Conservation Biology Institute is a partner in a new $1 million grant from a new interdisciplinary NSF program to foster building an “open knowledge network.” The inspiration for this type of network comes from Tim Berners-Lee’s (best known founder of the World-wide Web) vision for the “semantic web,” which applies tags with relationships to information on the Internet, allowing computers to do basic reasoning for improving search results and answering questions. Apple’s Siri, Amazon’s Alexa, and Google’s Assistant all use these technologies.

Dr. John Gallo co-wrote the proposal and leads CBI’s participation in the team of 13 researchers and practitioners from 10 other institutions. The team is focused on improving access and contributions to tools for analyzing geographic data called spatial decision support systems. “The proliferation of online mapping technologies has greatly increased access to and utility of these kinds of tools, and a logical next step is increasing our ability to find the appropriate data and tools for your problem and link these together for more complex analyses,” says Principal Investigator Sean Gordon of Portland State University. Through engaging stakeholders in three applied case studies (the management of wildland fire, water quality, and biodiversity conservation), the interdisciplinary project team will develop and test participatory and automated methods for finding and sharing decision-relevant information using semantic web technologies.

The new NSF Convergence Accelerator program is named for its focus on bringing together interdisciplinary teams to address one of NSF’s 10 big ideas, specifically “Harnessing the Data Revolution“, also known as building an Open Knowledge Network. Eighteen other of these phase 1 grants were made, covering areas from molecular manufacturing to tracking potentially disruptive solar phenomena. The “accelerator” part comes from the short time frame. “The application required a 3-week turn around, which is very quick for a NSF grant,” Gordon said. “Our success was largely due to having formed the Spatial Decision Support Consortium, a professional networking group four years ago, so we had ideas and people ready to go.” Each phase 1 project is eligible to submit a phase 2 proposal for up to $5 million by next March, and the process will include giving a short “pitch” talk to a panel of experts and potential funders, much like a venture capital approach.

*Learn more about this ongoing project here.

The USDA Conservation Reserve Program (CRP) works with farmers and landowners to implement conservation management practices on enrolled lands, with paid contracts ranging from 10 to 15 years in length. The CRP Grasslands practices target restoration of agricultural grassland systems by augmenting native vegetation for pollinators, providing habitat for grassland plants and animals, increasing biodiversity, reducing soil erosion, and improving water quality. The USDA’s CRP has been successful in improving the conservation value of millions of acres of farmlands; however, the program currently lacks spatially explicit information on land cover and vegetation within CRP-enrolled tracts. 

In partnership with the USDA FSA program, the Conservation Biology Institute (CBI) used a combination of remote sensing and machine learning algorithms deployed on the innovative cloud-computing platform, Google Earth Engine, to map grassland characteristics. We used a rich suite of enviro-climatic data, multiple sources of satellite imagery, and Random Forest modeling techniques to predict land cover for study areas in Washington, Colorado, and Kansas, where CRP Grasslands holdings are most prevalent. We used machine learning to create predictive maps of vegetation type by leveraging an extensive set of satellite-derived variables, environmental layers, and federal survey data (from BLM’s AIM and USDA NRCS’s NRI programs). Our initial investigation utilized Landsat 8 satellite data to model vegetation cover across the Washington study area and then scaled up to the Colorado-Kansas study area. The Washington study site was selected for further model enhancements and an in-depth comparison of Landsat 8, Sentinel-2, and MODIS satellite imagery, to evaluate differences in model development and performance among sensor types. We generated vegetation cover predictions for the year 2019 using Random Forest classification models. Classified outputs for the five vegetation cover models – annual grass, perennial grass, annual forb, perennial forb, and bare soil – were post-processed to exclude water and urban land cover and areas that were not relevant for mapping grasslands.

Mapped outputs showing vegetation percent cover predictions from our pilot project have been integrated into CBI’s CRP online decision support tool. This online tool offers functionality for managers and landowners to view, filter, compare and summarize geospatial information relevant for assessing CRP tracts in the study areas. You will need permission from USDA to use the tool, but it is available at https://crptool.org/. Anyone can view the design of the tool at USDA CRPtool.

You can read more details in the following publication.

Degagne, Rebecca; Pizzino, Declan; Friedrich, Hannah; Gough, Mike; Joseph, Gladwin; Strittholt, James; et al. (2022): Mapping Conservation Reserve Program Grasslands in Washington, Colorado, and Kansas with Remote Sensing and Machine Learning. figshare. Journal contribution. https://doi.org/10.6084/m9.figshare.19141853.v1 

Environmental scientists and decision-makers often employ mapping and modeling to address a wide range of complex environmental challenges. Barriers practitioners face include long data processing times, lack of access to robust and up-to-date datasets, and complex programming languages and libraries.

GEODE (the Global Environmental Online Decision Engine) is a web-based mapping and modeling system currently under development at the Conservation Biology Institute. The goal of the GEODE project is to put the power of Google Earth Engine into the hands of environmental scientists, decision makers, and land managers – no programming experience required. 

GEODE is a complete spatial decision support modeling system that can be used to help answer complex management questions and provide critical insight into the challenging environmental problems that threaten biodiversity and the planet’s fragile ecosystems. Users will be able to publish, share, edit, and modify GEODE models so results can be applied to environmental issues anywhere across the globe.

Empowered by GEODE, users benefit from:

By coupling the modeling framework of GEODE with the power of Google Earth Engine, anyone able to use a simple interface will have access the power Google Earth Engine has to offer – and that is a lot!

Conservation Biology Institute is working in partnership with Riverside County Habitat Conservation Agency, Bureau of Land Management, U.S. Fish and Wildlife Service, San Diego Zoo Wildlife Alliance Academy, and others to develop and implement a rangewide conservation plan for the Stephens’ kangaroo rat (Dipodomys stephensi, SKR), a tiny rodent native to Southern California’s shrinking grassland habitats.

The SKR Rangewide Management and Monitoring Plan, developed in collaboration with species managers, researchers, and land owners, complements existing management plans rather than replaces them, recognizing that each location has unique management priorities. Coordinating across local conservation efforts will facilitate collaborative conservation action across the species’ entire range.

The SKR Plan recommends management actions to improve habitat and ameliorate threats from human activities and climate change and provides  a standardized monitoring protocol to track the species’ population status and trends. CBI has developed a customized field data collection application using ArcGIS Field Maps, and our SKR data management team supports the field monitoring effort and ensures long-term integrity of the data in partnership with USFWS’ Ecosphere Program.

This work builds upon a habitat suitability model developed in 2019 by Conservation Biology Institute using Sentinel-2 satellite imagery and being updated in time to support the 2024 monitoring season. These updatable landscape-scale habitat maps are the foundation for statistically-defensible monitoring and play a key role in planning coordinated conservation of the species.

This work is funded by the U.S. Bureau of Land Management. For more information about this effort, please contact Wayne Spencer at wdspencer@consbio.org or Brian Shomo at bshomo@wrcog.us.

Please see the SKR Rangewide Management and Monitoring Website for The SKR Rangewide Management and Monitoring Plan and Protocol, as well as other documents, maps, and data from this project.

Stephens’ kangaroo rat (Dipodomys stephensi, SKR). Photo by Moose Peterson.

Landscape connectivity is critical for species dispersal and population resilience. This project is part of the collaborative Landscape Conservation Design (LCD) for the Pacific Northwest coastal ecoregion and conducted in partnership with the North Pacific Landscape Conservation Cooperative. The goal is to identify connectivity pathways and prioritize corridors for 2-4 focal species West of the Cascades in Oregon and Washington. In Oregon, we will work closely with the members of the Oregon Habitat Connectivity Consortium (OHCC) for both the coastal and Willamette valley ecoregions of the state. The methods tested and refined in this project will feed into future Oregon-wide connectivity mapping.

To learn more and explore related maps and datasets, please visit the Data Basin gallery, “Connectivity of Naturalness in Western Washington“. The gallery includes outputs showing the structural connectivity (i.e. naturalness connectivity) for Western Washington.

These data can be used to help guide connectivity conservation efforts. They are the results from the pilot project comparing Omniscape (coreless) and Linkage Mapper (core areas) modeling methods. Extra attention was made to the data inputs and the rigor of the analyses so that the results can be applied, in addition to answering the driving research question.

Primary forests make up approximately one-third of the world’s remaining forests. Globally, they are grossly under-represented in protected areas and subject to industrial-scale logging and “sustainable forest management” that otherwise fragment intact areas. They face unprecedented threats from logging, mining, energy development, and climate change. British Columbia contains two globally important temperate rainforests with substantial primary and intact forest landscapes distributed from the coast (i.e. Great Bear Rainforest – GBR) inland (i.e., Inland Rainforest). Geos Institute proposes to map and assess conservation importance of the primary forests in these regions as a scientific basis for an international campaign aimed at protecting these globally important rainforests. CBI will support Geos Institute and partners in Canada to help map the area accurately, provide scientific input, and also do a carbon flux model for these primary rainforests.

In this project, CBI is a member of and also providing support to the Fort Bragg Headlands Consortium, with a mission to to help achieve environmentally sound restoration and development solutions that will improve the quality of life and economy for current and future residents of
our Coast.

CBI’s major contribution to the Consortium is to develop and maintain the Fort Bragg Headlands web-mapping Gallery. Powered by Data Basin, this web-mapping Gallery is a feature-rich platform for local citizens, stakeholders and decision-makers to access publicly available spatial data (e.g. maps of streams, wetlands, hazards, soils, geology, etc.). This is timely, as Fort Bragg is currently making a significant Local Coastal Program (LCP) Amendment. Currently zoned Forest Light Industrial, these zoning changes will make the third of the city that was once a lumber mill into prime real estate zoned for profitable development. Fort Bragg is also figuring out how to deal with the remaining wetlands out there that still contain hazardous materials despite a first round of clean-up by the landowner. Providing easy access to data and maps will facilitate decisions that conserve the landscapes and biodiversity of the Fort Bragg region while bringing much needed development and jobs to sustain current and future generations. You can donate directly to this cause here.

Wildfires are a natural part of California ecosystems and play an important role in maintaining ecological structure and function. However, different fire regimes in the state have been altered due to past management practices, climate change, invasive species, and population growth and urban expansion. Given the potential for conflicts between fire management and conserving biodiversity and ecological functioning, solutions are needed to balance ecosystem health with human welfare and community safety.

CBI is partnering with Dr. Jon Keeley (USGS) and an international team of landscape ecologists, biologists, geographers and economists to study the factors that control wildfire activity in southern California, which experiences the largest number of housing losses to wildfire in the U.S. This work focuses on the role of different ignition sources, climate patterns, vegetation change, and housing location and arrangement in altering fire patterns and contributing to housing loss at the wildland-urban interface. Other topics of research include the effectiveness and effects of fuel treatments and prescribed fire in controlling large fire behavior; the role of homeowner practices, such as minimizing vegetation around homes and upgrading building construction materials to prevent house loss; and the relative importance of land planning decisions that could best minimize housing loss while preventing negative impacts to biodiversity.

While the research takes place primarily in southern California, the findings are applicable to other fire-prone non-forested ecosystems such as the Great Basin and the other Mediterranean-climate ecosystems across the world.

The results of this research are shared with management agencies like the National Park Service and U.S. Forest Service, in addition to local and state planners and policy makers, to identify the best strategies to increase community safety while minimizing effects on natural ecosystems.

nflicts between fire management and biodiversity conservation

Destructive wildfires are sudden, extreme events: In a matter of hours, both social and ecological communities are transformed by the loss of homes and lives, and change in natural vegetation. After such an event, residents take stock of their transformed landscape and environment, deciding to remain, rebuild, or move, while ecological communities restructure and regrow. These combined social and ecological responses to wildfire may present a ‘hot moment’ or ‘window of opportunity’ where governments, communities, and residents can take action to reduce the future exposure to disaster.

An interdisciplinary team of researchers, convened by CBI’s Dr. Alexandra Syphard, Dr. Miranda Mockrin from Northern Research Station, USDA Forest Service and Dr. Van Butsic, from the Department of Environmental Science, Policy, & Management at University of California, Berkeley, are examining the question “Do wildfires lead to transformative adaptation, reducing future wildfire risk or do they lead to entrenchment, as residents and institutions re-create hazard-prone environments?”

To examine this question, they will review national data of post-fire housing change (rebuilding, sales, new development, land subdivision) and investigate how social and ecological settings and impacts, as well as event characteristics, influence subsequent housing and ecological trends. They will also determine, at the household scale, how changes in housing patterns relate to the post-wildfire ecological setting and socioeconomic characteristics, determining adaptation or entrenchment.

Wildfire is an important ecological process in California, where a diversity of fire regimes shape the structure and composition of plant and animal communities. Fire regimes are changing beyond their historical range of variability, however, due to several factors, including past fire management, invasive species, land use change, and climate change. These changes not only threaten the integrity and diversity of biological communities, but affect human communities, too, as residential losses to wildfire have skyrocketed in the last several decades. Two of these drivers, land use and climate, are expected to change dramatically in the coming century, raising substantial concern about their effects on fire regimes and subsequent impacts to human communities and biological diversity.

CBI has partnered with University of California, Berkeley to develop and implement a scenario-based integrated modeling framework to quantify the relative importance of climatic and land use factors on current and future projected fire patterns and risk of structure loss for three study areas in California. Select research questions driving this project include:

1)  How do patterns of fire activity vary by land use change and climate?

2)  How does structure loss vary by land use and climate change?

3)  How do these relationships varyby geographic region?

4)  Given these relationships, how are large fires and associated structure risk likely to change in the future?

Results of the assembled model output will be distributed to appropriate stakeholders and Data Basin will host the mapped output data.