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3,737 results for “plant species”
Plant community responses to functional group and species removals along biodiversity experiment vegetation transects at the Jornada Basin LTER site, 1997-2002
This dataset contains vegetative cover data of plots that have had various plant functional groups or species experimentally removed at the Jornada Basin LTER site in southern New Mexico, USA. This data was collected with the objective to distinguish the differential effects of plant community biomass, functional groups, and biodiversity within functional groups on ecosystem and plant community function. To make these distinctions, treatments were established by the selective removal of plant species or functional groups within experimental plots. There are eight treatments: control (C, no removals); four functional group removal treatments (PG, perennial grass removed; S, shrubs removed; SSh, subshrubs removed; Succ, succulents removed), and three species richness manipulation treatments. Richness manipulations included a simplified treatment (Simp), where only the single most abundant species of each growth form is preserved and all other species in the growth form are removed, a reduced‐Larrea treatment (rL), where the Larrea is assumed to be the dominant and is removed while minority components remain, and a reduced-Prosopsis treatment (rP), where Prosopis rather than Larrea is removed as the shrub dominant. Following treatments, vegetative data was collected by sampling each plot along three transects twice a year (Spring and Fall) for 5 years from 1997-2002 (no data collected in 1998). This data set consists of the date of collection, plot number, treatment type, transect number, quadrat number, species codes, two diameters, height, condition, count, record IDs, and error codes. This study is complete.
Plant species composition in black sand extended growing season experiment, 2018 - 2023.
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 in a range of hydrological conditions (e.g. dry meadows, moist meadows, wet meadows). We accelerated snowmelt in one plot of each block by adding chemically inert black sand, while keeping the second plot as an unmanipulated control; black sand was added to these plots after snow had naturally melted. This dataset includes measurements of plant species composition.
Species diversity and plant dominance influence grassland stability in response to extreme climatic events and anthropogenic drivers across three LTER sites: Cedar Creek, Konza Prairie, and Kellogg Biological Station, 1982-2023.
The data in this package is associated with the analysis for a manuscript titled "Multiple community properties drive ecosystem resistance and resilience to extreme climate events across mesic grasslands". The files include compiled data on plant biomass production, species abundance, experimental treatments, extreme climate event values, and calculated diversity and stability measures from grassland plots in experiments at CDR, KBS, and KNZ LTER sites.
Leaf and Flower Phenology of Woody Plant Species at Harvard Forest and Southern Quebec 2015
Accurate predictions of spring plant phenology with climate change are critical for projections of growing seasons, plant communities and a number of ecosystem services, including carbon storage. Progress towards prediction, however, has been slow because the major cues known to drive phenology – temperature (including winter chilling and spring forcing) and photoperiod – generally covary in nature and may interact, making accurate predictions of plant responses to climate change complex and nonlinear. Alternatively, recent work suggests many species may be dominated by one cue, which would make predictions much simpler. Here, we manipulated all three cues across 28 woody species from two North American forests. Study sites were Harvard Forest and St. Hipplolyte, Quebec. Species were selected for this study based on their prevalence at the study sites; 28 species are included in this study. At each site, multiple cuttings of six or more representative individuals were collected. In total, we tracked the phenology of 2,137 cuttings from 275 individual source plants. All species responded to all cues examined. Chilling exerted a strong effect, especially on budburst (-15.8 d), with responses to forcing and photoperiod greatest for leafout (-19.1 and -11.2 d, respectively). Interactions between chilling and forcing suggest that each cue may compensate somewhat for the other. Cues varied across species, leading to staggered leafout within each community and supporting the idea that phenology is a critical aspect of species’ temporal niches. Our results suggest that predicting the spring phenology of communities will be difficult, as all species we studied could have complex, nonlinear responses to future warming.
Evaluation of Mask R-CNN Model for Counting Reproductive Structures of Six Plant Species 1895-2018
Phenology––the timing of life-history events––is a key trait for understanding responses of organisms to climate. The digitization and online mobilization of herbarium specimens is rapidly advancing our understanding of plant phenological response to climate and climatic change. The current common practice of manually harvesting data from individual specimens greatly restricts our ability to scale data collection to entire collections. Recent investigations have demonstrated that machine-learning models can facilitate data collection from herbarium specimens. However, present attempts have focused largely on simplistic binary coding of reproductive phenology (e.g., flowering or not). Here, we use crowd-sourced phenological data of numbers of buds, flowers, and fruits of more than 3000 specimens of six common wildflower species of the eastern United States (Anemone canadensis, A. hepatica, A. quinquefolia, Trillium erectum, T. grandiflorum, and T. undulatum} to train a model using Mask R-CNN to segment and count phenological features. A single global model was able to automate the binary coding of reproductive stage with greater than 90% accuracy. Segmenting and counting features were also successful, but accuracy varied with phenological stage and taxon. Counting buds was significantly more accurate than flowers or fruits. Moreover, botanical experts provided more reliable data than either crowd-sourcers or our Mask R-CNN model, highlighting the importance of high-quality human training data. Finally, we also demonstrated the transferability of our model to automated phenophase detection and counting of the three Trillium species, which have large and conspicuously-shaped reproductive organs. These results highlight the promise of our two-phase crowd-sourcing and machine-learning pipeline to segment and count reproductive features of herbarium specimens, providing high-quality data with which to study responses of plants to ongoing climatic change.
Plant species-level responses to functional group and species removals in biodiversity experiment plots at the Jornada Basin LTER site, 1999
This dataset contains individual species size data in vegetation plots that have had various plant functional groups or species experimentally removed at the Jornada Basin LTER site in southern New Mexico, USA. This data was collected with the objective to distinguish the differential effects of plant community biomass, functional groups, and biodiversity within functional groups on ecosystem and plant community function. To make these distinctions, treatments were established by the selective removal of plant species or functional groups within experimental plots. There are eight treatments: control (C, no removals); four functional group removal treatments (PG, perennial grass removed; S, shrubs removed; SSh, subshrubs removed; Succ, succulents removed), and three species richness manipulation treatments. Richness manipulations included a simplified treatment (Simp), where only the single most abundant species of each growth form is preserved and all other species in the growth form are removed, a reduced‐Larrea treatment (rL), where the Larrea is assumed to be the dominant and is removed while minority components remain, and a reduced-Prosopsis treatment (rP), where Prosopis rather than Larrea is removed as the shrub dominant. In 1999, this pilot study attempted to assess individual species responses of representative individuals in these treatments. Ten randomly selected individuals of eight plant species were measured in each experimental plot, and this dataset reports volumetric data (diameters and height) for each. The study was designed as an individual-based complement to the transect data in EDI dataset knb-lter-jrn.210121001 but was not continued past 1999. This dataset is complete.
Plant species list for Niwot Ridge and Green Lakes Valley, 1970 - ongoing.
A plant species list was created for Niwot Ridge and Green Lakes Valley from species identified in those areas by NWT scientists, working primarily at the Saddle and Martinelli sites. Additions to this list included species identified by Komarkova (1979) in the Indian Peaks Wilderness area but not on Niwot Ridge or in the Green Lakes Valley because of the likelihood that those species might exist within the LTER research area. Additions to the list were also provided by Terry Theodose, Leeanne Lestak, Teresa Nettleton, Susan Sherrod, Laura Mujica-Crapanzano (2004), Hope Humphries (2006), and Jane G. Smith (2019-2025). The list was revised to remove duplicate entries, correct typos, and resolve synonymy problems. Species and non-species categories received USDA PLANTS database names and codes.
Langenheim Plant Species Data (1953) and Associated Resurvey Datasets (2014), Gunnison Basin, Colorado, USA
Quantitative plant abundance data were collected from the same 121 sites at two time periods separated by 65 years (1948-1952 and 2012-2014) in the Colorado Rocky Mountains to examine changes in plant community composition. The sites range in elevation from 2600m to 4100m. Approximately 30 sites were sampled from each of four habitat types: sagebrush (2528-3119m, n=27 sites), spruce-fir forest understory (3001-3520m, n=31 sites) , upland herb = montane meadow (3124-3850m, n=30 sites), and alpine (3549-4013m, n=33 sites). The earlier data set was collected by Jean H. Langenheim (1953, 1962) and consisted of counts of species occurrences along approximately 100m paced transects, noting species touching her boot tip every pace (n=100 sampled points per site). The later data set was collected by Stephanie D. Zorio (2015, 2016) consisting of counts of species occurrences every 1m along 300m transects (n=300 sampled points per site). The sites resurveyed by Zorio (2015, Zorio et al. 2016) were placed as close as possible to the original sites based on the written descriptions of Langenheim, but are only approximate. The GPS coordinates given for the resurveyed sites are the centerpoint of 2 perpendicular 150m transects, one across the slope and the other perpendicular to the slope. GPS coordinates for alpine sites along narrow ridges are the start and end points of three 100m transects along the ridge. Georeferenced localities and environmental site data are presented in Table 2: Lang Zorio Env Site Data. Langenheim’s original data were extracted from tables in her thesis (Langenheim 1953). These data omitted species that occurred in fewer than 14% of sites of a given habitat type (constancy). Species that occurred at very low frequencies (<1% per site) were only denoted as an x in the tables. Zorio converted these to frequencies of 0.5 for quantitative comparative purposes. This data set contains 157 species from 27 families across all sites and habitats. Species in seve
Vascular Plant Species at Harvard Forest 1992
This dataset contains a list of vascular plant species found in 269 22.5 x 22.5 m plots sampled in the 1992 Prospect Hill vegetation survey. The species list was compiled on 5 May 1993.
CGP01 Gall-insect densities on selected plant species in watersheds with different fire frequencies
Long-term monitoring of gall-insect densities on Solidago canadensis, Vernonia baldwinii, and Ceanothus herbaceous. Gall abundances are censused in watersheds burned at one- to twenty- year intervals to asses the role of fire frequency and time since fire on gall-insect population dynamics. The data sets contain the following: Watershed fire frequency, number of growing seasons since last fire, plant species, number of galled stems, and number of censused stems. Censuses conducted for the 1989-1996 growing seasons except 1992 and 1994, next scheduled census is fall 1997.
Plant species composition for sensor network array, 2017 - ongoing.
Above-ground plant species cover was recorded for vegetation plots in the sensor network, starting in 2017. Cover was measured annually at peak biomass using a 100 point-intercept method.
Plant species composition in ITEX subplots in black sand extended growing season experiment, 2018 - 2023.
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 species composition within all snow and warming treatments.
Plant species composition data for Saddle grid, 1989 - ongoing.
Permanent 1 m^2 vegetation plots were established near each of the 88 Saddle grid stakes in 1989 by Marilyn Walker, who led the sampling effort until 1997. To estimate plant canopy cover, point quadrat measurements have been made at irregular intervals from 1989 to the present (1989, 1990, 1995, 1997, 2006, 2008 and yearly from 2010 onward). The point-quadrat technique used for sampling was described in Spasojevic et al. (2013) and Auerbach (1992). Auerbach, N. 1992. Effects of road and dust disturbance in minerotrophic and acidic tundra ecosystems, northern Alaska. University of Colorado, Boulder, Colorado, USA. Spasojevic, Marko J, William D Bowman, Hope C Humphries, Timothy R Seastedt, and Katharine N Suding. Changes in alpine vegetation over 21 years: Are patterns across a heterogeneous landscape consistent with predictions?” Ecosphere 4, no. 9 (2013): 1–18. https://doi.org/10.1890/es13-00133.1.
Plant species cover and biomass for Sevilleta dominant species removal experiment.
The purpose of this research project was to connect the removal of dominant grass species in grasslands at the Sevilleta National Wildlife Refuge to changes in plant community composition and subsequent changes in aboveground biomass. We used species cover data for 23 years of a dominant species removal experiment (https://doi.org/10.6073/pasta/fd3c777524231ae245bf1916715c9140) and converted percent cover values to aboveground standing biomass using methods from Rudgers et al. 2019 (https://doi.org/10.1111/1365-2435.13463). For this project, only two sites from the original study were used blue grama (site 1) and black grama (site 3) as they are referred to in the original study.
Species cover, community biomass, and richness in global grasslands from NutNet (2007–2023): Dominant species predict plant richness and biomass in global grasslands
The Nutrient Network (NutNet) is a globally coordinated research initiative designed to investigate the impacts of human-driven alterations in nutrient availability and consumer presence on grassland ecosystems. Data were collected from over 130 herbaceous-dominated sites worldwide, spanning diverse environmental conditions from desert grasslands to arctic tundra. Standardized methodologies were employed across all sites to enable direct comparisons of productivity, diversity, and ecosystem responses. Experimental treatments included nutrient additions to assess co-limitation of plant growth by multiple nutrients, as well as grazer manipulations to examine their role in regulating biomass, species diversity, and community composition. By compiling these cross-site data, NutNet aims to enhance our understanding of productivity-diversity relationships and provide new insights into the ecological consequences of anthropogenic changes to nutrient cycles and food webs at a global scale.
Species richness of vascular plants and bryophytes in nine grassland sites (Europe and California collected in 2013-2016)
We sampled vascular plants (VP) and bryophytes (non-vascular plant; NVP) 1×1 m experimental plots in nine sites belonging to the Nutrient Network. Three sites were in California, two in Finland and UK and one in Germany and Switzerland. The data were collected to compare the responses of NVPs and VPs to nutrient addition and grazing exclusion treatments. The NVP and VP cover sampling was conducted in March-August 2016, except for heron.uk and rook.uk, which had been sampled for VPs in 2013. NVPs were mostly identified to species, but in absence of necessary diagnostic characters (capsules, other reproductive organs, distinctive gametophytic features), some specimens were identified at morphospecies group, subgenus, or genus level. We calculated three plant diversity indices for NVPs, VPs and total (NVPs and VPs combined) in each plot. First, species richness (S) is the number of species per 1 m2 for NVPs and VPs. For plots having no NVPs, NVP richness is zero. Second, for plots having at least one NVP, we calculated Inverse Simpson’s index of diversity (referred to as species diversity), which is equivalent to the Probability of Interspecific Encounter or Effective Number of Species (ENSPIE). Third, we calculated Simpson’s evenness (E = ENSPIE/S; referred to as evenness), which was expected to reflect changes in species’ dominance. We also sampled aboveground plant biomass at peak biomass of vascular plants (in May- August, depending on local site level characteristics) by clipping at ground level and removing all aboveground vegetation (live and dead) from two 0.1 × 1 m strips, sorting the current year’s VP and NVP biomass from the previous year’s biomass (dead litter), drying the biomass to a constant mass at 60 °C, and weighing it to the nearest 0.01 g. Except for two sites (heron.uk and rook.uk), we also measured photosynthetically active radiation (PAR) at the ground surface and above grassland canopy at time of peak biomass and calculated the proportion of tra
Relative percent cover of plant species in low nutrient LTER moist acidic tundra experimental plots (MAT06) established in 2006 for years 2008, 2010-2025, Arctic LTER Toolik Field Station Alaska.
Relative percent cover of plant species was measured in low nutrient LTER moist acidic tundra experimental plots (MAT06). Treatments include a gradient of nitrogen and phosphorus additions along with ammonium and nitrate alone.
Block summaries of biomass, carbon, nitrogen, and phosphorus allocation among tissue types, species, and plant functional types from Arctic LTER 1981 Moist Acidic Tussock (MAT81) long-term experiment harvests: 2000 and 2015, Toolik Lake Field Station, Alaska.
A complete accounting of biomass, C, N, and P allocation both among tissue types (leaves, stems, rhizomes, roots) and among species and plant functional types from Arctic LTER 1981 Moist Acidic Tussock (MAT81) long-term experiment’s untreated control plots and plots that were fertilized annually, harvested after 20 and 35 years, near Toolik Lake Field Station, Alaska. Data are gram per meter squared summarized by block.
May to July 2018 regions of interest (ROIs) of tidal marsh and tidal forest plant species to be used as ground reference data in habitat mapping
We collected field data from sites distributed in habitats along the salinity axis of the Altamaha River estuary and the Duplin River to be used as ground reference data for habitat mapping. Regions of interest (ROIs) for tidal marsh (salt, brackish, tidal fresh) and tidal fresh forest vegetation species were generated near ground control points (GCP) by digitizing vegetation areas in ArcGIS 10.4 based on field maps.These observations will be used to create habitat maps from aerial photographs of the Altamaha River estuary, GA taken following Hurricane Irma to better understand how the storm surge affected tidal vegetation and to examine any shifts in vegetation type.
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
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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.