DOI: 10.5061/dryad.8cz8w9h2d
title: Data from: Recent climate change strongly impacted the population dynamic of a North American insect pest species

description: Climate change is redefining the dynamics of forest ecosystems globally,
 particularly through its impact on forest pest populations such as the
 spruce budworm (SBW, Choristoneura fumiferana [Clem.]), a major defoliator
 in North American boreal forests. This study investigates the shifts in
 the population dynamics of spruce budworm across its range in response to
 recent climate change. We used a process-based, temperature-dependent
 ecophysiological model combined with the ERA5 reanalysis to assess changes
 in SBW phenology, reproduction rate, winter survival, and population
 growth rates from 1950 to 2022 across North America. Our findings
 demonstrate a pronounced northward expansion of suitable climate
 conditions for SBW, accompanied by earlier phenological events and
 increased reproduction rates in northern regions. Conversely, the southern
 parts of its range are experiencing increased winter mortality due to
 warmer temperatures. This study highlights the significant impact of
 elevated temperatures, particularly during critical developmental windows
 such as spring and summer, which are pivotal for spruce budworm survival
 and reproduction. Additionally, our results reveal that the observed
 shifts in pest dynamics are more strongly driven by climate change than by
 changes in landscape composition and structure. We estimated that suitable
 growth rates have shifted northward by over 68 km on average, but this
 shift reached more than 200 km in the easternmost portions of its range.
 Climate-induced shift in suitable conditions for SBW underscores the need
 for adaptive forest management strategies that consider the rapid
 ecological changes and the potential for increased forest vulnerability
 due to climatic and biotic stressors. This study provides vital insights
 that can inform adaptive management, ensuring the sustainability of forest
 ecosystems in the face of ongoing climate change.
description: The study employed a detailed individual-based spruce budworm
 (SBW) model to simulate development, survival, and reproduction rates
 under varying temperature conditions. This model integrates
 laboratory-derived development rates for SBW life stages and uses a
 non-linear development summation approach. Simulations, performed in
 BioSIM 11, utilized high-resolution ERA5 reanalysis temperature data from
 1950 to 2022, spanning the United States and Canada. The model provided
 outputs on larval and adult phenology, reproduction, winter survival, and
 annual population growth rates. These were further analyzed using
 statistical methods to assess spatial and temporal trends in SBW
 ecophysiological parameters, focusing on the impacts of recent climate
 change. Additionally, changes in landscape
 vulnerability were assessed using historical forest inventory data from
 Quebec’s commercial forests, which documented forest composition and age
 over multiple decades. Trends in ecophysiological parameters were compared
 with alterations in forest landscapes across areas heavily defoliated
 during the last two major SBW outbreaks (1967–1991 and 2007–2022). This
 comparison highlighted the relative influence of climate and forest
 changes on SBW dynamics, providing insights into spatial shifts in
 vulnerability and suitability for SBW reproduction and survival under
 changing environmental conditions.
description: # Data from: Recent climate change strongly impacted the population
 dynamic of a North American insect pest species
 [https://doi.org/10.5061/dryad.8cz8w9h2d](https://doi.org/10.5061/dryad.8cz8w9h2d) ## Description of the data and file structure The study employed a detailed individual-based spruce budworm (SBW) model to simulate development, survival, and reproduction rates under varying temperature conditions. This model integrates laboratory-derived development rates for SBW life stages and uses a non-linear development summation approach. Simulations, performed in BioSIM 11, utilized high-resolution ERA5 reanalysis temperature data from 1950 to 2022, spanning the United States and Canada. The model provided outputs on larval and adult phenology, reproduction, winter survival, and annual population growth rates. These were further analyzed using statistical methods to assess spatial and temporal trends in SBW ecophysiological parameters, focusing on the impacts of recent climate change. * Export_(ExecuteModel_SBW).csv reports winter survival, reproduction rate and annual population growth Variable explanation: * KeyID: ID ERA5 cell * Name: Same as KeyID, deprecated * Latitude: Latitude in degree * Longitude: Longitude in degree * Elevation: Elevation in meters * P: deprecated * Replication: deprecated * Year: Year * GrowRate: SBW population growth rate (unitless) as assessed from mortality rate in winter and progeny rate  * ProgenyRate: Rate of reproduction (unitless) * WinterSurvival: proportion of individuals surviving in winter (from 0 to 1) * Export_(Analysis_SBW_Biology_max).csv reports larval and adult phenology Variable explanation: * KeyID: ID ERA5 cell * Name: Same as KeyID, deprecated * Latitude: Latitude in degree * Longitude: Longitude in degree * Elevation: Elevation in meters * P: deprecated * Replication: deprecated * Year: Year * L2o: Initialisation of overwintering larvae. Always January 1st each year * L2: Date with maximum number of stage 2 larvae * L3: Date with maximum number of stage 3 larvae * L4: Date with maximum number of stage 4 larvae * L5: Date with maximum number of stage 5 larvae * L6: Date with maximum number of stage 6 larvae * Pupae: Date with maximum number of pupae * Adults: Date with maximum number of adults * DeathAdult: Date with maximum number of adults dying * OvipositingAdult: Date with maximum number of ovipositing adults * Brood: Date with maximum number of eggs per brood * Eggs+: Date with maximum percentage of eggs of the new generation * L1+: Date with maximum percentage of first stage of the new generation * L2o+: Date with maximum percentage of overwintering second stage of the new generation * L2+: Date with maximum percentage of feeding second stage of the new generation * Average instar: Date with maximum average instar of the current (L2o..adults) year * MalePupae: Date with maximum number of male pupae * FemalePupae: Date with maximum number of female pupae * MaleAdult: Date with maximum number of adult male * FemaleAdult: Date with maximum number of adultfe male * MaleEmergence: Date with maximum number of male emergence from pupa * FemaleEmergence: Date with maximum number of female emergence from pupa * MaleFlight: Flight activity of male * FemaleFlight: Flight activity of male Additionally, changes in landscape vulnerability were assessed using historical forest inventory data from Quebec’s commercial forests, which documented forest composition and age over multiple decades. Trends in ecophysiological parameters were compared with alterations in forest landscapes across areas heavily defoliated during the last two major SBW outbreaks (1967–1991 and 2007–2022). This comparison highlighted the relative influence of climate and forest changes on SBW dynamics, providing insights into spatial shifts in vulnerability and suitability for SBW reproduction and survival under changing environmental conditions. These files are reporting the different analyses done in R to calculate the trends in the variables considered in the study. These includes SBW larval and adult phenology, reproduction, winter survival, and annual population growth rates.  * MapsPlotERA5Trends.R R code used to make maps and calculate mean trends within the species range * MKTEST_tfpw_SM_21Avr2023.R R code to calculate significant trends using the modified Mann-Kendall test for growth rate, progeny rate and winter survival * MKTEST_tfpw_YB_phenologie.R R code to calculate significant trends using the modified Mann-Kendall test phenological variables * ShiftCentroidByLongitude.R R code to calculate the centroid for suitable conditions by longitude for each variable