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1,662 results for “phenology”
Assessing Plant Phenological Character Displacement Across the Eastern United States Since 1895
Reproductive character displacement has long been hypothesized to be a key determinant of speciation and co-existence in flowering plants. A central tenet of this hypothesis is that reproductive traits of close relatives growing in sympatry diverge more than they do where close relatives do not grow together. However, this idea remains untested across taxa and at large spatial scales. Here, we use data collected from tens of thousands of herbarium specimens to examine evidence for character displacement in flowering time for 91 closely-related pairs of animal-pollinated angiosperm species in the eastern USA. We see no evidence for overall phenological divergence in sympatry across regions, clades, or life histories. Rather our results indicate widespread convergence of flowering times in sympatry for species pairs that generally tend to flower close in time. We also find that climate change could alter the nature of these convergent flowering events by shifting them further apart in a majority species pair comparisons. Specifically, congeneric species in New England and the Atlantic Coastal Plain are projected to flower 2–4 days further apart, on average, by the mid-21st century as warming temperatures drive species-specific phenological shifts within genera. This may have significant consequences for species interactions and gene flow, especially if current sympatric convergence in flowering times has resulted from facilitative interactions between species.
Observed phenological indicators and environmental drivers at global change experiments at the Jornada Basin LTER site, 2014-2020
This dataset contains plant phenological data extracted from phenocams installed at a global exchange experiment involving Chihuahuan desert plant communities at the Jornada Basin LTER site in southern New Mexico, U.S.A. Cycles of plant growth, termed phenology, are tightly linked to environmental controls, and our overarching objective in this study is to determine if temperature or precipitation are relatively more important for determining shrub and grass greenup date (start of season) and senescence date (end of season). At these camera locations, we experimentally manipulated incoming precipitation at the Jornada Basin LTER for over a decade and recorded plant leaf phenology at the daily scale for seven years using phenocams. The data here are derived from raw "phenocam" camera data collected at two ongoing studies at the Jornada Basin LTER site, one studying ecosystem responses to long term changes in water and nitrogen availability, and one studying plant productivity and partitioning responses to water availability and herbivory (studies 349 and 456, respectively). Phenocams at the sites have collected images since 2014, and basic color and greenness data extracted from those images are available in a companion dataset on EDI (knb-lter-jrn.210574001). This dataset includes the derived annual and quarterly phenological indices and greenness indices for each plot monitored by phenocams, and temperature and precipitation variables aggregated to the same frequency. The dataset also includes R code and input files used to generate these derived data. See Currier and Sala 2022 for more details. This study is ongoing.
Vegetative Phenology observations at the Andrews Experimental Forest, 2009 - Present
The vegetation phenology study is part of a larger effort to understand the influence of climate variability and change on trophic interactions in mountainous terrain. Phenology Core Sites were selected to capture the variation in elevation and topography across Lookout Creek watershed. Priority was given to sites with long-term air and soil temperature records (Reference stands) and previous phenology observations (Reference stands and stream gauging stations). Sixteen sites were established. At each site five individuals of from each 18 common species (if occurring within the site) from tree, shrub and herb layers were mapped and marked for observation. Weekly observations are conducted each year beginning in March or April depending on winter conditions and snowpack and continuing through June or July. Plant vegetative and reproductive phenophases are scored using a numbered system adapted to each plant species.
Air temperature at core phenology sites and additional bird monitoring sites in the Andrews Experimental Forest, 2009 to present
The H.J Andrews phenology study air temperature network includes 16 core phenology sites, 40 core bird sites and 128 auxiliary bird sites. This study examines air temperatures at multiple sites within the Andrews Experimental Forest. Air temperatures were recorded 1.5 m above ground at 184 sites distributed on an 800-m incomplete grid throughout much of the Andrews Forest. Data were collected using automated sensors starting in June of 2009 at 56 sites and in June 2011 128 additional sensors were added. These data document the complex spatial and temporal patterns of air temperature variation within the Andrews Forest, which is governed by multiple processes including inversions, regional air mixing, cold air drainage and pooling, and the effects of vegetation on temperature extremes. The data entities provided indicate various methods of data quality checking over time.
PhenoCam Images and Canopy Phenology at the Harvard Forest EMS Tower since 2008
The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server at the University of New Hampshire, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations of tree phenology at Harvard Forest (HF003). Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons. This dataset contains one mid-day image for each camera. Please see the PhenoCam Network website (http://phenocam.sr.unh.edu) for more information and additional images.
Canopy Phenology and Greenness Indices at 13 Sites across North America 2003-2012
This data set contains camera-derived color index data, which serve as a proxy for canopy phenology. The data set spans 13 geographically distinct research sites, including 17 different cameras it total, each of which was mounted on a eddy flux tower for intercomparison of canopy and photosynthesis phenology. Each site was dominated by one of three PFTs: deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops (see HF215-01 for details). On each eddy covariance tower, a digital camera was installed in a fixed position, with a view across the top of the canopy. Most cameras collected photos, which were saved in 24-bit JPEG format, at 30-60 minute intervals, 12-24 hours a day. Time series were first visually inspected for camera shifts and changes in field of view. Noting these changes, we processed the image archives to extract regions of interest (ROI) that encompassed all portions of the full canopy within the foreground. To quantify canopy greenness, we calculated the green chromatic coordinate (GCC), which is widely used to monitor canopy development and identify phenological phase changes, as follows: GCC = DNG / (DNR + DNG + DNB) where DN is the digital number and R, G and B denote the red, green and blue channels, respectively. The Excess Green (ExG) index was then calclated as follows: ExG = 2 * DNG - (DNR + DNB) To characterize canopy coloration in fall, the red chromatic coordinate (RCC) was calculated using the same form as GCC, substituting DNR in the numerator. Indices have been smoothed along a 3-day interval, using a 90th percentile filter (Sonnentag et al. 2012). For each deciduous broadleaf site, there are three files – one each for GCC, ExG and RCC. For the grassland and evergreen needleleaf sites, there are two files, one each for GCC and ExG.
Eastern Massachusetts Flowering Phenology 1852-2013
Climate change has resulted in major changes in the phenology of some species but not others. Long-term field observational records provide the best assessment of these changes, but geographic and taxonomic biases limit their utility. Plant specimens in herbaria have been hypothesized to provide a wealth of additional data for studying phenological responses to climatic change. However, no study to our knowledge has comprehensively addressed whether herbarium data are accurate measures of phenological response, and thus applicable to addressing such questions. We compared flowering phenology determined from field observations (years 1852-1858; 1875; 1878-1908; 2003-2006; 2011-2013) and herbarium records (1852-2013) of 20 species from New England, USA. Earliest flowering date estimated from herbarium records faithfully reflected field observations of first flowering date and substantially increased the sampling range across climatic conditions. Additionally, although most species demonstrated a response to inter-annual temperature variation, long-term temporal changes in phenological response were not detectable. Our findings support the use of herbarium records for understanding plant phenological responses to changes in temperature, and also importantly establish a new use of herbarium collections: inferring primary phenological cueing mechanisms of individual species (e.g., temperature, winter chilling, photoperiod). These latter data are lacking from most investigations of phenological change, but are vital for understanding differential responses of individual species to ongoing climate change.
Assessing Plant Phenological Patterns in the Eastern United States Over the Last 120 Years
Phenology is a key biological trait of an organism’s success and is one of the best indicators of its response to recent climate change. Plants are among the most well-studied organisms in this regard, but observational data bearing on this topic are largely restricted to woody species of the northern hemisphere, mostly from ca. the last three decades. Recent research has demonstrated that mobilized online herbarium specimens provide important, albeit mostly neglected, information on plant phenology. Here, we use the web tool CrowdCurio to crowdsource phenological data from more than 10,000 herbarium specimens representing 30 flowering plant species broadly distributed across the eastern United States. Our results, spanning 120 years and generated from over 2,000 crowdsourcers, clarify numerous aspects of plant phenology. First, they reveal that plant reproductive phenology is significantly advancing in response to warming, which is consistent with previous studies. Second, among those species with broad latitudinal ranges, populations from more southern latitudes are significantly more phenologically sensitive to temperature than those from northern populations. Last, contrary to some recent findings, plants in warmer, less variable climates may be much more dynamic, on average, in their phenological sensitivity. Our results are robust to a variety of confounding factors and span large phylogenetic distances and myriad life histories. These may represent more global trends in the latitudinal gradient of phenological response with myriad potential ecological and evolutionary consequences, and leads us to hypothesize that phenological sensitivity across species' ranges is driven by adaptation to local climates.
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.
Phenology and Vegetation Growth in Prospect Hill Soil Warming Experiment at Harvard Forest 1992-1993
As the mean annual temperature of northeast North America rises as a component of global climatic change, it is important to understand how the predominant vegetation of the region will be affected. Existing experimental and correlative evidence from field sites suggests that temperature rise will significantly modify soil processes, nutrient availability, and plant growth. We investigated the responses of temperate deciduous forest vegetation to artificial soil warming at 20 sampling dates during the 1992 and 1993 growing season. We explored whether soil warming measurably altered growth and the temporal dynamics of leaf and fruit production in 26 species of three contrasting plant growth forms (herbaceous perennials, shrubs, and canopy trees). We hypothesized that soil warming would exert differential effects on emergence, phenology, leaf expansion rates, growth, photosynthesis, and vegetative and sexual reproduction among species, with implications for changing community structure in these forests. Timing of leaf emergence and flower production was not affected by treatment in saplings; however, mature trees and shrubs leafed out slightly earlier and in larger numbers in heated plots. Soil warming significantly enhanced relative growth in stem diameters of woody plants, especially shrubs, in 1992. This effect was less pronounced in 1993. Species richness was lower in heated plots than in intact control plots in both years; disturbed but unheated control plots showed the lowest species richness of all plots. Changes in relative abundance of herbaceous species from 1992 to 1993 were not significantly affected by treatment. Rank abundances of species were more stable between years in the heated and disturbance-control plots than in the intact plots. Total density of herbaceous species was highest in heated plots during April and May of both years, reflecting greatly accelerated emergence of two dominant species, Maianthemum canadense and Uvularia sessilifolia, due t
Nonstructural Carbon, Phenology and Wood Formation in Three Tree Species at Harvard Forest 2017-2019
This data set comprises various observations and measurements across the 2017 to 2019 growing season for seven red maple (Acer rubrum), eight red oak (Quercus rubra), and six white pine (Pinus strobus) in the Prospect Hill Tract of Harvard Forest. The observations include spring and fall leaf phenology and basic allometry, such as diameter at breast height and height. For the leaf phenology, we followed the protocol from John O’Keefe (HF003). Measurements include wood growth data from weekly microcores and a three time characterisation of growing season nonstructural carbon concentrations (soluble sugars and starch) for stems and leaves. Additionally, stem CO2 efflux was measured once a month for the 2018 growing season and weekly for the 2019 growing season.
PhenoCam Images and Canopy Phenology at the Harvard Forest LPH Tower 2010-2021
The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server at the University of New Hampshire, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations of tree phenology at Harvard Forest (HF003). Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons. This dataset contains one mid-day image for each camera. Please see the PhenoCam Network website (https://phenocam.nau.edu/webcam/) for more information and additional images.
PhenoCam Images and Canopy Phenology at the Harvard Forest Barn Tower since 2011
The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server at the University of New Hampshire, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations of tree phenology at Harvard Forest (HF003). Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons. This dataset contains one mid-day image for each camera. Please see the PhenoCam Network website (https://phenocam.nau.edu/webcam/) for more information and additional images.
PhenoCam Images and Canopy Phenology at the Harvard Forest Farm since 2015
The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server at the University of New Hampshire, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations of tree phenology at Harvard Forest (HF003). Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons. This dataset contains one mid-day image for each camera. Please see the PhenoCam Network website (https://phenocam.nau.edu/webcam/) for more information and additional images.
PhenoCam Images and Canopy Phenology at the Harvard Forest Hemlock Tower since 2010
The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server at the University of New Hampshire, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations of tree phenology at Harvard Forest (HF003). Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons. This dataset contains one mid-day image for each camera. Please see the PhenoCam Network website (https://phenocam.nau.edu/webcam/) for more information and additional images.
PhenoCam Images and Canopy Phenology at the Harvard Forest Witness Tree since 2014
The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server at the University of New Hampshire, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations of tree phenology at Harvard Forest (HF003). Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons. This dataset contains one mid-day image for each camera. Please see the PhenoCam Network website (https://phenocam.nau.edu/webcam/) for more information and additional images.
Using Phenology to Forecast Species Distributions across the Eastern United States in the 2070s
Studies that use species distribution models (SDMs) to document the relationship between species’ geographic range and environmental conditions rarely consider functional traits, such as phenology, that strongly affect species’ demography and fitness. Using more than 120,000 herbarium specimens representing 360 plant species across the eastern United States, we created a novel “phenology-informed” SDM that integrates dynamic phenological responses to changing climates. Compared to standard SDMs based only on abiotic variables, our phenology-informed SDMs forecast significantly lower species habitat loss, and less species turnover within communities under climate change. These results suggest that phenotypic plasticity and/or local adaptation in phenology may help many species adjust their ecological niches and persist in their habitats during periods of rapid environmental change. By modeling historical data that link phenology, climate and species distributions, our findings reveal how species’ reproductive phenology mediates their geographic distributions along environmental gradients and affect regional biodiversity patterns under future climate changes. More importantly, our newly developed model also circumvents the need for mechanistic models that explicitly link traits to occurrences for each species, and could thus facilitate the deployment of trait-based SDMs across unprecedented spatial and taxonomic scales.
Canopy Phenology, Remote Sensing and Microclimate at Harvard Forest 2006-2011
Our research at the Harvard Forest walk-up tower site examines how seasonality of canopy leaf area, or canopy phenology, influences, and is influenced by, local climate. As part of this activity we are studying methods for (and limits to) remote sensing of canopy phenology. To address this research topic, we have initiated measurements to quantify how radiation fluxes through a deciduous forest canopy are modified by seasonal canopy leaf dynamics. We continuously measure above- and below-canopy radiation fluxes at a variety of spectral bands (shortwave, photosynthetic) and with digital photography. These measurements provide a surrogate measures of canopy leaf area dynamics, and directly represent the radiation component of the surface energy balance. These measurements complement ongoing microclimate and eddy covariance measurements of water and carbon exchange at the EMS flux tower.
Phenology and Carbon Allocation of Roots at Harvard Forest 2011-2013
The objective of this study is to estimate the phenology and partitioning of C allocated belowground across the growing season at Harvard Forest in two hardwood stands dominated by Quercus rubra and Fraxinus americana, respectively, and one conifer stand dominated by Tsuga canadensis. The phenology of fine root production was characterized by multiple flushes of growth and mortality, especially in the red oak (Q. rubra) stand. Root exudation rate did not have a clear seasonal signal. The deciduous hardwood stands allocated C belowground earlier in the season compared to the conifer-dominated stand. Deciduous stands also allocated a greater proportion of total belowground C flux (TBCF) to root growth compared to the conifer-dominated hemlock (T. canadensis) stand. Of the three stands, red oak partitioned the greatest proportion of TBCF (~50%) to root growth, while hemlock partitioned the least.
Landscape Phenology from Unmanned Aerial Vehicle Photography at Harvard Forest 2013
This data set contains orthophotos in the vicinity of the EMS tower at Harvard Forest, as well as the flight logs from the unmanned aerial vehicle (UAV) used to obtain the digital images used in orthophoto creation. Orthophotos were created by mosaicking approximately 200 JPEG images from each date of observation. The orthophotos cover the spatial extent of the 250 meter resolution MODIS pixel that contains the EMS tower. Land cover types in the area of photography include deciduous and evergreen forest, and wetlands. The research goal of data collection for this data set was to observe spatial variance in plant phenology. Therefore, photos were taken from before leaf out until after leaf drop. Orthophotos were collected approximately every 5 days during spring and weekly during fall; see filenames for specific dates. The nominal spatial resolution of the orthophotos is 6 cm, however due to various factors including inaccuracy of the onboard GPS, wind-blown motion of trees, the automated orthophoto mosaicking process, and user error in final georeferencing, image analysis has been conducted at 10 m resolution. The orthophotos are available as GeoTIFF files.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.