It is probably safe to say that the job description of an ecologist in 2016 is quite different from that of an ecologist back in the 1970’s or 1980’s. Our work today involves computer programs and fancy technology, some of which make our work much easier. But some appear to make it a lot harder.

How much statistics and mathematics does an ecologist need to know nowadays? Quite a bit, as I have come to find out. Of course employers still seek individuals with a well-rounded background in the environmental sciences, natural resource management, biological sciences, and social sciences. However, they are also increasingly demanding proficiency in geographic information systems (GIS) such as ArcGIS or QGIS, programming skills such as R code or Python, and advanced statistical knowledge.

For too many of us, this comes as somewhat of a surprise at the end of our academic programs. We think back to our second or third year when we got to choose our elective courses – and we remember quite distinctly how we dismissed that intermediate statistics course. Instead, we chose that field course in ecology where we got to spend time in the mountains to count birds or live-trap cute mammals. At the time, the decision was a no-brainer, but in retrospect many of us wish that we hadn’t selected only fun courses.

Most early-career ecologists wish that they had acquired a better understanding of statistics and programming in their academic programs. (Creative Commons; Photo by Sybren Stuevel)

A recent online survey conducted by one of Lincoln University’s researchers (Tim Curran) showed that most early-career scientists who had studied biology as undergraduates now found themselves lacking in the mathematics and statistics department. What was surprising to me was how many of them wished that they had taken more quantitative courses: 90% of respondents wanted more mathematics designed for ecology students, and an astonishing 95% wanted more statistics classes. The vast majority of them (75%) felt that they didn’t learn enough about mathematical models in their ecology classes and that the level of mathematics was too low. In retrospect, some wished that roughly a third of their program had focused on quantitative disciplines to prepare them better for their career.

Having had only one introductory statistics course myself, I now share that sentiment. The reason for this is that we need to analyse increasingly large sets of data: data that used to take years (sometimes decades) to collect on foot, we can now collect within months. Instead of working with a few dozen samples, we can now work with hundreds, even thousands, of samples. Our computers become better at analysing these complex datasets, but we often have a difficult time understanding the results.

Particularly with regards to monitoring in wildlife research, technological advancement has been incredibly rapid in the past decade. As a result, wildlife ecologists are spending an increasing amount of time in the office instead of in the field. We are now able to conduct more of our field research from a distance using satellite and remote sensing technology. This is somewhat ironic, given how many people enter this area of biology to spend more time in nature.

In my undergraduate studies at the University of Alberta (Canada) I attended a seminar by Lu Carbyn. He lectured on how he spent several years in the 1980’s following wolves in Wood Buffalo National Park in northern Alberta – on foot and unpaid. His mission was to get data on bison and wolf movements on the landscape and observe the interactions between the animals. At the time, Lu of course didn’t have the technology available that we do today.

Today we would capture a few bison and a few wolves and fit them with GPS-collars to track them via satellites. It would require some initial man-power and resources to get the collars on the animals, but once they were released again, the information on the animals’ movements would be collected remotely: GPS-collars transmit signals at set intervals to satellites orbiting Earth, which in turn pass the signal on to a remote server on the ground which biologists can access at any time. The only time the animals would need to be approached again would be either to retrieve a collar from a dead animal or to gather additional information on body condition or reproduction. What I have often wondered is whether Lu, had he had the technology we do today, would have done his research on foot anyway to spend time in the wilderness instead of in an office.

     

For those of us who want to bring their knowledge up to speed, books are of course an excellent choice. But our greatest resource is the internet: never has our access to (free!) education been easier than it is today. Coursera is only one of many examples of MOOCS (Massively Open Online Courses) that offer distance courses on a variety of topics run by renowned universities such as Stanford University, University of Michigan, and Harvard University. These include subjects in ever-increasing popularity such as web design, R programming, and academic English writing.

While it is certainly debatable whether this kind of education is as effective as in-class or hands-on learning (or how it might impact the future of small universities), it is an option for students who find themselves lacking experience on a certain topic.

I believe that these are very exciting times to be an ecologist. Our technological advances in ecology enable us to gather information on our natural world more quickly and in greater quantities than ever before. In addition, we have access to information and resources that our colleagues could only dream of 30 years ago. Our challenge now is to keep pace.

The author Christina Stinn is a postgraduate student in the Master of International Nature Conservation taught jointly at Lincoln University and University of Göttingen. She wrote this article as part of her assessment for ECOL 608 Research Methods in Ecology.