In 2006, the Micronesia Challenge began as a commitment by the Republic of Palau, Guam, the Commonwealth of the Northern Mariana Islands, the Federated State of Micronesia, and the Republic of the Marshall Islands to preserve the marine and terrestrial resources crucial to the survival of the Pacific traditions, cultures, and livelihoods. The overall goal of the initial Micronesia Challenge was to effectively conserve at least 30% of the near-shore marine resources and 20% of the terrestrial resources across Micronesia by 2020.

During the 24th Micronesia Island Forum in 2019, the regional leadership recognized the success of the first 15 years of the Micronesia Challenge and endorsed the new Micronesia Challenge 2030 goals to effectively manage 50% of the marine resources and 30% of terrestrial resources by 2030.

In 2016, the USFS Forest Inventory and Analysis (FIA) team, regional partners and CBI developed the Micronesia Challenge Regional Terrestrial Monitoring Initiative tool (mcterrestrialmeasures.org) to allow users to visualize the spatial data from the Micronesia Challenge monitoring effort by regional framework indicator(s) that measure the status of managed conservation areas set aside under the program. The first version of the tool included forest data collected between 2003 and 2018 and determined the status and trends in forest area, forest health, understory vegetation, biomass, and carbon storage.

In this new phase of work, the Terrestrial Measure Initiative tool will be updated with the most recent data and information. The team also plans to develop a webinar presentation to communicate with local stakeholders and others about the tool and the ongoing success of the Micronesia Challenge.

The need to plan strategic, effective forest management is urgent in the southern Sierra Nevada, where forests have been ravaged by drought, fire, and catastrophic tree mortality. Multiple, sometimes conflicting, management objectives must be balanced, and multiple agencies need help coordinating their forest restoration actions. A common, readily accessible system evaluating landscape-scale forest condition is needed.

Conservation Biology Institute is working with the Sierra Nevada Conservancy, Sequoia National Forest, Sequoia National Parks, Sequoia Parks Conservancy, Save the Redwoods League, and others to develop forest resilience models and create a toolkit for exploring these data to support the planning of a range of resource management goals. These goals include the protection of sequoia groves, overall forest health, wildfire protection, and endangered species habitat management.  The project is supported by CBI’s data sharing and mapping platform Data Basin.  The project is funded by the Save the  Redwood League and Sequoia National Park through its partner the Sequoia Parks Conservancy, and CAL FIRE Forest Health Research Grant Program.

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.

Cachuma Resource Conservation District (RCD) is working in partnership with Conservation Biology Institute, LegacyWorks, and Sharyn Main Consulting on the Regional Priority Plan to Reduce Wildfire Risk and Improve Forest Health in Santa Barbara County (RPP), which is a flagship project of the Santa Barbara County Conservation Blueprint. Funded by the California Coastal Conservancy, the RPP helps with the planning, mapping, and prioritization of projects that will proactively address wildfire threat in Santa Barbara County, as well as improve forest and habitat health.

The RPP is a multi-prong collaboration, which focuses on public and private land in the wildland/urban interface (WUI). CBI is the lead for a component of the project, to develop a sophisticated decision-support mapping tool to not only predict areas of high fire-risk on a landscape scale, but also help the community prioritize where fire risk mitigation projects should occur. The tool will serve as a community resource within the Santa Barbara County Conservation Blueprint and should improve communication, network building, and support community priorities through a regional approach to fire resilience and habitat health. The project team is talking with the many agencies and stakeholders involved, and facilitating the collaborative decision-making process.

CBI recently worked with the Pacific Marine & Estuarine Fish Habitat Partnership (PMEP) to update the West Coast Estuaries Explorer, a tool designed to engage a broad range of users with detailed information about estuaries along the U.S. West Coast.  The first version of this tool was developed in partnership with PMEP and the North Pacific Landscape Conservation Cooperative.  The partnership between CBI and PMEP continues with support from NOAA and the Pacific States Marine Fisheries Commission (PSMFC).  The Estuaries Explorer got several performance and design updates to make it easier to use and more visually engaging.  In addition to the latest available information for estuary boundaries and biological habitats, the Explorer now includes aerial images for each of the estuaries in Washington, Oregon, and California.  Later this year, CBI and PMEP will incorporate additional information on the location of eelgrass habitat and areas of tidal wetland loss.  PSMFC has taken over long-term hosting of this exciting tool.

CBI is collaborating with the Rogue River-Siskiyou National Forest and the Klamath National Forest in their effort to conserve the Alaska yellow Cedar in its southern range, located in Southern Oregon and Northern California, where it faces extreme extinction risk due to climate change. Concerted conservation efforts are needed to develop and implement conservation and reforestation strategies, in order to manage forest tree species for sustainability in the future. CBI will help coordinate the collection of seeds from trees from 8 sites, tag and geo-reference each tree, gather information on the general health of these stands, and submit the seeds to the national seedbank in Fort Collins. In addition, current-year needles will be also collected from each seed tree for later genetic/genomics analysis by Richard Cronn and team at the Pacific Northwest Research Station of the USFS.

Alaska Yellow Cedar (Callitropsis nootkatensis) has an extensive range from Alaska to Northern California (Fig. 1). It is declining in the northern part of its range due to a combination of factors associated with climate change and is a rare species in the southern part of its range in California and Southern Oregon. These southern populations are relics that occur in isolated stands in sub-alpine zones in cool wet sites at higher elevation > 5000 ft (Fig 2). The species is currently under review for listing as a threatened or endangered species.

Update 12/18

CBI finished cone collections in September, 2018, from six populations across three sites in Southern Oregon and three sites in Northern California. Access to other sites was restricted due to the Klondike Fire burning in Southern Oregon. This completes the first systematic collection of mature cones from these southern populations.

We have recieved word from the US Forest Service, Bend Seed Extractory, located in Bend Oregon, that they have successfully extracted viable seeds. The next step is to send them to the National Seed Laboratory in Dry Branch, Georgia, USA. Once there, these seeds will be entered into the the national germplasm bank making these the very first entries for these relic southern populations.

Needle tissue that was collected from 10 trees at each site will be genetically analyzed by researchers at the USFS Forest Science lab in Corvallis.This analysis will help determine if these populations are genetically distinct sub-populations from their northern counterparts which will help guide conservation of this species.

The Rogue River-Siskiyou National forest office is planning to use some of these seeds to grow seedlings to test for certain traits such as disease resistance and drought tolerance. The hope is that seeds collected from these southern populations may be used for restoration plantings in the northern regions.

In the north, Alaska Yellow Cedar is a valuable timber species but has been declining as a result of the climate crisis.

Conservation of these southern populations may prove to be critical for the longterm management of northern Alaska Yellow Cedars on public and private lands.

Fig 1. Range map for Alaska yellow cedar.

Source: http://tidcf.nrcan.gc.ca/en/trees/factsheet/376

Figure 2. Current known yellow cedar locations in the Siskyou Mountains (CBI 2017)

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.