STS Decisions in 2008
     
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    Table of PPA characteristics in 2008

State  Area Distance   N     Max   Max   Backgr. Priority Delimit   Action    Action Comment
PPA ID sqkm    km    traps  catch before  moths    index   index  recommended taken
MN-145   20  265.4      0     -1     -   0.000      0.53    0.00      -      delimit
MN-146   18  248.7      1      1     -   0.000      1.41    0.10      -      delimit
MN-147   10  255.0      1      0     -   0.000      0.51    0.13      -      delimit
MN-151    5  252.6      1      1     -   0.000      1.42    0.14      -      delimit
MN-159    9  257.7      0     -1     -    -         0.52    0.00      -      delimit
MN-165    5  250.9      0     -1     -    -         0.50    0.00      -      delimit
MN-166    7  228.9      1      1     -   0.000      1.37    0.12      -      delimit
MN-171   18  224.7      0     -1     -   0.000      0.45    0.00      -      delimit
MN-174    9  224.4      0     -1     -   0.000      0.45    0.00      -      delimit
MN-179    7  215.5      0     -1     -   0.000      0.43    0.00      -      delimit
MN-182    7  225.1      1      0     -   0.000      0.45    0.13      -      delimit
MN-195   18  193.2      5      0     -   0.000      0.39    0.51      -      delimit
MN-196    7  190.4      1      1     -   0.000      1.30    0.12      -      delimit

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.

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    Maintained By Jiang Wu