Find research datasets worth reusing

Climate warming could free cold-adapted trees from C-conservative allocation strategy of storage over growth

Carbon allocation has been fundamental for long-lived trees to survive cold stress at their upper elevation range limit. Although carbon allocation between NSC (non-structural carbohydrate) storage and structural growth is well-documented, it still remains unclear how ongoing climate warming influences these processes, particularly whether these two processes will shift in parallel or respond divergently to warming. Using a combination of an in situ downward-transplant warming experiment and an ex situ chamber warming treatment, we investigated how subalpine fir trees at their upper elevation limit coordinated carbon allocation priority among different sinks (e.g., NSC storage and structural growth) at whole-tree level in response to elevated temperature. We found that transplanted individuals from the upper elevation limit to lower elevations generally induced an increase in specific leaf area, but there was no detected evidence of warming effect on leaf-level saturated photosynthetic rates. Additionally, our results challenged the expectation that climate warming will accelerate structural carbon accumulation while maintaining NSC constant. Instead, individuals favored allocating available carbon to NSC storage over structural growth after one year of warming, despite the amplification in total biomass encouraged by both in situ and ex situ experimental warming. Unexpectedly, continued warming drove a regime shift in carbon allocation priority, which was manifested in the increase of NSC storage in synchrony to structural growth enhancement. These findings imply that climate warming would release trees at their cold edge from C-conservative allocation strategy of storage over structural growth. Thus, understanding the strategical regulation of the carbon allocation priority and the distinctive function of carbon sink components is of great implication for predicting tree fate in the future climate warming.

Data from: Climate warming and sea turtle sex ratios across the globe

Climate warming and the feminisation of populations due to temperature-dependent sex determination may threaten sea turtles with extinction. To identify sites of heightened risk, we examined sex ratio data and patterns of climate change over multiple decades for 64 nesting sites spread across the globe. Over the last 62 years the mean change in air temperature was 0.85 °C per century (SD = 0.65 °C, range = -0.53 to +2.5 °C, n = 64 nesting sites). Temperatures increased at 40 of the 64 study sites. Female-skewed hatchling or juvenile sex ratios occurred at 57 of the 64 sites, with skews > 90% female at 17 sites. We did not uncover a relationship between the extent of warming and sex ratio (r62 = -0.03, p = 0.802, n = 64 nesting sites). Hence, our results suggest that female-hatchling sex ratio skews are not simply a consequence of recent warming but have likely persisted at some sites for many decades. So other factors aside from recent warming must drive these variations in sex ratios across nesting sites, such as variations in nesting behaviour (e.g., nest depth), substrate (e.g., sand albedo), shading available and rainfall patterns. While overall across sites recent warming is not linked to hatchling sex ratio, at some sites there is both is a high female skew and high warming, such as Raine Island (Australia; 99% female green turtles; 1.27 °C warming per century), nesting beaches in Cyprus (97.1% female green turtles; 1.68 °C warming per century), and in the Dutch Caribbean (St Eustatius; 91.5% female leatherback turtles; 1.15 °C warming per century). These may be among the first sites where management intervention is needed to increase male production. Continued monitoring of sand temperatures and sex ratios are recommended to help identify when high incubation temperatures threaten population viability.

opencc-by-4.0May 2023View details →

Climate warming drives rockfall from an increasingly unstable mountain slope

This readme file provides all data and R codes used to perform the analyses presented in Figs. 2-4 of the main text and Supplementary Information Figures S1-S2-S3. FIGURE 2 -  Seasonally_dated_GDs.txt: Contains information on the timing (Season) of rockfall (GD) in a given tree (Id) and a given year (yr) over the past 100 years. Inv refers to the operators which analyzed growth disturbances in the tree-ring series. Lat / Long refers to the position of the tree in CH1903/ Swiss Grid projection. Intensity (1-4) refers to (1), intermediate (2)  and strong (3) GD. Intensity 4 was attributed to injuries (I). Only the 408 GD rated 3 (strong TRD) and 4 (injuries) were used in Fig. 2. Acronyms used for Response_type read as follows: TRD: Tangential rows of traumatic resin ducts; I: Injuries. Acronyms used for Season refer to Dormancy (1_D), early (2_EE), middle (3_ME) and late (4_LE) earlywood, whereas a GD found in the latewood was attributed to either the early (5_EL) or late (6_LL) latewood. - Trends_in_seasonality_R1.R: The data contained in "Seasonally_dated_GDs" were processed with the R script "Trends_in_Seasonality.R". This seasonal trend analysis code is inspired by work published by Schlögl et al. (2021; https://doi.org/10.1016/j.crm.2021.100294) and Heiser et al. (2022; https://doi.org/10.1029/2011JF002262). FIGURE 3-4-S1 - Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - Rockfall_frequency_climate.R: The data contained in "Tasch_GD.txt" were processed with the R script "Rockfall_frequency_climate.R".   - The temperature (Imfeld23_tmp.txt) and precipitation (Imfeld23_prc.txt) data used in Fig. 3 are from the Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Täschgufer site. - The script set with temperature series enables to compute Fig. 4 (l.149:216) and Fig. 3 (l. 216:330); the script set with precipitation series enables to compute Fig. S1 FIGURE S2 - Tasch_GD.txt: Contains the raw data on rockfall impacts (GD) at the Täschgufer site in a given year (yr) as found in all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - Rockfall_frequency_borehole.R: is adapted from "Rockfall_frequency_climate.R" to work with the borehole dates.   - Corvatsch0_6R1: Contains the Corvatsch borehole temperature series (2000-2020, 0.6m depth) (Hoelzle, M. et al. https://doi.org/10.5194/essd-14-1531-2022, 2022). FIGURE S3 - Plattje_GD.txt: Contains the raw data on rockfall impacts (GD) at the Plattje site in a given year (yr) as found all trees available in that same year (Sample_depth) as well as the cumulated diameter at breast height (cumulated_DBH) of all trees present in that same year. - - Rockfall_frequency_climate_Plattje.R: The data contained in "Plattje_GD.txt" were processed with the R script "Rockfall_frequency_climate_Plattje.R".   - The temperature (Imfeld23_tmp_Plattje.txt) and precipitation (Imfeld23_prc_Plattje.txt) data used in Fig. 3 are from Imfeld et al. 2023 (10.5194/cp-19-703-2023) gridded dataset (1x1 km lat/long) and were extracted at the grid point centered on the Plattje site.

Diversity of endemic cold-water amphipods threatened by climate warming in northwestern China

Aim: Climate change threatens freshwater faunal diversity. To prioritize areas for conservation, patterns in the distribution of species must be understood. We apply genetic analysis and species distribution models to identify patterns in the distribution of freshwater amphipods around Xinjiang, China, and project the impact of climate change on endemic species. Location: Xinjiang, China. Methods: A time-calibrated tree containing 37 freshwater amphipod molecular samples from Xinjiang is built to calculate phylogenetic diversity, the standardized effect sizes of phylogenetic diversity, weighted endemism, and phylogenetic endemism, in 100 × 100 km grid cells. Niche differentiation among species in an area of high phylogenetic endemism is explored using n-dimensional hypervolumes and principal components analyses. Present-day and projected future suitability of habitat of endemic freshwater amphipod species is described using species distribution models. Results: Areas of high freshwater amphipod diversity occur along the western boundary of Xinjiang; Areas north of Irtysh River, Tian Shan mountains, and the eastern margin of Pamir, have high phylogenetic endemism. Seasonal temperature and average annual water temperature contribute most to niche differentiation between geographically related freshwater species, negatively affect the projected distributions of endemic amphipods, and with continued warming, reduce future range distributions or latitudinal shifts of species. Main Conclusions: High freshwater amphipod phylogenetic endemism occurs in Xinjiang. Environmental factors are responsible for niche differentiation of endemic species. Future climate change will substantially affect the geographic distributions of endemic amphipods. Conservation efforts should be prioritized in areas with highly concentrated phylogenetic endemism.

Data from: Frost damage measured by electrolyte leakage in subarctic bryophytes increases with climate warming

1. Observed climate change in northern high latitudes is strongest in winter, but still relatively little is known about the effects of winter climate change on tundra ecosystems. Ongoing changes in winter climate and snow cover will change the intensity, duration, and frequency of frost events. Bryophytes form a major component of northern ecosystems but their responses to winter climate changes are largely unknown. 2. Here, we studied how changes in overall winter climate and snow regime affect frost damage in three common bryophyte taxa that differ in desiccation tolerance in a subarctic tundra ecosystem. We used a snow manipulation experiment where bryophyte cores were transplanted from just above the treeline to similar elevation (i.e., current cold climate) and lower elevation (i.e., near-future warmer climate scenario) in Abisko, Sweden. Here we measured frost damage in shoots of Ptilidium ciliare, Hylocomium splendens and Sphagnum fuscum with the relative electrolyte leakage (REL) method, during late winter and spring in two consecutive years. We hypothesized that frost damage would be lower in a milder climate (low site), higher under reduced snow cover, and that taxa from moister habitats with assumed low desiccation tolerance would be more sensitive to lower temperature and thinner snow cover than those from drier and more exposed habitats. 3. Contrary to our expectations, frost damage was highest at low elevation, while the effect of snow treatment differed across sites and taxa. At the high site, frost damage was reduced under snow addition in the taxon with the assumed lowest desiccation tolerance, S. fuscum. Surprisingly, frost damage increased with mean temperature in the bryophyte core of the preceding 14 days leading up to REL measurements and decreased with higher frost degree sums, i.e., was highest in the milder climate at the low site. 4. Synthesis. Our results imply that climate warming in late winter and spring increases frost damage in bryophytes. Given the high abundance of bryophytes in tundra ecosystems, higher frost damage could alter the appearance and functioning of the tundra landscape, although the short and long-term effects on bryophyte fitness remain to be studied.

opencc-by-4.0Dec 2023View details →

Dataset for "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling

This dataset allows the user to reproduce figures from the journal article "Impacts and state-dependence of AMOC weakening in a warming climate" by Bellomo & Mehling.

Supplementary data for "Increasing risks of extreme salt intrusion events across European estuaries in a warming climate", published in Communications Earth & Environment

This data repository contains python scripts and post-processed climate model and salt intrusion length data to reproduce figures in the paper below. ==================== Title: Increasing risks of extreme salt intrusion events across European estuaries in a warming climate (<a href="https://www.nature.com/articles/s43247-024-01225-w">Link to the full paper</a>) Author: Jiyong Lee, Bouke Biemond, Huib de Swart, and Henk A. Dijkstra Journal: Communications Earth & Environment Year: 2024 Publisher: Nature ====================

Dataset from the project entitled HimFunDiff. Related to research article: Global warming alters Himalayan alpine shrub growth dynamics and climate sensitivity.

We examined a total of 9 populations of Rhododendron anthopogon, which were located between 3200 m and 4200 m above sea level (asl). These populations were distributed across three geographically distant transects, with each transect consisting of three sites (along an elevation gradient). The transects are referred to as northern, intermediate, and southern, while the sites at each transect are categorized as low, mid, and high (as depicted in Thakur et al 2024). The northern transect exhibited colder temperatures and lower rainfall compared to the other two transects. On the other hand, the two remaining transects had relatively similar temperatures, but the southernmost transect received higher levels of precipitation. The mean annual temperature of these populations ranged from 2 °C to 5 °C from 2021 through 2022, while volumetric soil moisture levels varied from 0.198 to 0.377 based on onsite measurements using TMS4 dataloggers (Wild et al., 2019). We collected a total of 81 wood disc samples, with 9 samples obtained from each of the 9 sites studied (9 populations × 9 discs). The samples were collected by cutting a single piece from the thickest stem segment, approximately 5 cm in length, from 81 different mature and healthy individuals. Within each site, the 9 samples were obtained from three separate plots (three samples per plot), each covering an area of approximately 100 m2. The selection criteria for these plots included: (1) the presence of Rhododendron anthopogon as one of the dominant species; (2) minimal anthropogenic disturbance; and (3) the absence of large shrubs or trees. The sampled individuals within a plot were spaced at least 5 m apart from each other, and the plots themselves were at least 20 m apart. To prevent rapid drying, the cut stem samples were immediately placed in a wet paper towel. Within 48  hours of sampling, the stem samples underwent dehydration by being immersed in 50 % ethanol for the initial 3 days, followed by 70 % ethanol for the subsequent 7 to 10 days. After the ethanol dehydration process, the samples were air-dried for 72  hours and then stored in paper bags until further processing. Plant age and growth data for each of the sampled individuals were obtained following established protocols (Doležal et al., 2018). In the laboratory, we utilized a sledge microtome to cut cross-sections from each stem sample. These cross-sections were then stained with Astra Blue and Safranin and permanently affixed to microscope slides using Canada Balsam (Doležal et al., 2022). High-resolution images of the fixed sections were captured using an Olympus BX53 microscope equipped with an Olympus DP73 camera. The software CellSense Entry 1.9 was employed to analyse the best image obtained from each individual. We measured annual radial growth increments from pith to bark to the nearest micrometre.  More details are given in the article entitled  <h1>Global warming alters Himalayan alpine shrub growth dynamics and climate sensitivity. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scitotenv.2024.170252" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.scitotenv.2024.170252</a></h1>

GEOSCCM Simulations for Thresholds for Volcanic Climate Warming 4

Selected output in NetCDF format from simulations performed with the GEOSCCM global climate model.

GEOSCCM Simulations for Thresholds for Volcanic Climate Warming 3

Selected output in NetCDF format from simulations performed with the GEOSCCM global climate model.

Datasets for "Peatland evaporation across hemispheres: contrasting controls and sensitivity to climate warming driven by plant functional types" - Version 2

Version 2 of datasets used for analyses in the paper titled "Peatland evaporation across hemispheres: contrasting controls and sensitivity to climate warming driven by plant functional types" submitted to Biogeosciences. There are two datasets - one from Kopuatai bog, Aotearoa New Zealand, and one from Mer Bleue bog, Canada - which contain gap-filled and filtered data that were used to produce the results of our study. Due to improvements made to our methodology following the paper peer review process, the data in this version slightly differs from that of the previous version. Information on these revisions can be found in the README file below or the Discussion/Peer Review tab of our paper.

opencc-zeroFeb 2024View details →

Data from: Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR) – key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades, and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

opencc-zeroMar 2024View details →

Data for: Climate warming and projected loss of thermal habitat volume in lake populations of brook trout

We applied an ensemble of climate warming models and the seasonal temperature profile model for lakes (STM) to assess changes in brook trout thermal habitat volume (THV) among lakes (N=100) within a large, protected area under two climate warming scenarios, RCP 4.5 and RCP 8.5. Brook trout thermal habitat was defined as 9-17°C. Climate warming projections for the balance of this century, regardless of RCP category, will result in the loss of brook trout habitat in lakes that range widely in size. THV loss will be most extensive in lakes that are relatively shallow given their surface area. By 2071-2100 under RCP 4.5, the 90th percentile of THV loss = 31% vs. 63% under RCP 8.5. By the century's end under RCP 8.5, the protected area landscape will be a matrix of lakes with some serving as climate refugia (with reduced THV) and others having severe reductions in THV (>90th percentile THV loss).

Model output for a storyline analysis of hurricane Irma's precipitation under various levels of climate warming

Understanding how extreme weather, such as tropical cyclones, will change with future climate warming is an interesting computational challenge. Here, the hindcast approach is used to create different storylines of a particular tropical cyclone, Hurricane Irma (2017). Using the Community Atmosphere Model, we explore how Irma's precipitation would change under various levels of climate warming. Analysis is focused on a 48-hour period where the simulated hurricane tracks reasonably represent Irma's observed track. Under future scenarios of 2 K, 3 K, and 4 K global average surface temperature increase above pre-industrial levels, the mean 3-hourly rainfall rates in the simulated storms increase by 3-7%/K compared to present. This change increases in magnitude for the 95th and 99th percentile 3-hourly rates, which intensify by 10-13%/K and 17-21%/K, respectively. Over Florida, the simulated mean rainfall accumulations increase by 16-26%/K, with local maxima increasing by 18-43%/K. All percent changes increase monotonically with warming level.

opencc-by-4.0Apr 2024View details →

Dataset for "Competing climate feedbacks of ice sheet freshwater discharge in a warming world", Part II

This is Part II of the output dataset from coupled ice sheet-climate model simulations that investigate the interactions between ice sheet freshwater flux and the warming climate. Description of models, coupling scheme, and design of these simulations is provided in a paper titled "Competing climate feedbacks of ice sheet freshwater discharge in a warming world", which is currently under peer review. More information will be updated when available.

opencc-by-4.0Apr 2024View details →

Dataset for "Competing climate feedbacks of ice sheet freshwater discharge in a warming world", Part I

This is Part I of the output dataset from coupled ice sheet-climate model simulations that investigate the interactions between ice sheet freshwater flux and the warming climate. Description of models, coupling scheme, and design of these simulations is provided in a paper titled "Competing climate feedbacks of ice sheet freshwater discharge in a warming world", which is currently under peer review. More information will be updated when available.

opencc-by-4.0Jul 2024View details →

Data set for the study "Interplay between climate and carbon cycle feedbacks could substantially enhance future warming"

This repository contains the data necessary to reproduce the results of the paper:  "Interplay between climate and carbon cycle feedbacks could substantially enhance future warming"  <a href="https://iopscience.iop.org/article/10.1088/1748-9326/adb6be" target="_blank" rel="noopener">https://iopscience.iop.org/article/10.1088/1748-9326/adb6be</a> <h3>Data organization:</h3> The Zenodo repository is organized as follows inside of <code>results.zip</code>: <ul> <li>Figure generation are given by "*.pynb" and "*.m" files </li> <li>Data files as NetCDF output are organized with the following structure inside of <code>data</code>: <ul> <li>Experiment/emission scenario: <code>hist-aer</code>, <code>ssp126</code>, <code>ssp434</code>, and <code>ssp245</code> <ul> <li>Equilibrium climate sensitivity: <code>ecs_2.0K</code>, <code>ecs_2.5K</code>, <code>ecs_3.0K</code>, <code>ecs_3.5K</code>, <code>ecs_4.0K</code>, <code>ecs_4.5K</code>, and <code>ecs_5.0K</code> <ul> <li>Experiment: <code>comp</code>, <code>comp_fix_ch4</code>, <code>comp_fix_co2_ch4</code>, <code>comp_ssp_co2_ch4</code> <ul> <li>Component: atmosphere (<code>atm</code>), ocean (<code>ocn</code>), land (<code>lnd</code>), sea ice (<code>sic</code>), carbon dioxide (<code>co2</code>), methane (<code>ch4</code>) </li> <li>File type: for some experiments, files are divided into timeseries (<code>*_ts.nc</code>) or 2D data (<code>*.nc</code>) </li> <li>Note: <code>comp_ssp_co2_ch4</code> are the CLIMBER-X runs which used prescribed concentrations (rather than emissions) and is only available for ECS 3°C </li> <li>Note: <code>comp_fix_ch4</code> and <code>comp_fix_co2_ch4</code> is only available for ECS 2°C, 3°C, and 5°C (as shown in Fig. 4 in the manuscript)</li> </ul> </li> </ul> </li> </ul> </li> </ul> </li> </ul>

opencc-by-4.0Dec 2021View details →

Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Kortrijk Kennedy Park, Belgium

Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Kortrijk Kennedy Park (50°48'2"N 3°16'13" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016).  The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).

opencc-by-4.0Dec 2021View details →

Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Antwerp Berchem, Belgium

Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Antwerp Berchem (51°12'00"N 4°26'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016).  The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).