Data from: Intra- and interspecific density dependence mediates weather effects on the population dynamics of a plant-insect herbivore system
Cite this dataset
Hambäck, Peter (2021). Data from: Intra- and interspecific density dependence mediates weather effects on the population dynamics of a plant-insect herbivore system [Dataset]. Dryad. https://doi.org/10.5061/dryad.qz612jmf4
Abstract
Temperature and precipitation are two major factors determining arthropod population densities, but the effects from these climate variables are seldom evaluated in the same study system and in combination with inter- and intraspecific density dependence. In this study, I used a 19 year time series on plant variables (shoot height and flowering incidence) and insect density in order to understand direct and indirect effects of climatic fluctuations on insect population densities. The study system includes two closely related leaf beetle species (Galerucella spp.) and a flower feeding weevil (Nanophyes marmoratus) attacking the plant purple loosestrife (Lythrum salicaria). Results suggest that both intraspecific density dependence and weather variables affected Galerucella population densities, with interactive effects of rain and temperature on insect densities that depended on the timing relative to insect life cycles. In spring, high temperatures increased Galerucella densities only when combined with high rain, as low rain implies a high drought risk. Low temperatures are only beneficial if combined with little rain, as high rain cause chilly and wet conditions that are bad for insects. In summer, interactive effects of rain and temperature are different because high temperatures and little rain cause drought that induce wilting in plants, thus reducing food availability for the leaf feeding larvae. In contrast, the density of the flower feeding weevil was less affected by temperature and precipitation directly, and more indirectly interspecific density dependent effects through reduced resource availability caused by previous Galerucella damage.
Methods
Field data were collected annually, at the end of June, in 29 populations in a 245 km gradient along the Baltic Sea shoreline during the period 2000-2018, with some variability in the starting and ending of time series. Within each population, I surveyed all insect species on 56 randomly selected L. salicaria shoots along transects. On each shoot, I counted all insects (egg, larvae and adults), measured shoot height (cm) and flowering incidence at the shoot level. Galerucella densities were estimated as egg counts per shoot, whereas Nanophyes densities were estimated as adults per shoot. As climate factors, I used data on hourly temperatures and daily precipitation recorded from the SMHI weather station (www.smhi.se) that was located sufficiently close to the shore to resemble the climate at the study sites. From the weather data, I extracted mean temperatures (oC) and total precipitation (mm) for May, June and July respectively. Because insect densities and plant variables were estimated at the end of June, climate factors for May and June were included from year (t) whereas climate factors for July were included from year (t-1).
Usage notes
Four sites were excluded because roedeer had completely removed the plant, leading to dramatic reductions in insect density. Thus, the total number of populations included are 25. A few missing values are indicated with NA. Additional site information is included in the published paper. Variables: GalerucellaEggs_per_shoot, Floral_incidence (%flowering shoots in the site), Mean_shoot_length (cm), %_Cut_shoots (roedeer herbivory), NanoAdults_per_shoot, Temp_May_t (mean May temperature in year t), Temp_June_t (mean June temperature in year t), Temp_July_t-1 (mean July temperature in year t-1), Prec_May_t (total May precipitation in mm in year t), Prec_June_t (total June precipitation in mm in year t), Prec_July_t-1 (total July precipitation in mm in year t-1). Additional weather data is available from https://www.smhi.se/data/meteorologi/ladda-ner-meteorologiska-observationer#param=airtemperatureInstant,stations=all (stations-temperatures: Brämön, Eggegrund, Hudiksvall, Kuggörarna, Söderarm, Örskär; precipitation: Bergsjö, Brämön, Gävle, Kuggörarna, Norrsundet, Söderhamn, Väddö, Örskär).