How to Do Ecology (the easy way)

How to do Ecology

(the easy way)

Suhel Quader

TAKING IT EASY

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 differenceThe 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?


EVEN THOUGH (in the back of our minds we know that)... … the null hypothesis is almost always wrong



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


We also know that there is a distribution of the magnitude of effectsSo 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

EVEN THOUGH (in the back of our minds we know that)... … 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

EVEN THOUGH (in the back of our minds we know that)...

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… but don't say that you're an explorer


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… but don't say that you're an explorer


… 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 estimatesUncertaintyMeasures of fit


R2 = 0.3

… P-values don't make much sense except in very specific study designs

… These are much more valuable:Parameter estimatesUncertaintyMeasures 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

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 communicationand 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 easy way)

Science

Transcript of How to Do Ecology (the easy way)