Tag Archives: Publishing

Scientific journals should be judged, not ranked

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Aspiring scientists quickly learn that where they publish their hard earned data is important for career progression. A paper in a prestigious journal pushes them up the professional ladder faster than the same paper in an obscure one.

This has led to an obsession with quantifying the prestige of a journal using impact metrics. Over at Conservation Bytes, Corey Bradshaw presents a RShiny App to rank ecology and conservation journals using a composite of different citation metrics. His app is based on a published paper, so you can be sure that it technically sound. It is not my intention to criticise these efforts; if you want to rank jounals, then this composite approach is definitely the way to go.

However, I don’t think there is much to gain from ranking journals based on their impact metrics. Moreover, scientists – especially early-career scientists – would be better off judging journals based on whether is will ensure that their paper reaches the right audience.

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The scalability of macroecology

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Russian Dolls

No matter at which scale you look at it, nature is remarkable.

Like many others, I was taught ecology in a very hierarchical way: individual organisms are part of a wider populations of species, collections of species form communities and communities come together to make up ecosystems. Similarly, single trees are nested within forests, which aggregate to form biomes. I’m sure you can come up with many comparable examples.

The trouble with such neat spatial hierarchies is that they lure us into believing that if patterns appear similar at several different spatial scales, then the processes leading to these patterns should also be similar. It’s so easy to assume that nature is like a set of Russian Dolls: each daughter exactly the same as its mother, only slightly smaller. But this is not necessarily the case.

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Species distribution modelling is not as simple as you think

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One of the most fruitful sub-fields in ecology is using climate variables to predict species’ geographic distributions. For the uninitiated, species distribution modelling assumes that species are limited in their distributions to suitable climate zones. By studying the environmental conditions where species are known to occur, you can infer the total geographic distribution by calculating the suitability of unsampled regions based on the environmental. Furthermore, using the same principle, species distribution modelling can forecast the effect of future climate change of the distribution of life on earth.

Unfortunately, studies have shown that these fancy climate-based techniques cannot consistently outperform much simpler ones based on spatial phenomena. For instance, spatial interpolation between point occurrences outperforms sophisticated climate-based predictions. Similarly, elaborate climate-based predictions perform no better than expected from random chance.

The trouble lies in the spatially-structured world we live in. Species distributions, especially at large spatial scales, are spatially-autocorrelated due to constrained dispersal. Similarly, climate variables are also spatially structured because the meteorological processes at proximal regions are generally more similar than those at distant sites.

When trying to link species distributions to climate conditions, the challenge lies is separating spatial and environmental correlations in species distributions. Specifically, we should identify three patterns in the geographical species distributions.

  • We must first identify ‘true’ correlations with the environment, which are independent of spatial patterns (E|S).
  • Next, we must identify the environmental-associations that also have a strong spatial structure (E∩S). This is known as exogenous spatial autocorrelation because it is due to autocorrelation is the underlying variables.
  • Finally, we need to identify spatial patterns that are completely independent of environmental conditions (S|E). This is called endogenous spatial autocorrelation because it supposedly stems from spatial processes, such as dispersal.

In our latest study just published online at Ecography, we set out to quantify the degree of environmental correlation, exogenous and endogenous spatial autocorrelation in the distributions of 4 423 species of amphibians, reptiles, birds and mammals in Africa. Continue reading →

The startup culture of conservation entrepreneurship

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I’ve written about the need for self-started conservation initiatives on this blog before. And now I am pleased to boast that some of these ideas have just been published online in Conservation Biology. (If you don’t have subscription access through the publisher’s website, feel free to leave a comment below and I’ll forward the article to you as a PDF).

It’s a short opinion piece that is mainly intended to introduce the concept of social entrepreneurship to an audience of conservation scientists. The article should definitely not be considered as a how-to guide to conservation entrepreneurship, nor is it a comprehensive review of all the ways entrepreneurship can help to protect biodiversity. Instead, I hoped to convey three key points:

(1) there are conservation problems that are especially amenable to small, fast bootstrapped solutions;

(2) there are new ways of funding conservation initiatives that weren’t available 10 years ago; and

(3) most early-career conservation biologists in the current employment landscape will, at some point, be unemployed, so self-started conservation initiatives could become a necessity.

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MacArthur and Wilson’s Radical Theory wasn’t actually radical (even great ideas in ecology go unnoticed)

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Most ecologists know about the Theory of Island Biogeography; the theory that diversity patterns on islands are the consequence of dispersal from a mainland source. Robert MacArthur and E.O. Wilson presented this theory first as a research paper in 1963 and then as a monograph in 1967. The rest, as they say, is history.

The Theory of Island Biogeography is remarkable because it suggests that patterns of species co-existence are the consequence of chance, history and random dispersal. Before its publication, community ecologists generally assumed that species co-existence was due to deterministic niche-assembly, where the number and relative abundance of species were a result of ecological niches and the functional roles of each species.

The theory placed randomness at the forefront to community ecology. It also paved the way for Stephen Hubbell’s Unified Neutral Theory of Biodiversity and Biogeography; one of the most influential ecological theories in 21st century. In fact, the introductory chapter of Hubbell’s monograph (like this blog post) was titled “MacArthur and Wilson’s Radical Theory” in reverence to their path-breaking work.

Like the theory itself, MacArthur and Wilson have also reached cult-like status. Perhaps a most telling way of illustrating this fact is not by listing the prizes awarded to these two men (and there were many), but rather by listing the academic prizes named after them! The Ecological Society of America, for instance, awards the ‘Robert H. MacArthur Award‘ to eminent mid-career ecologists and the American Society of Naturalists grants the ‘Edward O. Wilson Naturalist Award‘ to mid-career researchers who make significant contributions to a particular ecosystem of group of organisms. Similarly, the International Biogeography Society has the ‘MacArthur & Wilson Award‘ for notable contributions to the field of biogeography.  Needless to say, MacArthur and Wilson are very influential and well-respected by contemporary ecologists (well, in most cases…).

The funny thing is that their paradigm shifting idea was actually proposed two decades earlier, by the less well-known lepidopterist Eugene Munroe. Continue reading →

A how-to guide to getting your paper published in Nature or Science (UPDATED)

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NatureandScience

As an aspiring ecologist, I am well aware that publishing a paper in Nature or Science would give my career an incredible kick-start. But, like so many others, I didn’t know how to get my name printed on the glossy pages of the two oldest and most prestigious weekly scientific journals. So I did what any good scientist would do – no, this time I didn’t check Wikipedia – I knuckled down and poured over the pages in these celebrated periodicals. I spent countless nights without sleep, trying to crack the code.

Just as I was about to give up, I saw a glimmer of hope: a golden thread linking the fortunate submissions to these two behemoths of academic excellence. I managed to reverse-engineer the path to success and I will be so generous to share my astounding findings with you. But before I do that, a word of warning: my how-to guide only applies to ecological studies. Physicists, physiologists and… um… uh… anyone else (I ran out of alliterative scientific sub-fields) will have to find their own strategies. Continue reading →