Land Treatment Exploration Tool
Land Treatment Exploration Tool
The User Guide contains detailed instructions on how to correctly use this tool. Incorrect use of this tool may result in inaccurate assessment(s) of the planned treatment site(s) and may result in decisions that do not improve the odds of success. If you have additional questions, comments, or suggestions for improvements to the Exploration Tool or this user guide contact email@example.com or call 541-750-1030.
Navigate to the 'Start Planning' button at the top of the home page (Figure 1 D). The Exploration Tool will open in a new browser tab and will start at Step 1.
Planning Map - Clicking the 'Start Planning' button will display the Planning Map on the main pane (Figure 1). Change the basemap by clicking the 'Basemaps' button in the upper right-hand corner of the map (Figure 1 N). Pan the map by holding a left click and moving the mouse. A single left click acts as an identify tool to view attributes of current features displayed on the map. Use the scroll wheel on the mouse to zoom in and out. To export the map to a PDF, click the 'Print Map' button at the upper right-hand corner, below the 'Basemaps' button (Figure 1 N). Once the PDF is ready, the Print button will change to a Printout link. There is no print limit on the number of map iterations with different layers and/or scales.
Left Side Pane - The left side of the screen is where the user enters or selects details about their planned treatment area. There are two main tabs in this left-hand section. The 'Plan Treatment' tab is where information is entered or selected on planned treatment area, summarization layers, similar treatments, and results filters (Figure 1 F). The 'Layers/Legend' tab is where the user selects the layers to view on the map (Figure 1 G).
Plan Treatment -
Go to the User Guide, Steps 1-6 for detailed instructions on how to use the LTET to plan a treatment.
Layers are grouped into categories and selecting the category will expand the section to show you the available layers (Figure 2 A-E). You can turn individual layers on/off by checking or unchecking the boxes to the left of the layer name. A selected layer displays a '-' symbol to the right of the layer name (Figure 2). Clicking the '-' collapses the layer's details. If the selected layer contains sub-layers, the sub-layers will display as a list under the 'Sublayers' tab (Figure 2 C). Selecting a layer or sub-layer reveals Legend information on what each color represents and an Opacity slider to allow more than one background layer to be displayed on the map. It is recommended the map be limited to no more than three visible background layers at once to avoid confusion from multiple background layers with similar color schemes.
Upper Tabs - The tabs within Start Planning (Figure 1 H-M: Planning Map, Site History, Results, Report, USFWS IPaC, and Drought Forecast) are where input selections and result are displayed. All tabs have a default setting and view. Additional information and details are added as the user steps through the planning process. Go to the User Guide: Site History, USFWS Information for Planning and Consultation, Drought Forecast, and Customized Report for detailed information on what is displayed in these tabs.
Enter project name, treatment type, and output file name for the planned treatment. Keep the typed text short and descriptive as they will be added to the Report and included on all exported material. Select the treatment type from the dropdown menu. To plan a post wildfire rehabilitation action, select 'ESR Wildfire Project' from the dropdown menu. A multiselect section will appear where the user can select multiple ESR treatment types (Figure 3B). 'File Name' is the exported file name. To use the 'Project Name' as the 'File name', select the 'same as project name' box. A green check mark will appear as each field is completed. When all three fields are complete and display green check marks, click the 'Next Step >>' button to move to Step 2.
The Exploration Tool is designed to assist you with the planning process, but requires, at minimum, a general idea of where the land treatment will occur. An existing treatment boundary can be uploaded as a compressed (.zip) shapefile or drawn as a boundary using the interactive web map. The 'View layers you can turn on and off' on the lower right will take you back to the Layers/Legend tab where layers can be added or removed to help with boundary determination. Select 'Next Step >>' to continue the planning process.
Have a shapefile? Use the 'Upload zip file' button (Figure 4 A) to upload a zipped folder containing the shapefile of an identified area. The map will automatically zoom to the location of the uploaded shapefile. To edit the shape, click on the shape and click and drag the dots (vertices) along the boundary lines.
Don't have a shapefile or want to add additional areas to the uploaded shapefile? Add features using the 'Rectangle', 'Polygon',
Rectangle: Left-click (holding the mouse button down) on the map and drag diagonally to create a rectangular area. The rectangle is finished when you release the mouse.
Polygon: Left-click (and release) on the map at each location you want the polygon to change direction (creating a new vertex). Double click to add the final vertex and complete the feature.
Freehand: Left-click (holding the mouse button down) on the map and draw to create an area, much like you would with a pencil. Release the mouse when finished to complete the area.
To edit the drawn shape, click on the shape and click and drag the dots (vertices) along the boundary lines. Multiple polygon areas can be uploaded and drawn for a single treatment. A record is created for each area and displayed in the left-hand section. Individual areas can be zoomed in on the map by clicking the 'Zoom' link or deleted by clicking the 'Delete' link next to each polygon record (Figure 4 C).
All the drawn and uploaded treatment boundaries can be deleted by clicking the 'Remove all user polygons'. Proposed treatment polygons can be exported as kml (google earth), geoJSON (open source spatial format), or shapefile by clicking on the appropriate link (Figure 4 D). Any of these formats can be incorporated into most GIS applications. Once the proposed treatment boundaries are set, click the 'Next Step >>'button to move to Step 3.
This step directs you to the Planning Map, Site History, IPaC, and Drought Forecast tabs to allow the user to explore different aspects of the site characteristics based on their selected treatment boundaries and adjust the boundaries as needed. Refer to individual sections within this User Guide for details on each tab and instructions on how to use and interpret the information.
When no more adjustments to the treatment boundaries are needed, click the 'Next Step >>' button to move to Step 4.
Layer attributes inside the planned treatment boundary can be selected for summary and reporting as tables (Figure 5) within the Report tab. Continuous layers, such as elevation, precipitation and temperature, are summarized across the treatment area with a mean, range, and standard deviation. Categorical layers, such as soil temperature regimes, heat load, and conifer invasion risk, will display the categories intersecting the treatment area along with the percentage and acreage of each intersecting category. Layers can be reviewed by navigating to the 'Layers/Legend' tab at the top of the left side pane and toggling the layers on and off. Not all layers are available across the entire U.S. Once all layer attributes to be summarized and reported are selected, click the 'Add to Report' button to move to Step 5.
NOTE: Calculations are made real-time and may take a few minutes. The results will appear automatically within the Report tab when the calculations are finished. If internet speeds are slow, data loss may occur. If additional attribute summaries need to be added to the report or certain layers did not calculate due to data loss, re-run the summarization by clicking 'Add to Report' again or by selecting 'Retry' under the summary table. It is best to wait until Step 4 processing is complete before moving onto Step 5. Notes can be added to the Site History tab while the Tool is calculating results for the Report.
If the Exploration Tool is used to only view summary data of a planned area, the results can be exported to a pdf when Step 4 calculations are complete. Additional information about how to export the Report can be found in the 'Customized Report' section of this User guide.
Pop-up window: Welcome to your developing report
The summary tables are being generated. If the tables do not fill in with data and continue to say 'Waiting for data' after several minutes, click the 'Add to Report' button in Step 4 again. If a table returns an error, run an individual table again by selecting 'Retry' under the summary table. These actions will reset the calculation(s) and populate the table(s).
The map shown here is linked to the Planning Map tab. Adjustments can be made to this Report map by changing the layers in the Planning Map tab. The zoom scale of this map determines the scale on maps included in the report pdf.
The Land Treatment Digital Library Matches table is populated in Step 6 when treatments of interest are selected for the project. User Annotations from Site History and the generating report are included in the report pdf.
Background: The purpose of this step is to find previously reported land treatments that may contain useful information to help improve the design of a planned treatment or provide justification for current plans. Currently, previous treatment data from the Land Treatment Digital Library (LTDL, https://ltdl.wr.usgs.gov) are the only available, detailed treatment data within the tool that will be displayed in the results table. However, additional sources of treatment layers are included to view in the Layers/Legend. The LTDL data contains legacy Bureau of Land Management (BLM) treatments collected from BLM offices across the western U.S., with a few treatments dating all the way back to the early 1900s. These data represent the best information available at the time the legacy data were collected from field offices and entered into the LTDL. Some records have been lost to time, are incomplete, or are still being entered. A limited number of treatments within the last 5 years have been entered into the LTDL, but data entry continues. If data appear to be missing or incorrect in the LTDL, contact us at firstname.lastname@example.org or call 541-750-1030.
How to Search for Treatments There are two main search methods: Spatially by buffer or boundary (Figure 6 A) alone or optionally include a statistical Bray Curtis Dissimilarity Model (Figure 6 B). First, select a buffer or boundary search distance:
If 'User-defined buffer distance' is selected, a section will appear where a buffer distance can be specified (Figure 7 A). The selected buffer can be displayed as a grey shaded area on the 'Planning Map' using the 'Show Buffer' button and turned off with the 'Remove Buffer' button. A treatment will be included in the query results if any part falls within the buffer.
Once the search area is defined, a similarity ranking can be optionally calculated for climate, heat load, and landform by selecting the desired attribute(s) (Figure 6 B, Figure 7 B). Selection of a similarity attribute is not required to run the Report. If similarity attributes are selected, the similarity index will run a model comparing the proposed treatment to the LTDL treatments within the buffer based on a pre-defined set of characteristics - climate, landform topography, or heat load. The proposed treatment is measured against the LTDL treatments using a Bray-Curtis dissimilarity calculation (Bray and Curtis 1957, McCune and Grace 2002). Similarity models are calculated in real-time and increasing the number of similarity statistics or treatments within the search radius will increase the Tool's processing time.
Climate - This model extracts the 30-year (1981-2010) monthly averages from the PRISM 800m precipitation and mean temperature rasters (http://www.prism.oregonstate.edu/). Using monthly temperature and precipitation, as opposed to annual climate variables, ensures that the similar treatments match seasonally and not annually to provide a better fit.
Heat Load - This model combines extracted values from the Heat load raster. Heat load, a unitless value from 0 (low incident radiation) to 1 (high incident radiation), is calculated using aspect, slope, and latitude (McCune and Dylan 2002). Given the high variability possible within a small area, heat load is classified into 6 categories ranging from very low to very high.
Landform Topography - Landform classifications were developed by the USGS to categorize the landscape into different categories based on the terrain (https://pubs.usgs.gov/sim/3085/). This model extracts landform class percent coverages within the planned treatment area and compares those categories and percentages to those within the LTDL polygons.
If you select one or more of the similarity models (Figure 7 B, Climate, Landform, and Heat load), returned similar treatment results within your boundary or buffer will be ranked based on each model. Only treatments within your buffer or boundary area are tested. If you select a large buffer or boundary, returned treatments may overwhelm the geoprocessing and fail to return results (Figure 8). You can reduce the number of returned treatments by selecting a smaller buffer or boundary.
Once all selections are made, click the 'Query LTDL' button to run the query (Figure 6 C and 7 C). The query process is in real-time and may take some time. The status of the calculations is displayed along the left side panel (Figure 6 D and 7 D). The query status will read 'Done' and the Results table will be filled in when the processing is finished. If the query status returns an error message (Figure 8), try and submit the query again by re-clicking the 'Query LTDL' button. If the message persists, try reducing the size of the search area or contact the Exploration Tool staff at email@example.com or call (541) 750-1030.
This section describes how to filter through the LTDL treatments Results that were generated in Step 5. Filtering will help identify those treatments that are most similar to the planned treatment to reference and learn from. Multiple options can be selected per dropdown by making additional selections from the drop down. The selected values will appear in blue under each search criteria (Figure 9 B). To remove search values, hover over the value, which will display with a strikethrough, and click it. To explain the field, click the '?' to the right of the filter name. Filter fields that do not display a dropdown menu are not applicable to the generated results.
Field definitions are available under 'Table Structure' below the filter list. The list of filter fields are as follows:
Once similar past treatments are returned, presented, and filtered in the Results tab (Figure 10A), a final selection of only the most relevant past treatments can be made for inclusion in the report (Figure 10). Each past treatment returned contains basic attribute information with an expandable window for additional information (Figure 10 D). Full attribute information on a past treatment can be found in the LTDL (https://ltdl.wr.usgs.gov).
Table Structure - Column Information: The column headers are found along the top of the table. Each column can be used to sort the table by clicking on the down-up arrows to the lower right of each column header. Treatment evaluation color-coded columns on the right side of the table can be used to quickly identify the data quality. In general, the more green columns a treatment has, the more complete and potentially useful it is for informing future treatment plans. Full column descriptions are below. Columns displayed will vary from report to report and depend on selected search criteria.
Climate Rank: Corresponds with the Climate Similarity Limit filter. If you selected a climate similarity model then this column will appear and populate. The value represents the relative similarity to the planned treatment area. A value of '1' shows the most similar treatment, regarding climate.
Heat load Rank: Corresponds with the Heat Load Similarity Limit filter. If you selected a heat load similarity model then this column will appear and populate. The value represents the relative similarity to the planned treatment area. A value of '1' shows the most similar treatment, regarding heat load.
Landform Rank: Corresponds with the Landform Similarity Limit filter. If you selected a landform similarity model then this column will appear and populate. The value represents the relative similarity to the planned treatment area. A value of '1' shows the most similar treatment, regarding landform.
Project: Corresponds with the Project Name filter. This field is always visible. It shows the project name that the treatment falls within.
Treatment Category: Corresponds with the Treatment Category filter. This field is always visible. It shows the major category that the treatment falls within. Possible categories are: Biological Control, Closure/Exclosure, Cultural Protection, Facilities/Fences/Roads, Herbicide/Weeds/Chemical, Other, Prescribed Burn, Seeding, Soil Stabilization, Vegetation/Soil Manipulation.
Treatment Type: Corresponds with the Treatment Type filter. This field is always visible. It shows the most specific treatment type name. There are 237 possible names.
Year: Corresponds with the Implementation Status filter. This field is always visible. It shows the treatment start year.
Imp: Corresponds with the Implementation Status filter. This is the first color-coded column included for treatment evaluation. Implementation status of the treatment is based on the best available data during LTDL data entry for this treatment.
I - Implemented (green)
U - Unknown Implementation (yellow)
Poly: Corresponds with the Treatment Polygon Implementation Status filter. This is a color-coded column included for treatment evaluation. Implementation status of the GIS shape based on available data when LTDL data entry for this treatment occurred.
AP - Approximate point created by LTDL data entry personnel, true location unknown (yellow)
AU - Approximate point created by non-LTDL personnel, true location unknown (yellow)
BA - Digitized by BLM field office personnel, using computer program from aerial imagery (green)
BG - Digitized by BLM field office personnel, using a GPS unit on the ground or aircraft (green)
BI - Digitized by BLM field office personnel, using computer program from satellite imagery (green)
BP - Digitized by BLM field office personnel, using paper map (green)
BU - Digitized by BLM field office personnel, method unknown (yellow)
DU - Digitized by DOD personnel, method unknown (yellow)
EU - Digitized from an external website, method unknown (yellow)
FS - Digitized by Forest Service personnel, method unknown (yellow)
GS - Exported from an internal USGS Fire Perimeter Layer (yellow)
LC - Digitized by LTDL data entry personnel using a confirmed map (green)
LI - Digitized by LTDL data entry personnel using location information within documentation (yellow)
LP - Digitized by LTDL data entry personnel using a planned map (yellow)
LU - Digitized by LTDL data entry personnel using a map of unknown origin (yellow)
LV - Digitized by LTDL data entry personnel, merged map from various sources (yellow)
PS - Digitized by NPS field office personnel, method unknown (yellow)
SL: Corresponds with the Seed List Implementation Status filter. This is a color-coded column included for treatment evaluation. This shows the status of the seed list based on available data when LTDL data entry for this treatment occurred.
C - Confirmed seed list (green)
U - Unknown seed list (yellow)
P - Planned seed list (yellow)
N - No seed least (yellow)
NA - Not applicable (non-seeding treatment) (white)
Res: Corresponds with the Effectiveness\Monitoring Results filter. This is a color-coded column included for treatment evaluation. This field indicates if there is text written in the 'Effectiveness and Monitoring' field in the LTDL. Text in this field is typically qualitative. This data is only current to the available data when LTDL data entry for this treatment occurred.
Y - Yes, there is text written in this field (green)
N - No, this field has no value (yellow)
Mon: Corresponds with the Quantifiable Monitoring Information filter. This is a color-coded column included for treatment evaluation. This field indicates if the 'Monitored' field is selected in the LTDL. This field is to be checked in the LTDL when quantitative monitoring data for at least one of the treatments was available when the legacy data was added to the LTDL. The LTDL does not contain comprehensive monitoring data. Additional monitoring data may be available from individual BLM offices.
Y - Yes, quantifiable monitoring data indicated in documentation (green)
N - No quantifiable monitoring data currently available (yellow)
Ver: Corresponds with the Verified by BLM Personnel filter. This is a color-coded column included for treatment evaluation. This field indicates that a BLM employee familiar with the treatment verified the information for the project in the LTDL.
Y - Yes, a BLM employee familiar with the treatment has verified this information (green)
N - No, a BLM employee familiar with the treatment has not verified this information (yellow)
Additional information displayed in the expanded window includes:
Treatment ID: Unique identifying number of the treatment.
BLM Field Office: BLM field office the treatment falls within.
Date Confirmation: Confirmation status of the treatment start and end dates.
Unknown: Date status is unknown
Estimated: The dates are estimated
Confirmed: The dates are confirmed
Start Date: Corresponds with the Start Year filter. Start date of the treatment.
End Date: Corresponds with the End Year filter. End date of the treatment.
Units: The type of unit recorded for the treatment.
Number of Units: The number of land measurement units.
GIS Feature Type: Type of shapefile (line, point, multipoint, polygon, and polyline) used to define the treatment boundary.
Feature Status: Implementation status of the GIS shape assigned when the legacy data was added to the LTDL. This field may say: confirmed, unknown, planned, or approximate point.
GIS calculated acres: Number of acres calculated by ArcGIS
BLM Reported Success: The success category as recorded in the documentation from the BLM. Success categories are not comparable across treatments and care should be taken in interpretation.
Objectives: Text description of objectives the treatment was trying to accomplish.
Treatment Results: Corresponds to Effectiveness\Monitoring Results filter. Text in this field is typically qualitative description of the results of the treatment and is what was available when the legacy data was added to the LTDL.
Seed List Status: Implementation status of the seed list assigned when the legacy data was added to the LTDL. Options are: confirmed in field, confirmed in GIS, confirmed on paper, in progress, no seed list, not applicable, plan, and unknown seed list origin.
Seeds or Seedlings Planted: Indicates if the treatment used seeds, seedlings, or if it is unknown.
Seed List Table: If the treatment includes a seed list, then the seed list table will appear. It includes information on: USDA plant symbol, species name, common name, bulk seed pounds, bulk pounds/acre, Pure Live Seed (PLS) rate, PLS seed pounds, PLS pounds/acre.
Checkboxes: The right side of the expanded box displays checkboxes for what documentation and general information is available from the LTDL for the project (note - this is specific to the project, not the individual treatments within the project).
The entire table of Land Treatment Digital Library Matches can be exported in the Results tab. Use the filters in Step 5 to refine the table to export. Click 'Copy Filtered Rows ' to copy the filtered rows to your clipboard. Simply paste these in excel or other applicable software.
Additional information displayed in the expanded window of the selected treatments populate the 'Land Treatment Digital Library Matches' section at the bottom of the report displayed in the Report tab.
Previously Treated Areas: The Exploration Tool utilizes BLM land treatment data from the Land Treatment Digital Library (LTDL). The LTDL database stores information on thousands of treatments recorded by western U.S. BLM offices. To maximize the usefulness of the data used by the Exploration Tool, a subset of the data that have a polygon spatial area and are considered a 'main' treatment type (e.g, actual land manipulations) are displayed in this section. For full treatment details and all information collected in the LTDL, visit https://ltdl.wr.usgs.gov.
The maps show areas within and around the proposed treatment boundary that have a record of a previous land treatment including unknown implementation in addition to implemented treatments or implemented treatments only in the LTDL (Figure 11). Unknown implementation treatments are included because LTDL data entry specialists are not always able to identify if a treatment took place based on the data available at the time of data entry. Many of the Unknown Implementation treatments likely occurred. It is highly recommended one verify treatments, both unknown or implemented, took place by consulting with the BLM field office associated with the treatment.
Previously Treated Areas Maps: Two Previously Treated Areas maps display various treatment layers represented as count rasters to describe the number of times an area has been treated (Figure 11 C) and the type of treatments to see where specific treatments occurred on the landscape (Figure 11 D). For example, one can view all main treatments (e.g., actual land manipulations) that overlap the proposed treatment boundary or even refine the map display to show only seeding treatments. The default view is to display all main LTDL treatments (e.g., actual land manipulations). You can also choose to only view treatments with 'Confirmed Implementation' or all treatments regardless of implementation status. Select the 'Confirmed Implementation' radial button to only see confirmed treatment or the 'Confirmed and Unknown Implementation' option to see all. The legends display the count of times an area has been treated and the types of treatments, respectively. The maps are linked to each other and will display the same view results, meaning zooming in on one map, zooms the other accordingly. Change what information is displayed on the maps by selecting from the 'Select Major Treatment' dropdown menu and 'Implementation status of treatments' options (Figure 11).
Previously Treated Areas Annotation Box: A text box beneath the 'Previously Treated Areas' maps is where one can annotate notes on the treatment history to include in the report.
Overlapping Treatments from the Land Treatment Digital Library Table: Beneath the 'Previously Treated Areas' maps and annotation box is a list of the main LTDL treatments (e.g., actual land manipulations) that overlap the planned treatment polygon. You can re-order the table by clicking on a column header. 'Trt_ID' is the unique numeric identifier assigned to a treatment in the LTDL. 'Treatment_Type' displays the general category of the treatment. 'Project' displays the name of the project. Clicking on the project name opens a new tab to the LTDL where one can view additional, detailed information about the project. 'Percent_Overlap' displays the percentage of the planned area intersected by the LTDL treatment.
NOTE: You must have a login to access the LTDL project details. To request access, email the LTDL (firstname.lastname@example.org).
Wildfire History: The wildfire history for the proposed treatment area is the third section in Site History. The map displays the proposed treatment boundary and one of four wildfire layers: 1) Number of Times Burned (1878-2019), 2) First Year Burned (1878-2019), 3) Most Recent Year Burned (1870-2015), or 4) Polygon Perimeters of Each Wildfire (1878-2019; Figure 12). See Fire History Reference Information to learn more about how these wildfire layers were created. To change the wildfire layer, use the checkboxes on the right (Figure 12 B). The legend beneath the layer names will display the symbology for the selected layer (Figure 12 C). Use the legend to identify how many times different areas around and within the proposed treatment boundary have burned. The opacity slider allows you to change the transparency of the fire layer on the map. To identify and further interact with these layers, navigate to the Planning Map and Layers/Legend tab to turn wildfire layers on from the 'Wildfire' grouping.
Wildfire History Annotation Box:A text box beneath the 'Wildfire History' map is where one can annotate notes on the wildfire history to include in the report. Image of Wildfire History and Climate for proposed treatment area.
Historical Climate: The historical climate data for the planned treatment area are summarized in the climatogram beneath the Wildfire History section (Figure 13). Monthly precipitation and temperature information are averaged over a 30-year period (Figure 13, 1981-2010). Months are found on the x-axis. Precipitation is found as the blue bars and associated with the left-hand y-axis. Minimum (blue), mean (green), and maximum (red) temperature are found as the points connect by lines that are associated with the right-hand y-axis. The climatogram can be exported as a pdf or a png image file by clicking the appropriate button on the bottom left of the graph.
Historical Drought: This section is a map of one of the most useful indices for translating meteorological conditions into a representation of ecosystem water balance, the Standardized Precipitation Drought Index - or SPEI (Vicente Serrano et al. 2010). The map helps assess how "drought" prone the selected area of interest is or has been. Several other drought indices are available, but SPEI has become more widely used in settings such as the western U.S. because the index incorporates temperature through basic calculation of precipitation minus potential evapotranspiration, and has been standardized using more complex calculations making the index scalable for different applications - from local sites to whole continents. SPEI values should be zero in the long term, unless directional change in moisture availability is occurring across the specified time range. SPEI typically ranges from approximately +2 to -2 for substantive wet and dry periods, respectively, and up to +4 and -4 for extreme wet or dry periods.
You can easily find indices, such as SPEI, that may be useful for gauging climatic drought from a meteorological perspective, but they may not always relate well to land treatments (O'Connor et al. 2020). For example, a USGS Climate Adaptation Science Center (CASC) study (O'Connor et al. 2020) over many decades of historic seeding of sagebrush across the Great Basin discovered that sites having sagebrush many years after seeding compared to those that didn't had no difference in SPEI in the years immediately following fire and seeding. Instead, the CASC study found that successful sites had a greater number of wet degree days in the critical spring period for seedling germination and survival in the year following seeding. Specifically, the hundreds of sites having sagebrush years to decades after fire and seeding, had a mean of seven more days in the spring - March - immediately following seeding that had daily mean temperatures greater than 0°C and simulated soil water availability within the plant-extractable range in the top 5 cm of soil. The soil water threshold was -2.5 MPa, which is a measure and units used by plant physiologists. Key demographic steps are dependent on water availability, which is affected strongly by temperature, in precise places and times, such as in springtime and near the soil surface where seeds and seedlings reside. While indices such as SPEI can help gauge water availability in terms of bulk soil water storage and water levels in streams or ponds, they are more apt to relate to productivity of established perennial stands rather than success of particular restoration steps.
Historical Drought Maps: The map displays the proposed treatment boundary and the mean SPEI (2001-2014), standard deviation of SPEI (2001-2014), or mean yearly SPEI (2001 through 2014). See Barnard and Germino 2020 to learn more about how these SPEI layers were created. To change the displayed SPEI layer, click the checkboxes on the right (Figure 14). The legend beneath the layer names will display the symbology for the selected layer (Figure 14). The opacity slider allows you to change the transparency of the SPEI layer displayed on the map. To identify and further interact with these layers, navigate to the Planning Map and Layers/Legend tab to turn SPEI layers on from the 'Climate' grouping.
Historical Drought Annotation Box: A text box beneath the 'Historical Drought' map is where one can annotate notes on the drought history to include in the report.
Links for Additional Drought Information: The bottom of the Site History tab includes links to additional resources about drought. Each link has a hyperlinked title and brief explanation of the resource.
Resources: The Exploration Tool integrates directly with other tools that allow users to spatially upload a polygon and display the other tool's results within the Exploration Tool interface. The first tool integrated into the Exploration Tool is the USFWS Information for the Planning and Consultation (IPaC) tool (https://ecos.fws.gov/ipac/). The polygon created in Step 2 is automatically uploaded to IPaC to generate results. A unique URL to the IPaC tool is generated for the planned treatment and is found on the 'USFWS IPaC Tab'. Sign in to the IPaC tool is required for full report access, but a draft report of the affected resources in the planned treatment area can be generated without login access by clicking the 'Print Resource List' button on the left. Clicking the 'Define Project' button on the IPaC website will also require a user login to their system, but will create a more thorough IPaC report, if needed. Four attributes are displayed on the 'USFWS IPaC' tab in the Exploration Tool and on the IPaC website (Figure 15):
Endangered Species: Information on listed species in the proposed treatment area. Data can be viewed as photo thumbnails or a list on the IPaC website. A list is displayed within the Exploration Tool.
Migratory Birds: Information on the migratory birds designated as a USFWS Birds of Conservation Concern that might be found in the planned treatment area. Data can be viewed as photo thumbnails or a list on the IPaC website. A list is displayed within the Exploration Tool.
Facilities: Information on USFWS Wildlife Refuges or Fish Hatcheries within the planned treatment area.
Wetlands: Information on wetlands from the USFWS National Wetlands Inventory.
Weather variability, specifically intra-annual variations in seasonal water and temperature as they are affected by particular storms or short-term events that are a week or months-long, are well known to have strong effects on land treatment application and outcomes, particularly in dryland ecosystems. Past research has demonstrated the importance of weather, and drought in particular, on the success or failure of dryland restoration (Brabec et al. 2017, Hardegree et al. 2018, Shriver et al. 2018, Moffett et al. 2019).
The Seasonal Ecological Drought Forecast module of the Exploration Tool provides seasonal forecasts of weather and soil water availability that can aid in the planning of treatments, such as herbicide or seeding after wildfires. These forecasts may also be useful for understanding past treatment success, and/or evaluating climate and weather effects on treatments.
Seasonal Ecological Drought Forecast: This tool integrates regional seasonal outlooks by the National Weather Service for temperature and precipitation, including uncertainty, with an ecosystem water balance model that estimates soil moisture conditions for 12 months in the future. Users specify a location and, if desired, soil texture. The tool calculates site-specific outlooks for temperature, precipitation, and soil moisture and compares those outlooks to historical conditions at a 4km resolution. This information can be useful for assessing the potential impact of drought on land treatments in the coming year. Currently, the tool calculates potential sagebrush establishment in the coming season. Metrics for additional plant species are planned for future versions of the tool.
Instructions for using the tool: Upon creating the planned treatment, a latitude and longitude representing the planned treatment area is calculated and used by the Short-term Drought Forecast API. A different location can be selected by clicking on the 'Point' button below the map and then clicking the new location on the map. By default, the tool will use gridded soils data to determine the percent clay and sand for the location. Click the 'Specify Soils' radio button to reveal text boxes where you can enter other values for the percent of clay and sand. Click the 'Calculate' button to generate the Seasonal Ecological Drought Forecast report. The calculations take 3-5 minutes to run. When they are complete, graphs will populate the Drought Forecast tab. A summary will display at the top with seven sections that can be expanded by clicking each section. Sections include: Soil Moisture, Temperature, Precipitation, Sagebrush Seedling Success, Potential Natural Sagebrush Seeding Survival, References, and Methods.
Your Seasonal Ecological Drought Forecast: To the right is the Quick View summary displaying the 30-day rolling average of soil moisture, temperature, and precipitation for the selected site for the past six months and the modeled future 12 months (Figure 16).
Below are three metrics: Soil Moisture, Temperature, Precipitation, in more detail and in comparison to long-term historical average conditions and long-term variation in historical conditions (Figure 17). Figures also show the difference between forecasted conditions and the long-term average, which can be used to assess how the coming year is expected to differ from typical conditions at the site (Figure 18). These results can be useful for evaluating the potential outcomes of land treatments and land management decisions.
Soil Moisture displays volumetric water content (cm/cm), temperature displays air temperature (degrees C), and precipitation the total daily precipitation (cm). Each of the three sections includes two graphs. The first displays an 18-month time series of values (Figure 17). The time series includes recent (the last 6 months) observations on the left of the vertical red dashed line and forecasted values (the next 12 months) on the right. Variability in forecasted values is a result of uncertainty in the seasonal outlooks for temperature and precipitation. The soil moisture section includes an additional level of detail to toggle the soil depth to in shallow (0-15cm), intermediate (16-50cm) or deep soil depths (>50cm; Figure 17 A).
The historical median of the 30-day rolling average (black line), and 10th and 90th percentiles (gray shaded area) are calculated for the climatological normal period (1981 - 2011) and represent reference conditions for the site. The vertical, dashed red line on the figure is the date the Seasonal Ecological Drought Forecast tool is run, and the vertical, dashed black line is the date of the most recent weather data from gridMet. To the left of the vertical dashed red line are the daily observations from gridMet (dashed yellow line), and a 30-day rolling average of gridMet observations (solid yellow line). To the right of the vertical, dashed red line are the approximated daily means (thick purple line), and the 10th and 90th percentiles (shaded purple) for the upcoming year. More information about the development of these forecasts can be found at https://github.com/DrylandEcology/ShortTermDroughtForecaster.
The second graph in each of first three sections displays an 18-month time series of deviations from the historical normal, or long-term mean conditions observed during a historical period of 1981-2011, for the site (Figure 18). The time series includes recent (the last 6 months) observations on the left of the vertical red dashed line and forecasted values (the next 12 months) on the right. The long-term historical normal (median of the 30-day rolling average) for each day is plotted in the background to compare the recent past and future to reference conditions. This figure helps users determine if soils are expected to be wetter or drier than normal, if the temperature is expected to be warmer or cooler than normal, and if the precipitation is expected to be less than or greater than normal.
The historical normal is calculated as the median of 30-day rolling average taken over 1981 - 2011. In the second graph the normal is set to zero (horizontal black line) and the area between the 10th to 90th percentile of this period is shaded in gray. The vertical, dashed red line on the figure is the date the Seasonal Ecological Drought Forecast tool is run and the vertical, dashed black line is the date of the most recent weather data from gridMet. The difference between the historical normal (median of the 30-day rolling average) and the recent past/upcoming year are shaded green when soil moisture is greater, red when temperature is warmer, and green when precipitation is greater than the historical normal. The shading is brown when soil moisture is less than, blue when temperature is cooler, and brown when precipitation is less than the historical normal. The differences between the 10th and 90th percentiles of the future and the historical normal are represented as dashed purple lines.
Future forecasts show variation at the monthly timescale, interpolated to daily to match the timescale of the National Weather Service forecasts. A full description of the future weather forecast logic can be found here. More detail about the interpretation of these figures can be found here.
Generic example to help interpret the figures: A hypothetical example for a date to the right of the Today line (modeled future). The logic for the interpretation is similar for soil moisture, temperature, and precipitation. The following example is written for soil moisture.
At 'date x',
Black line - The historical median of the 30-day rolling average is 0.20. This is the median reference condition.
Gray shaded area - The 10th (0.15) to 90th (0.28) percentile of the historical data. This is the historical range of variation for this site on 'date x.'
Purple line - The median of the forecasted values for 'date x' is 0.25.
Purple shaded area - The forecasted 10th (0.18) to 90th (0.27) percentile for 'date x.' This represents the variation in the forecast. Soil moisture for this date is likely to fall within this range, based on the output from the SOILWAT model and forecast data from the National Weather Service (NWS). NWS forecasts are updated every month, and these figures will change as those forecasts are incorporated.
Gray shaded area - The difference between the 10th (0.15-0.20= -0.50) and 90th (0.28-0.20= 0.08) historical percentiles and the historical median.
Green shading - The difference between the forecast median and the historical monthly median (0.25-0.21= 0.04) at 'date x.' The green color means the predicted soil moisture is expected to be more than the historic median. If it was predicted to be less than, it would be brown.
Dashed purple lines - The different between the forecasted 10th (0.18-0.21= -0.03) and 90th (0.27-0.21= 0.60) percentiles and the historical median value.
Note: Monthly historical medians (0.21 in the above example) were used to calculate the difference between the future forecasts and historical. This is because all future data is calculated at a monthly scale (and interpolated to dailys). This monthly historical data was calculated 'behind the scenes' and is not visualized on these figures. More detail about this process can be found here.
Sagebrush Seeding Success: Estimates of future seeding success can be made from the findings of historic relationships of post-fire sagebrush seeding success to soil-moisture and temperature conditions in and around the Great Basin. This section displays estimates of big sagebrush seeding outcomes for the coming season derived from two recent publications. Study 1 - Shriver et al. 2018 identified that seeding success is greater where and when spring moisture is greater. Study 2 - O'Connor et al. 2020 , further discovered that successful seedings had seven additional days of soil water available to seeds and seedlings based on soil physical properties, such as texture, when soils were above freezing, compared to unsuccessful sites.
Study 1 - Shriver et al. 2018, was developed by the SageSuccess Project, a joint effort between USGS, BLM, and USFWS. This study related soil water content in early spring and site air temperature the first half of the year to post-wildfire sagebrush seeding success. The results indicated big sagebrush occurrence is most strongly associated with relatively cool temperatures and wet soils in the first spring after seeding. The resulting forecasts help identity where and when seedings might be more or less successful. The Study 1 box plot depicts historical and predicted probability of sagebrush establishment (Figure 19). The boxplot on the left shows the median and range of sagebrush establishment in the climatic normal period (1981 - 2011; Figure 19 B). Individual points of probability of success in more recent years are shown as individual points with a year label. The center boxplot is the prediction for probability of success for the current year and the right boxplot for the upcoming year; Figure 19 C, D). The current and upcoming years' Forecasted Establishment boxplots represent the range across potential realizations of the future. Data for the subsequent year will not be displayed until at least 6 months of forecast data are available for the subsequent year. Text above the center and right-most box plots indicate how the predicted probability of establishment compares to the historical values (Figure 19 A).
Study 2 - O'Connor et al. 2020, was developed by the USGS by the Climate Adaptation Science Center (CASC) Ecological Drought Index study. This study used SageSuccess data and included additional post-wildfire seeding areas for statistical validation, and considered whether the modeled soil-water contents were in the plant-available range during sagebrush germination and emergence - March. Soil-water availability relates to how strongly bound soil water is to soil. Values 0 to -1.5 MPa (megapascals) are typically easily extracted by most wildland plants while values below -2.5 MPa cannot be extracted by most plants, including sagebrush seedlings. This study found that successful seedings had seven additional days of soil water available to seeds and seedlings based on soil physical properties, such as texture, when soils were above freezing, compared to unsuccessful sites. These figures allow for the comparison between the user selected location and sites where sagebrush was or was not present.
The graphs for Study 2 shows the mean daily soil water potential within the top layer of soil/0-5cm only (Figure 20 A) and soil temperature (Figure 20 B) in March across all sites used in the O'Connor et al. 2020 study, where sagebrush was present (orange) and absent (blue). Predicted conditions are in purple. The 95% confidence interval is the shaded band and the line is the mean (Figure 20 A). If the date the Seasonal Ecological Drought Forecast is run date falls in March, days in March before the run date are observed values (black) and days in March after the run date are the predicted values (purple) for the remainder of the month. If the purple and orange ribbons are similar, then the selected site is predicted to have a similar soil water potential and/or soil temperature in March as did sites where sagebrush was present post wildfire seeding. Note that predicted values are more accurate for values in the near future than those in the more distant future.
Potential Natural Sagebrush Seedling Survival: Previous research (Schlaepfer et al. 2014a) evaluated how natural sagebrush regeneration, such as germination and survival from seed produced by established big sagebrush plants, is influenced by soil moisture, temperature, snowpack, and other conditions. Natural regeneration is a very different process from seeding establishment during restoration. This section displays the forecasted probability of conditions supporting sagebrush seedling survival for natural regeneration in an unburned, intact sagebrush plant community (Figure 21). The associated box plots depict the mean of conditions supporting sagebrush in the climatic normal period (1981 - 2010; Figure 21 B) and predictions for sagebrush survival in the current and upcoming year (2020 and 2021 in Figure 21 C, D). The boxplots represent the range across potential realizations of the future. Text above the two right-most box plots indicate how the predicted probability of establishment compares to the historical values (Figure 21 A).
Methods & More info: The Climate Prediction Center (CPC) of the National Weather Service (NWS) provides 'long-lead outlooks' for temperature and precipitation for 102 regions for the 48 contiguous U.S. states. These outlooks are the probability of whether a region will be hotter or cooler (temperature) and wetter or drier (precipitation) than their 30-year climatological normal (1980-2010) for multi-month forecasts and are updated each month.
The Short-term Drought Forecast API translates the information from the NWS CPC into predictions that are fine-tuned for specific locations, instead of the broad outlooks provided for 102 regions. In addition, monthly predictions are translated to a finer temporal scale, to be utilized as the climate driver in a daily driven, water-balance model, SOILWAT2 . SOILWAT2 is a site-specific model, that takes inputs about daily weather, vegetation, and soils (multi-layer), and mechanistically predicts daily soil moisture, a metric used for evaluating likely success of plant germination and survival.
In order to integrate regional outlooks to site-specific predictions, historical weather for a site is downloaded from gridMet. gridMET is a dataset of daily high-spatial resolution (~4-km) surface meteorological data covering the contiguous U.S. from 1979-present. Using patterns between historical temperature and precipitation data, alongside NWS forecasts, a distribution of future anomalies is predicted using multivariate sampling. These predicted anomalies corrected and integrated with historical data from the climatic normal period to simulate potential trajectories in upcoming climate and soil moisture.
Detailed information about this downscaling and statistical process is documented here.
The Site Characterization Report will initiate after summary statistics are calculated in Step 3 (Figure 22). User Annotations from Site History and the generating report are included in the report pdf. The selected land treatments from Step 6 are displayed at the bottom of the report. The developing report is displayed in the Report tab and a preview of the static, formatted version can be seen by clicking the 'Preview Report' button in the top left of the tab display (Figure 23).
Pop-up when you click '?' Welcome to your developing report: The summary tables are being generated. If the tables do not fill in with data and continue to say 'Waiting for data' after several minutes, click the 'Add to Report' button in Step 4 again. If a table returns an error, run an individual table again by selecting 'Retry' under the summary table. These actions will reset the calculation(s) and populate the table(s). The map shown here is linked to the Planning Map tab. Adjustments can be made to this Report map by changing the layers in the Planning Map tab. The zoom scale of this map determines the scale on maps included in the report pdf. The Land Treatment Digital Library Matches table is populated in Step 6 when treatments of interest are selected for the project. User Annotations from Site History and the generating report are included in the report pdf.
Clicking the 'Preview Report' button in the top left will format the report into a static display for export. Clicking 'Print Report' will create the printable pdf version (Figure 24). Clicking the 'Hide Report Preview' will return the view to the developing report, which changes as the user adds or removes information from the various steps.
It will take a few minutes to generate the pdf after clicking the 'Print Report' button. A 'Save As' dialog will appear when the report pdf is generated.
Planned Treatment Overview: The first part of the report will display an overview of the planned treatment. This includes the planned project name entered in Step 1, the treatment(s), and an overview map. It also includes a brief description of the Land Treatment Exploration Tool.
Annotations: This section displays any notes added from the Site History tab and developing report tab. Annotation sections are included for treatment history, wildfire history, drought history, and the report summary tables.
Summary Statistics for the Planned Treatment Area: This section displays the information for the layer(s) selected in Step 4: Summarize the proposed treatment area. Each layer is displayed and includes its name, a short description, the summary table, and a thumbnail map of the layer (Figure 25). The PRISM section will also include the climatogram.
Vegetation cover and height: This section displays functional group values for annual herbaceous, bare ground, big sagebrush, herbaceous, sagebrush, and shrub cover (USGS 2016, Boyte and Wylie 2019). It also shows values for sagebrush and shrub height (Figure 26).
Summary Table Annotations: There is a text box in the developing report beneath the summary statistics where the user can add notes they would like to include in the report (Figure 27). This text box is specifically for text regarding the summary statistics of the planned treatment area shown in the developing report.
Wildfire History: This section shows the wildfire frequency map (Figure 28) and the notes added in the Site History tab.
Treatment History: This section displays the LTDL record of treatment frequency summary (Figure 29) and the notes added in the Site History tab.
Treatments selected from the Land Treatment Digital Library: This section displays the selected rows from Step 6. The results are expanded to show the details for each selected treatment (Figure 30).
To contact the development team for the Exploration Tool, you can email: email@example.com .
|The right-side pane drops below the left-side pane.||Try to change the zoom of your browser window and refresh the page. Make sure you save your polygon, first.|
|Some of the layers are not showing up in the Layers/Legend.||Try to refresh your page, but make sure to save your polygon, first.|
|The climatogram does not load on the Site History Tab.||Click the retry button in the climatogram section of the Site History Tab.|
|One or more of the summary tables did not populate after Step 4.||Navigate back to Step 4 and click Add to Report again with the same tables still selected.|
|The maps in the report are too zoomed out.||In the developing report, zoom in on the main map at the top of the Report Tab. This should define the extent of the thumbnail maps in the report.|
|When Print Report is clicked, it seems like nothing happens.||This process takes a few minutes, so be patient while the computer builds the custom report. If the 'Save As' dialog never pops up after letting it sit for several minutes (>15min), try hiding the report preview and entering back into the report preview to print the pdf again.|
|The report pdf seems to have a weird formatting.||Try hiding the report preview and entering back into the report preview to print the pdf again.|
|The report map seems off center.||Try hiding the report preview and entering back into the report preview to print the pdf again. Zooming in and out of the developing report map can also fix this issue.|
|The search query returned 'Match query failed'||A large query or poor internet connection may cause the query to fail. It is advised to try a smaller buffer or boundary.|
Barnard, D.M., and Germino, M.J., 2020, Standardized Precipitation-Evapotranspiration Index for western United States, 2001-2014, derived from gridMET climate estimates: U.S. Geological Survey data release, https://doi.org/10.5066/P9MZKCWZ
Brabec, M.M., Germino, M.J. and Richardson, B.A., 2017. Climate adaption and post-fire restoration of a foundational perennial in cold desert: Insights from intraspecific variation in response to weather. Journal of Applied Ecology, 54(1), pp.293-302. https://doi.org/10.1111/1365-2664.12679
Bray J.R. and Curtis J.T. (1957) An ordination of the upland forest communities of Southern Wisconsin. Ecological Monographies, 27:325-349. https://doi.org/10.2307/1942268
Hardegree, S.P., Abatzoglou, J.T., Brunson, M.W., Germino, M.J., Hegewisch, K.C., Moffet, C.A., Pilliod, D.S., Roundy, B.A., Boehm, A.R. and Meredith, G.R., 2018. Weather-centric rangeland revegetation planning. Rangeland Ecology & Management, 71(1), pp.1-11. https://doi.org/10.1016/j.rama.2017.07.003
McCune, B. and Dylan, K. (2002) Equations for potential annual direct incident radiation and heat load. Journal of Vegetation Science, 13, 603-606. https://doi.org/10.1111/j.1654-1103.2002.tb02087.x
McCune, B. and Grace, J.B. (2002) Analysis of Ecological Communities. Gleneden Beach, OR, USA: MjM Software. 304 p. http://dx.doi.org/10.1016/S0022-0981(03)00091-1
Moffet, C.A., Hardegree, S.P., Abatzoglou, J.T., Hegewisch, K.C., Reuter, R.R., Sheley, R.L., Brunson, M.W., Flerchinger, G.N. and Boehm, A.R., 2019. Weather Tools for Retrospective Assessment of Restoration Outcomes. Rangeland ecology & management, 72(2), pp.225-229. https://doi.org/10.1016/j.rama.2018.10.011
O'Connor, R.C., Germino, M.J., Barnard, D.M., Andrews, C.M., Bradford, J.B., Pilliod, D.S., Arkle, R.S. and Shriver, R.K., 2020. Small-scale water deficits after wildfires create long-lasting ecological impacts. Environmental Research Letters, 15(4), p.044001. https://doi.org/10.1088/1748-9326/ab79e4
Pilliod, D.S., Welty, J.L., and Jeffries, M.I., 2019, USGS Land Treatment Digital Library Data Release: A centralized archive for land treatment tabular and spatial data (ver. 3.0, November 2020 ): U.S. Geological Survey data release, https://doi.org/10.5066/P98OBOLS
Schlaepfer, D. R., W. K. Lauenroth, and J. B. Bradford. 2014a. Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions. Ecological Modelling 286:66-77. https://doi.org/10.1016/j.ecolmodel.2014.04.021
Schlaepfer D. R., Lauenroth W. K., and Bradford J. B. 2014b. Natural regeneration processes in big sagebrush (Artemesia tridentata) Rangeland Ecol. Manage.67344-57. https://doi.org/10.2111/REM-D-13-00079.1
Shriver R K, Andrews C M, Pilliod D S, Arkle R S, Welty J L,Germino M J, Duniway M C, Pyke D A and Bradford J B 2018. Adapting management to a changing world: warm temperatures, dry soil, and interannual variability limit restoration success of dominant woody shrub in temperate drylands. Glob. Change Biol.244972-82. https://doi.org/10.1111/gcb.14374
Welty, J.L., and Jeffries, M.I., 2020, Combined wildfire datasets for the United States and certain territories, 1878-2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9Z2VVRT