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151 results for “Ecological scales”
LAGOS-US GEO v1.0: Data module of lake geospatial ecological context at multiple spatial and temporal scales in the conterminous U.S.
The LAGOS-US GEO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The GEO module contains data on the geospatial and temporal ecological setting (e.g., land use, terrain, soils, climate, hydrology, atmospheric deposition, and human influence) quantified at multiple spatial divisions (e.g., equidistant buffers around lakes, watersheds, hydrologic basins, political boundaries, and ecoregions) relevant to the LAGOS-US lake population defined in the LAGOS-US LOCUS module. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and LIMNO (in situ lake physical, chemical, and biological measurements through time) that are each found in their own data packages.
Evaluation of stormwater urban ecological infrastructure in Phoenix, Arizona (USA): a case study of a small-scale bioretention basin system
In 2017, Arizona State University finished construction on a pedestrian mall central to its Tempe campus, which included a small-scale bioretention basin system for stormwater management. This study analyzed the flood control and water quality improvement performance of the small-scale bioretention basin system in the Phoenix Metropolitan Area, AZ USA. Flood control efficacy was quantified by calculating discharge from the basin system using water level loggers and measuring soil moisture levels using soil moisture probes. Stormwater runoff samples were collected for twenty-one storm events and analyzed for nitrogen and phosphorus constituent concentrations. Nutrient concentrations at the system inflow and outflow were used to determine percent change in concentration. Water quality improvement performance was compared to results from previous studies on bioretention basin system performance. These data were used to create relevant graphical figures. Results were obtained by performing statistical analysis calculations on the data measurements. The results indicated that the bioretention basin system performed adequately for flood control and water quality improvement, supporting the use of stormwater urban infrastructure systems in arid and semi-arid climates. Further research can reveal how these systems may perform during more severe storm events and offer improvements for future designs.
Data from: Invasion timing affects multiple scales, metrics and facets of biodiversity outcomes in ecological restoration experiments (Missouri, 2009-2016)
Vegetation responses to experimental ecological restoration treatments at Tyson Research Centre of Washington University in Missouri, USA. These data include species-level cover responses to various factorial restoration treatments. Treatments were applied starting in 2009 and were measured in 2016. Treatment responses reflect these long term responses, but the dataset is comprised to one time point.
Data from: Basin-scale biogeochemical and ecological impacts of islands in the tropical Pacific Ocean
<p><strong>Abstract</strong></p> <p>In the relatively unproductive waters of the tropical ocean, islands can enhance phytoplankton biomass and create hotspots of productivity and biodiversity that sustain upper trophic levels, including fish that are crucial to the survival of islands’ inhabit- ants. This phenomenon, termed the island mass effect 65 years ago, has been widely described. However, most studies focused on individual islands, and very few documented phytoplankton community composition. Consequently, basin-scale impacts on phytoplankton biomass, primary production and biodiversity remain largely unknown. Here we systematically identify enriched waters near islands from satellite chlorophyll concentrations (a proxy for phytoplankton biomass) to analyse the island mass effect for all tropical Pacific islands on a climatological basis. We find enrichments near 99% of islands, impacting 3% of the tropical Pacific Ocean. We quantify local and basin-scale increases in chlorophyll and primary production by contrasting island-enriched waters with nearby waters. We also reveal a significant impact on phytoplankton community structure and biodiversity that is identifiable in anomalies in the ocean colour signal. Our results suggest that, in addition to strong local bio- geochemical impacts, islands may have even stronger and farther-reaching ecological impacts.</p> <p> </p> <p><strong>Data set and method</strong></p> <p>For each island, an algorithm detected the Island Mass Effect (IME) from climatological satellite chlorophyll maps as a contour enclosing the island and surrounding high-chlorophyll waters, termed IME region. A reference (REF) region of the same size was detected alongside each IME region, enclosing nearby non-IME waters. The IME and REF regions were used to build the IME database described in Messié et al. (2022), that includes variables related to satellite chlorophyll, primary production, and PHYSAT phenoclass diversity metrics in IME and REF regions on a climatological basis.</p> <p>This data set includes 4 files:</p> <ul> <li>island_database.csv: information regarding the 664 islands and shallow reefs where the IME detection was applied</li> <li>IME_masks.nc: monthly climatological masks for the IME and REF regions for all islands,</li> <li>IME_database.nc: IME database as a function of island and climatological month (chlorophyll, primary production, and phenoclass-derived variables calculated within the IME and REF masks).</li> <li>PHYSAT_climatology.nc: climatological maps for each PHYSAT phenoclass, used to calculate phenoclass-derived variables in the IME database.</li> </ul> <p>See details regarding data sources and calculations in <a href="https://rdcu.be/cO4qr">Messié et al. (2022)</a>.</p>
LAGOS-NE-LIMNO v1.087.3: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 1925-2013
This data package, LAGOS-NE-LIMNO v1.087.3, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. With this release, only this data package is being updated and users are expected to use prior releases of the other types of data. Please see the attached additional documentation for a full description of the changes that have been made for this new release.The data packages that make up LAGOS-NE include the following information on lakes and reservoirs in 17 lake-rich states in the Northeastern and upper Midwestern U.S. (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes greater than one hectare. (2) LAGOS-NE-GEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes and for all spatial resolutions, also called ‘zones’ (i.e., ecoregions, states, counties). These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. (3) LAGOS-NE-LIMNO v1.087.3: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This module includes variables that are most commonly measured by state agencies and researchers for studying eutrophication. For each water quality data value, we also include metadata related to the sampling program, methods, qualifiers with data flags from the original program (qual, not standardized for LAGOS-NE), censor codes from our quality control procedures (censorcode, standardized for LAGOS-NE), and the date of each sample. (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-N
LAGOS-NE Shallow Lakes: a dataset of lake variables and multi-scaled ecological context variables used to predict and compare trophic status and TP:CHLa relationships between shallow and non-shallow lakes in the Upper Midwest and Northeastern United States.
We conducted a macroscale study of 2,210 shallow lakes (mean depth ≤ 3m or a maximum depth ≤ 5m) in the Upper Midwestern and Northeastern U.S. We asked: What are the patterns and drivers of shallow lake total phosphorus (TP), chlorophyll a (CHLa), and TP–CHLa relationships at the macroscale, how do these differ from those for 4,360 non-shallow lakes, and do results differ by hydrologic connectivity class? To answer this question, we assembled the LAGOS-NE Shallow Lakes dataset described herein, a dataset derived from existing LAGOS-NE, LAGOS-DEPTH, and LAGOS-CLIMATE datasets. Response data variables were the median of available summer (e.g., 15 June to 15 September) values of total phosphorus (TP) and chlorophyll a (CHLa). Predictor variables were assembled at two spatial scales for incorporation into hierarchical models. At the local or lake-specific scale (including the individual lake, its inter-lake watershed [iws] or corresponding HU12 watershed), variables included those representing land use/cover, hydrology, climate, morphometry, and acid deposition. At the regional scale (e.g., HU4 watershed), variables included a smaller set of predictor variables for hydrology and land use/cover. The dataset also includes the unique identifier assigned by LAGOS-NE(lagoslakeid); the latitude and longitude of the study lakes; their maximum and mean depths along with a depth classification of Shallow or non-Shallow; connectivity class (i.e., whether a lake was classified as connected (with inlets and outlets) or unconnected (lacking inlets); and the zone id for the HU4 to which each lake belongs. Along with the database, we provide the R scripts for the hierarchical models predicting TP or CHLa (TPorCHL_predictive_model.R), and the TP—CHLa relationship (TP_CHL_CSI_Model.R) for depth and connectivity subsets of the study lakes.
Data for Marine Ecological Niche Models, for 2019 and across RCP 2.6, 4.5, and 8.5 scenarios in 2050 and 2100: Global-scale Environmental parameters at 0.1° and 0.5° resolutions, Presence and Absence Records of 1508 European-seas Species
<p>Data for Ecological Niche Models: Global-scale Environmental parameters at 0.1° and 0.5° resolutions, Presence and Absence Records of 1508 European-seas Species.</p>
Qualitative Data on 60 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain)
<h2><span lang="EN-US">Dataset name</span></h2> <p><span lang="EN-US">Small_Scale_Fishery_Data_2023_v2 </span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Title</span></h2> <p><span lang="EN-US">Qualitative Data on 60 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain). </span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Description </span></h2> <p><span lang="EN-US"> This dataset was created for the Fish2Sustainability research project, which aims to evaluate how small-scale fisheries (SSF) contribute to Sustainable Development Goals (SDGs). The dataset includes 60 case studies across eight countries and was developed using a rapid appraisal framework. The framework includes a four-step process: </span></p> <p><span lang="EN-US"> 1. Identifying specific SDG targets influenced by SSF;</span></p> <p><span lang="EN-US"> 2. Extracting relevant variables from UN indicators;</span></p> <p><span lang="EN-US"> 3. Gathering expert input via a questionnaire to score these variables;</span></p> <p><span lang="EN-US"> 4. Creating composite indicators to measure SSF performance against SDGs.</span></p> <p><span lang="EN-US"> The dataset contains raw data from step 3, case study details, variable scores, and comments from data collectors (contributing authors). The dataset is valuable for researchers interested in small-scale fisheries and socio-ecological systems. By incorporating expert judgments from individuals with expertise in SSF, particularly in data-poor contexts, the dataset offers a wealth of knowledge for conducting comparative analyses across different contexts.</span><span lang="EN-US"> </span></p> <h2><span lang="EN-US">Authors </span></h2> <p><span lang="EN-US">Léopold, M.1, Bitoun, R.E.2, Beckensteiner, J.3, Chuenpagdee, R.4, Fondo, E.N.5, Akintola, S.L.6, Bach, P.7, Frangoudes, K.8, Gaibor, N.9, Gutierrez-Cala, L.10, Massey, Y.7, Randrianandrasana, R.11, Razanakoto, T.11, Saavedra-Díaz, L.M.10, Schreiber Arias, M.12,13, Salas, S.14, Devillers, R.2,4 </span></p> <h3><span lang="EN-US">Affiliations </span></h3> <p><span lang="EN-US">1 ENTROPIE (IRD, University of La Reunion, CNRS, University of New Caledonia, Ifremer), c/o IUEM, Plouzané, France </span></p> <p><span lang="EN-US">2 Espace-Dev (IRD, Univ. </span>Montpellier, Univ. Guyane, Univ. La Réunion, Univ. Antilles, Univ. Nouvelle Calédonie), Montpellier, France</p> <p>3 AMURE (Ifremer, UBO, CNRS), Plouzané, France</p> <p><span lang="EN-US">4 Department of Geography, Memorial University of Newfoundland, St. John’s, NL, Canada</span></p> <p><span lang="EN-US">5 Kenya Marine and Fisheries Research Institute, Mombasa, Kenya</span></p> <p><span lang="EN-US">6 Department of Fisheries, Faculty of Science, Lagos State University, Nigeria</span></p> <p><span lang="EN-US">7 MARBEC, University of Montpellier, CNRS, Ifremer, IRD, Sète, France</span></p> <p>8 Université de Bretagne Occidentale: Brest, France</p> <p>9 Instituto Público de Investigación de Acuicultura y Pesca (IPIAP), Universidad del Pacifico (UPAC), Guayaquil, Ecuador</p> <p>10 Grupo de Investigación en Sistemas Socioecológicos para el Bienestar Humano (GISSBH), Programa de Biología, Universidad del Magdalena, Colombia</p> <p>11 Centre d’Etudes et de Recherches Economiques pour le Développement (CERED), Université d’Antananarivo, Madagascar</p> <p><span lang="EN-US">12 EqualSea Lab, Universidad Santiago de Compostela, A Coruña, Spain</span></p> <p><span lang="EN-US">13 School of Global Studies, University of Gothenburg, Gothenburg, Sweden</span></p> <p>14 Centro de Investigación y de Estudios Avanzados (CINVESTAV), IPN, Unidad Mérida, Mexico </p> <h2><span lang="EN-US">Method </span></h2> <p><span lang="EN-US">Case studies were selected in eight countries by national SSF experts, based on specific criteria and research priorities. Case studies were not selected to represent the full diversity of SSF globally or even nationally. Instead, they were chosen to capture a range of fisheries that could showcase different contributions to SDGs. SSF were defined based on various characteristics, such as resources harvested, gear used, and location of the fishery. </span><span lang="EN-US"> </span></p> <h3><span lang="EN-US">Geographical Coverage </span></h3> <p><span lang="EN-US">60 small-scale fisheries located in seven countries are documented in the data:</span></p> <ul> <li><span lang="EN-US">Colombia (4 case studies) – Pacifico: La Guajira, San Andrés y Providencia; Caribe: Chocó, Cauca, Valle del Cauca, Nariño.</span></li> <li><span lang="EN-US">Ecuador (3) – Region: Esmeraldas, Manabi, Guayas, El Oro.</span></li> <li><span lang="EN-US">France (2) – Region: Bretagne, Occitanie.</span></li> <li><span lang="EN-US">Kenya (22) – County: Kilifi, Kwale, Lamu, Mombasa, Tana River.</span></li> <li><span lang="EN-US">Madagascar (20) – Region: Analanjirofo, Anosy, Atsimo Andrefana, Boeny, Diana, Menabe, Vatovavy Fitovinany.</span></li> <li><span lang="EN-US">Mexico (2) – State: Baja California Sur, Campeche, Yucatan.</span></li> <li><span lang="EN-US">Nigeria (6) – State: Bayelsa, Cross River, Lagos, Ondo, Ogun. </span></li> <li><span lang="EN-US">Spain (1) – State: Galicia.</span> </li> </ul> <h3><span lang="EN-US">Data Collection </span></h3> <p><span lang="EN-US">Data collection took place from November 30, 2022, to July 3, 2023, spanning approximately seven months. The data presented serve as a snapshot of the conditions within a specific small-scale fishery during the assessment period. To consider the evolution of trends such as exports, economic growth, and income, we considered any relevant variables over the past decade. </span></p> <p><span lang="EN-US">Data collection approaches varied depending on the context, and data collectors received training to ensure survey consistency. We used primary data sources such as interviews, observations, and measurements whenever possible. In cases where resources were limited, we preferred secondary sources such as existing datasets and literature. Our methods were standardized, but data collectors could adjust them based on their resources. We primarily used direct observation, focus groups, and interviews to collect data. Scoring in interviews and focus groups was done directly or through group analysis by interviewers. Disagreements were resolved through additional interviews or group discussions, with secondary data used if needed. Please refer to the methods in : </span></p> <p><strong><span lang="EN-US">Bitoun et al., (2024). A methodological framework for capturing marine small-scale fisheries’ contributions to the sustainable development goals. Sustainability Science, 19(4), 1119–1137. https://doi.org/10.1007/s11625-024-01470-0. </span></strong><span lang="EN-US"><strong> </strong> </span></p> <h3><span lang="EN-US">Ethics </span></h3> <p><span lang="EN-US">Participants had the option to join of their own accord, were fully briefed on the research goals, and were given the opportunity to review interview guidelines before proceeding. Depending on the circumstances, interviews could last 45 minutes to 4.5 hours. Participants were guaranteed confidentiality and anonymity in the handling and reporting of their data.</span><span lang="EN-US"> </span></p> <h3><span lang="EN-US">Suggested citation</span></h3> <p><span lang="EN-US">Léopold, M., Bitoun, R., & Devillers, R. (2023). Qualitative Data on 61 Small-Scale Fisheries: A socio-ecological rapid appraisal applied to cases from America (Colombia, Ecuador, and Mexico), Africa (Kenya, Madagascar, and Nigeria), and Europe (France and Spain) (Version 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.16077739</span></p> <h2><span lang="EN-US">Data Files</span></h2> <p><span lang="EN-US">The dataset includes the following:</span></p> <ul> <li><span lang="EN-US">The raw dataset (.xls format).</span></li> <li><span lang="EN-US">A data dictionary describing and defining each dataset column (.xls format).</span></li> </ul>
LAGOS-NE-LOCUS v1.01: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 1925-2013
This data package, LAGOS-NE-LOCUS v1.01, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. Three of the data packages each contain different types of data for 51,101 lakes and reservoirs larger than 4 ha in 17 lake-rich U.S. states to support research on thousands of lakes. These three package are: (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes. (2) LAGOS-NEGEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes. These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. And, (3) LAGOS-NE-LIMNO v1.087.1: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. The other two data packages contain supporting data for the LAGOS-NE database: (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-NE-GEO module. (5) LAGOS-NE-RAWDATA: the original 87 datasets of lake water quality prior to processing, the R code that converts the original data formats into LAGOS-NE data format, and the log file from this procedure to create LAGOS-NE. This latter data package supports the reproducibility of LAGOS-NE-LIMNO. The LAGOS-NE-LOCUS v1.01 module includes information on the physical location and features of all lakes > 4 ha. The information provided for this population of lakes includes: lake unique identifiers, lake area, perimeter, latitude and longitude, and the zone IDs that the lake is located within (e.g., state, county, the hydrologic unit at each level (4, 8, and 12). Citation for
LAGOS-NE-GEO v1.05: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 1925-2013
This data package, LAGOS-NE-GEO v1.05, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. Three of the data packages each contain different types of data for 51,101 lakes and reservoirs larger than 4 ha in 17 lake-rich U.S. states to support research on thousands of lakes. These three package are: (1) LAGOS-NE-LOCUS: lake location and physical characteristics for all lakes. (2) LAGOS-NE-GEO: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes. These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. And, (3) LAGOS-NE-LIMNO: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. The other two data packages contain supporting data for the LAGOS-NE database: (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-NEGEO module. (5) LAGOS-NE-RAWDATA: the original 87 datasets of lake water quality prior to processing, the R code that converts the original data formats into LAGOS-NE data format, and the log file from this procedure to create LAGOS-NE. This latter data package supports the reproducibility of LAGOS-NE-LIMNO. The LAGOS-NE-GEO v1.05 module includes information on the ecological context of the census lakes, all lakes > 4 ha in the study extent, their watersheds, and their regions. The information provided in the data tables for this module is organized into three main themes: CHAG - climate, hydrology, atmospheric deposition of nitrogen and sulfur, and surficial geology; LULC - land use/cover, impervious co
Rethinking the fundamental unit of ecological remote sensing: Estimating individual level plant traits at scale
<p>derived data of leaf and plant structural traits for two National Ecological Observatory Network (NEON) Airborne Observatory Platform (AOP) sites. Dataset contains spatial explicit information for 4.5 million trees, and include: Nitrogen (%mass), Phosphorus (%mass), Leaf mass per area (g m<sup>-2</sup>), diameter at breast height (cm), crown area (m2), tree height (m) and other physical topographic variables (Albedo, Elevation, Slope, Aspect). data are associated to the </p>
Ecological barriers mediate spatiotemporal shifts of bird communities at a continental scale
<p>### Ecological barriers mediate spatiotemporal shifts of bird communities ###</p> <p>Marjakangas, Bosco et al. 2022</p> <p>Methods explained in the publication (open access)</p> <p>--> readme file explains how to use the data and code</p>
LAGOS-NE-GIS v1.0: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 2013-1925
This data package, LAGOS-NE-GIS v1.0, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. Three of the data packages each contain different types of data for 51,101 lakes and reservoirs larger than 4 ha in 17 lake-rich U.S. states to support research on thousands of lakes. These three package are: (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes. (2) LAGOS-NE-GEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes. These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. And, (3) LAGOS-NE-LIMNO v1.087.1: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. The other two data packages contain supporting data for the LAGOS-NE database: (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-NE-GEO module. (5) LAGOS-NE-RAWDATA: the original 87 datasets of lake water quality prior to processing, the R code that converts the original data formats into LAGOS-NE data format, and the log file from this procedure to create LAGOS-NE. This latter data package supports the reproducibility of LAGOS-NE-LIMNO. The LAGOS-NE GIS v1.0 module includes GIS datasets for: lake polygons and their hydrologic classification; wetland polygons and their classification; streams as a line coverage and their classification by stream order; the zones used for this study (state and county; hydrologic units [at the 4, 8 and 12 scales]); and, lake watersheds (IWS). We also include boundaries of U.S. stat
Identifying the drivers and responses of abrupt changes across spatial and temporal scales in ecology: a review
Recently, the theoretical basis for understanding abrupt changes in ecosystems relative to regime shifts has emerged (Ratajczak et al. 2018). Abrupt changes are defined as, “substantial changes in the mean or variability of a system that occur in a short period of time relative to typical rates of change” (Ratajczak et al. 2018). Despite a driver-response framework to guide the environmental conditions under which abrupt changes are likely to occur coupled with many examples of unexpected changes from long-term ecological research, our theoretical basis of understanding of abrupt changes doesn’t include long-term scales, variability in drivers and responses, changes in the magnitude or direction of drivers, or the interactions among multiple drivers across spatiotemporal scales (sensu Ratajczak et al. 2018). Further, a critical review of the literature is lacking and essential to further understanding how common abrupt changes are detected and reported, as well as patterns and scales of drivers and responses of abrupt change in ecosystems. To address this knowledge gap, we searched the existing ecological literature for evidence and commonalities of abrupt change across ecosystems to identify commonalities and differences of abrupt change drivers and responses across terrestrial, freshwater, and marine ecosystems. We specifically asked the following questions: (1) How common are abrupt changes reported in the ecological literature? (2) How do driver and response temporal and spatial scales of abrupt changes compare and vary across terrestrial, freshwater, and marine ecosystem types? (3) Is there relative congruence between the temporal and spatial scale of drivers and responses? (3) What are common types of drivers and responses to abrupt changes, and how do they vary across ecosystem types? (4) What terms are most associated with drivers and responses of abrupt changes among ecosystem types?
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>
Data supporting "Large-scale citizen science programs can support ecological and climate change assessments"
<p>Text file of phenology observations pulled from the USA National Phenology Network's database (www.usanpn.org) and used in this analysis. </p>
Text-fig. 8. SEM (a, b) and SRXTM (c, d) images of fruit associated with Miranthus elegans and Miranthus kvacekii; Mira locality, Portugal. a: Apical view of capsular fruit with five, partly open valves revealing the enclosed reticulate seeds (arrows). b: Detail of fruit wall showing an enclosed seed (arrow). c: Transverse section (orthoslice xy1200) of fruit showing central column (cc) of placenta and numerous angular and bitegmic seeds; note that the outer integument (black arrow) is thicker than inner integument (white arrow). d: Longitudinal section (orthoslice yz1239) of fruit showing perigynous attachment of calyx, central column (cc) of the placenta and sections through seeds. Specimen, Mira 99-S156331 (a–d). Scale bars = 600 µm (a, c, d), 200 µm (b). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 8. SEM (a, b) and SRXTM (c, d) images of fruit associated with Miranthus elegans and Miranthus kvacekii; Mira locality, Portugal. a: Apical view of capsular fruit with five, partly open valves revealing the enclosed reticulate seeds (arrows). b: Detail of fruit wall showing an enclosed seed (arrow). c: Transverse section (orthoslice xy1200) of fruit showing central column (cc) of placenta and numerous angular and bitegmic seeds; note that the outer integument (black arrow) is thicker than inner integument (white arrow). d: Longitudinal section (orthoslice yz1239) of fruit showing perigynous attachment of calyx, central column (cc) of the placenta and sections through seeds. Specimen, Mira 99-S156331 (a–d). Scale bars = 600 µm (a, c, d), 200 µm (b).
Text-fig. 5. SRXTM images of Miranthus elegans gen. et sp. nov.; Mira locality, Portugal. a, b: Transverse sections of flower (a, orthoslice xy0665 close to the apex of placenta; b, orthoslice xy0800 in middle part of placenta) showing remains of calyx with distinct bundles (arrows), ovary wall (ow) and numerous ovules (ov) on the central mushroom-shaped globose placenta (pl) with central column (cc). c: Transverse section of flower (orthoslice xy0620) through perianth and ovary (ow) at a level above the placenta showing ovules (ov) and cellular preservation of the sepal bundles (arrows shown for one sepal); note abaxial surface of sepals with thick-walled epidermal cells, thick cuticle, and fine pointed verrucae. d: Longitudinal section of flower (orthoslice xz0500) showing perigynous position of calyx and semi-inferior ovary (ow, ovary wall) with a central placenta (pl), central column (cc) and numerous ovules (ov); note spiny verrucae on abaxial surface of calyx lobes. Specimens, Mira 100-S153145 (a, b), Mira 100-S170155 (c, d, holotype). Scale bars = 600 µm (a–d). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 5. SRXTM images of Miranthus elegans gen. et sp. nov.; Mira locality, Portugal. a, b: Transverse sections of flower (a, orthoslice xy0665 close to the apex of placenta; b, orthoslice xy0800 in middle part of placenta) showing remains of calyx with distinct bundles (arrows), ovary wall (ow) and numerous ovules (ov) on the central mushroom-shaped globose placenta (pl) with central column (cc). c: Transverse section of flower (orthoslice xy0620) through perianth and ovary (ow) at a level above the placenta showing ovules (ov) and cellular preservation of the sepal bundles (arrows shown for one sepal); note abaxial surface of sepals with thick-walled epidermal cells, thick cuticle, and fine pointed verrucae. d: Longitudinal section of flower (orthoslice xz0500) showing perigynous position of calyx and semi-inferior ovary (ow, ovary wall) with a central placenta (pl), central column (cc) and numerous ovules (ov); note spiny verrucae on abaxial surface of calyx lobes. Specimens, Mira 100-S153145 (a, b), Mira 100-S170155 (c, d, holotype). Scale bars = 600 µm (a–d).
Text-fig. 7. SEM (a) and SRXTM (b–e) images of Miranthus kvacekii sp. nov.; Mira locality, Portugal. a: Lateral view of flower bud showing corolla lobes extending beyond calyx; note surface of pedicel, calyx and corolla with small equiaxial epidermal cells and indumentum of densely spaced, short stiff trichomes. b, c: Longitudinal sections through floral bud in two directions perpendicular to each other (a, orthoslice yz1024; b, orthoslice xz0950) showing corolla (co), calyx (ca), stamens (st) and semi-inferior ovary with thin ovary wall (ow) and central mushroom-shaped globose placenta (pl) bearing numerous ovules (ov). d, e: Transverse sections through floral bud above placenta (d, orthoslice xy0915; e, orthoslice xy1095) showing calyx (ca), corolla (co), ovary wall (ow) and ovules (ov); yellow outlines indicate the positions of anthers (d) and filaments (e); orange outlines indicate the position of three of the possible staminodes. Specimen, Mira 100-S170157 (a–e, holotype). Scale bars = 600 µm (a–c), 300 µm (d, e). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 7. SEM (a) and SRXTM (b–e) images of Miranthus kvacekii sp. nov.; Mira locality, Portugal. a: Lateral view of flower bud showing corolla lobes extending beyond calyx; note surface of pedicel, calyx and corolla with small equiaxial epidermal cells and indumentum of densely spaced, short stiff trichomes. b, c: Longitudinal sections through floral bud in two directions perpendicular to each other (a, orthoslice yz1024; b, orthoslice xz0950) showing corolla (co), calyx (ca), stamens (st) and semi-inferior ovary with thin ovary wall (ow) and central mushroom-shaped globose placenta (pl) bearing numerous ovules (ov). d, e: Transverse sections through floral bud above placenta (d, orthoslice xy0915; e, orthoslice xy1095) showing calyx (ca), corolla (co), ovary wall (ow) and ovules (ov); yellow outlines indicate the positions of anthers (d) and filaments (e); orange outlines indicate the position of three of the possible staminodes. Specimen, Mira 100-S170157 (a–e, holotype). Scale bars = 600 µm (a–c), 300 µm (d, e).
Text-fig. 2. SEM images of Miranthus elegans gen. et sp. nov.; Mira locality, Portugal. a, b: Flowers in oblique lateral view showing remains of calyx and slightly semi-inferior ovary with elongated apical style (a); note larger openings in the floral tissue (asterisk) interpreted as schizogenous secretory cavities and the stomata-like secretory structures on the upper portion of the ovary (arrows) that are interpreted as nectariferous (b). c: Detail of ovary surface showing secretory stomata-like structures (arrows). d: Flower in lateral view showing fragmentary calyx and broken slightly semi-inferior ovary with secretory stomata-like structures; note the point of attachment of the central placenta (pl). e: Cluster of seeds removed from the ovary in (d) showing reticulate surface. f: Outer (abaxial) surface of calyx lobe showing the slightly pointed papillae and scattered, fine trichomes (arrows). g: Triaperturate pollen grains from the ovary surface. Specimens, Mira 100-S153146 (a, b), Mira 100-S170155 (c), Mira 100-S101266 (d, e), Mira 105-S100732 (f), Mira 100-S170125 (g). Scale bars = 600 µm (a, b, d), 300 µm (f), 100 µm (c, e), 10 µm (g). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 2. SEM images of Miranthus elegans gen. et sp. nov.; Mira locality, Portugal. a, b: Flowers in oblique lateral view showing remains of calyx and slightly semi-inferior ovary with elongated apical style (a); note larger openings in the floral tissue (asterisk) interpreted as schizogenous secretory cavities and the stomata-like secretory structures on the upper portion of the ovary (arrows) that are interpreted as nectariferous (b). c: Detail of ovary surface showing secretory stomata-like structures (arrows). d: Flower in lateral view showing fragmentary calyx and broken slightly semi-inferior ovary with secretory stomata-like structures; note the point of attachment of the central placenta (pl). e: Cluster of seeds removed from the ovary in (d) showing reticulate surface. f: Outer (abaxial) surface of calyx lobe showing the slightly pointed papillae and scattered, fine trichomes (arrows). g: Triaperturate pollen grains from the ovary surface. Specimens, Mira 100-S153146 (a, b), Mira 100-S170155 (c), Mira 100-S101266 (d, e), Mira 105-S100732 (f), Mira 100-S170125 (g). Scale bars = 600 µm (a, b, d), 300 µm (f), 100 µm (c, e), 10 µm (g).
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.