DOI: 10.5061/dryad.4j0zpc8np
title: Data from: Thermal homogenization of boreal communities in response to climate warming

description: 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: 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.
description: # Thermal homogenization of boreal communities in response to climate
 warming ## 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 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 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 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 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](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](mailto: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. ## 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/](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: 1. Read in species and environmental data. 2. Set data for models and run models for all response variables (CTImean, CTIdiv, STBImean, STBIdiv, and population trends). 3. Save estimated models. * File 8 Name: Run_inference_no_Epirrita_autumnata.R * File 8 Description: 1. Read in moth species (excluding Epirrita autumnata) and environmental data. 2. Set data for models and run models for all response variables (CTImean, CTIdiv, STBImean, STBIdiv, and population trends). 3. Save estimated models.