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A Conceptual Framework to Integrate Biodiversity, Ecosystem Function, and Ecosystem Service Models

Global biodiversity and ecosystem service models typically operate independently. Ecosystem service projections may therefore be overly optimistic because they do not always account for the role of biodiversity in maintaining ecological functions. We review models used in recent global model intercomparison projects and develop a novel model integration framework to more fully account for the role of biodiversity in ecosystem function, a key gap for linking biodiversity changes to ecosystem services. We propose two integration pathways. The first uses empirical data on biodiversity–ecosystem function relationships to bridge biodiversity and ecosystem function models and could currently be implemented globally for systems and taxa with sufficient data. We also propose a trait-based approach involving greater incorporation of biodiversity into ecosystem function models. Pursuing both approaches will provide greater insight into biodiversity and ecosystem services projections. Integrating biodiversity, ecosystem function, and ecosystem service modeling will enhance policy development to meet global sustainability goals.

biodiversity models

Native bee Pollination Ecosystem Services in Agricultural Wetlands and Riparian Protected Lands

Abstract Many freshwater wetlands and riparian systems are protected within agricultural landscapes. Yet, pollinator ecosystem services are seldom considered key ecosystem services provided by these conservation easements. The purpose of this study is to explore the extent of protected aquatic lands to provide pollination ecosystem services by assessing pollinator abundances, crop yield changes, and value estimations of increased soybean yields from a subset of common native solitary bees. We created a novel geodatabase of United States Department of Agriculture (USDA) conservation easements and used this database in the InVEST crop pollination model to model wild solitary bee pollination. We then estimated the monetary value of yield increases provided by pollinators. We found that wetland uplands provided the greatest potential for pollination services for ground nesting bees, followed by herbaceous and forested riparian respectively. Stem nesters preferred forested riparian, then upland habitats. In soybeans fields, we found wild pollinators can provide up to 5.5% yield response from current private aquatic conservation lands. The current landscape is not optimized to use wetlands and riparian conservation lands as pollinator habitat, but these results suggest protected aquatic lands can sustainably increase wild pollination services to agricultural crops if landscapes are managed, protected, and optimized with pollinator services as co-benefit.

Hinson, Audra L. (ORCID:0000000242314820)

Modeling the Ecosystem Services Provided by Trees in Urban Ecosystems: Using Biome-BGC to Improve i-Tree Eco

As the world becomes increasingly urban, the need to quantify the effect of trees in urban environments on energy usage, air pollution, local climate and nutrient run-off has increased. By identifying, quantifying and valuing the ecological activity that provides services in urban areas, stronger policies and improved quality of life for urban residents can be obtained. Here we focus on two radically different models that can be used to characterize urban forests. The i-Tree Eco model (formerly UFORE model) quantifies ecosystem services (e.g., air pollution removal, carbon storage) and values derived from urban trees based on field measurements of trees and local ancillary data sets. Biome-BGC (Biome BioGeoChemistry) is used to simulate the fluxes and storage of carbon, water, and nitrogen in natural environments. This paper compares i-Tree Eco's methods to those of Biome-BGC, which estimates the fluxes and storage of energy, carbon, water and nitrogen for vegetation and soil components of the ecosystem. We describe the two models and their differences in the way they calculate similar properties, with a focus on carbon and nitrogen. Finally, we discuss the implications of further integration of these two communities for land managers such as those in Maryland.

Brown, Molly E.

A multi-objective optimization model for cropland design considering profit, biodiversity, and ecosystem services

More sustainable agricultural methods are needed to alleviate the decreases in biodiversity and ecosystem services that have occurred because of industrial agriculture. One such method is the inclusion of alternative crops into croplands that can support biodiversity, reduce erosion and chemical runoff, and sequester carbon in the soil. However, the question of where such crops should be planted to balance competing economic and environmental objectives remains open. To this end, we develop a mixed-integer quadratically constrained program to optimize the layout of a cropland considering economic, biodiversity, greenhouse gas emissions, and water quality objectives. We include spatially varying fertilization as a decision variable in addition to crop establishment location. We further include the effect of core area and edges between different crops on biodiversity. To demonstrate the applicability of the model, we apply it to an example field, showing how the optimal cropland design changes as a decision-maker prioritizes different objectives and as edges have different impacts on biodiversity.

54 ENVIRONMENTAL SCIENCES

Building Capacity to Use Earth Observations for Ecosystem Services & Biodiversity Applications: A Summary of NASA’s DEVELOP Program and Projects in Central and South America

NASA’s DEVELOP program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. Since 2018, DEVELOP conducted 21 projects in Central and South America, eight of those in collaboration with Sistema de la Integración Centroamericana (SICA) and its member state partner agencies. These projects addressed a diverse set of community needs across multiple themes, including 11 addressing issues related to biodiversity and ecosystem services that utilized a suite of EO to measure and monitor deforestation, habitat suitability, and land change impacts on watershed health in Peru, Costa Rica, Panama, Honduras, and Colombia. This poster introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision making in the area of ecosystem services and biodiversity.

Capacity Building

Assessing Ecosystem Service Provision Under Climate Change to Support Conservation and Development Planning in Myanmar

Inclusion of ecosystem services (ES) information into national-scale development and climate adaptation planning has yet to become common practice, despite demand from decision makers. Identifying where ES originate and to whom the benefits flowunder current and future climate conditionsis especially critical in rapidly developing countries, where the risk of ES loss is high. Here, using Myanmar as a case study, we assess where and how ecosystems provide key benefits to the countrys people and infrastructure. We model the supply of and demand for sediment retention, dry-season baseflows, flood risk reduction and coastal storm protection from multiple beneficiaries. We find that locations currently providing the greatest amount of services are likely to remain important under the range of climate conditions considered, demonstrating their importance in planning for climate resilience. Overlap between priority areas for ES provision and biodiversity conservation is higher than expected by chance overall, but the areas important for multiple ES are underrepresented in currently designated protected areas and Key Biodiversity Areas. Our results are contributing to development planning in Myanmar, and our approach could be extended to other contexts where there is demand for national-scale natural capital information to shape development plans and policies

Climate change

Field–scale evaluation of ecosystem service benefits of bioenergy switchgrass

Purpose-grown perennial herbaceous species are nonfood crops specifically cultivated for bioenergy production and have the potential to secure bioenergy feedstock resources while enhancing ecosystem services. This study assessed soil greenhouse gas emissions (CO 2 and N 2 O), nitrate (NO 3 -N) leaching reduction potential, evapotranspiration (ET), and water-use efficiency (WUE) of bioenergy switchgrass (Panicum virgatum L.) in comparison to corn (Zea mays L.). The study was conducted on field-scale plots in Urbana, IL, during the 2020–2022 growing seasons. Switchgrass was established in 2020 and urea-fertilized at 56 kg N ha –1 year –1 . Corn management followed best management practices for the US Midwest, including no-till and 202 kg N ha –1 year –1 fertilization, applied as urea–ammonium nitrate (32%). Our results showed lower direct N 2 O emissions in switchgrass compared to corn. Although soil CO 2 emissions did not differ significantly during the establishment year, emissions in subsequent years were over 50% higher in switchgrass than in corn, likely due to increased belowground biomass, which was over five times higher in switchgrass. Nitrate-N leaching decreased as the switchgrass stand matured, reaching 80% lower than in corn by the third year. Differences in ET and WUE between corn and switchgrass were not significant; however, results indicate a trend toward reduced WUE in switchgrass under drought, driven by lower aboveground biomass production. Our study demonstrates that switchgrass can be implemented at a commercial scale without negatively impacting the hydrological cycle, while potentially reducing N losses through nitrate-N leaching and soil N 2 O emissions, and enhancing belowground C storage.

09 BIOMASS FUELS

Data for "Field-scale Evaluation of Ecosystem Service Benefits of Bioenergy Switchgrass"

Purpose-grown perennial herbaceous species are nonfood crops specifically cultivated for bioenergy production and have the potential to secure bioenergy feedstock resources while enhancing ecosystem services. This study assessed soil greenhouse gas emissions (CO2 and N2O), nitrate (NO3-N) leaching reduction potential, evapotranspiration (ET), and water-use efficiency (WUE) of bioenergy switchgrass ( Panicum virgatum L.) in comparison to corn ( Zea mays L.). The study was conducted on field-scale plots in Urbana, IL, during the 2020–2022 growing seasons. Switchgrass was established in 2020 and urea-fertilized at 56 kg N ha−1 year−1. Corn management followed best management practices for the US Midwest, including no-till and 202 kg N ha−1 year−1 fertilization, applied as urea–ammonium nitrate (32%). Our results showed lower direct N2O emissions in switchgrass compared to corn. Although soil CO2 emissions did not differ significantly during the establishment year, emissions in subsequent years were over 50% higher in switchgrass than in corn, likely due to increased belowground biomass, which was over five times higher in switchgrass. Nitrate-N leaching decreased as the switchgrass stand matured, reaching 80% lower than in corn by the third year. Differences in ET and WUE between corn and switchgrass were not significant; however, results indicate a trend toward reduced WUE in switchgrass under drought, driven by lower aboveground biomass production. Our study demonstrates that switchgrass can be implemented at a commercial scale without negatively impacting the hydrological cycle, while potentially reducing N losses through nitrate-N leaching and soil N2O emissions, and enhancing belowground C storage.

field data

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today, as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017 in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating the rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Son Do

InVEST Urban Development: Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Urban flooding poses as one of the biggest issues for cities today as its impacts are amplified by both climate change and urbanization. The Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation (UFRM) model, which benefits from its simplicity and robustness, is commonly used in NASA DEVELOP projects for disaster mitigation, urban planning, and environmental justice issues. While the InVEST UFRM model was able to produce the surface water runoff and retention map sufficient for the scopes of past projects, the model’s accuracy and spatial variability need improvement. Since the current InVEST UFRM model employs constant rainfall depth for all pixels in the area of interest (AOI), the model suffers from inaccurately estimating rainfall depth, runoff volume, and flood depth. Therefore, we adapted the model so that satellite-based precipitation raster datasets (i.e., Integrated Multi-satellitE Retrievals for Global Precipitation Measurement [GPM IMERG]) can be used instead of a single constant value. We simulated the flood events on August 21st and August 22nd, 2017, in Wyandotte County, Kansas using both our modified and the original InVEST UFRM model and then compared the results after incorporating rainfall raster into the model. Areas with developed land on the land use map predicted moderate to high flood volume in the original volume regardless of the actual amount of precipitation. The modified model considered the rainfall depth’s spatial variation achieving less overestimation of flood runoff and volume at low-to-moderate rainfall area.

Urban flooding

Milwaukee Urban Development: Assessing the Drivers of Urban Flood Vulnerability in Milwaukee using the Integrated Valuation of Ecosystem Services and Tradeoffs Urban Flood Risk Mitigation Model (InVEST)

Milwaukee County has experienced an increase in flooding due to climate change and urbanization. The frequency and severity of flooding vary spatially due to differences in land cover, surface permeability, and infrastructure. Marginalized communities tend to experience disproportionately high flooding and damage due to infrastructural inequalities and limited access to resources. To quantify these differences, we used the Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model to calculate and create maps of runoff retention, nominal flood depth, and economic damage to buildings in Milwaukee. Our model inputs included land cover, surface permeability, and rainfall. To inform our precipitation inputs, we used NASA’s Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) and National Weather Service (NWS) data. We assessed the relationship between flood risk and social and environmental spatial data including redlining, racial demographics, greenspace, and community resilience. The data demonstrate that flood risk is higher in historically redlined neighborhoods, majority Hispanic and Black census block groups, areas that lack parks and trees, and areas of low community resilience as measured by the Census Bureau’s Community Resilience Estimates (CRE). These findings will support our partners, Groundwork Milwaukee and Groundwork USA, in their efforts to promote the equitable distribution of resources and support environmental health in urban spaces. The end products of this project provide our partners with tools to assess urban flooding vulnerability, guide future intervention projects, quantify the effects of environmental injustice, and improve stakeholder access to data.

Madeleine Tango

Mangrove Carbon Stocks in Pongara National Park, Gabon

Mangroves are recognized for their valued ecosystem services to coastal areas, and the functional linkages between those services and ecosystem carbon stocks have been established. However, spatially explicit inventories are necessary to facilitate management and protection of mangroves, as well as providing a foundation for payment for ecosystem service programs such as REDD+. We conducted an inventory of carbon stocks in mangroves within Pongara National Park (PNP), Gabon using a stratified random sampling design based on forest canopy height derived from TanDEM-X remote sensing data. Ecosystem carbon pools, including aboveground and belowground biomass and necromass, and soil carbon to a depth of 2 m were assessed using measurements and samples from plots distributed among three canopy height classes within the park. There were two mangrove species within the inventory area in PNP, Rhizophora racemosa and R. harrisonii. R. harrisonii was predominant in the sparse, low-stature stands that dominated the west side of the park. In the east side of the park, both species occurred in tall-stature stands, with tree height often exceeding 30 m. Canopy height was an effective means to stratify the inventory area, as biomass was significantly different among the height classes. Despite those differences in aboveground biomass, the soil carbon density was not significantly different among height classes. Soils were the main component of the ecosystem carbon stock, accounting for over 84% of the total. The ecosystem carbon density ranged from 644 to 943 Mg C ha−1 among the three height classes. The ecosystem carbon stock within PNP is estimated to be 40,588 Gg C. The combination of pre-inventory information about stand conditions and their spatial distribution within the assessment area obtained from remote sensing data and a spatial decision support system were fundamental to implementing this relatively large-scale field inventory. This work exemplifies how mangrove carbon stocks can be quantified to augment national C reporting statistics, provide a baseline for projects involving monitoring, reporting and verification (i.e., MRV), and provide data on the forest composition and structure for sustainable management and conservation practices.

Carl C Trettin

Achieving Sustainability Goals for Urban Coasts in the US Northeast: Research Needs and Challenges

In the wake of Hurricane Sandy and other recent extreme events, urban coastal communities in the northeast region of the United States are beginning or stepping up efforts to integrate climate adaptation and resilience into long-term coastal planning. Natural and nature-based shoreline strategies have emerged as essential components of coastal resilience and are frequently cited by practitioners, scientists, and the public for the wide range of ecosystem services they can provide. However, there is limited quantitative information associating particular urban shoreline design strategies with specific levels of ecosystem service provision, and research on this issue is not always aligned with decision context and decision-maker needs. Engagement between the research community, local government officials and sustainability practitioners, and the non-profit and private sectors can help bridge these gaps. A workshop to bring together these groups discussed research gaps and challenges in integrating ecosystem services into urban sustainability planning in the urban northeast corridor. Many themes surfaced repeatedly throughout workshop deliberations, including the challenges associated with ecosystem service valuation, the transferability of research and case studies within and outside the region, and the opportunity for urban coastal areas to be a focal point for education and outreach efforts related to ecosystem services.

urban coasts

Applications of NASA’s LANCE Earth Observations for Ecosystem Assessments

As one of NASA's open and free data systems, NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) provides a wide range of near real-time, low latency and expedited data products from NASA and other earth science satellite missions to support users in their understanding of the value and distribution of ecosystem services. LANCE data can support the System of Environmental Economic Accounting-Ecosystem Accounting (SEEA-EA) framework by both facilitating the creation of ecosystem spatial extent and condition accounts, as well as the quantification and mapping of ecosystem services, much more quickly than routine data processing allows. During the past 13 years, LANCE near real-time satellite data products (e.g., surface reflectance, albedo, vegetation height, thermal anomalies, soil moisture, snow cover etc.) have been used to produce ecosystem-related indicators such as vegetation indexes, biomass, land cover maps, fire, and flood products. These ecosystem-related indicators can be integrated into ecosystem services models, tools, and platforms to monitor land cover and land use changes in ecosystem composition in support of land and natural resource management. When using ecosystem services accounts in decision-making, low latency is essential because having up-to-date information can be critical to support decisions being made. With adequate spatial resolution, long time series length, and low latency data products, LANCE would promote the sustainable use of land and natural resources.

Tian Yao

Bringing Together Users and Developers of Forest Biomass Maps

Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the private sector because much forest acreage in the United States is privately held and needs data for forest management. Additional key outcomes identified by meeting participants include the following: (1) Priority should be given to building into the biomass product ease of use and low costs (including costs of hardware, software, and analysis requirements), (2) CMS products should also be relevant to other biomass measures for forest watershed management, habitat protection for biodiversity, and assessment of markets for ecosystem services, (3) CMS leadership should engage with the Subsidiary Body for Scientific and Technological Advice of the United Nations Framework Convention on Climate Change as they establish measuring, reporting, and verification standards, and (4) CMS leadership should continue to keep sister agencies and other organizations informed as CMS develops, particularly via the agencies active in the U.S. Global Change Research Program Carbon Cycle Interagency Working Group (U.S. Geological Survey, U.S. Department of Agriculture, and National Oceanic and Atmospheric Administration) and nongovernmental organizations.

Forest