Governance of ecosystem services : A framework for empirical analysis

Go e nance o Ecosys em Se ices: A amewo k o empi ical analysis Ee a P imme a, n , Pekka Jokinen b , Malgo za a Blicha ska c,d , Da id N. Ba on e , Rob Bug e , Ma ion Po schin g a Finnish En i onmen Ins i u e (SYKE), Finland b Uni e si y o Tampe e (UTA), Finland c Swedish Uni e si y o Ag icul u al Sciences (SLU), Sweden d Swedish Biodi e si y Cen e, Sweden e No wegian Ins i u e o Na u e Resea ch (NINA), No way Al e a, Pa o Wageningen Uni e si y and Resea ch, The Ne he lands g Cen e o En i onmen al Managemen , Uni e si y o No ingham, UK a icle in o A icle his o y: Recei ed 17 Oc obe 2014 Recei ed in e ised o m 8 Ap il 2015 Accep ed 11 May 2015 A ailable online 26 May 2015 Keywo ds: Ecosys em se ices Biodi e si y conse a ion Go e nance Policy implemen a ion A gumen s abs ac Biodi e si y conse a ion policies jus ified wi h science and in insic alue a gumen s ha e p oduced disappoin ing ou comes, and he need o conse a ion is now being addi ionally jus ified wi h he concep o ecosys em se ices. Howe e , li le, i any empi ical a en ion is paid o ways in which di - e en ypes o ecosys em se ice decisions a e made, o wha a gumen s a e e ec i e in u ning policy in o p ac ice and u he in o conse a ion ou comes and, in gene al, o how ecosys em se ices a e go e ned. To close his gap, his pape iden ifies he di e en modes o go e nance in policy im- plemen a ion om biodi e si y and en i onmen al conse a ion li e a u e and inco po a es hem in a concep ual model o ecosys em se ices commonly u ilised a p esen , he cascade model. The esul ing concep ual amewo k encompasses: (1) hie a chical go e nance; (2) scien ific- echnical go e nance; (3) adap i e collabo a i e go e nance; and; (4) go e ning s a egic beha iou . This comp ehensi e a- mewo k p o ides a s uc u e o empi ical analysis o ecosys em se ices go e nance, which akes in o accoun he people and o ganisa ions making decisions, and, in pa icula , he di e en a gumen s ha a e used when implemen ing policies. The amewo k will acili a e holis ic ecosys em se ice analyses and suppo policies in gene a ing conse a ion and sus ainabili y impac . &2015 The Au ho s. Published by Else ie B.V. This is an open access a icle unde he CC BY-NC-ND license (h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/). 1. In oduc ion The global consensus on he impo ance o biological di e si y and he need o conse e i has been o malised in nume ous ag eemen s and s a egies (e.g. UN, 1992; EC, 2011). S opping species ex inc ions and p o ec ing a p opo ion o land a ea ha e been se as explici a ge s. The igo ous e alua ion o hese a - ge s o e ecen decades has, howe e , p oduced disappoin ing esul s, e ealing ha he appa en poli ical will and ca e ully d a ed policies ha e no hal ed biodi e si y decline (Rod iguez e al., 2004;Rands e al., 2010). The ailu e o p o ec habi a s om deg ada ion and con e sion, o species om decline and ex inc- ion, has o ced scien is s and decision-make s o ake an in- c easingly holis ic app oach o conse a ion, which ecognises humans as impo an beneficia ies o na u e. As a esul , he a - gumen s o biodi e si y conse a ion now add ess he complex social–ecological in e ac ions and he mul iple benefi s ha eco- sys ems p o ide o people (Ca dinale e al., 2012). As an a gumen - making de ice, he so called ecosys em se ice app oach en e s a wide se o social and poli ical p ocesses, in ol ing a ange o complex s a egies and mo i es (Haines-Young and Po schin, 2014; Tu npenny e al., 2014). The e is an expec a ion ha he holis ic ecosys em se ice app oach would e en ually be embedded in hese p ocesses; cons i u e a basis o policy design and be in- eg a ed in go e nance a all le els. The holism is well wa an ed bu , as esea ch concen a es on p oducing knowledge abou ecosys ems and hei alue o hu- mans, he issues o decision-making, policy implemen a ion and go e nance a e la gely igno ed. Simply assuming ha decisions will e en ually change, as new knowledge abou ecosys em se - ices is p oduced, is a significan impedimen o he conse a ion and sus ainable use o ecosys em se ices. This assump ion does no ake in o accoun he complex in e ac ions wi hin and ac oss he go e nance sys ems ha may ha e implica ions o ac ual implemen a ion o policies (Nie, 2003;Ra amäki e al., 2015). Con en s lis s a ailable a ScienceDi ec jou nal homepage: www.else ie .com/loca e/ecose Ecosys em Se ices h p://dx.doi.o g/10.1016/j.ecose .2015.05.002 2212-0416/&2015 The Au ho s. Published by Else ie B.V. This is an open access a icle unde he CC BY-NC-ND license (h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/). n Co esponding au ho . E-mail add ess: ee a.p imme @ympa is o.fi(E. P imme ). Ecosys em Se ices 16 (2015) 158–166 The e o e, he way in which new knowledge eeds in o decision- making should be a a ge o analysis i sel , building on explici esea ch on how ecosys em se ices a e go e ned, how policies a e implemen ed and wha a gumen s a e used in hese p ocesses. The limi ed a en ion o policy implemen a ion and go e nance in he ecosys em se ice con ex is su p ising, gi en he empi ical e idence base ha biodi e si y conse a ion and en i onmen al managemen analys s ha e accumula ed o e he las 50 yea s. To close his gap, his pape iden ifies he di e en modes o go - e nance in policy implemen a ion om biodi e si y conse a ion and en i onmen al managemen li e a u e and inco po a es hem in a concep ual model o ecosys em se ices commonly u ilised a p esen , he cascade model (Po schin and Haines-Young, 2011). The cascade model is a use ul simplifica ion o he eal wo ld, communica ing he ela ionships be ween ecosys em se ices and human well-being a a gene al le el. The model has been applied, c i icised and elabo a ed, o be e add ess pa icula ela ions and issues, such as ecosys em se ice supply and demand (Po schin, 2015). Ou analysis elabo a es he model wi h go e nance aspec s. We p opose a amewo k o empi ical analysis o ecosys em se ices go e nance. We s a by laying ou he way in which he ecosys em se ice amewo k is expec ed o b oaden he a gu- men s o conse ing biodi e si y and o gene a ing be e con- se a ion ou comes. We hen e iew empi ical biodi e si y and en i onmen al go e nance li e a u e, paying a en ion o di e en implemen a ion mechanisms ha ep esen dis inc modes o go e nance as well as he ways in which he e ec s o a gumen s o biodi e si y conse a ion a e e alua ed wi hin each go e n- ance mode. We conclude by placing he iden ified go e nance modes in o he concep ual amewo k o ecosys em se ices, and discussing he ele an in e ac ions and eedback be ween go - e nance modes and he pa icula componen s o he ecosys em se ices model. The esul ing concep ual amewo k encompasses: (1) hie a chical op-down go e nance; (2) scien ific- echnical go e nance; (3) adap i e collabo a i e go e nance; and, (4) go - e ning s a egic beha iou . This comp ehensi e amewo k p o- ides a s uc u e o empi ical analysis o ecosys em se ices go e nance, which akes in o accoun he people and o ganisa- ions making decisions, and, in pa icula , he di e en a gumen s ha a e used when implemen ing policies. The amewo k will acili a e holis ic ecosys em se ice analyses and suppo policies in gene a ing conse a ion and sus ainabili y impac . 2. Conse a ion e ec s and he concep o ecosys em se ices E alua ion o he e ec s o specific biodi e si y conse a ion policies usually ocuses on he ou comes and impac s, a he han on he ways in which go e nance u ns he policies in o p ac ice. The e ec s and e olu ion o he a gumen s o conse a ion ex- p essed in he design o he policy goals a e no gene ally ollowed h ough when e alua ing he policy o he a ious p ocesses o implemen a ion ha make up go e nance and e en ually p oduce conse a ion e ec s. E ec i eness indica o s, such as hec a es o p o ec ed a eas and numbe s o endange ed species, ha e a well acknowledged (and well dese ed) s a us in biodi e si y conse a ion epo ing, and mo e de ailed analyses mos ly ake hese as a p oxy o he e - ec i eness o p o ec ion s a egies. Fo example, e alua ing con- se a ion ac ion plans akes species s a us as a su oga e o con- se a ion e ec s (Laycock e al., 2009) and a mo e elabo a e cos - e ec i eness analysis uses de ailed species-habi a in o ma ion o measu ing e ec s o di e en pa cel sizes o p o ec ed a eas (Mönkkönen e al., 2011). Elsewhe e, o es co e is used as he p oxy o e ec in cos -e ec i eness analyses o conse a ion paymen s (Fe a o and Simpson, 2002) and p o ec ed a eas (Andam e al., 2008). In an analysis o cos -e ec i eness o he Eu opean Na u a 2000 P o ec ed A ea Managemen Plans, Wä - zold e al. (2010) iden i y a ious sou ces o cos s, and hus ake a s ep u he in conside ing he di e en ac i i ies equi ed o implemen ing he p o ec ed a ea a ge s. Gene ally, howe e , e - ec i eness e alua ions pay li le a en ion o wha ac i i ies and which a gumen s di ec he decisions and he esou ces, u he shaping he p ac ices ha deli e he conse a ion ou pu . The hea y eliance on simplified measu es o conse a ion e - ec s in e alua ing policies is su p ising, gi en he ex en o knowledge abou biodi e si y and he e ol ing a ie y o a gu- men s o conse a ion. Fo example, biodi e si y conse a ion policies elying on e hical and mo al a gumen s o p o ec ing na u e (Sago , 1996) ha e g adually been backed up by elabo a e science-based a gumen s abou he habi a condi ion, size and connec i i y ha species and popula ions equi e (e.g., Hanski 2000;Ma gules and P essey, 2000;Su he land e al., 2004;Hu h and Possingham, 2011). Elsewhe e, hese ecological a gumen s ha e been supplemen ed by long- e m benefi a gumen s, o en ope a ionalized h ough mone a y alues (Sago , 2011). In he de elopmen o mo e di e se a gumen s o biodi e si y conse a ion, he concep o ecosys em se ices ep esen s a majo a emp o cap u e he complexi y and di e en alue bases o conse a ion (Daily, 1997;Cos anza e al., 1997;MA, 2005;Gómez- Bagge hun e al., 2010;Po schin and Haines-Young, 2011). The concep ualisa ion o ecosys em se ices en ails a b idge, o 'cas- cade’, om he ecosys em's biophysical s uc u es and p ocesses (suppo ed by unde lying biodi e si y), o he benefi s and alues ha humans expe ience (Po schin and Haines-Young, 2011,Fig. 1). As highligh ed in he li e a u e applying he ecosys em se ices concep ual model (Po schin and Haines-Young, 2011) depic ed in Fig. 1 and simila models (De G oo e al., 2002,2010;Ba eman e al., 2011;Mace e al., 2014;Van Oudenho en e al., 2012), he c ucial a gumen s o biodi e si y conse a ion can be de i ed om he scien ific unde s anding o each o he model's compo- nen s: ecosys em s uc u e, unc ions, se ices, benefi s and a- lues, as well as he ela ionships be ween hese componen s. Fo example, unde s anding which elemen s o ecosys em s uc u e and unc ion con ibu e o he deli e y o impo an se ices may mo i a e decision-make s o implemen policies ha aim a be e conse a ion o hese pa icula elemen s. The e is an u ge o u he scien ific analysis o suppo he unde s anding o each o he componen s o he model and, o add holism, he ela ionship be ween hem. The esul s, hen, a e expec ed o allow u he elabo a ion o a gumen s o ecosys em and biodi e si y conse a ion. By displaying a back-loop om alues o ecosys em s uc u es (and unde lying biodi e si y), he ecosys em se ices model dis- plays an assump ion ha he knowledge o alue and alue a - gumen s a e necessa y o go e ning ecosys em se ices and im- plemen ing biodi e si y policy (Fig. 1). The easoning goes ha as many policy decisions a e based on economic a gumen s, he Ecosys em s uc u e P essu e Ecosys em se ices Ecosys em unc ions Bene i s om ecosys ems Limi p essu e h oughpolicy Ecosys em alues Fig. 1. A concep ual model o analysing ecosys em se ices (‘cascade model’), adap ed om Po schin and Haines-Young (2011). E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166 159 mone a y alua ions o ecosys em se ices will eed in o decision- making and, by allowing ade-o analysis, will suppo he de- cisions ha educe he p essu e on ecosys ems and biodi e si y (Cos anza e al., 1997;Ch is ie e al., 2006;Ba eman e al., 2011; Po schin and Haines-Young, 2011). Mone a y alua ion o biodi- e si y- ela ed benefi s may also encou age people o suppo na u e conse a ion, as hey inc easingly ela e hese benefi s o hei indi idual well-being (Fische and Young, 2007;Buijs, 2009; Liu e al., 2010). Addi ionally, iden i ying he cos s and benefi s o p o ec ing o using ecosys em se ices may show he impo ance o biodi e si y ou side p o ec ed a eas, going beyond adi io- nal,'ho -spo ’based e alua ion me hods (Hasle e al., 2010;Ba- eman e al., 2013). In p ac ice, howe e , alua ion o benefi s does no fil e a - gumen s di ec ly in o decisions (Spash, 2007;Va n, 2009;Span- genbe g and Se ele, 2010;P imme and Fu man, 2012;Spangen- be g e al., 2014). Academic li e a u e on mone a y alua ion s udies has had a poo eco d in influencing ac ual policy making (Lau ans e al., 2013). On he con a y, he p ocesses by which o mal decisions a e fil e ed o p ac ical implemen a ion a e un- likely o ca y he alue a gumen s as nume ical figu es. One eason is ha he s a ed p e e ence alua ion me hods, which a e he mos flexible in e ms o add essing non-use alues, o en use hypo he ical policy amings. The decision al e na i es o alua ion s udies do no easily scale o ans e o he ac ual policy se ings ha un old (Gómez-Bagge hun and Ba on, 2013). This may be one explana ion o lacking fil e ing o ope a ional decision-making a di e en le els o go e nance. Ne e heless, he e is a b oad ag eemen ha quan ified economic alues can be an impo an pa o decision-making as long as o he alue a gumen s a e also gi en conside a ion, and he p ocess in ol es pa icipa ion o hose who a e a ec ed by he decision (Spash and Va n, 2006; Va n, 2009;Chan e al., 2012;Co nell 2011;Sago , 2011;Plan and Ryan, 2013;Spangenbe g e al., 2014). To acili a e e ec i e go - e nance o biodi e si y, based on he ecosys em se ices concep and he ela ed app oaches o aluing na u e, he e is a need o deepe analysis o how ecosys em se ices hinking, and he en- suing a gumen s, fi in wi h di e en modes o go e nance (De G oo e al., 2010;Tu npenny e al., 2014). Imp o ing he e ec- i eness o biodi e si y conse a ion wi h he ecosys em se ice amewo k should he e o e s a om he analysis o go e nance. Analysing go e nance allows elabo a ing on some o he simpli- fica ions o he cascade model (Spangenbe g e al., 2014). 3. D awing lessons om biodi e si y and en i onmen al go e nance 3.1. Iden i ying di e en modes o go e nance To analyse wha condi ions he e ec i eness o ecosys em se ice a gumen s and o lea n how e ec i eness indica o s, ela- bo a e ecological knowledge and he imp o ed unde s anding o ecological unc ions and human benefi s can oge he eed in o he p ac ice o policy implemen a ion, go e nance needs o be ana- lysed empi ically. The new empi ical analyses should make use o exis ing analyses o go e nance, which a e ample in he a eas o biodi e si y and en i onmen al conse a ion policy and implemen a ion. O e he las 20 yea s, analys s o policy implemen a ion, managemen , decision suppo , pa icipa o y decision-making and poli ics ha e buil a solid unde s anding o decision-making and a gumen a ion in go e nance (No on, 2005;Wu zel e al., 2013). To achie e his analy ical unde s anding in ecosys em se ices go e nance analyses, i makes sense o link he app oach o he amilia cascade model (Fig. 1;Po schin and Haines-Young, 2011). S a ing om he cascade model o ecosys em se ices and assuming ha alues a e fil e ed o decision-making, he analysis o go e nance should begin wi h a ocus on ag eed policies o decisions and hei implemen a ion. In e na ional ag eemen s se e as an illus a i e example o such decisions. They eflec collec i ely ag eed alues and a e implemen ed by na ion s a es, in a hie a chically o ganised ashion (Young, 2002;Wu zel e al., 2013). Simila hie a chical s uc u es can be obse ed o na ional biodi e si y policies, o wi hin o ganisa ions, a leas as one mode o go e nance (P imme , 2011a).We sugges ha 'hie a chical go e nance’should be he fi s mode o be analysed. Following he ideas o ecosys em se ice li e a u e, go e nance equi es science-based knowledge on he p obable influence o he decisions on he ecosys ems (Vihe aa a e al., 2012). Accu a e scien ific- echnical suppo would allow ade-o analyses and he alloca ion o land-uses in an in o med ashion (de G oo e al., 2010;Po schin and Haines-Young, 2011). Also biodi e si y con- se a ion has been an a ea whe e scien ific knowledge is sough o sys ema ically suppo decision-making (Su he land e al., 2004; Hu h and Possingham, 2011). This second go e nance mode can be e med 'scien ific- echnical go e nance’. Shi ing a en ion om knowledge o he ac o s who use and p oduce i , we obse e go e nance modes whe e knowledge p oduce s and decision-make s communica e ac oss sec o s and go e nance le els wi h he aim o finding ways o ad ance sha ed goals (Gunde son and Holling, 2002;P imme , 2011b;P imme and Fu man, 2012;Hauck e al., 2013). Lea ning and commi men a e he co e assump ions in his hi d mode o go e nance ha can be called 'adap i e collabo a i e go e nance’. Finally, because he e is an assump ion ha he ac o s u ilising ecosys ems o economic pu poses end o beha e in ways ha secu e hei own in e es s, a he han hose o he collec i e (Gómez-Bagge hun e al., 2010;Kuma , 2010;Lockie, 2013), ways o dealing wi h such s a egic in e es -based beha iou should be analysed as well. 'Go e ning s a egic beha iou ‘is he e o e he final mode o go e nance we iden i y o u he analysis. Taking hese ou app oaches o go e nance as he basis, we e iewed biodi e si y and en i onmen al conse a ion li e a u e, o in es iga e how he a gumen a ion o ecosys em se ices migh be cap u ed and could be suppo ed by empi ical analyses. By ocusing on a gumen s, we sough o iden i y empi ical e i- dence o ways in which decisions a e jus ified and u ned in o implemen a ion p ac ices, o e en ually p oduce conse a ion e - ec s. We s a ed ou e iew by conduc ing sea ches in Scopus (be ween 10 and 20 Ap il 2012), wi h sea ch e ms: ‘policy’,‘a - gumen *‘and’‘e ec *‘and specified he ou come wi h ‘empi ical’, ‘biodi e si y’,‘conse a ion’o ‘en i onmen *‘and expanded his ou come by including also ‘ he o ic*‘,‘impac ’,o ‘e alua *‘.A e his sys ema ic pa o he in es iga ion, we picked hose a icles ha add essed he opic o go e ning ecosys ems, i.e., na u al en i onmen s o na u al esou ces and epo ed empi ical ana- lyses o policy gene a ing e ec s, paying a en ion o a gumen s. We hen complemen ed hese wi h seminal a icles desc ibing he mode o go e nance o illus a i ely add essing he ways in which a gumen s, policy and ecosys ems a e in in e play. We p io i ised a icles epo ing empi ical analyses. In he ollowing, we epo he obse a ions om hese a icles. 3.2. Hie a chical go e nance We ound ha a numbe o law and in e na ional poli ics s u- dies analyse he ways in which o mula ions in ag eemen s and laws ha e been influenced by highe le el policies, and hese in- cluded pape s dealing wi h di e sions om majo policies. These analyses disclose he ways in which in e na ional en i onmen al decisions ha e been fil e ed o na ional policies, and u he o E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166160 mo e local go e nance le els. E alua ion o he a ifica ion and en o cemen o in e na ional o o he high-le el en i onmen al ag eemen s a he na ional le el (Sand, 2001;Beunen e al., 2009; Mo is, 2011), can be conside ed a model o his ype o hie - a chical implemen a ion analysis. Al hough he in e na ional policy implemen a ion analyses ocus on legal defini ions and he na ion s a es' o mal ake-up o in e na ionally ag eed p inciples in na ional laws, also coun ies' s a egic choices in implemen ing in e na ional en i onmen al policy a e a poin o in e es (Mo is, 2011). Ce ain powe ul sec o s and ac o s play an impo an ole in making na owe na ional in e p e a ions o he ypically e y b oadly defined in- e na ional commi men s (Dekke e al., 2007). The e a e e en cases o s a egic manipula ion in hie a chical go e nance (Mo is, 2011). In some cases, in e na ional policies, aiming o suppo a ansi ion owa ds mo e ambi ious en i onmen al p ac ices, a e channelled owa d al eady exis ing less ambi ious na ional aims (Kanowski e al., 2011). In o he si ua ions, na ional egula ions a e al eady mo e ambi ious han he ones imposed by he in e na- ional policy (Paa ola e al., 2009;Kanowski e al., 2011). I can be in e ed ha he pe sis ence o he ideas ans e ing om he highe le el policy o he lowe go e nance le els implies e ec i eness o he policy and o he unde lying a gumen s. The main obs acles o gene a ing e ec s ela e o na ional o sec o ial in e es s (Gulb andsen, 2003;Dekke e al., 2007;Rajamani, 2007; Mo is, 2011;P imme , 2011a) o e y echnical a gumen a ion (Beunen e al., 2009). Fo example, in hei analysis o Eu opean Union policy implemen a ion a a na ional le el in The Ne he - lands, Beunen e al. (2009) find ha he a gumen a ion a ound he Wa e F amewo k, and he Bi ds and Habi a s Di ec i es con- cen a es on legal echnicali ies, a he han on conse a ion i sel . Also Suma es and Fidélis (2011) asse ha sup ana ional egula- ion, illus a ed by Na u a 2000, aces di ficul ies when EU le el objec i es a e ansla ed o egional and local policies. T ans e o a gumen s in mul ile el go e nance is also somewha associa ed wi h less hie a chical ins i u ional change (A a al, 2010), di usion (Jiménez, 2005) o in e play o policies and a gumen s (Wilson, 2008;Paa ola e al., 2009). 3.3. Scien ific- echnical go e nance We hen iden ified examples o biodi e si y go e nance ha emphasise he cons uc ion o knowledge and suppo sys ems ha maximise e ec i eness in eaching policy goals (Su he land e al., 2004;Hu h and Possingham, 2011). These ypes o analyses usually ocus on a pa icula conse a ion issue, such as c ea ion o a p o ec ed a eas ne wo k (Ma gules and P essey, 2000), o on policy o a pa icula sec o , such as o es y (S u e an e al., 2007). In hese analyses, he policies and scien ific a gumen s a e some imes o iginally assumed o be ope a ionalized and simpli- fied o p agma ic a gumen s o conse a ion, and u he placed in he local con ex . Whe e he scien ific- echnical go e nance is no s aigh o wa d despi e assumed smoo h knowledge flow, a - en ion is paid o p o essional and communica ion ac o s shaping go e nance (Peuhku i and Jokinen 1999;P imme and Ka ppinen, 2010;Val e e al., 2013). An illus a i e example is he analysis o he implemen a ion o a Po uguese o es policy p og amme wi h sus ainabili y goals (Mendes, 2006). He e, go e nance is depic ed as ope a ionaliza- ion, esou cing and communica ion ac i i ies ha can be some- wha con olled by he policy designe ; he ou come (i.e. e ec- i eness o he p og amme) is e en ually measu ed simply as a - o es ed hec a es and numbe s o o es -owne o ganisa ions e- c ui ed. The analysis e eals, howe e , ha a gumen s p eceding he policy gene a e unexpec ed ic ion in implemen a ion and hus impede he o e all e ec i eness o he p og amme, along wi h sho age o knowledge and esou ces. O he empi ical analyses o scien ific- echnical go e nance also ou line he science-based a gumen s embedded in he policies and analyse hem paying a en ion o a gumen s ha ha e eme ged in he p ac ical go e nance si ua ions, abou o example he local condi ions and exis ing p ac ices ha only pa ially allow he in- eg a ion o new knowledge (Wol and P imme , 2006;Kaljonen, 2008;P imme and Ka ppinen, 2010;Val e e al., 2013). These analyses poin o impo an de ia ions om echnically aided planning p ocesses, which can be iden ified and sol ed only by p ac i ione s. Se e al analyses o ope a ional biodi e si y con- se a ion e o s hus highligh he ole o expe s and o he ac o s in o mula ing easible local conse a ion solu ions and ways o in eg a ing many di e en goals as well as sha ing in o ma ion (Kaljonen, 2008;Wol and P imme , 2006;Ka ez and Cas o, 2008; P imme and Ka ppinen, 2010;Ande sson e al., 2012). Al hough many analyses wi h a echnical ocus ake knowledge esou ces o be he main bo leneck o eaching policy goals, hey a e also c i ical o he assump ions o knowledge ans e as jus a simple echnical ask suppo ed by sma in o ma ion managemen (Ji- ménez, 2005;Mendes, 2006;Ka ez and Cas o, 2008). Wi hin his go e nance domain he e is a s and o esea ch on he sys ema ic desc ip ion o unce ain y o models equi ed o assess ou comes o policies, which shows ha he scale misma ch be ween he decision con ex and wha is calcula ed wi h a ailable me hods and da a hinde communica ing findings o policy (Gómez-Bag- ge hun and Ba on, 2013). 3.4. Adap i e collabo a i e go e nance As a nex s ep, we looked o examples o collabo a i e go - e nance app oaches, which a e commonly analysed in he field o sus ainable en i onmen al managemen (Haje and Wagenaa , 2003;Reed, 2008;Sands öm, 2009). These analyses aim a in- eg a ing a ange o a gumen s, bo h analy ically and p agma i- cally and highligh in eg a ion o no ms and s akeholde com- mi men in line wi h wha has amously been e med “collec i e go e nance”(Os om, 1990). The collabo a i e app oaches e- iewed emphasise he impo ance o knowledge accumula ion, collec i e lea ning and sensi i i y o changes, which a e he ideas o adap i e go e nance o social–ecological sys ems (Gunde son and Holling, 2002;C ona and Bodin, 2006). The e iew showed ha hese app oaches do no ake hie - a chical go e nance as a s a ing poin ; hey ac ually posi ion hemsel es by in oducing he concep o “bo om up”go e nance (e.g. F ase e al., 2006;S u e an e al., 2007). While biodi e si y conse a ion e alua ions ocus on conse a ion ou comes and e - ec i eness, he empi ical analyses o collabo a ion and pa icipa- ion do no always assess he conse a ion ou comes a all. In- s ead, hey concen a e dominan ly on sus ainable go e nance ou comes, e.g. he quali y o he decision-making o im- plemen a ion p ocess, and sensi i i y o di e en con ex -specific a gumen s. The ocus is on o e coming conflic s as well as secu - ing legi imacy and lea ning (Paloniemi and Va ho, 2009;Sand- s öm, 2009;Saa ikoski e al., 2012). Gene ally, howe e , b oad a gumen a ion, inclusi e s akeholde pa icipa ion, well o ganised pa icipa o y p ocesses and genuine knowledge sha ing a e con- side ed o con ibu e o posi i e ecological ou comes as well (Reed, 2008;Williams, 2011). In a me a-analysis o 47 pa icipa ion s udies, Newig and F i sch (2009) find ha pa icipa ion, o , e en mo e ambi ious di ec in e ac ion among pa icipan s, gene ally ad ance en i onmen al goals. To combine he oppo uni ies o collabo a i e go e nance and e ec i eness e alua ion, Rausch- maye e al. (2009) p opose bo h aspec s o be e alua ed join ly. The gene al message om collabo a i e adap i e go e nance e- sea ch is one o op imism, and endo semen o i s posi i e e ec s, E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166 161 e en in cases whe e ecological impac s a e no he main a ge o e alua ion. 3.5. Go e ning s a egic beha iou Finally, we paid a en ion o in e es s in a gumen s and go - e nance. While many ac o s pa icipa ing in go e nance ake po- licies as manda es o guidance, some pe cei e hem a he as challenges o e en con es able ba ie s o hei p e e ed ac ion (Oli e , 1991). S a egic campaigning agains conse a ion a gu- men s ypically akes place a he policy o mula ion phase and diminishes as he policy is implemen ed (Ri e a e al., 2009; Hiedanpää and B omley, 2011). Howe e , hose s akeholde s who expe ience economic losses om conse a ion some imes con- inue o a gue agains he policy, pa icula ly i hey a e in a po- si ion whe e hey can domina e he discou ses su ounding he policy implemen a ion (Ri e a e al., 2009;Hiedanpää and B om- ley, 2011;Casho e and Ve insky, 2000). The e iew showed ha biodi e si y policies appea o be in- fluenced by s ong ac o s' in e es s and a gumen s e en in si ua ions ha a e hie a chically well o ganised o echnically s aigh o wa d. Fo example, in e na ional ag eemen s a e in e - p e ed in ways o secu e na ional economic in e es s when im- plemen ed (Gulb andsen, 2003) and biodi e si y policies a e op- e a ionalized wi h na u al esou ce dependen sec o s influencing he p ocess (P imme , 2011b;Newig and F i sch, 2009;Saa ikoski e al., 2012). Also he biodi e si y conse a ion adminis a ion secu es i s manda e and esponsibili ies in si ua ions whe e col- labo a i e adap i e go e nance is he assumed go e nance mode (P imme e al., 2013;Val e e al., 2013). On he o he hand, s a egic app oaches o policy can also be p oac i e s ances, e- defining and aming wha he policy en ails, and ad ancing bio- di e si y as a pa o he economic ac i i y (Casho e and Ve insky, 2000;P imme , 2011a). Go e ning s a egic beha iou is no an explici a ge o many empi ical analyses o go e nance, bu i is o en epo ed as a finding. 3.6. Empi ical me hods o iden i ying a gumen s and analysing go e nance When explo ing empi ical me hods o he analysis o ecosys- em se ices go e nance, we ound ha he s udies mos ly used quali a i e me hods. This is o be expec ed among he s udies ha allow he iden ifica ion o a gumen s in he implemen a ion p o- cess, which we ocused on. Howe e , ou e iew was a ge ed a empi ical analyses o he e ec i eness o biodi e si y and en- i onmen al policy in gene al, which did no ule ou quan i a i e measu emen o policies, ac i i ies, e ec s and ou comes (Mick- wi z, 2003). Hie a chical go e nance analyses dominan ly u ilised quali a- i e documen analysis in gene a ing e idence, howe e some- imes e e ing o lessons om pa icula cases documen ed in mul iple o ma s. Some o he hie a chical analyses de i ed a - gumen s om heo y, and o he s om o he empi ical analyses. The scien ific- echnical analyses add essing go e nance ypically used a mix o documen , ocus-g oup, in e iew and su ey da a, acknowledging a gumen s exp essed in policy documen s, p ac- ical guidelines, ope a ionaliza ion p ocesses and one-on-one communica ion si ua ions. Much o his analysis appea ed o be explo a i e. Those analyses ha wen u he in es ing he e ec s ope a ionally used also quan i a i e analyses o es he p e alence o a gumen s. Empi ical collabo a i e go e nance analyses o en used a b oad ange o mos ly quali a i e me hods o elici ing a - gumen s and e alua ing he e ec s o a policy. In hese analyses he a gumen s o conse a ion ended o be iden ified as a esul o an explo a i e, desc ip i e analysis o , o example, a pa icipa o y p ocess o a ne wo k. The analyses o go e ning s a egic beha iou we e, as men ioned, no always a ge ed a he policies, bu he in e es conflic s became e iden , e.g. in hie - a chical go e nance o adap i e–collabo a i e go e nance ana- lyses. These analyses also based hei e idence on quali a i e da a, usually d awing on mul iple sou ces. Using also media co e age, he mos common sou ces o iden i ying go e ning o s a egic beha iou we e policy documen s and in e iews. 4. A amewo k o analysing go e nance o ecosys em se ices Ou e iew o empi ical analyses o go e nance has ocused on a gumen s used in policy implemen a ion and he ways in which e ec i eness o policies is e alua ed unde di e en go e nance modes. I e eals ha he a en ion o a gumen s and hei e ec s a ies o a la ge ex en . Those analyses p incipally e alua ing e - ec i eness o policy implemen a ion, ocusing on echnical ele- men s and using quan i a i e indica o s, pay less a en ion o he ange o jus ifica ions and ope a ionaliza ion o he policy han he ones analysing s akeholde iews. These findings ba e ele ance o he applica ion and de elopmen o he ecosys em se ice concep , which, i e en ually embedded in go e nance, is expec ed o unc ion as a alue-a icula ing ins i u ion i sel (Va n, 2005). As he ecosys em se ice app oach and esea ch a e expec ed o in oduce new a gumen s o biodi e si y conse a ion and mains eam he unde s anding o sys emic in e dependencies o ecosys ems and humans, i should ake se iously he challenge o unde s anding human beha iou in go e ning ecosys em se ices (Hodgson e al., 2007). The ecosys em se ices model's eedback loop om he benefi s ha people de i e om ecosys em se ices o he biophysical condi ions ha deli e hese se ices, ells li le abou wha decision-making p ocesses ake place o a e used behind his a ow, o in ela ion o o he componen s o he model (Po schin and Haines-Young, 2011;Fig. 1). Go e nance, indeed, also influences ecosys em unc ions, ecosys em se ices as well as benefi s and alues de i ed om he se ices (Spangenbe g e al., 2014). Addi ionally, go e nance p ocesses de i e in o ma ion abou all he componen s depic ed in he cascade model, a he han elying solely on alue in o ma ion. These connec ions be- ween he componen s o he ecosys em se ices and he di e en go e nance modes a e shown in he concep ual amewo k p e- sen ed in Fig. 2. Assuming decisions a e made based on weighing alues and he e alua ion o ade-o s, a decision made a he op o a hie - a chy “ ickles down” o p ac ice, aiming a e en ually influencing he s a us o he ecosys em, o i s biophysical s uc u e (shown as he back-loop in Fig. 2). This is in ui i e when conside ing deci- sions made a e y high le els; e en a a global le el. Howe e , he ecosys em se ice li e a u e highligh s ha decisions a e made a many le els (Kuma , 2010;Hauck e al., 2013). The e is a endency Ecosys em s uc u e Ecosys em alues Scien i ic- echnical go e nance Go e ning s a egic beha io Hie a chical go e nance Adap i e collabo a i e go e nance Ecosys em se ices Ecosys em unc ions Bene i s om ecosys ems Fig. 2. A amewo k o analysing go e nance o ecosys em se ices. E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166162 o add ess go e nmen al decision-making, a he han decisions made by di e en ac o s in he socie y, which migh be due o much emphasis placed on land-use planning ha is o en he e- sponsibili y o public au ho i ies (Ka ei a e al., 2011;Po schin and Haines-Young, 2011;Plan and Ryan, 2013). Howe e , whe he we conside go e nmen al decisions, o p i a e sec o o ganisa ional decisions, some hie a chical sys ems a e gene ally deployed o- wa ds hei implemen a ion (P imme , 2011a). Ou e iew shows ha hose s udies ha ake hie a chical implemen a ion as a s a ing poin ecognise many ac o s shaping he implemen a ion a di e en le els, including hose ha cons ain o dis o hie - a chical implemen a ion. Fo his eason, i is impo an o pay a en ion o he hie a chical mode when analysing ecosys em se ices go e nance, e en when he analysis has a local o o he - wise na ow ocus. Fo hie a chical go e nance o gene a e e ec s in he ecosys- em s uc u e, as is shown in he ecosys em se ices model (see Fig. 1), he p o ision o science-based knowledge is necessa y o in o m managemen . In o he wo ds, scien ific- echnical go e n- ance is needed (Fig. 2). Howe e , hie a chical go e nance can in- o m scien ific- echnical go e nance only wi h gene al a gumen s ha ope a ionalise he goals o he policy, o example by de- ploying a selec ion o policy ins umen s (Wu zel e al., 2013). Fo his eason, scien ific- echnical go e nance mus d aw on u he scien ific a gumen s and de i e in o ma ion abou he biophysical ecosys em s uc u e and p ocess di ec ly (depic ed by a da k a - ow om biophysical s uc u e o scien ific- echnical go e nance in Fig. 2). Addi ionally, scien ific- echnical go e nance influences also ecosys em unc ions o example by con olling wa e flow o adding e ilize s o a field. As he need o science-based in- o ma ion and decision suppo sys ems is commonly endo sed in ecosys em se ices esea ch (Ka ei a e al., 2011;de G oo e al., 2010;Po schin and Haines-Young, 2011), he scien ific- echnical go e nance mode fi s he model and hus needs o be conside ed when analysing go e nance o ecosys em se ices. Ou e iew demons a es addi ionally, ha as long as his analysis is sensi i e o di e en a gumen s, i p oduces impo an findings ha ela e o o he go e nance modes as well. The concep o ecosys em se ices connec s na u e and people. The e o e i is no su ficien o deal wi h echnical a gumen s and ope a ionalise science-based unde s anding o ecosys ems. Adap- i e–collabo a i e go e nance joins ac o s who use science-based knowledge and a gumen s abou ecosys em unc ions and ac o s who unde s and and a gumen o he di e en benefi s ha hu- mans de i e om ecosys ems (Fig. 2). Adap i e–collabo a i e go e nance influences ecosys em unc ions and ecosys em se - ices and also shapes he benefi s ha di e en ac o s can make use o o enjoy. Ecosys em se ice li e a u e acknowledges he need o conside di e en s akeholde s’ iews and knowledge in decision-making p ocesses, and ini ial empi ical analyses e eal he c ucial ole ha unde s anding he di e en ac o s has o secu ing he ele ance o mo e na u al science-d i en analyses (Cowling e al., 2008;Rauschmaye e al., 2009;Menzel and Teng, 2010;P imme and Fu man, 2012;Hauck e al., 2013). These em- pi ical analyses should in eg a e also he di e en ac o s’ igh s o he benefi s ha ecosys em se ices con ibu e o, which ha e been concep ualised ecen ly, pa icula ly o he analysis o eco- sys em se ice paymen s (Lockie, 2013). In any case, he adap i e collabo a i e mode o go e nance me i s he analy ical a en ion o ecosys em se ice esea che s, and should build on ea lie empi ical wo k on biodi e si y and en i onmen al conse a ion go e nance. As benefi a gumen s a e made wi h no ma i e o nume ical e ms, using knowledge abou , o example, mul iple uses o he same ecosys em and weighing hem agains each o he , he in- e es s o di e en ac o s s a o influence go e nance. Go e ning in e es -d i en s a egic beha iou makes use o knowledge and a gumen s abou ecosys em benefi s and alues, and also shapes he ways in which he benefi s a e amed and alues weighed (Fig. 2). Value a gumen s eed back o he decisions ha a e made, o be implemen ed again, h ough a hie a chy. Wi h he assump- ion ha alue a gumen s a e sys ema ically weighed in decision- making, as long as knowledge abou alues exis , he ecosys em se ice li e a u e has pu much emphasis on alua ion and mea- su ing ecosys em se ices in mone a y o o he nume ical uni s (De G oo e al., 2002;Kuma , 2010;Ba eman e al., 2011). While his analysis some imes eaches us new lessons abou wha is alued o how alues ela e o pa icula decision- ac o s, i u ns a en ion away om he ways in which alue a gumen s a e con inuously used and es ed in eal wo ld decision-si ua ions. Go e ning s a egic beha iou akes place in e e y nego ia ion and is conduc ed by go e nmen s as well as o he ac o s. Ou e iew shows how impo an i is o conside his mode o go e nance also when o he modes a e in he ocus. Finally, hie a chical go e nance does no gene a e e ec s only h ough scien ific- echnical go e nance, bu also h ough adap- i e–collabo a i e go e nance and by go e ning s a egic beha- iou , as has been an icipa ed in hose analyses ha highligh he mul ile el-cha ac e o ecosys ems se ice decision-making (Hauck e al., 2013). Assump ions abou mo i a ions and a ion- ali y a e qui e s ong in he ecosys em se ice paymen li e a u e, pe haps, because economic analyses a e based on assump ions abou he mo i a ions o hose ac o s who ha e he igh o manage ecosys ems and use ecosys em se ices (Va n, 2010; Lockie, 2013). Howe e , he in e play be ween hie a chical go - e nance and go e ning s a egic beha iou and in e es s me i s mo e empi ical a en ion, as he e iew demons a es: hie a chical implemen a ion o high-le el commi men s is influenced by in- e es s appea ing a lowe go e nance le els. The di e en go e nance modes should be ecognised also when analysing policy ins umen design and implemen a ion (Schneide and Ing am, 1990;Wu zel e . al., 2013). The s a ing poin o ins umen design is o en hie a chical: he design is a a cen al le el, e.g. a he s a e, and he adminis a ion implemen s i o pa icipa es in i s ope a ionaliza ion (P imme , 2011a;Wu zel e al., 2013). The design and implemen a ion o he ins umen s can be suppo ed wi h scien ific- echnical ools (Cowling e al., 2008;Gómez-Bagge hun and Ba on, 2013), o applied in a colla- bo a i e adap i e ashion (Hauck e al., 2013). Ins umen s can be designed o add ess he s a egic beha iou o ac o s in secu ing hei in e es s, and o balance he di e en in e es s. Paymen s o ecosys em se ices, o example, a e conside ed o balance he di e ing in e es s allowing public demand o ecosys em se ices o mee hei p i a e p o ision (Fe a o and Simpson, 2002;Va n, 2010;Lockie, 2013). To be able o make use o he ange o go - e nance mechanisms, ins umen s ha e de eloped in pa allel, as policy-mixes (Ring and Sch ö e -Schlaack, 2011;Ba on e al., 2014;Ring and Ba on, o hcoming). The analysis o policy-mixes is gene ally sensi i e o di e en go e nance mechanisms, and is he e o e likely o benefi om ou amewo k when add essing ins umen s o ecosys em se ices. Ou e iew demons a es ha he concep ual amewo k would suppo empi ical analysis o biodi e si y and ecosys em se ices go e nance a di e en le els and di ec a en ion o he di e en , pa allel, modes o go e nance. As an example, he Eu - opean Union Na u a 2000 ne wo k implemen a ion illus a i ely alida es he need o analy ical a en ion o he di e en go - e nance modes (Wä zold e al., 2010;Mo is, 2011;Suma es and Fidélis, 2011). A ocus on he hie a chical go e nance mode would pay a en ion o he p o ec ed a ea ne wo k implemen a ion by he na ion s a es and, u he , by he egional and local adminis- a ion, ocusing on legal and adminis a i e a gumen s. A ocus on E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166 163 scien ific- echnical go e nance would add ess he da a and knowledge esou ces applied in he implemen a ion, paying a - en ion o he scien ific a gumen s used o jus i y and ca y h ough es ablishing he Na u a 2000 p o ec ed a eas. Focusing on an adap i e collabo a i e mode o go e nance, a en ion would be paid o di e en ac o s exchanging in o ma ion and iews on he a eas o be assigned and hei di e en uses. A ange o di e en a gumen s would be used in his kind o delibe a ion, o example when de ising he Na u a 2000 managemen plans (Wä zold e al., 2010). Focusing on go e ning s a egic beha iou , a en ion would be on o he in e es s and land-uses conflic ing wi h he Na u a 2000 p o ec ed a eas, elying on a gumen s o di e en benefi s and alues. Fo example when new in as uc u e is de- eloped, in e es s a e weighed and s a egic beha iou can be go e ned h ough nego ia ions, pe mi ing and possibly compen- sa ion (Suma es and Fidélis, 2011). Go e ning s a egic beha iou akes place also a he in e na ional le el, when he EU goals a e nego ia ed and ope a ionalised o na ional le el (Mo is, 2011). The simple example demons a es he need o conside di e en modes o go e nance, e en i analy ical a en ion is ocused on a pa icula issue o policy implemen a ion. Using he app oach o ame he analysis o much b oade ecosys em se ice policy ha acknowledges complexi y and mul- iple benefi s (e.g., EC, 2011) would sensi ise he analys o he modes o go e nance ha a e assumed and obse ed. As we ge uned o conside di e en modes o ecosys em se ices go e n- ance, we will be in a posi ion o iden i y he po en ial eedbacks be ween all he o he componen s o he ecosys em se ices model, because o he in e ac ion and o e lap o he di e en go e nance modes and policy-mixes. A sys ema ic app oach o analysing go e nance allows iden i ying and disen angling he ange o a gumen s used in u ning policies in o p ac ice in ways ha eflec di e en modes go e nance. 5. Conclusions As biodi e si y conse a ion a gumen s ha e no been e ec i e enough in changing human beha iou , he expec a ion is ha u ili a ian a gumen s abou alues and benefi s de i ed om ecosys em se ices migh do so, oge he wi h scien ific a gu- men s abou ecosys em p ocesses and unc ions as well as he unde lying biodi e si y. Thus i is impo an o analyse wha condi ions he e ec i eness o such a gumen s. To unde s and his, we need o analyse go e nance. This en ails iden i ying how he a gumen s a e assumed o p oduce he desi ed biodi e si y conse a ion ou comes in he p ac ice o policy implemen a ion, and analysing his p ac ice empi ically. In his pape , we ha e se ou he basis o such an analysis, by e iewing empi ical s udies o policy implemen a ion, and by fi - ing he iden ified go e nance modes o a well-es ablished con- cep ual model o ecosys em se ices, he cascade model. By o- cusing on empi ical li e a u e ha pays a en ion o a gumen s in he implemen a ion o biodi e si y and en i onmen al conse a- ion policies, we demons a e how hie a chical, scien ific- echnical and adap i e go e nance as well as go e ning s a egic beha iou in e ac . The de eloped concep ual amewo k p o ides a s uc u e o empi ical analysis o ecosys em se ices go e nance, which akes in o accoun he people and o ganisa ions making decisions, and, pa icula ly, he di e en a gumen s ha a e used when im- plemen ing policies. The amewo k is mean o enable holis ic ecosys em se ice analyses and, u he , o suppo policies in gene a ing conse a ion and sus ainabili y impac . Acknowledgemen s The esea ch ha his a icle builds on has been unded by he Eu opean Union FP7 p ojec s BESAFE (G an 282743) and Open- NESS (G an 308428). The au ho s wish o hank Ee a Fu man, Ul G andin, Lasse Lo , Ca s en Mann, Be nd Hansjü gens and Leon B aa who ha e p o ided ideas and commen s a di e en s ages o de eloping his a icle. We hank also he wo help ul e iewe s. Re e ences Andam, K.S., Fe a o, P.J., P a , A., Sanchez-Azo ei a, G.A., Robalino, J.A., 2008. Measu ing he e ec i eness o p o ec ed a ea ne wo ks in educing de o - es a ion. P oc. Na l. Acad. Sci. USA 105, 16089–16094. A a al, E., 2010. Re o m o wa e ins i u ions: e iew o e idences and in e na ional expe iences. Wa e Policy 12, 8–22. Ande sson, I., Pe e sson, M., Ja sjo, J., 2012. Impac o he Eu opean Wa e F ame- wo k Di ec i e on local-le el wa e managemen : case s udy Oxunda Ca ch- men . Sweden Land Use Policy 29 (1), 73–82. Ba on, D.N., Ring, I., Rusch, G., B ouwe , R., G ieg-G an, M., P imme , E., May, P., San os, R., Lindhjem, H., Sch ö e -Schlaack, C., Lienhoop, N., Similä, J., An unes, P., Caixe a And ade, D., Rome io, A., Chacón-Cascan e, A., DeCle ck, F., Tings ad, M., Si e sen, K., 2014. Guidelines o mul i-scale policy mix assessmen s POLICYMIX Technical B ie 12. Ba eman, I.J., Ha wood, A.R., Mace, G.M., Wa son, R.T., Abson, D.J., And ews, B., Binne , A., C owe, A., Day, B.H., Dugdale, S., Fezzi, C., Foden, j, Hadley, D., Haines-Young, R., Hulme, M., Kon oleon, A., Lo e , A.A., Munday, P., Pascual, U., Pa e son, J., Pe ino, G., Sen, A., Si iwa dena, G., an Soes , D., Te mansen, M., 2013. B inging ecosys em se ices in o economic decision-making: land use in he Uni ed Kingdom. Science 341 (6141), 45–50. Ba eman, I.J., Mace, G.M., Fezzi, C., A kinson, G., Tu ne , K., 2011. Economic analysis o ecosys em se ice assessmen s. En i on. Resou . Econ., 177–218. Beunen, R., an de Knaap, W.G.M., Biesb oek, R.G., 2009. Implemen a ion and In- eg a ion o EU En i onmen al Di ec i es. Expe iences om The Ne he lands. En i on. Policy Go . 19, 57–69. Buijs, A.E., 2009. Public suppo o i e es o a ion: A mixed-me hod s udy in o local esiden s’suppo o and aming o i e managemen and ecological es o a ion in he Du ch floodplains. J. En i on. Manag. 90, 2680–2689. Chan, K.M.A., Sa e field, T., Golds ein, J., 2012. Re hinking ecosys em se ices o be e add ess and na iga e cul u al alues. Ecol. Econ. 74, 8–18. Ca dinale, B.J., Du y, J.E., Gonzalez, A., Hoope , D.U., Pe ings, C., Venail, P., Na wani, A., Mace, G.M., Tilman, D., Wa dle, A., Kinzig, D., Daily, A.P., Lo eau, G.C., G ace, M., La igaude ie, J.B., S i as a a, A., Naeem, D.S., 2012. Biodi e si y loss and i s impac on humani y. Na u e 486, 59–67. Casho e, B., Ve insky, I., 2000. Policy ne wo ks and fi m beha iou s: go e nance sys ems and fi m eponses o ex e nal demands o sus ainable o es Man- agemen . Policy Sci. 33, 1–30. Ch is ie, M., Hanley, N., Wa en, J., Mu phy, K., W igh , R., Hyde, T., 2006. Valuing he di e si y o biodi e si y. Ecol. Econ. 58 (2), 304–317. Co nell, S., 2011. The Rise and Rise o Ecosys em Se ices: Is “ alue” he bes b idging concep be ween socie y and he na u al wo ld? P oc. En i on. Sci. 6, 88–95. Cos anza, R., d’A ge, R., de G oo , R.S., Fa be , S., G asso, M., Hannon, B., Limbu g, K., Naeem, S., O’Neill, R.V., Pa uelo, J., Raskin, R.G., Su on, P., an den Bel , M., 1997. The alue o he wo ld’s ecosys em se ices and na u al capi al. Na u e 387, 253–260. Cowling, R.M., Egoh, B., Knigh , A.T., O’Fa ell, P.J., Reye s, B., Rouge , M., Roux, D.J., Welz, A., Wilhelm-Rechman, A., 2008. An ope a ional model o mains eaming ecosys em se ices o implemen a ion. P oc. Na l. Acad. Sci. 105 (28), 9483–9488. C ona, B., Bodin, Ö., 2006. Wha you know is who you know? Communica ion pa e ns among esou ce use s as a p e equisi e o co-managemen . Ecol. Soc. 11 (2), 7, URL oh p://www.ecologyandsocie y.o g/ ol11/iss2/a 7/4. Daily, G.C., 1997. Na u e’s Se ices. Island P ess, Washing on DC. De G oo , R.S., Wilson, M.A., Boumans, R.M.J., 2002. A ypology o he classifica ion, desc ip ion and alua ion o ecosys em unc ions, goods and se ices. Ecol. Econ. 41, 393–408. De G oo , R.S., Alkemade, R., B aa , L., Hein, L., Willemen, L., 2010. Challenges in in eg a ing he concep o ecosys em se ices and alues in landscape planning, managemen and decision making. Ecol. Complex. 7, 260–272. Dekke , M., Tu nhou , E., Bauwens, B.M.S.D.L., e al., 2007. In e p e a ion and im- plemen a ion o Ecosys em Managemen in in e na ional and na ional o es policy. Fo es Policy Econ. 9, 546–557. EC, 2011. Communica ion om he commission o he Eu opean Pa liamen , he council, he economic and social commi ee and he commi ee o he egions: Ou li e insu ance, ou na u al capi al: an EU biodi e si y s a egy o 2020. COM (2011) 244. Fe a o, P.J., Simpson, R.D., 2002. Cos -E ec . Conse . Paym. Land Econ. 78, 339–353. Fische , A., Young, J.C., 2007. Unde s anding men al cons uc s o biodi e si y: implica ions o biodi e si y managemen and conse a ion. Biol. Conse . 136, E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166164 271–282. F ase , E.D.G., Dougill, A.D., Mabee, W.E., e al., 2006. Bo om up and op down: analysis o pa icipa o y p ocesses o sus ainabili y indica o iden ifica ion as a pa hway o communi y empowe men and sus ainable en i onmen al man- agemen . J. En i on. Manag. 78, 114–127. Gómez-Bagge hun, E., de G oo , R., Lomas, P.L., Mon es, C., 2010. The his o y o ecosys em se ices in economic heo y and p ac ice: om ea ly no ions o ma ke s and paymen schemes. Ecol. Econ. 69, 1209–1218. Gómez-Bagge hun, E., Ba on, D.N., 2013. Classi ying and aluing ecosys em se - ices o u ban planning. Ecol. Econ. 86, 235–245. Gulb andsen, L.H., 2003. The e ol ing o es egime and domes ic ac o s: s a egic o no ma i e adap a ion? En i on. Poli . 12, 95–114. Gunde son, L.H., Holling, C.S., 2002. Resilience and adap i e cycles. Pana chy, 25–62. Haines-Young, R., Po schin, M., 2014. The ecosys em app oach as a amewo k o unde s anding knowledge u ilisa ion. En i on. Plan. C: Go . Policy 32 (2), 301–319. Haje , M., Wagenaa , H. (Eds.), 2003. Delibe a i e Policy Analysis: Unde s anding Go e nance in he Ne wo k Socie y. Camb idge Uni e si y P ess. Hanski, I., 2000. Ex inc ion deb and species c edi in bo eal o es s: modelling consequences o di e en app oaches o biodi e si y conse a ion. Ann. Zool. Fennici 37, 271–280. Hasle , J.R., Be y, P.A., Bela, G., Jongman, R.H.G., Pa aki, G., Samways, M.J., Zobel, M., 2010. Changing conse a ion s a egies in Eu ope: a amewo k in eg a ing ecosys em se ices and dynamics. Biodi e s. Conse . 19, 2963–2977. Hauck, J., Gö g, C., Va jopu o, R., Ra amäki, O., Jax, K., 2013. Benefi s and limi a ions o he ecosys em se ices concep in en i onmen al policy and decision mak- ing: some s akeholde pe spec i es. En i on. Sci. Policy 25, 13–21. Hiedanpää, J., B omley, D.W., 2011. The ha moniza ion game: easons and ules in Eu opean biodi e si y policy. En i on. Policy Go . 21, 99–111. Hodgson, S.M., Mal by, L., Pae zold, A., Phillips, D., 2007. Ge ing he measu e o na u e: ecosys em se ices as a way o unde s and en i onmen and socie y. In e discip. Sci. Re . 32, 249–262. Hu h, N., Possingham, H.P., 2011. Basic ecological heo y can in o m habi a e- s o a ion o woodland bi ds. J. Appl. Ecol. 48, 293–300. Jiménez, O., 2005. Inno a ion-o ien ed en i onmen al egula ions: Di ec e sus indi ec egula ions. An empi ical analysis o small and medium-sized en- e p ises in Chile. En i on. Plan. A 37, 723–750. Kaljonen, M., 2008. Co-cons uc ion o agency and en i onmen al managemen . The case o ag i-en i onmen al policy implemen a ion a Finnish a ms. J. Ru al S ud. 22, 205–216. Kanowski, P.J., McDe mo , C.L., Casho e, B.W., 2011. Implemen ing REDDþ: lessons om analysis o o es go e nance. En i on. Sci. Policy 14, 111–117. Na u al Capi al Theo y and P ac ice o Mapping Ecosys em Se ices. In: Ka ei a, P., Tallis, H., Ricke s, T.H., Daily, G.C., Polasky, S. (Eds.), Ox o d Uni e si y P ess, New Yo k. Ka ez, J., Cas o, M., 2008. In o ma ion in o ac ion: biodi e si y da a ou each and municipal land conse a ion. J. Am. Plan. Assoc. 74, 467–480. Founda ions, The Economics o Ecosys ems and Biodi e si y: Ecological and Eco- nomic Founda ions. In: Kuma , P. (Ed.), 2010. Ea hscan, London. Lau ans, Y., Ranko ic, A., Billé, R., Pi a d, R., Me me , L., 2013. Use o ecosys em se ices economic alua ion o decision making: ques ioning a li e a u e blindspo . J. En i on. Manag. 119, 209–219. Laycock, H., Mo an, D., Sma , J., e al., 2009. E alua ing he cos ‐e ec i eness o conse a ion: The UK Biodi e si y Ac ion Plan. Biol. Conse . 142, 3120–3127. Liu, S., Cos anza, R., Fa be , S., T oy, A., 2010. Valuing ecosys em se ices. Ann. N.Y. Acad. Sci. 1185, 54–78. Lockie, S., 2013. Ma ke ins umen s, ecosys em se ices, and p ope y igh s: as- sump ions and condi ions o sus ained social and ecological benefi s. Land Use Policy 31, 90–98. MA, 2005. Millennium ecosys em assessmen , Ecosys ems and Human Well-being: Syn hesis. Island P ess, Washing on DC, p. 137. Mace, G.M., No is, K., Fi e , A.H., 2014. Biodi e si y and ecosys em se ices: a mul ilaye ed ela ionship. T ends Ecol. E ol. 27 (1), 19–26. Ma gules, C.R., P essey, R.L., 2000. Sys ema ic conse a ion planning. Na u e 405 (11), 243–253. Mendes, A., 2006. Implemen a ion analysis o o es p og ammes: some heo e ical no es and an example. Fo es Policy Econ. 8, 512–528. Menzel, S., Teng, J., 2010. Ecosys em se ices as a s akeholde -d i en concep o conse a ion sciences. Conse . Biol. 24, 907–909. Mickwi z, P., 2003. A amewo k o e alua ing en i onmen al policy ins umen s: con ex and key concep s. E alua ion 9, 415–436. Mo is, R.K.A., 2011. The applica ion o he Habi a s Di ec i e in he UK: Compliance o gold pla ing? Land Use Policy 28, 361–369. Mönkkönen, M., Reunanen, P., Ko iaho, J.S., Juu inen, A., Tikkanen, O.-P., Kouki, J., 2011. Cos -e ec i e s a egies o conse e bo eal o es biodi e si y and long- e m landscape-le el main enance o habi a s. Eu . J. Fo es Res. 130 (5), 717–727. Newig, J., F i sch, O., 2009. En i onmen al go e nance: pa icipa o y, mul i-le el- and e ec i e? En i on. Policy Go . 19, 197–214. Nie, M., 2003. D i e s o na u al esou ce-based poli ical conflic . Policy Sci. 36, 307–341. No on, B., 2005. Sus ainabili y: A Philosophy o Adap i e Ecosys em Managemen . The Uni e si y o Chicago P ess, p. 608. Oli e , C., 1991. S a egic esponses o ins i u ional p ocesses. Acad. Manag. Re . 16, 145–179. Os om, E., 1990. Go e ning he Commons: The E olu ion o Ins i u ions o Col- lec i e Ac ion. Camb idge Uni e si y P ess, Camb idge, p. 280p. Paa ola, J., Gouldson, A., Klu ánko á-O a ská, T., 2009. In e play o ac o s, scales, amewo ks and egimes in he go e nance o biodi e si y. E i on. Policy Go ., 19; , pp. 148–158. Paloniemi., R., Va ho, V., 2009. Changing ecological and cul u al s a es and p e- e ences o na u e conse a ion policy: he case o na u e alues ade in Sou h- Wes e n Finland. J. Ru al S ud. 25, 87–97. Peuhku i, T., Jokinen, P., 1999. The ole o knowledge and spa ial con ex s in bio- di e si y policies. A sociological pe spec i e. Biodi e s. Conse . 8, 133–147. Plan , R., Ryan, P., 2013. Ecosys em se ices as a p ac icable concep o na u al esou ce managemen : some lessons om Aus alia. In . J. Biodi e s. Sci. Eco- sys . Se . Manag. 9 (1), 44–53. Po schin, M., 2015. Defining and measu ing ecosys em se ices. In: Po schin, M., Haines-Young, R., Fish, R., Tu ne , R.K. (Eds.), Rou ledge Handbook o Ecosys em Se ices. Rou ledge, London and New Yo k. Po schin, M., Haines-Young, R., 2011. Ecosys em se ices: explo ing a geog aphical pe spec i e. P og. Phys. Geog . 35 (5), 575–594. P imme , E., Ka ppinen, H., 2010. P o essional judgmen in non-indus ial p i a e o es y: o es e a i udes and social no ms influencing biodi e si y con- se a ion. Fo es Policy Econ. 12 (2), 136–146. P imme , E., 2011a. Analysis o ins i u ional adap a ion: in eg a ion o biodi e si y conse a ion in o o es y. J. Clean. P od. 19, 1822–1832. P imme , E., 2011b. Policy, p ojec and ope a ional ne wo ks: channels and con- dui s o lea ning in o es biodi e si y conse a ion. Fo es Policy Econ. 13, 132–142. P imme , E., Fu man, E., 2012. Ope a ionalising ecosys em se ice app oaches o go e nance: do measu ing, mapping and aluing in eg a e sec o -specific knowledge sys ems? Ecosys . Se . 1, 85–92. P imme , E., Paloniemi, R., Similä, J., Ba on, D.N., 2013. E olu ion in Finland’s o es biodi e si y conse a ion paymen s and he ins i u ional cons ain s on es- ablishing new policy. Soc. Na . Resou . 26 (10), 1137–1154. Rajamani, L., 2007. The igh o en i onmen al p o ec ion in India: Many a slip be ween he cup and he lip?. Re . Eu . Communi y In . En i on. Law, 16; , pp. 274–286. Rands, M.R.W., Adams, W.M., Bennun, L., Bu cha d, S.H.M., Clemen s, A., Coomes, D., En wis le, A., Hodge, I., Kapos, V., Scha lemann, J.P.W., Su he land, W.J., Vi a, B., 2010. Biodi e si y conse a ion: challenges beyond 2010. Science 329, 1298–1303. Ra amäki, O., Jokinen, P., Sø ensen, P.B., B eeze, T., Po s, S., 2015. A mul ile el analysis on pollina ion- ela ed policies. Ecosys . Se ., in p ess. Rauschmaye , F., Be ghö e , A., Omann, I., Zikos, D., 2009. Examining p ocesses o / and ou comes? –e alua ion concep s in Eu opean go e nance o na u al e- sou ces. En i on. Policy Go . 19 (3), 159–173. Reed, M.S., 2008. S akeholde pa icipa ion o en i onmen al managemen : a li - e a u e e iew. Biol. Conse . 141, 2417–2431. Ring, I., Ba on, D.N., 2015. Economic ins umen s in policy mixes o biodi e si y conse a ion and ecosys em go e nance. In: Ma inez-Alie J. and R. Mu adian (Ed.), Handbook o Ecological Economics. Chel enham, Edwa d Elga , (Fo hcoming). Ring, I., Sch ö e -Schlaack, C., 2011. Jus i ying and assessing policy mixes o biodi e si y and ecosys em go e nance. In: Ring, I., Sch ö e -Schlaack, C., (Ed.), Ins umen Mixes o Biodi e si y Policies. POLICYMIX Repo , Issue No. 2/2011. Ri e a, J., Oe zel, J., deLeon, P., e al., 2009. Business esponses o en i onmen al and social p o ec ion policies: owa d a amewo k o analysis. Policy Sci. 42, 3–32. Rod iguez, A.S., Andelman, S.J., Baka , M.I., e al., 2004. E ec i eness o he global p o ec ed a ea ne wo k in ep esen ing species di e si y. Na u e 428, 640–643. Saa ikoski, H., Åke man, M., P imme , E., 2012. The challenge o go e nance in egional o es planning: an analysis o pa icipa o y o es p og am p ocesses in Finland. Soc. Na . Resou . 25, 667–682. Sago , M., 1996. On he alue o endange ed and o he species. En i on. Manag. 20 (6), 897–911. Sago , M., 2011. The quan ifica ion and alua ion o ecosys em se ices. Ecol. Econ. 70, 497–502. Sand, P.H., 2001. A cen u y o g een lessons: he con ibu ion o na u e conse a- ion egimes o global go e nance. In . En i on. Ag eem.: Poli . Law Econ. 1, 33–72. Sands öm, C., 2009. Ins i u ional dimensions o co-managemen : pa icipa ion, powe , and p ocess’. Soci. Na . Resou . 22, 230–244. Schneide , A., Ing am, H., 1990. Beha io al assump ions o policy ools. J. Poli . 52, 510–529. Spash, C.L., Va n, A., 2006. T ans e ing en i onmen al alue es ima es: issues and al e na i es. Ecol. Econ. 60, 379–388. Spash, C.L., 2007. Delibe a i e mone a y alua ion (DMV): issues in combining economic and poli ical p ocesses o alue en i onmen al change. Ecol. Econ. 63, 690–699. Spangenbe g, J.H., Se ele, J., 2010. P ecisely inco ec ? Mone ising he alue o ecosys em se ices. Ecol. Complex. 7, 327–337. Spangenbe g, J.H., on Haa en, C., Se ele, J., 2014. The ecosys em se ice cascade: u he de eloping he me apho . In eg a ing socie al p ocesses o accom- moda e social p ocesses and planning, and he case o bioene gy. Ecol. Econ. 104 (2014), 22–32. S u e an , B.R., Fall, A., Kneeshaw, D.D, Simon, N.P.P., Papaik, M.J., Be ninge , K., Doyon, F., Mo gan, D.G., Messie , C., 2007. A oolki modeling app oach o sus ainable o es managemen planning: achie ing balance be ween science E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166 165 and local needs. Ecol. Soc. 12, 7 oh p://www.ecologyandsocie y.o g/ ol12/ iss2/a 7/4. Suma es, D., Fidélis, T., 2011. Na u a 2000 and he na a i e na u e o na u e: a case o c i ical discou se analysis. J. In eg . En i on. Sci. 8, 53–68. Su he land, W.J., Pullin, A.S., Dolman, P.M., Knigh , T.M., 2004. The need o e i- dence-based conse a ion. T ends Ecol. E ol. 19 (6), 35–38. Tu npenny, J., Russel, D., Jo dan, A., 2014. The challenge o embedding an ecosys- ems se ices app oach: pa e ns o knowledge u ilisa ion in public policy ap- p aisal. En i on. Plan. C: Go . Policy 32 (2), 247–262. Val e, H., Åke man, M., Kaljonen, M., 2013. You only s a filling in he boxes’: na u al esou ce managemen and he poli ics o plan-abili y. En i on. Plan. A 45, 2084–2099. Van Oudenho en, A.P.E., Pe z, K., Alkemade, R., Hein, L., de G oo , R.S., 2012. F a- mewo k o sys ema ic indica o selec ion o assess e ec s o land managemen on ecosys em se ices. Ecol. Indic. 21, 110–122. Va n, A., 2005. Ra ionali y, ins i u ions and en i onmen al policy. Ecol. Econ. 55, 203–217. Va n, A., 2009. An ins i u ional analysis o me hods o en i onmen al app aisal. Ecol. Econ. 68, 2207–2215. Va n, A., 2010. An ins i u ional analysis o paymen s o en i onmen al se ices. Ecol. Econ. 69, 1245–1252. Vihe aa a, P., Kumpula, T., Ruokolainen, A., Tanskanen, A., Bu kha d, B., 2012. The use o de ailed bio ope da a o linking biodi e si y wi h ecosys em se ices in Finland. In . J. Biodi e s. Sci. Ecosys . Se . Manag. 8 (1–2), 169–185. Wä zold, F., Mewes, M., Van Apeldoo n, R., e al., 2010. Cos -e ec i eness o managing Na u a 2000 si es: an explo a o y s udy o Finland, Ge many, he Ne he lands and Poland. Biodi e s. Conse . 19, 2053–2069. Williams, B.K., 2011. Adap i e managemen o na u al esou ces – amewo k and issues. J. En i on. Manag. 92, 1346–1353. Wilson, J., 2008. Ins i u ional in e play and e ec i eness: assessing e o s o con- se e wes e n hemisphe e sho ebi ds. In . En i on. Ag eem.-Poli . Law Econ. 8, 207–226. Wol , S.A., P imme , E., 2006. Be ween incen i es and ac ion: A pilo s udy o biodi e si y conse a ion compe encies o mul i unc ional o es managemen in Finland. Soci. Na . Resou . 19 (9), 845–861. Wu zel, R., Zi o, A.R., Jo dan, A.J., 2013. En i onmen al Go e nance in Eu ope: A Compa a i e Analysis o he Use o New En i onmen al Policy Ins umen s. Edwa d Elga Publishing, Chel enham. Young, O.R., 2002. The Ins i u ional Dimensions o En i onmen al Change: Fi , In- e play, and Scale. The MIT P ess, Camb idge, p. 221. UN, 1992. Rio de Janei o: Uni ed Na ions, T ea y Se ies No. 30619. E. P imme e al. / Ecosys em Se ices 16 (2015) 158–166166