HYDROLOGICAL PROCESSESINVITED COMMENTARY

Hydrol. Process. 18, 3683–3686 (2004)Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hyp.5762

Ecohydrology: it’s all in the game?

Albert van Dijk*†

Department of Geo-environmentalSciences and Hydrology, VrijeUniversiteit Amsterdam,Amsterdam, The Netherlands

*Correspondence to/†Presentaddress: Albert van Dijk, CSIROLand and Water, GPO Box 1666,Canberra, 2601 ACT, Australia.E-mail: albert.vandijk@csiro.au

Reflecting the widespread merging of Earth and life sciences, recentyears have seen the emergence of ecohydrology as a new branch onthe hydrological tree. The term itself was coined only a few yearsago (see Baird and Wilby (1999)), but its objective—to understandthe role of ecosystems in hydrology and vice versa—is not new. Thehydrology of land-use change has a distinguished past and the (realor perceived) understanding of it drives land management decisionsworld-wide. Milestones in the development of ecohydrological theoryincluded the description of the role of the vegetation in controllingevapotranspiration (ET), in affecting the amount of rainfall inter-cepted and evaporated again and, conversely, the effect of soil wateravailability on vegetation water use. To this should be added the roleof ecosystems in maintaining or altering soil structure and, thereby,its hydraulic properties, although a consistent physical theory is stilllacking in this respect.

Despite this good understanding of most ecohydrological pro-cesses, the application of physical deterministic models describingthese processes has met with variable success. A case in point isthe Penman–Monteith model, which is arguably the greatest con-tribution to ecohydrology so far and the basis of most currentsurface–vegetation–atmosphere transfer models (e.g. Sellers et al.,1997). Despite its often good performance in describing observedevaporative fluxes, it has proved difficult to obtain robust a prioriestimates of a key vegetation characteristic, surface conductance.Upscaling leaf-level measurements of stomatal conductance to standlevel has proved a non-trivial affair, and, in fact, variability at standlevel appears to be less than at leaf level (Kelliher et al., 1995).We face similar discrepancies when describing rainfall intercep-tion, the effect of (seasonal) water shortage on ET and the surfaceenergy balance, and the effect of land-use change on infiltration.At larger scales, relationships between ET, rainfall and radiationenergy generally appear to become more straightforward, and wateruse by vegetation in similar climates more conservative, than may beexpected on the basis of Penman–Monteith theory (Roberts, 1983;Zhang et al., 2001).

What causes this inconsistency? Probably, we are missing a phys-ical scaling ‘trick’ or two, and improved scaling rules may helpto overcome some of the discrepancy. However, there may be a sec-ond, more profound cause, related to the complex and self-regulatingnature of ecosystems. Complex systems theory shows how individualcomponents (cell, leaf or tree) may follow one particular set of rules,

Received 9 February 2004

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A. VAN DIJK

but, through their interactions, produce a verydifferent macroscale or emergent behaviour. Canthe complexity of ecosystem behaviour explainthe apparent conservancy in ET? In that case,the surface conductance term in the Penman–Monteith model effectively may be no more thanan ‘emergent’ property, having a value that fol-lows from model fitting but that is actually con-trolled by other rules. Complex systems theoryhas matured, and it may help us to understandbetter the relationships between the spatial andtemporal vegetation structure on the one hand,and hydrological processes, such as ET, but alsorainfall interception, partitioning and infiltration,on the other hand.

A link between complex systems behaviour andET is particularly likely in water-limited ecosys-tems. For example, Rietkerk et al. (2002) usedmathematical theory describing chemical self-organization in living cells to reproduce the veg-etation patterns found in semi-arid areas likethe Sahel: from a continuous vegetation in wet-ter areas, via banded ‘tiger-bush’, to a patternof scattered vegetation patches in a dry environ-ment. The different patterns form automaticallywhere the vegetated soil can absorb more rain-fall than the bare patches in between. Althoughother processes may also play a role in form-ing these patterns, the consequences are easy toappreciate: less water is lost via surface runoffor soil evaporation, and overall ecosystem water-use efficiency is higher than would be expectedwithout taking into account lateral water fluxes.Vegetation patchiness also has wider implicationsfor surface–atmosphere exchanges of water andenergy, as demonstrated by the HAPEX-SAHELexperiments (Goutorbe et al., 1997).

If ecosystem structure can be important for itshydrological functioning, then how can we studyits complex machinery? One can approach thisproblem from the top down or from the bottomup. In the former case, we can consider the overallor emergent behaviour of the system and describeit by what may be called macro-rules. Advanceshave been made with the top-down or ‘systems’approach in (eco-) hydrology: see for instancethe recent Hydrological Processes special issue onthe topic (Sivapalan et al., 2003). The potentialstrength of such an empirical approach lies in its

simplicity; as such, it has important applications.For example, the empirical curves of Zhang et al.(2000) are now widely used in Australia for esti-mating the effects of plantation establishment onstream flow and stream salinity. However, it doesnot explain the links between lower level interac-tions and overall systems behaviour, and its capac-ity to extrapolate beyond observed conditions islimited by the implicit assumption that these linksremain unchanged. Thus, ‘Zhang curves’ do notprovide us with insight into how forest structureaffects water use, or how water use may changeafter a disturbance or climate change.

As an alternative, therefore, we may attempt toexplain ecosystem–water interactions at the sys-tems level with mechanistic process models. Exam-ples of this approach include the optimality the-ory developed by Eagleson (2002) and the workof Rodrıguez-Iturbe and colleagues (2000; Porpo-rato and Rodrıguez-Iturbe, 2002), which takes intoaccount the stochastic nature (in time and space)of the vegetation, soil and climate properties andthe processes involved. This approach requires anumber of assumptions about the behaviour of thesystem as a whole. More particularly, a (dynamic)equilibrium is commonly assumed, in which adap-tation acts to maintain the equilibrium. This, inturn, requires assumptions about the magnitudeof disturbance or climate extreme that the adaptedecosystem can experience without carry-on effects(i.e. a subsequent recovery phase; see Gutschickand BassiriRad (2003)). Therefore, the systems-level optimality approach may not always pro-vide sufficient understanding of the ecosystem’sinternal workings to predict its behaviour aftersuch events. Once brought out of equilibrium,the ecosystem may not return to its former state,but instead move to an alternative state (Schefferet al., 2001). Given that ecohydrology is, to a largedegree, a ‘what if’ science, concerned with thestability of ecosystem structure and its behaviourafter natural or human disturbances, this is not aminor problem.

We can also take a bottom-up approach andtry to describe the interactions between ecosys-tem components explicitly, e.g. between individ-ual plants or clusters of plants. This presents agreat challenge: If we already find it difficult todescribe processes as we observe them at stand

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INVITED COMMENTARY

level, how can we hope to describe interactionsamong individual trees? Yet this may be posingthe wrong question, as complex systems theorytells us that the parts behave in a different man-ner than does the whole. Working our way upthrough the system may, therefore, lead us toanswers rather than more questions. To use ananalogy from water chemistry: we know the physi-cal properties (the emergent behaviour) of water asa liquid or solid quite well, yet this has not helpedscientists much in understanding exactly why, toput it simply, ice floats. Computers simulatingthe interactions between large numbers of indi-vidual molecules, however, have helped to formu-late and confirm theories and explain observationsof the many structures water can assume. Sim-ilar computer simulations have also found theirway into ecology, sociology and cybernetics, amongothers, as well as producing a new generation ofcomputer games (Johnson, 2001). Despite theirapparent potential, so far they have hardly beenused in ecohydrology, however—the closest exam-ple to date may well be the use of a cellularautomata model by Van Wijk and Rodr ıguez-Iturbe (2002).

Can this games approach be fruitful in ecohy-drology? Evidently it will not suit all purposes, andfor many research problems more conventional,empirical methods will be more suitable. However,when it comes to understanding the relationshipbetween structure and function, complex systemstheory can certainly make an important contribu-tion, as it already has in ecology and many otherdisciplines (Janssen, 1998; Gunderson and Holling,2002). It will not be easy: plants themselves arecomplex organisms; they dynamically adapt tochanging conditions and do not obey a simpleset of fixed rules. As mentioned, disturbances,droughts and other climate extremes introducean additional level to the game: the playing fieldkeeps changing. The erratic climate forces plantsto develop a strategy somewhere between thoseof the proverbial tortoise and hare, i.e. low gainor high risk (Gutschick and BassiriRad, 2003; inEagleson (1994) for a hydrological context). Inno-vative ways need be found to incorporate thesemany trade-off mechanisms and interactions inour computer games.

Fortunately, considerable headway has alreadybeen made by scientists in other disciplines. Indi-vidual-based modelling has been applied success-fully to reproduce the emergent results at for-est stand level for light competition, reproductionand mortality between trees (Deutschman et al.,1997). Still, many aspects of plant physiologicalbehaviour remain to be described.

A promising way forward is offered by focus-ing on the limits of adaptive strategies. Win–winstrategies do not exist, and so any particular plantform and function must express some form oftrade-off. Probably the example most familiar toecohydrologists is the trade-off regulated by leafstomata: balancing CO2 gain, water vapour lossand leaf temperature. Another is that betweenallocating biomass above ground to compete forlight, or below ground to compete for water andnutrients. Various trade-off strategies have alreadybeen described for different plant functional typesin global dynamic vegetation models (e.g. Crameret al., 2001). Although these models operate at amuch larger scale, some of these algorithms maybe transferable to lower levels.

Evidence is also mounting rapidly that thenature of the trade-offs described above resultsin a surprisingly limited range of combinations ofmost physiological properties, and that these com-binations often lead to identical outcomes througha process called functional convergence. For exam-ple, research by Reich et al. (1997) on plants froma wide variety of ecosystems has shown that leafnitrogen content, assimilative capacity, respirationcosts and longevity are all strongly correlated.Similarly, Meinzer (2003) found functional con-vergence in plant hydraulic properties.

Given these efforts in other disciplines, whyshould ecohydrologists contribute to fanciful com-puter games? Ecohydrologists are ideally placed toappreciate the physical processes in the vegetation,atmosphere and soil and the way in which theseinteract both vertically and laterally. Complex sys-tems theory in general, and playing the ‘ecosystemgame’ in particular, may help us to understandand eventually overcome scaling problems, and toextrapolate our physical understanding to a futureenvironment. The world is changing and ecosys-tems are changing with it. It is the task of eco-hydrologists to anticipate these changes, whether

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fast or gradual, human or natural, and how thiswill ultimately affect our livelihoods. Simulatingecosystem hydrological processes may prove to bean exciting game, but a serious one.

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