Overview
The Nature Conservancy’s Carbon Project Prefeasibility tool based in Shiny is an attempt to consolidate key pieces from the original Prefeasibility Toolkit into a web-based application. This tool is simply a first step towards a feasibility analysis under Improved Forest Management (IFM) methodologies (i.e., American Carbon Registry’s IFM v2.0 or Verra’s VM00045 dynamic baseline). The ultimate aim of the tool is to a) provide an estimated inventory for your project area using TreeMap to identify most similar FIA plots, b) outline broad business-as-usual scenarios for the area and c) output key values to be used in the ACR Pro Forma tool provided in the original toolkit in the ‘CreditYieldEstimator’ folder or there is a link to the Pro Forma tool in the web application.
Please note, this is just the first version of the tool. We already have plans for future developments, including being able to download data directly from FIA DataMart, updating the TreeMap dataset, and improving model forecasts on the ‘Evaluate Harvest Behavior’ page. Please contact Cat Chamberlain if you have any other suggestions.
Home page
On the home page, you can answer the question “Do you have inventory data for your site?”. If you already have inventory data for the site and you do not require estimates for total Mt CO2e per acre, species, forest type, BG:AG biomass, or growth rate, you can proceed to the second page, ‘Evaluate Harvest Behavior’. If you are missing any of the above information, we recommend using the ‘Stocking Estimator’ page to help guide you through the Carbon Pro Forma tool.
Stocking Estimator
On this page, please follow the below steps:
- Enter the state you are interested in (e.g., MI). Please just enter the two letter abbreviation using the drop down list. You can enter more than one state.
- Select which types of ownership you are interested in. For FFCP projects, we recommend using “Multiple private”, whereas for Working Woodlands projects, you may want to select “Private and Public lands”. Unfortunately, at this time, we cannot discern which type of private ownership it may be. By selecting “Multiple private”, this will include individual families, corporations, public universities, and Native American land.
- Click “Browse…”. Select the shapefile for your site including all associated files (i.e., .shp, .dbf, .sbn, .sbx, .shx, .prj).
- Click “Go!”. Please only click the “Go!” button once. It may take a second to show the progress bar but if you click the button more than once, the app will run through the code multiple times and potentially crash. If this happens on accident, please just refresh the webpage and start again at Step 1 on the ‘Stocking Estimator’ page.
The code can take between 3-10 minutes to run depending on the size of your parcel and the state you are working in. Once the progress bar disappears, it can still take a few seconds for the figures and table to load, please be patient. Also, the download buttons will not work until everything has fully loaded.
What is the code doing?
After you click the “Go!” button, the webpage begins downloading all the FIA plots in the state and the TreeMap raster file. The TreeMap raster is a large (4GB) file that matches every 30x30m pixel across the US to the most similar FIA plot . Downloading all of this data is typically what takes so long.
** Please note, at this time Shiny applications cannot handle all the memory space that would be required to download FIA data directly from DataMart. The data in the tool sourced FIA data on 18 April 2023. We will continue to update the data as FIA releases new information.
After the data is downloaded, the code then matches all of the FIA data plots that fit within the shapefile provided, with some FIA plots being represented numerous times. We can then determine plot level estimates of Total Mt CO2e per acre, QMD, Basal Area per acre, etc.
Currently, a harvest is defined as greater than or equal to 10% decline in relative density without any other disturbance noted on the site. The relative density is calculated by summing the total RD of trees that were harvested in the current measurement (STATUSCD=3) but were previously standing, live trees (STATUSCD.PREV=1), divided by the total RD of currently standing, live trees (STATUSCD=1) that were previously standing, live trees (STATUSCD.PREV=1). All trees in this calculation must be greater than 4 inches in diameter.
What is being outputted?
In blue text you will see a series of data points provided:
- The overall mean total Mt CO2e per Acre for the site, which can be inputted in B10 of the Pro Forma tool and used on the ‘Evaluate Harvest Behavior’ page.
- The BG to AG MtCO2e/ac Ratio, which can be inputted in in B11 of the Pro Forma tool.
- The dominant forest types on the site as estimated by TreeMap and FIA. These forest types can be used on the ‘Evaluate Harvest Behavior’ page. We recommend you use your discretion and knowledge of the site to help inform these estimates as TreeMap is not a perfect resource.
Next, you will see two figures:
The first figure is
a breakdown of trees per acre across diameter class bins for each
species by common name. The species, again, are imperfect estimates but
should hopefully provide a guideline for what to expect. The next set of
histograms are showing a) basal area per acre and b) QMD by forest type.
All of these figures are interactive in the Shiny app, which means you
can hover your mouse over the bars and it will give you the exact
information for that point. You can download these figures and the
species level information in the links below the figures.
Next, you will see a table providing site level estimates. The table is also interactive and should allow you to filter and sort. You can also download the site level data below this table.
Finally, you will see a series of maps with point estimates within your shapefile polygon.
Again, all of the maps are interactive so if you hover your mouse over a point estimate, it will give you exact details on that site. The first map estimates QMD for each acre stand (points on the plot), the second map is for total Mt CO2e per acre, and the final map is an estimate for dominant forest type in that area.
You can download these maps and the updated shapefile below.
Evaluate Harvest Behavior
On this page, please follow the below steps:
- Enter the state you are interested in (e.g., “MI”).
Please just enter the two letter abbreviation using the drop down list.
You can enter more than one state.
- Select which types of ownership you are interested in. For FFCP projects, we recommend using “Private”, whereas for Working Woodlands projects, you may want to select “All private and public lands”. Again, unfortunately at this time, we cannot discern which type of private ownership it may be. By selecting “Multiple private”, this will include individual families, corporations, public universities, and Native American land.
- Select all forest types of interest. Use information from the ‘Stocking Estimator’ page to select the forest types most likely found on your site.
- Enter the estimated total Mt CO2e per acre for the site (e.g., 100), which can be found on the ‘Stocking Estimator’ page on the first line in blue.
- Enter the year you plan on implementing your project (e.g., 2024).
- Enter the ecosection code you plan on working in (e.g., 212). You can also enter more than one ecosection. Please separat each entry by a comma and a space (e.g., 212, 222). If you want to look at the entire state, simply type in NA.
- Click ‘Go!’. Please only click the ‘Go!’ button once. It may take a second to show the progress bar but if you click the button more than once, the app will run through the code multiple times and potentially crash. If this happens on accident, please just refresh the webpage and start again at Step 1 on the ‘Evalute Harvest Behavior’ page.
What is the code doing?
This time, the code is taking all potential baseline plots in the state that match the above criteria (i.e., state, forest type, ownership). From there, it is assessing harvest intensity and likelihood and prepares a series of figures to be interpreted by the user.
What is being outputted?
In blue text you will see a series of data points provided:
- The annual growth rate (%) for the site, which can be inputted in B13 of the Pro Forma tool
- The 90% Inventory Confidence as % of Mean for the site, which can be inputted in B14 of the Pro Forma tool
- The ACR BSL Conversion Rate (%) for the site, which can be inputted in B19 of the Pro Forma tool
- The Verra IFM dynamic BSL Conversion Rate (%) for the site, which can be inputted in B19 of the Pro Forma tool
** Please note, the annual growth rate is an average estimate across all FIA plots found on the site, whether or not they were harvested. This will be a conservative estimate.
Emulating Baselines
The ACR methodology maximizes net present value, which is a heavier harvest rate. For this reason, we are estimating a conversion rate for ACR to be the 75% quantile of harvest intensity. Whereas, the Verra dynamic conversion rate is a more conservative estimate. To calculate the dynamic baseline conversion rate, we use the median of the harvest intensity. Depending on the methdology you are interested in, you can use either of these values above in B19 of the Carbon Pro Forma tool.
Next, you will see two figures:
In the top figure, the x-axis represents the previous QMD and the y-axis is most recent QMD measurement minus the previous QMD. Points above the 1:1 line potentially suggest a thin from above treatment, with QMD being higher than previously after harvest. If points fall below the 1:1 line, this potentially suggests a thin from above with a decline in QMD after harvest. Points along the 1:1 line could indication a thin throughout.
In the bottom figure, the x-axis represents diameter classes (by 2 inches) and the y-axis shows percent removed across those diameter classes. Plots that show a ‘J’ formation, would suggest a thin from above treatment, with the higher diameter classes being harvested at a higher intensity than the lower diameter classes. An inverse ‘J’ would suggest a thin from below treatment and a more even distribution across the diameter classes would suggest a thin throughout.
Finally, you will see a panel of four figures:
The top left panel is a histogram of relative density removed (%) across ownership type. The top right is a histogram across the four management buckets by ownership type. The bottom left represents the estimates of total Mt CO2e per acre across management bucket and ownership type after harvest. And the final figure is the projected estimates of average total Mt CO2e per acre over the next 20 years across the four management buckets.
Explaining the four management bucket classifications
- Exploitative Regen:
- post-harvest basal area per acre at less than or equal to 60 ft2/ac and there is a decrease in QMD
- post-harvest basal area per acre at less than or equal to 60 ft2/ac, there is an increase or no change in QMD, and a decrease in species desirability post-harvest.
- Exploitative Thinning:
- post-harvest basal area per acre at greater than 60 ft2/ac and there is a decrease in QMD
- post-harvest basal area per acre at greater than 60 ft2/ac, there is an increase or no change in QMD, and a decrease in species desirability post-harvest.
- Silvicultural Regen:
- post-harvest basal area per acre at less than or equal to 60 ft2/ac, there is increase in QMD, and an increase in species desiribility post-harvest
- Silvicultural Thinning:
- post-harvest basal area per acre at greater than 60 ft2/ac, there is increase in QMD, and an increase in species desiribility post-harvest
Acknowledgements
This tool was a major collaborative effort pooling together many resources that already existed at TNC. It would not have been possible to build without the development of the original Prefeasibility Toolkit lead by Aaron Holley. I would also like to thank Ethan Belair and Catherine Henry for all of their code analyzing FIA data and making figures. Thank you to all the state BUs for sharing shapefiles and helping troubleshoot the webpage, specifically Thomas Reddick, Emily Clegg, John Den Uyl, Chris Zimmerman, Brittany Wienke, and Tanu Biswas. Finally, a major thank you to John Gunn for the endless meetings centered on tweaking the output and thinking through what would be most useful.