Does ‘best’ conservation method mean ‘best’ results?

Simon Black –

Best practice standards are commonly seen as a sure-fire route to successful improvement. After all – who could question the value of implementing best practice? However a prudent conservation leader should be prepared to question the supposed value of ‘best practice’. What does the approach mean in the context of your conservation work?

Why question it?

Any method has to make sense in the context and purpose of what it is trying to deliver. Best practice in cleaning tables might be vital in preparing an operating theatre but might be excessive, costly and irrelevant when applied to a door making factory. The purpose of the work is important. For example, best practice in breeding passerines might not be ‘best’ for your species if you find that all of your captive clutches perish.

Conservation is rife with uncertainty and unknowns. In delivering conservation projects you need to build in flexibility. This means that you have to think carefully about what your species and ecosystems of concern need and therefore what you must do to meet that need – otherwise a poorly considered method will not deliver what is really needed. Deming, the management ‘guru’ of the 20th century always used to ask ‘by what method?’ What he meant was this – the way that you go about something influences the outcomes that you achieve.

Over and above this, if you do implement a standard way of working, you tend to build in both rigidity (a lack of flexibility to meet differing needs). This rigidity has proven to hold many conservation projects back from achieving real progress (Clark, 1994; Black, Groombridge and Jones, 2011). You are also likely  to push your results further away from the ideal, because natural systems experience huge amounts of variation; one clutch of birds in one tree will differ in their needs (to some degree) from the clutches in any other tree.

Seddon states “Don’t codify method”  – in other words don’t write it all down and demand that everyone sticks to the written code.  But why?  Surely standardisation will ensure quality (especially if the standard is shown to be best)? Of course writing down method tells us what we are doing, but if a better way becomes available we need to be ready to flex the method, or apply a one-off approach if needs demand it. However as conservation scientists we should not do this as a random approach – we need to use proper experimental design and hypothesis testing.

We need to keep observing and thinking as we conduct conservation work, not just carry out procedures ‘parrot fashion’. To paraphrase Mitch Ditkoff, when imitation replaces creativity, something invariably gets lost – and innovation eventually goes down the drain.

As a leader keep thinking and encourage your team to think about their work too.


Black, S. A., Groombridge, J. J., & Jones, C. G. (2011a). Leadership and Conservation Effectiveness: Finding a Better Way to Lead. Conservation Letters, 4, 329-339.

Deming, W.E. (1993) The New Economics, MIT CAES, Cambridge MA.

Seddon, J. (2005) Freedom from Command and Control, Vanguard Press, Buckingham, UK.

Never forget this fact: There is no such thing as factual information

Simon Black –

This blog title is provocatively paradoxical. The assumption is that somthething measured is something proved. this is a habit of thinking which we are trained to establish in our minds as scientists.

This is not the case.

In practice, when we decide to define a fact, we then define what it is, how it is to be measured, then measure to verify.

In deciding the measurement, we simply place a judgement – our opinion of reality, onto something that isn’t there. For example:

The label on a blanket reads “50 per cent wool” What does this mean? Half wool, on the average, over this blanket, or half wool over a month’s production? What is half wool? Half by weight? If so, at what humidity? By what method of chemical analysis? How many analyses? The bottom half of the blanket is wool and the top half is something else. Is it 50 per cent wool? Does 50 per cent wool mean that there must be some wool in any random cross-section the size of a half dollar? If so, how many cuts shall be tested? How select them? What criterion must the average satisfy? And how much variation between cuts is permissible? Obviously, the meaning of 50 per cent wool can only be stated in statistical terms (Deming 1975).

Is it now becoming clear?

“Without theory (hypothesis), data are meangingless or nonexistent. There is thus no true value of anything: true value is undefinable operationally. There are, however, numerical values that people can use with confidence if they understand their meaning (for the tensile strength of a batch of wire, for example, or for the proportion of the labor force unemployed last month).” (Deming 1967).

The trick is to understand the meaning of numbers. this is clearly important if we are conudcting a population census (which individuals, where, within what boundaries, at what point in time, by what method of observation, how to record etc.) buit more so when we consider more nebulous things, like the ‘perceptions of local communities’, or ‘support for conservation action’ or the ‘involvement of local partners’.

Not everything that can be counted counts.
Not everything that counts can be counted.

 So the first useful question about somethnig is:

“what do we know about this?”

Think about this next time you set a goal, or measure results…

 Further Reading:

Deming W.E. (1967) Walter A. Shewhart, 1891-1967. The American Statistician, 21(2): 39-40

Deming (1974) On probability as a basis for action. The American Statistician, 29 (4): 146-152