Table Of ContentCoastal and Estuarine Studies
Managing Editors:
Malcolm J. Bowman Richard T. Barber
Christopher N. K. Mooers John A. Raven
Coastal
and Estuarine Studies
formerly Lecture Notes on Coastal and Estuarine Studies
32
F. Wulff J.G. Field K.H. Mann
(Eds.)
Network Analysis
in Marine Ecology
Methods and Applications
Springer-Verlag
Berlin Heidelberg New York London Paris Tokyo Hong Kong
Managing Editors
Malcolm J. Bowman
Marine Sciences Research Center, State University of New York
Stony Brook, N.Y. 11794, USA
Richard T. Barber
Monterey Bay Aquarium Research Institute
Pacific Grove, CA 93950, USA
Christopher N. K. Mooers
Institute for Naval Oceanography
National Space Technology Laboratories
MS 39529, USA
John A. Raven
Dept. of Biological Sciences, Dundee University
Dundee, DD1 4HN, Scotland
Contributing Editors
Ain Aitsam (Tallinn, USSR) . Larry Atkinson (Savannah, USA)
Robert C. Beardsley (Woods Hole, USA) . Tseng Cheng-Ken (Qingdao, PRC)
Keith R. Dyer (Merseyside, UK) . Jon B. Hinwood (Melbourne, AUS)
Jorg Imberger (Western Australia, AUS) . Hideo Kawai (Kyoto, Japan)
Paul H. Le Blond (Vancouver, Canada) . L·. Mysak (Montreal, Canada)
Akira Okuboi (Stony Brook, USA) . William S. Reebourgh (Fairbanks, USA)
David A. Ross (Woods Hole, USA) . John H. Simpson (Gwynedd, UK)
Absornsuda Siripong (Bangkok, Thailand) . Robert L. Smith (Covallis, USA)
Mathias Tomczak (Sydney, AUS) . Paul Tyler (Swansea, UK)
Editors
F. Wulff
Institute of Marine Ecology, Ask6 Laboratory, University of Stockholm
10691 Stockholm, Sweden
J.G. Field
Marine Biology Research Institute
Zoology Department, University of Cape Town
Rondebosch 7700, South Africa
K.H. Mann
Department of Fisheries and Oceans
Habitat Ecology Division, Bedford Institute of Oceanography
Box 1006, Darthmouth, Nova Scotia, Canada B2Y 4A2
ISBN -13: 987-3-642-75019-9 e-ISBN -13:987-3-642-75017-5
DOl: 10.1007/987-3-642-75017-5
This work is subject to copyright. All rights are reserved, whether the whole or part of the material
is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation,
broadcasting, reproduction on microfilms or in other ways, and storage in data banks. Duplication
of this publication or parts thereof is only permitted under the provisions of the German Copyright
Law of September 9, 1965, in its version of June 24, 1985, and a copyright fee must always be
paid. Violations fall under the prosecution act of the German Copyright Law.
© Springer-Verlag Berlin Heidelberg 1989
Softcover reprint of the hardcover 1st edition 1989
2131/3140-543210 - Printed on acid-free paper
To obtain a diskette containing the software for
the techniques used in this book, (for IDM or
compatible computers on a MS DOS 360 kB
diskette, for a Macintosh computer on a 3.5"
diskette) send a money order or bank draft for US
$ 10.00 payable to SCaR to:
Excecutive Secretary, SCOR
Department of Oceanography
Dalhousie University
Halifax, N. S. CANADA
B3H 4JI,
requesting Network Analysis Software.
CONTENTS
DEDICATION
PART I INTRODUCTION
Chapter 1 The need to analyze ecological networks 3
1. G. Field, F. Wulff & K H. Mann
PART II MErnODS AND rnEORY
Chapter 2 A detailed guide to network analysis. 15
1. 1. Kay, L. A. Graham & R E. Ulanowicz.
Chapter 3 Construction of flow networks using inverse methods. 62
A.F. Vezina
Chapter 4 A generic simulation model for treating 84
incomplete sets of data.
R. E. Ulanowicz
Chapter 5 Dealing with the "mixed units" problem in 90
ecosystem network analysis.
R Costanza & B. Hannon
PART III APPUCATIONS
Cnapter 6 Network information indices with an 119
estuarine model.
1. N. Kremer
Chapter 7 Network analysis of simulated succession 132
after an upwelling event.
c.
1. G. Field, C. L. Moloney & G. Attwood
Chapter 8 Derivation and analysis of flow networks 159
for open ocean plankton systems.
H. W. Ducklow, M.1. R Fasham &A. F. Vezina
Chapter 9 Network analysis of the North Inlet 206
salt marsh ecosystem.
M. L. Asmus & H. N. McKellar, Ir
Chapter 10 Analysis of the flow network in 220
an estuarine benthic community.
R. M. Warwick & P. 1. Radford
Chapter 11 A comparative anatomy of the Baltic Sea 232
and Chesapeake Bay ecosystems.
F. Wulff & R. E. Ulanowicz
PART IV DISCUSSION AND CONCLUSIONS
Chapter 12 Network analysis in marine ecology: 259
an assessment.
K H. Mann, I. G. Field & F. Wulff
INDEX 283
DEDICATION
This volume is dedicated to the memory of Dr David F. Smith who died suddenly
on 19 May 1987 at the age of 52. From 1976 to 1982 he was a member of the
working group" Mathematical Models in Biological Oceanography" established
by the Scientific Committee on Oceanic Research (SCOR). By his knowledge,
wit and wisdom he made a major contribution that will be long remembered
with affection by his colleagues and friends. He made a further important
contribution to a second working group,"Ecosystem Theory in Relation to
Biological Oceanography" whose deliberations culminated in the present
volume.
Those who worked with him mourn his early death but'recognize that it was a
privelege to have known him.
PART I
INTRODUCTION
Chapter 1
THE NEED TO ANALYZE ECOLOGICAL NETWORKS
JohnG.Fudd Fredrik Wulff
Marine Biology Research Institute AskO Laboratory
University of Cape Town University of Stockholm
7700 Rondebosch S-10691 Stockholm
SouthAfrica SWEDEN
Kenneth H. Mann
Bedford Institute of Oceanography
POBox 1006
Dartmouth, NS
CANADA B2Y 4A2
BACKGROUND TO mIS VOLUME
This volume arises out of the activities of two working groups organized under the auspices of the
Scientific Committee on Oceanic Research (SCOR). The first, SCOR Working Group 59 on
"Mathematical Models in Biological Oceanography" met in 1977, 1979 and 1982, under the
co-chairmanship of Kenneth Mann and Trevor Platt. A book with the same title (Platt, Mann &
Ulanowicz 1981) resulted from these meetings. In a nutshell, the group achieved some consensus that
simulation modeling was a useful activity, but that simulation models of ecosystems had strict
limitations: they were not predictive because qualitative changes of state often occurred in ecosystems,
and these could at that time usually not be predicted or modeled. The group therefore resolved to
explore the properties of ecosystems other than those revealed by simulation models. A theme which
developed was that it is necessary to have at least as much information on the fluxes among the
components of marine ecosystems as on the biomasses. This led in 1982 to a symposium reviewing
knowledge of the "Flows of Energy and Materials in Marine Ecosystems", organized in the NATO
Advanced Research Institute series, the proceedings of which have been published (Fasham 1984).
Here the theme persisted that there was a need to measure flows of energy and materials.
4
In 1982 Working Group 59 disbanded, and a new SCOR Working Group 73 was established under the
same chairmanship and with the same nucleus of oceanographers to explore "Ecosystem Theory in
relation to Biological Oceanography". Five topics were identified with potential to reveal
ecosystem-level properties: Thermodynamics, Statistical Mechanics, Input-Output Analysis,
Information Theory, and Ataxonomic Aggregations. Experts in each of these fields were invited to
address the topic and discuss ecosystem theory with oceanographers at a colloquium held in Quebec
in 1984. The colloquium was an outstanding success and the proceedings were published as a volume
(Ulanowicz & Platt 1985).
There emerged from the topics and discussions at the colloquium, a recognition that input-ouput
analysis, flow analysis, information networks and dynamic network analysis are a family of related
techniques with some potential to provide additional insights into properties of whole ecosystems.
This volume attempts to explore that potential.
NETWORK ANALYSIS IN OTHER DISCIPLINES
Economic input-output analysis was developed by Leontief (1951) to quantify the amount of raw
materials and industrial services required to produce a quantity of consumer goods. This work traced
outputs from components of an economic flow diagram or model (the demand for consumer goods)
back to the sources of raw materials or inputs. Thus input-output analysis is the term normally applied
to tracing flows backwards from the ouputs to the sources. Hannon (1973) was the first to apply
Leontiefs analysis to ecological systems. The backward form of analysis in ecology is usually termed
flow analysis. In flow analysis, flows into each compartment are defined as linear functions of the total
outflow from that compartment.
Augustinovics (1970) later worked out a forward form of economic analysis to trace the fate of system
inputs through the economic flow diagram to their destinations. Finn (1976) developed a forward case
analysis for ecological systems, and simultaneously introduced several measures of ecosystem function,
including cycling, that aid in the ecological interpretation of ecosystem model results. The forward
form of analysis is usually termed compartmental analysis. In compartmental analysis, outflows from
each compartment are defined as linear functions of the total inflow into that compartment.
The termflow analysis has also been used in a more general way to include both forward and backward
analyses, but we prefer the term network analysis for the general case to avoid ambiguity. Network
analysis goes further than the original input-output analysis in that it includes analysis of cycles,
through-flows, storages (Patten 1985) and information theory.
5
Network analysis has been applied in many disciplines. It forms a branch of statistics, is used in control
theory, and is most widely applied to analyze electrical networks in which flow diagrams represent the
flows of electric currents in circuit diagrams with resistors, transistors, condensors etc. as the
components. Forms of network analysis have been developed to a very advanced level for the design
of printed-circuit boards in electronics, and sophisticated software packages such as SPICE are used
to develop simulation models from flow networks, bridging the gap between flow diagrams and
simulation models. A theory of "network thermodynamics" has also been developed and applied to
analyze the distribution of drugs through human body organs (Mikulecky 1985). "Network
thermodynamics" may include non-linear relationships between flows in networks, but has not yet been
applied to ecosystem flows.
In this volume we are only concerned with linear relationships of flows to donor and recipient
compartments of ecosystems. We use the term network analysis to indicate that we are dealing with
ecosystems which form networks of flows of energy, nitrogen, carbon, and many other elements. The
term is also used to include the analysis of flows using information theory.
RELEVANCE OF NETWORK ANALYSIS TO ECOLOGY
Ecologists are used to the concepts of food chains and food webs, and to those of species richness and
diversity. Network analysis provides tools for bringing these and many other concepts together by
depicting ecosystems as a number of compartments interconnected by flows of energy or matter from
one compartment to another. The compartments are defined by the ecologist. They may be species or
they may be functional groups such as detritivores, a nutrient pool, particulate organic matter, etc.
Thus each network analysis is based upon a model of the ecosystem being studied, at the level of detail
decided upon by the ecologist. The analysis therefore depends upon the structure of flows among the
system components and their magnitude as measured, estimated, or deduced by the researcher. The
flows are of course rates per unit of time, and may vary greatly from second to second, but at the
ecosystem level are more usually measured on a daily, monthly, seasonal or anrtual time scale. We
believe that these flows contain a lot of information about the dynamic structure of a whole system and
of how it functions, and introduce some of the terms and concepts of ecological network analysis below.
Details of the methods and formulae are given by Kay, Graham & Ulanowicz (1989) in Part II of this
volume.
A cycling index
A cycling index shows the proportion of the flow in a system that is recycled compared with the total
flow. For example, it is well known that in tropical forests, nutrients such as nitrogen and phosphorus
are tightly recycled. At any given time a large proportion of the nutrients present are bound up in the
