Tuesday, January 22, 2013
Bob Paine's footprint
A great post by Ed Yong on Bob Paine's influence on ecology -both conceptually and numerically, with a large number of academic children and grandchildren.
Thursday, January 17, 2013
Who are you writing your paper with?
Choosing who you work with plays an important role in who
you become as a scientist. Every grad student knows this is true about choosing
a supervisor, and we’ve all heard the good, the bad, and the ugly when it comes
to student-advisor stories. But writing a paper with collaborators is like dealing with the
supervisor-supervisee relationship writ small. Working with coauthors can be
the most rewarding or the most frustrating process, or both.
Ultimately, the combination of personalities involved merge in such a way as to
produce a document that is usually more (but sometimes less) than the sum of its parts. The writing process and collaborative interactions are fascinating to consider all on their own.
Field Guide to Coauthors
The Little General
The Little General is willing to battle till the death for
the paper to follow his particular pet idea. Regardless of the aim or outcome
of an experiment, a Little General will want to connect it to his particular
take on things. Two Little Generals on a paper can spell disaster.
The Silent Partner
These are the middle authors, the suppliers of data and
computer code, people who were involved in the foundations of the work, but not
actively a part of the writing process.
The Nay-sayer
These are the coauthors who disagree, seemingly on
principle, with any attempt to generalize the paper. Given free rein, such
authors can prevent a work from having any generality beyond the particular
system and question in the paper. These authors do help a paper become
reviewer-proof, since every statement left in the paper is
well-supported.
The Grammar Nazi
The Grammar Nazi returns your draft of the paper covered in edits, but he has mostly corrected for grammar and style rather than content. This is not the worst coauthor type, although it can be annoying, especially if these edits are mostly about personal taste.
The Snail
This is the coauthor that you just don’t hear from. You can
send them reminder emails, give them a phone call, pray to the gods, but they
will take their own sweet time getting anything back to you. (And yes, they are probably really busy).
The Cheerleader can encourage you through a difficult writing
process or fuel an easy one. These are the coauthors who believe in the value
of the work and will help motivate you through multiple edits,
rejections, or revisions, as needed.
The Good Samaritan
The Good Samaritan is a special type of person. They aren’t
authors of your manuscript, but they read it for you out of pure generosity They
might provide better feedback and more useful advice than any of your actual
coauthors. They always end up in the acknowledgements, but you often feel like
you owe them more.
The Sage
The Sage is probably your supervisor or some scientific silverback.
They read your manuscript and immediately know what’s wrong with it, what it
needs, and distill this to you in a short comment that will change everything.
The Sage will improve your work infinitely, and make you realize how far you
still have to go.
There are probably lots of other types that I haven't thought of, so feel free to describe them in the comments. And, it goes without saying that if you coauthored a paper with me, you were an excellent coauthor with whom I have no complaints. Especially Marc Cadotte, who is often both Cheerleader and Sage :)
Thanks to Lanna Jin for the amazing illustrations!
Wednesday, January 9, 2013
Replicable methods
This has been making the internet rounds: If you were being truly honest in your methods, what would you say?
Overly honest methods in science
Mine would probably something like: "We had a sample size of 260 individuals. It may sound like we planned to have 260 plants, but actually 40 seedlings died, luckily leaving us with a nice round number."
A friend joked that hers would be: "All this work was done with a totally different experiment in mind, but this is all I could salvage."
I'm sure everyone has a few of these...
Overly honest methods in science
Mine would probably something like: "We had a sample size of 260 individuals. It may sound like we planned to have 260 plants, but actually 40 seedlings died, luckily leaving us with a nice round number."
A friend joked that hers would be: "All this work was done with a totally different experiment in mind, but this is all I could salvage."
I'm sure everyone has a few of these...
Tuesday, January 8, 2013
Monday, January 7, 2013
Reinventing the ecological wheel – why do we do it?
Are those who do not
learn from (ecological) history are doomed to repeat it?
A pervasive view within ecology is that discovery tends to
be inefficient and that ideas reappear as vogue pursuits again and again. For
example, the ecological implications of niche partitioning re-emerges as an
important topic in ecology every decade or so. Niche partitioning was well
represented in ecological literature of the 1960s and 1970s, which focused theoretical and experimental attention on how
communities were structured through resource partitioning. It
would be fair to say that the evolutionary causes and the ecological
consequences of communities structured by niche differences were one of the
most important concepts in community ecology during that time. Fast-forward 30
years, and biodiversity and ecosystem functioning (BEF) research slowly has come to the conclusion that niche
partitioning to explains the apparent relationship between species diversity and
ecosystem functioning. Some of the findings in the BEF literature could be criticized as simply being rediscoveries of classical theory and experimental evidence already in existence. How does
one interpret these cycles? Are they a failure of ecological progress or
evidence of the constancy of ecological mechanisms?
Ecology is such a young science that this process of
rediscovery seems particularly surprising. Most of the fundamental theory in
ecology arose during this early period: from the 1920s (Lotka, Volterra), 1930s (Gause) to 1960s (Wilson, MacArthur,
May, Lawton, etc). There are several reasons why this was the foundational
period for ecological theory – the science was undeveloped, so there was a void
that needed filling. Ecologists in those years were often been trained in other
disciplines that emphasized mathematical and scientific rigor, so the theory
that developed was in the best scientific tradition, with analytically resolved
equations meant to describe the behaviour of populations and communities. Most
of the paradigms we operate in today owe much to this
period, including an inordinate focus on predator-prey, competitive
interactions, and plant communities, and the use of Lotka-Volterra and consumer-resource models. So
when ecologists reinvent the wheel, is this
foundation of knowledge to blame, is it flawed or incomplete? Or does ecology fail
in education and practice in maintaining contact with the knowledge base that already
exists? (Spoiler alert – the answer is going to be both).
Modern ecologists face the unenviable task of prioritizing
and decoding an exponentially growing body of literature. Ecologists in the
1960s could realistically read all the literature pertaining to community
ecology during their PhD studies –something that is impossible today with an
exponentially growing literature. Classic papers can be harder to access than new ones: old papers are less likely to be accessible
online, and when they are, the quality of the documents is often poor. The
style and accessibility of some of these papers is also difficult for
readers used to the succinct and direct writing more common today. The cumulative
effect of all of this is that we read very little older literature and instead
find papers that are cited by our peers.
True, some fields may have grown or started apart from a
base of theory that would have been useful during their development. But it would
also be unfair to ignore the fact that ecology’s foundation is full of cracks. Certain
interactions are much better explored than others. Models of two species
interactions fill in for complex ecosystems. Lotka-Volterra and related
consumer-resource models make a number of potentially unrealistic assumptions,
and parameter space has often been incompletely explored. We seem to lack a
hierarchical framework or synthesis of what we do know (although a few people
have tried (Vellend 2010)). When models are explored in-depth, as Peter Abrams has done in many papers, we discover the complexity and possible futility
of ecological research: anything can result from complex dynamics. The cynic
then, would argue that models can predict anything (or worse, nothing). This is
unfair, since most modelling papers test hypotheses by manipulating a single
parameter associated with a likely mechanism, but it hints at the limits that current theory exhibits.
So the bleakest view of would be this: the body of knowledge that makes up ecology is inadequate and poorly
structured. There is little in the way of synthesis, and though we know many,
many mechanisms that can occur, we
have less understanding of those that are likely
to occur. Developing areas of ecology often have a tenuous connection to the
existing body of knowledge, and if they eventually connect with and contribute
to the central body, it is through an inefficient, repetitive process. For
example a number of papers have remarked that invasion biology has dissociated
itself from mainstream ecology, reinventing basic mechanisms. The most
optimistic view, is that when we discover similar mechanisms multiple times, we
gain increasing evidence for their importance. Further, each cycle of
rediscovery reinforces that there are a finite number of mechanisms that
structure ecological communities (maybe just a handful). When we use the same
sets of mechanisms to explain new patterns or processes, in some ways it is a
relief to realize that new findings fit logically with existing knowledge. For
example niche partitioning has long been used to explain co-occurrence, but
with a new focus on ecosystem functioning, it has leant itself as an
efficacious explanation. But the question remains, how much of what we do is
inefficient and repetitive, and how much is advancing our basic understanding
of the world?
By Caroline Tucker & Marc Cadotte
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