A workshop was held at IIASA 14 to 16 January 1974 to develop a case study to explore the advantages of combining good ecological data, computer models and policy analysis in a coordinated whole. There are no examples available of this full combination, and the attempt to do it, therefore, forces modification and expansion of a considerable set of ecological, sampling, modeling, and policy techniques. The particular focus was an insect pest, the spruce budworm, of the coniferous forests of eastern North America

Holling, C.S.

International Institute for Applied Systems Analysis (IIASA)

Summary of Budworm WorkshopHolling, C.S.IIASA Working PaperWP-74-0031974 Holling, C.S. (1974) Summary of Budworm Workshop. IIASA Working Paper. WP-74-003 Copyright © 1974 by the author(s). http://pure.iiasa.ac.at/168/ Working Papers on work of the International Institute for Applied Systems Analysis receive only limited review. Views or opinions expressed herein do not necessarily represent those of the Institute, its National Member Organizations, or other organizations supporting the work. All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage. All copies must bear this notice and the full citation on the first page. For other purposes, to republish, to post on servers or to redistribute to lists, permission must be sought by contacting repository@iiasa.ac.at SUMMARY OF BUDWORM WORKSHOPc. S. HollingJanuary 1974 WP-74-3Working Papers are not intended fordistribution outside of IIASA, andare solely for discussion and infor-mation purposes. The views expressedare those of the author, and do notnecessarily reflect those of IIASA.SlJfU1I'J1Yofｦ Ｓ ｬ ｬ ｭ ａ ｪ ｏ ｮ ｊ ｾ HOm:SnOpA workshop \lms he Id at 111',5/\ Ilj to 16 January 1')"( Ii todevelop a case study to explore the advantares of conblninr[ood ecolof:ical da ta, computer models and policy ｡ ｮ ｡ ｬ ｾ ｩ Ｘ is ina coordinated whole. There are no examples available of thisfull combination,and the ｡ ｴ ｴ ･ ｾ ｰ ｴ to do it, therefore, forcesmodification and expansion of a considerable set of ccolo[ical,samplinE:, mouellinp:, and policy technioues.The particular focus was an insect pest, the sprucebudworm, of the coniferous forests of ('CIstern IJorth ｦ ｜ Ｇ ｘ ｾ ｬ ﾷ ｩ ｣ Ｚ ｬ ＮIt was ctlosen because there was an existing set of data collecteduSlnc good statistical sampling procedures over tllP pJ.st 30ｹ ｾ ｡ ｲ ｳ in Canada. In addition, a simulation model was availablewhich roufhly cantured some of the causal relntions Clno noreaccurately ropresented the C1ualitotive nroperties. ':!hat viasDlsslnr was rigorous refinement and validation of the model,analysis of the effects of the stochastic behavior of weatherand of the subprocesses and, ｾ ｯ ｳ ｴ important, conceptualizationand desiEn of useable policy instruments. If these [:.1)1:'3 couldbe effectively filled, then a valuable pac]<a-re of ｴ ･ ｣ ｾ ｭ ｩ Ｇ Ｑ ｵ ･ ｳwould be available of brand applicability to any problem ofsinGle ｳ ｰ Ｈ ｾ ｣ ｩ ･ ｳ r.lanaremt'nt, whether of ｲ ･ ｾ Ｉ ｴ ｳ of crops or of nanor of populations of fish or wildlife.-2-ｲ ｣ ｡ ｾ ［ ［ ｩ ｢ ｩ ｬ ｩ ｴ ｹ research vJaS initia.tc:cl jointl:: b.'l r'!'!thedolorist.s,hydI'O lOfi s t s, and ec olori st sat I ｉＡ｜ｾｉＧ｟ in :J o'/C'/':b,,'r . It 'illiek}ybecar.:le clear that expansions ltlere r0CJuil'cd of ｴ ｨ ｴ ｾ c):i stin,r'techniques of optimization so th,'lt they COllJ.r] ｃＢＧｬＩＨｾ 1:!5 i:;h v:f1a tto the ･ ｣ ｯ ｬ ｯ ｾ ｩ ｳ ｴ ｳ was a simple system, and to ｴ ｾ ･ ｮ ｾ ｴ ｨ Ｐ ､ ｯ ｬ ｯ ｲ ｪ ｳ ｴ ｳa conplcx on8 (non-linear, larre nunber of ｾ ｴ ｡ ｴ ･ variables,spatial pattern). Such expansions ｷ ｯ ｵ ｬ ｾ be one Ｓ ｌ ｾ ｲ ｴ ｯ ｾ ｱ ｲ ､ ｳdevelopinr more broadly \1Seflll ｯ ｰ ｴ ｩ ｲ Ｚ Ｚ ｩ Ｚ ｾ ｡ ｴ ｩ Ｈ Ｉ ｮ tee:n] i our'::; ;;n:! 2tthe sane time would force ,'1 rip-oraus anc:lys:i.;-; Df th': ｣ ｣ ｯ ｬ ｯ ｣ ｩ ｊ ｾ Ｎ Ｑ ｬmodel and of relevant policy options.intensive period of research in which the nodel was ｳ ｩ ｲ ｾ ｲ ｬ ｩ ｦ ｩ ｮ ､to 4 state variables in 265 ［Ｚ［ｵＱｾｲ･ｾｩｯｮｳＬ ｴ･｣Ａｭｩｾ［［Ｎｊ rr'])lcns ofthe model were id('ntifi.ccl, data ｲ ｾ ｌ ｬ ｮ Ｌ Ｓ ｜ Ｇ Ｎ Ｇ ｬ ｾ ｲ ｣ ｃ Ｇ Ｚ ｔ ｮ ［ ［ Ｇ ＾ ｾ Ｌ ;l(\,l :, rir'::;phase dynamic prorramminr nodel desir-ne''! for (i;:t.:lri.znti.c:: 1:!it;hinone ｳ ｵ ｢ ｲ ･ ｾ ｩ ｯ ｮ Ｎ ｾ ｮ Ｓ ｴ sirnificantly, ｾ ｮ nltern3tc ｮ ｯ ｬ ｩ ｾ ｹ frame-work ber-an to be conceived that was more qlDlit:ltive, butricher in its ability to contain ecolorical ｡ ｮ ｾ ｔ Ｇ ｯ ｝ ｩ ｣ ｾ ｲ ｯ ｡ ｬ ｩ ｴ ｩ Ｐ ｾ Ｎｾ ｜ Ａ ｣ becan to call this "Corprcssed Polir.v ｊ Ｂ ｮ ［ Ｇ ｊ Ｎ Ｇ Ａ ［ Ｉ ｩ ［ ｾ ［ ﾷ ::.r<:' :i ';showed pror.:isc of providinr a policy frf1]':1Cvl(Jr].: i::15 r.h ﾷ Ｇ ﾷ Ｇ Ｚ Ｉ ｬ ｾ Ｎ ｬ ､nakeY's.Hitli this feasibility study c:oT'lDLeted, Vi"- ｃＭＺＭｉｾ［｝Ｈｊ ＺＮ［ＨＢＬＮｾＧ ｲｲｃＺＮｾｩＬprofi t in further E;Xp lorinc 3.nr] into rr;:::. tinF- tilrc·:; ｴ ｨ ｣ ［ ﾫ ｾ Ｚ:1odel refinement and validation, nynamic prn["nn"ninr, 21',r:Cor..rressc:rl rolic.'! analysis. But to do so, it Ｇ ｩ Ａ ｾ ｾ Ｎ Ｂ e:';:;r:-Et,},'d telrlevclop v:orLin[ contact \'litl! the ::;cir;nt::"fic ｴ ｃ ｾ ｬ ｲ Ｍ Ｇ ｾ Ｇ ｊ ｨ Ｚ Ｚ Ｈ Ｌ Ｂ ｬ h;'r! l"("pconcent.ratinc on this !)roblcf"..-3-lIenee the vlOrkshop, which expanded the inteY'DrO:1 I?C tlinkages developed within IIASA to ｬ ｩ ｮ ｾ with an active warkinrr:roup in the Canadian Department of the ｅ ｮ ｶ ｩ ｲ ｯ ｮ ｾ ｃ Ｇ ｮ ｴ Ｎ '].'hc ronlsof this working session were:(1) to define the objective functions and develop theframework for a dynamic procramninr nonel (, f' .'1sincle sUbregion;(2) to analyze, clarify, and PlocJify the ｦ ｾ ｸ Ｚ ｩ Ｎ ｳ ｴ ｩ ｮ ｲ ﾷsir:1Ulation I71odcl;(3) to derine future steps and r:oals for a short termcooperative effort which would be of value notjust to the participants but broadly to theseconcerned with problems of ｾ Ｚ ［ ｩ ｮ ｦ ｬ ･ ｳ Ｉ ｬ ｴ ｾ ｣ ｩ Ｇ ｊ ｾ ［ w.lm1f"':J11cnt.Each of these foals vJQS achieved for tl:P. three thcr;e3.The IIASA budworI71 workshop was able to answer ｳ ｯ ｾ ･ criticalquestions about the budwormsystem. Until these questions werea.ns"'Iered, some of the avenues of invc2,tiration Ｇ Ｚ ｮ ｾ ｲ ｣ hlocked.The following steps and prerequisites for their conpJetion wereidentified:Model RefinementThe assumptions ""hich went into the original modelwere clarified.Procedures were established to correct the codfnrto more accurately portray the real world ｾ ･ ｣ ｨ ｡ ｮ ｩ ｳ ｲ ｮ ｳ Ｎ-11-:Jev,' data were obtained \'1hich extend the ri1rJ.re 0 rseveral of the variables.'.l'l1e T:lodel Has restructured to incorpornte within-tiflc-per lad feedbac ks of forest concH t ions on ]luch':ormsurvival.ｾ ｾ Ｎ ｣ ｾ ､ ･ ｬ ｔ ｾ ｳ ｾ ｩ ｮ ｣'I'he ne'd model strueture will be cOf!parccl '..lith v::lriou::field measures of buclworm dynamics.[Jew field data or. forest and ｢ ｵ ､ ｶ ｬ ｯ ｲ ｲ ｾ ｣ ｯ ｮ ｣ ｬ ｾ Ｎ ｴ ｩ ｯ ｮ ｾ Ｌ ",ereobtained and will be coded as input to the mortel.IL real and simulated historical record ｾ ｊ ｩ ｮ ｣ ｃ Ｇ :LSd;;will be generated to allow conparison.Measures of ｴ ･ ｾ ｰ ｯ ｲ ｡ ｬ and soatial outbreak patternsVlhich capture their qualitative (lSpccts ":ill be de-veloped for both the real and simulated data.ｾ ｬ ｯ ｾ ･ ｬ f,nalysis'l'he revisions and refi.nements developed in the \\'orkshopwill be incorporated into the analysis of th8 Modeldynamics.Dynamic ｐ ｲ ｯ ｲ ｲ ｡ ｲ ｲ ｾ ｩ ｮ ｲThe principal aim of the policy froup was to determinethe objective function for the optimization nodel and to developthe necessary data. This work was done in three staces:-5-(1) Determination of discount factor;ｾ (2) Determination of yearly costs (or benefits)per ｳ ｩ ｾ ･in terms of conditions in site and policy of thR.t Y0al"';(3) Determination of final value function.(1) Discount factor'I'he choice of a discount factor is SOrr.ChOVT orbi trriry. It\'las fel t that it s!lOulcl be between .01\ and .10. A . v n 1u e 0 f . rJ :>was agree(l upon as a reasonable value for th:: firr,t tries.(2) Costs (or benefits_)_per_."yearThe costs incurred are those of Ｓ ｮ ｲ ｡ ｙ ｬ ｮ ｾ (adults or larvae)and the benefits come from wood production and ｾ ｩ ｬ ､ ｬ ｪ ｲ ｣ Ｏ ｲ ･ ｣ ｲ ･ ｡ ｴ ｩ Ｐ ｮ Ｎ(a) Sprayinr for adultsWhen spraying for adults we incur a cost of t.30/acre.(b) ｓ ｰ ｲ ｡ ｹ ｩ ｮ ｾ larvaeThere is a fixed cost of $.20/acre for snrayinr, plusand addi tional v8.riable cost (1ependin,r en the dosis,anrt which reflects the cost of the insccticirlc of ｾ ｬ Ｎ Ｒ Ｕper pound.Irenc e,ounce:::; /acrc.'i.e., no1tTherc SE= ()...'0.)E{o if.20 + .073 x sC(S ) =EFor a dosis of 3 ounces of insecticide per acre, this Cives ncost of 43.4 cents/acre.-6-obtained fro!'l the follo\dnc :i.nf'orr:c:t·:on:(i) one acre of ave (TOUr 3 tree.'; yields :?() ClliliL,(1 cunit ｾ 100 eft) of wood.(ii) The net benefits derived fron th8 ｦ ｯ ｲ ･ ｾ ｴ ｩ ｮ ｾ ｵ ｳ ｴ ｲ ｹt t · 1 r' t . P ·2 ') ') Ij () 1'-' 6o a pro ..Juc Ton 0.. '. ,_,_ .,X ,) C lwl ts .benefit of ｾ Ｕ Ｕ per cunit.Hence 1t!e ret a net benefit of Ｑ Ｑ Ｐ Ｐ ｾ ｨ Ｎ ｣ ｬ Ｇ ･ fo1' trees in ｡ ｃ ｾ Ｓｾ ｲ ｯ ｵ ｰ 3, whenever the total ｰ ｲ ｯ ｾ ｵ ｣ ｴ ｩ ｯ ｮ is bptwoen2.xl0 6 to 3.xl0 6 cunits.(d) Wildlife/recreation benefitsThe vlildlife/recreatjon benefits are est5riatcd to be$1000 per square nile per year when the forest compo-sition is uniform over arc, and very len'l v,'hon ｴｨＨｾｲｯ isonly one tree are. The ｦ ｯ ｬ ｬ ｯ ｷ ｩ ｮ ｾ function is ｄ ｲ ｯ ｰ ｯ ｾ ･ ､ Ｚ(3) Pinal Value PunctionIt was acreed that the final value function ｾ Ｓ Ｑ Ｑ Ｐ ｕ ｊ ､ be ｴ ｬ Ｑ Ｇ ｾpresent value (at time T) of all future benefits due Lo theforest. ri.'his ",ray, if at time T there ｩ ｾ Ｓ no olltll1'c::ik (I = 0,small egg density), its value will depend mainly on a3. Ifthere is an outbreak, then the benefits from Ci3 should be reducedby a factor [':(1)1 if-7-1=0.5 at value of I where trees start dyinrwhere g(l) =o at 30 units over value at which treesstart dyingand the linear interpolation value forother Is.Besides that, we should subtract the value of sprayinr insectIcideto reduce the larvae to a density eouivalent to ｴ Ａ ｾ ｬ ｴ of a norralperiod.Hence,where g(I) is as Vlven above and f(E),<l1,a2 anri a3 cnn beca le ulated from the econor.1ic informn t ion a vEli 13 bIe ｡ ｲ ｾ ｾ Ｑ the'Compressed Policy ｬ Ｇ Ｎ ｮ ｡ ｾ ｹ ｳ ｩ ｳL:xtensive use of the simUlation model is conterlplatcd inorder to test a ranre of policy options. Several modes ofoperation will be developed, all based en systematic Ｑ Ｎ Ｂ ･ ｮ Ｈ ｾ ｲ ｡ ｴ ｩ Ｈ Ｉ ｮof weather at many locations in the province.(1) The wori: essential to renerate extensive traces of "ra\'jdata" at 10 sites, and to convert these to biolor1callyrelevant weather states (1, 2, 3) at Ｒ ｇ ｾ ｪ plots, 11<12. beenallocated. These reconstituted data vlill ｰ ｲ ｯ ｾ Ｓ ･ ｲ ｶ ･ thetemporal and spatial correlations inherent in thp observedsequences.-8-(2) Using the model with a single lone synthetic trace, He, will r,enerate rer:ression equations relatin[ err, densit.y(dependent) to previous density, deriving separate rela-tionships for each of a small number of weather patterns.Departure from trendline estimates can be attributed tostand conditions and stress index; the cumulative effectof these will be neasured by the residual variance in·theregressions. This will rive an initial approxination tothe magnitude of the smear or cloud of data points inthe prototype.(3) The full model will be used to renerate transition natricesover 1 year; the states will include food, errs, ｾ ｰ ｾ ｴ ｨ ･ ｲand stress index. Nine states are visualized:1 - Threat ( food > S), weather pattern 12 - Threat 1'lea ther pattern 23 - Threat Heather pattern 3II - Threat weather pattern Ij5 - Endemic level; no threat; food < C'L-'6 - Decline of outbreak7 - ｏｵｴ｢ｲ･｡ｾ［ｳｴｲ･ｳｳ index 18 - Outbreak; stress index 29 - Outbreak; stress index :>Long traces vJ'ill be run to investip;ate the transi tionprobabilitities for a variety of ｾ ｴ ｲ ｡ ｴ ･ ｲ ｩ ･ ｳ Ｎ(4) Full scale weather models will be used to test spatialpolicy effects." '!l rcsearC:l schedule \'1,'18 then ,::lfTCECl to (slwn:.lri :::-:,(1 in'rable 1) l'lhicll would lead to a finCll report by ｾ Ｇ ｩ ｯ :1D,'! 107 Ij._In order to achieve this, responsibili ties for qllc;·cifictasks were defined:(1) By 1 February, detailed inforr'12 tion on pas t ｆＺ｡ｮｃｬｌｾ｣ｭ｣Ｚｮｴpolicies usinr insecticides (size of blocks sprayed, dose,hazard trigger by year by area in the forn of a write un andmaps) .fIction: !Hller(2) By 1 February, detailed ｩ ｮ ｦ ｯ ｲ ｾ ｡ ｴ ｩ ｯ ｮ on ｾ ｡ ｮ ｾ ｦ ･ Ｒ ･ ｮ ｴ nolicjesby tree cuttinc by sub-rerion in 5 or 10 year periods Ｈ ｾ ｮ ｰ ｳ Ｉ Ｎ'.J\ction: n:)::;l':Cl'viJ 1,,'(3) By 15 February, weather records of raw datu from 10 ｾ ｴ ｡ ｴ ｬ ｯ ｮ ｾover 60 years punched for a cOT:1f)lete Y'ectan[ular :lrrn:l, tocethcrwith a map ｬｯ｣｡ｴｩｮｾ weather stations and ｣ ｯ ｮ ｴ ｩ ｾ ｵ ｯ ｕ Ｓ rcr:ionsassociated with each.Action: !1il1er(11) l3y 15 February, data provided on Cf'J': ｣Ｑ･ｲＺｳｩｴＺＺＧｃＧｾ［ :Hlr.l ['nl'NiLcondition by 265 ｳｵ｢Ｍｲ･ｾｩｯｮｳ for each year fron Ｑ ｾ Ｔ ｂ ＮJ\ction: Baskerville ｾ ｾ ｪ ｊ ｬ ｣ ｲ(5) By 28 February, mapping of above data and ｶ ｡ ｬ ｩ ､ ｡ ｴ ｩ ｯ ｾ runsusinc these data.fI.c t ion: ,J one s-10-(6) By 23 February descrirtion and data justification for ｜ Ｇ Ｚ ｣ ｾ ｴ ｨ ｣ ｲｩ ｮ ､ ･ ｾ ＮI\ction: :H llcr(7) On or' about 30 filarch, a return ｶ ｩ ｾ Ｎ Ｌ ｩ ｴ by ｾ ｉ ｩ ｬ ｬ ｣ ｲ at D.a.E.expense to help define realistic policy sets.(8) By 30 !ilay, a brief summary of dynanic ｲ ｲ ｯ ｲ ｔ Ｍ ｊ ｲ Ｇ ｾ ｲ ［ ｩ ｮ ｩ Ｓ forthe practi tioner usinr insect ｄ ･ ｳ ｴ ｾ Ｉ as the exoTmle.Action: DantzirAdditional PlansBy 30 May, therefore, there should be a conplcted reportemphasi zinr: a c onbina t ion of exnandcd ec olor j CD 1, riod c:1 l.i ｲ Ｚ ｾ Ｂ 8.11,1policy techniques as illuminated by this specific Rxnrnle ofr,1anagement of a pest \·lithin an ecosystem. nut there vriLL :;tillbe missinE elements:(1) informinc and involvinf:" croups \'lith sid.l8.r nr()l;Jerr,cjin other countries;(2) the full decision process in the real world invclvesas we 11 the tec hniques of idcnti fy inr a 1 terno to ob,i cc 1:. i vC's inour socie ty and of rat ionali :dnr often con f1.:i c t in r onp s . ｾｬｬｃ htechniaues cannot possibly be well desirned in isolation ｦ ｲ ｯ ｾthe actual decision-makers and those vIho are affected by thedecisions.Steps have already been initi8ted to identify interestedcroups in other countries, particularly ｕ ｾ ｓ ｒ Ｌ FRG, GDR, France,Poland, and USA. But the exact pattern of involveMont of then8people will depend on the results of this caf;,? stuet:!. [\nd trwtdec i ::0 ion Gil:.i. 1if" in ::l. S ｰｾＩ c i fi. c n I'0 Llen." t'',' .Table 1. Research Schedule - Budworm Projectb-Area Completion Dates for StagesResponsibility)16 Jan. 1 Feb. 28 Feb. 15 March 30 March 30 April 30 MayResolve tech- rewrite pollate 1948- final modelSimulation nical r concep- Simulation ｾ Ｙ Ｗ Ｐ data by revision; pre- FINALModel tual and data model; design y-ear and 265 paration of REPORT(Jones) problems output indi- ｾ ｵ ｢ ｲ ･ ｧ ｩ ｯ ｮ ｳ ［ figures; com-cators reflect- lValidate runs plete analyticsing spatial pf model of modelpatternstandard conceptuali-Dynamic Define optimization zation of FINALProgramming objective model com- inter-site REPORT(C.Winkler) function plete and optimization(for sub- run Bcheme & iden-region) tification ofproblemsdefine min. r.reather data simulation develop graphicCompressed Conceptualize states of the Prom 10 runs coupling define production packages forPolicy technique system in stations for weather model reasonable runs decision makers;Analysis terms of bud- ｾ ｏ years with ecological policy sets FINAL(Fiering) worm food punched and simulation and alter- REPORTthreshold, ｾ ｮ ｡ ｬ ｹ ｺ ･ ､ ［ model for nate actionsbudworm densi- ｾ ｴ ｯ ｣ ｨ ｡ ｳ ｴ ｩ ｣ tests ofty thresholds l10del of sensitivity;and relevant ｾ ･ ｡ ｴ ｨ ･ ｲ com- test runs to[Weather pleted identify alt.patterns mgmt. options& useful out-put indicatorsrequired forpolicy assess-ment. iI

Summary of Budworm Workshop

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