The causes and consequences of pest population variability in agricultural landscapes

Abstract

Variability in population densities is key to the ecology of natural systems but also has great implications for agriculture. Farmers' decisions are heavily influenced by their risk aversion to pest outbreaks that result in major yield losses. However, the need for long-term pest population data across many farms has prevented researchers from exploring the drivers and implications of pest population variability (PV). Here, we demonstrate the critical importance of PV for sustainable farming by analyzing 13 years of pest densities across >1300 Spanish olive groves and vineyards. Variable populations were more likely to cause major yield losses, but also occasionally created temporal windows when densities fell below insecticide spray thresholds. Importantly, environmental factors regulating pest variability were very distinct from factors regulating mean density, suggesting variability needs to be uniquely managed. Finally, we found diversifying landscapes may be a win-win situation for conservation and farmers, as diversified landscapes promote less abundant and less variable pest populations. Therefore, we encourage agricultural stakeholders to increase the complexity of the landscapes surrounding their farms through conserving/restoring natural habitat and/or diversifying crops.

Increasing crop field size does not consistently exacerbate insect pest problems

“… Grapes, Vitis vinifera , in southern Spain from 2006 to 2018. These data were gathered by pest control advisors employed by the Regional Government of Andalusia to promote integrated pest management (RAIF (Red de Alerta e Informacion Fitosanitaria) Network; 45 , 48 ). Density estimates and targeted pesticide applications were available for Lobesia botrana (Lepidoptera: Tortricidae; the European grapevine moth, n = 996 and 929, respectively) and Jacobiasca spp.…”

“…(Hemiptera: Cicadellidae; leafhoppers, n = 1,113 and 929, respectively). Olives, Olea europaea , also in southern Spain from 2006 to 2018 and also part of the RAIF Network ( 45 , 48 ). Density estimates and targeted pesticide applications were available for B. oleae (Diptera: Tephritidae; the olive fruit fly, n = 16,207 and 9,340, respectively) and Prays oleae (Lepidoptera: Yponomeutidae; the olive moth, n = 15,944 and 9,340, respectively).…”

“…Agronomic covariates were included to provide statistical control for what would otherwise be unexplained variation in our response variables; in many cases, these covariates also provided useful internal checks on overall data quality, showing that the dataset was capable of revealing clear evidence of factors shaping pest densities. Indeed, in all cases, these large datasets had already been shown capable of detecting drivers of pest population densities or crop performance ( 43 – 48 , 60 ). We were thus confident that they could reveal effects of field size on pest dynamics.…”

“…Together, our datasets encompassed more than 20,000 field years of observations of 14 pest and 1 natural enemy species across both annual and perennial agroecosystems in the United States (cotton and citrus), Peru (potatoes), and Spain (grapes and olives). The pest taxa studied include, for each crop, the arthropod species that generate the greatest economic damage ( 43 – 48 ). Field sizes varied widely both between and within each of the studied cropping systems.…”

Long-term expansion of cereal crops promotes regional population increase of polyphagous Helicoverpa armigera

“…Identi cation through eld trials of landscape-level elements that in uence pest occurrence can provide insights into the effects of land use changes on "source-sink" processes and population dynamics of pests (Paredes et al, 2022b;Tabuchi et al, 2017). In general, the abundance of herbivore pests should be highest in landscapes with the most suitable host crops or with the highest connectivity between host habitats, which makes it easier for pests to access continuous food resources (i.e., resource concentration hypothesis) (Peirce et al, 2021;Rand et al, 2014).…”