How to do Ecology the Wrong Way

How to do Ecology
(the easy way)
Suhel Quader

TAKING IT EASY
12 rules to follow in designing and analysing your study
Follow these, and you'll become an ecologist with ease

1. ASK TRIVIAL QUESTIONS
Describe without attempting to explain
● What is the road kill rate along road X?
● What is the species diversity in habitat Y?
Ask questions to which the answer is obvious
● Are there differences in grass cover in ungrazed versus heavily
grazed areas?
● Does species diversity differ between different habitats?

Ignore 150 years of ecology and start afresh each time
● What is the time-activity budget of species X
● What is the diet of species Y
● What are the habitat preferences of species Z
COROLLARY

Road kill
● What explains variation in roadkill rate over space and time?
● Can one investigate the most effective mitigation measures?
● What rates are ecologically significant?
Grazing and not grazing
● What is the shape of the response curve?
● What does the response depend on?
● Do domestic and wild ungulates have different effects?
EVEN THOUGH (in the back of our minds we know that)...
… there are a multitude of much more interesting questions

2. ASK YES/NO QUESTIONS
Is there a difference, or not?
Is there a relationship, or not?

Is there a difference, or not?
Is there a relationship, or not?
Ignore:
How much of a difference
The form and strength of the relationship

The best studies are those where you are most likely get a YES answer,
no matter how trivial
COROLLARY
● Do tiny fragments have fewer species than intact forest?

… the null hypothesis is almost always wrong

We also know that there is a distribution of the magnitude of effects
So most things have some effect, even if the effect is small

We also know that there is a distribution of the magnitude of effects
So most things have some effect, even if the effect is small
We also know that the outcome can be of several forms.

3. LET THE TECHNIQUE GUIDE THE QUESTION
Focus on the technique, not on the ecological question
Know GIS? Use it for your study: after all, almost all ecological
questions are spatial
Know molecular techniques? Throw them at your study organism.
Learnt occupancy techniques? Search for a question you can apply
them to.
To someone with a hammer, every problem looks like a nail

3. LET THE TECHNIQUE GUIDE THE QUESTION
Techniques and technology are tools in your toolkit, not goals
in themselves
… if we want to understand ecology, we must start with ecology

4. DON'T WORRY MUCH ABOUT STUDY DESIGN

It's hard to think about things like:
● Validity
● Representativeness
● Psuedoreplication
● Interspersion
● Sample size and sampling error
● Appropriate spatial and temporal scale
● Measurement error
● Collinearity
● Non-linearity
Let's just get out into the field!

… Study design is more important than what stats you use
… Garbage in / Garbage out
… You and others may be completely misled

5. COLLECT THE DATA FIRST, THEN WORRY ABOUT ANALYSIS

One advantage of doing this is more complex stats
COROLLARY
Others are less likely to understand your analysis
and less likely to question it

… Simpler design – simpler stats – simpler interpretation
… Thinking about analysis can help clarify the question
and can feed back to motivate a more robust design
with greater statistical power

6. MINE THE DATA FOR PATTERNS
… ideally using automated techniques

… The more you look for patterns, the more spurious patterns
you expect to find

… The more you look for patterns, the more spurious patterns
you expect to find
… The less you think about the underlying processes, the less
likely you are to detect causal effects

7. EXPLORE THE DATA IN MANY WAYS
… but don't say that you're an explorer
Use all possible “researcher degrees of freedom”
- explore all variables but report only a few
- explore all comparisons but report only a few
- eliminate outliers if they help your case, else don't
- explore data transformations, and keep the best ones
- explore different model formulations and report only the best one(s)

The more variables you measure
and the vaguer your goals/hypotheses are,
and the less you have thought about the question
the more degrees of freedom you have!
COROLLARY

Explore the data as much as you want, then treat the study as
confirmatory (ie testing hypotheses).
Patterns that you noticed while or after collecting the data can
confidently be analysed and reported as though you had an a
priori hypothesis.
COROLLARY

… Exploiting research degrees of freedom leads to
Inflated false positive rate
Therefore increased likelihood of interpreting chance
patterns as real
Therefore hindering, rather than helping the progress of
ecology

8. FOCUS ON P-VALUES
… and don't worry about the rest

Don't attempt to interpret your statistical results
But if you do, don't worry if they don't make ecological sense
(you can always make up an explanation if you need to)
COROLLARY
… and don't worry about the rest

… P-values don't make much sense except in very specific study designs
We know that these are much more valuable:
Parameter estimates
Uncertainty
Measures of fit

R2
= 0.3
… P-values don't make much sense except in very specific study designs
… These are much more valuable:
Parameter estimates
Uncertainty
Measures of fit

… We should perhaps be worrying more about Type S and Type M errors
Type M
Type S

9. DON'T SHOW THE ACTUAL DATA
… show model results without plotting data

The more you hide (apart from p-values), the better
COROLLARY
… show model results without plotting data

… Presenting the actual data sets you up for examination on:
Study design
Treatment of data
Validity of analyses and results

10. INFER CAUSE FROM CORRELATION
It's just nit-picking to refuse to do this

Avoid triangulating using multiple lines of evidence
Avoid testing all links in the possible causal chain
(these would require planning in advance.)
COROLLARY

… correlations can arise from reverse causation and from
unmeasured third variables

11. MAKE SWEEPING GENERALISATIONS
… dutifully following points 1-10

Be confident, not tentative
Don't point out caveats and cautions
Treat starting/intermediate results as ending points
COROLLARY
… dutifully following points 1-10

… The conclusions from most individual studies must necessarily
be tentative
… The specifics of our studies can severely limit our ability to
generalise
… Exploration is not confirmation

12. MAKE RECOMMENDATIONS BASED ON COMMON SENSE
… rather than on evidence

Don't worry, no-one will hold you accountable
COROLLARY
… rather than on evidence

… Common sense is a notoriously bad guide
… Our conclusions should be driven by data, not by our convictions

IN SUM
● Ask crude questions
● Collect data on anything that's easy – the more the better
● Play fast and loose with analysis
● Oversell your results

IN SUM
● Ask crude questions
● Collect data on anything that's easy – the more the better
● Play fast and loose with analysis
● Oversell your results
Because doing is easy;
but thinking hurts

WAIT A MOMENT
Good research requires thought and planning
Useful research requires transparency in analysis and communication
and honesty in reporting uncertainty and limitations

TO CONCLUDE
Ecological research can be easy to do
With no guarantee that it's
interesting
or
true

How to do Ecology the Wrong Way

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