Conservation organizations that want to show the economic benefits from their programs should follow these tips to ensure credible, accurate findings that are more locally relevant. 

By Elizabeth Schuster, Environmental Economist

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Your conservation organization wants to show that your nature preserves, forests and wetlands have economic value. Yet too often, we see the same pattern: your team completes the analysis, and yet your stakeholders have no interest in your findings.

As a leader from a public conservation agency shared with me, “We recently put a dollar value on the carbon benefits from our preserves, and I don’t think anyone took the data to heart. What can we do differently next time we’re measuring the economic benefits from our efforts?”

Here’s a simple thought exercise to illustrate one reason why your stakeholders may not care about your findings.

Imagine you are buying a home in your small city in Ohio. You want to buy a 3-bedroom home with 2 bathrooms and an acre of land. Yet your real estate agent brings you a comp from San Francisco and you say, “But this house in San Francisco has nothing to do with the value of a house in a small city in Ohio!”

This is an example of what can make the findings feel less credible to your target audience. The other challenge is accuracy: the value of a house in San Francisco is also unlikely to be an accurate representation of the value of a house in a neighborhood in Ohio.

This may sound unrealistic but actually, it’s common in this field…this is a real method that is called “benefit transfer” (described more in the following section). When done poorly, it means that you are taking the value from another location and applying it to a study site with completely different characteristics. 

Rushed benefit transfer is the most common reason why many ecosystem service valuation studies are not embraced by your audience. Yet small changes can be made in your methods, resulting in more accurate, credible findings. 

One argument for putting a dollar value on nature is that it allows ecosystems to be compared directly to programs in other sectors by using a standard unit of measurement.

To do this well, it means that compared to a baseline state, your organization can show that the economic outcomes are higher than the baseline because of your organization.

Many organizations do not have access to good baseline data so, instead, they use an environmental economics method called benefit transfer. 

Benefit transfer means taking quantitative data from one study site where research was conducted on the wellbeing outcomes and transferring that value to a different study site. 

To show a concrete example, a 2022 study from Connecticut analyzed data on the combined pediatric asthma emergency department visits and hospitalizations (from 2010 to 2014) and tree canopy coverage. Their analysis showed that a 4% decrease in asthma ED visit/hospitalization rates was associated with a 10% increase in tree canopy.

If your organization borrows that statistic and applies it to tree cover in the neighborhoods where you work, that’s an example of benefit transfer.

A seminal 2018 paper from Johnston, Rolfe and Zawojska documented issues and opportunities with benefit transfer. They share years of research that has validated when benefit transfer works well, with relatively high accuracy. This is great news because it means it can serve as a more affordable method for many public agencies and nonprofits.

However, while benefit transfer is a valid research method, it’s often applied inconsistently, or even misused. This leads to findings that are less likely to be trusted by the public.

Weak benefit transfers use no local data, and they are not vetted to the local conditions. Another challenge is that conditions change over time. Let’s imagine that in 2021, you used benefit transfer to show the value of the wetlands that your nonprofit manages. Then, in 2026, you apply that same value to your wetlands. Even if you adjust for inflation, you will get close to the same value that you found five years earlier. Benefit transfer won’t show the increase in economic value due if you’ve improved the habitat quality through ecological restoration or stewardship. 

This section includes real-life examples that you can apply  to your own conservation programs. We merge recommendations from the Johnston et al. paper with tips from our own case studies, to help your team have more locally relevant findings.

One: Before you begin your assessment of economic outcomes, ask: What is the baseline you are comparing to? 

Are you assessing the economic outcomes resulting from your organization’s investments in ecosystem health? 

Are you assessing the economic benefits of land preserved for habitat that otherwise would have been lost to development?

Are you comparing what economic values would be lost if all of your organization’s programming were to cease to exist?

Two: Choose economic benefits that align with the local context and audience. 

Let’s go back to the 2022 asthma study as an example. If your community does not believe they have an asthma or an air quality problem, a study like that may not resonate. When a benefit transfer doesn’t align with community perceptions in a way that is intuitive, “This can lead to transfers that lack plausibility.” (Johnston et al., p. 192).

The implication is two-fold. Choose to evaluate economic benefits that are of interest to your local community and, when using benefit transfer, use studies that are similar to the local socioeconomic and political context.

Three: When using benefit transfer, select studies with similar sites.

This can mean the habitat types, ecological quality of the site, hydrology of the site, etc. One low-cost method to ensure site similarity is to conduct expert interviews. As an example, if your team is assessing avoided stormwater-management costs from forested lands, interview your local stormwater utility to understand the local hydrologic and water-supply connections.

Spatial data on habitat type, soil type, topography, etc. can also be a tool for confirming site similarity (and site suitability) for this type of analysis. 

Four: Make a credible case that attribution is possible. 

This tip gets at the crux of the issue: If your organization’s intention is to measure the impact from your efforts, then your team must make the case that the benefit being measured is linked in some way to your programs, land preserved for habitat, or ecological restoration. We are sympathetic to the fact that with modest nonprofit budgets for evaluation, it is nearly impossible to show causality to the degree that a researcher would in a peer-reviewed, published journal article. 

But there are ways you can build the case through interviews and/or focus groups, published data from partner organizations, surveys, and other data sources to validate that outcomes you are assessing could be possible locally. 

One could envision a scenario where a nonprofit claims that their pollinator habitat is increasing the yields for nearby farm fields, yet interviews reveal that nearby agricultural production is exclusively corn – a crop that does not benefit from native pollinators.

Five: Collect local data to supplement and further customize the benefit transfer (this is formally referred to as benefit function transfer).

To ensure that benefit transfer is locally relevant, use existing survey, polling, visitor, or member data to customize the benefit transfer. However, in our experience, it is challenging to find existing data in the correct format and the organization typically needs to collect additional supplemental data through a survey. 

Technically, benefit function transfer means inserting local data into a statistical analysis that was completed by another researcher on the same topic. However, there is another simple and effective way to update the calculation. 

Here’s an example. A robust study from 2025 showed that 150 minutes of moderate intensity equivalent aerobic activity per week led to $2,025 healthcare cost savings per year compared to those who were inactive. Because the sample size was large (76,016), representative, and of national scale, this study would be a good candidate for benefit transfer.

Customizing the calculation for local conditions would, at a minimum, mean obtaining data on the percentage of residents who are active, insufficiently active, and inactive (the three categories assessed in the original study). Then – if your team wants to link exercise to your nature preserves – you do need to collect data showing that at least some of that activity takes place in your nature preserves.

Measuring the economic value of nature is not about getting to the biggest dollar value possible. In fact, when nonprofits and public agencies focus on getting to the big number, you risk losing relevance for local audiences. Benefit transfer remains a practical bridge for organizations operating on modest budgets, and it is a useful tool allowing leaders to apply rigorous research from other regions. The findings from research using benefit transfer help your team make evidence-based decisions and have the potential to influence the decisions of your supporters and constituents. 

The most effective economic impact assessments that link your work to tangible economic benefits are founded on a powerful story, grounded in the local context. Choose outcomes that make sense locally, and follow the tips in this article to build the case for your impact using data. 

Your ability to point to real local data and conversations to back up your study will go a long way in building local trust.