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2,260 results for “climate change”
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Fine Root Damage
Root damage, as relative electrolyte leakage, was assessed following winter freeze-thaw cycle experimental treatments in 2014 and 2015 on all Climate Change Across Seasons Experiment (CCASE) plots. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). Analysis and results from these data are presented in Sanders-DeMott 2018. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Sanders-DeMott, R., Sorensen, P.O., Reinmann, A.B. et al. Growing season warming and winter freeze–thaw cycles reduce root nitrogen uptake capacity and increase soil solution nitrogen in a northern forest ecosystem. Biogeochemistry 137, 337–349 (2018). https://doi.org/10.1007/s10533-018-0422-5
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Root Nitrogen Uptake Capacity
Fine root nitrogen uptake capacity was measured on excised roots prior to experimental treatment in 2013 and throughout the growing seasons of 2014 and 2015 on all Climate Change Across Seasons Experiment (CCASE) plots. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). Analysis and results from these data are presented in Sanders-DeMott 2018. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Sanders-DeMott, R., Sorensen, P.O., Reinmann, A.B. et al. Growing season warming and winter freeze–thaw cycles reduce root nitrogen uptake capacity and increase soil solution nitrogen in a northern forest ecosystem. Biogeochemistry 137, 337–349 (2018). https://doi.org/10.1007/s10533-018-0422-5
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Soil Solution Resin Available Nitrogen
Resin available soil solution nitrogen was measured during seasonal incubations in 2014 and 2015 on all Climate Change Across Seasons Experiment (CCASE) plots. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). Analysis and results from these data are presented in Sanders-DeMott 2018. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Sanders-DeMott, R., Sorensen, P.O., Reinmann, A.B. et al. Growing season warming and winter freeze–thaw cycles reduce root nitrogen uptake capacity and increase soil solution nitrogen in a northern forest ecosystem. Biogeochemistry 137, 337–349 (2018). https://doi.org/10.1007/s10533-018-0422-5
Hubbard Brook Experimental Forest: In-situ Nitrogen Mineralization and Nitrification measurements for 4 winter climate change projects
These data are from four separate projects undertaken between 1997 and 2017. The first of these are two snow manipulation (freeze) projects: 1) In 1997, as part of a study of the relationships between snow depth, soil freezing and nutrient cycling, we established eight 10 x 10-m plots located within four stands; two dominated (80%) by sugar maple (SM1 and SM2) and two dominated by yellow birch(YB1 and YB2), with one snow reduction (shoveling) and one reference plot in each stand. 2) In 2001, we established eight new 10-m x 10-m plots (4 treatment, 4 reference) in four new sites; two high elevation, north facing and (East Kineo and West Kineo) two low elevation, south facing (Upper Valley and Lower Valley) maple-beech-birch stands. To establish plots, we cleared minor amounts of understory vegetation from all (both treatment and reference) plots (to facilitate shoveling). Treatments (keeping plots snow free by shoveling through the end of January) were applied in the winters of 1997/98, 1998/99, 2002/2003 and 2003/2004. The Climate Gradient Project was established in October 2010. Here we evaluated relationships between snow depth, soil freezing and nutrient cycling along an elevation/aspect gradient that created variation in climate with little variation in soils or vegetation. We established 6 20 x 20-m plots (intensive plots) and 14 10 x 10-m plots (extensive plots), with eight of the plots facing north and twelve facing south. The Ice Storm project was designed to evaluate the damage and changes ice storms cause to northern hardwood forests in forest structure, nutrient cycling and carbon storage. Ten 20x30 meter plots were established in a predominately sugar maple stand, with 4 icing treatments and 2 control plots. The treatments are as follows: Low (0.25"), Mid (0.5"), Midx2 (0.5") 2 Years in a row, High: (0.75"), Control. The icing treatment was conducted in the winter of 2015-2016, with a second year of icing on the Midx2 treatments plots in the winter of 20
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: growth and enzyme activity traits of soil fungi isolated from CCASE in July 2017, grown under a common garden experiment in the laboratory that mimicked CCASE soil temperature treatments
Projections for the northeastern U.S. indicate that mean air temperatures will rise and snowfall will become less frequent, causing more frequent soil freezing. To test fungal responses to these combined chronic and extreme soil temperature changes, we conducted a laboratory-based common garden experiment with soil fungi that had been subjected to different combinations of growing season soil warming, winter soil freeze/thaw cycles, and ambient conditions for four years in the field. We found that fungi originating from field plots experiencing a combination of growing season warming and winter freeze/thaw cycles had inherently lower activity of acid phosphatase, but higher cellulase activity, that could not be reversed in the lab. In addition, fungi quickly adjusted their physiology to freeze/thaw cycles in the laboratory, reducing growth rate and potentially reducing their carbon use efficiency. Our findings suggest that less than four years of new soil temperature conditions in the field can lead to physiological shifts by some soil fungi, as well as irreversible loss or acquisition of extracellular enzyme activity traits by other fungi. These findings could explain field observations of shifting soil carbon and nutrient cycling under simulated climate change. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Tree Growth Data in support of "Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems", Conrad-Rooney et al. PNAS 2025
Data associated with the publication: Conrad-Rooney E, AB Reinmann, PH Templer. Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems. Proceedings of the National Academy of Sciences, 2025. This dataset includes cumulative stem biomass carbon data (from pre-treatment in 2012 until 2022) and annual stem biomass growth rates (not cumulative) for 2015-2022 for the red maple trees at the Climate Change Across Seasons Experiment. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest: Soil Temperature, Soil Frost, and Snow Depth Data in support of "Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems", Conrad-Rooney et al. PNAS 2025
Data associated with the publication: Conrad-Rooney E, AB Reinmann, PH Templer. Declining Winter Snowpack Offsets Carbon Storage Enhancement from Growing Season Warming in Northern Temperate Forest Ecosystems. Proceedings of the National Academy of Sciences, 2025. This dataset includes soil temperature (winter 2021-2022) and snow depth and frost depth (winter 2022-2023) at the Climate Change Across Seasons Experiment. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Climate change perception interview questions for Kunene, Namibia
<p>The files contain interview question used to collect data on climate change perception in Kunene Region Namibia, from a pastoralist Himba tribe.</p>
Data for 'Future Transboundary Water Stress and Its Drivers Under Climate Change: A Global Study'
<p><strong>This dataset is a supplement to the following publication (please cite that when using the data):</strong></p> <p>Munia et al. 2020. Future transboundary water stress and its drivers under climate change: a global study. Earth’s future. <a href="https://doi.org/10.1029/2019EF001321">https://doi.org/10.1029/2019EF001321</a></p> <p> </p> <p><strong>Water stress category data</strong></p> <p>Dataset presents the water stress category in transboundary basins at sub-basin level for different scenarios (see article for details):</p> <ul> <li> <p>stress_category_Historical.gpkg: stress for years 1980 and 2010</p> </li> <li> <p>stress_category_SSP1‐RCP26.gpkg: stress for year 2050, SSP1‐RCP2.6 scenario</p> </li> <li> <p>stress_category_SSP1‐RCP45.gpkg: stress for year 2050, SSP1‐RCP4.5 scenario</p> </li> <li> <p>stress_category_SSP2‐RCP60.gpkg: stress for year 2050, SSP2‐RCP6.0 scenario</p> </li> <li> <p>stress_category_SSP3‐RCP60.gpkg: stress for year 2050, SSP3‐RCP6.0 scenario</p> </li> </ul> <p> </p> <p><strong>Dataset specifications:</strong></p> <p>Type: geopackage (gpkg)</p> <p>Spatial extent: -165, 141.5, -54.5, 70.5 (xmin, xmax, ymin, ymax)</p> <p>Temporal extent: see above</p> <p>Projection: long/lat WGS84 (EPSG:4326)</p> <p>Information: sub-basin name, country, stress level, stress category</p> <p>Unit: -</p> <p> </p>
Database and model code for "Material efficiency and climate change mitigation of passenger vehicles"
<p>This record provides all data points and model code necessary to compute the results presented in P. Wolfram, Q. Tu, N. Heeren, S. Pauliuk, E. Hertwich (2020) "Material efficiency and climate change mitigation of passenger vehicles", published in Journal of Industrial Ecology. All data is described in section 2 of the manuscript. The code can be run in MATLAB. </p>
Data from: A changing climate is snuffing out post-fire recovery in montane forests
Aim: <p>Climate warming is increasing fire activity in many of Earth's forested ecosystems. Because fire is an important catalyst for change, investigation of post-fire vegetation response is crucial for understanding the potential for future conversions from forest to non-forest vegetation types. To better understand effects of wildfire and climate warming on forest recovery, we assessed the extent to which climate and terrain influence spatiotemporal variation in past and future post-fire tree regeneration.</p> Location: <p>Montane forests, Rocky Mountains, USA</p> Time Period: <p>1981-2099</p> Taxa Studied: <p><i>Pinus ponderosa</i>; <i>Pseudotsuga menziesii</i></p> Methods: <p>We developed a network of dendrochronological samples (n = 717) and field plots (n = 1301) from post-fire environments spanning a range of topographic and climatic settings. We then used boosted regression trees to predict annual suitability for post-fire seedling establishment and generalized linear mixed models to predict total post-fire seedling abundances, reconstructing recent trends in post-fire recovery and projecting future dynamics using three general circulation models (GCMs) under moderate and extreme emission scenarios.</p> Results: <p>Though 1981-2015 declines in growing season (April-September) precipitation were associated with declining suitability for seedling establishment, 2021-2099 trends in precipitation were widely variable among GCMs, leading to mixed projections of future establishment suitability. In contrast, climatic water deficit (CWD), strongly tied to warming temperature and increased evaporative demand, was projected to increase throughout our study area. Our projections strongly suggest that future increases in CWD and an increased frequency of extreme drought will reduce post-fire seedling abundances.</p> Main Conclusions: <p>Our findings highlight the key roles of warming and drying in declines in forest resilience to wildfire. The striking differences in projections of post-fire recovery between moderate and extreme emissions scenarios suggest that the most extreme impacts on forest resilience in the latter part of the 21<sup>st</sup> century may be mitigated with aggressive emissions reductions in the next two decades.</p>
Investigation on the Use of Passive Microclimate Frames in View of the Climate Change Scenario
<p>Passive microclimate frames are exhibition enclosures able to modify their internal climate in order to comply with paintings’ conservation needs. Due to a growing concern about the effects of climate change, future policies in conservation must move towards affordable and sustainable preservation strategies. This study investigated the hygrothermal conditions monitored within a microclimate frame hosting a portrait on cardboard with the aim of discussing its use in view of the climate expected indoors in the period 2041–2070. Its effectiveness in terms of the ASHRAE classification and of the Lifetime Multiplier for chemical deterioration of paper was assessed comparing temperature and relative humidity values simultaneously measured inside the microclimate frame and in its surrounding environment, first in the Pio V Museum and later in a residential building, both located in the area of Valencia (Spain). Moreover, heat and moisture transfer functions were used to derive projections over the future indoor hygrothermal conditions in response to the ENSEMBLES-A1B outdoor scenario. The adoption of microclimate frames proved to be an effective preventive conservation action in current and future conditions but it may not be sufficient to fully avoid the chemical degradation risk without an additional control over temperature.</p>
Data from: Climate drives the geography of marine consumption by changing predator communities
<p>The global distribution of primary production and consumption by humans (fisheries) is well-documented, but we have no map linking the central ecological process of consumption within food webs to temperature and other ecological drivers. Using standardized assays that span 105° of latitude on four continents, we show that rates of bait consumption by generalist predators in shallow marine ecosystems are tightly linked to both temperature and the composition of consumer assemblages. Unexpectedly, rates of consumption peaked at midlatitudes (25 to 35°) in both Northern and Southern Hemispheres across both seagrass and unvegetated sediment habitats. This pattern contrasts with terrestrial systems, where biotic interactions reportedly weaken away from the equator, but it parallels an emerging pattern of a subtropical peak in marine biodiversity. The higher consumption at midlatitudes was closely related to the type of consumers present, which explained rates of consumption better than consumer density, biomass, species diversity, or habitat. Indeed, the apparent effect of temperature on consumption was mostly driven by temperature-associated turnover in consumer community composition. Our findings reinforce the key influence of climate warming on altered species composition and highlight its implications for the functioning of Earth's ecosystems.</p>
Participatory Conceptual Diagrams to research small-scale farmers´ information sharing for adapting to climate change in Mozambique
<p>Data collected from focus groups discussions with local communities of 4 distrcits of Mozambique in November 2019. The data are a series of conceptual maps describing a) the farming practices improvements most needed to adapt to climate change, and b) the most useful information for enabling the selected improvements, the most effective information sharing sources - e.g. institutional actors, members of the community, technical support, etc. - and means of communication - e.g. radio, mobile phone, word-of-mouth, etc. For the second purpose, connections were drawn by the members of the community between information sources and the actions needed for climate change adaptation. Participants also assigned a weight to the connections, selecting between: strong, medium or a weak connection.</p> <p>Notes about the discussions and opinions expressed by participants, written down by the research team, are also included.</p> <p>Together with the data, PDF files describing metadata and detailed methodology followed are included.</p>
Forest carbon prospecting for climate change mitigation: Version 1.0
<p>This data package includes the two 1-km resolution global maps (.tif) of tropical forests between ~23.44°N and 23.44°S produced from the study: 1) investible forest carbon (in tCO<sub>2</sub>e ha<sup>-1</sup>y<sup>-1</sup>) and 2) forest carbon return-on-investment (Net Present Value in USD ha<sup>-1</sup>y<sup>-1</sup>) over a 30-year timeframe. It also includes the R script to reproduce these layers and their uncertainties. </p> <p><em><strong>Investible Forest Carbon</strong>: </em>The investible forest carbon map was produced based on the total volume of CO<sub>2</sub>e associated with the three main carbon pools in the tropics, namely aboveground carbon, belowground carbon and soil organic carbon. This is followed by the application of key Verified Carbon Standard (VCS) criteria including additionality, to determine the magnitude and areas of investible forest carbon across the tropics.</p> <p><em>Aboveground carbon.</em> A stoichiometric factor of 0.475 was applied to recent spatial data on aboveground carbon biomass to obtain carbon stock based on established carbon accounting methodologies. An uncertainty analyses was also performed to account for potential variability in stoichiometric factor. Subsequently, a conversion factor of 3.67 was applied to the carbon stock layer to obtain the volume of CO<sub>2</sub>e associated with this carbon pool.</p> <p><em>Belowground carbon</em>. Belowground carbon biomass was firstly derived by applying two allometric equations relating to root to shoot biomass to the most recent spatial dataset on aboveground carbon biomass following established carbon accounting methodologies. The two equations are:</p> <p> Belowground biomass = 0.489×aboveground biomass^0.89; and</p> <p> Belowground biomass = 0.26×aboveground biomass</p> <p>A stoichiometric factor of 0.475 was subsequently applied to the estimated belowground carbon biomass to obtain the carbon stock. An uncertainty analyses was then performed to determine the mean, minimum and maximum values for belowground carbon. Following that, a conversion factor of 3.67 was applied to the carbon stock layer to obtain the volume of CO<sub>2</sub>e associated with this carbon pool.</p> <p><em>Soil Organic Carbon</em>. Organic carbon density of the topsoil layer (0-30 cm) was obtained from the European Soil Data Centre as it represented the best data available for soil organic carbon. A conversion factor of 3.67 was subsequently applied to derive the volume of CO<sub>2</sub>e associated with this carbon pool.</p> <p><em>Applying VCS criteria</em>. The criterion of additionality is a pre-condition for carbon credits to be certified under the VCS. This implies that only the volume of forest carbon that are under imminent threat of decline or loss if left unprotected by a conservation intervention can be certified under the VCS. The volume of forest carbon under threat of loss was based on the best available data on predicted deforestation rates across the tropics (through to the year 2029), and annualized over predicted 15-year period. The estimated annual deforestation rates was then applied to the total volume of CO<sub>2</sub>e associated with tropical forests as estimated above, deriving the volume of CO<sub>2</sub>e that would be certifiable and thus investible under the VCS. In addition, a conservative 10-year decay estimate was assumed for the estimate of the belowground carbon pool, and lands that will likely not be certifiable for other reasons, including recently deforested areas (i.e. for the period of 2010-2017), a well as human settlements, were excluded. Lastly, the VCS requirement to set aside buffer credits of 20% was accounted for to consider the risk of non-permanence associated with Agriculture, Forestry and Other Land Use (AFOLU) projects.</p> <p><strong><em>Return</em>-<em>on-Investment</em></strong>. From the investible forest carbon map, the relative profitability of these areas was then modelled to produce a global forest carbon return-on-investment map based on their NPV. The NPV of returns were based on several simplifying assumptions following established values from previous studies. </p> <p><em>Cost of project establishment</em>. The cost of project establishment was estimated to be at $25 ha<sup>-1</sup>. This was based on a range of costs that are key to the development of a project, including but not limited to project design, governance and planning, enforcement, zonation, land tenure and acquisition, surveying and research. </p> <p><em>Cost for annual maintenance</em>. The cost for annual maintenance was estimated to be $10 ha<sup>-1</sup>, which included aspects such as in education and communication, monitoring, sustainable livelihoods, marketing, finance and administration.</p> <p><em>Carbon price</em>. A constant carbon price of $5.8 t<sup>-1</sup>CO­<sub>2</sub>e for the first five years was applied. This price was based on an average price of carbon for avoided deforestation projects reported recently by Forest Trends’ Ecosystem Marketplace (i.e. for the period 2006 – 2018). Subsequently, a 5% price appreciation was applied annually over a project timeframe of 30 years.</p> <p><em>Discount rate</em>. We calculated NPV of annual and accumulated profits over 30 years based on a 10% risk-adjusted discount rate. </p> <p>Further details for these datasets and their uncertainties are presented in Koh et. al. For questions or issues on the spatial data layers, please contact Yiwen Zeng (<a href="mailto:zengyiwen@nus.edu.sg">zengyiwen@nus.edu.sg</a>). </p>
Latitudinal core habitat prediction data for the manuscript: "Seascape topography slows predicted range shifts in fish under climate change"
<p>Latitudinal locations of core environmental habitat for yellowtail kingfish (<em>Seriola lalandi</em>), Australian bonito (<em>Sarda australis</em>), Australian spotted mackerel (<em>Scomberomorus munroi</em>), narrow-barred Spanish mackerel (<em>Scomberomorus commerson</em>) and common dolphinfish (<em>Coryphaena hippurus</em>) nearshore of the continental shelf break (i.e. 200-m isobath) within 145 – 160°E, 15 – 45°S and between years 1998 – 2018.</p>
Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event (dataset and R scripts)
<p>The present digital archive is the outcome of the paper: <strong>Lawrence, D., Palmisano, A., and de Gruchy, M.W., 2021. <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244871">Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event</a></strong><a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0244871">.</a> <em><strong>PLoS ONE</strong></em><strong>,</strong> <strong><em>16</em></strong>(1).</p> <p>The dataset included here provides a collection of <strong>920 </strong>radiocarbon dates and <strong>1070</strong> sites from archaeological surveys. In addition, the digital archive related to this paper provides reproducible analyses in the form of three scripts written in R statistical computing language.</p>
Wildfires and climate change push low-elevation forests across a critical climate threshold for tree regeneration
Climate change is increasing fire activity in the western United States, which has the potential to accelerate climate-induced shifts in vegetation communities. Wildfire can catalyze vegetation change by killing adult trees that could otherwise persist in climate conditions no longer suitable for seedling establishment and survival. Recently documented declines in postfire conifer recruitment in the western United States may be an example of this phenomenon. However, the role of annual climate variation and its interaction with long-term climate trends in driving these changes is poorly resolved. Here we examine the relationship between annual climate and postfire tree regeneration of two dominant, low-elevation conifers (ponderosa pine and Douglas-fir) using annually resolved establishment dates from 2,935 destructively sampled trees from 33 wildfires across four regions in the western United States. We show that regeneration had a nonlinear response to annual climate conditions, with distinct thresholds for recruitment based on vapor pressure deficit, soil moisture, and maximum surface temperature. At dry sites across our study region, seasonal to annual climate conditions over the past 20 years have crossed these thresholds, such that conditions have become increasingly unsuitable for regeneration. High fire severity and low seed availability further reduced the probability of postfire regeneration. Together, our results demonstrate that climate change combined with high severity fire is leading to increasingly fewer opportunities for seedlings to establish after wildfires and may lead to ecosystem transitions in low-elevation ponderosa pine and Douglas-fir forests across the western United States.
Data from paper: Large carbon sink potential of Secondary Forests in Brazilian Amazon to mitigate climate change (public)
<p><strong>Title</strong>: Large carbon sink potential of Secondary Forests in the Brazilian Amazon to mitigate climate change</p> <p><strong>Contact:</strong> Viola Heinrich (viola.heinrich@bristol.ac.uk)</p> <p><strong>This repository contains</strong>:</p> <ol> <li>Zipped folder:<strong> Fig1_data_input.zip</strong> - all the files needed to produce Figure 1a-e of the main paper. Set the working directory to folder containing the file and use the script "Fig1a_f_plot.R" to run (see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 1 - these files are in the format "<strong><driver>_assessment_v2.csv</strong>". The columns in the files are: A: age of secondary forest; B: 50th percentile (median) of the modal Aboveground Biomass (AGB) value for the given age (note, units are in biomass not carbon: Mg/ha/yr); C: The bias-corrected AGB value, calculated by subtracting the lowest AGB value in column B such that the AGB data starts at or near 0Mg/ha/yr at age 1. D: the number of secondary forest pixels observed to have the given age, E: "Threshold" : the threshold limits of the given driver e.g. 0 Fires in fire_assessmentv2.csv implies the corresponding secondary forest pixels experienced 0 fires throughout the analysis period. The folder also contains the output regrowth models seen in Figure 1 in the format "<strong>regrowth_model_<driver_threshold>.RData" </strong>where driver_threshold refers to the driving variable name and the associated threshold limit for the given driver.</li> <li>Zipped folder:<strong> Fig2_regions_outline.zip</strong> - contains the boundaries of the 4 regions identified in Figure 2a of the main paper in a shapefile (.shp) format and the corresponding file formats needed to produce and load a shapefile. </li> <li>Zipped folder: <strong>Fig1g_2b_e_variable_importance.zip</strong> - contains the output files of the random forest analysis assessing the variable importance for the whole Amazon ("whole_Amazon" subfolder) and for the different regions identified in Figure2a. Files are given as .RDS files that can be loaded in R and the corresponding figures produced using the script "Fig1g_2b_e_plot.R". Files start with the region of interest e.g. "whole_Amazon" or "NE_sector". Middle part of the filename - importance_conditionalTrue/False - this determines whether the importance was calculated using the conditional permutation (True) or not (False). The end of the file name - seed<NUM> - denotes the number of the random seed that was set to extract the sample data. e.g. whole_Amazon_2500_cforest_important_conditionalTrue_seed200.RDS - shows the conditional permutation importance assessment using a sample size of 2500 when the setseed parameter was set to 200 to extract a random sample representing the whole Amazon. The remaining files are the random forest output - as .RDS file. Please note the code to produce the random forest model and the importance assessment has not been included here - this code takes multiple days to run, so only the input and outputs have been included here. Please contact the corresponding author (see end) for more information on this. </li> <li>Zipped folder: <strong>Fig3_data_input.zip</strong> - all the files needed to produce Figure 3a-d of the main paper. Set the working directory to folder containing the file and use the script "Fig3_plot.R" to run (see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 3 - these files are in the format "<strong><REGION>-Group.csv</strong>". See bullet point 1 for explanations for the columns in the file. Again column E -"threshold" denotes the code used to identify the the 4 subclasses of regrowth seen in the Figure. Where 11 = No disturbance; 12 = Only burning; 21 = Only (multiple) deforestations; 22 = Both burning and multiple deforestations as disturbance. The code takes data in AGB and converts to AGC. The folder also contains the output regrowth models seen in Figure 3 in the format <strong>"regrowth_model_<region_disturbance_type>.RData" </strong>where region_disturbance refers to the region and the type of disturbance experienced. </li> <li> Zipped folder: <strong>Fig4_5_carbon_sink_2017.zip </strong>- Contains two subfolders: a) <strong>Map_aggre_0.1deg</strong> -this folder contains .tiff files (and associated files) of the losses, gains and net change in AGC between 2016 - 2017 in secondary forests in Amazonia - this has been aggregated to 0.1 degree grid cells so each cell contains the total sum of the losses/gains experienced by secondary forests in that 0.1degree grid cell. b) <strong>secondary_forest_by_region_and_disturbance </strong>- this folder contains .tiff files (and associated files) of the secondary forest data at the original resolution (30m) for 2016 and 2017 split up according to the regions identified in Figure 2, and the type of disturbance (if any). The associated files include a .dbf file which includes additional data [read "README.txt" file in folder] - upon loading the data in a GIS software - the age of the secondary forest pixel will be displayed - open the attribute table to see more data associated with that given pixel e.g. modelled associated AGB for a given pixel. Files in this folder can be used to make Figure 4d and Figure 5 - see script "Fig4_Fig5_plot.R" in the code repository (see below). </li> </ol> <p><strong>Code: </strong>The corresponding code mentioned here can be access here: <a href="https://github.com/heinrichTrees/secondary-forest-regrowth-amazon-public">heinrichTrees/secondary-forest-regrowth-amazon-public (github.com)</a></p> <p><strong>Data usage: </strong>When using any code or data in this repository or another related to this study please cite Heinrich et al.2021 and the original paper as well as the DOI of this repository. </p> <p>If you need anything else, please contact the corresponding author: Viola Heinrich (viola.heinrich@bristol.ac.uk)</p>
Run and output files from: Holocene population expansion of a tropical bee coincides with early human colonisation of Fiji rather than climate change
<p><span><span><span><span><span><span><span><span><span><span><span>There is substantial debate about the relative roles of climate change and human activities on biodiversity and species demographies over the Holocene. In some cases, these two factors can be resolved using fossil data, but for many taxa such data are not available. Inferring historical demographies of taxa has become common, but the methodologies are mostly recent and their shortcomings often unexplored. The bee genus <i>Homalictus</i> is developing into a tractable model system for understanding how native bee populations in tropical islands have responded to past climate change. We greatly expand on previous studies using sequences of the mitochondrial gene COI from 474 specimens and between 171 and 3,928 autosomal (DArTSeq) SNP loci from 19 specimens of the native Fijian bee, <i>Homalictus fijiensis</i> (Perkins & Cheesman, 1928), to explore its historical demography using coalescent and mismatch analyses. We ask whether past changes in demography were human- or climate-driven, while considering analytical assumptions. We show that inferred changes in population sizes are too recent to be explained by past climate change. Instead we find that a dramatic increase in population size for the main island of Viti Levu coincides with increasing occupation by humans and their modification of the environment. We found no corresponding change in bee population size for another major island, Kadavu, where human populations and agricultural activities have been historically very low. Our analyses indicate that molecular approaches can be used to disentangle the impacts of humans and climate change on a major tropical pollinator and that stringent analytical approaches are required for reliable interpretation of results. </span></span></span></span></span></span></span></span></span></span></span></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.