BUSCADOR RECOLECTA

Supplementary material 1., Consejería de Sanidad, Junta de Castilla y León Agencia Estatal de Investigación Junta de Castilla y León Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

This dataset contains the raw ring-width and climate data (1952-2020), as well as the R code to run the model and the model output used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation"., beech_rawtrw.txt. This dataset contains the raw ring-width and climate data (1952-2020) used in the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation"., final_cwb_model.R. R code to run the model behind the results of the research article "No future growth enhancement expected at the northern edge for European beech due to continued water limitation". Requires beech_rawtrw.txt., SwissForestLab, Grant/Award: SFL20 P5. Swiss National Science Foundation, Grant/Award: 183571., Peer reviewed

Dataset for published paper "Optimistic growth of marginal region plantations under climate warming: assessing divergent drought resilience", including the original tree-ring for four species and site features (topographic information, soil conditions, and LIDAR extracted data)., Peer reviewed

NSCdata: This database contains seasonal non-structural carbohydrates data (NSC; including total NSC, starch and soluble sugars) for terrestrial land plants (global scope), and it is based on a compilation of data from the literature. We selected only data that fulfilled the following criteria: (1) study duration was at least four months, (2) the same individuals or populations were measured at least three times spanning the length of the study, (3) plants were mature, (4) measurements were taken on leaves, stems, or belowground organs, (5) tissue was not bark, phloem or cortex, (6) values reported were total NSC, starch/fructans or soluble sugars, and (7) species were land plants (i.e., saltwater and freshwater species were not included)., NSCdata_sources: This file lists the sources of all the individual datasets included in our final NSC database (”NSCdata_DRYAD.csv” file)., Plants store large amounts of non-structural carbohydrates (NSC). While multiple functions of NSC have long been recognized, the interpretation of NSC seasonal dynamics is often based on the idea that stored NSC is a reservoir of carbon that fluctuates depending on the balance between supply via photosynthesis and demand for growth and respiration (the source-sink dynamics concept). Consequently, relatively high NSC concentrations in some plants have been interpreted to reflect excess supply relative to demand. An alternative view, however, is that NSC accumulation reflects the relatively high NSC levels required for plant survival; an important issue that remains highly controversial. Here, we assembled a new global database to examine broad patterns of seasonal NSC variation across organs (leaves, stems and belowground), plant functional types (coniferous, drought deciduous angiosperms, winter deciduous angiosperms, evergreen angiosperms, and herbaceous) and biomes (boreal, temperate, Mediterranean and tropical). We compiled data from 123 studies, including seasonal measurements for 179 species under natural conditions. Our results showed that, on average, NSC account for ~10% of dry plant biomass and are highest in leaves and lowest in stems, whereas belowground organs show intermediate concentrations. Total NSC, starch and soluble sugars (SS) varied seasonally, with a strong depletion of starch during the growing season and a general increase during winter months, particularly in boreal and temperate biomes. Across functional types, NSC concentrations were highest and most variable in herbaceous species and in conifer needles. Conifers showed the lowest stem and belowground NSC concentrations. Minimum NSC values were relatively high (46% of seasonal maximums on average for total NSC) and, in contrast to average values, were similar among biomes and functional types. Overall, although starch depletion was relatively common, seasonal depletion of total NSC or SS was rare. These results are consistent with a dual view of NSC function: whereas starch acts mostly as a reservoir for future use, soluble sugars perform immediate functions (e.g., osmoregulation) and are kept above some critical threshold. If confirmed, this dual function of NSC will have important implications for the way we understand and model plant carbon allocation and survival under stress., Peer reviewed

Peer reviewed

Peer reviewed

How to name and use data files: The "code.R" file includes R code that is used to create all figures in the main text. The file of “raw data” contains the raw data files that were analyzed to produce the statistics and figures reported in the paper. 1. field survey data: This file includes data from three plots, i.e., E1, E2, and M1. The raw data was divided according to species, where "a" represents "Fir" and "b" represents "Birch". 2. Bivariate analysis: This file includes data of bivariate analysis. E1, Everest plot 1; E2, Everest plot 2; and M1, Manang plot 1; A, fir; B, birch; a, age <50 y.; b, age ≥50 y. 3. simulated data: This file includes simulated data. The "..._spin_up.csv" files represent 500-year spin up period, and "..._real_simulation.csv" files represent real simulations during 1901-2020. The file of “Figures” contains all figures in the main text., Discerning how climate change drives species succession for forecasting future forest composition is a fundamental challenge. Controlled experiments have suggested that climatic warming accelerates species succession, putting pioneer species at a disadvantage. Warmers conditions would thus be expected to accelerate successional dynamics in populations at the limits of their thermal ranges, such as alpine treelines where conditions are harsh. We tested this hypothesis by reconstructing the spatiotemporal patterns of two tree species, the early- and late-successional Himalayan birch and Himalayan fir, respectively, at alpine treelines. We also examined how species interactions and successional strategies affect treeline dynamics using plot data and by fitting an individually based treeline model. Fir showed increasing recruitment and a higher rate of upslope shift (0.11 ± 0.02 m y-1) compared to birch (0.06 ± 0.03 m y-1) over the last 200 years. Spatial analyses evidenced that strong competition between these two species, particularly when the trees were young. Following an initial colonization by birch, fir started to establish 21 years later. Model outputs from various warming scenarios indicate that fir will likely accelerate its upslope movement in response to higher temperatures. By contrast, birch recruitment tends to decline with warming, forming stable treelines. Our findings point to accelerating successional dynamics in mixed treelines with late-successional species rapidly outcompeting pioneer species. Our findings provide strong evidence that climatic warming is affecting forest composition at climatically controlled range limits, offering a crucial insight into future changes and their threat on ecosystem services and conservation of bioresources., National Science and Technology Major Project of China ：Second Tibetan Plateau Scientific Expedition and Research Programme (STEP)（2019QZKK0000）, Peer reviewed

This item is made of 2 files: the dataset in netcdf format, a Readme.txt file including a small description of the computed variables, and 1 figure showing a map of the simulation nodes of the model, Return values of 25, 50 and 100 years period obtained from a distribution function of the wave data modeled using the SWANST model, with the aim of studying the wave regime along the Galician coast between January 2000 and June 2021, This research/work is a contribution to the CSIC Interdisciplinary Thematic Platform OCEANS+, funded by the European Union – NextGeneration EU – as part of the MITECO program for the Spanish Recovery, Transformation and Resilience Plan (Recovery and Resilience Facility of the European Union established by the Regulation (EU) 2020/2094), and was entrusted to CSIC, AZTI, SOCIB, and the universities of Vigo and Cadiz, Peer reviewed

This item is made of 2 files: the dataset in netcdf format, a Readme.txt file including a small description of the computed variables, and 1 figure showing a map of the simulation nodes of the model, Statistical parameters obtained from a distribution function of the wave data modeled using the SWANST model, with the aim of studying the wave regime along the Galician coast between January 2000 and June 2021, This research/work is a contribution to the CSIC Interdisciplinary Thematic Platform OCEANS+, funded by the European Union – NextGeneration EU – as part of the MITECO program for the Spanish Recovery, Transformation and Resilience Plan (Recovery and Resilience Facility of the European Union established by the Regulation (EU) 2020/2094), and was entrusted to CSIC, AZTI, SOCIB, and the universities of Vigo and Cadiz, Peer reviewed

This item is made of 2 files: the dataset in netcdf format, a Readme.txt file including a small description of the computed variables, and 1 figure showing a map of the simulation nodes of the model, Statistical parameters obtained from the analysis of wave data modeled using the SWANST model, with the aim of studying the wave regime along the Galician coast between January 2000 and June 2021, This research/work is a contribution to the CSIC Interdisciplinary Thematic Platform OCEANS+, funded by the European Union – NextGeneration EU – as part of the MITECO program for the Spanish Recovery, Transformation and Resilience Plan (Recovery and Resilience Facility of the European Union established by the Regulation (EU) 2020/2094), and was entrusted to CSIC, AZTI, SOCIB, and the universities of Vigo and Cadiz, Peer reviewed