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Exploring sustainable land use in forested tropical social-ecological systems: A case-study in the Wet Tropics


Abstract and Figures

Tropical countries lie at the nexus of three pressing issues for global sustainability: agricultural production, climate change mitigation and biodiversity conservation. The forces that drive forest protection do not necessarily oppose those that drive forest clearance for development. This decoupling, enhanced by the stronger economic forces compared to conservation, is detrimental for the social-ecological sustainability of forested tropical landscapes. This paper presents an integrated, and spatially-explicit, Agent-Based Model that examines the future impacts of land-use change scenarios on the sustainability of the Wet Tropics region of tropical Queensland, Australia. In particular, the model integrates Bayesian Belief Networks, Geographical Information Systems, empirical data and expert knowledge, under a land-sharing/land-sparing analysis, to study the impact of different landscape configurations on trade-offs and synergies among biodiversity and two ecosystem services (sugarcane production and carbon sequestration). Contrary to most tropical regions, model simulations show that Business As Usual is helping to reconcile these contrasting goals in the forested landscape of the Wet Tropics. The paper analyses which combination of governance and socioeconomic factors is causing these positive results. This is an outstanding achievement for a tropical region, considering that most tropical areas are characterized for having stronger economic-land clearing forces compared to conservation forces, which reduce important ecosystem services for human wellbeing and the health of ecosystems.
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1. Introduction
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2. Material and Methods
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I=: 0:I -GDE>8H 0DGA9 !:G>I6<: G:6 0-0! 6C9 I=: G:6I 6GG>:G
+::;  +V -=: 6G:6 >H =DB: ID 7DI= 6 G>8= 6C9 :C9JG>C< 7DG><>
C6A 8JAIJG6A =:G>I6<: 6C9 DC: D; I=: BDHI 7>DAD<>86AAN 9>K:GH: 6G:6H >C
I=: LDGA9 L>I= ;DG:HIH G:8D<C>O:9 6H E6GI D; DC: D; I=: I=>GINSK: >C
I:GC6I>DC6A <AD76A 7>D9>K:GH>IN =DIHEDIH 0>AA>6BH :I 6A   D;
8JGG:CI A6C9 >C I=: 0:I -GDE>8H >H EGDI:8I:9 6 8DCH>9:G67AN A6G<:G 6G:6
I=6C I=: B6>C >C9JHIGN HJ<6G86C: EGD9J8I>DC  6C9 I=: IDI6A
H>K: JH:H  ,"-"  !DL:K:G I=: HJ<6G86C: >C9JHIGN >H DC:
D; I=: BDHI >BEDGI6CI GJG6A >C9JHIG>:H >C JHIG6A>6 <G>JIJG:H 
6C9 >IH :ME6CH>DC LDJA9 I=G:6I:C I=: G>8= 7>D9>K:GH>IN D; I=: CDGI=:6HI
D; *J::CHA6C9 -=: 8JGG:CI . 8DCI:MI >C I=: 0:I -GDE>8H H=DLH 6C
>C8G:6H: >C EGDI:8I:9 6G:6H 7N 6GDJC9  H>C8:  L>I= I=: 6G:6
8DK:G:9 7N HJ<6G EA6CI6I>DCH G:B6>C>C< G:A6I>K:AN HI67A: ,"-" 
-=JH 6 . H8:C6G>D >C DJG BD9:A G:;:GH ID 6 8DCI:MI L=:G: EGDI:8I:9
6G:6H >C8G:6H: L=>A: HJ<6G86C: EGD9J8I>DC G:B6>CH HI67A:
 ':,>4,66C0B:64.4> 79/066482 91 >30 6,8/ =3,<4826,8/ =:,<482
-=: 0:I -GDE>8H EGDK>9:H 6 96I6 G>8= 86H: ;DG >CK:HI><6I>DC D; %,)
%,! DEI>DCH JH>C< 6 HE6I>6AAN:MEA>8>I BD9:A 0>I= 6ABDHI  D; A6C9
EGDI:8I:9 6C9 6 HI67A:  D; 6<G>8JAIJG6A A6C9 6AAD86I:9 ;DG HJ<6G86C:
86A G:<>DCH D; I=: <AD7: H:: ,"-"  6C9 6H CDI:9 67DK: >IH G:A
6I>K: HD8>D:8DCDB>8 69K6CI6<: B:6CH I=6I 8DBEDJC9>C< ;68IDGH HJ8=
6H G6E>9 EDEJA6I>DC <GDLI= 6C9 EDK:GIN 6G: 67H:CI -=: 8=6G68I:G>HI>8
:CK>GDCB:CI6A 8DC9>I>DCH L>I= 6 =><= <G69>:CI 68GDHH I=: A6C9H86E: D;
G6>C;6AA 6C9 HD>A 8DC9>I>DCH ID <GDL HJ<6G86C: 6H L:AA 6H HIGDC< 8DC
H:GK6I>DC ;DG8:H L=>8= B6>CI6>C A6C9 8A:6G>C< EGD8:HH:H 6I 6 ADL G6I:
G:>C;DG8: 6 8A:6G H:<G:<6I>DC D; A6C9JH:H 67DJI L=>8= G:<JA6GAN JE96I:9
96I6 6G: EJ7A>86AAN 6K6>A67A: -=>H HE6I>6AAN:MEA>8>I 8DCI:MI EGDK>9:H 6
HJ>I67A: H8:C6G>D ID BD9:A I=: 8DCH:FJ:C8:H D; %,) DG %,! >C I=: 0:I
><  H=DLH 6 HE6I>6A H:<G:<6I>DC D; I=: I=G:: EG>B6GN 8A6HH:H D;
A6C9JH: INE:H >C I=: G:<>DC >: EGDI:8I:9 6G:6H ) HJ<6G86C: A6C9
,. 6C9 H:B>C6IJG6A 6G:6H ,' L=>8= 8G:6I:H 6 EA6I;DGB ID 6E
EAN I=>H ;G6B:LDG@ ;GDB 6 HE6I>6A E:GHE:8I>K: -=: :CK>GDCB:CI6A 6C9
A6C9JH: 8=6G68I:G>HI>8H D; H:B>C6IJG6A 6G:6H 6A><C L>I= I=: 8DC8:EI D;
%,! L=>A: 7DI= HJ<6G86C: EA6CI6I>DCH 6C9 EGDI:8I:9 6G:6H 8DB7>C:9
6A><C L>I= I=: DC: D; %,) &DG: HE:8>;>86AAN I=: A6C9JH: 8A6HH>S86I>DC
9:K:ADE:9 7N %.&)V  G:;:GH ID H:B>C6IJG6A 6G:6H 6H 6 EG>
9:SC:9 6H A6C9 I=6I >H JH:9 B6>CAN ;DG EG>B6GN EGD9J8I>DC L>I= A>B
>I:9 8=6C<: ID I=: C6I>K: K:<:I6I>DC -=JH H:B>C6IJG6A 6G:6H L=>8= >C
8AJ9: C6I>K: ;DG:HIH 6C9 <G6HHA6C9H 6G: HJ7?:8I ID G:A6I>K:AN ADL A:K:AH
D; >CI:GK:CI>DC 6C9 I=: HIGJ8IJG: D; I=: C6I>K: K:<:I6I>DC <:C:G6AAN G:
B6>CH >CI68I %.&)  %,! 6AHD 86AA:9 L>A9A>;:;G>:C9AN ;6GB
>C< >H @CDLC 6H 6 A6C9JH: HNHI:B I=6I 8DB7>C:H ADL >CI:CH>IN 6<G>
:I 6A  !JAB: :I 6A  )=6A6C :I 6A  6C9 I=:G:;DG:
6A><CH L>I= I=: H:B>C6IJG6A 6G:6H >C DJG HIJ9N G:<>DC 6H 9:SC:9 >C
%.&)  ,>B>A6GAN EGDI:8I:9 6G:6H 6C9 HJ<6G86C: A6C9 6G: 9:
SC:9 7N %.&)  6H EG>B6GN 8A6HH:H 8DCH>HI>C< D; 8DCH:GK6I>DC
-=>H E6E:G DCAN ;D8JH:H DC I=: 0:I -GDE>8H 6C9 6C6ANH:H DC I=: + 6G: 7:NDC9 I=:
8JGG:CI H8DE: D; DJG BD9:A AI=DJ<= I=: >BE68IH D; A6C9JH: DC I=: :8DHNHI:BH 6G:
L:AA9D8JB:CI:9 06I:G=DJH: :I 6A 
%.&) HI6C9H ;DG JHIG6A>6C DAA67DG6I>K: %6C9JH: 6C9 &6C6<:B:CI )GD<G6B
8A6HH>S86I>DC H8=:B: ;DG JHIG6A>6
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
Fig. 1. :D<G6E=>8 AD86I>DC D; I=: 0:I -GDE>8H '6IJG6A +:HDJG8: &6C6<:B:CI G:<>DC CDGI=:6HI *J::CHA6C9 JHIG6A>6 -=>H 9><>I6A A6C9 JH: B6E >H 6 EGD9J8I D; I=: *J::CHA6C9 %6C9 .H:
&6EE>C< )GD<G6B *%.&) 6C9 L6H EGD9J8:9 7N I=: *J::CHA6C9 DK:GCB:CI -=: 96I6H:I 8DBEG>H:H 6C ,+" K:8IDG <:D96I676H: 6I 6 CDB>C6A H86A: D;  -=: EG>B6GN A6C9JH:H
9>HEA6N:9 6G: ;DG:HIGN 6G:6H  =DGI>8JAIJG: !( DI=:G 8GDEH ( EGDI:8I:9 6G:6H ) G:H>9:CI>6A 6C9 >C9JHIG>6A 6G:6H +", H:B>C6IJG6A 6G:6H ,' HJ<6G86C: A6C9H ,. 6C9 L6I:G
7D9>:H 0 >G8A:9 6G:6H H=DL I=: 9>;;:G:CI HJ<6G86C: B>AA6G:6H EG:H:CI >C I=: G:<>DC -=: E=DID<G6E=H DC I=: 7DIIDB H=DL AD86A :M6BEA:H D; I=: I=G:: EG>B6GN A6C9JH:H 8DCH>9:G:9
EGDI:8I:9 A:;I H:B>C6IJG6A 8:CIG: 6C9 HJ<6G86C: G><=I 6G:6H
E6G@H 6C9 DI=:G 8DCH:GK:9 6G:6HV 6C9 >CI:CH>K: HJ<6G86C: EGD9J8I>DC
;GDB >GG><6I:9 6C9 9GNA6C9 6<G>8JAIJG: G:HE:8I>K:AN -=JH I=: 8DB7>
C6I>DC D; 7DI= EGDI:8I:9 6G:6H 6C9 HJ<6G86C: 6<G>8JAIJG6A A6C9 6A><CH
L>I= I=: 8DC8:EI D; %,) L=>8= >H 76H:9 DC >CI:CH>;N>C< EGD9J8I>DC ID
B6M>B>O: 6<G>8JAIJG6A N>:A9 L>I=>C 6 SM:9 6G:6 L=>A: 9:9>86I>C< DI=:G
A6C9 ID 7>D9>K:GH>IN 8DCH:GK6I>DC  G::C :I 6A  !JAB: :I 6A 
)=6A6C :I 6A  -67A:  H=DLH 6 FJ6A>I6I>K: 9:H8G>EI>DC D; I=: G6
I>DC6A: ;DG I=: 9>;;:G:CI H8:C6G>DH BD9:AA:9
>9:CI>86A >C I=: 0:I -GDE>8H L>I= EGDI:8I:9 6G:6H B6C6<:B:CI 86I:<DG>:H ""/ 6H 9:SC:9
7N I=: ".' ,DB: HB6AA 6G:6H D; =><=AN H><C>S86CI C6IJG6A :CK>GDCB:CIH C:6G I=:
8D6HIA>C: I=6I 6G: CDI ".' EGDI:8I:9 6G:6H 6G: 86I:<DG>H:9 7N %.&) 6H L:IA6C9H
6C9 6G: :M8AJ9:9 >C8AJ9:9 ;GDB DJG 6C6ANH>H %.&) 9>H6<<G:<6I:H 8DCH:GK6I>DC 6C9
C6IJG6A :CK>GDCB:CIH>CID 9>U:G:CI EGDI:8I>DC 86I:<DG>:H L=>8= 6G: 6AA >CI:<G6I:9 6H
EGDI:8I:9 6G:6H>C DJG BD9:A
"C H=DGI DJG BD9:A :MEADG:H %. 9NC6B>8H L>I= G:<6G9 ID H:B>C6I
JG6A 6G:6H %,! 6C9 I=: C:MJH D; EGDI:8I:9 6G:6HHJ<6G86C: A6C9 %,)
-=: %. H8:C6G>DH :MEADG:9 >C8AJ9: %,! L=:G: H:B>C6IJG6A 6G:6H >C
8G:6H:9:8G:6H: %,) L=:G: EGDI:8I:9 6C9 HJ<6G86C: 6G:6H >C8G:6H:
9:8G:6H: 6C9 . L=:G: EGDI:8I:9 6G:6H >C8G:6H: 6I I=: H6B: G6I: 6H
9JG>C< I=: E:G>D9  H:: ,"-"  (JG BD9:A :MEADG:H
I=: >BE68I DK:G I>B: D; I=:H: %. EGD8:HH:H DC HJ<6G86C: EGD9J8
I>DC 86G7DC H:FJ:HIG6I>DC 6C9 7>D9>K:GH>IN 8DCH:GK6I>DC "C I=>H G:<6G9
6AI=DJ<= %,) K:GHJH %,! HIJ9>:H 6G: JHJ6AAN ;D8JH:9 DC B>C>B>O>C<
IG69:DUH 7:IL::C 7>D9>K:GH>IN 6C9 6 EGD9J8I>DC <D6A HJ<6G86C: >C I=>H
86H: DJG G:H:6G8= 6AHD >CI:<G6I:H I=: HIJ9N D; DC: DI=:G , >: 86G7DC
I>K: D; 86G7DC :B>HH>DCH ;GDB 9:;DG:HI6I>DC >C IGDE>86A G:<>DCH JGI=:G
BDG: I=: HE6I>6AAN:MEA>8>I C6IJG: D; I=: BD9:A 6>BH ID 8DCIG>7JI: ID I=:
A68@ D; HE6I>6AAN:MEA>8>I %,)%,! HIJ9>:H >H8=:G :I 6A  %6L :I
6A 
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
Table 1
'6GG6I>K:H D; I=: H8:C6G>DH BD9:AA:9 ;DG I=: E:G>D9 
 :H8G>EI>DC
JHIG6A>66H6 ;DD97DLA;DGDI=:G8DJCIG>:H
 !9/066482 1<,70A9<5
&H 6G: 6G<J:9 ID 7: =:AE;JA ;DG HIJ9N>C< 8DBEA:M 9NC6B>8H >C
HD8>6A:8DAD<>86A HNHI:BH ,, 6H L:AA 6H <6>C>C< >CH><=IH I=6I HJE
EDGI I=: HJHI6>C67A: B6C6<:B:CI D; C6IJG6A G:HDJG8:H C :I 6A 
>A6IDK6 :I 6A  DCO6A:O+:9>C :I 6A  ,8=JAO: :I 6A 
-=: & EG:H:CI:9 >C I=>H E6E:G 86C 7: 8DCH>9:G:9 ID 7: 6C <:CI
6H:9 %6C9.H: &D9:A %.& H:: &6II=:LH :I 6A  )DA=>AA
:I 6A  L=>8= 8DB7>C:H ' ", :BE>G>86A 96I6 6C9 :ME:GI
@CDLA:9<: -=>H >CI:<G6I:9 BD9:AA>C< 6EEGD68= 6>BH ID 8DCIG>7JI: ID
DC: B6>C 9:B6C9 L>I=>C 7DI= I=: & 6C9 %.& 8DBBJC>I>:H
(,JAA>K6C :I 6A  ID 7J>A9 =N7G>9 &H I=6I >CI:<G6I: 9>;;:G:CI
I:8=C>FJ:H 6C9 I=JH 86EIJG: I=: 69K6CI6<:H D; 9>;;:G:CI BD9:AA>C< 6E
!:G: 'H 8DCHIGJ8I:9 JH>C< :'": 7J>A9:G IDDA  :'": 6C9
,&"%  6C9 ", A6N:GH JH>C< G8 ", 6C9 * ",  6H L:AA 6H
:BE>G>86A 96I6 6C9 :ME:GI DE>C>DC 6G: >CI:<G6I:9 >CID 6C & 8DC
HIGJ8I:9 JH>C< ':I%D<D 0>A:CH@N  ><  H=DLH I=: BD9:AA>C<
;G6B:LDG@ D; DJG BD9:A CDI: I=6I I=: >CI:<G6I:98=6G68I:G>HI>8 9D:H
CDI G:;:G ID I=: 68IJ6A >CI:<G6I>DC D; 6C & HD;IL6G: >CID 6 ",NHI:B
DG ' HD;IL6G: DG I=: DI=:G L6N 6GDJC9 7JI ID I=: JH: D; HE6I>6A
96I6 >: ", A6N:GH 6C9 'H >C 6 ':I%D<D BD9:A
-=: BD9:A 7J>A9>C< EGD8:HH HI6GI:9 7N >BEDGI>C< I=: EG>B6GN
A6C98DK:G B6E ;DG I=: 0:I -GDE>8H   6H 6 K:8IDG SA: >CID
':I%D<D -=>H EGD8:HH EGDK>9:9 6C >C>I>6A 9>HIG>7JI>DC D; A6C9JH:H ;DG
I=: 86H:HIJ9N 6G:6 L=:G: I=: A6C9JH: B6E H=DLC >C ><  L6H >B
EDGI:9 >CID ':I%D<D >: I=: B6E >C ><  H 6 G:HJAI :68= 8:AA >C
DJG ':I%D<D BD9:A 8DK:GH 6C 6G:6 D; =6 D; I=: 86H:HIJ9N 6G:6
H:: "BEDGI>C< ", A6N:GH >CID ':I%D<D ," 9D8JB:CI ;DG 9:I6>AH (JI
D; I=: I:C A6C9JH: INE:H EG:H:CI >C I=: 0:I -GDE>8H H:: ><  DCAN
I=G:: 6G: 8DCH>9:G:9 ;DG DJG G:H:6G8= 6C6ANH>H -=:H: >C8AJ9: G6>C;DG:HI
EGDI:8I:9 6G:6H C6I>K: E6HIJG:  EGD9J8I>DC ;DG:HIGN H:B>C6IJG6A 6G
:6H 6C9 HJ<6G86C: A6C9 9:K:ADE:9 6G:6H -=:H: I=G:: A6C9JH: INE:H
8DK:G  D; I=: IDI6A A6C9 >C I=: 0:I -GDE>8H JGI=:GBDG: I=: ;D8JH
DC I=:H: A6C9JH:H ;DAADLH I=: %,) K:GHJH %,! G6I>DC6A: :MEA6>C:9 6I I=:
7:<>CC>C< D; I=: &6I:G>6A 6C9 &:I=D9H H:8I>DC 6H L:AA 6H I=: 8DC8:E
IJ6A BD9:A 9:K:ADE:9 7N !>AA :I 6A 7 -=: %. ;DG I=: G:B6>C>C<
H:K:C A6C9JH:H =:G:6;I:G 86AA:9 DI=:G A6C9JH:H H:: .&% 9>6<G6B >C
><  6G: CDI 6C6ANH:9 >C I=: +:HJAIH  H:8I>DC 6AI=DJ<= I=:>G %.
EGD8:HH:H 6G: HI>AA 8DBEJI:9 ;DG I=: H6@: D; G:6A>HB
Fig. 2. &D9:AA>C< ;G6B:LDG@ L=:G: I=: 9>;;:G:CI BD9:AA>C< I:8=C>FJ:H 6C9 96I6 HDJG8:H >: & ' ", :BE>G>86A 96I6 6C9 :ME:GI @CDLA:9<: 6G: 8DB7>C:9 ID<:I=:G ID 7J>A9 I=:
>CI:<G6I:9 BD9:A EG:H:CI:9
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
Fig. 3. "C>I>6A  EG>B6GN A6C9JH: 9>HIG>7JI>DC ;DG I=: 0:I -GDE>8H D7I6>C:9 7N >CI:<G6I>C< 6 EG>B6GN A6C9JH: B6E   >CID ':I%D<D 'DI: I=6I I=: 86H:HIJ9N 6G:6 >H AD86I:9
7:IL::C I=: )68>S8 (8:6C ID I=: G><=I >C 7AJ: 6C9 DI=:G I:GG:HIG>6A :8DHNHI:BH ID I=: A:;I >C A><=I DG6C<: L=>8= 6G: CDI 8DCH>9:G:9 ;DG I=>H G:H:6G8= -=: A:<:C9 ;GDB I=>H S<JG: >H
6AHD JH:9 ;DG ><  7:ADL DG >CI:GEG:I6I>DC D; I=: G:;:G:C8:H ID 8DADJG >C I=>H S<JG: A:<:C9 I=: G:69:G >H G:;:GG:9 ID I=: 0:7 K:GH>DC D; I=>H 6GI>8A:
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6G: H86G8: $D8676H 6C9 G6<>8:K>8  ,JC 6C9 &PAA:G  &DG:
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>08>4,6 ,8/ 69A .98=0<@,>498 :9>08>4,6 =?4>,-60 >9 -0 .98@0<>0/ 48>9 =?2,<.,80
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6C9 ," 9D8JB:CI
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%>@:L>H: $,208>= G:EG:H:CI ;DG8:H 9G>K>C< %,! 6C9 %,) EGD8:HH:H 6I
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G:EG:H:CI>C< I=DH: EDA>8>:H >C8:CI>K:H 6C9 <DK:GC6C8: ;DG8:H 9G>K>C<
6<G>8JAIJG6A :ME6CH>DC 7N ;6GB:GH L=>8= >H I=: B6>C A6C9 8A:6G>C<
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Fig. 4. .&% 8I>K>IN >6<G6B ,IGJ8IJG: 9>6<G6B H=DL>C< I=: HI:E 7N HI:E EGD8:HH 8DBEJI:9 7N $,208>= 6C9 A6C9JH:H E6I8=:H8:AAH >C I=: BD9:A
EGD8:HH D88JGG>C< 6I I=: A6C9H86E:G:<>DC6A A:K:A >C I=: 0:I -GDE
>8H !>AA :I 6A 6 -=: H6B: >H I=: 86H: ;DG 7DI= $V:,208>= 6C9
$V7<,208>= L=>8= G:EG:H:CI EGDI:8I>DC 6C9 G:HIDG6I>DC HIG6I:<>:H >BEA:
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Fig. 5. 6N:H>6C :A>:; ':ILDG@ ' M6BEA: D; 6 ' 9:K:ADE:9 JH>C< :'":VQ L>I= 6 DC9>I>DC6A )GD767>A>IN -67A: )- DC I=: 7DIIDB DI= A><=I G:9 6C9 <G::C 7DM:H G:EG:H:CI
7>DE=NH>86A HE6I>6AAN :MEA>8>I >: ", CD9:H >: >CEJI CD9:H L=>A: 96G@ G:9 >: >CI:GB:9>6I: 6C9 N:AADL >: DJIEJI CD9:H 6G: 8DBEA:I:9 JH>C< :ME:GI @CDLA:9<: DADJG:9 76GH
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EGD767>A>IN ;DG DC: H:B>C6IJG6A A6C9JH: ID 7: EGDI:8I:9 =6K>C<  D; DCH:GK6I>DC )DI:CI>6A6C9  D; ,J<6G86C: )GD9J8I>DC )DI:CI>6A >H  7:>C< I=: EGD767>A>IN ID G:B6>C
6H H:B>C6IJG6A  6C9 ID 7:8DB: 9:K:ADE:9  J: ID  7:>C< =><=:G I=6C  I=: EG>DG LDJA9 8DBEJI:9 6H '*@,6?0 ;DG I=>H HE:8>S8 A6C9JH: DG >CI:GEG:I6I>DC D; I=: G:;:G:C8:H
ID 8DADJG >C I=>H S<JG: A:<:C9 I=: G:69:G >H G:;:GG:9 ID I=: 0:7 K:GH>DC D; I=>H 6GI>8A:
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BDK: 6GDJC9 I=: A6C9H86E: G:EG:H:CI>C< ;DG8:H 9G>K>C< %. DBEJI6
I>DC D; %. ;DAADLH I=: ;DAADL>C< G6I>DC6A: ;DG :68= A6C9JH: 8:AA 6 ID
I6A D; I=G:: %. HJ>I67>A>IN K6AJ:H >: '*@,6?0= 6G: 8DBEJI:9 E:G I>B:
HI:E DC: ;DG :68= INE: D; %. EGDI:8I>DC G:HIDG6I>DC 6C9 A6C9 8A:6G
>C< ;DG HJ<6G86C: -=JH ;DG :68= A6C9JH: DC: K6AJ: ;DG '*V:HJ>I67>A
>IN D; I=: A6C9JH: >; JCEGDI:8I:9 ID 7:8DB: 6 EGDI:8I:9 6G:6 DG ID
G:B6>C 6H EGDI:8I:9 >; 6AG:69N EGDI:8I:9 6CDI=:G ;DG '*V7< HJ>I67>A>IN
D; I=: A6C9JH: ID 7: 8DCK:GI:9 ID H:B>C6IJG6A A6C9 DG ID G:B6>C 6H
H:B>C6IJG6A >; 6AG:69N H:B>C6IJG6A 6C9 '*V/HJ>I67>A>IN D; I=: A6C9JH:
ID 7: 8DCK:GI:9 ID HJ<6G86C: DG ID G:B6>C 6H HJ<6G86C: A6C9 >; 6AG:69N 6
8GDE >H 8DBEJI:9 -=JH '*@,6?0= HI6I: I=: EGD767>A>IN D; :68= A6C9JH:
ID 7: 8DCK:GI:9 ID 6CDI=:G A6C9JH:DG ID G:B6>C I=: H6B: '*@,6?0=
6G: D7I6>C:9 ;GDB ", 6C9 ' :MEA6>C:9 7:ADL 6C9 K6GN ;GDB DC:
H8:C6G>D ID 6CDI=:G
K:GN I>B: HI:E :68= $,208> H:A:8IH I=: A6C9JH: L>I= I=: =><=
:HI 8DBE6I>7A: ID I=>H $,208>'*@,6?0 -=JH $V:,208>= DCAN H:6G8=
;DG '*V:@,6?0=$V7<,208>= DCAN ;DG '*V7<@,6?0= 6C9 $V/,208>= DCAN ;DG
'*V/@,6?0= &DG:DK:G :68= INE: D; $,208> H:A:8IH I=: A6C9JH: L>I=
I=: A6G<:HI CJB7:G D; C:><=7DJG>C< A6C9JH:H 8DGG:HEDC9>C< ID I=6I
$,208> INE: I=>H >H 8DBEJI:9 ID :C=6C8: E6I8=8:AA 8DCC:8I>K>IN
DG >CHI6C8: $V:,208>= H::@ A6C9JH:H L>I= BDG: V:A6C9JH:H 6GDJC9
$V/,208>= ;DG V/ 6C9 ) VBG6<:CIH ;DG V7< "; I=:G: 6G: CD A6C9JH:H D;
I=: H6B: INE: >C C:><=7DJG>C< A6C9JH:H I=: H:6G8=>C< G69>JH>H >C
8G:6H:9 JCI>A A6C9JH:H D; I=: H6B: INE: 6G: ;DJC9
6H:9 DC I=:H: GJA:H :K:GN I>B: HI:E :68= $,208> L>AA H:A:8I DC:
H>C<A: SC6A A6C9JH: 86AA:9 >,<20>:,>.3$,208>= I=:C BDK: ID I=:>G
8DGG:HEDC9>C< I6G<:IE6I8= 6C9 8DBEJI: DC: G6C9DBTD6I CJB7:G 7:
IL::C  6C9  86AA:9 $&@,6?0 >; I=: K6AJ: A>:H 7:IL::C  6C9 I=:
'*K6AJ: >C I=: I6G<:IE6I8= %. >C I=>H A6C9JH: >H 8DBEJI:9 !:C8:
I=: =><=:G I=: '*@,6?0 >C DC: A6C9JH: I=: =><=:G >IH EGD767>A>IN ID
8DBEJI: %. "; I=: K6AJ: 9D:H CDI A>: 7:IL::C  6C9 I=: '*@,6?0 I=:
A6C9JH: G:B6>CH 6H >I >H
-=>H 8N8A: >H 8DBEJI:9 :K:GN I>B: HI:E ;DG :68= $,208> I=JH 9G>
K>C< BD9:A DJI8DB:H +:<6G9A:HH D; L=:I=:G %. I6@:H EA68: DG CDI
:68= A6C9JH: 8DBEJI:H 9>;;:G:CI HJ<6G86C: EGD9J8I>DC 86G7DC H:FJ:H
IG6I>DC 6C9 7>D9>K:GH>IN 6A<DG>I=BH :K:GN I>B: HI:E 'DI: I=6I I=:G: 6G:
CD 6HHD8>6I:9 8DHIH ID 6<:CIH BDK:B:CI H>C8: $V/,208>=$V:,208>=
6C9 $V7<,208>= G:EG:H:CI ;DG8:H G:T:8I>C< <DK:GC6C8: 6GG6C<:B:CIH
I=6I 9G>K: %. 6C9 CDI HE:8>S8 H8=:B:H DG EDA>8>:H I=6I 8DJA9 7: HE:8>;
>86AAN 688DJCI:9
 ;JAA (K:GK>:L :H><C 8DC8:EIH 6C9 :I6>AH ( EGDID8DA 9:
H8G>7>C< I=: BD9:A >C 9:I6>A >H 6K6>A67A: >C I=: ,JEEDGI>C< "C;DGB6I>DC
," 9D8JB:CI
 ,C0=4,8 06401 "0>A9<5= ,8/ 0B:0<> 589A60/20
 ' >H 6 <G6E=>86A G:EG:H:CI6I>DC D; 6 H:I D; K6G>67A:H CD9:H
6C9 I=:>G 86JH6A G:A6I>DCH=>EH A>C@H ;DGB>C< 6 9>G:8I:9 68N8A>8 <G6E=
=6GC>6@  'D9:H G:EG:H:CI HNHI:B K6G>67A:H HJ8= 6H 7>D9>K:G
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
Fig. 6. ,E6I>6A H8:C6G>D DJIEJIH %6C9JH: K6G>6I>DCH 6G: H=DLC ;DG :68= H8:C6G>D . JH>C:HH H .HJ6A %,)  %6C9,E6G>C< %,!  %6C9,=6G>C< G:<6G9>C< I=: N:6GH  
6C9  'DI: I=6I I=: A:<:C9 ;GDB ><  =6H ID 7: JH:9 ;DG I=>H S<JG:
H>IN DG HJ<6G86C: N>:A9 L=>A: A>C@H G:EG:H:CI 86JH6A EGD767>A>HI>8 G:A6
I>DCH=>EH 7:IL::C ILD CD9:H 0>I=>C 6 ' :68= CD9: =6H 6 9:SC:9 H:I
D; HI6I:H86I:<DG>:H 6ADC< L>I= 6 DC9>I>DC6A )GD767>A>IN -67A: )-
L=>8= 9:SC:H ;DG :68= 86I:<DGN I=: EGD767>A>IN D; >I D88JGG>C< <>K:C
6AA EDHH>7A: 86I:<DGN 8DB7>C6I>DCH ;GDB I=: E6G:CI CD9:H
"C DJG BD9:A 'H 6G: >CI:<G6I:9 >C DJG & 6C9 JE96I:9 :K:GN
I>B: HI:E 76H:9 DC $,208>=%. 9:8>H>DCB6@>C< L=:G: DC: '
>H 8G:6I:9 ;DG :68= 6C6ANH:9 A6C9JH: INE: >: V: V, V/ '>C: IDI6A
'H 6G: 8DBEJI:9 >: DC: ' E:G INE: D; $,208>  JC9:G :68=
H8:C6G>D  L=:G: :68= ' =6H I=: H6B: HIGJ8IJG: 6C9 CD9:H 6H I=:
DC: H=DLC >C ><  -=: EGD767>A>I>:H >C :68= )- 8=6C<: :K:GN I>B:
HI:E L=:G: >C>I>6A K6AJ:H 6G: H:I 76H:9 DC 6 EGD9J8I 7:IL::C :ME:GI
DE>C>DC 6C9 ", 96I6 0=>A: I=: )- 86I:<DG>:H ;GDB I=: >CEJI CD9:H
:< <G>8JAIJG6A %6C9 A6HH>S86I>DC>C ><  G:EGD9J8: I=: 6IIG>7
JI:H ;GDB I=: ", A6N:GH I=JH CD :ME:GI76H:9 >CI:GEG:I6I>DC >H C::9:9
;DG I=:>G 8DBEA:I>DC I=: )-H ;GDB >CI:GB:9>6I: >: ,J<6G86C: )GD
9J8I>DC )DI:CI>6A 6C9 DJIEJI >: %. ,J>I67>A>IN CD9:H 6G: 8DB
EA:I:9 JH>C< :ME:GI DE>C>DC >C6AAN I=: %. ,J>I67>A>INDJIEJI CD9:
=6H I=G:: 9>;;:G:CI 86I:<DG>:H DC: ;DG :68= INE: D; %. EGD8:HH EGDI:8
I>DC G:HIDG6I>DC 6C9 EGD9J8I>DC9:K:ADEB:CI 0>I= 6 K6AJ: 7:IL::C
 6C9  :68= 86I:<DGN ;GDB I=>H DJIEJI CD9: :HI>B6I:H I=: EGD767>A>IN
;DG :68= %. INE: ID I6@: EA68: >C :68= A6C9JH: :K:GN I>B: HI:E >:
-=: EGD767>A>I>:H D; I=DH: )-H ;GDB >CI:GB:9>6I: 6C9 DJIEJI '
CD9:H ><  L:G: 8DBEJI:9 JH>C< :ME:GI DE>C>DC "C DG9:G ID <6I=:G
:ME:GI76H:9 FJ6A>I6I>K: 96I6 I=: ;D8JH <GDJEHB:I=D9 L6H JH:9
$>IO>C<:G  &DG<6C  >AA :I 6A  JGI=:GBDG: I6G
<:I K6AJ:H :68= H8:C6G>D 6C9 I=: BD9:AH I>B:H86A: L:G: :HI67A>H=:9
I=GDJ<= :ME:GI @CDLA:9<: 6C9 9>H8JHH:9 9JG>C< I=: ;D8JH <GDJE B::I
>C<H ,:: "CI:<G6I>C< :ME:GI @CDLA:9<: >C I=: BD9:AH:8I>DC >C I=: ,"
9D8JB:CI ;DG BDG: 9:I6>AH
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
3. Results
+:HJAIH G:<6G9>C< I=: >C9>86IDGH H:A:8I:9 L:G: D7I6>C:9 ;DG :68= D;
I=: I=G:: H8:C6G>DH . %,) %,! 6C9 <GDJE:9 >CID I=:>G HE6I>6A 6C9
:BE>G>86A >BE68IH  FJ6A>I6I>K: 6C6ANH>H L6H E:G;DGB:9 7:86JH: D; DJG
B6>C >CI:G:HI >C :MEADG>C< I=: DK:G6AA 9>;;:G:C8:H >C IG:C9H 6BDC< I=:
>C9>86IDGH 6C9 H8:C6G>DH I:HI:9
 =>47,>0/ =:,>4,6 47:,.>=
><  H=DLH I=: HE6I>6A :MEA>8>I DJIEJIH D7I6>C:9 L>I= ':I%D<D
CDI: I=6I I=: A:<:C9 ;GDB ><  >H JH:9 ID 9:H8G>7: ><  -=G:: DJIEJI
B6EH L:G: D7I6>C:9 ;DG :68= H8:C6G>D DC: ;DG :68= I>B: HI:E N:6G
  6C9  G:HJAI>C< >C C>C: B6EH >C IDI6A -=: ;DAADL>C<
H:8I>DCH  9:H8G>7: I=: HE6I>6A G:HJAIH D7I6>C:9 ;DG :68= D;
I=: I=G:: H8:C6G>DH . %,) %,!
 ?=480== = ?=?,6 )
-=: IDE GDL D; ><  H=DLH I=: HE6I>6A 9>HIG>7JI>DC D; A6C9JH:H
;DG I=: . H8:C6G>D "C I=>H H8:C6G>D EGDI:8I:9 6G:6H >C8G:6H: 7N 
>C DG9:G ID B::I I=: 8DCH:GK6I>DC I6G<:IH D; I=: 0DGA9 !:G>I6<: A>HI
>C< L=>A: EGD9J8I>DC B6>CAN HJ<6G86C: G:B6>CH HI67A: DK:G I>B: -=:
BDHI HE6I>6A CDI:LDGI=N IG:C9 >H 76H:9 DC I=DH: H:B>C6IJG6A 6G:6H >:
EDI:CI>6A 6C9 =><= 8DCH:GK6I>DC EDI:CI>6A K6AJ:H 7:>C< 8DCK:GI:9 >CID
EGDI:8I:9 6G:6H B6>CAN AD86I:9 ID I=: L:HI D; 8JGG:CIAN EGDI:8I:9 G6>C
;DG:HIH (I=:G EDI:CI>6A H>I:H ;DG C:L EGDI:8I:9 6G:6H 6G: AD86I:9 >C I=:
CDGI=L:HI &DHHB6C 6C9 HDJI=L:HI !:G7:GI +>K:G 6G:6H H:: >< 
;DG I=: HE:8>S8 AD86I>DC D; I=:H: 6G:6H H :HI>B6I:9 7:ADL I=>H H8:
C6G>D =6H EDH>I>K: >BE68IH DC 7>D9>K:GH>IN 6C9 86G7DC H:FJ:HIG6I>DC 7JI
C:<6I>K: >BE68IH DC HJ<6G86C: EGD9J8I>DC
 ,8/ =:,<482  '$
-=: 0:I -GDE>8H 8DCI>CJ:H ID B::I 8DCH:GK6I>DC I6G<:IH 7N >C8G:6H
>C< EGDI:8I:9 6G:6H 7N  8DB7>C:9 L>I= >C8G:6H:H >C HJ<6G86C: EGD
9J8I>DC 7N  ><  >C I=: B>99A: GDL H=DLH I=: HE6I>6A 9>HIG>7J
I>DC D; C:L EGDI:8I:9 6G:6H 6C9 C:L HJ<6G86C: A6C9H 8DCK:GI:9 ;GDB
H:B>C6IJG6A 6G:6H ,:B>C6IJG6A 6G:6H L>I= =><= 8DCH:GK6I>DC EDI:CI>6A
6C9 ADL HJ<6G86C: EGD9J8I>DC EDI:CI>6A K6AJ:H =6K: 6 =><=:G EGD76
7>A>IN D; 7:>C< EGDI:8I:9 L=>A: I=DH: L>I= =><= EGD9J8I>DC EDI:CI>6A
6C9 ADL 8DCH:GK6I>DC K6AJ:H =6K: 6 =><=:G EGD767>A>IN D; 7:>C< 9:K:A
DE:9 ;DG HJ<6G86C: EGD9J8I>DC ':L EGDI:8I:9 6G:6H ;DAADL 6 H>B>
A6G HE6I>6A 9>HIG>7JI>DC E6II:GC 6H >C . H8:C6G>D =DL:K:G I=:>G :M
I:CI >H ADL:G 9J: ID C:L HJ<6G86C: A6C9 D88JEN>C< H:B>C6IJG6A 6G:6H
I=6I 8DJA9 =6K: 7:8DB: EGDI:8I:9 DI=:GL>H: ':L HJ<6G86C: 6G:6H 6G:
B6>CAN AD86I:9 ID I=: :6HI D; I=: -67A:A6C9H L>I= HB6AA:G 6G:6H >C "CC>H
;6>A -JAAN 6C9 !:G7:GI +>K:G H :HI>B6I:9 7:ADL I=>H H8:C6G>D =6H EDH>
I>K: >BE68IH DC HJ<6G86C: EGD9J8I>DC 6C9 C:<6I>K: DG G:A6I>K:AN HI67A:
 ,8/ =3,<482  '
-=: *J::CHA6C9 6C9 JHIG6A>6C DK:GCB:CIH A:69 6 IG6CH>I>DC ID
L6G9H 6 BDG: BJAI>;JC8I>DC6A 9>H8DJGH: >: %,! L=:G:
L>A9A>;:;G>:C9AN ;6GB>C< EG68I>8:H >: H:B>C6IJG6A 6G:6H 6G: :C=6C8:9
 6I I=: :ME:CH: D; HJ<6G86C: N>:A9H 6C9 EGDI:8I:9 6G:6H "C ><
 I=: B6EH >C I=: 7DIIDB GDL H=DL C:L H:B>C6IJG6A 6G:6H >: C6
I:8I:9 6C9 HJ<6G86C: A6C9H 0=>A: C:L C6I>K: E6HIJG: 6G:6H 6G: B6>CAN
K6AJ: -67A:A6C9H C:L EGD9J8I>DC ;DG:HIGN 6G:6H 6G: 8DCK:GI:9 ;GDB
7DI= EG:K>DJHAN EGDI:8I:9 6G:6H 6C9 HJ<6G86C: A6C9H L>I= ADL 8DC
8:CIG::6HI D; I=: HIJ9N 6G:6 >: "CC>H;6>A -JAAN 6C9 !:G7:GI +>K:G
-=>H HE:8>S8
9>HIG>7JI>DC >: ADL K:<:I6I:9 C6I>K: E6HIJG: ID I=: L:HI 6C9 =><=AN
K:<:I6I:9 ;DG:HIGN 6G:6H <D>C< ;GDB I=: 8:CIG: ID I=: :6HI >H 9J: ID G6>C
;6AA K6AJ:H +6>C;6AA >H 6C >BEDGI6CI ;68IDG >C I=: IGDE>8H A>B>I>C< I=: :M
I:CI ID L=>8= =><=AN K:<:I6I:9 6C9 ;DG:HI:9 6G:6H <GDL L>I= G6>C;6AA K6A
J:H ADL:G I=6C  BB "C I=: 0:I -GDE>8H I=DH: 6G:6H L>I= G6>C;6AA
K6AJ:H 67DK:  BB 6G: AD86I:9 ;GDB I=: 8:CIG: ID I=: :6HI >: 6AA 6G
:6H 7JI I=: -67A:A6C9 H:: ><  -=JH 6G:6H AD86I:9 ID I=: L:HI =6K:
6 =><=:G EGD767>A>IN ID 7: 8DCK:GI:9 >CID EGD9J8I>DC ;DG:HIGN L=>A: 6G
:6H ID I=: :6HI >: -67A:A6C9 6G: BDG: A>@:AN ID H=DL C6I>K: E6HIJG:
H :HI>B6I:9 7:ADL I=: %,! H8:C6G>D =6H G:A6I>K:AN HI67A: DG EDH>I>K:
>BE68IH DC 7>D9>K:GH>IN 6C9 86G7DC H:FJ:HIG6I>DC N:I C:<6I>K: >BE68IH
 =>47,>0/ 47:,.>=
><  H=DLH I=: :BE>G>86A <G6E=>86A G:HJAIH ;GDB I=: >C9>86IDGH H:
>D9>K:GH>IN 6C9 :MI>C8I>DC 9:7I >C9>86IDGH H=DL I=: K6G>6I>DC D;
8JGG:CI 7>D9>K:GH>IN K6AJ:H 6C9 I=: ;JIJG: :MI>C8I>DC D; HE:8>:H 9J: ID
:K:CIH >C I=: E6HI G:HE:8I>K:AN L=:G: I=: A6II:G D88JGH 7:86JH: D; I>B:
9:A6NH 7:IL::C >BE68IH DC HE:8>:H 6C9 I=: HE:8>:H JAI>B6I: 9>H6EE:6G
6C8: #68@HDC 6C9 ,6M  "C H=DGI 7>D9>K:GH>IN H=DLH I=: <GDHH
7>D9>K:GH>IN L=:G:6H :MI>C8I>DC 9:7I H=DLH I=: C:I;JIJG: 7>D9>K:G
H>IN -=: . H8:C6G>D ><  H=DLH EDH>I>K: IG:C9H ;DG 7>D9>K:GH>IN
6C9 HA><=IAN 9:8G:6H>C< ;DG :MI>C8I>DC 9:7I L=>A: %,! H=DLH HA><=IAN
EDH>I>K: IG:C9H ;DG 7DI= >C9>86IDGH 6C9 %,) H=DLH 6 HI:69N HI67A: IG:C9
;DG 7>D9>K:GH>IN 6C9 6 9:8G:6H: ;DAADL:9 7N 6C :MEDC:CI>6A >C8G:6H: ;DG
:MI>C8I>DC 9:7I DI= 7>D9>K:GH>IN 6C9 :MI>C8I>DC 9:7I K6GN 76H:9 DC I=:
EGDEDGI>DC D; =67>I6I G:HIDG:9 6C9 9:HIGDN:9 6H L:AA 6H =67>I6I 8DCC:8
I>K>IN >: I=: =><=:G I=: 8DCC:8I>K>IN 6C9 =67>I6IH G:HIDG:9 I=: =><=:G
7>D9>K:GH>IN 6C9 ADL:G :MI>C8I>DC 9:7I K6AJ:H -=JH L=>A: . B6N 7:
6 HJHI6>C67A: H8:C6G>D ;DG 7>D9>K:GH>IN >C I=: H=DGII:GB H:: 7>D9>K:G
H>IN . I=>H H8:C6G>D 8DJA9 :C9 JE 9>B>C>H=>C< I=: 7>D9>K:GH>IN >C
I=: ADC<I:GB H:: :MI>C8I>DC 9:7I . ,>B>A6GAN N:I ID 6 =><=:G :M
I:CI I=: :MEDC:CI>6AAN >C8G:6H>C< :MI>C8I>DC 9:7I K6AJ:H D7I6>C:9 ;DG
%,) 6;I:G  8DJA9 6AHD B:6C I=6I 7>D9>K:GH>IN LDJA9 :C9 JE 9GDEE>C<
JC9:G %,) EG68I>8:H >C I=: ADC<I:GB H:: :MI>C8I>DC 9:7I %,) G:<6G9
A:HH D; I=: 8JGG:CI G:A6I>K:AN EDH>I>K: 7>D9>K:GH>IN G:HJAIH H:: 7>D9>K:G
H>IN %,) -=: >H8JHH>DC  H:8I>DC 6C6ANH:H I=: >BEDGI6C8: D; :MI>C8
I>DC 9:7I 6C9 C:I 7>D9>K:GH>IN K6AJ:H >C I=: 0:I -GDE>8H
+:<6G9>C< HJ<6G86C: EGD9J8I>DC . H=DLH HI:69N HI6I: HJ<6G86C:
K6AJ:H 7DI= >C IDCH 6C9 BDC:I6GN K6AJ: L=:G:6H %,! H=DLH 9:8G:6H
>C< K6AJ:H 6C9 %,) >C8G:6H>C< ,J<6G86C: K6AJ:H >C8G:6H: L>I= BDG:
A6C9 8A:6G:9 ;DG 6<G>8JAIJG: HJ8= 6H E6GI>6AAN >C %,) L=>A: EGD9J8I>DC
9:8G:6H:H L>I= 6G:6 EGDI:8I>DC . 6C9 G:HIDG6I>DC EGD8:HH:H %,!
-=: G:6HDC L=N HJ<6G86C: EGD9J8I>DC 9D:H CDI 9:8G:6H: JC9:G .
L=:G: BDG: 6C9 BDG: 6G:6H 6G: EGDI:8I:9 >H 7:86JH: HJ8= EGDI:8I>DC
D88JGH >C 8JGG:CI H:B>C6IJG6A 6G:6H >CHI:69 D; HJ<6G86C: A6C9 6G7DC
H:FJ:HIG6I>DC K6AJ:H A>@:L>H: HJ<6G86C: EGD9J8I>DC 8=6C<: DK:G I>B:
76H:9 DC %. L=>8= 6;;:8IH K:<:I6I>DC 8DK:G 6C9 <GDLI= !:G: .
H=DLH 6C :MEDC:CI>6A >C8G:6H: >C I=: 6BDJCI D; 86G7DC H:FJ:HI:G:9 6C9
%,! H=DLH 6 G:A6I>K:AN A>C:6G >C8G:6H: %,) >C 8DCIG6HI >H I=: DCAN H8:
6C9 BDC:I6GN K6AJ:
><  H=DLH I=: EDL:G 6C9 >CTJ:C8: D; EGDI:8I>DC 6C9 9:K:ADE
B:CI ;DG8:H DC 7>D9>K:GH>IN 6I I=: A6C9H86E: A:K:A "C E6GI>8JA6G >I
H=DLH I=: >BE68I DC 7>D9>K:GH>IN D; ILD H:IH D; 86H:H L>I= 9>;;:G:CI
>C>I>6A 6BDJCI D; EGDI:8I>DC ;DG8:H 9G>K>C< A6C9 EGDI:8I>DC $V:,208>=
6C9 9:K:ADEB:CI ;DG8:H 9G>K>C< A6C9 8A:6G>C< ;DG HJ<6G86C: EGD9J8
I>DC $V/,208>= -=: =:6IB6E DC IDE D; ><  H=DLH 7>D9>K:GH>IN G:
HJAIH L>I= DC: H>C<A: >C>I>6A $V:,208> 6C9 9>;;:G:CI >C>I>6A CJB7:G D;
$V/,208>= L=>A: I=: 7DIIDB =:6IB6E H=DLH G:HJAIH ;DG DC: H>C<A: >C>
I>6A $V/,208> 6C9 9>;;:G:CI >C>I>6A CJB7:G D; $V:,208>= -=: =><=:G
K6G>67>A>IN D; 7>D9>K:GH>IN >C I=: IDE =:6IB6E 8DBE6G:9 ID I=: 7DIIDB
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
Fig. 7. G6E=>86A H8:C6G>D DJIEJIH +:HJAIH 6G: H=DLC 6H I=: I:BEDG6A K6G>6I>DC >C C:I <6>CH ADHH:H D; 9>;;:G:CI HD8>D:8DCDB>8 6C9 :CK>GDCB:CI6A >C9>86IDGH ;DG :68= H8:C6G>D
.  <G::C %,)  G:9 %,!  7AJ: H:: A:<:C9 DI= HJ<6G86C: EGD9J8I>DC 6C9 86G7DC H:FJ:HIG6I>DC 6G: H=DLC >C IDCH 6C9 JHIG6A>6C DAA6GH . DADJG 76C9H G:EG:H:CI I=: HI6C
96G9 :GGDG 76C9H G:<6G9>C< 6AA I=: GJCH 8DBEJI:9 ;DG :68= >C9>86IDG JC9:G :K:GN H8:C6G>D -=: 7A68@ 8DADJG:9 A>C:H H=DL I=: B:6C K6AJ:H DG >CI:GEG:I6I>DC D; I=: G:;:G:C8:H ID 8DADJG
>C I=>H S<JG: A:<:C9 I=: G:69:G >H G:;:GG:9 ID I=: 0:7 K:GH>DC D; I=>H 6GI>8A:
=:6IB6E H=DLH I=6I 6H :ME:8I:9 7>D9>K:GH>IN >C I=: 0:I -GDE>8H >C
8G:6H:H 8DCH>9:G67AN L>I= HIGDC<:G EGDI:8I>DC ;DG8:H >: =><=:G CJB7:G
D; $V:,208>= "C 8DCIG6HI 9:K:ADEB:CI ;DG8:H $V/,208>= =6K: 6 A>B
>I:9 >CTJ:C8: DC 7>D9>K:GH>IN 7DIIDB =:6IB6E :K:C >C I=DH: H8:C6G
>DH L>I= HIGDC< 9:K:ADEB:CI ;DG8:H 9G>K>C< A6C9 8A:6G>C< ;DG 6<G>8JAIJG:
>: =><=:G CJB7:G D; $V/,208>= -=:H: G:HJAIH EGDK>9: 6 76H:A>C: ;DG
<DK:GC6C8: 9>H8JHH>DC 699G:HH:9 >C I=: >H8JHH>DC  H:8I>DC
4. Discussion
0=6I HD8>D:8DCDB>8 <DK:GC6C8: 6C9 :CK>GDCB:CI6A ;68IDGH 6G:
=:AE>C< ID G:8DC8>A: ;DD9 EGD9J8I>DC 8A>B6I: 8=6C<: B>I><6I>DC 6C9
7>D9>K:GH>IN 8DCH:GK6I>DC >C I=: 0:I -GDE>8H
.C9:G I=: ;G6B:LDG@ 6C9 BD9:AA>C< 6EEGD68= 8DCH>9:G:9 G:HJAIH
H=DL I=6I I=: . H8:C6G>D >C I=: ;DG:HI:9 A6C9H86E: D; I=: 0:I -GDE
>8H >H =:AE>C< ID EGDK>9: ;DD9 8DCH:GK: 7>D9>K:GH>IN 6C9 H:FJ:HI:G 6I
BDHE=:G>8 86G7DC -=:H: G:HJAIH 6G: D; BDG: >BEDGI6C8: 8DCH>9:G>C<
I=6I I=>H IGDE>86A 6G:6 6H L>I= DI=:G IGDE>86A G:<>DCH >H B6C6<:9 JC
9:G <AD76A 6C9 C6I>DC6A B6G@:I :8DCDB>:H I=6I <:C:G6AAN ;6KDJG A6C9
8A:6G>C< ;DG 6<G>8JAIJG: DK:G 8DCH:GK6I>DC 6AAH  JGI=:GBDG:
IG6CHA6I>C< I=: G:HJAIH ;GDB ><  >CID 6 <DK:GC6C8: 8DCI:MI I=: 8JG
G:CI HIG:C<I= D; I=: EDL:G D; <DK:GC6C8: >C I=: 0:I -GDE>8H ;D8JH:9 DC
EGDI:8I>C< G6>C;DG:HIH B6>CI6>C>C< =><= 7>D9>K:GH>IN 6C9 A>B>I>C< A6C9
;DG 9:K:ADEB:CI >H G:A6I>K:AN =><= ,>B>A6GAN I=: HIG:C<I= D; I=: EDL:G
D; <DK:GC6C8: 9G>K>C< A6C9 8A:6G>C< ;DG HJ<6G86C: EGD9J8I>DC >C I=: 0:I
-GDE>8H >H CDI HJ;S8>:CIAN HIGDC< ID 9:8G:6H: 7>D9>K:GH>IN :K:C >C I=DH:
H8:C6G>DH L=:G: 9:K:ADEB:CI ;DG8:H 6G: 8DCH>9:G67AN HIGDC<:G I=6C EGD
I:8I>DC ;DG8:H -=:G:;DG: I=:H: G:HJAIH ID<:I=:G L>I= I=: 7>D9>K:GH>IN
DJI8DB:H D7I6>C:9 JC9:G . H8:C6G>D ><  H=DL I=6I I=: 0:I
-GDE>8H LDJA9 CDI C::9 :M8:HH>K: 699>I>DC6A 8DCH:GK6I>DC <DK:GC6C8:
EDL:G >C DG9:G ID B6>CI6>C I=: 8JGG:CI >C8G:6H>C< 7>D9>K:GH>IN 6C9 86G
H H=DLC 7N DJG BD9:A I=: EDH>I>K: 7>D9>K:GH>IN 6C9 86G7DC H:
J:H =6K: I=:>G DG><>C >C I=: HIGDC<:G 8DCH:GK6I>DC ;DG8:H 8DBE6G:9 ID
:8DCDB>8 A6C9 8A:6G>C< ;DG8:H >C I=: 0:I -GDE>8H AI=DJ<= CDI :B
E>G>86AAN 699G:HH:9 >C DJG BD9:A N:I >CI:<G6I:9 >C I=: 8DC8:EIJ6A C6
IJG: D; $V:,208>= L: 6G<J: I=6I I=: 8DB7>C6I>DC D; 7DI= HIGDC< 7DI
IDBJE 6C9 IDE9DLC 8DCH:GK6I>DC ;DG8:H =6H 7::C I=: B6>C 9G>K:G D;
HJ8= DJI8DB:H DK:G I=: E6HI 9:869:H DIIDBJE ;DG8:H HI6GI:9 ID DG><
>C6I: >C I=: H I=GDJ<= I=: <GDL>C< EJ7A>8 @CDLA:9<: 6C9 6L6G:
C:HH D; I=: :CK>GDCB:CI6A HD8>6A 6C9 :8DCDB>8 H><C>;>86C8: D; L>A9:G
C:HH 6G:6H >C I=>H G:<>DC JG<  -=JH I=: A68@ D; HJ7HI6CI>6A :CK>
GDCB:CI6A BDK:B:CI I=6I =69 9DB>C6I:9 I=: 'DGI= *J::CHA6C9 HD8>:IN
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
Fig. 8. "BE68I D; <DK:GC6C8: 6C9 EDA>I>86A EDA>8N ;DG8:H DC 7>D9>K:GH>IN $V:,208>= 6C9 $V/,208>= G:;:G ID 8DCH:GK6I>DC 6C9 9:K:ADEB:CI ;DG8:H G:HE:8I>K:AN -=: =:6IB6E DC IDE H=DLH
7>D9>K:GH>IN K6G>6I>DC DK:G I>B: 8DCH>9:G>C< I=: B>C>BJB CJB7:G D; >C>I>6A $V/,208>= >: SK: ;DG 9>;;:G:CI >C>I>6A $V:,208>= >: K6AJ:H DC 16M>H -=: 7DIIDB =:6IB6E H=DLH 7>D9>
K:GH>IN K6G>6I>DC DK:G I>B: 8DCH>9:G>C< I=: B>C>BJB CJB7:G D; >C>I>6A $V:,208>= >: SK: ;DG 9>;;:G:CI >C>I>6A $V/,208>= (CAN G:HJAIH ;DG I=: %,) H8:C6G>D 6G: H=DLC 9J: ID I=>H H8:C6G>D
>C8AJ9>C< 9:K:ADEB:CI 6C9 EGDI:8I>DC ;DG8:H 8DBE:I>C< ;DG A6C9
H>C8: H:IIA:B:CI >C I=: H HI6GI:9 ID 8=6C<: DCH:GK6I>DC <GDJEH
AD86A 8>I>O:CH 6C9 EGDB>C:CI C6I>DC6A 6C9 >CI:GC6I>DC6A H8>:CI>HIH >C>I>
6I:9 6 9G>K: 76H:9 DC AD77N>C< 9>G:8I 68I>DC B6HH BD7>A>H6I>DC 6C9
EDA>I>86A :C9DGH:B:CIH 6<6>CHI I=: :8DCDB>8 ;DG8:H 9G>K>C< A6C9 8A:6G
>C< -=>H 7DIIDBJE BDK:B:CI L6H 67A: ID 8=6C<: EJ7A>8 6C9 <DK:GC
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I=: 67DK:CDI:9 7DIIDBJE 69KD868N >: :CK>GDCB:CI6A 6L6G:C:HH
ID B6@: G:BDK>C< AD<<>C< ;GDB I=: 0:I -GDE>8H 6 KDI:L>CC:G C6
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>8H ;DG:HIH  8@4<98708>,6=.408>4E. I=: G:<>DC >H I=: C9 BDHI >G
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>C< G:BC6CIH D; DC9L6C6 I=6I 6G: CDI ;DJC9 :AH:L=:G: *J::CHA6C9
DK:GCB:CI  :86JH: I=: 0:I -GDE>8H >H 6 0DGA9 !:G>I6<: ,>I:
>C 8DCIG6HI ID BDHI IGDE>86A 6G:6H AD86I:9 >C 9:K:ADE>C< 8DJCIG>:H 6C9
6 8DCH:GK6I>DC =DIHEDI >I >H :6H>:G ID ?JHI>;N 6C9 G:8:>K: HJEEDGI L>I=
G:<6G9 ID 8DCH:GK6I>DC  .98974. I=: IGDE>86A ;DG:HIH 6G: 6GDJC9
>:  (  ,:9?D 6C9 ,>BEHDC  JGI=:GBDG: L>I=
I=: 0DGA9 !:G>I6<: EGDI:8I>DC >C  86B: I=: 76CC>C< D; AD<<>C<
L>I=>C I=: CDL EGDI:8I:9 ;DG:HIH /6C8A6N  L=:G: ID96N DCAN
G:9J8:9 ;DG:HI 8A:6G>C< 6C9 H:A:8I>K: =6GK:HI>C< 8DCI>CJ:H DC EG>K6I:
A6C9 -=JH I>B7:G EGD9J8I>DC ;GDB ;DG:HIH >C I=: 0:I -GDE>8H >H 6 G:A6
I>K:AN JC8DBE:I>I>K: :8DCDB>8 JH: /6A:CI>C: 6C9 !>AA  :H>9:H
I=>H I=: :8DIDJG>HB >C9JHIGN >C I=: 0:I -GDE>8H L=>8= >H B6@>C<
6 A6G<: 8DCIG>7JI>DC ID I=: C6I>DC6A :8DCDBN 0--  >H 8JG
G:CIAN =:AE>C< ID 9>B>C>H= I=: >CTJ:C8: 6C9 C::9 D; 6<G>8JAIJG: 6C9
I>B7:G >C9JHIG>:H 6H :8DCDB>8 9G>K:GH D; I=: 0:I -GDE>8H :H>9:H I=>H
JHIG6A>6 >H 6 G>8= 9:K:ADE:9 8DJCIGN L=>8= IG6CHA6I:H >CID BDG: ;JC9
8DJCIG>:H L=>8= 6G: BDG: ;D8JH:9 DC HDAK>C< EDK:GIN 6C9 HD8>6A >HHJ:H
:99>6 :I 6A  !>AA :I 6A   9@0<8,8.0 EJ7A>8 <DK:G
C6C8: >C JHIG6A>6 8DBE6G:9 ID DI=:G 8DJCIG>:H >C ,DJI=:6HI H>6 >H
8JGG:CIAN 9D>C< 7:II:G L>I= G:<6G9 ID 9>;;:G:CI >C9>86IDGH HJ8= 6H 8DG
GJEI>DC 6C9 EDDG <DK:GC6C8: ,D9=> :I 6A  DJCIG>:H L>I= <DK
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
I>DC 8DCIGDA FJ6A>IN EJ7A>8 H:GK>8:H 6G: BDG: A>@:AN ID :ME:G>:C8: I=:
HE6I>6A :ME6CH>DC D; 6<G>8JAIJG: L=>A: I=DH: <DK:GCB:CIH L>I= =><=
I>DC :99>6 :I 6A  JGI=:GBDG: EJ7A>8 <DK:GC6C8: >C JHIG6A>6
FJ>G:H I=: HJHI6>C67A: JH: D; C6IJG6A 86E>I6A >C I=: 0:I -GDE>8H  09
2<,:34.,6 JHIG6A>6 =6H CD HE6I>6A 8DCT>8IH L>I= C:><=7DJG>C< 8DJCIG>:H
>C I:GBH D; A6C9H86E: B6C6<:B:CI 6C9 EGDI:8I:9 6G:6 8G:6I>DC -=JH
I=: *J::CHA6C9 DK:GCB:CI 86C B6C6<: I=: 0:I -GDE>8H L>I=DJI =6K
-=:H: ;68IDGH =6K: 8G:6I:9 6 8DCI:MI >C I=: 0:I -GDE>8H L=:G: 8DC
H:GK6I>DC >H EG>DG>I>O:9 DK:G A6C9 8A:6G>C< ;DG 6<G>8JAIJG: 1:I G:<6G9A:HH
D; I=: EDH>I>K: H=DGI 6C9 B:9>JBI:GB G:HJAIH D7I6>C:9 ;DG 7>D9>K:G
H>IN 6C9 8DCH:GK6I>DC ><H  6C9  CD 6HHJBEI>DCH H=DJA9 7: B69:
7>D9>K:GH>IN D7I6>C:9 >C DJG BD9:A ;DG :MI>C8I>DC 9:7I ><  0=>A:
I=: 7>D9>K:GH>IN S<JG: H=DLH I=: K6G>6I>DC D; 8JGG:CI <GDHH 7>D9>K:G
H>IN K6AJ:H :MI>C8I>DC 9:7I H=DLH I=: ;JIJG: :MI>C8I>DC D; HE:8>:H 9J:
ID :K:CIH >C I=: E6HI L=>8= D88JGH 7:86JH: D; I>B: 9:A6NH 7:IL::C
>BE68IH DC HE:8>:H 6C9 I=: HE:8>:H JAI>B6I: 9>H6EE:6G6C8: #68@HDC
6C9 ,6M  -=JH :MI>C8I>DC 9:7I EGDK>9:H @:N >C;DGB6I>DC 67DJI
I=: :FJ>A>7G>JB 7>D9>K:GH>IN >C I=: 0:I -GDE>8H L=>8= G:;:GH ID I=: ;J
IJG: ADC<I:GB C:I 7>D9>K:GH>IN K6AJ:H DC8: :MI>C8I>DC 9:7I G:68=:H
O:GD 6C9 I=: HNHI:B 8DB:H >CID :FJ>A>7G>JB#68@HDC 6C9 ,6M 
-=: 9>;;:G:C8: 7:IL::C I=: 8JGG:CI <GDHH 7>D9>K:GH>IN 6C9 I=: :FJ>
A>7G>JB C:I 7>D9>K:GH>IN >H E6GI>8JA6GAN >BEDGI6CI JC9:G I=: %,) H8:
7:8DB: C:<6I>K: >C I=: ADC<I:GB 9J: ID I=: >C8G:6H>C< :MI>C8I>DC 9:7I
H:: ><  H 6 G:HJAI L: 6G<J: I=6I 6CN H=DGI 6C9 B:9>JBI:GB EDH
>I>K: 7>D9>K:GH>IN K6AJ:H >C I=: 0:I -GDE>8H C::9 ID 7: 8DCH>9:G:9 L>I=
I=: 8G:6I>DC D; C:L EGDI:8I:9 6G:6H >C I=: 0:I -GDE>8H 8DJA9 7: 8JG
G:CIAN L:6@:C>C< EGDI:8I>DC ;DG8:H :AH:L=:G: >C JHIG6A>6 :HE:8>6AAN >C
*J::CHA6C9 L=:G: DCAN  D; A6C9 >H 8JGG:CIAN EGDI:8I:9 ;6G 7:
ADL I=:  HI6I:9 >C I=: >8=> >D9>K:GH>IN -6G<:I  -=>H 8DJA9 7:
G:A6I:9 ID I=: HD86AA:9 EJ7A>8 7>D9>K:GH>IN 9>H8DJGH: >BE68IH :MEADG:9
7N !>AA :I 6A 7 -=>H 8DC8:EI H6NH I=6I HD8>:IN 6HHD8>6I:H >C8G:6H:H
B:CIH I=JH A:69>C< ID 6 EJ7A>8 E:G8:EI>DC I=6I BDG: 7>D9>K:GH>IN >H 7:
>C< EGDI:8I:9 :< >C I=: 0:I -GDE>8H 6C9 I=:G:7N G:9J8>C< EJ7A>8 9>H
8DJGH: 67DJI I=: G>H@H D; 7>D9>K:GH>IN ADHH :AH:L=:G: :< >C I=: G:HI
D; *J::CHA6C9JHIG6A>6 -=JH G6I=:G I=6C :C=6C8>C< EGD8DCH:GK6I>DC
6G:6H >C I=: 0:I -GDE>8H 8DJA9 7: 9>B>C>H=>C< I=:B !>AA :I 6A 7
(K:G6AA L: 6G<J: I=6I I=: EDH>I>K: G:HJAIH D7I6>C:9 JC9:G DJG .
H8:C6G>D ;DG I=: 0:I -GDE>8H 86CCDI 7: 8DBE6G:9 ID . H8:C6G>DH >C
DI=:G IGDE>86A 6G:6H -=>H >H 7:86JH: I=: 0:I -GDE>8H EDHH:HH:H >IH DLC
E6GI>8JA6G HD8>D:8DCDB>8 :CK>GDCB:CI6A 8JAIJG6A 6C9 EDA>I>86A 8=6G
68I:G>HI>8H JGI=:GBDG: . H8:C6G>DH JC9:G<D E:G>D9H D; CDCA>C:6G
6C9 67GJEI 8=6C<:H I=JH 9>;;:G>C< ;GDB EA68: ID EA68: &JAA:G 
6C9 A>B>I>C< I=: EG:9>8I67>A>IN 6C9 :MIG6EDA6I>DC D; A6C9HNHI:BH J:
ID I=>H 9:8>9>C< L=>8= 6EEGD68= %,) DG %,! >H BDG: HJHI6>C67A: ;DG 6
IGDE>86A ,, >H 9>;S8JAI 8DCH>9:G>C< I=: 8=6AA:C<>C< <D6A D; B::I>C< 9>;
;:G:CI I6G<:IH JC9:G H>C<A: %,) 6C9 %,! H8:C6G>DH %6L :I 6A  "C
;68I I=: 9:76I: DK:G %,) DG %,! 8DJA9 7: 7AJGG:9 7N I=: 9>;;:G>C< HE6
I>6A H86A:H 8DCH>9:G:9 @GDDH :I 6A  !:C8: HDB: H8=DA6GH HJ<
<:HI DI=:G 6EEGD68=:H HJ8= 6H 6 B>MIJG: D; %,! L>I= %,)  DG9DC :I
6A  +:CL>8@ 6C9 ,8=:AA=DGC  DG BJAI>EA:H86A: A6C9 HE6G>C<
@GDDH :I 6A  6H EDI:CI>6A E6I=L6NH ID DK:G8DB: I=: %,) K:GHJH
%,! 9>8=DIDBN +:CL>8@ 6C9 ,8=:AA=DGC 
5. Conclusions
-=: I6@: =DB:B:HH6<: D; I=>H 6GI>8A: >H ILD;DA9
 -=: 8JGG:CI . 8DCI:MI >C I=: ;DG:HI:9 ,, D; I=: 0:I -GDE
>8H G:<>DC >H =:AE>C< ID G:8DC8>A: 7>D9>K:GH>IN 8DCH:GK6I>DC 8A>B6I:
8=6C<: B>I><6I>DC 6C9 HJ<6G86C: EGD9J8I>DC -=>H >H 9J: ID I=:
8DJA9 =6K: >IH DG><>C >C I=: 8DB7>C6I>DC 6C9 >CI:<G6I>DC D; 7DI
IDBJE 6C9 IDE9DLC 8DCH:GK6I>DC ;DG8:H DK:G I=: A6HI 9:869:H 6H
L:AA 6H ;JGI=:G HD8>DEDA>I>86A A:<6A :CK>GDCB:CI6AH8>:CI>S8 :8D
CDB>8 <DK:GC6C8: 6C9 <:D<G6E=>86A ;68IDGH -=>H >H 6C DJIHI6C9>C<
68=>:K:B:CI ;DG 6 IGDE>86A G:<>DC 8DCH>9:G>C< I=6I BDHI D; I=:B
6G: 8=6G68I:G>O:9 ;DG =6K>C< HIGDC<:G :8DCDB>8 A6C9 8A:6G>C< ;DG8:H
8DBE6G:9 ID 8DCH:GK6I>DC I=JH :C=6C8>C< 7>D9>K:GH>IN ADHH =67>I6I
9:HIGJ8I>DC 8A>B6I: 8=6C<: 6C9 DI=:G :CK>GDCB:CI6A >HHJ:H
 :8>9>C< 7:IL::C %,) DG %,! 6EEGD68=:H 86CCDI 7: 6C :>I=:GDG
EGDEDH>I>DC -=JH 6 B>MIJG: D; H=6G>C< 6C9 HE6G>C< L>AA 7: >C DG9:G
ID B::I 8DCH:GK6I>DC <D6AH >C 6 LDGA9 L>I= 6 <GDL>C< 9:B6C9 ;DG
9>;;:G:CI , -GDE>86A ,, 6G: 8DBEA:M 9NC6B>8 6C9 CDCA>C:6G HNH
I:BH I=:G:;DG: I=: 6INE>86A . 8DCI:MI >C I=: 0:I -GDE>8H 86CCDI
7: :MIG6EDA6I:9 CDG 8DBE6G:9 ID . H8:C6G>DH ;GDB DI=:G IGDE>
86A 6G:6H 6H I=: 0:I -GDE>8H EDHH:HH:H >IH DLC E6GI>8JA6G HD8>D:8D
CDB>8 :CK>GDCB:CI6A 8JAIJG6A 6C9 EDA>I>86A 8DCI:MI -=JH :68= <:
D<G6E=>8 8DCI:MI 6C9 H:I D; HI6@:=DA9:GH L>AA C::9 ID :MEADG: 6AI:G
C6I>K: HJHI6>C67A: HDAJI>DCH 76H:9 DC I=:>G DLC AD86A 6C9 G:<>DC6A
8=6G68I:G>HI>8H 'DC:I=:A:HH I=: %,) K:GHJH %,! ;G6B:LDG@ =6H I=:
EDI:CI>6A ID B::I BJAI>EA: <D6AH I=6I L=:C >CI:<G6I:9 L>I=>C HE6
;DG 8DBEA:M ,,
-=>H G:H:6G8= 9>9 CDI G:8:>K: 6CN HE:8>S8 <G6CI ;GDB ;JC9>C< 6<:C
8>:H >C I=: EJ7A>8 8DBB:G8>6A DG CDI;DGEGDSI H:8IDGH
Declarations of interest
Appendix A. Supplementary data
,JEEA:B:CI6GN 96I6 ID I=>H 6GI>8A: 86C 7: ;DJC9 DCA>C: 6I =IIEH
%.&) JHIG6A>6C DAA67DG6I>K: %6C9JH: 6C9 &6C6<:B:CI )GD<G6B )6GIC:GH 
-=: JHIG6A>6C %6C9JH: 6C9 &6C6<:B:CI A6HH>S86I>DC 3DCA>C:4 K6>A67A: 6I =IIE
!6C97DD@:9C)6GI5.E96I:(8ID7:GE9; 88:HH:9  &6G8= 
<G>JIJG:H  ,J<6G86C:DK:GK>:L 3(CA>C:4 K6>A67A: 6I =IIELLL6<G>;JIJG:H
8DB6J;6GB9>K:GH>INHJ<6G86C:88:HH:9  &6G8= 
A6B<>G & :I 6A  HH:HH>C< G:<JA6I>C< 6C9 EGDK>H>DC>C< :8DHNHI:B H:GK>8:H >C 6
8DCIG6HI>C< IGDE>86A ;DG:HI A6C9H86E: 8DA "C9>86I  
C<:AH:C  9  &DK>C< =:69 L>I= + "HHJ:H (EI>DCH 6C9 "BEA>86I>DCH
"(+ D<DG "C9DC:H>6
C % :I 6A  <:CI 76H:9 BD9:AA>C< >C 8DJEA:9 =JB6C 6C9 C6IJG6A HNHI:BH
!', A:HHDCH ;GDB 6 8DBE6G6I>K: 6C6ANH>H CC HHD8 B :D<G  
6AAH   0=N -GDE>86A DJCIG>:H G: .C9:G9:K:ADE:9 -=: '6I>DC6A JG:6J D; 8D
CDB>8 +:H:6G8= 3DCA>C:4 K6>A67A: 6I =IIELLLC7:GDG<9><:HI?JCL
=IBA88:HH:9  #JAN 
JG< &   6>GCH 6C9 6G 'DGI= CK>GDCB:CI :CI:G  !DL I=: 0:I -GDE
>8H 06H 0DC ' 3DCA>C:4 K6>A67A: 6I =IIE86;C:8DG<6J67DJI86;C:8
=DLI=:L:IIGDE>8HL6HLDC88:HH:9  #6CJ6GN 
:99>6 &  :I 6A  DK:GC6C8: 6<G>8JAIJG6A >CI:CH>S86I>DC 6C9 A6C9 HE6G>C< >C
IGDE>86A HDJI= B:G>86 )GD8 '6IA 869 ,8> . ,    
98D,60D&0/480>,6 9?<8,6918@4<98708>,6!,8,20708> BBB  BBBBBB
:A>D  :I 6A  &D9:A>C< A6C9 JH: 9:8>H>DCH L>I= 6N:H>6C C:ILDG@H HE6I>6AAN
:MEA>8>I 6C6ANH>H D; 9G>K>C< ;DG8:H DC A6C9 JH: 8=6C<: CK>GDC &D9:A ,D;IL 
=6GC>6@   6N:H>6C C:ILDG@H L>I=DJI I:6GH " &6<   
JGI>H  :I 6A  -=: <G:6I :ME:G>B:CI L>I= 9:KDAK:9 '+& <DK:GC6C8: A:HHDCH ;GDB
8DBBJC>IN :C<6<:B:CI >C JHIG6A>6 6C9 ':L 2:6A6C9 H>C8: I=: H JHIG6A6H #
CK>GDC &6C6<   
  :E6GIB:CI D; <G>8JAIJG: 6C9 >H=:G>:H ,I6I: D; *J::CHA6C9  %6C9JH: &6E
E>C< 0:I -GDE>8H 3B6E4 ,86A: D;  K6>A67A: 6I *J::CHA6C9 ,E6I>6A 6I
6AD<J: *,E6I>6A %6HI JE96I:9 'DK:B7:G  =IIEFA9HE6I>6A>C;DGB6I>DCFA9
<DK6J86I6AD<J: 88:HH:9 (8I 
0!  6N:H>6C ':ILDG@H 6 J>9: ;DG -=:>G EEA>86I>DC >C '6IJG6A +:HDJG8:
&6C6<:B:CI 6C9 )DA>8N -:8=C>86A +:EDGI CD  :E6GIB:CI D; I=: CK>GDCB:CI
06I:G !:G>I6<: 6C9 I=: GIH JHIG6A>6C DK:GCB:CI
,"-"  %6C9JH: ,JBB6GN  0:I -GDE>8H :E6GIB:CI D; ,8>:C8: "C
;DGB6I>DC -:8=CDAD<N 6C9 "CCDK6I>DC *J::CHA6C9 DK:GCB:CI 3DCA>C:4 K6>A67A:
6I =IIEHEJ7A>86I>DCHFA9<DK6J96I6H:IA6C9JH:HJBB6GNG:HDJG8:
7;9::8;:88:HH:9  (8ID7:G 
@GDDH # :I 6A  ,E6G>C< A6C9 ;DG 7>D9>K:GH>IN 6I BJAI>EA: HE6I>6A H86A:H GDCI 8DA
KDA 3
( DD9 6C9 <G>8JAIJG: (G<6C>O6I>DC D; I=: .C>I:9 '6I>DCH  -=: ,I6I: D; DD9
6C9 <G>8JAIJG: <G>8JAIJG: ,:G>:H 
:9DGDU '/ :I 6A  +69>86AAN G:I=>C@>C< 6<G>8JAIJG: ;DG I=: HI 8:CIJGN ,8>:C8:
  
:CC>C< -  =6AA:C<:H 6C9 (EEDGIJC>I>:H ;DG I=: 0DGA9H DG:HIH >C I=: ,I :C
IJGN SGHI :9H ,EG>C<:G DG9G:8=I ':I=:GA6C9H
>A6IDK6 - /:G7JG< )! )6G@:G  ,I6CC6G9   ,E6I>6A 6<:CI76H:9 BD9:AH
;DG HD8>D:8DAD<>86A HNHI:BH 8=6AA:C<:H 6C9 EGDHE:8IH CK>GDC &D9:A ,D;IL  
>H8=:G # :I 6A  %6C9 HE6G>C< K:GHJH A6C9 H=6G>C< BDK>C< ;DGL6G9 DCH:GK %:II
  
ANK7?:G<   >K: B>HJC9:GHI6C9>C<H 67DJI 86H:HIJ9N G:H:6G8= *J6A "CF  
DA:N # :I 6A  AD76A 8DCH:FJ:C8:H D; A6C9JH: ,8>:C8:   
:'": ,&"%  G6E=>86A ':ILDG@ "CI:G;68: :'": ,&"% 3DCA>C:4K6>A67A: 6I
=IIELLL76N:H;JH>DC8DB 88:HH:9 #JA 
>AA ) :I 6A  &:I=D9H D; 96I6 8DAA:8I>DC >C FJ6A>I6I>K: G:H:6G8= >CI:GK>:LH 6C9 ;D
8JH <GDJEH G :CI #  
DCO6A:O+:9>C # :I 6A  ,E6I>6A 6N:H>6C 7:A>:; C:ILDG@H 6H 6 EA6CC>C< 9:8>H>DC
  
DCO6A:O+:9>C # :I 6A  "IH CDI I=: L=6I 7JI I=: =DL :MEADG>C< I=: GDA: D; 9:7I
>C C6IJG6A G:HDJG8: JCHJHI6>C67>A>IN )AD, (C:   :
DG9DC "# :I 6A  DD9 )GD9J8I>DC 6C9 '6IJG: DCH:GK6I>DC =6AA:C<:H 6C9 ,DAJ
I>DCH SGHI :9 -6NADG 6C9 G6C8>H ADG:C8:
G::C + :I 6A  6GB>C< 6C9 I=: ;6I: D; L>A9 C6IJG: ,8>:C8:  
!6GG>HDC ) :I 6A  %>C@6<:H 7:IL::C 7>D9>K:GH>IN 6IIG>7JI:H 6C9 :8DHNHI:B H:G
K>8:H 6 HNHI:B6I>8 G:K>:L 8DHNHI ,:GK  
!>AA + :I 6A  96EI>K: 8DBBJC>IN76H:9 7>D9>K:GH>IN 8DCH:GK6I>DC >C JHIG6A>6H
IGDE>86A G6>C;DG:HIH CK>GDC DCH:GK   
!>AA + :I 6A  -=: B6IJG6I>DC D; 7>D9>K:GH>IN 6H 6 <AD76A HD8>6A:8DAD<>86A >HHJ: 6C9
>BEA>86I>DCH ;DG ;JIJG: 7>D9>K:GH>IN H8>:C8: 6C9 EDA>8N JIJG:H  
!>AA + :I 6A 6 DAA67DG6I>DC BD7>A>H:H >CHI>IJI>DCH L>I= H86A:9:E:C9:CI 8DBE6G6
I>K: 69K6CI6<: >C A6C9H86E:H86A: 8DCH:GK6I>DC CK>GDC ,8> )DA  
!>AA + :I 6A 7 0=N 7>D9>K:GH>IN 9:8A>C:H 6H EGDI:8I:9 6G:6H >C8G:6H: I=: :;;:8I
D; I=: EDL:G D; <DK:GC6C8: G:<>B:H DC HJHI6>C67A: A6C9H86E:H ,JHI6>C ,8>  
!DUB6CC & :I 6A  -=: >BE68I D; 8DCH:GK6I>DC DC I=: HI6IJH D; I=: LDGA9H K:GI:
7G6I:H ,8>:C8:   
!JAB: & :I 6A  DCH:GK>C< I=: 7>G9H D; .<6C96H 76C6C68D;;:: 6G8 A6C9 HE6G
>C< 6C9 A6C9 H=6G>C< 8DBE6G:9 )AD, (C:  
#68@HDC ,- ,6M   6A6C8>C< 7>D9>K:GH>IN >C 6 8=6C<>C< :CK>GDCB:CI :MI>C8
I>DC 9:7I >BB><G6I>DC 8G:9>I 6C9 HE:8>:H IJGCDK:G -G:C9H 8DA KDA  
$>IO>C<:G #  -=: B:I=D9DAD<N D; ;D8JH <GDJEH I=: >BEDGI6C8: D; >CI:G68I>DC 7:
IL::C G:H:6G8= E6GI>8>E6CIH ,D8 !:6AI= "AAC  
$D8676H / G6<>8:K>8 ,  6N:H>6C C:ILDG@H 6C9 6<:CI76H:9 BD9:A>C< 6EEGD68=
;DG JG76C A6C9JH: 6C9 EDEJA6I>DC 9:CH>IN 8=6C<: 6 ', BD9:A # :D<G ,NHI 
 
%6L  :I 6A  :II:G A6C9JH: 6AAD86I>DC DJIE:G;DGBH A6C9 HE6G>C< 6C9 A6C9 H=6G
>C< 6EEGD68=:H ID 8DCH:GK6I>DC >C :CIG6A $6A>B6CI6C "C9DC:H>6 >DA DCH:GK 
%NC6B - :I 6A  96EI>C< H8>:C8: ID 696EI>K: B6C6<:GH HE>9:G<G6BH 7:A>:; BD9
:AH 6C9 BJAI>6<:CI HNHI:BH BD9:A>C< DCH:GK 8DA   
&6II=:LH + :I 6A  <:CI76H:9 A6C9JH: BD9:AH 6 G:K>:L D; 6EEA>86I>DCH
%6C9H8 8DA   
&DG<6C %  -=: D8JH GDJE J>9: DD@ ,6<: )J7A>86I>DCH %DC9DC
&JAA:G   +:<>B: H=>;IH A>B>I I=: EG:9>8I67>A>IN D; A6C9HNHI:B 8=6C<: AD76A CK
>GDC =6C<:   
':AA:B6C  :I 6A  -=: CK>GDCB:CI6A DD9 G>H>H I=: CK>GDCB:CIH +DA: >C
K:GI>C< JIJG: DD9 G>H:H  .') +6E>9 +:HEDCH: HH:HHB:CI .C>I:9 '6I>DCH C
K>GDCB:CI )GD<G6B +"G:C96A G:C96A 'DGL6N
'>8=DAHDC " :I 6A  >HIJG76C8: G:<>B:H >C 'DGI= *J::CHA6C9 G6>C ;DG:HIH 6
G::K6AJ6I>DC D; I=:>G G:A6I>DCH=>E ID HE:8>:H G>8=C:HH 6C9 9>K:GH>IN JHI # 8DA 
(,JAA>K6C  :I 6A  ,IG6I:<>8 9>G:8I>DCH ;DG 6<:CI76H:9 BD9:AA>C< 6KD>9>C< I=:
10' HNC9GDB: # %6C9 .H: ,8>   
):G:O&>C6C6   "BEGDK>C< :8DHNHI:B H:GK>8:H BD9:AA>C< >CH><=IH ;GDB 6 6N:H>6C
C:ILDG@ IDDAH G:K>:L CK>GDC &D9:A ,D;IL  
)=6A6C  :I 6A  +:8DC8>A>C< ;DD9 EGD9J8I>DC 6C9 7>D9>K:GH>IN 8DCH:GK6I>DC A6C9
H=6G>C< 6C9 A6C9 HE6G>C< 8DBE6G:9 ,8>:C8:  
)DA=>AA #  :I 6A  <:CI76H:9 BD9:AA>C< D; A6C9JH: :;;:8IH DC :8DHNHI:B EGD8:HH:H
6C9 H:GK>8:H # %6C9 .H: ,8>   
*J::CHA6C9 DK:GCB:CI ,I6I: D; I=: CK>GDCB:CI  0:I -GDE>8H D; *J::CHA6C9
0DGA9 !:G>I6<: '6IJG6A G>I:G>6 3DCA>C:4 K6>A67A: 6I =IIEHLLL:=EFA9<DK6J
HI6I:D;I=::CK>GDCB:CISC9>C<>988:HH:9  &6G8= 
+:9S:A9   CDGI= *J::CHA6C9H IGDE>86A G6>C;DG:HIH I=: LDGA9 =:G>I6<: 8DCIGDK:GHN
"C "C )6AD & &:GN 9H ,JHI6>C67A: DG:HIGN =6AA:C<:H ;DG :K:ADE>C< DJC
IG>:H CK>GDCB:CI6A ,8>:C8: 6C9 -:8=CDAD<N %>7G6GN KDA  ,EG>C<:G DG9G:8=I
+:CL>8@  ,8=:AA=DGC '   E:GHE:8I>K: DC A6C9 HE6G>C< K:GHJH A6C9 H=6G>C< "C
CH:AA  >7HDC  ,6AI  9H %:6GC>C< ;GDB <G>:CK>GDCB:CI ,8=:B:H >C JH
IG6A>6 "CK:HI>C< >C >D9>K:GH>IN 6C9 (I=:G 8DHNHI:B ,:GK>8:H DC 6GBH '1 )G:HH
6C7:GG6 - JHIG6A>6
,8=JAO: # :I 6A  <:CI76H:9 BD9:AA>C< D; HD8>6A:8DAD<>86A HNHI:BH 68=>:K:B:CI
8=6AA:C<:H 6C9 6 L6N ;DGL6G9 #,,,   
,:9?D + ,>BEHDC +  -6G>U %>7:G6A>O6I>DC 0DD9 -G69: ADLH 6C9 AD76A
DG:HIH >H8JHH>DC )6E:G  +:HDJG8:H ;DG I=: JIJG: 06H=>C<IDC 
,B>I= +" :I 6A  (E:G6I>DC6A>H>C< :8DHNHI:B H:GK>8: 6HH:HHB:CI >C 6N:H>6C 7:A>:;
C:ILDG@H ME:G>:C8:H L>I=>C I=: (E:C', EGD?:8I 8DHNHI ,:GK   
,D9=> ', :I 6A  -=: HI6I: 6C9 8DCH:GK6I>DC D; ,DJI=:6HI H>6C 7>D9>K:GH>IN >D
9>K:GH DCH:GK  
,JC 2 &PAA:G    ;G6B:LDG@ ;DG BD9:AA>C< E6NB:CIH ;DG :8DHNHI:B H:GK>8:H
L>I= 6<:CI76H:9 BD9:AH 6N:H>6C 7:A>:; C:ILDG@H 6C9 DE>C>DC 9NC6B>8H BD9:AH C
K>GDC &D9:A ,D;IL CK>GDC &D9:A ,D;IL  
-:9:H8D ) :I 6A  HI>B6I>C< =DL B6CN JC9:H8G>7:9 HE:8>:H =6K: <DC: :MI>C8I
DCH:GK >DA   
I:C GD:@:  :I 6A  0=>8= H:CH>I>K>IN 6C6ANH>H B:I=D9 H=DJA9 " JH: ;DG BN
6<:CI76H:9 BD9:A # GI>; ,D8 ,D8 ,>BJA6I   
.'  .C>I:9 C6I>DCH ;G6B:LDG@ 8DCK:CI>DC DC 8A>B6I: 8=6C<: 9G6;I 9:8>H>DC
)  "C DC;:G:C8: D; I=: )6GI>:H I= ,:HH>DC  :8:B7:G DE:C=6<:C
/6A:CI>C: ), !>AA +  -=: :HI67A>H=B:CI D; 6 LDGA9 =:G>I6<: 6G:6 "C ,IDG@ '
-JGIDC ,& 9H %>K>C< >C 6 NC6B>8 -GDE>86A DG:HI %6C9H86E: A68@L:AA )J7
A>H=>C< (M;DG9 EE 
/6C8A6N #$  -GDE>86A G6>C;DG:HI AD<<>C< >C CDGI= *J::CHA6C9 L6H >I HJHI6>C67A:
CC DG   
/6C8A6N #$  DCIG6HIH 7:IL::C 7>DAD<>86AAN76H:9 EGD8:HH BD9:AH 6C9 B6C6<:
B:CIDG>:CI:9 <GDLI= 6C9 N>:A9 BD9:AH ,JHI6>C67A: I>B7:G =6GK:HI>C< H>BJA6I>DC
HIJ9>:H >C I=: IGDE>86A G6>C;DG:HIH D; CDGI= *J::CHA6C9 DG 8DA &6C6<  
/:CI:G ( :I 6A  ,>MI::C N:6GH D; 8=6C<: >C I=: <AD76A I:GG:HIG>6A =JB6C ;DDIEG>CI
6C9 >BEA>86I>DCH ;DG 7>D9>K:GH>IN 8DCH:GK6I>DC '6I DBBJC  
06I:G=DJH: # :I 6A   ,8>:CI>S8 DCH:CHJH ,I6I:B:CI %6C9 .H: "BE68IH DC
G:6I 6GG>:G +::; 06I:G *J6A>IN 6C9 8DHNHI:B DC9>I>DC G>H76C: JHIG6A>6 -=:
,I6I: D; *J::CHA6C9
0> #  %6C9H86E: HJHI6>C67>A>IN H8>:C8: :8DHNHI:B H:GK>8:H 6C9 =JB6C L:AA7:>C<
>C 8=6C<>C< A6C9H86E:H %6C9H8 8DA   
0>A:CH@N .  ':IAD<D :CI:G ;DG DCC:8I:9 %:6GC>C< 6C9 DBEJI:G76H:9 &D9:A
0>AA>6BH $# :I 6A  DG:HIH D; :6HI JHIG6A>6 I=: I= 7>D9>K:GH>IN =DIHEDI "C
268=DH G6C@  =G>HI>6C !67:A #6C 9H >D9>K:GH>IN !DIHEDIH >HIG>7JI>DC 6C9
)GDI:8I>DC D; DCH:GK6I>DC )G>DG>IN G:6H ,EG>C<:G :GA>C !:>9:A7:G< :GA>C !:>9:A
7:G< EE 
0-& 0:I -GDE>8H &6C6<:B:CI JI=DG>IN  3DCA>C:4 K6>A67A: 6I =IIEHLLL
L:IIGDE>8H<DK6J 88:HH:9  #JAN 
0-- 0DGA9 -G6K:A  -DJG>HB DJC8>A  -G6K:A  -DJG>HB 8DCDB>8 "BE68I
 JHIG6A>6 3DCA>C:4 K6>A67A: 6I =IIEHLLLLII8DG<B:9>6SA:HG:EDGIH
:8DCDB>8>BE68IG:H:6G8=8DJCIG>:H6JHIG6A>6E9;88:HH:9  &6G8=
1>C +$  /6A>9>IN 6C9 <:C:G6A>O6I>DC >C ;JIJG: 86H: HIJ9N :K6AJ6I>DCH K6AJ6I>DC
  
... Then, the agent of governance has to choose the policy to implement according to these ranks, among others. In two articles governance interacts only with the ecological system Gonzalez-Redin et al., 2019). In these articles, governance is represented by an agent that manages its own parcels of land. ...
... For example, in the work of Gross et al. (2006), subsidies depend on droughts. In two articles, the links are bidirectional Gonzalez-Redin et al., 2019). In only one case, the link is from governance to the ecological system : a case where governance acts directly on the forest (cutting) (Dupont et al., 2016). ...
L’approvisionnement des citoyens en eau potable de qualité est un enjeu de santé publique, auquel s’ajoutent des enjeux environnementaux et économiques. L’agriculture est l’une des principales menaces pour la qualité de la ressource en eau potable, notamment à cause des pollutions diffuses dans les aires d’alimentation de captages. Les programmes de protection des captages vis-à-vis des pollutions diffuses d’origine agricole reposent principalement sur la participation volontaire des agriculteurs. L’objectif de cette thèse est d’étudier, à l’aide d’un modèle multi-agents, quels sont les impacts de la gouvernance sur l’évolution des pratiques agricoles, en prenant en compte les interactions entre les mesures de protection mises en œuvre, les dynamiques comportementales des agriculteurs et les facteurs liés au système écologique. Pour ce faire, nous avons dans un premier temps réalisé une revue de littérature des modèles multi-agents de systèmes socio-écologiques représentant la gouvernance. Nous nous sommes intéressés aux apports et perspectives de ce champ de recherche. Nous nous sommes appuyés sur cette revue afin de construire un modèle multi-agents pour analyser la gouvernance de la qualité de l’eau dans une aire l’alimentation de captage en décrivant les comportements des agriculteurs grâce à la théorie du comportement planifié. Un premier modèle nous a permis d’analyser l’efficacité et l’efficience de programmes de protection composés de deux mesures, une compensation financière et une mesure de formation. Nous avons ainsi pu tester l’impact des caractéristiques comportementales des agriculteurs et des interactions entre les agriculteurs sur les résultats des programmes en termes d’évolution des pratiques agricoles. Dans un second modèle, nous nous sommes intéressés plus particulièrement à l’effet de l’information sur le niveau de pollution de l’eau, en fonction des préférences environnementales des agriculteurs et de l’état initial du système écologique. Les simulations permettent de mettre en évidence le rôle positif des instruments d’information dans la gestion de la qualité de l’eau. Cette thèse met en évidence, sur la base d’une approche pluridisciplinaire, le rôle des caractéristiques des mesures de protection, des agriculteurs et du système écologique dans l’impact de la gouvernance de la qualité de l’eau sur les évolutions des pratiques agricoles.
... The shrink in ES globally affects more than 3 billion people (Nkonya et al. 2016) and comes at a degradation cost of 60% of the ES (WHO 2005). Moreover, the land degradation and subsequently diminishing ES have now become a global issue, which is highlighted regularly by various researchers across the world under different timelines (Gonzalez-Redin et al. 2019;Nkonya et al. 2016;Sutton et al. 2016;Gibbs and Salmon 2015;Gisladottir and Stocking 2005;Oldeman et al. 1990). Although different restoration measures were adopted to overcome these issues, there is still a need to assess land degradation thoroughly and monitor the adopted restoration practices. ...
Full-text available
Restoring degraded land is essential for regaining ecosystem services (ES) and attaining the UN-Sustainable Development Goals by 2030. Unfortunately, 24% of the global lands are degraded, significantly affecting the lives of 3.2 billion people worldwide. Therefore, innovative restoration practices are vital during 'UN-Decade on Ecosystem Restoration.' A meta-analysis of 2093 documents on land degradation and restoration was conducted in this context, and 117 empirical studies were analyzed in detail. These studies were based on the different drivers of land degradation as per the criteria of IPBES and IPCC, respectively. Results suggested that woodland encroachment (18.25%), cropland expansion (18.11%), species loss/ compositional shifts (16.06%), climatic factors (14.96%), infrastructure development/urbanization (14.17%), water erosion (13.87%), wind erosion (9.49%) and other demographic pressures (8.66%) were the significant drivers of land degradation. Interestingly, there was a continent-wide change in the critical drivers of land degradation and depleting ES. The infrastructure development/urbanization, demography, and economic attributes were the essential drivers in Asia-Pacific and African regions. In contrast, the fire-regime shift and invasiveness were the significant drivers in Europe, and the climatic attribute was the crucial driver in the Americas. Out of the 117 studies selected worldwide, some ongoing restoration efforts had little emphasis on research-driven on-site restoration for improving different ES. Furthermore, some restoration projects lack proper stakeholder involvement thereby, fail to attract large-scale public acceptance. Moreover, only 12.8% of the studies focused on improving the ES in highly degraded lands. Therefore, this meta-analysis suggests that site-specific, research-driven, and on-site restoration strategies coupled with proper stakeholder engagement are imperative for regaining the ES and functions of the degraded landscape to attain UN-SDG.
... To capture the complexity of highly dynamic SES and explore drivers of and responses to a trap situation, agent-based models (ABM) have evolved as promising extensions of other modelling approaches (Filatova et al., 2013;Schulze et al., 2017). ABMs have been widely used to present and analyse LULCC (Amadou et al., 2018;Bert et al., 2011;Gonzalez-Redin et al., 2019;Murray-Rust et al., 2014), to explore human-environment interactions of complex SES (Bitterman and Bennett, 2018;Iwamura et al., 2014), regime shifts (Filatova et al., 2016;Lade et al., 2015), social networks (Manson et al., 2016), environmental management (Le Page et al., 2013), or to understand livestock mobility (Fust and Schlecht, 2018) and poverty traps (Dou et al., 2020). One of the main advantages of ABM is its ability to depict human behaviour in a more realistic way and simultaneously take into account heterogeneity, learning, and human-environment interactions (Filatova et al., 2013;Smajgl et al., 2011). ...
CONTEXT In Madagascar land use pressure on natural resources has increased drastically over the last decades. For subsistence farmers this situation often leads to an accelerated unsustainable exploitation of resources with negative consequences for their livelihood, which can be described as a social-ecological trap (SET). OBJECTIVE Our paper seeks to understand the dynamics of SETs and demonstrates a model-driven scenario on how farmers may escape the trap. For this, we developed a spatially explicit empirical agent-based model (SEALM) to simulate possible future trends of farmers' crop management and the effects of these trends on the environment, household (HH) economy, food self-sufficiency (FSS) and HH coping strategies to food insecurity. METHODS Using links between social-ecological system (SES) components that depict real-world conditions, SEALM focuses on three village communities for which extensive data were available from transdisciplinary research comprising surveys, remote sensing analysis, and field-based validation. To identify the most significant parameters and to quantify how parameter uncertainty influences model outcomes, local and global sensitivity analyses were performed. Simulations were conducted in annual time steps from 2015 to 2045 to depict two contrasting scenarios: A baseline scenario (A) and an improved crop management scenario to increase FSS (B). For scenario assessments we used direct simulation outputs (FSS, HH income, land cover) and further indices calculated based on model outcomes (coping strategy index, landscape fragmentation, and the Gini coefficient). RESULTS AND CONCLUSIONS Scenario A predicted expansion of cropland and fragmentation of remaining forest areas. Simulations at each time step displayed how SET situations occurred due to self-reinforcing ecological and social constraints and affected HHs future coping capacity to food shortages. Here, FSS was insufficient (< 1.0) for most HHs and was <0.5 for years with rainfall deficits. Scenario B demonstrated a way to navigate out of the SET by increasing crop yields reflecting improved management and resulting in significantly higher FSS values and a lower coping strategy index. SEALM considers the heterogeneity in farmers' abilities, constraints, behaviour and decision-making and depicts the dynamic interplay of SES components contributing to SET. SIGNIFICANCE SEALM serves as a discussion support with local stakeholders and experts and it allows to better tailor site specific land use recommendations due to its empirical driven and spatially explicit character. However, strategies and interventions that lower the poverty rate in the long term and encourage exit out of trap situations require major policy changes.
... Land selection for agricultural production is an important area of research because accurate territorial determination is essential for successful product growth and for sustainable agriculture. Because of the need for land that is built, while the existing land area is very limited, so that land shortages will occur in the future [37]. The impact of agricultural land shortages will affect food production and food security [3]. ...
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Increasing the population of the population increased demand for agricultural production, so this has an impact on reducing the use of agricultural land. Identification of land suitability is important so that there is an evaluation of land use to increase land productivity now and in the future. the purpose of this study is to evaluate the suitability of agriculture land to increase the production of paddy harvest on each paddy field with physical constraints. therefore, that it can help the stakeholder of agriculture land to take sustainable strategic decision making. Therefore, dynamic system modeling is applied to analyze the level of land suitability for paddy based on plant requirements, quality and land characteristics. This study can be used as a condition forecast that develops a system dynamics model to learn about future patterns of change in land use management that can support multipurpose analysis of the objectives for optimal agricultural productivity concerning food security.
... To illustrate, the impact of landscape structure on ecosystem services has been investigated through empiric statistical models (e.g., [21][22][23]) and system dynamics modelling (e.g., [24]). Agent based modelling has also been used to model decision-making of agents (e.g., farmers) and analyze interrelations of ecosystem services and land-use at the landscape scale (e.g., [25,26]). ...
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Agroforestry has been promoted as a key forest landscape restoration (FLR) option to restore ecosystem services in degraded tropical landscapes. We investigated the share and type of agroforestry selected in an optimized landscape, accounting for a mosaic of alternative forest landscape restoration options (reforestation and natural succession) and forest and common agricultural land-uses. We extend previous studies on multi-objective robust optimization and the analytic hierarchy process by a systematic sensitivity analysis to assess the influence of incorporating agroforestry into a landscape. This approach accounts for multiple objectives concurrently, yet data and computational requirements are relatively low. Our results show that experts from different backgrounds perceive agroforestry (i.e., alley cropping and silvopasture) very positively. Inclusion of large shares of agroforestry (41% share of landscape) in the FLR mix enhanced simulated ecosystem service provision. Our results demonstrate that landscapes with high shares of agroforestry may also comprise of high shares of natural forest. However, landscapes dominated by single agroforestry systems showed lower landscape multifunctionality than heterogeneous landscapes. In the ongoing effort to create sustainable landscapes, our approach contributes to an understanding of interrelations between land-covers and uncertain provisions of ecosystem services in circumstances with scarce data.
... Land selection for agricultural production is an important area of research because accurate territorial determination is essential for successful product growth and for sustainable agriculture. Because of the need for land that is built, while the existing land area is very limited, so that land shortages will occur in the future [37]. The impact of agricultural land shortages will affect food production and food security [3]. ...
... By using TEK, they have maintained sustainable traditional agricultural practices, traditional forest management and conservation practices, and traditional livelihoods within their territories. These practices are important for maintaining biodiversity and ecosystem services that help people adapt and mitigate climate change [87]. Consequently, the areas under an indigenous community's control are effectively conserved and can be considered as Indigenous and Community Conserved Areas, ICCAs [88]. ...
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The traditional knowledge of indigenous people is often neglected despite its significance in combating climate change. This study uncovers the potential of traditional ecological knowledge (TEK) from the perspective of indigenous communities in Sarawak, Malaysian Borneo, and explores how TEK helps them to observe and respond to local climate change. Data were collected through interviews and field work observations and analysed using thematic analysis based on the TEK framework. The results indicated that these communities have observed a significant increase in temperature, with uncertain weather and seasons. Consequently, drought and wildfires have had a substantial impact on their livelihoods. However, they have responded to this by managing their customary land and resources to ensure food and resource security, which provides a respectable example of the sustainable management of terrestrial and inland ecosystems. The social networks and institutions of indigenous communities enable collective action which strengthens the reciprocal relationships that they rely on when calamity strikes. Accordingly, the communities maintain their TEK through cultural festivals and oral traditions passed from one generation to another. TEK is a practical tool that helps indigenous communities adapt to climate risks and promotes socio-ecological resilience, which upholds social empowerment and sustainable resource management.
Finding the optimal land allocation for providing ecosystem services, conserving biodiversity and maintaining rural livelihoods is a key challenge of agricultural management and land-use planning. Agroforestry has been widely discussed as a sustainable land-use solution and as one strategy to improve the provision of multiple ecological and economic functions in agricultural landscapes. In this study, we use the backdrop of agroforestry research to evaluate a method from the multi-criteria decision analysis toolbox: robust multi-objective optimization. The key feature of this modelling approach is its capacity to integrate uncertain ecological and socio-economic data. We illustrate the optimization model with a case study from eastern Panama, showing how the model can bring together scientific and practical knowledge to provide potentially desirable landscape compositions from the perspective of farmers, a public perspective, and a compromise solution. Example results of our case study show how to assess whether agroforestry is a desirable component in a landscape composition to satisfy multiple objectives of different interest groups. Furthermore, we use the model to demonstrate how different objectives influence the optimal area share and type of agroforestry. Due to its parsimonious nature, the model could be used as a starting point of an interactive co-learning process with decision-makers, researchers and other stakeholders. The model, however, is not yet suitable for an exact prediction of future land-use dynamics, for questions of spatially explicit land-use configuration, studies going beyond the regional scale or for socio-economic interactions of agents. Therefore, we outline future research needs and recommendations for other types of models or hybrid approaches.
Terrestrial ecosystem services (ES) are vulnerable to land use and land cover changes (LULCC). These changes are triggered by different drivers of change (e.g., economic, social, political, environmental - climate change). Understanding the potential future LULCC is an effective way to anticipate the impacts on ES supply. In recent years, some researchers applied different spatial modelling methods to assess the potential LULCC future impacts on ES supply, but so far, no systematic review was carried out. This work aims to do a bibliographic review about future LULCC and their implications on ES supply (provisioning, regulating, and cultural services). After a rigorous bibliographic review, we identified 957 papers. However, only 79 papers meet the criteria to be used in the review. The results showed that (i) the studies have been mainly focused on Asia (55.70%) and Europe (17,72%); (ii) the most common and extensively used models to project future LULCC were cellular automata (30.86%), CLUE-S model (8.64%) and Land Change Modeler (8.64%); and (iii) the most used methods to assess future impacts on ES were the InVEST model (24.04%), and equations used in previous works (12.5%). These studies were mainly focused on measuring future impacts on provisioning (44.11%) and regulating services (43.59%). Also, most of the works lack external validation. The diversity of studies evaluated allowed to recognise gaps and outline insights into the current scientific research on this scientific domain, representing an essential contribution to the current state of knowledge by supporting both practitioners and scientists.
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Tropical regions cover approximately 36% of the Earth's landmass. These regions are home to 40% of the world's population, which is projected to increase to over 50% by 2030 under a remarkable climate variability scenario often exacerbated by El Niño Southern Oscillation (ENSO) and other climate teleconnections. In the tropics, ecohydrological conditions are typically under the influence of complex land-ocean-atmosphere interactions that produce a dynamic cycling of mass and energy reflected in a clear partition of water fluxes. Here, we present a review of 7 years of a concerted and continuous water stable isotope monitoring across Costa Rica, including key insights learned, main methodological advances and limitations (both in experimental designs and data analysis), potential data gaps, and future research opportunities with a humid tropical perspective. The uniqueness of the geographic location of Costa Rica within the mountainous Central America Isthmus, receiving moisture inputs from the Caribbean Sea (windward) and the Pacific Ocean (complex leeward topography), and experiencing strong ENSO events, poses a clear advantage for the use of isotopic variations to underpin key drivers in ecohydrological responses. In a sequential approach, isotopic variations are analyzed from moisture transport, rainfall generation, and groundwater/surface connectivity to Bayesian and rainfall-runoff modeling. The overarching goal of this review is to provide a robust humid tropical example with a progressive escalation from common water isotope observations to more complex modeling outputs and applications to enhance water resource management in the tropics.
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A debt-based economy cannot survive without economic growth. However, if private debt consistently grows faster than GDP, the consequences are financial crises and the current unprecedented level of global debt. This policy dilemma is aggravated by the lack of analyses factoring the impact of debt-growth cycles on the environment. What is really the relationship between debt and natural resource sustainability, and what is the role of debt in decoupling economic growth from natural resource availability? Here we present a conceptual Agent-Based Model (ABM) that integrates an environmental system into an ABM representation of Steve Keen’s debt-based economic models. Our model explores the extent to which debt-driven processes, within debt-based economies, enhance the decoupling between economic growth and the availability of natural resources. Interestingly, environmental and economic collapse in our model are not caused by debt growth, or the debt-based nature of the economic system itself (i.e. the ‘what’), but rather, these are due to the inappropriate use of debt by private actors (i.e. the ‘how’). Firms inappropriately use bank credits for speculative goals–rather than production-oriented ones–and for exponentially increasing rates of technological development. This context creates temporal mismatches between natural resource growth and firms’ resource extraction rates, as well as between economic growth and the capacity of the government to effectively implement natural resource conservation policies. This paper discusses the extent to which economic growth and the availability of natural resources can be re-coupled through a more sustainable use of debt, for instance by shifting mainstream banking forces to partially support environmental conservation as well as economic growth.
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Understanding social-ecological systems (SES) is crucial to supporting the sustainable management of resources. Agent-based modelling is a valuable tool to achieve this because it can represent the behaviour and interactions of organisms, human actors and institutions. Agent-based models (ABMs) have therefore already been widely used to study SES. However, ABMs of SES are by their very nature complex. They are therefore difficult to parameterize and analyse, which can limit their usefulness. It is time to critically reflect upon the current state-of-the-art to evaluate to what degree the potential of agent-based modelling for gaining general insights and supporting specific decision-making has already been utilized. We reviewed achievements and challenges by building upon developments in good modelling practice in the field of ecological modelling with its longer history. As a reference, we used the TRACE framework, which encompasses elements of model development, testing and analysis. We firstly reviewed achievements and challenges with regard to the elements of the TRACE framework addressed in reviews and method papers of social-ecological ABMs. Secondly, in a mini-review, we evaluated whether and to what degree the elements of the TRACE framework were addressed in publications on specific ABMs. We identified substantial gaps with regard to (1) communicating whether the models represented real systems well enough for their intended purpose and (2) analysing the models in a systematic and transparent way so that model output is not only observed but also understood. To fill these gaps, a joint effort of the modelling community is needed to foster the advancement and use of strategies such as participatory approaches, standard protocols for communication, sharing of source code, and tools and strategies for model design and analysis. Throughout our analyses,we provide specific recommendations and references for improving the state-of-the-art. We thereby hope to contribute to the establishment of a new advanced culture of agent-based modelling of SES that will allowus to better develop general theory and practical solutions.
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Feeding the world's growing human population is increasingly challenging, especially as more people adopt a western diet and lifestyle. Doing so without causing damage to nature poses an even greater challenge. This book argues that in order to create a sustainable food supply whilst conserving nature, agriculture and nature must be reconnected and approached together. The authors demonstrate that while the links between nature and food production have, to some extent, already been recognized, until now the focus has been to protect one from the impacts of the other. Instead, it is argued that nature and agriculture can, and should, work together and ultimately benefit from one another. Chapters describe efforts to protect nature through globally connected protected area systems and illustrate how farming methods are being shaped to protect nature within agricultural systems. The authors also point to many ways in which nature benefits agriculture through the ecosystem services it provides. Overall, the book shows that nature conservation and food production must be considered as equally important components of future solutions to meet the global demand for food in a manner that is sustainable for both the human population and the planet as a whole.
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Human pressures on the environment are changing spatially and temporally, with profound implications for the planet's biodiversity and human economies. Here we use recently available data on infrastructure, land cover and human access into natural areas to construct a globally standardized measure of the cumulative human footprint on the terrestrial environment at 1 km(2) resolution from 1993 to 2009. We note that while the human population has increased by 23% and the world economy has grown 153%, the human footprint has increased by just 9%. Still, 75% the planet's land surface is experiencing measurable human pressures. Moreover, pressures are perversely intense, widespread and rapidly intensifying in places with high biodiversity. Encouragingly, we discover decreases in environmental pressures in the wealthiest countries and those with strong control of corruption. Clearly the human footprint on Earth is changing, yet there are still opportunities for conservation gains.
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A common approach to the conservation of farmland biodiversity and the promotion of multifunctional landscapes, particularly in landscapes containing only small remnants of non-crop habitats, has been to maintain landscape heterogeneity and reduce land-use intensity. In contrast, it has recently been shown that devoting specific areas of non-crop habitats to conservation, segregated from high-yielding farmland (“land sparing”), can more effectively conserve biodiversity than promoting low-yielding, less intensively managed farmland occupying larger areas (“land sharing”). In the present paper we suggest that the debate over the relative merits of land sparing or land sharing is partly blurred by the differing spatial scales at which it is suggested that land sparing should be applied. We argue that there is no single correct spatial scale for segregating biodiversity protection and commodity production in multifunctional landscapes. Instead we propose an alternative conceptual construct, which we call “multiple-scale land sparing,” targeting biodiversity and ecosystem services in transformed landscapes. We discuss how multiple-scale land sparing may overcome the apparent dichotomy between land sharing and land sparing and help to find acceptable compromises that conserve biodiversity and landscape multifunctionality.
Nine Bayesian Belief Networks (BBNs) were developed within the OpenNESS project specifically for modelling ecosystem services for case study applications. The novelty of the method, its ability to explore problems, to address uncertainty, and to facilitate stakeholder interaction in the process were all reasons for choosing BBNs. Most case studies had some local expertise on BBNs to assist them, and all used expert opinion as well as data to help develop the dependences in the BBNs. In terms of the decision scope of the work, all case studies were moving from explorative and informative uses towards decisive, but none were yet being used for decision-making. Three applications incorporated BBNs with GIS where the spatial component of the management was critical, but several concerns about estimating uncertainty with spatial modelling approaches are discussed. The tool proved to be very flexible and, particularly with its web interface, was an asset when working with stakeholders to facilitate exploration of outcomes, knowledge elicitation and social learning. BBNs were rated as very useful and widely applicable by the case studies that used them, but further improvements in software and more training were also deemed necessary.
Numerous studies attempt to unravel the role played by Biodiversity in ecosystems and ES reliance on Biodiversity. Achieving this aim is difficult given: the multi-layered Biodiversity-ES relationship; the temporal and spatial heterogeneity of ES; and, the interactions between biotic and abiotic components in ecosystems influencing processes and services. Bayesian networks have recently gained importance in ecological modelling. The integration of empirical data with expert knowledge and the explicit treatment of uncertainties, demonstrate their usefulness. Publications describing network-based Biodiversity-ES models, demonstrate their application is still limited. A watershed's environmental risk management network modelled from a Biodiversity-ES perspective is discussed. It demonstrates an improvement on conventional approaches, expressing risk in terms of the underlying causal relations between environmental risk events, triggers, controls and consequences. The model is developed in AgenaRisk and two other tools, Netica and Hugin. A comparison between them highlights the dependence on the tool of choice.
Existing methodologies of sensitivity analysis may be insufficient for a proper analysis of Agent-based Models (ABMs). Most ABMs consist of multiple levels, contain various nonlinear interactions, and display emergent behaviour. This limits the information content that follows from the classical sensitivity analysis methodologies that link model output to model input. In this paper we evaluate the performance of three well-known methodologies for sensitivity analysis. The three methodologies are extended OFAT (one-factor-at-a-time), and proportional assigning of output variance by means of model fitting and by means of Sobol’ decomposition. The methodologies are applied to a case study of limited complexity consisting of free-roaming and procreating agents that make harvest decisions with regard to a diffusing renewable resource. We find that each methodology has its own merits and exposes useful information, yet none of them provide a complete picture of model behaviour. We recommend extended OAT as the starting point for sensitivity analysis of an ABM, for its use in uncovering the mechanisms and patterns that the ABM produces.