Learning Objectives

By the end of this section, you will be able to do the following:

• Identify the characteristics of the nature of science.
• Explain how facts, hypotheses, and theories are related and be able to apply the terms.
• Explain the difference between how the term “theory” is used in science and in everyday life.
• Describe why a hypothesis cannot be proven true and be able to apply that principle when concluding data.
• Evaluate whether a hypothesis is testable.
• Build models to describe biological phenomena.

Introduction: What is Science?

The word “science” probably brings to mind many different pictures: a fat textbook, white lab coats, and microscopes, an astronomer peering through a telescope, a naturalist in the rainforest, Einstein’s equations scribbled on a chalkboard, the launch of a space shuttle, bubbling beakers… All those images reflect some aspect of science, but none provide a full picture. Science is complex and multi-faceted, but the most important characteristics are straightforward:

• Science focuses exclusively on the natural world and does not deal with supernatural explanations.
• Science is both a body of knowledge and a process. In school, science may sometimes seem like a collection of isolated and static facts listed in a textbook, but that’s only a small part of the story. Just as importantly, science is also a process of discovery that allows us to link isolated facts into coherent and comprehensive understandings of the natural world. Science is a way of learning about what is in the natural world, how the natural world works, and how the natural world got to be the way it is. It is not simply a collection of facts; rather, it is a path to understanding.
• Scientists work in many different ways, but all science relies on testing ideas by figuring out what expectations are generated by an idea and making observations to find out whether those expectations hold true.
• Accepted scientific ideas are reliable because they have been subjected to rigorous testing, but as new evidence is acquired and new perspectives emerge, these ideas can be revised.
• Science is a community endeavor. It relies on a system of checks and balances, which helps ensure that science moves in the direction of greater accuracy and understanding. This system is facilitated by diversity within the scientific community, which offers a broad range of perspectives on scientific ideas.
• Science is ongoing. Science is continually refining and expanding our knowledge of the universe, and as it does, it leads to new questions for future investigation. Science will never be “finished.”

To many, science may seem like an arcane, ivory-towered institution, but that impression is based on a misunderstanding of science. In fact:

• Science is useful. The knowledge generated by science is powerful and reliable. It can be used to develop new technologies, treat diseases, and deal with many other sorts of problems. Science affects your life every day in all sorts of different ways. You can apply an understanding of how science works to your everyday life.
• Science is exciting. Science is a way of discovering what’s in the universe and how those things work today, how they worked in the past, and how they are likely to work in the future. Scientists are motivated by the thrill of seeing or figuring out something no one has done before. Science can be fun and accessible to everyone.
• Science is a global human endeavor. People all over the world participate in the process of science. Anyone can become a scientist, whether of the amateur or professional variety.

Science Has Limits

Science is powerful. It has generated the knowledge that allows us to call a friend halfway around the world with a cell phone, vaccinate a baby against polio, build a skyscraper, and drive a car. Science helps us answer important questions like which areas might be hit by a tsunami after an earthquake, how the hole in the ozone layer forms, how we can protect our crops from pests, and who were our evolutionary ancestors.

With such breadth, the reach of science might seem endless, but it is not. Science has definite limits.

Science doesn’t make moral judgments. When is euthanasia the right thing to do? What universal rights should humans have? Should other animals have rights? Questions like these are important, but scientific research will not answer them. Science can help us learn about terminal illnesses and the history of human and animal rights — and that knowledge can inform our opinions and decisions. But ultimately, individual people must make moral judgments. Science helps us describe how the world is, but it cannot make any judgments about whether the state of affairs is right, wrong, good, or bad.

Science doesn’t tell you how to use scientific knowledge. Although scientists often care deeply about how their discoveries are used, science itself doesn’t indicate what should be done with scientific knowledge. Science, for example, can tell you how to recombine DNA in new ways, but it doesn’t specify whether you should use that knowledge to correct a genetic disease, develop a bruise-resistant apple, or construct an unknown bacterium. For almost any important scientific advance, one can imagine both positive and negative ways that knowledge could be used. Again, science helps us describe how the world is, and then we have to decide how to use that knowledge.

Science doesn’t draw conclusions about supernatural explanations. Do gods exist? Do supernatural entities intervene in human affairs? These questions may be important, but science won’t help you answer them. Questions that deal with supernatural explanations are, by definition, beyond the realm of nature — and hence, also beyond the realm of what can be studied by science. For many, such questions are matters of personal faith and spirituality.

How Does Science Work?

The scientific method is traditionally presented in the first chapter of science textbooks as a simple recipe for performing scientific investigations (Figure 1.1). Though many useful points are embodied in this method, it can easily be misinterpreted as linear and “cookbook”: pull a problem off the shelf, throw in an observation, mix in a few questions, sprinkle on a hypothesis, put the whole mixture into a 350° experiment, and voila, 50 minutes later you’ll be pulling a conclusion out of the oven! That might work if science were like baking a cake, but science is complex and cannot be reduced to a single, prepackaged recipe.

 

The linear, stepwise representation of the process of science is simplified, but it does get at least one thing right. It captures the core logic of science: testing ideas with evidence. However, this version of the scientific method is so simplified and rigid that it fails to accurately portray how real science works. It more accurately describes how science is summarized after the fact — in textbooks and journal articles — than how science is actually done.

The simplified, linear scientific method implies that:

• Scientific studies follow an unvarying, linear recipe.
  • But in reality, in their work, scientists engage in many different activities in many different sequences. Scientific investigations often involve repeating the same steps many times to account for new information and ideas.
• Science is done by individual scientists working through these steps in isolation.
  • But in reality, science depends on interactions within the scientific community. Different parts of the process of science may be carried out by different people at different times.
• Science has little room for creativity.
  • But in reality, the process of science is exciting, dynamic, and unpredictable. Science relies on creative people thinking outside the box!
• Science concludes.
  • But in reality, scientific conclusions are always revisable if warranted by the evidence. Scientific investigations are often ongoing, raising new questions even as old ones are answered.

The Real Process of Science

The process of science is iterative.

Science circles back on itself so that useful ideas are built upon and used to learn even more about the natural world. This often means that successive investigations of a topic lead back to the same question at deeper and deeper levels. Let’s begin with the basic question of how biological inheritance works. In the mid-1800s, Gregor Mendel showed that inheritance is particulate — that information is passed along in discrete packets that cannot be diluted. In the early 1900s, Walter Sutton and Theodor Boveri (among others) helped show that those particles of inheritance, today known as genes, were located on chromosomes. Experiments by Frederick Griffith, Oswald Avery, and many others soon elaborated on this understanding by showing that the DNA in chromosomes carried genetic information. And then, in 1953, James Watson and Francis Crick, again aided by the work of many others, provided an even more detailed understanding of inheritance by outlining the molecular structure of DNA. Rosalind Franklin’s work on DNA structure took place primarily between the years 1951 and 1953. During this time, she obtained and analyzed the X-ray diffraction image known as “Photo 51,” which provided critical data for understanding the structure of DNA. Still later, in the 1960s, Marshall Nirenberg, Heinrich Matthaei, and others built upon this work to unravel the molecular code that allows DNA to encode proteins. And it doesn’t stop there. Biologists have continued to deepen and extend our understanding of genes, how they are controlled, how patterns of control themselves are inherited, and how they produce the physical traits that pass from generation to generation.

The process of science is not predetermined

Any point in the process leads to many possible next steps, and where that next step leads could be a surprise. For example, instead of leading to a conclusion about tectonic movement, testing an idea about plate tectonics could lead to observing an unexpected rock layer. And that rock layer could trigger an interest in marine extinctions, which could spark a question about the dinosaur extinction — which might take the investigator off in an entirely new direction.

At first, this process might seem overwhelming. Even within the scope of a single investigation, science may involve many different people engaged in all sorts of different activities in different orders and at different points in time; it is simply much more dynamic, flexible, unpredictable, and rich than many textbooks represent it to be. But don’t panic! The scientific process may be complex, but the details are less important than the big picture.

There are many routes into the process.

From serendipity (e.g., being hit on the head by the proverbial apple) to concern over a practical problem (e.g., finding a new treatment for diabetes) to technological development (e.g., the launch of a more advanced telescope), scientists often begin an investigation by plain old poking around: tinkering, brainstorming, trying to make some new observations, chatting with colleagues about an idea, or doing some reading.

Scientific testing is at the heart of the process.

In science, all ideas are tested with evidence from the natural world, which may take many forms — from Antarctic ice cores to particle accelerator experiments to detailed descriptions of sedimentary rock layers. You can’t move through the process of science without examining how that evidence reflects on your ideas about how the world works — even if that means giving up a favorite hypothesis.

Testing hypotheses and theories is at the core of the process of science. Any aspect of the natural world could be explained in many different ways. It is the job of science to collect all those plausible explanations and to use scientific testing to filter through them, retaining ideas that are supported by the evidence and discarding the others. You can think of scientific testing as occurring in two logical steps: (1) If the idea is correct, what would we expect to see, and (2) does that expectation match what we actually observe? Ideas are supported when actual observations (i.e., results) match expected observations and are contradicted when they do not match.

Analysis Within the Scientific Community

The stereotype of a scientist (a recluse who speaks in a jumble of technical jargon) doesn’t exactly paint a picture of someone whose work depends on communication and community, but in fact, interactions within the scientific community are essential components of the process of science. Scientists don’t work in isolation. Though they sometimes work alone (fussing over an experiment in the lab, trekking through the Amazon, scribbling on a notepad at a desk), scientists are just as likely to be found emailing colleagues, arguing with other scientists over coffee, sitting in on a lab meeting, or preparing conference presentations and journal articles. In science, even those few working entirely on their own must ultimately share their work for it to become part of the lasting body of scientific knowledge.

Interactions within the scientific community and the scrutiny they entail take time and can slow the process of science. However, these interactions are crucial because they help ensure that science provides us with more and more accurate and useful descriptions of how the world works.

Benefits of Science

The process of science is a way of building knowledge about the universe by constructing new ideas that illuminate the world around us. Those ideas are inherently tentative, but as they cycle through the process of science again and again and are tested and retested in different ways, we become increasingly confident in them. Furthermore, through this same iterative process, ideas are modified, expanded, and combined into more powerful explanations. For example, a few observations about inheritance patterns in garden peas can, over many years and through the work of many different scientists, be built into the broad understanding of genetics offered by science today. So although the process of science is iterative, ideas do not churn through it repetitively. Instead, the cycle actively serves to construct and integrate scientific knowledge. And that knowledge is useful for all sorts of things: from designing bridges to slowing climate change to prompting frequent handwashing during flu season. Scientific knowledge allows us to develop new technologies, solve practical problems, and make informed decisions — both individually and collectively.

Because its products are so useful, the process of science is intertwined with those applications:

• New scientific knowledge may lead to new applications. For example, the discovery of the structure of DNA was a fundamental breakthrough in biology. It formed the underpinnings of research that would ultimately lead to a wide variety of practical applications, including DNA fingerprinting, genetically engineered crops, and tests for genetic diseases.
• New technological advances may lead to new scientific discoveries. For example, developing DNA copying and sequencing technologies has led to important breakthroughs in many areas of biology, especially in the reconstruction of evolutionary relationships among organisms.
• Potential applications may motivate scientific investigations. For example, the possibility of engineering microorganisms to cheaply produce drugs for diseases like malaria motivates many researchers in the field to continue their studies of microbe genetics.

Science at Multiple Levels

The process of science works at multiple levels, from the small scale (e.g., a comparison of the genes of three closely related North American butterfly species) to the large scale (e.g., a half-century-long series of investigations into the idea that geographic isolation of a population can trigger speciation). The process of science works in much the same way, whether embodied by an individual scientist tackling a specific problem, question, or hypothesis over the course of a few months or years or by a community of scientists coming to agree on broad ideas over the course of decades and hundreds of individual experiments and studies.

Similarly, scientific explanations come at different levels:

Hypotheses

Hypotheses are proposed explanations for a fairly narrow set of phenomena (Fig 1.4). These reasoned explanations are not guesses of the wild or educated variety. When scientists formulate new hypotheses, they are usually based on prior experience, scientific background knowledge, preliminary observations, and logic. For example, scientists observed that alpine butterflies exhibit characteristics intermediate between two species that live at lower elevations. Based on these observations and their understanding of speciation, the scientists hypothesized that this species of alpine butterfly evolved as the result of hybridization between two other species living at lower elevations (Fig 1.4).

Theories

Theories, on the other hand, are broad explanations for a wide range of phenomena. They are concise (i.e., generally don’t have a long list of exceptions and special rules), coherent, systematic, predictive, and broadly applicable. In fact, theories often integrate and generalize many hypotheses. For example, the theory of natural selection broadly applies to all populations with some form of inheritance, variation, or differential reproductive success, whether that population is composed of alpine butterflies, fruit flies on a tropical island, a new form of life discovered on Mars, or even bits in a computer’s memory. This theory helps us understand a wide range of observations (from the rise of antibiotic-resistant bacteria to the physical match between pollinators and their preferred flowers), makes predictions in new situations (e.g., that treating AIDS patients with a cocktail of medications should slow the evolution of the virus), and has proven itself time and time again in thousands of experiments and observational studies.

Overarching Theories

Some theories, which we’ll call over-arching theories, are particularly important and reflect broad understandings of a particular part of the natural world. Evolutionary theory, atomic theory, gravity, quantum theory, and plate tectonics are examples of this over-arching theory. These theories have been broadly supported by multiple lines of evidence and help frame our understanding of the world around us.

Such over-arching theories encompass many subordinate theories and hypotheses, and consequently, changes to those more minor theories and hypotheses reflect a refinement (not an overthrow) of the over-arching theory. For example, when punctuated equilibrium was proposed as a mode of evolutionary change and evidence was found supporting the idea in some situations, it represented an elaborate reinforcement of evolutionary theory, not a refutation of it. Overarching theories are so important because they help scientists choose their methods of study and mode of reasoning, connect critical phenomena in new ways, and open new areas of study. For example, evolutionary theory highlights an entirely new set of questions for exploration: How did this characteristic evolve? How are these species related to each other? How has life changed over time?

References and Acknowledgements

van der Valk, T., Dehasque, M., Chacón-Duque, C.J., Oskolkov, N., Vartanyan, S., Heintzman, P.D. (2022). Evolutionary consequences of genomic deletions and insertions in the woolly mammoth genome. iScience 25: 104826.

Adapted from Clark, M.A., Douglas, M., and Choi, J. (2018, March 28). Biology 2e. OpenStax. Retrieved from https //openstax org/books/biology 2e/pages/1introduction.

Adapted from Understanding Science. 2022. University of California Museum of Paleontology. November 2023 <http://www.understandingscience.org>.