Scientific thinking comes with two parts: creative new ideas about how the world works, and tough challenges that find out if the idea warrants confidence. Clearly most of the creative new ideas that scientists developed were wrong, either fundamentally or just around the edges. The ideas that withstood the challenges of testing have transformed the planet, feeding billions more people than our historical planet could have fed, sending machines across the solar system, and giving us an understanding of how our atoms formed in a collapsing star and how those same stellar reactions can be harnessed to obliterate cities. The idea that investigating whether an idea might be wrong has proven to be the most powerful insight humans have ever developed.
Returning to forests, trees and forests continue to be parts of art, religion, and science. When it comes to the scientific understanding of forests, both parts of science are needed: the generation of creative ideas and the challenging of those ideas to see if they warrant confidence. How do creative ideas about forests arise? That complex question has no simple answer, though creative ideas might arouse observation, learning, thinking, and pondering. The second part is more straightforward; once an idea is expressed, the hard work can begin on challenging the idea, to see if it's a better idea for accounting how forests differ across space and time.
A key point in science is being clear on which of these two aspects is being developed. The generation of a creative idea should not be mistaken for a reliable, challenge‐based conclusion. Challenging an existing idea is important, though real gains in insights might depend on new ideas and new methods of measuring and interpreting.
How Confident Should You Be?
The confidence warranted in the truth of art or religion does not depend on the strength of evidence. The confidence warranted in scientific ideas always depends on evidence. Some scientific ideas warrant more confidence than others, and a scale of increasing confidence would be:
Weakest: Ideas based on appealing thoughts or concepts;
Weak: Analogies where well‐tested insights from another area of knowledge are extended to a new area;
Moderately strong: Ideas supported by good evidence from one or a few case studies or experiments; and
Strong: Evidence‐based ideas with robust trends across many locations and periods of time.
This is also a scale representing how surprising it would be to find out an idea was wrong, with the level of surprise increasing down the list. These distinctions may seem a bit dull and uninteresting, but the differences are as important as a person trying to fly on a magic carpet, to fly like a bird, to fly in an experimental airplane, or to fly in airplane certified to be safe with a record of thousands of hours of safe flights. Which approach to flying warrants the highest confidence for arriving safely at a distant destination?
One of the most common sources of creative ideas is making analogies. This tree has fruits that look like acorns, just like oaks have acorns, so this tree belongs with the group of oak species. Another analogy would be that aspen trees regenerate across burned hillsides and so do lodgepole pine trees, so aspen belongs in the group that lodgepole pine belongs in. Analogies may be true or false, but the key is to recognize that analogies represent only an initial, incomplete step of science. An analogy is reliably useful only when challenged by evidence. The acorn example could be challenged in many ways, including comparing other features of the tree with other oak trees, or especially by comparing DNA and genes. The analogy between the aspen and pine is not so obviously useful. If a grouping included trees that do well after severe fires, the trees indeed share useful features. For any other grouping, such as a suitability to feed beavers or mountain pine beetles, they clearly do not.
Creative ideas may begin as concepts or analogies, but gauging confidence depends on taking the next step to list the similarities and differences between the objects or sets of objects. An analogy might have more potential for useful insights when the similarities include major, diverse features. Analogies are less useful (or even harmful) when the list of key differences is substantial (Neustadt and May 1986).
All Forest Ecology Fits Into a Framework and a Method
Whether a creative idea originated in a concept, an analogy or another line of reasoning, science is incomplete if the idea is not challenged by evidence. The challenge needs to include ways that have a chance to show the idea to be wrong. This book raises questions about how forests work, and examines how the ideas have been challenged by evidence.
A good step for thinking about complex systems is developing a framework for understanding pieces of the system, and how the pieces interact. This book uses a core framework that can be used in every forest at all times (Figure A).
FIGURE A The ecology of all forests can be approached with a core framework and a core method, each asking three questions. The questions apply very generally, while the answers always depend on local details.
The core framework is structured by three simple questions. “What's up with this forest?” leads to familiar methods of measurement. “How did the forest get that way?” can be investigated with a variety of approaches for finding and interpreting historical evidence. “What's comes next?” usually can have only fuzzy answers because the future is not yet written for forests.
This set of core framework questions leads to a second trio of method‐related questions that develop the necessary details to answer the core questions.
1 What is the central tendency (or mean) for this set of objects? (The set could be trees in this forest, forests across this landscape, or the forests at this location across millennia.)
2 How much variation occurs around that central tendency? (Do all trees increase in growth rate across all ages, or do some decline?)
3 What factors help explain when cases fall above (or below) the central tendency? (Are suppressed trees likely to decline in growth rate while large trees continue to increase?)
The core framework and core method may seem a bit awkward or unclear, but they should become clearer (and more useful) as the book uses them to investigate how forests work.
A Picture May Be Worth 1000 Words, But a Graph Can Be Worth Even More
A graph is full of answers, and the only work a reader needs to do is to bring the right questions, and know how to interrogate the graph. A good place to start exploring a graph is to apply a few questions:
1 What exactly does the horizontal X axis represent?
2 What exactly does the vertical Y axis represent?
3 When X increases, what happens to Y?
Reading information from graphs becomes easier with practice, and a few points about the graphs in this book might be helpful. Some of the points are obvious, but others will take some thought before insights can be pulled out of graphs.
