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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276311
Dataset

DESERT LIZARD DIVERSITY WORLDWIDE: EFFECTS OF ENVIRONMENT, TIME, AND EVOLUTIONARY RATE

  • Tejero-Cicuéndez, Héctor
This dataset is embargoed and will be released when the associated article is published., [Aim] Biodiversity is not uniformly distributed across the Earth's surface, even among physiographically comparable biomes in different biogeographic regions. For lizards, the world's large desert regions are characterized by extreme heterogeneity in species richness, spanning some of the most species-rich (arid Australia) and species-poor (central Asia) biomes overall. Regional differences in species diversity may arise as a consequence of the interplay of several factors (e.g., evolutionary time, diversification rate, environment), but their relative importance for biogeographic patterns remains poorly known. Here we use distributional and phylogenetic data to assess the evolutionary and ecological drivers of large-scale variation in desert lizard diversity., [Location] Deserts worldwide., [Major taxa studied] Lizards (non-snake squamates)., [Methods] We specifically test whether diversity patterns are best explained by differences in the ages of arid-adapted lineages (evolutionary time hypothesis), by regional variation in speciation rate, by geographic area of the arid systems, and by spatial variation related to the environment (climate, topography, and productivity)., [Results] We found no effect of recent speciation rate and geographic area on differences in desert lizard diversity. We demonstrate that the extreme species richness of the Australian deserts cannot be explained by greater evolutionary time, because species began accumulating more recently there than in more species-poor arid regions. We found limited support for relationships between regional lizard richness and environmental variables, but these effects were inconsistent across deserts, showing a differential role of the environment in shaping the lizard diversity in different arid regions., [Main conclusions] Our results provide evidence against several classic hypotheses for interregional variation in species richness, but also highlight the complexity of processes underlying vertebrate community richness in the world's great arid systems., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/276311
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276311
HANDLE: http://hdl.handle.net/10261/276311
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276311
PMID: http://hdl.handle.net/10261/276311
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276311
Ver en: http://hdl.handle.net/10261/276311
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276311

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276331
Dataset

DATASET FOR: INTERACTIVE EFFECTS OF TREE SPECIES COMPOSITION AND WATER AVAILABILITY ON GROWTH AND DIRECT AND INDIRECT DEFENCES IN QUERCUS ILEX

  • Galmán, Andrea
  • Vázquez-González, Carla
  • Röder, Gregory
  • Castagneyrol, Bastien
[Methods] - Experimental design: This study was conducted in the ORPHEE experimental trial established in 2008 in South-West France (44°440 N, 00°460 W). The experimental design consisted of eight blocks and 32 plots within each block. Each plot represented a tree species composition treatment, corresponding to 31 possible combinations of one to five tree species (Betula pendula, Quercus robur, Q. pyrenaica, Q. ilex, and Pinus pinaster) and an additional plot replicate of the five species mixture. Each plot contained 10 rows of 10 trees planted 2 m apart (100 trees on 400 m²). Tree species mixtures were established according to a substitutive design, keeping tree density of tree neighbours equal across plots. Within plots, individual trees from different species were planted in a regular alternate pattern, such that a tree from a given species had at least one neighbour from each of the other species within a 2-m radius. From 2015 four out of the eight experimental blocks were allocated to an irrigation treatment consisting of sprinkling the equivalent of 3 mm precipitation from a 2 m height pole in the centre of each irrigated plot. Blocks were irrigated on a daily basis, at night, from May to October. The four remaining blocks were kept as controls. This datasets collects data for Q. ilex. In particular, we focused on Quercus ilex as target species and selected six blocks (three irrigated and three control) and four plots (tree species composition treatments) in each block corresponding to the monoculture of Q. ilex and its combinations with B. pendula and P. pinaster (Q. ilex + B. pendula, Q. ilex + P. pinaster and Q. ilex + B. pendula + P. pinaster). Therefore, a total of 24 experimental plots (4 tree species composition treatments × 2 irrigation treatments × 3 blocks) were included in the study. - Sampling and measurements: At the end of the growing season (September 2019), we haphazardly selected four Q. ilex trees in each of the 24 plots (N = 96 trees). Trees in the plot margins were not selected to avoid border effects. First, we estimated total height and basal diameter (± 30 cm aboveground) in all experimental trees with a tape-measure and a digital caliper respectively. After tree growth measurements, we collected VOCs for each tree. Briefly, we bagged one branch of each tree with a 1L nalophan bag and we trapped the compounds on a charcoal filter by pulling air through the filter using an air-sampling pump for 2 h at a rate of 250 ml min-1. Importantly, we sampled air VOCs in empty bags (one bag placed in the middle of each plot within each block) as controls, in order to identify compounds that may contaminate the blend of VOCs taken from the focal trees (e.g., VOCs emitted by neighbour species). After collecting the VOCs, we stored the filters at -80ºC until chemical analyses. Right after VOCs collection, we haphazardly collected 20 fully expanded and developed leaves throughout the tree’s canopy. Importantly, because Q. Ilex is an evergreen species, sampled leaves may have consisted of one to three cohorts of leaves (i.e. produced between 2017 and 2019; up to two-years old). For each leaf, we visually estimated the percentage of leaf area removed by insect herbivores (mostly leaf chewers) using the following scale: 0 = no damage; 1 = 1–5% damaged; 2 = 6–10% damaged; 3 = 11–25% damaged; 4 = 26–50% damaged; 5 = 51–75% damaged; 6 = >75% damaged (“leaf herbivory” hereafter). We averaged class values across all leaves to obtain a mean value per tree for statistical analyses. We selected a subset of 4-5 leaves with little or no evidence of herbivory for further chemical analyses of phenolic compounds. Leaves were oven-dried for 48 h at 40ºC. - Chemical analyses: Quantification of volatile organic compounds (VOCs). To analyse VOCs, we performed gas chromatography and mass spectrometry analyses. To extract the compounds from the charcoal traps, we first added 5 μl of naphthalene (20 ng ml−1) as an internal standard to the traps (Pellissier et al., 2016), and then eluted their contents with 400 μl of dichloromethane. We then injected 2 μl of the extract for each sample into a gas chromatograph (GC) coupled with a mass selective detector (MSD) fitted with a 30 m × 0.25 mm × 0.25 mm film thickness HP-5MS fused silica column. We operated the GC in splitless mode with helium as the carrier gas (constant flow rate 0.9 ml min−1). The GC oven temperature program was: 1 min hold at 40°C, and then 10°C min−1 ramp to 240°C. We identified individual volatile compounds (i.e., terpenes) using Kovats retention index from published work, the NIST Standard Reference Database 1A v17, and by comparison with commercial standards when available. Volatile emissions are reported as nanograms naphthalene equivalents. For subsequent analyses, we selected VOCs identified as either monoterpenes or sesquiterpenes. We quantified individual monoterpenes and sesquiterpenes relative to the internal standard and used for statistical analyses those exhibiting a relative abundance higher than 1%. Importantly, for those compounds present in both the samples and the corresponding control, we only consider those which intensity in the sample was at least double than in the control. Finally, we quantified the total concentration of VOCs as the sum of concentrations of all individual compounds. Quantification of phenolic compounds. We extracted phenolic compounds from 20 mg of dry leaf tissue with 1 ml of 70% methanol in an ultrasonic bath for 15 min, followed by centrifugation (Moreira et al., 2020) and transferred the extracts to chromatographic vials. To analyse the phenolic compounds, we performed chromatographic analyses using ultra-high performance liquid chromatography equipped with a Nexera SIL-30AC injector and one SPD-M20A UV/VIS photodiode array detector. The compound separation was carried out on a Kinetex 2.6 μm C18 82–102 Å, LC Column 100 × 4.6 mm, protected with a C18 guard cartridge. The flow rate was 0.4 ml min−1 and the oven temperature was set at 25°C. The mobile phase consisted of two solvents: water–formic acid (0.05%) (A) and acetonitrile–formic acid (0.05%) (B), starting with 5% B and using a gradient to obtain 30% B at 4 min, 60% B at 10 min, 80% B at 13 min and 100% B at 15 min. The injection volume was 15 μl. For phenolic compound identification, we used an ultra-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry. We identified four groups of phenolic compounds: flavonoids, ellagitannins and gallic acid derivates (‘hydrolysable tannins’ hereafter), proanthocyanidins (‘condensed tannins’ hereafter) and hydroxycinnamic acid precursors to lignins (‘lignins’ hereafter). We quantified flavonoids as rutin equivalents, condensed tannins as catechin equivalents, hydrolysable tannins as gallic acid equivalents, and lignins as ferulic acid equivalents . The quantification of these was conducted by external calibration using the corresponding calibration curve at 0.25, 0.5, 1, 2 and 5 μg ml−1 for each of the four standards used (rutin, catechin, gallic acid and ferulic acid). We expressed phenolic compound concentrations in mg g−1 tissue on a dry weight basis., Plant diversity has often been reported to decrease insect herbivory in plants. Of the numerous mechanisms that have been proposed to explain this phenomenon, how plant diversity influences plant defences via effects on growth has received little attention. In addition, plant diversity effects may be contingent on abiotic conditions (e.g., resource and water availability). Here, we used a long-term experiment to explore the interactive effects of tree species composition and water availability on growth, direct (i.e. phenolics) and indirect (i.e. Volatile Organic Compounds – VOCs) defences and leaf herbivory in Quercus ilex. We quantified herbivory by chewing insects, phenolic compounds and VOCs in Q. ilex trees growing in stands differing in tree species composition (Q. ilex, Q. ilex + Betula Pendula, Q. ilex + Pinus pinaster and Q. ilex + B. pendula + P. pinaster) and water availability (irrigated vs control). Both direct and indirect defences were affected by tree species composition, but such changes were not mediated by changes in tree stem diameter. Q. ilex trees growing in stands with P. pinaster had the lowest concentration of both direct and indirect defences. Importantly, the effects of tree species composition on VOCs were exacerbated on irrigated blocks. Despite variation in defences, tree species composition did not affect herbivory in Q. ilex. Accordingly, we did not find any association between defences and insect herbivory. Our results suggest that changes in the micro-environment rather than growth-defence associations may mediate tree diversity effects on defences. In addition, reduced defensive investment in more diverse stands could negatively impact tree resistance masking the beneficial effects of species diversity at reducing insect herbivory., Consejo Superior de Investigaciones Científicas, Award: I-LINK12212018-2019., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/276331
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276331
HANDLE: http://hdl.handle.net/10261/276331
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276331
PMID: http://hdl.handle.net/10261/276331
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276331
Ver en: http://hdl.handle.net/10261/276331
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276331

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276339
Dataset

MORE SOIL ORGANIC CARBON IS SEQUESTERED THROUGH THE MYCELIUM-PATHWAY THAN THROUGH THE ROOT-PATHWAY UNDER NITROGEN ENRICHMENT IN AN ALPINE FOREST

  • Zhu, Xiaomin
  • Zhang, Ziliang
  • Wang, Qitong
  • Peñuelas, Josep
  • Sardans, Jordi
  • Li, Na
  • Liu, Qing
  • Yin, Huajun
  • Liu, Zhanfeng
  • Lambers, Hans
These data were generated to investigate how N addition affect SOC accural and chemical composition through the root-pathway and mycelium-pathway in an alpine coniferous forest. Samples of plant and soil were collected from each treatment plots (non-N addition and N-addition) in 2019 and 2020. Therefore, each parameter has 6 replicates (n = 3 replicates for each treatment * 2 sampling date =6),except for the plant-derived C in different soil size fractions (only measured the samples collected in 2019)., [Methods] Isolation of roots and mycelia using ingrowth cores: To isolate roots and mycelia, we adopted an ingrowth-core technique modified from Zhang et al. (2018) and Keller et al. (2021). Ingrowth cores (6 cm inner diameter and 15 cm depth) were wrapped with a mesh with different pore sizes: mesh size of 2000 µm allowed the ingrowth of fine roots and mycelia (both roots and mycelia accessible); 48-µm mesh permitted the growth of mycelia but not of fine roots (only mycelia accessible), and 1-µm mesh excluded the growth of both roots and mycelia (only the soil) (Fig. 2). The C source in the 2-mm mesh cores was mainly derived from roots, mycelia and litter leachates, that of the 48-µm mesh cores was derived from mycelia and litter leachates, while the 1-µm mesh cores received C only from litter leachates. The soil was collected from the mineral layer (0-15cm) at each plot. After removing the visible roots, the soil from the same plot was homogenized and sieved through a 5-mm mesh. The sieved soil was filled into ingrowth cores corresponding to the soil bulk density at 0-15 cm depth (0.796 g cm-3, approximately 337 g per core). Six sets of ingrowth cores with different mesh-size (1-µm, 48-µm and 2000-μm) were installed in each treatment plot. In total, 108 ingrowth cores (2 N levels * 3 replicates * 6 sets * 3 mesh-sizes) were installed in this coniferous forest. Ingrowth cores were randomly placed in the topmost mineral horizon (0-15cm depth) in each plot in July 2017. The bottom of the ingrowth cores was covered with the corresponding size of the mesh to prevent inputs of roots and mycelia, respectively, and the top was covered by multiple layers of the corresponding size of the mesh to block the entry of coniferous litter but to allow gas and water exchange. When the cores were retrieved, we did not detect any external litter in the cores. To block the influx of new C derived from the saprophytic mycelia outside the cores, we spread a 2 mm-thick layer of silica sand around the cores. Silica sand as a growth substrate effectively reduces the disturbance of saprophytic hyphae (Hagenbo et al., 2017). Ingrowth cores were harvested in August 2019 and August 2020, respectively. Two sets of ingrowth cores were collected in each plot at each sampling date. Cores were transported to the laboratory within the icebox. After the removal of roots, soils inside the cores were sieved through a 2-mm mesh and divided into two subsamples: one subsample stored in -4 °C was used for the analyses of enzyme activities and microbial community composition; the second subsample was air-dried to perform soil aggregate fractionation, SOC determination, and soil biomarkers analysis. Root and mycelium biomass: Roots inside the 2000-µm mesh cores were manually picked out, washed thoroughly, oven-dried at 60°C for 48 hours and then weighed to determine the total root biomass. The ectomycorrhizal mycelium biomass was estimated using mesh bags (2 cm inner diameter, 15 cm depth; mesh size: 48 µm) filled with different particle sizes of HCl-washed silica sand (60 g, 0.36-2 mm) (Wallander et al., 2001). The mesh bags were randomly buried into the 0-15 cm soil depth in each plot in July 2017, and recovered at the same time as the ingrowth cores. The concentration of ergosterols was measured to characterize the biomass of ectomycorrhizal mycelia in the mesh bags (see details in the Supplementary Methods) (Parrent & Vilgalys, 2007). Soil aggregate fractionation and SOC concentration: To understand the physico-chemical protection of SOC in the RP and MP under N addition, soils were physically fractionated into three size fractions to examine the allocation of C and biomarkers among macroaggregates (Macro: 250~2000 µm), microaggregates (Micro: 53~250 µm) and slit-clay (< 53 µm) by using the wet-sieving technique (Six et al., 1998). The proportions of SOC and the concentrations of biomarkers in the three fractions were measured to characterize the role of physical protection by aggregates. The SOC and total N (TN) concentrations in bulk soil and size fractions were analyzed using an elemental analyzer (Vario MACRO, Elementar Analysensysteme GmbH, Hanau, Germany). To assess the protection of SOC by minerals, two forms of Fe and Al oxides, oxalate-extractable Fe/Al oxides (Feo + Alo) and dithionite-extractable Fe/Al (Fed + Ald) were measured by using the extraction method proposed by Gentsch et al (2018). The Fed + Ald indicates the amount of pedogenic Fe and Al within oxides, silicates and organic complexes, whereas Feo + Alo represents poorly crystalline oxyhydroxides (Gentsch et al., 2018). The concentrations of Fe and Al oxides in extracts were determined by inductively coupled plasma-optical emission spectrometry (ICP-OES, Optima 8300, Perkin Elmer, USA). SOC chemical composition: A range of major biomarkers, which are widely accepted to trace plant-derived and microbial-derived C, respectively, were selected to reveal the changes of the chemical composition of SOC in two pathways under N addition (Barré et al., 2018; Liang et al., 2019). Air-dried soil (1 g) was sequentially extracted (solvent extraction, base hydrolysis, and CuO oxidation) to isolate solvent-extractable free lipids (long-chain fatty acids), cutin- and suberin-derived compounds and lignin-derived phenols (vanillyls, syringyls and cinnamyls), respectively, according to standard protocols (Otto & Simpson, 2007; Tamura & Tharayil, 2014). Since the direct contribution of microbial living biomass to soil amino sugars is negligible, amino sugars are good indicators of microbial necromass (Liang et al., 2017, Joergensen, 2018). Four types of amino sugars, including glucosamine, galactosamine, manosamine, and muramic acid, were tested in this study. By assessing them in soils, we can investigate microbial necromass dynamics at the community-level (i.e., fungi and bacteria) and evaluate the contributions of necromass to SOC storage under different environmental conditions (Joergensen, 2018; Liang et al., 2019). The detailed chemical extractions and analyses of plant and microbial biomarkers are provided in Supplementary Methods. Microbial community composition: Soil microbial community composition was characterized using the phospholipid fatty acids (PLFAs) methods (see details in Supplementary Methods) (Bossio & Scow, 1998). The identification of the extracted fatty acid was based on a MIDI peak identification system (Microbial ID Inc., Newark, DE, USA). The PLFAs i15:0, α15:0, i16:0, i17:0, α17:0 were used to indicate the relative biomass of Gram-positive (G+) bacteria. The PLFAs 16:1ω9c, 16:1ω7c, 18:1ω7c, cy17:0, cy19:0 were used to indicate the relative biomass of Gram-negative (G-) bacteria. The PLFA 18:2ω6c was used as an indicator of saprotrophic fungal biomass. The PLFAs 10Me16:0, 10Me17:0 and 10Me18:0 were used to indicate actinomycete (AC) biomass. Microbial community composition was assessed by the ratio of saprotrophic fungal biomass to bacterial biomass (F/B ratio). Extracellular enzyme activity: The activities of three extracellular enzymes involved in the decomposition of lignin and fungal residues were measured as described by Saiya-Cork et al. (2002) (see details in Supplementary Methods). The β-N-acetyl-glucosaminidase(NAG)participates in chitin and peptidoglycan degradation, hydrolyzing chitobiose to glucosamine (Sinsabaugh et al., 2009). NAG activity was measured fluorometrically using 4-methylumbelliferyl N-acetyl-β-D-glucosaminide as the substrate. Phenol oxidases (POX) and peroxidases (PER) play an important role in degrading polyphenols, and their activities were measured colorimetrically using L-dihydroxyphenylalanine (DOPA) as the substrate. Data calculation and statistical analysis: To isolate the effects of root and mycelium on the SOC dynamics and associated microbial characteristics (i.e., SOC, biomarkers concentrations, fungal and bacterial biomass, and enzymes activities), net changes of the observations mediated by the root-pathway and mycelium-pathway were quantified by the difference of corresponding variables between the 2-mm mesh cores and 48-µm mesh cores, or between the 48-µm cores and 1-µm mesh cores, respectively (Fig. 2). The recent concept proposed by Zhu et al (2020) highlighted the contribution of microbial necromass to the SOC pool (i.e., MCP efficacy). Based on this concept, the changes of MCP efficacy (i.e., the contribution of increased microbial residual C to the increased SOC) under N addition were calculated as follow: Changes of MCP efficacy (% SOC) under N addition = , where MRCN, SOCN, MRCCK, and SOCCK represent the concentration of microbial residual C and SOC in the N-addition plots and the non-N addition plots, respectively. Additionally, the contribution of increased plant-derived C to the increased SOC induced by N addition was calculated using Eq. 1 but replacing microbial residual C with plant-derived C., Plant roots and associated mycorrhizae exert a large influence on soil carbon (C) cycling. Yet, little was known whether and how roots and ectomycorrhizal extraradical mycelia differentially contribute to soil organic C (SOC) accumulation in alpine forests under increasing nitrogen (N) deposition. Using ingrowth cores, the relative contributions of the root-pathway (RP) (i.e., roots and rhizosphere processes) and mycelium-pathway (MP) (i.e., extraradical mycelia and hyphosphere processes) to SOC accumulation were distinguished and quantified in an ectomycorrhizal-dominated forest receiving chronic N addition (25 kg N ha-1 yr-1). Under the non-N addition, the RP facilitated SOC accumulation, while the MP reduced SOC accumulation. Nitrogen addition enhanced the positive effect of RP on SOC accumulation from +18.02 mg C g-1 to +20.55 mg C g-1 but counteracted the negative effect of MP on SOC accumulation from -5.62 mg C g-1 to -0.57 mg C g-1, as compared to the non-N addition. Compared to the non-N addition, the N-induced SOC accumulation was 1.62~2.21 mg C g-1 and 3.23~4.74 mg C g-1, in the RP and the MP, respectively. The greater contribution of MP to SOC accumulation was mainly attributed to the higher microbial C pump (MCP) efficacy (the proportion of increased microbial residual C to the increased SOC under N addition) in the MP (72.5%) relative to the RP (57%). The higher MCP efficacy in the MP was mainly associated with the higher fungal metabolic activity (i.e., the greater fungal biomass and N-acetyl glucosidase activity) and greater binding efficiency of fungal residual C to mineral surfaces than those of RP. Collectively, our findings highlight the indispensable role of mycelia and hyphosphere processes in the formation and accumulation of stable SOC in the context of increasing N deposition., National Natural Science Foundation of China, Award: 32171757. The Chinese Academy of Sciences (CAS) Interdisciplinary Innovation Team, Award: xbzg-zysys-202112. The Second Tibetan Plateau Scientific Expedition and Research, Award: 2019QZKK0301. European Research Council Synergy project, Award: SyG-2013-610028 IMBALANCE-P. The Spanish Government, grant, Award: PID2019-110521GB-I00. National Natural Science Foundation of China, Award: 31901131. National Natural Science Foundation of China, Award: 42177289. The Spanish Government, grant, Award: PID2020-115770RB-I00., Peer reviewed

DOI: http://hdl.handle.net/10261/276339
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276339
HANDLE: http://hdl.handle.net/10261/276339
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276339
PMID: http://hdl.handle.net/10261/276339
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276339
Ver en: http://hdl.handle.net/10261/276339
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276339

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276369
Dataset

DATA FROM: PYROGEOGRAPHY ACROSS THE WESTERN PALEARCTIC: A DIVERSITY OF FIRE REGIMES

  • Pausas, J. G.
[Methods] We first defined eight large ecoregions based on their environment and vegetation: Mediterranean, Arid, Atlantic, Mountains, Boreal, Steppes, Continental, and Tundra. These ecoregions were defined by aggregating 81 WWF ecoregions with the help of the bioregions (https://www.oneearth.org/bioregions-2020/). We provide the shape files with these ecoregions. Then we intersected each ecoregion with individual-fire data obtained from remote sensing hotspots to estimate fire regime parameters for each environment. Specifically, we computed the following fire statistics for each ecoregion and year (2001-2019): area burnt; mean fire size; fire intensity; fire season; fire patchiness (CV of the fire intensity in each fire); fire recurrence and pyrodiversity. This data was estimated based on individual-fire data provided in GlobFire (Artés et al. 2019) except fire intensity that was estimated using MODIS hotspots (Collection 6 Active Fire Products from Terra and Aqua satellites, dataset MCD14ML; downloaded from the University of Maryland, USA; period 2001-2021). Fire recurrence for each ecoregion was estimated as the number of times each patch was burnt. The pyrodiversity of each ecoregion (i.e., fire-caused landscape heterogeneity) was estimated as the Shannon diversity of fire patches, that is, considering the relative abundance (sizes) of fire-produced patches in each ecoregion. The data provided is the average by ecoregion and year, except for patchiness we provide the area of each patch in each ecoregion, and the number of times the patch burned. More details are provided in the original article. [Usage Notes] The ecoregion map is in "shape" format and can be opened with most GIS softwares (e.g., QGIS). The data is provided as comma-delimited files (csv; ASCII) and can be opened with most softwares for numerical analysis (e.g. in R using the function read.csv) or with a spreadsheet (e.g., LibreOffice Spreadsheet)., We characterised fire regimes and estimated fire regime parameters (area burnt, size, intensity, season, patchiness, pyrodiversity) at broad spatial scales using remotely sensed individual-fire data. Specifically, we focused on the western part of the Palearctic realm, i.e., Europe, North Africa, and the Near East. We first divided the study area into eight large ecoregions based on their environment and vegetation (ecoregions): Mediterranean, Arid, Atlantic, Mountains, Boreal, Steppes, Continental, and Tundra. Then we intersected each ecoregion with individual-fire data obtained from remote sensing hotspots to estimate fire regime parameters for each environment. This allowed us to compute annual area burnt, fire size, fire intensity, fire season, fire patchiness, fire recurrence, and pyrodiversity for each ecoregion. We then related those fire parameters with the ecoregions’ climate and analysed the temporal trends in fire size. The results suggest that fire regime parameters vary across different environments (ecoregions). The Mediterranean had the largest, most intense, and most recurrent fires, but the Steppes had the largest burnt area. Arid ecosystems had the most extended fire season, Tundra had the patchiest fires, and Boreal forests had the earliest fires of the year. The spatial variability in fire regimes was largely explained by the variability of climate and vegetation, with a tendency for greater fire activity in the warmer ecoregions. There was also a temporal tendency for fires to become larger during the last two decades, especially in Arid and Continental environments. In conclusion, fire regime characteristics of each ecoregion are unique, with a tendency for greater fire activity in warmer environments, and for increasingly large fires in recent decades., European Commission, Award: GA 101003890 (fireUrisk)., Peer reviewed

DOI: http://hdl.handle.net/10261/276369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276369
HANDLE: http://hdl.handle.net/10261/276369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276369
PMID: http://hdl.handle.net/10261/276369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276369
Ver en: http://hdl.handle.net/10261/276369
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276369

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276375
Dataset

DATA FROM: PYROGEOGRAPHY ACROSS THE WESTERN PALEARCTIC: A DIVERSITY OF FIRE REGIMES

  • Pausas, J. G.
The ecoregion map is in "shape" format and can be opened with most GIS softwares (e.g., QGIS). The data is provided as comma-delimited files (csv; ASCII) and can be opened with most softwares for numerical analysis (e.g. in R using the function read.csv) or with a spreadsheet (e.g., LibreOffice Spreadsheet)., We characterised fire regimes and estimated fire regime parameters (area burnt, size, intensity, season, patchiness, pyrodiversity) at broad spatial scales using remotely sensed individual-fire data. Specifically, we focused on the western part of the Palearctic realm, i.e., Europe, North Africa, and the Near East. We first divided the study area into eight large ecoregions based on their environment and vegetation (ecoregions): Mediterranean, Arid, Atlantic, Mountains, Boreal, Steppes, Continental, and Tundra. Then we intersected each ecoregion with individual-fire data obtained from remote sensing hotspots to estimate fire regime parameters for each environment. This allowed us to compute annual area burnt, fire size, fire intensity, fire season, fire patchiness, fire recurrence, and pyrodiversity for each ecoregion. We then related those fire parameters with the ecoregions' climate and analysed the temporal trends in fire size. The results suggest that fire regime parameters vary across different environments (ecoregions). The Mediterranean had the largest, most intense, and most recurrent fires, but the Steppes had the largest burnt area. Arid ecosystems had the most extended fire season, Tundra had the patchiest fires, and Boreal forests had the earliest fires of the year. The spatial variability in fire regimes was largely explained by the variability of climate and vegetation, with a tendency for greater fire activity in the warmer ecoregions. There was also a temporal tendency for fires to become larger during the last two decades, especially in Arid and Continental environments. In conclusion, fire regime characteristics of each ecoregion are unique, with a tendency for greater fire activity in warmer environments, and for increasingly large fires in recent decades., Funding provided by: European Commission, Award Number: GA 101003890 (fireUrisk)., Peer reviewed

DOI: http://hdl.handle.net/10261/276375
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276375
HANDLE: http://hdl.handle.net/10261/276375
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276375
PMID: http://hdl.handle.net/10261/276375
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276375
Ver en: http://hdl.handle.net/10261/276375
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276375

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276381
Dataset

DATA ON: WINTER WARMING OFFSET ONE HALF OF THE SPRING WARMING EFFECTS ON LEAF UNFOLDING

  • Wang, Huanjiong
  • Dai, Junhu
  • Peñuelas, Josep
  • Ge, Quansheng
  • Fu, Yongshuo H.
  • Wu, Chaoyang
[Methods See the Materials and methods section in the original paper., [Usage Notes] Microsoft Excel are required to open the data files., This dataset is the data used to create figures in paper of Global change biology entitled "Data on Winter warming offset one half of the spring warming effects on leaf unfolding", we constructed a phenological model based on the linear or exponential function between the chilling accumulation (CA) and forcing requirements (FR) of leaf-out. We further used the phenological model to quantify the relative contributions of chilling and forcing on past and future spring phenological change. The results showed that the delaying effect of decreased chilling on the leaf-out date was prevalent in natural conditions, as more than 99% of time series exhibited a negative relationship between CA and FR. The reduction in chilling linked to winter warming from 1951-2014 could offset about one half of the spring phenological advance caused by the increase in forcing. In future warming scenarios, if the same model is used and a linear, stable correlation between CA and FR is assumed, declining chilling will continuously offset the advance of leaf-out to a similar degree. Our study stresses the importance of assessing the antagonistic effects of winter and spring warming on leaf-out phenology., National Key R&D Program of China, Award: 2018YFA0606102. National Natural Science Foundation of China, Award: 41871032. Youth Innovation Promotion Association, CAS, Award: 2018070. National Natural Science Foundation of China, Award: 42125101., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/276381
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276381
HANDLE: http://hdl.handle.net/10261/276381
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276381
PMID: http://hdl.handle.net/10261/276381
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276381
Ver en: http://hdl.handle.net/10261/276381
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276381

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276396
Dataset

EMERGING STABILITY OF FOREST PRODUCTIVITY BY MIXING TWO SPECIES BUFFERS TEMPERATURE DESTABILIZING EFFECT

  • del Río, Miren
  • Ruiz-Peinado, Ricardo
  • Holm, Stig Olof
  • Jansons, Aris
  • Nord‐Larsen, Thomas
  • Verheyen, Kris
  • Bravo-Oviedo, Andrés
  • Pretzsch, Hans
  • Jactel, H.
  • Coll, Lluis
  • Löf, Magnus
  • Aldea, Jorge
  • Ammer, Christian
  • Avdagić, Admir
  • Barbeito, Ignacio
  • Bielak, Kamil
  • Bravo, Felipe
  • Brazaitis, Gediminas
  • Cerný, Jakub
  • Collet, Catherine
  • Condés, Sonia
  • Drössler, Lars
  • Fabrika, Marek
  • Heym, Michael
  • Hylen, Gro
  • Kurylyak, Viktor
  • Lombardi, Fabio
  • Matović, Bratislav
  • Metslaid, Marek
  • Motta, Renzo
  • Nothdurft, Arne
  • den Ouden, Jan
  • Pach, Maciej
  • Pardos, Marta
  • Poeydebat, Charlotte
  • Ponette, Quentin
  • Pérot, Tomas
  • Reventlow, Ditlev Otto Juel
  • Sitko, Roman
  • Sramek, Vit
  • Steckel, Mathias
  • Svoboda, Miroslav
  • Vospernik, Sonja
  • Wolff, Barbara
  • Zlatanov, Tzvetan
[Methods] The research unit is the forest stand. We used data from a total of 261 forest stands belonging to three triplet-transects across Europe. Each triplet consists of a plot established in a two species mixed stands, and two plots on the respective monospecific stands; the three stands are located close to each other under similar environmental conditions. The species composition of the mixtures changes in the three triplet-transects. The first transect covers monospecific and mixed stands of Fagus sylvatica and Pinus sylvestris (32 sites, 96 stands), the second of Quercus petraea and Pinus sylvestris (35 sites, 105 stands), and the third of Picea abies and Pinus sylvestris (20 sites, 60 stands). Plot sizes varies from 0-02 to 0.15 ha depending on stand density a local site characteristics. In each plot the diameter of all trees was measured, and two increment cores per tree were taken at a 1.3 m stem height in a sample of approximately 20 trees per species and plot. Annual ring widths were measured and cross-dated using standardized dendrochronological techniques. The studied period was 2000-2013 for the beech-pine transect and 2004-2017 for the oak-pine and spruce-pine transects (except in five triplets where the period was 2000-2013), the last year corresponding to triplet establishment. Using data from cored trees, tree diameter increment-diameter models were fitted by year, species and plot to estimate diameter increments of noncored trees for the studied period. Dead trees during the last 14 years were estimated using stumps, standing and lying dead trees, and their decomposition status. Based on measured tree diameters and annual diameter increments we estimated species and stand annual basal area (BA) and basal area growth (BAI), which conforms the dataset. Annual climate data were obtained from meteorological weather stations located in the proximity of each triplet (50 triplets). When local station data were not available, national digital climatic atlas data (24 triplets) or more general gridded data (13 triplets) were used (mostly CRU gridded database). For each triplet mean and standard deviation of annual precipitation (P) and mean annual temperature (T) for the studied period were calculated., [Usage Notes] The are presented in an excel-table which can be open freely in different ways (open office, google docs, etc.)., The increasing disturbances in monocultures around the world are testimony to their instability under global change. Many studies have claimed that temporal stability of productivity increase with species richness, although the ecological fundaments have mainly been investigated through diversity experiments. To adequately manage forest ecosystems, it is necessary to have a comprehensive understanding of the effect of mixing species on the temporal stability of productivity and the way in which this it is influenced by climate conditions across large geographical areas. Here, we used a unique dataset of 261 stands combining pure and two-species mixtures of four relevant tree species over a wide range of climate conditions in Europe to examine the effect of species mixing on the level and temporal stability of productivity. Structural equation modelling was employed to further explore the direct and indirect influence of climate, overyielding, species asynchrony and additive effect (i.e. temporal stability expected from the species growth in monospecific stands) on temporal stability in mixed forests. We showed that by adding only one tree species to monocultures, the level (overyielding: +6%) and stability (temporal stability: +12%) of stand growth increased significantly. We identified the key effect of temperature on destabilizing stand growth, which may be mitigated by mixing species. We further confirmed asynchrony as the main driver of temporal stability in mixed stands, through both the additive effect and species interactions, which modify between-species asynchrony in mixtures in comparison to monocultures. Synthesis and applications. This study highlights the emergent properties associated with mixing two-species, which result in resource efficient and temporally stable production systems. We reveal the negative impact of mean temperature on temporal stability of forest productivity and how the stabilizing effect of mixing two species can counterbalance this impact. The overyielding and temporal stability of growth addressed in this paper are essential for ecosystem services closely linked with the level and rhythm of forest growth. Our results underline that mixing two species can be a realistic and effective nature-based climate solution, which could contribute towards meeting EU climate target policies., Ministerio de Ciencia, Innovación y Universidades., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/276396
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276396
HANDLE: http://hdl.handle.net/10261/276396
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276396
PMID: http://hdl.handle.net/10261/276396
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276396
Ver en: http://hdl.handle.net/10261/276396
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276396

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276488
Dataset

EFFECT OF WATER AVAILABILITY ON VOLATILE-MEDIATED COMMUNICATION BETWEEN POTATO PLANTS IN RESPONSE TO INSECT HERBIVORY

  • Vázquez-González, Carla
  • Pombo-Salinas, Laura
  • Martín-Cacheda, Lucia
  • Rasmann, Sergio
  • Roeder, Gregory
  • Abdala-Roberts, Luis
  • Mooney, Kailen A.
  • Moreira Tomé, Xoaquín
[Methods] In April 2021, we sowed 168 tubers from three different Solanum tuberosum varieties (cv. Baraka, cv. Desiree, and cv. Monalisa) in 4-L pots containing potting soil and peat (Gramoflor GmbH & Co. KG Produktion, Vechta, Germany). We grew plants in a glasshouse under controlled light (minimum 10 h per day, Photosynthetically Active Radiation = 725 ± 19 μmol m-2 s-1) and temperature (10°C night, 25°C day), and watered them twice a week up to field capacity. Five weeks after germination, we assigned half of the plants to one of two water availability treatments: high (i.e., well-watered) vs. low (i.e., reduced watering) water availability (Fig. 1). We watered plants in the high water availability treatment every three days to replenish the 100% of their water demand, whereas for plants in the low water availability treatment watering was reduced to meet the 25% of the total water demand. We estimated water demand gravimetrically.To corroborate that plants in the low water availability treatment were under higher physiological stress in comparison to well-watered plants, two weeks after the start of the treatments (right before applying the herbivory treatment, see below) we used a subset of 24 plants (half high and half low water availability; four of each potato variety) to measure stomatal conductance and photosynthesis. We measured stomatal conductance and net photosynthetic rate on a leaflet of a young, fully-expanded leaf from 11:30 to 12:30 am at an irradiance of 1500 μmol m-2 s-1 and CO2 concentration of 400 μmol mol-1 with a portable photosynthesis system Li-6400XT (Li-Cor Inc., Lincoln, NE, USA). Plants in the low water availability treatment exhibited significantly lower stomatal conductance (F1,22 = 22.1, P < 0.001) and photosynthetic rates (F1,22 = 31.5. P < 0.001) compared to well-watered plants. Specifically, reduced watering resulted in a 90 % and an 80% decrease in stomatal conductance (high water availability: 0.073 ± 0.01 mol H2O m-2 s-1; low water availability: 0.008 ± 0.01 mol H2O m-2 s-1) and photosynthesis rates (high water availability: 9.31 ± 0.94 µmol CO2 m-2 s-1; low water availability: 1.88 ± 0.94 µmol CO2 m-2 s-1), respectively (Fig. S1a, b). Seven weeks after germination (two weeks after establishing the water availability treatments), we paired 144 potato plants in 37.5 × 37.5 × 96.5 cm plastic cages to prevent VOCs cross-contamination between replicates. One plant of each pair (i.e., replicate) acted as the emitter (average height ± SE = 51.17 ± 0.64 cm) and the other served as the receiver (48.52 ± 0.70 cm). Within each cage, emitter and receiver plants were placed 20 cm apart so that they did not touch each other. Plants in each water stress treatment were randomly selected as either receiver or emitter plants resulting in a factorial design consisting on four combinations of water availability treatment in the emitter (two levels; high vs. low) and water availability treatment in the receiver (two levels; high vs. low) (Fig. 1). In addition, we randomly assigned emitter plants within each cage to one of the following herbivory treatments: (1) subjected to S. exigua feeding (“herbivore-induced plants” hereafter) or (2) control (intact; no herbivory) plants (Fig. 1). Overall, the experiment consisted in 72 replicate cages, namely 36 for the herbivore-induced treatment (nine per emitter vs. receiver water availability combination) vs. 36 for the control (nine per emitter vs. receiver water availability combination). Emitter and receiver plants were always of the same variety and varieties were similarly distributed across treatment combinations. For herbivore-induced emitters, we placed two third-instar larvae of S. exigua on each of three fully expanded leaves per plant using a fine paintbrush and covered these leaves with a nylon bag to prevent herbivore dispersal. For control plants, we covered three fully expanded leaves with a nylon bag but without adding the larvae to control for a possible bagging effect. After four days of herbivore feeding, we removed all emitter plants from cages and collected VOCs from each emitter (see below). After VOCs sampling, we collected leaves subjected to larvae feeding and photographed them with a Samsung Galaxy A30s (25 effective megapixels, 4× digital zoom). We estimated the percentage of leaf area consumed using the mobile application BioLeaf - Foliar Analysis™ (Brandoli Machado et al., 2016). Average percentage leaf area consumed by S. exigua for herbivore-induced emitters was 77.58% (± 3.72) and was homogeneously distributed among plants in the high (80.46% ± 3.50) vs. low (73.63% ± 4.25) water availability treatments (F1,33 = 0.7; P = 0.399). We collected aboveground VOCs produced by emitter plants following Rasmann et al. (2011). Briefly, we bagged plants with a 2-L Nalophan bag and trapped VOCs on a charcoal filter (SKC sorbent tube filled with anascorb CSC coconut-shell charcoal) for two hours at a rate of 0.25 L min-1. We eluted traps with 150 μL dichloromethane (CAS#75-09-2, Merck, Dietikon, Switzerland) to which we had previously added one internal standard (tetralin [CAS#119-64-2], 200 ng in 10 μL dichloromethane). We then injected 1.5 μL of the extract for each sample into an Agilent 7890B gas chromatograph (GC) coupled with a 5977B mass selective detector (MSD) fitted with a 30 m × 0.25 mm × 0.25 μm film thickness HP-5MS fused silica column (Agilent, Santa Clara, CA, USA). We operated the GC in pulsed splitless mode (250 ºC, injection pressure 15 psi) with helium as the carrier gas (constant flow rate 0.9 mL min-1). The GC oven temperature programme was: 3.5 min hold at 40ºC, 5ºC min-1 ramp to 230ºC, then a 3 min hold at 250ºC post run. Transfer line was set at 280 ºC. In the MS detector (EI mode), a 33-350 (m/z) mass scan range was used with MS source and quadrupole set at 230ºC and 150ºC, respectively. We identified volatile terpenes using the NIST MS Search Program v.2.3 and by comparison with the terpenes reference database developed at the University of Neuchâtel and based on pure standards. We quantified total emission of individual VOCs using normalized peak areas and expressed it as nanograms per hour (ng h-1). We obtained the normalized peak area of each individual compound by dividing their integrated peak area by the integrated peak area of the internal standard (Abdala-Roberts et al., 2022). The total emission of VOCs was then calculated as the sum of individual VOCs. The same day after collecting emitter VOCs, we set up an herbivore bioassay for receiver plants to test whether prior exposure to VOCs from herbivore-induced emitters increased herbivore resistance. For this, we placed one third-instar S. exigua larvae on each of two fully expanded leaves per plant following the same procedure described above for emitter induction. We kept larvae on receivers for three days and then estimated the percentage of leaf area consumed by S. exigua (‘leaf damage’ hereafter) using the same procedure described above for emitter plants., Airborne plant communication is a widespread phenomenon in which volatile organic compounds (VOCs) from damaged plants boost herbivore resistance in neighbouring, undamaged plants. Although this form of plant signalling has been reported in more than 30 plant species, there is still a considerable knowledge gap on how abiotic factors (e.g., water availability) alter its outcomes. We performed a greenhouse experiment to test for communication between potato plants (Solanum tuberosum) in response to herbivory by the generalist insect Spodoptera exigua and whether communication was affected by water availability. We paired emitter and receiver potato plants, with half of the emitters damaged by S. exigua larvae and half serving as undamaged controls. Both emitter and receiver plants were subjected to one of two water availability treatments: high (i.e., well-watered) vs. low (i.e., reduced watering) availability, thus effectively teasing apart water availability effects on the emission and reception components of signalling. After four days of herbivore feeding, we collected emitter VOCs and receivers were subjected to feeding by S. exigua to test for effects of signalling on induced resistance. Herbivory by S. exigua led to increased VOCs emissions as well as changes in VOCs composition in emitter plants. Furthermore, emitters subjected to low water availability exhibited a weaker induction of VOCs in response to herbivory relative to well-watered emitters. Results from the feeding bioassay indicated that receivers exposed to VOCs from herbivore-induced emitters showed lower S. exigua damage (i.e. higher induced resistance) compared to receivers exposed to undamaged emitters. However, we did not observe a significant effect of water availability in either emitters or receivers on plant communication. Overall, our study contributes to the understanding of how the abiotic context affects plant communication by providing evidence of water availability effects on the induction of VOCs that may act as airborne signals between plants. The observed changes in induced VOCs had no visible consequences for plant communication. These findings thus suggest that the induction of key compounds mediating communication was not compromised by our experimental conditions., Ministerio de Ciencia, Innovación y Universidades, Award: RTI2018-099322-B-I00. Consejo Superior de Investigaciones Científicas, Award: 2021AEP082. Xunta de Galicia, Award: IN607A 2021/03. Xunta de Galicia, Award: IN606B 2021/004., Peer reviewed

DOI: http://hdl.handle.net/10261/276488
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276488
HANDLE: http://hdl.handle.net/10261/276488
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276488
PMID: http://hdl.handle.net/10261/276488
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276488
Ver en: http://hdl.handle.net/10261/276488
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276488

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276627
Dataset

CHROMATOGRAPHIC DATA FOR THE DETERMINATION OF SULFONAMIDES IN WATERS ASSOCIATED TO FIG. 7 (IN CSV) OF THE PAPER &QUOT;PREPARATION AND FURTHER EVALUATION OF L-MENTHOL-BASED NATURAL DEEP EUTECTIC SOLVENTS AS SUPPORTED LIQUID MEMBRANE FOR THE HOLLOW FIBER LIQUID-PHASE MICROEXTRACTION OF SULFONAMIDES FROM ENVIRONMENTAL WATERS&QUOT; TO BE PUBLISHED IN ADVANCES IN SAMPLE PREPARATION

  • Díaz-Álvarez, Myriam
  • Martín-Esteban, Antonio
Data were automatically generated by the instrument., In this work, the use of a hydrophobic natural deep eutectic solvent (NADES) as supported liquid membrane (SLM) for hollow fiber liquid-phase microextraction (HF-LPME) of sulfonamides is proposed. The combination of formic acid:L-menthol (1:1) was selected as optimum. The optimized HF-LPME procedure was applied to the analysis of an artificial water containing humic acids, tap and river water samples by HPLC with UV detection at 268 nm. The chromatographic data associated to Fig.7 of paper published in Advances of Sample Preparation are provided as csv files as follows: Fig7Aa: Milli-Q water; Fig7Ab; artificial water; Fig7Ba: Tap water (a); Fig7Bb: Manzanares river; Fig7Bc: Jarama river. All the samples were spiked with selected sulfonamides at 10 µg/L concentration level., "Hacia un analisis medioambiental verde: nuevos disolventes, materiales y dispositivos (GREENNESS)" (Grant PID2021-122327OB-I00 funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”)., Fig7Aa_Díaz-Álvarez and Martín-Esteban_SAMPRE.csv, Fig7Ab_Díaz-Álvarez and Martín-Esteban_SAMPRE.csv, Fig7Ba_Díaz-Álvarez and Martín-Esteban_SAMPRE.csv, Fig7Bb_Díaz-Álvarez and Martín-Esteban_SAMPRE.csv, Fig7Bc_Díaz-Álvarez and Martín-Esteban_SAMPRE.csv, Peer reviewed

DOI: http://hdl.handle.net/10261/276627
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276627
HANDLE: http://hdl.handle.net/10261/276627
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276627
PMID: http://hdl.handle.net/10261/276627
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276627
Ver en: http://hdl.handle.net/10261/276627
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/276627

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/277378
Dataset

DATASET OF CANTABRIAN MOUNTAINS INSECTS, STUCK ON TOP OF A MOUNTAIN: CONSEQUENCES OF DISPERSAL LIMITATIONS FOR ALPINE DIVERSITY. DATASET

  • Laiolo, Paola
  • Illera, Juan Carlos
  • Obeso Suárez, José Ramón
Spanish Ministry of Science and Innovation (CGL2017-85191-P/AEI/FEDER.UE, PID2020-115259GB-I00 by MCIN/AEI/10.13039/501100011033) and Principado de Asturias (IDI/2021/000075), Peer reviewed

DOI: http://hdl.handle.net/10261/277378, https://doi.org/10.20350/digitalCSIC/14717
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/277378
HANDLE: http://hdl.handle.net/10261/277378, https://doi.org/10.20350/digitalCSIC/14717
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/277378
PMID: http://hdl.handle.net/10261/277378, https://doi.org/10.20350/digitalCSIC/14717
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/277378
Ver en: http://hdl.handle.net/10261/277378, https://doi.org/10.20350/digitalCSIC/14717
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/277378

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