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132 results for “ecological networks”
Soil Organic Matter Mechanisms of Stabilization (SOMMOS) - enhanced soil characterization data from 40 National Ecological Observatory Network (NEON) sites
Soil organic matter (SOM) is a critical linkage among many ecosystem services that sustain our society and life on Earth. It is the primary energy source for microbes and the principal storehouse of water necessary for plant growth. SOM also stores nutrients for plants and sorbs pollutants that otherwise could contaminate food and water supplies. Soils also help regulate climate by storing carbon that would otherwise be released to the atmosphere and contribute to climate change. The SOMMOS project investigated processes in the soil that protect SOM from being decomposed by microbes, processes that increase its sensitivity to environmental changes, and how changes in climate and land management influence the amount and stability of SOM. The project, which was a collaboration between scientists from the National Ecological Observatory Network (NEON), University of Colorado, University of Michigan, Oregon State University, Virginia Polytechnic Institute and State University, and the USDA-Forest Service, took advantage of soil samples collected across NEON, a major NSF investment in environmental monitoring that covers the entire United States. This continental-scale soil sample set was analyzed for a wide array of physical and chemical properties, well beyond those typically measured on such a large-scale sample set, including radiocarbon, extractable metals, organic matter chemistry by pyrolysis-GCMS, liquid extract fluorescence spectroscopy, and more. In addition to this dataset, archived samples are available from the project for sharing with interested researchers.
Metabolism dataset: one year of high-frequency temperature, dissolved oxygen, wind, photosynthetically active radiation observations and low-frequency nutrient data for 58 lakes in the Global Lake Ecological Observatory Network
Understanding controls on primary productivity is essential for describing ecosystems and their responses to environmental change. Lake primary production is strongly controlled by inputs of nutrients and colored dissolved organic matter. While past studies have developed mathematical models of this nutrient-color paradigm, broad empirical tests of these models are scarce. We compiled data from 58 diverse and globally distributed and mostly temperate lakes to test such a model and improve understanding and prediction of the controls on lake primary production. These lakes varied widely in size (0.02-2300 km2), pelagic gross primary production (20-8000 mg C m-2 d-1), and other characteristics. The data package includes high-frequency dissolved oxygen, water temperature, wind speed, and solar radiation data as well as daily estimates of GPP and ER derived from those data. In addition, the data package includes median in-lake and stream concentrations of dissolved organic carbon and total phosphorus for a subset of 18 of those lakes.
National Park Service - South Florida/Caribbean Inventory & Monitoring Network - SARI SET Surface Water level data from Salt River Bay National Historical Park and Ecological Preserve, St. Croix, US Virgin Islands.
Surface water level data (m) was collected in Salt River Bay National Historic Park and Ecological Preserve (SARI) by the South Florida/Caribbean Inventory and Monitoring Network (SFCN) as part of the Soil Elevation Table (SET) vital sign monitoring program. Water level data collected from 2017 to 2024 is included in this dataset. The water level data was collected using HOBOware Onset Water Level Data Loggers. This data-package is complete.
Explosive networking: the role of adaptive host radiations and ecological opportunity in a species-rich host-parasite assembly
<p>Dataset for Cruz-Laufer et al. (2021) Explosive networking: the role of adaptive host radiations and ecological opportunity in a species-rich host-parasite assembly.</p> <p><strong>Abstract: </strong>Many species-rich ecological communities emerge from adaptive radiation events. The effects of this explosive speciation on community assembly remain poorly understood. Here, we explore the well-documented radiations of African cichlid fishes and their interactions with the flatworm gill parasites <em>Cichlidogyrus </em>spp., including 10529 reported infections and 477 different host-parasite combinations collected through a survey of peer-reviewed literature. We assess how evolutionary, ecological, and morphological parameters determine host-parasite meta-communities affected by adaptive radiation events through network metrics, host repertoire measures, and network link prediction. The hosts’ evolutionary history mostly determined host repertoires of the parasites. Ecological and evolutionary parameters determined host-parasite interactions. Generally, ecological opportunity and fitting have shaped cichlid-<em>Cichlidogyrus</em> meta-communities suggesting an invasive potential for hosts used in aquaculture. Meta-communities affected by adaptive radiations are increasingly specialised with higher environmental stability. These trends should be verified across other systems to infer generalities in the evolution of species-rich host-parasite networks.</p>
Dataset and framework for the Open Potential Ecological Network of Tuscany
<p>This repository contains the main output of the related research, specifically: two Open Potential Ecological Networks (OPEN) of Tuscany in the Cytoscape format: "tuscany_potential_directed.cys" and "tuscany_potential_undirected.cys".</p> <p>Please see the "annotations.txt" file to more detailed explanation regarding the content in this repository.</p>
Networking nutrients: how nutrition determines the structure of ecological networks - Dataset
<p>Raw sequencing data and other metadata files are associated with Cuff et al. (2021a, 2022a), available at https://doi.org/10.5281/zenodo.4708418</p> <p>Data/code relating to the macronutrient contents and delineation of tropho-species clusters are associated with Cuff et al. (2021b, 2022b), available at https://doi.org/10.5281/zenodo.5738016</p> <p>Cuff, Jordan P. (2021a). A molecular analysis of the diet and biocontrol potential of spiders in cereal crops - Dataset. <em>Zenodo</em>. doi: 10.5281/zenodo.4708419</p> <p>Cuff, Jordan Patrick, Tercel, M. P., Vaughan, I. P., Drake, L. E., Wilder, S. M., Bell, J. R., … Symondson, W. O. (2021b). Evidence for nutrient-specific foraging of predators under field conditions. <em>Zenodo</em>. doi: 10.5281/zenodo.5738015</p> <p>Cuff, Jordan P., Tercel, M. P. T. G., Drake, L. E., Vaughan, I. P., Bell, J. R., Orozco-terWengel, P., … Symondson, W. O. C. (2022a). Density-independent prey choice, taxonomy, life history and web characteristics determine the diet and biocontrol potential of spiders (Linyphiidae and Lycosidae) in cereal crops. <em>Environmental DNA</em>, in press. doi: 10.1002/edn3.272</p> <p>Cuff, Jordan P., Tercel, M. P. T. G., Vaughan, I. P., Drake, L. E., Wilder, S. M., Bell, J. R., … Symondson, W. O. C. (2022b). Evidence for nutrient-specific foraging of predators under field conditions. <em>Authorea</em>. doi: 10.22541/au.164908092.21266343/v1</p>
Ecological Niche Models, in 2019 and across RCP 2.6, 4.5, and 8.5 scenarios in 2050 and 2100, of 1508 European Marine Species, developed with Artificial Neural Networks, Maximum Entropy, Support Vector Machines, and AquaMaps at 0.5° Resolution
<p>Native ecological niche models of 1508 European species (894 fish and 614 non fish) developed with AquaMaps, Artificial Neural Networks, Maximum Entropy, and Support Vector Machines, for 2019 and under RCP 2.6, 4.5, and 8.5 scenarios in 2050 and 2100, at 0.5° spatial resolution.</p>
Biodiversity Index, in 2019 and across RCP 4.5, and 8.5 scenarios in 2050 and 2100 of 1508 European Marine Species based on ensemble Ecological Niche Models developed with Artificial Neural Networks, Maximum Entropy, Support Vector Machines, and AquaMaps at 0.5° Resolution
<p>Biodiversity Index in 2019 and across RCP 4.5, and 8.5 scenarios in 2050 and 2100 of 1508 European marine species based on ensemble Ecological Niche Models developed with Artificial Neural Networks, Maximum Entropy, Support Vector Machines, and AquaMaps at 0.5° Resolution. The Index counts the number of species (among the 1508) potentially present in each 0.5° cell according to the ensemble models. For each ensemble model, a threshold of at least 3 models agreeing on species presence in the cell was used to indicate species presence.</p>
Ecological Niche Models of 96 European Marine Species, for 2019, developed with AquaMaps, Artificial Neural Networks, Maximum Entropy, and Support Vector Machines at 0.1° Resolution
<p>Native ecological niche models of 96 European marine species of particular commercial and conservation interest developed with AquaMaps, Artificial Neural Networks, Maximum Entropy, and Support Vector Machines, for 2019 at 0.1° spatial resolution.</p>
Ensemble Ecological Niche Models and Biodiversity Index for 2019 of 96 European Marine Species based on Ecological Niche Models developed with Artificial Neural Networks, Maximum Entropy, AquaMaps, and Support Vector Machines at 0.1° Resolution
<p>Ensemble Ecological Niche Models for 2019 of 96 European marine species of particular commercial and conservation interest, based on Ecological Niche Models developed with (i) Artificial Neural Networks, (ii) Maximum Entropy, (iii) Support Vector Machines, and (iv) AquaMaps at 0.1° Resolution. The data report, for each 0.1° cell, how many models (from 0 to 4) overcome a model-specific decision threshold to assess species presence in the cell. A Biodiversity Index is also provided as the count of the number of species (among the 96) potentially present in each 0.1° cell according to the ensemble models. For each ensemble model, a threshold of at least 3 models agreeing on species presence in the cell was used to indicate species presence.</p>
Lignin, litter, and soil carbon decomposition from soil samples collected from 20 National Ecological Observatory Network (NEON) sites in 2019
These data support the findings of a manuscript by Huang et al. (2023) published in Nature Communications (doi pending). We used incubations of soil and stable isotope measurements to measure lignin, litter, and SOC decomposition over an 18-month lab incubation and assessed their relationships with geochemical, microbial, N-related and climatic factors across 156 mineral soils collected from 20 National Ecological Observatory Network (NEON) sites, which span broad biophysical gradients (climate, soil, and vegetation type) across North America. The soils were collected in 2019. Lignin decomposition and biogeochemical variables were also measured in an approximately 12-month field incubation.
Network properties data and code used in "Ecological plasticity governs ecosystem services in multilayer networks".
<p>Code and network properties data used in the analyses presented in "Ecological plasticity governs ecosystem services in multilayer networks". Further information can be requested of the author David A. Bohan (David.Bohan@inrae.fr).</p>
Dataset: Multi-level network dataset of social-ecological interdependencies in ten Swiss wetlands based on qualitative interviews and quantitative surveys
<p>The dataset originated from quantitative online surveys and qualitative expert interviews with organizational actors relevant to the governance of ten Swiss wetlands from 2019 till 2021. Multi-level networks represent the wetlands governance for each of the ten cases. The collaboration networks of actors form the first level of the multi-level networks and are connected to multiple other network levels that account for the social and ecological systems those actors are active in. 521 actors relevant to the management of the ten wetlands are included in the collaboration networks; quantitative survey data exists for 71% of them. A unique feature of the collaboration networks is that it differentiates between positive and negative forms of collaboration specified based on actors' activity areas. Therefore, the data describes not only if actors collaborate but also how and where actors collaborate. Further additional two-mode networks (actor participation in forums and involvement in other regions outside the case area) are elicited in the survey and connected to the collaboration network. Finally, the dataset also contains data on ecological system interdependencies in the form of conceptual maps derived from 34 expert interviews (3-4 experts per case).</p>
Social networks and transformative behaviors in a grassland social-ecological system
<p>Dataframe for analysis presented in Nesbitt et al.'s <span>Social networks and transformative behaviors in a grassland social-ecological system published in People and Nature. Dataframe includes responses from an ego network survey administered to Nebraska (USA) ranchers in 2021. </span></p> <p><span>Metadata describes each variable in further detail including the question number from the survey.</span></p> <p> </p>
Quantity and composition of POM and MAOM in 156 soil samples collected from 20 National Ecological Observatory Network (NEON) sites in 2019
While it is generally assumed that particulate organic matter (POM) and mineral associated organic matter (MAOM) have distinct biogeochemical characteristics, it remains unresolved where and why POM and MAOM differ in their composition and relationships to total SOM decomposition among heterogenous soils. To address these questions, we analyzed elemental, isotopic, and chemical composition, including diffuse reflectance infrared Fourier transform (DRIFT) spectra, of POM and MAOM in 156 soil samples collected from 20 National Ecological Observatory Network (NEON) sites spanning diverse ecosystems (tundra to tropics) across North America in 2019. We used a classic size separation method for POM (53–2000 µm) and MAOM (< 53 µm) following chemical dispersion.
Long Term Ecological Research (LTER) Network Site Boundaries
This is a set of Long Term Ecological Research (LTER) site boundaries preserved as a shapefile. Note that for some sites “real” boundaries are included while others–particularly marine sites–use a simpler bounding box method. Each site is listed both with its three-letter abbreviation and its unabbreviated name. World Geodetic System 1984 (WGS84) is the coordinate reference system used (EPSG:4326). More information about any of the sites can be found on the LTER Site Profiles page on the LTER Network website (https://lternet.edu/site). This data product was made possible by the contributions of the Information Managers for the LTER sites, each of whom contributed their sites' boundaries. This version of the data includes the following changes from the prior version: - Arctic (ARC) updated - Cedar Creek (CDR) updated - Florida Coastal Everglades (FCE) updated - Harvard Forest (HFR) updated - Konza Prairie (KNZ) updated - McMurdo Dry Valleys (MCM) updated - Moorea Coral Reef (MCR) updated
Global Lake Ecological Observatory Network: Long term chloride concentration from 529 lakes and reservoirs around North America and Europe: 1940-2016
This dataset compiles long term chloride concentration data from 529 freshwater lakes and reservoirs in Europe and North America. All lakes in the dataset had greater than or equal to ten years of data. For each lake the following landscape and climate metrics were calculated: mean annual precipitation, mean monthly air temperatures, road density and impervious surface in 100 to 1500 m buffer zones, sea salt deposition. The dataset includes three files: 1) Descriptive data of lake sites (physical lake metrics, climate, land-cover characteristics), 2) Chloride time-series, and 3) GIS shapefiles.
Non-trophic interactions amplify kelp harvest-induced biomass oscillations and biomass changes in a kelp forest ecological network model
<p><span>Kelp forests are important marine ecosystems providing habitat for numerous species. Despite over 50 years of mechanical harvesting in the Northeast Atlantic, the indirect impacts of kelp harvesting and associated habitat loss on faunal species within kelp forests remain poorly understood. We investigated the consequences of kelp harvesting by developing an allometric trophic network model for a subtidal Northeast Atlantic kelp forest (dominated by <em>Laminaria</em> <em>hyperborea</em>). Additionally, we designed a novel mechanistic model to explore the non-trophic interactions between kelp and age class 0 Atlantic cod (<em>Gadus</em> <em>morhua</em>) and kelp and European lobster (<em>Homarus</em> <em>gammarus</em>), specifically focusing on the increased survival benefits provided by the kelp habitat. Simulations were conducted over a 50-year period, incorporating harvesting cycles of 2, 5, and 9 years, as well as low and high harvesting intensities. Our findings reveal the complex dynamics resulting from kelp harvesting. The recovery of kelp biomass was observed with 5- and 9-year harvesting cycles, whereas a decline was observed with a 2-year cycle. Furthermore, the non-trophic interaction facilitated a higher pre-harvest biomass for both the European lobster and the Atlantic cod compared to scenarios without this interaction. These results highlight the multitrophic effects of kelp harvesting and emphasize that the recovery of kelp-associated species may not necessarily align with kelp recovery, depending on harvesting intensity and recovery periods. Importantly, our study contributes to a better understanding of the ecological consequences of kelp harvesting and underscores the need for sustainable management practices to mitigate habitat loss in kelp ecosystems.</span></p>
Spanning Scales: The Airborne Spatial and Temporal Sampling Design of the National Ecological Observatory Network
<p>Supporting information, datasets, and R and JavaScript code for the the National Ecological Observatory Network’s Airborne Observation Platform (AOP) sampling design and publication, <em>"Spanning Scales: The Airborne Spatial and Temporal Sampling Design of the National Ecological Observatory Network"</em></p>
R_JAGS code for estimation and analysis of species-area-relationship (SAR) parameters from NEON (National Ecological Observatory Network) data on plant surveys
<p><span>Invasive species science is heavily geared toward the invasive agent. </span>However, management to protect native species also requires a proactive approach focused on understanding the features affecting community vulnerability to invasion impacts<span>. </span><span>Vulnerability </span><span>is likely the result of </span><span>factors acting across spatial scales, from </span><span>local to regional, and it is the combined effects of these factors that will determine the magnitude of vulnerability.</span><span> We introduce an analytical framework that quantifies the scale-dependent impact of biological invasions from the shape of the native species-area-relationship (SAR). We leverage newly available, biogeographically extensive vegetation data from the US National Ecological Observatory Network to assess plant community vulnerability to invasion impact as a function of factors acting across scales. We analyzed more than 1000 SARs widely distributed across the USA along environmental gradients and under different levels of invasion. </span>Results show that a decrease in native richness is consistently associated with invasive species cover<span>, but it is only at relatively high levels of invasion that native richness is compromised. After accounting for variation in baseline ecosystem diversity, net primary productivity, and human modification, ecoregions that are colder and wetter seem to be most vulnerable to losses of native plant species at the local level, while warmer and wetter areas seem most susceptible at the landscape level. We also document how the combined effects of cross-scale factors result in a heterogenous spatial pattern of vulnerability. </span><span>This pattern </span><span>cannot be predicted by analyses at any single scale, underscoring the importance of accounting for factors acting across scales. Simultaneously assessing differences in vulnerability between distinct plant communities at local, landscape and regional scales provided outputs that can be used to inform policy and management aimed at reducing vulnerability to the impact of plant invasions.</span></p>
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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.