There are currently many nature-based initiatives (NBIs) operating in the public sector, all with the aim of reconnecting people with nature and improving wellbeing. While they share common aims, they are, by the very nature of these things, currently separate.
While each of these NBIs are more than free to collect their own data to evaluate their program’s success, there are a number of barriers to doing this effectively. NBIs, especially smaller ones, often cannot be expected to have evaluation expertise; nor can they expect to know all the intricacies of the literature the way academics do. This makes survey design extra work. And, if they do manage to put in that work, they face the pesky reality that the sample size they can expect to generate themselves is rather small—you can’t do much with data from 20 people.
But 20 people here, and another 20 there, and one more handful of 30 somewhere else quickly adds up to a meaningful sample. Trouble is, right now, the first 20 are taking one survey, the second 20 another, and the 30 still yet a third! This patchwork data is no use.
But what if we all used the same survey? Then the data CAN be pooled. Then, ~20 becomes 70—and that’s only with three NBIs.
We can then use that data to, first, conduct analyses that require larger sample sizes (e.g., answering sector-wide questions, such as “Does using the pathways to nature connectedness predict greater increases in nature connectedness than using no framework?”—our data using this method hints at yes). We can also use that data, second, to provide benchmarks against which smaller initiatives can evaluate themselves. For example, if our data suggests that nature connectedness increases by 10% across all initiatives, it can be informative to Program A to know that they saw a 20% increase; and even more informative for Program B to know that they only saw a 5% increase. Program A knows, with some imperfection of course (see the paper for such caveats), that they are performing above average, and, therefore, may not need to change. Program B knows that they are underperforming. In fact, this may give them the impetus to hire actual evaluation experts to determine just what might be going wrong.
So what?
So here’s the gist. Funders frequently require funded initiatives to evaluate their programs. This costs money, and requires resources these initiatives may not have—so some of that funding gets eaten up creating scattered and fragmented datasets too small to be useful.
To reduce burden and enhance the literature, we propose, in our paper, that funders create a dashboard—which Natural England already piloted (with my consultation!)—that draws from a standardized survey to provide the benchmark data we describe and to allow academics to conduct sector-wide analyses.
We provide such a survey in our paper. And we provide the guidance needed for such a dashboard to be implemented. The question is whether funders will heed our recommendation!
Read the paper:
Lengieza, M. L., Richardson, E., & Richardson, M. (2026). Amplifying social benefits from multiple nature-based initiatives by crowdsourcing nature connectedness and wellbeing data: A proof of concept. Ambio. https://doi.org/10.1007/s13280-026-02472-1
