Less is MORE
EER abstracts must be lean and to the point. That style will increase their value to our busy readers. Accordingly, EER abstracts will henceforth look more like abstracts in medical journals.
Design your abstract using one of the templates
below as a suggestion. Organize your abstract in separate paragraphs. As in
the examples, begin each paragraph with a heading. Be as clear and as terse
as you can.
A useful abstract tells the reader what question you wanted to answer, what you did to do it, approximately how you did it, and what you discovered/demonstrated. No more.
EER has a broad readership so avoid the use of narrow jargon. Where you must use jargon, explain the word in the abstract.
Abandon, shun, renounce and eschew the following:
- Providing the introduction inside the abstract
- Summarizing the discussion inside the abstract
- Puffery or sales talk
- Detailing the methods
- Using unneeded phrases (like "In this study...")
- Passive voice intoxication
- Complex tenses (the simple present and past tenses almost always do the best work)
- Empty sentences (Examples: We studied the relationship of x to y. We discuss topic A. We plan to expand this study. More research is needed.)
- Talking about future research (yours or anyone else's)
- Introducing arguments or conclusions not developed in the body of the paper
abstracts that fail to adopt these guidelines will be returned for revision.
No manuscript will be reviewed until it contains an adequate abstract.
EER offers the following templates as suggestions. Below the templates are three examples. But you will see many others in EER papers since 2006; the abstracts of all are available on our website even if your institution has not yet subscribed — just click on any paper in "Final Editions."
Often you will want to add a Background section as the very first section. This would serve to introduce the reader to the general topic and to any needed jargon. It might also state what motivated you to undertake the work.
- Mathematical Method
- Key Assumptions
- Data description
- Search Method
- Site of Experiments
- Features of Model
- Ranges of Key Variables
- Data Incorporated
- Analysis Method
- Times and Places
- Analytical Methods
Example One paraphrased from:
Ido Filin & Yaron Ziv. 2004.
New theory of insular evolution: unifying the loss of dispersability and body-mass
change. Evolutionary Ecology Research, 6: 115–124.
Questions: Why do species on islands often lose the ability
to disperse? Why do they often evolve dwarfism or gigantism?
Mathematical Methods: Optimization and allometry based on Skellam's
diffusion-reaction equation of dispersal.
Key Assumptions: Organisms spread in a landscape by a random-walk.
Dispersal distances of offspring are distributed normally. Dispersals that are
too long result in offspring leaving the island thus reducing population growth
rate. Dispersability depends on body size (mass) according to a power-law allometric relationship. One body size on the mainland, the optimal size, maximizes population growth
Predictions: Dispersability declines on islands. Owing to change
in dispersability, individuals of island populations evolve towards an optimal
body mass different to mainland optimal body mass. The new optimum could be
larger or smaller than the mainland optimum depending on the sign of the allometric
exponent of dispersability. The rate of evolution is inversely proportional
to the area of the island. The smaller the island, the larger the shift in optimal
body mass, either towards gigantism or towards dwarfism. Existing data tend to support
some of these predictions.
Example Two paraphrased from:
Guy Beauchamp & Esteban Fernández-Juricic. 2004.
Is there a relationship between forebrain size and group size in birds?
Evolutionary Ecology Research, 6: 833–842.
Question: Does group living favour larger brain sizes? Analyses
of primate species suggest that this is true.
Data Studied: Forebrain size, body mass, mean and maximum flock
size and flocking propensity (solitary or gregarious) in 202 bird species, mostly
European and North American, during their non-breeding season. Relationship
data came mostly from molecular sources.
Search Method: Phylogenetically uncorrected:
We regressed forebrain size on body mass. Then we regressed the residual values
from that regression against the three flocking variables. Phylogenetically
corrected: We calculated independent contrasts with the CAIC program
(Purvis and Rambaut, 1995), ignoring branch lengths throughout.
Conclusions: Avian forebrain size is not related to any flocking
variable. No consistent changes in the contrasts for forebrain size accompanied
transitions from solitary to gregarious foraging.
Example Three paraphrased from:
Joseph H. Tien, Simon A. Levin & Daniel I. Rubenstein. 2004.
Dynamics of fish shoals: identifying key decision rules.
Evolutionary Ecology Research, 6: 555–565.
Question: How do fish maintain their social aggregations (i.e.,
Hypothesis: They move toward their nearest neighbour when farther away than
a certain distance (the attraction zone) and away from it when closer than a
certain distance (the repulsion zone).
Organisms: A mixed shoal of juvenile creek chubs (Semotilus
atromaculatus) and juvenile blacknose dace (Rhinichthys atratulus).
Field site: Natural 240cm-wide pool in Cleveland Brook, Stony
Ford Ecological Research Center, NJ, USA.
Methods: We tracked the movements of individual fish using
video recording and digitization of images. We did it at times when we did not
disturb the fish and at other times when we added a simulated predator to the
Conclusions: Both attraction and repulsion zones appear to
exist, but do not abut. A neutral zone exists between them. In the presence
of the simulated predator, the fish stay closer together by reducing the maximum
distance at which they repel each other and the minimum distance at which they