DOI:   http://dx.doi.org/10.22092/jaep.2016.106611           

Nezara viridula  Brachynema germarii (: )             

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1*23  @1: @B3% Q R%  $ Nezara viridula  Brachynema germarii D $ D1 $ &3 N1 &% OP/ >B)  ; M=1 6  A"Z3 6Z=#  &% Nezara viridula "Z3 X3 .  X U,  6) UB71 VW=1  8=:%# O 7)B# (Maxent) #B) % T:%/ N1 &% $SB3% \ $\: &% $SB\3%  8=:%# N1 . D3% 6B7# 31  O1. [R OR)  6B7# D Brachynema germarii "Z3 X3   S P \=+=1 \& ab\3 _`\ &% $S B\3% \ " ) 8=:%# UR% N1 6 , $ Maxent $; .  DR$ .  6 , R%  ]B1 DS  6) ^/ X ')\ 1 6\=1%$  6)d3 c3B1 %/ 6$   ]B1 6:  _9(1 Jackknife @1& &%    .  6Z3+1 ( Area Under the Curve ) @B71&  h(`  Q R% $%$ @() >B) . )$ N. viridula  B. germarii 8=:%# = 8 # N1 $   ]B1 X,%J  g ,f &% e ,, 6 6)%& 6\) 8=:%# N1 . )$ e3=1 B. germarii 6) ^/ % @1: @B3% ":1  i   D 7R $ -  7 , - @B7 ,  h=` -\  \7 @B\7 ,  h\=` \, N\BU1 @B71&  % h(` Q R% $ @1: @B3% =  D 7R $ 6) X% $%$ @() " ) N. viridula @\() 6\: \1 D3 k/k  % N. viridula %  /k  %  B. germarii 6) %  =+=1 & ab3 _` X ') 1 %*1 . $%$ 8=:%# . . )%$` d DR$ &%  6) X% % 1 D3  N1  $ 1 . . Maxent  Pentatomidae  Nezara  Brachynema &3 N 1 8=:%# :*  14

Distribution scenario of two species of green bugs Brachynema germarii and Nezara viridula (Hemiptera; Pentatomidae) in Kerman province

T. TAVANPOUR 1, A. M. SARAFRAZI 2, M. R. MEHRNEJAD 3 and S. IMANI 1 1- Department of Plant Protection, Islamic Azad University, Science and Research Branch, Tehran, Iran; 2- Iranian Research Institute of Plant Protection, AREEO, Tehran, Iran; 3- Pistachio Research Institute of Iran, Rafsanjan Abstract In order to determining of the distribution models and potential areas of two heteropteran green bugs, namely Brachynema germarii and Nezara viridula , the Maximum Entropy model (Maxent) was used to predict their potential distribution in 11 climates of Kerman province. Nezara viridula is known as the important pest of cotton as well as for vegetables and cucurbits. Brachynema germarii is a well- known pest of pistachio trees, which transmits fungi and causes stigmatomycosis. Distribution model was obtained using seven environmental predictors and presence records. The accuracy of distribution models was also evaluated by the area under receiver operating characteristic curve (AUC) value. According to the Jackknife test, the annual mean temperature and the mean diurnal range were the most contributing bioclimatic variables in B. germarii and N. viridula distribution modeling. The results showed that dry climate with cool winters and warm to very warm summer in the northern and central parts of the Kerman province were suitable for occurrence of B. germarii . Species distribution model of N. viridula showed its suitable distribution in dry climates with mild to cool winters and very warm summers, in the southern of Kerman province. The AUC values, based on training data, were 0.81 for B. germarii , 0.90 for N. viridula confirming the high accuracy of Maxent in predicting the distribution model of the two stink bugs. Keywords: Brachynema , Nezara , Pentatomidae, Maxent , Species distribution model.

 Corresponding author: [email protected] ... Nezara viridula  Brachynema germarii (Hemiptera: Pentatomidae)      : 6     

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. 9 B $ 6\) \U | &, $ g1 )&     B:  3 &% \.2W%   |\  \M=1 6\ :  1  ; C < X \ % \1 X \=q )$ ) U1 % @ i { {= Q \R%  $ N. viridula  B. germarii X\3 6) $ 8=:%# h \ $ . \)$:  &\3&  k N\3 $ % @\ i 6 (/ $ .(  O;\ ) D\ \P  %$\ 6\) ) @\1: @B3% %\\g% \\#B)% T:%\\/ ? &% $SB\\3% \\ \\' $ V \\ *+,  k  \ N\3 \W $ @B3% $ 6*b=1 ‚k p A1  \ X\3 ( ‚k k ‚k ) \=  | &,  %  { % ], \'  $ 6\*b=1 k $  DZg $:   D ) $ .  3 Nabis pseudoferus  Nabis palifer Seidenstucker, 1954   \ 6\) ) &% \.2W% O \ ;,  %\ . \() D  % 6) )  X \1& 8\# . D\3% \ 6Uib1 @% % $ Remane, 1949 \* *+, 8\9 ) n) %& 1 h   %(/ &1 $ $1  $\ 6\) $ X % 6=1%$ ?B7 $ gƒ1 O1. $ ) (  ( \(: ;\"#   * *+, 6731 %(/  = $    \\S=1 \\g% N. pseudoferus   %\\  {  \\ ], \B:$ \s9 @ \7;: $ \  %$ 6\')   6) ) " ) % > \\\B) X \\\ .% D\\\3% 6B\\\%$ D\\\ZT1  g\\\, N. palifer D\Zg  \ $%$  6)  3= &% n# .  $SB3% $%~)1 $\\ \\: 6\\ D  \\1 h ~,%B\\3%  \\ 6\\1) $ @%\\, \\1 ArcGIS %"\% -\) $ nw\3  O7:% %"% -) $ %B %  \Uib1 $ X \=q . (Solhjouy-Fard and Sarafrazi, 2014) X\\3 6\\) $ \\U 8=:%\\# 6\\(*)  $% version 10.1  %\\ e\\3=1  \\ \\ D\\7 & Erfanfar et al . (2014) @\1: @B3% zB91   Q R% $ N. viridula  B. germarii Orius n=\\  \\ X\\3 &% 6\)  \\=   \\U 8=:%\# . .  6 , $\\1 Maxent ? &% $SB\\3% \\ @% \\ % $ Wolff , 1811 8=:%\# \= 8 \#  %\ : . FG +   D -E  \=  | \ &,  %\ e3=1 VW=1  D3% 6B %R &%  D \\\3 &% \\\b +1  \\\ ]B1  %\\\B % 6\\\) $ X \\\ % N\1 $ e\3=1 QB 'i% {9B)% .  $%$ @()  6) X %  6B (1km 2) 6 )g k DR$  http://www.worldclim.org/ O R   S, zB91   N1 % & D3% Q1  7  &3 N\1 $ %  fg \, X B( 6:   ]B1 DS nw3 ( N ) Phillips et al ., 2006; ) \)%$ $\`  \ = 8 # $ , \ 8=:%\# N\1  \U   " i)  {9B)% =B%$ 8=:%#  \ ?   \3 \ 67 *1 $ Maxent N1 .( Pearson, 2007 \ {\9B)%  \)    ]B1 .  -A)%   ]B1 X % †3% Elith et al ., 2006; ) D\3% $%$ @\() %  B %% X "'  e\iR $ 6\: 6\) $ \^/  \ $: \ % R% \=t N\1 X\% . ( Philips et al ., 2006; Pearson et al ., 2007 X \ U,  %\ \^/  \ $: . $  6 , O7:% N D3% _R) .2W% &% i B/% | &, z P,  % M=1     6(*)  $% Maxent %"% -) $ 8=:%# 8 = # N1 . (Pearson et al ., 2007) . . 1 D3 6)   % h ;S, 6 N1 ?B\7 &% \: D`= O i$ 6  6) 8=:%# X U, $ \ 6\) 8=:%\# N\1 : F    $ H* 'B\7 & X \ U,   \  %] 8=:%\#  \ R% & \ )  R% . $ 1 8 = # #B)% T:%/ †3%  Maxent QB 'i% 6\  B D  1 $  )  %] ei $ e3=1   %\ 6\) \^/ ?%"   $%$ &% Maxent %"% -) $ . (Pearson et al ., 2007; Tognelli et al ., 2009) =: 1 h : 1 $SB\3% \M) $\1  \ 6) 8=:%# 8 = #  &3 N1 @$ #  % Maxent N1 &% $SB3%  „/ 6Uib1 X % = ‡ \) N\1 D`\3  %\ 6)    $%$ &% P$ l .  X \=q \ 6\) | &, $ O1%. X ,g1  Q R%  g, 6 )\ {\9B)% N\1 D\7, @%=. 6 P$ ‚  ; oi:%  B. germarii  \\ 6\\) e\\3=1  \\ \\ D\\7 & X \\ U, D`\3  %\ 6)    $%$ $%U, . (Pearson et al ., 2007) .  -A)% N. viridula ... Nezara viridula  Brachynema germarii (Hemiptera: Pentatomidae)      : 6     

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@1: @B3% $ Nezara viridula  Brachynema germarii 8=:%# N1 D`3 $  $SB3% +1 b    ]B1 -0 H*< Table 1. Selection environmental variables in distribution model for Brachynema germarii and Nezara viridula in Kerman province. Codes Layer's Name  / I *  / I J bio1 Annual Mean Temperature * bio2 Mean Diurnal Range (Mean of monthly (max temp – min temp)) □ bio3 Isothermality bio4 Temperature Seasonality □ bio5 Max Temperature of Warmest Month * □ bio6 Min Temperature of Coldest Month * bio7 Temperature Annual Range □ bio8 Mean Temperature of Wettest Quarter * bio9 Mean Temperature of Driest Quarter * bio10 Mean Temperature of Warmest Quarter * bio11 Mean Temperature of Coldest Quarter * bio12 Annual Precipitation □ bio13 Precipitation of Wettest Month bio14 Precipitation of Driest Month bio15 Precipitation of Seasonality bio16 Precipitation of Wettest Quarter bio17 Precipitation of Driest Quarter □ bio18 Precipitation of Warmest Quarter □ bio19 Precipitation of Coldest Quarter * Bioclimatic variable selected in distribution model of Brachynema germarii . .Brachynema germarii 8=:%# N1 $ 6B ;   ]B1 * □ Bioclimatic variables selected in distribution model of Nezara viridula . .Nezara viridula 8=:%# N1 $ 6B : 6   ]B1 □

D W  1$   _` 6 ˆ 1   :  @1: @B3% R%  = 6=# KL H*< Table 2. Climatic zones of Kerman province, their code and temperature and moisture characteristics

Number Climates Codes Moisture Winter Summer P / .   * N9O M$ M9 1 A-C-VW Aride h(` Cool h=` Very Warm - `  2 A-C-W Aride h(` Cool h=` Warm - 3 A-K-M Aride h(` Cold $3 Mild NBU1 4 A-K-W Aride h(` Cold $3 Warm - 5 A-M-VW Aride h(` Mild NBU1 Very Warm - `  6 A-M-W Aride h(` Mild NBU1 Warm - 7 HA-C-VW Hyper Aride h(` 7 Cool h=` Very Warm - `  8 HA-M-VW Hyper Aride h(` 7 Mild NBU1 Very Warm - `  9 SA-C-W Semi Aride h(` 6 ) Cool h=` Warm - 10 SA-K-M Semi Aride h(` 6 ) Cold $3 Mild NBU1 11 SA-K-W Semi Aride h(` 6 ) Cold $3 Warm -

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R+9  Q   &% $SB\3% \ 6Uib1 D+,   6) U 8=:%# 6(*) -\) h\ :  @1: @B3% R% 6 d   DZg   $:   \ 6\(*) .( O;\ ) \ $ 6 , ArcGIS version 10.1 %"%  B. germarii X\\3 6\\) $ 8=:%\\# 8 \\= \\# N\\1 6\)% P 6 Maxent %"% -) &% $SB3%  N. viridula 6\) V \ *+, X \ % >  \B) †\3% \ .  6 , %;, ‚   e\% p\S,%   %\  { c  %\  % $` B. germarii

 Brachynema germarii \\\ R% 8=:%\\\# 6\\\(*) 0L S2FFF? $ r\Z  *, 6\:  \W 6\ D3% $%$ ?&3 @1: @B3% ˆ*) Brachynema germarii . A . @\1: @B\3% Q \R%  $ Nezara viridula $%$ % ^/ O 7)B#   6B  ?B7 @B3% @ VW=1 B( . . D3% 1 ‚ N $ Q R%  .2W% . Nezara viridula .B *i\ 'B\7 & Maxent N\1 &% $ SB\3% \ .( zi%  O; ) Fig. 1. The current distribution map of Brachynema germarii 6\\:  \\W 6\\ \\ 8 \\= \\# B. germarii  %\\ e\\3=1 (A) and Nezara viridula (B) in different climates of Kerman province. For climate codes see Table 2. @%\\=. 6\\ @B\\3% R\\  \\= VW\\=1 &%  \\ D \\7R ... Nezara viridula  Brachynema germarii (Hemiptera: Pentatomidae)      : 6     

\ @\     B. germarii X3 . (Xin-Rong et al ., 2004) @()  Jackknife D7, †3%  -A)%   3 $ \\  Peganum harmala Linnaeus =S\\3% \\=)1 =\\7#  B. germarii 6\\) 8=:%\\# N\\1 D`\\3 $ 6\\: \\ $%$ X \=q  $%$ D \ iU | \3 \b Salsola kali Linnaeus $ gƒ\1 \ R% O\1. X , Q1 (bio1) 6)d3  1$ X ') 1 Linnavuori, 2012; Mehrnejad et al ., ) D\3% 6B7#  . D .(  O;\ ) D\3% @1: @B3% $ X3 X % 8=:%#  &3 N 1 )\   h\(` VW\=1 $ 6B7# . (2013; Mehrnejad, 2014a OR%\/  (bio11) 6 1 63 X ,$3  1$ X ') 1    ]B1 $/ 6)d3 ) c3B1  %%$ 6: $ 1 D(: (: X ,%J\\ gf, \\U 6\\/1 $ (bio6) \\1 X ,$\\3  \\1$ 6\\$  \\1$ OR%\\/ ) $\\3 @B\\71& \\B1 1 \\ kk \  ]B1 X , g% Q: 1 X , -  1$ T:%/  ]B1   ]B1  † 73 6$   1$ T:%/  - @B7 ,  ( † 73 \P$ ‚/  6)d3  1$ X ') 1  ]B1 .(  O; ) )% $ \M) &% B. germarii X\3 . (Hosseinifard et al. , 2008) D\3% %$\ ) \ V \b1 . D\%$ N\1 D`3 $ % 8*) X B( 6B\7#  \ Œ $ ei 6) D U  Q:%,  8=:%# ab3  \  ]B1 $ % h \ # %\*1 X  B\( 6: *W=1 Response Mehrnejad et al ., 2013; ) $ \\1  \ 6\\ @\1: @B\3%  1$ OR%/  6 1 63 X ,$3  1$ 6)d3  1$ X ') 1 @\     6B\7# \ 2\. 6) X % . (Mehrnejad, 2014b 6\) X \ % 8=:%\#  %\ *i\ VW\=1 )%$ 1 X ,$3  S. kali   Alhagi maurorum Medikus B` =)1 S. . =B7  Cynanchum acutum Linnaeus †,\:  P. harmala =w\3% O;\ ) B. germarii X3 8=:%# O 7)B# 6(*) 6 6,  $%$ D iU " ) Zygophyllum eurypterum Boiss. & Buhse ‡ R % 6\) X \ % 8=:%#  % -&d c % @1: @B3%  (zi% ‚ †\3% \ . (Hashemi Rad et al ., 2002; Mehrnejad, 2014b) $ 6\) X \ % *i\ ?B7 . $%$ e3=1 'B7 & @%=. 6    "\:1 VW\=1 $ 6B7# 6Uib1 X % $ )% 1   3 $ B. germarii . D\3% @\1: @B\3%  ":1  i  VW=1 c  %\ $\ \ 2\. 6\: D3%  D(: @B3% i  ?B\7 @;1% " )  % 6)%B 1 6„/ $  h B:‹i# 6*b=1 X \ % $ @  % " )  %J |Z=1 X3 X %  % e3=1 R% (Ribes and Pagola-Carte, 2007; Linnavuori, 2012; ) $%$ @B3% R {=   =   89 $ . D3%  1 /%) @% \ % \ R%  7*, VZW . (Ribes and Pagola-Carte, 2013 X \ % 6\: $%\) $\ X3 X %  % 8=:%# O 7)B# @1: @B\71& \ h\(` VW\=1 6) X %  (de Pauw et al ., 2002)

VW\=1 X \ % $ e\3=1 @\ " 1 $\ -. O i$ 6 )%, 1  $ 1 a , 8=:%# % % - 7  , - @B7 ,  h=` 6) 8=:%# &%  6 , ; oi:% ‡ ) N1 †3%  .    \3 $ 6\) X \ .% (Abdykairovna, 2011) ( z\i% ‚ O;\ ) $%$ @\\() \\1 D\\3 6\\(*)  ({ ‚ O;\\ ) N. viridula @\A)& @= \3 †\   \„ @3%` =)1 @% % VW=1 @B\3% \=  \ D \7R 6 $+1 =, 6) X % 8=:%# 8=:%\\#  \\„ @\\3%`  @B\\7t  @B\\7 3 @B\\7 N\BU1 @B\71& \ h(`   Q R% $ X % = . D3% @1: Wagner, 1968; Linnavuori, 2008; Hashemi Mehneh ) $%$ ( A-C-VW  A-M-VW ) -  ` , - @B7 ,  h=` , n)\\ ;\\(` 8 %"\\% . (et al ., 2010; Linnavuori, 2012 @B\\3% VW\\=1  \\3 $  ( ‚ N\\ ) $%$ 8=:%\\# N\\ B/% \^/ N\ B/% 6\;  W 6\ \ $ 1 8 : % 6) ^/  \7 \, h(` c %  R  i  VW=1  M) @1: h(`  7 c %  @1: @B3% R   89 $ 6) N B/% -  7 @B7 ,  NBU1 , h=` @B71&  h(` =B7 % 631  X VW=1   %& h )   : *W=1 6: V \ *+, X \ % >  \B) †\3%  . D3% B : N. viridula ^/ \^/ .( zi% ‚ O; ) D3% 6B  8 : (Bakhtiyari, 1998) \(9  {\=  $ x=: $ Z=. D  Q VW=1 D\3% ˆ\Z,% $ @ @ " 1  %(/ &% ` OT1  i,   ",@A /!? # " 1 ? # => *< : .   9  :%;

@B\3 X \=q  e3=1 Q R%  %%$ @1: @B3 &% ^/  % e3=1  $/ , >= 6UR @=1 D   |\  VW\=1 X \ % $ r2\ . \ " ) 6\) X .% D3% N. viridula . .   6\=1%$ 6\:  _9(1  Jackknife D7, > B) 6 6,    &\3 N\1 $ R% O1. X ,gƒ1 (bio2) 6)%& X ') 1 .(  O;\ ) D\3% @\1: @B\3% $ N. viridula 6) 8=:%# 6\=1%$  (bio4) \s  \1$ 6\  &% \  ]B1 ' $ X =q )  ]B1  8*) X , 8 e ,, 6 (bio7) 6)d3  1$ 6\) X \ % 8=:%\# $ % 8*) X B : 6 1 63 X , h(` 6)%& X ') 1 6=1%$  ]B1   ]B1 @ 1 $ .(  O; ) =B%$ D`\3 $ % D:\(1 Q\3 X B( P$ l  l/ (bio2)  ; o\i O\ +, \ Response  \ =+=1 . D%$ N1 6\=1%$ h # 6: *W=1 . =B%$ '=  6) 'B7 & a , )$ %%$ % 6)d3  1$ 6=1%$  s  1$ 6)%& X ') 1 % @\1: @B\3% $ N. viridula 6\) | &, O 7)B# X B( Linnavuori, ) D\3%  & \ 6 6) h  N. viridula . =B%$ 6) X % | &, O 7)B# . (2008; Ribes and Pagola-Carte, 2013   %%$ 6 \ /) X \ % 6\: \ $ 1 @() @1: @B3% {= $

Brachynema .A \\ 6\\) 8=:%\\# O \\7)B# 6\\(*) KL S2FF? 6) X .(% { ‚ O; ) D3% X3 X % 8=:%#  %  &3  ') z W †3%  .@1: @B3% $ Nezara viridula . B .germarii 6\ )    \71 /%\) $ ys9 % 6)%B 1 6 /) $ X\, e3=1)  Š)  6*b=1 X, e3=1 "1R Š)  6*b=1 "1R , Schaefer and Panizzi, 2000; ) $%$ \` 8=:%#   71 . . $&3 1 @ ) % 6*b=1 Ribes and Pagola-Carte, 2013 Fig. 2. Prediction of habitat suitability Brachynema germari (A) N\BU1   @B71&  %%$ 6: ( and Nezara viridula (B) in Kerman province. According to color %\/ 6\$  $\ -  h(`   @B7 ,  )%  range from red to blue, areas with red are suitable for species D\\3% † \\73 6\\$ ‚‚ &% 8 \\ @ \\1 X \\, -\\ distribution. . (Bolle, 2003) Simmons and Yeargan (1988) 6\Uib1 >  \B) †\3% \ de Pauw ) @% \\\ % \\\ R%  \\\7*, †\\\3% \\\ D.\3 † 73 6$ ‚l  d  1$ $  X3 X % O1;, { ‚ O;\ ) Response \=+=1  \ %$ )  ( et al ., 2002 $%\ B)\3 6\$ ‚l &% 8 \  1$ $ i $%%  $  1  h\=` , NBU1 @B71&  h(` VW=1 X3 X  (% O; (Underhill, 1934) X\3 x\` X =q . =B7 &%# UB71 a \, % D\3% d\ %  1$ 6: -  ` , - @B7 , Mcpherson, ) $%$ 'B7 1$ 6  @ D iU  &# $ &%  Underhill, 1934; Kamming et al ., 2012; Grozea ) \ $ \1 1982; Underhill, 1934; Musolin, 2011 (. . =B7 e3=1 6) X % ^/  %  ( et al ., 2012 ... Nezara viridula  Brachynema germarii (Hemiptera: Pentatomidae)      : 6     

D\7, †\3% \b +1 \  ]B1 D % .D . Brachynema germarii 6) 8=:%# N1 $ R%   ]B1 &% h   g, %$ ) . C # B # A TL S2? %\) ) \ ]B1 \ $%\S)%  g\, ( "1R %) ) b +1   ]B1 O *B1 g% &% 1 D3$ 6 O: $3 : Di/ 63 $ Brachynema germarii 6) % Jackknife $. $. p ( ) N 6   ]B1 O1: -)  (1 % "Z3( %) ) 6W 1  ]B1 @ O: $3 (  Fig. 3. A, B, C, Marginal response curves of the predicted probability of Brachynema germarii occurrence for explanatory variables that contributed substantially to the Kerman province Maxent model. Red lines indicate mean values for the 25 iterations of the Model. Blue shading indicates the range of environmental values of the 25 iterations of the model. D, Maxent Jackknife tests of the environmental variable importance. See Table 1 for definition of bio variables.

D\7, †\3% \b +1 \  ]B1 D\ % .D . Nezara viridula 6\) 8=:%\# N\1 $ \ R% \  ]B1 &% h   g, %$ ) . C # B # A UL S2? ( ( \  %\) ) \ ]B1 \ $%S)%  g, ( "1R %) ) b +1   ]B1 O *B1 g% &% 1 D3$ 6 O: $3 : Di/ 63 $ Nezara viridula 6) % Jackknife $. $. p ( ) N 6   ]B1 O1: -)  (1 % "Z3( %) ) 6W 1  ]B1 @ O: $3 Fig. 4. A, B, C, Marginal response curves of the predicted probability of Nezara viridula occurrence for explanatory variables that contributed substantially to the Kerman province Maxent model. Red lines indicate mean values for the 25 iterations of the Model. Blue shading indicates the range of environmental values of the 25 iterations of the model. D, Maxent Jackknife tests of the environmental variable importance. See Table 1 for definition of bio variables.  ",@A /!? # " 1 ? # => *< : .   9  :%;

%"% -) X % &% $SB3%  . $%$ @() " ) 6Uib1 $1   6) \ R% c  %\ X \=t  %%$ 6\: " ) @% % ˆ*)  3 $ . \ = 8 # M) $1   6)  % e3=1   'B7 & @\\3%` †\\  \\ @B\\3% &%  \\ 8\\9 \\=)1 =B\\7 ?')  6) 8=:%# N B/% &% V *+, %X > B) 6 6,  $\\ \\1 D\\  6\\) X \\ % @\\A)& @B\\7 @B\\3&` $\A %   @ ; oi:% 8=:%#   oi:% 6 DZ7)   Hoberlandt, 1995; Modarres Awal, 1997; Linnavuori 2008, ) $ 6\Uib1 $\1  \ 6) 6: $%$ @() B)> .%X D3%  X3 X % „/ V *+, $ )% 1   3 †3% .( 2012 .%X .%X = 6B%$ 8=:%# =)%, 1 @1: @B3% &% *W=1 6t X B( 6:  D  6A)    " i ds+1   B( =  $ D   6) ^/  %  b`% =)%, 1 VW=1 .(Anonymous, 2014 ) \)%$ @B\3% {= $ % D(: ab3 6\t X \=q . =\ \ @ \^/ -\.  %  ,   \') 6\ 6\ N. viridula 6\: D3% $%$ @() Uib1 D\3% 6B%$  g,  @ 8=:%# $ R%  ; oi:% O1%. \=: \1 $% \7` " \ )  `  6A)  %":  = 1& e 3 . D\3% \ 6)  oi:%  Ps` )  $ |R% $ 6: . (Todd, 1976; Musolin et al ., 2011) -\.  b` $ @%, 1 ,.2W% =t X XB%$  X % =  \ X3  % % N1 {`  7 $; .  AUC > B) \ \ 2\. . $\ ) = 8 # 6*b=1 h $ % D b` $ &% B\( AUC %\*1 .( AUC > l /k ) $%$ @\() 6Uib1 D+,    \ D\ -\A g% $ 7` $A % &% @%, 1 %X @ \= 8 \#  )%,  N1 @$ e3=1 = $ @() l /k . . $ ) u9,% &Z1 1% $ % D3$ Q s,  $ )  %\ \1 D\3 >  \B) †3% . (Elith et al., 2006) D3% training  )%,  Did$ ˆ*) ?&% 6Uib1 $1   6) X \ U,  8=:%\# \= 8 \# $ \ 6\v%%   N1  d  X $%$ 6\Uib1 D\+,  \ 6\)  %\ e\3=1  \ 'B7 &   * *+, 6731 ) n) %& 1 h  %(/ &1 &% Falsafi et al ., 2014; Sadeghzadh-Khayati et al ., ) ( N\ ) X\3   6) )  %J Ž%B% 6  (% @%, @% % ;"# 2014; Poulos et al ., 2012; Solhjouy-Fard et al ., 2013; .  Rider \7# &% X =q . Q B7 %"'3w3 &1 $ $1 .( .( Yasemi et al ., 2015   \3=  \3  %\  i \  \,:%$ \Bi % '()%$ $\\ 1\\` "\\:%1 &% . \\Q %$ % ;\\(, N\\ : \\ 6\\) ) @B\3 \,Z) }\S/ r\Ps91 @\1: @B\3%  &(: Brachynema  6) $ Maxent N1 1 3 T H*< . . Nezara viridula  germari \)$ ) Q %\ %  %$ 6) )  % -&d );1% 6: @1: Table 3. Statistical evaluation of Maxent model of Brachynema Q. Q.  ) 1 )%$R germarii and Nezara viridula .

 *V V W+  AUC  Sample size SD Species Brachynema 108 0.02 0.81 germarii

60 0.01 0.90 Nezara viridula

Elith et al ., 2006; ) 6\B -\A)% \Uib1 \ V \b1

Crawford and Hoagland, 2010; Wilson et al ., 2011 QB 'i% ( 8=:%\# \= 8 \#  \ N1 6 , $  d  )%, Maxent ... Nezara viridula  Brachynema germarii (Hemiptera: Pentatomidae)      : 6     

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