DOI: 10.5061/dryad.qz612jmf4
title: Data from: Intra- and interspecific density dependence mediates weather effects on the population dynamics of a plant-insect herbivore system

description: 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.
description: 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 <i>L. salicaria</i> 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.
 <i>Galerucella</i> densities were estimated as egg counts per
 shoot, whereas <em>Nanophyes</em> 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
 (<sup>o</sup>C) 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).
description: 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).