The influence of agricultural occupation and climate on the spatial distribution of Plusiinae (Lepidoptera: Noctuidae) on a latitudinal gradient in Brazil

• Autor(a) principal: Santos,Sabrina Raisa dos
• Data de Publicação: 2021
• Outros Autores: Specht,Alexandre, Carneiro,Eduardo, Casagrande,Mirna Martins
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista brasileira de entomologia (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0085-56262021000100203
• topic: Abundance; Assemblage structure; Looper moths; Pest species

Abstract Studies have reported the presence of certain Plusiinae species in both natural and agricultural landscapes, but their turnover in association with agricultural activities remains unexplored. Aiming to understand how the assemblages of Plusiinae are structured by agricultural occupation and climate, this study used automated light traps sampled moths in 18 sites in Brazil, across a broad latitudinal gradient. Our data has demonstrated that climate variables prevails as the most important variables influencing both the composition of Plusiinae and the abundance of its dominant species Chrysodeixis includens. On the other hand, the lack of significance found for the effect of variables representing agricultural occupation evidences that pest species are present both in agricultural and natural ecosystems, also sharing similar abundances at those locations. In other words, instead of following a gradient of agricultural occupation (e.g. crop sizes around sample sites) the composition of these extremely polyphagous insects is more clearly shaped by the latitudinal gradient, in which temperature and precipitation are better predictors. Thus, in contrary to our expectations, pest species inhabits both natural and agricultural landscapes at similar latitudinal sites, probably due to their wide polyphagy spectrum. These results can be used in management and monitoring programs of pest species in South America, since the local abundance variation and species composition can be more reliable predicted by changes in climate conditions.