STS Decisions in 2011
     
Foreground: 
Background: 
        Click inside the map to zoom in.
        Click near the border to see a neighboring map

Legend

    Table of PPA characteristics in 2011

State  Area Distance   N     Max   Max   Backgr. Priority Delimit   Action    Action Comment
PPA ID sqkm    km    traps  catch before  moths    index   index  recommended taken
WV- 59    1   16.3      1      3     0   0.171      1.58    0.45      -         -       
WV- 67    4   -0.6      2     59     4   0.854      0.90    0.35      -         -       
WV- 73   26    9.0      8     11     8   0.325      2.46    0.77   delimit   delimit    
WV- 74    1   44.8      1      3     0   0.014      1.79    0.45      -      delimit    
WV- 75    3   20.6     12      9    11   0.129      3.93    2.52    treat    delimit    
WV- 78    1    8.2      1     12     6   0.399      2.05    0.39      -         -       
WV- 84    1   10.0      1      5     2   0.244      1.27    0.37      -         -       
WV- 85    1    9.6      1      3     1   0.289      0.49    0.47      -      delimit    
WV- 86    1    8.3      1     10     1   0.312      1.28    0.42      -      delimit    
WV- 96    1  -19.9      1    203    18   2.176      0.00    0.32      -         -       

ID = Identification number of the potential problem area (see the map).
Distance =
 
Distance from the beginning of the STS action zone, km. Negative distance means that the PPA is in the monitoring zone.
N traps = Number of traps in the problem area.
Max catch = Maximum number of moths captured within the problem area.
Max before = Maximum number of moths captured in a 3-km neighborhood in the previous year.
Priority index = Shows the priority for STS action (either treatment or delimiting).
Delimit index = Shows how well the area was delimited in the previous year.
Backgr. moths = Mean log moth counts in a 25-km neighborhood.

See details in: Decision algorithm explained.

Home


    For more information, please contact Patrick Tobin or Andy Roberts
    Maintained By Jiang Wu