approximating nature’s variation: selecting and r using...

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Restoration Ecology Vol. 5 No. 4, pp. 338–349

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1997 Society for Ecological Restoration

Approximating Nature’s Variation: Selecting and Using Reference Information in Restoration Ecology

Peter S. White

1

Joan L. Walker

2

Abstract

Restoration ecologists use reference information todefine restoration goals, determine the restoration po-tential of sites, and evaluate the success of restorationefforts. Basic to the selection and use of reference in-formation is the need to understand temporal andspatial variation in nature. This is a challenging task:variation is likely to be scale dependent; ecosystemsvary in complex ways at several spatial and temporalscales; and there is an important interaction betweenspatial and temporal variation. The two most commonforms of reference information are historical datafrom the site to be restored and contemporary datafrom reference sites (sites chosen as good analogs ofthe site to be restored). Among the problems of histor-ical data are unmeasured factors that confound the in-terpretation of historical changes observed. Amongthe problems of individual reference sites is the diffi-culty of finding or proving a close match in all rele-vant ecological dimensions. Approximating and un-derstanding ecological variation will require multiplesources of information. Restoration, by its inherentlyexperimental nature, can further the understanding ofthe distribution, causes, and functions of nature’svariation.

Introduction

eference information is used to define restorationgoals, determine the restoration potential of sites,

and evaluate the success of restoration efforts. Refer-ence information can also contribute to a larger goal—determining the conditions under which restored eco-systems are likely to be self-sustaining and thereforelikely to have low costs of management. Even whenself-sustaining behavior is not possible (e.g., for an areathat is too small for a natural disturbance regime) oreven desirable (e.g., for historic communities that requiremanagement against natural successional change), refer-ence information helps us determine a site-specific setof feasible restoration goals and forecast the need formanagement that will replace or counteract naturalprocesses. In essence, selecting and using reference in-formation requires that we address a fundamental issuein ecology: understanding the nature, cause, and func-tion of variation in ecosystems and landscapes. Hence,the selection and use of reference information is a cen-tral and defining issue for restoration ecology and willprobably play an important role in the development ofthis field.

All reference information is implicitly time- and space–based: that is, it is about a particular place (a referencesite) at a particular time, even if the place and time arebroadly or imprecisely defined, the site is no longer anextant natural area, or the historical conditions nolonger apply. Selecting and using

extant reference sites

isbasic to restoration ecology, but it is only part of thelarger problem of using a wide range of historical andcontemporary information, including information col-lected on the site to be restored (Table 1).

Restoration is carried out for a wide range of pur-poses, including ones that are not centered on restoringnatural processes, but rather on direct human uses suchas improving water quality or supporting harvestablepopulations of fish and game. Although our emphasisin this paper is natural area restoration, the issues weraise are broad ones, because all restoration projects re-quire analysis of the same kinds of information. For ex-ample, restoration for water quality requires prescrip-tions appropriate to geology, climate, terrain, history,human influence, and vegetation—that is, it requiresthe selection and use of reference information.

We begin with an outline of sources of variation inecosystems. We then discuss the values and limitationsof different kinds of reference information and describehow multiple sources of information must be used tounderstand variation in nature. We conclude our dis-cussion with an overview of topics for future researchand application. Although restoration decisions includeeconomic, social, and political criteria (Higgs 1997), weconfine our discussion to ecological issues.

R

1

Department of Biology, Campus Box 3280, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, U.S.A.

2

U.S. Forest Service, 233 Lehotsky Hall, Department of Forest Resources, Clemson University, Clemson, SC 29634, U.S.A.

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Variation in Nature

Why is the selection and use of reference informationdifficult? The simple answer is that nature is variable intime and space. We often must use fragmentary infor-mation about this variation to understand current con-ditions, deduce the potential for restoration, set restora-tion goals, and propose restoration methods. In thissection we expand upon this answer by discussing theeffect of observational scale on our interpretations ofvariation and by outlining sources of temporal and spa-tial variation in ecosystems.

Scale Dependence in Observations of Variation in Nature.

Per-ceptions of ecological variation depend both on the char-acteristics of the variation and on the scale of observa-tion. Observational scale has two components: grain andextent (Fig. 1; Wiens 1989; Allen & Hoekstra 1992). Grainis the unit of resolution for an observation, the contigu-ous area over which one observation is made (e.g., plot,quadrat, or pixel size). Extent is the area over which sep-arate observations are distributed. In sampling an histor-ical record, grain and extent are, respectively, resolution(the time span of the individual sample) and duration(the time span of the set of observations).

Grain and extent affect observations in different ways.For the simplest case—an ecosystem that is relativelyhomogeneous (e.g., an even-aged stand on a site of uni-form topography and substrate)—individual quadratsthat are smaller than the size of dominant organismswill vary despite the relatively homogeneous condition.For example, in a forest sampled with small quadrats,one quadrat may contain a tree base, another the forestfloor. As the grain size of quadrats increases, the quad-rats average across this small-scale variation. Hence,variation among quadrats will likely decrease as grainsize increases.

Extent also influences perceived variation. For anygrain size and number of quadrats, increasing the ex-tent of a sample (that is, distributing the quadrats over alarger area) is likely to increase the range of environ-mental conditions sampled. Quadrats that are farther

apart are less likely to be influenced by spatially corre-lated factors like seed rain. The variation among quad-rats will generally increase with increasing extent.

Many ecosystem parameters are scale dependent. Forexample, Busing and White (1993) showed that the coef-ficients of variation for density and basal area were de-pendent on quadrat size in an old growth Southern Ap-palachian forest. Further, early successional trees hadhigher coefficients of variation across a series of quad-

Table 1.

Types of reference information used to document and infer change in composition (including invasions and extirpations), structure, dynamics, and physical factors.

Reference Information

Current Conditions Historic Records Legacy and Latency

Climate variables Data on composition and structure Fire scarsTopography and hydrology Written and oral history Snags and coarse woody debrisSoil and substrate Historic photos Dendrochronologies and age structureSpatial context Land survey records Pollen, spores, and microfossilsComposition, structure, and dynamics Management and land use records Macrofossils and subfossilsSuccessional trends Fire records Geomorphological features (e.g., meander bends)

Hydrologic records Relict distributionsWeather records

Figure 1. Grain and extent of sample observations affect the number of species observed at a fixed total area sampled (based on findings in Palmer & White (1994). (A) Three grain sizes and three extents. (B) Expected effects of variation in grain and extent on the species–area relation.


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rat sizes (0.01 to 1 ha) than later successional trees, asmight be expected, since they reproduce only in scat-tered recent tree fall gaps. Structure (stand density andbasal area) was less variable at smaller quadrat sizes(variance in these values was stable at 0.3 to 0.4 ha) thancomposition, which still had high variance at the largest(1 ha) grain size. Busing et al. (1993) concluded that pre-vious studies in these old growth forests had overesti-mated biomass because relatively small plots had beenplaced subjectively around patches of large trees and hadavoided gaps. Such subjective placement will bias esti-mates of tree mortality and growth rates as well. Thestrength of correlations between ecosystem attributesand the environment are also scale dependent. In a studyof a 6.5 ha stand, the variables correlated with composi-tion varied with the grain size of the quadrats (Reed etal. 1993).

Scale dependence is also important in conclusions aboutpopulation structure and dynamics. Zedler & Goff (1973)showed that a shade-tolerant tree had a reverse-J, all-aged population structure at relatively small grain sizes,but a shade-intolerant tree attained this stable distribu-tion only at grain sizes large enough to include manyindependent patches of different successional age. Anumber of rare plant species reproduce only at longintervals after disturbance to established adults or onpatches spatially disjunct from adults (Menges & Gawler1986; see discussion in White 1996). Reproduction insuch populations will appear to be absent and age struc-tures skewed if observed at small scales of time andspace.

Species-area data are also strongly scale dependent onthe scale of the observations (Fig. 1; Palmer & White1994). As a result, species-area data are clearly interpret-able only when the influence of sample grain and extentare known. Further, the scaling of species presence (asdepicted by species-area curves) does not tell us aboutthe scaling of the processes that are responsible for thatpresence. A species is counted as present when the firstindividual is encountered, but the presence of individu-als may depend on phenomena at larger scales. In es-sence, species presence can be observed at a smallerscale that the area required for long-term populationpersistence. Different species will have different abso-lute probabilities of persistence for a given amount ofarea or population size. For example, Schoenwald-Cox(1983) examined the increase in population size of threegroups of mammals with increasing preserve size. Us-ing a population size of 1,000 individuals as a predictorof long-term persistence, she found that small herbi-vores required at least 10

3

ha, large herbivores requiredat least 10

5

ha, and large carnivores required at least 10

6

ha. Species were present on preserves that were smallerthan these sizes, but presumably suffer higher risks ofextinction as preserve sizes and population sizes de-

crease; indeed, preserve size is correlated with the num-ber of extirpated mammal species in the western UnitedStates (Newmark 1987).

Conclusions about variation in ecosystems and theprocesses responsible for that variation will change withthe temporal and spatial scale of observation. This isparticularly a problem when events are temporally rareand episodic and spatially patchy, conditions that applyto causes of mortality and reproduction for a variety ofspecies. A tendency to select the oldest patches as refer-ence stands will bias results (leading to higher mean val-ues and reduced variance for parameters like biomass);natural communities can be expected to show an inter-nal patchiness related to the turnover of individuals andlarger disturbance events. The ideal solution is to docu-ment scale dependence directly by sampling at a seriesof scales; failing this, we should acknowledge when con-clusions are potentially limited by the scale of the obser-vations.

Variation in Time.

Temporal variation includes seasonalvariation, interannual variation, and the dynamics pro-duced by disturbance and succession (Fig. 2). Examplesof seasonal changes include shifting dominance in her-baceous plant communities, migrations of animal popu-lations, and variation in the rates of ecosystem processessuch as productivity, nutrient transformations, and de-composition rates. Interannual variation includes ran-dom year-to-year variation, periodic or semi-periodicvariation expressed over several to many years (the South-ern Oscillation; Swetnam & Betancourt 1990), and short-to long–term directional change. Year-to-year variationmay be an important mechanism by which biologicalvariation is maintained, as the species finding optimumconditions for growth and reproduction vary from yearto year (DeAngelis & White 1994; Tilman et al. 1996). Fi-nally, the interplay of disturbance and succession is awell studied source of temporal variation in ecosystems.Reestablishing or simulating disturbance regimes is oneof the most common goals in natural area restoration,particularly with regard to fire (Baker 1994) and riverflow (Dahm et al. 1995).

Data on climate variability can inform restoration de-cisions. The history of climate helps us interpret currentconditions, anticipate future events, and evaluate pro-cesses responsible for ecosystem change. The probabili-ties of disturbances vary with climate (Swetnam & Be-tancourt 1990; Swetnam 1993). Ecosystems may alsopossess characteristics whose origins are explained bypast, not current, environment, and may be on a trajec-tory of successional change that was determined by pastevents. It also will be important to evaluate whether fu-ture climatic variations have historic precedents.

At least in some cases, restoration must address mul-tiple and interacting causes of temporal change. For ex-


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ample, in the Everglades, local composition and struc-ture reflect such factors as climate trends, sea level rise,seasonal precipitation, intense storms, human influenceon water quality and flow, fires of various intensities,and successional processes (White 1994).

Variation in Space.

Ecosystems vary in space because thephysical environment varies along spatial gradients,human and natural disturbances create a mosaic of suc-cessional states, and ecological processes vary with thespatial context. The first two of these have relativelystraightforward consequences for the selection and useof reference information. For example, similarity in en-vironmental conditions is often used to match referencesites with the site to be restored. We consider spatialcontext in more detail.

Spatial context is the relationship of sites, be they refer-ence sites or sites to be restored, to their surroundings.Spatial context includes the nature of the matrix sur-rounding sites, the nature of edges and boundaries, andthe size, distribution, and isolation of the sites themselves.Spatial context can affect physical factors (e.g., edge ef-fects on temperature and humidity) and disturbance re-gimes (e.g., increased rate of treefall along new forestedges). Further, spatial context can directly affect speciescomposition and species-mediated functions, indepen-dent of the effects on environment and disturbance.

Changes to spatial context will often be a constraintin restoration. Many of the ecosystems we seek to re-store will have altered spatial context—among otherchanges, they will often be smaller and more isolatedthan they were historically or in presettlement times.Changes in spatial context have consequences for eco-system composition and process (Turner 1989; Harris &Silva-Lopez 1993; Pickett & Parker 1994; White 1996)and for the restoration potential of sites (Aronson & LeFloc’h 1996). Noss & Harris (1986) argue for restorationof site connectedness through protection of corridors.

A species may be absent from an isolated site not be-cause it cannot compete on the site but because it has notyet dispersed to the site or, stated more generally, be-cause its rate of dispersal to the site is less than its rate ofextinction after it arrives on the site. Likewise, a speciesmay be present on a site not because it is a good compet-itor or reproduces there, but because a high rate of dis-persal to the site from nearby populations compensatesfor high mortality or low competitive ability. This is themass effect or the source-sink dynamics of metapopula-tions (Shmida & Wilson 1985; Hanski & Gilpin 1991;White 1996).

The size, isolation, and surroundings of sites can haveboth deterministic and stochastic influences on speciespresence (Bell et al. 1997; Ehrenfeld & Toth 1997). Deter-ministic variation results from differences among spe-cies in extinction and dispersal rates. If some species arearea-sensitive (prone to extinction on small sites becausethey occur in sparse populations or have low reproduc-tive outputs), their loss will be predictable from the sizeof the site. If some species have poor dispersal, they willbe absent from isolated sites; their presence will be pre-dictable from site isolation. The result of such variationin extinction and dispersal rates will be that species listswill be hierarchically nested. That is, the species lists ofsmall and isolated areas will be predictable subsets ofthe species list of larger and less isolated areas. The lossof area-sensitive species after habitat fragmentation is anexample of this deterministic effect. The importance ofsite area and isolation in restoration will be greatest foranimals dependent on large home ranges and seasonalmigrations. The most obvious example is the loss ofarea-sensitive predators, with resulting increases in her-

Figure 2. Temporal variation in a two-dimensional ordination or similarity space based on community structure and compo-sition (after Walker & Boyer 1993). Temporal variation in eco-systems includes seasonal variation, interannual variation, and the dynamics caused by disturbance and succession. Hu-man disturbance can displace systems within the bounds of the variation or outside these bounds—to points (B), (C), or (D). Disturbed states (B), (C), and (D) may have their own tra-jectories if left alone, and they may move toward the envelope or away from it. Restoration can then be defined as the at-tempt to move the composition, structure, or process back to-ward the envelope of natural variation (Walker & Boyer 1993). These envelopes of variation represent hypotheses, rather than facts demonstrated for any particular ecosystem. Even if real, the envelopes would likely change shape through time. Reference sites selected to represent locations (A1), (A2), and so on would also show variation due to sampling artifacts, dif-ferences in environment, history, and biotic interactions among reference sites, and stochastic factors.


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bivores and grazing impacts to plant communities.However, spatial context can also influence species withother important ecosystem roles, such as pollinators,seed dispersers, mycorrhizal fungi, pathogens, and her-bivores.

Variation in species presence can also be stochastic,leading to non-nested species lists. For example, thesimplest form of the theory of island biogeography pre-dicts that species richness will be correlated with islandsize and isolation, but that species composition willshow continuous turnover (MacArthur & Wilson 1967).Composition at any one time will be an unpredictablesubset of the species pool. Small and isolated areas willhave a subset of the species pool, but the subset presentwill differ among sites at any particular time of obser-vation. Non-nested species lists can be caused by mech-anisms other than those proposed by island biogeogra-phy. For example, if a habitat becomes fragmented,random extinctions in each fragment would producenon-nested species lists.

The nestedness of species lists is critical to how resto-ration provides for overall species richness (Patterson1987). If species lists among a series of restored sites arenested, the largest area contains the species of all othersites. A sufficiently large restored area may contain allpossible species. On the other hand, if species lists arenot nested, only a collection of separate sites will con-tain the full species pool. Managers can potentially con-trol the overlap of species lists and the movement ofspecies among sites to support the species richness of acollection of small restored areas.

A Paradigm for Regional Spatial Variation: the Distance Decay of

Similarity.

Geographic variation results from climaticgradients, disturbance history, the biogeography of spe-cies, and spatial context. This spatial correlation amongbiotic, environmental, and historical factors produces ageneral expectation termed the “distance decay” of sim-ilarity or the “first law of geography” (Tobler 1970), theproposition that the similarity between any two placeswill decrease or decay with the distance between them.This means that, at some level, nature is everywhereunique and that the value of reference sites varies di-rectly with distance to the restored area. Regional varia-tion suggests that no one reference site is ever a perfectmatch for a site to be restored; rather, our conceptualmodel should be one of interpolation among multiplesites and sources of information. Pickett and Parker(1994) make an analogous claim for temporal variation:ecosystems are likely to have unique histories, so thatno one reference site observed at an arbitrary timeshould be used to determine goals for a restorationproject. The distance decay of similarity among intactnatural areas is likely to be more rapid for composi-tional similarity than for structural similarity, and more

rapid for infrequent and rare species than for commonand dominant ones.

Relations between Temporal and Spatial Variation.

Variation inspace and time is not independent, as our discussionhas already implied. For example, the seasonal move-ment of animals implies a place to move to and returnfrom and a matrix that permits this movement (seeGardner et al. 1989 for a quantitative treatment of thisproblem). Interannual variation that causes shifts ofpopulations along gradients implies that an adequateamount of gradient space is available to accommodatethese shifts (e.g., the shifting prairie mosaic of Cottam1987; Fig. 3). Mass effects on local composition and thedynamics of metapopulations also imply a dependenceof temporal dynamics on spatial variation. Disturbancemay create a shifting mosaic of successional states—and thus a situation in which a temporal source of vari-ation creates a dynamic spatial pattern. In turn, the spa-tial pattern provides conditions for both early and latesuccessional species and, hence, influences temporaldynamics (Pickett & Thompson 1978). The role of spa-tial variation in providing for response to temporalchange suggests that some ecosystem functions are de-pendent on large spatial scales. Spatial extent and con-nectedness are sometimes the explicit focus of conser-vation and restoration (Noss & Harris 1986).

The interaction of spatial and temporal variation hasbeen addressed in studies of disturbance at landscapescales. Disturbance can produce a dynamic equilibriumor shifting mosaic of patch states. Factors that increasethe likelihood of achieving equilibrium are small patchsize relative to landscape size, disturbance return timeslonger than recovery times, probabilities of disturbancebeing independent in space, and a feedback betweenpatch state and the probability of disturbance (Shugart1984; White & Pickett 1985).

Turner et al. (1993) examined equilibrium, stability,and variance as functions of two ratios: the ratio be-tween the area disturbed in a disturbance event andlandscape extent, and the ratio between disturbance in-terval and recovery time (Fig. 4). Equilibrium is definedas a constant proportion of the landscape in varioussuccessional states, although the location of patches ofvarious successional age shifts through time (Fig. 5).Stability is defined as the continued presence of all suc-cessional states, although the proportion of each mayfluctuate greatly (high variance landscapes) or hardly atall (low variance landscapes). Turner et al. (1993) sug-gest that managing high variance landscapes and dise-quilibrium landscapes will be difficult; this argumentalso applies to the restoration of natural disturbance re-gimes in such landscapes.

Reference information has been used to define tem-poral and spatial variation as a basis for ecosystem


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management (Landres 1992; Swetnam 1993; Morgan etal. 1994; Wright et al. 1995; Stephenson 1996). One se-ries of approaches seeks to describe the extremes andbounds of ecological variation. The “natural range ofvariation” in its purest form is the range of variation inthe absence of human influence. The “historical rangeof variation” is a phrase that avoids the connotations of“natural,” given the important but often undocumentedinfluence of Native Americans on some sites. The his-torical range of variation is the range of variation over aperiod of record, ideally encompassing multiple gener-ations of dominant plants, a time span that would alsoencompass much of the relevant variation in animalpopulations and physical factors. “Ecological variation”explicitly encompasses both spatial and temporal varia-tion. Finally, “reference variation” is the variation de-fined through reference sites and other sources of refer-ence information. Aronson et al. (1995) term reference

variation the “ecosystem of reference”; this “ecosys-tem” is an abstraction and generalization of informa-tion from multiple sources. Aronson and co-workershave presented operational definitions for vital ecosys-tem attributes (Aronson et al. 1993) and vital landscapeattributes (Aronson & Le Floc’h 1996) that they proposeas key variables to assess with reference information atthese two scales.

Defining bounded variation recognizes that ecosys-tems are neither static nor spatially homogeneous. It al-lows us to ask whether particular ecosystem states havea precedent and whether current trajectories and resto-ration methods are leading the ecosystems toward therange of historical variation. However, it cannot be as-sumed that ecosystems had well-defined bounds ofvariation, nor that such bounds are stable through time.In the best cases, variation would have recognizablebounds on time scales of decades or centuries to several

Figure 3. Prairie community shifts on the University of Wisconsin Arboretum’s re-stored prairies. Much of the change was attributed to cli-mate variation (Cottam 1987).


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millennia and on spatial scales of hundreds to thou-sands of hectares. In the worst cases, no such bounds ofvariation are recognizable: the bounds of variation sim-ply increase continuously as we expand the temporal orspatial scale of observation (Fig. 5).

Discussion: Approximating Ecological Variation

The Values and Limitations of the Sources of Reference Informa-

tion.

The place- and time–based nature of reference in-formation allows us to classify reference informationbased on closeness in space and time to the site to be re-stored (Table 2). These categories can be used to de-scribe four broad kinds of reference information: con-temporary information from the site to be restored(same place, same time), historical information from thesite to be restored (same place, different time), contem-porary information from reference sites (different place,same time), and historical information from referencesites (different place, different time).

Contemporary information from the site to be restored (sameplace, same time).

The value of contemporary on-site in-formation is that the problem of reference site match ismoot and we can collect direct evidence on trends (suc-cession, population age, and size structure), change inprocess (relict fire dependent species, absence of repro-

duction), change in components (absent species, exoticspecies invasions), and process legacies (meander bendsin channelized rivers). Contemporary data give us a di-rect picture of current conditions, like the physical andchemical properties of soils, hydrology, topography, mi-crobial populations, species composition, and succes-sional status, thereby suggesting methods for restora-tion, as well as allowing us to conjecture about past andfuture states. The limitation of contemporary on-site in-formation is that snapshot views of ecosystem processcan be misleading; we need long-term data to give con-text to the “invisible present” (Magnuson et al. 1991).Ecosystem processes have nonstationary rates, and re-sponses often are nonlinear, involve time lags, or are in-direct (the response of some species is mediated by theresponse of others). Also, human impacts may have ob-scured the very variables that require restoration—thereis a danger of using a site to be restored as the only refer-ence for its own restoration. We often lack models to ex-trapolate current conditions backward or forward intime.

Figure 4. Landscape equilibrium and stability as a function of two ratios, disturbed area/landscape area and disturbance in-terval/recovery time (Turner et al. 1993). Equilibrium land-scapes are stable and have constant proportions of the land-scape in various successional states (they have no variance). Stable landscapes can range from low to high variance (all successional states persist, but the proportion of the landscape each occupies varies through time).

Figure 5. The range of variation in ecosystem parameters as a function of spatial and temporal scale. (A) The structure of a community varies widely at the patch scale, as a function of disturbance and succession. If many independent patches are averaged across a landscape, structural attributes have a sta-ble mean. (B) Variation in temperature at several temporal scales. The historic range of variation depends on the time scale of the observations.


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Historical data from the site to be restored (same place, differ-ent time).

The value of historical data from the site to berestored is, again, that the question of site match ismoot and we can discover direct evidence for changesthat mandate restoration. The limitations of historicaldata include a record of insufficient length or resolu-tion, poor spatial resolution, biases in the historicalrecord (e.g., the differential production and preserva-tion of pollen), unmeasured but correlated changes inthe environment, and complex responses to past envi-ronmental change. Understanding the causes of tempo-ral variation can be difficult because of spurious corre-lations, inertia, time lags, and non-linear responses.Between the period of historical record and the present,environmental conditions may have changed in un-known ways; our conclusions may not apply to currentconditions. Different species (e.g., trees versus herba-ceous plants) may respond at different rates to the samephysical change (e.g., climate change or disturbance).Historical phenomena can depend in unknown wayson spatial context. For example, historical fire fre-quency may reflect fires that ignited in areas adjacent tothe study area, rather than fires originating within it.

Historical data are often ambiguous on a key point:our ability to directly associate physical environmentalfactors and disturbance regimes with ecosystem struc-ture and function. The farther back in time we go, themore problematic this ambiguity becomes. Understand-ing the “rules” by which the past state becomes thepresent state would allow us to extrapolate trends frompast to predicted current state. In this sense, historicaldata can represent important reference points, eventhough they cannot be accepted as descriptions of resto-ration goals for contemporary environments (Falk 1990).

Contemporary information from reference sites (differentplace, same time).

The value of contemporary reference

sites is that they provide direct evidence of how mea-sured processes affect composition, structure, and dy-namics under current environmental conditions—wedo not have to worry about unknown environmentalconditions. Further, if the natural areas selected for ref-erence sites are extant, we can continue to collect infor-mation, test new hypotheses, and use the sites for con-trolled experiments. Potential limitations of referencesites derive from all aspects of spatial variation in eco-systems (Table 3). Reference sites may represent rem-nants of natural habitat and thus may be small in size.Thus, the reference site may represent only a sample ofthe original spatial and temporal variation present. Afragmentary reference site may already have been com-promised by species loss or edge effects. Reference sitesmay be set in an altered spatial context so that some ofthe ecosystem characteristics reflect either altered pro-cesses or are a relict of previous conditions (e.g., popu-lations of herbivores increase because of surroundingland use). Conversely, reference sites with an intact spa-tial context may have conditions that will never beachievable for a site whose context cannot be restoredas part of the project. Reference sites may be at a largespatial distance from the site to be restored, may be dif-ferent in environmental conditions (surviving sites maybe less productive or accessible than sites to be re-stored), and may reflect ecosystem inertia (i.e., ecosys-tem characteristics do not reflect the current environ-mental conditions). Current ecosystem conditions mayreflect historic but undocumented rare events.

A related use of reference sites is space-for-time sub-stitution, in which chronosequences of stands are as-sembled to infer historical variation and long-term eco-system dynamics (Pickett 1989). While this has valueand may be the only means to infer temporal dynamics,

Table 2.

A short synopsis of the values and limitations of reference information for four sources of data defined by closeness in space and time to the site to be restored.

Closeness in Space

Closeness in Time Same Place Different Place

Same Time Climate equivalency mootUnknown historical effects

Indirect evidence for past statesSite equivalency

mootSite not equivalent; all sites

unique environmentally or historically

Different Time Unknown past climates and historic effectsDirect evidence of past states

Site equivalency moot

Site not equivalent; all sites unique environmentally or historically

Table 3.

Typical limitations of reference information from reference sites.

Limitations of Reference Sites

Small size, unknown scale dependence, partial sample of spatial and temporal variation

Changed spatial contextSpatial distance from the site to be restoredBias of remnant natural areas to less productive or accessible

sitesEnvironmental distance from the site to be restoredEcosystem inertia: lack of correspondence of composition and

structure with current environmental conditionsUndocumented environmental factorsUndocumented rare eventsThe asymmetry of information:

Presences tell us that a species can tolerate the conditions but not how well it is doing

Absences don’t distinguish between a failure to disperse to the site and an inability to tolerate the site


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it does suffer from the limitation that currently ob-served rates and processes may differ from the unob-servable ones of the past. Further, this application hasthe same problem we have just discussed: non-equiva-lency of the sites in the chronosequence.

Historical data from reference sites (different time, differentplace).

The value of historical data from reference sites isthat they provide a direct picture of past states, variabil-ity, and human impacts. The limitations are potentiallymore severe than those for historical data from the siteto be restored, since both temporal and spatial uncer-tainties apply.

Interpolating and Extrapolating Nature’s Variation.

The selec-tion of reference information often begins with thesearch for sites and periods of time that are a closematch with the conditions we seek to restore. We might,for example, seek reference information from sites thatare in all ways identical to the site to be restored, exceptfor the elements or processes that require restoration.The reference information would tell us about bothwhat the ecosystem should be like and what should berestored. This matching (to establish comparability) andsubtraction (to establish the factors that require restora-tion) is perhaps the most obvious approach to selectingand using reference information.

The value of reference sites used in this way will varydirectly with the closeness of the match and the com-pleteness of our understanding of the factors that causevariation. Ideally, reference sites would be close in envi-ronmental conditions and geographical position andhave documented disturbance history, known and min-imal, of human influence, and known and minimalfragmentation effects. The problem of understandinghistorical environments suggests that the closer in timereference data are to the present and the more recentlythat a site diverged (for whatever reason) from refer-ence conditions, the more apt we are to be able to inter-pret the implications of reference site data.

While this “match and subtraction” approach for us-ing reference information is attractive, it has limits. Allreference sites may differ in some significant ways fromthe site to be restored, all reference sites may have beenaltered, or historical data may be absent. Further, thesite to be restored could represent unique or novel con-ditions; the potential reference sites may have never ex-isted. Some reference conditions, while they give us in-sight into ideal conditions, cannot be directly applied inrestoration (e.g., the pristine reference area is large enoughto support area-sensitive species and natural patch dy-namics, but the area to be restored is small). Finally, atleast at some scales, nature is made up of unique placeswith unique histories (Pickett & Parker 1994), so that noone reference site should be expected to be an ideal

match with a site to be restored. In sum, spatial datahave the problem of uncertainty about site match, andhistorical data have the problem of uncertainty abouttemporally correlated change in unmeasured variables.

The problem of identifying matching, undisturbedsites reinforces the need for an alternative approach: theuse of multiple sources of information from sites andtimes that have both similarities and differences withthe site to be restored. Multiple sources of reference in-formation can be used to produce a description of eco-logical variation. This is a broader and more importantgoal than selecting a single reference site as a restora-tion target, since it will give a spatial and temporal con-text to the restoration project and allow us to determinewhat part of that variation is to be restored. Achievingthe ideal condition of high similarity between referenceand restoration sites is a special case of the more gen-eral problem, the analysis of all similarities and differ-ences.

Recognizing the multivariate nature of selecting andusing reference information expands the potential in-formation sources. Reference information need not befrom identical sites; its use can be interpreted as a func-tion of similarity to the site to be restored. In general,few sites will represent an ideal match to the site to berestored, and many more than stand at some distancefrom that site. The value of such sites is a function oftheir spatial, historical, and environmental distancefrom the site to be restored: the lower the distance andthe more we can understand this distance, the morevaluable the information will be.

Restoring nature suggests an image of restoring atapestry that has developed holes and worn spots. Theexistence of the holes is what compels us to do restora-tion, but the same holes make our task difficult. Thesurviving parts of the tapestry may represent a biasedsubset of the original pattern (e.g., old growth forestsmay survive only on the least productive sites in a land-scape), some of the functional attributes of the tapestrymay have been provided by the unbroken nature of thecloth, and to some degree each spot on the tapestry mayhave been unique rather than an element repeated else-where in the design. Of course, nature, unlike a tapes-try, also continues to evolve through time: even withouthuman-imposed changes, nature does not remain static.This image and our discussion of the values and limita-tions of reference information suggest that the processof using reference information is one of interpolationand extrapolation using multiple sources of informa-tion. Our challenge is to combine insights from data setsthat are individually incomplete and to form hypothe-ses about how ecosystems can be restored. Restorationcan, in fact, help us achieve a better understanding ofecosystems because it is inherently experimental (Dia-mond 1987).


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Summary: Research Questions for the Selection and Use of Reference Information

The selection and use of reference information is a chal-lenging, but fundamental, task in restoration ecology.Only research and additional practical experience willhelp us meet this challenge. In this section, we outlinefive research areas that will advance the practice of res-toration: ecological variation at multiple scales; modelsand tests for integrating diverse sources of reference in-formation; sensitivity of restoration to variation in ref-erence information; feasible, site-specific restorationgoals; and ecological variation, diversity, and resilience.

Ecological Variation and Multiple Scales.

Using reference in-formation requires that we address the patterns andcauses of ecological variation at multiple scales (Michener1997). Long-term data give context to present observa-tions (Magnuson et al. 1991). We need additional workon climate variation, including ties between climate anddisturbance regimes. We need to examine the nature ofhistoric variation and the usefulness of the range ofvariation approach to determining restoration goals.We need to further document the influence of NativeAmerican populations. We need to further assess the in-fluence of spatial context on species with important eco-logical functions and be able to assess when an alteredspatial context limits restoration.

Models and Tests for Integrating Diverse Sources of Informa-

tion.

The use of multiple sources of reference informa-tion involves building a model, at least conceptual andsometimes quantitative, of temporal and spatial varia-tion. Yates & Hobbs (1997) provide an example of aquantitative model defining a series of ecosystem statesand rates of transitions between these states (degrada-tive in one direction and restorative in the other). Weneed continued development and tests of such models.Because this is usually done informally, we need tolearn to more carefully document how we determinerestoration goals from multiple sources of information.We need to learn how to link historical information andcurrent conditions, determining the rules by which thepast became the present and the present will lead to arange of possible future states.

Sensitivity of Restoration to Variation in Reference Informa-

tion.

Given variation in nature, we can ask: how pre-cise does a restoration prescription have to be? Whencan we determine that a site is in fact restored because iteither fits within a range of ecological variation or is ona trajectory that will allow it to develop toward thatrange of variation? What are the most meaningful kindsof data and ecosystem attributes and processes thatmake the most difference in successful restoration?

How does the cost of restoration alternatives affect ben-efits—the degree of approach to restoration goals?

Some ecosystem characteristics are likely to be rela-tively easy to predict with reference information, whileothers are more difficult. Among the former are domi-nant species, species presences (versus abundances),and successional pathways (versus the amount andspatial distribution of patches). Among the most diffi-cult will be rare species, rare and extreme events, sto-chastic events and processes, interannual variation, andfragmentation effects. We may have to be very precisewhen we want natural disturbance regimes to prevailunassisted by management and when we manage rarespecies, species with sporadic or episodic reproduction,and species with narrow ecological tolerance. On theother hand, patterns of dominants and persistence at re-gional scales may not require as much precision.

Feasible, Site-Specific Restoration Goals.

Reference informa-tion can be used to determine the potential of a site forvarious restoration goals. For example, an altered spa-tial context can be a constraint in restoration. On smalland isolated sites of an ecosystem type that was oncecontinuous and extensive, only a subset of restorationgoals is feasible. How do we establish feasible, site-spe-cific restoration goals, when restoration of natural pro-cesses or restoration to an original ecosystem is impos-sible? For example, restoration goals can be nested: asmall patch of remnant prairie can be restored andmanaged for wildflower diversity even though naturalfire and buffalo are absent. At the other extreme, largeexpanses of prairie could be restored in such a way thatthese factors were given free reign.

Feasible restoration goals also can include getting anecosystem into a condition from which it will developtoward a longer-term goal (versus putting it in that con-dition through immediate restoration). Feasible goalscan include getting a site off a human-induced trajec-tory (i.e., preventing further loss), rather than restora-tion toward an original condition.

Ecological Variation, Diversity, and Resilience.

Because resto-ration often seeks to undo the last several centuries ofhuman influence, restoration ecologists often focus onthe past. However, this focus obscures a goal that ismore important than simply recreating past conditions:the restoration of ecosystems that will be self-sustainingand resilient (Pavlik 1996). Resilience can be defined asthe persistence of species and community variation de-spite fluctuation in abundance and shifts in location(DeAngelis & White 1994). Self-sustaining describes astate in which natural processes, without the aid of hu-man management, maintain the desired dynamic state.

Nature’s resilience may be a function of its spatialand temporal variation (Tilman et al. 1996). We need to


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know what the roles of short-term temporal variationand small-scale spatial variation are in maintaining di-versity and whether diversity, in turn, generally sup-ports resilience. We need to know how much variationis enough, given likely environmental change, and howclose we have to be—that is, how quantitatively (versusqualitatively) we have to characterize and restore thisvariation. These questions are central to restoration andto our understanding of nature itself.

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