Journal of Aquatic Ecosystem Stress and Recovery6: 253–257, 1999.M. Power (ed.), Recovery in Aquatic Ecosystems.©1999Kluwer Academic Publishers. Printed in the Netherlands.

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Recovery in aquatic ecosystems: an overview of knowledge and needs

M. PowerDepartment of Biology, University of Waterloo, Waterloo, ON, N2L 3G1, Canada

Key words:recovery, aquatic stress, variability, ecosystem dynamics

Abstract

This article summarizes the views of scientists asked to address some of the critical unanswered questions concern-ing recovery in aquatic systems. Spatial and temporal variability were emphasized because of their implicationsfor our abilities to distinguish between recovered and non-recovered ecosystems and the consequent effects suchvariability has on the statistical precision of developed recovery metrics. There was also consensus that pre-disturbance ecosystem states may not be re-established in the absence of a disturbance event and that better datasets will be required to separate the influences of natural variability from disturbance event induced fluctuations inmany biological measures. Although discussions tended to focus at the population or community level, evidencefrom physiological-based measures of recovery indicates divergent rates of recovery at varying levels of biologicalorganization, a fact which suggests a role for biomarkers in developing a complete understanding of recovery.Critical questions concerning the determination and understanding of recovery that remain to be answered areidentified.

1. Introduction

The primary aim of the articles in this special issuewas the provision of a broad perspective on the theoryand practice of determining recovery in impactedaquatic ecosystems. Each of the contributing authorshas examined recovery from a unique perspective,varying from the philosophical (O’Neill, 1999) to thestatistical (Chapman, 1999). As with previous assess-ments of aquatic ecosystem theory and/or recovery(e.g., Standford & Crovich, 1988; Gore et al.,1990), this collection of articles has broadly concludedthat further advances in our understanding ofrecovery phenomena could be made through researchemphasizing the variety of spatial and temporal scalesat which ecosystem structure and function occur. Forexample, Galatowitsch et al. (1999) note the promiseof community-based metrics for assessing the degreeand rate of recovery, but caution that developedcommunity-level metrics will require validation acrossa range of spatial and temporal scales. Chapman(1999) expands on this point when discussing thechallenges spatial and temporal variability pose for

determining the statistical significance of observedrecovery trajectories and Depledge (1999) extends theargument to consideration of the differential rates atwhich recovery occurs at varying levels of biologicalorganization.

For any particular disturbance, traditionalapproaches to evaluating recovery have favouredusing the inverse of the deviation from the nominalecosystem state to measure resistence, and the timerequired to return to equilibrium to characterizeresilience (e.g., Pimm, 1991). Although usefulfor characterizing recovery from short-term,one of disturbances, traditional measures do nottake appropriate account of ecosystem variability.Increased variability can complicate the determinationof recovery times in many instances, and requiresadditional knowledge of ecosystem states both beforeand after the disturbance event (Chapman, 1999).As a result, the studies in this issue did not focuson the use of traditional recovery metrics. Instead,the studies in this issue tended to view ecosystemsas complex, nonlinear dynamic systems in whichspecific endpoints (e.g., population abundance)

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were not guaranteed to return to pre-disturbancevalues in the post-disturbance period. The possibleestablishment of new ecosystem configurations inthe post disturbance period has been establishedtheoretically (May & Oster, 1976) and empirically(Allen et al., 1977), and when actually observedgreatly complicates both the definition and statisticaldetermination of when recovery has been achieved(O’Neill, 1999; Chapman, 1999).

Simple recovery metrics suffer from other deficien-cies. Resilience, for example, varies with the typeand magnitude of disturbance (Gore et al., 1990).For pulse events, the rate of recovery is largelycontrolled by the biological attributes of the affectedcommunity, its degree of isolation from potential re-colonizing sources, organism dispersal capabilitiesand the characteristics of available refugia (Niemiet al., 1990). Understanding of recovery from pulseevents, accordingly, requires more than an under-standing of resilience, it requires understanding therole that each of these factors play in determiningrecovery times. Recovery from press events, however,is not so easily characterized. As a result, therecovery process can take years and may neces-sitate human intervention to restore habitat and re-introduce lost species (Allan, 1995; Keller et al.,1999a). In many circumstances, this makes recoveryand restoration synonymous and, as Chapman (1999)argues, necessitates careful experimental design fordetermining when successful recovery has beenachieved. Extended time frames further complicatethe assessment of recovery from press disturbancesby increasing the chance of confounding events influ-encing the recovery trajectory. For example, throughdrought events, weather patterns can have profoundeffects on measured trends in lake chemistry (Kelleret al., 1999a). Unfortunately, most of the finan-cial resources available for ecosystem restoration andrecovery are utilized for the activities associated withrestoration itself, not for studying the ecologicalappropriateness or effectiveness of restoration initi-atives (Minns et al., 1996) or the consequences ofconfounding factors on the determination of recovery.Undoubtedly, this prejudice for action has hampereddevelopment of our understanding of ecosystemresponses to most press disturbances.

2. Ecology, society and recovery

To some extent the lack of a general consensusfor recovery theory is attributable to the practiceof ecology itself. For example, aquatic ecologistshave tended to assume that temporal variations inlotic communities are largely the result of physico-chemical disturbances (Hildrew & Giller, 1994). Thisassumption has lead naturally to focusing on waterquality impacts, to charting ‘recovery’ from chemicalchanges, and to the widespread use of null hypoth-eses postulating that recovery has occurred whenthere is no longer a statistically significant differencebetween the pre- and post-disturbance measurementendpoints describing critical physico-chemical vari-ates (e.g., Niemi et al., 1993). Keller et al. (1999a),however, have shown that this is not always thecase. Even at near neutral pH some previously acid-ified Sudbury, Ontario, area lakes exhibit unusualbiological characteristics suggestive of changes inthe functional processes of productivity and nutrientcycling.

Knowledge that changes in the chemical natureof water can impair the recovery process, and mayrequire restorative aid for recovery to be fully achieved(Cairns, 1986), has reinforced the simple waterquality approach to recovery determination. Further-more, work in lotic ecology has tended to downplay the significance of many disturbance events byarguing that communities are often pre-adapted to theperiodicity associated with those same events. Forexample, studies of stream invertebrate communitieshave demonstrated their adeptness at recovering fromthe frequent, small-scale, low intensity disturbancesthat dominate the flow regimes of many streamsystems (Townsend, 1989) and which play criticalroles in determining community structure and function(Resh et al., 1988).

Much of the evidence assembled from studiesof aquatic systems also points to relatively rapidrecovery. The estimates of recovery times for manywater quality and summary biological measuresindicate ecosystem recovery can occur in very shortperiods of time, often less than three years (Niemiet al., 1990). In spite of this evidence, distinctionsbetween abiotic and biotic recovery will be necessarybecause the sample sizes required to detect differ-ences, and assess recovery, in most biological vari-ables are significantly larger than those required forphysico-chemical variates (Niemi et al., 1993). Unfor-tunately the importance of this observation for our

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ability to detect recovery in ecological measures isnot fully understood, and the notion persists thatrecovery in easily measured water quality parametersnecessarily implies recovery in dependent biologicalvariables, albeit with appropriate lags.

An equally important reason for focusing onrecovery to pre-disturbance states, however, stemsfrom the role that society invariably plays in deter-mining, or agreeing, on how recovery is ultimatelydefined. Society rarely intervenes to aid recoverywithout at least some conceptual model that definesthe preferred outcomes (Minns et al., 1996). All toooften those preferred outcomes equate with the re-establishment of the pre-disturbance state. O’Neill(1999), however, notes that this may be impractical.Hystersis implies that a disturbed ecosystem may notrevert to its pre-disturbance state even when the stressis completely removed. The establishment of measur-ably different ecosystem configurations does occur.Keller et al. (1999b) provide some concrete examplesin the context of lake recovery from acidificationstresses, noting that despite reductions in sulphuremissions only limited evidence of chemical andbiological recovery has been collected to date. Phys-ical barriers to fish migration, high competition fromacid tolerant species, and the coincident action ofother stressors (e.g., reduction in base cation deposi-tion) may all be hindering recovery to pre-disturbancestates.

If, as Holling (1987) has argued, the structuraland functional elements of ecosystems are linkedby cyclical changes in the amounts of energy andnutrients sequestered, and the degree of ecologicalcomplexity and connectance exhibited, re-attainmentof pre-disturbance states may be more the exceptionthan the rule. Aquatic macrophyte communities innatural lakes and reservoirs will wax and wane asthe systems eutrophy with age. Storm events, througha redistribution of substrate, nutrients and species,can induce rejuvenation in affected ecosystems thatimply a constantly evolving state at odds with thenotion of a unique equilibrium state. Even in caseswhere recovery trajectories suggest the attainment ofpre-disturbance states, recovery may be slow andrequire the added stimulus of human intervention (e.g.,species stocking or habitat restoration). Keller et al.(1999b) also point out there is no reason to supposethat the disturbances created by decades of exposure(e.g., acidification) should be corrected within yearsof the removal of the stress. The temporal scales ofecosystem responses may well exceed the scales over

which humans are typically able, or willing, to under-stand how recovery responses are mechanisticallylinked to causal factors.

3. The implications of scale for recovery

Patterns of spatial change and ecosystem responses tostress may likewise hold implications for conclusionsabout recovery from localized events. Unfortunatelylittle work has been done to address the consequencesof large scale land transformation for aquatic ecosys-tems (Allan, 1995). Given the importance of suchtransformations for the structure and functioning ofaquatic ecosystems, the deficiency is a critical one.As Galatowitsch et al. (1999) have demonstrated, it isimportant to look beyond the banks of aquatic systemsand to understand how the qualities of the riparianzone and the entire landscape determine the statusof natural aquatic systems. The consequences andimplications of large scale influences on the manage-ment of aquatic resources clearly poses numerouschallenges. In the context of wetlands management,Galatowitsch et al. (1999) show that some communitybased response metrics are relatively insensitive tospatial scale, while others are not. Chapman (1999)goes further, pointing out that the inevitable inter-action of natural patterns in time and space impliesthat human induced ecosystem changes can only bemeasured as interactions in time and space againsta complex background. Galatowitsch et al. (1999)add case-specific results to the general argument whennoting the need to consider the patterns of inter-annualvariation and the consequent effects of well-definednatural cycles (e.g., wet–dry cycles) for assessingthe significance of chosen recovery metrics. Keller etal. (1999a) similarly note the potential significanceof natural cycles when discussing the implicationsof drought for conclusions concerning the status ofacidified lakes. While community-based metrics holdpromise for assessing the degree and rate of recovery,there is common agreement that those same metricswill need to be validated across a range of spatial andtemporal scales before they can be reliably employedin environmental decision-making situations.

Discussions of recovery have tended to focusat the population, community or ecosystem level.Systems, however, are comprised of a nested seriesof hierarchies, each with its own structural and func-tional properties (Picket et al., 1989). Depledge(1999) argues this implies that recovery proceeds at

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differing rates and extents, depending on the level ofbiological organization being considered. Biomarkersof physiological condition may continue to signalimpairment when higher level measures of abun-dance or presence and absence indicate a degradedsystem has recovered. Compensation mechanismsthat adjust survival rates in response to organismdensity or colonization events can act to mask themost obvious effects of stress at many levels ofbiological organization. Depledge (1999) suggests thatthose same mechanisms can compromise our abil-ities to determine the extent of recovery by presentingconflicting signals as to the recovery status of asystem depending on the level of biological organiza-tion studied. This complexity suggests that no singleapproach to establishing recovery will be suitable andthat a suite of measures will be required to developa complete understanding of ecosystem status in thepost-disturbance period.

The fact that ecological systems are not staticalso complicates the issue of determining the successof remediative action. Comparisons of a recoveringecosystem against degraded, but non-restored sites,non-degraded sites, and measures of before and afterrestorative action are all required to understand theefficacy of management action. The potential influ-ence of watershed history and the cumulative influenceof other stressors on mediating recovery paths andrates must also be considered in study design (Keller etal., 1999a). As a result, temporal measures of recoveryat a single site only indicate that some state change hasoccurred, not that the observed change is attributableto action. While the requirement for multiple compar-isons, more detailed sampling design that controlsfor other possible effects and replication may raisethe costs associated with restorative programmes inthe short-term, the payoff will be increased knowl-edge of action efficacy and an overall improvement inour ability to positively intervene in the environment.In that regard, the review by Chapman (1999), vali-dated by the detailed field studies of Galatowitsch etal. (1999) and Keller et al. (1999a, b) represents animportant step forward in our thinking about recoveryissues.

4. The questions that remain

Two critical points emerge from the studies in thisissue: (1) recovery cannot be defined without refer-ence to the spatial and temporal relations that influ-

ence the endpoint being measured, and (2) better datasets are required to separate the influences of naturalvariation from those induced by a disturbance event.Further research will be required to adequately addresseither issue. Of necessity much of that researcheffort will have to focus on improving our knowl-edge of ecosystem functioning, including: the effect ofdisturbance on the functional dynamics of ecosystemprocesses; the determination of recovery in the contextof natural variability (Chapman, 1999); the implica-tions of associated indirect disturbances (Keller et al.,1999b); and, the way in which the ecological andphysical mechanisms that generate patterns at onespatial and/or temporal scale may be mapped ontothe patterns occurring at other spatial and temporalscales (Levin, 1992; Galatowitsch et al., 1999; Kelleret al., 1999a). For most ecologists, the latter require-ment implies that effective means of extrapolatingthe results of controllable, small scale experimentalstudies to the dynamics of large ecosystem scales mustbe developed.

Furthermore, the meaning of divergent rates ofrecovery at differing levels of biological organiza-tion and the influence of habitat, in its widest sense,must be understood. This latter requirement shouldinclude: an understanding of the physiological toler-ance for disturbance; the consequence of indirecteffects arising from spatial and temporal intercon-nectedness (O’Neill, 1999), and the influence oflandscape- and watershed-level attributes in deter-mining or modifying ecosystem dynamics (Galatow-itsch et al., 1999; Keller et al., 1999a). At thepopulation-level, we must be able to determine whichlife-stages are most sensitive to disturbance and, there-fore, which require most attention when attemptingto manage or remediate disturbed systems. Knowl-edge of population dynamics will also be critical toinsure that management efforts do not trigger compen-satory processes normally designed to insure popula-tion stability. Detailed knowledge of community andpopulation processes will not guarantee a properassessment of recovery if physiological indicators ofstress fail to show recovery at the individual level hasoccurred (Depledge, 1999). In this regard, biomarkersmay serve as potentially useful indicators of thecompleteness of recovery from disturbance.

From a practical point of view, there are clearlydifficulties associated with establishing when we have,or have not, been successful in restoring a damagedsystem to its natural state. This may stem from theway in which the issues of recovery and restoration

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have mixed politics and science. It is now commonfor ecologists to be asked to recommend, design,and implement programs aimed at redressing themost obvious consequences of human action for theenvironment well before they possess the scientificknowledge needed to adequately address and under-stand recovery issues (Minns et al., 1996). Once thepolitical will has been mobilized for action, it hasbeen typically more important to act, than it has beento understand the consequences of action. The pref-erence for action stands in obvious contrast to thescientific study of degradation where, for reasons oflitigation and the need to establish liability, there hasbeen a more focused attempt to quantify the effectsand causes of environmental interventions and theirassociated damage. In that regard, restoration ecologyis still in its infancy and the call for more preci-sion in sampling design, quantification of effects, andunderstanding of ecological mechanisms represents areal challenge to the development of the science as awhole.

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