Forest Loss in Protected Areas and Intact Forest Landscapes: A Global Analysis

RESEARCH ARTICLE Fo es Loss in P o ec ed A eas and In ac Fo es Landscapes: A Global Analysis Ma ias Heino 1 , Ma i Kummu 1 *, Ma ika Makkonen 2 , Ma k Mulligan 3 , Pe e H. Ve bu g 4 , Mika Jala a 1 , Timo A. Räsänen 1 1Wa e and De elopmen Resea ch G oup, Aal o Uni e si y, Tie o ie 1E, 02150, Espoo, Finland, 2Na u al Resou ces Ins i u e Finland (Luke), Jokiniemenkuja 1, 01301, Van aa, Finland, 3Depa men o Geog aphy, King's College London, S and, London, WC2R 2LS, Uni ed Kingdom, 4En i onmen al Geog aphy G oup, VU Uni e si y Ams e dam, de Boelelaan 1087, 1081 HV, Ams e dam, he Ne he lands *[email p o ec ed] Abs ac In spi e o he high impo ance o o es s, global o es loss has emained ala mingly high du - ing he las decades. Fo es loss a a global scale has been un eiled wi h inc easingly ine spa ial esolu ion, bu he o es ex en and loss in p o ec ed a eas (PAs) and in la ge in ac o es landscapes (IFLs) ha e no so a been sys ema ically assessed. Mo eo e , he impac o p o ec ion on p ese ing he IFLs is no well unde s ood. In his s udy we conduc ed a con- sis en assessmen o he global o es loss in PAs and IFLs o e he pe iod 2000–2012. We used ecen ly published global emo e sensing based spa ial o es co e change da a, being a uni o m and consis en da ase o e space and ime, oge he wi h global da ase s on PAs’ and IFLs’loca ions. Ou analyses e ealed ha on a global scale 3% o he p o ec ed o es , 2.5% o he in ac o es , and 1.5% o he p o ec ed in ac o es we e los du ing he s udy pe iod. These o es loss a es a e ela i ely high compa ed o global o al o es loss o 5% o he same ime pe iod. The a ia ion in o es losses and in p o ec ion e ec was la ge among geog aphical egions and coun ies. In some egions he loss in p o ec ed o es s exceeded 5% (e.g. in Aus alia and Oceania, and No h Ame ica) and he ela i e o es loss was highe inside p o ec ed a eas han ou side hose a eas (e.g. in Mongolia and pa s o A ica, Cen al Asia, and Eu ope). A he same ime, p o ec ion was ound o p e en o es loss in se e al coun ies (e.g. in Sou h Ame ica and Sou heas Asia). Globally, high a ea- weigh ed o es loss a es o p o ec ed and in ac o es s we e associa ed wi h high g oss domes ic p oduc and in he case o p o ec ed o es s also wi h high p opo ions o ag icul u al land. Ou indings ein o ce he need o imp o ed unde s anding o he easons o he high o es losses in PAs and IFLs and s a egies o p e en u he losses. In oduc ion Fo es s play a c ucial ole in sus aining li e on ea h. They main ain ecological di e si y, egu- la e clima e, s o e ca bon, p o ec soil and wa e and p o ide esou ces and li elihoods o he wo ld’s popula ion [1–4]. Despi e he inc easing awa eness o he impo ance o hese ecosys- ems, global de o es a ion a es ha e emained ala mingly high o e he pas decades [2]. PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 1/21 OPEN ACCESS Ci a ion: Heino M, Kummu M, Makkonen M, Mulligan M, Ve bu g PH, Jala a M, e al. (2015) Fo es Loss in P o ec ed A eas and In ac Fo es Landscapes: A Global Analysis. PLoS ONE 10(10): e0138918. doi:10.1371/jou nal.pone.0138918 Edi o : Madhu Anand, Uni e si y o Guelph, CANADA Recei ed: Ma ch 16, 2015 Accep ed: Sep embe 4, 2015 Published: Oc obe 14, 2015 Copy igh : © 2015 Heino e al. This is an open access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License, which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal au ho and sou ce a e c edi ed. Da a A ailabili y S a emen : All ele an da a a e wi hin he pape and i s Suppo ing In o ma ion iles. Funding: The wo k was unded by Maa- ja esi ekniikan uki y. In addi ion, MK was unded by he Academy o Finland p ojec SCART (g an no. 267463) and MMa by he Academy o Finland p ojec G een Economy and Policies (g an no. 257919). PHV hanks he ERC g an ag eemen n . 311819 (GLOLAND) and he FP7 p ojec LUC4C o suppo . The unde s had no ole in s udy design, da a collec ion and analysis, decision o publish, o p epa a ion o he manusc ip . In yea 2010 o es co e ed a ound 40 million km 2 o 31% o he global land a ea acco ding o coun y epo s [2]. Es ima es o global o es loss a es wi hin he pas decade a y be ween 130,000 km 2 /y [2] and 177,000 km 2 /y [5]. A he same ime, some e o es a ion and na u al eg ow h ha e occu ed, leading o ne o es loss epo s anging be ween 52,000 km 2 /y and 115,000 km 2 /y , espec i ely. Al hough o es loss is s ill ema kably high, i has shown some signs o decline: FAO [2] epo s ha du ing he 1990s, he o es loss a e was 160,000 km 2 /y ; whe eas be ween 2000–2010, he a e was 130,000 km 2 /y . Acco ding o FAO [2] he opics we e he only domain whe e he a e o o es loss inc eased in he i s decade o he 21 s cen- u y compa ed o 1990s: de o es a ion inc eased in he opics by 2,101 km 2 /y on a e age ac oss he decade. De o es a ion in he opics accoun ed o 32% o global o es loss wi hin he pe iod o 2000–2012 [5]. Howe e , he e a e also posi i e signs in he opics: he a e o o es loss in he B azilian Amazon has declined in ecen yea s [6,7]. The main d i e s o global de o es a ion a e linked o expansion o ag icul u e, wood ex ac- ion, in as uc u e ex ension, popula ion g ow h, and expansion o ag icul u e [8–13]. The dom- inan d i e s, howe e , a y among he egions [8–13]. In addi ion o ag icul u e and popula ion g ow h, a me a-analysis o 117 de o es a ion s udies by Fe e i-Gallon and Busch [9]sugges s ha de o es a ion is gene ally lowe in high, s eep and we a eas while i is highe in a eas whe e o es s a e close o oads and u ban a eas. De o es a ion has also shi ed om a dominan ly s a e ini ia ed o an en e p ise d i en p ocess in he opics be ween 1970 and 2000 [14]. Ala ming de o es a ion a es combined wi h he inc easing awa eness o he impo ance o o - es s ha e esul ed in exponen ial g ow h o he wo ld’s p o ec ed a eas (PA) o e he pas decades [15–17]. Schmi e al. [18] es ima e he global o es co e using ea h obse a ion sa elli e da a om MODIS2005 and he ex en o p o ec ed o es using he Wo ld Da abase o P o ec ed A eas (WDPA) o he yea 2008. They ind ha 7.7% o global o es co e ell wi hin IUCN’s ou s ic es p o ec ion ca ego ies (I-IV) and 13.5% wi hin IUCN’s all six p o ec ion ca ego ies (I-VI) (IUCN p o ec ion ca ego ies a y om s ic ly p o ec ed a eas (I) o p o ec ed a eas wi h sus ain- able esou ce use (VI); o mo e de ailed ca ego y de ini ion see [19]).Schmi e al.[18] u he conclude ha o es p o ec ion a ied g ea ly be ween di e en egions and o es ypes, and ha o es p o ec ion in p io i y a eas, such as biodi e si y ho spo s, was insu icien . Conside able e o s o p o ec ion a e a ge ed o he p ima y o es s and la ge in ac o es landscapes (IFLs, i.e. unb oken expanse o na u al ecosys ems). These o es a eas play c ucial oles in sus aining ecological di e si y [2,20]. FAO [2] es ima es ha p ima y o es s accoun ed 14 million km 2 (36% o he global o al o es s) in yea 2010, ha ing dec eased ala ming 400,000 km 2 o e he pe iod o 2000–2010 (annual a e 0.4%). Po apo e al. [20] epo ha he ex en o IFL is 13.1 million km 2 . Vas majo i y o he IFLs a e ound ei he in dense T opi- cal and Sub-T opical o es s (45% o wo ld o al) o in Bo eal Fo es s (44%). The lowes p o- po ion o IFL was ound in Tempe a e B oadlea and Mixed Fo es s. Po apo e al. [20] u he ind ha 18.9% o IFLs a e unde p o ec ion o IUCN p o ec ion ca ego ies I-VI and only 9.7% o IFLs is s ic ly p o ec ed unde IUCN p o ec ion ca ego ies I-III. The p o ec ion e ec o PAs is, howe e , ques ioned. The PAs a e conside ed in many cases o be biased in hei loca ion, meaning ha PAs a e loca ed in a eas ha a e unlikely o ace land con e sion p essu es [21]. Joppa and P a [22] e eal ha a majo i y o he PA ne wo ks a e loca ed in high ele a ions, s eep slopes and a om oads and ci ies. Joppa and P a [21] a gue ha his bias has esul ed in o e es ima ions in he p o ec ion e ec o PAs. Local case s udies (e.g. [23]) suppo hese global indings. Joppa and P a [24] use ‘ma ching’app oach ha a emp s o a oid he o e es ima ion o p o ec ion e ec o PAs in 147 coun ies by com- pa ing p o ec ed and non-p o ec ed a eas wi h simila land cha ac e is ics. They ind ha ma ching educed he p o ec ion e ec in 80% o he coun ies compa ed o an assessmen wi hou ma ching. Al oge he hey ind ha he p o ec ion educed con e sion o na u al land P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 2/21 Compe ing In e es s: The au ho s ha e decla ed ha no compe ing in e es s exis . co e in 75% o he assessed coun ies. P o ec ed a eas a e also epo ed o become inc easingly isola ed, especially in opics [25]. This is ala ming because smalle p o ec ed a eas a e o en unde g ea h ea [26] and isola ion o hese a eas es ic s he habi a size, i.e. limi s he su - i al o a g ea numbe o auna and lo a species (e.g. [27,28]).Al hough he unde s anding o o es loss a a global scale wi h an inc easing spa ial esolu ion is g owing apidly [5], he global o es loss in PAs and in IFLs a e no assessed wi h de ailed and uni o m da ase s ha allow consis en o es ex en compa isons o e space and ime. So a only egional analyses exis a his le el, o example, o Indonesia [29]. Fu he mo e, he success o p o ec ion in p ese ing he IFLs is no ye well unde s ood. The e o e, in his s udy, we aim o conduc a consis en and spa ially explici assessmen o he global o es loss, pa icula ly wi hin p o- ec ed and in ac o es s by ocusing on he a ia ion among he coun ies be ween 2000 and 2012. Addi ionally, we aim o s udy whe he socio-economic indica o s can o e po en ial explana ion o hese obse ed global o es losses in PAs and IFLs. We hypo hesised ha i) he ex en o o es loss wi hin PAs and IFLs a ies s ongly among he coun ies bu is always less mani es ed wi hin PAs han ou side o hem, and ii) coun y le el indica o s o popula ion size, land use change and s a e economy can o e po en ial explana ion o he obse ed global o es losses in PAs and IFLs. The key e minology used in his s udy is explained in Table 1. Ma e ials and Me hods To conduc he assessmen , we combined ou global da ase s (Fig 1;Table 2): o es ex en based on he Global Fo es Change (GFC) da a [5], o es loss based on he GFC da a [5], he Wo ld Da abase o P o ec ed A eas (WDPA) [30] and he global La ge In ac Fo es Land- scapes (IFL) da a [20]. F om GFC we assessed he o es ex en and o es loss while WDPA and IFL da ase s we e used o de e mine how much o ha loss ook place in p o ec ed a eas and in ac o es landscapes espec i ely. The esul ing spa ial da a we e agg ega ed o coun y- scale and analysed wi h Weigh ed Leas -Squa es (WLS) eg ession analyses o assess whe he one o a se ies o socio-economic indica o s a e associa ed o o es loss pa e ns, possibly explaining hei occu ence. The o es loss esul s a e gi en a na ional and global scale and by geog aphical egions, while eg ession analyses we e conduc ed a na ional scale o co espond wi h he socio-economic indica o da a and he pu sued o es go e nance le el. Below he da a and me hods a e desc ibed in mo e de ail. Da a We used he GFC da ase [5] o map he o es ex en and o es loss (Fig 1A and 1B;Table 2). GFC da a a e based on Ea h obse a ion sa elli e da a and ha e a esolu ion o ~30 me e s a Table 1. Key e minology used in he s udy. Te m Defini ion Fo es Vege a ion alle han 5 m wi h 20% ee co e canopy h eshold using Global Fo es Change (GFC) da a by Hansen e al. [5]. Fo es loss ”S and eplacemen dis u bance o comple e emo al o o es canopy”as defined by Hansen e al. [5] in GFC da a. Fo es gain was no aken in o accoun . P o ec ed a ea (PA) P o ec ed a ea as in Wo ld Da abase on P o ec ed A eas (WDPA) [30]. P o ec ed o es Fo es wi hin PA (i.e. p o ec ed a ea). In ac o es landscape (IFL) ”An unb oken expanse o na u al ecosys ems wi hin a eas o cu en o es ex en ,wi hou signs o significan human ac i i y,and ha ing and a ea o a leas 500 km 2 ”as in IFL da ase by Po apo e al. [20]. In ac o es Fo es wi hin IFL (i.e. In ac o es landscape). P o ec ed in ac o es In ac o es wi hin PA (i.e. p o ec ed a ea). doi:10.1371/jou nal.pone.0138918. 001 P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 3/21 he equa o (i.e. 1 a c-second). The o es ex en in he GFC da a a e gi en as canopy co e pe - cen age pe ou pu g id cell o all ege a ion alle han 5 me e s o he yea 2000 [5]. The o - es loss in he GFC da ase is de ined as s and- eplacing dis u bance, o comple e emo al o ee canopy, which has occu ed be ween yea s 2000 and 2012 [5]. In his s udy, we used he same de ini ion o o es loss (Table 1). The GFC da ase p o ides g oss and ne o es loss da a. We chose o ocus on g oss o es loss ins ead o ne o es loss, as we belie e he o me e lec s be e he occu ence o o es dis u bances in p o ec ed and in ac o es s han he la - e . The use o ne o es loss could ha e masked some o he dis u bances h ough o es gain. I should be no ed ha he GFC da ase does no speci y he easons behind o es loss and hus, he epo ed o es loss inside p o ec ed a eas migh be due o di ec human ac ions (e.g. illegal logging, managemen s a egies) as well as na u al causes (e.g. o es i es, diseases, pes s Fig 1. Agg ega ed (A-B) and con e ed (C-D) da ase s used o he o es loss analyses. A) Fo es ex en in pe cen age o g id a ea a 1 km esolu ion, based on Global Fo es Change (GFC) da a [5]; B) Fo es loss in pe cen age o g id a ea a 1 km esolu ion, based on GCF da a [5]; C) P o ec ed a eas based on Wo ld Da abase o P o ec ed A eas (WDPA) [30], con e ed o 1 km esolu ion; and D) La ge In ac Fo es Landscapes (IFLs) based on da ase by Po apo e al [20], con e ed o 1 km esolu ion. doi:10.1371/jou nal.pone.0138918.g001 Table 2. A desc ip ion o he da ase s used in his s udy. GFC s ands o Global Fo es Change da ase . Da ase Spa ial ex en Time pe iod Spa ial esolu ion Re e ence GFC: Fo es loss La : 80N - 60S Lon: 90E - 90W 2000–2012 30 m (a equa o ; 1 a c-second x 1 a c-second) Hansen e al. [5] GFC: Fo es ex en La : 80N - 60S Lon: 90E - 90W 2000 30 m (a equa o ; 1 a c-second x 1 a c-second) Hansen e al. [5] Wo ld Da abase o P o ec ed A eas (WDPA) Global 2010 ( e e ence yea ) Vec o da a wi h a ying esolu ion IUCN and UNEP-WCMC [30] La ge In ac Fo es Landscapes (IFL) Global 2000 Vec o da a wi h app oxima e esolu ion o 1 km (scale: 1:1,000,000) Po apo e al. [20] doi:10.1371/jou nal.pone.0138918. 002 P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 4/21 and s o ms) [2,5,31,32]. Fo example, na u al o es i es a e epo ed o be he mos signi ican cause o o es loss in he bo eal o es s [33]. We used he WDPA da ase o map he p o ec ed a eas o he globe (Fig 1C;Table 2). The da ase is a join p ojec o IUCN and UNEP and i is s a ed o be he mos ex ensi e da ase on p o ec ed a eas con aining bo h na ionally and in e na ionally designa ed p o ec ed a eas [30]. The da ase is based on bo h au ho i y and communi y sou ces. We included only he p o- ec ed a eas epo ed by au ho i y sou ces in o ou assessmen . Fo he in ac o es a eas we used he global ex en o IFLs (Fig 1D;Table 2)[20]. The da a- se is c ea ed using a ious emo ely sensed da ase s and maps, including da a om MODIS and Landsa . They de ine IFL as an unb oken a ea o na u al ecosys ems wi hin o es s, wi hou signs o signi ican human ac i i y, and ha ing an a ea o a leas 500 km 2 . The e e ence yea o his da ase is 2000, i.e. he s a ing yea o ou analysis. Me hods: o es ex en and o es loss We conduc ed he analyses on 1 km esolu ion (a he equa o ; i.e. on 30 a c-second esolu- ion). All da ase s we e ei he agg ega ed ( o es ex en and o es loss) o con e ed (PA and IFL) o his esolu ion. The con e sion p ese ed he o iginal esolu ion o he inpu da a (Table 2) and he agg ega ion o coa se esolu ion was ca ied ou in a way ha o iginal in o - ma ion was no dis o ed (see below o mo e de ails). Be o e any da a agg ega ion, we ans o med he o iginal GFC o es co e da a in o boolean ype a 30 m esolu ion. Fo he ans o ma ion we used 20% ee canopy co e h eshold, simi- la ly o Po apo e al. [33], o de ine whe he he 30 m esolu ion g id cells a e classi ied as o es o no- o es . These boolean o es co e da a we e mul iplied by a su ace a ea o 30 m cell in ques ion. The o es ex en a ea da a (in km 2 ) we e hen agg ega ed in o 1 km esolu ion by sum- ming he su ace a ea o o es om 30 m g id cells wi hin each 1 km g id cell (no e: he a ea o 30 m g id cells a y o e la i udes in he o iginal WGS84 p ojec ion and his was aken in o accoun in a ea calcula ions). The GFC o es loss da a a e boolean da a in na u e (loss o no loss). These o es loss boolean da a we e mul iplied by a su ace a ea o 30 m cell in ques ion and agg ega ed o 1 km esolu ion simila ly as o es ex en (see abo e). Possible o es loss was only accoun ed in hose 30 m g id cells ha had ee canopy co e o e he 20% h eshold in he o es ex en da ase . As a esul we go he o es ex en and o es loss in km 2 o each 1 km g id cell wi hou losing any in o ma ion in he agg ega ion p ocess. To illus a e he agg ega ed da ase s, he o es ex en and o es loss in pe cen ages o g id cell a ea a e p esen ed in Fig 1A and 1B. IFL and WDPA da ase s (Fig 1C and 1D;Table 2) we e used o calcula e he ex en and loss o p o ec ed o es , in ac o es and p o ec ed in ac o es . We i s con e ed he ec o da a o bo h da ase s o as e da a wi h 1 km esolu ion, being he o iginal esolu ion o IFL da a while esolu ion o WDPA da a a ies be ween he en ies. A e his we used he agg ega ed GFC da a o calcula e he a ea o o es ex en and o es loss inside each ype o spa ial c i e ia wi hin an analysis uni (coun y, egion o global): i) o al o es ex en and loss, ii) o es ex en and loss wi hin p o ec ed a eas, iii) o es ex en and loss wi hin in ac o es landscapes, and i ) o es ex en and loss wi hin p o ec ed in ac o es landscapes. We epo bo h absolu e and ela i e alues o o es ex en and loss. By using hese esul s, we analysed he o es p o ec ion e ec o p o ec ed a eas. The e ec was es ima ed by calcula ing anomaly a ios o ela i e loss o p o ec ed and non-p o ec ed o es , in ac and non-in ac o es , and o p o ec ed in ac and non-p o ec ed in ac o es . The anomaly a ios we e calcula ed a na ional scale by di iding he ela i e o es loss in he p o ec ed a eas in ques ion by he ela i e o es loss in he co esponding non-p o ec ed a eas, e.g. [( ela i e loss o p o ec ed in ac o es / ela i e loss o non-p o ec ed in ac o es )–1]. P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 5/21 Thus he anomaly a ios p o ide in o ma ion on he e ec o p o ec ed a eas on o es loss as hey indica e whe he he ela i e o es loss is lowe (<0) o highe (>0) in he p o ec ed o es han in he non-p o ec ed o es . We u he iden i ied simila i ies in o es loss pa e ns be ween coun ies by clus e ing he coun y scale esul s wi h k-mean clus e ing me hod. In his me hod he clus e ing o he obse a ions (i.e. coun y- alues) is based on minimizing he sum o he squa ed Euclidean dis- ances be ween each obse a ion and he clus e -cen oid- alue. We assessed goodness o i in e ms o a ia ion wi hin clus e s. To de ine he op imal numbe o clus e s we used he SSE cu e. We pe o med wo di e en clus e analysis, each conside ing ou di e en pa ame e s. In he i s clus e analysis, we iden i ied clus e s based on absolu e and ela i e losses in o al o es and p o ec ed o es a eas while in he second clus e analysis, we conside ed absolu e and ela i e o es losses in in ac o es landscapes and p o ec ed in ac o es landscapes. I should be no ed ha while o o es ex en and in ac o es da ase s he e e ence yea is 2000, o p o ec ed a eas he co e age in yea 2010 was aken. The e e ence yea 2010 o p o- ec ed a eas was chosen because ha moniza ion o he e e ence yea was no easible. The WDPA da ase does no epo he es ablishmen yea o all p o ec ed a eas. This howe e did no comp omise he analyses as we ound ha he WDPA da a om he yea 2010 adequa ely e lec he p o ec ion s a us o he o es o e he s udy pe iod: only 8% o he wo lds p o ec ed a eas (whe e an es ablishmen yea is p o ided) we e es ablished a e he yea 2000. Me hods: he ela ionship be ween o es loss and socio-economic indica o s To s udy he ela ionship be ween obse ed o es loss and socio-economic a ibu es, we employed WLS (i.e. Weigh ed Leas Squa es) eg ession analysis, which allowed he o al ex en o o es ype in ques ion o be used as weigh s. The deg ee o which he socio-economic a i- bu es can accoun o he ela i e o es loss was analysed o each o he ou o es loss mea- su es conside ed in his s udy: o al o es loss, loss in p o ec ed o es , loss in in ac o es , and loss in p o ec ed in ac o es . Al oge he 11 commonly used socio-economic indica o s we e selec ed and hey a e lis ed in Table 3. The socio-economic indica o s we e, mo eo e , selec ed Table 3. The socio-economic indica o s used in he eg ession analysis. The indica o s we e used as independen a iables in he assessmen o he o es loss d i e s wi h Weigh ed Leas -Squa es (WLS) eg ession analysis. Va iable Da a ype Time pe iod Re e ence Popula ion densi y pe squa e km 2010 UN [34] Popula ion densi y g ow h % 2000–2010 UN [34] GDP g ow h % 2000–2010 Wo ld Bank [35] GDP pe capi a (PPP) In e na ional USD 2010 Wo ld Bank [35] Ru al popula ion o o al popula ion % 2010 Wo ld Bank [35] Popula ion g ow h % 2000–2010 Wo ld Bank [35] Co up ion pe cep ion index a 0.. 10 2010 T anspa ency In e na ional [36] Poli y index b -10.. 10 2010 Ma shall and Gu [37] Human De elopmen Index (HDI) c 0.. 1 2012 UNDP [38] Ag icul u e o o al land a ea % 2010 Wo ld Bank [35] Ag icul u al land a ea g ow h % 2000–2010 Wo ld Bank [35] a Low co up ion pe cep ion index co esponds wi h high co up ion and ice e sa b Low poli y index co esponds wi h low democ acy and ice e sa c High HDI co esponds wi h high human de elopmen and ice e sa doi:10.1371/jou nal.pone.0138918. 003 P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 6/21 o ep esen he widely acknowledged causes o global de o es a ion: popula ion size, land-use change, s a e go e nance and s a e economy. The selec ion was ca ied ou wi h a equi emen o a ailable homogeneous da a a he global scale. We b ie ly desc ibe he WLS eg ession analysis below while s ep-by-s ep desc ip ion is gi en in S3 Appendix. The dependen a iables we e log 10 – ans o med p io o analyses o ensu e he no mali y o hei dis ibu ions. Simila ly, he independen a iables we e ans o med wi h a link unc- ion in cases i imp o ed he linea i y o he ela ion wi h he analysed o es loss measu es. The link unc ion o each independen a iable was de ined sepa a ely o each ou dependen a iables. Despi e he ans o ma ions, he da a included some s a is ical ou lie s. Exclusion o hese ou lie s did no a ec he signi icance o he esul s and hus he epo ed esul s we e gained wi hou omi ing he s a is ical ou lie s. The mul iple eg ession models we e buil by s a ing wi h he ull model comp ising o all 11 independen a iables and ending wi h a model whe e no mul icollinea i y was de ec ed. Mul icollinea i y was de e mined by he Va ia- ion In la ion Fac o (VIF, a se limi o VIF <4) and he collinea independen a iable wi h he lowes explana o y powe was always excluded om he model. Resul s Ou analyses based on GFC da a [5] e ealed ha o es co e ed one hi d o he o al land a ea (app oxima ely 43 million km 2 ) in he yea 2000, and 19% o his o es (o e 8 million km 2 ) was unde some o m o p o ec ion (Table 4). Acco ding o ou analyses 25% (11 million km 2 ) o global o es s we e in ac , o which almos 35% was p o ec ed. A eas ha a e bo h in ac and p o ec ed co e ed hus a o al o almos 3.7 million km 2 (o 8.7% o he o al o es ex en ) (Table 4). The global o es loss based on GFC da a was 2.14 million km 2 be ween he yea s 2000 and 2012, being o e 5% o he o al o es ex en in yea 2000 (Table 4). This global o es loss a e co esponds o calcula ions by Hansen e al. [5]. Fu he , acco ding o ou analyses, o e 10% o he o al o es loss occu ed in p o ec ed a eas: 219,000 km 2 o p o ec ed o es (3% o he o al p o ec ed o es ) was los wi hin ha ime pe iod. We u he ound ha 269,000 km 2 (2.5%) o in ac and 55,000 km 2 (1.5%) o p o ec ed in ac o es we e los du ing he yea s 2000–2012 (Table 4). In he ollowing sec ions he esul s a e p esen ed in mo e de ail. The nume ic esul s a e also gi en o each coun y in S2 Table o he supplemen a y in o ma ion. I is wo h o highligh ha ou es ima es on o al o es ex en and o al o es loss on a global scale p esen ed in his sec ion a e gi en only o alida e ou analyses (i.e. compa ison o Han- sen e al. [5]) and o pu ou esul s on PAs and IFLs in o a con ex . Fo es ex en s and hei p o ec ion s a us In yea 2000 he absolu e o es ex en was la ges in Russia, China, Indonesia, Democ a ic Republic o he Congo, B azil, Uni ed S a es, and Canada, exceeding 1 million km 2 (Fig 2A). Toge he hese coun ies con ained o e 60% o he global o es ex en . When examining ela- i e o es ex en (Fig 2B), pa icula ly Scandina ia and Finland (No dic coun ies om he e on), and coun ies in cen al A ica and Sou heas Asia had a ema kable po ion o hei e i- o y unde o es . The coun ies wi h he la ges p o ec ed o es a eas we e mainly he same coun ies wi h he g ea es ex en o o es (Fig 2C). Howe e , when assessing he a io o p o- ec ed o es ex en and he o al o es ex en , he la ges p o ec ed o es a eas we e loca ed in Cen al Eu ope, Aus alia, and in some coun ies o Sou h Ame ica, Sub-Saha an A ica and he Middle Eas (Fig 2D), whe e o e 30% o he o es s we e p o ec ed ( hough hese o en ep- esen small a eas o o es ). P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 7/21 The coun ies wi h he la ges o al o es ex en had also he la ges a eas o in ac o es (o e 400,000 km 2 ), excep Indonesia, Uni ed S a es and China (Fig 2E). On he o he hand, a la ge pa o Eu opean, Middle Eas e n, No h A ican and Sou he n A ican coun ies did no ha e any in ac o es landscapes (Fig 1D). When compa ing he a ea o in ac o es o he a ea o o al o es , we ound ha in many coun ies o No h and Sou h Ame ica, Sou heas Asia, Middle A ica and Aus alia sha es o in ac o es o o al o es we e e y high (Fig 2F). In con as o hese coun ies, No dic coun ies had a la ge p opo ion o hei land unde o - es (Fig 2B) bu only less han 2% o ha o es was classi ied as in ac o es (Fig 2F). Only B azil had o e 1 million km 2 o p o ec ed in ac o es (Fig 2G). Russia, Canada, Uni ed S a es and no he n coun ies o Sou h Ame ica had o e 100,000 km 2 o hei in ac o es s unde p o ec ion. When examining he ela i e ex en o p o ec ed in ac o es (ex en o p o ec ed in ac o es e sus ex en o o al in ac o es ), we ound ha majo i y o in ac o es , o e 70%, we e p o ec ed in coun ies such as Thailand, New Zealand, Japan, Madagas- ca , and E hiopia as well as No dic coun ies (Fig 2H). On he con a y, in some coun ies less han 20% o he in ac o es was unde p o ec ion, including Russia, Canada and Democ a ic Republic o he Congo (Fig 2H). Loss o o al and p o ec ed o es The la ges absolu e o es loss alues we e encoun e ed in B azil, Canada, Uni ed S a es, Rus- sia and Indonesia. Each o hem expe ienced o es losses o o e 100,000 km 2 du ing he pe iod o 2000–2012 (Fig 3A). The la ges ela i e losses, o e 10% o hei o es ex en , we e Table 4. Fo es ex en in 2000 and i s loss o e he pe iod o 2000–2012. The o es ex en and loss a e calcula ed o geog aphical egions in absolu e [10 3 km 2 ] and ela i e alues [%]. Fo es ex en [10 3 km 2 ] Fo es loss [10 3 km 2 ] Region To al ex en P o ec ed ex en (o o al ex en ) In ac ex en (o o al ex en ) P o ec ed in ac ex en (o o al in ac ex en ) To al loss (o o al ex en ) P o ec ed loss (o o al p o ec ed ex en ) In ac loss (o o al in ac ex en ) P o ec ed in ac loss (o o al p o ec ed in ac ex en ) Aus alia and Oceania 1,101 251 (23%) 256 (23%) 71 (28%) 48 (4%) 12 (5%) 4 (2%) 2 (3%) Cen al Ame ica 1,038 221 (21%) 60 (6%) 47 (78%) 54 (5%) 11 (5%) 1 (1%) 0.4 (1%) Eas e n Asia 2,203 193 (9%) 32 (1%) 10 (33%) 70 (3%) 5 (3%) 1 (5%) 0.4 (4%) Eas e n Eu ope and Cen al Asia 8,759 1,067 (12%) 2,039 (23%) 300 (15%) 357 (4%) 43 (4%) 72 (4%) 10 (3%) La in Ame ica 9,665 3,322 (34%) 4,400 (46%) 2,415 (55%) 531 (5%) 41 (1%) 31 (1%) 9 (0.4%) Middle and Sou h A ica 6,768 1,054 (16%) 998 (15%) 212 (21%) 201 (3%) 22 (2%) 3 (0.3%) 0.4 (0.2%) Middle Eas 188 12 (6%) 4 (2%) 0.4 (9%) 3 (2%) 0.1 (0.4%) 0.004 (0.1%) 0.0003 (0.1%) No h A ica 219 15 (7%) - (-) - (-) 2 (1%) 0.2 (1%) - (-) - (-) No h Ame ica 7,298 837 (11%) 2,408 (33%) 418 (17%) 513 (7%) 47 (6%) 152 (6%) 32 (8%) Sou h Asia 592 84 (14%) 31 (5%) 8 (26%) 10 (2%) 1 (1%) 0.1 (0%) 0.03 (0.3%) Sou heas e n Asia 3,234 657 (20%) 478 (15%) 203 (42%) 271 (8%) 23 (4%) 3 (0.7%) 1 (0.3%) Wes e n Eu ope 1,481 353 (24%) 11 (0.8%) 9 (81%) 83 (6%) 12 (3%) 0.03 (0.2%) 0.01 (0.1%) Global 42,562 8,068 (19%) 10,717 (25%) 3,693 (34%) 2,144 (5%) 219 (3%) 269 (2.5%) 55 (1.5%) doi:10.1371/jou nal.pone.0138918. 004 P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 8/21 ound in some coun ies in no h-wes e n and sou he n A ica, and Sou heas Asia (Fig 3B). In hese coun ies he ela i e losses we e high in hei p o ec ed o es s oo (Fig 3D). Rela i ely high (>5%) p o ec ed o es losses occu ed in Aus alia, Uni ed S a ed and some Eu opean coun ies. Sou h Asia, Middle Eas and Cen al Asia showed, on he o he hand, small numbe s o bo h absolu e and ela i e p o ec ed o es losses (Fig 3C and 3D). Fig 2. Absolu e and ela i e o es ex en by coun y in yea 2000. Absolu e o es ex en s (le column) a e p esen ed in km 2 and ela i e o es ex en s ( igh column) a e in %. A and B) To al o es ex en ; C and D) P o ec ed o es ex en ; E and F) In ac o es ex en ; G and H) P o ec ed in ac o es ex en . doi:10.1371/jou nal.pone.0138918.g002 P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 9/21 assessed coun ies (76%), ela i e o es loss was smalle in p o ec ed a eas han ou side hem (anomaly a io <–0.125: Fig 5A). The p o ec ion, mo eo e , seemed o be pa icula ly e ec i e o educing o es loss in Sou h Ame ica, Sou heas Asia and Sub-Saha an A ica (Fig 5A). Ne e heless, he e ec o p o ec ion on o es loss was he opposi e in some coun ies in Mid- dle A ica, Eu ope, Middle Eas and Mongolia in Asia and hus ejec s ou i s hypo hesis o a uni ied posi i e p o ec ion e ec . On coun y scale, ou indings sugges posi i e news o B a- zilian Amazon whe e p o ec ion was ound o be e y e ec i e in p e en ing o es loss. This is in ag eemen wi h he ea lie esea ch indings on he B azilian Amazon [6,39]. In he case o in ac o es , he global esul s we e simila , i.e. p o ec ion was e ec i e in 43 o 60 o assessed coun ies (72%) (Fig 5B). La ges de ia ions o he global majo i y we e shown by Mongolia, Nepal and Aus alia. I is wo h o acknowledge ha he PAs a e no necessa ily always aimed o p o ec he o es s ands pe se, ins ead p o ec ion can ha e o he goals. P io o ou s udy, he e ec i eness o p o ec ion is globally analysed by Joppa and P a [24]. Ou s udy u he s eng hens hose indings, ye ou indings a e e ie ed da a-wise in mo e consis en manne by using empo ally compa able o es ex en da ase s (Table 2), which only became a ailable a e he s udy by Joppa and P a [24]. D i e s o o es loss Impo an ly, we also explo ed he d i e s o o es loss by looking a he s a is ical linkage be ween socio-economic indica o s and weigh ed o es loss (Table 5). Weighing he coun y speci ic o es losses by hei o al o es ex en in ques ion allowed ou analysis o indica e he d i e s ha a e exp essi e o he global o es ex en ins ead o ocusing on d i e s explaining he in e -coun y a ia ion. This globally uni o m assessmen showed o es loss ha ing a s ong connec ion wi h ag icul u al land ex en . Mo eo e ag icul u al land expansion is ecog- nised as one o he mos impo an p ocesses causing o es loss (see e.g. [8–13]) and ou analy- sis ag ees well wi h his, pa icula ly conce ning he p o ec ed in ac o es s (Table 5). Howe e , i is wo h o ecognise ha ag icul u e ela ed o es loss in ol es much mo e com- plex dynamics han ou eg ession analyses a e able o cap u e (see e.g. [40]). We u he ound s ong connec ion be ween losses in p o ec ed and/o in ac o es s and popula ion densi y and GDP o ully suppo ou second hypo hesis. While se e al global scale s udies ha e ound ha highe popula ion densi y inc eases o es loss (e.g. [41,42]), hese all epo o al o es loss. We did no ind signi ican ela ionship be ween o al o es loss and popula ion densi y, whe eas ou indings o losses in in ac and p o ec ed in ac o es s (Table 5) show opposi e di ec ion compa ed o hese exis ing s udies on o al o es loss. Ou indings also seem o disag ee wi h a me a-analysis by Po e -Bolland e al. [43]. Howe e , a di ec compa ison be ween ou esul s and hose o Po e -Bolland e al. [43] is discou aged by he di e en scopes and app oaches in he s udies. Unlike ou s udy, he me a-analysis assessed he e ec i eness o only 40 p o ec ed a eas in he opics. Addi ionally, popula ion densi ies a e measu ed by di e en manne s: in ou s udy popula ion densi ies we e coun y a e ages while he me a-analysis based i s da a on popula ion densi y in he immedia e neighbou hood o p o ec ed a eas. Ou desi e o single s a is ical analysis including mul iple explana o y a iables de e mined he selec ion o coun y a e ages on he popula ion me ic o ma ch wi h he a ailable le el o he o he a iables. All in all, ou indings oge he wi h hose by Po e -Bolland e al. [43] poin o a need o u he esea ch on he ole o popu- la ion dynamics in o es loss. In e ms o GDP, we did no ind a s a is ically signi ican ela ionship wi h o al o es loss (Table 5). This inding is in line wi h some p e ious s udies [44–46], whe eas some o he s ud- ies sugges ha lowe GDP could indica e highe o es loss (e.g. [47,48]). While he e ec o P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 16 / 21 GDP on o es loss in p o ec ed a eas has no been assessed p e iously on a global scale, i is e alua ed by Nagend a [49] on 56 p o ec ed a eas. He indings indica e ha he a es o land co e clea ing do no di e signi ican ly be ween coun ies wi h di e en le els o GDP pe capi a. We ound, in u n, high GDP pe capi a o indica e high weigh ed o es loss a e in p o- ec ed a eas (Table 5). This ela ion be ween GDP and weigh ed o es loss on p o ec ed a eas can possibly indica e di e en managemen s a egies in coun ies wi h a ying GDP, i.e. coun- ies wi h highe GDP may ha e mo e e sa ile managemen s a egies such as, hose ha aim o s eng hen biodi e si y o p o ide habi a s o speci ic species, compa ed o coun ies wi h lowe GDP. Ou assessmen , i.e. looking a he o es loss d i e s globally, na u ally used a he limi ed se o socio-economic indica o s on a coa se scale. This cons ic ion on indica o s was needed o he sake o homogeneous da a. Ano he s o y would be e ealed by mo e local and egional s udies ha could o e ui ul insigh s o his global s udy, as is o example shown by he global me a-analysis looking a he d i e s behind he e ec i eness o p o ec ion managemen [50]. Ou s udy p o ides a global empi ical assessmen , weigh ed by he o al o es ex en s in ques ion, ha can be used as a e e ence poin o mo e de ailed s udies a o he spa ial scales. Taking u he –subna ional esul s and compa ison among da ase s We acknowledge ha he coun y le el esul s p esen ed in his s udy do no e eal ine le el he e ogenei y. The e o e, as an example, we explo ed how he o es loss in PAs a ies wi hin a coun y. Taking Colombia as an example, in ou esul s we showed ha he mean a e o o es loss wi hin all p o ec ed a eas was 0.08% pe yea . In a ine scale assessmen using he same da ase (i.e. GFC) we ound ha he o es loss a ied among he indi idual Colombian PAs om ze o o 1.48%, he obse ed a es being low o e la ge PAs in he Amazon and gene ally highe o p o ec ed a eas in he Andes. The mean a e o annual o es loss pe PA was 0.12% wi h s anda d de ia ion o 0.19%. This highligh s he impo ance o s udy u he he impac o p o ec ion on o es loss in lowe spa ial scales. Fu he mo e, we ca ied ou he same analysis by using an al e na i e da ase , Te a-I [51], o explo e possible di e ences in a ailable da ase s. Te a-i da ase de ia es om GFC in i s use o MODIS (250 m esolu ion) ins ead o Landsa (30 m esolu ion) and 2004–2014 ins ead o 2000–2012. The ange in o es loss in he indi idual p o ec ed a eas (0% o 1.72%) was simi- la o he inding made by GFC bu he mean annual o es loss a e wi hin he PAs was one hi d (mean a e o 0.043% wi h s anda d de ia ion 0.14%) o he ound losses compa ed o GFC da ase indings. This compa ison e lec s di e ences in da a ype, me hodology and pe iod bu also indica es he unce ain y associa ed wi h hese da ase s and, hus calls o u - he compa isons be ween he widely used da ase s. Me hodological limi a ions and ways o wa d I is impo an o expand he discussion owa ds he limi a ions c ea ed by he used da ase s ha also ou s udy is na u ally subjec ed o. Fo example, o he o es co e and loss we used he GFC da ase [5], which can gi e de ia ing esul s compa ed o o he da ase s mainly due o he di e ences in me hods such as: de ini ion o o es , sepa a ion o an h opogenic om na u- ally occu ing o es loss, and handling o a mosphe ic dis o ions (e.g. cloud co e ) in map- ping he o es co e . Al hough, di ing deepe in o hese di e ences and he e ec s hey ha e on he indings is beyond he scope o his analysis, i would o e a ui ul opic o a compa a- i e s udy. In addi ion, Lee [52] aises a conce n on he IFL da ase [20] ha i s de ini ion o in ac ness o o es may no cap u e he socio-ecological a ia ion be ween di e en geog aphi- cal egions and may hus in oduce inaccu acies in coun y speci ic analyses. In e -compa ison P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 17 / 21 o global scale da ase s as well as mo e de ailed analyses a he coun y/ egional le el would be needed o un a el he s a e o global classi ica ion o IFLs. I should be no ed ha ou s udy ocused on o es loss, o mo e p ecisely on s and- eplac- ing dis u bance, igno ing he possible o es gain. This ocus ga e us mo e space o explo e he loss o o iginal habi a s wi hin p o ec ed a eas and in ac o es landscapes and he d i e s behind hese losses. A compa ison o ou indings o indings ha would be based on he ne o es loss, i.e. a loss assessmen including he plan ing o o es s and na u al o es egene a- ion (see [2,5] and e e ences he ein o u he in o ma ion), would allow acking o he o - es canopy co e pe se. Ou es ima ions on he e ec i eness o p o ec ion o educe o es loss wi hin PAs com- pa ed o he o es loss ou side hose a eas p o ide use ul in o ma ion he p o ec ion e ec a he coun y le el. A he coun y le el, we we e ne e heless no able o assess he leakage e ec o indi idual p o ec ed a eas, as done by e.g. Oli ei a e al [53]. As highligh ed by Ewe s and Rod igues [54] a compa ison o o es loss in he icini y o and inside p o ec ed a eas is essen- ial in unde s anding he e ec s o o es p o ec ion on a local scale. I is also wo hwhile o ec- ognise ha o es ed a eas migh ha e been p o ec ed o o he easons han p o ec he o es s ands pe se. The global da ase s used in his s udy could be u he employed o his kind o assessmen , compa ing he leakage e ec wi hin and among egions and u he mo e ex ending i all he way o global le el. Mos impo an ly, global da a on o es managemen goals pe each p o ec ion a ea would be highly needed o suppo mo e de ailed assessmen on he impac o p o ec ion on o es loss. Conclusions Ou global scale analysis indica es ha subs an ial a eas o p o ec ed (3%) and in ac o es s (2.5%) we e los o e he pas decade, and la ge pa o ha loss occu ed in coun ies wi h well-es ablished p o ec ion (e.g. in Aus alia and Oceania, and No h Ame ica). In e ms o compa ison be ween o es loss inside and ou side o PAs and IFLs we could no con i m ou i s hypo hesis, which s a ed ha o es loss would always be less mani es ed wi hin PAs han ou side o hem. Al hough he ela i e o es loss was smalle inside he PAs and p o ec ed IFLs in global a e ages and in majo i y o coun ies, he e we e nume ous coun ies ha showed an opposi e e ec . Also ou second hypo hesis was no en i ely con i med: while popula ion size and o he indica o s we e able o explain di e ences in weigh ed global o es loss wi hin PAs and IFLs, a la ge pa o he a ia ion emained unexplained. Mo eo e , he s a is ical associa- ions did no always co espond wi h ou causal unde s anding o o es loss p ocesses. Ou indings hus highligh ha p o ec ion o o es ed a eas does no always gua an ee a lowe a e o o es loss. The e is, indeed, a high geog aphical a ia ion in he e ec i eness o p o ec ion agains o es loss, a a ia ion ha is p obably a leas o some ex en explained by coun ies’ di e en means and in ensi ies o comba agains o es loss. Suppo ing In o ma ion S1 Appendix. C oss-co ela ion ables. C oss-co ela ion ables o socio-economic indices in cases o di e en o es loss ca ego ies. (PDF) S2 Appendix. Compa ison o ou indings o p e ious s udies: o es ex en and loss. (PDF) S3 Appendix. Weigh ed Leas Squa es (WLS) eg ession analysis s eps. (PDF) P o ec ed and In ac Fo es Loss PLOS ONE | DOI:10.1371/jou nal.pone.0138918 Oc obe 14, 2015 18 / 21 S1 Table. Socio-economic da a a coun y le el. Socio-economic da a used in he WLS eg es- sion analysis. (XLSX) S2 Table. Coun y le el esul s. Fo es ex en and o es loss esul s p esen ed a coun y le el. (XLSX) Acknowledgmen s We a e g a e ul o CSC—IT Cen e o Science o p o iding he compu a ional acili ies o he analyses. We also hank he e iewe s o hei cons uc i e commen s and P o . Olli Va is, D . Joseph Guillaume, and o he membe s o ou esea ch eam a Aal o Uni e si y o hei encou agemen s and ui ul discussions. Au ho Con ibu ions Concei ed and designed he expe imen s: MH MK M. Mulligan TAR. Pe o med he expe i- men s: MH MK M. Mulligan MJ TAR. Analyzed he da a: MH MK M. Makkonen M. Mulligan MJ TAR. Con ibu ed eagen s/ma e ials/analysis ools: MH MK M. Makkonen M. Mulligan MJ TAR. W o e he pape : MH MK M. Makkonen M. Mulligan PHV TAR. Re e ences 1. 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