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CASCADE is a global dataset for 139 extant coccolithophore taxonomic units. CASCADE includes a trait database (size and cellular organic and inorganic carbon contents) and taxonomic-specific global spatiotemporal distributions (Lat/Lon/Depth/Month/Year) of coccolithophore abundance and organic and inorganic carbon stocks. CASCADE covers all ocean basins over the upper 275 meters, spans the years 1964-2019 and includes 33,119 taxonomic-specific abundance observations. Within CASCADE, we characterise the underlying uncertainties due to measurement errors by propagating error estimates between the different studies. Full details of the data set are provided in the associated Scientific Data manuscript. The repository contains five main folders: 1) "Classification", which contains YAML files with synonyms, family-level classifications, and life cycle phase associations and definitions; 2) "Concatenated literature", which contains the merged datasets of size, PIC and POC and which were corrected for taxonomic unit synonyms; 3) "Resampled cellular datasets", which contains the resampled datasets of size, PIC and POC in long format as well as a summary table; 4) "Gridded data sets", which contains gridded datasets of abundance, PIC and POC; 5) "Species lists", which contains spreadsheets of the "common" (>20 obs) and "rare" (<20 obs) species and their number of observations. The CASCADE data set can be easily reproduced using the scripts and data provided in the associated github repository: https://github.com/nanophyto/CASCADE/ (zenodo.12797197) Correspondence to: Joost de Vries, joost.devries@bristol.ac.uk v.0.1.2 has some fixes: 1. The wrongly specified S. neapolitana was removed from synonyms.yml (this species is now S. nana)2. Longitudes were corrected for Guerreiro et al., 20233. A double entry for Dimizia et al., 2015 was fixed4. Units in Sal et al., 2013 were correct to cells/L (previously cells/ml)5. Data from Sal et al., 2013 was re-done, as some species were missing6. Duplicate entries from Baumann et al., 2000 were dropped

Marcelo A. Aizen, Gabriela R. Gleiser, Thomas Kitzberger, Ruben Milla. Being a tree crop increases the odds of experiencing yield declines irrespective of pollinator dependence (to be submitted to PCI) Data and R scripts to reproduce the analyses and the figures shown in the paper. All analyses were performed using R 4.0.2. Data 1. FAOdata_21-12-2021.csv This file includes yearly data (1961-2020, column 8) on yield and cultivated area (columns 6 and 10) at the country, sub-regional, and regional levels (column 2) for each crop (column 4) drawn from the United Nations Food and Agriculture Organization database (data available at http://www.fao.org/faostat/en; accessed July 21-12-2021). [Used in Script 1 to generate the synthesis dataset] 2. countries.csv This file provides information on the region (column 2) to which each country (column 1) belongs. [Used in Script 1 to generate the synthesis dataset] 3. dependence.csv This file provides information on the pollinator dependence category (column 2) of each crop (column 1). 4. traits.csv This file provides information on the traits of each crop other than pollinator dependence, including, besides the crop name (column1), the variables type of harvested organ (column 5) and growth form (column 6). [Used in Script 1 to generate the synthesis dataset] 5. dataset.csv The synthesis dataset generated by Script 1. 6. growth.csv The yield growth dataset generated by Script 1 and used as input by Scripts 2 and 3. 7. phylonames.csv This file lists all the crops (column 1) and their equivalent tip names in the crop phylogeny (column 2). [Used in Script 2 for the phylogenetically-controlled analyses] 8.phylo137.tre File containing the phylogenetic tree. Scripts 1. dataset This R script curates and merges all the individual datasets mentioned above into a single dataset, estimating and adding to this single dataset the growth rate for each crop and country, and the (log) cumulative harvested area per crop and country over the period 1961-2020. 2. analyses This R script includes all the analyses described in the article’s main text. 3. figures This R script creates all the main and supplementary figures of this article. 4. lme4_phylo_setup R function written by Li and Bolker (2019) to carry out phylogenetically-controlled generalized linear mixed-effects models as described in the main text of the article. References Li, M., and B. Bolker. 2019. wzmli/phyloglmm: First release of phylogenetic comparative analysis in lme4- verse. Zenodo. https://doi.org/10.5281/zenodo.2639887.

[Methods for processing the data] The Easyflux datalogger program (Easyflux-DL, Campbell Scientific, 2020) corrected the raw high-frequency data from the EC tower using the full suite of standard corrections and adjustments, including spike filtering, measurement quality control flags and applying correction for high/low frequency losses, to generate corrected half-hourly turbulent fluxes. More details of EC data post-processing are available in the EasyFlux-DL product manual (Campbell Scientific, 2020). UAV images were processed using OpenDroneMap (https://www.opendronemap.org/), an open-source drone processing software. Raw TIR H20T image tiles (i.e. in R-JPEG format) were first converted to single band radiometric temperatures using the open-source DJI Thermal SDK software (https://www.dji.com/downloads/softwares/dji-thermal-sdk). These individual temperature image tiles were then mosaicked together with OpenDroneMap. Congruently, multispectral images from Sequoia+ were radiometrically calibrated using camera corrections, such as vignetting, black level and gain/exposure compensations, using the available routines developed for OpenDroneMap (https://github.com/OpenDroneMap/ODM/blob/master/opendm/multispectral.py). [Description of methods used for collection/generation of data] For the data located in 'meteo' folder, an Eddy-Covariance (EC) tower was used to sample all variables described above. The tower was instrumented with an integrated open-path infrared gas analyzer and 3D Sonic anemometer Campbell Scientific1 (IRGASON, Campbell Scientific, Logan, UT, USA) to measure ecosystem-level carbon and water gas exchanges alongwith meterological forcings. The raw data were sampled at a frequency of 20 Hz and recorded using a CR6 datalogger (Campbell Scientific, Logan, UT, USA). Regarding the images from the UAV system in the 'inputs' folder, a DJI Matrice-300 UAV (DJI Technology Co., Ltd, Shenzhen, China) was used to acquire visible near infrared (VNIR), thermal (TIR) and RGB imagery using the sensors Parrot Sequoia+ (Parrot S.A., Paris, France), DJI’s Zenmuse H20T and DJI’s Zenmuse P1, respectively. Regarding the images in the 'outputs' folder, these are the images resulting from applying the different versions of TSEB as shown in the python script ('run_tseb_main.py') All the inputs and outputs of the two-source energy balance (TSEB) model are in the 'inputs' and 'outputs folder. Another readme file explicitely describes this data. Also described below: ## inputs ### meteo A csv file with meterological and EC measurements during UAV overpass time. ### UAV UAV imagery are stored in seperate folders for each date (in YYYYMMDD). Each input is available over the study site at 2m spatial resolution. ## outputs The model outputs are available for both TSEB-PT and TSEB-2T versions using pyTSEB (https://github.com/hectornieto/pyTSEB). In each folder, both Main ('Main') and ancillary ('Anc') output data is made available.

- Sampling plots methodology. The number of systematic sampling plots, setting a maximum error of 6% was 256. The sampling plots centres were located at the nodes of a 55 m side square net. The corresponding UTM coordinates (Datum WGS84) were identified and located in field with a sub-metric precision GPS. Circular plots of 4 m diameter were marked on the terrain and the measurements of the following data were concentrated on them: shrub crown cover (CC, %), species composition, number of plants per hectare (N), and average shrub height (H, m). Subsequently, all the plants were cut at ground level and were weighted with a 40 kg ± 10 g digital dynamometer. Four samples per shrubland (2.5 kg per sample), including rockrose trunk, branches and leaves, were collected and sent to the Laboratory of Biomass Characterization (LCB) at CEDER-CIEMAT in Soria (Centre for the Development of Renewable Energy Sources) to measure moisture content in order to estimate dry biomass weight per study area. - The dataset includes field data from 290 rockrose sampling plots (Ø 4 m). 256 plots were used for developing a biomass weight per hectare equation and the rest of them for completing validation process. - Location of the four studied shrublands in Soria. Coordinates of sampling areas central point (Datum WGS84): - Lubia: Latitud 41º35´57.69” N, Longitud 2º29´53.57” W; Huso UTM: 30, Coord. X: 541816.48, Coord. Y: 4605416.65 - Acrijos: Latitud 42º2´38.99” N, Longitud 2º31´44.46” W; Huso UTM: 30, Coord. X: 566565.63, Coord. Y: 4654992.73 - Navalcaballo: Latitud 41º40´8.51” N, Longitud 2º31´36.14” W; Huso UTM: 30, Coord. X: 539399.58, Coord. Y: 4613138.42 - Centenera: Latitud 41º30´48.89” N, Longitud 2º41´31.76” W; Huso UTM: 30, Coord. X: 525688.09, Coord. Y: 4595817.82 Descripción del proyecto: The purpose of field data collection is building weight equations to predict dry biomass weight per hectare (t/ha) and dry biomass weight per plant (kg/plant) of rockrose (Cistus laurifolius L.) shrublands in Central Spain. Descripción del dataset: The dataset contains 2 data files with dasometric measurements from 290 rockrose Ø 4 m sampling plots (shrub crown cover, shrub mean height, green and oven-dried biomass weight), and individual measurements from 426 rockrose plants (plant height, mean crown diameter and oven-dried plant weight). The sampling date and the location of the study areas are also included. in. Excel, 10

Peer reviewed

Live woody vegetation is the largest reservoir of biomass carbon with its restoration considered one of the most effective natural climate solutions. However, carbon fluxes associated with terrestrial ecosystems still remain the largest source of uncertainty of the global carbon balance. Here, we develop spatially explicit estimates of global carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show live biomass has removed 4.9-5.5 PgC yr-1 from the atmosphere in this century, offsetting 4.6±0.1 PgC yr-1 of gross emissions from land-use and environmental disturbances and adding substantially (0.23-0.88 PgC yr-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.

En el present projecte s’estudia la viabilitat tècnica i econòmica d’implantar un sistema de calefacció i d’aigua calenta sanitària centralitzat, de manera que amb una sola central de generació d’energia tèrmica i una xarxa de distribució de calor, es pugui subministrar energia tèrmica a diferents edificis a Sant Martí de Tous. El sistema estudiat es basa en una central de biomassa com a generadora d’energia tèrmica i un entramat de canonades que distribueixen aquesta calor pels diferents edificis, situats en un radi inferior a 350m del punt de generació de calor. Per entrar en situació, s’estudia l’estat de l’art, tant de la biomassa com de les xarxes de calor. D’aquest primer pas se n’extreu: - La selecció del tipus de biomassa més adequat tenint en compte diversos factors com el preu per unitat d’energia, la disponibilitat al municipi, les potències i consums recomanats per a cada tipus de biomassa i la petjada ecològica. - L’elecció del tipus d’entramat de distribució de calor, quins elements el formen, quin tipus de connexió amb l’usuari final és la més adequada i quines temperatures de funcionament s’utilitzaran entre altres temes. Es presenta cadascun dels edificis a tractar i les característiques rellevants pel projecte. Per estimar la demanda energètica de la instal·lació, s’ha modelitzat cada edifici per separat prenent-lo com una carcassa que té guanys i pèrdues energètiques amb l’ambient, tenint en compte les ocupacions i les renovacions d’aire necessàries per garantir la qualitat de l’aire. Pel que fa a la demanda d’aigua calenta sanitària, es proposen dues opcions: instal·lar o no una acumulador d’ACS a cada edifici. La xarxa de distribució de calor es calcula d’acord amb la demanda energètica, igual que el dimensionat de la caldera. Tenint en compte el tipus de combustible i la demanda tèrmica, es proposa la instal·lació d’un volum d’inèrcia, suavitzant així els pics i valls de demanda i permetent treballar la caldera a un règim relativament constant. La solució proposada té una amortització de 4 anys, de manera que a partir d’aquest el VAN ja és positiu. Es recomana la implantació del sistema utilitzat, reduint la despesa anual en energia i les emissions de CO2.

ABSTRACTThe aquifer system of Doñana (SW Spain) represents the most important freshwater source in the Doñana Natural Area. Its spatiotemporal dynamics favours the hydrological connection between surface and subsurface ecosystems, and promotes matter fluxes among the different terrestrial and aquatic systems present here. This aquifer has been intensively studied from a hydrogeological point of view but little is known from an ecological perspective. In order to understand the ecological roles played by microbial communities in this system, we conducted a long‐term seasonal study of bacterial abundance, cell biomass, bacterial biomass and functional activities over a 2‐year period. Bacterial abundance ranged between 2.11 ± 1.79 × 105 and 8.58 ± 6.99 × 107 bacteria mL−1 groundwater, average cell biomass was estimated to be 77.01 ± 31.56 fgC and bacterial biomass varied between 8.99 ± 4.10 × 10−2 and 5.65 ± 0.70 µgC mL−1. Iron‐related bacteria showed the highest activities among the functional groups studied. Moreover, among the variables that usually control spatial distributions of microbial communities in aquifer systems, depth did not have a relevant effect on this aquifer, at least in the range of depths studied, but grain size, probably due to its direct effects on hydrogeological parameters, such as permeability or porosity, appeared to exert moderate control, principally in terms of bacterial abundance. Finally, significant seasonal differences in the means of these microbiological variables were also observed; temperature seems to be the main factor controlling the temporal distribution of microbial communities in this aquifer system.

Efforts are needed in order to increase confidence for carbon accounts in the land use sector, especially in tropical forest ecosystems that often need to turn to default values given the lack of precise and reliable site specific data to quantify their carbon sequestration and storage capacity. The aim of this study was then to estimate biomass and carbon accumulation in young secondary forests, from 4 and up to 20 years of age, as well as its distribution among the different pools (tree including roots, herbaceous understory, dead wood, litter and soil), in humid tropical forests of Costa Rica. Carbon fraction for the different pools and tree components (stem, branches, leaves and roots) was estimated and varies between 37.3% (±3.3) and 50.3% (±2.9). Average carbon content in the soil was 4.1% (±2.1). Average forest plant biomass was 82.2 (±47.9) Mg ha−1 and the mean annual increment for carbon in the biomass was 4.2 Mg ha−1 yr−1. Approximately 65.2% of total biomass was found in the aboveground tree components, while 14.2% was found in structural roots and the rest in the herbaceous vegetation and necromass. Carbon in the soil increased by 1.1 Mg ha−1 yr−1. Total stored carbon in the forest was 180.4 Mg ha−1 at the age of 20 years. In these forests, most of the carbon (51&-83%) was stored in the soil. Models selected to estimate biomass and carbon in trees as predicted by basal area had R2 adjustments above 95%. Results from this study were then compared with those obtained for a variety of secondary and primary forests in different Latin-American tropical ecosystems and in tree plantations in the same study area. Universidad Nacional de Costa Rica Ministerio de Ciencia y Tecnología, Costa Rica

Continuous phosphorus discharges in bodies of water, generated by human activities, such as agriculture, domestic effluences or wastewater from industrial processes, produce contaminated water and eutrophication. For this reason, efficient and low-cost systems that can remove phosphorus from contaminated water are necessary. In addition, it is important to generate renewable energy such as the energy produced in biomass power plants, taking advantage of the available biomass waste in each place. When producing this renewable energy, the resulting ash is a residue that can be used for phosphorus removal by adsorption processes. Moreover, according to the concept of the circular economy, the ash waste generated in this bio energy process should be reduced as much as possible. One of the advantages of this research being that surplus phosphorus-laden ash can be reused as fertilizer in agricultural fields. Considering this, the efficiency of reed ash (RA) (Phragmites australis) has been analysed in batch experiments, as well as the effect of several parameters on the removal of phosphate, such as contact time, phosphate-ash ratio, ash dose and temperature. Significant results obtained show that RA can be used to improve water quality.