was that we did not necessarily have to develop monetary metrics.
So estimate system values in monetary metrics like dollars to have impact.
Sometimes that information was required, but often decision makers,
there was unmet demand by development banks and governments in particular, for
measures of ecosystem service value that were in social or biophysical terms.
For example, how ecosystems support food security and
prevent malnutrition or how green space supports improvements in mental health.
And those did not have to be in monetary metrics to have impact.
So that was our second main lesson.
And our third and
final lesson which maybe the most important one was that the legitimacy of
the information we're producing that was really fundamentally important.
The most important factor in determining whether how do you on decision making.
And by just legitimacy, what we defined legitimacy as,
is the information being perceived as unbiased.
And being seen as representing multiple, views of multiple stakeholders.
So what was interesting to me about this finding, was that it indicates
that the process for us doing our science is as important as the results themselves.
I would now like to tell you a story from Belize that illustrates these lessons.
So the oceans and coasts are very important for the Belizean economy and
society, and the tourism sector is important for their economy.
It constituted 36% of GDP in 2013.
They have habitats like sea grass, mangroves and
coral reefs that are preventing erosion over 300 kilometers of coast,
preventing property damage of almost two and a half billion US dollars a year.
And a particular fishery from the spiny lobster is very important.
Brings in $8 million US of revenue every year.
So the oceans ans coast very important for their economy and society.
The Belizean government recognized this and
asked a local authority called the Coastal Zone Management Authority and
Institute to develop a coastal zone management plan.
And the challenge they faced was how to balance multiple objectives.
Grow their fisheries, sector, grow their tourism, protect communities on the coast,
and still conserve habitat for species.
And so how could they do all of this in a balanced way?
So the team co-developed ecosystem service information in order to develop this plan
and it really had an impact, it was used to develop this first plan,
the first one we know of in the world that really systematically plays natural
capital information.
The information showed how nature benefits people in multiple ways and
then they co-developed these scenarios which are basically zoning schemes
around the coast and the ocean to say what activities can be permitted, where,
in a way that is acceptable to balancie across the multiple objectives.
So the breaking news is that the Belizean government recently approved this plan.
And UNESCO dubbed it one of the most forward thinking
ocean management plans in the world.
So it's projected to increase coastal protection from storms by
more than 25% and also double revenue from fisheries.
So at the same time as balancing needs for habitats and species.
So what enabled your system service information to play such a pivotal role in
planning and decision making in the Belize example, well,
I'd like to just illustrate, I think it's a great example that illustrates the three
points I made earlier from our research across 30 places.
First, in Belize, the plan was based on relatively simple ecosystem
service production function models that are in the InVEST software, and
that simple information was sufficient to inform this plan.
Second, although the decision makers did use some information in monetary metrics
like the value of fisheries that were caught in local currency,
and the value of property that was avoiding damage from storms.
They also wanted information in social and biophysical metric, like the area of
the coastline that was protected, the tourist visitation rates, and so on.
So this mix of metrics was needed.
No one asked for one big dollar value.
And in fact, decision makers proved adept at making decisions based
on multiple metrics.
