Brazilian Journal of Biology (Jan 2022)
Percentage of importance indice-production unknown: loss and solution sources identification on system
Abstract
Abstract Indices are used to help on decision-making. This study aims to develop and test an index, which can determine the loss (e.g., herbivorous insects) and solution (e.g., natural enemies) sources. They will be classified according to their importance regarding the ability to damage or to reduce the source of damage to the system when the final production is unknown. Acacia auriculiformis (Fabales: Fabaceae), a non-native pioneer species in Brazil with fast growth and rusticity, is used in restoration programs, and it is adequate to evaluate a new index. The formula was: Percentage of the Importance Indice-Production Unknown (% I.I.-PU) = [(ks1 x c1 x ds1)/Σ (ks1 x c1 x ds1) + (ks2 x c2 x ds2) + (ksn x cn x dsn)] x 100. The loss sources Aethalion reticulatum L., 1767 (Hemiptera: Aethalionidae), Aleyrodidae (Hemiptera), Stereoma anchoralis Lacordaire, 1848 (Coleoptera: Chrysomelidae), and Tettigoniidae, and solution sources Uspachus sp. (Araneae: Salticidae), Salticidae (Araneae), and Pseudomyrmex termitarius (Smith, 1877) (Hymenoptera: Formicidae) showed the highest % I.I.-PU on leaves of A. auriculiformis saplings. The number of Diabrotica speciosa Germar, 1824 (Coleoptera: Chrysomelidae) was reduced per number of Salticidae; that of A. reticulatum that of Uspachus sp.; and that of Cephalocoema sp. (Orthoptera: Proscopiidae) that of P. termitarius on A. auriculiformis saplings. However, the number of Aleyrodidae was increased per number of Cephalotes sp. (Hymenoptera: Formicidae) and that of A. reticulatum that of Brachymyrmex sp. (Hymenoptera: Formicidae) on A. auriculiformis saplings. The A. reticulatum damage was reduced per number of Uspachus sp., but the Aleyrodidae damage was increased per number of Cephalotes sp., totaling 23.81% of increase by insect damages on A. auriculiformis saplings. Here I show and test the % I.I.-PU. It is an new index that can detect the loss or solution sources on a system when production is unknown. It can be applied in some knowledge areas.
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