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62 results for “New Hampshire”
Social Network Survey of Forest Landowners in New Hampshire and Vermont 2010
Forests provide invaluable services, and nationally a significant portion of them are owned by millions of individual, private decision makers. Butler (2008) reports that the vast majority of owners (92%, representing 87% of all family forest lands) make management decisions for their land on their own, with a very small minority relying on the advice of professional foresters. Nationally, Butler (2008) goes on to report that 4 % of family forest owners (representing 17% of family forest land) have a professionally prepared management plan for their lands. It is clear that family forests are important, yet millions of owners are apparently not making decisions on the basis of professional advice. Our goal was to improve our understanding of who landowners seek information from when making decisions about their forestland. More specifically, our objective was to explore the possible role of egocentric social networks that landowners may rely upon for information when making a decision. Can we estimate their composition, the possible role of professionals, and the nature of the relationships, in terms of involvement, helpfulness, and trust? Finally, we explored landowner egocentric networks in two similar and adjacent states (Vermont and New Hampshire) that have different programmatic approaches to reaching landowners. Do these result in different ways that landowners acquire information? Using two different approaches through a mail survey methodology, we assessed the extent to which private woodland owners are connected to other people, the degree to which they are considered information sources, and the nature of their decision making behavior. Respondents consistently report valuable connections to non-professionals. They similarly report nominal contact to public foresters, whose role is to inspire prudent forest stewardship on privately held lands. This minimal contact is consistent in two different states with rather different programmatic goals (e.g., educatio
Northern red oak regeneration in burned and unburned stands in the White Mountain National Forest, New Hampshire, USA, 2023-2024
This project aimed to determine whether prescribed burning of managed forest stands improves the regeneration of Quercus rubra near its northern range limit in New Hampshire. We measured oak seedling density and growth rates in three pairs of managed stands in which one had received a prescribed burn since 2017. We also measured the density of competing seedlings and shrubs, leaf area index above seedling height, soil nutrients, mycorrhizal colonization, foliar carbon/nitrogen ratio, and stable isotopes of nitrogen and carbon. We found greater oak seedling density and faster oak seedling growth rates in burned stands relative to unburned stands. A subset of these measurements were also collected in additional burned and unburned study stands in the region. A companion mesocosm experiment showed faster growth in oak seedlings grown in soil from burned vs. unburned stands. Together these studies show that the benefits of fire to oak regeneration are mediated both via greater light availability as well as effects mediated via soil.
Lamprey River New Hampshire Greenhouse Gas Data, 2014-2023
The Lamprey River watershed, located in southeastern New Hampshire (USA), drains 554 km² of low elevation land before discharging into the Great Bay Estuary (Wymore and others 2021). The watershed is classified as suburban with mixed land-use that includes forests (73%), wetlands (10%), development (7%), and agriculture (NOAA Coastal Change Analysis Program 2016). We selected four distinct sites within the watershed to capture the dynamics of both tributaries and the mainstem, while accounting for variations in land use, land cover, and nutrient availability. Wednesday Hill Brook (WHB) is a 1st-order stream that drains a residential landscape and has the highest NO3 concentrations among the sites due to a high density of septic systems (Flint and McDowell 2015). Dowst Cate Forest (DCF) is a 2nd-order stream draining a headwater wetland and forested landscape and is characterized by the highest concentrations of dissolved organic carbon (DOC). The two main stem Lamprey River sites, LMP72 and LMP73, exhibit moderate concentrations of both DOC and NO3 and are located approximately 1 km apart. LMP72 is located at a low-head run-of-river dam while LMP73 is free-flowing water downstream of the reservoir. Our dataset includes weekly water chemistry and dissolved gas data collected from April 2014 through May 2023, except for DCF where data collection ended in 2021, resulting in a total of 1,179 observations across the four different sites.
Filtered chlorophyll a time series for Beaverdam Reservoir, Carvins Cove Reservoir, Claytor Lake, Falling Creek Reservoir, Gatewood Reservoir, Smith Mountain Lake, Spring Hollow Reservoir in southwestern Virginia, and Lake Sunapee in Sunapee, New Hampshire, USA during 2014-2025
Water column chlorophyll a was analyzed from 2014 to 2025 in seven freshwater reservoirs in southwestern Virginia (VA), USA, and one freshwater lake in central New Hampshire (NH), USA. These waterbodies are: Beaverdam Reservoir (Vinton, VA), Carvins Cove Reservoir (Roanoke, VA), Claytor Lake (Pulaski, VA), Falling Creek Reservoir (Vinton, VA), Gatewood Reservoir (Pulaski, VA), Smith Mountain Lake (Bedford, VA), Spring Hollow Reservoir (Salem, VA), and Lake Sunapee (Sunapee, NH). Beaverdam, Carvins Cove, Falling Creek, and Spring Hollow Reservoirs are owned and operated by the Western Virginia Water Authority as primary or secondary drinking water sources for Roanoke, Virginia; Gatewood Reservoir is a drinking water source for the Town of Pulaski, Virginia; and Smith Mountain Lake is jointly treated by the Bedford Regional Water Authority and the Western Virginia Water Authority as a drinking water source for Franklin County, Virginia. Claytor Lake is managed for hydroelectric power generation by the Appalachian Power Company. Lake Sunapee is a glacially-formed lake known for its oligotrophic water quality. The dataset consists of depth profiles of chlorophyll a samples generally measured at the deepest site of each reservoir adjacent to the dam or at the buoy site of Lake Sunapee. The water column samples were collected approximately fortnightly from March-April and weekly from May-October from 2014 - present at Falling Creek Reservoir and Beaverdam Reservoir, approximately fortnightly from May-August in most years at Carvins Cove Reservoir, approximately fortnightly from May-August in Gatewood and Spring Hollow Reservoirs from 2014-2016, approximately fortnightly from May-August of 2014 in Smith Mountain Lake, sporadically from May-August of 2014 in Claytor Lake, and sporadically from June-August of 2021-2022 and 2024-2025 in Lake Sunapee. From 2018-2025, samples were collected primarily at a single depth in each reservoir, with sample collection at two depths in F
Functional Traits of Selected Tree Species in Harvard Forest, New Hampshire, and Southern Quebec 2015
Increasing evidence suggests that species' phenological responses may predict their performance with warming, but this work has generally ignored whether phenology is correlated with other traits known to drive plant performance. This is perhaps surprising given that interest in functional traits has also increased in recent decades, yet within the functional traits literature there has been an equally limited consideration of phenology, perhaps because robustly estimating it is time-intensive, and simple field estimates will show extreme variation across sites of different latitudes and climate regimes. Here we collected a suite of trait data on the same species for which we collected phenological data (see related dataset HF314, Leaf and Flower Phenology of Woody Plant Species at Harvard Forest and Southern Quebec 2015) to help address this gap. We focused on populations of trees in temperate forests in the Northeast face, which face different environmental conditions across their ranges. This project measured functional traits of trees at two to four sites, to provide a foundation for studies on the relationship between range shift, phenology, and functional traits.
Long-term Vegetation Dynamics in Southwestern New Hampshire from 13000 BP to Present
The paleoecological record allows contemporary ecologists to put current phenomena into the context of a longer time-frame, thereby providing the opportunity to evaluate the importance of slowly operating processes, past cyclic or unusual events, disturbance regimes, and historically constrained phenomena. We briefly outline the environmental history of the Quaternary, discuss the spatial and temporal resolution of the paleoecological evidence for biotic change, and summarize data relevant to such current issues as the nature of the biotic community, the role of disturbance, stability versus rapid change, evolutionary theory, explanations of species diversity, and refugia theory. Finally, we offer examples of the utility of paleoecological techniques for ecologists and environmental scientists.
New Hampshire Soil Sensor Network: Soil CO2 Fluxes
The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes air temperature, soil temperature at 5 cm, and soil volumetric water content at 5 cm, and soil CO2 flux at the time of sampling, as well as gap-filled soil CO2 fluxes using non-linear least squares regression. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH.
High-frequency winter water temperature and dissolved oxygen at Lake Sunapee, New Hampshire, USA, 2014-2023
The Lake Sunapee Protective Association (LSPA) has been monitoring water quality in Lake Sunapee, New Hampshire, USA, since the 1980s. Beginning in the winter of 2014-2015, the LSPA deployed a string of HOBO temperature sensors at a location near Loon Island (43.391N, 72.058W, where their instrumented buoy is located during the summer months) for under-ice water temperature profile monitoring. A HOBO U26 dissolved oxygen sensor was added to this monitoring string during the winter of 2017-2018 through the winter of 2019-2020. All sensors record data in 15-minute intervals over the winter and are downloaded after ice-off. All data have been QAQC'd to remove obviously errant readings and artifacts of maintenance and flag highly suspicious readings.
Molecular and Taxonomic Reevaluation of the Digitaria filiformis Complex (Poaceae) including a Globally Extinct, Single Site Endemic from New Hampshire, USA, and a New Species from Mexico
<p>We examine the <em>Digitaria filiformis </em>complex, to determine the proper taxonomic rank and rarity of each taxon. The taxonomy of the <em>D. filiformis </em>complex is highly debated and includes two widespread species, <em>D. filiformis </em>and <em>D. villosa</em>; a possibly extinct species endemic to a single-site in New Hampshire, <em>D. laeviglumis</em>; and a rare species of southern Florida and the West Indies, <em>D.</em><em> dolichophylla. </em>We conducted morphologic comparisons and molecular analysis of the four members of the <em>D. filiformis</em> complex, together with specimens from Mexico and Venezuela purportedly identified as <em>D. laeviglumis</em> (morphology only). Based on results of phylogenetic analyses of plastid and nuclear ITS sequences and morphologic comparisons, we recognize five species in the <em>D. filiformis </em>complex, including a newly described Mexican endemic <em>D. glabrifloris. </em>After field investigation we have moved the global rank of <em>D. laeviglumis </em>from globally historical (GH) to extinct (GX), as there is virtually no likelihood of rediscovery. <em>Digitaria</em><em> dolichophylla </em>is much rarer than previously recognized, moving from secure (T5) to imperiled with extinction (G2).</p>
New Hampshire Soil Sensor Network: Snow depth (2012-2022)
The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes data from snow depth sensors. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH.
High resolution stream temperature, pressure, and estimated depth from transducers in streams in the Lake Sunapee watershed, New Hampshire, USA 2010-2018
Seven in-stream HOBO pressure transducers and one reference HOBO pressure transducer have been deployed within the Lake Sunapee, NH, USA watershed. Six of the transducers have been in operation since 2010 and an additional transducer was added in 2016. The transducers record data every 15 minutes, and data are downloaded approximately three times per year (early Spring, mid Summer and late Fall). Shortly after download, the data are processed to estimate stream depth using HOBOware's Barometric Compensation Assistant and converted to a .csv file in HOBOware. The data have been QAQC'd to recode obviously errant data to NA using R programming language. No data transformation has occurred beyond basic QAQC of the data to remove known data issues and obviously errant data. The barometric pressure data from the reference transducer located on land are also included in this data package.
Wood alpha-cellulose stable C and O isotope ratios from New Hampshire and Vermont
To quantify the effects of tree height and canopy position on delta13C and delta18O of wood cellulose, we sampled 399 trees and saplings of eight species at nine forest stands across New Hampshire and Vermont, along with nearby saplings growing in the open. Samples were collected in 2017-18, and we analyzed the combined alpha-cellulose from growth rings formed in 2013-2017 for each tree. Carbon data are published in: Vadeboncoeur, M., K. Jennings, A. Ouimette, and H. Asbjornsen. (2020) Correcting tree-ring d13C time series for tree-size effects in eight temperate tree species. Tree Physiology. https://doi.org/10.1093/treephys/tpz138
PIE LTER stream chemistry characteristics studied for methane ebullition at four headwater streams in Massachusetts and New Hampshire.
Sediment, stream, and canopy characteristics were measured in four headwater streams in Massachusetts and New Hampshire associated with methane ebullition monitoring. Canopy cover, water depth, sediment organic matter content, the percent sediment less than 2mm in diameter, sediment depth, sediment percent carbon, and sediment percent nitrogen were measured. Other files to reference: WAT-Stream-Ebullition
University of New Hampshire Pressure Mapped Munition (PMM) Experiments 2019 - 2021
<p>This project contains the data collected by the University of New Hampshire (UNH) Coastal Processes Lab for three field experiments focusing on investigating munition mobility in nearshore/surfzone regions. The first experiment took place on May 17 2019, the second experiment took place on February 1-2 2021, and the last experiment to place on October 26-27 2021. The data was collected at Wallis Sands Beach in Rye, New Hampshire. </p> <p>The main instrument utilized was the Pressure Mapped Munition (PMM), which is a fully autonomous cylindrical surrogate munition that can resolve the pressure field on its surface. The PMM is constructed from a 229 mm long section of 304 stainless steel pipe with a 140 mm outside diameter and 12.7 mm wall thickness. To make autonomous measurements of surface pressure and relative position, the PMM houses 16 high resolution TE Connectivity MS5837-02BA absolute pressure sensors and a Lord MicroStrain 3DM®-GX5-25 inertial measurement unit (IMU). There are two rings of pressure sensors around the cylinder. Pressure sensors 1-8 are in ring 1 and pressure sensors 9-16 are in ring 2. Each ring is 6.35 cm from the ends of the cylinder and the rings are 15.24 cm apart. The radial spacing between sensors around each ring is 45°, which minimizes the arc length and height difference between sensors while maintaining axial pairs of sensors. This orientation allows for sensor redundancy in the case of sensor failure and allows for error correction if faulty values from one of the sensors is suspected. When the PMM is lying flat the vertical displacement between the topmost and bottommost sensor is 129 - 140 mm depending on the orientation of the instrument. </p> <p>For the May experiment, a Nortek Vector was deployed along with the PMM. The Nortek Vector is an Acoustic Doppler Velocimeter (ADV) which collects high-resolution, single-point, 3-dimensional velocity data (Nortek, 2022b). For this experiment the ADV transducer was about 30 cm above the sediment bed while the ADV pressure sensor was about 50 cm above the sediment bed. The Nortek Vector was not deployed for the Feburary and October experiments.</p> <p>For the February and October experiments, another instrument, the Pressure Stick (PS), was deployed with the PMM. The Pressure Stick is a fully autonomous pressure-profiling instrument. The PS contains eight micro-controlled, time-synced TE Connectivity MS5837-02BA absolute pressure and temperature sensors distributed along a 70 cm distance to measure pressure throughout the water column and into the sediment bed. The Pressure Stick allows for a quantification of intermittent bed instability (momentary liquefaction) and its potential role in munition mobility. More information about the PS can be found in Marry & Foster (2024).</p> <p>Global Positioning System (GPS) surveys of the beach profile were also completed on February 2, 2021 (at the end of the experiment) and October 26, 2021 (at the beginning of the experiment), and the survey data is included in this project. Data of the offshore wave conditions as measured by the Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC) (https://www.ndbc.noaa.gov/station_page.php?station=44098) for all three experiments are given here as well.</p> <p>This effort was supported by Strategic Environmental Research and Development Program (SERDP, Project Number 17 MR-2731). These datasets are presented in the final report for Project Number 17 MR-2731.</p> <h2>Dataset files</h2> <p>A description of each data file is given below:</p> <h3>Pressure Mapped Munition (PMM) Data</h3> <p>1. PMM_20190517.txt<br> This file contains the raw data from the PMM for the experiment on May 17, 2019<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 in mbar<br> - P2 = pressure from sensor 2 in mbar<br> - P3 = pressure from sensor 3 in mbar<br> - P4 = pressure from sensor 4 in mbar<br> - P5 = pressure from sensor 5 in mbar<br> - P6 = pressure from sensor 6 in mbar<br> - P7 = pressure from sensor 7 in mbar<br> - P8 = pressure from sensor 8 in mbar<br> - P9 = pressure from sensor 9 in mbar<br> - P10 = pressure from sensor 10 in mbar<br> - P11 = pressure from sensor 11 in mbar<br> - P12 = pressure from sensor 12 in mbar<br> - P13 = pressure from sensor 13 in mbar<br> - P14 = pressure from sensor 14 in mbar<br> - P15 = pressure from sensor 15 in mbar<br> - P16 = pressure from sensor 16 in mbar<br> - T = temperature in degrees Celsius</p> <p>2. IMU_20190517.txt<br> This file contains the raw IMU data from the PMM for the experiment on May 17, 2019<br> - Date = date of sample<br> - Time = time of sample<br> - yaw = orientation of the IMU in the yaw direction, measured in degrees<br> - pitch = orientation of the IMU in the pitch direction, measured in degrees. Due to the orientation of the IMU in the PMM, the pitch time series refers to when there are changes in rotation along the long axis of the PMM (i.e. when it rolls). <br> - roll = orientation of the IMU in the roll direction, measured in degrees. Due to the orientation of the IMU in the PMM, the roll time series refers to when there are changes in rotation along the short axis of the PMM (i.e. when it tilts and one end of the cylinder is higher than the other end). </p> <p>3. PMM_20210202.txt<br> This file contains the raw data from the PMM for the experiment on February 1-2, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 in mbar<br> - P2 = pressure from sensor 2 in mbar<br> - P3 = pressure from sensor 3 in mbar<br> - P4 = pressure from sensor 4 in mbar<br> - P5 = pressure from sensor 5 in mbar<br> - P6 = pressure from sensor 6 in mbar<br> - P7 = pressure from sensor 7 in mbar<br> - P8 = pressure from sensor 8 in mbar<br> - P9 = pressure from sensor 9 in mbar<br> - P10 = pressure from sensor 10 in mbar<br> - P11 = pressure from sensor 11 in mbar<br> - P12 = pressure from sensor 12 in mbar<br> - P13 = pressure from sensor 13 in mbar<br> - P14 = pressure from sensor 14 in mbar<br> - P15 = pressure from sensor 15 in mbar<br> - P16 = pressure from sensor 16 in mbar<br> - T = temperature in degrees Celsius</p> <p>4. IMU_20210202.txt<br> This file contains the raw IMU data from the PMM for the experiment on February 1-2, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - yaw = orientation of the IMU in the yaw direction, measured in degrees<br> - pitch = orientation of the IMU in the pitch direction, measured in degrees. Due to the orientation of the IMU in the PMM, the pitch time series refers to when there are changes in rotation along the long axis of the PMM (i.e. when it rolls). <br> - roll = orientation of the IMU in the roll direction, measured in degrees. Due to the orientation of the IMU in the PMM, the roll time series refers to when there are changes in rotation along the short axis of the PMM (i.e. when it tilts and one end of the cylinder is higher than the other end). </p> <p>5. PMM_20211026.txt<br> This file contains the raw data from the PMM for the experiment on October 26-27, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 in mbar<br> - P2 = pressure from sensor 2 in mbar<br> - P3 = pressure from sensor 3 in mbar<br> - P4 = pressure from sensor 4 in mbar<br> - P5 = pressure from sensor 5 in mbar<br> - P6 = pressure from sensor 6 in mbar<br> - P7 = pressure from sensor 7 in mbar<br> - P8 = pressure from sensor 8 in mbar<br> - P9 = pressure from sensor 9 in mbar<br> - P10 = pressure from sensor 10 in mbar<br> - P11 = pressure from sensor 11 in mbar<br> - P12 = pressure from sensor 12 in mbar<br> - P13 = pressure from sensor 13 in mbar<br> - P14 = pressure from sensor 14 in mbar<br> - P15 = pressure from sensor 15 in mbar<br> - P16 = pressure from sensor 16 in mbar<br> - T = temperature in degrees Celsius</p> <p>6. IMU_20211026.txt<br> This file contains the raw IMU data from the PMM for the experiment on October 26-27, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - yaw = orientation of the IMU in the yaw direction, measured in degrees<br> - pitch = orientation of the IMU in the pitch direction, measured in degrees. Due to the orientation of the IMU in the PMM, the pitch time series refers to when there are changes in rotation along the long axis of the PMM (i.e. when it rolls). <br> - roll = orientation of the IMU in the roll direction, measured in degrees. Due to the orientation of the IMU in the PMM, the roll time series refers to when there are changes in rotation along the short axis of the PMM (i.e. when it tilts and one end of the cylinder is higher than the other end). </p> <h3>Nortek Vector Data</h3> <p>Vector_20190517.txt<br> This file contains the Nortek Vector data from the experiment on May 17 2019.<br> - Vec_time = time of Vector samples<br> - Vpress = pressure in mbar<br> - Vpress_smooth = smoothed pressure in mbar<br> - Vu = cross-shore velocity in m/s<br> - Vv = along-shore velocity in m/s<br> - Vw = vertical velocity in m/s</p> <h3>Pressure Stick (PS) Data</h3> <p>1. PS_20210202.txt</p> <p> This file contains the raw data from the Pressure Stick for the experiment on February 1-2, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 (topmost sensor) in mbar, sensor 1 is about 25 cm above the sediment bed<br> - P2 = pressure from sensor 2 in mbar, sensor 2 is about 15 cm above the sediment bed<br> - P3 = pressure from sensor 3 in mbar, sensor 3 is about 9 cm above the sediment bed<br> - P4 = pressure from sensor 4 in mbar, sensor 4 is about 3 cm above the sediment bed<br> - P5 = pressure from sensor 5 in mbar, sensor 5 is about 3 cm in the sediment bed<br> - P6 = pressure from sensor 6 in mbar, sensor 6 is about 13 cm in the sediment bed<br> - P7 = pressure from sensor 7 in mbar, sensor 7 is about 28 cm in the sediment bed<br> - P8 = pressure from sensor 8 (bottom-most sensor) in mbar, sensor 8 is about 43 cm in the sediment bed<br> - T1 = temperature from sensor 1 (topmost sensor) in degrees Celsius, sensor 1 is about 25 cm above the sediment bed<br> - T2 = temperature from sensor 2 in degrees Celsius, sensor 2 is about 15 cm above the sediment bed<br> - T3 = temperature from sensor 3 in degrees Celsius, sensor 3 is about 9 cm above the sediment bed<br> - T4 = temperature from sensor 4 in degrees Celsius, sensor 4 is about 3 cm above the sediment bed<br> - T5 = temperature from sensor 5 in degrees Celsius, sensor 5 is about 3 cm in the sediment bed<br> - T6 = temperature from sensor 6 in degrees Celsius, sensor 6 is about 13 cm in the sediment bed<br> - T7 = temperature from sensor 7 in degrees Celsius, sensor 7 is about 28 cm in the sediment bed<br> - T8 = temperature from sensor 8 (bottom-most sensor) in degrees Celsius, sensor 8 is about 43 cm in the sediment bed </p> <p>2. PS_20211026.txt</p> <p> This file contains the raw data from the Pressure Stick for the experiment on October 26-27, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 (topmost sensor) in mbar, sensor 1 is about 19 cm above the sediment bed<br> - P2 = pressure from sensor 2 in mbar, sensor 2 is about 9 cm above the sediment bed<br> - P3 = pressure from sensor 3 in mbar, sensor 3 is about 3 cm above the sediment bed<br> - P4 = pressure from sensor 4 in mbar, sensor 4 is about 3 cm in the sediment bed<br> - P5 = pressure from sensor 5 in mbar, sensor 5 is about 9 cm in the sediment bed<br> - P6 = pressure from sensor 6 in mbar, sensor 6 is about 19 cm in the sediment bed<br> - P7 = pressure from sensor 7 in mbar, sensor 7 is about 34 cm in the sediment bed<br> - P8 = pressure from sensor 8 (bottom-most sensor) in mbar, sensor 8 is about 49 cm in the sediment bed<br> - T1 = temperature from sensor 1 (topmost sensor) in degrees Celsius, sensor 1 is about 19 cm above the sediment bed<br> - T2 = temperature from sensor 2 in degrees Celsius, sensor 2 is about 9 cm above the sediment bed<br> - T3 = temperature from sensor 3 in degrees Celsius, sensor 3 is about 3 cm above the sediment bed<br> - T4 = temperature from sensor 4 in degrees Celsius, sensor 4 is about 3 cm in the sediment bed<br> - T5 = temperature from sensor 5 in degrees Celsius, sensor 5 is about 9 cm in the sediment bed<br> - T6 = temperature from sensor 6 in degrees Celsius, sensor 6 is about 19 cm in the sediment bed<br> - T7 = temperature from sensor 7 in degrees Celsius, sensor 7 is about 34 cm in the sediment bed<br> - T8 = temperature from sensor 8 (bottom-most sensor) in degrees Celsius, sensor 8 is about 49 cm in the sediment bed </p> <h3>GPS Data</h3> <p>1. UNH_GPS_WS_20210202.txt (.pos)</p> <p> This file contains data from a GPS survey taken on February 2nd 2021 as the post-deployment survey for the February experiment. <br> - GPST = time stamp of the survey sample <br> - latitude = latitude in degrees<br> - longitude = longitude in degrees<br> - height = elevation height, relative to WGS84/ellipsoidal in meters<br> - Q = quality of the data point. Q = 1 is a 'good' data point, Q = 2 is an 'okay' data point, and Q > 2 are 'bad' data points. <br> - ns = Number of satellites<br> <br>2. UNH_GPS_WS_20211026.txt (.pos)</p> <p> This file contains data from a GPS survey taken on October 26th 2021 as the pre-deployment survey for the October experiment. <br> - GPST = time stamp of the survey sample <br> - latitude = latitude in degrees<br> - longitude = longitude in degrees<br> - height = elevation height, relative to WGS84/ellipsoidal in meters<br> - Q = quality of the data point. Q = 1 is a 'good' data point, Q = 2 is an 'okay' data point, and Q > 2 are 'bad' data points. <br> - ns = Number of satellites</p> <h3>Waverider Buoy (NDBC station 44098) Data</h3> <p>1. NDBC_44098_JeffreysLedgeBuoy_May2019.txt</p> <p> This file contains offshore wave data from Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC)(https://www.ndbc.noaa.gov/station_page.php?station=44098) throughout the May 2019 experiment (May 17th 2019 00:08:00 - May 18th 2019 12:38:00). Please see "Description of Measurements" at https://www.ndbc.noaa.gov/measdes.shtml for a discussion of each of the variables in this file.</p> <p>2. NDBC_44098_JeffreysLedgeBuoy_February2021.txt</p> <p> This file contains offshore wave data from Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC)(https://www.ndbc.noaa.gov/station_page.php?station=44098) throughout the February 2021 experiment (February 1st 2021 01:26:00 - Feburary 2nd 2021 09:56:00). Please see "Description of Measurements" at https://www.ndbc.noaa.gov/measdes.shtml for a discussion of each of the variables in this file.</p> <p>3. NDBC_44098_JeffreysLedgeBuoy_October2021.txt</p> <p> This file contains offshore wave data from [Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC)](https://www.ndbc.noaa.gov/station_page.php?station=44098) throughout the October 2021 experiment (October 26th 2021 00:26:00 - October 27th 2021 23:56:00). Please see "Description of Measurements" at https://www.ndbc.noaa.gov/measdes.shtml for a discussion of each of the variables in this file.</p>
Sodium, chloride and specific conductance in stream water and groundwater in New Hampshire 1991, 2000 – 2021
Stream water was collected at weekly to monthly intervals at 29 stream sites in New Hampshire (USA). Ten of the stream sites were instrumented with high‐frequency sensors. Twenty-one of the stream sites (including 5 sensor sites) are in the Lamprey River Hydrologic Observatory (LRHO; Wymore et al 2021) and two stream sites were nearby the LRHO. Groundwater was collected from two riparian well fields (JF, 14 wells and WHB, 13 wells). Wells were installed in 2004 and sampled monthly through May 2007, then quarterly until December 2009, after which a subset (JF, 6 and WHB, 5) was generally sampled quarterly. Stream and groundwater samples span a 17-year collection period and were analyzed for sodium, chloride and specific conductance. Methods and findings are described in the associated Limnology and Oceanography Letters manuscript.
New Hampshire Soil Sensor Network: Air Temperature, Soil Temperature, Soil Water Content, and Soil Electrical Conductivity, 2012 - ongoing
The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes data from the air temperature, soil temperature, soil volumetric water content, and electrical conductivity sensors. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH.
Sugar Maple Regeneration in New Hampshire, 2019-2023
Overview: These data sets are the culmination of a five-year community science project done in collaboration with the Society for Protection of NH Forests. Co-authors on the resulting paper were: Carrie Deegan, Sarah Thorne, Ana Suppé, Kimberly L. Colson and Wanda Rice. Funding was provided by: Engaged Research Grant from the Einhorn Center for Community Engagement at Cornell University 2019 - 2023; Public Engagement with Science Grant (NSF grant #1713204) subcontract from Hubbard Brook Research Foundation; USDA Climate Hub; NSF-REU supplement under the HBR LTER (NSF grant #1637685) in 2021 and 2022 and HBR LTER in 2023 (NSF grant #2224545 ). Undergraduate students who helped on the project: Katie Sims, Alex Ding, Esmée deCortie, Sage Wentzell-Brehme, Colin Craig, Linda Mahecha, Roxy Moore. Community volunteers who contributed to field data collection and project meetings: Paul Doscher, Dave Heuss, Kim Sharp, Chris Brown, Tim Kendrick, Dan Poor, Rickey Poor, and Blaine Kopp. The study was conducted in four mature forest stands with a notable sugar maple component owned and managed by the Society for Protection of New Hampshire Forests (Forest Society) and spanning most of the latitudinal gradient in the state. Plots were established in autumn of 2018. In general, 12 plot locations were established for each of the four forest stands. Plots are spatially-uniform and placed as close to a 100 m grid system as possible with the restriction that the plot had to include three canopy sugar maple trees. The plots are 0.05 hectares or 500 m2 in size measured in a 12.62 m radius circular plot. Marked_sdlg_site_EDI: This data set contains survival, leaf area and leaf damage for 1191 sugar maple seedlings at four sites in New Hampshire. The sugar maple seedlings were two years old at the time of marking in 2019 and were from the 2017 mast year. The study followed the seedlings on 12 plots per site for 5 years (2019-2023). The data file also contains plot and site variables for t
PIE LTER time series of methane, CO2 and N2O ebullition measurements at four headwater streams in Massachusetts and New Hampshire.
Methane ebullition was monitored at four headwater streams during 2018 and 2019. Stationary bubble traps were deployed from approximately May through October. CC and SB were monitored in 2018 and 2019, while DB and CB were only monitored in 2019. 12 traps were deployed at CC, SB, and DB, and 9 traps were deployed at CB. The concentration measured in the emitted gas was multiplied by the volume measured in a trap to calculated the total methane flux via ebullition. The traps were visited at least once weekly. The mean, median, minimum, and maximum rate of ebullition across all traps at a site over a two week period are listed here. Relevant publications: Robison, A.L. (2021) Carbon emissions from streams and river: Integrating methane emission pathways and storm carbon dioxide emissions into stream and river carbon balances. Doctoral Dissertation. University of New Hampshire. Robison, A.L., W.M. Wollheim, B. Turek, C. Bova, C Snay, & R.K. Varner (in review). Spatial and temporal heterogeneity of methane ebullition in lowland headwater streams. Limnology and Oceanography.
PIE LTER dissolved methane and water temperature from four headwater streams in Massachusetts and New Hampshire.
Dissolved methane was measured in the surface water of four headwater streams during 2019. Relevant publications: A.L. Robison (2021) Carbon emissions from streams and river: Integrating methane emission pathways and storm carbon dioxide emissions into stream and river carbon balances. Doctoral Dissertation. University of New Hampshire. A.L. Robison, W.M. Wollheim, C.R. Perryman, A. Cotter, J.E. Mackay, R.K. Varner, P. Clarizia, and J.G. Ernakovich (in review). Dominance of diffusive methane emissions from lowland headwater streams promotes oxidation and isotopic enrichment. Frontiers in Environmental Science.
PIE LTER Methane isotopes (13C and D) for methane in sediments and dissolved in surface water from four headwater streams in Massachusetts and New Hampshire.
Gas samples for methane isotopes were collected from four headwater streams. Benthic gas samples were collected by physcially distrubing the sediment and collecting ebullated gas. Dissolved gas samples were extracted from surface water. 13C and deuterium isotopes were analyzed. Relevant publications: A.L. Robison (2021) Carbon emissions from streams and river: Integrating methane emission pathways and storm carbon dioxide emissions into stream and river carbon balances. Doctoral Dissertation. University of New Hampshire. A.L. Robison, W.M. Wollheim, C.R. Perryman, A. Cotter, J.E. Mackay, R.K. Varner, P. Clarizia, and J.G. Ernakovich (in review). Dominance of diffusive methane emissions from lowland headwater streams promotes oxidation and isotopic enrichment. Frontiers in Environmental Science.
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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.