this is not the end of limnology (or of science): the world may well be a lot simpler than we think
TRANSCRIPT
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OPINION ARTICLE
This is not the end of limnology (or of science): the worldmay well be a lot simpler than we think
GRAHAM HARRIS
CSIRO Land & Water, GPO Box 1666, Canberra ACT 2601 Australia
SUMMARY
1. Reynolds (1998) recently wrote a short piece in this journal lamenting the state of the art of
freshwater ecology. Others have recently foreshadowed the end of science altogether. It is my
argument here that theendof science isnotnighand that there are fundamental advances to be
madeinunderstandingecosystemfunction.Despitechangestothefundingbaseof freshwater
ecology over the years, the discipline can continue to make fundamental contributions to
ecology. We have an excellent base of raw material to work with, however, collected.
2. As a rebuttal to Reynolds (1998) I present evidence that ecosystems (and freshwater
ecosystems in particular) may well be a lot simpler than we think. Buried deep within a
very complex world there are some general modes of behaviour, determined by
fundamental principles, which impart certain kinds of high level order and predictability.
3. By means of six propositions I argue the case for the existence of these fundamental
principles and present empirical evidence for each.
4. In conclusion it is clear that there is a need for fundamental information about the role of
biodiversity in ecosystem function. There is also a need to understand the interplay
between environmental perturbations, biodiversity and functional groups which together
determine the cycling of energy and materials within freshwater and estuarine systems.
While we have considerable information about northern hemisphere aquatic ecosystems
less is known about southern hemisphere systems.
Keywords: the end of limnology, freshwater ecology, ecosystem function
Preamble
In a recent book Horgan (1996) announced the `end of
science'. By this he meant that we have now discovered
the fundamental natural laws of evolution and the
cosmos and that pure or `aesthetic' science had all but
run its course. According to Horgan the world runs
according to fundamental laws, most of which we now
know. This is not the first time that such assertions have
been made; it can be seen, if you wish, as another
millennial prediction, or as a fin de sieÁcle phenomenon.
Holland (1998) takes the alternative view, this is by no
means the `end of science' ± all is not completely known.
In particular Holland argues persuasively that we are
only just beginning to understand the properties of
complex systems and the rules of emergence ± the ways
in which complexity is generated from simple causes in
systems such as ecosystems. Wilson (1998) would agree
that this remains a major scientific challenge for the new
millennium.
Reynolds (1998) has questioned the `state of fresh-
water ecology' in particular and has engaged in what he
thought might be called some `academic whinging'
about the state of the discipline and of funding for pure
science in general. I do not see a crisis in pure science or
Freshwater Biology (1999) 42, 689±706
ã 1999 Blackwell Science Ltd. 689
Graham Harris, CSIRO Land & Water, GPO Box 1666, CanberraACT 2601 Australia. E-mail: [email protected]
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freshwater ecology other than a tendency, perhaps, to
concentrate on short-term solutions to contracts and
consultancies rather than on some of the deeper
questions. True, the modus operandi and the funding
base of science is changing (Gibbons et al., 1994). The
foundations of the intellectual edifices may be hard to
find amidst all the least publishable units and the
contract reports, but `chaos in the brickyard' is not new
(Forscher, 1963). A change in the funding base is no
reason for despair. As in other sciences, for ecology to be
a stronger science, we need to take a step back and
address the fun-damentals. The way to answer Rey-
nolds' concerns is to take the data to hand and to make
whatever use of it we can. There is no shortage of raw
material, however, generated. There is no reason why
aquatic ecology should not continue to provide leader-
ship in theoretical ecology as it has done in the past
(Harris, 1985). Ecosystems are complex, but not impos-
sibly so.
Complexity and its causes
Ideas about complex systems and complexity have had,
and are having, a major impact on ecological theory. If
we begin by accepting that evolution is fundamentally
an algorithmic process (Dennett, 1995) then the com-
plexity that we observe in the real world arises from
simple causes and from the interaction of agents acting
on local information driven by Darwinian processes (for
an application of this argument to aquatic systems see
Harris, 1994, 1998). In this view, to study ecology is to
study the rules that constrain the walk through evolu-
tionary design space (Eldredge, 1986, 1995; Dennett,
1995). Ecosystems exhibit hierarchical structures at a
numberoflevels. (Harris,1985,1986;O'Neillet al.,1986).
The fundamental ecological questions then become,
``How complex are the rules and what kind of knowl-
edge do we need in order to understand and predict
emergent phenomena at various levels?'' In addition
there is a question as to whether or not a structuralist
explanation is necessary (Dennett's ``sky hooks'') or
whether these structures emerge naturally from the
underlying ``pandemonium'` (via `cranes', Dennett,
1995).
Thanks to the popularity of complexity theory in
the 1990s, we have begun to understand, in a formal
sense, the ways by which systems that are composed
of many interacting components (``agents'` in Hol-
land's (1998) terminology) may, through the endless
working out of simple rules (or algorithms, Dennett,
1995), produce emergent properties and hierarchical
organisations. This is a change from the usual
preoccupation with reductionism in science. It is
simply not possible to understand the properties of
complex systems by looking just at the parts, because
we now have to understand not only the parts
themselves but also the interactions between them.
The ensemble of parts and interactions in ecosystems
is too complex to unravel other than by looking at
emergent properties. Reductionist explanations of
ecosystems do not work; instead we have to seek
`macro-laws' at various levels (Harris, 1998; Holland,
1998; Wilson, 1998).
In this paper I will argue that we have ways of
understanding why ecosystems work the way they do
and that the rules which govern the natural world are a
lot simpler than we might think. Deep within a very
complex world there are some general modes of
behaviour, determined by fundamental principles,
which impart certain kinds of high level order and
predictability. The existence of such order has signifi-
cant implications for the kinds of science that we might
do, and does, in my view, call for a revision of some of
basic descriptions of reality. I will argue here that the
complexity of ecosystems that we observe has simple
origins. A better understanding of the fundamental
processes that generate ecosystems will produce both
more focussed and testable ecological theories as well
as better management techniques.
While a simple conceptual explanation might be
possible, limitations to predictability in these systems
will arise from the interdependence of evolution,
biogeography, immigration and natural history (the
`frozen accidents' of history which determine the
local species pool), from the complexity of interac-
tions and the internal ``pandemonium'` (Dennett,
1995) and from variability in the external forcing
functions (climate variability). Predictive power is
therefore fundamentally limited (Harris, 1994). We
will only ever be able to understand this complexity if
we can identify functional groups of species, and if
there are emergent `complicit' features at defined
scales (Cohen & Stewart, 1994) which are consistent
across aquatic ecosystems of various types under
various forcing functions even though they might be
composed of different species (Holland, 1998). In
aquatic ecosystems this seems to be the case (Harris,
1985, 1994, 1998).
690 G. Harris
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Simple models with complex outcomes ± sixpropositions
I will put forward six propositions, designed to argue
that it is possible to make simple explanations of
complex phenomena. For each proposition I will
present empirical data that will support the argu-
ments put forward. Whether or not the data were
collected by virtue of pure or applied research is not
relevant (Reynolds, 1998).
The first proposition
For any given lake or water body, biogeography and the
vagaries of immigration and dispersal determine the
species pool. The populations and species within the
pelagic community make up a diverse set of ecological
entities filling the space of the available ecological
envelope. Energy (light) and nutrient inputs from the
catchments control the overall biomass. Lake morpho-
metry and flushing time control a number of major
structuring factors.
It has been clear since the early work of Talling (1950)
that the particular set of species comprising the
community of any lake or pond is idiosyncratic ±
based, that is, on the vagaries of immigration and
dispersal, and drawn from that pool of species
determined by the biogeography of the region in
question. Most phytoplankton are cosmopolitan and
occur widely when conditions are suitable (Reynolds,
1984; Harris, 1986), but for other organisms the
continents may have very distinct species comple-
ments. The species pool at any point therefore results
from basic evolution, biogeography and the `frozen
accidents' of history and evolution. The high biodiver-
sity of ecosystems leads to a ``pandemonium'` of
interactions between individuals and populations
(Dennett, 1995) and the properties of ecosystems that
we observe arise from those interactions. Nonetheless,
as we shall see, some things are predictable in these
systems ± there are some similar features. As the
phytoplankton in particular are quite cosmopolitan,
their distribution is predictable to a degree and some
workers, particularly Reynolds (1984, 1997), have made
significant advances in this regard.
It has long been known that the overall biomass in
the pelagic system is set by nutrient loads. Vollenwei-
der's canonical work is well tested and has long been
used as a management tool (Cullen, 1990). Vollenwei-
der and his co-workers showed how the biomass in
the pelagic part of deep glacial lakes was related to the
nutrient load and the hydrological regime and placed
statistical limits on the predictive ability of his models
(Vollenweider, 1968, 1969, 1975, 1976; Vollenweider &
Kerekes, 1980; Vollenweider, Rast & Kerekes, 1980;
Janus & Vollenweider, 1981, 1984). Subsequent work by
the McGill University limnology group has extended
the empirical data base for lakes, from algal biomass to
almost all of the common functional groups (bacteria to
fish and macrophytes) and to such things as size
distributions and species composition (for references
see, e.g. Peters, 1983, 1986; Seip & Ibrekk, 1988; Watson,
McCauley & Downing, 1992; Harris, 1994).
Because of the response of the entire ecosystem to
changing nutrient loads, essentially we are seeing the
titration of whole ecosystems. When a much broader
data base is brought together (Kelly & Levin, 1986) it
is clear that the response is universal and applies
across terrestrial, marine and freshwater systems. The
biomass of primary producers rises until it reaches a
ceiling, limited by the total nutrient load. There are
common responses. Harris (1994) explained why
Vollenweider's models work. It is because of regular
changes in a series of population responses across a
range of trophic states primarily coupled with the
development of blooms of large, poorly grazed
phytoplankton. Many food chain minipulation experi-
ments now show the importance of grazing in
determining the biomass of primary producers in
lakes (eg. Carpenter et al., 1987; Mazumder, 1994;
Reynolds, 1994). The impact of grazing decreases as
trophic state increases and there are both direct and
indirect effects at work (Harris, 1996; Reynolds, 1994).
The total biomass in both the pelagic system and the
benthos is also set by the energy constraints of the
environment ± limitation by light. Light plays an
important role in structuring lake ecosystems (Sterner
et al., 1997). Limitation by micronutrients is also
frequently encountered. In all cases care is required in
the interpretation of the term `limitation' ± limitation of
total biomass is not the same as limitation of rate
processes such as photosynthesis or growth (Harris,
1986). Light limitation usually results either from
seasonal light restrictions at high latitudes, extensive
and persistent cloud cover or from highly coloured
waters (Kirk, 1983). Micronutrient limitation is less
frequent in fresh water than in oceanic waters where
iron limitation is presently much studied (De Baar et al.,
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1995). Nevertheless, silica limitation is frequently
important in freshwater systems; if nothing else, it can
play a major role in determining the
species composition of the phytoplankton commun-ity
and the losses due to sinking from the photic
zone (export production, Wassmann et al., 1996; Wass-
mann, 1998).
An important plank of the arguments supporting
this first proposition is that, as far as possible,
ecosystems develop in such a way as to `fill the
ecospace available' until light or nutrients become
limiting. This argument was first developed by
Vollenweider (1970) who showed that it was possible
to compute the maximum biomass in the photic zone
of eutrophic lakes (Wofsy, 1983). This biomass was
reached when nutrient limitation was released and
the phytoplankton community became totally self
shaded. This idea of `envelope dynamics' was further
developed by Harris (1985, 1986) and commented
upon and extended to soil ecosystems by MacFadyen
(1986). The same kind of idea was developed quite
independently by Eagleson in the context of water
availability and hydrology in catchments (see Hatton,
Salvucci & Wu, 1997; references therein). Eagleson
developed the concept of an ecohydrological equili-
brium for water-limited catchments: in short, the plant
cover evolved until it reached an equilibrium with the
available water and the hydrology, so that water use
efficiency was maximised. Thus we may postulate
that any ecosystem will, given enough time and a
supply of immigrants, develop so as to fill the
ecospace and make maximal use of the resources
available. The limits to the envelope are set by energy,
major and minor elements (and water, if the system is
terrestrial in Australia or other arid places). The
corollary of this postulate is that fully developed
ecosystems make the maximal use of resources by
recycling as much as possible and leak little to the
surrounding environment (MacFadyen, 1986). Nutri-
ent retention coefficients (Dillon & Rigler, 1974;
Larsen & Mercier, 1976) in lakes with long water
residence times are high ± at least 80% of the nutrient
inputs are retained and recycled within the ecosys-
tem.
The first sentence of the last paragraph contained the
words `as far as possible'. It is clear from work on
phytoplankton that the tracking ability of some ecolo-
gical communities is good but not perfect. Phytoplank-
ton track changing light and nutrient levels first by
physiological adaptation at time scales of minutes to
hours (Harris, 1978, 1980, 1986) and then by population
and community changes at longer time scales (Harris,
1983, 1986; Leibold et al., 1997). Other populations and
communities use fundamentally the same mechanisms
but the time scales of change depend on physiology,
growth rates, reproduction and dispersal abilities. The
tracking cannot be perfect however, so that increasing
environmental (physical) variability reduces the bio-
mass of phytoplankton in the photic zones of lakes
(Harris, 1983, 1986). Lag times between stimulus and
responsearesignificant (Harris&Trimbee,1986;Harris,
1987). Similarly large scale changes in the lake environ-
ment due to marked seasonal change, fire or flood in the
catchment can cause marked transitions in the pelagic
populations and reversals in the successional sequence
(Reynolds, 1984, 1997). So the pelagic situation is one in
which at least some populations track environmental
fluctuations but never perfectly respond. Thus biomass
changes with time and nutrient retention is never
perfect. As I shall show below, while these environ-
mental fluctuations may depress the biomass res-ponse
they are nevertheless essential for a diverse pelagic
community(and thesameis true forother communities)
and they are essential for ecosystem function.
Forested catchments (or catchments dominated by
other equilibrium vegetation stands) export only small
amounts of nutrients to rivers and lakes (e.g. Attiwill
et al., 1996; Young, Marston & Davis, 1996) so oligo-
trophic conditions would have been the norm in fresh-
waters before large scale human-induced change
became prevalent. By removing the native vegetation
we have greatly modified the hydrology of the land-
scape and adjusted the flow regimes of our rivers (e.g.
Puckridge et al., 1998). We have both increased run-off
(by land clearance) and decreased run-off (by weirs,
dams and river regulation) and changed the frequency
distributions of flows. In doing so we have made major
alterations to our aquatic ecosystems.
One thing that phytoplankton ecologists and those
interested in pelagic processes need to remember is that
in many cases there are strong links to catchments,
through allochthonous loads of carbon, and to the
littoral zone (Wetzel, 1995). The limnological `envelope'
is therefore subject to catchment and littoral subsidies.
Only deep lakes (Tilzer, 1990) and the oceans have truly
pelagic planktonic communities that dominate the
cycling of energy and materials. As water bodies get
smaller and shallower, important interactions develop
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between the pelagic and the littoral zones (Schindler
et al., 1996; Vanni, 1996). As these authors show, many
lakes support fish populations that can survive only
with large energy subsidies from the littoral zone. This
seems to be a common, but largely unreported,
observation.
Many fresh water lakes and rivers show super-
saturation of pCO2 in surface waters ± where the
``extra'` CO2 (above air-equilibrium) comes from the
metabolism of allochthonous C from terrestrial sources
(Cole et al., 1994) and from photolysis of DOC by
sunlight (Townsend, Luong-Van & Boland, 1996;
Molot & Dillon, 1997). Lakes are frequently net hetero-
trophic systems (del Giorgio & Peters, 1993, 1994;
Wetzel, 1995) and many river systems are the same
(Vannote et al., 1980; Heath, 1995). Similar processes are
also important in many coastal waters (Heath, 1995;
Vodacek et al., 1997) where C subsidies from allochtho-
nous terrestrial C are important for ecosystem function
(Zweifel et al., 1995).
It is worth restating the obvious fact that there are
fundamental differences between deep and shallow
systems. Shallow systems have no deeper waters
separated by density stratification and are mixed to
the bottom, thus enhancing exchange between the
sediments and surface waters (Sas, 1989). In shallow
systems, wave action and water movement increase
the rate of diffusion of sediment pore waters into the
mixed layer (Riedl, Huang & Machan, 1972; Shum &
Sundby, 1996; Asmus et al., 1998) and resuspend
particulate material. The light reaching the sediment
surface in shallow systems can allow abundant
growth of macrophytes and microphytobenthos
which have a major impact on the biogeochemistry
of the system (Harris et al., 1996; Sigmon & Cahoon,
1997). Resuspension of particulates is much reduced
in the presence of dense stands of submerged
macrophytes (Barko & James, 1998).
Submerged and emergent macrophytes are a very
important part of the overall ecosystem function (Moss
et al., 1997). Seagrasses are abundant in oligotrophic
coastal marine waters and they tend to decline in
abundance and be replaced by macroalgae when
conditions become more eutrophic (Silberstein, Chiff-
ings & McComb, 1986; Shepherd et al., 1989). Fresh-
water macroalgae (Chara and Nitella) are limited to clear
oligotrophic systems or more calcareous waters and are
replaced by a wide range of submerged and emergent
angiosperms as the trophic status is increased (Hutch-
inson, 1975). Large macrophyte beds have a major
impact on the ecology of shallow lakes (Carpenter &
Lodge, 1986) but it seems that nearly half of the lake area
must be filled by macrophytes to produce a significant
impact on nutrient cycling and retention (Canfield &
Jones, 1984). It is not only the ability of the macrophytes
to sequester large amounts of nutrients that is im-
portant, but also the fact that the plants harbour a large
biomass of epiphytes and bacterial biofilms
that provide a much enlarged surface area for microbial
metabolism. They are also refuges for grazers when
predation is significant (Jeppesen et al., 1998).
Shallow aquatic systems (in which there is extensive
interaction between the sediments and the water
column) can exist in two states ± either clear and
macrophyte-dominated or turbulent and dominated
by phytoplankton and meroplankton (Blindow et al.,
1993,1998).WhilstGasith&Hoyer(1998)defineshallow
lakes as those which are macrophyte-dominated (see
Moss, 1995) many lakes exist in a turbid state dominated
by phyto-and meroplankton, or the lake may switch
between the two states over periods of many years
(Blindow et al., 1993; Scheffer et al., 1993). There is
competition between the littoral and the pelagic for light
and nutrients and the two states of lakes and estuaries
can be modelled by some simple relationships which
rely on some simple physiological properties of the
major groups (Harris, 1997, 1998)
One final point needs to be made. In all cases the
overall cycling of major and minor elements within
lakes and estuaries is controlled by microbial pro-
cesses. The connections between carbon, nitrogen,
phosphorus and the minor elements, and the stoichio-
metry, are controlled by populations and functional
groups of heterotrophic microbes and the stoichio-
metry is well understood (Froelich et al., 1979). The
microbial groups are ubiquitous (Finlay, Maberley &
Cooper, 1997) and mediate most, if not all of the redox
reactions in sediments. Microbial processes control
the nitrogen cycle (Smith & Hollibaugh, 1997) and the
mobilisation of phosphorus (Roden & Edmonds, 1997)
explaining most of the differences in biogeochemistry
between marine and freshwater systems. Microbial
interactions with the large detrital pools in ecosystems
are vital for the overall functioning of these systems.
In lake sediments, remineralisation of organic matter
is also related to some simple measures of lake and
catchment area, littoral zone width and water resi-
dence times (den Heyer & Kalff, 1998)
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Lakes and estuaries are driven by their catchments
and by hydrology, and are shaped by morphometry.
The biomass of many groups of organisms grows to
fill the `ecological envelope', limited by energy
supplies (including C subsidies), light and nutrients.
Many of the major interactions and limiting factors
can be explained by the physiological properties of the
major groups of organisms.
The second proposition
Population and community dynamics in the phyto-
plankton can be predicted by some relatively simple
transition functions which link population dynamics
to the state of the pelagic and benthic environments
(Reynolds, 1997). To make these predictions we need
to know both the means and the variances of the
major driving factors. Allometric relationships control
the abundance of various size fractions in the pelagic
community (the size spectra). Human-induced change
alters both the mean and the variance components of
the aquatic environment and causes consequent
adjustments in populations and community struc-
tures.
In order to characterise the behaviour of complex
systems, Holland (1998) showed that we need to be
able to identify the interacting agents, the initial state
of the systems, the rules of the game (as it were) and
the transition functions which link the basic agents
and cause the changes in state. In ecology we can
identify the agents (populations of species), we can
enumerate the population and community structures
(the state variables) and we can begin to work out the
transition functions. If these are not too complicated
we can develop adequate explanations of complex
outcomes from simple causes even if we cannot
always predict precisely what any given outcome
might be. In these systems of great complexity we
must expect both damping (and incorporation) of
some external perturbations, as well as surprising
non-linear responses and hysteresis to others.
In his recent book, `Vegetation processes in the
pelagic: a model for ecosystem theory', Reynolds
(1997) has brought together a vast array of useful
information (much of it his own) and shown that
some simple models of phytoplankton dynamics
could explain much of what is observed in the surface
waters of lakes and rivers. Effectively, Reynolds (1997)
has begun to identify the agents, describe the
transition functions and make predictions about
outcomes. Reynolds has, however, restricted his
observations, theory and predictions to population
dynamics and community structure of the freshwater
phytoplankton. Here I want to go a step further and
show that these or similar simple models of phyto-
plankton dynamics can, when supplemented by
additional considerations, be descriptive of the dy-
namics of entire aquatic ecosystems. The world may
indeed be a lot simpler than we think.
Reynolds (1997) elegantly shows that many of the
basic functional characteristics of phytoplankton can
be related to some simple correlated measures of size,
form and growth rates. Others have, over the years,
made similar observations (Lewis, 1976; Wen, Vezina
& Peters, 1979; Peters, 1983). The determining en-
vironmental conditions include temperature, light,
mixed layer physics and nutrient levels. Combina-
tions of these parameters can be used to predict the
occurrence of phytoplankton species with some cer-
tainty in many habitats (Margalef, 1978; Reynolds,
1997). Size and morphology are particularly strong
determinants of physiology in single-celled organ-
isms.
What is the empirical test for this second proposi-
tion? Reynolds (1997) identifies some of the transfer
functions for phytoplankton and shows that much is
predictable within this framework, even down to the
level of the dominant species (Reynolds & Irish, 1997).
Reynolds (1997) documents much of the empirical
data available for testing these models.
Diversity within the pelagic environment is deter-
mined by the variance spectra of the environment, the
`intermediate disturbances' which interact most
strongly with growth and competition. Environmental
variability is essential for the preservation of biodi-
versity. The relationship between disturbances and
biodiversity is presumed to be `hump shaped' as
explained in Connell (1978), Harris (1986), Huston
(1994) and Reynolds (1997). Low (small or infrequent)
disturbances lead to competitive exclusion and high
(large or frequent) disturbance leads to environments
in which many species find it difficult to survive
(Connell, 1978). Intermediate disturbances maximise
biodiversity.
The scales of turbulence and the phytoplankton
response are usually such as to ensure coexistence by
a large number of species in the pelagic system
(Harris, 1980, 1986; Reynolds, 1984, 1997). Lampert &
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Sommer (1997) make a similar point. The species
present in any given environment usually find ways
to exploit the disturbances (Harris, 1980, 1986;
Reynolds, 1992). The most powerful intermediate
disturbances for the phytoplankton are those that
last a week or so (the passage of atmospheric highs
and lows, see Harris, 1985, 1986) and the 40 day
oscillations in wind speed which occur widely in
Australia (Harris et al., 1991; Harris & Baxter, 1996).
Competitive exclusion in the phytoplankton is fre-
quently avoided by strong intermediate disturbances
and exclusion is not common except in stable
metalimnia and similar environments (Harris, 1983).
In more structured environments (e.g. in catch-
ments where trees dominate and in benthic habitats
where macrophytes dominate), through trophic inter-
actions, migration and dispersal of the organisms,
there is much interplay between the interactions of the
agents and the structure of the habitat so generated.
Wu & Loucks (1995) have discussed the role of patch
dynamics in the interactions between agents in
systems structured in two dimensions. Systems
dominated by macrophytes are not fundamentally
different from pelagic environments; there is more
physical structure which is dependent on the organ-
isms themselves, but many of the basic determinants
are similarly based on physiology, growth and loss
rates (Wardle et al., 1998). Spatial patchiness is
important for whole lake function because of littoral
subsidies and transfers of energy and nutrients within
lake basins (Schindler et al., 1996). Both horizontal and
vertical transport are important. At the scale of
landscapes dominated by larger macrophytes, spatial
patterns matter and scaling up from small scales to
large scales is much more difficult (Wu & Loucks,
1995). Equilibrium is rarely, if ever, achieved because
interactions between patches at various scales are
influenced by external driving forces also at a range of
scales. Nevertheless there are still regular allometric
size and abundance distributions of higher plants and
evidence for flux constancy and `ecospace filling'
across different communities (Enquist, Brown & West,
1998). Despite the environmental noise there is still
much that is predictable.
It has long been known that body size is a
fundamental scaling parameter for many physiologi-
cal functions and much is known about aquatic
examples (Wen, Vezina & Peters, 1979, Peters 1983).
In all aquatic ecosystems there is a spectrum of
organism size, of functional groups and of turbulence.
The size spectra of pelagic systems are well known
from the work of Sprules and Mullin (Rodriguez &
Mullin, 1986; Sprules, Casselman & Shuter, 1983;
Sprules & Munawar, 1986). The size spectra are
controlled by allometric rules relating growth and
physiology to body size (Peters, 1983). Regular
population density/size structure relationships are
found both in aquatic and in terrestrial communities
(Cyr, Peters & Downing, 1997). More recently it has
been shown that there are some fundamental fractal
scaling functions for more complex organisms as well,
and that basic physics controls a lot of physiology as
we see it (West,Brown & Enquist, 1997; Williams,
1997; Enquist et al., 1998). The fact that even complex
physiological functions of higher plants can be
reduced to parameters relating size and shape, and
that there is evidence for `envelope dynamics' even in
forests and other vegetation types, is an argument for
some universality of responses and simple underlying
causes (Enquist et al., 1998)
The emergent properties of the ecosystem produce
a set of hierarchical emergent entities that respond to
different features of the spectrum of perturbations
(Harris, 1980, 1985). The intermediate disturbances
(which differ for each community) prevent competi-
tive exclusion. For example, the disturbances that are
significant for macrobenthos are different from those
for the pelagic organisms; there are differences in the
size spectrum of the organisms (Schwinghamer, 1981)
and differences in growth rates and dispersal.
Perturbations such as changes in lake level, storms
and variations in productivity are more relevant. The
dynamics of the physical environment at relevant
scales controls the biodiversity (Huston, 1994; Rey-
nolds, 1997) while the flows of energy and nutrients
control the distribution of size classes and abundance.
Grazing interactions are critical here, in the pelagic
system, in shaping the overall biomass distribution ±
shaping of the biomass spectrum depends on energy,
nutrient recycling and grazing efficiencies (Vezina,
1986; Hansson, Bergman & Cronberg, 1998; Havens,
1998). `Bottom up' and `top down' factors both shape
the biomass spectrum and determine the fate of
primary production.
There is therefore a set of transition functions
between the environment, biodiversity and ecosystem
function which feed forward and backwards between
structure, function and fluctuation. Reynolds (1997)
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elegantly displays the necessary functions for pelagic
organisms but the transition functions include inter-
actions between organisms (competition and trophic
interactions) as well as interactions with the external
environment. Much of the dynamics is driven by
some basic physiology of size-structured groups and
their response to nutrient loads and to grazing
pressure.
The third proposition
The internal pandemonium arising from the interac-
tions between the populations in the ecosystem
produces hierarchical emergent functional groups
which structure the ``economics'` of the ecosystem
(Eldredge, 1986, 1995). These are the emergent
ecological engineering rules of aquatic ecosystems
and have simple causes (Harris & Griffiths, 1987;
Bascompte & SoleÂ, 1995).
So far we see that the basic determinants of the
overall biomass, of the distribution of sizes and of
the individual agents are to some degree predictable
on the basis of simple rules while the identity of the
individual species is more difficult to predict. Do
these populations of phytoplankton growing in the
pelagic zone show emergence?, i.e. are there higher
level emergent entities which are more consistent
and predictable? Harris (1997, 1998) has argued that
the answer is yes, and that we can aggregate the
population dynamics of the phytoplankton into
functional groups on the basis of form, function
and fate. These functional groups are emergent in
that they arise from the interactions in the pelagic
system, are consistent (``complicit'`, Cohen & Stew-
art, 1994) across ecosystems, comprise different
species in different cases, and take a functional
role in the nutrient and energy economies of entire
systems. Thus Reynolds's (1997) predicted popula-
tion and community structure for the phytoplankton
also participates in and determines function at
higher levels in the emergent system hierarchy.
As predicted by Holland (1998) these emergent
functional groups abide by `macro-laws'. There is a
complete interpenetration of structure, function and
fluctuation by which the biodiversity interacts with
the external forcing spectrum to give emergent groups
which in turn provide the functional structure of the
system. This, in turn generates internal fluctuations
which further determine the structure and biodiver-
sity of the system. Nevertheless there are consistent
emergent functional groups across systems which are
logically tractable and can be modelled.
In order to make some sense of all this we need
to understand the key transition functions and
intermediate disturbance frequencies for pivotal
functional groups. As explained in Reynolds (1984,
1997) and Harris (1986) these will depend on
physics, physiology, species design and the climatic
setting of the aquatic ecosystem in question. The
physical and geographical setting and natural
history are important. The classic distinction is
between the functional groups of small, grazed
phytoplankton and the group of larger phytoplank-
ton whose primary loss process is sedimentation
(Harris, 1984; Cushing, 1989). Microbial populations
classified on the basis of biogeochemical function
also make definition of functional groups a simple
matter in sediments and soils.
The specification of functional groups for model-
ling, for example (Harris, 1997, 1998), requires that
transfer functions appropriate for particular func-
tional groups and biogeochemistries be chosen so as
to be suitable for their particular climates and
biogeographies. The problem must be well posed
and the macro-laws must be specified at the correct
level in the hierarchy.
We know that there is a regular pattern of
response of aquatic ecosystems to altered nutrient
loads. We know that this response is based on
consistent, linked patterns in the dominant size
classes and on their physiology and changes in loss
mechanisms that depend on trophic state. The
distinctions between functional groups can be
found in a small number of basic physiological
and physical properties of the groups (Duarte et al.,
1995; Reynolds, 1997): maximum growth rates, half
saturation coefficients for nutrient uptake and
sedimentation rates for phytoplankton; reproduction
rates, grazing rates and efficiencies for zooplankton
(Harris, 1998).
Functional groups require a minimum biodiversity
in order to function in the face of external forcing.
Recent papers by Tilman and others on biodiversity
and function have shown that there is a strong
relationship between biodiversity and system func-
tion (e.g. Tilman, Lehman & Thomson, 1997; Chapin
et al., 1998) and that there is a good theoretical basis
for this (Symstad et al., 1998). The forces which
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maintain biodiversity run orthogonally to those which
control the `economics' of the system (Eldredge, 1986).
Biodiversity is essential to maintain ecosystem func-
tion. Each functional group requires a small, finite
number of species to maintain function, and there is a
response of improved function which is correlated
with increased species diversity up to a plateau
(Chapin et al., 1998). In diverse ecosystems this
implies a high degree of functional redundancy
(Walker, 1992). The relationship between function
and biodiversity implies that there are differences in
the performances of the constituent species (Lawton
et al., 1998) which, in the case of phytoplankton, are
based on size, physiology and fate. Some species are
effective ecosystem engineers, modifying the environ-
ment for themselves and others (Jones, Lawton &
Shachak, 1994).
The use of functional groups to model aquatic
ecosystems is common (e.g. Christian et al., 1996;
Harris et al., 1996; Harris, 1997, 1998) and can
reproduce most of the dynamics of lakes and
estuaries, including the switch between alternative
stable states (Janse, 1997; Harris, 1999). Functional
groups are as valid for benthic communities as they
are for the pelagic (Steneck & Dethier, 1994). Many
lakes exist in a turbid state dominated by phyto-and
meroplankton, or the lake may switch between the
two states over periods of many years (Blindow,
Hargeby & Anmdersson, 1993; Scheffer et al., 1993;
Jeppesen et al., 1998). Functional group modelling can
reproduce this behaviour. The incorporation of
competition for light and nutrients between functional
groups in the pelagic community and the benthos is a
crucial factor in structuring lake and estuarine
communities and reproducing the observed dynamics
and responses to nutrient loads (Blindow et al., 1993;
Borum & Sand-Jensen, 1996; Janse, 1997; Harris, 1999).
It is a further reminder that the functioning of lakes
and estuaries can be critically dependent on the
presence of aquatic macrophytes (Asaeda & van
Bon, 1997).
This proposition was discussed on similar grounds
by Harris (1997, 1998) who argued that the properties
of simple nutrient : phytoplankton : zooplankton
(NPZ) models of coupled pelagic and benthic pro-
cesses, while showing complex non-linear responses,
are in fact based on a small number of physiological
parameters ± about eight or nine. The requirement
here is to aggregate the systems on the basis of
functional groups, largely defined by some simple
relationships between form and function (Duarte
et al., 1995; Reynolds, 1997). The reason the functional
groups are common across systems (`complicit',
Cohen & Stewart, 1994) is precisely because (as
argued in proposition two) the physiological para-
meters required are fundamental and based on
simple rules of size and shape. As argued in
proposition two above, the world does indeed show
complex behaviour which arises from simple causes
(Bascompte & SoleÂ, 1995). Some ``simple physics,
physiology and the design of the organisms'' is
probably all we need to know (Harris & Griffiths,
1987).
The fourth proposition
The larger emergent properties of ecosystems, such as
succession, also arise from simple causes, namely the
interactions within and between functional groups.
The interactions within and between functional
groups are controlled by some basic physiological
properties of the organisms.
Harris (1985) claimed that it was not possible to
model ecosystems with their observed complexity,
but the approach outlined here, that of using func-
tional groups, makes such modelling possible. This
statement is reinforced by the recent work of Loreau
(1998) who has shown that the properties of ecological
successions emerge from some very simple under-
lying physiological properties of the organisms. We
do not need to invoke `holistic' or structural succes-
sional rules (Dennett, 1995; Harris, 1998). Successional
trends such as reductions in P : B ratios and increased
nutrient cycling efficiencies arise from competition
and interaction between species that have varying
growth rates and nutrient uptake characteristics. A
product of Loreau's (1998) argument is that, left to
their own devices, ecosystems evolve to a state
whereby the key rate constants are determined by
selection for rapid (and closed) cycling of nutrients
and energy. When the half saturation constants for
nutrient uptake are minimal and growth rates are
maximised through competition, the system proper-
ties emerge.
The fundamental postulate is merely that selection
for maximum growth rates and maximum nutrient
uptake efficiencies is all that is needed for the systems
properties to emerge (Tilman, 1982). Symstad et al.
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(1998) have used the same argument to provide the
theory of the relationships between biodiversity and
the functioning of functional groups. Changes in
ecosystem properties are the indirect result of selec-
tion for functional or demographic trends in the
organisms involved. Physical disturbances disrupt the
progression towards the `climax' state (which is the
state of maximum nutrient retention, maximum
growth rates and recycling efficiency, and maximum
biodiversity if sufficient time is allowed for immigra-
tion, Reynolds, 1997) and make the system more
`leaky' and less efficient. Increased environmental
perturbations, reduced biodiversity (to a monocul-
ture, frequently) and a mismatch between regenera-
tion (or addition of N from fertiliser, etc.) and
autotrophic uptake of N by plants (Durka et al.,
1994; Hedin, 1994) lead to poor selection for the
most efficient cycling system and release of nutrient to
lakes and waterways. In highly disrupted systems
competition may not be a strong structuring force
(Harris, 1986). Even at `equilibrium' with some
perturbations, systems are still `leaky' to some extent.
This may be because systems have not perfectly co-
evolved, mostly being composed of `kludges' (Den-
nett, 1995) of various kinds ± `make do' assemblages
of whatever evolution, biogeography and dispersal
have left in that particular system at the time. The
vagaries of natural history and contingent dispersal
have a real effect on the performance of the entire
system.
If there is something fundamental about the NPZ
functional group relationship, in that there is some
kind of equilibrium between the rate of nutrient
uptake by the plants and the rate of generation of
nutrients by microbial action from, say, detritus both
in the pelagic and in the littoral zones (Harris, 1997),
then this implies that the entire system is subject to the
optimisation of the rate constants, even those of the
critical microbial communities which are responsible
for the decomposition and redox transformations.
Natural ecosystems seem to evolve into a state where
losses from dissolved nutrient pools in soil and water
by physical means (groundwater and transport by
flushing) are low (MacFadyen, 1986). Increases in
nutrient loads or a decrease in autotrophic plant
growth change the balance so that nutrient exports
begin. This balance can now be understood and
modelled (Durka et al., 1994; Creed et al., 1996;
Emmett et al., 1997).
The fifth proposition
In order to display the properties that we see, aquatic
systems must be sufficiently complex (`space filling')
to display pandemonium and emergence, and must
be non-linear in their responses to external forcing.
Interactions with large, slow, detrital pools determine
the directions of the successional sequences and lead
to the hysteresis effects.
Complex non-linear systems show both amplifica-
tion and damping of external forcing functions and
may switch between states after small changes in
external conditions (Holland, 1998). Aquatic ecosys-
tems do indeed show marked non-linearity in their
responses to external perturbations such as nutrient
loads and, on occasion, switches between different
stable states may be evident (Harris, 1998).
Wherein lies the non-linearity and how do we
explain such behaviour? There are three causes. One
is that the interactions in surface waters are inherently
non-linear (the `paradox of enrichment', Rosenzweig,
1971; De Angelis, 1992): as nutrient loads are in-
creased, the pelagic system switches between being
predominantly grazed, with nutrients recycled within
surface waters, to being dominated by larger poorly
grazed forms with losses primarily through sedimen-
tation to the sediments. (This is the basis of Vollen-
weider's successful models of eutrophication, Harris,
1994). This first cause is physiological. It happens
because of the relationships between size, growth rate
and nutrient uptake kinetics of the phytoplankton.
The build up of nutrients in the water of lakes
undergoing nutrient loading is controlled by the
growth rates of the phytoplankton and their half
saturation constants for nutrient uptake.
The second cause lies in the large changes in the
internal load of nutrients derived from the sediments
as the development of anoxia switches the sediments
from being a sink, in oligotrophic lakes, to being a
source in eutrophic lakes. This non-linearity is a func-
tion of sediment geochemistry, stratification, oxygen
diffusion and microbial ecology (Sas, 1989; Martinova,
1993). The phenomenon has been known since the
early classic work of Einsele (1936) and Mortimer
(1941±42) and is connected with the chemistry of Fe
and S, but it is now known to be biologically mediated
by microbial populations in the sediment (Roden &
Edmonds, 1997). It happens after a pause, because as
the nutrient load is increased it is transferred to the
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sediments and the deoxygenation slowly builds up.
Then, quite suddenly, the internal load increases and
the whole system switches over to the new (eutrophic)
state. As Vollenweider showed, this is all a function of
catchment loads and lake morphology (Vollenweider
& Janus, 1982). Shallow and deep lakes react differ-
ently because of the larger volume of the hypolimnia
in deep lakes. Macrophytes also play a key role in
sequestering nutrients and so have a major impact on
the functioning of shallow lakes and estuaries (Chris-
tian et al., 1996; Janse, 1997; Harris, 1999) delaying the
onset of algal blooms.
The third cause lies in the interaction of the pelagic
with the macrophytes and other organisms of the
benthos and the littoral. Much of the non-linear
behaviour of the entire system arises from the
sequestration of nutrients in the macrophytes which
turn over slowly and from competition between
pelagic and benthic organisms for nutrients and
light (Janse, 1997; Harris, 1999). Lake and estuary
morphometry plays an important role in these
interactions, as do flushing rates and water residence
times. Small changes in water residence times have a
major impact on the competition between the pelagic
and the littoral organisms (Harris, 1999). Flushing
removes pelagic organisms whilst leaving the
attached littoral plants in place.
Thus, directional changes in successions and non-
linearities arise from the intrinsic physiological
properties of the plankters and their interactions
with a number of large, slowly turning over, nutrient
pools in the system (Harris, 1988, 1997). The sedi-
ments, the macrophyte beds, and dissolved organic
nutrients in the water column can structure the
succession by accumulating large amounts of nutri-
ents and taking them out of circulation over time
scales of seasons to years. For this reason some non-
linear changes in ecosystem state may be essentially
irreversible (Harris et al., 1996) if they are associated
with strong hysteresis and the initiation of new (e.g.
anoxic) conditions or with the elimination of nutrient
pools in the sediments or organic matter that were
essential for the development of the initial state.
The sixth proposition
Nested loops of energy and nutrient recycling at
various scales are a convergent state which responds
to external forcing. The ``goal'' state of ecosystems is
biologically diverse and nutrient (and water use)
efficient. It arises as a result of interactions between
external perturbations and internal competition plus
the natural spectrum of allometric `space filling' rules.
The range of turnover times of nutrient pools in the
sediments and the water column, and the emergent
properties of ecosystems, arise naturally from the
basic rules of organism design, body size, physiology,
physics and chemistry. There is therefore no need to
invoke any special structural rules of emergence
(Dennett, 1995), neither is there any need for a
`Great Central Meaner' or a Cartesian Theatre
(Dennett, 1993), or any `Gaia' (Lovelock, 1979). All
that is required is a pandemonium of interactions and
the algorithmic working out of many processes.
All aquatic ecosystems seem to have a wide range
of sizes of nutrient and energy pools and turnover
times with much spatial and temporal variation. It
seems that aquatic ecosystems converge on this state
and that there is both `signal' and `noise' in the
properties of these highly complex, non-linear sys-
tems (Harris & Griffiths, 1987) so that biodiversity and
ecosystem function are maintained in the face of
external forcing functions. The properties emerge
from the underlying pandemonium and from the
interaction of smaller `faster' (pelagic) nutrient pools
with larger `slower' (sedimentary and macrophyte)
nutrient pools which may cause non-linearities in the
ecosystem response to the natural spectrum of
perturbations.
To understand the dynamics of aquatic ecosystems
therefore we merely need to invoke a small number of
physiological and functional properties of the organ-
isms together with their interaction with the other
emergent features (large, slow pools of nutrients) in
the system. There is interaction between various levels
in the hierarchy (Harris, 1985), between populations
within functional groups and between functional
groups (Loreau, 1998) and between the various
groups across the size spectrum of organisms. In the
face of external perturbations the most stable state for
ecosystems seems to be a range of organism sizes and
of turnover times. Presumably this has evolved as a
set of most stable relationships between the driving
(external) variance spectra and the internal pandemo-
nium and response. We must assume that the most
stable state is that with a range of species growth
rates, dispersal abilities, nutrient turnover times and
buffering pools.
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In the oceanographic and limnological literature the
concept of ``f'` numbers is used to explain the
interactions of nutrient loads, regeneration and algal
growth (Eppley & Peterson, 1979). What emerges as a
system is a nested grouping of ``f'` numbers and
possible sizes, in which the nesting goes from
microbial loops in the pelagic system all the way to
sediment and water column interactions (Harris,
1998). General observations indicate that small, tightly
coupled microbial loops often occur in the pelagic
zone; larger, looser, grazed loops occur in eutrophic
water; and finally, there are sedimentary and macro-
phyte interactions and export losses. These relation-
ships are governed by similar interactions between
nutrient uptake kinetics, growth rates and grazing
efficiencies, and microbial processes in the water
column and in the sediments. The same patterns exist
in sediments and soils (MacFadyen, 1986), and there
are strong parallels between water, sediments and
soils in terms of the possible ranges of sizes and
microbial processes (Wagener, Oswood & Schimel,
1998).
The evolved solution is not perfect because of
environmental perturbations (and the impact of
extreme events), and because of the vagaries of
biogeography and immigration and the presence of
`kludges' (Dennett, 1993) of various kinds. Ecosystems
are not perfectly coevolved, there is much `make do'
of the biodiversity with whatever is to hand, whatever
immigrant populations arrive. Ecosystems can only
achieve high biodiversity, fully tracking ability and
high nutrient retention over evolutionary time scales,
and even then assuming that nutrient and energy
inputs are high and that the environment stays
constant (in terms of both means and variances)
over very long time scales. Eventually we might
expect that the system would evolve to become
independent of the initial, contingent conditions, i.e.
over long enough time scales the `economy rules'
(Eldredge, 1986, 1995) would dominate and efficien-
cies would be maximal. Given the usual environ-
mental variability and the present strong
anthropogenic impact on natural ecosystems, less
than perfect, contingent solutions might be the norm.
The occasional, large perturbation (storm, flood or
fire) resets many of the system pools (as well as the
phytoplankton succession, Reynolds, 1997) and
ensures that steady state conditions are rarely, if
ever, reached. This condition is reinforced by the fact
that climate variability in countries like Australia,
with characteristic frequencies corresponding to El
NinÄ o and Southern Oscillation events (Harris et al.,
1988; Harris & Baxter, 1996), interacts strongly with
macrophyte regrowth and the development of sedi-
ment nutrient pools over similar time scales. Austra-
lian and other subtropical aquatic ecosystems
probably rarely reach any kind of steady state and
have evolved to cope with strong environmental
variability. Frequency components in the environ-
mental variability are more important than means
(Harris & Griffiths, 1987; Puckridge et al., 1998).
Conservation in these situations is therefore an
attempt to preserve a moving target (Harris, 1994).
Nevertheless there is an urgent need for conserva-
tion of aquatic biodiversity, not just biodiversity (as
species richness) for aesthetic reasons, but also to
ensure proper landscape function. Ecosystem services
are extraordinarily valuable resources, both globally
and nationally (Costanza et al., 1997). Aquatic biodi-
versity ensures the functioning of our lakes, wetlands
and estuaries. In addition there is a pressing need to
keep extreme perturbations to a minimum and to
ensure that we maintain oligotrophic conditions in
our waters. Land use must therefore be restored in
ways which are beneficial to the preservation of our
aquatic ecosystems.
In addition there is a need to be better informed
about the basic biology and physiology of key aquatic
groups and species and their responses to environ-
mental variability. The reason that Reynolds (1997)
was able to bring so much information together into a
predictive framework was because there is a sound
base of fundamental biology and physiology already
known for northern hemisphere species. This has
been built up over the years by organisations such as
the Freshwater Biological Association in UK and the
major European limnological laboratories, all of which
have long and proud histories of fundamental work.
The work that is required in the rest of the world is
neither `trendy' nor, probably, fundable in this era
which tends to concentrate on mission-oriented work
(Gibbons et al., 1994; Reynolds, 1998). Nevertheless it
is essential if we are to conserve and preserve our
aquatic ecosystems and resources for future genera-
tions. Studies of basic physiology and biology will
lead to fundamental advances and an improved
understanding of ecological complexity, and at the
same time it will provide managers with useful tools.
700 G. Harris
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We now have the data and understanding to make
significant advances. We have urgent need of the
basic information, of the factors which produce
deep patterns of behaviour in these complex ecosys-
tems.
Acknowledgments
The author wishes to thank Michael Raupach, John
Williams, Garry Jones, Colin Townsend and an
anonymous referee for valuable comments on earlier
drafts of this manuscript. The manuscript was much
improved by the editorial skills of Ann Milligan who,
as usual, was able to turn a stream of consciousness
into something more like a reasoned argument.
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