Providing Tools for USDA Monitoring and Assessment

CBI is using the latest remote sensing, machine learning, and modeling approaches to assess the quality of grasslands and pollinator habitat. Outputs from this analysis will be delivered to USDA through an online-decision support system, designed and built by CBI, called the USDA Conservation Toolkit. This suite of map-based tools will support the USDA Conservation Reserve Program (CRP) and other land-based conservation and restoration programs operating across the United States. CRP currently covers ~24.8 million acres of working lands nationwide.

Goal: Assess ecosystems services across the CRP portfolio

• Generate products to support USDA policies and program initiatives
• Provide actionable conservation intelligence

Targets

• Quantify foundational supporting ecosystem services across CRP enrollments
  • Grasslands ecosystem quality
  • Pollinator habitat quality
• Incorporate resulting spatial data and metrics into online applications, allowing for program reporting at multiple scales
• A priority for this effort is to quantify the CRP national portfolio return on investment, screening enrolled farms, and assessing at state, regional and national scales

CBI CRP Grassland Quality Model – Overview

Components

• Integrative, comprehensive approach to modeling using the best available spatial data and remotely sensed metrics (e.g. National vegetation surveys, NLCD, Rangeland Analysis Platform (RAP), custom CBI products)
• Leverages outputs from the Google Earth Engine (GEE) cloud-computing platform with CBI’s customized library of 200+ vegetation indices

How is it unique?

• Hierarchical measure of grassland ecosystem vigor, community composition, and resilience
• Expandable framework produces multidimensional metrics to quantify patterns across the landscape
• Summarizes information across CRP farms and practices
• Offers insights on baseline current state and local condition at multiple scales

Pollinator Habitat Quality Model – Overview

What does it offer USDA?

• Multi-dimensional, non-monetary valuation of pollinator habitat
• Foundation for field to landscape-level spatial analytics for CRP assessment and reporting
• Illustrates CRP return on investment at a programmatic scale and quantifies enrolled land performance with nuanced metrics

How is it unique?

• Builds on the benchmark InVest© model framework 
• Informed by 300,000 bee observations from the Global Biodiversity Information Facility (GBIF)
• Innovations for bee flight, nesting, and floral suitability estimates

Abstract:

“Wildfires can be devastating for social and ecological systems, but the recovery period after wildfire presents opportunities to reduce future risk through adaptation. We use a collective case study approach to systematically compare social and ecological recovery following four major fire events in Australia and the United States: the 1998 wildfires in northeastern Florida; the 2003 Cedar fire in southern California; the 2009 Black Saturday bushfires in Victoria, southeastern Australia; and the 2011 Bastrop fires in Texas. Fires spurred similar policy changes, with an emphasis on education, land use planning, suppression/emergency response, and vegetation management. However, there was little information available in peer-reviewed literature about social recovery, ecological recovery was mostly studied short term, and feedbacks between social and ecological outcomes went largely uncon- sidered. Strategic and holistic approaches to wildfire recovery that consider linkages within and between social–ecological systems will be increasingly critical to determine if recovery leads to adaptation or recreates vulnerability.

Southern California’s montane conifer forests are primarily restricted to the “sky islands” of the San Jacinto, San Bernardino, and San Gabriel Mountains. These unique ecosystems protect the upper watersheds of all of the region’s major rivers and provide ecosystem services critical to both human and ecosystem climate resilience. Managers are in a race to restore resilience to these forests, which are threatened with conversion to hardwood and shrub due to severe wildfires and regeneration failure. 

This partnership between the US Forest Service, San Diego State University, and Conservation Biology Institute is applying the latest research on interactions between multiple disturbances specific to this ecoregion to plan effective conservation action. 

The effort expands on research from the Connecting Wildlands and Communities project that developed a landscape-scale framework to map refugia from multiple stressors, and ongoing research projects at CBI developing dynamic wildfire and vegetation succession models for understanding the synergistic impacts of climate change, land use change, and different management scenarios.

The team will work with scientists and managers to build interactive spatial models using CBI’s Environmental Evaluation Modeling System (EEMS) with location-specific data to support the collaborative development of a conservation strategy customized to address the threats faced by southern California’s montane forests.

By disrupting wildfire regimes, climate and land use change transform ecosystems, alter carbon budgets, and drive socio-economic impacts in California. We propose to quantify how projected peri-urban growth in the wildland urban interface, climate change, and local management actions influence wildfire activity and downstream effects on vegetation transitions, carbon release, biodiversity, and vulnerable human communities. 

 We will model wildfire risk as a function of a limited set of stakeholder-guided, realistic future scenarios, using the LANDIS-II simulation model. Past studies have shown the importance of human ignition location and timing on wildfire activity in Southern California, a mechanism we will explore using different land use change scenarios. 

 We will also model and analyze the potential influence of increasing atmospheric aridity on fire size and severity in forests and compare these effects to adjacent shrubland plant communities. 

 Taken together, climate, land use, and other environmental variables can lead to fire-driven vegetation type conversion, which can influence carbon sequestration, biodiversity, and even future fire risk to human communities. 

  Finally, we will explicitly evaluate how different modeled management actions influence wildfire, plant succession, and carbon sequestration. The resulting maps and spatial products will help managers prioritize locations for conservation and management actions. Overlaying maps of vulnerable human communities and biodiversity hotspots with future wildfire change and downstream impacts can better define locations for priority action to facilitate co-benefits to human and natural resources.   This research will contribute to scientific publications and be directly relevant to managers, including the Southern California Montane Forests Project.

The San Diego Zoo Wildlife Alliance (SDZWA) is a world-renowned conservation organization with a 1800-acre zoo, the Safari Park, that houses more than 2600 animal and 3500 plant species. Located in Escondido (northern San Diego County), the Safari Park also includes a 800-acre biodiversity preserve with some of the most well-preserved, California-endemic coastal sage habitat. 

 In 2007, the Witch fire burned through 600 acres of the biodiversity reserve and stopped just outside the Safari Park borders. Since then, the SDZWA has transformed their in-house wildfire preparedness program, including hiring a team of dedicated wildfire suppression staff, fire suppression equipment boxes scattered throughout the park, an infrared and visible spectrum camera array for early ignition detection, and a 8500-gallon water tank for aerial suppression by local first responders. 

 While these investments in wildfire readiness are important for protecting the Safari Park grounds, landscape-scale risk analyses are needed to determine where fires may start and spread outside of park boundaries and which additional management activities could mitigate risk from fires originating beyond Park borders. Conservation Biology Institute (CBI) and Dudek have proposed to co-create the needed wildfire risk analysis for the SDZWA Safari Park.

 At the core of the risk analysis is a fusion and comparison between two commonly employed modeling efforts used in

The USDA Conservation Reserve Program (CRP) works with private landowners to advance conservation on their lands. This voluntary program currently comprises over 23 million acres making it an extremely important component of conservation in America, particularly in locations with limited public conservation lands. Management actions taken on enrolled lands include augmenting native vegetation for pollinators, providing habitat for grassland plants and animals, increasing biodiversity, reducing soil erosion, and improving water quality.

CBI is working with USDA to improve the effectiveness and efficiency of the program as it strives to expand enrollment in the coming years. Working in several pilot states (Mississippi, Kansas, Colorado, Washington, Nebraska, and the Dakotas), CBI is focusing on the following tasks:

• Create an online service open to the public that assists landowners to identify plant mixes most appropriate for their locations and management goals and vendors where seeds/seedlings can be acquired.
• For agency and CRP contract holders, create an online service that helps manage emergency haying/grazing requests.
• Develop and implement technology and protocols (e.g., phone field assessment app) that will involve contract holders more in the implementation of their agreements, which will provide important monitoring for improved program evaluation.
• Improve mapping and monitoring of forests and grasslands as they relate to CRP goals and objectives using the latest remote sensing technology, machine learning, and high-end processing resources.
• Conduct spatial analyses to help the program prioritize areas for more targeted enrollment.
• For agency users, provide an online service that allows for rapid and meaningful assessments of conservation management outcomes on CRP lands.

CBI Takes a Field Trip!

CBI headed to Jamestown, North Dakota, to speak with producers and USDA county staff regarding the USDA Mobile App, a tool designed for self-reporting, assessment, and communication surrounding CRP fields. We tested the app on over 35 fields to incorporate feedback from on-the-ground users, train remote sensing data, and test the effectiveness and ease-of-use of the tool. We coordinated with USGS, as well, testing this app on several of their pollinator plots, in conjunction with another CBI project.

Additionally, CBI traveled to Bismark and spoke with state NRCS staff, in order to hone and edit management questions and expand the usefulness of the app for reporting requirements and data gathering. Our experience was invaluable, as truthful reactions and deliberate responses from those who will eventually be using the tool, are critical in creating something that will be utilized and, ultimately, successful.

CBI will develop and apply a forest management decision-support system (DSS) for forest resilience planning in the southern Sierra Nevada that integrates the latest science on how vegetation, terrain, climate, and weather interact to influence fire risks and forest resilience. The interdisciplinary team led by CBI includes ecological modelers, forest ecologists, fire scientists, physicists, and statisticians. The core of the DSS will be a Forest Resilience Model built using EEMS (Ecosystem Evaluation Modeling System; Sheehan and Gough 2016). The DSS will be tested, refined, and applied to resilience planning in that portion of the modeling region of greatest concern to the interagency Sequoia Regional Partnership, which is working to restore ecologically resilient conditions in and near Sequoia National Forest and Sequoia-Kings Canyon National Park.

The resilience model evaluates forest resilience to fire, drought, and other factors based on landscape conditions. The DSS will allow managers to simulate fuel-reduction treatments, evaluate their effects on a range of risks and resources (e.g., fire, sequoias, fisher habitat), project the impacts into the future, and assess levels of uncertainty.  The DSS and component models will help managers understand how, in concert with terrain and weather, vegetation structure influences fire behavior and forest resilience. Importantly, the DSS will for the first time consider how fire-atmosphere coupling affects fire in models to support forest planning. This will apply how vegetation structure influences fire via both fuel arrangements and air flows, and thus more accurately reflect the full picture of how vegetation treatments may affect fire and fire effects on the landscape.

The DSS will be further refined and applied to resilience planning by the Sequoia Regional Partnership, whose primary focus is reducing fire risks to giant sequoia groves, fishers, and human communities.  

External Team members include: Joe Werne (NorthWest Research Associates NWRA), Christopher Wikle (Department of Statistics, University of Missouri) and David Marvin (SALO Science).   

Map of project study area.

The Forest Treatment Planner was developed to provide forest managers a platform for exploring the potential consequences of different forest management alternatives in both the short and long-term, examine the resource-based trade-offs inherent in any proposed vegetation management action, and clearly substantiate the rationale behind management planning. Originally envisioned as a means to help balance fisher habitat conservation with fuel reduction efforts, the Treatment Planner provides a dynamic link between GIS, the Forest Vegetation Simulator (FVS) modeling software, and any resource model (e.g. habitat, hydrology, fuel, economic) that uses the EEMS (Environmental Evaluation Modeling System) modeling environment. As such, the Treatment Planner is not a model per-se, but a system of communication between existing software that, when used together, can facilitate spatially-explicit comparisons and project refinement. By exporting an FVS output directly into the EEMS modeling environment, this framework allows for a transparent evaluation of the impacts to multiple resource values and a straightforward process for communicating these impacts to stakeholders.

The Treatment Planner supports an iterative process of treatment project simulation, adaptive management, and outcomes analysis, the steps in what we refer to as the “4-Box” decision making framework. The 4-Box model is a conceptual representation of a process designed to help predict future landscape conditions based on simulated management actions and change over time (see Figure).  In this process, the forest manager first examines the current conditions of the landscape through the lens of a particular question or management objective (e.g., where is there a need for protection or restoration?). They can then explore the predicted effects of various simulated management alternatives (e.g., thin from above, or thin from below), to see how they would affect the stand structure (e.g., stand density, basal area, and average DBH) over time, both immediately and into the future. Finally, the manager can examine how those new conditions would then affect a particular phenomenon of interest such as, severe fire risk, or wildlife habitat suitability. This process is then repeated under a different set of treatment options (scenarios) to inform the development of an effective management strategy.

Figure 1. The 4-Box model represents a process for evaluating future conditions based on simulated treatments and change over time.

You can check out the detailed steps to use the treatment planner using the document on the file tab. The relevant code for the treatment planner is available at github, click here to download.

As the Sierra Nevada town of Paradise rebuilds after the devastating Camp Fire of 2018, the community has an opportunity to incorporate strategies to increase its resilience to fire and climate change, enhance the safety and well-being of its residents, and at the same time care for the surrounding natural areas that make it a beautiful place to live.

CBI and the The Nature Conservancy helped Paradise seize this opportunity when the Paradise Recreation and Park District asked us to help them explore community design principles that could provide all of these benefits. The CBI team created geographic models of “Wildfire Risk Reduction Buffers” between the structures and the surrounding wildlands to reduce exposure of homes to wildfire risks. These buffers, which can be made up of parklands, orchards, and other low fire-risk land uses, can be managed to provide many benefits, including buffering homes from ignition, providing safe-haven refuges for residents to escape from fire, strategically-placed staging areas for fire-fighters, recreational access to open space, and protecting natural habitat from the effects of an encroaching urban landscape.

The team combined spatial data about the landscape with local knowledge to prioritize locations for fire risk-reduction and analyzed ignition risks and co-benefits with and without the buffers. The resulting maps illustrate the potential for local partnerships to make a real difference in the town’s future. Through innovative thinking about the role of land use planning, the community of Paradise is changing its approach to living with fire and providing a model for fire-prone communities everywhere.

The Conservation Biology Institute’s recent work with the Deschutes Trails Coalition (DTC) and the Deschutes National Forest focuses on designing a Trails Assessment and Planning Tool for Deschutes County. We have developed a blueprint for the design, in collaboration with the U.S. Forest Service and the DTC. In this new phase of the project, funded by the U.S. Forest Service, CBI will partner with the DTC to build a prototype of the trails decision-support tool and sustainability model for Deschutes County. Then we will scale up and customize this prototype to meet the requirements of the U.S. Forest Service and its partners in the states of Oregon and Washington. The Trail Assessment and Planning Tool design includes creating a preliminary version of a sustainability framework that incorporates an interactive spatially-explicit model, addressing the physical, environmental, social, and economic aspects of sustainability. The model is powered by CBI’s Environmental Evaluation Modelling System (EEMS), allowing for its collaborative development with a diverse group of stakeholders, to create a transparent framework for local, regional, and national organizations to answer important questions relevant to trails planning and management.

Proxy Falls, Oregon

Michael Riffle / Flickr