Exploring the influence of density-dependence and weather on the spatial and temporal variation in common vole (Microtus arvalis) abundance in Castilla y León, NW Spain

Pest Manag Sci. 2023 Dec 28. doi: 10.1002/ps.7954. Online ahead of print.

Abstract

Background: The common vole has invaded the agroecosystems of northwestern Spain, where outbreaks cause important crop damage and management costs. Little is yet known about the factors causing or modulating vole fluctuations. Here, we used 11 years of vole abundance monitoring data in 40 sites to study density-dependence and weather influence on vole dynamics. Our objective was to identify the population dynamics structure and determine whether there is direct or delayed density-dependence. An evaluation of climatic variables followed, to determine whether they influenced vole population peaks.

Results: First- and second-order outbreak dynamics were detected at 7 and 33 study sites, respectively, together with second-order variability in periodicity (2-3 to 4-5-year cycles). Vole population growth was explained by previous year abundance (mainly numbers in summer and spring) at 21 of the sites (52.5%), by weather variables at 11 sites (27.5%; precipitation or temperature in six and five sites, respectively), and by a combination of previous abundance and weather variables in eight sites (20%).

Conclusions: We detected variability in vole spatiotemporal abundance dynamics, which differs in cyclicity and period. We also found regional variation in the relative importance of previous abundances and weather as factors modulating vole fluctuations. Most vole populations were cyclical, with variable periodicity across the region. Our study is a first step towards the development of predictive modeling, by disclosing relevant factors that might trigger vole outbreaks. It improves decision-making processes within integrated management dealing with mitigation of the agricultural impacts caused by voles. © 2023 Society of Chemical Industry.

Keywords: common vole; dense-dependence drivers; population dynamics; spatiotemporal fluctuations; weather modulation.