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455 results for “dynamic response”
Impacts of microplastics on wetland ecosystem dynamics: a mesocosm study of trophic interactions and community responses, 2021-2025
This dataset documents a mesocosm experiment conducted to evaluate the ecological impacts of microplastics (MP) on wetland communities representative of eastern USA wetlands. The study focused on key organisms across trophic levels, including tadpoles (Lithobates pipiens), snails (Helisoma trivolvis), zooplankton (Daphnia pulex), phytoplankton, and periphyton communities, to assess the effects of three microplastic types (low-density polyethylene–LDPE, medium-density polystyrene–PS, and high-density polyester–PES) at two concentrations (1 mg/L and 5 mg/L), alongside a no-microplastic control. Experimental units consisted of 70 mesocosms (19-L buckets) with 10 replicates per treatment, established between July 1–15, 2021, at Binghamton University’s Ecological Research Facility. Response variables included survival and developmental traits (mass, snout-vent length, shell width) of tadpoles and snails, microplastic ingestion, zooplankton abundance, phytoplankton biomass (chlorophyll and phycocyanin concentrations), and periphyton mass. The dataset provides comprehensive measurements of community responses and water quality parameters, offering insights into the ecological consequences of microplastic pollution in wetland ecosystems. This dataset is suitable for researchers studying ecotoxicology, wetland ecology, and the impacts of anthropogenic pollutants on aquatic food webs.
Soil organic carbon and nutrient dynamics in response to anaerobic digestate application to farm fields, Eastern Iowa, 2011-2023
This dataset documents a long-term, field-scale study of anaerobic digestate application on commercial croplands in eastern Iowa, USA. It includes detailed records of digestate composition, application rates, and timing, as well as soil test results collected over a 12-year period (2011–2023) from 14 agricultural fields. The dataset supports analysis of soil organic carbon (SOC), nutrient dynamics, and isotopic composition in response to digestate inputs. It contains 421 georeferenced soil samples, digestate nutrient profiles, field management histories, and spatial boundaries. The data were collected as part of a collaborative effort between researchers at Iowa State University and Sievers Family Farms to evaluate the agronomic and environmental implications of integrating anaerobic digestion into row crop and livestock systems.
DNA methylation dynamics during stress-response in woodland strawberry (Fragaria vesca)
<p><strong>Genome sequence and annotation of Fragaria vesca cv. Reine des Vallées</strong></p> <p>In order to generate a reference genome for Fragaria vesca cv. Reine des Vallées, we used MinIon long-read sequencing data to substitute the <em>F. vesca</em> genome v.4.0.a2 genome. The detailed method used to obtain these results were the following:</p> <p><em>Genome sequencing and assembly NIL Fb2</em></p> <p>Genomic DNA from strawberry plants was extracted by a Hexadecyltrimethylammonium bromide (Cetrimonium bromide, CTAB) modified protocol (Healey, Furtado, Cooper, & Henry, 2014) and purified with Agencourt AMPure XP beads (cat# A63880). Long-read sequencing was performed for the genome assembly; Genomic DNA by Ligation (Oxford Nanopore, cat# SQK-LSK109) library was prepared as described by the manufacturer and sequenced on a MinION for 72 h (Oxford Nanopore).</p> <p><em>Reference genome polishing</em></p> <p>Reads obtained from nanopore were filtered with Filtlong v0.2.1 (<a href="https://github.com/rrwick/Filtlong">https://github.com/rrwick/Filtlong</a>) using --min_mean_q 80 and --min_length 200. Cleaned reads were then aligned to the most recent version of the <em>F. vesca</em> genome v4.0.a2, downloaded from the Genome Database for Rosaceae (GDR) (<a href="https://www.rosaceae.org/species/fragaria_vesca/genome_v4.0.a2">https://www.rosaceae.org/species/fragaria_vesca/genome_v4.0.a2</a>), using minimap2 v2.21 (H. Li, 2018) with parameters -aLx map-ont --MD -Y. The generated BAM file was then sorted and indexed with samtools v1.11 (H. Li et al., 2009). We used mosdepth v0.3.1 (Pedersen & Quinlan, 2018) to verify that coverage on chromosomic scaffolds was over 50 X. Sniffles v1.0.12a (Sedlazeck et al., 2018) with parameters -s 10 -r 1000 -q 20 --genotype -l 30 -d 1000 was used to detect structural variations larger than 30 bp. The VCF files obtained from Sniffles was sorted and filtered with BCFtools v1.14 (Danecek et al., 2021) to keep only structural variants (SV) with smaller than 200,00 bp (we observed that larger SV were most of the time false positive caused by misalignments in regions with gaps or Ns), supported by 10 or more reads and with allelic frequencies above 0.8 (we were interested in homozygous changes). The complete filtering command used is “bcftools view -q 0.8 -Oz -i '(SVTYPE = "DUP" || SVTYPE = "INS" || SVTYPE = "DEL" || SVTYPE = "TRA" || SVTYPE = "INV" || SVTYPE = "INVDUP") && %FILTER = "PASS" && FMT/DV>9 && SVLEN>29 && SVLEN<200000' “</p> <p>From the VCF listing all the structural variants that we detected in our <em>F. vesca </em>accession, we generated a substituted genome version based on the reference <em>F. vesca</em> genome v.4.0.a2. The reference genome was first indexed with samtools faidx v1.11(Danecek et al., 2021) and a sequence dictionary was generated with Picard CreateSequenceDictionary v2.25.6 (<a href="https://broadinstitute.github.io/picard">https://broadinstitute.github.io/picard</a>). The VCF containing the SV produced from our Nanopore sequencing was also indexed with gatk (Van der Auwera GA & O'Connor BD, 2020) IndexFeatureFile v4.2.0.0 (<a href="https://gatk.broadinstitute.org/hc/en-us/articles/360037262651-IndexFeatureFile">https://gatk.broadinstitute.org/hc/en-us/articles/360037262651-IndexFeatureFile</a>). FastaAlternateReferenceMaker v4.2.0.0 (<a href="https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker">https://gatk.broadinstitute.org/hc/en-us/articles/360037594571-FastaAlternateReferenceMaker</a>) was then run with the reference genome and the VCF file to generate a substituted genome representative of our <em>Fragaria</em> accession.</p> <p>As substituting our genome with the detected structural variants changes genomic coordinates, we also corrected the public GFF genome annotation of <em>F. vesca</em> (Y, Pi, Gao, Liu, & Kang, 2019) using liftoff v1.6.1 (Shumate & Salzberg, 2021). Liftoff also detects and annotates duplications within the substituted genome.</p> <p>Transposable elements annotation was carried out using the EDTA transposable element annotation pipeline v. 1.9.6 (S. Ou et al., 2019) on the substituted genome using default parameters<em>.</em></p> <p><strong>Differentially methylated regions</strong></p> <p>The file Stress_vs_control_DMRs.zip file contains the DMRs that were called using the reads submitted to ENA (ERP135585) and obtained as follows:</p> <p>First, bedGraph files from wgbs pipeline were pre-filtered for a minimum coverage of 5 reads using awk command. These output files were then used as input for the EpiDiverse/dmr bioinformatics analysis pipeline for non-model plant species to define DMRs (Nunn <em>et al</em>., 2021) with default parameters (minimum coverage threshold 5; maximum q-value 0.05; minimum differential methylation level 10%; 10 as minimum number of Cs; Minimum distance (bp) between Cs that are not to be considered as part of the same DMR is 146 bp). The pipeline uses metilene v.0.2.6.1 (<a href="https://www.bioinf.uni-leipzig.de/Software/metilene/">https://www.bioinf.uni-leipzig.de/Software/metilene/</a>) for pairwise comparison between groups and R-packages ggplot2 v.3.3.5 and gplots v.3.1.1, for visualization results (Fig. S1). Based on our <em>F. vesca</em> genome transcript annotation and methylation data (overlapped regions with DNA methylation cytosines and DMRs), we detected the methylated genes, promoters, 3’ UTRs, 5’UTR and transposable elements in strawberry. Global DNA methylation and DMR plots were performed with R-package ggplot2. Gene analyses by methylation patterns and analysis of per-family TE DNA methylation profiles were performed with deepTools v.3.5.0 (Ramírez <em>et al</em>., 2014). DMRs comparison between treatments were done by the Venn diagram v.1.7.0 R-package.</p> <p>We produced several genome browsers tracks with DMRs that we integrated in our local instance of JBrowse available at the following url: <a href="https://jbrowse.agroscope.info/jbrowse/?data=fragaria_sub">https://jbrowse.agroscope.info/jbrowse/?data=fragaria_sub</a></p>
The DR-Train dataset: dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh
<p><strong>Note: Downloading the large data file could have a timeout issue. If you cannot directly download it here, please use the following link as a complementary method for getting the data. </strong></p> <p><a href="https://drive.google.com/drive/folders/1oKn7IN7zznQuhwjDCDdjq8r9wHJYBEhj?usp=sharing">https://drive.google.com/drive/folders/1oKn7IN7zznQuhwjDCDdjq8r9wHJYBEhj?usp=sharing</a></p> <p> </p> <p>This dataset contains the dynamic responses (acceleration records) of two passenger trains with corresponding GPS positions, environmental conditions and track maintenance schedules for a light rail network in the city of Pittsburgh, Pennsylvania in the United States of America.</p> <p>In particular, two light rail vehicles were instrumented (identified as LRV4306 and LRV4313): <br> LRV 4306 has 5 acceleration channels, corresponding to the two uni-axial accelerometers inside the train and the three channels of the tri-axial accelerometer on the wheel truck.</p> <p><em>- The last digit of each acceleration file: 1, 2, 3, 4, 5<br> - Corresponding sensor channels: tri-axial x, tri-axial y, tri-axial z, front cabinet uni-axial, back cabinet uni-axial</em></p> <p><br> LRV 4313 has 8 acceleration channels, corresponding to the two uni-axial accelerometer and the two tri-axial accelerometers inside the train.</p> <p><em>- The last digit of each acceleration file: 1, 2, 3, 4, 5, 6, 7, 8<br> - Corresponding sensor channels: front cabinet uni-axial, back cabinet uni-axial, front tri-axial x, front tri-axial y, front tri-axial z, back tri-axial x, back tri-axial y, back tri-axial z.<br> - x longitudinal (vehicle moving direction); y-axis, transverse; z-axis, vertical.</em></p> <p>The dataset contained in this repository is a condensed version of the original raw data. While the accelerometers on the train were sampled continuously, this dataset contains only those measurements for when the train was actually moving along the track (i.e. not idling at a terminal).</p> <p>The data is stored in binary MAT-files (a MATLAB/Octave data format). These files contain MATLAB objects of the class "pass", which is defined in the file pass.m that can be found in the "code" folder. Specifically, two MAT-files named "obj_dic.mat", and found in the "LRV4306" and "LRV4313" folders, contain the "pass" objects of the two trains, respectively.</p> <p>Each category is described in detail. For more detail on the regions of the track, refer to the 'region.fig' file in this folder. The track was divided into distinct regions so that the data over specific sections of track could be compared. These regions were chosen for two reasons: <br> (1) within a region, the train always followed the same track and <br> (2) there are no tunnels in them so the GPS data is relatively consistent. </p> <p>To get started, using MATLAB or Octave try running "main_script.m" in the "code" folder.</p> <p>A data descriptor paper with details of the data collection process was published.</p> <p>Please cite as</p> <p><strong>Liu, J., Chen, S., Lederman, G., Kramer, D. B., Noh, H. Y., Bielak, J., Garrett, J. H., Kovačević, J., & Berges, M. Dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh. Scientific Data, 6, 146. <a href="https://doi.org/10.1038/s41597-019-0148-9">https://doi.org/10.1038/s41597-019-0148-9</a>(2019)</strong></p> <p><strong>Liu, J., Chen, S., Lederman, G., Kramer, D. B., Noh, H. Y., Bielak, J., Garrett, J. H., Kovačević, J., & Berges, M. The DR-Train dataset: dynamic responses, GPS positions and environmental conditions of two light rail vehicles in Pittsburgh. Zenodo, <a href="https://doi.org/10.5281/zenodo.1432702">https://doi.org/10.5281/zenodo.1432702</a>(2018).</strong></p> <p>For questions or suggestions please e-mail Jingxiao Liu <liujx@stanford.edu></p>
Raw data from: "Thermal mismatches explain consumer-resource dynamics in response to environmental warming".
<p>Data from:</p> <p>Álvarez-Codesal, S, Faillace CA, Garreau, A, Bestion, E, Synodinos, AD, & Montoya, JM. 2023. Thermal mismatches explain consumer-resource dynamics in response to environmental warming. Ecology and Evolution.<br> </p> <p>Composed of seven associated datasets:</p> <p>- Algae_Net_Photosynthesis.csv</p> <p>- Daphnia_Ingestion.csv</p> <p>- Algae_Respiration.csv</p> <p>- Daphnia_Ingestion.csv</p> <p>- Daphnia_respiration.csv</p> <p>- Interaction_Strength.csv</p> <p>- Energy_Balance_Ratios_dataset.csv</p> <p> </p> <p>A detailed explanation of the methods is provided in the related Alvarez-Codesal et al. 2023 article, please refer to it for a full understanding of the methods and results.</p> <p>Briefly: our aim was to quantify the impact of warming on consumer-resource interactions, using as consumer <em>Daphnia pulex</em>, and as resources two algae species, <em>Chlamydomonas reinhardtii</em> and <em>Desmodesmus</em> sp.</p> <p>First, we measured thermal dependencies of physiological rates related to energy gain (i.e., ingestion, net photosynthesis) and loss (i.e., respiration) for <em>Daphnia</em> and the algae in basal conditions at eight temperatures. From these, we calculated species energetic balances as net photosynthesis-to-respiration ratio (P/R<sub>r</sub>) for resources, or as ingestion-to-respiration ratio (I/R<sub>c</sub>) for consumers, using predicted values of each (per capita) rate from the models. We used energetic balances as an indicator of how species respond to increasing temperatures, defining intraspecific energetic mismatches when the energetic balance decreases.</p> <p>Second, we inferred interspecific thermal mismatches (inter-TM) by comparing individual energetic balances for both consumer-resource pairs, and identified the thermal mismatch regions, where: 1) trends of energetic balances contrast between the interacting species; and 2) both species reduce their energetic balance with increasing temperature. The inter-TMs were used to increase our qualitative understanding on the outcomes of thermal dependencies of interaction strength.</p> <p>Third, we calculated the natural logarithm of the consumer-resource energetic balance for each interacting pair as the ratio between consumer energetic balance and the resource energetic balance to get qualitative predictions on the trends of interaction strength with temperature.</p> <p>Finally, we measured experimentally thermal dependencies of interaction strength for each consumer-resource pair and verified if our predictions using the thermal mismatches fitted the trends of interaction strengths across temperatures.</p>
The role of fire in the carbon dynamics of the boreal forest I. - Response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach (2003-2100).
The boreal forest contains large reserves of carbon, and across this region wildfire is a common occurrence. To improve the understanding of how wildfire influences the carbon dynamics of this region, methods were developed to incorporate the spatial and temporal effects of fire into the Terrestrial ecosystem Model (TEM). The historical role of fire on carbon dynamics of the boreal region was evaluated within the context of ecosystem responses to changing atmospheric CO2 and climate. These results show that the role of historical fire on boreal carbon dynamics resulted in a net carbon sink; however, fire plays a major role in the interannual and decadal scale variation of source/sink relationships. To estimate the effects of future fire on boreal carbondynamics, spatially and temporally explicit empirical relationships between climate andfire were quantified. Fuel moisture, monthly severity rating, and air temperature explained a significant proportion of observed variability in annual area burned. These relationships were used to estimate annual area burned for future scenarios of climate change and were coupled to TEM to evaluate the role of future fire on the carbon dynamics of the North American boreal region for the 21st Century. Simulations with TEM indicate that boreal North America is a carbon sink in response to CO2 fertilization, climate variability, and fire, but an increase in fire leads to a decrease in the sink strength. While this study highlights the importance of fire on carbon dynamics in the boreal region, there are uncertainties in the effects of fire in TEM simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. Future studies should incorporate the role of dynamic vegetation to more accurately represent post-fire successional pr
Dataset for article: Perakakis P., Idrissi S., Vila J., Ivanov Ch.P. (2012). Dynamical patterns of human postural responses to emotional stimuli. Psychophysiology, 49 (9), pp. 1225–1229
<p>Dataset for article: Perakakis P., Idrissi S., Vila J., Ivanov Ch.P. (2012). Dynamical patterns of human postural responses to emotional stimuli. Psychophysiology, 49 (9), pp. 1225–1229</p>
Reproducing nonlinear seismic response from in-situ soil dynamic parameters: application to the Delaney Park Downhole Array, Alaska
<p>The zip file named 'seismic data at DPDA.zip' contains all the seismic data used in our study.</p> <p>The DEEPSOIL file named 'ground response analysis at DPDA.dp' contains the numerical models used in our study.</p>
Data from: Diversity dynamics of microfossils from the Cretaceous to the Neogene show mixed responses to events
<p>Microfossils have a ubiquitous and well-studied fossil record with temporally and spatially fluctuating diversity, but how this arises and how major events affect speciation and extinction is uncertain. We present the first application of PyRate to a micropaleontological global occurrence data set, reconstructing diversification rates within a Bayesian framework from the Mesozoic to the Recent in four microfossil groups: planktic foraminiferans, calcareous nannofossils, radiolarians and diatoms. Calcareous and siliceous groups demonstrate opposed, but inconsistent, responses in diversification. Siliceous groups increased origination from ~104 Ma, maintaining high rates into the Cenozoic. Calcareous microfossils diversification rates significantly decline across the Cretaceous–Paleogene boundary, while rates in siliceous microfossil groups remain stable until the Paleocene–Eocene transition. Diversification rates in the Cenozoic are largely stable in calcareous groups, whereas the Paleogene is a turbulent time for diatoms. Diversification fluctuations are driven by climate change and fluctuations in sea surface temperatures, promoting selectivity in both microfossil composition and foraminiferal size. Extinctions appear induced by changes in anoxia, acidification, and stratification, while speciation tends to be associated with upwelling, productivity, and ocean circulation. These results show promise for further quantitative analyses in micropaleontological diversity studies and effects of major transitions in the fossil record. Despite extensive occurrence data, regional diversification events were not recovered, neither were some global events. These unexpected results show the need to consider multiple spatiotemporal levels of diversity and diversification analyses, and implies occurrence data sets of different clades may be more appropriate to testing some hypotheses than others.</p>
Peculiar torsion dynamical response of spider dragline silk
<p>These data are related to our paper "Dabiao Liu, Longteng Yu, Yuming He*, Kai Peng, Jie Liu, Juan Guan, and D. J. Dunstan. Peculiar Torsion Dynamical Response of Spider Dragline Silk. Applied Physics Letters, 111 (2017), 013701." In this work, the torsional properties of spider dragline silks from Nephila edulis and Nephila pilipes spiders are investigated by using a torsion pendulum technique. A permanent torsional deformation is observed after even small torsional strain. This behaviour is quite different from that of the other materials tested here, i.e., carbon fiber, thin metallic wires, Kevlar fiber, and human hair. The spider dragline thus displays a strong energy dissipation upon the initial excitation (around 75% for small strains and more for a larger strain), which correspondingly reduces the amplitude of subsequent oscillations around the new equilibrium position. The variation of torsional stiffness in relaxation dynamics of spider draglines for different excitations is also determined. The experimental result is interpreted in the light of the hierarchical structure of dragline silk.</p> <p>This project has received funding from the EU’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 704292.</p>
Figure 3. The effective population size through recent time for 3 in Comparative analyses of past population dynamics between two subterranean zokor species and the response to climate changes
Figure 3. The effective population size through recent time for 3 clades of Gansu zokor (Eospalax cansus).
Dataset article "Demand-Response Control of Electric Storage Water Heaters Based on Dynamic Electricity Pricing and Comfort Optimization"
<p>"README-SupplementaryMaterial.txt" explains the information gathered in each csv files, and including the DHW consumption profiles generated, the hourly electricity pricing for 2022 (Spain), and the experimental data utilized for the validation of the model. </p>
Numerical response of predator to prey: Dynamic interactions and population cycles in Eurasian lynx and roe deer
<p>The dynamic interactions between predators and their prey have two fundamental processes; numerical and functional responses. Numerical response is defined as predator growth rate as a function of prey density or both prey and predator densities [dP/dt = f(N, P)]. Functional response is defined as the kill rate by an individual predator being a function of prey density or prey and predator densities combined. Although there are relatively many studies on the functional response in mammalian predators, numerical response remains poorly documented. We studied numerical response of Eurasian lynx (<em>Lynx lynx</em>) to various densities of its primary prey species, roe deer (<em>Capreolus</em> <em>capreolus</em>), and to itself (lynx). We exploited an unusual natural situation, spanning three decades where lynx, after a period of absence in central and southern Sweden, during which roe deer populations had grown to high densities, subsequently recolonized region after region, from north to south. We divided the study area into seven regions, with increasing productivity from north to south. We found strong effects of both roe deer density and lynx density on lynx numerical response. Thus, both resources and intraspecific competition for these resources are important to understand the lynx population dynamic. We built a series of deterministic lynx–roe deer models and applied them to the seven regions. We found a very good fit between these Lotka-Volterra-type models and the data. The deterministic models produced almost cyclic dynamics or dampened cycles in five of the seven regions. Thus, we documented population cycles in this large-predator-large-herbivore system, which is rarely done. The amplitudes in the dampened cycles decreased towards the south. Thus, the dynamics between lynx and roe deer became more stable with increasing carrying capacity for roe deer, which is related to higher productivity in the environment. This increased stability could be explained by variation in predation risk, where human presence can act as prey refugia, and by a more diverse prey guild that will weaken the direct interaction between lynx and roe deer.</p>
Data from: Diversity dynamics of microfossils from the Cretaceous to the Neogene show mixed responses to events
Open the record for dataset details and reuse information.
Numerical response of predator to prey: Dynamic interactions and population cycles in Eurasian lynx and roe deer
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Dynamic self-organization in fire ant rafts underpins collective longevity and threat responsiveness
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Intermediate habitat fragmentation buffers droughts: How individual energy dynamics mediate mammal community response to stressors
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Plant and soil organic matter responses to ten years of nutrient enrichment in the Nutrient Network:Nutrient Network. A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
Satellite-based habitat monitoring reveals long-term dynamics of deer habitat in response to forest disturbances
<p class="StandardohneEinzug">Disturbances play a key role in driving forest ecosystem dynamics, but how disturbances shape wildlife habitat across space and time often remains unclear. A major reason for this is a lack of information about changes in habitat suitability across large areas and longer time periods. Here, we use a novel approach based on Landsat satellite image time series to map seasonal habitat suitability annually from 1986 to 2017. Our approach involves characterizing forest disturbance dynamics using Landsat-based metrics, harmonizing these metrics through a temporal segmentation algorithm, and then using them together with GPS telemetry data in habitat models. We apply this framework to assess how natural forest disturbances and post-disturbance salvage logging affect habitat suitability for two ungulates, roe deer (<i>Capreolus capreolus</i>) and red deer (<i>Cervus elaphus</i>), over 32 years in a Central European forest landscape. We found that red and roe deer differed in their response to forest disturbances. Habitat suitability for red deer consistently improved after disturbances, whereas the suitability of disturbed sites was more variable for roe deer depending on season (lower during winter than summer) and disturbance agent (lower in windthrow versus bark-beetle-affected stands). Salvage logging altered the suitability of bark beetle-affected stands for deer, having negative effects on red deer and mixed effects on roe deer, but generally did not have clear effects on habitat suitability in windthrows. Our results highlight long-lasting legacy effects of forest disturbances on deer habitat. For example, bark beetle disturbances improved red deer habitat suitability for at least 25 years. The duration of disturbance impacts generally increased with elevation. Methodologically, our approach proved effective for improving the robustness of habitat reconstructions from Landsat time series: integrating multi-year telemetry data into single, multi-temporal habitat models improved model transferability in time. Likewise, temporally segmenting the Landsat-based metrics increased the temporal consistency of our habitat suitability maps. As the frequency of natural forest disturbances is increasing across the globe, their impacts on wildlife habitat should be considered in wildlife and forest management. Our approach offers a widely applicable method for monitoring habitat suitability changes caused by landscape dynamics such as forest disturbance</p>
Calcareous nannofossil size and abundance response to the Messinian Salinity Crisis onset and paleoenvironmental dynamics
<p>The file contains calcareous nannofossils (<em>Helicosphaera carteri, Sphenolithus abies, Umbilicosphaera rotula, Coccolithus pelagicus, Reticulofenestra minuta</em>) biometry data collected in the Messinian Perales section (Sorbas Basin, Spain) and in the Banengo and Pollenzo sections (Piedmont Basin, Italy)</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.