How much is too much in sampling? How much is enough?

Physical - Biological Interactions Influencing Marine Plankton Production

Physical - Biological Interactions Influencing Marine Plankton Production
Kendra L. Daly, Walker O. Smith, Jr.
Annual Review of Ecology and Systematics, Vol. 24 (1993) pp 555-585

An excellent review article.
Daly and Smith(1993) review biological and physical interactions in oceans to see how they influence plantonik growth (mostly phytoplankton, but zooplanktons are also discussed) . As the paper talks only about marine environment the discussion is difficult to apply to a much smaller estuarine system; the currents in the oceans and the light gradient due to a much much greater depth are not applicable. also the freshwater influence, which will be significant for esturies, is not accounted for.
The similarity however is that they are both fluid and the organisms of interests are the same. Some questions are applicable to both ecological systems. It is also interesting to see how coastal estuarine systems interacts with the larger scale marine environment, from the latter's perspective. the discussion of estuarine systems is too peripheral and too generic to be of much direct use.

The paper is well organised; it is divided into 2 sections-

a) Physical interactions
which talk about physical processes like motion and light etc.
large scale - 1,000 to >10,000 km & years to centuries
mesoscale - 100 m to 100 km & days to months
smallscale - mm to meters & seconds to hours

b) Biological interactions
which talk about interactions between biological entities and between biological entities and their physical environment. these are further classified into large scale; mesoscale and small scale - (i found this classification system fuzzier).
large scale interactions
e.g. large scale heat absorbtion at a global level that impacts global temperature.
mesoscale interactions
at this scale plankton appear to temprarily adapt
??
small scale interactions
phytoplankton - nutrient interactions.
interactions with environment due to physiological response in the cells.

The paper, then, presents two case studies to discuss complexity of interactions. these are marine examples and did not interest me considerably.

interesting quotes from the paper are classified under following headings -

1. Scales of Interaction
2. Aquatic ecosystem
3. Physical indicators and their influence
4. Primary Production

Scales of Interaction

Quotes from Daly and Smith, 1993
1.

2. The scale of a varying property is defined as the distance (or time) over which its quantity remains the same before significantly changing. The physical processes most likely to influence biological activity in the ocean are those that occur in the space/time domain intrinsic to specific organisms.
For example, the doubling time of phytoplankton ranges from about 0.5 to 10 days, in which time an individual cell may be transported several kilometers by currents. Thus, small- to meso-scale physical processes are relevant to the study of phytoplankton.

3. This review indicates that biological processes may be more important at smaller scales where behavior such as vertical migration and predation may control the location and production of plankton. Physical processes may be more important at larger scales in structuring biological communities and determining particle flow, but the magnitude of biological distributions also is determined by biological interactions.

4. Non-linearities in biological dynamics over different scales often confound interpretation of patterns. Thus, understanding and prediction of ecosystem function must derive from the study of fundamental processes in conjunction with the coupling of circulation and biological models.

5. The variability of physical forcing, particularly unpredictable fluctuations, may be more important to understanding biological activity than the mean conditions. Spectral analysis provides information on the scales of variability and is useful for comparing the effects of external forcing on different ecosystems.

On matching techniques and problems

In Kanal (1993), the following figure is shown to present the various techniques used for various aspects of pattern recognition. It is suggested that we may look at the sceanario as a "bag of tools for a bag of problems".

My point is we really need to see what is the limiting factor here - if data is the limiting factor then using fancier technique would not help - and therefore more than one technique is sufficient.*
If we do not observed an entire cycle of the process then we cannot expect the fancier techniques to help. The problem really does boil down to knowing if we are observing at the right temporal scale.

Another diagram in the paper which is of relevance (and is presented wrt a case study)


*it is difficult to see how can one argue against the other techniques if they have not even been applied (specially since all these papers argue that each technique and each problem need to be matched; there are no general solutions for all complex problems). however, i wonder what would be use the use of the above arguement if all techniques are applied to test its validity.

What can I infer from 'Results of Statistical Tests'?

Statistical results done on data throws up many patterns much like the data itself. It is getting interesting as I try and figure out

- which of the results are showing a pattern because of the pattern inherent in the statistical test. In my case, especially in SA by partial derivation method

- which are being shown because of extreme values present in the data set. In my case, especially when the point keeps moving between training, validating and testing data sets.

(and the most brilliant one)
- how much of it getting stuffed up because I am using the wrong scale to look the environment.

Scale

Determining natural Scales of Ecological Systems
RL Habeeb; J Treilco; S Wotherspoon and CR Johnson
(UTAS)
Ecological Monographs 75(4) 2005 pp 267-287

The paper does not seem to include much introductory material. The problem, as explained in the abstract, is very exciting. The rest of the paper, more or less, gives a feeling as being a part of a continuing discussion. Might revisit later - not thrilled. note also - the paper is sent from utas.

Characteristic length scale (CLS): The characteristic length is a natural scale of a system at which the underlying deterministic dynamics are most clearly observed.
A key issue in ecology is to identify the appropriate scale(s) at which to observe trends in ecosystem behaviour.