uid=HFR,o=lter,dc=ecoinformatics,dc=org all public read doi:10.6073/pasta/6fd68596ded940145e9a1080e1e1b1c5 Audrey Barker Plotkin https://orcid.org/0000-0002-4473-9785 Danielle Ignace Liza Nicoll Jim Tang https://orcid.org/0000-0003-2498-9012 Joshua Rapp https://orcid.org/0000-0002-7767-5837 Michael Dietze https://orcid.org/0000-0002-2324-2518 Researcher David Foster https://orcid.org/0000-0003-1171-3762 Researcher Glenn Motzkin Researcher David Orwig https://orcid.org/0000-0001-7822-3560 Researcher 2023 English

Northern temperate forests function as an important carbon sink in the global carbon budget. Eddy covariance and plot-based measurements indicate that the Harvard Forest carbon sink is substantial and that the rate of carbon sequestration has increased over the past 20 years. A synthesis effort is underway to better understand how forest development, response to disturbance, and dominant tree species drive the patterns and mechanisms of forest carbon dynamics at the Harvard Forest. The goal of this project is to sample and analyze forest carbon stocks and dynamics across a suite of permanent plots established in 1937 and re-measured in 1992 in order to understand how and why forest carbon stocks have changed between 1937 and 2013. Data from this suite of plots will give spatial and temporal context to a synthesis of detailed, site-specific permanent forest plot studies. Other goals, such as vegetation biodiversity, and a more detailed study of root patterns in soils and belowground carbon distribution, are of strong interest but not addressed in detail in this sampling effort.

carbon diameter at breast height forest disturbance forest ecosystems hemlock land use maple oak pine soil LTER controlled vocabulary primary production populations LTER core area Harvard Forest HFR LTER USA HFR default

This dataset is released to the public under Creative Commons CC0 1.0 (No Rights Reserved). Please keep the dataset creators informed of any plans to use the dataset. Consultation with the original investigators is strongly encouraged. Publications and data products that make use of the dataset should include proper acknowledgement.

Creative Commons Zero v1.0 Universal https://spdx.org/licenses/CC0-1.0.html CC0-1.0 https://harvardforest.fas.harvard.edu/exist/apps/datasets/showData.html?id=hf271 Prospect Hill Tract (Harvard Forest). Coordinates based on WGS84 datum. -72.194 -72.169 +42.552 +42.527 300 400 meter 2013 2013 genus Acer species rubrum red maple genus Aralia species nudicaulis sarsaparilla genus Maianthemum species canadense Canada mayflower genus Osmunda species cinnamomea cinnamon fern genus Pinus species strobus white pine genus Quercus species rubra northern red oak genus Tsuga species canadensis eastern hemlock complete Information Manager Harvard Forest

324 North Main Street Petersham MA 01366 USA

(978) 724-3302 hf-im@lists.fas.harvard.edu Harvard Forest

324 North Main Street Petersham MA 01366 USA

(978) 724-3302 (978) 724-3595 https://harvardforest.fas.harvard.edu

Forest inventories of the three main tracts of the Harvard Forest have been completed every 10-30 years since 1907. The timing and methods used in the 1937 inventory make it a particularly valuable data set. The inventory covers the range of forest types and the three main tracts of the Harvard Forest land base. It was conducted one year before 75% of the standing timber at Harvard Forest was blown down by the Great 1938 Hurricane, so these measurements show maximum vegetation development since agricultural abandonment. The inventory used fixed-radius plots (0.025-0.1 ha) with measurements of individual trees and information on the understory flora, which allow direct comparisons of net change in forest biomass and species composition. Although the hurricane eliminated the plot markers, plot locations were carefully recorded on large-scale maps, allowing us to re-establish plots in the same location. In 1992, most of the plots on the Prospect Hill Tract were located and sampled (Motzkin et al. 1999). All data from 1937 and 1992 are available electronically (HF039, HF015). We considered the merits of focusing on the Prospect Hill Tract (PH) 1937/1992 plots versus a broader suite of plots from the 1937 forest inventory across the Harvard Forest. The PH plots would leverage and give context to the eddy-flux measurements and plots, and the 35-ha SIGEO plot. The broader suite would cover a larger spatial scale and perhaps additional forest types. For the 2013 sampling, we decided to focus on the PH plots sampled in both 1937 and 1992 (n=169). Since examining change in soil carbon stocks between 1992 and 2013 was a goal, we further refined our pool of plots to those that also had soils sampled in 1992 (n=137). We stratified these 137 plots based on key determinants of forest composition and structure by Motzkin et al. (Motzkin, G., Wilson, P., Foster, D. R., Allen, A. E. 1999. Vegetation patterns in heterogeneous landscapes: the importance of history and environment. Journal of Vegetation Science 10: 903-920). They identified historical land-use, soil drainage, and soil CN ratio as three key determinants of forest composition and structure in 1992, so we stratified the plots along these three gradients, and chose plots that spanned these gradients. From the 1992 data, we binned the plots based on land-use history (4 categories), soil drainage (6 categories) and quartiles of CN ratio (4 categories). Since finding the plots in the field was a nontrivial challenge, we also prioritized sampling plots that had been located prior to the 2013 field season.

Plot location and marking (hf271-01). The plots sampled in 1992 are each 22.5m x 22.5m (0.056 ha). In 1995, one corner of each of the 269 plots sampled in 1992 was marked by an iron pipe engraved with the plot number. Plot locations in a GIS file are approximate, so the true location of the plot corner was typically within 1-30m from the mapped location. In Spring 2013 we searched, flagged, and recorded the location of with a GPS for as many plots as possible. We located 80 plots prior to the field season. During the summer, we located an additional 14 plots that were sampling priorities based on the stratification scheme described above. We established the square 22.5 x 22.5m plot using a compass and tapes. The error tolerance was 1m (that is, if the square closed with greater than 1m error, we re-ran the lines until the plot closed with less than 1m error). In some cases, the plot corner that the iron pipe marked was ambiguous. First off, the plot file ‘orientation’ column indicates not the plot corner where the iron pipe is, but the orientation of the plot relative to the pipe (that is, a NE orientation means that the plot is located to the NE of the pipe, and therefore the pipe is in the SW corner of the plot). In the majority of cases the actual and recorded orientation is NE (that is, the pipe is in the SW corner). However, in several cases the orientation from the 1992 study is not NE, and it is ambiguous whether the final iron pipes were all (or mostly?) put in the SW corner, or if some of the pipes did end up at a different corner as recorded. The file from 1992 and the 1999 paper don’t match. Motzkin thought that they did place the iron pipe in the SW corner for all plots, but wasn’t sure. For these ambiguous plots, we used the 1992 tree data and any other clues (whether the plot would cross into a road or over a wall, for instance) to determine the correct plot orientation. We did find that most of the plots in question are oriented NE, but there were 3 plots that we decided were oriented as recorded in the 1992 file. Are you confused? We were too, but think we puzzled our way to the correct solution in most or all cases. We marked all 4 corners of each plot with pvc posts painted red and engraved with the plot number and corner (e.g. PH106-SW). The posts typically extend ~0.5m high. Combined with the more-accurate GPS locations of each plot, finding and laying out the plots for future sampling should be easy. From late May through mid-July, 2013, we sampled 60 plots: Plot layout and posts: all 60. Live and dead trees: all 60. Coarse and fine woody debris: all 60. Litter and soils: 46 of the 60 plots. Understory physiology: 33 of the 60 plots. Tree cores: 4 of the 60 plots. Barker Plotkin led the field sampling, along with Nicoll and assisted by REU students Sophie Bandurski, Pat O’Hara, Christine Pardo, Hannah Wiesner. Live and dead trees (hf271-02; hf271-03). We measured all live and dead trees (not woody shrubs) greater than 2.5cm diameter at breast height (dbh). We recorded species and status (L or D) for all. For live trees and intact dead trees (that is, those with unbroken tops and most branches), we measured diameter at breast height. For standing dead trees (minimum height 0.5m), we recorded base diameter, top diameter, height, and decay class (see below). For height estimates, we directly measured snags less than 2m, estimated height relative to a person of known height (up to 3-4 person-heights) and used a clinometer to estimate height for taller stems. Leaning stems were included if they were greater than 45 degrees relative to the ground. Coarse and fine woody debris (hf271-04; hf271-05). We measured downed coarse wood (minimum diameter = 7.5cm, minimum length = 1m) along two line-intercept transects (Harmon, M.E. and J. Sexton. 1996. Guidelines for measurements of woody detritus in forest ecosystems.) across the plot diagonals (total ~64m transect), recording species, the diameter in both directions and decay class. If we were unsure of the species, we attempted to classify it as ‘deciduous’ or ‘conifer’ but in some cases the species is recorded as ‘unknown.’ If the debris had a hollow, the diameter of the hollow was measured to be subtracted later. We tallied downed fine wood (FWD) along a random 3-m part of each transect. We tallied the number of FWD pieces in two diameter classes: 0.6-2.5cm; 2.5-7.5cm. Litter and soils (hf271-06; hf271-07). Samples archived: 4oz. containers of sieved (less than 2mm) mineral and organic soils archived. We collected the surface litter from three, 50cm x 50cm quadrats in the plots in which we sampled soils. We chose sample locations based on probing soils to find a rock-free area (not so easy!) and to spread the samples across the plot. In the 50 cm *50 cm quadrat where litter is collected, we cut a 15cm x 15cm quadrat into the organic layer based on a wooden frame. Peel the organic layer and measure the depth. Put the organic layer into the bag. After the organic layer was removed, we pounded in a hammer corer (5cm in diameter) into soils (15 cm depth) and collected mineral soil. We had some concerns that the hammer corer sleeve often did not fill all the way, although the sample hole was indeed 15cm deep. If the soils was getting compressed in the corer, that would be okay. If the soil was getting compacted at the bottom of the hole, then the bulk density calculations may be too low.

Live and Dead Trees. For live trees, we used species-specific allometric equations to estimate aboveground biomass. A list of allometric equations used can be found in the script ‘U:\PH-FOREST\functions\biomass.R’. For dead trees, we estimated biomass based on allometries if the tree was intact. If not, we used the height, top diameter, and base diameter measurements to estimate the volume as a frustrum of a cone, then used decay-class and species-group specific density values (from Liu, W.H., D.M. Bryant, L.R. Hutyra, S.R. Saleska, E. Hammond-Pyle, D. Curran and S.C. Wofsy. 2006. Woody debris contribution to the carbon budget of selectively logged and maturing mid-latitude forests. Oecologia 148:108-117) to estimate biomass. Snag volume and mass calculations depended on the data available, split into 5 methods: VOLUME FORMULAE - per piece: (1) frustrum of cone. volume = (height_m*(((3.14159*((baseD/200)^2)) +( ((3.14159*((baseD/200)^2))*(3.14159*((topD/200)^2)))^0.5)+(3.14159*((topD/200)^2))))/3 (2) frustrum of cone. volume = (height_m*(((3.14159*((dbh_cm/200)^2)) +( ((3.14159*((dbh_cm/200)^2))*(3.14159*((topD/200)^2)))^0.5)+(3.14159*((topD/200)^2))))/3 (3) cylinder. volume = 3.14159*((dbh_cm/200)^2)*height_m (4) allometry. step 1. figure out biomass based on dbh_cm and species. Step 2. get volume by dividing mass in grams by density (5) not enough information to calculate volume (18 trees) Then, to get mass: Mass in g/m2 = (volume*(10,00,000*dens). Density units are g/cm3, so multiply by 10,00,000 to get density as g/m3. Coarse and fine woody debris. Volume of coarse woody debris and fine woody debris were calculated based on equations and constants found in Harmon and Sexton. For CWD, species and decay-specific densities from Liu et al. (2006) were used to estimate mass from the volumes. Add details as we work through any issues – especially with the FWD. Outstanding FWD questions include: (1) Is d2q in the lookup table in cm2 or m2? (2) Which values for d2q should we use? One for all plots, or vary depending on dominant species in the plot? (3) Double-check density values and choose what to use – again, one value for all plots, or vary depending on dominant species in the plot? Litter and soils: (1) Oven-dry the soils until they are dry enough to easily pass through a sieve. Sieve the soil (2mm), and separate the rocks. Estimate the volume of total rocks by putting into a measuring flask with water. The increased volume of water is the volume of the rocks. Subtract the rock volume from the total soil volume, which is the core area multiplied by the soil depth. (2) We did not separate fine or coarse roots from the soil in this study, although that would have been a valuable (and time-consuming) addition. Most roots would be in the greater than 2mm fraction. (3) Record the oven-dry mass of each greater than 2mm and less than 2mm fraction of the soil sample. (4) Grind a sub-sample of soil and pack for CN analysis. CN analysis done by lab manager Patel using the Elementar CHN Analyzer in the Torrey Lab. (5) Calculate soil bulk density (dry soil, g/m3). The volume is calculated from the depth of the soils cores and the area of the auger. (6) Archive a 4oz container of the less than 2mm fraction of the mineral and organic soils. Discard the rest of the soils. (7) Dry the litter for 2 days at 70oC. Weigh the oven-dry samples, then discard.

Harvard Forest

324 North Main Street Petersham MA 01366 USA

(978) 724-3302 (978) 724-3595 https://harvardforest.fas.harvard.edu https://ror.org/059cpzx98 pointOfContact The Harvard Forest Long-Term Ecological Research (LTER) program examines ecological dynamics in the New England region resulting from natural disturbances, environmental change, and human impacts. National Science Foundation LTER grants: DEB-8811764, DEB-9411975, DEB-0080592, DEB-0620443, DEB-1237491, DEB-1832210. hf271-01-plots.csv plots hf271-01-plots.csv 31411 705495c3b47afd398a1d9bbadf52cd82 1 \r\n column , https://harvardforest.fas.harvard.edu/data/p27/hf271/hf271-01-plots.csv plot.92 plot number (1-269; see pipe.92 & plot.37 for alternative plot identifiers) plot number (1-269; see pipe.92 & plot.37 for alternative plot identifiers) NA missing value comp compartment of Prospect Hill tract in which plot is located (1-9) compartment of Prospect Hill tract in which plot is located (1-9) NA missing value pipe.92 the pipes marking one corner of each plot in the field are engraved with the set of Tract-Compartment-Pipe Number (e.g. P-1-1), so this is the third part of the unique pipe identifier the pipes marking one corner of each plot in the field are engraved with the set of Tract-Compartment-Pipe Number (e.g. P-1-1), so this is the third part of the unique pipe identifier NA missing value plotno.37 plot number assigned in 1937 plot number assigned in 1937 NA missing value lat.gps latitude of plot, based on Garmin GPS in 2013 (degrees N; 94/269 plots located) degree 0.00000001 real NA missing value long.gps longitude of plot, based on Garmin GPS in 2013 (degrees W; 94/269 plots located) degree 0.00000001 real NA missing value lat.92 approximate location (latitude, degrees N) degree 0.00000001 real NA missing value long.92 approximate location (longitude, degrees W) degree 0.00000001 real NA missing value veg.37 trees and understory vegetation sampled in 1937 1 yes 0 no NA missing value veg.92 trees and understory vegetation sampled in 1992 1 yes 0 no NA missing value soils.92 soil cores sampled and analyzed in 1992 1 yes 0 no NA missing value veg.13 trees and dead wood pools sampled in 2013 1 yes 0 no NA missing value soils.13 soil cores sampled and analyzed in 2013 1 yes 0 no NA missing value phys.13 ecophysiology measurements of plants in 2013 1 yes 0 no NA missing value treecore.13 tree cores sampled from all stems greater than or equal to 10 cm dbh 1 yes 0 no NA missing value orient.92 orientation recorded from the 1992 inventory. The plot is oriented in this direction relative to the iron pipe (e.g. NE means that the pipe is in the SW corner of the plot) orientation recorded from the 1992 inventory. The plot is oriented in this direction relative to the iron pipe (e.g. NE means that the pipe is in the SW corner of the plot) NA missing value orient.13 plot is oriented in this direction relative to the iron pipe when plot was set out in 2013 (e.g. NE means that the pipe is in the SW corner of the plot). In 2013, all 4 corners of each plot (in which veg.13 = 1) were marked with painted pvc pipes. plot is oriented in this direction relative to the iron pipe when plot was set out in 2013 (e.g. NE means that the pipe is in the SW corner of the plot). In 2013, all 4 corners of each plot (in which veg.13 = 1) were marked with painted pvc pipes. NA missing value notes.13 notes relevant to plot set-up in 2013 notes relevant to plot set-up in 2013 NA missing value aspect aspect measured by compass (degrees, 0-359), from 1992 survey degree 1 whole NA missing value slope slope (degrees, not percent), from 1992 survey degree 1 whole NA missing value position landscape position (factor with levels: LOW, MID LOW, MID, MID LEV, UPPER). Documentation of the level meanings not found, from 1992 survey. landscape position (factor with levels: LOW, MID LOW, MID, MID LEV, UPPER). Documentation of the level meanings not found, from 1992 survey. NA missing value relief microrelief, probably related to prevalence of pits/mounds and stumps (factor with levels 1-4). Documentation of the level meanings not found, from 1992 survey. microrelief, probably related to prevalence of pits/mounds and stumps (factor with levels 1-4). Documentation of the level meanings not found, from 1992 survey. NA missing value rocks cover-abundance of rocks, from 1992 survey 0 none 1 less than 1% 2 1-3% 3 less than 5% 4 5-15% 5 16-25% 6 26-50% 7 51-75% 8 greater than 75% NA missing value hurricane 1938 hurricane damage (1-6) , from Rowlands (1941) maps 0 no damage 1 1-10% damage 2 11-25% damage 3 26-50% damage 4 51-75% damage 5 76-90% damage 6 >90% damage NA missing value fire1957 1957 fire, based on HF archive map 1 yes 2 no NA missing value abandon abandonment date for sites that were cleared for agriculture. After Foster map of abandonment in HF Archives. YYYY 1 year NA missing value series soil series, from 1992 survey 1 Canton loam 2 Whitman loam 3 Montauk fine sandy loam 4 Scituate loam 5 Charlton loam 6 Brookfield loam 7 peat 8 Agawam fine sandy loam 9 Windsor loamy sand 10 rock outcrop 11 shallow peat 12 made land 13 Freetown muck 14 Chatfield fine sandy loam NA missing value use most intensive historical land-use, from 1992 survey 1 cultivated 2 improved pasture 3 unimproved pasture 4 woodlot NA missing value drainage soil drainage class, from 1992 survey 1 somewhat excessively drained 2 well drained 3 moderately well drained 4 poorly drained 5 very poorly drained 6 somewhat poorly drained NA missing value plantation plantation (planted trees) 1 yes 0 no NA missing value 269 hf271-02-live-trees.csv live trees hf271-02-live-trees.csv 106415 1a5cd28c077b1411e1f8fa78222e6817 1 \r\n column , https://harvardforest.fas.harvard.edu/data/p27/hf271/hf271-02-live-trees.csv year year, 2013 YYYY 1 year NA missing value plot plot number (matches plot.92) plot number (matches plot.92) NA missing value treenum tree number within each plot. Re-starts at ‘1’ in each plot. Trees are not tagged in field. tree number within each plot. Re-starts at ‘1’ in each plot. Trees are not tagged in field. NA missing value species tree species code ACPE Acer pensylvanicum ACRU Acer rubrum ACSA Acer saccharum ACSC Acer spicatum BEAL Betula alleghaniensis BELE Betula lenta BEPA Betula papyrifera BEPO Betula populifolia BESP Betula, species not determinded (either BELE or BEAL) CADE Castanea dentata FAGR Fagus grandifolia FRAM Fraxinus americana NYSY Nyssa sylvatica PIRE Pinus resinosa PIRU Picea rubens PISP Picea, species not determined PIST Pinus strobus POGR Populus grandidentata PRSE Prunus serotina QUAL Quercus alba QURU Quercus rubra TSCA Tsuga canadensis NA missing value dbh.cm diameter at breast height centimeter 0.1 real NA missing value notes tree-specific notes. If a 5-digit number is recorded, that matches to the 35-hectare SIGEO plot (HF253) tree-specific notes. If a 5-digit number is recorded, that matches to the 35-hectare SIGEO plot (HF253) NA missing value 3701 hf271-03-snags.csv standing dead trees hf271-03-snags.csv 101059 eb4e618b3bfa0a672648c5e0c60fa59e 1 \r\n column , https://harvardforest.fas.harvard.edu/data/p27/hf271/hf271-03-snags.csv year year, 2013 YYYY 1 year NA missing value plot plot number (matches plot.92) plot number (matches plot.92) NA missing value species tree species code ACPE Acer pensylvanicum ACRU Acer rubrum ACSA Acer saccharum ACSP Acer, species not determined BEAL Betula alleghaniensis BELE Betula lenta BEPA Betula papyrifera BEPO Betula populifolia BESP Betula, species not determined CADE Castanea dentate CONF conifer DECD deciduous (hardwood) FAGR Fagus grandifolia FRAM Fraxinus americana PIRE Pinus resinosa PISP Picea, species not determined PIST Pinus strobus PRSE Prunus serotine PRSP Prunus serotine QUAL Quercus alba QURU Quercus rubra TSCA Tsuga Canadensis UNKN unknown NA missing value method method for determining volume, based on measurements available 1 calculate volume as frustrum of cone inputting baseD; topD; height_m 2 calculate volume as frustrum of cone with slightly too-small base diameter inputting dbh, topD, height_m 3 calculate volume as cylinder inputting dbh_cm and height_m 4 calculate MASS with species-specific allometric equation, then use the INVERSE of the DENSITY to calculate volume 5 do not calculate volume: too much missing information (18 trees total) NA missing value decay decay class 1 solid wood, recently fallen, bark and twigs present 2 solid wood, significant weathering, branches present 3 wood not solid, bark may be sloughing but nail still must be pounded into wood 4 wood sloughing and/or friable, nail may be forcibly pushed into wood 5 wood friable, barely holding shape, nail may be easily pushed into wood NA missing value type category of dead wood intact intact tree, most branches/crown remaining snag standing dead tree with branches and part of crown missing NA missing value treenum tree number within each plot. Re-starts at ‘1’ in each plot. Trees are not tagged in field. tree number within each plot. Re-starts at ‘1’ in each plot. Trees are not tagged in field. NA missing value dbh.cm diameter at breast height for the dead tree centimeter 0.1 real NA missing value base.d diameter at the base of the down wood piece centimeter 0.1 real NA missing value mid.d diameter at the midpoint of the down wood piece centimeter 0.1 real NA missing value top.d diameter at the midpoint of the down wood piece centimeter 0.1 real NA missing value ht.direct.m height of wood piece in meters, measured directly with tape or estimated with pole meter 0.01 real NA missing value clinht.d if height determined with clinometer, the distance measurement meter 1 real NA missing value clinht.t if height determined with clinometer, the top measurement (percent) dimensionless 1 natural NA missing value clinht.b if height determined with clinometer, the bottom measurement (percent) dimensionless 1 integer NA missing value height.m height of snag (meters), either directly measured, or calculated by clinomter (ht = (clinht.t-clinht.b)*clinht.d) meter 0.01 real NA missing value dens.gcm3 density, grams per cubic cm, based on species (species group) and decay class values from Liu, W.H., D.M. Bryant, L.R. Hutyra, S.R. Saleska, E. Hammond-Pyle, D. Curran and S.C. Wofsy. 2006. Woody debris contribution to the carbon budget of selectively logged and maturing mid-latitude forests. Oecologia 148:108-117. gramPerMeterCubed 0.01 real NA missing value volume.m3tree calculated volume based on method specified, m3 (for the individual snag). For method 4, volume is back-calculated using biomass calculated from allometries and the inverse of density, ie., divide mass (g) by density (g/1000000*cm3) cubicMeter 0.000000001 real NA missing value vol.m3m2 volume of snag, m3 per m2, based on snag volume and plot size (506.25m2). Sum by plot to get total volume per unit area. meterCubedPerMeterSquared real NA missing value biomass.g.tree for method 4 only, mass of snag calculated by allometry gram 0.000001 real NA missing value mass.gm2 calculated mass in g/m2, based on volume per area (m3/m2) and density (g/cm3). Sum by plot to get total mass per unit area. gramsPerSquareMeter 0.000000001 real NA missing value notes snag-specific comment. If a 5-digit number is recorded, that matches to the 35-hectare SIGEO plot (HF253) snag-specific comment. If a 5-digit number is recorded, that matches to the 35-hectare SIGEO plot (HF253) NA missing value 901 hf271-04-cwd.csv coarse woody debris hf271-04-cwd.csv 27865 174f8c2f214fa34c22ecb229b8bbb68a 1 \r\n column , https://harvardforest.fas.harvard.edu/data/p27/hf271/hf271-04-cwd.csv year year of measurement YYYY 1 year NA missing value plot number of the 22.5 m x 22.5 m plot (matches plot.92) number of the 22.5 m x 22.5 m plot (matches plot.92) NA missing value tran transect number. Aggregate by plot & transect for volume or mass of cwd per unit area transect number. Aggregate by plot & transect for volume or mass of cwd per unit area NA missing value num sequence of cwd pieces measured, start at 1 for each transect; just to keep spreadsheet in order sequence of cwd pieces measured, start at 1 for each transect; just to keep spreadsheet in order NA missing value tlength transect length meter 0.1 real NA missing value species tree species code ACPE Acer pensylvanicum ACRU Acer rubrum BEAL Betula alleghaniensis BELE Betula lenta BEPA Betula papyrifera BEPO Betula populifolia BESP Betula (species not identified) CADE Castanea dentata CASP Carya (species not identified) CONF conifer DECD deciduous (hardwood) FRAM Fraxinus americana PIRU Picea rubens PIST Pinus strobus PRSE Prunus serotina QURU Quercus rubra TSCA Tsuga canadensis UNKN unknown NA missing value decay decay class 1 solid wood, recently fallen, bark and twigs present 2 solid wood, significant weathering, branches present 3 wood not solid, bark may be sloughing but nail still must be pounded into wood 4 wood sloughing and/or friable, nail may be forcibly pushed into wood 5 wood friable, barely holding shape, nail may be easily pushed into wood NA missing value diam1 diameter of wood where it crosses the transect. A negative number measures the hollow within a log in the same transect centimeter 0.1 real NA missing value diam2 second measurement of diameter taken perpendicular to first. Sometimes a second diameter isn’t possible to measure, if the log is pressed into the ground. centimeter 0.1 real NA missing value diamavg elliptical average diameter; if only one diameter recorded, it is in this column (linetran) centimeter 0.00000001 real NA missing value volume.m3m2 volumem3m2=9.869*(((diamavg/100)^2)/(8*tlength)) meterCubedPerMeterSquared 0.000000001 real NA missing value density.gcm3 density, grams per cubic cm, based on species (species group) and decay class values from Liu, W.H., D.M. Bryant, L.R. Hutyra, S.R. Saleska, E. Hammond-Pyle, D. Curran and S.C. Wofsy. 2006. Woody debris contribution to the carbon budget of selectively logged and maturing mid-latitude forests. Oecologia 148:108-117. gramPerMeterCubed 0.01 real NA missing value mass.gm2 mass=volume*(dens*1000000) gramsPerSquareMeter 0.0000001 real NA missing value notes notes notes NA missing value 368 hf271-05-fwd.csv fine woody debris hf271-05-fwd.csv 13752 d9f2aacd13f6efe9ddd6e68ca0c41624 1 \r\n column , https://harvardforest.fas.harvard.edu/data/p27/hf271/hf271-05-fwd.csv year year of measurement (2013) YYYY 1 year NA missing value plot plot identifier (matches plot.92) plot identifier (matches plot.92) NA missing value transect transect number (1 or 2) transect number (1 or 2) NA missing value distance.m transect length fwd tallied (m) meter 1 natural NA missing value size.class size class of fwd 1 0.65 - 2.4 cm 2 2.5 - 7.5 cm NA missing value count number of fwd pieces along the transect number 1 whole NA missing value d2q squared average quadratic mean diameter, m2, by species/species type and size class (Harmon and Sexton 1996) squareMeter 0.000001 real NA missing value a species-specific constant used to calculate volume (Harmon and Sexton 1996) dimensionless 0.01 real NA missing value dens species-specific density, g/cm3, used to calculate mass (Harmon and Sexton 1996) gramsPerCubicCentimeter 0.001 real NA missing value volume volume, m3/m2, calculated with the equation [V= 9.869*count*a*(d2q/(8*distance.m))], where V is volume per unit area, d is the quadratic mean piece diameter for a size class, and a is the average secant piece along the transect (Harmon and Sexton 1996). gramsPerSquareMeter 0.000000001 real NA missing value mass mass, g/m2, calculated from the equation dens*(1/0.000001))*volume}. Do not sum mass for a plot; each transect stands alone, so you'd average if there is >1 mass per plot. gramsPerSquareMeter 0.0000001 real NA missing value 240 hf271-06-litter.csv litter mass hf271-06-litter.csv 3823 c9a02a176d30d598c43a8ff688edaad3 1 \r\n column , https://harvardforest.fas.harvard.edu/data/p27/hf271/hf271-06-litter.csv year year of sample (2013) YYYY 1 year NA missing value plot plot identifier (matches plot.92) plot identifier (matches plot.92) NA missing value sample in most cases, three samples of litter (and soils) taken from each plot in most cases, three samples of litter (and soils) taken from each plot NA missing value mass.g oven dry mass of the litter gram 0.1 real NA missing value litter.gm2 mass of litter on a per-m2 basis gramsPerSquareMeter 0.1 real NA missing value note there were a few litter samples that may have been mis-labeled; these and other comments are here there were a few litter samples that may have been mis-labeled; these and other comments are here NA missing value 138 hf271-07-soils.csv soils hf271-07-soils.csv 32650 7917d83723f5de351f503b32ec9f9897 1 \r\n column , https://harvardforest.fas.harvard.edu/data/p27/hf271/hf271-07-soils.csv year year of sample (2013) YYYY 1 year NA missing value plot plot identifier (matches plot.92) plot identifier (matches plot.92) NA missing value sample in most cases, three samples of litter (and soils) taken from each plot (45 plots had soil sampled in 2013), and separated into mineral and organic horizons in most cases, three samples of litter (and soils) taken from each plot (45 plots had soil sampled in 2013), and separated into mineral and organic horizons NA missing value horizon soil horizon M mineral O organic NA missing value depth.cm depth of the sample (15cm for M; variable depth for O) centimeter 0.1 real NA missing value core.area.cm2 O layer collected with a 15cm by 15cm frame (225 cm2); M layer collected with a cylindrical corer with inside diameter of 5 cm (2 in.) but also with a plastic sleeve insert, making the effective diameter 4.7cm squareCentimeters 0.00000001 real NA missing value core.vol.cm3 calculated based on depth.cm and core.area.cm2 centimeterCubed 0.0000001 real NA missing value rock.vol.cm3 volume of rocks in the sample, estimated by water displacement centimeterCubed 0.1 real NA missing value soil.vol.norock.cm3 core volume after removing rock volume is the soil volume (core.vol.cm3 – rock.vol.cm3) centimeterCubed 0.0000001 real NA missing value mass.fine.g oven-dry mass of soil that passed through a 2mm sieve gram 1 whole NA missing value mass.coarse.g oven-dry mass of soil too large to pass through a 2mm sieve gram 1 whole NA missing value mass.tot.g mass.fine.g + mass.coarse.g gram 1 whole NA missing value bulk.dens.gcm3 bulk density, based on mass.tot.g/soil.vol.norock.cm3 gramsPerCubicCentimeter 0.000000001 real NA missing value c.percent Carbon content based on ground subsample prepared for Elementar CHN Analyzer dimensionless 0.000000001 real NA missing value c.gg conversion from percent carbon to carbon on a gC per g soil basis (C.percent/100) dimensionless 0.000000001 real NA missing value carbon.gm2 soil carbon stock on an area basis (g carbon per m2). Formula = bulk.dens.gm3 * C.gg * 1,000,000 * (depth.cm/100) gramsPerSquareMeter 0.000001 real NA missing value n.percent Nitrogen content based on ground subsample prepared for Elementar CHN Analyzer dimensionless 0.000000001 real NA missing value note notes notes NA missing value 270 biodiversity plot community long-term measurement https://harvardforest.fas.harvard.edu/exist/apps/datasets/showData.html?id=hf015 https://harvardforest.fas.harvard.edu/exist/apps/datasets/showData.html?id=hf039 gramPerMeterCubed