Shadow of ignorance veiling society despite more science communication

19 04 2016

imagesI’ve been thinking about this post for a while, but it wasn’t until having some long, deep chats today with staff and students at Simon Fraser University‘s Department of Biological Sciences (with a particular hat-tip to the lovely Nick Dulvy, Isabelle Côté & John Reynolds) that the full idea began to take shape in my brain. It seems my presentation was a two-way street: I think I taught a few people some things, and they taught me something back. Nice.

There’s no question at all that science communication has never before been so widespread and of such high quality. More and more scientists and science students are now blogging, tweeting and generally engaging the world about their science findings. There is also an increasing number of professional science communication associations out there, and a growing population of professional science communicators. It is possibly the best time in history to be involved in the generation and/or communication of scientific results.

Why then is the public appreciation, acceptance and understanding of science declining? It really doesn’t make much sense if you merely consider that there has never been more good science ‘out there’ in the media — both social and traditional. For the source literature itself, there has never before been as many scientific journals, articles and even scientists writing. Read the rest of this entry »

Getting your conservation science to the right people

22 01 2016

argument-cartoon-yellingA perennial lament of nearly every conservation scientist — at least at some point (often later in one’s career) — is that the years of blood, sweat and tears spent to obtain those precious results count for nought in terms of improving real biodiversity conservation.

Conservation scientists often claim, especially in the first and last paragraphs of their papers and research proposals, that by collecting such-and-such data and doing such-and-such analyses they will transform how we manage landscapes and species to the overall betterment of biodiversity. Unfortunately, most of these claims are hollow (or just plain bullshit) because the results are either: (i) never read by people who actually make conservation decisions, (ii) not understood by them even if they read the work, or (iii) never implemented because they are too vague or too unrealistic to translate into a tangible, positive shift in policy.

A depressing state of being, I know.

This isn’t any sort of novel revelation, for we’ve been discussing the divide between policy makers and scientists for donkey’s years. Regardless, the whinges can be summarised succinctly: Read the rest of this entry »

All (fisheries) models are wrong, but some are useful (to indigenous people)

1 08 2015

miracle_cartoonAnother post from Alejandro Frid. (Note: title modified from George Box‘s most excellent quote).

As an ecologist working for indigenous people of coastal British Columbia, western Canada, I live at the interface of two worlds. On the one hand, I know that computer models can be important management tools. On the other hand, my job constantly reminds me that whether a model actually improves fishery management depends, fundamentally, on the worldview that shapes the model’s objectives. To explore why, I will first review some general concepts about what models can and cannot do. After that, I will summarize a recent model of herring populations and then pull it all together in a way that matters to indigenous people who rely on marine resources for cultural integrity and food security.

Models do a great job of distilling the essence of how an ecosystem might respond to external forces—such as fisheries—but only under the specific conditions that the modeller assumes to be true in the ‘world’ of the model. Sometimes these assumptions are well-grounded in reality. Sometimes they are blatant but necessary simplifications. Otherwise, it would be difficult to ask questions about how major forces for which we have no historical precedent—such as the combined effects of industrial fisheries, ocean acidification and climate change—might be altering the ocean. For instance, due to our greenhouse gas emissions, the ocean is warming and contains less dissolved oxygen. These stressful conditions hamper the capacity of fish to grow, and appear to be on their way to shrinking the body sizes of entire fish communities1. If you want even to begin to comprehend what the ocean will look like in the long term due to these effects of climate change, it makes sense to assume, in the ‘world’ of your model, that fishing does not exist, even though you know it does. Of course, you would then acknowledge that climate change probably exacerbates the effects of fisheries, which highlights that you still have to examine the combination of these effects. And that is exactly what an excellent team of modellers did1. Read the rest of this entry »