Introduction to Geographic Science
1.1 Science as a Way of Knowing
The Nature of Science
Science can be defined as the systematic examination of the natural world’s structure and functioning, including its physical and biological attributes. Science is also a rapidly expanding body of knowledge, whose ultimate goal is to discover the most straightforward general principles that can explain the enormous complexity of nature. These principles can be used to gain insights into the natural world and make predictions about future change.
Science is a relatively new way of learning about natural phenomena, having largely replaced the influences of less objective methods and world views. The primary alternatives to science are belief systems that are influential in all cultures, including those based on religion, morality, and aesthetics. These belief systems are primarily directed toward different ends than science, such as finding meaning that transcends mere existence, learning how people ought to behave, and understanding the value of artistic expression. (Environmental Science – Simple Book Publishing, n.d.)
Modern science evolved from a way of learning called natural philosophy, which was developed by classical Greeks and was concerned with the rational investigation of existence, knowledge, and phenomena. Compared with modern science, however, studies in natural philosophy used unsophisticated technologies and methods and were not mainly quantitative, sometimes involving only the application of logic.
Inductive and Deductive Logic
The English philosopher Francis Bacon (1561-1626) was highly influential in the development of modern science. Bacon was not an actual practitioner of science but was a strong proponent of its emerging methodologies. He promoted the application of inductive logic, in which conclusions are developed from the accumulating evidence of experience and the results of experiments. Inductive logic can lead to unifying explanations based on large bodies of data and observations of phenomena. Consider the following illustration of inductive logic, applied to an environmental topic:
- Observation 1: Marine mammals off the Atlantic coast have significant DDT residues and other chlorinated hydrocarbons in their fat and other body tissues.
- Observation 2: So do marine mammals off British Columbia.
- Observation 3: As do those in the Arctic Ocean, although in lower concentrations.
Inductive conclusion: There is widespread contamination of marine mammals with chlorinated hydrocarbons. Further research may demonstrate that contamination is a global phenomenon. This suggests a potentially crucial environmental problem. (Environmental Science – Simple Book Publishing, n.d.)
In contrast, deductive logic involves making one or more initial assumptions and then drawing logical conclusions from those premises. Consequently, the truth of a deductive conclusion depends on the veracity of the original assumptions. If those assumptions are based on false information or supernatural beliefs, then any deduced conclusions are likely to be wrong. Consider the following illustration of deductive logic:
- Assumption 1: TCDD, an extremely toxic chemical in the dioxin family, is poisonous when present in even the smallest concentrations in food and water – even a single molecule can cause toxicity.
- Assumption 2: Exposure to anything poisonous in even the smallest concentrations is unsafe.
- Assumption 3: No unsafe exposure should be allowed.
Deductive conclusion 1: No exposure to TCDD is safe.
Deductive conclusion 2: No emissions of TCDD should be allowed.
The two conclusions are consistent with the original assumptions. However, there is disagreement among highly qualified scientists about those assumptions. Many toxicologists believe that exposure to TCDD (and any other potentially toxic chemicals) must exceed a threshold of biological tolerance before poisoning results. In contrast, other scientists believe that even the smallest exposure to TCDD carries some degree of toxic risk. Thus, the strength of deductive logic depends on the acceptance and truth of the original assumptions from which its conclusions flow.
In general, inductive logic plays a much stronger role in modern science than does deductive logic. In both cases, however, the usefulness of any conclusions depends significantly on the accuracy of any observations and other data on which they were based. Poor data may lead to an inaccurate conclusion through the application of inductive logic, as will inappropriate assumptions in deductive logic. (Environmental Science – Simple Book Publishing, n.d.)
Scientists seek to understand the fundamental principles that explain natural patterns and processes. Science is more than just a body of knowledge; science provides a means to evaluate and create new knowledge without bias. Scientists use objective evidence over subjective evidence to reach sound and logical conclusions.
Objective observation is without personal bias and the same by all individuals. Humans are biased by nature, so they cannot be completely objective; the goal is to be unbiased. A subjective observation is based on a person’s feelings and beliefs and is unique to that individual.
Another way scientists avoid bias is by using quantitative over qualitative measurements whenever possible. Quantitative measurement is expressed with a specific numerical value. Qualitative observations are general or relative descriptions. For example, describing a rock as red or heavy is a qualitative observation. Determining a rock’s color by measuring wavelengths of reflected light or its density by measuring the proportions of minerals it contains is quantitative. Numerical values are more precise than general descriptions, and they can be analyzed using statistical calculations. This is why quantitative measurements are much more useful to scientists than qualitative observations.
It is challenging to establish truth in science because all scientific claims are falsifiable, which means any initial hypothesis may be tested and proven false. Only after exhaustively eliminating false results, competing ideas, and possible variations does a hypothesis become regarded as a reliable scientific theory. This meticulous scrutiny reveals weaknesses or flaws in a hypothesis and is the strength that supports all scientific ideas and procedures. Proving current ideas are wrong has been the driving force behind many scientific careers.
Falsifiability separates science from pseudoscience. Scientists are wary of explanations of natural phenomena that discourage or avoid falsifiability. An explanation that cannot be tested or does not meet scientific standards is not considered science, but pseudoscience. Pseudoscience is a collection of ideas that may appear scientific but does not use the scientific method. Astrology is an example of pseudoscience. It is a belief system that attributes the movement of celestial bodies to influencing human behavior. Astrologers rely on celestial observations, but their conclusions are not based on experimental evidence, and their statements are not falsifiable. This is not to be confused with astronomy, which is the scientific study of celestial bodies and the cosmos.
Science is also a social process. Scientists share their ideas with peers at conferences, seeking guidance and feedback. Research papers and data submitted for publication are rigorously reviewed by qualified peers, scientists who are experts in the same field. The scientific review process aims to weed out misinformation, invalid research results, and wild speculation. Thus, it is slow, cautious, and conservative. Scientists tend to wait until a hypothesis is supported by an overwhelming amount of evidence from many independent researchers before accepting it as a scientific theory.
Goals of Science
The broad goals of science are to understand natural phenomena and explain how they may be changing over time. To achieve those goals, scientists undertake investigations based on information, inferences, and conclusions developed through a systematic application of logic, usually of the inductive sort. As such, scientists carefully observe natural phenomena and conduct experiments.
A higher goal of scientific research is to formulate laws that describe the workings of the universe in general terms. Universal laws, along with theories and hypotheses, are used to understand and explain natural phenomena. However, many natural phenomena are incredibly complicated and may never be fully understood in terms of physical laws. This is particularly true of the ways that organisms and ecosystems are organized and function.
Scientific investigations may be pure or applied. Pure science is driven by intellectual curiosity – it is the unfettered search for knowledge and understanding, without regard for its usefulness in human welfare. Applied science is more goal-oriented and deals with practical difficulties and problems of one sort or another. Applied science might examine how to improve technology, advance the management of natural resources, or reduce pollution or other environmental damages associated with human activities. (Environmental Science – Simple Book Publishing, n.d.)
Facts, Hypotheses, and Experiments
A fact is an event or thing known to have happened, to exist, and to be true. Facts are based on experience and scientific evidence. In contrast, a hypothesis is a proposed explanation for the occurrence of a phenomenon. Scientists formulate hypotheses as statements and then test them through experiments and other forms of research. Hypotheses are developed using logic, inference, and mathematical arguments in order to explain observed phenomena. However, it must always be possible to refute a scientific hypothesis. Thus, the hypothesis that “cats are so intelligent that they prevent humans from discovering it” cannot be logically refuted, and so it is not a scientific hypothesis.
A theory is a broader conception that refers to a set of explanations, rules, and laws. These are supported by a large body of observational and experimental evidence, all leading to robust conclusions. The following are some of the most famous theories in science:
- the theory of gravitation, first proposed by Isaac Newton (1642-1727)
- the theory of evolution by natural selection published simultaneously in 1858 by two English naturalists, Charles Darwin (1809-1882) and Alfred Russel Wallace (1823-1913)
- the theory of relativity, identified by the German-Swiss physicist, Albert Einstein (1879-1955)
Large bodies of evidence strongly support celebrated theories like these, and they will likely persist for a long time. However, we cannot say that these (or any other) theories are known with certainty to be exact – some future experiments may yet falsify even these famous theories. (Environmental Science – Simple Book Publishing, n.d.)
The scientific method begins with identifying a question involving the structure or function of the natural world, which is usually developed using inductive logic. The question is interpreted in terms of existing theory, and specific hypotheses are formulated to explain the character and causes of the natural phenomenon. The research might involve observations made in nature or carefully controlled experiments, and the results usually give scientists reasons to reject hypotheses rather than accept them. Most hypotheses are rejected because their predictions are not borne out during research. Any viable hypotheses are further examined through additional research, primarily involving experiments designed to disprove their predictions. Once a large body of evidence accumulates in support of a hypothesis, it can corroborate the original theory.
The scientific method is only to investigate questions that can be critically examined through observation and experiment. Consequently, science cannot resolve value-laden questions, such as the meaning of life, good versus evil, or the existence and qualities of God or any other supernatural being or force.
An experiment is a test or investigation designed to provide evidence in support of, or preferably against, a hypothesis. A natural experiment is conducted by observing actual variations of phenomena in nature, and then developing explanations by analyzing possible causal mechanisms. A manipulative experiment involves the deliberate alteration of factors that are hypothesized to influence phenomena. The manipulations are carefully planned and controlled to determine whether predicted responses will occur, thereby uncovering causal relationships.
By far, the most useful working hypotheses in scientific research are designed to disprove rather than support. A null hypothesis is a specific testable investigation that denies something implied by the central hypothesis being studied. Unless null hypotheses are eliminated based on contrary evidence, we cannot be confident of the central hypothesis. (Environmental Science – Simple Book Publishing, n.d.)
This is an essential aspect of scientific investigation. For instance, a particular hypothesis might be supported by many confirming experiments or observations. However, this does not serve to “prove” the hypothesis; instead, it only supports its conditional acceptance. As soon as a clearly defined hypothesis is falsified by an appropriately designed and well-conducted experiment, it is disproved for all time. This is why experiments designed to disprove hypotheses are a vital aspect of the scientific method.
Revolutionary advances in understanding may occur when an important hypothesis or theory is rejected through discoveries of science. For instance, once it was discovered that the Earth is not flat, it became possible to sail beyond the visible horizon confidently without fear of falling off the edge of the world. Another example involved the discovery by Copernicus that the planets of our solar system revolve around the Sun. The related concept that the Sun is an ordinary star among many – these revolutionary ideas replaced the previously dominant one that the planets, Sun, and stars all revolved around the Earth.
Thomas Kuhn (1922-1995) was a philosopher of science who emphasized the critical role of “scientific revolutions” in achieving significant advances in our understanding of the natural world. In essence, Kuhn (1996) said that a scientific revolution occurs when a well-established theory is rigorously tested and then collapses under the accumulating weight of new facts and observations that cannot be explained. This renders the original theory obsolete, to be replaced by a new, more informed paradigm (i.e., a set of assumptions, concepts, practices, and values that constitutes a way of viewing reality and is shared by an intellectual community).
A variable is a factor that is believed to influence a natural phenomenon. For example, a scientist might hypothesize that the productivity of a wheat crop is potentially limited by such variables as the availability of water or nutrients such as nitrogen and phosphorus. Some of the most powerful scientific experiments involve manipulating key (or controlling) variables and comparing the results of those treatments with a control that was not manipulated. In the example just described, the specific variable that controls wheat productivity could be identified by conducting an experiment in which test populations are provided with varying amounts of water, nitrogen, and phosphorus, alone and in combination, and then comparing the results with a non-manipulated control.
In some respects, however, the explanation of the scientific method offered above is a bit uncritical. It perhaps suggests a too-orderly progression in terms of logical, objective experimentation and comparison of alternative hypotheses. These are, in fact, essential components of the scientific method. Nevertheless, it is essential to understand that scientists’ insights and personal biases are also significant in the conduct and progress of science. In most cases, scientists design research that they think will “work” to yield useful results and contribute to the orderly advancement of knowledge in their field. Karl Popper (1902-1994), a European philosopher, noted that scientists tend to use their “imaginative preconception” of the workings of the natural world to design experiments based on their informed insights. This means that competent scientists must be more than knowledgeable and technically skilled – they should also be capable of a degree of insightful creativity when forming their ideas, hypotheses, and research. (Environmental Science – Simple Book Publishing, n.d.)
Much scientific investigation involves the collection of observations by measuring phenomena in the natural world. Another essential aspect of science involves making predictions values of variables. Such projections require a degree of understanding of the relationships among variables, influencing factors, and recent patterns of change. However, many kinds of scientific information and predictions are subject to inaccuracy. This occurs because measured data are often approximations of the true values of phenomena, and predictions are rarely fulfilled precisely. The accuracy of observations and predictions is influenced by various factors, primarily those described in the following sections. (Environmental Science – Simple Book Publishing, n.d.)
A few phenomena are considered to have a universal character and are consistent wherever and whenever they are accurately measured. One of the best examples of such a universal constant is the speed of light, which always has a value of 2.998 × 108 meters per second, regardless of where it is measured or of the speed of the body from which the light is emitted. Similarly, certain relationships describing transformations of energy and matter, known as the laws of thermodynamics, always give reliable predictions.
However, most natural phenomena are not consistent – depending on circumstances, there are exceptions to general predictions about them. This circumstance is particularly true of biology and ecology, related fields of science in which almost all general predictions have exceptions. Laws or unifying principles of biology or ecology have not yet been discovered, compared to the several esteemed laws and 11 universal constants of physics. Thus, biologists and ecologists have great difficulties making accurate predictions about the responses of organisms and ecosystems to environmental change.
Many natural phenomena are highly variable in space and time. This is true of physical and chemical variables as well as biological and ecological ones. Within a forest, the amount of sunlight reaching the ground varies significantly with time, depending on the hour of the day and the season of the year. It varies spatially, depending on the density of foliage over any place where sunlight is being measured. Similarly, the density of a particular species of fish within a river typically varies in response to changes in habitat conditions and other influences. Most fish populations also vary over time, mainly migratory species such as salmon. In environmental science, replicated (or independently repeated) measurements and statistical analyses are used to measure and account for these temporal and spatial variations.
Accuracy and Precision
Accuracy refers to the degree to which a measurement or observation reflects the actual or true value of the subject. For example, the insecticide DDT and the metal mercury are potentially toxic chemicals that occur in trace concentrations in all organisms, but their small residues are challenging to analyze chemically. Some of the analytical methods used to determine the concentrations of DDT and mercury are more accurate than others and provide relatively useful and reliable data compared with less accurate methods. Analytical data are usually approximations of the real values – rigorous accuracy is rarely attainable.
Precision is related to the degree of repeatability of a measurement or observation. For example, suppose that the actual number of caribou in a migrating herd is 10,246 animals. A wildlife ecologist might estimate that there were about 10,000 animals in that herd, which for practical purposes is a reasonably accurate reckoning of the actual number of caribou. If other ecologists also independently estimate the herd’s size at about 10,000 caribou, there is a reasonable degree of precision among the values. If, however, some systematic bias existed in the methodology used to count the herd, giving consistent estimates of 15,000 animals (remember, the actual population is 10 246 caribou), these estimates would be considered precise, but not particularly accurate.
Precision is also related to the number of digits with which data are reported. If you were using a flexible tape to measure the lengths of 10 large, wriggly snakes, you would probably measure the reptiles only to the nearest centimeter. The strength and squirminess of the animals make more precise measurements impossible. The reported average length of the ten snakes should reflect the original measurements and might be given 204 cm and not a value such as 203.8759 cm. The latter number might be displayed as a digital average by a calculator or computer, but it is unrealistically precise.
Significant figures are related to accuracy and precision and can be defined as the number of digits used to report data from analyses or calculations. Examples most easily understand significant figures. The number 179 has three significant figures, as does the number of 0.0849 and 0.000794 (the zeros preceding the significant integers do not count). However, the number 195,000,000 has nine significant figures (the zeros following are meaningful), although the number 195 × 106 has only three significant figures.
It is rarely useful to report environmental or ecological data to more than 2-4 significant figures. This is because any more would generally exceed the accuracy and precision of the methodology used in the estimation and would be unrealistic. For example, the United States approximate population in 2020 was 330 million people, (or 330 × 106; both of these notations have three significant figures). However, the population should not be reported as 333,000,000, which implies an unrealistic accuracy and precision of eight significant figures.
A Need for Scepticism
Environmental science is filled with many examples of uncertainty – in present values and future changes of environmental variables and predictions of biological and ecological responses to those changes. To some degree, the difficulties associated with scientific uncertainty can be mitigated by developing improved methods and technologies for analysis and modeling and examining changes occurring in different parts of the world. The latter approach enhances our understanding by providing convergent evidence about the occurrence and causes of natural phenomena.
However, scientific information and understanding will always be subject to some degree of uncertainty. Therefore, predictions will always be inaccurate to some extent, and this uncertainty must be considered when trying to understand and deal with the causes and consequences of environmental changes. As such, all information and predictions in environmental science must be critically interpreted with uncertainty in mind. This should be done whenever one is learning about an environmental issue, whether it involves listening to a speaker in a classroom, at a conference, or on video, or when reading an article in a newspaper, textbook, website, or scientific journal. Because of the uncertainty of many predictions in science, and particularly in the environmental realm, a certain amount of skepticism and critical analysis is always useful.
Environmental issues are acutely important to the welfare of people and other species. Science and its methods allow for a critical and objective identification of crucial issues, the investigation of their causes, and a degree of understanding of the consequences of environmental change. Scientific information influences decision making about environmental issues, including whether to pursue expensive strategies to avoid further, but often uncertain, damage.
However, scientific information is only one consideration for decision-makers, who are also concerned with the economic, cultural, and political contexts of environmental problems. When deciding how to deal with the causes and consequences of environmental changes, decision-makers may give greater weight to non-scientific (social and economic) considerations than scientific ones, especially when there is uncertainty about the latter. The most critical decisions about environmental issues are made by politicians and senior bureaucrats in government, or by private managers, rather than by environmental scientists. Decision-makers typically worry about the short-term implications of their decisions on their chances for re-election or continued employment, and on the economic activity of a company or society at large, as much as they do about environmental damage. (Environmental Science – Simple Book Publishing, n.d.) That is why the United States struggled so much with the COVID-19 pandemic. On one end of the response, was a focus on health science. On the other were economists worried about collapsing the economy. It was ultimately up to politicians to make the decision on how much the nation should “lockdown” and how much the nation needed to stay economically “open.”
Science Denial and Evaluating Sources
Introductory science courses usually deal with accepted scientific theory and do not include opposing ideas, even though these alternate ideas may be credible. This makes it easier for students to understand complex material. Advanced students will encounter more controversies as they continue to study their discipline.
Some groups argue that some established scientific theories are wrong, not based on their scientific merit but the group’s ideology. This section focuses on how to identify evidence-based information and differentiate it from pseudoscience.
Science denial happens when people argue that established scientific theories are wrong, not based on scientific merit but rather on subjective ideology – such as for social, political, or economic reasons. Organizations and people use science denial as a rhetorical argument against issues or ideas they oppose. Three examples of science denial versus science are:
- Teaching evolution in public schools
- Linking tobacco smoke to cancer
- Linking human activity to climate change.
Among these, denial of climate change is strongly connected with geography. A climate denier denies explicitly or doubts the objective conclusions of geologists and climate scientists. Science denial generally uses three false arguments. The first argument tries to undermine the scientific conclusion’s credibility by claiming the research methods are flawed, or the theory is not universally accepted—the science is unsettled. The notion that scientific ideas are not absolute creates doubt for non-scientists; however, a lack of universal truths should not be confused with scientific uncertainty. Because science is based on falsifiability, scientists avoid claiming universal truths and use language that conveys uncertainty. This allows scientific ideas to change and evolve as more evidence is uncovered.
The second argument claims the researchers are not objective and motivated by ideology or economic agenda. This is an ad hominem argument in which a person’s character is attacked instead of the merit of their argument. They claim results have been manipulated so researchers can justify asking for more funding. They claim that because a federal grant funds the researchers, they are using their results to lobby for expanded government regulation.
The third argument is to demand a balanced view, equal time in media coverage, and educational curricula to engender the false illusion of two equally valid arguments. Science deniers frequently demand equal coverage of their proposals, even when there is little scientific evidence supporting their ideology. For example, science deniers might demand religious explanations to be taught as an alternative to the well-established theory of evolution. Alternatively, all possible causes of climate change are discussed as equally probable, regardless of the body of evidence. Conclusions derived using the scientific method should not be confused with those based on ideologies.
Furthermore, conclusions about nature derived from ideologies have no place in science research and education. For example, it would be inappropriate to teach the flat earth model in modern geography or earth science courses because this idea has been disproved by the scientific method. Unfortunately, widespread scientific illiteracy allows these arguments to be used to suppress scientific knowledge and spread misinformation.
The formation of new conclusions based on the scientific method is the only way to change scientific conclusions. We would not teach Flat Earth geology and plate tectonics because Flat Earthers do not follow the scientific method. The fact that scientists avoid universal truths and change their ideas as more evidence is uncovered should not be seen as meaning that the science is unsettled. Because of widespread scientific illiteracy, these arguments are used by those who wish to suppress science and misinform the general public.
In a classic case of science denial, beginning in the 1960s and for the next three decades, the tobacco industry and their scientists used rhetorical arguments to deny a connection between tobacco usage and cancer. Once it became clear scientific studies overwhelmingly found that using tobacco dramatically increased a person’s likelihood of getting cancer, their next strategy was to create a sense of doubt about the science. The tobacco industry suggested the results were not yet fully understood, and more study was needed. They used this doubt to lobby for delaying legislative action to warn consumers of the potential health hazards. This tactic is currently employed by those who deny the significance of human involvement in climate change.
Evaluating Sources of Information
In the age of the internet, information is plentiful. Geologists, scientists, or anyone exploring scientific inquiry must discern valid sources of information from pseudoscience and misinformation. This evaluation is especially critical in scientific research because scientific knowledge is respected for its reliability. Textbooks such as this one can aid this complex and crucial task. At its roots, quality information comes from the scientific method, beginning with the empirical thinking of Aristotle. The application of the scientific method helps produce unbiased results. A valid inference or interpretation is based on objective evidence or data. Credible data and inferences are clearly labeled, separated, and differentiated. Anyone looking over the data can understand how the author’s conclusion was derived or come to an alternative conclusion.
Scientific procedures are clearly defined, so the investigation can be replicated to confirm the original results or expanded further to produce new results. These measures make a scientific inquiry valid and its use as a source reputable. Of course, substandard work occasionally slips through, and retractions are published from time to time. An infamous article linking the MMR vaccine to autism appeared in the highly reputable journal Lancet in 1998. Journalists discovered that the author had multiple conflicts of interest and fabricated data, and the article was retracted in 2010.
In addition to methodology, data, and results, the authors of a study should be investigated. When looking into any research, the author(s) should be investigated. An author’s credibility is based on multiple factors, such as having a degree in a relevant topic or being funded from an unbiased source.
The same rigor should be applied to evaluating the publisher, ensuring the results reported come from an unbiased process. The publisher should be easy to discover. Good publishers will show the latest papers in the journal and make their contact information and identification clear. Reputable journals show their peer review style. Some journals are predatory, where they use unexplained and unnecessary fees to submit and access journals. Reputable journals have recognizable editorial boards. Often, a reputable journal will associate with a trade, association, or recognized open-source initiative.
One of the hallmarks of scientific research is peer review. Research should be transparent to peer review. This allows the scientific community to reproduce experimental results, correct and retract errors, and validate theories. This allows the reproduction of experimental results, corrections of errors, and proper justification of the research to experts.
Citation is imperative to avoid plagiarism, and also allows readers to investigate an author’s line of thought and conclusions. When reading scientific works, it is essential to confirm that the citations are from reputable scientific research. Most often, scientific citations are used to reference paraphrasing rather than quotes. The number of times a work is cited is said to measure the investigation has within the scientific community, although this technique is inherently biased. (Environmental Science – Simple Book Publishing, n.d.)
Critical Evaluation of an Overload of Information
More so than any previous society, we live today in a world of accessible and abundant information. It has become remarkably easy for people to communicate with others over vast distances, turning the world into a “global village” (a phrase coined by Marshall McLuhan (1911-1980), a Canadian philosopher, to describe the phenomenon of universal networking). Technologies have facilitated this global connectedness for transferring ideas and knowledge – mainly electronic communication devices, such as radio, television, computers, and their networks. Today, these technologies compress space and time to achieve a virtually instantaneous communication. So much information is now available that the situation is often referred to as an “information overload” that must be analyzed critically. Critical analysis is the process of sorting information and making scientific inquiries about data. Involved in all aspects of the scientific process, critical analysis scrutinizes information, and research by posing sensible questions such as the following:
- Is the information derived from a scientific framework consisting of a hypothesis that has been developed and tested within the context of an existing body of knowledge and theory in the field?
- Were the methodologies used likely to provide data that are objective, accurate, and precise? Were the data analyzed using statistical methods appropriate to the data structure and the questions being asked?
- Were the results of the research compared with other pertinent work that has been previously published? Were key similarities and differences discussed and a conclusion deduced about what the new work reveals about the issue being investigated?
- Is the information based on research published in a refereed journal that requires highly qualified reviewers in the subject area to scrutinize the work, followed by an editorial decision about whether it warrants publication?
- If the analysis of an issue was based on incomplete or possibly inaccurate information, was a precautionary approach used to accommodate the uncertainty inherent in the recommendations? All users of published research have an obligation to critically evaluate what they are reading in these ways in order to decide whether the theory is appropriate, the methodologies reliable, and the conclusions sufficiently robust. Because so many environmental issues are controversial, with data and information presented on both sides of the debate, people need to formulate objectively critical judgments. Thus, people need a high degree of environmental literacy – an informed understanding of the causes and consequences of environmental damage. Being able to analyze information critically is a key personal benefit of studying environmental science.