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For example, I have never get closed to a whale. The only source I have is research from who has get close to it. If I read their research and find a new thing, would my "discovery" be scientific? If yes, can you give some example of such research?
There is a related question in Philosophy SE: “Dinosaurs did exist once”. Is it knowledge or is it only justified belief? However this question is more about the knowledge directly produced by field researchers, while in this question I focus more on researchers who can only access secondary research. Plus that dinosaurs extincted, so in a sense I and a paleontologist are equal: neither of us can have direct experience to a living dinosaur. But whales are still living, and that equality is gone. So maybe the threshold for scientific research between a living organism and an extinct one is different?
See also: Is it possible to have a scientific review of a method if the author doesn't have direct experience of it?
Some may say this question is opinion-based. But there are good subjective questions as well.
It depends on one's field - whether what you study actually requires first-hand knowledge of the experimental subject and the methods of dealing with or not. Moreover, one could invert the question and ask, whether a field, based solely on the knowledge of the experimental subject, can be considered science?
In some sciences, such as physics, there is traditional division into experimentalists and theoreticians - the former are people who actually work in a lab, but who limit themselves to very basic statistical analysis of the phenomena observed. The latter are providing deeper, model-based, analysis of the data and description of the phenomena. Very often their work is not tied to any particular experiment, bordering on very abstract math. Looking at the list of the Nobel prize winners in physics one can easily convince oneself that this work is no less valuable than the experimental work.
Similar division exists in other fields, e.g., one can freely talk about quantum/theoretical/computational chemistry.
Computational biology, bioinformatics, biostatistics, epidemiology, population genetics
Although biology is relatively young science, the times when it was frowned upon by physicists as mere stamp collecting have long been gone: evolutionary theory and epidemiology have been put on a firm mathematical footing, and the explosion of genomic data in the last couple of decades has ushered in the professions of bioinformatician and computational biologist - all complete with designated job descriptions and advanced university programs. Less noticeable, but no else widespread is the observation using modern technology - such as video and sound recording - every conference features a few talks like this, related to swarms of insects, flocks of birds, or behavior of whales (incidentally, whales have been extensively studied in connection to tracing enemy submarines. The analysis of the data is often done very far away from the sea.)
All science is either physics or stamp collecting. - a quote attributed to Ernest Rutherford, but likely of even earlier origin.
A student’s guide to undergraduate research
I have thoroughly enjoyed my experience working in a materials-chemistry laboratory at Northwestern University in Evanston, Illinois, for the past two years. Being able to mix an undergraduate education with original research in a proper laboratory has been a fantastic opportunity.
Three months into my first year of college, I contacted a professor about working part-time in their lab, and I was fortunate enough to be recruited. My project resulted in me being named as co-first-author on a paper 1 , and the group feels like family. The experience helped to prepare me for graduate school and made me realize which aspects of science I am passionate about.
However, I also struggled to cope with failure, with balancing my undergraduate classes with research responsibilities and with the internal pressure I imposed on myself to make the project work. Looking back, I wish someone had told me what to expect and offered advice on how to get the most from my research. Because there are few guides for undergraduate researchers, here is some advice based on my experiences.
The science of ghosts
People love scary, spooky stories of spectral phantoms. While there’s no science to support the existence of ghosts, research does provide plenty of explanations for why we might genuinely sense a supernatural presence.
October 31, 2019 at 5:45 am
A shadowy figure rushed through the door. “It had a skeletal body, surrounded by a white, blurry aura,” recalls Dom. The figure hovered and didn’t seem to have a face. Dom, who prefers to use only his first name, had been fast asleep. Just 15 at the time, he panicked and closed his eyes. “I only saw it for a second,” he recalls. Now, he’s a young adult who lives in the United Kingdom. But he still remembers the experience vividly.
Was the figure a ghost? In the mythology of the United States and many other Western cultures, a ghost or spirit is a dead person who interacts with the living world. In stories, a ghost may whisper or groan, cause things to move or fall, mess with electronics — even appear as a shadowy, blurry or see-through figure.“I’d been hearing noises on the ceiling at the same time each night,” says Clare Llewellyn-Bailey, who is now a student at the University of South Wales. One night, a big thud prompted her to grab her camera. This was the first picture she took. Other photos she took on that and later nights showed nothing unusual. Does this story make it seem like ghosts exist? Or is the glowing figure a flash of light that the camera accidentally captured? Clare Llewellyn-Bailey
Ghost stories are lots of fun, especially on Halloween. But some people believe that ghosts are real. Chapman University in Orange, Calif., runs a yearly survey that asks people in the United States about their beliefs in the paranormal. In 2018, 58 percent of those polled agreed with the statement, “Places can be haunted by spirits.” And almost one in five people from the United States said in another survey, conducted by the Pew Research Center in Washington, D.C., that they’ve seen or been in the presence of a ghost.
On ghost-hunting TV shows, people use scientific equipment to attempt to record or measure spirit activity. And numerous creepy photos and videos make it seem like ghosts exist. However, none of these offer good evidence of ghosts. Some are hoaxes, created to fool people. The rest only prove that equipment sometimes can capture noise, images or other signals that people don’t expect. Ghosts are the least likely of many possible explanations.
Not only are ghosts supposed to be able to do things that science says are impossible, such as turn invisible or pass through walls, but also scientists using reliable research methods have found zero evidence that ghosts exist. What scientists have discovered, though, are lots of reasons why people might feel they have had ghostly encounters.
What their data show is that you can’t always trust your eyes, ears or brain.
‘Dreaming with your eyes open’
Dom began having unusual experiences when he was eight or nine. He would wake up unable to move. He researched what was happening to him. And he learned that science had a name for it: sleep paralysis. This condition leaves someone feeling awake but paralyzed, or frozen in place. He can’t move or speak or breathe deeply. He may also see, hear or feel figures or creatures that aren’t really there. This is called a hallucination (Huh-LU-sih-NA-shun).
Sometimes, Dom hallucinated that creatures were walking or sitting on him. Other times, he heard screaming. He only saw something that one time, as a teenager.
Sleep paralysis happens when the brain messes up the process of falling asleep or waking. Usually, you only start dreaming after you’re fully asleep. And you stop dreaming before you waken.
While dreaming in REM sleep, the body is usually paralyzed, unable to act out the motions the dreamer might see herself performing. Sometimes, a person wakes up while still in this state. That can be terrifying. sezer66/iStock/Getty Images Plus
Sleep paralysis “is like dreaming with your eyes open,” explains Baland Jalal. A neuroscientist, he studies sleep paralysis at the University of Cambridge in England. He says this is why it happens: Our most vivid, lifelike dreams happen during a certain stage of sleep. It’s called rapid eye movement, or REM, sleep. In this stage, your eyes dart around under their closed lids. Though your eyes move, the rest of your body can’t. It’s paralyzed. Most likely, that’s to prevent people from acting out their dreams. (That could get dangerous! Imagine flailing your arms and legs as you play dream basketball, only to whack your knuckles on the wall and tumble to the floor.)
Your brain usually turns this paralysis off before you wake up. But in sleep paralysis, you wake up while it’s still happening.
Faces in the clouds
You don’t have to experience sleep paralysis to sense things that aren’t there. Have you ever felt your phone buzz, then checked to find there was no message? Have you heard someone calling your name when no one was there? Have you ever seen a face or figure in a dark shadow?
These misperceptions also count as hallucinations, says David Smailes. He’s a psychologist in England at Northumbria University in Newcastle-upon-Tyne. He thinks that just about everyone has such experiences. Most of us just ignore them. But some may turn to ghosts as the explanation.
Scientists Say: Pareidolia
We’re used to our senses giving us accurate information about the world. So when experiencing a hallucination, our first instinct is usually to believe it. If you see or feel the presence of a loved one who died — and trust your perceptions — then “it has to be a ghost,” says Smailes. That’s easier to believe than the idea that your brain is lying to you.
The brain has a tough job. Information from the world bombards you as a mixed-up jumble of signals. The eyes take in color. The ears take in sounds. The skin senses pressure. The brain works to make sense of this mess. This is called bottom-up processing. And the brain is very good at it. It’s so good that it sometimes finds meaning in meaningless things. This is known as pareidolia (Pear-eye-DOH-lee-ah). You experience it whenever you stare at clouds and see rabbits, ships or faces. Or gaze at the moon and see a face.
Can you see the three faces in this image? Most people can easily find them. Most people also realize that they aren’t real faces. They are an example of pareidolia. Stuart Caie/Flickr (CC BY 2.0)
The brain also does top-down processing. It adds information to your perception of the world. Most of the time, there is way too much stuff coming in through the senses. Paying attention to all of it would overwhelm you. So your brain picks out the most important parts. And then it fills in the rest. “The vast majority of perception is the brain filling in the gaps,” explains Smailes.
What you see right now isn’t what’s actually out there in the world. It’s a picture your brain painted for you based on signals captured by your eyes. The same goes for your other senses. Most of the time, this picture is accurate. But sometimes, the brain adds things that aren’t there.
For example, when you mishear the lyrics in a song, your brain filled in a meaning that wasn’t there. (And it will most likely continue to mishear those words even after you learn the right ones.)
This is very similar to what happens when so-called ghost hunters capture sounds that they say are ghosts speaking. (They call this electronic voice phenomenon, or EVP.) The recording is probably just random noise. If you listen to it without knowing what was supposedly said, you probably won’t hear words. But when you know what the words are supposed to be, you might now find that you can discern them easily.
Your brain may also add faces to images of random noise. Research has shown that patients who experience visual hallucinations are more likely than normal to experience pareidolia — see faces in random shapes, for instance.
In one 2018 study, Smailes’ team tested whether this might also be true for healthy people. They recruited 82 volunteers. First, the researchers asked a series of questions about how often these volunteers had hallucination-like experiences. For example, “Do you ever see things other people cannot?” and “Do you ever think that everyday things look abnormal to you?”
This is one of the images that Smailes’ study participants looked at. This one contains a difficult-to-detect face. Do you see it? D. Smailes
Next, the participants looked at 60 images of black and white noise. For a very brief moment, another image would flash in the center of the noise. Twelve of these images were faces that were easy to see. Another 24 were hard-to-see faces. And 24 more images showed no faces at all — just more noise. The volunteers had to report whether a face was present or absent in each flash. In a separate test, the researchers showed the same volunteers a series of 36 images. Two-thirds of them contained a face pareidolia. The remaining 12 did not.
Participants who had initially reported more hallucination-like experiences were also more likely to report faces in the flashes of random noise. They were also better at identifying those images that contained face pareidolia.
In the next few years, Smailes plans to study situations in which people might be more likely to see faces in randomness.
When people sense ghosts, he points out, “They’re often alone, in the dark and scared.” If it’s dark, your brain can’t get much visual information from the world. It has to create more of your reality for you. In this type of situation, Smailes says, the brain may be more likely to impose its own creations onto reality.
Did you see the gorilla?
The brain’s picture of reality sometimes includes things that aren’t there. But it can also completely miss things that are there. This is called inattentional blindness. Want to know how it works? Watch the video before you keep reading.
The video shows people in white and black shirts passing a basketball. Count how many times the people in white shirts pass the ball. How many did you see?
Partway through the video, a person in a gorilla suit walks through the players. Did you see it? About half of all viewers who count passes while watching the video miss the gorilla completely.
If you too missed the gorilla, you experienced inattentional blindness. You were likely in a state called absorption. That’s when you are so focused on a task that you tune out everything else.
“Memory does not work like a video camera,” says Christopher French. He is a psychologist in England at Goldsmiths University of London. You only remember things you’re paying attention to. Some people are more likely to become absorbed than others. And these people also report higher levels of paranormal beliefs, he says, including beliefs in ghosts.
How could these things be related? Some strange experiences that people blame on ghosts involve unexplained sounds or movements. A window may seem to open all by itself. But what if someone opened it and you just didn’t notice because you were so absorbed in something else? That’s a lot more likely than a ghost, French says.
In one 2014 study, French and his colleagues found that people with higher levels of paranormal beliefs and higher tendencies to get absorbed are also more likely to experience inattentional blindness. They also tend to have a more limited working memory. That’s how much information you can hold in your memory at once.
If you have trouble keeping lots of information in your memory or paying attention to more than one thing at once, then you risk missing sensory cues from the environment around you. And you might blame any misperceptions that result on a ghost.
The power of critical thinking
Anyone may experience sleep paralysis, hallucinations, pareidolia or inattentional blindness. But not everyone turns to ghosts or other supernatural beings as a way to explain these experiences. Even as a child, Dom never thought he had come face to face with a real ghost. He went online and asked questions about what might have happened. He used critical thinking. And he got the answers he needed. When an episode happens now, he uses a technique that Jalal developed. Dom doesn’t try to stop the episode. He just focuses on his breathing, tries to relax as much as possible and waits for it to pass. He says, “I deal with it far better. I just sleep and enjoy sleeping.”
Robyn Andrews is a psychology student at the University of South Wales in Treforest. She wondered if people with stronger critical-thinking skills might be less likely to believe in the paranormal. So she and her mentor, psychologist Philip Tyson, recruited 687 students for a study about their paranormal beliefs. The students majored in a wide range of different fields. Each was asked how strongly he or she agreed with statements such as, “It is possible to communicate with the dead.” Or “Your mind or soul can leave your body and travel.” The research team also looked at the students’ grades on a recent assignment.
The seated woman longs for her dead twin. She may “feel” her sister is trying to reach out to her, physically or mentally. But her brain is likely just misreading some sensory cues — such as soft air currents in the environment around her. valentinrussanov/E+/Getty Images
Students with higher grades tended to have lower levels of paranormal beliefs, this study found. And students in the physical sciences, engineering or math tended not to believe as strongly as those studying the arts. This trend also has been seen in research by others.
This study did not actually assess the students’ ability to think critically. “That’s something we would look into as a future study,” says Andrews. However, previous research has shown that science students tend to have stronger critical-thinking skills than art students. That’s probably because you need to think critically in order to conduct scientific experiments. And thinking critically can help you scout out likely causes for an unusual experience without involving ghosts (or aliens, or Bigfoot).
Even among science students and working scientists, though, paranormal beliefs persist. Andrews and Tyson think that’s a problem. If you can’t judge whether a ghost story or spooky experience is real or not, you may also get fooled by advertisements, bogus medical cures or fake news, says Tyson. It’s important for everyone to learn how to question information and seek reasonable, realistic explanations.
So if someone tells you a ghost story this Halloween, enjoy it. But remain skeptical. Think about other possible explanations for what was described. Remember that your mind may fool you into experiencing spooky things.
Wait, what’s that behind you? (Boo!)
Kathryn Hulick has been a regular contributor to Science News for Students since 2013. She’s covered everything from laser “photography” and acne to video games, robotics and forensics. This piece — her 43rd story for us — was inspired by her new book: Strange But True: 10 of the world’s greatest mysteries explained. (Quarto, October 1, 2019, 128 pages).
alien A non-native organism. (in astronomy) Life on or from a distant world.
colleague Someone who works with another a co-worker or team member.
culture (n. in social science) The sum total of typical behaviors and social practices of a related group of people (such as a tribe or nation). Their culture includes their beliefs, values and the symbols that they accept and/or use. Culture is passed on from generation to generation through learning. Scientists once thought culture to be exclusive to humans. Now they recognize some other animals show signs of culture as well, including dolphins and primates.
engineering The field of research that uses math and science to solve practical problems.
environment The sum of all of the things that exist around some organism or the process and the condition those things create. Environment may refer to the weather and ecosystem in which some animal lives, or, perhaps, the temperature and humidity (or even the placement of things in the vicinity of an item of interest).
field An area of study, as in: Her field of research was biology. Also a term to describe a real-world environment in which some research is conducted, such as at sea, in a forest, on a mountaintop or on a city street. It is the opposite of an artificial setting, such as a research laboratory.
hallucination A term for seeing, hearing or experiencing things that do not exist. It can occur when the brain tries to make sense of stimuli it received from various sensory organs. It can also be a side effect of some types of disease or mental illness.
inattentional blindness The brain’s ability to ignore things occurring right before your eyes as an individual focuses intently on something else, also within the field of view.
information (as opposed to data) Facts provided or trends learned about something or someone, often as a result of studying data.
mentor An individual who lends his or her experience to advise someone starting out in a field. In science, teachers or researchers often mentor students or younger scientists by helping them to refine their research questions. Mentors also can offer feedback on how young investigators prepare to conduct research or interpret their data.
neuroscientist Someone who studies the structure or function of the brain and other parts of the nervous system.
paranormal An adjective meaning supernatural or not explainable by science. Examples include ghosts, demons, telekinesis and clairvoyance.
pareidolia The phenomenon where people see a a pattern or meaning where none really exists. One example: Seeing a face when when you look at the moon. The craters that give rise to the “features” are in fact randomly placed.
perception The state of being aware of something — or the process of becoming aware of something — through use of the senses.
phenomenon Something that is surprising or unusual.
physical science Fields of science (such as chemistry, physics and materials science) that deal with laws of nature and the physical attributes of systems, such as color, temperatures, winds, electricity, magnetism, speeds, energy, mass, chemical reactions, changes of state (such as solids turning into liquids or gases), and forces (such as gravity).
psychology (adj. psychological ) The study of the human mind, especially in relation to actions and behavior. To do this, some perform research using animals. Scientists and mental-health professionals who work in this field are known as psychologists.
random Something that occurs haphazardly or without reason, based on no intention or purpose.
range The full extent or distribution of something. For instance, a plant or animal’s range is the area over which it naturally exists.
recall (in cognition) To remember.
risk The chance or mathematical likelihood that some bad thing might happen. For instance, exposure to radiation poses a risk of cancer. Or the hazard — or peril — itself. (For instance: Among cancer risks that the people faced were radiation and drinking water tainted with arsenic.)
sequence The precise order of related things within some series.
skeptical Not easily convinced having doubts or reservations.
sleep paralysis A condition that happens when the brain fails to fall asleep or wake up completely. A person in this state feels awake, but cannot move, and may hallucinate.
supernatural Something that is attributed to unnatural forces, such as gods or ghosts.
survey To view, examine, measure or evaluate something, often land or broad aspects of a landscape. (with people) To ask questions that glean data on the opinions, practices (such as dining or sleeping habits), knowledge or skills of a broad range of people. Researchers select the number and types of people questioned in hopes that the answers these individuals give will be representative of others who are their age, belong to the same ethnic group or live in the same region. (n.) The list of questions that will be offered to glean those data.
temporoparietal junction A region of the brain that integrates a lot of sensory information to help the body make sense of itself in terms of its surroundings. It plays a role in giving attention to details — and to spotting things that seem unusual or to deviate from the expected.
United Kingdom Land encompassing the four “countries” of England, Scotland, Wales and Northern Ireland. More than 80 percent of the United Kingdom’s inhabitants live in England. Many people — including U.K. residents — argue whether the United Kingdom is a country or instead a confederation of four separate countries. The United Nations and most foreign governments treat the United Kingdom as a single nation.
Wales One of the three components of Great Britain (the other two being England and Scotland. It’s also part of the United Kingdom (whose other members include England, Scotland and Northern Ireland).
Western (n. the West) An adjective describing nations in Western Europe and North America (from Mexico northward). These nations tend to be fairly industrialized and to share generally similar lifestyles levels of economic development (incomes) and attitudes toward work, education, social issues and government.
working memory The ability to hold something in the mind for a short period of time and to adapt it for use, such as hearing a sequence of numbers, then reciting them backwards.
Journal: R.A.F Andrews and P. Tyson. “The Superstitious scholar: Paranormal belief within a student population and its relationship to academic ability and discipline.” Journal of Applied Research in Higher Education. Vol. 11, No. 3, p. 415. July 1, 2019. doi: 10.1108/JARHE-08-2018-0178.
Journal: A. Richards et al. “Inattentional blindness, absorption, working memory capacity, and paranormal belief.” Psychology of Consciousness: Theory, Research, and Practice. Vol. 1, p. 60. March 2014. doi: 10.1037/css0000003.
About Kathryn Hulick
Kathryn Hulick is a freelance science writer and the author of Strange But True: 10 of the World's Greatest Mysteries Explained, a book about the science of ghosts, aliens and more. She loves hiking, gardening and robots.
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HISTORY OF PEER REVIEW
The concept of peer review was developed long before the scholarly journal. In fact, the peer review process is thought to have been used as a method of evaluating written work since ancient Greece (2). The peer review process was first described by a physician named Ishaq bin Ali al-Rahwi of Syria, who lived from 854-931 CE, in his book Ethics of the Physician (2). There, he stated that physicians must take notes describing the state of their patients’ medical conditions upon each visit. Following treatment, the notes were scrutinized by a local medical council to determine whether the physician had met the required standards of medical care. If the medical council deemed that the appropriate standards were not met, the physician in question could receive a lawsuit from the maltreated patient (2).
The invention of the printing press in 1453 allowed written documents to be distributed to the general public (3). At this time, it became more important to regulate the quality of the written material that became publicly available, and editing by peers increased in prevalence. In 1620, Francis Bacon wrote the work Novum Organum, where he described what eventually became known as the first universal method for generating and assessing new science (3). His work was instrumental in shaping the Scientific Method (3). In 1665, the French Journal des svans and the English Philosophical Transactions of the Royal Society were the first scientific journals to systematically publish research results (4). Philosophical Transactions of the Royal Society is thought to be the first journal to formalize the peer review process in 1665 (5), however, it is important to note that peer review was initially introduced to help editors decide which manuscripts to publish in their journals, and at that time it did not serve to ensure the validity of the research (6). It did not take long for the peer review process to evolve, and shortly thereafter papers were distributed to reviewers with the intent of authenticating the integrity of the research study before publication. The Royal Society of Edinburgh adhered to the following peer review process, published in their Medical Essays and Observations in 1731: “Memoirs sent by correspondence are distributed according to the subject matter to those members who are most versed in these matters. The report of their identity is not known to the author.” (7). The Royal Society of London adopted this review procedure in 1752 and developed the 𠇌ommittee on Papers” to review manuscripts before they were published in Philosophical Transactions (6).
Peer review in the systematized and institutionalized form has developed immensely since the Second World War, at least partly due to the large increase in scientific research during this period (7). It is now used not only to ensure that a scientific manuscript is experimentally and ethically sound, but also to determine which papers sufficiently meet the journal’s standards of quality and originality before publication. Peer review is now standard practice by most credible scientific journals, and is an essential part of determining the credibility and quality of work submitted.
Psychology Is WEIRD
Photo by JEAN-PIERRE CLATOT/AFP/Getty Images
How did you lose your virginity? Maybe it was in a romantic garden under a full moon with the scent of roses all around, in the arms of your one true love? Maybe it was at the drunken party after prom night, with your underwear around your ankles, hoping no one could see you to take pictures? Maybe it was on your wedding night, maybe it was long before. Maybe it was even long after. Regardless, I hope you enjoyed it, because a recent study has shown that your sexual well-being today has a lot to do with how much you enjoyed it then. But there’s a major problem (one of several, really) with this study: This study is WEIRD.
Yes, it’s certainly odd that the researchers were checking whether how you lose your virginity influences your future sex life, but this is WEIRD in a methodological context. WEIRD is the phenomenon that plagues a lot of psychology and other social science studies: Their participants are overwhelming Western, educated, and from industrialized, rich, and democratic countries. They’re WEIRD. And not only are they WEIRD, they are overwhelmingly college students in the United States participating in studies for class credit. Thinking about the source of the data for a lot of hyped, overinterpreted psychology research puts the results into a whole new light.
WEIRD subjects (perhaps you were one?) are still human, of course, so you might think that what’s generalizable to them must be generalizable to the rest of humanity. But in fact, that’s not the case. WEIRD subjects, from countries that represent only about 12 percent of the world’s population, differ from other populations in moral decision making, reasoning style, fairness, even things like visual perception. This is because a lot of these behaviors and perceptions are based on the environments and contexts in which we grew up. There’s a big dose of sociology in our psychology. For example, WEIRD people are better at optical illusions involving line length, possibly because our environments contain a lot of straight lines in things like buildings.
Something that doesn’t make it into the WEIRD acronym is the participants’ age. Sixty-seven percent of American psychology studies use college students, for example. This means that many or even most of the subjects are teenagers. And this has big consequences for behavior. Throughout life, the brain is changing connections: building some, losing others. While most of the major neural developments have taken place during adolescence, they are by no means complete when you hit the magic age of 18. Adolescents and college students differ in risk evaluation compared to adults, for example, and are more sensitive to reward.Such changes could drastically impact the outcomes of a psychology study.
When recruiting for many of these WEIRD studies, scientists often make the sample as homogeneous as possible, in an effort to detect small differences. Take the virginity study I mentioned above. The researchers eliminated from the sample anyone whose first exposure to sex involved “physical force” (that is, anyone who had been raped). This eliminated a small number (12 out of 331 participants). And they eliminated anyone who did not have heterosexual intercourse. The sample is so homogeneous that it applies only to heterosexual college students—who on average, according to information they supplied to the researchers, had lost their virginity only two years before.
Human studies have other limitations, of course. Often you can get people to participate for only a short period of time. In the case of the virginity study, subjects kept an “intimate relations” diary for two weeks. Out of about 300 participants, the researchers got records of a total of 639 intimate encounters, about two per person. From these two intimate encounters per person, in college students who had lost their virginity on average two years before, the authors concluded that sexual satisfaction in the present was strongly affected by how you lost your virginity and that the effects of how you lost your virginity could persist for years to come.
The majority of these “intimate relations” were not actually sexual intercourse they were experiences where the “goal was sexual arousal.” The authors don’t report what these experiences included, but it could have been everything from first base to a home run. And, as with many human studies, the encounters were all measured by participant report. You can’t help it, of course—you can hardly keep people in the lab and having sex with each other for weeks, but self-report studies are always open to things like exaggeration or covering up, especially when it comes to studies about sex, where a lot of cultural pressure comes into play.
And there are personal pressures as well as cultural ones, all of which could affect the outcome of the study. Are subjects’ current partners coloring their memories of earlier experiences? How comfortable are members of the group in general with expressing themselves sexually? After all, if you’re volunteering for a sex study, you may well be part of a self-selecting population. So is the link between first and subsequent sexual experience really true? It might be, but it also might not generalize to the study’s college students or to college students overall. And if it does, does that mean it’s true for the rest of us? If we really are doomed to have sex like we had it our first time … most of us are screwed. And that is just considering awkward first-time fumblings, without taking into account the many people who had truly terrible experiences. But from the media attention to this story, you would assume that we were all facing dysfunctional sex lives.
Why are WEIRD college students so popular in research? Well, to be honest, they’re cheap. Free in some cases. Many will fill out a survey or three for a chocolate bar.
It’s not a bad thing to be WEIRD. And most of these studies do have value. They can tell us a lot about how college students think and behave. And many studies probably can be generalized to the rest of the population, at least the rest of the WEIRD population. But do most WEIRD studies generalize to humanity as a whole? In the case of social punishment, probably not, but in the case of emotional expression, it looks like they do. It depends on what question you’re asking.
Psychologists have become very careful about this in the past several years, and they have begun to really examine the WEIRD population and whether it is representative. Most studies now will carefully add qualifiers, such as “in college populations” or “in Western society.” For example, the study on virginity loss concluded that, “In sum, the present study provides strong evidence of the link between virginity loss and subsequent sexual functioning. This linkage represents an important step forward in the understanding of the development of adolescent sexuality.”
But the WEIRD context is often lost in translation, with many journalists and commenters easily assigning the findings to the world population in general.
So the next time you see a study telling you that semen is an effective antidepressant, or that men are funnier than women, or whether penis size really matters, take a closer look. Is that study WEIRDly made up of college psychology students? And would that population maybe have something about it that makes their reactions drastically different from yours? If so, give the study the squinty eye of context. As we often add “… in bed” to our reading of the fortunes in fortune cookies, it’s well worth adding “… in a population of Westernized, educated, industrialized, rich, and democratic college students” to many of these studies. It can help explain many of the strange conclusions.
Common Statistical Pitfalls in Basic Science Research
The analysis of clinical samples, population samples, and controlled trials is typically subjected to rigorous statistical review. This fact is understandable, given that the results of clinical investigation will often be used to inform patient care or clinical decision making. One would not want to predicate patient advice on research findings that are not correctly interpreted or valid. For this reason, most major journals publishing clinical research include statistical reviews as a standard component of manuscript evaluation for publication. Clinical data, regardless of publication venue, are often subject to rather uniform principles of review.
In contrast, basic science studies are often handled less uniformly, perhaps because of the unique challenges inherent in this type of investigation. A single basic science manuscript, for example, can span several scientific disciplines and involve biochemistry, cell culture, model animal systems, and even selected clinical samples. Such a manuscript structure is a challenge for analysis and statistical review. Not all journals publishing basic science articles use statistical consultation, although it is becoming increasingly common. 1 In addition, most statistical reviewers are more comfortable with clinical study design than with basic science research. Consequently, there are multiple reasons why the statistical analysis of basic science research might be suboptimal. In this review, we focused on common sources of confusion and errors in the analysis and interpretation of basic science studies. The issues addressed are seen repeatedly in the authors' editorial experience, and we hope this article will serve as a guide for those who may submit their basic science studies to journals that publish both clinical and basic science research. We have discussed issues related to sample size and power, study design, data analysis, and presentation of results (more details are provided by Katz 2 and Rosner 3 ). We then illustrated these issues using a set of examples from basic science research studies.
Sample Size Considerations
Sample Size: What Constitutes the Experimental “n” in Basic Research?
The unit of analysis is the entity from which measurements of “n” are taken. The units could be animals, organs, cells, or experimental mixtures (eg, enzyme assays, decay curves). The sample size, which affects the appropriate statistical approach used for formal testing, is the number (ie, n value) of independent observations under 1 experimental condition. Most common statistical methods assume that each unit of analysis is an independent measurement. A common pitfall in basic science research is the treatment of repeated measurements of a unit of analysis as independent when, in fact, they are correlated, thus artificially increasing the sample size. A simple example is a single measurement (eg, weight) performed on 5 mice under the same condition (eg, before dietary manipulation), for n=5. If we measure the weight 12 times in 1 day, we have 12 measurements per mouse but still only 5 mice therefore, we would still have n=5 but with 12 repeated measures rather than an n value of 5×12=60. In contrast, the 12 repeated measures of weight could be used to assess the accuracy of the mouse weights therefore, the 12 replicates could be averaged to produce n=1 weight for each mouse. Things become even more vague when using cell culture or assay mixtures, and researchers are not always consistent. By convention, an independent experiment infers that the researcher has independently set up identical experiments each time rather than just measuring the outcome multiple times. The former reflects the inherent biological variability, whereas the latter may simply measure assay variability.
Sample Size Determination and Power
Sample size determination is critical for every study design, whether animal studies, clinical trials, or longitudinal cohort studies. Ethical considerations elevate the need for sample size determination as a formal component of all research investigations. In basic science research, studies are often designed with limited consideration of appropriate sample size. Sample sizes are often quite small and are not likely to support formal statistical testing of the underlying hypothesis. Although determining an appropriate sample size for basic science research might be more challenging than for clinical research, it is still important for planning, analysis, and ethical considerations. When determining the requisite number of experimental units, investigators should specify a primary outcome variable and whether the goal is hypothesis testing (eg, a statistical hypothesis test to produce an exact statistical significance level, called a P value) or estimation (eg, by use of a confidence interval). We find that most basic science studies involve hypothesis testing. In addition, investigators should specify the details of the design of the experiment to justify the choice of statistical test used. Will comparison groups, for example, be independent (eg, experimental units randomized to competing conditions) or dependent (the same units measured under each experimental condition, sometimes called a matched, paired, or repeated‐measures design)? Careful specification of the experimental design will greatly aid investigators in calculating sample size.
A particular challenge in sample size determination is estimating the variability of the outcome, particularly because different experimental designs require distinct approaches. With an independent samples design, for example, variability pertains to the outcome measure (eg, weight, vascular function, extent of atherosclerosis), whereas a paired samples design requires estimating the difference in the outcome measure between conditions over time. A common mistake is not considering the specific requirements to analyze matched or paired data. When hypothesis testing is to be performed, a sample size that results in reasonable power (ie, the probability of detecting an effect or difference if one exists) should be used. A typical “reasonable” value is ≥80% power. In basic science research, there is often no prior study, or great uncertainty exists regarding the expected variability of the outcome measure, making sample size calculations a challenge. In such cases, we recommend that investigators consider a range of possible values from which to choose the sample size most likely to ensure the threshold of at least 80% power.
An important implication of appropriate sample determination is minimizing known types of statistical errors. A significant statistical finding (eg, P<0.05 when the significance criterion is set at 5%) is due to a true effect or a difference or to a type I error. A type I error is also known as a false‐positive result and occurs when the null hypothesis is rejected, leading the investigator to conclude that there is an effect when there is actually none. The probability of type I error is equal to the significance criterion used (5% in this example). Investigators can limit type I error by making conservative estimates such that sample sizes support even more stringent significance criteria (eg, 1%). Conversely, a comparison that fails to reach statistical significance is caused by either no true effect or a type II error. A type II error is described as a false‐negative result and occurs when the test fails to detect an effect that actually exists. The probability of type II error is related to sample size and is most often described in terms of statistical power (power=1‐type II error probability) as the probability of rejecting a false‐null hypothesis. Minimizing type II error and increasing statistical power are generally achieved with appropriately large sample sizes (calculated based on expected variability). A common pitfall in basic science studies is a sample size that is too small to robustly detect or exclude meaningful effects, thereby compromising study conclusions.
Basic science studies often involve several outcome variables from the same sample (eg, group of mice), making sample size decisions challenging. In this instance, an efficient approach is to perform sample size computations for each outcome, and the largest practical sample size could be used for the entire experiment. If the calculated sample size is not practical, alternative outcome measures with reduced variability could be used to reduce sample size requirements.
Issues to Consider in Designing Studies
In designing even basic science experiments, investigators must pay careful attention to control groups (conditions), randomization, blinding, and replication. The goal is to ensure that bias (systematic errors introduced in the conduct, analysis, or interpretation of study results) and confounding (distortions of effect caused by other factors) are minimized to produce valid estimates of effect. Concurrent control groups are preferred over historical controls, and littermates make the best controls for genetically altered mice. With large samples, randomization ensures that any unintentional bias and confounding are equally present in control and experimental groups. In developing competing treatments or experimental conditions, the various conditions should be identical in every way except for the experimental condition under study. This includes control of conditions that may unknowingly have an impact on the effects of the treatments under study (eg, time of day, temperature). Ideally, investigators performing measurements should be blinded to treatment assignments and experimental conditions. Stratification is a means to combat bias and confounding. This technique provides for randomization of treatment and control groups equally across potential sources of bias and confounding, such as time of day stratification by morning or afternoon time slots would prevent any impact by time of day. Replication is also a critical element of many experiments. Replication provides additional information to estimate desired effects and, perhaps more important, to quantify uncertainty in observed estimates (as outlined). The value of replication is understood however, replication is useful only if the repeated experiment is conducted under the same experimental conditions.
Investigators can also minimize variability by carefully planning how many treatments, experimental conditions, or factors can be measured in an individual unit (eg, animal). One might wish to determine, for example, the impact of genotype and diet on animal weight, blood pressure, left ventricular mass, and serum biomarkers. It is common to see investigators design separate experiments to evaluate the effects of each condition separately. This may not be the most efficient approach and introduces additional bias and confounding by performing serial sets of experiments that are separated in time. In contrast, factorial experiments, in which multiple conditions or factors are evaluated simultaneously, are more efficient because more information can be gathered from the same resources. In the above example, wild‐type and genetically altered littermates could be randomized in sufficient numbers to competing diets and observed for blood pressure, left ventricular mass, and serum biomarkers. This design provides information on the effect of diet, the effect of genotype, and the combination of the 2. It might be that the effect of diet and genotype is additive, or there may be a statistical interaction (a different effect of diet on blood pressure depending on genotype). This latter observation would escape detection if performed in separate experiments, and the factorial design has the advantage of involving fewer mice than would be required for the 2 separate experiments.
Issues in Presenting Data
A critically important first step in any data analysis is a careful description of the data. This description includes the sample size (experimental n value) and appropriate numerical and graphical summaries of the data. The sample size is most informative and is presented to provide the reader with the true size of the experiment and its precision. The habit of presenting sample sizes as ranges (eg, n=5 to 12 in each group) is not useful from a statistical perspective. It is more appropriate to clearly indicate the exact sample size in each comparison group.
In clinical studies, the first summary often includes descriptive statistics of demographic and clinical variables that describe the participant sample. Continuous variables such as age, weight, and systolic blood pressure are generally summarized with means and standard deviations. If variables are not normally distributed or are subject to extreme values (eg, cholesterol or triglyceride levels), then medians and interquartile ranges (calculated as Q3−Q1, in which Q indicates quartile) are more appropriate. Several approaches can be used to determine whether a variable is subject to extreme or outlying values. One of the most popular is based on Tukey fences, which represent lower and upper limits defined by the upper and lower quartiles and the interquartile range, specifically, values below Q1−1.5 (Q3−Q1) or above Q3+1.5 (Q3−Q1). 4 Extreme values should always be examined carefully for errors and corrected if needed but never removed.
In basic science studies, investigators often move immediately into comparisons among groups. If the outcome being compared among groups is continuous, then means and standard errors should be presented for each group. There is often confusion about when to present the standard deviation or the standard error. Standard deviations describe variability in a measure among experimental units (eg, among participants in a clinical sample), whereas standard errors represent variability in estimates (eg, means or proportions estimated for each comparison group). When summarizing continuous outcomes in each comparison group, means and standard errors should be used. When summarizing binary (eg, yes/no), categorical (eg, unordered), and ordinal (eg, ordered, as in grade 1, 2, 3, or 4) outcomes, frequencies and relative frequencies are useful numerical summaries when there are relatively few distinct response options, tabulations are preferred over graphical displays (Table 1).
Correlational research can be used to see if two variables are related and to make predictions based on this relationship.
Interpret results using correlational statistics
- There are some instances where experimental research is not an option for practical or ethical reasons. In these situations, correlational research can still be used to determine if two variables are related.
- Correlations can be used to make predictions about the likelihood of two variables occurring together.
- Correlation does not imply causation. Just because one factor correlates with another does not mean the first factor causes the other or that these are the only two factors involved in the relationship. Only an experiment can establish cause and effect.
- causation: The act by which an effect is produced in psychological research, the assumption that one variable leads to another.
- negative correlation: A relationship between two variables such that as one increases the other decreases. On a graph, a negative correlation will have a negative slope.
- positive correlation: A relationship between two variables such that as one increases or decreases the other does the same. On a graph, a positive correlation will have a positive slope.
Correlational studies are used to show the relationship between two variables. Unlike experimental studies, however, correlational studies can only show that two variables are related—they cannot determine causation (which variable causes a change in the other). A correlational study serves only to describe or predict behavior, not to explain it. In psychological research, it is important to remember that correlation does not imply causation the fact that two variables are related does not necessarily imply that one causes the other, and further research would need to be done to prove any kind of causal relationship.
Positive and Negative Correlations
The attributes of correlations include strength and direction. The strength, or degree, of a correlation ranges from -1 to +1 and therefore will be positive, negative, or zero. Direction refers to whether the correlation is positive or negative. For example, two correlations of.78 and -.78 have the exact same strength but differ in their directions (.78 is positive and -.78 is negative). In contrast, two correlations of.05 and.98 have the same direction (positive) but are very different in their strength. Although.05 indicates a relatively weak relationship,.98 indicates an extremely strong relationship between two variables. A correlation of 0 indicates no relationship between the variables.
A positive correlation, such as.8, would mean that both variables increase together. You might expect to see a positive correlation between high school GPA and college GPA—in other words, that those students with high grades in high school will also tend to have high grades in college.
A negative correlation, such as -.8, would mean that one variable increases as the other increases. You might expect to see a negative correlation between the amount of partying the night before a test and the score on that test—in other words, that more partying relates to a lower grade.
It is extremely rare to find a perfect correlation between two variables, but the closer the correlation is to -1 or +1, the stronger the correlation is.
Correlations of varying directions and strengths: Panels (a) and (b) show the difference between strong and weak positive linear patterns—the strong pattern more closely resembles a straight line. The same is true for panels (c) and (d)—the strong negative linear pattern more closely resembles a straight line than does the weak negative pattern. Finally, comparing panels (a) and (c) shows the difference between positive and negative linear patterns—a positive linear pattern slopes up (both variables increase at the same time), and a negative linear pattern slopes down (one variable decreases while the other increases).
Statistical testing must be done to determine if a correlation is significant. Even a seemingly strong correlation, such as.816, can actually be insignificant due to a variety of factors, such as random chance and the size of the sample being tested. With smaller sample sizes, it can be easy to obtain a large correlation coefficient but difficult for that correlation coefficient to achieve statistical significance. In contrast, with large samples, even a relatively small correlation of.20 may achieve statistical significance.
Benefits of Correlational Research
An experiment is not always the most appropriate approach to answering a research question. Sometimes it is not possible to carry out a true experiment for practical or ethical reasons because it is impossible to manipulate the independent variable. If a researcher was to look at the psychological effects of long-term ecstasy use, it would not be ethical to randomly assign participants to a condition of long-term ecstasy use. An experiment is also not feasible when examining the effects of personality and individual differences since participants cannot be randomly assigned into these categories. Correlational research allows a researcher to determine if there is a relationship between two variables without having to randomly assign participants to conditions.
The strength of correlational research is its predictive capabilities. With a large sample size, you can use one variable to predict the likelihood of the other when there is a strong correlation between the two. For instance, you could take two measurements from 1,000 families—whether the father is an alcoholic and whether a son is an alcoholic—and calculate the correlation. If there is a strong correlation between the two measurements, it will allow you to predict, within certain limits of probability, what the chances are that the son of an alcoholic father will also have a problem with alcohol.
Limitations of Correlational Research
A correlational study serves only to describe or predict behavior, not to explain it. Always remember that correlation does not imply causation. Since there is no random assignment to conditions, a researcher cannot rule out the possibility that there is a third variable affecting the relationship between the two variables measured. Even if there is no third variable, it is impossible to tell which factor is influencing the other. Only experimental research can determine causation. In the above example, while a research could predict the likelihood of an alcoholic father having an alcoholic son, they could not describe why this was the case.
An excellent example used by Li (1975) to illustrate the “third variable” problem is the positive correlation in Taiwan in the 1970’s between the use of contraception and the number of electric appliances in one’s house. Of course, using contraception does not induce you to buy electrical appliances or vice versa. Instead, the third variable of education level affects both.
Another popular example is that there is a strong positive correlation between ice cream sales and murder rates in the summer. As ice cream sales rise, so do murder rates. Is this because eating ice cream makes us want to murder people? The actual explanation is that when the weather is hot, more people buy ice cream, but they also go out more, drink more, and socialize more, leading to an increase in murder rates. Extreme temperatures observed in the summer also have been shown to increase aggression. In this case, there are many other variables at play that feed the correlation between murder rates and ice cream sales.
6. It Promotes a Love of Reading, Writing, Analyzing, and Sharing Valuable Information
Research for Critical Thinking
Research entails both reading and writing. These two literacy functions help maintain critical thinking and comprehension. Without these skills, research is far more difficult. Reading opens the mind to a vast reservoir of knowledge, while writing helps us express our own perspectives and transform our thoughts into more concrete ideas in a way others can understand.
Apart from reading and writing, listening and speaking are also integral to conducting research. Conducting interviews, attending knowledge-generating events, and participating in casual talks can help us gather information and formulate research topics. These things also facilitate our critical thinking process, much like reading and writing. Listening to experts discuss their work can help us analyze issues from new perspectives and add new techniques to our information-gathering arsenal.
Sharing Research for Wider Understanding
With the wide array of ideas floating around and the interconnectedness of people and places through the internet, scholars and non-scholars involved in research are able to share information with a larger audience. Some view this process as ego-boosting, while others see it as a means to stimulate interest and encourage further research into certain issues or situations.
Literacy is integral in improving a person&aposs social and economic mobility and in increasing awareness, and research hones these basic life skills and makes learning a lifelong endeavor.
Exercising your mind is just as important as exercising your body.
Hi, Reddit! We’re scientists at the Smithsonian’s National Zoo and Conservation Biology Institute’s Center for Conservation Genomics. We use genomics to save threatened species – ask us anything!
The Smithsonian’s Center for Conservation Genomicshttps://nationalzoo.si.edu/center-for-conservation-genomics (CCG) uses genomics to better understand how we can care for and sustain genetically diverse animal populations in human care and in the wild. We use DNA, RNA and more to uncover information about the evolutionary history of animals and to determine the importance of genetic variation in their future survival.
This information can be used to answer questions about everything from diseases to animal behavior. We collaborate with other scientists across the Smithsonian, and with institutions and agencies around the world.
Here are just some of the things we do with genomics:
Use non-invasive DNA collection from feces, hair, saliva and more to help conservationists find and count endangered species (link)
Identify new species or use ancient DNA to determine when and if speciation reversal occurs (link)
Use DNA from century-old deceased bats to analyze how white-nose syndrome impacts bats living today (link)
Determine the sex of a baby animals from a small DNA sample (e.g., a baby porcupine and a quill)
Map genomes to decode family trees of animals like Asian elephants to better understand health concerns and treatments (link)
Determine if an invasive species is actually invasive (link)
We’re doing this AMA as part of the National Human Genome Research Institute’s National DNA Day Reddit AMA series and are excited to answer any questions you have about genomics, DNA research or conservation biology! Ask us anything!
Your hosts are:
Nancy McInerney, B.S., Marquette University. I train students, researchers and visiting scientists in how genomics can be used in conservation and assist the Zoo with projects like disease detection, sex identification of newborn animals and paternity testing.
I have worked on projects including sequencing mitogenomes of California sea otters, analyzing eDNA to locate endangered freshwater turtles, monitoring the impact Chytrid fungus on amphibians and sequencing the DNA of museum specimens.
Jesus Maldonado, B.S. and M.S., Shippensburg University of Pennsylvania Ph.D., University of California, Los Angeles. I have been a research geneticist at SCBI since 1998. My research applies molecular genetics tools to answer questions about conservation and evolutionary biology in mammals. I assess the genetic variation within and among populations and species to document levels of genetic diversity and determine evolutionary, taxonomic and conservation significance.
While my research has many theoretical aspects, the outcomes of these studies have direct applications that help threatened and endangered animals. I am active in education programs and have mentored more than 26 undergraduate students on research projects dealing with the population genetics of mammals, birds and reptiles.
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What types of ancient DNA have you worked on? What was the most surprising or strange discovery from ancient DNA you've seen?
We have worked on a diversity of ancient DNA materials from museum specimens such as bone fragments, skin, pieces of tissue that stick to the bones. We also get DNA from bones that have been collected by anthropologists. These might be found in caves, middens, or anthropological sites.
One of my first surprising discoveries was when we looked at museum wolf bone samples back in 2004 that were collected in India in the 1800s. My Indian collaborators and I were interested in the genetic diversity of wolves worldwide, and with these India samples, we found that Indian wolves had a more ancient lineage from the rest of the wolves worldwide.
Are there any new techniques or tools in the field of genomics that you're excited about? I studied genomics in college but it's been a few years and bio in general changes so quickly. I want to know what I've missed.
You are right, the field changes so quickly. We are eager to utilize human genomics techniques for conservation. We can now sequence whole genomes in a few days, and at a fraction of the cost. A few years ago we couldn't afford to sequence a genome on a Sanger sequencer, but now we have a next-gen sequencer in our lab so the types of work and research we can do has greatly expanded.
Targeted Sequence Capture is an exciting new tool that allows us to target specific regions of the genome in good quality DNA as well as degraded samples. We can compare museum specimen DNA to modern animal DNA. This technique uses RNA probes to hybridize to our DNA, and then wash away anything that's not bound. Then we sequence these short DNA segments on our next-gen sequencer and we're able to compare samples at thousands of loci. This would have been very laborious and expensive with PCR-based technology.
Can genomic mapping help bring back extinct species in the future if their DNA is still retrievable?
Understanding the architecture of a genome is an important first step. The exact location of the DNA in the genome is imperative for the function of a living animal.
We do not want to set up an extinct species for failure. We all need to address the reasons a species went extinct in the first place.
If humans have sperm/egg banks and plants have seed banks, do you also keep some sperm/eggs of threatened or extinct species somewhere? Would it be a good idea to start collecting the eggs/sperms of existing animal species today?
When dealing with a threatened or endangered species in a captive breeding program, how do you make decisions on which individuals to mate? Do you know whether certain mutations will prove to be advantageous, are there certain mutations you aim to cull from the heard, or is it a case of trying to conserve as much variability as possible?
We provide the genomic information about a species in question to the Species Survival Plan (SSP). They will take this information, such as age, etc to make breeding decisions.
The SSP is trying to build genetic diversity into a captive breeding population. Yes, trying to conserve variabilty.
We are currently undertaking some projects that are looking at genes that confer protection against disease. We published the first MHC (Major Histocompatability Complex) variability paper in wild elephants. This region would be helpful to research for captive breeding programs in all animals.
Does the research you conduct get repurposed for other scientific studies e.g. for CDC NCEZID disease control or USDA APHIS wildlife services? What sort of interactions do you have with their staff and scientists?
Our major role is to conduct research and publish our work in scientific journals. Any scientist or agency can then use our data and our findings. We have worked with APHIS, USFWS, USGS and various NGOs.
Can you say a little more about how DNA from animal poop helps you understand genomic variation in different species?
Animal poop is one of our best materials for understanding genomic variation in species. It is not very easy to go out and collect a blood or tissue sample from an endangered species (whether that's because of the habitat or how rare they are). Poop contains DNA from the species, as well as it's diet and parasites and microbiome.
To determine the genetic diversity of a population, we need as many samples of the population as we can get. We go into the field and collect many samples by walking transects and picking up whatever we see, or poop-detecting dogs specially trained to identify the poop we're looking for!
We have a long term project with the conservation of endangered kit fox in the San Joaquin Valley in California. The poop-sniffing dogs are trained to detect kit fox poop by scent. The dog then sits down by it, and the handler picks it up and ships it to us in baggies filled with silica gel to dry it out and prevent degradation. We then extract the DNA, and we sequence it to identify the species, sex, and number of individuals in the area. It is a great tool for monitoring the population over time.
How do you stay optimistic about conservation efforts in light of a lot of negative messaging about global climate change? What makes you hopeful?
The students I work with make me optimistic. We train the next generation of conservation scientists, and we're so proud to help them accomplish their goals. I want to be part of the solution!
The data that shows how humans are impacting the earth is troubling. This is what motivates me, and keeps me wanting to do my work of monitoring the genetic diversity of animals in a fast changing world.
Why and how did you find and follow your career path(s)?
I have always been interested in Biology, but could never decide on one topic. I studied Biology in undergrad and then STILL couldn't decide what to do, but I knew I liked working in a laboratory. I got a job out of college doing DNA sequencing in a Human Genomics laboratory in Milwaukee, WI, where I learned how to PCR and sequence DNA using robots. I WAS HOOKED. Then I wanted to move to Boston, so I was lucky enough to snag a lab manager job at Harvard's Ornithology laboratory that happened to have the same equipement. I segued to studying birds and found that the research and stories around studying animals was more interesting than humans (ha!). I wanted to move to DC, and got a job at Smithsonian in the Bird Strike Laboratory at the Natural History Museum with Carly Dove. I sequenced the CO1 gene in any sort of debris the pilots/mechanics could wipe of the planes, and we could identify the birds for them. Definitely google that. And now I'm back to lab managing at SCBI and am lucky to help all the students and scientists sequence DNA of animals from all over the world, as well as the animals in the Zoo. I get to sequence the baby pandas when they're born to figure out male/female, as a perk!
I grew up in the suburbs of Mexico City in the 1960s. My house faced the mountains and fields and loved to go outside and explore as a child. In the 70s my house was in the middle of Mexico City and all the wildlife and habitat was destroyed and replaced by condos and roads. This really motivated me to pursue biology and conservation biology. My path was lucky because my father was stationed at the War Collage in PA, and the closest college was Shippensburg State University. There, I was mentored by the mammal curator of the vertebrate museum and participated in many internships and field trips to the surrounding areas, which greatly increased my interest in studying mammals. That led to a masters degree looking at morphometric variation of skunks parasatised by a nematode. This involved measuring hundreds of skulls in museum collections with and without evidence of parasites. I then got a job as a curatorial assistant at LA County Museum of Natural History, because of this museum experience during my masters. At the museum I learned about how little we knew about some mammal species in California, and in my case, shrews. Shrews are difficult to find and study, and the morphology was very consistent across species, so I needed to use the new genetic tools available then to study these animals. That lead me to enroll at UCLA in one of the first conservation genetics labs. I then came to DC to join the Smithsonian and continue studying the genomics of animals.
18 Advantages and Disadvantages of Light Microscopes
Light microscopes work by employing visible light to detect small objects, making it a useful research tool in the field of biology. Despite the many advantages that are possible with this equipment, many students and teachers are unaware of the full range of features that are possible. Because the cost of the instrument increases with its versatility and quality, the best ones are not usually available to most academic programs. That makes it challenging to provide a well-rounded education to anyone except those who can afford the expense.
Despite the changes in feature availability which are present with light microscopes today, even beginner model can help students to begin seeing the vast array of views that are possible when we start looking inward instead of outward. This instrument can even help teachers to conduct some reasonably sophisticated assignments and experiments without a massive investment in the program.
Many people believe that the key to getting the most out of a microscope is to get a strong enough magnification. There are actually four different challenges that come before this issue: sufficient contrast, finding the focal plane, resolution levels, and recognizing the subject.
If you are getting ready to begin studying in the field of biology, then these are the advantages and disadvantages of light microscopes to review.
List of the Advantages of Light Microscopes
1. Light microscopes are relatively easy to use.
Because the only resource you need to have available with a light microscope is light waves, you can use this equipment almost anywhere to complete your studies. It is also possible to create an artificial environment which provides artificial light in large quantities to make using the microscope possible. You will not need any special aids to operate the equipment unless it malfunctions for some reason. Because of its overall simplicity, almost anyone can afford and use them for their research.
Entry-level models for student studying are about $100 per unit. If you pay about $250, then you will receive a top-of-the-line option that can take you through your student career or provide more teaching opportunities. Upper echelon models are typically priced between $10,000 to $50,000, depending on the exact features that you want.
2. Light microscopes are small and lightweight.
Unlike other microscope designs, the light microscope does not contain anything that is excessive or unnecessary to the structures you wish to view. Entry-level models are some of the lightest and smallest microscopes that you can find in the world today. Because this equipment is exceptionally portable, you can study your findings at almost any location, making it possible to experience instant results.
You won’t receive this advantage if you are trying to use an electron microscope for your work. Some models require an entire room for their operations, which means you need to bring the research to it instead of taking your equipment to where you need to work.
3. Light microscopes offer high levels of observational quality.
When you use this equipment in natural light, then the magnification you receive through the lens will use the spectrum of light waves that you use every day. That process makes it possible to study almost anything in its natural colors thanks to the reflections that occur. You don’t need to worry about any alterations to the color of the cells or the textures of what you are looking at with this unit. That means there are never any questions about the authenticity of what you are seeing because this equipment doesn’t require dyes or visual aids to the same extent as other microscope designs.
If you were to use an electron microscope, then everything you would see would be in black and white. That outcome occurs because electrons do not possess any color since there is no light involved. When a better visual impression is necessary, one must add artificial coloring to the results, which you receive automatically when using a light microscope.
4. Light microscopes are unaffected by electromagnetic fields.
When you are using a light microscope, then the equipment in your hands adapts to changing natural conditions with relative ease. Although darkness and rain are obvious obstacles to the successful use of this item, you will not experience the aberrations that are possible when there are disrupting factors in the environment. Some microscopes will not provide you with accurate results when they are in the presence of a magnetic field. If your work requires that exposure, then this design is your best option.
5. Light microscopes do not require radiation to operate.
If you are using an electron microscope for your research, then the equipment will create a strong beam of high radiation that will kill whatever living objects are in its path as you look at the sample. This issue does not exist when using a light microscope. Although there might be quality issues to consider, especially in low-light conditions, it is also much easier to maintain the overall integrity of each slide with this equipment compared to other operations.
When you work with a premium-quality light microscope, then you can still see many of the critical details that are necessary for the learning process. You will receive details about the cell walls of your sample, bacteria that may be present, and even nuclei details or cellular components to facilitate your progress through the curriculum.
6. Light microscopes require very little training.
You won’t find any microscopes that offer an experience that is comparable to a computer’s plug-and-play design, but a light microscope comes pretty close. Most people can figure out how to use the equipment within a few minutes, even if there aren’t any instruction manuals available to review. That means this equipment is the perfect option for teachers who are teaching an introduction to biology class or specific scientific concepts in this smaller world. You can spend more time on the curriculum because you are spending less time training everyone on how to use each microscope.
7. Light microscopes allow you to observe living organisms.
If you want to observe living microorganisms through a microscope, then a light microscope is your only option. Electron microscopes will kill the organisms because of the radiation they emit. Although this won’t impact your health any, it could impede your studies since there won’t be anything moving around. This process includes bacteria, which is why it is such a beneficial tool in the study of biology.
You won’t be able to observe every structure of some living things because of the natural limitations of light’s wavelengths, but you will get a good sense of what the cellular components of your sample are when using this equipment.
8. Light microscopes come with two common options to use.
There are two different types of light microscopes that are typically used for biology research right now. The first is called a compound microscope, which allows you to have the strongest magnification possible for this equipment option. You must work with specimens which are quite thin and bright for the light to pass through appropriately. Glass slides are mandatory for this unit, which cannot produce a 3-D image even if there are two eye pieces available for the user.
Stereo (dissecting) microscopes provide users with an opportunity to observe larger specimens if they are opaque. They can only magnify up to 70 times with even the top-tier models, but you will receive a panoramic view of what you are studying. The image delivered to each eye is slightly different with this option, which is why the view is beneficial. You don’t need to go through the process of elaborate sample preparation with a dissecting microscope either.
9. Light microscopes have a minor maintenance cost compared to other models.
Not only are light microscopes typically cheaper to purchase, but they are also less expensive to maintain at an operational quality. This advantage applies to both compound and stereo microscopes. The costs may still be too high for some facilities, teachers, or families to afford in some circumstances, but there are more options available with this design compared to any of the different types of electron microscopes that are available today.
If you have a single ocular microscope that you are using, then there is nothing you need to do with the eyepiece except to keep it clean.
10. Light microscopes can use fluorescent lights to display a sample visually.
If you find yourself in a laboratory setting, then you might be able to use a fluorescent light microscope for your work. Although this option is not usually available to the general public, the intensity of light that is available with this option helps to create a longer wavelength that researchers can use for studying. That means you don’t need to use high-intensity light to observe the living sample, which means there is more clarity available with less harm to your research compared to previous evolutions of this technology.
11. Light microscopes are fully adjustable to the comfort level of the user.
This advantage applies directly to the compound or binocular-style light microscopes that are available today. You can adjust the eyepiece on the unit for separation just as you would when looking through a set of binoculars to obtain the clearest view possible of your specimen. Then you can adjust the intensity of the illumination, move the slide if one is present, and adjust your contrast to ensure that you’re viewing something with accuracy.
One or both of the eyepieces on a binocular-style light microscope might offer a telescoping feature as well, allowing you to perfect the focus while working. Since the average person doesn’t have eyes that match perfectly, most will focus on one eyepiece to match the other to create the necessary outcome for study.
List of the Disadvantages of Light Microscopes
1. Light microscopes do not magnify at the same level as other options.
The typical light microscope cannot magnify as closely as an electron microscope when looking at some of the world’s smallest structures. Most models are capped at 2,000 times or thereabouts, with some entry-level models offering significantly less to the user. Because the relatively long wavelength of light decreases the ability of the equipment to magnify in the small focus lens, you may not always see everything that is going on with a slide when choosing this option.
Although some electron microscopes go into magnification factors that are in the millions, you would spend several thousand dollars on the average optical microscope with a 2,000x resolution. You can grab a student electron model for less than $500.
2. Light microscopes have a lower resolution.
The reason why a light microscope has a lower resolution compared to other equipment options is because the refracted light waves are spread out when viewed through the lens. That results in the image that you see being blurry. Even if you can increase the magnification of the unit by adding additional lenses, you will not improve this disadvantage to the point where what you see becomes useful. When you want to view something that is exceptionally small, then you must seek out an alternative microscope.
When you compare this style to an electron microscope, the disadvantage becomes clear when compared to light microscopes. An electron microscope can magnify up to 2 million times, allowing you to visualize structures that are rarely visible when using a form of optical microscopy.
3. Light microscopes make it challenging to view living internal structures.
When you want to view the internal structure of a living thing, then you must use dye to highlight the cells that are present. The only way currently known to science to make this work is to either extract biological elements from the specimen (such as a blood draw or biopsy) or to kill it. Then you must fix it during the dyeing process to ensure that what you can see is an accurate representation of what is on the slide. Following all of these steps will typically eliminate what is usually one of the most significant advantages of using a light microscope for your work or studies.
4. Light microscopes cannot operate in darkness.
The most obvious disadvantage of a light microscope is that you must use it under specific conditions. Although you can add artificial light to the equipment to improve your view, some models do not offer that opportunity. Built-in illuminators are another feature that can be added to the unit if you’re willing to spend enough on the feature. If you don’t have access to any natural or artificial light, then you’re not going to work. It is that simple.
This disadvantage applies to some of the smaller objects that you may wish to study in the world of biology as well. A micrometer, which is often referred to as a “micron,” is one-thousandth of a millimeter. Light microscopes use a white light wave that is the equivalent of 0.55 microns. That means you cannot observe the details of anything smaller than 50% of the wavelength with clarity, which is 0.275 microns.
5. Light microscopes cannot provide three-dimensional renderings.
When you are using a stereo microscope, then you can sometimes see depth in the sample thanks to the fact that you’re receiving two slightly different views of the object you are studying. If you need to see the 3-D external shape of an object with your work, then your best option will always be an electron microscope. You will need to use an SEM (Scanning Electron Microscope) to counter this disadvantage of the light microscope design, so expect to pay about $1 million for an upper-echelon field emission model.
6. Light microscopes require you to have an expectation of what you want to find.
It is challenging to locate something when you have no expectations about what it will look like under the microscope. You will need to consider whether it is moving or not. The item might be stained, pigmented, or filtered with markers, so you must understand what is aiding the color of the slide or object under study. Many students will look through a light microscope for the first time and think that what they are looking at is dirt if the settings are at a low enough magnification level.
When you have an electron microscope (especially a scanning model), then you have an equipment option which can allow you to match the pictures you see with current textbooks, online resources, and other research materials. You do not have that luxury when using a light microscope.
7. Light microscopes can come with very low magnification caps.
It is not unusual for an entry-level microscope to come equipped with a maximum magnification level of just 40x if you purchase one of the models priced under $100. Some models come with a power level as low as 3.5x to help you find the initial specimen that you wish to study, but there are models that do not go up much higher than this. The most frequently used lens when operating a light microscope is 10x, which can give you a final magnification of 100x when used in conjunction with a 10x ocular lens.
Is a Light Microscope the Best Option for Your Studies?
The advantages and disadvantages of a light microscope are taking advantage of an explosion in technological evolution that is occurring in this field. Advanced models that include fluorescent lighting making it possible for researchers to see two different proteins at the same location without requiring dyes that could harm the sample. When using the standard red and green markers, they overlap to form a yellow color that makes it easier than ever before to identify key components.
Although a light microscope does not come with the advanced components of an electron microscope, a compound model is very affordable and easy to use. You can still access more information about the micro-world when studying biology while enjoying an exceptional level of portability. That is why almost everyone’s first microscope ends up being a light microscope.