Integrating Remote Sensing and Machine Learning with Ecosystem Services Modeling

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

A miraculous recovery of the Yellowstone National Park ecosystem, due to the reintroduction of wolves, has completely reshaped the northern range through a trophic cascade – changes at the top of the food chain having a domino effect down the entire ecosystem. Check out these two articles featuring CBI’s William Ripple!

Wolves Transform Yellowstone’s Landscape: 1,500% Growth in Riverside Plants Shows Nature’s Comeback

“Our findings emphasize the power of predators as ecosystem architects,” said William Ripple from Oregon State University, who led the research. “The restoration of wolves and other large predators has transformed parts of Yellowstone, benefiting not only willows but other woody species such as aspen, alder, and berry-producing shrubs.”

Restoring predators, restoring ecosystems: Yellowstone wolves and other carnivores drive strong trophic cascade

The research, which utilized previously published data from 25 riparian (streamside) sites and collected over a 20 year period, from 2001 to 2020, revealed a remarkable 1,500% increase in willow crown volume along riparian zones in northern Yellowstone National Park, driven by the effects on elk due to a restored large carnivore guild following the reintroduction of wolves in 1995–96, and other factors. The study was led by Dr. William J. Ripple of Oregon State University and the Conservation Biology Institute in Corvallis, OR, and published in Global Ecology and Conservation.

Abstract

Trophic cascades, the indirect effects of predators propagating downward through food webs, play a critical role in shaping ecosystems. We evaluated the strength of a large carnivore-induced trophic cascade in northern Yellowstone National Park, focusing on riparian willows (Salix spp.) as primary producers. Using the log₁₀ response ratio, a standardized indicator of trophic cascade strength, we quantified changes in willow crown volume following the 1995–96 reintroduction of gray wolves (Canis lupus), which completed the large carnivore guild. Reduced herbivory pressure from Rocky Mountain elk (Cervus canadensis) followed their reintroduction, leading to increased growth in willows. Crown volume, a proxy for above-ground biomass, was calculated using a predictive model based on willow height and was used to index primary producer response. Data from a 20-year study (2001–2020) revealed a relatively strong trophic cascade, with a ∼1500 % increase in average willow crown volume and a log₁₀ ratio of 1.21. This ratio surpassed 82 % of those reported in a global meta-analysis of trophic cascades. These results emphasize the importance of long-term monitoring to capture gradual and nonlinear ecosystem responses following predator reintroductions. They also underscore the substantial effect restored large carnivores can have on riparian vegetation and highlight the utility of crown volume as a metric for assessing trophic cascade strength.

Map-based tools that support the Conservation Reserve Program (CRP) of USDA and other land-based conservation and restoration programs in the U.S

USDA contracted the Conservation Biology Institute (CBI) to design and build a free online easy-to-use Plant and Vendor finder to support the producers associated with the Conservation Reserve Program (CRP). However, the tool is not limited to the CRP program and can serve the needs of any land stewardship effort requiring native seeds/seedlings. In partnership with the Institute for Applied Ecology (IAE) we have added features to address the needs of the Native Seed Network and significantly expanded the native seed customer and vendor base.

The seed and vendor finder can be found here: Plant and Vendor Finder

Currently, CBI has seeded the tool with 214 vendors found through an online search from across the country with limited profiles, and 45 have voluntarily completed full profiles which includes their plant catalogue. The tool is designed for easy uploading of their profile and inventory. It also provides an opportunity for vendors without a website to have an online presence and be found by customers looking for seeds. 

The map-based Plant Finder tool allows you to easily find plants suitable for your location that meet particular growing conditions (e.g., ecological sites, soil conditions, moisture requirements, and specific environmental tolerances) as well as provide specific benefits (e.g., livestock browse, wildlife habitat, and pollinator support). Once a species list is generated, the Vendor Match tool identifies where seeds and/or seedlings from your species list can be purchased. The Vendor Browse tool allows you to easily browse a map view of the registered vendors in your state or across the country where seeds and seedlings can be purchased. 

All data content is from authoritative sources, including NRCS state resources, NRCS Ecological Site program, and the USDA PLANTS database. 

The vendor match and browse tools have been updated in partnership with the Institute for Applied Ecology (IAE)for the Native Seed Network. Note that IAE uses its legacy name `Seed Finder tool’ for what is essentially the same as the USDA Plant and Vendor finder tool.

Tutorial Videos

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.

Secondary tropical forests provide critical hydrological services through modulating transpiration and soil infiltration of precipitation. However, vegetation studies establishing direct mechanistic linkages between stand transpiration, soil moisture and streamflow are significantly lacking in tropical montane forests (TMFs) in Himalaya. We quantified the impact of diel and seasonal transpiration on catchment water balance and lean season streamflow in a broad-leaved evergreen secondary TMF in Eastern Himalaya. Stand transpiration (T) and streamflow (Q) were measured concurrently at one of the wettest (4500 mm yr⁻¹) and highest elevation (2100 m) sites worldwide to date. The observed daily transpiration rates (1.29±0.99 mm d ^− 1) were double the reported values from TMFs in relatively drier Central Himalaya but at the lower bound of TMFs globally. Moderate precipitation pulses (10–25 mm volume) followed by clear skies significantly increased stand transpiration. The proportional contribution of evaporative losses (50–77%) and stand transpiration (2–13%) to catchment water balance increased with the progression of the wet season. The phase lags between T, soil moisture (S) and Q were confounded by significant pre-dawn sap flux movement and the presence of secondary diel peaks. Transpiration was a significant predictor of streamflow in the dry season and, to a lesser extent, in the wet season. Thus, changes in vegetation cover and precipitation patterns will likely impact hydrological services from the regenerating secondary TMFs and the regional water security in the Eastern Himalaya.

Abstract

Improving geo-information decision evaluation is an important part of geospatial decision support research, particularly when considering vulnerability, risk, resilience, and sustainability (V-R-R-S) of urban land–water systems (ULWSs). Previous research enumerated a collection of V-R-R-S conceptual component commonalties and differences resulting in a synthesis concept called VRRSability. As a single concept, VRRSability enhances our understanding of the relationships within and among V-R-R-S. This paper reports research that extends and deepens the VRRSability synthesis by elucidating relationships among the V-R-R-S concepts, and organizes them into a VRRSability conceptual framework meant to guide operationalization within decision support systems. The core relationship within the VRRSability framework is ‘functional performance’, which couples land and water concerns within complex ULWS. Using functional performance, we elucidate other significant conceptual relationships, e.g., scale, scenarios and social knowledge, among others. A narrative about the functional performance of green stormwater infrastructure as part of a ULWS offers a practical application of the conceptual framework. VRRSability decision evaluation trade-offs among land and water emerge through the narrative, particularly how land cover influences water flow, which in turn influences water quality. The discussion includes trade-offs along risk–resilience and vulnerability–sustainability dimensions as key aspects of functional performance. Conclusions include knowledge contributions about a VRRSability conceptual framework and the next steps for operationalization within decision support systems using artificial intelligence.

The Giant Sequoia Lands Coalition (GSLC) is a collaboration of public and non-governmental organizations committed to the conservation of giant sequoia grove ecosystems. CBI is supporting the GSLC’s Sequoia Grove Protection and Resiliency Project with tools and assistance that will enable GSLC partners and stakeholders to work collaboratively to protect the species from the impacts of drought, beetles, and wildfire made more intense by climate change.

CBI is using its Data Basin platform (databasin.org) to host the Giant Sequoia Data Portal. The portal will be populated with custom maps of the sequoia groves linked to standard metrics and data for assessing grove condition, fuel treatments, and other range-wide information. To inform this giant sequoia management “dashboard” CBI is working with the GSLC to catalog an extensive collection of assessment, monitoring, and remote sensing datasets created by different agencies and projects over many decades of forest management and research. CBI will train and support the GSLC partners in their use of the Giant Sequoia Data Portal for promoting coordinated scientific research, monitoring, long-term species conservation, and continuing to share new data as it becomes available.

This study addresses two main questions in an East Himalayan broad-leaved wet evergreen TMF: (A) How do the sap flow patterns differ between co-occurring pioneer and late-successional species in a secondary forest? and (B) What are the environmental and ecophysiological drivers of variability in sap flow responses? We hypothesize that the plant water use by the pioneer species would be high but equally likely to be highly sensitive to environmental extremes, whereas late-successional species will have relatively stable water-use patterns. We also predict that, unlike other TMFs, the ecosystem productivity is more likely to be limited by energy availability than water in the wet East Himalayan eco-climate.

Abstract: Spatial conservation prioritization does not necessarily lead to effective conservation plans,
and good plans do not necessarily lead to action. These “science-action” gaps are pernicious and need
to be narrowed, especially if the international goal of conserving 30% of the planet by 2030 is to be
realized. We present the Earthwise Framework, a flexible and customizable spatial decision support
system (SDSS) architecture and social process to address the challenges of these science-action gaps.
Utilizing case study experience from regions within California, South Africa, and British Columbia,
we outline the framework and provide the Little Karoo, South Africa SDSS data, code and results to
illustrate five design strategies of the framework. The first is to employ an “open science” strategy
for collaborative conservation planning and action. Another is that marginal value functions allow
for the continuous accounting of element (e.g., habitat) representation in prioritization algorithms,
allowing for an SDSS that is more automated and saves valuable time for stakeholders and scientists.
Thirdly, we program connectivity modeling integrated within the SDSS, with an algorithm that not
only automatically calculates all the least cost corridors of a region, but prioritizes among them and
removes the ones that do not make ecological sense. Fourth, we highlight innovations in multi-criteria
decision analysis that allow for both cost-efficient plan development, like representative solution
sets, but also land-use planning requirements, like site specific valuation, in what appears to be a
more transparent, understandable, and usable manner than traditional approaches. Finally, strategic
attention to communicating uncertainty is also advocated. The Earthwise Framework is an open
science endeavor that can be implemented via a variety of software tools and languages, has several
frontiers for further research and development, and shows promise in finding a better way to meet
the needs of both humans and biodiversity.