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86 results for “long-term research”
Towers Forestry Plot, Long-term Vegetation Monitoring in a 1-ha old-growth Rainforest, La Selva Research Station, OTS, Sarapiquí, Heredia, Costa Rica, 2010–2020
The Towers Plot is a 1-hectare permanent vegetation plot established in 2010 under the canopy towers at La Selva Research Station, Sarapiquí, Heredia, Costa Rica. The plot was created by the Organization for Tropical Studies (OTS) to monitor long-term changes in forest structure, composition, and dynamics in an old-growth tropical rainforest. All woody stems with a diameter at breast height (DBH) of 10 cm or greater—including trees, palms, and lianas—were tagged, mapped, and measured following standardized procedures. Censuses were conducted between 2010 and 2020 to document growth, mortality, and recruitment. The dataset includes taxonomic identifications, stem diameter measurements, spatial coordinates within the plot, and metadata describing field methods and species composition. The plot was established beneath three canopy towers that had been previously constructed through the NSF-funded Major Research Instrumentation (MRI) project, NSF 0722741, which provided key infrastructure for canopy and environmental research at La Selva. This proximity created a valuable opportunity to integrate vegetation monitoring with existing environmental instrumentation. Johana Hurtado, coordinator of the Tropical Ecology, Assessment and Monitoring (TEAM) project at La Selva, collaborated with OTS staff in the establishment of the plot, ensuring methodological consistency with other tropical forest monitoring sites. This dataset provides a comprehensive record of woody plant diversity and forest structure in a lowland old-growth Neotropical rainforest. It supports research on forest dynamics, carbon storage, and ecosystem change. The overall monitoring project is ongoing; this data package contains observations from 2010 through 2020.
Woody vegetation composition and structure at long-term monitoring plots on the Stevenson-Hamilton Research Supersite, Kruger National Park, South Africa (2012)
This dataset contains measurements of woody vegetation composition and structural attributes collected in 2012 from long-term ecological monitoring plots located on the Stevenson-Hamilton Research Supersite in the Kruger National Park, South Africa. The study region is characterized by granitic soils, broad-leaved savanna vegetation, and a long history of fire, herbivory, and climate-driven ecological dynamics. Vegetation surveys were conducted in sixteen 0.25-ha sampling plots to quantify woody species composition, stem density, and size structure. Additional measurements of vegetation structure were collected, including grass biomass, canopy cover, canopy height, and canopy diversity, providing a broader assessment of both woody and herbaceous layers. These data establish an important baseline for monitoring ecological change, evaluating woody vegetation dynamics under variable fire and herbivore regimes, and supporting ongoing research on savanna ecosystem functioning within the Kruger National Park.
Forest tree, woody debris, root ingrowth, soil respiration and characterization data from long-term research plots for LTREB at the University of Michigan Biological Station
The NSF-funded project "LTREB: Drivers of temperate forest carbon storage from canopy closure through successional time" (2014-2024) supports research to meet the following goals: 1) elucidate mechanisms responsible for changes in C storage over decades to centuries; 2) link processes leading to persistence and resilience of forest C storage following disturbance; 3) quantify the effects of potential drivers such as forest structure, N availability, climate change, and atmospheric deposition on decadal and longer-term trajectories of C storage. Field activities for this research are conducted at the University of Michigan Biological Station (UMBS) on a pair of chronosequences and several old reference forests. Synthesis activities utilize data collected from these field sites in support of the LTREB project, as well as data synthesized from other sources (e.g., long-term UMBS plot data, AmeriFlux data, FIA data) all intended to address the core questions of the LTREB project. This dataset has been compiled and expanded over a series of versions, with new data types and observations appended periodically. Presently, the dataset includes observations from tree inventory censuses, woody debris sampling, fine root ingrowth cores, soil respiration measurements, and two sets of soil collections aimed at quantifying a range of physical, chemical, and biological properties of soil.
Above ground plant, belowground stem and root biomass in Arctic Long-term Ecological Research's 2006 moist acidic tussock tundra experimental sites, 2012, Toolik Lake, Alaska.
Above ground plant, belowground stem and root biomass was measured in moist acidic tussock tundra experimental sites established in 2006 by the Arctic Long-term Ecological Research site (ARC-LTER. Control plots and plots amended with three different levels of nitrogen(N) and phosphorus(P), F10 (10 g/m2 N and 5 g/m2 P); F5 (5 g/m2 N and 2.5 g/m2 P); F2 (2 g/m2 N and 1 g/m2 P), were sampled.
Long-term monitoring and research of the ecology of the Tres Rios constructed treatment wetland, Phoenix, Arizona, USA, ongoing since 2011
# Project Description In order to better understand the water, nutrient and treatment dynamics of aridland constructed treatment wetlands, we have developed datasets tracking primary productivity (aboveground and belowground), nutrient and water budget dynamics, soils, and aquatic metabolism at the Tres Rios wetlands, operated by the City of Phoenix Water Services Department, since July 2011. The 3-cell Tres Rios Wetlands were completed in 2010 and are associated with the 91st Avenue Wastewater Treatment Plant, the largest in Phoenix. This project is focused on the largest of the three wetlands treatment cells which was the first to be planted and became operational in Summer 2010. The wetland cells are bounded by roads (the "shoreline"), and the system we study is 42 ha in size, approximately half of which is open water and half of which is fringing vegetated marsh. Water depth is relatively consistent across the marsh (approximately 25cm) and effluent inflow to the cell varies seasonally from 95,000 to over 270,000 m3 d-1. Measurements are taken along two gradients representing the two hydraulic pathways of the system: The whole-system, from inflow to outflow, within the vegetated marsh itself. # Abstract Constructed treatment wetlands (CTW) provide cost effective and ecosystem-service based solutions to the problem of urban wastewater treatment. They are a particularly attractive option for water reuse in arid cities, where water resources are scarce, and understanding CTW function in these environments is critical to facilitating sustainable water use practices. Although CTW are well established and studied in mesic climates, how they function in and respond to hot, arid climates is comparatively not well understood. Specifically, large atmospheric water losses via evaporation and plant transpiration comprise a much larger component of the whole-system water budget than in mesic climates. Additionally, given the primary role that emergent macrophytes play in nit
Long-Term Field Research Sites at Harvard Forest since 1937
The Harvard Forest is an iconic field station, hosting hundreds of field-based studies since it was founded in 1907. Site-based, long-term research increased sharply starting in 1988, when Harvard Forest became a Long-Term Ecological Research Site. This dataset documents the locations of most long-term research studies initiated since 1988; a few studies that began earlier and are still active are also included. Short-term studies, or studies that focus on sampling individual organisms, are not included.
Long-term (1935-2019) tree population data from remeasurements of a large network of permanent study plots in old-growth forest, Dukes Research Natural Area, Marquette Co., MI, USA
The Dukes Research Natural Area (Hiawatha National Forest, Marquette Co., MI) amounts to ca. 100 ha of minimally disturbed original forests, including a mix of mesic 'hemlock-northern hardwood' types and peaty wetlands dominated by several species of swamp conifers and black ash (Fraxinus nigra). The RNA hosts a regular grid of 250 0.2-acre (~0.08 ha) permanent monitoring (CFI) plots. This package includes tree censuses for subsets of CFI plots conducted in 1935, 1948, and 1974-1980, and repeated censuses with mapped stems from 1989 to 2019. This 84-year record constitutes one of the longest repeated-measurement, permanent-plot data-sets for old-growth temperate forest.
Tussock watershed thaw depth survey summary for 1990 to present, Arctic Long-Term Ecological Research (LTER), Toolik Research Station, Alaska.
Thaw depth was measured since 1990 using a steel probe in the Tussock watershed just south of Toolik Lake, Alaska, on a gentle slope dominated by moist, non-acidic tussock tundra. At least two surveys are conducted each summer, on 2 July and on 11 August (plus or minus 1 day).
warmXtrophic: plant community responses to the individual and interactive effects of climate warming and herbivory across multiple years at Kellogg Biological Station Long-Term Ecological Research Sites (KBS LTER), Michigan, USA, and University of Michigan Biological Station (UMBS), Michigan, USA.
Climate change has both direct and indirect effects on ecological communities. Whereas most climate change ecology experiments manipulate abiotic drivers to measure direct effects of climate on species or communities, fewer quantify the indirect effects through biotic interactions, especially over multiple sites and years. In this factorial experiment we manipulate temperature through open-top chambers, and the level of insect herbivory through insecticide. At two early successional field sites separated by 3 degrees of latitude and 3°C of mean annual temperature (University of Michigan Biological Station, Pellston, MI and Kellogg Biological Station, Hickory Corners, MI), 6 replicate 1-m2 plots per treatment were installed in May 2015. 12 plots per site are at ambient temperature, 12 are warmed with year-round non-UV filtering polycarbonate and wood frame construction OTCs for tall-stature plants (Welshofer et al. 2018 MEE). Insecticide reduces insect herbivory in half the plots (Welshofer et al. 2018 Oecologia). Over the course of the experiment, OTCs warmed the plant communities by 1.9°C-3.0°C on average over the growing season. Each year, through 2021, plant traits and community responses were measured at the species level: plant phenology (green-up, flowering, flowering duration, seed set); plant percent cover (aerial % cover of the 1m2 plot); plant traits (specific leaf area, C and N content), herbivory damage to leaves, and plant species biomass (only in 2021). Further methodological details are found within each response variable metadata. This experiment is ongoing and further data package updates are planned. L0 data is available upon request. R scripts can be found here: https://github.com/SpaCE-Lab-MSU/warmXtrophic. The biotic and abiotic community context and relative strengths of direct vs. indirect effects may yield ecological surprises under climate change unless addressed together. Large-scale experiments like this one can improve our ability to unde
Long-term (1993-2019) tree population measurements from a mapped 2.9-ha permanent plot in old-growth northern hardwood forest, Dukes Research Natural Area, Marquette Co., MI, USA
The Dukes Research Natural Area (Hiawatha National Forest, Marquette Co., MI) amounts to ca. 100 ha of minimally disturbed original forests, including a mix of mesic 'hemlock-northern hardwood' types and peaty wetlands dominated by several species of swamp conifers and black ash (Fraxinus nigra). The RNA hosts a regular grid of 250 permanent monitoring plots (data to be provided in a separate package). In 1993-95, a macroplot of 2.91 ha was established in a mixed mesic upland forest area within the RNA, in which all woody stems >2 cm diameter at breast height (DBH) were identified, measured, and mapped. In 1999 and again every five years subsequently through 2019, the macroplot was recensused; all stems were remeasured, stems newly recruited (>2 cm DBH) were measured and mapped, and any mortality since previous census was noted and described. A severe storm in 2002 resulted in extensive mortality throughout the RNA, particularly in the area in and around the macroplot.
Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network
<p><strong>Data Description</strong>:</p> <p>The USDA Long-Term Agroecosystem Research (LTAR) Network coordinates agricultural research across 18 research sites in the conterminous United States (CONUS). However, it is unclear how well these sites represent the totality of agricultural working lands within the CONUS. Therefore, we performed a quantitative analysis of the 18 sites, based on 15 climatic and edaphic characteristics, to produce maps of representativeness and constituency across the CONUS. Representativeness shows how well the combination of environmental drivers at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location.</p> <p>Files in collection (22):</p> <p>Collection contains 11 geospatial rasters and 11 PNGs visualizing them.</p> <p>TIF files:</p> <p>├── conus_ltar_constituency_workinglands.tif [Constituency of LTAR network]<br> ├── conus_ltar_representativeness_workinglands.tif [Representativeness of LTAR network]<br> ├── conus_ltar_v5.pc1.tif [Principal Component 1]<br> ├── conus_ltar_v5.pc2.tif [Principal Component 2]<br> ├── conus_ltar_v5.pc3.tif [Principal Component 3]<br> ├── conus_ltar_v5.pc4.tif [Principal Component 4]<br> ├── conus_ltar_v5.pc5.tif [Principal Component 5]<br> ├── conus_ltar_v5.pc6.tif [Principal Component 6]<br> ├── conus_ltar_v5.pc7.tif [Principal Component 7]<br> ├── LTAR_NEON_LTER_bestnetwork_workinglands.tif [Raster identifying best network, among LTAR, NEON, LTER, representing the location]<br> └── LTAR_NEON_LTER_representativeness_workinglands.tif [Representativeness of combined LTAR + NEON + LTER networks]</p> <p>PNG files:</p> <p>├── conus_ltar_constituency_workinglands.png [Constituency of LTAR network]<br> ├── conus_ltar_representativeness_workinglands.png [Representativeness of LTAR network]<br> ├── conus_ltar_v5.pc1.png [Principal Component 1]<br> ├── conus_ltar_v5.pc2.png [Principal Component 2]<br> ├── conus_ltar_v5.pc3.png [Principal Component 3]<br> ├── conus_ltar_v5.pc4.png [Principal Component 4]<br> ├── conus_ltar_v5.pc5.png [Principal Component 5]<br> ├── conus_ltar_v5.pc6.png [Principal Component 6]<br> ├── conus_ltar_v5.pc7.png [Principal Component 7]<br> ├── LTAR_NEON_LTER_bestnetwork_workinglands.png [Raster identifying best network, among LTAR, NEON, LTER, representing the location]<br> └── LTAR_NEON_LTER_representativeness_workinglands.png [Representativeness of combined LTAR + NEON + LTER networks]</p> <p><strong>Data format</strong>:</p> <p>Geospatial files are provided in Geotiff format in Lat/Lon WGS84 EPSG: 4326 projection at 30 arc second resolution, while the geospatial visualizations are provided in PNG format.</p> <p><strong>Geospatial projection</strong>: </p> <pre><code class="language-bash">GEOGCS["GCS_WGS_1984", DATUM["D_WGS_1984", SPHEROID["WGS_1984",6378137,298.257223563]], PRIMEM["Greenwich",0], UNIT["Degree",0.017453292519943295]] (base) [jbk@theseus ltar_regionalization]$ g.proj -w GEOGCS["wgs84", DATUM["WGS_1984", SPHEROID["WGS_1984",6378137,298.257223563]], PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433]] </code></pre> <p><strong>Category labels for Constituency data</strong>:</p> <table> <caption> </caption> <thead> <tr> <th scope="col">Cat</th> <th scope="col">LTAR Siite</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>Archbold-University of Florida</td> </tr> <tr> <td>2</td> <td>Central Mississippi River Basin</td> </tr> <tr> <td>3</td> <td>Central Plains Experimental Range</td> </tr> <tr> <td>4</td> <td>Eastern Corn Belt</td> </tr> <tr> <td>5</td> <td>Great Basin</td> </tr> <tr> <td>6</td> <td>Gulf Atlantic Coastal Plain</td> </tr> <tr> <td>7</td> <td>Jornada Experimental Range</td> </tr> <tr> <td>8</td> <td>Kellogg Biological Station</td> </tr> <tr> <td>9</td> <td>Lower Chesapeake Bay</td> </tr> <tr> <td>10</td> <td>Lower Mississippi River Basin</td> </tr> <tr> <td>11</td> <td>Northern Plains</td> </tr> <tr> <td>12</td> <td>Platte River High Plains Aquifer</td> </tr> <tr> <td>13</td> <td>R.J. Cook Agronomy Farm</td> </tr> <tr> <td>14</td> <td>Southern Plains</td> </tr> <tr> <td>15</td> <td>Texas Gulf</td> </tr> <tr> <td>16</td> <td>Upper Chesapeake Bay</td> </tr> <tr> <td>17</td> <td>Upper Mississippi River Basin</td> </tr> <tr> <td>18</td> <td>Walnut Gulch Experimental Watershed</td> </tr> </tbody> </table> <p><strong>Paper describing data and methods</strong>:</p> <p>Kumar, J., Coffin, A. W., Baffaut, C., Ponce-Campos, G. E., Witthaus, L., & Hargrove, W. W. (2023). Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks. In Environmental Management. Springer Science and Business Media LLC. https://doi.org/10.1007/s00267-023-01834-9</p> <p> </p>
Long-term moss monitoring network for atmospheric deposition in Germany, link to research data and scientific software
<p>Research data and scientific software related to a study that aims to restructure a long-term monitoring network using moss as biomonitor for atmospheric deposition in Germany. Data from the European Moss Survey 2005 and a statistically based methodology including a decision support system were used to design the spatial network for the 2005 survey.</p>
Coral growth data for the research article "Reconstruction of long-term sub-lethal effects of warming on a temperate coral in a climate change hotspot" in Journal of Animal Ecology
<p>This repository contains the coral growth data files used to generate the results for the following article:</p> <p> </p> <p>MJ. Vergotti, JP. D’Olivo, T. Brachert, P. Capdevila, J. Garrabou, C. Linares, P. Spreter, DK. Kersting (2024) Reconstruction of long-term sub-lethal effects of warming on a temperate coral in a climate change hot-spot. <em>Journal of Animal Ecology</em>. https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2656.14225</p> <p> </p> <p><strong>Abstract: </strong>The impact of warming on zooxanthellate corals is widespread, from tropical to temperate seas, with their associated mortalities causing global concern. The temperate coral <em>Cladocora caespitosa</em> is the only zooxanthellate coral with reef-building capacity in the Mediterranean Sea, a climate change hotspot with warming rates triple the global average. Over the past two decades, <em>C. caespitosa</em> populations have suffered severe mortality events associated with marine heatwaves (MHWs). However, with monitoring efforts beginning, at best, in the 2000s, the occurrence of MHWs before to that period, as well as the sub-lethal effects of these events remain poorly understood. Here we use sclerochronology to reconstruct the histories of past stress events and long-term sub-lethal effects on <em>C. caespitosa</em> in three locations within the NW Mediterranean Sea, each with different environmental conditions. Skeletal extension, density and calcification rates were compared to the <em>in situ</em> seawater temperature of each site to assess their relationship. Additionally, we assessed the occurrence of skeletal growth anomalies to reconstruct stress events between 1991 and 2021, a period that encompasses the onset and evolution of warming-related mass mortality events in the NW Mediterranean Sea. Our results reveal a positive association between calcification and temperature, following a latitudinal temperature gradient. However, the evolution of the likelihood distribution of growth rates in the warmest site (Columbretes Islands) since the 1990s indicates a decrease in linear extension and calcification rates during the most recent years. With the increase in the frequency of MHWs and growth anomalies during the last decade, this decline suggests a recurrence in physiological stress events. These results unravel information on the long-term impacts of warming on coral growth and highlight the potential of applying sclerochronology to reconstruct sub-lethal effects of warming using <em>C. caespitosa</em>. </p> <p> </p> <p> </p> <p><strong>Funding</strong>: This research is supported by the Horizon 2020 program of research and innovation of the European Union under the MaCoBioS grant agreement, by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project no. 401447620) and by the Spanish Ministry of Science, Innovation and Universities under the project UndResCoral (project no. PID2022-137539OA-C22). D.K.K. was supported by a Ramon y Cajal postdoctoral grant funded by the Ministry of Science and Innovation (PEICTI 2021–2023; grant no. RYC2021-033576-I). C.L. acknowledges the support by ICREA Academia. J.G. acknowledges the grant “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S) funded by AEI 10.13039/501100011033.</p>
Relative percent cover of plant species for years 2012-2017 in the Arctic Long-term Ecological Research (ARC-LTER) 1989 moist acidic tundra (MAT89) experimental plots, Toolik Field Station, Alaska.
Relative percent cover of plant species was measured in ARC-LTER 1989 moist acidic tundra experimental plots. Treatments include Control (CT), Nitrogen Phosphorus (NP), Nitrogen (N), Phosphorus (P), and Greenhouse Control (GHCT). In 1996 on unassigned plots, an experiment that manipulate herbivory presence and nutrients was started. Treatments include Control Unfenced (NFCT), Nitrogen Phosphorus Unfenced (NFNP), and Small Fenced Control (CTSF). Not all treatments were measured each year.
Illustrations for AI for multiple long-term conditions: Research Support Facility
<p>Illustrations created by <a href="http://www.scriberia.co.uk/">Scriberia</a> as part of <a href="https://www.turing.ac.uk/research/research-projects/ai-multiple-long-term-conditions-research-support-facility">AI for multiple long-term conditions: Research Support Facility.</a> The archived website link is available <a href="https://web.archive.org/web/20250212145350/https://www.turing.ac.uk/research/research-projects/ai-for-multiple-long-term-conditions-research-support-facility?__cf_chl_rt_tk=XKaDrLiiU8hmzZk2rKaWDBVpnO8exVqC4EHijqlWTIQ-1739372030-1.0.1.1-hmHFksRkdOQcBH9PsOgRVdNAatQdr3i4hFOqtyPcyZU">here</a>.</p> <p>The AIM RSF is funded by the NIHR Artificial Intelligence for Multiple Long-Term Conditions (AIM) programme (NIHR202647).</p> <p>When using any of the images, please credit them with</p> <p><em>"This image was created by <a href="http://www.scriberia.co.uk/">Scriberia</a> for AI for multiple long-term conditions: Research Support Facility and is used under a CC-BY licence."</em><br><br>We have created Alternative texts (Alt text) for all images stored in PDF and text format.</p>
International Long-Term Ecological Research Network (ILTER) Atmospheric Deposition and Stream Nitrogen Synthesis
We identified variables controlling stream nitrogen concentrations and fluxes, and how they have changed over time, by synthesizing 20 time series ranging from 5 to 51 years of data collected from forest and grassland dominated watersheds across Europe, North America, and East Asia and across four climate types (tropical, temperate, Mediterranean, and boreal) using the International Long-Term Ecological Research Network. We found declining trends in bulk ammonium and nitrate deposition, with ammonium contributing significantly more to atmospheric nitrogen deposition over time. Among sites, there were significant positive relationships between (1) precipitation and stream ammonium and nitrate fluxes and (2) atmospheric nitrogen inputs and stream nitrogen concentrations and fluxes. There were no significant relationships between air temperature and stream nitrogen export. Our long-term data shows that although nitrogen deposition is declining over time, atmospheric nitrogen inputs and precipitation remain the main predictors for nitrogen exported from forested and grassland watersheds. Overall, we also demonstrate that long-term monitoring provides understanding of ecosystems and biogeochemical cycling that would not be possible with short-term studies alone. Acknowledgements: We thank the organizers and funders of the ILTER Nitrogen Initiative Training Course and Workshop in Hokkaido, Japan in June 2016, which brought together many of the participants in this project. Templer was supported by a US National Science Foundation LTER grant NSF DEB 1637685. McDowell was supported by US National Science Foundation LTER grant NSF DEB 1831592. We are grateful to the EU Horizon 2020 funded eLTER PLUS project (Grand Agreement No. 871128) for financial support to Haase and Dirnböck. Dirnböck was also funded by the LTER-CWN project (FFG project number 858024). This study was partly supported by the Research Initiative Grants of the ILTER, Grants-in-Aid for Scientific Research (1
Climate Data Summaries for Long-Term Ecological Research Sites
This dataset contains historical climate data and climate summaries from Long-Term Ecological Research sites and other climate stations in their vicinity. It has as its basis "A Climatic Analysis Of Long-Term Ecological Research Sites" created by David Greenland, Timothy KIttel, Bruce Hayden and David Schimel in 1996 (http://climhy.lternet.edu/documents/climdes/). The dataset includes monthly data and summaries aggregating years and months to produce climatic summaries.
Long-term research and hierarchical models reveal consistent fitness costs of being the last egg in a clutch
1. Maintenance of phenotypic heterogeneity in the face of strong selection is an important component of evolutionary ecology, as are the consequences of such heterogeneity. Organisms may experience diminishing returns of increased reproductive allocation as clutch or litter size increases, affecting current and residual reproductive success. Given existing uncertainty regarding trade-offs between the quantity and quality of offspring, we sought to examine the potential for diminishing returns on increased reproductive allocation in a long-lived species of goose, with a particular emphasis on the effect of position in the laying sequence on offspring quality. 2. To better understand the effects of maternal allocation on offspring survival and growth, we estimated the effects of egg size, timing of breeding, inter- and intra-annual variation, and position in the laying sequence on gosling survival and growth rates of black brent (Branta bernicla nigricans) breeding in western Alaska from 1987–2007. 3. We found that gosling growth rates and survival decreased with position in the laying sequence, regardless of clutch size. Mean egg volume of the clutch a gosling originated from had a positive effect on gosling survival (β = 0.095, 95% CRI: 0.024, 0.165), and gosling growth rates (β = 0.626, 95% CRI: 0.469, 0.738). Gosling survival (β = -0.146, 95% CRI: -0.214, -0.079) and growth rates (β = -1.286, 95% CRI: -1.435, -1.132) were negatively related to hatching date. 4. These findings indicate substantial heterogeneity in offspring quality associated with their position in the laying sequence. They also potentially suggest a trade-off mechanism for females whose total reproductive investment is governed by pre-breeding state. 20-Mar-2020
Chemical variations in Quercus pollen as a tool for taxonomic identification: implications for long-term ecological and biogeographical research
<p><strong>Aim</strong> </p> <p>Fossil pollen is an important tool for understanding biogeographic patterns in the past, but the taxonomic resolution of the fossil-pollen record may be limited to genus or even family level. Chemical analysis of pollen grains has the potential to increase the taxonomic resolution of pollen, but present-day chemical variability is poorly understood. This study aims to investigate whether a phylogenetic signal is present in the chemical variations of <em>Quercus</em> L. pollen and to assess the prospects of chemical techniques for identification in biogeographic research.</p> <p><strong>Location</strong> </p> <p>Portugal</p> <p><strong>Taxon</strong> </p> <p>Six taxa (five species, one subspecies) of <em>Quercus</em> L., <em>Q. faginea, Q. robur, Q. robur</em> ssp. <em>estremadurensis, Q. coccifera, Q. rotundifolia</em> and <em>Q. suber</em> belonging to three sections: <em>Cerris, Ilex</em>, and <em>Quercus</em> (<a href="https://www.biorxiv.org/content/10.1101/761148v2#ref-13">Denk, Grimm, Manos, Deng, & Hipp, 2017</a>)</p> <p><strong>Methods</strong> </p> <p>We collected pollen samples from 297 individual <em>Quercus</em> trees across a 4° (∼450 km) latitudinal gradient and determined chemical differences using Fourier-transform infrared spectroscopy (FTIR). We used canonical powered partial least-squares regression (CPPLS) and discriminant analysis to describe within- and between-species chemical variability.</p> <p><strong>Results</strong> </p> <p>We find clear differences in the FTIR spectra from <em>Quercus</em> pollen at the section level (<em>Cerris</em>: ∼98%; <em>Ilex</em>: ∼100%; <em>Quercus</em>: ∼97%). Successful discrimination is based on spectral signals related to lipids and sporopollenins. However, discrimination of species within individual <em>Quercus</em> sections is more difficult: overall, species recall is ∼76% and species misidentifications within sections lie between 18% and 31% of the test-set.</p> <p><strong>Main Conclusions</strong> </p> <p>Our results demonstrate that subgenus level differentiation of <em>Quercus</em> pollen is possible using FTIR methods, with successful classification at the section level. This indicates that operator-independent FTIR approaches can surpass traditional morphological techniques using the light microscope. Our results have implications both for providing new insights into past colonisation pathways of <em>Quercus</em>, and likewise for forecasting future responses to climate change. However, before FTIR techniques can be applied more broadly across palaeoecology and biogeography, our results also highlight a number of research challenges that still need to be addressed, including developing sporopollenin-specific taxonomic discriminators and determining a more complete understanding of the effects of environmental variation on pollen-chemical signatures in <em>Quercus</em>.</p>
Questionnaire and interview guidelines related to Süsser et al. (2024) on how the COVID-19 pandemic changed stakeholder engagement processes in sustainability research in the long-term
<p>The survey questionnaire and the interview guidelines have been designed in the framework of the EU H2020 projects SENTINEL to study the impact of the coronavirus disease 2019 (COVID-19) on the stakeholder engagement processes in susatinability research in the longterm. We conducted interviews with researchers and engaged stakeholders, using a semi-structured interview guideline. We designed the survey as an explorative, semi-quantitative, self-completion online questionnaire, using the online tool “LimeSurvey”. The survey was reworked based on our previous survey. The study was a follow-up study on our own work (<em>Süsser, D., Ceglarz, A., Stavrakas, V., & Lilliestam, J. COVID-19 vs. stakeholder engagement: the impact of coronavirus containment measures on stakeholder involvement in European energy research projects [version 1; peer review: awaiting peer review]. Open Research Europe 2021,1:57. doi: <a href="https://doi.org/10.12688/openreseurope.13683.1">https://doi.org/10.12688/openreseurope.13683.1</a>). </em></p> <p>If you use this questionnaire or the interview guideline in an academic publication, please cite the following article:</p> <p><em>Süsser, D., Schibline, A. Ceglarz, A., Lilliestam, J., Stavrakas, V., & Schweizer, P.J. (2024), How the COVID-19 pandemic changed stakeholder engagement processes in sustainability research in the long-term, F1000 Research (to be published).</em></p> <p><em> </em></p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.