Climate science

Aerial view of a wooden bridge spanning over a clear river, surrounded by dense green forest.

#jhonysjaguar

Our species is racing to solve a dynamic problem so we can have a #SolarPunk future instead of a zombie apocalypse. We’ve made our decision. Which one are you choosing?

grillo climate science

Planetary ecology is more than just carbon. While carbon credits are undeniably useful, we have to extend markets to full ecosystems, and understand Nature’s role and intelligence in balancing elements.

Biodiversity credits from sentinal, rare, endangered, or umbrella species may be a better metric for intact ecosystems.   Biodiversity credits from sentinal, rare, endangered, or umbrella species may be a better metric for intact ecosystems.  

Six co-benefits

(aka. HOW to measure an ecosystem.)

Nature has meta-organisms. Ecosystems live, breathe, and grow just like humans. Our scientific work is ecology, the study of humans and their ecosystems.

Just like you can describe complex shapes in math using three dimensions, we measure ecosystems using the Ecological Benefits Framework. This is using six, orthogonal dimensions: soil, air, water, biodiversity, carbon, and equity. (Yes, three are already Rio Accords and corresponding markets!)

Right now, emerging science and technology is changing fast in each of these dimensions so we ‘stack’ our climate credits (measure in layers) for better data science and accounting integrity.

That means holistic ecological benefits and transparent accounting and evidence-based results.

So let’s talk about the shared language of how these credits are defined and why.

Equity

Soil

Carbon

Water

Biodiversity

Air

We’re scientists

Savimbo was founded by scientists — Western and Indigenous experts with years of training in botanicals, medicine, biology, animal behavior, silviculture, biogeochemistry, academic research, and technology. We are dead serious about making a real, concrete difference today, not hundreds of years from now, when it’s too late. We’re more than proud to prove to the world that we did it. We stop deforestation now — the smart, kind, and equitable way. Our impact extends globally as we reverse-engineer the external forces that seemed insurmountable to us when we were children. We believe that if you are reading this, if you have arrived here, then you also, have the power, and the responsibility, to act with us.

EVIDENCE-BASED ACTION

We’re learning

We don’t have it all figured out — and we wouldn’t trust anyone who said they did. We’re doing the best we can, with what we have and getting better at it every day. We wish we could look to another generation, an authority figure, a government or a school that could help us with the problems we have — but we can’t. We have one planet, one planet-wide globalization and industrialization problem, and we can never return to the ancient ways of life that previously protected it’s balance. The only way out is forward and we are going to go there as fast as we can because there are too many people, and species that rely on our success. We are perfectly positioned to solve the relationship between nature, and civilization, and we will.

ITERATIVE CHANGE

PARADIGM


Climate science has a paradigm problem, and it’s a doozy. In fact, it explains why everyone is so mad about carbon metrics all the time.

LINEAR


The problem is, our best science is done when data is linear, when things correlate neatly.

Data points S-curve away from the diagonal reference line at the extremes — visible signal that the data isn't actually normal.

NON-LINEAR


Self-similarity at every scale. This isn't a metaphor. This is a vegetable.

When it’s not exactly a 1:1 relationship, then our science might seem to fit, but then it turns out our models aren’t very predictive.

A straight line forced onto curved data — the line misses both the low and high ends.
Scatter points spreading above the 1:1 reference line — linear models systematically underestimate the high end.

FRACTAL


The line goes through the middle. But misses both ends. The data isn't linear.

Sigh, it would be so great if curvy data were our only problem in climate. The reality is nature has some pretty complex patterns, called fractal patterns, which are a common property of complex systems.

Nature science
vegetable nature
Nature vegetable

COMPLEXITY


This is real data, from a real system. There IS a pattern. It's just smarter than us.
(Disclaimer: No vegetables were harmed in the making of this science page.)

Complex systems have a lot of other properties; for instance, they are dynamic, and you can’t know everything about them. They are really dependent on what happened before, and resistant to big changes, while easily disrupted by small ones. Sound familiar?

Thousands of inputs feeding back into each other in this Amazon stream. Nothing here can be reduced to one variable.
amazon river Colombia

DAMN!


Climate scientists continue to evaluate highly complex systems and data relativity. There is a pattern, but it’s quite complicated. When you map the data, it looks more like this…

A bifurcation diagram showing the transition from a single stable value through period-doubling into chaos
Zoomed view of the chaotic region, revealing bands of order embedded inside the chaos.

YELLING


So that’s why everyone always gets mad about climate science. We’re still trying to put a line down somewhere. And there is a pattern, it’s just still a lot smarter than we are. But we do have tools for working with complex systems.

Dragonfly colombian amazon

BUTTERFLIES


When data is linear, points fall neatly on a line. Like this.

Well in our case, its mostly dragonflies. But yes. You can disrupt a climate system with a very small input, better known as the butterfly effect. It works if you know how to do it, and we do. So that’s what Savimbo does. Very small changes, very simple metrics, and all for a very good reason.❤️

CLIMATE SCIENCE

Chaos & complexity theory

(If you prefer your deep nerd with citations head here)

  • “Right. I don't believe in the idea that there are a few peculiar people capable of understanding math, and the rest of the world is normal. Math is a human discovery, and it's no more complicated than humans can understand. I had a calculus book once that said, 'What one fool can do, another can.' What we've been able to work out about nature may look abstract and threatening to someone who hasn't studied it, but it was fools who did it, and in the next generation, all the fools will understand it. There's a tendency to pomposity in all this, to make it deep and profound.”

    — Richard Feynman