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24 results for “plot size”
Soil aggregate size distribution and particulate organic matter content from Arctic LTER moist acidic tundra nutrient addition plots, Toolik Field Station, Alaska, sampled July 2011.
Soil aggregate size distribution, aggregate carbon and nitrogen, and light fraction carbon were determined for mineral soils in moist acidic tundra. Soil was sampled in control, and N+P plots of the Arctic LTER Moist Acidic Tundra plots established in 1989 and 2006.
Figure 2. Box-plot head centroid size. A. Rhodnius prolixus instars. B in Head geometric morphometrics of two Chagas disease vectors from Venezuela
Figure 2. Box-plot head centroid size. A. Rhodnius prolixus instars. B. Triatoma maculata instars. Abbreviation: I—First instar; II— Second instar; III—Third instar; IV—Fourth instar; V—Fifth instar; F—Adult female; M—Adult male.
Fig. 4. Partial dependence plot for topographic Fig. 5 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance
Fig. 4. Partial dependence plot for topographic Fig. 5. Partial dependence plot for terrain roughness wetness index (TWI). index (tri).
Fig. 3. Partial dependence plot for BIO17 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance
Fig. 3. Partial dependence plot for BIO17 = Precipitation of Driest Quarter; gray area = 95 % confidence interval.
Text-fig. 4. Bivariate plots of the upper teeth (M2 – P3) of small to medium sized Miocene hyaenodonts from African localities. Data source: Pilgrim (1912, 1914, 1932), Colbert (1935), Savage (1965), Barry (1988), Morales et al. (1998a, 2007), Holroyd (1999), Rasmussen et al. (2009), Borths et al. (2016), Borths and Seiffert (2017). in New Hyaenodonts (Ferae, Mammalia) From The Early Miocene Of Napak (Uganda), Koru (Kenya) And Grillental (Namibia)
Text-fig. 4. Bivariate plots of the upper teeth (M2 – P3) of small to medium sized Miocene hyaenodonts from African localities. Data source: Pilgrim (1912, 1914, 1932), Colbert (1935), Savage (1965), Barry (1988), Morales et al. (1998a, 2007), Holroyd (1999), Rasmussen et al. (2009), Borths et al. (2016), Borths and Seiffert (2017).
Text-fig. 3. Bivariate plots of the lower teeth (m3 – m2) of small to medium sized Miocene hyaenodonts from African localities. Data source: Pilgrim (1912, 1932), Colbert (1935), Savage (1965), Barry (1988), Morales et al. (1998a, 2003, 2007, 2008, 2010), Holroyd (1999), Morlo et al. (2007), Rasmussen et al. (2009), Borths et al. (2016), Borths and Seiffert (2017). in New Hyaenodonts (Ferae, Mammalia) From The Early Miocene Of Napak (Uganda), Koru (Kenya) And Grillental (Namibia)
Text-fig. 3. Bivariate plots of the lower teeth (m3 – m2) of small to medium sized Miocene hyaenodonts from African localities. Data source: Pilgrim (1912, 1932), Colbert (1935), Savage (1965), Barry (1988), Morales et al. (1998a, 2003, 2007, 2008, 2010), Holroyd (1999), Morlo et al. (2007), Rasmussen et al. (2009), Borths et al. (2016), Borths and Seiffert (2017).
SGS-LTER CO2 Elevation Study: Stipa comata basal size and plant density per Open Top Chamber plot on the Central Plains Experimental Range, Nunn, Colorado, USA 1997 - 2001
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82454. At the end of the Open Top Chamber experiment the number and basal size of Stipa comata plants in ambient and elevated (720ppm) chambered and unchambered plots was measured. There was a greater number of small plants and seedlings in the elevated CO2 plots. This research was conducted at the Central Plains Experimental Range, near Nunn, CO; lat.40degrees 40 minutes N; long. 104 degrees 45 minutes W in the shortgrass steppe region of NE Colorado, USA and as a collaboration between SGS-LTER and USDA-ARS researchers.
Sediment grain size in seagrass restoration plots in the Virginia coastal bays, 2010-2016
This dataset contains particle size distributions for sediment samples collected from Z. marina restoration plots in Hog Island Bay and South Bay, VA. Samples were collected every three years starting in 2010 from 64 sites in Hog Island Bay (58 restored seagrass sites, 6 bare sites), and 12 sites in South Bay (6 restored seagrass sites, 6 bare sites). Bare sites in South Bay were no longer sampled after 2013, due to colonization of the sites by seagrass. Restored sites were seeded between 2001-2008; plot-level particle size distributions were combined based on the age of the plots during each sampling year.
Canopy size, gap size, plant height, and scaled height in NEAT plots at Jornada Basin LTER, Summer 2017
This data package contains estimates of vegetation indicators derived from UAV overflights and comparable field observatons at the NEAT experiment in the Jornada Basin of southern New Mexico, USA. The purpose of this study is to develop a UAV-based remote sensing method that can estimate vegetation indicators in arid and semiarid rangelands. This method was used to characterize six rangeland indicators (canopy size, bare soil gap size, plant height, scaled height, vegetation cover, and bare soil cover) in a semiarid grass-shrub ecosystem at the NEAT site. The drone-based estimates were validated with field measurements by using the standard transect methods (gap intercept, drop disk, and line-point intercept methods) in the spring and summer of 2017. Further, we use these results to show possible applications of drone-based products on arid and semiarid rangelands: the spatially explicit input of an ecological model, to detect and characterize non-stationarity, and to detect landscape anisotropy.
Data from: Informative plot sizes in presence-absence sampling of forest floor vegetation
1. Plant communities are attracting increased interest in connection with forest and landscape inventories due to society's interest in ecosystem services. However, the acquisition of accurate information about plant communities poses several methodological challenges. Here we investigate the use of presence-absence sampling with the aim to monitor state and change of plant density. We study what plot sizes are informative, i.e. the estimators should have as high precision as possible. 2. Plant occurrences were modeled through different Poisson processes and tests were developed for assessing the plausibility of the model assumptions. Optimum plot sizes were determined by minimizing the variance of the estimators. While state estimators of similar kind as ours have been proposed in previous studies, our tests and change estimation procedures are new. 3. We found that the most informative plot size for state estimation is 1.6 divided by the plant density, i.e. if the true density is 1 plant per square meter the optimum plot size is 1.6 square meters. This is in accordance with previous findings. More importantly, the most informative plot size for change estimation was smaller and depended on the change patterns. We provide theoretical results as well as some empirical results based on data from the Swedish National Forest Inventory. 4. Use of too small or too large plots resulted in poor precision of the density (and density change) estimators. As a consequence, a range of different plot sizes would be required for jointly monitoring both common and rare plants using presence-absence sampling in monitoring programmes.
Fig. 7. Bayesian Skyline Plot analysis showing population size over time. The x in Echinoderes galadrielae Grzelak & Sørensen 2022, sp. nov.
Fig. 7. Bayesian Skyline Plot analysis showing population size over time. The x-axis is the time to the present in years, while the y-axis is the product between the effective population size (Ne) and the generation length (t) in a log scale. The mean estimate (black solid line) and 95% highest probability density limits (grey area) are shown.
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The model codes, data, and plot scripts used in the paper, "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>7_experiments.zip contains modified model code and output data of each experiment in this study.</li> <li>off-line test.zip contains off-line test code and output data.</li> <li>plot_scripts.zip are the NCL scripts used for figures in the paper.</li> </ul>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The model codes, data, and plot scripts used in the paper, "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>Figs&Table are the NCL scripts used for figures and table in the paper.</li> <li>Model_Results contains output data of each experiment in this study.</li> <li>Mods_Scripts contains modified model code.</li> <li>Offline_Code contains off-line test code.</li> </ul>
FIGURE 2. Scatter plots for Dataset 2 in GroupStruct: An R Package for Allometric Size Correction
FIGURE 2. Scatter plots for Dataset 2 (Amolops) showing the regression slopes of each trait variate plotted against SVL. Data were log-transformed but not size-adjusted. The blue line represents the best-fit regression line. Within-species slopes are presented in Table 1. Points represent individual measurements.
FIGURE 1. Scatter plots for Dataset 1 in GroupStruct: An R Package for Allometric Size Correction
FIGURE 1. Scatter plots for Dataset 1 (Cyrtodactylus) showing the regression slopes of each trait variate plotted against SVL. Data were log-transformed but not size-adjusted. The blue line represents the best-fit regression line. Within-species slopes are presented in Table 1. Points represent individual measurements.
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The code, scripts, and data used in the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>All Figures&Table and their corresponding NCL scripts are under the directory of Figs&Table. </li> <li>The modified model code, corresponding original model code, and model run scripts are under the directory of Mods_Scripts.</li> <li>The postprocessing NCL scripts, which select useful variables from simulation results, are under the directory of PostProcessing.</li> <li>The zonal mean data from model results used for making figures and corresponding data processing scripts are under the directory of Model_Results.</li> <li>The FORTRAN code used for offline tests is under the directory of Offline_Code.</li> <li>The code, data, and NCL scripts used for the figures and table in the Appendix are under the directory of Appendix.</li> </ul>
Figure 2. Bubble plot showing diamondback terrapin clutch sizes recorded 1998–2012 in Long-term increases in clutch size in common snapping turtles (Chelydra serpentina) and diamondback terrapins (Malaclemys terrapin)
Figure 2. Bubble plot showing diamondback terrapin clutch sizes recorded 1998–2012. Bubble size indicates the number of clutches of the same size.
Figure 1. Bubble plot showing snapping turtle clutch sizes recorded 2004–2015 in Long-term increases in clutch size in common snapping turtles (Chelydra serpentina) and diamondback terrapins (Malaclemys terrapin)
Figure 1. Bubble plot showing snapping turtle clutch sizes recorded 2004–2015. Bubble size indicates the number of clutches of the same size.
Data from: Informative plot sizes in presence-absence sampling of forest floor vegetation
Open the record for dataset details and reuse information.
Presence-absence sampling for estimating plant density using survey data with variable plot size
1. Presence-absence sampling is an important method for monitoring state and change of both individual plant species and communities. With this method only the presence or absence of the target species is recorded on plots and thus the method is straightforward to apply and less prone to surveyor judgment compared to other vegetation monitoring methods. However, in the basic setting all plots must be equally large or otherwise it is unclear how data should be analyzed. In this study we propose and evaluate five different methods for estimating plant density based on presence-absence registrations from surveys with variable plot sizes. 2. Using artificial plant population data as well as empirical data from the Swedish National Forest Inventory we evaluated the performance of the proposed methods. The main analysis was conducted through sampling simulation in the artificial populations, whereby bias and variance of density estimators for the different methods were quantified and compared. 3. Both for state and change estimation of plant density, we found that the best method to handle variable plot size was to perform generalized least squares regression, using plot size as an independent variable. Methods where plots smaller than a certain threshold were excluded or their registrations recalculated were, however, almost as good. Using all registrations as if they were obtained from plots with the nominal plot size resulted in substantial bias. 4. Our findings are important for plant population studies in a wide range of environmental monitoring programmes. In these programmes plots are typically randomly laid out and may be located across boundaries between different land use or land cover classes, resulting in subplots of variable size. Such splitting of plots is common when large plots are used, e.g. with the 100 m2 plots used in the Swedish National Forest Inventory. Our methods overcome problems to estimate plant density from presence-absence data observed in plots that vary in size.
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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)
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DANDI Archive for NWB datasets
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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.