Urban tree database

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\Data\TS1_Regional_information.csv: Comma-delimited ASCII text file containing information on the regions for which data were collected; includes city and year of collection. Below is a list of variables included in the data file.

Region Code = Short name / code used to represent each region.

Region Name = Full region name.

City = Name of city.

State = Name of state.

Airport Code = Code for airport near the specified city.

Data Collection Year = Year(s) data were collected.

Entity_and_Attribute_Detail_Citation:

none provided

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\Data\TS2_Regional_species_and_counts.csv: Comma-delimited ASCII text file containing urban tree counts by species for 17 U.S. cities. Below is a list of variables included in the data file.

Region = 16 U.S. climate regions, abbreviations are used (see \Data\TS1_Regional_information.csv).

Scientific Name = Botanical name of species.

Common Name = Common name of species.

SpCode = 4 to 6 letter code consisting of the first two letters of the genus name and the first two letters of the species name followed by two optional letters to distinguish two species with the same four-letter code.

Tree Type = 3 letter code where first two letters refer to life form (BD=broadleaf deciduous, BE=broadleaf evergreen, CE=coniferous evergreen, PE=palm evergreen) and the third letter is mature height (S=small which is < 8 meters, M=medium which is 8-15 meters, and L=large which is > 15 meters).

Dbh_class1 = Count of trees of size class 1 (0-3 inches [in]).

Dbh_class2 = Count of trees of size class 2 (3-6 in).

Dbh_class3 = Count of trees of size class 3 (6-12 in).

Dbh_class4 = Count of trees of size class 4 (12-18 in).

Dbh_class5 = Count of trees of size class 5 (18-24 in).

Dbh_class6 = Count of trees of size class 6 (24-32 in).

Dbh_class7 = Count of trees of size class 7 (32-36 in).

Dbh_class8 = Count of trees of size class 8 (36-42 in).

Dbh_class9 = Count of trees of size class 9 (> 42 in).

Grand Total = Total count of trees.

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none provided

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\Data\TS3_Raw tree data.csv: Comma-delimited ASCII text file containing information on the raw tree data. Below is a list of variables included in the data file.

DbaseID = Unique id number for each tree.

Region = 16 U.S. climate regions, abbreviations are used (see \Data\TS1_Regional_information.csv).

City = City/state names where data collected.

Source = Original *.xls filename (not available in this data publication).

TreeID = Number assigned to each tree in inventory by city.

Zone = Number/ID/name of the management area or zone that the tree is located in within a city; or nursery if young tree data collected there.

Park/Street = Data listed as Park, Street, Regional Big Tree, or Nursery (for young tree measurements).

SpCode = 4 to 6 letter code consisting of the first two letters of the genus name and the first two letters of the species name followed by two optional letters to distinguish two species with the same four-letter code (See \Data\TS2_Regional_species_and_counts.csv for a list of the SpCodes and corresponding scientific names.)

ScientificName = Botanical name of species.

CommonName = Common name of species.

Tree Type = 3 letter code where first two letters refer to life form (BD=broadleaf deciduous, BE=broadleaf evergreen, CE=coniferous evergreen, PE=palm evergreen) and the third letter is mature height (S=small which is < 8 meters, M=medium which is 8-15 meters, and L=large which is > 15 meters).

Address = From inventory, street number of building where tree is located.

Street = From inventory, the name of the street the tree is located on. (NOTE: zero values denote data were not recorded in that city. These values were left unchanged because they originated from city inventories.)

Side = From inventory, side of building or lot tree is located on (F=front, M=median, S=side, P=park). (NOTE: zero values denote data were not recorded in that city. These values were left unchanged because they originated from city inventories.)

Cell = From inventory, the cell number (i.e., 1, 2, 3, …), where protocol determines the order trees at same address are numbered (e.g., driving direction or as street number increases).

OnStreet = From inventory (omitted if not a field in city’s inventory), for trees at corner addresses when tree is on cross street rather than addressed street.

FromStreet = From inventory, the name of the first cross street that forms a boundary for trees lining un-addressed boulevards. Trees are typically numbered in order (1, 2, 3 …) on boulevards that have no development adjacent to them, no obvious parcel addresses.

ToStreet = From inventory, the name of the last cross street that forms a boundary for trees lining un-addressed boulevards.

Age = Number of years since planted. (NOTE: zero values represent newly planted trees, < 1 year old.)

DBH (cm) = Diameter at breast height (1.37 meters [m]) measured to nearest 0.1 centimeters (tape). For multi-stemmed trees forking below 1.37 m measured above the butt flare and below the point where the stem begins forking, as per protocol.

TreeHt (m) = From ground level to tree top to nearest 0.5 m (omitting erratic leader).

CrnBase (m) = Average distance between ground and lowest foliage layer to nearest 0.5 m (omitting erratic branch).

CrnHt (m) = Calculated as TreeHT minus Crnbase to nearest 0.5 m. (NOTE: zero values indicate no live crown was present, hence no other tree dimension data were available.)

CdiaPar (m) = Crown diameter measurement taken to the nearest 0.5 m parallel to the street (omitting erratic branch).

CDiaPerp (m) = Crown diameter measurement taken to the nearest 0.5 m perpendicular to the street (omitting erratic branch).

AvgCdia (m) = The average of crown diameter measured parallel and perpendicular to the street.

Leaf (m2) = Estimated using digital imaging method to nearest 0.1 squared meter (m2).

Setback = Distance from tree to nearest air-conditioned/heated space (may not be same address as tree location): 1=0-8 m, 2=8.1-12 m, 3=12.1-18 m, 4=> 18 m.

TreeOr = Taken with compass, the coordinate of tree taken from imaginary lines extending from walls of the nearest conditioned space (may not be same address as tree location).

CarShade = Number of parked automotive vehicles with some part under the tree's drip line. Car must be present (0=no autos, 1=1 auto, etc.).

LandUse = Predominant land use type where tree is growing (1=single family residential, 2=multi-family residential [duplex, apartments, condos], 3=industrial/institutional/large commercial [schools, gov't, hospitals], 4=park/vacant/other [agric., unmanaged riparian areas of greenbelts], 5=small commercial [minimart, retail boutiques, etc.], 6=transportation corridor).

Shape = Visual estimate of crown shape verified from each side with actual measured dimensions of crown height and average crown diameter (1=cylinder [maintains same crown diameter in top and bottom thirds of tree], 2=ellipsoid, the tree's center [whether vertical or horizontal is the widest, includes spherical], 3=paraboloid [widest in bottom third of crown], 4=upside down paraboloid [widest in top third of crown]).

WireConf = Utility lines that interfere with or appear above tree (0=no lines, 1=present and no potential conflict, 2=present and conflicting, 3=present and potential for conflicting). (NOTE: -1 denotes data were not collected.)

dbh1 = Dbh (centimeters [cm]) for multi-stemmed trees; for non-multi-stemmed trees, dbh1 is same as Dbh (cm).

dbh2 = Dbh (cm) for second stem of multi-stemmed trees.

dbh3 = Dbh (cm) for third stem of multi-stemmed trees.

dbh4 = Dbh (cm) for fourth stem of multi-stemmed trees.

dbh5 = Dbh (cm) for fifth stem of multi-stemmed trees.

dbh6 = Dbh (cm) for sixth stem of multi-stemmed trees.

dbh7 = Dbh (cm) for seventh stem of multi-stemmed trees.

dbh8 = Dbh (cm) for eight stem of multi-stemmed trees.

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\Data\TS4_Growth_eqn_forms.csv: Comma-delimited ASCII text file containing the list of equation forms applied to the urban tree data. Below is a list of variables included in the file.

EQNAME = Short name for equation.

EQUATION = Full equation (where a, b, c, d, and e are coefficients; LN = natural log; age = tree age; dbh = diameter at breast height; mse = mean squared error).

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none provided

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\Data\TS5_Foliar_biomass_leaf_samples.csv: Comma-delimited ASCII text file containing urban Foliar samples data by species for 17 U.S. cities. Below is a list of variables included in the data file.

Region = 16 U.S. climate regions, abbreviations are used (see \Data\TS1_Regional_information.csv).

Scientific Name = Botanical name of species.

Common Name = Common name of species.

SpCode = 4 to 6 letter code consisting of the first two letters of the genus name and the first two letters of the species name followed by two optional letters to distinguish two species with the same four-letter code.

Tree Type = 3 letter code where first two letters refer to life form (BD=broadleaf deciduous, BE=broadleaf evergreen, CE=coniferous evergreen, PE=palm evergreen) and the third letter is mature height (S=small which is < 8 meters, M=medium which is 8-15 meters, and L=large which is > 15 meters).

Avg dw/fw (g) = Average of foliar dry weight (dw) in grams to fresh weight (fw) in grams.

dw/fw sd = Standard deviation of foliar dry weight (dw) to fresh weight (fw).

Avg dw g/m2 = Average foliar dry weight (dw) in grams per square meter (g/m2).

dw g/m2 sd = Standard deviation of foliar dry weight (dw) in grams per square meter (g/m2).

n = Number of samples.

Notes = Sampling notes.

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none provided

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\Data\TS6_Growth_coefficients.csv: Comma delimited ASCII text file containing equations for predicting tree growth parameters by species and predicted parameter in different climate zones. Units of predicted components: age = years, dbh = centimeters, cdiameter = meters, crown height = meters, la = squared meters. Model components: dbh = diameter at breast height, cdia = cdiameter, cht = crown height, tht = tree height, la = leaf area. Below is a list of variables included in the data file. (NOTE: blank cells mean not applicable)

Region = 16 U.S. climate regions, abbreviations are used (see \Data\TS1_Regional_information.csv).

Scientific Name = Botanical name of species.

SpCode = 4 to 6 letter code consisting of the first two letters of the genus name and the first two letters of the species name followed by two optional letters to distinguish two species with the same four-letter code.

Independent variable = Name of independent variable.

Predicts component = Variable being predicted.

Units of predicted components = Units for the predicted component.

Model weight = Model weight used.

EqName = Equation name referring to equations in \Data\T4_Growth_eqn_forms.csv. (Loglog and exponential models require an input for mean-squared-error (mse) which is listed in column 'c' (do not calculate and use sigma2).

a = Value of coefficient a in the specified model.

b = Value of coefficient b in the specified model.

c = Value of coefficient c in the specified model.

d = value of coefficient d in the specified model.

e = Value of coefficient e in the specified model.

Apps min = Reasonable minimum data value to use when applying this equation.

Apps max = Reasonable maximum data value to use when applying this equation.

Sigma = Standard deviation of the model.

n = Number of data points in the model.

adj R2 = Adjusted R-squared.

Data min (from raw data) = Actual minimum value for the data collected.

Data max (from raw data) = Actual maximum value for the data collected.

DF = Degrees of freedom.

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none provided

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\Data\T7_Volume_eqns_from_urban.csv: Comma-delimited ASCII text file containing volume equations for 28 urban tree species requiring 1) only diameter at breast height (dbh) or 2) dbh and height measurements to calculate volume. All equations predict aboveground volume in cubic meters per tree. Below is a list of variables included in the data file.

Equation Species = Botanical name of species.

DBH lower (cm) = Lower range of dbh (centimeters) of the trees used to derive the equations.

DBH upper (cm) = Upper range of dbh (centimeters) of the trees used to derive the equations.

Equation = Full equation (where dbhcm = diameter at breast height [centimeters] and htm = height [meters]).

Predicts = Variable being predicted, which in this case is above ground volume (cubic meters per tree).

DW Density = Dry weight density factor (for Jenkins: see Jenkins et al. 2004; for DRYAD (Global Wood Density Database): see Zanne et al. 2009 and Chave et al. 2009). The general equations predict cubic meters of fresh wood volume. Fresh wood volume is then multiplied by the species’ DW density factor to obtain aboveground DW biomass. Resulting units are kilograms per cubic meter.

Equation Source = Name of the source from which the equation was obtained.

Entity_and_Attribute_Detail_Citation:

Aguaron, E.; McPherson, E. G. 2012. Comparison of methods for estimating carbon dioxide storage by Sacramento's urban forest. In: R. Lal and B. Augustin. eds. Carbon Sequestration in Urban Ecosystems. Dordrecht, Netherlands, Springer-Verlag: 43-71. https://doi.org/10.1007/978-94-007-2366-5_3

Chave, J.; Coomes, D.; Jansen, S.; Lewis, S.; Swenson, N.; Zanne, A. 2009. Towards a worldwide wood economics spectrum. Dryad Digital Repository. Ecology Letters 12 (4): 351-366. https://doi.org/10.1111/j.1461-0248.2009.01285.x

Jenkins, Jennifer C.; Chojnacky, David C.; Heath, Linda S.; Birdsey, Richard A. 2004. Comprehensive database of diameter-based biomass regressions for North American tree species. Gen. Tech. Rep. NE-319. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 45 p. [1 CD-ROM]. https://doi.org/10.2737/ne-gtr-319

Lefsky, Michael; McHale, Melissa R. 2008. Volume estimates of trees with complex architecture from terrestrial laser scanning. Journal of Applied Remote Sensing 2(1):023521-023521. https://doi.org/10.1117/1.2939008

Pillsbury, N.; Reimer, J. L.; Thompson, R. 1998. Tree volume equations for fifteen urban species in California. San Luis Obispo, CA, Urban Forest Ecosystems Institute, California Polytechnic State University: 45.

Zanne, A.; Lopez-Gonzalez, G.; Coomes, D.; Ilic, J.; Jansen, S.; Lewis, S.; Miller, R.; Swenson, N.; Wiemann, M.; Chave, J. 2009. Data from: Towards a worldwide wood economics spectrum. Dryad Digital Repository. https://doi.org/10.5061/dryad.234

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\Data\TS8_Volume_and_biomass_eqns_from_rural.csv: Comma-delimited ASCII text file containing dry weight biomass and volume equations from rural forests. Below is a list of variables included in the data file.

Equation Species = Botanical name of species.

DBH lower (cm) = Lower range of dbh (centimeters) of the trees used to derive the equations.

DBH upper (cm) = Upper range of dbh (centimeters) of the trees used to derive the equations.

Equation = Full equation (where dbhcm = diameter at breast height [centimeters] and htm = height [meters]).

Predicts = Variable being predicted, which in this case is above ground volume (cubic meters per tree).

DW Density = dry weight density factor (for Jenkins: see Jenkins et al. 2004; for DRYAD (Global Wood Density Database): see Zanne et al. 2009 and Chave et al. 2009). Resulting units are kilograms per cubic meter.

Equation Source = Name of the source from which the equation was obtained.

Entity_and_Attribute_Detail_Citation:

Chave, J.; Andalo, C.; Brown, S.; Cairns, M. A.; Chambers, J. Q.; Eamus, D.; ,Folster, H.; Fromard, F.; Higuchi, N.; Kira, T.; Lescure, J.-P.; Nelson, B. W.; Ogawa, H.; Puig, H.; Riera, B.; Yamakura, T. 2005. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145(1): 87-99. https://doi.org/10.1007/s00442-005-0100-x

Chave, J.; Coomes, D.; Jansen, S.; Lewis, S.; Swenson, N.; Zanne, A. 2009. Towards a worldwide wood economics spectrum. Dryad Digital Repository. Ecology Letters 12 (4): 351-366. https://doi.org/10.1111/j.1461-0248.2009.01285.x

Frangi, Jorge L.; Lugo, Ariel E. 1985. Ecosystem dynamics of a subtropical floodplain forest. Ecological Monographs 55(3): 351-369. https://doi.org/10.2307/1942582

Harris, W. F.; Goldstein, R. A.; Henderson, G. S. 1973. Analysis of forest biomass pools, annual primary production and turnover of biomass for a mixed deciduous forest watershed. In Proc. IUFRO Conference on Forest Biomass Studies, edited by H. Young, pp 41-64. Orno: University of Maine Press.

Jenkins, Jennifer C.; Chojnacky, David C.; Heath, Linda S.; Birdsey, Richard A. 2004. Comprehensive database of diameter-based biomass regressions for North American tree species. Gen. Tech. Rep. NE-319. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 45 p. [1 CD-ROM]. https://doi.org/10.2737/ne-gtr-319

Pillsbury, Norman H.; Kirkley, Michael L. 1984. Equations for total, wood, and saw-log volume for thirteen California hardwoods. Res. Note PNW-RN-414. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 52 p. https://doi.org/10.2737/pnw-rn-414

Ter-Mikaelian, Michael T.; Korzukhin, Michael D. 1997. Biomass equations for sixty-five North American tree species. Forest Ecology and Management 97(1): 1-23. https://doi.org/10.1016/s0378-1127(97)00019-4

Van, T. K.; Rayachhetry, M. B.; Center, T. D. 2000. Estimating above-ground biomass of Melaluca quinquenervia in Florida, USA. Journal of Aquatic Plant Management 38:62-67.

Vieilledent, G.; Vaudry, R.; Andriamanohisoa, S. F. D.; Rakotonarivo, O. S.; Randrianasolo, H. Z.; Razafindrabe, H. N.; Rakotoarivony, C. B.; Ebeling, J; Rasamoelina, M. 2012. A universal approach to estimate biomass and carbon stock in tropical forests using generic allometric models. Ecological Applications 22(2):572-583. https://doi.org/10.1890/11-0039.1

Zanne, A.; Lopez-Gonzalez, G.; Coomes, D.; Ilic, J.; Jansen, S.; Lewis, S.; Miller, R.; Swenson, N.; Wiemann, M.; Chave, J. 2009. Data from: Towards a worldwide wood economics spectrum. Dryad Digital Repository. https://doi.org/10.5061/dryad.234

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\Data\T9_Biomass_density_factors.csv: Comma-delimited ASCII text file containing an expanded list of biomass density factors for common urban species. Species without a specific equation and/or dry weight density factor are matched to known species. Below is a list of variables included in the data file.(blank cells = not applicable)

SpCode = 4 to 6 letter code consisting of the first two letters of the genus name and the first two letters of the species name followed by two optional letters to distinguish two species with the same four-letter code.

Scientific Name = Botanical name of species that needs to be matched.

Common Name = Common name of species that needs to be matched.

DW Density = Dry weight density factor (for Jenkins: see Jenkins et al. 2004; for DRYAD (Global Wood Density Database): see Zanne et al. 2009 and Chave et al. 2009). Resulting units are kilograms per cubic meter.

Matched Equation Species = Botanical name of species that has been chosen as the match.

Matched Equation SpCode = Species code (see SpCode) for the species that has been chosen as the match.

Eq Source = name of the source from which the equation was obtained.

Entity_and_Attribute_Detail_Citation:

Aguaron, E.; McPherson, E. G. 2012. Comparison of methods for estimating carbon dioxide storage by Sacramento's urban forest. In: R. Lal and B. Augustin. eds. Carbon Sequestration in Urban Ecosystems. Dordrecht, Netherlands, Springer-Verlag: 43-71. https://doi.org/10.1007/978-94-007-2366-5_3

Chave, J.; Andalo, C.; Brown, S.; Cairns, M. A.; Chambers, J. Q.; Eamus, D.; ,Folster, H.; Fromard, F.; Higuchi, N.; Kira, T.; Lescure, J.-P.; Nelson, B. W.; Ogawa, H.; Puig, H.; Riera, B.; Yamakura, T. 2005. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145(1): 87-99. https://doi.org/10.1007/s00442-005-0100-x

Chave, J.; Coomes, D.; Jansen, S.; Lewis, S.; Swenson, N.; Zanne, A. 2009. Towards a worldwide wood economics spectrum. Dryad Digital Repository. Ecology Letters 12 (4): 351-366. https://doi.org/10.1111/j.1461-0248.2009.01285.x

Frangi, Jorge L.; Lugo, Ariel E. 1985. Ecosystem dynamics of a subtropical floodplain forest. Ecological Monographs 55(3): 351-369. https://doi.org/10.2307/1942582

Harris, W. F.; Goldstein, R. A.; Henderson, G. S. 1973. Analysis of forest biomass pools, annual primary production and turnover of biomass for a mixed deciduous forest watershed. In Proc. IUFRO Conference on Forest Biomass Studies, edited by H. Young, pp 41-64. Orno: University of Maine Press.

Jenkins, Jennifer C.; Chojnacky, David C.; Heath, Linda S.; Birdsey, Richard A. 2004. Comprehensive database of diameter-based biomass regressions for North American tree species. Gen. Tech. Rep. NE-319. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 45 p. [1 CD-ROM]. https://doi.org/10.2737/ne-gtr-319

Lefsky, Michael; McHale, Melissa R. 2008. Volume estimates of trees with complex architecture from terrestrial laser scanning. Journal of Applied Remote Sensing 2(1):023521-023521. https://doi.org/10.1117/1.2939008

Pillsbury, Norman H.; Kirkley, Michael L. 1984. Equations for total, wood, and saw-log volume for thirteen California hardwoods. Res. Note PNW-RN-414. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 52 p. https://doi.org/10.2737/pnw-rn-414

Pillsbury, N.; Reimer, J. L.; Thompson, R. 1998. Tree volume equations for fifteen urban species in California. San Luis Obispo, CA, Urban Forest Ecosystems Institute, California Polytechnic State University: 45.

Ter-Mikaelian, Michael T.; Korzukhin, Michael D. 1997. Biomass equations for sixty-five North American tree species. Forest Ecology and Management 97(1): 1-23. https://doi.org/10.1016/s0378-1127(97)00019-4

Van, T. K.; Rayachhetry, M. B.; Center, T. D. 2000. Estimating above-ground biomass of Melaluca quinquenervia in Florida, USA. Journal of Aquatic Plant Management 38: 62-67.

Vieilledent, G.; Vaudry, R.; Andriamanohisoa, S. F. D.; Rakotonarivo, O. S.; Randrianasolo, H. Z.; Razafindrabe, H. N.; Rakotoarivony, C. B.; Ebeling, J; Rasamoelina, M. 2012. A universal approach to estimate biomass and carbon stock in tropical forests using generic allometric models. Ecological Applications 22(2):572-583. https://doi.org/10.1890/11-0039.1

Zanne, A.; Lopez-Gonzalez, G.; Coomes, D.; Ilic, J.; Jansen, S.; Lewis, S.; Miller, R.; Swenson, N.; Wiemann, M.; Chave, J. 2009. Data from: Towards a worldwide wood economics spectrum. Dryad Digital Repository. https://doi.org/10.5061/dryad.234

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SUPPLEMENTAL FILES

\Supplements\Errata_Jan2020_PSW-GTR-253.pdf: Portable Document Format file containing a list of January 2020 changes for the General Technical Report associated with the Urban Tree Database: McPherson, E. Gregory; van Doorn, Natalie S.; Peper, Paula J. 2016. Urban tree database and allometric equations. Gen. Tech. Rep. PSW-GTR-253. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station. 86 p. https://www.fs.usda.gov/treesearch/pubs/52933

\Supplements\Errata_Jan2020_RDS-2016-0005.pdf: Portable Document Format file containing a list of changes made to Urban Tree Database (https://doi.org/10.2737/RDS-2016-0005) in January 2020.

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Metadata_Reference_Information:

Metadata_Date: 20200121

Metadata_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Natalie S. van Doorn

Contact_Organization: USDA Forest Service, Pacific Southwest Research Station

Contact_Position: Research Forester

Contact_Address:

Address_Type: mailing and physical

Address: 800 Buchanan Street

City: Albany

State_or_Province: CA

Postal_Code: 94710

Country: USA

Contact_Voice_Telephone: 510-883-8856

Contact_Electronic_Mail_Address: natalie.vandoorn@usda.gov

Metadata_Standard_Name: FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001.1-1999