Darwin and von Humboldt

I discuss agian the interesting paper on Nature about the determinants of productivity.  I discuss it again since it is very good science, and yet the interpretation is flawed by philosophical biases that are not fully recognized.

The paper says that productivity is directly related to size and age and indirectly related to climate. I said in the previous post that indirect relationship are considered not real by ecologists. It took much time in law to ackowledge that indirect responsability are as real as direct responsabilities. But there is another consideration, this time concerning the history of science. We have two main schools in ecology: the German and the anglo-saxon. German school was founded by Alexander von Humboldt, anglo-saxon school by Darwin. The German school focuses on the relationship betwwen the physical environment and the organisms, whereas the anglo-saxon school tries to explain ecosystems relying only on organisms. Representatives of the German school often define their appraoch as "holistic", but this word makes little sense; what matters is emphasis on the physical environment.

The above papers shows that both the physical environment (the climate) and the organisms (size and age) play a role in productivity. The physical environment has only indirect effect. but this is trivial, since the effect of environment on ecosystems is always mediated by organisms. And yet you have not the full explanation if you do not consider the physical environemtn. Organisms are immersed in the environment, and are shaped by it, although of course a very relevant part of their life are organism to organism relationships (as stressed by Darwin in the Origin of Species).

But anglosaxon think generally that the German approach is unscientific, and anglo-saxon are hegemonic. Therefore climate cannot be a determinant of productivity.

Indirect relationships

It seems that chicken can count up to 3. But ecologists seem to be able to count only up to 2. Consider the following diagram.

In the seqeunce above, AB and BC are direct relationships, whereas AC is an indirect relationship. You need to know the two direct relationship to accurately model the sequence of relationships, but you need to take into account indirect effects, i.e. the complete picture, in order to understand the system. If you consider only part of the system, you  explain nothing. If I pay a killer and the killer kills you, the judge will condemn me, and the killer to a lesser punishment. But ecologists think tha indirect relationship do not exist. They will codnemn only the killer, not the instigator. Consider for instance this interesting paper on Nature about the determinants of productivity. It says that productivity is directly related to size and age and indirectly related to climate. This is a major insight, since it retrieves the killer and the instigator. But in the paper the indirect relationship is considered in some way unreal. 

Ecologists are slowly recognizing that often different factors are at play at the same time. But they accept only parallel chains of caustions, like that below in the diagram, and not series of causation like that below. But "closer" does not mean "stronger". In the chain above, if the rate of AB is slower than the rate of BC, the bottleneck is AB and not BC. We should consider the complete picture, and stress not the "closer" or the stronger relationship, but the bottlenects. In the case of parallel systems this is slowly getting recognized (consider for instance this paper on Ecology Letters)

Correlation is not causation

Correlation is not causation, as we often repat, but correlation is nonetheless always informative.

If you detect a correlation between A and B only three possibilities exist:

Only the first case is true correlation, but from the above graphic it is evident that also cases 2 and 3 allow to analyse the structure of data, once the factors C and D are discovered.

Case 2 is spurious correlation. But if you find C you have a model.

Case 3 is indirect correlation. In this case A and B are proxies or indicators of C and D, and can be used interchangeably. Often A and B are easier to measure than C and D.

It has been observed a drop in explanatory power in ecological studies in recent year. This is probably because we don't take into account the above very general patterns.

Structural Equation Models (SEM) allow to study the three cases, but unfortunately they can deal only with linear relationships.