In 2016, the California Energy Commission funded the Conservation Biology Institute to undertake an advanced landscape condition analysis to use as a foundation for evaluation of ecosystems, species’ habitats, and areas planned for renewable energy development. This was subsequently incorporated into programmatic assessments by multiple State agencies, including the California Department of Forestry and Fire Protection’s Fire and Resource Assessment Program (FRAP 2017 Assessment) and the California Department of Fish and Wildlife’s State Wildlife Action Plan (SWAP 2025 Update).

The modeling approach employed by CBI synthesizes complex spatial information into a suite of accessible metrics to quantify terrestrial intactness, an estimate of the naturalness – or lack of human disturbance across the landscape – through a multidimensional lens. The resulting interactive product allows for identification of intact natural areas that maintain ecosystem integrity, thus maximizing support of wildlife and ecosystem services returned to Californians. It also highlights factors affecting the State’s landscape condition, such as infrastructure/urban development, and facilitates understanding the multitude of human impacts co-occurring along that continuum.

In 2024, the California Department of Forestry and Fire Protection (CAL FIRE) funded an update to produce a new version of this terrestrial intactness product, incorporating the most recent data on landscape impacts and providing a more comprehensive view of important considerations with new invasive vegetation and habitat fragmentation metrics. This analysis provides a present-day estimate of the degree to which California’s natural landscapes have been impacted by human disturbance and the drivers at play in any given location. The updated model and accompanying dataset’s comprehensive attribute information can be used for a variety of applications by both agencies and NGOs. These include characterization of intact natural areas that maximize ecosystem services to communities, such as access to nature and improvements in water quality, as well as assessment of ecosystem and species’ habitat condition, considering how various human impacts can be mitigated via strategic planning and targeted restoration efforts.  

Significant improvements in data availability and quality inform the updated version of the landscape intactness product, as well as new metrics described above. The 2016 version was limited by lower quality input data and less sophisticated land cover mapping techniques than are currently available. The 2025 version has been crafted with an eye towards incorporating data derived from more advanced methods, likely to be updated at regular intervals, thus setting the stage for products more directly comparable across time. These upgrades and advancements in the analytical platform provide a basis for future work, such as finer resolution modeling that offers additional detail and functionality to the agencies, NGOs, and decision makers using CBI’s products to support scientifically-rigorous management of California’s resources.

View the map in Data Basin!

Bats provide critical pest control services in agricultural landscapes, yet agriculture poses significant direct and indirect threats to bats, primarily through habitat alteration and driving insect declines. This project investigated how agroecological land use—including the types of crops, the amount of protected land, and habitat restoration through the USDA Conservation Reserve Program (CRP)—affects bat activity and diversity in the Columbia Plateau ecoregion of Eastern Washington, focusing on the state candidate species, Townsend’s big-eared bat (Corynorhinus townsendii), and other bat species of conservation concern.

We deployed acoustic monitors to monitor bats and camera traps to monitor nocturnal flying insects across nine protected sites (BLM and WDFW) in Douglas County from July–October 2024 and March–June 2025, spanning 163 monitoring nights. These sites represented a gradient of surrounding land types—cropland, CRP restoration, and protected natural habitat. Using generalized linear mixed-effects models, we analyzed how bat activity, species richness, diversity, and feeding behavior were influenced by environmental variables including climate, land cover, water features, and nocturnal flying insect abundance.

Key Findings

We recorded all 14 bat species expected in the region, including all Washington State Species of Greatest Conservation Need (SGCN) expected in the region. We detected C. townsendii 19 times across six of nine sites and all three study regions. Temperature emerged as the dominant environmental driver of bat activity, with both short-term nightly temperatures and long-term minimum temperatures strongly predicting bat diversity, activity, and feeding intensity.

Agricultural practices showed contrasting effects on bat communities. Insect-pollinated crops and greater crop diversity within 2–5 km were strongly associated with increased bat diversity and activity, particularly benefiting C. townsendii and other moth specialists, while more wind-pollinated crops at 20 km scales were associated with decreased bat diversity and activity. Bat activity, diversity, and foraging showed consistent negative relationships with CRP land across multiple spatial scales and CRP practices, including permanent grass plantings (CP1, CP2) and wildlife enhancements (CP38E).

Protected areas increased the chances of detecting several species, including C. townsendii. The presence of more springs and seeps had positive effects on total bat diversity and activity, underscoring the importance of water features for bats. Nocturnal insect abundance showed modest but significant effects on bat feeding activity, with fine-scale temporal correlations observed throughout the night.

Management Implications

These findings indicate that diverse bat communities, including vulnerable species like C. townsendii, are an active and important component of the agricultural landscapes of Eastern Washington. The positive associations between bats and diverse insect-pollinated crops suggests that diversified agricultural systems may provide more valuable foraging habitat than simplified agricultural systems composed primarily of cereal grains, and perhaps more even than grassland restoration through the CRP. Indeed, although they warrant further investigation, our results suggest that in order to better support bats, the CRP should strive to encompass habitat types and landscape features, such as water sources, that bats and their insect prey rely on. Furthermore, our results highlight that maintaining and expanding protected areas, particularly those that include water sources, is critical for the conservation of rare and vulnerable species like C. townsendii in agricultural landscapes.

Recommendations

1. Expand protected areas in key habitat areas for C. townsendii and other rare and vulnerable bat species
2. Prioritize conservation efforts for C. townsendii in northern Douglas County, where the species mostly occurs
3. Prioritize protection and restoration of springs, seeps, and other point water sources in agricultural landscape conservation planning
4. Investigate additional factors (e.g., contract age) that may affect the value of CRP land to bats, and reevaluate CRP habitat management practices to incorporate habitat features that better support bats and their insect prey
5. Encourage diverse crop rotations that include insect-pollinated species
6. Implement long-term monitoring programs using validated passive acoustic and camera-based techniques

Because of the importance of the Central Valley of California to shorebirds along the Pacific Flyway, considerable conservation investments have been made in the area’s agricultural fields and managed wetlands. Through their BirdReturns and Bid4Birds programs, The Nature Conservancy and the California Ricelands Waterbird Foundation pay rice farmers to flood fields to decompose post-harvest rice thatch and, in doing so, create habitat for shorebirds. Previous research by CBI and The Nature Conservancy researchers found that shorebird density (birds/hectare) increased with earlier fall flooding and in fields managed to be approximately 50% flooded, 5-10 cm deep, and with minimal straw or stubble cover in fall. Lower soil clay content and flooding consistency – either at a site that is continually flooded over many months or a site that has been flooded in previous years – was also associated with higher shorebird density. Finally, the team found preliminary evidence that fields flooded by groundwater, instead of surface water, were associated with higher shorebird density. These findings are important for guiding continued shorebird management in agricultural landscapes.

Combining the five years of data on shorebird abundance used in the original study with an additional five years of more recent data, we are going to expand our preliminary analysis on the importance of water source on shorebird abundance. Specifically, we are going to explore whether more shorebirds are found in fields flooded with surface water versus groundwater. Assuming that shorebirds prefer groundwater in the expanded analysis, our next priority is to explore why, where our first hypothesis is water quality. Using a number of public resources that sample groundwater quality (nitrates, sodium, and arsenic) and surface water quality (pH, turbidity, temperature, conductance, and dissolved oxygen), we will explore whether shorebird abundance is associated with any of these water metrics. Determining the best practices for habitat creation in agricultural landscapes is critically important for conservation and recovery of declining shorebird populations.

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.