNet Fellowships: These are run by The Nature Conservancy and you apply at one of their partner universities: Columbia, Cornell, Princeton, Stanford, the University of

Pennsylvania, and Yale.  According to the NatureNet site they are looking for outstanding early-career scientists who seek to improve and expand their research skills while directing their efforts toward problems at the interface of conservation, business and technology.

Henry Horn

Henry is a Renaissance Man who is a naturalist, statistician, historian, artist and musician. He had some really interesting stories about debates and conflicts in ecology and has been involved in some himself. His insights on these conflicts were interesting. He observed that in a lot of cases, debating ecological concepts seems to cause people to abandon their original moderate views and become polarised such that both sides end up unreasonable. Listening to his stories I resolved not to fall into this trap whenever I take part in an ecological debate. During our conversation he also showed me a song he has composed about statistics called ‘The Kuhn and Popper Knee-jerk Philosophy of Science Blues’ which features memorable lines such as “If you publish random papers, with your students working in teams, 5% of what you say will be statistical truth or so it seems. And if anyone says you’re a Fisherian liar, you can rescue yourself with a Bayesian Prior”.

Aneike Van Leeuwen

Aneike studies size structured population dynamic models which take into account energy flows in the system. We bonded over terminological difficulties. I told her about my woodland bird problem and she told me about how people tend to generalise between age structured population dynamic models and size structured ones. Both terms are used to refer to models will a vast range of complexity only some of which take into account feedback loops between size, resource availability, population size and growth. Apparently this often leads to miscommunication between researchers. We talked about how these misunderstandings could be ameliorated but didn’t come to any good conclusions.

Lyndon Estes

Lyndon has a wide range of interests but it seemed that his passion lies in examining land use change in Africa. We talked primarily about my work on ecological terms and how that related to stuff he’s come across over the years. He spoke about:

  • taxonomic change in birds where sometimes the divisions between species are based on the most minor characteristics.
  • The species concept: he studied Mountain Bongo antelope which is a subspecies with extremely limited distribution where the other subspecies is widespread – depending on whether you are interested in species or subspecies level protection these animals may or may not get protection
  • A recent article by Holly Gibbs found some surprising results about land degradation, particularly in tropical forests which has prompted a review of how consistently tropical forest is being classified, particularly how it is distinguished from tropical savannah.

David Wilcove

David is the head of his own lab at Princeton which focuses on protecting biodiversity particularly in Asia and the Americas (and often with a focus on birds). He’s an extremely engaging guy and he had some interesting insights into my current work.

At the moment I’m working with Martine Maron, Alex Kutt, Jeremy Simmonds, and my supervisors to try and get Australia’s woodland bird community listed as a Threatened Ecological Community under the EPBC Act. David suggested that I should identify which species are threatened and declining and the processes that are threatening them as a way of prioritising which species should be protected. This is definitely something that I will consider as we approach this problem in the coming months. David was also kind enough to set me up to meet a number of his lab members who I will describe next.

Fangyuan Hua

Fangyuan is studying how the current reforestation efforts in China are affecting regional economies and biodiversity (with an emphasis on birds). She’s using a whole swathe of indices to measure biodiversity including species richness, community composition, changes in abundance and beta diversity. As part of her research she studies forest dependent and open dependent species because it’s a necessary simplification but believes that studying resource/habitat preference on continuous scales (creating a n-dimensional hyper-volume resource niche) would be a more rigorous approach in many cases.

Janice Ser Huay Lee

Janice studies agricultural intensification in Sumatra and how (and why) various farmers make decisions about how to use their land. She simulates these changes across the landscapes and looks at the social, economic and environmental consequences these decisions and (perhaps) how to influence them. She was interested in my topic and suggested that I write a review article about the influence of ecological terms to broaden the emphasis of my current research which is fairly firmly grounded in one example. I think this is something I will pursue… once I’ve written my thesis.

Umesh Srinivasan

Umesh studies the effect of landuse change on bird demography and how species turnover on an elevation gradient relates to community level metrics. One of the metrics he is particularly interested in at the moment is body size. I don’t know much about this but it appears that there is a trend towards larger species having smaller population sizes. Therefore the population size of these larger species can be used as a measure of how well a community is doing.

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America Trip: New York

In New York I stayed at the cheapest (safe place with ensuite bathrooms) that I could find but it was still by far the most expensive place I stayed for the trip, despite the horn honking, sirens and loud conversations which continued all night and were completely audible from my room. Fortunately I was so exhausted by the trip that I slept like a log anyway. I spent my first day there trying to stay awake and riding one of those (ridiculously overpriced) hop on hop off busses around the city and seeing placed like Central Park (which was just as good as described) and Times Square (which I found totally overrated).

On the second day I met with Justin Bledin at New York University where he is doing a sabbatical. At the time when I was organising my trip I had recently received a review of  my (now published) manuscript which basically said that I didn’t understand the basic precepts of linguistics, had  ignored a vast literature in linguistics and philosophy of science (since Aristotle) and therefore all of my arguments were completely invalid. As you can image this left me a bit insecure and I thought that this trip would be a fantastic opportunity to meet up with some linguists, discuss my paper and see if anyone spat on me or offered advice. I found Justin and his description online led me to believe that he would be interested in my work (on terminology and standardisation) – well it turns out I misunderstood his description and he wasn’t really working in that sort of field. However, he is a linguist and, while he hasn’t studied everything since Aristotle, his understanding of linguistics was sufficient to give me two important pieces of advice.

  • He doesn’t think I need to study linguistics to do my work or look at standardising terminology within ecology. He thought that, unless I wanted to switch fields I would be better off focussing on the ecological literature. Huge relief there – reading linguistics texts gives me a headache.
  • The question of whether or not it is possible or desirable to standardise terms or words is debated by historical and modern day linguists and is not yet resolved. Therefore, my suggestion that ecological terms should be standardised (starting with ‘woodland birds’) is completely valid.

Based on his advice I feel confident that I can forge onwards with my studies without fear that I am flouting centuries of well established proof that standardising terms is impossible and undesirable. This means that I can let go of the toxic comments from that review and return, with gusto, to my work!

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Consequences of inconsistently classifying woodland birds

After over a year in and out of review I am pleased to announce the publication of my first article Consequences of inconsistently classifying woodland birds in Frontiers in Ecology and Evolution, co-authored by Georgia Garrard, Libby Rumpff, Cindy Hauser and Michael McCarthy. It’s been a long slog; I have battled constructive and un-constructive reviewers, self doubt and fatigue but I am finally triumphant! I am now a published scientist! All that remains is to ensure that people read our article (and finish my PhD and get a job…) I’ll give a short run down of the article here and then you can make up your mind about whether to read it. Cindy has also written up a nice short summary of the work which you can find here

I blogged about my preliminary findings many moons ago but our article has come some way since then.

This project arose because, during my Masters, I had wanted to study the effect of restoration on woodland birds but was stymied by my inability to determine which species to include in this group. I didn’t have the expertise to determine which species to include and trawling the literature unearthed a multitude of non-identical lists. I wanted to get to the bottom of this and discover how and why these lists differed and whether this impacts the results of research.

We systematically reviewed the literature and compiled a set of 38 lists of woodland birds which allowed us to work out how consistently each species was classified as a woodland bird. The graph below shows the frequency distribution of species classification (as seen in Fraser et al. 2015) where the bars represent the number of species falling into a classification bin (e.g. 0-10: classified as a woodland bird in between 0 and 10% of studies).

Frequency distribution of the percentage of studies in which individual species are classified as a woodland bird (total number of species = 165). Complete consistency in classification would appear as a binary distribution, where species are either regarded as woodland species 100% of the time or 0% of the time. Maximum inconsistency would occur if all species were classified as woodland birds in 50% of lists

Frequency distribution of the percentage of studies in which individual species are classified as a woodland bird (total number of species = 165). Complete consistency in classification would appear as a binary distribution, where species are either regarded as woodland species 100% of the time or 0% of the time. Maximum inconsistency would occur if all species were classified as woodland birds in 50% of lists

You can see that, although there are peaks at either end of the spectrum, indicating that 56% of species are mostly classified as either woodland or non-woodland birds, there is little consistency in the classification of the remaining species. My supervisors and I felt that this was a fairly high degree of inconsistency so we wanted to find out if it’s just woodland bird researchers who classify things inconsistently or whether its a broader problem.

It turns out that ecologists have been noticing and writing about the inconsistent use of terms for as long as the field has existed. A few examples of this are; Mason and Langenheim’s 1957 article about the use of the term ‘environment’, Peet et al.’s 1974 investigation of the term ‘species diversity’, Hall et al.’s 1997 study of the term ‘habitat’, and most recently Herrando-Perez et al.’s 2014 call for ecology to develop a convention for nomenclature. Despite this, no one has ever comprehensively discussed the reasons for this or quantified it’s effects which is where my article comes in.

Why do researchers us the term ‘woodland bird’ differently?

We surveyed woodland bird authors and found that the main reasons that researchers classify different species as woodland birds were

  • different aims of research. Researchers tailor their list of ‘woodland birds’ to include species that they expect to respond most strongly to the phenomenon they are interested in.
  • disagreement about what a woodland is. Bird researchers variously consider woodlands to be i) any area with trees, ii) low density treed areas, iii) areas with vegetation matching Specht’s classification or iv) areas designated as woodlands by vegetation maps (e.g. EVC maps)
  • disagreement about how to determine which birds depend on woodlands. Researchers variously determine which species are woodland birds based on i) whether they saw them in a woodland, ii) whether they occur more often in woodlands than in other habitats, iii) their nesting and foraging traits, iv) what types of habitat they require or avoid (e.g. do they need large areas of habitat or do they avoid degraded areas), v) process of elimination where certain types of species like water birds are excluded from the category, or vi) whether they have been classified as a woodland bird in another article/book

What impact does classifying species differently have on results

Garrard et al. (2012) modeled the effect of habitat aggregation (which is roughly the inverse of habitat fragmentation) on the occurrence of woodland birds, using a subset of species that they classified as woodland birds. We re-ran their model first using the entire complement of species and then being increasingly more selective about which species qualify as woodland birds. We excluded species based on the % of lists in which they were classed as woodland birds. The graph below shows the results where at 10 on the x axis, all species that are classified as woodland birds in more than 10% of articles are included in the analyses and at 80 only the species which are classified as woodland birds in more than 80% of lists are included. The horizontal line and shaded area represent the original model estimate and credible intervals.

The predicted effect of tree cover aggregation on species prevalence, for different subsets of species representing frequency thresholds of 10, 20, 30,…80%. At 80 on the horizontal axis, only species which are regarded as woodland birds in 80% or more of studies are included in the model. Error bars represent 95% credible intervals. Mean estimate from the original Garrard et al. (2012) model is represented by the line and the 95% credible intervals by the grey shaded area.

It is evident that the estimated effect of habitat aggregation differs depending on which species are included. If all species found in woodlands are included (as they are in some studies) the estimated effect of habitat aggregation is substantially lower than the original model estimate and that achieved above the 40% classification frequency threshold (where all species are classed as woodland birds in 40% or more of lists). Furthermore there is an upward trend in estimates as the woodland birds classification becomes more selective. This is an indication of a systematic bias in results where studies which are less selective about which species are woodland birds are likely to always obtain different results (probably with lower effect sizes) than those that are very selective about their classification.

In this case we looked at how classification effects results when the data collection, survey area and analyses are identical and found significant differences. When comparing results from studies using different classifications it is impossible to know whether differences are attributable to data collection, survey area or analyses or whether they are due to differences in classification. The more different lists of woodland species are the less comparable their results will be.

This is particularly problematic when you’re trying to understand woodland bird ecology or predict how they will react to management. Only a small subset of research uses identical lists of woodland birds, so researchers must choose between including all available information (which risks differences in classification confounding results) or only including studies which use the same list of woodland birds (which risks excluding valuable insights from other studies).

We propose that woodland bird researchers unite behind a single definition and list of woodland birds. Our research shows that this is likely to be an unpopular idea but we believe that standardization will make it easier to find and compile relevant evidence in the literature, avoid redundant scientific investigations and ease communication of research (MacGregor-Fors, 2011; Herrando-Perez et al., 2014)

References

Fraser, H., Garrard, G.E., Rumpff, L., Hauser, C.E. & McCarthy, M.A. (2015) Consequences of inconsistently classifying woodland birds. Frontiers in Ecology and Evolution, 3, 1–8.

Garrard, G.E., McCarthy, M.A., Vesk, P.A., Radford, J.Q. & Bennett, A.F. (2012) A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change. The Journal of Animal Ecology, 81, 14–23.

Hall, L.S., Krausman, P.R. & Morrison, M.L. (1997) The habitat concept and a plea for standard terminology. Wildlife Society Bulletin, 25, 173–182.

Herrando-Perez, S., Brook, B.W. & Bradshaw, C.J.A. (2014) Ecology needs a convention of nomenclature. BioScience, 64, 311–321.

MacGregor-Fors, I. (2011) Misconceptions or misunderstandings? On the standardization of basic terms and definitions in urban ecology. Landscape and Urban Planning, 100, 347–349.

Mason, H.L. & Langenheim, J.H. (1957) Language analysis and the concept ‘environment’. Ecology, 38, 325–340.

Peet, R.K. (1974) The measurement of species diversity. Annual Review of Ecological Systems, 5, 285–307.

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Under my new name

In April (2015) I married into the Fraser family and, seeing as I am yet to publish an article, have decided to transform myself from Hannah Pearson to Hannah Fraser. This involves jumping through a whole lot of hoops. For example, it takes about 50 days for the Office of Birth, Deaths and Marriage to register that you are married, then you have to apply for your certificate which takes a few weeks. Until you receive it you can’t change your name at Melbourne University so my emails are still under my original name which has caused some confusion.

Unfortunately, by far the biggest issue so far is that I keep forgetting that my name has changed and introducing myself as the wrong thing. So if any of you catch me at it, let me know.

Anyway, the purpose of this post is to let you know that, from now on, I will be posting updates on my research on this site under this name. Hopefully, you will find something interesting.

All the best

Hannah Fraser

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