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Owls, such as the young snowy owls on the previous page, have for centuries been symbols of both wisdom and mystery. To many cultures their piercing eyes have conveyed a look of intelligence. Their silent flight through darkened landscapes in search of prey has projected an air of power or wonder. For this chapter and this book, owls are an engaging example of a living organism from the world of biology—the study of life. BIOLOGY AND YOU Living in a small town, in the country, or at the edge of the suburbs, one may be lucky enough to hear an owl's hooting. This experience can lead to questions about where the bird lives, what it hunts, and how it finds its prey on dark, moonless nights. Biology, or the study of life, offers an organized and scientific framework for posing and answering such questions about the natural world. Biologists study questions about how living things work, how they interact with the environment, and how they change over time. Biologists study many different kinds of living things ranging from tiny organisms, such as bacteria, to very large organisms, such as elephants. Each day, biologists investigate subjects that affect you and the way you live. For example, biologists determine which foods are healthy. As shown in Figure 1-1, everyone is affected by this impor- tant topic. Biologists also study how much a person should exer- cise and how one can avoid getting sick. Biologists also study what CHARACTERISTICS OF LIFE The world is filled with familiar objects, such as tables, rocks, plants, pets, and automobiles. Which of these objects are living or were once living? What are the criteria for assigning something to the living world or the nonliving world? Biologists have established that living things share seven characteristics of life. These characteristics are organization and the presence of one or more cells, response to a stimulus (plural, stimuli), homeostasis, metabolism, growth and development, reproduction, and change through time. Organization and Cells Organization is the high degree of order within an organism’s internal and external parts and in its interactions with the living world. For example, compare an owl to a rock. The rock has a spe- cific shape, but that shape is usually irregular. Furthermore, differ- ent rocks, even rocks of the same type, are likely to have different shapes and sizes. In contrast, the owl is an amazingly organized individual, as shown in Figure 1-2. Owls of the same species have the same body parts arranged in nearly the same way and interact with the environment in the same way. Copyright © by Holt, Rinehart and Winston. All rights reserved. ORGANISM (Barn Owl) ORGAN (Owl’s Ear) TISSUE (Nervous Tissue Within the Ear) CELL (Nerve Cell) your air, land, and fAll living organisms, whether made up of one cell or many cells, have some degree of organization. A cell is the smallest unit that can perform all life’s processes. Some organisms, such as bacteria, are made up of one cell and are called unicellular (YOON-uh-SEL-yoo-luhr) organisms. Other organisms, such as humans or trees, are made up of multiple cells and are called multicellular (MUHL-ti-SEL-yoo-luhr) organisms. Complex multicellular organisms have the level of orga- nization shown in Figure 1-2. In the highest level, the organism is made up of organ systems, or groups of specialized parts that carry out a certain function in the organism. For example, an owl’s ner- vous system is made up of a brain, sense organs, nerve cells, and other parts that sense and respond to the owl’s surroundings. Organ systems are made up of organs. Organs are structures that carry out specialized jobs within an organ system. An owl’s ear is an organ that allows the owl to hear. All organs are made up of tissues. Tissues are groups of cells that have similar abilities and that allow the organ to function. For example, nervous tissue in the ear allows the ear to detect sound. Tissues are made up of cells. A cell must be covered by a membrane, contain all genetic information necessary for replication, and be able to carry out all cell functions. Within each cell are organelles. Organelles are tiny structures that carry out functions necessary for the cell to stay alive. Organelles contain biological molecules, the chemical compounds that provide physical structure and that bring about movement, energy use, and other cellular functions. All biological molecules are made up of atoms. Atoms are the simplest particle of an ele- ment that retains all the properties of a certain element. Response to Stimuli Another characteristic of life is that an organism can respond to a stimulus—a physical or chemical change in the internal or external environment. For example, an owl dilates its pupils to keep the level of light entering the eye constant. Organisms must be able to respond and react to changes in their environment to stay alive. ORGANELLE (Mitochondrion) BIOLOGICAL MOLECULE (Phospholipid) ATOM (Oxygen) cell from the Latin, cella meaning “small room,” or “hut” Word Roots and Origins www.scilinks.org Topic: Characteristics of Life Keyword: HM60257 mb06se_bios01.qxd 5/18/07 10:37 AM Page 7 8 CHAPTER 1 Homeostasis All living things, from single cells to entire organisms, have mecha- nisms that allow them to maintain stable internal conditions. Without these mechanisms, organisms can die. For example, a cell’s water content is closely controlled by the taking in or releas- ing of water. A cell that takes in too much water will rupture and die. A cell that doesn’t get enough water will also shrivel and die. Homeostasis (HOH-mee-OH-STAY-sis) is the maintenance of a stable level of internal conditions even though environmental conditions are constantly changing. Organisms have regulatory systems that maintain internal conditions, such as temperature, water content, and uptake of nutrients by the cell. In fact, multi- cellular organisms usually have more than one way of maintain- ing important aspects of their internal environment. For example, an owl’s temperature is maintained at about 40°C (104°F). To keep a constant temperature, an owl’s cells burn fuel to produce body heat. In addition, an owl’s feathers can fluff up in cold weather. In this way, they trap an insulating layer of air next to the bird’s body to maintain its body temperature. Metabolism Living organisms use energy to power all the life processes, such as repair, movement, and growth. This energy use depends on metabolism (muh-TAB-uh-LIZ-uhm). Metabolism is the sum of all the chemical reactions that take in and transform energy and materials from the environment. For example, plants, algae, and some bacteria use the sun’s energy to generate sugar molecules during a process called photosynthesis. Some organisms depend on obtaining food energy from other organisms. For instance, an owl’s metabolism allows the owl to extract and modify the chemi- cals trapped in its nightly prey and use them as energy to fuel activities and growth. Growth and Development All living things grow and increase in size. Some nonliving things, such as crystals or icicles, grow by accumulating more of the same material of which they are made. In contrast, the growth of living things results from the division and enlargement of cells. Cell division is the formation of two new cells from an existing cell, as shown in Figure 1-3. In unicellular organisms, the primary change that occurs following cell division is cell enlargement. In multi- cellular life, however, organisms mature through cell division, cell enlargement, and development. Development is the process by which an organism becomes a mature adult. Development involves cell division and cell differen- tiation, or specialization. As a result of development, an adult organism is composed of many cells specialized for different func- tions, such as carrying oxygen in the blood or hearing. In fact, the human body is composed of trillions of specialized cells, all of which originated from a single cell, the fertilized egg. This unicellular organism, Escherichia coli, inhabits the human intestines. E. coli reproduces by means of cell division, during which the original cell splits into two identical offspring cells. FIGURE 1-3 Observing Homeostasis Materials 500 mL beakers (3), wax pen, tap water, thermometer, ice, hot water, goldfish, small dip net, watch or clock with a second hand Procedure 1. Use a wax pen to label three 500 mL beakers as follows: 27°C (80°F), 20°C (68°F), 10°C (50°F). Put 250 mL of tap water in each beaker. Use hot water or ice to adjust the tem- perature of the water in each beaker to match the temperature on the label. 2. Put the goldfish in the beaker of 27°C water. Record the number of times the gills move in 1 minute. 3. Move the goldfish to the beaker of 20°C water. Repeat observations. Move the goldfish to the beaker of 10°C. Repeat observations. Analysis What happens to the rate at which gills move when the temp- erature changes? Why? How do gills help fish maintain homeostasis? Quick Lab mb06se_bios01.qxd 5/18/07 10:37 AM Page 8 THE SCIENCE OF LIFE 9 Reproduction All organisms produce new organisms like themselves in a process called reproduction. Reproduction, unlike other characteristics, is not essential to the survival of an individual organism. However, because no organism lives forever, reproduction is essential for the continuation of a species. Glass frogs, as shown in Figure 1-4, lay many eggs in their lifetime. However, only a few of the frogs’ off- spring reach adulthood and successfully reproduce. During reproduction, organisms transmit hereditary informa- tion to their offspring. Hereditary information is encoded in a large molecule called deoxyribonucleic acid, or DNA. A short segment of DNA that contains the instructions for a single trait of an organism is called a gene. DNA is like a large library. It contains all the books—genes—that the cell will ever need for making all the struc- tures and chemicals necessary for life. Hereditary information is transferred to offspring during two kinds of reproduction. In sexual reproduction, hereditary information recombines from two organisms of the same species. The resulting offspring are similar but not identical to their parents. For example, a male frog’s sperm can fertilize a female’s egg and form a single fer- tilized egg cell. The fertilized egg then develops into a new frog. In asexual reproduction, hereditary information from different organisms is not combined; thus the original organism and the new organism are genetically the same. A bacterium, for example, reproduces asexually when it splits into two identical cells. Change Through Time Although individual organisms experience many changes during their lifetime, their basic genetic characteristics do not change. However, populations of living organisms evolve or change through time. The ability of populations of organisms to change over time is important for survival in a changing world. This factor is also impor- tant in explaining the diversity of life-forms we see on Earth today. 1. How does biology affect a person’s daily life? 2. How does biology affect society? 3. Name the characteristics shared by living things. 4. Summarize the hierarchy of organization found in complex multicellular organisms. 5. What are the different functions of homeostasis and metabolism in living organisms? 6. How does the growth among living and nonliv- ing things differ? 7. Why is reproduction an important characteristic of life? CRITICAL THINKING 8. Applying Information Crystals of salt grow and are highly organized. Why don’t biologists con- sider them to be alive? 9. Analyzing Models When a scientist designs a space probe to detect life on a distant planet, what kinds of things should it measure? 10. Making Comparisons Both cells and organisms share the characteristics of life. How are cells and organismsood supply will be like in the near future.EVOLUTION OF LIFE Individual organisms change during their lifetime, but their basic genetic characteristics do not change. However, populations of liv- ing organisms do change through time, or evolve. Evolution, or descent with modification, is the process in which the inherited characteristics within populations change over generations, such that genetically distinct populations and new species can develop. Evolution as a theme in biology helps us understand how the various branches of the “tree of life” came into existence and have changed over time. It also explains how organisms alive today are related to those that lived in the past. Finally, it helps us understand the mechanisms that underlie the way organisms look and behave. Natural Selection The ability of populations of organisms to change over time is important for survival in a changing world. According to the theory of evolution by natural selection, organisms that have certain favorable traits are better able to survive and reproduce success- fully than organisms that lack these traits. One product of natural selection is the adaptation of organisms to their environment. Adaptations are traits that improve an indi- vidual’s ability to survive and reproduce. For example, rabbits with white fur and short ears in a snowy place, such as the one in Figure 1-7a, may avoid predators and frostbitten ears more often than those with dark fur and long ears. Thus, the next generation of rabbits will have a greater percentage of animals carrying the genes for white fur and short ears. In contrast, the brown, long- eared rabbit, as shown in Figure 1-7b, would survive and reproduce more successfully in a hot desert environment. The survival and reproductive success of organisms with favor- able traits cause a change in populations of organisms over gener- ations. This descent with modification is an important factor in explaining the diversity of organisms we see on Earth today. 1. Name three unifying themes found in biology. 2. How is the unity and diversity in the living world represented? 3. Identify the three domains and the kingdoms found in each domain. 4. How are organisms interdependent? 5. Describe why evolution is important in explain- ing the diversity of life. 6. Distinguish between evolution and natural selection. CRITICAL THINKING 7. Applying Information Assign the various top- pings you put on pizza to the appropriate domains and kingdoms of life. 8. Analyzing Graphics According to the “tree” in Figure 1-5, which of these pairs are more closely related: Archaea:Bacteria or Archaea:Eukarya? 9. Making Hypotheses Fossil evidence shows that bats descended from shrewlike organisms that could not fly. Write a hypothesis for how natural selection might have led to flying bats. SECTION 2 REVIEW (a) This short-eared arctic hare, Lepus arcticus, is hidden from predators and protected from frostbite in a snowy environment. (b) The mottled brown coats of desert rabbits blend in with the dirt and dry grasses, and their long ears help them radiate excess heat and thus avoid overheating. FIGURE 1-7 (a) (b) Copyright © by Holt, Rinehart and Winston. All rights reserved. THE SCIENCE OF LIFE 13 TH E STUDY OF BIOLOGY Curiosity leads us to ask questions about life. Science provides a way of answering such questions about the natural world. Science is a systematic method that involves forming and testing hypotheses. More importantly, science relies on evidence, not beliefs, for drawing conclusions. SCIENCE AS A PROCESS Science is characterized by an organized approach, called the scientific method, to learn how the natural world works. The methods of science are based on two important principles. The first principle is that events in the natural world have natural causes. For example, the ancient Greeks believed that lightning and thunder occurred because a supernatural god Zeus hurled thunderbolts from the heavens. By contrast, a scientist considers lightning and thunder to result from electric charges in the atmos- phere. When trying to solve a puzzle from nature, all scientists, such as the one in Figure 1-8, accept that there is a natural cause to solve that puzzle. A second principle of science is uniformity. Uniformity is the idea that the fundamental laws of nature operate the same way at all places and at all times. For example, scientists assume that the law of gravity works the same way on Mars as it does on Earth. Steps of the Scientific Method Although there is no single method for doing science, scientific studies involve a series of common steps. 1. The process of science begins with an observation. An observation is the act of perceiving a natural occurrence that causes someone to pose a question. 2. One tries to answer the question by forming hypotheses (singular, hypothesis). A hypothesis is a proposed explanation for the way a particular aspect of the natural world functions. 3. A prediction is a statement that forecasts what would happen in a test situation if the hypothesis were true. A prediction is recorded for each hypothesis. 4. An experiment is used to test a hypothesis and its predictions. 5. Once the experiment has been concluded, the data are analyzed and used to draw conclusions. 6. After the data have been analyzed, the data and conclusions are communicated to scientific peers and to the public. This way oth- ers can verify, reject, or modify the researcher’s conclusions. SECTION 3 OBJECTIVES ● Outline the main steps in the scientific method. ● Summarize how observations are used to form hypotheses. ● List the elements of a controlled experiment. ● Describe how scientists use data to draw conclusions. ● Compare a scientific hypothesis and a scientific theory. ● State how communication in science helps prevent dishonesty and bias. VOCABULARY scientific method observation hypothesis prediction experiment control group experimental group independent variable dependent variable theory peer review All researchers, such as the one releasing an owl above, use the scientific method to answer the questions they have about nature. FIGURE 1-8 Copyright © by Holt, Rinehart and Winston. All rights reserved. 14 CHAPTER 1 OBSERVING AND ASKING QUESTIONS The scientific method generally begins with an unexplained observa- tion about nature. For example, people have noticed for thousands of years that owls can catch prey in near total darkness. As shown in steps and of Figure 1-9, an observation may then raise ques- tions. The owl observation raises the question: How does an owl detect prey in the dark? FORMING A HYPOTHESIS After stating a question, a biologist lists possible answers to a sci- entific question—hypotheses. Good hypotheses answer a question and are testable in the natural world. For example, as shown in step Figure 1-9, there are several possible hypotheses for the question of how owls hunt at night: (a) owls hunt by keen vision in the dark; (b) owls hunt by superb hearing; or (c) owls hunt by detecting the prey’s body heat. Predicting To test a hypothesis, scientists make a prediction that logically fol- lows from the hypothesis. A prediction is what is expected to hap- pen if each hypothesis were true. For example, if hypothesis (a) is true, (owls hunt by keen night vision) then one can predict that the owl will pounce only on the mouse in either a light or a dark room. If hypothesis (b) is true (owls hunt by hearing), then one can pre- dict that in a lighted room, the owl will pounce closer to the mouse’s head. But, in a dark room, the owl should pounce closer to a rustling leaf attached to the mouse. Finally, if hypothesis (c) is true (owls hunt by sensing body heat), then an owl would strike only the prey no matter the room conditions, because owls hunt by detecting the prey’s body heat. 3 1 2 Copyright © by Holt, Rinehart and Winston. All rights reserved. A scientific study includes observations, questions, hypotheses, predictions, experiments, data analysis, and conclu- sions. A biologist can use the scientific method to set up an experiment to learn how an owl captures prey at night. FIGURE 1-9 1 OBSERVATION Owls capture prey on dark nights. 2 QUESTION How do owls detect prey on dark nights? 3 HYPOTHESES a) Owls hunt in the dark by vision. b) Owls hunt in the dark by hearing. c) Owls hunt in the dark by sensing body heat. THE SCIENCE OF LIFE 15 Notice that these predictions make it difficult to distinguish be- tween the vision and body heat hypotheses. The reason is that both hypotheses predict that the owl could grab the mouse in a dark room. Also, these three hypotheses do not eliminate all other factors that could influence how the owl finds its prey. However, testing predictions can allow one to begin rejecting hypotheses and thus to get closer to determining the answer(s) to a question. DESIGNING AN EXPERIMENT Biologists often test hypotheses by setting up an experiment. Step in Figure 1-9 outlines an experiment to test the hypotheses about how an owl hunts at night. First, experimenters set up a room with an owl perch high on one side and a small trap door on the other side for releasing mice. Then, they tied a leaf to each mouse’s tail with a string and released each mouse into the room. Next, each mouse ran silently across the room, but the leaf trailed behind, making a rustling noise. During half of the trials, the lights were on. During the other half, the room was dark. Technicians videotaped all the action in the chamber with an infrared light, which owls cannot see. The researchers then viewed the videos and measured the position of the owl’s strike relative to each mouse’s head. Performing the Experiment Many scientists use a controlled experiment to test their hypotheses. A controlled experiment compares an experimental group and a control group and only has one variable. The control group pro- vides a normal standard against which the biologist can compare results of the experimental group. The experimental group is iden- tical to the control group except for one factor, the independent variable. The experimenter manipulates the independent variable, sometimes called the manipulated variable. 4 4 EXPERIMENT 5 DATA COLLECTION AND ANALYSIS Measure and compare the distance from the owl’s strike to the mouse and to the leaf in light and dark. 6 CONCLUSION Data supported the hearing hypothesis: Owls hunt in the dark by hearing. prey Test predictions of the three hypotheses. Control: In the light Experimental: In the dark 1 2 3 4 5 6 7 8 9 10 11 Predicting Results Materials 2 Petri dishes with agar, cellophane tape, wax pen Procedure 1. Open one of the Petri dishes, and streak your finger across the surface of the agar. 2. Replace the lid, and seal it with the tape. Label this Petri dish with your name and a number 1. 3. Seal the second Petri dish with- out removing the lid. Label this Petri dish with your name and the number 2. 4. Write a prediction about what will happen in each dish. Store your dishes as your teacher directs. Record your observations. Follow your teacher’s directions for disposal of your dishes. Analysis Was your prediction accurate? What evidence can you cite to support your prediction? If you did not obtain the results you predicted, would you change your testing method or your prediction? Explain. Evaluate the importance of obtaining a result that does not support your prediction. Quick Lab mb06se_bios03.qxd 5/18/07 10:40 AM Page 15 16 CHAPTER 1 The independent variable in the owl experiment is the presence or absence of light. In the owl experiment, the control group hunts in the light, and the experimental group hunts in the dark. In addi- tion to varying the independent variable, a scientist observes or measures another factor called the dependent variable, or respond- ing variable, because it is affected by the independent variable. In the owl experiment, the dependent variable is distance from the owl’s strike to the mouse’s head. Testing the Experiment Some controlled experiments are conducted “blind.” In other words, the biologist who scores the results is unaware of whether a given subject is part of the experimental or control group. This factor helps eliminate experimenter bias. Experiments should also be repeated, because living systems are variable. Moreover, scien- tists must collect enough data to find meaningful results. COLLECTING AND ANALYZING DATA Most experiments measure a variable—the dependent variable. This measurement provides quantitative data, data measured in numbers. For example, in the experiment above, scientists mea- sured the distance of an owl’s strike from the prey’s head in cen- timeters, as shown in step of Figure 1-9. An event’s duration in milliseconds is also an example of quantitative data. Biologists usually score the results of an experiment by using one of their senses. They might see or hear the results of an experiment. Scientists also extend their senses with a micro- scope for tiny objects or a microphone for soft sounds. In the owl experiment, biologists extended their vision with infrared cameras. Analyzing and Comparing Data After collecting data from a field study or an experiment and then organizing it, biologists then analyze the data. In analyzing data, the goal is to determine whether the data are reliable, and whether they support or fail to support the predictions of the hypothesis. To do so, scientists may use statistics to help determine relation- ships between the variables involved. They can then compare their data with other data that were obtained in other similar studies. It is also important at this time to determine possible sources of error in the experiment just per- formed. Scientists usually display their data in tables or graphs when analyzing it. For the owl study, biologists could have made a bar graph such as the one in Figure 1-10, which shows the average distance from the owl’s strike relative to the mouse’s head or the leaf in the light and in the dark. 5 5 0 10 15 20 25 In the light In the dark Average distance from strike (cm) Distance Between Owl Strike and a Mouse or From a Leaf Attached to Mouse 30 Mouse Leaf Mouse Leaf The data below are hypothetical results that might occur from the described owl experiment.The independent variable is the darkness of the room, and the dependent variable is how far the owl struck from the mouse’s head.The data show that the owl strikes more accurately at the mouse in the light but strikes more accurately at the leaf in the dark. FIGURE 1-10 Copyright © by Holt, Rinehart and Winston. All rights reserved. THE SCIENCE OF LIFE 17 DRAWING CONCLUSIONS Biologists analyze their tables, graphs, and charts to draw conclu- sions about whether or not a hypothesis is supported, as shown in step of Figure 1-9. The hypothetical owl data show that in the light, owls struck with greater accuracy at the mouse than at the leaf, but in the dark, owls struck with greater accuracy at the leaf than the mouse. Thus, the findings support the hearing hypothe- sis, but not the vision hypothesis. An experiment can only disprove, not prove, a hypothesis. For example, one cannot conclude from the results that the hearing hypothesis is proven to be true. Perhaps the owl uses an unknown smell to strike at the mouse. One can only reject the vision hypothe- sis because it did not predict the results of the experiment correctly. Acceptance of a hypothesis is always tentative in science. The scientific community revises its understanding of phenomena, based on new data. Having ruled out one hypothesis, a biologist will devise more tests to try to rule out any remaining hypotheses. Making Inferences Scientists often draw inferences from data gathered during a field study or experiment. An inference (IN-fuhr-uhns) is a conclusion made on the basis of facts and previous knowledge rather than on direct observations. Unlike a hypothesis, an inference is not directly testable. In the owl study, it is inferred that the owl detects prey from a distance rather than by direct touch. Applying Results and Building Models As shown in Figure 1-11, scientists often apply their findings to solve practical problems. They also build models to represent or describe things. For example in 1953, James Watson and Francis Crick used cardboard balls and wire bars to build physical models of atoms in an attempt to understand the structure of DNA. Mathematical models are sets of equations that describe how dif- ferent measurable items interact in a system. The experimenter can adjust variables to better model the real-world data. CONSTRUCTING A THEORY When a set of related hypotheses is confirmed to be true many times, and it can explain a great amount of data, scientists often reclassify it as a theory. Some examples include the quantum the- ory, the cell theory, or the theory of evolution. People commonly use the word “theory” in a different way than scientists use the word. People may say “It’s just a theory” suggesting that an idea is untested, but scientists view a theory as a highly tested, generally accepted principle that explains a vast number of observations and experimental data. 6 Copyright © by Holt, Rinehart and Winston. All rights reserved. Biologists often apply their knowledge of the natural world to practical problems. Studies on the owl’s keen ability to locate sounds in space despite background noise are helping biotechnologists and bioengineers develop better solutions for people with impaired hearing, such as the people shown in this picture. FIGURE 1-11 18 CHAPTER 1 COMMUNICATING IDEAS An essential aspect of scientific research is scientists working together. Scientists often work together in research teams or sim- ply share research results with other scientists. This is done by publishing findings in scientific journals or presenting them at sci- entific meetings, as shown in Figure 1-12. Sharing information allows others working independently to verify findings or to con- tinue work on established results. For example, Roger Payne pub- lished the results of his owl experiments in a journal in 1971. Then, other biologists could repeat it for verification or use it to study the mechanisms introduced by the paper. With the growing impor- tance of science in solving societal issues, it is becoming increas- ingly vital for scientists to be able to communicate with the public at large. Publishing a Paper Scientists submit research papers to scientific journals for publica- tion. A typical research paper has four sections. First, the Introduction poses the problem and hypotheses to be investigated. Next, the Materials and Methods describe how researchers proceeded with the experiment. Third, the Results state the findings the experiment presented, and finally, the Discussion gives the significance of the experiment and future directions the scientists will take. Job Description Forensic biolo- gists are scientists who study biological materials to investigate potential crimes and other legal issues against humans and animals. Forensic scientists have knowledge in areas of biology, such as DNA and blood pattern analysis, and work in private sector and public laboratories. Focus On a Forensic Biologist As a law enforcement forensic specialist for the Texas Parks and Wildlife Department, Beverly Villarreal assists the game warden in investigations of fish and wildlife violations, such as illegal hunting and fishing. Villarreal analyzes blood and tissue samples to identify species of animals such as fish, birds, and reptiles. Her work helps game wardens as they enforce state laws regarding hunting and fishing. Most people think of forensic scientists as the glamorous crime investigators on TV, but according to Villarreal real forensic scientists “spend a great deal of time at a lab bench running analysis after analysis.” Many of the methods used in animal forensics, such as DNA sequenc- ing, are also used in human forensics. Education and Skills • High school—three years of science courses and four years of math courses. • College—bachelor of science in biol- ogy, including course work in zoology and genetics, plus experience in per- forming DNA analyses. • Skills—patience, attention to detail, and ability to use fine tools. Careers in BIOLOGY Forensic Biologist For more about careers, visit go.hrw.com and type in the keyword HM6 Careers. www.scilinks.org Topic: Scientific Investigations Keyword: HM61358 mb06se_bios03.qxd 5/18/07 10:40 AM Page 18 THE SCIENCE OF LIFE 19 1. What two principles make the scientific method a unique process? 2. Define the roles of observations and hypotheses in science. 3. Summarize the parts of a controlled experiment. 4. Summarize how we make conclusions about the results of an experiment. 5. Why is the phrase, “it’s just a theory” misleading? 6. Give another example of a conflict of interest. CRITICAL THINKING 7. Making Hypotheses On a nocturnal owl’s skull, one ear points up, and the other ear points down. Suggest a hypothesis for this observation. 8. Designing Experiments Design an experiment to establish if owls hunt by keen sight or hunt by heat seeking. 9. Calculating Information What was the average distance between the owl’s strike and the mouse if the recorded differences in this experiment were 25, 22, 19, 19, and 15? SECTION 3 REVIEW After scientists submit their papers to a scientific journal, the editors of that journal will send the paper out for peer review. In a peer review, scientists who are experts in the field anonymously read and critique that research paper. They determine if a paper pro- vides enough information so that the experiment can be duplicated and if the author used good experimental controls and reached an accurate conclusion. They also check if the paper is written clearly enough for broad understanding. Careful analysis of each other’s research by fellow scientists is essential to making scientific progress and preventing scientific dishonesty. HONESTY AND BIAS The scientific community depends on both honesty and good sci- ence. While designing new studies, experimenters must be very careful to prevent previous ideas and biases from tainting both the experimental process and the conclusions. Scientists have to keep in mind that they are always trying to disprove their favorite ideas. Scientists repeat experiments to verify previous findings. This allows for science to have a method for self-correction and it also keeps researchers honest and credible to their peers in the field. Conflict of Interest For most scientists, maintaining a good reputation for collecting and presenting valid data is more important than temporary prestige or income. So, scientists try to avoid any potential conflicts of interest. For example, a scientist who owns a biotechnology company and manufactures a drug would not be the best researcher to critically test that drug’s safety and effectiveness. To avoid this potential con- flict of interest, the scientist allows an unaffected party, such as a research group, to test the drug’s effectiveness. The threat of a potential scandal based on misleading data or conclusions is a pow- erful force in science that helps keep scientists honest and fair. Scientists present their experiments in various forms. The scientists above are presenting their work in the form of a poster at a scientific meeting. FIGURE 1-12 Copyright © by Holt, Rinehart and Winston. All rights reserved. The Internet can provide a wealth of scientific information for a report, but the information may not always be credible or accurate. You can use the methods above to check the accuracy and credibility of your sources. SCIENCE TECHNOLOGY SOCIETY SCIENCE ON THE INTERNET: A New Information Age I n the past, students research- ing a science topic would typ- ically begin their research by visiting a library to use printed reference materials, such as encyclopedias. Today, most stu- dents research topics by using a computer and searching for information on the Internet. The Internet can provide students with a wealth of infor- mation. But which Web sites have accurate information, and which Web sites do not? Checking Web Addresses Students should use the Web address, or URL, to establish the Web site’s credibility. Usually, the domain name can suggest who has published the Web site. Web sites can be pub- lished by governmental agen- cies (ends in “dot gov” or .gov), by educational institutions (ends in “dot edu” or .edu), by organizations (ends in “dot org” or .org), or by commercial businesses (ends in “dot com” or .com). Government Web sites are usually reliable. Examples of credible governmental Web sites are the National Institutes of Health (NIH) and the Food and Drug Administration (FDA). University and medical school sites are also reliable sources of information. Many organiza- tions that research and teach the public about specific diseases and conditions can also provide reliable information. Examples of such organizations are the American Cancer Society and the American Heart Association. Evaluating Web Sites The credibility of the author of the Web site should also be checked. Make sure the author is not trying to sell anything and is established in his or her field. For example, a health Web site’s author should be a med- ical professional. It is also important to check the date that the information was posted on the Web to ensure that the information is current. Also, the Web site should provide ref- erences from valid sources, such as scientific journals or govern- ment publications. Finally, the student should always double-check informa- tion between several reliable Web sites. If two or three reliable sites provide the same informa- tion, the student can feel confi- dent in using that information. Web Sites for Students The Internet Connect boxes in this textbook have all been reviewed by professionals at the National Science Teachers Association (NSTA). Students can trust that these sites are reliable sources for science- or health-related topics. REVIEW 1. Which types of Web addresses are the most reliable? 2. List four important features to evaluate when using a Web site for research. 3. Supporting Reasoned Opinions Why do you think a Web site that is advertising a product may not offer accurate information? REVIEW 20 www.scilinks.org Topic: Using the Internet Keyword: HM61589 mb06se_biosts.qxd 5/18/07 10:42 AM Page 20 TOOLS AND TECHNIQUES With proper equipment and good methods, biologists can see, manipulate, and understand the natural world in new ways. Microscopes are one of many useful tools used to unlock nature’s biological secrets. MICROSCOPES AS TOOLS Tools are objects used to improve the performance of a task. Microscopes are tools that extend human vision by making enlarged images of objects. Biologists use microscopes to study organisms, cells, cell parts, and molecules. Microscopes reveal details that otherwise might be difficult or impossible to see. Light Microscopes To see small organisms and cells, biologists typically use a light microscope, such as the one shown in Figure 1-13. A compound light microscope is a microscope that shines light through a spec- imen and has two lenses to magnify an image. To use this micro- scope, one first mounts the specimen to be viewed on a glass slide. The specimen must be thin enough for light to pass through it. For tiny pond organisms, such as the single-celled paramecium, light passing through the organism is not a problem. For thick objects, such as plant stems, biologists must cut thin slices for viewing. There are four major parts of a compound light microscope. For further description of the parts of a micro- scope, see the Appendix. 1. Eyepiece The eyepiece (ocular (AHK-yoo-luhr) lens) magnifies the image, usually 10 times. 2. Objective Lens Light passes through the specimen and then through the objective lens, which is located directly above the specimen. The objective lens enlarges the image of the specimen. Scientists sometimes use stains to make the image easier to see. 3. Stage The stage is a platform that supports a slide holding the specimen. The slide is placed over the opening in the stage of the microscope. 4. Light Source The light source is a light bulb that provides light for viewing the image. It can be either light reflected with a mirror or an incandescent light from a small lamp. SECTION 4 OBJECTIVES ● List the function of each of the major parts of a compound light microscope. ● Compare two kinds of electron microscopes. ● Describe the importance of having the SI system of measurement. ● State some examples of good laboratory practice. VOCABULARY compound light microscope eyepiece (ocular lens) objective lens stage light source magnification nosepiece resolution scanning electron microscope transmission electron microscope metric system base unit Compound light microscopes open the human eye to an interesting world including tiny pond organisms, healthy and diseased cells, and the functioning of cell parts. FIGURE 1-13 Objective lens Eyepiece (ocular lens) Stage Light THE SCIENCE OF LIFE 21 Copyright © by Holt, Rinehart and Winston. All rights reserved. 22 CHAPTER 1 Magnification and Resolution Microscopes vary in powers of magnification and resolution. Magnification is the increase of an object’s apparent size. Revolving the nosepiece, the structure that holds the set of objective lens, rotates these lenses into place above the specimen. In a typical com- pound light microscope, the most powerful objective lens produces an image up to 100 times (100) the specimen’s actual size. The degree of enlargement is called the power of magnification of the lens. The standard ocular lens magnifies a specimen 10 times (10). To compute the power of magnification of a microscope, the power of magnification of the strongest objective lens (in this case, 100) is multiplied by the power of magnification of the ocular lens (10). The result is a total power of magnification of 1000. Resolution (REZ-uh-LOO-shuhn) is the power to show details clearly in an image. The physical properties of light limit the ability of light microscopes to resolve images, as shown in Figure 1-14a. At pow- ers of magnification beyond about 2,000, the image of the speci- men becomes fuzzy. For this reason, scientists use other microscopes to view very small cellsHi, Sam. Are you ready for the spelling test on Monday? Yes, I am ready. Would you like to practice spelling words on the computer? I have a spelling game. Yes, that sounds like fun! How do I play? You can use the keyboard to write the words. You can use the mouse to click. Wow, this game is great! Yes, it's a good computer game. We will do well on this Monday's test.أنت خبير متمكن في تعليم اللغة الإنجليزية ولديك خبرة واسعة في صياغة أسئلة تكمل الكلمات الناقصة بطريقة تعزز مهارات الطلبة في المفردات والقواعد. يرجى إعداد عشر أسئلة من نوع "أكمل أجمل بالكلمات الصحيحة" بناءً على الصورة المرفقة، مع مراعاة النقاط التالية: **1- صياغة الأسئلة:** - صياغة جمل تحتوي على فراغات يجب ملؤها بالكلمة الصحيحة من المربع الإنجليزي. - تنوع في نوع الكلمات المطلوبة (أسماء، أفعال، صفات، ظرف). **2- مستوى الصعوبة:** - توجيه الأسئلة لتناسب مستوى متوسط إلى متقدم، بحيث تتحدى المتعلم وتحفزه على التفكير. **3- وضوح التعليمات:** - توضيح المطلوب في كل سؤال بشكل دقيق مع تقديم مثال إذا لزم الأمر. **4- التنوع الموضوعي:** - تضمين مفردات متنوعة في مجالات مختلفة لكي توسع دائرة معارف المتعلمين. **5- ترتيب الأسئلة:** - تنظيم الأسئلة من الأسهل إلى الأصعب بشكل تدريجي لتحفيز المتعلم على الاستمرارية. **6- التأكد من صحة الإجابات:** - تقديم الإجابات النموذجية بشكل منفصل لتسهيل عملية التصحيح. **7- جمالية العرض:** - استخدام لغة تعليمية جذابة ومحفزة لتعزيز تفاعل المتعلم مع المحتوى. أعتمد على خبرتك الواسعة في تصميم أسئلة تعليمية مبتكرة لتحويل محتوى الصورة إلى نشاط تدريبي فعال يدعم تحسين مهارات اللغة الإنجليزية لدى الطلاب. Words in the box: save, volunteer, available, devices, empty, plant, public, pollution Sentences: Somebody ate all the chocolates. The box is __________________________. My brother uses __________________________ transport to go to work. If you turn off the lights when you leave a room, you __________________________ energy. I took my old mobile phone and some other electronic __________________________ to the computer shop to recycle them. The new computer game will be __________________________ in shops next month. The problem of __________________________ is getting worse in my city. We must __________________________ trees, not cut them down. I want to become a(n) __________________________ to help protect the environment.Title: The Adventures of Max and the Magical Computer (Shortened Version) Once upon a time, in a small town called Techville, there lived a curious fourth-grader named Max. One day, while exploring his grandma’s attic, he found an old, dusty computer. As he cleaned it, the screen lit up, and a cheerful voice said, “Hello, Max! I’m Compy, your magical computer. Let’s learn about operating systems, files, and folders!” Max was thrilled. “A talking computer? Let’s go!” Chapter 1: The World of Windows Compy explained, “I run on Windows, the brain of the computer. It uses a Graphical User Interface (GUI), so you can interact with me using icons, menus, and buttons. Let’s start by changing my desktop background—the image on the screen.” Max chose a spaceship picture. “Cool! Can I add a screen saver too?” “Of course!” said Compy. “It’s an image that appears when I’m inactive. Try this swirling galaxy!” Max set the screen saver and giggled as it appeared. “This is fun!” Chapter 2: Organizing with Folders and Files Compy’s screen filled with random icons. “Oh no! My files are a mess. Can you help?” “Sure! What are files and folders?” asked Max. “A file is information, like a picture or document. Files have names, like ‘Homework.docx.’ The part after the dot, like .docx, is the file extension. It tells you the file type,” Compy explained. Max pointed to “Game.exe.” “So, this is a program file?” “Yes!” said Compy. “To organize, we use folders—like drawers for files. You can even put folders inside folders!” Max created a “School” folder, added his homework files, and made a “Projects” folder inside it. “Now everything’s neat!” Chapter 3: The File Explorer Adventure Compy’s screen flickered. “Some files are missing. Let’s use Windows Explorer to find them. It’s like a map for files and folders.” Max opened Windows Explorer and saw a tree-like list of folders. “This is like a tree with branches!” “Exactly!” said Compy. “Search for the missing files and move them to the right folders.” Max found the files in “Downloads” and moved them. “I feel like a computer detective!” Chapter 4: The Final Challenge Compy’s screen turned into a game board. “Time for a quiz! What’s the purpose of an operating system? How do you change the desktop background? What’s the difference between a file and a folder?” Max answered all the questions correctly, and fireworks lit up the screen. “Congratulations, Max! You’re a computer whiz!” The End Max smiled. “Thanks, Compy! I can’t wait to teach my friends!” Compy replied, “Remember, Max, learning is an adventure. Keep exploring!” As Max turned off the computer, he knew his journey into technology had just begun.In this video we take a look at the 0:02 fetch to code 0:03 execute cycle including its effect on 0:06 the various registers we've previously 0:12 [Music] 0:14 discussed a computer is defined Definition 0:17 as an electronic device that takes an 0:20 input 0:22 processes data 0:25 and delivers output 0:29 in this simple example you can see we're 0:31 taking the input 5 0:35 we're multiplying it by 2 that's our 0:37 process 0:39 and we're outputting 10. 0:44 but this could be way more complex for 0:46 example of a game console 0:48 the input could be the buttons you press 0:50 on a controller 0:53 the processes would then be carried out 0:55 by the console itself 0:59 and the output would be some form of 1:01 update to a monitor 1:02 and sound out for a speaker possibly 1:04 vibration feedback through the 1:06 controller 1:10 to process data a computer follows a set 1:13 of instructions 1:14 known as a computer program 1:18 if we take the lid off a typical desktop 1:20 computer we can identify 1:22 two critical components the memory 1:26 that stores the program and the central 1:29 processing unit or processor 1:31 which is under this large fan and 1:33 carries out the instructions 1:37 a computer carries out its function by 1:40 fetching 1:41 instructions decoding them and then 1:43 executing them 1:44 in a continuous repetitive cycle 1:46 billions of times a second 1:48 let's look at each of these stages in a 1:50 little more detail Fetch 1:53 so let's start with the fetch stage the 1:55 very first thing that happens 1:57 is the program counter is checked as it 2:00 holds the address 2:01 of the next instruction to be executed 2:07 the address stored is then copied into 2:09 the memory address register 2:14 the address is then sent along the 2:16 address bus to main memory 2:18 where it waits to receive a signal from 2:21 the control 2:22 bus so it knows what to do 2:27 as we want to read the data that's 2:29 stored in memory address 2:30 0 0 0 0 the control unit sends 2:34 a read signal along the control bus to 2:36 main memory 2:41 now main memory knows the data needs to 2:44 be read 2:45 the content stored in memory address 000 2:49 can be sent along the data bus to the 2:51 memory data register 2:56 now as we're currently in the process of 2:58 fetching an instruction 3:00 the data received by the memory data 3:03 register gets copied 3:04 into the current instruction register 3:11 the instruction effectively has now been 3:14 fetched from memory 3:16 just before we proceed to the decode 3:18 phase we now 3:19 increment the program counter so that 3:22 the address it contains 3:24 points to the address of the next 3:26 instruction which will need to be 3:30 executed 3:32 the instruction now being held in the 3:33 current instruction register 3:35 is ready to be decoded 3:39 now as we mentioned in the previous 3:41 video the instruction is made up of two 3:43 parts 3:44 we have the op code that's what it is we 3:47 need to do 3:50 and we have the operand what are we 3:53 going to do it to 3:55 now the operand could contain the actual 3:57 data 3:58 or indeed it could contain an address of 4:01 where the data is to be found 4:06 by decoding this instruction we can see 4:08 the operation we need 4:10 is a load operation so we need to load 4:14 the contents of memory location0101 4:18 into the cpus accumulator 4:25 in the exam a simple model will be used 4:27 to describe the 4:29 structure of any given instruction 4:32 you're not going to be expected to 4:34 define how an opcode is made up 4:36 but simply to interpret opcodes in the 4:39 given context of an exam 4:40 question in the example here 4:44 you can see there's a total of 16 4:46 different opcodes available 4:48 and this is because we're using four 4:50 bits for our representation 4:56 so now we've fetched the instruction and 4:59 we've decoded it so we know what we need 5:00 to do 5:01 we're finally ready to execute it 5:05 so we now send address 0101 5:08 to the memory dress register 5:13 now we're in the memory address register 5:15 we can finally send the address 5:18 down the address bus to main memory 5:24 this time we want to read the data 5:26 that's stored in memory 5:28 and so the control unit again sends a 5:30 read signal along the control bus 5:36 so main memories now receive an address 5:38 and a read signal 5:40 so the content stored at memory location 5:43 0101 5:44 can now be sent along the data bus back 5:46 to the cpu 5:47 and into the memory data register 5:54 finally the contents of the memory data 5:56 register are copied to the accumulator 5:59 and this is one of a number of general 6:00 purpose registers found in the cpu 6:04 this first instruction is now complete Branching 6:11 so what does this program actually do 6:14 you should be able to work it through 6:16 carefully and figure it out 6:19 we're now pointing instructions zero 6:21 zero zero one in the program counter 6:23 and we're ready to fetch the second 6:25 instruction 6:27 at the end of this video we're gonna 6:29 provide you with the answer 6:34 so let's talk a second about programs 6:37 that branch 6:40 on the left here we have a very simple 6:42 piece of pseudo code 6:44 line zero says first execute this line 6:46 of code 6:47 line 1 now execute this line and then 6:50 line 2 says 6:52 if the age is greater than 18 then 6:56 we're going to execute lines 3 and 4 6:58 otherwise 6:59 we're going to execute lines six and 7:02 seven 7:03 so this program doesn't necessarily 7:05 follow strictly in sequence from line 7:07 zero through to seven there's a chance 7:10 here the program may branch and jump 7:14 around 7:16 so we're going to pretend that this 7:17 program has been loaded into memory 7:20 each line of code on the left here has 7:23 ended up 7:24 as a location in memory now this is not 7:27 strictly how this would happen in this 7:28 one-to-one way 7:29 but for the purpose of example it's 7:31 absolutely fine 7:35 so the program counter starts by 7:37 pointing to memory address zero 7:39 and we fetch the first instruction 7:41 decode it and execute it 7:44 it then updates and tells us the next 7:47 instruction 7:48 is zero zero zero one because remember 7:50 the program counter is being incremented 7:52 so we fetch it decode it and we execute 7:55 line one of our program 7:59 we then fetch line two which in binary 8:01 is one 8:02 zero 8:06 now at this point depending on what 8:10 happens during the execution 8:11 of line two the program may be required 8:15 to fetch line three from memory or 8:18 line five from memory 8:25 so let's look at how this actually works 8:27 because we've said the program counter 8:28 simply gets incremented 8:31 well in the current instruction register 8:33 we have an instruction with the op code 8:36 0 1 1 0. 8:41 now when we look this up in the decode 8:43 unit we discover that this 8:45 code means branch always 8:51 this replaces the value held in the 8:54 program counter 8:56 with the contents of the operand that's 8:58 the second part of the instruction 9:01 from the current instruction register so 9:03 this case 9:04 one zero zero one 9:09 now when the next fetch cycle begins the 9:12 program counter is obviously checked 9:14 and as its contents have been previously 9:16 updated to a new memory location 9:19 and not simply incremented the program 9:22 effectively is able to jump 9:24 around memory 9:28 so having watched this video you should 9:30 be able to answer the following key 9:32 question 9:33 how does a cpu work 9:39 okay so let's um answer the question we 9:41 posed 9:42 earlier what did that program actually 9:48 do 9:50 so this is the first fetch to code 9:53 execute cycle 9:55 and this is the one that we ran through 9:57 in detail earlier 9:58 it effectively loaded the contents of 10:01 the memory 10:02 stored at location location0101 10:05 into the accumulator in other words 10:08 the dna number 3 is moved 10:11 from memory into the cpu 10:18 we then proceed onto the second fetch 10:20 decode execute cycle 10:23 now this one adds the contents of memory 10:27 located at 0 1 1 0 10:30 to the current contents of the 10:32 accumulator 10:34 so in other words the dna number one 10:38 because that's what's stored at address 10:40 zero one one zero 10:43 is added to the number three that was in 10:45 the accumulator 10:46 the results are stored back over the 10:48 accumulator 10:49 so effectively we've done three plus one 10:53 equals four 10:58 the third fetch to code execute cycle 11:00 stores the contents which are in the 11:02 accumulator 11:03 into memory location zero one one one 11:07 and that's because the op code the first 11:09 part of this current instruction 11:10 zero zero one one is the command to 11:13 store when we look it up in the decoder 11:15 unit 11:16 so in other words the result of the 11:17 previous calculation three plus one 11:19 equals four 11:20 is now written back into main memory 11:28 the fourth fetch decode execute cycle 11:30 outputs the contents of the accumulator 11:33 remember they were copied into main 11:34 memory but they're still held in the 11:35 accumulator 11:37 so in this simple abstraction the number 11:40 four is now 11:41 output to the user so they can see the 11:43 result of the calculation 11:49 the fifth and final fetch code execute 11:51 cycle 11:52 brings a halt to the current program 11:58 so this very simple program which has 12:01 five 12:02 fetch decode execute cycles has 12:04 performed the calculation 12:06 three plus one is then stored the result 12:09 in main memory 12:10 and displayed the result four to the 12:12 user 12:13 and in a high-level language this may 12:15 look something very similar to the 12:17 following two lines of code 12:20 sum variable equals num1 plus num2 12:24 print sum to the user 12:27 so you can start to get an appreciation 12:29 here of how the high level code you 12:32 write actually ends up being fetched 12:34 decoded 12:35 and executed inside a processor 12:38 of course your processor is doing 12:40 billions and billions of these 12:42 operations a second 12:43 which when you think about it is really 12:45 very impressive 12:52 [Music] 13:03 you. make 10 questions for a standerd of a levelOw are you? like the new flat in New York. It isn't big, but it's very nice. It's in a tall building. There are lots of kids my age in the building. Oliver is 10 years old, like me. We're in the same class. Oliver has a very big flat. There's a game room with a sofa, a big TV, a computer and lots of games Gota is also 10 years old. But we aren't in the same class. Gota is from Japan He has a cool guitar. It's blue, black and green. Molly is 11 years old. She's in grade 6. She has a very special cat. It sits on the toilet! It's funny to see a cat in the bathroom. Now Molly wants to teach her cat to ride a skateboard )סקייטבורד / لوح التزلج( I'm going to Oliver's flat now. Write to me soon,“There’s No Such Thing as Sound Science” by By Christie Aschwanden was a lead science writer for FiveThirtyEight. FiveThirtyEight, Science, Dec. 6, 2017 Science is being turned against itself. For decades, its twin ideals of transparency and rigor have been weaponized by those who disagree with results produced by the scientific method. Under the Trump administration, that fight has ramped up again. In a move ostensibly meant to reduce conflicts of interest, Environmental Protection Agency Administrator Scott Pruitt has removed a number of scientists from advisory panels and replaced some of them with representatives from industries that the agency regulates. Like many in the Trump administration, Pruitt has also cast doubt on the reliability of climate science. For instance, in an interview with CNBC, Pruitt said that “measuring with precision human activity on the climate is something very challenging to do.” Similarly, Trump’s pick to head NASA, an agency that oversees a large portion the nation’s climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that “global temperatures stopped rising 10 years ago.” Kathleen Hartnett White, Trump’s nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we “need to have more precise explanations of the human role and the natural role” in climate change. The same entreaties crop up again and again: We need to root out conflicts. We need more precise evidence. What makes these arguments so powerful is that they sound quite similar to the points raised by proponents of a very different call for change that’s coming from within science. This other movement strives to produce more robust, reproducible findings. Despite having dissimilar goals, the two forces espouse principles that look surprisingly alike: Science needs to be transparent. Results and methods should be openly shared so that outside researchers can independently reproduce and validate them. The methods used to collect and analyze data should be rigorous and clear, and conclusions must be supported by evidence. These are the arguments underlying an “open science” reform movement that was created, in part, as a response to a “reproducibility crisis” that has struck some fields of science.1 But they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. “Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.” Calls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer. A 1992 Environmental Protection Agency report identified secondhand smoke as a human carcinogen, and Philip Morris responded by launching an initiative to promote what it called “sound science.” In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to “discredit the EPA report,” “prevent states and cities, as well as businesses from passing smoking bans” and “proactively” pass legislation to help their cause. The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions. Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.” The tobacco industry’s brilliant tactic was to turn this baked-in uncertainty against the scientific enterprise itself. While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve. “Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since, said Stanford University science historian Robert Proctor. The sound science push is no longer just Philip Morris sowing doubt about the links between cigarettes and cancer. It’s also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to “install uncertainty” about the link between greenhouse gas emissions and climate change. It’s industry-funded groups’ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didn’t want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPA’s scientists had deemed risky to children. Now comes a move by the Trump administration’s EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?” said Karen Levy, researcher on information science at Cornell University. But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money. Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary “Merchants of Doubt” (based on the book by the same name). Morano’s site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.” Some of these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said. But what’s most telling about the Data Quality Act is how it’s been used, Levy said. A 2004 Washington Post analysis found that in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate. Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3 is another example of what Levy calls a “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration. That might sound perfectly reasonable, and in many cases it is, Goodman said. But sometimes there are good reasons why researchers can’t conform to these rules, like when the data contains confidential or sensitive medical information.4 Critics, which include more than a dozen scientific organizations, argue that, in practice, the rules would prevent many studies from being considered in EPA reviews.5 It might seem like an easy task to sort good science from bad, but in reality it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’” Nosek said. Most scientific controversies aren’t about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement. Michael Carolan, who researches the sociology of technology and scientific knowledge at Colorado State University, wrote in a 2008 paper about why objective knowledge is not enough to resolve environmental controversies. “While these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,” Carolan writes. The dispute over tobacco was never about the science of cigarettes’ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them. Similarly, the debate over climate change isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book “Merchants of Doubt,” science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. “None of this is about the science. All of this is a political debate about the role of government,” she said in the documentary. These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence. For instance, in Europe, many decisions are guided by the precautionary principle — a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations. Both approaches have critics, but the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated? In other words, under what circumstances do we agree to act on a risk? How certain do we need to be that the risk is real, and how many people would need to be at risk, and how costly is it to reduce that risk? Those are moral questions, not scientific ones, and openly discussing and identifying these kinds of judgment calls would lead to a more honest debate. Science matters, and we need to do it as rigorously as possible. But science can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.Of the 7 billion people on Earth roughly 0:02 6 billion own a cell phone which is 0:05 pretty shocking given that only 4 and2 0:07 billion have access to a working toilet 0:09 so how are these popular gadgets 0:11 changing your body and brain If you're 0:13 looking down at your phone right now 0:15 your spine angle is equivalent to that 0:17 of an 8-year-old child sitting on your 0:19 neck which is fairly significant 0:21 considering people spend an average of 0:23 4.7 hours a day looking at their phone 0:26 this combined with the length of time 0:28 spent in front of computers has led to 0:30 an increase in the prevalence of myopia 0:32 or nearsightedness in North America in 0:34 the 1970s about one quar of the 0:36 population had myopia where today nearly 0:39 half do and in some parts of Asia 80 to 0:41 90% of the population is now nearsighted 0:44 and it can be hard to put your phone 0:46 down take for example the game Candy 0:48 Crush as you play the game you achieve 0:50 small goals causing your brain to be 0:52 rewarded with little bursts of dopamine 0:54 and eventually you're rewarded in the 0:56 game with new content this novelty also 0:58 gives little bursts of dopamine and 1:00 together create what is known as a 1:01 compulsion Loop which just happens to be 1:04 the same Loop responsible for the 1:05 behaviors associated with nicotine or 1:07 cocaine our brains are hardwired to make 1:10 us novelty seeking and this is why apps 1:12 on our phones are designed to constantly 1:14 provide us with new content making them 1:16 hard to put down as a result 93% of 1:19 young people aged 18 to 29 report using 1:21 their smartphone as a tool to avoid 1:23 boredom as opposed to other activities 1:26 like reading a book or engaging with 1:27 people around them this has created a 1:29 new term nomophobia the fear or anxiety 1:32 of being without your phone we also see 1:35 a change in brain patterns Alpha rhythms 1:37 are commonly associated with wakeful 1:39 relaxation like when your mind wanders 1:41 off whereas gamma waves are associated 1:44 with conscious attentiveness and 1:46 experiments have shown that when a cell 1:47 phone is transmitting say during a phone 1:49 call the power of these Alpha Waves is 1:52 significantly boosted meaning phone 1:54 Transmissions can literally change the 1:56 way your brain functions your smartphone 1:58 can also disrupt your sleep the screen 2:00 emits a blue light which has been shown 2:02 to alter our circadian rhythms 2:03 diminishing the time spent in deep Sleep 2:06 which is linked to the development of 2:07 diabetes cancer and obesity Studies have 2:10 shown that people who read on their 2:11 smartphone at night have a harder time 2:13 falling asleep and produce less 2:15 melatonin a hormone responsible for the 2:17 regulation of sleep wake Cycles Harvard 2:20 medical school advises the last 2 to 3 2:22 hours before bed be technology free so 2:24 pick up a book before bed instead of 2:26 course smartphones also completely 2:28 change our ability to access information 2:30 most notably in poor and minority 2:32 populations 7% of Americans are entirely 2:35 dependent on smartphones for their 2:37 access to the internet a 2014 study 2:40 found that the majority of smartphone 2:41 owners use their phone for online 2:43 banking to look up medical information 2:45 and searching for jobs so while phones 2:47 are in no way exclusively bad and have 2:50 been part of a positive change in the 2:51 world there's no denying that they are 2:53 changing us but many successful people 2:56 have now decided to take smartphone 2:58 vacations in order to increase 3:00 productivity in our new ASAP thought 3:01 video we break down the top six reasons 3:04 you should take a smartphone vacation 3:06 and how it could benefit your life right 3:08 now and subscribe for more weekly 3:09 science videos