They always whinge about the maths

18 11 2010

If you don’t know what a differential equation is, you are not a scientist” – Hugh Possingham 2009

At the end of 2009 I highlighted a new book edited by good mates Navjot Sodhi and Paul Ehrlich, Conservation Biology for All, in which Barry Brook and I had written a chapter. Now, despite my vested interest, I thought (and still think) that it was one of the best books on conservation biology yet published, and the subsequent reviews appear to be validating my subjective opinion.

I’ve given snippets of the book’s contents, from Paul Ehrlich‘s editorial on the human population’s rising negative influences on biodiversity, to a more detailed synopsis of our chapter, The Conservation Biologist’s Toolbox, and I’ve reproduced a review printed in Trends in Ecology and Evolution.

The latest review by Nicole Gross-Camp of the University of East Anglia published in Ecology is no less flattering – in fact, it is the most flattering to date. So this is by no means a whinge about a whinge; rather, consider it an academic lament followed by a query. First, the review:

Reaching higher in conservation

If a book could receive a standing ovation—this one is a candidate. Sodhi and Ehrlich have created a comprehensive introduction to conservation biology that is accessible intellectually, and financially, to a broad audience—indeed it is Conservation biology for all. The book is divided into 16 chapters that can stand alone and are complementary when read in sequence. The authors make excellent use of cross citations of chapters, a useful and often overlooked feature in texts of this nature. In the introductory chapter, Sodhi and Ehrlich eloquently summarize the gravity of the conservation crisis and still retain an optimistic outlook that encourages the reader to continue. I particularly found their recognition of population growth, consumption, and ethics in the conservation arena refreshing and a step toward what will likely become the next major issues of discussion and research in the conservation field.

The quality and clarity of the writing makes this book an invaluable asset to the conservationist’s toolbox. In Chapter 1, the description of the emergence of the conservation field provides a foundation for understanding how the field of conservation has changed and is changing. Chapters 2 through 12 summarize the major accomplishments and emerging areas of conservation research, detailing progression in pertinent domains such as ecosystem services, climate change, invasive species, and extinction. Peres’s ‘‘overexploitation’’ chapter astutely presents the current state of research surrounding hunting and extraction, flagging knowledge gaps such as understanding the impacts of selective logging, how extraction of non-timber forest products (NTFPs) affects demographic viability of plant populations, and the degree to which spillover from source–sink populations can sustain human needs for protein. In this regard, Conservation biology for all may be viewed as a resource for students searching for a pertinent research topic.

Chapters 13 to 15 focus explicitly on the human role in conservation exploring issues at the boundary between conservation and the social sciences. Claus et al. (Chapter 14) stands out among other conservation texts in its unabashed premise that, ‘‘understanding human activities and human roles in conservation is fundamental to effective conservation,’’ (emphasis mine). The authors’ eloquently describe the complex interplay of the disciplines within conservation biology highlighting the importance of incorporating the social dimensions beyond empty rhetoric. Claus et al. explore the role of power, equity, institutional and cultural beliefs, and governance in affecting conservation outcomes including excellent integration of succinct case studies.

In the final chapter, Bradshaw and Brook provide an overview on the ‘‘tools’’ for designing and analyzing ecologically grounded conservation research. This chapter is likely to be the most challenging for non-English speakers based on the inclusion of technical language and basic statistics. Though I commend the authors for their extensive references, I would have appreciated a few examples to clarify some of the techniques described (i.e., replication versus pseudoreplication, randomization, or the importance of controls). Furthermore I would have liked to see a similar chapter focusing on social science methods of data collection.

A final aspect that I would particularly note is the editors’ explicit targeting of people from tropical countries and intention to, ‘‘[p]rovide cutting-edge but basic conservation science to developing as well as developed country inhabitants.’’ True to the editors’ declaration, the book is available for free download online (www.ebook3000.com). The editors, in partnership with the publishers, have also arranged that the proceeds from the book will go toward the purchase and distribution of hard copies for conservationists in developing nations who would otherwise be unable to purchase the book. This is an ethic that I hope we can all emulate to achieve the common goal of conservation biology for all.

First, a big thanks to Dr. Gross-Camp for her resounding thumbs-up of the book. What I want to do now though is share with you a growing concern I have about the demise of numeracy amongst conservation biology students.

It is my opinion, and I have many colleagues who support this, that the questions with which we conservation biologists are increasingly faced are becoming more complex. Ecosystems are by definition complicated creatures that require a good deal of data and sophistication to tease pattern from the emergent chaos they present to the empiricist. You can’t put an ecosystem in a bottle and subtly adjust single conditions one at a time, so we must fall back on more mensurative (gradients) approaches. We talk a lot about this in our chapter.

If you accept the above argument, then it’s no stretch of logic to understand that increasingly sophisticated mathematical skills are required to handle the masses of data, the complicated questions and multi-dimensional settings that conservation issues are throwing at us. I argue strongly that without mathematical skills, you won’t ever be a very effective conservation scientist (although you *may* successfully apply conservation knowledge without the ability to count to 3 – think of most politicians).

So why is it then that instead of increasing the mathematical component of ecological education, we are (at least in many circumstances), reducing it? Even my own university, recently rated 73rd best university in the world and 4th in Australia, is abandoning mathematics pre-requisites for its incoming undergraduates. Is this just insane, or merely a short-term approach to put the maximum number of (under-trained) bums on seats?

And I see the results every day. Most of my own students and post-docs are not from around here. I even discussed the faltering mathematical and grammatical training of high school students with some Adelaide private school teachers last weekend, who all agreed with me (well, at least from the poor grammar side of things). The result is that most of our students can’t  write properly, nor do they have basic mathematical training, so I can’t use them.

So when I read Dr. Gross-Camp’s line that our chapter would be the “most challenging for non-English speakers based on the inclusion of technical language and basic statistics”, I was a bit taken aback. First, don’t most mathematical terms transcend language barriers (numbers certainly do, and even pseudoreplication is pseudoreplicación in Spanish, pseudoréplication in French, pseudoreplicação in Portuguese, or the same word in many other languages)? Second, I thought we did a pretty good job of defining every bit of jargon used in the chapter (please correct me if you disagree).

I admit that many people seem to have a mental block when it comes to maths, but considering they are essential for good conservation science, and they are no more difficult than the other conservation complexities (biological, socio-economic and otherwise) we must tackle, the whinge about maths seems a little superficial to me.

I don’t know – I’m admittedly biased. But considering the large number of people who requested our Conservation Biologist’s Toolbox chapter (and of course, you are welcome to request a copy if you haven’t already) after the post came out online, it obviously struck a chord. So, for those of you who have read it, and especially those of you who live in developing countries and whose first language is not English, please, provide some feedback here.

I need to get this right so that future generations of conservation biologists have the mathematical skills necessary to solve our world’s biggest problems.

CJA Bradshaw

 


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16 03 2019
Modelling for Empirical Scientists Introduction: Our ‘functional’ world – The Bonser Lab

[…] couldn’t really do ecology if you didn’t know how to construct even the most basic mathematical model — even a simple regression is a model (the non-random relationship of some variable to […]

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22 03 2016
Sensitive numbers | ConservationBytes.com

[…] couldn’t really do ecology if you didn’t know how to construct even the most basic mathematical model — even a simple regression is a model (the non-random relationship of some variable to another). […]

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20 01 2011
CJAB

This book is now available free to download here.

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18 11 2010
Melanie HAMEL

Corey, I remember our long conversations about this subject at the SER in Darwin a few years ago and I am pleased to say that these taught me a lot lot more than you think… I think I am myself a pretty good example. I have not read your chapter yet (will do though), but here is my story to illustrate your say:

As a student, I was not that attracted to numbers (not repulsed either, by the way), and I have to admit my thoughts were like the following ‘I did not undertake Ecology studies to learn further maths, I just want to understand everything about ecosystems’. I think most student think the same way at the beginning of their biology/ecology studies but tell me if I am wrong… Then I discovered during my numerous trainships/internships (professors encourage us to do so in the French academic system) the importance and utility of numbers in ecology, and more precisely models and programming software. I think that’s when I started to understand that a good ecologist has to be a good ‘quantitative’ ecologist… Although I did not want to be a ‘modeler’ nor a ‘mathematician’, I naturally started to develop my programming / stats / data analysis skills via those internships. I have tried to fight against it because this did not match my idea of what ecology should be. Today, with more experience (and quantitative skills), I have to admit that I get ecology/conservation jobs and contracts because I know how to use numbers to describe and analyze ecological processes… NOT because I know how to get along in the field ! Isn’t it a good argument to convince you, young students (ok I’m not much older…) ?

I have to thank you Corey for ‘showing me the way’. Because every single day at work, I can still hear you telling me this : ‘You have excellent quantitative skills to become a good conservation ecologist, don’t waste them focusing on one taxa or on fieldwork’. This statement, added to my current mentor’s one ‘The more important is the tool, not the subject’, have been driving all my science-related choices for the last few years and will hopefully drive the pursuit of my (young) conservation ecologist career.

I am modest, and definitely a fieldworker but I know that what makes me a better ecologist than another field person are my quantitative skills.

Anyway, I hope this is relevant. All the best to your readers, no matter if they like numbers or not.

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