Rapid Benefit Indicator Tools

Abstract

Given the many interconnections between socioeconomic and ecological systems, for Ecosystem-Based Management (EBM) to be effective, decision makers must consider metrics for both. Supply side tools and assessments characterize ecosystem condition, functioning, and potential to provide ecosystem goods and services (EGS). Demand side tools, including economic valuation, assess people's preferences for EGS and sometimes estimate the monetary amount people are willing to pay for a good or service. However, economic valuation is often omitted from assessments, due to lack of data or expertise; and economic valuation alone may not sufficiently capture all important aspects of some decisions. Benefit-relevant indicators have evolved as a way to measure the connection between goods or services that may be provided by an ecosystem, and people who may benefit from those services, while stopping short of valuation (Olander et al., Ecol Indic 85:1262-1272, 2018). Like economic valuation, benefit-relevant indicators can help assess trade-offs and compare alternative outcomes (National Ecosystem Services Partnership, Federal resource management and ecosystem services guidebook. National Ecosystem Services Partnership, Duke University, Durham, 2016). The Rapid Benefit Indicators (RBI) approach is an easy-to-use process for choosing a structured set of non-monetary benefit-relevant indicators for assessment (Mazzotta et al., Integr Environ Assess Manag 15:148-159, 2019). The RBI approach indicators are intended to be applied in conjunction with existing ecosystem service assessment approaches and tools, to connect changes in the availability of EGS to the locations where, and how, people benefit from those goods and services. Though developed for use with urban freshwater wetland restoration, the general RBI approach and indicator framework may be adapted and applied to other

A Geospatial Assessment of Flood Vulnerability Reduction by Freshwater Wetlands–A Benefit Indicators Approach

“…The Rapid Benefit Indicators (RBI) approach is a beneficiary-centric, non-monetary way to quickly compare restoration sites using indicators that address several questions related to the aspects of benefits that make them valuable. Spatial tools developed to apply the RBI approach answer these questions by assessing indicators for the area surrounding potential restoration sites from spatial datasets ( Bousquin et al, 2017 ). Most of the spatial input datasets have suggested national defaults for use where locally relevant data are not available.…”

The EPA Ecosystem Services Tool Selection Portal

“…The Rapid Benefit Indicator (RBI) approach ( https://www.epa.gov/water-research/rapid-benefit-indicators-rbi-approach , accessed on 21 January 2024) allows users to estimate and quantify environmental benefits of an ecological restoration decision [ 39 – 41 ]. It includes a fillable checklist and a spatial analysis toolset to help users develop and summarize indicators.…”

Synthesis of Two Decades of US EPA’s Ecosystem Services Research to Inform Environmental, Community and Sustainability Decision Making

“…Early US EPA research focused on measuring the effectiveness of environmental programs in terms of ES through a Relative Valuation of Multiple Ecosystem Services Index, which assigns a value to ES (both intermediate and final) and expresses the output in either relative units or in dollar value [57]. More recent US EPA research has focused on ES and decision support tools, such as the Rapid Benefit Indicators (RBI) approach, a systematic approach to compile non-monetary benefits indicators [58,59]. These decision support tools are described below in Section 3.6.…”

“…The term "linking indicators" refers to those biophysical indicators that inform interpretation of ecological conditions and change from a societal perspective in that they measure biophysical things directly affecting people's welfare [109]. Indicator-based methods can be used where direct economic valuation is either too complex to undertake, or otherwise inadequate to provide a complete picture [59]. In an application on recreation-focused benefits of ES, Angradi et al [116] examined how to develop metrics of benefits of good water quality for lakes, comparing subjective visual assessments quality (i.e., those that inform an individual's perspective on the value of a lake for recreational purposes) to environmental monitoring data of water clarity, including Secchi Disk depth, turbidity, and water-column chlorophyll-a concentration data.…”