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22,710 results for “Plant”
Fall 2018 plant monitoring survey -- shoot height and flowering status of plants in permanent plots at GCE sampling sites 1-10
A quadrat survey was conducted in October 2018 to measure the species and size distribution of plants at 10 GCE LTER sampling sites. The quadrats were established as permanent plots at GCE sampling sites in October 2000 by placing wooden stakes at random locations across two nominal zones at each site, designated based on marsh structure (creekbank and high marsh). New plots were added each year as necessary to replace those lost due to catastrophic wrack disturbance or creek bank erosion. The plots were visually surveyed and the species, shoot height, and flowering status was recorded individually for each shoot over 10 cm in height present in each plot. Observations from plots exhibiting signs of disturbance were noted in a separate data set (PLT-GCEM-1801). This survey will be repeated annually to assess changes in plant distribution and biomass in relation to environmental changes documented by other GCE LTER monitoring efforts.
Fall 2018 plant monitoring survey -- biomass calculated from shoot height and flowering status of plants in permanent plots at GCE sampling sites 1-10
The biomass of plants surveyed in permanent plots at 10 GCE LTER sampling sites in October 2018 was estimated based on allometric relationships between biomass and shoot height and flowering status derived for each site, zone, and species in October 2002 and October 2008. Biomass was calculated for dominant species, including Spartina alterniflora, S. cynosuroides, Juncus roemerianus, and Zizaniopsis miliacea, as well as rarer species including Scirpus spp, Panicum spp. And Typha angustifolia. This data set is based on GCE plant monitoring survey data set PLT-GCEM-1811a, and allometric relationships were based on GCE data sets PLT-GCEM-0211b, PLT-GCEM-0711, and PLT-GCEM-2011.
Fall 2019 plant monitoring survey -- shoot height and flowering status of plants in permanent plots at GCE sampling sites 1-10
A quadrat survey was conducted in October 2019 to measure the species and size distribution of plants at 10 GCE LTER sampling sites. The quadrats were established as permanent plots at GCE sampling sites in October 2000 by placing wooden stakes at random locations across two nominal zones at each site, designated based on marsh structure (creekbank and high marsh). New plots were added each year as necessary to replace those lost due to catastrophic wrack disturbance or creek bank erosion. The plots were visually surveyed and the species, shoot height, and flowering status was recorded individually for each shoot over 10 cm in height present in each plot. Observations from plots exhibiting signs of disturbance were noted in a separate data set (PLT-GCEM-1801). This survey will be repeated annually to assess changes in plant distribution and biomass in relation to environmental changes documented by other GCE LTER monitoring efforts.
Fall 2019 plant monitoring survey -- biomass calculated from shoot height and flowering status of plants in permanent plots at GCE sampling sites 1-10
The biomass of plants surveyed in permanent plots at 10 GCE LTER sampling sites in October 2019 was estimated based on allometric relationships between biomass and shoot height and flowering status derived for each site, zone, and species in October 2002 and October 2008. Biomass was calculated for dominant species, including Spartina alterniflora, S. cynosuroides, Juncus roemerianus, and Zizaniopsis miliacea, as well as rarer species including Scirpus spp, Panicum spp. And Typha angustifolia. This data set is based on GCE plant monitoring survey data set PLT-GCEM-1911a, and allometric relationships were based on GCE data sets PLT-GCEM-0211b, PLT-GCEM-0711, and PLT-GCEM-2011.
Estimation of Abundance and Distribution of Salt Marsh Plants from Images Using Deep Learning
Recent advances in computer vision and machine learning, most notably deep convolutional neural networks (CNNs), are exploited to identify and localize various plant species in salt marsh images. Three different approaches are explored that provide estimations of abundance and spatial distribution at varying levels of granularity in terms of spatial resolution. In the coarsest-grained approach, CNNs are tasked with identifying which of six plant species are present/absent in large patches within the salt marsh images. CNNs with diverse topological properties and attention mechanisms are shown capable of providing accurate estimations with > 90% precision and recall in the case of the more abundant plant species whereas the performance of the CNNs is observed to decline in the case of less common plant species. Estimation of percent cover of each plant species is performed at a finer spatial resolution, where smaller image patches are extracted and the CNNs tasked with identifying the plant species or substrate at the center of the image patch. In an ecological setting, several image patches (~100) are extracted and classified using this approach to estimate the percent cover of the various plant species in the image. For the percent cover estimation task, the CNNs are observed to exhibit a performance profile similar to that for the presence/absence estimation task, but with an ~ 5–10% reduction in precision and recall. Finally, estimation of the spatial distribution of the various plant species is performed via semantic segmentation of the input images at the finest level of granularity in terms of spatial resolution. The Deeplab-V3 semantic segmentation architecture is observed to provide very accurate estimations for abundant plant species; however, a significant degradation in performance is observed in the case of less abundant plant species and, in extreme cases, rare plant classes are seen to be ignored entirely. Overall, a clear trade-off is observed between
GCE-LTER Altamaha River Plant Community Monitoring Survey in October 2020
A quadrat survey was conducted in October 2020 to measure the species and size distribution of plants at 3 sampling sites on the creekbank of the Altamaha River. The sites were chosen to capture the transition from Spartina alterniflora to Spartina cynosuroides (site SCSA) and the transition from Spartina cynosuroides to Zizaniopsis miliacea (sites ZSC1 and ZSC2). The quadrats were established as permanent plots in October 2012 by placing PVC stakes along the creekbank at each site. Plots were evenly spaced, but were not randomly located because the goal was to start with mixtures of vegetation in most of the plots, and vegetation was distributed in patches along the creekbanks. Therefore, these plots provide useful measures of vegetation change, but are not a random sample of the vegetation at the site. Plots will be replaced each year as necessary to replace any lost to disturbance. The plots were visually surveyed and the species, shoot height, and flowering status was recorded individually for each shoot over 10 cm in height present in each plot. Observations from plots exhibiting signs of disturbance were noted in a separate data set. This survey will be repeated annually to assess changes in plant distribution and biomass in relation to environmental changes documented by other GCE LTER monitoring efforts.
Species Distribution Modeling of Carnivorous Plants Worldwide
Forecasting how carnivorous plant species will respond to climatic change is a key issue in their conservation and management but presents a number of challenges. These challenges derive from interactions between the relatively simplistic statistical methods typically used to forecast species responses to climatic change, which to date have been limited mainly to species distribution models (“SDMs) and particular aspects of the ecology of carnivorous plants, including their rarity, habitat specialization, and limited dispersal ability. The small ranges and oftentimes low local abundance of carnivorous plants provide few occurrence records, which increase the potential for poorly or over-fitted SDMs and misspecification of relationships with their “optimal” environments. The unique habitats in which carnivorous plants often grow also are difficult to characterize using the basic temperature and precipitation data that often undergird SDMs. Rather, habitats in which carnivorous plants are common often are decoupled from broader climatic patterns (e.g., many retain high soil moisture even during seasonal drought) and may be associated with frequent disturbance. Last, dispersal limitation also may constrain range shifts of carnivorous plants as the climate changes. These three issues raise two related questions that are critical for understanding and forecasting the future of carnivorous plants. First, to what extent are current carnivorous plants distributions constrained by climate; and second, how readily, if at all, might carnivorous plants disperse to colonize new habitat as it becomes climatically suitable? We estimated the vulnerability of carnivorous plants to climatic change in light of challenges identified with SDMs in general and their particular application to these unique species. We combined two approaches: “ensembles of small models”, which attempt to deal with the challenges of fitting SDMs for data-limited species; and “bioclimatic velocity”, which is
Density and cover of winter annual plants in three harvester ant habitats at the Jornada Basin LTER site, 1987
This dataset contains plant cover and density data collected in three harvester ant (Pogonomyrmex rugosus) nesting habitats at the Jornada Basin LTER site in 1987. The purpose of this investigation was to answer three general questions: 1. How does the modification of soil properties and the ratios of resources (e.g., water-N) by ants alter species assemblages of winter annual plants at the edge of the ant nests? 2. How does the "spring cleaning", clipping, predation or herbivory by ants affect success of the winter annual plants at the edge of ant nests? 3. Are there significant differences in the floristic assemblage and belowground standing crop (root biomass) between the edge of ant nest and the surrounding unaffected soils? Variables included in the dataset include density and cover of all winter annual plants measured at regular intervals between January and May of 1987. Density is expressed as the number of individuals of a species per square meter. The cover of each species was calculated as the area covered by a perpendicular (not vertical) projection of its aerial parts onto the ground surface and expressed in covered area (cm squared) per square meter. This study was completed in 1987.
Cover and frequency of biological soil crust community types, moss species, vascular plants, and abiotic land surface features, on gypsum & non-gypsum soils from the Chihuahuan and Mojave Deserts in 2023
This dataset contains raw and calculated percent cover and frequency data for biological soil crust (hereafter biocrust) functional groups, vascular plant functional groups, and abiotic land surface features on and off gypsum soils in the northern Chihuahuan and eastern Mojave Deserts. Abundance data were obtained from 20 study sites total, 10 located on soils derived from gypsum parent material and 10 located on soils derived from non-gypsum parent materials. Sites were grouped into 10 pairs, in which every gypsum site was partnered with a non-gypsum site located in the same region. Apart from soil type, partnered-site characteristics (topography, climate, elevation, slope, aspect, and presence of biocrusts) were held relatively constant. At each site, cover and frequency assessments were made using the line-point intercept method (LPI) and frequency quadrats (1.0 m^2), respectively. Biocrust functional groups included the following crusts: lichen, moss, incipient algal, light algal, dark algal, unknown photosynthetic crust, and vagrant cyanobacteria. Vascular plant categories included: perennial forbs, perennial graminoids, annual forbs, annual graminoids, subshrub, shrub, Yucca, and cacti. Abiotic land surface features included: woody litter, herbaceous litter, bare soil, rock, bedrock, and animal feces. Moss crusts identified within cover and frequency analyses were sampled, and classified to species level via microscopy. The resulting percent cover and frequency data was used to understand differences in biocrust and moss species abundance and diversity on and off gypsum soils; furthermore, how biocrust and moss species abundance was associated with the measured environmental variables. Soil physical and chemical data from this study can be accessed at knb-lter-jrn.210616002. This study and dataset are complete.
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
warmXtrophic plant-soil interaction greenhouse experiment, Kellogg Biological Station, Hickory Corners, MI, 2021
Climate warming influences plant communities through both direct effects, such as changes in temperature, and indirect pathways mediated by changes in soil microbial communities. These microbe-mediated indirect effects may alter plant traits and ecosystem dynamics in ways that are often overlooked in studies focused solely on the direct impacts of warming. To test these microbe-mediated indirect effects, we used field-conditioned soil from a 7-year (2015-2021) warming experiment (warmXtrophic) in an early successional plant community in Hickory Corners, Michigan, USA at Michigan State University's Kellogg Biological Station Long-Term Ecological Research site. In a greenhouse during 2021, we assessed how warmed versus ambient soil inocula influenced plant growth and traits of two species: Trifolium pratense (red clover) and Phleum pratense (Timothy grass). We measured above, below, and total biomass, height, number of leaves, timing of germination, leaf % carbon and nitrogen, C:N ratio, specific leaf area (SLA), and greenness (a proxy for chlorophyll content). We also measured the timing of emergence of the cotyledon and first leaf for Trifolium pratense.
Plant Community and Ecosystem Responses to Long-term Fertilization & Disturbance at the Kellogg Biological Station, Hickory Corners, MI (1989 to 2019)
Dataset AbstractThis work is part of the long-term sampling and monitoring of successional dynamics in abandoned fields – and responses to N-fertilization. Data from this research has been, and will continue to, contribute to LTER cross-site analysis of plant community dynamics, diversity-productivity, and responses to fertilization and disturbance.N-fertilized and tilled (disturbed) microplots are located in the NW corner of all treatment 7 (early successional communities) on the LTER main site. Experimental treatments are: 1) Nitrogen addition vs. no nitrogen addition and 2) Annual disturbance vs. undisturbedoriginal data source http://lter.kbs.msu.edu/datasets/60
NGE01 Chronic Addition of Nitrogen Gradient Experiment (ChANGE): Assessing threshold responses of plant community composition and ecosystem processes at Konza Prairie
Chronic nutrient additions can lead to drastic shifts in the plant community through time, both within tallgrass prairie in other grassland ecosystems worldwide. Nutrient addition experiments have answered many questions about patterns of diversity loss and community shifts; however, the level of nutrients which must be added to cause community shifts is unknown. To date, all nitrogen (N) addition experiments at Konza have added 10 g m-2 (e.g., NutNet Plots; Phosphorus (P) Plots; Belowground Plots), yet current rates of N deposition are one-tenth of that level. Even predicted rates of future N deposition in grasslands are not expected to exceed 5 g m-2 by the year 2050 and will likely be around 2 g m-2 for most of the US. This mismatch begs the question will 10 g/m2 affect grasslands the same way 2 or 5 g m-2 will? There are two main goals for this long-term experiment (1) to identify the nutrient threshold needed to drive plant community change with nutrient additions, and (2) to determine what factors underlie those threshold responses (build up of nutrients, mycorrhizal loss, invertebrate herbivory). Konza ChANGE is part of a multi-site experiment spanning grasslands on two different continents: North America – tallgrass prairie (KNZ) and shortgrass steppe (SGS), and China – three sites in Inner Mongolia. By including multiple grasslands, we expand our ability to make generalizations about how grasslands are affected by N additions, and whether thresholds, if they exist, vary with precipitation, natural nutrient availability, and species identity/composition. Research Questions: (1) Do ecosystems have N tolerance thresholds above which community composition will change, and does that differ between grassland types (i.e. mesic and xeric grasslands)? (2) Does adding a large amount of nutrients in one season result in an equivalent community change as adding a small amount over multiple years? (For example does 5 g m-2 for 6 years create the same community change as
AOP01 Correspondence between plant traits and NEON Airborne Observatory Platform (AOP) data at Konza Prairie (2017)
Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Observatory Ecological Network (NEON) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, allowing high-resolution trait mapping. However, the reliability of these data depend on establishing rigorous links with in-situ field measurements. We tested the accuracy of NEON’s readily available AOP derived data products – Leaf Area Index, Total biomass, Ecosystem structure (Canopy height model; CHM), and Canopy Nitrogen by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The weakest relationships were between AOP Canopy Nitrogen and ground-based measures of Nitrogen, as well as the CHM and ground-based canopy height measurements. We also examined how well the full reflectance spectra (380-2500 nm), as opposed to derived products, could predict vegetation traits using partial least-squares regression models. Only one of the eight traits examined, Nitrogen, had an R2 of more than 0.25. For all vegetation traits, R2 ranged from 0.08-0.29 and the root mean square error of prediction ranged from 14-64%. Our results suggest that currently available AOP derived data products are unreliable, at least at this grassland site, and should not be used without extensive ground-based validation. Relationships using the full reflectance spectra may be more promising, although additional assessment of varying spatial scales of field and AOP data, as well as corrections and data pre-processing to improve data quality, are recommended. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area,
RIV02 Plant transect data for the N2B experiment at Konza Prairie
Woody plant expansion is well-known to alter plant community composition, often including a decrease in plant biodiversity, such as species richness. This dataset was used to determine if plant communities are able to “bounce back” after repeated woody plant removal, returning to plant community more similar to tallgrass prairie without woody plant encroachment. Woody plant encroachment can affect plant communities in two key ways: increasing competition for light and limiting grassland propagules (if woody encroachment is widespread). Therefore, we also included a treatment in the riparian removal where seeds of native prairie plants were added to reduce propagule limitation. This data suggests that despite repeated tree removal, the plant community has not returned to a grassland state. Instead, shrubs and herbaceous woodland plants are dominant. Adding grassland propagules had no discernable impact.
PRP02 Plant diversity, richness, and plant species cover in konza prairie restoration heterogeneity plots, since 1998
The experiment is a randomized complete block design with four whole plot hetereogeneity treatments replicated within each of four blocks (n=16 whole plots). The whole plot treatments were created using different combinations of soil depth and nutrient manipulations. The control plots contained no depth or nutrient manipulations. The maximum hetereogeneity plots contained three 2 m x 8 m vertical strips assigned to ambient, enriched and reduced N treatments and four 2 m x 6 m horizontal strips assigned to deep and shallow soil to result in six treatment combinations. The maximum heterogeneity plots are a split-block design. Every plot contained 12 subplots (2 m x 2 m) for sampling. Prior to sowing, all of the plots were excavatedto a depth of approximately 25 cm. Natural limestone slabs were laid in strips assigned to the shallow soil treatment. The soil from all plots was then replaced, leveled, and disked (2-3 cm deep). In February 1998, we incorporated sawdust (49% C; C:N ratio=122) into the strips assigned to the reduced-N treatment. The average C concentration and bulk density in the surface 15 cm following long-term cultivation was 1.5% and 1.2 g cm-3, respectively. Sawdust was tilled into the soil at a rate of 5.5 kg dry wt./m2 to achieve a C concentration representative of native prairie soil (approx. 3% C). Surface applications of granular sugar were initiated in 2004 at a rate of 200 g sucrose m-2 (84.22 g C/m2) 3-4 times each growing season. Strips assigned to the enriched-N treatment were fertilized with 5 g N m2/y (applied as ammonium-nitrate) in July of the first growing season and early June of each subsequent years.
Wisconsin Lake Plants - multi source database of lake plant abundance 1930 - 2004
This data set provides sampling-point by sampling-point macrophyte data for lakes sampled by a number of agencies in Wisconsin. The relational tables in this dataset were originally used to generate plant community tables. This dataset contains detailed and recent data from approximately the 1970s onward. Sampling timing and intensity varied. Table DATSOUR contains sources of data for tables AQUAPLT2 and LAKEHAB. Table AQUAPLT2 gives an estimate of plant density at each sample point. Table MAXDEPLNG has initial lake parameters derived from data in AQUAPLT2 and LAKEHAB Table LAKEHAB contains habitat characteristics at macrophyte sampling locations. Table PLTNAME has species information for plants in tables AQUAPLT2 and LAKESPEC. Table LAKES contains information for lakes included in this dataset. Table COUNTY contains information associated with the counties where the lakes in the AQUAPLT2 dataset and the LAKESPEC dataset are located. . Sampling Frequency: varies Number of sites: 1938
Plant species composition and aboveground biomass data for Saddle snowfence, 1996 - ongoing.
Bowman et al. (1993) have demonstrated that alpine tundra is sensitive to nitrogen and phosphorus additions. Changes in productivity and species composition (belatedly) follow chronic fertilization. Exactly how this response is mediated by changes in precipitation is unknown but can be addressed using the snowfence experiment. Moreover, replication of the experiment will allow for additional sampling of biotic and abiotic components and processes not possible with the size of the Bowman plots. In 1993, 64 2x2m plots were placed in dry and mesic sites both within and outside of the snowfence area, so that 4 replicates of each treatment (nitrogen addition, phosphorus addition, nitrogen and phosphorus addition, and control) could be established in each meadow type with and without snowpack augmentation. 16 additional plots were established on a wet meadow site, but since a corresponding type site did not exist in the snowfence area, there was no snowpack manipulation for the wet meadow plots. In 2016, 9 existing plots were selected and 6 control plots added for assessing recovery from augmented snowpack treatment. Aboveground biomass, species richness, and species composition have been collected periodically since 1996.
Plant recruitment and seed quality in the Black Sand extended growing season experiment for East Knoll, Audubon, Lefty, and Trough sites, 2018 - 2020.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites, each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows and a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot at each site by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to control plots after snow had naturally melted. We used open top warming chambers (OTCs) to increase summer temperature in three subplots within each of the 10 x 40 m plots. This dataset includes measurements of plant recruitment and seed quality.
Plant root simulator nutrient availability data in the black sand extended growing season experiment, 2018 - 2020.
As a result of climate change, the Rocky Mountain Front Range is experiencing warmer summers and earlier snowmelt. Due to the importance of snow for regulating soil temperature, growing season length, and available moisture in alpine ecosystems, even small shifts in the snow-free period could have large impacts. The focus of the Black Sand Extended Growing Season Length Experiment is to examine how terrain-related differences in climate exposure influence the way alpine habitats respond to climate change via earlier snowmelt. To simulate how climate exposure may affect plant communities, NWT LTER researchers established 5 experimental sites, each containing a pair 10 x 40m rectangular plots. These sites include north and south facing aspects, subalpine and alpine tundra meadows and a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot at each site by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to control plots after snow had naturally melted. We used open top warming chambers (OTCs) to increase summer temperature in three subplots within each of the 10 x 40 m plots. This dataset includes plant nutrient availability as measured using plant root simulator probes.
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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
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