Placement experience by Vincent Keenan

Posted By on Mar 29, 2017


The Environmental consultancy was never a career path I had considered, but then again, never say never. This changed when I managed to dip my toes in the consultancy waters as part of an ACCE placement scheme when I travelled to Long Island, NY, to work with Lev Ginzburg and Nick Friedenberg at Applied Biomathematics. Despite there being differences with how work is conducted during my PhD, much to my surprise, the similarities with consultancy are plenty.
As an ACCE student, I have the option to take a placement of up to 3 months working with another organisation – preferably outside of academia – to widen our career perceptions. There is, however, catch, any work conducted cannot be used in your thesis – and it’s a good one. It’s a chance to show yourself that the skills you are learning can be used elsewhere outside of the lab – or office in my case. So, I applied to take my skills to the USA to see exactly what I could do in the consultancy world. Applied Biomathematics is a small company that develops mathematical and statistical software, as well as general consultancy in environmental and ecological predictions.
So, what was I working on? As a bit of background, the United States is one of the biggest producers of corn – often turned into corn syrup – which is grown predominately in an area known as the “Corn Belt”. Roughly, this is the area beginning East-West, from Lake Erie to the Rockies, and North-South, from Lake Superior to the Deep South…it’s immense! To hammer home the point, I lived in Iowa during an exchange while I was an undergraduate; to travel from Chicago to Iowa City takes 4 hours, after about 30 minutes you leave the greater Chicago area when the first corn field is met, after which there is nothing but corn until Iowa City — and it doesn’t stop there. So why am I banging on about the size and intensity of the agriculture? Well, it’s obvious that this has enormous economic significance, and a finer point is the interest in anything which may threaten this. Enter the other interested party; an army of invertebrates which can’t believe their luck! To get around this issue, the United States Dept. of Agriculture (USDA) have embraced GM crops in the form of Bt corn. This is corn seeds which are coated in a pesticide which also imbues the corn plant with toxins fatal to the pests. But this isn’t job done; the pests fight back by evolving resistance, and so begins the inevitable evolutionary arms race. Many producers, such as Monsanto and DOW, have come up with strategies to help counteract evolution, and one, in particular, is known as “pest refuges”. The idea is that 75% of the field is planted with Bt corn, the remaining 25% is untreated. The concept being that the pests will flock to the untreated corn and not develop resistance, any that do will breed with those that have no resistance and keep up the efficacy of the pesticide – or so the theory goes. In addition to the usage of Bt corn, the USDA requires a 10-year resistance plan, that is, to sell the product, the suppliers must ensure that resistance doesn’t develop over ten years. This is where Applied Biomathematics comes in, suppliers of Bt have contracted them to predict the absolute rate of resistance – a monumental task indeed. They are currently in the process of developing software which looks to address this. They have developed a model which considers pest demographics and genetics, transgenic trait characteristics, the spatial structure of treated-untreated fields, the dispersal of the pests, and resistance management. My role in this task was designing a more efficient dispersal algorithm than was previously being used. The pre-existing algorithm took approx. 1500 seconds to calculate 1 day of movement – not much movement in the grand scheme of things – whereas after my contribution I managed to reduce this to 35 seconds, a 420% increase in efficiency. It should be said that one of the main reasons I could do so was because of the regular geometry of fields in the Corn Belt — things are always easier when dealing with rectangles. Despite the incredible achievements this project has accomplished, the situation on the ground is difficult, to say the least. The assumptions of the model are not entirely realistic due to one somewhat unpredictable factor. Farmers. The human element here can make predictions unreliable; take for example the farmer who thinks “refuge? No thanks! I’ll plant the whole field this way; I need the money to stay afloat”; or another who says “25%? I’ll plant this in a part of the field that is less fertile since it’ll be eaten anyway”. These factors are very important for accurate predictions, but the farmer is thinking about his livelihood, not the long-term resistance of the pests. A bag of Bt corn is around $15,000, and if a farmer is unwilling to pay, or simply cannot, the overall spatial pattern is interrupted which can potentially increase the rate of resistance. Farmers aside, the pests themselves also evolve strategies to work around Bt corn, often farmers will rotate corn with soy to crash the pest population — they dislike soy — but diapause evolves, and they hatch the next season ready for the corn… These are some examples of the challenges within that project, and I think you’ll agree that it’s deeply fascinating.
Insect resistance management is not the only project Applied Biomathematics is involved in, two more they are currently involved with are: collision prediction models between Golden Eagles and wind turbines; and collaboration of a review of over 400 species for assessment under the Endangered Species Act. The former is looking to improve collision models for energy companies seeking to build wind turbines. The United States Fish and Wildlife Service approve permits for eagle fatalities, that is, a limit on how many can be struck without incurring a hefty fine. If the company breaches this limit, then they are subject to a fine, which can be so steep it could bankrupt the often-small energy firms. The rate of permit approval is increasing due to collision prediction models which reward developers for more hours logged surveying the area – in theory, a permit can be granted by having someone stand with binoculars for a long time. These current models can over- and under-predict where Golden Eagles are present because population sizes aren’t currently included as they are in current European models. This runs the risk of building wind farms where they shouldn’t and refraining from the building where they should. Applied Biomathematics is developing species distribution models that project the abundance of breeding and non-territorial individuals onto the landscape; this way sites can be considered without collecting new population data. It is also a challenge collecting the data they require because the field surveyors keep their data hidden. Once they hear an electricity company is involved, they fear nest sites will be removed so construction can begin. The second project works in conjunction with the Electric Power Research Institute which is a non-profit research group funded by electricity companies in the USA. An environmental group agreed on a settlement with the Fish and Wildlife Service to review over 400 species for assessment under the Endangered Species Act. A deadline has been given for the species assessment which has utility companies and regulators scrambling to conform to the nearly impossible timeline to produce assessments — which is when an army of consultants are contracted. Despite being a mainly mathematical consultancy, Applied Biomathematics has conducted a series of studies that required: a light dusting of theory; heavy reviews of literature; law; policy; and current practises to help suggest ways to get the best results out of conservation plans that address multiple species.
This has been a brief if on the long side, a summary of my time working in the consultancy sector. My first opinions of consultancy were common among others I have spoken to; that consultancy is an extortion racket preying on unsuspecting victims. This couldn’t be further from the truth. This myth seems to come from the “Golden Rule” of consultancy: however much you think it will cost, triple it. A premise not so unfamiliar in academic circles, but instead applied to time. This rule of thumb is true, but there is a good reason for it. In reality, the client approaches the consultant unaware how much a project will cost – which is why they approach the consultant in the first place; they’re not the expert – and, in truth, neither does the consultant. Any complex problem requires time and resources invested in a coherent attempt at an answer is provided. By quoting three times as much as what the consultant anticipates relieves the burden of asking for more funding if problems are encountered, or if the analysis takes longer than anticipated. If the project comes in under budget, well that’s money kept for a rainy day when contracts may be scarce. If there is an overspend, then more funding must be requested, which can reduce the client’s faith in the consultant. It actually makes a lot of sense in that regard. I also used to think that consultancy was very dry and wouldn’t utilise my skills. Where I got this idea from I, have no idea, but it was there and is probably true for many others. The working environment was almost identical to my daily PhD work, but the questions being asked were markedly different. In academic projects your work is mainly exploratory, one can investigate interesting phenomena as it’s encountered; whereas in consultancy the work is direct, where satisfying the client is the motivating factor. Funding is also similar, rather than applying for grants, the consultant is on the look-out for contracts. So, I can say that the only real differences that I found between consultancy and academia were that: questions are asked in a different way, and the focus on exploratory vs. focused work is almost polarised, albeit with some inevitable overlap.
I found the whole experience incredibly rewarding; not only was I able to gain a different scientific perspective, I also had a break from PhD work which gave me time to think about concepts and ideas. I managed to meet some wonderful people that offered me their gracious hospitality and gained a few friends along the way. There was also the additional benefit of living 2 hours outside of New York City, which allowed me to visit one of the most interesting places in the world. While I was there I managed to see no less than 4 Broadway shows; I highly recommend ‘Jersey Boys’. Long Island is a beautiful place, and I will look on my time there with fond memories. To sign off, I will leave a message from Nick Friedenberg to other PhD students contemplating consultancy:
“In my experience, people in the industry and regulatory agencies are commonly saddled with problems just beyond the scope of their training. This is true for academics as well, and it is the sort of thing that keeps us interested in our work. However, outside of academia is a world of limitations that make learning new things much harder. The analytical skills you are learning, particularly when they combine mathematical techniques with a mastery of metaphor, prepare you to fill the role of collaborator with non-academic scientists and engineers. Pursuing such roles can be done as an academic, but do not overlook opportunities in the private sector. Here at Applied Biomathematics, we have seen some people come through like post-docs, returning to university positions after three years. Others have gone on to other consultancies or into agency work. And a select few stayed, kept up their academic network, published regularly, and returned to academics as full professors. In short, the private sector needs you, will make you feel valuable, can help you flourish as a scientist, and is not a black hole.”