Urban trees provide cooling through two primary mechanisms: evapotranspiration and radiative modification. This dataset quantifies these cooling services across urban and peri-urban municipalities in all Swiss cantons, using the Greening Cooling Services Index (GCoS), a high-accuracy indicator developed by Rocha et al. (2022). GCoS is based on the Soil-Canopy Observation of Photosynthesis and Energy Fluxes (SCOPE) model, a process-based framework that simulates energy balance and radiative transfer within vegetated canopies. The cooling simulation follows a two-stage process. First, we estimate hourly urban evapotranspiration (ET) and soil temperature for the hottest day of the target year, at a spatial resolution of 300 m. Second, these outputs are downscaled to 10 m resolution using high-resolution urban tree fraction data. The final GCoS consists of two components: ECoS (Evapotranspirative Cooling Service) and RCoS (Radiative Cooling Service), providing a detailed spatial representation of vegetation-driven cooling. This dataset enables high-resolution assessments of nature-based climate adaptation strategies and supports research and planning aligned with the Sustainable Development Goals (SDGs). The calculations are based on the CH2018.

Data file accompanying the publication Biodiversity consequences of long-term active forest restoration in selectively-logged tropical rainforests. (https://doi.org/10.1016/j.foreco.2023.121414)This data file entails the calculated tree diversity and forest structure parameters presented in the above-named publication. The raw data on the adult tree data per plot can be accessed in the following repository: https://doi.org/10.5281/zenodo.8042468 , and the raw data on the seedling data per plot can be accessed in the following repository: https://zenodo.org/record/8063292 Use of these data require citation of this dataset, the raw data on adult trees, the raw data on seedlings, the associated publication (Keller et al. submitted), as well as the 2017 dataset (which describes the full set up process).  We also require that you inform us of the use of the data would also appreciate the opportunity to be involved in work making use of this data. The required citations are follows:Keller, Nadine, Niklaus, Pascal A., Ghazoul, Jaboury, Marfil, Tobias, Godoong, Elia, & Philipson, Christopher D. (2023). TreeDiversity_ForestStructure [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8041128Keller, Nadine, Karolus, Alexander, Murus, Remmy, O'Brien, Michael, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Philipson, Christopher D. (2023). 'Danum Revised' forest field plot data for thirty-five 0.28 hectare field plots, measured in 2020 (0.9) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8042468Marfil, Tobias, Keller, Nadine, Bin Abd Karim, Bin Jelling, Steven, Zenden, & Philipson, Christopher D. (2023). 'Danum Revised' seedling data for twenty-seven 4 m2 field plots, measured in 2020 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8063292Keller, Nadine, Pascal A Niklaus, Jaboury Ghazoul, Tobias Marfil, Elia Godoong, and Christopher D Philipson. 2023. "Biodiversity Consequences of Long-Term Active Forest Restoration in Selectively-Logged Tropical Rainforests." Forest Ecology and Management 549: 4. https://doi.org/10.1016/j.foreco.2023.121414.Philipson, Christopher D., Brodrick, Philip G., Milne, Sol, Murus, Remmy, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Asner, Gregory P. (2023). 'Danum Revised' forest field plot data for twenty 0.28 hectare field plots, measured in 2017 (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8042050

Data file accompanying the publication Biodiversity consequences of long-term active forest restoration in selectively-logged tropical rainforests. (https://doi.org/10.1016/j.foreco.2023.121414)This data file entails the calculated tree diversity and forest structure parameters presented in the above-named publication. The raw data on the adult tree data per plot can be accessed in the following repository: https://doi.org/10.5281/zenodo.8042468 , and the raw data on the seedling data per plot can be accessed in the following repository: https://zenodo.org/record/8063292 Use of these data require citation of this dataset, the raw data on adult trees, the raw data on seedlings, the associated publication (Keller et al. submitted), as well as the 2017 dataset (which describes the full set up process).  We also require that you inform us of the use of the data would also appreciate the opportunity to be involved in work making use of this data. The required citations are follows:Keller, Nadine, Niklaus, Pascal A., Ghazoul, Jaboury, Marfil, Tobias, Godoong, Elia, & Philipson, Christopher D. (2023). TreeDiversity_ForestStructure [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8041128Keller, Nadine, Karolus, Alexander, Murus, Remmy, O'Brien, Michael, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Philipson, Christopher D. (2023). 'Danum Revised' forest field plot data for thirty-five 0.28 hectare field plots, measured in 2020 (0.9) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8042468Marfil, Tobias, Keller, Nadine, Bin Abd Karim, Bin Jelling, Steven, Zenden, & Philipson, Christopher D. (2023). 'Danum Revised' seedling data for twenty-seven 4 m2 field plots, measured in 2020 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8063292Keller, Nadine, Pascal A Niklaus, Jaboury Ghazoul, Tobias Marfil, Elia Godoong, and Christopher D Philipson. 2023. "Biodiversity Consequences of Long-Term Active Forest Restoration in Selectively-Logged Tropical Rainforests." Forest Ecology and Management 549: 4. https://doi.org/10.1016/j.foreco.2023.121414.Philipson, Christopher D., Brodrick, Philip G., Milne, Sol, Murus, Remmy, Rasion, Joulu, Reynolds, Glen, Siew Yee, Hii, Ulok, Philip Ak, & Asner, Gregory P. (2023). 'Danum Revised' forest field plot data for twenty 0.28 hectare field plots, measured in 2017 (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8042050

1. With urbanization identified as being one of the key drivers of change in global land use, and the rapid expansion of urban areas worldwide, it is relevant to evaluate how novel ecological conditions in cities shape species functional traits, which are essential for how species interact with their environments and with each other. 2. Despite the many comparative studies on organisms living in urban and non-urban areas our knowledge on species responses to urban environments remains limited. For one, much of the ecological research has assumed that the environment changes in a linear fashion from the city core to the city edges, whereas in reality the environments within the cities are highly heterogeneous. Furthermore, studies on species responses to these highly variable ecosystems are often based on interspecific mean trait values, which ignore the potential for high levels of intraspecific variation among individuals in key functional traits. 3. The current study investigated intraspecific functional trait differences for four functional traits associated with body size, mobility, and resource selection among rural and urban populations of two common bumblebee species, Bombus pascuorum and Bombus lapidarius, in urban centers and adjacent rural areas in Switzerland. 4. We document shifts in functional traits towards smaller individuals and higher multidimensional trait variation in urban populations compared to rural conspecifics of both species. This shows that urban individuals for both species are on average smaller sized but populations are distinctively different from rural population by increasing their trait richness and diversifying their trait combinations. In addition, we found bimodality in tongue length within urban B. pascuorum populations. 5. Our results suggest that urban and rural populations possibly experience differential selection pressures resulting in trait differences across and among populations. We argue that variations in the respective foraging landscapes in cities leads to smaller-sized but phenotypically more diverse populations, and drive functional trait divergence.

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