Data from: Thermal homogenization of boreal communities in response to climate warming
Abstract
Globally, rising temperatures are increasingly favoring warm-affiliated species. Although changes in community composition are typically measured by the mean temperature affinity of species (the Community Temperature Index, CTI), they may be driven by different processes and accompanied by shifts in the diversity of temperature affinities and breadth of species thermal niches. To resolve the pathways to community warming in Finnish flora and fauna, we examined multidecadal changes in the dominance and diversity of temperature affinities among understory forest plant, freshwater phytoplankton, butterfly, moth, and bird communities. CTI increased for all animal communities, with no change observed for plants or phytoplankton. In addition, the diversity of temperature affinities declined for all groups except butterflies, and this loss was more pronounced for the fastest warming communities. These changes were driven in animals mainly by a decrease in cold-affiliated species and an increase in warm-affiliated species. In plants and phytoplankton the decline of thermal diversity was driven by declines of both cold- and warm-affiliated species. Plant and moth communities were increasingly dominated by thermal specialist species, and birds by thermal generalists. In general, climate warming outpaced changes in both the mean and diversity of temperature affinities of communities. Our results highlight the complex dynamics underpinning the thermal reorganization of communities across a large spatio-temporal gradient, revealing that extinctions of cold-affiliated species and colonization by warm-affiliated species lag behind changes in ambient temperature, while communities become less thermally diverse. Such changes can have important implications for community structure and ecosystem functioning under accelerating rates of climate change.
Description of the data and file structure
- File 1 Name: data/Data_repository.RData
- File 1 Description: Community temperature index (CTI) and population abundance in survey sites in survey years for all species groups.
- Columns:
- Year: year information so that first survey year = 1
- Longitude
- Latitude
- SiteID
- bc_zone: bioclimatic zone
- Year_coarse: year binned to five years intervals
- temp: annual mean temperature
- prec: annual precipitation sum
- CTI: community temperature index
- CTIdiv: standard deviation of species temperature index in a community
- CTBI: community temperature breadth index
- CTBIdiv: standard deviation of species temperature breadth index in a community
- Warm_sp_abundance: abundance of warm-affiliated species
- Cold_sp_abundance: abundance of cold-affiliated species
- Year_continuous: standardized year information
- Year_orig: non-modified year information
- siteID_tr_1: duplicated siteID for spatial random effect
- siteID_tr_2: duplicated siteID for spatial random effect
- bc_zone_2: bioclimatic zone
- intercept: intercept of ones
- File 2 Name: data/Data_repository_no_Epirrita_autumnata.RData
- File 2 Description: Community temperature index (CTI) and population abundance in survey sites in survey years for moths. Data is compiled without Epirrita autumnata.
- Columns:
- Year: year information so that first survey year = 1
- Longitude
- Latitude
- SiteID
- bc_zone: bioclimatic zone
- Year_coarse: year binned to five years intervals
- temp: annual mean temperature
- prec: annual precipitation sum
- CTI: community temperature index
- CTIdiv: standard deviation of species temperature index in a community
- CTBI: community temperature breadth index
- CTBIdiv: standard deviation of species temperature breadth index in a community
- Warm_sp_abundance: abundance of warm-affiliated species
- Cold_sp_abundance: abundance of cold-affiliated species
- Year_continuous: standardized year information
- Year_orig: non-modified year information
- siteID_tr_1: duplicated siteID for spatial random effect
- siteID_tr_2: duplicated siteID for spatial random effect
- bc_zone_2: bioclimatic zone
- intercept: intercept of ones
- File 3 Name: data/Lattice_k_bird.graph
- File 3 Description: Adjacency structure of the bird survey sites.
- File 4 Name: data/Lattice_k_butterfly.graph
- File 4 Description: Adjacency structure of the butterfly survey sites.
- File 5 Name: data/Lattice_k_moth.graph
- File 5 Description: Adjacency structure of the moth survey sites.
- File 6 Name: data/Lattice_k_phytoplankton.graph
- File 6 Description: Adjacency structure of the phytoplankton survey sites.
- File 7 Name: data/Lattice_k_plant.graph
- File 7 Description: Adjacency structure of the plant survey sites.
- File 8 Name: data/STI_butterfly.csv
- File 8 Description: table for butterfly STI and STIsd
- column species: species name
- column full species name: species name with the naming source in brackets
- column Family: species family
- column STI: species temperature index (STI), mean temperature within species range
- column STIsd: standard deviation of the temperature conditions within species range
- File 8 Description: table for butterfly STI and STIsd
- File 9 Name: data/STI_moth.csv
- File 8 Description: table for moth STI and STIsd
- column species: species name
- column STI: species temperature index (STI), mean temperature within species range
- column STIsd: standard deviation of the temperature conditions within species range
- File 8 Description: table for moth STI and STIsd
- File 10 Name: data/STI_phytoplankton.csv
- File 8 Description: table for phytoplankton STI and STIsd
- column species: species name
- column STI: species temperature index (STI), mean temperature within species range
- column STIsd: standard deviation of the temperature conditions within species range
- File 8 Description: table for phytoplankton STI and STIsd
- File 11 Name: data/STI_plant.csv
- File 8 Description: table for plant STI and STIsd
- column species: species name
- column STI: species temperature index (STI), mean temperature within species range
- column STIsd: standard deviation of the temperature conditions within species range
- File 8 Description: table for plant STI and STIsd
Data was derived from the following sources:
- Bioclimatic zones:
- Finnish Environment Institute: https://www.syke.fi/en-US/Open_information/Spatial_datasets/Downloadable_spatial_dataset
- Climate variables were computed based on the products from:
- Aalto, J., Pirinen, P., & Jylhä, K. (2016). New gridded daily climatology of Finland: Permutation‐based uncertainty estimates and temporal trends in climate. Journal of Geophysical Research: Atmospheres, 121(8), 3807-3823.
- Monitoring data:
- Bird: Finnish Museum of Natural History
- Butterfly: Finnish Environment Institute
- Moth: Finnish Environment Institute
- Phytoplankton: Finnish Environment Institute
- Plant: Natural Resource Institute Finland
- Species temperature index (STI) derived from European range maps. Range map sources:
- Butterfly (range maps and STI values):
- Schweiger, O., Harpke, A., Wiemers, M., and Settele, J. (2014). Climber: Climatic niche characteristics of the butterflies in europe. Zookeys, 65(367):65–84.
- Settele, J., Hammen, V., Hulme, P., Karlson, U., Klotz, S., Kotarac, M., Kunin, W., Marion, G., O’Connor, M., and Petanidou, T. (2005). Alarm: Assessing large-scale environmental risks for biodiversity with tested methods. GAIA-Ecological perspectives for science and society, 14(1):69–72.
- Moth:
- Fibiger, M. (1990). Noctuidae Europaeae, volume 1. Entomological Press, Sorø, Denmark.
- Fibiger, M. (1993). Noctuidae Europaeae, volume 2. Entomological Press, Sorø, Denmark.
- Fibiger, M. (2009). Noctuidae Europaeae, volume 11. Entomological Press, Sorø, Denmark.
- Fibiger, M. and Hacker, H. (2007). Noctuidae Europaeae, volume 9. Entomological Press, Sorø, Denmark.
- Fibiger, M., Hacker, H., and Goater, B. (1995). Noctuidae Europaeae, volume 7. Entomological Press, Sorø, Denmark.
- Fibiger, M., Ronkay, L., Yela, J. L., and Zilli, A. (2010). Noctuidae Europaeae, volume 12. Entomological Press, Sorø, Denmark.
- Freina, J. J. and de Witt, T. J. (1987). Die Bombyces und Sphinges der Westpalaearktis, volume 1. Forschung Wissenschaft Verlag GmbH, Munich, Germany.
- Freina, J. J. and de Witt, T. J. (1990). Die Bombyces und Sphinges der Westpalaearktis. Forschung Wissenschaft Verlag GmbH, Munich, Germany.
- Goater, B., Fibiger, M., and Ronkay, L. (2003). Noctuidae Europaeae, volume 10. Entomological Press, Sorø, Denmark.
- Hacker, H., Hreblay, M., Ronkay, L., and I., H. (2002). Noctuidae europaeae, volume 4. Entomological Press, Sorø, Denmark.
- Hausmann, A., Mironov, V., Sihvonen, P., Skou, P., and Viidalepp, J. (2014). The Geometrid Moths of Europe (update).
- Hausmann, A. and Viidalepp, J. (2012). The Geometrid Moths of Europe, volume 3. Apollo Books, Stensrup, Denmark.
- Hausmann, A. (2004). The Geometrid Moths of Europe, volume 2. Apollo Books, Stensrup, Denmark.
- Mironov, V., Haussmann, A., and Wilson, D. (2003). The Geometrid Moths of Europe, volume 4. Apollo Books, Stensrup, Denmark.
- Muller, B., Erlacher, S., Hausmann, A., Rajaei, H., Sihvonen, P., and Skou, P. (2019). The Geometrid Moths of Europe, volume 6. E J Brill, Leiden, Netherlands.
- Ronkay, G. and Ronkay, L. (1994). Noctuidae Europaeae. Entomological Press, Sorø, Denmark.
- Ronkay, G., Ronkay, L., Speidel, W., and Witt, T. (2012). Noctuidae Europaeae, volume 13. Sorø, Denmark, Entomological Press.
- Ronkay, L., Hreblay, M., and Yela, J. L. (2001). Noctuidae Europaeae. Entomological Press, Sorø, Denmark.
- Schweiger, O., Harpke, A., Wiemers, M., and Settele, J. (2014). Climber: Climatic niche characteristics of the butterflies in europe. Zookeys, 65(367):65–84.
- Settele, J., Hammen, V., Hulme, P., Karlson, U., Klotz, S., Kotarac, M., Kunin, W., Marion, G., O’Connor, M., and Petanidou, T. (2005). Alarm: Assessing large-scale environmental risks for biodiversity with tested methods. GAIA-Ecological perspectives for science and society, 14(1):69–72.
- Skou, P. and Sihvonen, P. (2015). The Geometrid Moths of Europe, volume 5. E J Brill, Leiden, Netherlands.
- Zilli, A., Ronkay, L., and Fibiger, M. (2005). Noctuidae Europaeae, volume 2005. Entomological Press, Sorø, Denmark.
- Phytoplankton
- Moe, S. J., Schmidt-Kloiber, A., Dudley, B. J., and Hering, D. (2012). The wiser way of organising ecological data from european rivers, lakes, transitional and coastal waters. Hydrobiologia, 704(1):11–28.
- Contact Birger Skjelbred (birger.skjelbred@niva.no) for data queries.
- Plant
- Auffret, A. G. et al. (2023). More warm-adapted species in soil seed banks than in herb layer plant communities across europe. Journal of Ecology, 111(5):1009–1020.
- Caudullo, G. et al. (2017). Chorological maps for the main european woody species. Data Brief, 12:662–666.
- Kalwij, J. M., Robertson, M. P., Ronk, A., Zobel, M., and Partel, M. (2014). Spatially-explicit estimation of geographical representation in large-scale species distribution datasets. PLoS One, 9(1):e85306.
- Kurtto, A., Sennikov, A., and Lampinen, R. (2013). Atlas florae europaeae: distribution of vascular plants in europe.
- Kurtto, A. K., Sennikov, A. N., and Lampinen, R. E. (2018). Atlas Florae Europaeae. Distribution of Vascular Plants in Europe: 17. Rosaceae (Sorbus s. lato). The Committee for Mapping the Flora of Europe Societas Biologica Fennica
- Vangansbeke, P., Malis, F., Hedl, R., Chudomelova, M., Vild, O., Wulf, M., Jahn, U., Welk, E., Rodrıguez-Sanchez, F., De Frenne, P., and Bahn, V. (2021). Climplant: Realized climatic niches of vascular plants in european forest understoreys. Global Ecology and Biogeography, 30(6):1183–1190.
- Butterfly (range maps and STI values):
Code/Software
This code and software have been used to create the analysis and results of the study. All analyses were run with R 4.3.1 (RStudio Team, 2020)). Inference is conducted with INLA (version 23.05.30, https://www.r-inla.org/).
- File 1 Name: Fig_S1.R
- File 1 Description: Plot figure 1 of the supporting information.
- File 2 Name: Fig_S3.R
- File 2 Description: Plot Figure 3 of the supporting information.
- File 3 Name: Fig2.R
- File 3 Description: Plot Figure 2 of the manuscript.
- File 4 Name: Fig3. R
- File 4 Description: Plot Figure 3 of the manuscript.
- File 5 Name: Fig4. R
- File 5 Description: Plot figure 4 of the manuscript.
- File 6 Name: Fig5. R
- File 6 Description: Plot Figure 5 of the manuscript.
- File 7 Name: Run_inference.R
- File 7 Description:
- Read in species and environmental data.
- Set data for models and run models for all response variables (CTImean, CTIdiv, STBImean, STBIdiv, and population trends).
- Save estimated models.
- File 7 Description:
- File 8 Name: Run_inference_no_Epirrita_autumnata.R
- File 8 Description:
- Read in moth species (excluding Epirrita autumnata) and environmental data.
- Set data for models and run models for all response variables (CTImean, CTIdiv, STBImean, STBIdiv, and population trends).
- Save estimated models.
- File 8 Description:
For birds, we used records collected in 1978–2020, including 145 species sampled across 1149 transects. Transects are 3-6 km long and visited once per survey year. Surveys are typically conducted in June, with some variation in exact dates as due to the latitudinally varying phenology of the breeding season. Not every transect is surveyed each year, whereas survey intensity (walking speed, survey methodology and width of surveyed area around a transect) is constant over surveys. The data have been curated and processed by the Finnish Museum of Natural History. We derived STIs for all species.
For butterflies, records were collected in 1999–2020 and included 91 species sampled across 101 transects. Surveys are conducted by volunteers and the monitoring program is directed by the Finnish Environment Institute (Syke). Not every transect is surveyed each year. Surveys are conducted at least seven times per site during May to August. Given latitudinal gradients in the length of the season, the survey period varies from 10 weeks in Northern Finland to 16 weeks in Southern Finland. The survey intensity of each single transect visit is held constant between sites and years and the species identification skill of the volunteers is high. We derived STIs for 90 species.
For moths, records were collected 1993–2023 and included 1573 species of micro- and macromoths sampled in 246 traps. The moth recording is conducted under the National Moth Monitoring scheme (Nocturna) and coordinated by Syke. Light traps are run from April to October/November in the south of Finland and May to September/October in the north, thus covering the entire activity period of moths. Traps are emptied on average weekly by volunteers, and identification of moth catches is also done by volunteers with quality control by the coordination team. Due to varying resource allocation and different moth activity periods, sites may have been visited different times between years and sites. The data have been curated by monitoring coordinators. We derived STIs for 722 macro-moths.
For forest plants, 1700 sample sites were monitored in 1985-1986 and 1995, with a resurvey of 443 sites in 2006. All sites are located on mineral soils. At each site, the percentage cover of vascular forest plants (small tree and shrub seedlings and saplings, dwarf shrubs, herbs and graminoids) was recorded in four 2 m x 2 m quadrats located systematically at three, six and eight meters distance from the plot center. The sites were located in clusters of four sites, 16 km apart from each other in Southern Finland, and clusters of three sites, 24 km apart in the east-west direction and in 32 km apart in the north-south direction in Northern Finland. In total, 487 vascular forest plant species were recorded. The data are curated and maintained by the Natural Resources Institute Finland (Luke). We derived STIs for 348 plants as some species were missing a range map.
Phytoplankton records were collected 1978-2017 in 853 lakes across 1057 study sites. In total, 1222 species were detected. The surveys were conducted during early July to late August, reflecting the peak productivity season of lake phytoplankton communities. All phytoplankton samples were preserved with acid Lugol’s solution and analysed using the standard Utermöhl technique. Phytoplankton communities have been monitored in inland and coastal waters by national environment authorities for the assessments of the state of the water bodies. The data set is curated and maintained by Syke (https://ckan.ymparisto.fi/dataset/kasviplanktontietojarjestelma-kplank). We derived STIs for 722 species.