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The data contains three supporting datasets: 1. Mid-intertidal data 2. Vertical transect data 3. GPS coordinates for all sites

Overview The following dataset presents the energy cycle characteristics for 5G/6G mobile systems supported by Renewable Energy Sources (RES) and/or Unmanned Aerial Vehicles (UAVs) and Reconfigurable Intelligent Surfaces (RISs). In addition, within the dataset, the energy gain related to the engagement of RES within the Radio Access Network (RAN) has also been distinguished. Scenario The considered network scenario includes 8 three- (_results_gcas.csv) or one-cell (_results_scas.csv & _results_kras.csv) base stations (BSs) placed within the Poznan city (surroundings of the old market) and supported by Renewable Energy Sources — photovoltaic panels (PVs) and/or wind turbines (WTs). The aforementioned base stations can be treated as stationary towers or mobile access points (e.g., drones/UAVs). Those latter have been additionally equipped with RIS devices, which are able to reflect and manipulate a radio signal to influence occurrences such as interferences, coverage, or human exposure. However, the use of RISs has been taken into account only to evaluate the impact of the engagement of such devices on the energy side of the mobile system, omitting the changes in radio characteristics. The network traffic has been assumed to be fixed (64 mobile users (UEs) with 100 Mbps downlink — DL, and 25 Mbps uplink — UL, per each), however, its density in specific parts of the city is modeled randomly for each simulation run. The simulation runs have been performed for 4 dates (vernal equinox, summer solstice, autumn equinox, winter solstice), each one from a different season of the year. The aim of such an approach was to highlight the impact of the time of the day and the year on the energy gain obtained thanks to enabling RES generators. The weather conditions assumed within the simulation are typical for the climate in Poland. Methodology The energy-cycle calculations (system's power consumption, renewable energy production, and excessive energy storage) have been based on the mathematical formulas from the scientific literature and performed within the digital simulation runs by using the Green Radio Access Network Design (GRAND) tool (developed by teams from the Ghent University & Poznan University of Technology). The UE-BS association process within the mobile system has been done by doing multi-objective optimization using the Gurobi software, which has taken into account parameters like path loss, predicted power consumption of BSs, and guaranteed DL & UL bit rates for UEs. Simulation setup The setup of the input parameters for used mathematical models (power consumption, energy generation, energy storage) has been done in accordance with the values attached within the delivered literature positions (cited within the publications included in the Related works section of the following dataset) and adjusted to the considered study. Furthermore, the data used to model the network environment (building distribution, coverage area, base stations' locations) as well as to predict weather conditions are the real data (for the year 2022) collected by the city hall of Poznan, one of the Polish mobile operators, and weather stations placed in Poznan, respectively. The number of simulation runs performed has been equal to 10 (each run has included energy-cycle calculations for 4 seasons of the year), with the time step of a single run set to 1 hour of the day. Results The results of the aforementioned investigations have been included in the attached files, which can be described as follows: File _results_gcas.csv The first column denotes the date (season of the year), for which the values have been obtained. The columns from second to fifth present observed values of the State of Charge (SoC) of a battery system (in %) for a single network cell on average in a time step. Those columns are the obtained values for the RAN, in which no RES, only PVs, only WTs, and both types of RES generators have been enabled, respectively. Files _results_scas.csv & _results_kras.csv The first column denotes the date (season of the year), for which the values have been obtained. The second and third columns denote the number of drone base station (DBS) exchanges within the wireless system on average in a particular time step, where no RES and only PVs are enabled, respectively. The fourth and fifth columns present the conventional (fossil-fuels-based) energy consumption (in kWh) for the whole system in a specific time step, in which no RES and only PVs are engaged for all the access nodes. The sixth column is the energy savings (in kWh) related to the use of RES generators within the mobile network. Furthermore, the seventh and eighth columns represent the amount of renewable energy harvested from the solar radiation in total and the peak value of this amount observed during the entire day, respectively. Acknowledgment More details about the conducted studies have been described within the attached papers (Related works section). The data has been collected within the COST CA10210 INTERACT. M. Deruyck is a Post-Doctoral Fellow of the FWO-V (Research Foundation – Flanders, ref: 12Z5621N). The work (including the following dataset preparation) by A. Samorzewski and A. Kliks was realized within project no. 2021/43/B/ST7/01365 funded by the National Science Center in Poland.

This data set describes the population dynamics of Wilson's Storm Petrels (Oceanites oceanicus) at King George Island (Isla 25 de Mayo, Antarctica) over a forty year period (1978 – 2020). It includes all available data on Wilson's Storm Petrels from two colonies: around the Argentinian Base Carlini (62°14′S, 58°40′W; CA, formerly called Base Jubany) and the Henryk Arctowski Polish Antarctic Station (62°09′S, 58°27′W; HA). Data on population productivity (number of nests, eggs, chicks and fledglings) was collected by regular visits to the colonies and searching for nest burrows, or monitoring of the egg or chick if found. Data on adult abundance and estimated age categories (i.e., presence of foot spots; Quillfeldt et al. (2000, doi:10.1007/s003000000167) were collected at CA by using the same size mistnet every study year in the same location within the breeding colony. Chicks were measured regularly (varying intervals depending on the study) at both CA and HA. Chick tarsus was measured using callipers (vernier or digital depending on the study year) to the nearest 0.1 mm, chick wing length was measured using wing rulers to the nearest 1 mm, and chick body mass was measured using mechanical or digital scales depending on the study year to the nearest 0.1 g. Chick growth rates were calculated based on the linear growth period following Ausems et al. (2020, doi:10.1016/j.scitotenv.2020.138768). Chick food loads (g) were recorded at CA and determined based on changes in chick body mass on consecutive days (Gladbach et al. (2009, doi:10.1007/s00300-009-0628-z); Kuepper et al. (2018, doi:10.1016/j.cbpa.2018.06.018). This study was further supported by the Erasmus+ programm and thee German Academic Exchange Service (DAAD)

This project contains the data obtained as a result of the Preludium Grant no 2022/45/N/ST8/01425 of the Polish National Science Centre fundings. Within the "Aeroacoustic investigations of streamwise vortex generators for boundary layer separation control" project, two main research tasks were defined: 1. Post-processing and analysis of acoustic measurements using beamforming techniques to investigate RVGs effect on acoustic sources 2. Post-processing and analysis of Particle Image Velocimetry (PIV) data to investigate a flow structure downstream of RVG The resutls from these tasks are uploaded here. The details of the data are included in the EOP_medata_1.docx document uploaded. Further information regarding the data is published in the paper https://www.researchgate.net/publication/380825438_Aeroacoustic_effect_of_boundary_layer_separation_control_by_rod_vortex_generators_on_the_DU96-W-180_airfoil

# Reproductive data Fagus sylvatica: Widespread masting breakdown in beech [https://doi.org/10.5061/dryad.qz612jmps](https://doi.org/10.5061/dryad.qz612jmps) This dataset, used in the Global Change Biology article "Widespread breakdown in masting in European beech due to rising summer temperatures", contains 50 time series of population-level annual reproductive data by European beech (*Fagus sylvatica*, L) across Europe. The dataset builds on the open-access dataset [MASTREE+](https://doi.org/10.1111/gcb.16130), and expands it for European beech. ## Description of the data The dataset column names follow that of MASTREE+. A description of MASTREE+ column names (Modified from Table 1 in the [MASTREE+ article)](https://doi.org/10.1111/gcb.16130): | *Columns* | *Description* | *Contains NA?* | | :-------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------- | | Alpha\_Number | Unique code associated with each original source of data, that is, the publication, report or thesis containing extracted data, or the previously unpublished data set included in MASTREE+. | No | | Segment | Temporal segment of a time-series containing gaps (note that years with no observations are not recorded). Individual timeseries can consist of multiple segments. | No | | Site\_number | Code to differentiate multiple sites from the same original source (Alpha\_Number/Study\_ID). | No | | Variable\_number | Code to differentiate multiple measures of reproductive output from the same species-site combination (e.g. where seeds and cones were recorded separately). | No | | Year | Year of observation. | No | | Species | Species identifier, standardised to The Plant List nomenclature. ‘spp.’ is used to indicate a record identified to the genus level only. ‘MIXED’ indicates a non-species-specific community-level estimate of annual reproductive effort. | No | | Species\_code | Six-character species identifier. | No | | Mono\_Poly | Monocarpic (semelparous) or Polycarpic (iteroparous) species. | No | | Value | The measured value of annual reproductive output. | No | | VarType | Continuous or ordinal data. Continuous time-series are recorded on a continuous scale. Ordinal series are recorded on an ordered categorical scale. All ordinal series are rescaled to start at 1 (lowest reproductive effort) and to contain only integer values. | No | | Max\_value | The unit of measurement, where VarType is continuous (otherwise: NA). | No | | Unit | The maximum value in a time-series. | No | | Variable | Categorical classification of the measured variable. Options limited to: cone, flower, fruit, seed, pollen, total reproduction organs. | No | | Collection\_method | Classification of the method used to measure reproductive effort. Options are limited to: cone count, cone scar count, flower count, fruit count, fruit scar sound, seed count, seed trap, pollen count, lake sediment pollen count, harvest record, visual crop assessment, other quantification, dendrochronological reconstruction. | No | | Latitude | Latitude of the record, in decimal degrees. | No | | Longitude | Longitude of the record, in decimal degrees. | No | | Coordinate\_flag | A flag to indicate the precision of the latitude and longitude. A = coordinates provided in the original source B = coordinates estimated by the compiler based on a map or other location information provided in the original source C = coordinates estimated by the compiler as the approximate centre point of the smallest clearly defined geographical unit provided in the original source (e.g. county, state, island), and potentially of low precision. | No | | Site | A site name or description, based on information in the original source. | No | | Country | The country where the observation was recorded. | No | | Elevation | The elevation of the sample site in metres above sea level, where provided in the original source (otherwise: NA). | Yes | | Spatial\_unit | Categorical classification of spatial scale represented by the record, estimated by the compiler based on information provided in the original source. stand = <100 ha, patch = 100–10,000 ha, region = 10,000–1,000,000 ha, super-region = >1,000,000 ha. | No | | No\_indivs | Either the number of monitored individual plants, or the number of litter traps. NA indicates no information in the original source, and 9999 indicates that while the number of monitored individuals was not specified, the source indicated to the compiler that the sample size was likely ≥10 individuals or litter traps. | No | | Start | The first year of observations for the complete time-series, including all segments. | No | | End | The final year of observations for the complete time-series, including all segments. | No | | Length | The number of years of observations. Note that may not be equal to the number of years between the Start and End of the time-series, due to gaps in the time-series. | No | | Reference | Identification for the original source of the data. | No | | Record\_type | Categorisation of the original source. Peer-reviewed = extracted from peer reviewed literature Grey = extracted from grey literature Unpublished = unpublished data. | No | | ID\_enterer | Identification of the original compiler of the data. AHP, Andrew Hacket-Pain; ES, Eliane Schermer; JVM, Jose Moris; XTT, Tingting Xue; TC, Thomas Caignard; DV, Davide Vecchio; DA, Davide Ascoli; IP, Ian Pearse; JL, Jalene LaMontagne; JVD, Joep van Dormolen. | No | | Date\_entry | Date of data entry into MASTREE+ in the format yyyy-mm-dd. | No | | Note on data location | Notes on the location of the data within the original source, such as page or figure number. If not provided, NA. | Yes | | Comments | Additional comments. If not provided, NA. | Yes | | Study\_ID | Unique code associated with each source of data. M\_ = series extracted from published literature; A\_ = series incorporated from Ascoli et al. (2020), Ascoli, Maringer, et al. (2017) and Ascoli, Vacchiano, et al. (2017); PLK\_ = series incorporated from Pearse et al. (2017); D\_ = unpublished data sets. NA is attributed if no study ID has been previously associated with this time-series in MASTREE+ v.1. | Yes | Note that the new beech reproductive data has been assigned an arbitrary Alpha_Number for the purpose of this study. Future MASTREE+ updates which incorporate this new data may alter the time series ID columns (e.g. Alpha_Number, Site_number, Variable_number). MASTREE+ updates can be found on [GITHUB](https://github.com/JJFoest/MASTREEplus). Climate change effects on tree reproduction are poorly understood even though the resilience of populations relies on sufficient regeneration to balance increasing rates of mortality. Forest-forming tree species often mast, i.e. reproduce through synchronised year-to-year variation in seed production, which improves pollination and reduces seed predation. Recent observations in European beech show, however, that current climate change can dampen interannual variation and synchrony of seed production, and that this masting breakdown drastically reduces the viability of seed crops. Importantly, it is unclear under which conditions masting breakdown occurs, and how widespread breakdown is in this pan-European species. Here, we analysed 50 long-term datasets of population-level seed production, sampled across the distribution of European beech, and identified increasing summer temperatures as the general driver of masting breakdown. Specifically, increases in site-specific mean maximum temperatures during June and July were observed across most of the species range, while the interannual variability of population-level seed production (CVp) decreased. The declines in CVp were greatest where temperatures increased most rapidly. Additionally, the occurrence of crop failures and low-seed years has decreased during the last four decades, signalling altered starvation effects of masting on seed predators. Notably, CVp did not vary among sites according to site mean summer temperature. Instead, masting breakdown occurs in response to warming local temperatures (i.e. increasing relative temperatures), such that the risk is not restricted to populations growing in warm average conditions. As lowered CVp can reduce viable seed production despite the overall increase in seed count, our results warn that a covert mechanism is underway that may hinder the regeneration potential of European beech under climate change, with great potential to alter forest functioning and community dynamics.

Overview The following dataset presents the power balance characteristics for Unmanned Aerial Vehicle Base Stations (UAV-BSs) equipped with Renewable Energy Sources (RES) and Reconfigurable Intelligent Surfaces (RISs). The dataset has been prepared for two different types of UAVs, i.e., multirotor and fixed-wing ones. Scenario The considered scenario includes 2 UAV-BSs (each of a different type) equipped with a single RF transceiver and an RIS device and RES — a single photovoltaic panel (PV) and a single wind turbine (WT). The UAV-BSs are placed within the city of Poznan and hover (multirotor) or follow a circular route (fixed-wing) above a single mobile user with fixed traffic demand (100 Mbps downlink — DL, and 50 Mbps uplink — UL). The simulation runs have been performed for 4 dates (vernal equinox, summer solstice, autumn equinox, winter solstice), each one from a different season of the year. The aim of such an approach was to highlight the impact of the time of the day and the year on the energy gain obtained thanks to enabling RES generators as well as on the power consumption of the hardware of each UAV-BS type. The weather conditions assumed within the simulation are typical for the climate in Poland. Methodology The power-balance calculations (UAV-BSs' power consumption, renewable energy production) have been based on the mathematical formulas from the scientific literature and performed within the digital simulation runs by using dedicated software developed in Python programming language. Simulation setup The setup of the input parameters for used mathematical models (power consumption, energy generation) has been done in accordance with the values attached within the literature positions (cited within the publication included in the Related works section of the following dataset) and adjusted to the considered study. Furthermore, the data used to predict weather conditions are the real data (for the year 2022) collected by the weather stations placed in Poznan. A single simulation run has been performed (which takes into account 2 types of UAV-BS simultaneously and estimates their power balance for 4 seasons of the year), where the time step has been set to 1 hour of the day. Results The results of the aforementioned investigations have been included in the attached files (_power_balance_multirotor.csv & _power_balance_fixed_wing.csv). The first column denotes the hour of a particular day. Next, 4 multicolumns have been presented for the following variants — No RES enabled, only PV enabled, only WT enabled, and both types of RES generators enabled. In addition, each multicolumn consists of 4 columns, each of which represents a UAV-BS's hardware power balance (in W) for a different date (season of the year). Acknowledgment More details about the conducted study have been described within the attached paper (Related works section). The work (including the following dataset preparation) was realized within project no. 2021/43/B/ST7/01365 funded by the National Science Center in Poland.

Climate change is impacting water flow worldwide and is particularly important for High Arctic basins. Thawing permafrost and melting of glaciers, as well as higher air temperatures and precipitation, affect hydrological regimes and retention in polar basins. However, knowledge is limited as regards long-term changes in discharge from catchments in the High Arctic. Our aim was to evaluate the impact of local conditions on hydrological regime in glacial-fluvio-lacustrine model system in the High Arctic. We used mainly hydrological and meteorological data from 9 summer seasons (June-September) between 2005 and 2019 extracted from the entire database (16 seasons in 1972-2019). Wide range of statistical methods was applied including bootstrapping, random forest and multiple regression, to determine the coupling between hydrometeorological parameters (air and water temperature, discharge, sunshine duration, precipitation). The hydrological regime exhibits a distinct seasonal pattern with a pronounced, snowmelt-derived peak (maximum discharge) in the early part of the season (June-July) affected by precipitation. In the late part of the season (August-September), low-intermediate discharge is primarily governed by air temperatures and, only secondarily by precipitation. The hydrometeorological coupling in August-September is stronger that in June-July. The statistically significant increase in air temperature (0.45°C per decade) in August-September during 1979-2018 makes this part of the season important in terms of long-term changes in the permafrost-underlain catchment. Thawing of the permafrost active layer thaw is clearly reflected by air–temperature-dependent low-to-intermediate discharge. Database consists of following data obtained from long-term discharge analyses: daily discharge data at the gauging station from 1983-2019 (1983-2019_Brattegg_River_Discharge_v1.csv), daily water stage data from 1972-1983 (1972-1983 _ Brattegg_River_Water_Stage_v1.csv), daily water level at gauging station and outflow from Bratteggbreen from 2017 (2017_Brattegg_River_water_stage_gauging_station_Bratteggbreen_v1.csv). This study is a contribution to the National Science Centre projects: 2021/43/D/ST10/00687 (SONATA17 funding scheme, ŁS), 2020/39/I/ST10/02129 (OPUS-LAP funding scheme, MB), 2017/27/B/ST10/01269 (OPUS funding scheme, KM), and SONATA 2015/19/D/ST10/02869 (SONATA funding scheme, MK). For the purpose of Open Access, the authors have applied a CC BY public copyright licence to any Author Accepted Manuscript (AAM) version arising from this submission. ŁS was also supported from the Bekker Programme (award no. BPN/BEK/2021/1/00431) at the Polish National Agency for Scientific Exchange. The study was carried out by DI, EL as part of scientific activity of the Centre for Polar Studies (University of Silesia in Katowice) with the use of research and logistic equipment (monitoring and measuring equipment, sensors, multiple AWS, GNSS receivers, snowmobiles and other supporting equipment) of the Polar Laboratory of the University of Silesia in Katowice. MW and HM acknowledge the statutory fund of University of Wrocław for suport during fieldwork in 2005-2010.

The presented data set consists of noise measurement and performance characteristics obtained as a part of the experimental campaign in the Open Jet Facility (OJF) at Delft University of Technology. The observations have been recorded for a typical Savonius vertical axis wind turbine. Refer to the file "setup" for further experimental campaign details.

24 cm ; The aim of the paper is to characterize the trends of sunshine duration (SDU) and air temperature in Poland, which may help understand the mechanism of contemporary climate change. The daily totals of SDU and daily data on air temperature from the years 1971-2020, from 25 synoptic stations in Poland are the basic source data. The series of records of the two variables showed that the points of change in the level of stabilization of the value of SDU and air temperature are close to each other, and confirm known in the literature “global dimming” and “global brightening” periods. The linear regression model confirmed that sunshine duration explains well the variability of, and increase in day-time air temperature in Poland in the warm part of the year. ; 24 cm ; The aim of the paper is to characterize the trends of sunshine duration (SDU) and air temperature in Poland, which may help understand the mechanism of contemporary climate change. The daily totals of SDU and daily data on air temperature from the years 1971-2020, from 25 synoptic stations in Poland are the basic source data. The series of records of the two variables showed that the points of change in the level of stabilization of the value of SDU and air temperature are close to each other, and confirm known in the literature “global dimming” and “global brightening” periods. The linear regression model confirmed that sunshine duration explains well the variability of, and increase in day-time air temperature in Poland in the warm part of the year.