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
PLEASE, 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.

Analytical theory

  • Question
  • Mathematical Method
  • Key Assumptions
  • Conclusions

Pattern search

  • Question
  • Data description
  • Search Method
  • Conclusions

Experimental test

  • Hypothesis
  • Organism
  • Site of Experiments
  • Methods
  • Results

Computer experiment

  • Question
  • Features of Model
  • Ranges of Key Variables
  • Conclusions


  • Question
  • Data Incorporated
  • Analysis Method
  • Conclusions
Natural experiment
  • Hypothesis
  • Organisms
  • Times and Places
  • Analytical Methods
  • Results



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 rate.
          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., shoals)?
          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 environment.
          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 attract.