Comparing floral resource maps and land cover maps to predict predators and aphid suppression on field bean.
Landsc Ecol
; 37(2): 431-441, 2022.
Article
em En
| MEDLINE
| ID: mdl-35221524
ABSTRACT
CONTEXT Predatory insects contribute to the natural control of agricultural pests, but also use plant pollen or nectar as supplementary food resources. Resource maps have been proposed as an alternative to land cover maps for prediction of beneficial insects. OBJECTIVES:
We aimed at predicting the abundance of crop pest predating insects and the pest control service they provide with both, detailed flower resource maps and land cover maps.METHODS:
We selected 19 landscapes of 500 m radius and mapped them with both approaches. In the centres of the landscapes, aphid predators - hoverflies (Diptera Syrphidae), ladybeetles (Coleoptera Coccinellidae) and lacewings (Neuroptera Chrysopidae) - were surveyed in experimentally established faba bean phytometers (Vicia faba L. Var. Sutton Dwarf) and their control of introduced black bean aphids (Aphis fabae Scop.) was recorded.RESULTS:
Landscapes with higher proportions of forest edge as derived from land cover maps supported higher abundance of aphid predators, and high densities of aphid predators reduced aphid infestation on faba bean. Floral resource maps did not significantly predict predator abundance or aphid control services.CONCLUSIONS:
Land cover maps allowed to relate landscape composition with predator abundance, showing positive effects of forest edges. Floral resource maps may have failed to better predict predators because other resources such as overwintering sites or alternative prey potentially play a more important role than floral resources. More research is needed to further improve our understanding of resource requirements beyond floral resource estimations and our understanding of their role for aphid predators at the landscape scale. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s10980-021-01361-0.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article