11

Why do we do science?Why do we do science?

What are the goals of science ? What are the goals of science ?

Understanding ? Explanation ? Discovery ? Understanding ? Explanation ? Discovery ? Prediction? Description?Prediction? Description?

A mixture of these? A mixture of these?

In what order?In what order?

In what proportions? In what proportions?

22

The goals of scienceThe goals of science

““Bacon: the role of science is the search for the causes Bacon: the role of science is the search for the causes of the different phenomena. Explanation is the goal of of the different phenomena. Explanation is the goal of science” (Bacon)science” (Bacon)

• ““The goal of marine biology is to (predict and) The goal of marine biology is to (predict and) understand the distribution and abundance of life in understand the distribution and abundance of life in the sea” (Redfield 1958)the sea” (Redfield 1958)

• “ “Ecology is the branch of science that predicts the Ecology is the branch of science that predicts the distribution, abundance, biomass, and kinds (sizes, distribution, abundance, biomass, and kinds (sizes, ecotypes, species...) of organisms” (Peters 1980)ecotypes, species...) of organisms” (Peters 1980)

Different views:Different views:

33

The goal of scienceThe goal of science

The “Circle” of ScienceThe “Circle” of Science First we observeFirst we observe

FactsFacts

TestsTests after manyafter manyTheoriesTheories

These hypothesesThese hypothesesbecomebecome

TestsTests

LawsLaws

After many moreAfter many more

These theoriesThese theoriesbecomebecome

These laws mayThese laws mayseem proven andseem proven and

may even bemay even beconsidered trueconsidered true

These facts suggestThese facts suggest

HypothesesHypotheses

Taken from J. M. GasolTaken from J. M. Gasol

44

The reality

““Too much research is done for the same reason that Too much research is done for the same reason that a mountain is climbed: “because it is there”, and a mountain is climbed: “because it is there”, and too little time is spent questioning the motives for too little time is spent questioning the motives for doing so” (Rigler and Peters 1995)doing so” (Rigler and Peters 1995)

55

Pace 2001

Emphasizes the importance of prediction as one of the main goals in contemporary science

Points to the dichothomy that has existed between the “empiricists” and the “mechanicists”

Suggests this dichothomy is useless and counter productive

66

Prediction versus understanding

Prediction is often associated to empirical, comparative studies that generate patterns and statistical models that describe these patterns

Understanding is often associated to experimental, manipulative studies that address mechanisms, and to analytical, deterministic models that use the mechanistic knowledge for prediction

77

Prediction and understanding

One does not need to understand mechanisms and processes in order to predict (or forecast)

Sishi Chaohou Sishi Chaohou TuTu

(< 1056)(< 1056)

88

Prediction and understanding

Understanding the mechanisms or processes does not necessarily allow prediction» Example: We now know that primary

production is limited by iron availability in large oceanic areas, and we understand many of the underlying biogeochemical and physiological mechanisms

» But can we predict the outcome of iron fertilization?

99

Explanation

Being able to explain a phenomenon does not guarantee that we will be able to predict the future occurrence of other similar or related phenomena

Retrospective Explanation ≠ Prediction

1010

Understanding versus prediction

A common view is that we must first understand, and then A common view is that we must first understand, and then attempt to predictattempt to predict

1111

Understanding versus prediction

A common view is that we must first understand, and then A common view is that we must first understand, and then attempt to predictattempt to predict

So how do we decide that we understand enough?So how do we decide that we understand enough?

1212

Understanding versus prediction

A common view is that we must first understand, and then A common view is that we must first understand, and then attempt to predictattempt to predict

So how do we decide that we understand enough?So how do we decide that we understand enough? And how can we test the accuracy of our understanding?And how can we test the accuracy of our understanding?

1313

Understanding versus prediction

A common view is that we must first understand, and then A common view is that we must first understand, and then attempt to predictattempt to predict

So how do we decide that we understand enough?So how do we decide that we understand enough? And how test the accuracy of our understanding?And how test the accuracy of our understanding? Pace proposes that scientific understanding should be Pace proposes that scientific understanding should be

assessed in terms of the quality of the predictions that can assessed in terms of the quality of the predictions that can result from it result from it

1414

Understanding versus prediction

A common view is that we must first understand, and then A common view is that we must first understand, and then attempt to predictattempt to predict

So how do we decide that we understand enough?So how do we decide that we understand enough? And how test the accuracy of our understanding?And how test the accuracy of our understanding? Pace proposes that scientific understanding should be Pace proposes that scientific understanding should be

assessed in terms of the quality of the predictions that can assessed in terms of the quality of the predictions that can result from it result from it

Understanding is difficult to judge, but predictions can be Understanding is difficult to judge, but predictions can be quantitatively falsifiedquantitatively falsified

1515

Importance of prediction Pace 2001

Testing predictions is one means to judge the adequacy of understanding

Needed for practial reasons and management Important both for the establishment and

evaluation of theory Predictive objectives for research may help to

discriminate among lines of research Predictive orientation keeps research efforts

focused on central questions

1616

Rigler’s story Frank Rigler worked on P regeneration by zooplankton

in lakes for over 2 decades All along he worked on the basis that he was contributing

a piece to a much bigger puzzle, and that eventually when all the pieces were put together into the “big model”, we would finally be able to predict P in lakes

One day, he realized the big model would never come, not at least during his lifetime

He dropped his detailed mechanistic studies and started to focus on large-scale patterns in P (and other important variables)

1717

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

The story of phosphorous in lakesThe story of phosphorous in lakes

0.1

1

10

100

1 10 100

Total Phosphorous (µg l-1

)

Chl = 0.06 x TP 1.53

r2 = 0.95

0.1

1

0.01 0.1 1 10

Production / respiration ratio

Chl / TP = 0.39 x P/R 0.52

r2 = 0.75

++++

1818

We want to understand, but understand what?

Understand the how a general process works? Understand how a small portion of the system

works, to eventually add all these portions so that we will understand the whole?

Limnology has traditionally suffered from “My Lake Syndrome”, people often sought to understand “their lake” because their lake was surely different

In oceanography, people may also try to understand their “patch” of ocean?

1919

We like to describe, but what should we

describe?

In the same way a pile of bricks does not make a house, a whole bunch of data or facts are not necessarily science

How do we judge when description is necessary and when is it enough?» Example: The description of microbial diversity

using molecular approaches

2020

We would like to predict things, but what?

Although empirical predictive models do not require an understanding of mechanisms, they should be based on prior knowledge and theory

We should seek to predict features of the ecosystem that are not only relevant, but also feasable

We should do a better job in dealing with uncertainty and error

2121

We would like to predict things, but what?

Primary production under scenarios of changing water temperature and movement, and nutrient inputs

Shifts in the biological pump Fish production Shifts in food web structure and in material

and energy fluxes in food webs Occurrence of toxic algal blooms

2222

Some potential benefits of comparative studies

The value of pattern» Help identify key forcing factors» Help identify ranges within which these key factors

operate» Help identify interactions and feedbacks between forcing

factors» Help identify regional or ecosystem-specific

The value of outliers» Help identify local deviations from general patterns» Help identify non-linearities» Help identify major state changes

2323

A good example

Redfield was one of the first “Comparative” scientists. The R Ratio was so compelling in part because it was a general pattern

The R Ratio generated multiple lines of research, some showing how other systems comformed to the pattern, others trying to explain departures

2424

Approaches in aquatic microbial ecologyApproaches in aquatic microbial ecology

Allocation of effort to different subjects and approaches in Allocation of effort to different subjects and approaches in Aquatic Microbial EcologyAquatic Microbial Ecology

0 50 100 150 200 250

Descriptive

Experimental

Models

Comparative

Number of papers published (1990-1995)Number of papers published (1990-1995)

0 20 40 60 80 100 120 140

Geochemical effects

Nutrients

Trophic interactions

Production & growth

Abundance & biomass

Methods

Taxonomy

Number of papers published (1990-1995)Number of papers published (1990-1995)

from Duarte et al. 1997from Duarte et al. 1997

2525

Approaches in aquatic microbial ecologyApproaches in aquatic microbial ecology

A diagnosis of common flaws:A diagnosis of common flaws:• Inappropriate extrapolation of experimental results Inappropriate extrapolation of experimental results

• Sampling and experimental designs that are too simple and primitiveSampling and experimental designs that are too simple and primitive

• Field experiments almost absentField experiments almost absent

• Method-oriented rather than question-orientedMethod-oriented rather than question-oriented

• Lack of falsifiable hypothesesLack of falsifiable hypotheses

Towards a stronger Aquatic Microbial Ecology:Towards a stronger Aquatic Microbial Ecology:• With more field and ecosystem experimentsWith more field and ecosystem experiments

• With quantitative tests of accepted paradigmsWith quantitative tests of accepted paradigms

• Experiments at the relevant scales for microorganismsExperiments at the relevant scales for microorganisms

• Combination of comparative approaches and field /ecosystem Combination of comparative approaches and field /ecosystem experiments through meta-experimentsexperiments through meta-experiments

From Pep GasolFrom Pep Gasol

2626

Cost-benefit analysis of scientific researchCost-benefit analysis of scientific research

Strategies to optimize the scientific output:Strategies to optimize the scientific output:• Suspect of paradigmsSuspect of paradigms

• Travel across fieldsTravel across fields

• Set your questions at the broadest possible levelsSet your questions at the broadest possible levels

• Build a large tool boxBuild a large tool box

• Stay open for surprise, excitement and frustrationStay open for surprise, excitement and frustration

Problem finding is as (or perhaps more) important as problem-solving. A scientist is Problem finding is as (or perhaps more) important as problem-solving. A scientist is an individual (1) able to pose relevant problems and (2) able to pose them in a way an individual (1) able to pose relevant problems and (2) able to pose them in a way that they can be operationally addressed. that they can be operationally addressed.

One credo for responsible researchers should be: “experiment when necessary, but One credo for responsible researchers should be: “experiment when necessary, but don't necessarily experiment”don't necessarily experiment”

From Pep GasolFrom Pep Gasol

2727

Cost-benefit analysis of scientific researchCost-benefit analysis of scientific research

from Duarte et al. 1997from Duarte et al. 1997

0 100 200 300 400 500 600

Hobbie et al. (1977)

Porter & Feig (1980)

Azam et al. (1983)

Fuhrman & Azam (1982)

Cole et al. (1988)

Simon & Azam (1989)

Fuhrman & Azam (1980)

Proctor & Fuhrman (1990)

Bergh et al. (1991)

Cho & Azam (1988)

Citations (92-95)

MethodsMethods

MethodsMethods

MethodsMethods

MethodsMethods

MethodsMethods

ConceptsConcepts

ConceptsConcepts

ComparativeComparative

ConceptsConcepts

ConceptsConcepts