Estimating Fluctuating Vital Rates From Time-Series Data: A Case Study of Aphid Biocontrol

Many ecological time series describe population dynamics. Indirectly, these data also provide information about the vital rates (e.g., birth rates, mortality rates) underlying these dynamics, but extracting this information from the data can be difficult. Here, we present a method for estimating fluctuating vital rates from ecological time series by using a model to re-code information in observed dynamics into information about unobserved vital rates. This model construction differs from most current models by replacing strong assumptions about the functional relationships dictating population dynamics with more conservative assumptions about how vital rates change with time. Thus, this method is a tool for analyzing time-series data that avoids strong assumptions about the mechanisms driving population dynamics. Our work is motivated by studying the biological control of pea aphids in alfalfa in south-central Wisconsin. Pea aphid populations are consistently held below economic threshold, although the source of this regulation is unclear. Here, we analyze monitoring data to understand the role that a specialist parasitoid plays in aphid biocontrol. Our modeling methodology allows us to estimate the vital rates that determine aphid dynamics (in particular, parasitism) without making arbitrary assumptions about the relationship between parasitism and aphid or parasitoid density. We find that, while parasitism depresses aphid population growth rate substantially, declines in aphid population growth rates do not coincide with increases in parasitism. Therefore, parasitism cannot be responsible for the density-dependent regulation of aphid populations observed in the field.