By : Praveen Kumar Neelappa
This article suggests that there is the gap between theory and practice in the use of analysis of competing hypotheses (ACH). It identifies several intellectual and practical barriers that discourage the use of multiple hypotheses in the field of ecology and evolution. This article points out that scientist have a bias or a motivation to consider one hypothesis over other (Intellectual barriers) and there are practical limitations inherent to factorial design, the standard experimental design that allows researchers to evaluate several explanatory variables and their interactions in the same study, one variable at a time (Practical barrier).
Cognitive bias makes us think that
we are making a logical, rational and effective decision while considering the
alternative hypothesis, but our unconscious bias influences the experiment and
its outcome. There is a tendency of scientist to put more weight on evidence
that supports favored ideas more than other evidence that is available
(Confirmation bias), seek for the pattern in their experiment (Pattern seeking
bias) and be judged only by their internal consistency (Belief bias). There are
several ways one might minimize the effect of cognitive bias in science so that
one does not rely exclusively on one’s perceptions. It can be achieved by
masking (kept) information about the experiment from the participant, to reduce
or eliminate bias, until after a trial outcome is known (Blind bias), working
with other scientists with different perspectives (Work with the enemy) and a
null model which generates a pattern in the absence of any biological process,
forcing the researcher to think about many different hypotheses, which could
potentially minimize the negative impacts of cognitive biases in science.
Any study that has a simple, easy to
understand explanation will be preferred over a study that employs complex and
perhaps less-elegant ideas (Simplicity bias) to avoid practical barrier.
Editors and reviewers tend to rely on prior knowledge when evaluating a
manuscript, creating additional difficulties for researchers when publishing
studies that confront well-established ideas. This tension between new and old
ideas could reflect a conflict between new and old generations (Publication
bias).
The article concludes by suggesting
that ecological and evolutionary research is aimed at understanding patterns
arising from nonlinear and stochastic interactions among a multitude of
processes and agents at multiple spatial and temporal scales. If we wish to
truly advance scientific progress despite this complexity, we must better
commit to strong inference in our scientific inquiries by simultaneously
evaluating multiple competing hypotheses.
Critique:
The use of ACH is widely promoted to
enhance the effectiveness of the scientific investigation. This article points
out some valid draw backs of using ACH in the different field of studies and
discusses these drawbacks and solutions to them in detail. The article clearly illustrates
various types of biases and the various stages where they can be encountered while
carrying out experiments. It is imperative that the individual carrying out the
experiment is objective in data collection and maintains an objective view at
every stage of the experiment which will be the best way to counter any possibility
of the final results being biased. Additionally, measures need to be put in
place to reassess for bias along the way to ensure the results are void of any
form of bias.
Citation:
Betini GS, Avgar T, Fryxell JM.
2017 Why are we not evaluating multiple competing hypotheses in ecology and
evolution?.R. Soc. open sci. 4: 160756. http://dx.doi.org/10.1098/rsos.160756
