This is not the end of limnology (or of science): the world may well be a lot simpler than we think

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 ènd of

science'. By this he meant that we have now discovered

the fundamental natural laws of evolution and the

cosmos and that pure or àesthetic' 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 ènd 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 àcademic 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]

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

ã 1999 Blackwell Science Ltd, Freshwater Biology, 42, 689±706

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.,

This is not the end of limnology 691


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 ènvelope 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 às 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 ènvelope'

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

692 G. Harris


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)



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 &

694 G. Harris


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)



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

696 G. Harris


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.



(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

698 G. Harris


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.



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


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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This is not the end of limnology (or of science): the world may well be a lot simpler than we think

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