TPS is a set of Python 3 modules for the aggregation of trees, plots, and stands from the USFS reference stands data maintained by the Corvallis Forest Science Lab.
- Main Modules
- Installation
- Documentation in the Literature
- Command Line Options
- Details About 1 Tree
- Biomass at the Stand Scale for All Stands
- Biomass at the Stand Scale for a set of one or more stands
- Biomass at the Plot Scale for All Plots
- Biomass at the Plot Scale for a set of one or more plots
- Biomass at the Stand Scale for All Studies
- Biomass at the Stand Scale for a set of one or more studies
- Biomass at the Stand Scale for Individual Trees for a set of one or more stands
- Biomass at the Plot Scale for Individual Trees on All Plots
- Biomass at the Stand Scale for Individual Trees on All Stands
- Biomass at the Tree Scale for Less Than 3 Trees
- Status Checks at the Tree Scale for Less Than 3 Trees
- NPP at the Stand Scale for All Stands
- NPP at the Stand Scale for a set of one or more stands
- NPP at the Plot Scale for All Plots
- NPP at the Plot Scale for a set of one or more plots
- NPP at the Stand Scale for All Studies
tps_Tree<- individual trees, to be computed ID by ID, and perform checks on individuals, ID by IDtps_Stand<- stands, plots on stands, trees on stands, for larger-scale computationstps_NPP<- net primary productivity for plots and standstps_cli<- command line interfacetps_Sample<- tests - queries to 'ncna' that should always work- SQL queries and configs in yaml files for interoperability!
- lots of docs! which you can READ at readthedocs.org.
Set up Python 3 on your computer, and then run the darn thing!
Best to start with tps_Sample, which will run a series of test trees and stands on a known dataset (that it will access from the server to test your connection) and output the results. To run it do:
$ python tps_Sample.pyAssuming this goes well, please read the docs! The docs are in index.html, currently in the _build/ folder. You'll be running the remainder of your analyses out of the command line interface (tps_cli.py) for now, but there are a lot of options.
If you have an issue with the code, please submit it using github and github only. Issues submitted via email or other methods will not be addressed. To get a fixed copy of the program, you'll need to install github and get your own clone of the repository, and keep it up to date with this master. Fox is not responsible for helping you maintain your local copy of the repository.
The latest development version can be installed directly from GitHub. Use this repository. Note that when Fox leaves, maintenance will be sporadic at best. Issues and pull requests will be addressed when possible, with pull requests receiving far more attention (as it shows you made an attempt to fix your own problems first :) ).
The biomass computations began with computations by Gody and Lutz. These were later passed on to Becky, Rob, and myself. There are two main sources, BIOPAK and dendrometer regressions. Dendrometer regressions are from volume, and use the TV009 or TP072 databases available from the FSDB. The TP072 database references the BIOPAK software. Metadata and data from TV009 is here.
For computation of height (where needed), the Garman et al.(1995) methods were used, and height was computed as Ht_m = 1.37 + (b0*(1-exp(b1*DBH_cm))**b2). Height computations are largely internal to the biomass_basis.py module.
If you are at Oregon State, you can also access the equations in the shared T-drive under GROUPS > FSDB > TP001 > biomass_programs to see the original documentation from Gody.
Seven different "forms" of biomass equation are used depending on source of data and tree species. The following shows the syntax for the math for every species of tree. When height is needed, the subsequent table shows the height calculation. Components are BAT (total aboveground biomass, Mg ), VSW (volume of the stemwood, m3 ), HT (height, m), VAE (volume aboveground entire tree, m3) and dbh (diameter at breast height, cm). When volume is the product, a wood density (woodden) value in g / m3 (see reference) is used to convert to biomass. A table is no longer included here as the equations in use may change and maintaining the table could become burdensome.
Some equations require height, which is not otherwise documented. The tables below show the height equations used as of 2015, by species, when necessary to run an equation. No output of height is generated.
| Species | Component | Height |
|---|---|---|
QUKE |
HT |
1.37 + 24.81869*(1-math.exp(-0.026937*dbh))**0.915991 |
ACMA |
HT |
1.37 + 30.41311*(1-math.exp(-0.034245*dbh))**0.682100 |
THPL |
HT |
1.37 + 56.91574*(1-math.exp(-0.012625*dbh))**0.935899 |
PIMO |
HT |
1.37 + 44.60542*(1-math.exp(-0.024401*dbh))**1.219469 |
PIPO |
HT |
1.37 + 44.60542*(1-math.exp(-0.024401*dbh))**1.219469 |
LIDE2 |
HT |
1.37 + 39.82180*(1-math.exp(-0.027393*dbh))**1.403222 |
ABPR |
HT |
1.37 + 78.60353*(1-math.exp(-0.013330*dbh))**1.185140 |
ABMA |
HT |
1.37 + 9.05185*(1-math.exp(-0.016177*dbh))**1.152987 |
CACH |
HT |
1.37 + 40.66479*(1-math.exp(-0.017775*dbh))**0.873626 |
Documentation for the TPS programs is located here. Documentation is autogenerated by sphinx autodoc.
The command line tool has a variety of options for your output. These have all been tested as of 11-06-2015. The command line options are set to organize your access to the data by the type of analysis, the scale of the analysis, the aggregation of the analysis, and finally specific targets for the analysis. Because there are some combinations of these that simply make no sense (bio tree composite ncna00100001, for example, could not run because there is no stand over which to aggregate by species one single tree), these options are blocked programmatically. Options that are allowed are as follows:
This command will get you details about 1 tree and either print them to the screen or to a file. Pretend the tree of your desire is ncna0001000001
$ python tps_cli.py dtx ncna000100001The computer will ask if you would like to have a file, and if so to type Y. If you type Y, the output will go to a file named (in this case for ncna0001000001) ncna000100001_tags_and_checks.csv. If you don't type Y (you can even just press enter), you will see on your screen something like:
Tree: ncna000100001
Year: 1979
Stand: NCNA
Plot: ncna0001
Study: HSGY
DBH: 52.5
Status: 1
DBH Code: G
Tag: 46
Notes:
-------------------
Tree: ncna000100001
Year: 1984
Stand: NCNA
Plot: ncna0001
Study: HSGY
DBH: 53.3
Status: 1
DBH Code: G
Tag: 46
Notes:
-------------------
Tree: ncna000100001
Year: 1989
Stand: NCNA
Plot: ncna0001
Study: HSGY
DBH: 54.0
Status: 1
DBH Code: G
Tag: 46
Notes:
-------------------But this will be for all the years of the tree, not just these first few.
To compute the biomass at the stand scale for all of the stands, use this command.
$ python tps_cli.py bio stand composite --allYour output will be in a file named `all_stands_biomass_composite_output.csv`. It will be organized like DBCODE, ENTITY, STANDID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
To compute the biomass at the stand scale for one or more stands, just add those stands to the end of the line tps_cli.py bio stand composite. You can add as many as you want! You don't need quotes, but you can put them. Don't put commas. Separate them with one space. Here's how you could ask for ncna, rs01, srnf, and wr01.
$ python tps_cli.py bio stand composite ncna rs01 srnf ws01If you have more than one stand, your output will in a file named selected_stands_biomass_composite_output.csv. It will be organized like DBCODE, ENTITY, STANDID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
If you just have one stand, your output will be in a file named [name of whatever stand]_stand_composite_output.csv. It will be organized like DBCODE, ENTITY, STANDID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
To compute the biomass at the plot scale for all of the plots on all of the stands, use this command.
$ python tps_cli.py bio plot composite --allYour output will be in a file named all_plots_biomass_composite_output.csv. It will be organized like DBCODE, ENTITY, PLOTID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
To compute the biomass at the plot scale for one or more plots, just add those plots to the end of the line tps_cli.py bio plot composite. You can add as many as you want! You don't need quotes, but you can put them. Don't put commas. Separate them with one space. You don't have to put them all from the same stand, either, or be organized about it. Here's how you could ask for ncna0001, rs010001, srnf0005, and ncna0004.
$ python tps_cli.py bio plot composite ncna0001 rs010001 srnf0005 ncna0004If you have more than one plot, your output will in a file named selected_plots_biomass_composite_output.csv. It will be organized like DBCODE, ENTITY, PLOTID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
If you just have one plot, your output will be in a file named [name of whatever plot]_plot_composite_output.csv. It will be organized like DBCODE, ENTITY, PLOTID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
To compute the biomass at the stand scale for all of the stands on all of the studies, use this command. Yes, this is exactly the same as the simpler tps_cli.py bio stand composite --all, but if you are thinking in study mode, it might be helpful.
$ python tps_cli.py bio study composite --allYour output will be in a file named all_studies_biomass_composite_output.csv. It will be organized like DBCODE, ENTITY, PLOTID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
To compute the biomass at the study scale for one or more studies, just add those studies to the end of the line tps_cli.py bio study composite. You can add as many as you want! You don't need quotes, but you can put them. Don't put commas. Separate them with one space. You don't have to put them all from the same stand, either, or be organized about it. Here's how you could ask for hsgy and alco
$ python tps_cli.py bio study composite hsgy alcoIf you have more than one study, your output will in a file named selected_studies_biomass_composite_output.csv. It will be organized like DBCODE, ENTITY, STUDYID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
If you just have one study, your output will be in a file named [name of whatever study]_studies_composite_output.csv. It will be organized like DBCODE, ENTITY, STUDYID, SPECIES, YEAR, PORTION, TPH_NHA, BA_M2HA, VOL_M3HA, BIO_MGHA, JENKBIO_MGHA.
You cannot process individual tree biomasses at the scale of ``plot``. There does not exist code to do this. You get ``Stand`` and ``Tree`` but not ``plot``.
To compute the biomass at the individual tree scale for one or more stands, just add those stands to the end of the line tps_cli.py bio stand tree. You can add as many as you want! You don't need quotes, but you can put them. Don't put commas. Separate them with one space. Here's how you could ask for ncna, rs01, srnf, and wr01.
$ python tps_cli.py bio stand tree ncna rs01 srnf wr01Your output will be in a file named selected_stands_indvtree_output.csv. It will be organized like DBCODE, ENTITY, TREEID, COMPONENT, YEAR, BA_M2, VOL_M3, BIO_MG, JENKBIO_MG.
If you just have one stand, your output will be in a file named [name of whatever stand]_stand_indvtree_output.csv. It will be organized like DBCODE, ENTITY, TREEID, COMPONENT, YEAR, BA_M2, VOL_M3, BIO_MG, JENKBIO_MG.
To compute the biomass at the individual tree scale for all of the plots on all of the stands, use this command.
$ python tps_cli.py bio plot tree --allYour output will be in a file named all_plots_indvtree_output.csv. It will be organized like DBCODE, ENTITY, TREEID, COMPONENT, YEAR, BA_M2, VOL_M3, BIO_MG, JENKBIO_MG.
To compute the biomass at the individual tree scale for all of the stands, use this command.
$ python tps_cli.py bio stand tree --allYour output will be in a file named all_stands_indvtree_output.csv. It will be organized like DBCODE, ENTITY, TREEID, COMPONENT, YEAR, BA_M2, VOL_M3, BIO_MG, JENKBIO_MG.
To compute the biomass at the individual tree scale for one or two trees, you can use the tree scale query. For example, to get ncna000100001 and ta01000100001
$ python tps_cli.py bio tree tree ncna000100001 ta010001000001Your output will be in a file named selected_trees_indvtree_output.csv. It will be organized like DBCODE, ENTITY, TREEID, COMPONENT, YEAR, BA_M2, VOL_M3, BIO_MG, JENKBIO_MG.
If you just have one tree, your output will be in a file named [name of whatever tree]_tree_indvtree_output.csv. It will be organized like ``DBCODE, ENTITY, TREEID, COMPONENT, YEAR, BA_M2, VOL_M3, BIO_MG, JENKBIO_MG`.
To check the status of the the biomass at the individual tree scale for one or two trees, you can use the tree scale query. This query will tell you whether or not your trees encountered a variety of non ideal conditions by generating a matrix of null or true values. The docs contain more descriptiosn of what these headers mean. But to work with the program, for example, to get ncna000100001 and ta01000100001
$ python tps_cli.py bio tree checks ncna000100001 ta010001000001Your output will be in a file named selected_trees_indvtree_checks.csv. It will be organized like TREEID, SPECIES, INTERVAL, SHRINK_X_FLAGGED, GROWTH_X_FLAGGED, DOUBLE_DEATH_FLAG, LAZARUS_FLAG, HOUDINI_FLAG, DEGRADE_FLAG.
IF A TREE ONLY HAS ONE REMEASUREMENT IT WILL NOT BE OUTPUT. THE STATUS CHECKS DEPEND ON A DIFFERENCE BETWEEN SUBSEQUENT REMEASUREMENTS. THE DEFINITIONS OF THE FLAGS ARE IN THE BUILD DOCUMENTATION.
If you just have one tree, your output will be in a file named [name of whatever tree]_tree_indvtree_checks.csv. It will be organized like TREEID, SPECIES, INTERVAL, SHRINK_X_FLAGGED, GROWTH_X_FLAGGED, DOUBLE_DEATH_FLAG, LAZARUS_FLAG, HOUDINI_FLAG, DEGRADE_FLAG.
To compute the NPP at the stand scale for all of the stands, use this command.
$ python tps_cli.py npp stand composite --allYour output will be in a file named all_stands_composite_npp.csv. It will be organized like DBCODE, ENTITY, STANDID, YEAR_BEGIN, YEAR_END, SPECIES, DELTA_TPH_NHA, DELTA_BA_M2HA, DELTA_VOL_M3HA, DELTA_BIO_MGHA, DELTA_JENKBIO_MGHA, MEAN_ANNUAL_NPP_BIO, MEAN_ANNUAL_NPP_JENKBIO.
To compute the NPP at the stand scale for one or more stands, just add those stands to the end of the line tps_cli.py npp stand composite. You can add as many as you want! You don't need quotes, but you can put them. Don't put commas. Separate them with one space. Here's how you could ask for ncna, rs01, srnf, and wr01.
$ python tps_cli.py npp stand composite ncna rs01 srnf ws01If you have more than one stand, your output will in a file named selected_stands_composite_npp.csv. It will be organized like DBCODE, ENTITY, STANDID, YEAR_BEGIN, YEAR_END, SPECIES, DELTA_TPH_NHA, DELTA_BA_M2HA, DELTA_VOL_M3HA, DELTA_BIO_MGHA, DELTA_JENKBIO_MGHA, MEAN_ANNUAL_NPP_BIO, MEAN_ANNUAL_NPP_JENKBIO.
If you just have one stand, your output will be in a file named [name of whatever stand]_stand_composite_npp.csv. It will be organized like DBCODE, ENTITY, STANDID ,YEAR_BEGIN, YEAR_END, SPECIES, DELTA_TPH_NHA, DELTA_BA_M2HA, DELTA_VOL_M3HA, DELTA_BIO_MGHA, DELTA_JENKBIO_MGHA, MEAN_ANNUAL_NPP_BIO, MEAN_ANNUAL_NPP_JENKBIO.
To compute the NPP at the plot scale for all of the plots on all of the stands, use this command.
$ python tps_cli.py npp plot composite --allYour output will be in a file named all_plots_composite_npp.csv. It will be organized like DBCODE, ENTITY, PLOTID, YEAR_BEGIN, YEAR_END, SPECIES, DELTA_TPH_NHA, DELTA_BA_M2HA, DELTA_VOL_M3HA, DELTA_BIO_MGHA, DELTA_JENKBIO_MGHA, MEAN_ANNUAL_NPP_BIO, MEAN_ANNUAL_NPP_JENKBIO.
To compute the NPP at the plot scale for one or more plots, just add those plots to the end of the line tps_cli.py npp plot composite. You can add as many as you want! You don't need quotes, but you can put them. Don't put commas. Separate them with one space. You don't have to put them all from the same stand, either, or be organized about it. Here's how you could ask for ncna0001, rs010001, srnf0005, and ncna0004.
$ python tps_cli.py npp plot composite ncna0001 rs010001 srnf0005 ncna0004If you have more than one plot, your output will in a file named either plotname_plotname_plotname_plot_npp_output.csv, or, if this cannot work, in selected_plots_composite_npp.csv. It will be organized like DBCODE, ENTITY, PLOTID, YEAR_BEGIN, YEAR_END, SPECIES, DELTA_TPH_NHA, DELTA_BA_M2HA, DELTA_VOL_M3HA, DELTA_BIO_MGHA, DELTA_JENKBIO_MGHA, MEAN_ANNUAL_NPP_BIO, MEAN_ANNUAL_NPP_JENKBIO.
If you just have one plot, your output will be in a file named [name of whatever plot]_plot_npp_output.csv. It will be organized like DBCODE, ENTITY, PLOTID, YEAR_BEGIN, YEAR_END, SPECIES, DELTA_TPH_NHA, DELTA_BA_M2HA, DELTA_VOL_M3HA, DELTA_BIO_MGHA, DELTA_JENKBIO_MGHA, MEAN_ANNUAL_NPP_BIO, MEAN_ANNUAL_NPP_JENKBIO.
To compute the NPP at the plot scale for all of the plots on all of the studies, use this command. This is basically the same as what would happen if you were to just compute it for all stands.
$ python tps_cli.py npp study composite --allYour output will be in a file named all_plots_composite_npp.csv. It will be organized like DBCODE, ENTITY, STANDID, YEAR_BEGIN, YEAR_END, SPECIES, DELTA_TPH_NHA, DELTA_BA_M2HA, DELTA_VOL_M3HA, DELTA_BIO_MGHA, DELTA_JENKBIO_MGHA, MEAN_ANNUAL_NPP_BIO, MEAN_ANNUAL_NPP_JENKBIO.