Data from: How do global forest pests respond to increasing temperatures?
Data files
Aug 29, 2024 version files 103.48 KB
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Data_sources.docx
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meta_analysis_data_table.xlsx
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README.md
Abstract
Biotic disturbances caused by insects and pathogens have a major impact on forests in the Northern hemisphere. Knowledge of the effects of increasing temperature on the performance of these forest pests will thus be crucial for predicting future disturbance risks. Here, we systematically review the direct effects of increasing temperatures on four functional subgroups of forest pests, including leaf chewers, sap suckers, bark and wood borers, and pathogens. We considered 118 studies (2003-2022) representing 72 pest species feeding on 33 host genera from sub-tropical, temperate and boreal forests in Asia, Europe and North America. Based on a subset of 89 studies reporting the required data, we conducted a meta-analysis (i) distinguishing the functional subgroups, and (ii) considering the main life-history traits, i.e. development, fitness, and survival. A temperature corresponding to the expected mean temperature during the growing season in the years 2081-2100 had a significant positive effect on the overall performance of leaf chewers (+18%) and bark and wood borers (+10%), while sap suckers and pathogens remained unaffected. In contrast, performance was not or even significantly negatively affected when a more pronounced temperature increase, i.e. corresponding to the temperature maxima in 2081-2100, was considered. This finding reflects the non-linear temperature-performance relationship beyond currently evolved temperature optima in insects and pathogens. Furthermore, we showed that differential responses of life-history traits to increased temperatures may counterbalance each other (e.g. development vs. survival), highlighting the importance of a multi-trait approach to assessing the impact of global warming on pest performance. By quantifying the effects of increasing temperatures on forest pest performance, our results facilitate the prediction of biotic disturbance impacts in a future climate. For instance, they could provide a valuable contribution to the parameterization of large-scale ecosystem models, which often do not explicitly consider the response of biotic disturbances to climate change.
README
Data from: How do global forest pests respond to increasing temperatures?
This dataset contains the data table and the reference list for all original studies used for the analyses in the article "How do global forest pests respond to increasing temperatures? - A meta-analysis". Further information on data collection, calculation of effect sizes and statistics can be found in the Methods section of the article.
Description of the data and file structure
Column | Description |
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Author(s) | Abbreviated indication of the authors of the study |
Year | Publication year of the study |
DOI/ISSN | DOI or, if not assigned, alternative identifier of the study |
Functional group | Classification of the studied organism, can be either leaf chewers, sap suckers, bark and wood borers or pathogens |
Species | Latin species name of the studied organism |
Biome | Biome from which the organism examined in the study was obtained (boreal, temperate or sub-tropical) |
Continent | Continent from which the organism examined in the study was obtained (Asia, Europe or North America) |
Latitude | Geographic latitude at which the organism examined in the study was obtained. If no exact coordinates were given, an approximate value was derived from the information in the text. |
Longitude | Geographic longitude at which the organism examined in the study was obtained. If no exact coordinates were given, an approximate value was derived from the information in the text. |
Trait | Classification of the response variable into one of the following traits: development, fitness or survival |
Response variable | Original designation of the response variable used in the study |
Unit | Unit of measurement of the response variable examined in the study |
T control | Temperature [°C] in control group |
T treatment | Temperature [°C] in treatment group |
n control | Number of observations in the control group |
n treatment | Number of observations in the treatment group |
Response variable control | Response variable at control temperature |
Response variable treatment | Response variable at treatment temperature |
SD control | Standard deviation of the response variable at control temperature |
SD treatment | Standard deviation of the response variable at treatment temperature |