This file was created by scanning the printed publication. Errors identified by the software have been corrected; however, some errors may remain. Wildl. Soc. Bull. 13:121-130, 1985
EVALUATINGPOPULATION-HABITAT MODELS USING ECOLOGICALTHEORY
CURTIS H. FLATHER, U.S. Department of Agriculture,Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO 80526
THOMAS W. HOEKSTRA, U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO 80526
Passage of the Forestand Rangeland Re- CRITERIA FOR SELECTION newableResources Planning Act (P.L. 93-378) Populationmodels can be classifiedas either (RPA), as amended by the National Forest energy-flowmodels, population-parameter ManagementAct (P.L. 94-588), requiresthe models, or habitat-evaluationmodels. We U.S.D.A., ForestService (FS) to develop and analyzed these3 approacheswith respectto conductperiodic national assessments of re- theirpotential for meeting assessment goals. newable natural resources on forestsand Energy-flowmodels are restrictivebecause rangelands.Such assessmentsreport the cur- the data requirementsand knowledgeneces- rentand expectedstatus of naturalresources, sary to constructthem are not available for and proposealternative opportunities with as- most wildlifespecies. Population-parameter sociatedecological, economic, and social im- modelscurrently are limitedbecause data are pacts (Hoekstraet al. 1979). difficultto obtainand applicationsdo not ad- The appraisalsof wildliferesources require dress populationresponse to land manage- theability to forecastconsequences of human- ment actions.Habitat evaluations,however, induced environmentalchanges accurately, attemptto establisha directlink betweena relativeto bothnational and forest-levelman- populationand the habitatto be altered.In agement planning.Models relatingwildlife addition,existing habitat data bases will sup- populationsto habitathave been developed. portregional analyses. Thus, we chosehabitat- The FS must develop, modify,and recom- based modelingas a startingpoint for research mend assessmentmethods for wildlife,and on techniquesfor national assessments. needs a basis forevaluating these methods. A We then rated specifichabitat-evaluation synthesisof existingecological knowledge and modelsbased on objectivityand cost of data, theoryinto a frameworkfor evaluating these abilityto directlyestimate population levels modelscan functionas thatbasis. ratherthan habitat quality, and capabilityto In termsof FS assessmentgoals, a synthesis predictchanges in wildlifepopulations from should expedientlyidentify ecological weak- alternativeland-management activities. In ad- nessesand limitationsin modelsand provide ditionto PATREC, some of the othermodels a mechanismfor proposing recommendations considered (Hawkes et al. 1983) includedthose and researchhypotheses. Accordingly, this pa- developedby Willis(1975), Hawes and Hud- per reviewsand organizesecological theory son (1976), Boyce (1977), U.S. ArmyCorps of relevantto predictingchanges in wildlifepop- Engineers(1980), and U.S. Departmentof the ulations(see Flather1982), and illustratesthe Interior(1980b). PATREC best met the cri- utilityof thisframework in a case exampleby teriaand warrantedfurther consideration in evaluatingthe PatternRecognition Method termsof ecologicaltheory. (PATREC) (Williamset al. 1977). Specifically, PATTERN RECOGNITIONAND PATREC we definereasons for selecting PATREC, de- scribethe method,review ecological theory, Patternrecognition generally refers to a and evaluatePATREC's use. processwith the objectiveof assigningobser- 122 Wildl. Soc. Bull. 13(2) 1985
CONSTRUCT SPECIES constructingindividual species models by de- MODELS 1) Determineclassification termining: categories 2) Determinehabitat attributes 1. The population-levelclasses based on user 3) Determinequantitative objectives. the relationshipsbetween (Is userinterested in pre- habitatattributes and dictingpresence/absence, or relative pop- MODEL classification categories DEVELOPMENT ulationlevels?) 2. A listof habitatattributes believed to be importantin differentiatingthe popula- tion-levelclasses chosen.
INDIVIDUAL SPECIES 3. Thequantitative relationship between hab- MODEL MODELS itatattributes and population-levelclasses APPLICATION (interpretedas a frequencyof occurrence ofeach habitatattribute within each pop- HABITAT INVENTORY PROBABILITY ulationclass). OF AREA STATEMENT Points2 and 3 are accomplishedthrough ex- HISTORICAL WEIGHTED POPULATION pertopinion, literature search, or empirical VERAGE TREND DATA investigation.Application involves the collec- tionof habitat data, which are compared with
LONG-TERM DENSITY theinformation in the species model to make POTENTIAL a probabilitystatement about the ability of an areato supporta population.Population esti- Fig. 1. Diagramaticrepresentation of the PATREC matesare desirablefor process. nationalassessments; PATRECcan providesuch estimates by cal- culatingan expectedvalue (Spurr and Bonini 1973).Historical population trends are used to vationsto classesbased upon a set of common estimatethe average abundance characteristic attributes(Tou and Gonzalez 1974). PATREC ofeach population-level class. These values are is only 1 methodthat could be used in the multipliedby their associated probabilities and assignmentprocess. Application has focused summedto estimate the long-term density po- on classifyinglandscape patternsas wildlife tential(Kling 1980). habitat by examining relationshipsamong PATRECprovides a probability that an area population-levelclasses and habitatcharacter- can supportuser-defined population classes, istics(Williams et al. 1977, Seitz et al. 1982). whichcan be convertedto a long-termpop- Each class has a nonexclusivebut character- ulationaverage for comparisons among areas. isticset of habitatattributes that define a pat- A morecomprehensive review of PATREC tern.The attributescan be used to categorize can be foundin Williamset al. (1977) and additional unclassifiedunits. PATREC uses Kling(1980). Bayesianstatistical inference (an alternativeto classicalstatistical inference), which employs ECOLOGICALTHEORY IN bothobjective data fromsamples and the sci- EVALUATIONS entist'ssubjective judgment (Spurr and Bonini The ConceptualModel 1973) to categorizepatterns. The PATREC classificationprocess com- Theoryprovides a logicalframework for prises2 steps:model developmentand model analyzingproblems and improvingexisting application (Fig. 1). Development involves assessmenttechniques. Techniques for nation- ECOLOGICAL THEORY IN APPLIED MODELS * Flatherand Hoekstra 123
/~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/ I Succession | , I II ,' - I I S Species-Habitat - Interspecific A 1. Relationships Interactions I Habitat Space Niche Theory Competition and SelectionCoptin
Ilk > /DISTRIBUTION
Territoriality ABUNDANCE OF Oter
' CarryingCap.
~~~Pouato Growth__ Density Density - Direct relationshipto distribution _Depend. Independ. w and abundance Factors Factors tndirectI relationship to distribution and abundance thruspecified channel
Fig. 2. Conceptualmodel relating distribution and abundanceto areasof ecologicaltheory. al wildlifeassessments must be able to with- spatialdistribution of a species,and is the standcritical evaluation based on ecological productof thebehavioral process of habitat theory;however, ecologists disagree which selection.Habitat selection principles assume theoriessupport evaluations of thistype. For thatit is adaptivefor an animalto selecta thisreason, the framework that we proposeis specificsite over another. Theoretically, nat- tentative.Our hypothesizedmodel depicts 5 uralselection favors those individuals that se- interrelatedareas of ecological thought lectbetter habitats, resulting in a correlation deemedimportant in evaluationsof habitat- betweenpreference for a givenpatch type and basedpopulation models (Fig. 2). fitnesswithin it (Pianka 1974:104).Conse- Species-HabitatRelationships.-The spe- quently,density decreases from areas of more cificareas of ecological theory that support the suitablehabitat to areas of less suitable habitat conceptof species-habitatrelationships in- (Andrewarthaand Birch1954, Wynne-Ed- cludehabitat space and selection,island bio- wards1962). Although this pattern appears to geography,territoriality, and carryingcapac- holdin general(Partridge 1978), the relation- ity. In addition,the principleof carryingship between density and habitatsuitability capacitymust be consideredtogether with life shouldbe examinedcarefully. VanHorne historystrategies, including the concept of r- (1983) suggestedconsideration be givento vs.K-selection (MacArthur and Wilson1967). seasonof criticalhabitat use (e.g., winter Habitatspace and habitatselection, al- range),time lags, and intraspecificinterac- thoughdifferent concepts, are inseparablein tionsthat temporarily may resultin higher our conceptualframework. Habitat space is densitiesin lowerquality habitat as subdom- describedempirically by thosestructural inantsare forcedout of optimal habitat. characteristicsofa landarea that relate to the Islandbiogeography also has implications to 124 Wildl.Soc. Bull. 13(2) 1985
species-habitatrelationships. This theoryfo- In contrast,populations of K-selectedor- cuses primarilyon communitydynamics and ganismsoccur at or near carryingcapacity. the influenceof island size, shape, and prox- Populationsize tendsto be constantover time imityon species richness.Application to na- and less influencedby density-independent turereserve design has been fraughtwith con- mortalityfactors (Pianka 1970). Selectionhas troversyover the appropriate strategy (a single favoredmore efficientuse of resources,high largereserve vs. severalsmall reserves) for the competitiveability, and lower reproductive preservationof species(Diamond 1975b,Sim- rates(Pianka 1970,Horn 1978). These r vs. K berloffand Abele 1976, 1982,Gilpin and Dia- comparisonsrepresent the extremesof this mond 1980,Kindlmann 1983). Notwithstand- continuum. ing thiscontroversy, island biogeography has PopulationGrowth.-Population growth is applicabilityto themanagement of individual a second major area of ecological theoryin- species. Diamond (1975b), Fritz (1979), and volvingintrinsic factors that regulateabun- Samson(1980) have used principlesof island dance. The logisticequation is a commonly biogeographyto determineminimum area re- cited mathematicalexpression of restricted quirementsfor individualpopulations. Such growth,and is thebasis upon whichmany so- investigationsindicate that the size and distri- phisticatedmodels have been built. Popula- butionof habitatpatches must be considered tiongrowth is speciesspecific for a particular when explainingthe distributionand abun- environment(Johnson 1977) and is perceived dance of species. as a productof 2 opposingforces: the biotic Otherareas of ecologicaltheory relevant to potentialof the species and density-dependent species-habitatrelationships include territori- or independentenvironmental limitations (El- ality,carrying capacity, and r- and K-selec- sethand Baumgardner1981). tion.Territoriality is a complexof behavioral InterspecificInteractions.-Habitat analy- mechanisms,part of whichfunction to mini- ses rarelyconsider interspecific interactions. mize overexploitationof resourcesby permit- The influencesof theseinteractions on animal tingsome individualsto have a sufficientre- distributionand abundanceare sometimesev- sourcebase to surviveand reproduce.Density ident (Abramskyet al. 1979, Williams and dependenceassociated with territorial behav- Batzli 1979a, b), yet at othertimes appear to ior is logicallylinked to carryingcapacity, a be nonexistent(Rotenberry and Wiens 1980). broaderconcept of populationlimits in any In addition,the actual effect can be direct(in- given habitat. Mathematically,carrying ca- terferencecompetition or consumptionof pacityis definedby theupper population lim- prey) or indirect(altering species-habitat re- itwhere the growth rate is equal to zero.How- lationships).Consequently, interspecific inter- ever, biological interpretationis complex actionsare difficultto representaccurately in because of confusingterminology and use a habitatmodel. (Giles 1978), and confoundingconcepts such Niche Theory.-Niche is describedby the as r- and K-selection. range of all physicaland biologicalvariables Species whichare r-selectedhave high re- that,in combination,permit a speciesto exist productiverates, reduced competitive ability (Pianka 1981). Hutchinson(1957) viewed a (Pianka 1970, Horn 1978), and rarelyreach niche as an abstractspace definedby many an equilibriumdensity. Populations usually are dimensions,with each dimensioncorrespond- belowcarrying capacity (Krebs 1978), but can ing to some requisitefor the species. overshootthe resources(Elseth and Baum- Niche theoryis depicted in Fig. 2 as a gardner1981). Populationsof r-selectedor- "bridge" between species-habitatrelation- ganismstend to be regulatedmore by density- shipsand interspecificinteractions. This rela- independentmortality factors (Pianka 1970). tionshipis a manifestationof the2 conceptual ECOLOGICAL THEORY IN APPLIED MODELS * Flatherand Hoekstra 125 componentsof a niche-the fundamental nicheand realizedniche (Hutchinson 1957). Theformer considers the animal-environment interactionsin isolation;the latterconsiders user definedpopulation theactual amount of resourcespace used by High classificationboundary an organismas restrictedby an interactingo Low community.Theoretically, knowledge of both /I I\ is requiredto predict distributional and abun- v I I dancechanges resulting from community dis- turbance. A Succession.-Successionrelates to the dy- ENVIRONMENTALGRADIENT namicnature of the biotic community rather Fig. 3. Hypotheticalrepresentation of an environ- thandirectly to the abundance or distribution mental gradient of a habitatvariable in PATREC. of populations.The theoreticaldevelopment and traditionalarguments concerning the againstestablished standards (Suchman 1967: mechanismsofsuccession are important toour 37). The standardwe use is ecologicaltheory; frameworkonly as theyrelate to thepredict- the framework we abilityof the process. conceptual (Fig. 2) propose for evaluatingpredictive models is our hy- Clements(1916) perceivedsuccession as a pothesisof relevantecological theory. We ex- regularsequence of seralstages that culmi- amine the natesin a climaxcommunity reflective of the implicit ecological assumptions made by thedevelopers of PATREC and eval- regionalclimate. However, many observations uate themagainst the describedtheory. do notsupport such orderliness. Several alter- nativeviews have been proposedto account PATREC forvariation in seralstage sequence and com- Evaluation of Assumptions positionof climaxcommunities. The alterna- The ecological literatureoffers theoretical tivesview plant communitiesas gradientsand empiricalsupport for the PATREC meth- ratherthan discrete units of association,with odology.This support stems from concepts ex- successionbeing a functionof species growth, pounded in habitatspace, habitatselection, survival,and dispersalcapability (Gleason and niche theory;all evidentin our interpre- 1926,Whittaker 1953, Drury and Nisbet 1973); tationof PATREC's basic ecologicalpremise. and thuspredictable within probability limits Premise 1.-Animal distributionand abun- (Johnson1977). This predictabilityof the dance can be explainedand predictedby en- successionprocess (when in conjunctionwith vironmentaldescriptors of a particularunit of theoriesof habitat space, habitat selection, and land. niche),is valuablein establishingthe relation- This assumptionis foundedon the theory shipbetween changes in speciescomposition that a species'ability to surviveand reproduce and abundanceand changesin vegetation. can be characterizedby a unique set of en- vironmentalattributes at a givenlevel of eco- logicalgeneralization. A CASE EXAMPLEEVALUATION: The varioushabitat attributes that comprise PATREC a PATREC species-habitatmodel represent the Nationalwildlife assessments need theca- environmentalgradients important in deline- pabilityto predicteffects of alternative man- ating the population-level classes on the agementactivities on wildliferesources. Eval- ground.Figure 3 depictsthis theoreticalre- uationinvolves appraising the utilityof a lationshipfor a single habitatvariable. The modelin attaining a goal; success being judged interceptsdefined by the populationclassifi- 126 Wildl.Soc. Bull. 13(2) 1985
cationboundary represent the rangeof values a speciesand itshabitat may notbe consistent (A-A') forthat variable that differentiate be- because of variationin the animal commu- tweenareas of highand low populationlevels. nity. Premise2.-Distributional abundance pat- Intraspecificinteractions can also invalidate ternscan be assessedsolely throughspecies- Premise2. Territorialbehavior may resultin habitatconsiderations. higherdensity in suboptimalhabitat by forc- Interspecificrelationships are not included ing individualsto move fromoptimal habitat explicitlyin PATREC models. This may be during highly productiveyears (VanHorne due to the difficultyin definingand quanti- 1983). Conversely,during years of low popu- fyingthese interactionsand a lack of data. lationsonly optimalhabitat will be occupied Problemsassociated with this supposition have (Partridge1978). Because such fluctuations been recognized (Kling 1980:34) but ad- may be independentof changes in habitat dressedinadequately through assumptions that characteristics(e.g., survivorshipin wintering errorscan be reduced by carefulinterpreta- areas), abundance patternsmay not be ex- tionand acknowledgmentof theinfluence that plainableon the basis of habitatrelated vari- competition,predation, and disease play in ables. regulatingnumbers. A corollaryof Premise2 is derived from Errorsin PATREC predictionsassociated general pattern recognitionprinciples. Be- withinterspecific interactions can resultfrom cause PATREC is based on perceptionand 2 situations.First, seemingly identical habitat recognitionof habitatpatterns, it presumes: can have differencesin species composition Premise3.-Similar patternsor configura- whichmay alter the species-habitatrelation- tionsof habitatwill reflectsimilar patterns of ships.Biogeographical studies have shownthat abundance,resulting in a consistentand ac- animals colonizing islands with few other curateclassification of sitesaccording to their specieswill expand theirniches-a phenom- abilityto supportpopulations. enon termed ecological release (MacArthur Descriptions of species habitat require- and Wilson1967, MacArthur1972). Williams mentsare based on observationsmade in the and Batzli(1979b) and Abramskyet al. (1979) contextof the entirefaunal community. The observedthe same phenomenonfollowing re- observedhabitat space occupiedby theorgan- movalof a suspectedcompetitor. In addition, ism has been influencedby othercoexisting diffusecompetition in species-richhabitats populations.Consequently, PATREC's habitat couldeliminate or excludea speciesthat would patterncharacterization for a speciesis an es- otherwisebe an expectedmember of the fau- timateof thatspecies' realized niche. Accord- nal communitybased on the habitatcharac- ing to nichetheory, however, a realizedniche teristics.This patternstimulated the develop- is not a unique entitylike its fundamental ment of community assemblage rules counterpart.Rather, it is dependentupon fau- (Diamond 1975a, Haefner1981). nal composition.Therefore, shifts in the real- A second error stems from situationsin ized niche are expectedto mirrorchanges in whichpredation limits a population.In such composition of a community. Because cases,the distributionor abundanceof a pop- PATREC has yetto incorporatevariables that ulationmay be more a functionof predation capturevariation in interactingfauna, devia- thanthe resourcebase (May 1977,Nelson and tionsfrom predicted population patterns may Mech 1981). be expected. As currentlyapplied, PATREC models do A finalpremise concerns the use of expect- not considercompetitor or predatorinterac- ed value (Spurrand Bonini 1973) in translat- tions.Thus, the associationpatterns between ing probabilitiesassociated with discrete rel- ECOLOGICAL THEORY IN APPLIED MODELS * Flatherand Hoekstra 127
ative populationclasses into a statementof terspecificinfluences implicitly because dif- average,long-term potential abundance. ferencesin populationclasses can be attrib- Premise 4.-The average populationasso- uted to variationin the habitatand faunal ciated witheach relativepopulation class de- community.The resultis an inaccuraterep- finesa potentialequilibrium level. These av- resentationoftrue population potential. Test- erages represent long-term potential ingof predictions isalso difficult because over- abundance. Therefore,if habitat conditions estimatescan be rationalizedbased on semantic remainrelatively static, the mean population differencesbetween potential and actual pop- level shouldbe constant.Although not explic- ulations.Such rationalizationmay preclude itlystated, this premise assumes that observed criticalexamination of theecological reasons populationsare at or near carryingcapacity. forthese discrepancies. Techniques that pre- The developersof PATREC recognizedthat dictpotential populations as describedhere wildlifepopulations fluctuate, and thus used ultimatelymust be testedagainst what ac- averagepopulation levels to estimateequilib- tuallycan be observed. riumlevels. The principlesof carryingcapac- Thesecond point concerns the lack of direct ity and r- and K-selection,however, suggest considerationofsuccessional changes in vege- that calculationof populationsbased on an tation.To accomplishthe assessment mandate assumedequilibrium level may be applicable ofpredicting the effects of future habitat con- onlyto certainspecies. ditions,PATREC mustbe linkedto other The opportunisticstrategy and variable models,such as timber-inventoryprojection populationscharacteristic of r-selectedorgan- models(Alig et al. 1984), to accountfor ismssuggest that populations of thesespecies successionalchanges. Otherwise, the temporal tendto be independentof the upperresource changesof PATREC variableswill require limitsof a particularhabitat. Consequently, subjectivedecisions. modelingof such wildlife populations through A thirdpoint concerns the influence of geo- habitatrelationships is difficult.On the other graphicscale on population-habitatmodels hand,the characteristicsof K-selectedspecies such as PATREC. Currentapplications of suggesta strongerrelationship between abun- PATREC,and habitat models in general, have dance and quantitiesof theirresource base. been sitespecific. However, national assess- Althoughpopulations of speciesfalling closer mentsnecessitate evaluations of wildlife hab- to K on the r-K continuummay be predicted itatover larger areas that are regionalin ex- more consistentlyin habitat-basedmodeling, tent.At this level of ecological generalization, theyare ironicallyless sensitiveto short-termsome ecologicalconcepts (e.g., selectionof habitatchanges. habitatat a particularsite, territorial behav- Threeadditional points from our evaluation ior) becomeless important in the modeling are notrelated directly to any assumptionsin- exercise.The modelermust be awareof scale herentin PATREC. The firstis the interpre- as it willinfluence the relative value of each tationof the expectedvalue estimateas a po- componentcomprising the proposed ecologi- tentialpopulation level. Potentialpopulation cal frameworkin explaining distributional and has been definedas habitatcapability without abundancepatterns. regardfor limiting effect from other species (U.S. Dep. Inter.1980a). Such an interpreta- CONCLUSIONSAND tion is an intuitivelyattractive concept, but RECOMMENDATIONS one thatis difficultto measureand confounds testingof model predictions.For example, In hisempirical examination of PATREC, constructionof PATREC modelsconsiders in- Kling(1980) found a lackof consistency in its 128 Wildl.Soc. Bull. 13(2) 1985
abilityto evaluate wildlifehabitat. One pos- interactionsas model componentsare de- sible explanationfor inconsistentpredictions veloped.Such a methodologyis furtherjus- is violationof ecological theory.We used a tifiedbecause K-strategistsare moreprone theoreticalframework considering species- to extinctionand shouldreceive preferen- habitatrelationships, population growth, in- tial considerationfor conservation (South- terspecificinteractions, niche, and succession wood 1981, Fowlerand MacMahon 1982). to evaluatethe premises inherent in PATREC. 3. Defininghabitat variables the same as land- Our evaluationrepresents a preliminarystep base and resourcevariables used in inven- in analyzingthe limitationsof PATREC and toryprojection models, including both hab- has been moreheuristic than definitive. Rec- itatvariables that are measureddirectly and ommendationsand researchneeded to im- thosecalculated from resource inventories. provehabitat-based models such as PATREC The temporal relationshipsin inventory include: projectionmodels would be incorporated explicitlyby habitat-basedmodels. Accom- 1. Makinga concertedeffort to examinethe plishingthis task requiresconcurrent re- influenceof interspecificinteractions on search on the utilityof existingresource model predictions of distributionand inventoryvariables in habitat-basedmod- abundance.The explanatorypower of in- elingof wildlifepopulations. Wildlife hab- terspecificinteractions is unknown.If in- itatvariables are measuredin resourcein- terspecificinteractions are significant,then ventories(McClure et al. 1979), however, competitorsand predatorsmay be treated criticalevaluation of thesevariables from as a compositerather than by examining thestandpoint of ecologicaltheory is need- interactionsamong all species. Diversity ed. In addition,application of resourcein- withina guild could be indicativeof com- ventoryvariables in habitat-basedmodels petition(Pianka 1981). The additionalin- will help definethe inventoryinformation fluenceof human predationcould be in- necessaryfor an accurateand efficientrep- corporatedthrough relative measures of resentationof wildliferesources. huntingpressure. 2. Categorizingspecies to minimizeerror as- Acknowledgments.-Wethank D. R. Smith, sociated with omissionof species interac- W. K. Seitz,and A. T. Cringanfor their assis- tionsas model components.This categori- tancein the developmentof thispaper. Grat- zation could be based on the theoryof itude is also extendedto R. H. Giles, J. M. r- and K-selection.Southwood (1981:42) Sweeney,J. W. Thomas, G. L. Williams,J. concludedthat K-strategists are less likely Verner,E. A. Gluesing,and R. W. Mannan to be influencedby otherspecies in the es- fortheir comprehensive and constructivere- tablishmentof equilibrialevels. Converse- viewsof earlierdrafts. ly,species intermediate on the r-K contin- uumare likelyto reachan equilibriumlevel LITERATURE CITED
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Wildl. Soc. Bull. 13:130-134, 1985
LANDSAT APPLICATION TO ELK HABITAT MANAGEMENT IN NORTHEAST OREGON
DONAVIN A. LECKENBY, Oregon Department of Fish and Wildlife,Range and WildlifeHabitat Laboratory, Route 2, Box 2315, La Grande, OR 97850
DENNIS L. ISAACSON, Environmental Remote Sensing Applications Laboratory, Oregon State University,Corvallis, OR 97331 SYLVAN R. THOMAS, USDA Forest Service, La Grande Ranger District, La Grande, OR 97850
Planning regulationspromulgated in re- sibilityof addressingpublic issues and con- sponse to the Forestand Rangeland Renew- cernsin a changingworld, and new proce- able ResourcesPlanning Act (RPA) of 1974 duresmay be requiredto meetthese added and the National Forest Management Act responsibilities. (NFMA) of 1976 requireinventory and mon- Aftercharacteristics for elk (Cervusela- itoringof wildlifehabitat (Legislative Affairs phus)habitat were defined for the Blue Moun- Staff1983). Forestmanagers have the respon- tainsof Oregon and Washington(Black et al.