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1,566 results for “decline”
Mark-Recapture of Rodent and Shrew Populations in a Declining Hemlock Stand at Harvard Forest 2012
Eastern Hemlocks (Tsuga canadensis) are foundation species, which are known to have a large influence on the species composition and ecosystem dynamics. The purpose of this study was to understand how rodent species richness and composition differed among different hemlock treatments consisting of intact forest, logged forest, and invaded hemlock stands in the Harvard Forest of Petersham, MA. Sherman live traps were arranged on 7x7m grids covering 0.49ha in four different hemlock treatments that were established in 2003: 1) the logged treatment, where commercial trees were removed 2) the girdled treatment, where the hemlocks were girdled using a chainsaw, thus killing the trees, and mimicking the effects of the woolly adelgid, an invasive insect 3) the hemlock control which is where hardwoods are at least 70% hemlocks, and 4) the hardwood control, where other hardwood species are dominate. Animals were marked and recaptured from June-July. Using Schnabel methods for population estimate, there appeared to be a shift in the population from more abundant Gapper’s Red-backed vole, Clethrionomys gapperi in the logged and girdled treatments to white-footed and deer mice (Peromyscus spp) in the hemlock and hardwood control plots. This shift in population may indicate that hemlocks support Peromyscus spp over voles. The species richness and overall population dynamic of these rodents surveyed may lead to a greater understanding as to the potential affect they may have on the seed dispersal in these plots and could account for many interactions between the vegetation and the animals also present.
White Pine Needle Decline in Walden Woods and Weston MA 2017-2018
White Pine Needle Decline (WPND) is a suite of four fungal pathogens that attack third, second and in extreme cases first year needles of eastern white pine (Pinus strobus). Premature needle shedding reduces photosynthetic activity and in turn reduces growth rates and overall health of the eastern white pine, an ecologically and economically valuable species in the Northeast United States. Our long-term forest dynamics plots in Weston and Walden Woods are ideal for monitoring these pathogens’ effects on overstory and understory pine. The unique aspect of our study sites is the dense population of understory pine. Many of our plots are typical old-field white pine stands and are densely stocked from lack of cutting. Densely stocked stands have been shown to be more affected by WPND than more open stands (McIntire, 2017).
Monitoring Amphibians in the Declined Hemlocks at Harvard Forest 2013-2014
Disturbances such as outbreaks of nonnative insects and pathogens can devastate unique habitats and directly reduce biodiversity. The foundation tree species Tsuga canadensis (eastern hemlock) is declining due to infestation by the nonnative insect Adelges tsugae (hemlock woolly adelgid). The decline and expected elimination of hemlock from northeastern US forests is changing forest structure, function, and assemblages of associated species. We assessed changes in occupancy, detection probability, and relative abundance of two species of terrestrial salamanders, Plethodon cinereus (eastern red-back salamander) and Notopthalmus viridescens viridescens (eastern red-spotted newt), in the experimental removal of T. canadensis at Harvard Forest. Four treatments (logging, girdling, hemlock control and hardwood control) have been applied and replicated in eight 0.81-ha plots. Salamanders were sampled under cover boards and using visual encounter surveys in June-July of 2013 and 2014. Removal of the hemlock canopy increased occupancy of P. cinereus but significantly reduced its estimated detection probability and abundance. Estimated abundance of N. v. viridescens also declined dramatically after canopy manipulations. Our results suggest that ten years after hemlock loss due to either the adelgid or pre-emptive salvage logging, and 50-70 years later when these forests have become mid-successional mixed deciduous stands, that the abundance of these salamanders likely will be less than 50% of their abundance in current, intact hemlock stands.
Structure of Ant Communities in Declining Hemlock Stands at Harvard Forest 2003
In biomass and ecological dominance, ants are the most important invertebrate taxon in terrestrial ecosystems and they can alter significantly fundamental processes and dynamics of soil ecosystems. Relative to deciduous stands, hemlock stands are depauperate in ant species that are linked to differences in rates of soil turnover and nutrient mineralization between these forest types. In both hemlock and deciduous stands, we will document ant species richness and abundance; assess their role in soil nutrient cycling; determine temporal trajectories of ant community assembly as hemlock declines following woolly adelgid infestation, and is subsequently replaced by birch; and discover how these trajectories influence nutrient availability during this transition. For more details see: Ellison, A. M., J. Chen, D. Dz, C. Kammerer-Burnham, and M. Lau. 2005. Changes in ant community structure and composition associated with hemlock decline in New England. Pages 280-289 in B. Onken and R. Reardon, editors. Proceedings of the 3rd Symposium on Hemlock Woolly Adelgid in the Eastern United States. US Department of Agriculgure - US Forest Service - Forest Health Technology Enterprise Team, Morgantown, West Virginia.
AMOC reconstruction between 1981 and 2016 from hydrographic data using an empirical linear regression model from Worthington, E. L., Moat, B. I., Smeed, D. A., Mecking, J. V., Marsh, R., and McCarthy, G. D.: A 30-year reconstruction of the Atlantic meridional overturning circulation shows no decline, Ocean Sci., 17, 285–299, https://doi.org/10.5194/os-17-285-2021, 2021.
<p>Dataset used to create Figure 8 in Worthington et al., 2021 (https://doi.org/10.5194/os-17-285-2021). Details of the data and methods can be found in the journal article.<br> <br> Worthington, E. L., Moat, B. I., Smeed, D. A., Mecking, J. V., Marsh, R., and McCarthy, G. D.: A 30-year reconstruction of the Atlantic meridional overturning circulation shows no decline, Ocean Sci., 17, 285–299, <a href="https://doi.org/10.5194/os-17-285-2021">https://doi.org/10.5194/os-17-285-2021</a>, 2021.</p>
Recent Upper Colorado River Streamflow Declines Driven by Loss of Spring Precipitation
<div> <div> <p>The dataset accompanying the manuscript titled "Recent Upper Colorado River Streamflow Declines Driven by Loss of Spring Precipitation" provides comprehensive information on streamflow patterns in the Colorado River since 2000. The dataset is needed to run the analysis available on GitHub available <a href="https://github.com/dlhogan97/Spring-Precipitation-Effect-CO-River.git">here</a>. This is version 2, please use this version for the most up-to-date results.</p> <p><strong>Please read the accompanying README (available in the README.md file) for individual file descriptions and file nesting strategy that should be employed to easily reproduce this analysis.</strong></p> <p>The dataset covers a range of variables related to streamflow and precipitation, including but not limited to discharge measurements, seasonal variations, and relevant meteorological data. The primary focus of the dataset is to elucidate the observed streamflow deficits in the Colorado River, attributing these changes to decreased spring precipitation.</p> <p>Key features of the dataset include:</p> <ul> <li> <p>Time Coverage: The dataset spans a specified time range that aligns with the investigation into recent streamflow deficits in the Colorado River between 1964 and 2022.</p> </li> <li> <p>Spatial Scope: It includes data from relevant monitoring stations along within the Upper Colorado River, but focusing in the hydrologically vital headwater regions, providing a spatially distributed perspective.</p> </li> <li> <p>Variables: The dataset encompasses a variety of variables essential for understanding streamflow dynamics, with a particular emphasis on the impact of reduced spring precipitation.</p> </li> </ul> <p>Researchers and stakeholders interested in hydrological patterns, climate-driven changes, and water resource management in the Colorado River Basin will find this dataset valuable. It serves as a foundational resource for reproducibility, further analysis, and collaboration within the scientific community. The dataset is deposited on Zenodo to facilitate open access, sharing, and citation for broader research endeavors.</p> </div> </div>
Code for "New land-use-change emissions indicate a declining CO2 airborne fraction"
<p>Data and programming scripts for reproducing the results from the Nature publication titled:</p> <p>"New land-use-change emissions indicate a declining CO2 airborne fraction".</p> <p>Authors: Margreet J. E. van Marle*, Dave van Wees*, Richard A. Houghton, Robert D. Field, Jan Verbesselt, and Guido R. van der Werf<br> * These authors contributed equally.</p> <p>DOI: https://doi.org/10.1038/s41586-021-04376-4</p> <p> </p> <p>This dataset includes the following (All files are preceded by "Marle_et_al_Nature_AirborneFraction_"):</p> <p>- "Datasheet.xlsx": Excel dataset containing all annual and monthly emissions and CO2 time series used for the analysis, and the resulting airborne fraction time series.</p> <p>- "Script.py":<br> BEFORE RUNNING THE SCRIPT: change the 'wdir' variable to the directory containing the provided script and files.<br> NOTE: This script requires the Python module: 'pymannkendall'<br> Python script used for reproducing the results and figures from the paper. The provided Datasheet.xlsx file and the .zip and .npz files are required for this program. In case all these files are found by the script, it should run within several seconds. Successful execution of the script will save Figures 1-4 from the main text and print the data from Table 1. In case script execution takes longer, please check if the .xlsx, .zip and .npz files are correctly present in the assigned 'wdir' directory. Otherwise the script will start recalculating these files, which might take a while (see notes below).</p> <p>- "MC10000_MK_ts_TRENDabs.zip": .zip file containing all results from the Monte-Carlo simulation for trend estimation for Figure 3 (calculated using Python function 'calc_AF_MonteCarlo()'). This .zip file contains multiple .npz files for different emission scenarios and data treatments. This .zip file is managed by the Python script function 'calc_AF_MonteCarlo_filemanager()', there is no need to unzip the file manually. In case the .zip file is not found by the Python script (e.g. because the .zip file was unpacked manually and deleted), the program will start recalculating and save a new .zip file. This can take several minutes dependent on the computer used. Recalculated results could differ very slightly due to the random factor in the Monte-Carlo approach, even though the 10,000 iterations bring this variation to a minimum.</p> <p>- "MC1000_MK_run50x50_TRENDabs.npz": .npz file containing the Monte-Carlo results used for producing Figure 4 (calculated using Python function 'calc_AF_MonteCarlo_ARR()'). In case the .npz file is not found by the Python script (e.g. because it was deleted or not downloaded), the program will start recalculating and save a new file. This can take around 30 hours(!) dependent on the computer used. Recalculated results could differ slightly due to the random factor in the Monte-Carlo approach.</p> <p>- "tol_colors.py": Additional Python module used in script.py, required for producing the colors used in the Main text figures. Source: https://personal.sron.nl/~pault/</p> <p>- Figure files: Figures 1-4 from the Main text saved as .pdf files. Figure 3 is saved as three independent panels. The Figures are also reproduced by script.py if executed successfully.</p> <p> </p>
Eco-evolutionary processes underlying early warning signals of population declines
<p>Datasets for the paper appearing in Journal of Animal ecology : "Eco-evolutionary processes underlying early warning signals of population declines". Also GitHub repository link :<a href="https://github.com/GauravKBaruah/ECO-EVO-EWS-DATA">https://github.com/GauravKBaruah/ECO-EVO-EWS-DATA</a></p>
Below-ground hydraulic constraints during drought-induced decline in Scots pine
<p>Dataset from the paper 'Below-ground hydraulic constraints during drought-induced decline in Scots pine'.</p> <p><strong>Files:</strong></p> <p>DOY refers to day of year 2012, idtree is tree identity and Class is defoliation class. Tree characteristics can be found in the supplementary materials of the paper. Variables are expressed in the same units as in the paper.</p> <p><em>WaterPotentials.csv</em> - water potential data (predawn, PD, midday MD, difference)</p> <p><em>SapFlowDeltaPResistbc.csv</em> - daily sap flow per unit leaf area (Jl_daily), delta pressure (deltaP), VPD,SWC, belowcrown resistance (r_bc).</p> <p><em>Resistbc_percent.csv</em> - below-crown resistance as a percentage of total tree resistance</p> <p> </p>
Rodent declines track regional climate variability in North American drylands
Regional long-term monitoring can enhance the detection of biodiversity declines associated with climate change, improving future projections by reducing reliance on space-for-time substitution and increasing scalability. Rodents are diverse and important consumers in drylands, which cover ~45% of Earth’s land surface and face increasingly drier and more variable climates. Here, we analyzed abundance data for 22 rodent species across grassland, shrubland, ecotone, and woodland habitats in the southwestern USA. We captured two time series: 1995-2006 and 2004-2013 that coincide with phases of the Pacific Decadal Oscillation (PDO), which influences drought in southwestern North America. Regionally, rodent species diversity declined 20-35%, with greater losses during the later time period. Abundance also declined regionally, but only during 2004-2013, with losses of ~5% of animals captured. During the first time series (PDO wet phase), plant productivity outranked climate variables as the best regional predictor of rodent abundance for 70% of taxa, whereas during the second period (dry phase), climate best explained rodent abundance for 60% of taxa. Temporal dynamics in rodent diversity and abundance differed spatially among habitats and sites, with the largest declines in woodlands and shrublands of central New Mexico and Colorado. Both habitat type and phase of the PDO modulated which species were winners or losers under increasing drought and amplified interannual variability in drought. Fewer taxa were significant winners (18%) than losers (30%) under drought, but the identities of winners and losers differed among habitats for 70% of taxa. Our results suggest that the sensitivities of rodent species to climate contributed to regional declines in diversity and abundance during 1995 - 2013. Whether these changes portend future declines in drought-sensitive consumers in the southwestern USA will depend on the climate during the next major phase of the PDO.
Data and code from: Insect biomass decline scaled to species diversity: General patterns derived from a hoverfly community
<p>To study changes in flying insect communities, and hoverflies in particular, malaise trap samples from a German site were compared between two years (Hallmann et al. 2020). The data files deposited here contain data obtained from six malaise traps in the Wahnbachtal (North Rhine-Westphalia, Germany, 50.851944N, 7.320833E) that were deployed in 1989 and again in 2014, at the exact same locations. Traps were situated in wet meadows as well as tall perennial meadows, in close proximity to shrub corridors, to forest–grassland borders, and to the Wahnbach River and surrounded by agricultural land, essentially a rather heterogeneous habitat. The Wahnbach River and the greater part of the valley are protected for watershed purposes and are subject to nature conservation management by the Wahnbach Talperrenverband. Hence, several restrictions apply to safeguard against water contamination.</p> <p>Total insect biomass collected with these traps was already included in Hallmann et al. (2017), but here we focus on additional information: the abundance and richness of hoverflies (Syrphidae) in each of the collected samples (pots). Methodologies of collection are described in Sorg (1990), Schwan et al. (1993), Sorg et al. (2013), Hallmann et al. (2017), and Ssymank et al. (2018). In brief, malaise traps were deployed throughout the growing season and operated continuously (day and night). Malaise trap construction (e.g., size, material, colouring, and ground sealing) and placing (e.g., positioning, orientation, and slope of the locations) were standardised in all aspects. Insect samples were preserved in 80% ethanol solution. Catches of the six traps investigated in the present study were emptied regularly: On average exposure intervals were 7.0 d (SD = 0.5) in 1989 and 16.7 d (SD = 5.6) in 2014. Across the six traps in 2014 the total exposure time (in number of days) was 42% higher compared to 1989. All collected samples (n = 196) were used in the present analysis with in total 19,604 individual hoverflies counted, distributed over 162 species and 59 genera.</p> <p>To assess how environmental conditions have changed over the 25 year, several additional datasets were assembled. Climatic<br> data were obtained from 169 climatic stations and were used to interpolate daily weather variables to each trap location, using spatiotemporal kriging. These steps are described in detail in Hallmann et al. (2017).</p> <p>Our analysis (see R code) consists of three components. First, we considered total abundance, species richness, and species diversity, at two temporal scales: pooled per year, i.e., across the sampling season, and seasonally (i.e., per day), and we compared these metrics between 1989 and 2014. Second, we examined how total flying biomass (i.e., the weight of all trapped insects, of which hoverflies are only a small proportion) related to total abundance as well as species richness of hoverflies. Third, we derived persistence probabilities and population growth rate trends per species, to examine interspecific variation in these parameters.</p> <p>Descriptions of the deposited files:</p> <p><strong>Groups.csv</strong><br> MF_NR = identifier of each of the six malaise trap locations<br> yrf = year of sampling<br> pot = sample identifier<br> dt = number of sampling days<br> from.dnr = day-of-the-year on which a pot was attached to a malaise trap<br> to.dnr = day-of-the-year on which a pot was collected from a malaise trap<br> mean.daynr = mean day-of-the-year of the sampling period<br> Nspec = number of different hoverfly species found in a pot<br> Nind = number of hoverfly individuals found in a pot</p> <p><strong>Counts.csv</strong><br> A matrix of counts of individual hoverflies per pot per species. The 196 rows represent the pots in the same order as in the file 'Groups.csv'. The columns represent the 162 different hoverfly species found. The scientific species names are indicated in the column headers.</p> <p><strong>PairedData.csv</strong><br> pot = sample identifier<br> JAHR = year of sampling<br> MF_NR = identifier of each of the six malaise trap locations<br> dt = number of sampling days<br> from.dnr = day-of-the-year on which a pot was attached to a malaise trap<br> to.dnr = day-of-the-year on which a pot was collected from a malaise trap<br> NI = number of hoverfly individuals found in a potbiomass.daily<br> NSP = number of different hoverfly species found in a pot<br> biomass.daily = daily fresh weight [gram] of flying insects: total fresh weight in a pot divided by the number of sampling days.</p> <p><strong>ModelFrame.csv</strong><br> MF_NR = identifier of each of the six malaise trap locations<br> yrf = year of sampling<br> pot = sample identifier<br> dt = number of sampling days<br> from.dnr = day-of-the-year on which a pot was attached to a malaise trap<br> to.dnr = day-of-the-year on which a pot was collected from a malaise trap<br> mean.daynr = mean day-of-the-year of the sampling period<br> plot = identifier of each of the six malaise trap locations<br> date = date for which the weather variables are interpolated<br> daynr = day-of-the-year for which the weather variables are interpolated<br> altitude = altitude [m] of the malaise trap locations<br> year = year of sampling<br> temperature = interpolated temperature [degrees Celsius]<br> precipitation = interpolated precipitation [mm per day]<br> wind.speed = interpolated wind speed [m/s]</p> <p><strong>Data_Rcode.pdf</strong><br> This pdf provides the R-code behind the analysis of the Hoverfly data. Three datasets are provided along with this R-code document, namely "Counts.csv", "Groups.csv", "PairedData.csv" and "ModelFrame.csv". Additionally, the BUGS-code ""syrphidModel.jag" is required for running the daily-activity model in JAGS.</p> <p><strong>syrphidModel.jag</strong><br> This BUGS-code is required for running the daily-activity model in JAGS.</p>
Weekly county-level pollution data for China from Zhang, Carleton, Lin, and Zhou (accepted, Nature Sustainability), "Estimating the role of air quality improvements in the decline of suicide rates in China"
<p>This dataset contains weekly, county-level air pollution data for 2,839 counties from 2013 to early 2018. These data are used and described in Zhang, Carleton, Lin, and Zhou (accepted, <em>Nature Sustainability</em>), "Estimating the role of air quality improvements in the decline of suicide rates in China". When the paper is published a link to the manuscript will be added here. </p> <p>The manuscript Methods section details data construction. In summary, these county-level observations are obtained from monitoring stations maintained by the China National Environmental Monitoring Center (CNEMC), which is affiliated with the Ministry of Ecology and Environment of China. CNEMC began publishing hourly air pollution data in 2013, including the Air Quality Index, PM2.5, PM10, ozone, sulfur dioxide, nitrogen dioxide, and carbon monoxide. We average hourly data to the station-day level and use inverse-distance weighting with a radius of 200km to convert data from station to the county level. We average across days to generate county-level weekly values. Any missing station-hour observations in the raw data are omitted in this spatial and temporal aggregation. Our main analysis relies on PM2.5, but all pollutants are released here.</p>
Pacific salmon population time-series dataset to support Appendix S1: Data and additional information on declines of Pacific Salmon
<p>Dataset used to support the main paper 'Protecting our coast for everyone’s future: Indigenous and scientific knowledge support marine spatial protections proposed by Central Coast First Nations in Pacific Canada' by Reid et al. 2022. Dataset cited in Appendix S1 regarding trends in adult salmon abundances in the Central Coast. The data were as compiled by Will Atlas from the <a href="https://wildsalmoncenter.org/">Wild Salmon Center</a> to describe trends in the abundance of adult salmon returning to the Central Coast, which is the sum of escapement and harvest, as derived from the following sources:</p> <ol> <li>Escapement data from DFO: <a href="https://open.canada.ca/data/en/dataset/c48669a3-045b-400d-b730-48aafe8c5ee6">NuSEDS-New Salmon Escapement Database System - Open Government Portal (canada.ca)</a></li> <li>Harvest rates estimated by Karl English and colleagues and available at: <a href="https://data.salmonwatersheds.ca/data-library/">Salmon Watersheds Program - Data Library</a>.</li> <li>Information on total harvest that is reported in the DFO post season review (DFO 2020).</li> </ol>
Lizards from warm and declining populations are born with extremely short telomeres
<p>These two datasets report the information at the populational ("Population_Biogeography2017-2018.csv") and individual ("Telomere_Zootocavivipara_2015-2017.csv") levels. At populational level, we studied the covariation of multiple biogeographic measures to obtain an integrative index of population extinction risk. At individual level, we examined what factors best explained the variation in lizard telomere length.</p> <p>We also uploaded the R code ("DataAnalysis_Telomerelizards_AndreazDupoue.R") used to analyse these data, in which we detailed all variables.</p>
Data from: Moth species richness and diversity decline in a 30-year time series in Norway, irrespective of species' latitudinal range extent and habitat
<p>Data from:</p> <p>Burner, R., V. Selås, S. Kobro, R. Jacobsen, A. Sverdrup-Thygeson. 2021. Moth species richness and abundance decline in a 30-year time series, irrespective of species’ latitudinal range extent and habitat. <em>Journal of Insect Conservation</em><br> </p> <p>Current contact info for corresponding author: Ryan C. Burner, rburner[at]usgs.gov</p> <p> </p> <p>These data consist of a 30-year time series (1984 to 2013) of moth captures from a single site in southeast Norway, along with trait data for many of the species and climate data for the site. The moths were collected and identified by Sverre Kobro for the entire 30-year period and we are grateful for his efforts. </p> <p> </p> <p>Abstract from manuscript:</p> <p><strong>Introduction</strong></p> <p>Insects are reported to be in decline around the globe, but long-term datasets are rare. The causes of these trends are elusive, with land use change and climate change among the top candidates. Yet if species traits can predict rates of population change, this can help identify underlying mechanisms. If climate change is important, for example, northern species may decline as southern species expand. Land use changes, however, may impact species that rely on certain habitats.</p> <p><strong>Aims and Methods</strong></p> <p>We present 30 years of moth captures (comprising 85,149 individuals of 885 species) from a site in southeastern Norway to test for population trends that are correlated with species traits. We use time series analyses and joint species distribution models combined with local climate and habitat data.</p> <p><strong>Results and Discussion</strong></p> <p>Species richness and abundance declined by 10.1% and 13.8% per decade, respectively. Capture rates declined for 19% of species during this time as well, though 6% have increased. Annual summer weather is correlated with annual rates of abundance change for many species. But, opposite to a general expectation, many species in our study responded negatively to increasing summer temperatures. Surprisingly, neither species’ northern range limits nor the habitat in which their primary food plants grow are strong predictors of their rates of change, or their responses to climatic factors. However, species with more southerly distributions are less likely to be declining. Complex and indirect effects of both land use and climate change may play a role in these declines.</p> <p><strong>Implications for insect conservation</strong></p> <p>Our results provide additional evidence for long-term declines in insect abundance. The multifaceted causes of population changes may limit the ability of species traits to reveal which species are most at risk. </p> <p> </p> <p><strong>ACKNOWLEDGEMENTS</strong></p> <p>Thanks to J. Fjelddalen, who helped with geometrid moth identifications. This project was supported by internal funding from the Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences.</p> <p> </p>
Data and R scripts for analyses of declines in invertebrate species from the Gulf of Maine, USA, 1997 - 2018
Data files and R scripts are for the analyses that are presented in an article that is under revision for Biology Communications. The title of the article is: Declines over the last two decades of five key invertebrate species found on rocky intertidal shores throughout the western North Atlantic. The three data files contain the abundances of four gastropod species and the recruitment of barnacles and mussels from 1997 to 2018, monthly temperature data from three buoys from 2001 to 2018, and pH and aragonite saturation state from 1997 to 2014. R scripts include details of Bayesian estimates for Poisson regressions of species over time, clean-up of environmental data, imputation of missing environmental data and analyses of species versus environmental parameters.
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.
Supplementary data and code from: Significant decline in habitat specialists in semi-dry grasslands over four decades
<h2>Supplementary code and data to the article:</h2><p>Klinkovská K., Sperandii M. G., Trávníček B. & Chytrý M. (2023) Significant decline in habitat specialists in semi-dry grasslands over four decades. Biodiversity and Conservation. <a href="https://doi.org/10.1007/s10531-023-02740-6">https://doi.org/10.1007/s10531-023-02740-6</a></p><h3>Data</h3><p>The data contain plant species composition data from resurveyed vegetation plots in the Central Moravian Carpathians (Czech Republic, 49°06'04''–49°13'31''N, 16°56'58''–17°20'47''E). The dataset comprises 90 vegetation plots first surveyed in 1985 and 1986 by Bohumil Trávníček (Trávníček 1987), and resurveyed in 2022 by Klára Klinkovská. Of these, 40 were inside protected areas and 50 were outside. To locate the historical plots as accurately as possible, a description of the location of each plot was used along with information on slope, aspect, elevation, and dominant species. In 2022, the geographical coordinates of each plot were measured using GPS with a location uncertainty of 3–5 m. All plots were squares of 16 m2.</p><p>The total percentage cover of vascular plants and bryophytes was recorded in each plot, and cover of individual vascular plant species was estimated using the seven-grade Braun-Blanquet scale in the 1980s and the nine-grade Braun-Blanquet scale in 2022 (Westhoff and van der Maarel 1978). The nine-grade scale divides degree 2 of the seven-grade scale into three grades, while the scales remain compatible.</p><p>In 2022, soil samples were collected from four places approximately in the middle of each quarter of the plot, below the litter layer at a depth of 5–10 cm. Mixed samples from each vegetation plot were dried at room temperature and sieved. A suspension with distilled water (weight ratio 1:2.5) was shaken in the Biosan PSU-10i orbital shaker for 5 minutes at 280 rpm and, after 5 hours, soil pH was measured using the HACH HQ40D digital multimeter.</p><p>The header data structure follows that of the ReSurveyEurope Database (<a href="http://euroveg.org/eva-database-re-survey-europe">http://euroveg.org/eva-database-re-survey-europe</a>).</p><p>The data on species composition and environmental variables are provided in two formats:</p><p>Turboveg 2 database (see <a href="https://www.synbiosys.alterra.nl/turboveg/">https://www.synbiosys.alterra.nl/turboveg/</a>) TurbovegDbBackup_Cz_0019_47.zip (<a href="https://euroveg.org/resurvey_metadata/CZ_0019_047.pdf">https://euroveg.org/resurvey_metadata/CZ_0019_047.pdf</a>). For using this dataset in Turboveg, the database dictionary (TurbovegDdBackup_Default_dictionary.zip) and the species list (TurbovegSlBackup_Czechia_slovakia_2015.zip) must be installed.</p><p>Three CSV files with columns separated by commas:</p><p>Klinkovska_et_al_semi_dry_grasslands_S_Moravia_species.csv contains the percentage covers of plant species in the plots, which are mid-values for cover-abundance categories of the seven-grade Braun-Blanquet scale. Plant nomenclature was harmonised according to Danihelka et al. (2012).</p><p>Klinkovska_et_al_semi_dry_grasslands_S_Moravia_species_data.csv contains ecological indicator values and information on the Red List status (Grulich 2017), alien species (Pyšek et al. 2022) and species diagnostic for the alliances Cirsio-Brachypodion pinnati and Bromion erecti (Chytrý et al. 2007).</p><p>Klinkovska_et_al_semi_dry_grasslands_S_Moravia_head.csv contains header data for the vegetation plots.</p><p>These data are also stored in the Czech National Phytosociological Database (Chytrý & Rafajová 2003; <a href="https://botzool.cz/vegsci/phytosociologicalDb">https://botzool.cz/vegsci/phytosociologicalDb</a>) and the ReSurveyEurope database (Knollová et al. 2023; <a href="http://euroveg.org/eva-database-re-survey-europe">http://euroveg.org/eva-database-re-survey-europe</a>).</p><h3>Scripts</h3><ul><li>Script_1.R: Transitions between vegetation types, changes in species richness, proportions of threatened species, specialists and alien species per plot</li><li>Script_2.R: Changes in species composition and ecological indicator values</li><li>Script_3.R: Temporal beta-diversity indices</li></ul>
Groundwater level data, aquifer system boundaries, and supplementary tables associated with Jasechko, S. et al. Rapid groundwater decline and some cases of recovery in aquifers globally. Nature, doi.org/10.1038/s41586-023-06879-8 (2024).
<p>Groundwater level data, aquifer system boundaries, and Supplementary Tables associated with Jasechko, S., Seybold, H., Perrone, D., Fan, Y., Shamsudduha, M., Taylor, R.G., Fallatah, O., Kirchner, J.W. Rapid groundwater decline and some cases of recovery in aquifers globally. Nature, https://doi.org/10.1038/s41586-023-06879-8 (2024).</p>
ScienceDex guides
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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.