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 »





Sensitive numbers

22 03 2016
toondoo.com

A sensitive parameter

You 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). The good thing about even these simple models is that it is fairly straightforward to interpret the ‘strength’ of the relationship, in other words, how much variation in one thing can be explained by variation in another. Provided the relationship is real (not random), and provided there is at least some indirect causation implied (i.e., it is not just a spurious coincidence), then there are many simple statistics that quantify this strength — in the case of our simple regression, the coefficient of determination (R2) statistic is a usually a good approximation of this.

In the case of more complex multivariate correlation models, then sometimes the coefficient of determination is insufficient, in which case you might need to rely on statistics such as the proportion of deviance explained, or the marginal and/or conditional variance explained.

When you go beyond this correlative model approach and start constructing more mechanistic models that emulate ecological phenomena from the bottom-up, things get a little more complicated when it comes to quantifying the strength of relationships. Perhaps the most well-known category of such mechanistic models is the humble population viability analysis, abbreviated to PVA§.

Let’s take the simple case of a four-parameter population model we could use to project population size over the next 10 years for an endangered species that we’re introducing to a new habitat. We’ll assume that we have the following information: the size of the founding (introduced) population (n), the juvenile survival rate (Sj, proportion juveniles surviving from birth to the first year), the adult survival rate (Sa, the annual rate of surviving adults to year 1 to maximum longevity), and the fertility rate of mature females (m, number of offspring born per female per reproductive cycle). Each one of these parameters has an associated uncertainty (ε) that combines both measurement error and environmental variation.

If we just took the mean value of each of these three demographic rates (survivals and fertility) and project a founding population of = 10 individuals for 1o years into the future, we would have a single, deterministic estimate of the average outcome of introducing 10 individuals. As we already know, however, the variability, or stochasticity, is more important than the average outcome, because uncertainty in the parameter values (ε) will mean that a non-negligible number of model iterations will result in the extinction of the introduced population. This is something that most conservationists will obviously want to minimise.

So each time we run an iteration of the model, and generally for each breeding interval (most often 1 year at a time), we choose (based on some random-sampling regime) a different value for each parameter. This will give us a distribution of outcomes after the 10-year projection. Let’s say we did 1000 iterations like this; taking the number of times that the population went extinct over these iterations would provide us with an estimate of the population’s extinction probability over that interval. Of course, we would probably also vary the size of the founding population (say, between 10 and 100), to see at what point the extinction probability became acceptably low for managers (i.e., as close to zero as possible), but not unacceptably high that it would be too laborious or expensive to introduce that many individuals. Read the rest of this entry »





Avoiding genetic rescue not justified on genetic grounds

12 03 2015
Genetics to the rescue!

Genetics to the rescue!

I had the pleasure today of reading a new paper by one of the greatest living conservation geneticists, Dick Frankham. As some of CB readers might remember, I’ve also published some papers with Dick over the last few years, with the most recent challenging the very basis for the IUCN Red List category thresholds (i.e., in general, they’re too small).

Dick’s latest paper in Molecular Ecology is a meta-analysis designed to test whether there are any genetic grounds for NOT attempting genetic rescue for inbreeding-depressed populations. I suppose a few definitions are in order here. Genetic rescue is the process, either natural or facilitated, where inbred populations (i.e., in a conservation sense, those comprising too many individuals bonking their close relatives because the population in question is small) receive genes from another population such that their overall genetic diversity increases. In the context of conservation genetics, ‘inbreeding depression‘ simply means reduced biological fitness (fertility, survival, longevity, etc.) resulting from parents being too closely related.

Seems like an important thing to avoid, so why not attempt to facilitate gene flow among populations such that those with inbreeding depression can be ‘rescued’? In applied conservation, there are many reasons given for not attempting genetic rescue: Read the rest of this entry »





When human society breaks down, wildlife suffers

22 01 2015

bearGlobal human society is a massive, consumptive beast that on average degrades its life-support system. As we’ve recently reported, this will only continue to get worse in the decades to centuries to come. Some have argued that as long as we can develop our societies enough, the impact of this massive demographic force can be lessened – a concept described by the environmental Kuznets curve. However, there is little evidence that negative societal impact on the environment is lessened as per capita wealth exceeds some threshold; unfortunately environmental damage tends to, on average, increase as a nation’s net wealth increases. That’s not to say that short-term improvements cannot be achieved through technological innovation – in fact, they will be essential to offset the inexorable growth of the global human population.

So poor nations as well as the wealthy ones are responsible for environmental damage. Poorer nations often have ineffective governance systems so they fail to enforce compliance in environmental regulations, but wealthier nations often exploit a high proportion of their natural resources, with the inevitable environmental damage this entails. In some cases however, biodiversity can temporarily escape some of the ravages of society because humans either perceive the area to be too dangerous, or otherwise have no incentive to go there. There are some good examples of the latter, such as the vicinity around the Chernobyl nuclear reactor that melted down in 1986, or the Korean demilitarised zone.

In this vein, I just stumbled across an extremely interesting paper today published online early in Conservation Biology that describes trends in charismatic wildlife (i.e., big mammals) as the former Soviet Union collapsed in 1991 and societal breakdown ensued. The authors had access to an amazing dataset that spanned the decade prior to the collapse, the decade immediately following, and a subsequent decade of societal renewal. What they found was fascinating. Read the rest of this entry »





Psychological toll of being a sustainability scientist

8 12 2014

depressed scientistLike many academics, I’m more or less convinced that I am somewhere on the mild end of the autism spectrum. No, I haven’t been diagnosed and I doubt very much that my slight ‘autistic’ tendencies have altered my social capacity, despite my wife claiming that I have only two emotions – angry or happy. Nor have they engendered any sort of idiot savant mathematical capability.

But I’m reasonably comfortable with mathematics, I can do a single task for hours once it consumes my attention, and I’m excited about discovering how things work. And I love to code. Rather than academics having a higher innate likelihood of being ‘autistic’, I just think the job attracts such personalities.

In the past few years though, my psychological state is probably less dictated by the hard-wiring of my ‘autidemic’ mind and more and more influenced by the constant battery of negative information my brain receives.

Read the rest of this entry »





Using ecological theory to make more money

1 12 2014

huge.9.46974Let’s face it: Australia doesn’t have the best international reputation for good ecological management. We’ve been particularly loathsome in our protection of forests, we have an appalling record of mammal extinctions, we’re degenerate water wasters and carbon emitters, our country is overrun with feral animals and weeds, and we have a long-term love affair with archaic, deadly, cruel, counter-productive and xenophobic predator management. To top it all off, we have a government hell-bent on screwing our already screwed environment even more.

Still, we soldier on and try to fix the damages already done or convince people that archaic policies should be scrapped and redrawn. One such policy that I’ve written about extensively is the idiocy and cruelty of the dingo fence.

The ecological evidence that dingoes are good for Australian wildlife and that they pose less threat to livestock than purported by some evidence-less graziers is becoming too big to ignore any longer. Poisoning and fencing are not only counter-productive, they are cruel, ineffective and costly.

So just when ecologists thought that dingoes couldn’t get any cooler, out comes our latest paper demonstrating that letting dingoes do their thing results in a net profit for cattle graziers.

Come again? Read the rest of this entry »





Human population size: speeding cars can’t stop quickly

28 10 2014

Stop breeding cartoon-Steve Bell 1994Here at ConservationBytes.com, I write about pretty much anything that has anything remotely to do with biodiversity’s prospects. Whether it is something to do with ancient processes, community dynamics or the wider effects of human endeavour, anything is fair game. It’s a little strange then that despite cutting my teeth in population biology, I have never before tackled human demography. Well as of today, I have.

The press embargo has just lifted on our (Barry Brook and my) new paper in PNAS where we examine various future scenarios of the human population trajectory over the coming century. Why is this important? Simple – I’ve argued before that we could essentially stop all conservation research tomorrow and still know enough to deal with most biodiversity problems. If we could only get a handle on the socio-economic components of the threats, then we might be able to make some real progress. In other words, we need to find out how to manage humans much more than we need to know about the particulars of subtle and complex ecological processes to do the most benefit for biodiversity. Ecologists tend to navel-gaze in this arena far too much.

So I called my own bluff and turned my attention to humans. Our question was simple – how quickly could the human population be reduced to a more ‘sustainable’ size (i.e., something substantially smaller than now)? The main reason we posed that simple, yet deceptively loaded question was that both of us have at various times been faced with the question by someone in the audience that we were “ignoring the elephant in the room” of human over-population.

Read the rest of this entry »








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