Seeing the wood for the trees

11 07 2016
The Forest Synopsis: Photo of the Anamalai Tiger Reserve, India, by Claire Wordley

The Forest Synopsis: Photo of the Anamalai Tiger Reserve, India, by Claire Wordley

From the towering kapoks of South America to the sprawling banyans of South Asia, from misty cloud forests to ice-covered pines, forests are some of the most diverse and important ecosystems on Earth. However, as conservationists and foresters try to manage, conserve and restore forests across the world, they often rely on scanty and scattered information to inform their decisions, or indeed, no information at all. This could all change.

This week sees the launch of the Forest Synopsis from Conservation Evidence, a free resource collating global scientific evidence on a wide range of conservation-related actions. These aim to include all interventions that conservationists and foresters are likely to use, such as changing fire regimes, legally protecting forests or encouraging seed-dispersing birds into degraded forests.

Making conservation work

“We hear a lot about how important it is to do evidence-based conservation”, says Professor Bill Sutherland at the University of Cambridge, UK, “but in reality getting a handle on what works is not easy. That’s why we set up Conservation Evidence, to break down the barriers between conservationists and the scientific evidence that they need to do their jobs.” 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 »





Disadvantages of marine protected areas

29 02 2016

 

 

 

Stop wasting time

Stop wasting time





Biowealth

24 02 2016

frogWhile I’ve blogged about this before in general terms (here and here), I thought it wise to reproduce the (open-access) chapter of the same name published in late 2013 in the unfortunately rather obscure book The Curious Country produced by the Office of the Chief Scientist of Australia. I think it deserves a little more limelight.

As I stepped off the helicopter’s pontoon and into the swamp’s chest-deep, tepid and opaque water, I experienced for the first time what it must feel like to be some other life form’s dinner. As the helicopter flittered away, the last vestiges of that protective blanket of human technological innovation flew away with it.

Two other similarly susceptible, hairless, clawless and fangless Homo sapiens and I were now in the middle of one of the Northern Territory’s largest swamps at the height of the crocodile-nesting season. We were there to collect crocodile eggs for a local crocodile farm that, ironically, has assisted the amazing recovery of the species since its near-extinction in the 1960s. Removing the commercial incentive to hunt wild crocodiles by flooding the international market with scar-free, farmed skins gave the dwindling population a chance to recover.

redwoodConservation scientists like me rejoice at these rare recoveries, while many of our fellow humans ponder why we want to encourage the proliferation of animals that can easily kill and eat us. The problem is, once people put a value on a species, it is usually consigned to one of two states. It either flourishes as do domestic crops, dogs, cats and livestock, or dwindles towards or to extinction. Consider bison, passenger pigeons, crocodiles and caviar sturgeon.

As a conservation scientist, it’s my job not only to document these declines, but to find ways to prevent them. Through careful measurement and experiments, we provide evidence to support smart policy decisions on land and in the sea. We advise on the best way to protect species in reserves, inform hunters and fishers on how to avoid over-harvesting, and demonstrate the ways in which humans benefit from maintaining healthy ecosystems. Read the rest of this entry »





It’s not always best to be the big fish

3 02 2016

obrien_fish_2Loosely following the theme of last week’s post, it’s now fairly well established that humans tend to pick on the big species first.

From fewer big trees, declines of big carnivores, elephant & rhino poaching, to fishing down the web, big species tend to cop it hardest when it comes to human-caused ecological disturbance.

While there are a lot of different combinations of traits that make some species more vulnerable to extinction than others (see examples for legumes, amphibians, sharks & teleosts, and mammals), one of the main ones is species size.

Generally speaking, larger species tend to produce fewer offspring and breed later in life than smaller species. This means that despite larger species tending to live longer than their smaller counterparts, their ‘slow’ reproductive output means that they are generally more susceptible to rapid environmental change (mainly via human intervention). In other words, their capacity for self-replacement is often too low to counteract the offtake from direct exploitation or habitat loss.

Despite a reasonable scientific understanding of this extinction-risk principle, the degree to which human disturbance affects species’ distributions is much less well quantified, and this is especially true for marine species.

I’m proud to announce another fascinating paper led by my postdoc, Camille Mellin, that has just come out online in Nature CommunicationsHumans and seasonal climate variability threaten large-bodied coral reef fish with small ranges.

With the world’s largest combined dataset of coral reef fish surveys for the entire Indo-Pacific (including the coral reef fish biodiversity hotspot — the Coral Triangle), we examined which conditions best described the distribution of fishes over a range of body sizes. 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 »





When science is ignored: Mauritius starts culling 18,000 threatened fruit bats

8 11 2015

JS7D2844aRrHere’s a depressing emergency post by Fabiola Monty.

I started working on this article to discuss how useful science is being ignored in Mauritius.

The Mauritian government has decided to implement a fruit bat cull as an ‘urgent response’ to the claims of huge economic losses by fruit farmers, a decision not supported by scientific evidence. We have now received confirmation in Mauritius through a local press communiqué that on 7 November 2015, The Mauritian Ministry of Agro Industry and Food Security in collaboration with the local Police Department and Special Mobile Force will start the culling of 18,000 bats in their natural habitats “with a view to reducing the extent of damages caused to fruits by bats”.

Tackling human-wildlife conflicts can indeed be challenging, but can the culling of 18,000 endemic Mauritian flying fox (Pteropus niger) resolve ‘human-wildlife conflict’ in the land of the dodo? In the case of Mauritius, scientific evidence not only demonstrates that the situation has been exaggerated, but that there are alternatives to bat culling that have been completely brushed aside by policy makers.

JS7D3726aRrAre the Mauritius fruit bats agricultural pests?

While fruit bats are being labelled as serious pests, scientific evidence shows instead that their impacts have been exaggerated. A recent (2014) study indicates that bats damage only 3-11% of fruit production, with birds also contributing to 1-8% of fruit loss. Rats are also probable contributors to fruit damage, but the extent remains unquantified. Interestingly, more fruits are lost (13-20%) because they are not collected in time and are left to over-ripen.

While the results of the study were communicated to legislators a few months before they made the decision to cull, it is clear that these were ignored in favour of preconceived assumptions.

Are there too many fruit bats? Read the rest of this entry »








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