This data set of leaf, stem, and root biomass for various plant taxa was compiled from the primary literature of the 20th century with a significant portion derived from Cannell (1982). Recent allometric additions include measurements made by Niklas and colleagues (Niklas, 2003). This is a unique data set with which to evaluate allometric patterns of standing biomass within and across the broad spectrum of vascular plant species. Despite its importance to ecology, global climate research, and evolutionary and ecological theory, the general principles underlying how plant metabolic production is allocated to above- and below-ground biomass remain unclear. The resulting uncertainty severely limits the accuracy of models for many ecologically and evolutionarily important phenomena across taxonomically diverse communities. Thus, although quantitative assessments of biomass allocation patterns are central to biology, theoretical or empirical assessments of these patterns remain contentious.

The purpose of the SNF study was to improve our understanding of the relationship between remotely sensed observations and important biophysical parameters in the boreal forest. A key element of the experiment was the development of methodologies to measure forest stand characteristics to determine values of importance to both remote sensing and ecology. Parameters studied were biomass, leaf area index, above ground net primary productivity, bark area index and ground coverage by vegetation. Thirty two quaking aspen and thirty one black spruce sites were studied. Sites were chosen in uniform stands of aspen or spruce. Aspen stands were chosen to represent the full range of age and stem density of essentially pure aspen, of nearly complete canopy closure, and greater than two meters in height. Spruce stands ranged from very sparse stands on bog sites, to dense, closed stands on more productive peatlands. Diameter breast height (dbh), height of the tree and height of the first live branch were measured. For each plot, a two meter diameter subplot was defined at the center of each plot. Within this subplot, the percent of ground coverage by plants under one meter in height was determined by species. For the aspen sites, a visual estimation of the percent coverage of the canopy, subcanopy and understory vegetation was made in each plot. Dimension analysis of sampled trees were used to develop equations linking the convenience measurements taken at each site and the biophysical characteristics of interest (for example, LAI or biomass). Fifteen mountain maple and fifteen beaked hazelnut trees were also sampled and leaf area determined. These data were used to determine understory leaf area. The total above-ground biomass was estimated as the sum of the branch and bole biomass for a set of sacrificed trees. Total branch biomass was the sum of the estimated biomass of the sampled and unsampled branches. Total biomass is the sum of the branch and bole biomass. Net primary productivity was estimated from the average radial growth over five years measured from the segments cut from the boles and the terminal growth measured as the height increase of the tree. The models were used to back project five years and determine biomass at that time. The change in biomass over that time was used to determine the productivity. Measurements of the sacrificed trees were used to develop relationships between the biophysical parameters (biomass, leaf area index, bark area index and net primary productivity) and the measurements made at each site (diameter at breast height, tree height, crown depth and stem density). These relationships were then used to estimate biophysical characteristics for the aspen and spruce study sites that are provided in this data set. Biomass density was highest in stands of older, larger Aspen trees and decreased in younger stands with smaller, denser stems. LAI remains relatively constant once a full canopy is established with aspen's shade intolerance generally preventing development of LAI greater than two to three. Biomass density and projected LAI were much more variable for spruce than aspen. Spruce LAI and biomass density have a tight, nearly linear relationship. Stand attributes are often determined by site characteristics. However, differences between maximum LAI for aspen and spruce may also be related to differences in the leaf distribution within the canopy.

Premise: The Mediterranean region is experiencing increasing aridity, affecting ecosystems and plant life. Plants exhibit various anatomical changes to cope with dry conditions, including anatomical changes. This study focused on five co-occurring Mediterranean plant species namely Quercus calliprinos, Pistacia palaestina, Pistacia lentiscus, Rhamnus lycioides, and Phillyrea latifolia in wet and dry sites, investigating anatomical differences in leaves and xylem. Methods: Leaf analysis involved stomatal density, stomatal length, Leaf Mass Area (LMA), lamina composition, quantification of leaf intercellular air spaces (IAS), and mesophyll cell area exposed to these spaces. Xylem anatomy was assessed through vessel length and area in branches. Results: In the dry site, three species showed increased stomatal density and decreased stomatal length. Four species exhibited increased palisade mesophyll (PM) and reduced air space volume. In contrast, the phenotypic change in the xylem was less pronounced, with vessel length remaining unaffected by the site conditions. Furthermore, vessel diameter decreased in two species. Intercellular air spaces (IAS) proved to be the most dynamic anatomical feature. Quercus calliprinos demonstrated the highest anatomical phenotypic changes, while Rhamnus lycioides exhibited minor changes. Conclusions: This study sheds light on the variation in anatomical responses among co-occurring Mediterranean plant species and identifies the most dynamic traits. Understanding these adaptations provides valuable insights into the ability of plants to thrive under changing climate conditions. Methods Histological preparations The samples were collected in June 2021, at the beginning of the dry season. For stem anatomy, one cm long segments of 0.5 to 1 cm in diameter were taken from the terminal branches of new growth. The same branches were used for leaf anatomy, where a rectangle of 1 x 2 cm was cut along the lamina while avoiding the midrib. All samples were fixed immediately after cutting in a formaldehyde-acetic acid–alcohol solution (FAA, 10:5:50 in double-distilled water) for 48 h. Following gradual dehydration in an ethanol series (70, 80, 90, 95, and 100%, for 30 min each), the samples were subjected to a gradual Histoclear solution (25, 50, 75, and 100%). The samples were incubated overnight at room temperature with Paraplast chips (Leica, Wetzlar, Germany, Paraplast Plus) followed by several hours of incubation at 42 °C. The dissolved pure paraffin was changed twice a day for four days at 62 °C before the samples were embedded in blocks. Following embedding, stem samples were immersed in water for a few days and then sectioned using a microtome (Leica RM2245, Leica Microsystems Ltd. , Nussloch, Germany) into 12 μm sections which were mounted on slides, incubated overnight at 40 °C, and stained with Fast Green and Safranin (Ruzin and others, 1999). Images were captured using a light microscope (Leica DMLB, Leica Microsystems Ltd. , Nussloch, Germany) with a Nikon DS-fi1 camera (Nikon Corporation, Japan). Image analysis was done using ImageJ software (Rasband, W.S., ImageJ, US National Institutes of Health, Bethesda, MD, USA, http:// imagej.nih.gov/ij/, 1997–2015). Leaf anatomy analyses The leaf parameters (Table 3) were measured in eight samples from each of the five studied species at each site. Leaf mass area (LMA) was computed by dividing the leaf dry mass (g) by the leaf area (cm²). Leaf area was determined through the analysis of RGB-scaled photos using ImageJ software. Subsequently, the leaves were dried at 70°C for 5 days, followed by measurement of the dry weight. Stomatal density was measured from adaxial and abaxial epidermal imprints, which were made using a dental impression gel (CounterFit II, Clinician's Choice), followed by an impression of clear nail polish, which was removed using adhesive tape and mounted on a microscope slide. Stomata were counted on an area of 0.0837 mm2 which represented the whole image size at the corresponding magnification (x40). Lamina anatomy was analyzed from leaf cross sectional images using the ImageJ software to obtain thickness values in microns for the different leaf organs: adaxial (Ad) and abaxial (Ab) epidermis layers, palisade mesophyll (Pal) and spongy mesophyll (SM) as well as total leaf thickness (T). Cuticle thickness assessment was available only on the adaxial side (Ac) as the abaxial cuticle was indistinct. All parameters were measured at three different locations on a cross section. The Midrib vessel area was assessed by measuring the ten largest vessels using the ImageJ software. Intercellular airspaces were evaluated from the mesophyll surface area exposed to intercellular airspace per unit leaf area , which was calculated according to (Evans et al., 1994):: Where is the total length of mesophyll cells facing the intercellular air space, is the section width and F is the curvature correction factor, which depends on the shape of the cells and was calculated as the weight average of the palisade and spongy mesophyll according to (Thain, 1983). The fraction of the intercellular air space (%IAS) was calculated as Where ΣSs is the sum of the cross-sectional areas of the mesophyll cells and is the thickness of the mesophyll between the two epidermal layers. Stem anatomy analyses The stem parameters (Table 3) were measured in eight samples from each of the five studied species at each site. Vessel length distribution was measured by the "air injection method" (Cohen et al., 2003), with some modifications according to Wang et al. (2014). Briefly, fresh long shoots were cut using a sharp razor blade. The basal end of the stem segment was attached to a flexible silicone tube (clamped to it) and connected to an air compressor which injected air into an old dial manometer and a digital pressure sensor (MPX5100 IC, NXP Semiconductors, Netherlands) wired to a datalogger (Campbell Sci. CR1000 datalogger, Campbell Scientific, Inc., Utah, United States), along with a "bleed" valve. Pressure was adjusted to 0.08-0.15 MPa and logged during the measurements. The distal end of each shoot was immersed in water. Stem segments (2 cm long) were cut back until bubbling was observed, and the length of the remaining stem was taken as the maximum vessel length (in some cases, bubbles appeared immediately before cutting, in which case the maximum vessel length was longer). Then, the stem was cut back consistently to measure air flow rate at several lengths. For each stem length, the bubbles flowing out from the distal end were collected in a volumetric cylinder by the water displacement method according to (Wang et al., 2014). The airflow rate [Q (mL/min)] was computed as follows: Q =(Wi − Wf)/(ΔTρ) Where Wi and Wf are the initial and final weights of the volumetric cylinder respectively, ΔT is the time interval for the water displacement by the bubbles and ρ is the density of water displaced by the air. Air conductivity (C) was calculated according to equation [4] at (Cohen et al., 2003) as follows: Where L is the length of the wood segment (m), P is the distal pressure (kPa) at which the flow rate Q was measured at the distal end is the average pressure in the segment and ΔP is the pressure difference across the segment. According to Cohen et al. (2003) C should decrease exponentially as:
Where is the limiting conductivity as x approaches zero, k is the extinction coefficient and x is the stem length. The plot of the natural log of C versus x resulted in a linear plot, from which k was evaluated from the slope. The most common of mode vessel length (Lmode) was −1/k. The mean vessel length was calculated from Lmean = 2Lmode. The probability density function (PDF) of vessel length was calculated as described in (Cohen et al., 2003) and (Sperry et al., 2005) was: Where is the probability of vessels of length x and k (negative value) is the slope of the linear plot. The vessel area/diameter was evaluated from the most two outer rings of the stem cross sections (described above), which were marked and measured manually by "tracking tool" by Image J software. The vessel diameter (D) was calculated from the vessel area as follows: Statistical analyses The individual data for each anatomical trait are presented as boxplots. To test the effect of site, species, and their interaction on the anatomical traits, a two-way ANOVA was conducted using Python software (Python Software Foundation, Wilmington, Delaware, United States; package: statsmodel).Traits for which variances were non-homogeneous underwent logarithmic transformation before analysis. To compare the two sites for each species, contrast t-tests were performed. To quantify the degree of the difference between the two sites for each species, the effect size was measured using Cohen's d method for each anatomy trait. The formula used for calculating Cohen's d is: Cohen's d = (M1 - M2) / pooled standard deviation where M1 - M2 is the difference between means, i.e., the absolute value of the difference between the mean values of the wet and arid sites, and the pooled standard deviation was calculated as follows: pooled standard deviation = sqrt[(SD1^2 + SD2^2)/2] where SD1 and SD2 are the standard deviations for the wet and dry sites, respectively.

File LFDP_CENSUS1 contains data for the Census 1 (Survey 1,2,and 3) of the LFDP including the Tag number Species code, quadrat location and date and stem diameter D130 (diameter measured at 130 cm from the ground (DBH). It also contains the diameter as recorded for all stems in survey 1, 2 and 3. LFDP_CENSUS1a has the same structure as LFDP_census1. In LFDP_census1a file, however, the stem diameters have been calculated to allocate "missed" stems that were found in survey 2, 3 or Census 2 to either Census 1 survey 1 (stems >=10 cm D130) or Census 1 survey 3 (stems >=1, <10 cm D130). We calculated the diameter the stem would have had, if it had been recorded at the same time the quadrat it was located in was assessed, in the appropriate survey for that stem size. To extrapolate the stem size back in time, we used the actual growth rate of that individual stem if more than one measurement was available. If only one diameter measurement was available we used the median growth rate for that species in the appropriate size class (median growthrate of stems <10 cm, or median for stems >=10, <30 cm D130). In our publications we will combine data sets LFDP_census1 and LFDP_census1a to make Census 1 and to reconstruct the forest for stems >= 10 cm D130 at the time of Hurricane Hugo. We have divided the data into two separate files to ensure that when stem diameters are compared to future censuses the diameter data in LFDP_census1a is not used to calculate growth rates. The dates in LFDP_census1a show the date at which the real diameter was measured in survey 2 or 3 and not the time that the calculated diameter (Fdiam sur1/s2/s3) represents for the quadrat in which the stem was located. Blank in the date field in LFDP_census1a means that the tree was first measured in Census 2 and the diameter given (Fdiam sur1/s2/s3) was extrapolated back in time to Census 1. The last corrections to the Census 1 data were made in May 2001. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals, as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Principal Investigators request that researchers intending to use this data comply with the requests below. Through complying with these requests we can ensure that the data are interpreted correctly, analyses are not repeated unnecessarily, beneficial collaboration between users is promoted and the Principal Investigators' investment in this project is protected. : · Submit to the LFDP PIs a short (1 page) description of how you intend to use the data; · Invite LFDP PIs to be co-authors on any publication that uses the data in a substantial way (some PIs may decline and other LFDP scientists may need to be included); · If the LFDP PIs are not co-authors, send the PIs a draft of any paper using LFDP data, so that the PIs may comment upon it; · In the methods section of any publication using LFDP data, describe that data as coming from the "Luquillo Forest Dynamics Plot, part of the Luquillo Experimental Forest Long-Term Ecological Research Program"; · Acknowledge in any publication using LFDP data the "The Luquillo Experimental Forest Long-Term Ecological Research Program, supported by the U.S. National Science Foundation, the University of Puerto Rico, and the International Institute of Tropical Forestry"; · Supply the LFDP PIs with 10 reprints of any publication using LFDP data; · Accept that the LFDP PIs can not guarantee that the LFDP data you intend to usee has not already been submitted for publication or published.

Leaf area index was estimated in an 18 ha plot at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. The plot was adjacent to the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil. Thirty litter traps were placed at 25-m intervals along two east–west transects in the 18 ha block. Litter samples were collected biweekly from the traps and returned to the lab where they were sorted, air dried, and weighed. The leaf area of a subsample of air-dried leaves was determined using a computer scanner and image processing software. The subsample was then dried in an oven and the air-dried weights were corrected to oven-dried weight. The area of leaf litter collected during each sampling was calculated using the relationship between weight and area measured for the subsample (Goulden et al., 2004). There is one comma-delimited data file with this data set.

The BOREAS TE-10 team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, chlorophyll content, carbon content, hydrogen content, and nitrogen content of boreal vegetation. This data set describes the relationship between sample location, age, chlorophyll content, and C-H-N concentrations at several sites in the SSA conducted during the growing seasons of 1994 and 1996.

Lianas are an important component of tropical forests and they have been shown to interact intensely with trees (Putz 1984, Schnitzer & Bongers 2002). Lianas decrease tree growth, reproduction, recruitment, sap velocity, and leaf area, and the negative effects of lianas on trees have important community and ecosystem ramifications, particularly for species diversity and for forest-level carbon accretion and storage (Toledo-Aceves 2015, Garcia-Leon et al. 2018, Estrada-Villegas et al. 2022). The ability to determine the relationship between lianas and long-term tree performance; however, has been impeded by the lack of large-scale, spatially explicit liana census data. Here we describe and release the 2007 liana dataset from the Barro Colorado Island, Panama (BCI) 50-ha plot, an intensely studied forest dynamics plot with a rich 40-year history of tree dynamics (See Condit et al. 2019). Our dataset includes the stem diameter, spatial location, and species identification for all liana stems larger than or equal to 1 cm diameter that were rooted within the BCI 50-ha plot. This dataset also includes information on whether the liana stem was clonal at the time of the census; i.e., clonal stems had their own root systems but were still attached to another stem in the census. To ensure that our dataset was accurate, we used multiple levels of quality control during field data collection and then we checked and cleaned the dataset multiple times, including updating all species names in 2023. The methods for the liana census were described in Gerwing (2006), Schnitzer et al. (2008, 2012, 2015); species information is described in Schnitzer et al. (2024a, 2024b). In 2007, we found 67,145 rooted liana stems with a basal area of 49.01 m2 comprising 165 species. Of the total rooted stems, 30.14% (20,235 stems) were clonal. We were able to positively identify 98.5% of the stems to species, with the remaining 1.5% of stems to genus. Liana stems were distributed throughout the BCI 50-ha plot; however, there was clear population and community structure, with liana density and diversity congregating around disturbed areas where trees had fallen and had not yet regenerated back to high canopy (Dalling et al. 2012, Ledo et al 2014). This rich dataset can be used to address numerous questions on the spatially explicit effects of lianas in forest dynamics looking both backwards and forwards in time (e.g., Schnitzer 2018). We welcome opportunities to collaborate with research groups interested in using this dataset; however, the data are free to be used with no restrictions other than citing this data paper and acknowledging NSF grant DEB-0613666, which funded this original liana census.

This data set provides mean leaf area index (LAI), dendrometry band measurements, and litterfall mass from samples collected at the km 67 research site, Topajos National Forest, Para, Brazil. Litterfall collections were from January 23, 2004 through December 3, 2004, dendrometer measurements were monthly between December 2003 and December 2004, and LAI measurements were collected from January 26, 2004 through November 3, 2004.

All measurements were taken at the km 67 site in the Tapajos National Forest. This site is situated in an area of Amazonian primary tropical forest belonging to the municipality of Belterra, Para, Brazil. The forest is mostly evergreen with a few deciduous species. The canopy is characterized by large emergent trees up to 55-m tall, with a closed canopy at approximately 40-m; there are few indications of recent anthropogenic disturbance other than hunting trails. Measurement plots (50) were established along 4 transects at the site and within each plot, 5 subplots were established. The longest transect (25 m x 500 m) was the location of 20 (25 m x 25 m) plots. The other 3 transects (25 m x 250 m) contain 10 plots per transect. Note that the assignment of plots to transects is not provided.

There are four comma-delimited data files (.csv) with this data set.

The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign between March 3 and March 18, 2000 to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance and transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. Leaf spectral data are provided in this data set. Leaf spectral measurements were made on samples from dominant tree, shrub, and grass species at 5 different Kalahari Transect sites - Mongu in Zambia and Pandamatenga, Maun, Okwa River, and Tshane in Botswana (from north to south) - where vegetation ranges from moist closed woodlands to arid sparsely-shrub-covered grasslands. Measurements were made on site with a LI-1800 portable spectroradiometer right after the leaves were cut from the trees or shrubs. Three or four sample leaves of each dominant species were measured.The data files, in ASCII comma-delimited (.csv) format, contain the wavelength of the measurement (from 400 nm to 1100 nm, at an interval of 1 nm) and the corresponding fraction of leaf reflectance, transmittance, and albedo (reflectance+transmittance). There is a separate data file for each tree and shrub species sampled at each site and a single file containing unidentified grass species collected from all of the sites. Average values for combined samples of trees and of shrubs at different sites are also provided.

LAI estimates computed from unweighted openness by the canopy program from digitized canopy photographs.

Knowledge of the optical properties of the components of the forest canopy is important to the understanding of how plants interact with their environment and how this information may be used to determine vegetation characteristics using remote sensing. During the summers of 1983 and 1984, samples of the major components of the boreal forest canopy (needles, leaves, branches, moss, litter) were collected in the Superior National Forest (SNF) of Minnesota and sent to the Johnson Space Center (JSC). At JSC, the spectral reflectance and transmittance characteristics of the samples were determined for wavelengths between .35 and 2.1 micrometers using the Cary-14 radiometer. This report presents plots of these data as well as averages to the Thematic Mapper Simulator (TMS) bands. There were two main thrusts to the SNF optical properties study. The first was to collect the optical properties of many of the components of the boreal forest canopy. The second goal of the study was to investigate the variability of optical properties within a species. The results of these studies allow a comparison of the optical properties of a variety of different species and a measure of the variability within species. These data provide basic information necessary to model canopy reflectance patterns.

The BOREAS TE-09 team collected several data sets related to chemical and photosynthetic properties of leaves. This data set contains canopy biochemistry data collected in 1994 in the NSA at the YJP, OJP, OBS, BS and OA sites including biochemistry lignin, nitrogen, cellulose, starch, and fiber concentrations. These data were collected to study the spatial and temporal changes in the canopy biochemistry of boreal forest cover types and how a high-resolution radiative transfer model in the mid-infrared could be applied in an effort to obtain better estimates of canopy biochemical properties using remote sensing.

This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported.

The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available.

These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file.

The BOREAS TE-12 team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, and gas exchange of boreal vegetation. This data set contains measurements of leaf gas exchange conducted in the SSA during the growing seasons of 1994 and 1995 using a portable gas exchange system.

This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources.

The BOREAS TF-11 team gathered a variety of data to complement their tower flux measurements collected at the SSA Fen site. This data set contains single-leaf gas exchange data from the SSA Fen site during 1994 and 1995. These leaf gas exchange properties were measured for the dominant vascular plants using portable gas exchange systems.

The BOREAS group TE-05 collected measurements in the NSA and SSA on gas exchange, gas composition and tree growth. The leaf photosynthetic gas exchange data were collected in the BOREAS NSA and the SSA using a Li-Cor 6200 portable photosynthesis system. The data were collected to compare the photosynthetic capacity, stomatal conductance and leaf intercellular CO2 concentrations among the major tree species at the BOREAS sites. The data are average values from diurnal measurements on the upper canopy foliage (sun leaves).

This dataset provides environmental, soil, and vegetation data collected in July 1994 from 56 study plots at the Happy Valley research site, located along the Sagavanirktok River in a glaciated valley of the northern Arctic Foothills of the Brooks Range. Data includes the baseline plot information for vegetation, soils, and site factors for the study plots subjectively located in 17 plant communities that occur in 5 broad habitat types across the glaciated landscape. Specific attributes include: dominant vegetation species, cover, indices, and biomass pools, soil chemistry, physical characteristics, moisture, and organic matter. This product brings together for easy reference all the available information collected from the plots that has been used for the classification, mapping, and analysis of geo-botanical factors in the Happy Valley region and across Alaska.

The leaf spectra datasets contain visible and near infrared reflectance spectra data for both fresh and dry leaf samples collected in the ACCP. These samples are from Blackhawk Island, WI, Harvard Forest, MA, Howland, ME, Jasper Ridge, CA field sites and the Douglas fir and bigleaf maple seedling canopy study sites. Data reported for each sample is absorbance [log(1/Reflectance)] from 400-2498nm at 2nm intervals and a resolution of 10nm. These data were collected for the purpose of determining the relationship of foliar chemical concentrations with visible and near infrared wavelength reflectance spectra.. Both multiple linear regression and partial least square regression techniques have been used to relate lab chemistry data to spectral reflectance. ORNL DAAC maintains information on the entire ACCP.