Is our modernizing culture killing Biophila? Natural versus Artificial Lighting

This topic submitted by Cassandra Solderitsch and Ross Meyer (solderce@miamioh.edu, meyerrp@miamioh.edu) at 3:37 pm on 12/7/00. Additions were last made on Wednesday, May 7, 2014. Section: Myers


Is our modernizing culture killing Biophilia?

Natural versus Artificial Light Affects on Mood

Cassandra Solderisch
Ross Meyer

Instructor: Chris Myers


Introduction and Relevance


The simplest and most lumpish fungus has a particular interest to us, compared with a mere mass of earth, because it is so obviously organic and related to ourselves, however mute . . . It is the expression of an idea; growth according to a law; matter not dormant, not raw, but inspired, appropriated by spirit . . . the humblest fungus betrays a life akin to my own. It is a successful poem in its kind.

Henry David Thoreau
W
riter and philosopher Henry David Thoreau writes of his intrinsic love toward nature in the October 10, 1858, entry to his journal (Mlot 1995). Thoreau evokes the essence of the feeling behind the Biophilia Hypothesis. This Biophilia Hypothesis was proposed more than a decade ago by sociobiologist and leading genetic researcher Edward O. Wilson in 1984 (Step 1994). The hypothesis states that Homo sapiens has a tendency to be interested in and respond emotionally to nature and that the response is genetically determined (Hill 1994). In other words, Biophilia proposes that people have an “innately emotional affiliation . . . to other living organisms” (Step 1994). Wilson went on to state that our emotions for living things are innate because of our having spent the bulk of our evolutionary history as hunter-gatherers in close contact with other species (Mlot 1995). Wilson then states that “whatever genetic configuration enabled our ancient ancestors to eke out a living persists in our urban lives today and expresses itself in our predilection for pets and houseplants, and in any responsiveness we might manifest to the loss of biological diversity
Edward O. Wilson
around us” (Mlot 1995). Therefore, as Wilson proposed in his Biophilia hypothesis, we as humans have a natural tendency to affiliate with nature.
However, could Biophilia be dying? We relate to our environment in differing ways, with different intensity and different sources. More simply, we learn to love what has become familiar (Orr 1994). Therefore, what we call “modernization” could represent a dramatic change in how we regard the natural world and our role in it. This “modernization” leads to a cultural affiliation with technology, human artifacts, and solely human interests rather than the natural world (Orr 1994). This new cultural affiliation with non-natural objects is termed biophobia, or, and aversion to nature (Orr 1994). This aversion to nature is “increasingly common among people raised with television, walkman radios attached to their heads, video games, and living amidst dense urban or suburban settings where nature is permitted as a decoration . . . it ranges from discomfort in ‘natural’ places to active scorn for whatever is not manmade, managed, or air-conditioned” (Orr 1994). So, has biophobia replaced the focus on a now-remote wilderness due to a changing culture, an adaptation of a sort? Do people still have a love, or affiliation, toward natural environments rather than artificial ones? Is Biophilia still applicable in our changing society as we “modernize”?

Therefore, we need to test the accuracy of the Biophilia Hypothesis. Do we affiliate with natural or artificial things? Does our upbringing cause this affiliation? To answer these questions, we need to discover if people have a tendency to prefer natural or artificial environments, and also if their preference correlates to their upbringing. If people preferred natural environments, then the Biophilia Hypothesis would be supported because it would display an affiliation to nature. Perhaps those people who prefer the natural would come from rural, naturalistic backgrounds that caused them to develop this love for nature. On the other hand, if people would have a tendency toward the artificial conditions, then perhaps the Biophilia Hypothesis is being replaced by biophobia. Perhaps these biophobics come from a background intensely urban fully exposed to the technological advances in our culture.
How then can we test people’s tendencies toward natural versus artificial conditions? One possibility is to test whether people prefer natural or artificial lighting. Also, we can test if natural light can affect our moods and behaviors, supporting Biophilia.
Much research has discovered that light definitely has an effect on human beings. Research has shown conclusively that light affects the human body in ways other than producing vision. The effects identified so far involve body rhythms. There are currently over 3000 references on light’s affect on human chronobiology (Kripke 1993). On example is the Seasonal Affective Disorder (SAD). SAD reveals some of the impacts of removing ourselves from natural light due to the changing society where people spend over 90 percent of their live indoors (Heimlich). SAD is a specific type of clinical depression due to shorter days and lack of natural light during winter (Heimlich).
Research has also been done exploring the affects of lighting on our human psychology. The amount of noise generated by groups of people under different luminous environments was the subject of study by Sanders and his associates (Sanders et al 1974). Sound pressure level readings were taken in a darkened corridor of a university classroom building. Highly significant results indicate that groups of students congregating in the hallway made less noise under the low light condition than with normal illuminance levels. A possible psychological interpretation is that low light levels are associated with contexts in which quietness is considered appropriate behavior, e.g. church, theater, museum, or cinema. Also, researches have studied the effects of illuminance levels on aggression. Their position that darkness acts as a disinhibitor was discussed in psychological terms and lead to the hypothesis that subjects would deliver stronger shocks to victims in a dimly lit setting than in a brightly lit setting (Page and Moss 1976). Three possible explanations for such disinhibiting were 1) darkness may increase feelings of anonymity, 2) people may be conditioned to associate darkness with uninhibited behavior (bars, parties, the bedroom, etc.), and 3) darkness isolates an aggressor from his victim. Both of these research studies demonstrate how lighting can affect human psychological behaviors.


Why does sunlight have such an impact on humans?
It is accepted that bright light can affect sleeping patterns, have an impact on the internal biological clock, and that the relative light during summer and winter can affect human energy levels (Heimlich). It is known that exposure to natural sunlight helps the human body process food better and encourages the production of vitamin D3 which is important for efficient use of calcium and phosphorus in the body (Heimlich). Also, sunlight activates an enzyme in the skin which produces a polymer of dopa (an amino acid) called melanin, which is the pigmentation in the skin (Heimlich). Furthermore, sunlight has an effect on the body through the eyes by stimulating the pineal gland to release a neurotransmitter called serotonin which helps regulate blood vessel constriction and a hormone called melatonin, which in excess induces sleep, drowsiness, and lethargy” (Heimlich). And last, natural light, or lack thereof, can affect our mood through neurophysiology. Lighting can also affect our mood based on our cognitive perceptions, and possibly unconscious perceptions (Zilber 1993). Light affects our levels of melatonin and serotonin. Melatonin, which helps us sleep, is produced in darkness. Light changes melatonin to serotonin. Serotonin helps us feel calm, alert and happy. Low light and low serotonin are linked to SAD and PMS, depression and irritability, weight gain, alcohol abuse, and migraines (Zilber 1993). This area of study is where our lab research comes into play. How can natural, or artificial, light affect our mood?
But first, we need to understand the differences between natural and artificial light. First, natural sunlight is more brightly lit—much more (Zilber 1993). The illuminance from the sky alone with the sun blocked can exceed 10,000 lux; and with direct sunlight added, illuminance can exceed 100,000 lux” (Rea 1993). How much light is usually around me?
Normal room 100-200 lux*
Brightly lit office or grocery store 1,000-2,000 lux*
Cloudy, January noon in Chicago 4,000 lux*
Spring sunrise 10,000 lux*
Summer early afternoon 100,000 lux*


*Lux is a measurement of light output or intensity (Rea 1993).

Artificial light, on the other hand, generally maximizes at only 1,000 lux (93 foot-candles) (Zilber 1993). Second, natural light from the sun is very uniform and diffuse and the amount of light varies smoothly over the course of the day (Zilber 1993). Also, the sky is blue (color temp. > 6000K), with changing color temperature smoothly throughout the course of the day, rarely dropping below 5000K (at noon), then increasing to over 10,000K (at dusk) (Rea 1993). Finally, there is significantly more UV light present, at all wavelengths (Zilber 1993). Natural light has the full spectrum of visible and invisible light with higher and lower wavelengths that artificial light lack (O.S.U.). Recent research suggests that people benefit more from full spectrum light than just bright light. Full spectrum light is the closest possible to natural sunlight. Also, full spectrum light is contains all the colors of the rainbow in proper balance.
What are the Reported Effects of Full Spectrum Light?
 Energy and moods
 Productivity and efficiency
 Mental alertness
 Visual acuity
 Immune system functioning
 Sleep patterns
 Blood pressure
 Stress & tension
 Sugar and starch cravings (O.S.U.).

Therefore, obviously, a natural light affects the human body in many ways due to its differences from artificial light. However, our research sets out to discover whether natural light affects human mood, supporting the Biophilia Hypothesis. Also, do people’s developmental backgrounds, gender, or attitude toward nature correlate with their affiliation to natural or artificial light and thus to Biophilia or Biophobia?

Hypothesis

We hypothesize that the Biophilia Hypothesis is still valid if people have a positive attitude/mood when exposed to natural sunlight rather than artificial light. Natural light and mood are positively correlated; increased natural light leads to increased positive mood, we hypothesize. Also, people more naturalistic and/or from more rural backgrounds less exposed to technology will have a higher affiliation to natural light than more urban, modernized people. If these relationships are validated by our research, then the Biophilia Hypothesis is still valid in our modernizing culture, or, at least, at the Miami University student body.


Materials and Methods


Materials
The only materials involved in this laboratory experiment are the six pictures we will be using to conduct our research inquiry.

Method

This method of testing is designed to determine if people have an aesthetic affiliation toward either natural light or artificial light. Also, this method will help us determine if the sun image affects a person’s affiliation with the light. It will also help us determine what mood people associate with a given type of light.
For this method, we will take one picture of a person in a dorm room sitting in a chair. This person will be wearing neutral clothing without many outstanding characteristics. Also, the room will be quite ordinary and plain without many outstanding features either. These constants are necessary so that the person’s perception isn’t swayed by other variables other than the one we are testing, light. We will then alter this photo on the computer to end up with six of the same picture with different light sources. The combinations of light sources will be as follows:
A. NO WINDOW, NO SUN, ARTIFICIAL LIGHT**
B. WINDOW PRESENT, NO SUN, NATURAL LIGHT
C. WINDOW PRESENT, NO SUN, ARTIFICIAL LIGHT*
D. WINDOW PRESENT, SUN PRESENT, NATURAL LIGHT
E. MULTIPLE WINDOWS, NO SUN, NATURAL LIGHT
F. MULTIPLE WINDOWS, SUN PRESENT, NATURAL LIGHT
* The artificial light will be coming from a typical dorm light or desk lamp.
** We added a piece of contemporary artwork in place of the window so that the pattern remains the same for all of the pictures. We thought that the pattern might be another variable affecting a person’s decisions. So, we added the painting to keep the pattern of the window. The painting is rather modern without any obvious images. It is simple shapes and colors. We needed a simple painting so that it would have minimal effect on a person’s decision.

We will then proceed to survey people’s moods associated with these pictures. We will do this by letting them judge the pictures in pairs, e.g. natural vs. artificial, or sun vs. no sun. We will show them all six pictures in these random pairs of two. We will select the picture pairs randomly so that the viewer doesn’t find out what we are testing and thus bias their perceptions. When we show a person the two pictures, we will have them fill out a mood rating that they associate with that picture versus the other. The mood rating will be a scale of 1 to 10, one being depressed and 10 being cheerful. They will do this rating for each of the six pictures in the pairs. Then, when they have finished rating the pictures, we will show them all of the pictures together and have them pick the most depressing and the most cheerful. We don’t initially show them all six pictures at once for fear they will know what we are testing. We want a completely unbiased initial response to the picture. Hopefully, if we can keep the variables low and constants high, they will be judging the pictures based on the form of light used in the picture. We surveyed 60 Miami students during a relatively short time period during the same time of day, probably between 12:00 and 3:00 on Tuesdays through Thursdays to try to eliminate other variables that may be factored in. The rating sheet we used to rate the people’s preferences is shown below.
PICTURE MOOD RATING SHEET

PICTURE SET 1 (PICS 1 & 2)
PIC 1

DEPRESSING CHEERFUL
1 2 3 4 5 6 7 8 9 10

PIC 2

DEPRESSING CHEERFUL
1 2 3 4 5 6 7 8 9 10


PICTURE SET 2 (PICS 3 & 4)
PIC 3

DEPRESSING CHEERFUL
1 2 3 4 5 6 7 8 9 10

PIC 4

DEPRESSING CHEERFUL
1 2 3 4 5 6 7 8 9 10

PICTURE SET 3 (PICS 5 & 6)
PIC 5

DEPRESSING CHEERFUL
1 2 3 4 5 6 7 8 9 10

PIC 6

DEPRESSING CHEERFUL
1 2 3 4 5 6 7 8 9 10

OVERALL
WHICH PIC WAS MOST DEPRESSING:
WHICH PIC WAS MOST CHEERFUL:
We used a three-part system to evaluate this rating system. First, we recorded the more cheerful rating for each picture set. In other words, if a person rated Picture 1 a 3 and Picture 2 a 7, we would count one for Picture 2. We recorded all of the higher ratings in each picture set (See “Picture Rating Results”). We recorded the higher rating and not the actual number ratings because of the possibility of bias. The person’s mood coming into the survey could drastically alter his/her ratings. Also, for this part of the survey, all we need to know is what picture people chose as more cheerful in respect to the other. We therefore don’t need to know how much more cheerful the person rated the picture. We are only trying to find out what picture the person saw as more cheerful. This set of data will be used qualitatively to assess people’s preferences for certain picture sets. Next, we recorded all of the Most Depressing and Most Cheerful pictures that people chose. This set of data will be used quantitatively to find out what pictures people chose as the most cheerful and most depressing. We will then graph these quantities for each picture on a bar graph. These will be used to compare the different variables, i.e. male vs. female, to determine any correlation and how the data differed according to each variable. We will then use a Spearman Rank Order Correlation Test to determine any differences or relationships between most depressing and most cheerful ratings for each picture. Next, we will use a Chi-Square Test to determine any significant differences between expected and actual results for each of the groups (See “Survey”). We will then use the Chi-Square Test to determine any significant differences between the total most cheerful and most depressing ratings for actual and expected results. All of these tests will determine if our research supports our hypotheses. Next, we surveyed the students. Below shows the survey we used.

Student Survey
NAME:
GENDER:
YEAR:
MAJOR:
BACKGROUND: (questions below)

HOW WOULD YOU DEFINE THE ENVIRONMENT IN THAT YOU GREW UP?

RURAL SUBURB URBAN

HOW NATURALISTIC WOULD YOU CONSIDER YOUR ATTITUDE TOWARD THE ENVIRONMENT?

1 2 3 4 5 6 7 8 9 10

NONE EXTREME

HOW MUCH LEISURE TIME, IF YOU COULD, IN ONE WEEK DO YOU SPEND OUTSIDE?

< 5 HOURS 16-25 HOURS
6-15 HOURS > 25 HOURS

HOW MUCH LEISURE TIME, IF YOU COULD, IN ONE WEEK DO YOU SPEND ON THE COMPUTER, PLAYING VIDEO GAMES, OR WATCHING THE TELEVISION?

< 5 HOURS 16-25 HOURS
6-15 HOURS > 25 HOURS

HOW MUCH CONCERN DO YOU HAVE FOR THE CONSERVATION OF THE NATURAL WORLD?

1 2 3 4 5 6 7 8 9 10

NONE AVERAGE EXTREME

CIRCLE ALL ACTIVITIES THAT YOU ENJOY DOING.
HIKING
WATCHING TV
PLAYING VIDEO GAMES
BIKING
USING THE INTERNET
OUTDOOR SPORTS

WHAT VACATION WOULD YOU GO ON IF YOU COULD? (CIRCLE ONE)
NEW YORK CITY
BAHAMAS
CHICAGO
L.A
ROCKY MOUNTAINS
TOKYO
YELLOWSTONE PARK
SKIING IN CANADA
From this survey, we will hopefully be able to identify any correlation between gender, attitude or background with a certain light affiliation. While gender and background are quite easily determined from the survey, determining a student’s attitude toward nature needed a systematic process. For our research, we wanted to determine if the students surveyed were either “Naturalistic” (strong respect and concern for nature), “Neutral” (middle ground of no clear opinion), or “Non-Naturalistic” (disrespect for nature). To do this, we asked a series of questions and then assessed the responses. We followed a set formula for evaluating the questions. First, we would use the student’s response to the question asking how naturalistic their attitude toward nature is. We rated a score of 1-3 as “Non-Naturalistic,” 4-6 as “Neutral,” and 7-10 as “Naturalistic.” This is the student’s initial score. Then, for the questions about time spent indoors and outdoors, if the student dedicated more time to outdoors activity, we would add one score to their first score. Likewise, if the student spent more time indoors, we would subtract one score from their initial score. Next, for the question about a concern for the environment, we used the same rating as the attitude question. If the person answered 7-10, then we would add one score to the existing score. If the person answered 4-6, then the existing score would not be changed. And last, if the person answered a 1-3, then we would minus one score from the existing score. From here, if the score were on the border (4 or 6), we would qualitatively assess the final two questions about activities and city/nature vacations to possibly push the score either way. Or, if there were no attitude apparent, then we would just keep that score. The reason we used these final two questions only qualitatively is because we understand that there are many other variables that need to be considered in these questions. For example, just because a person answered that they would go to New York City doesn’t necessarily mean that that person prefers a city environment for a vacation. Obviously, there are many other reasons why a person would want to go to New York City, not just because it is a city. So, we used these two questions only for a qualitative analysis if the score was borderline.
After analyzing each question, the student has a final score. A score of three or less would categorize that student as “Non-Naturalistic,” four to six as “Neutral,” and seven or above as “Naturalistic.” This is how we assessed a student’s attitude toward nature. We will use this data to determine if there are any correlations between attitude and light affiliations.
CLASS DAY:

For our class day, we decided to conduct the research on the students and then teach our study to the students to help them get a better understanding of the study. We first conducted the research so that the student’s responses weren’t biased. After we finished the research, we proceeded to discuss what people’s perceptions of the study were. We then went into a power-point presentation to present our study, hypothesis, background information, and relevant questions.
We decided not to let the students do the actual research because we thought that they would learn more about our study by actual engaging in it and then being taught the study. We thought that this was the best way to help the students become more acquainted with our study. Also, we needed to hold many constants in out study like time of surveying as well as the process of surveying. Many mistakes could be made and costs of copies of the color pictures would be tremendous.

RESEARCH TIMELINE:

Conducting Research:
Tuesday, Nov. 28
Wednesday, Nov. 29
Thursday, Nov. 30

Data Analysis:
Monday, Dec. 4
Tuesday, Dec. 5
Wednesday, Dec. 6
Thursday, Dec. 7

Post Final Report:
Friday, Dec. 8


Results


Data Sheet: Picture Ratings
The following data sheet is the results from our picture rating surveys of sixty Miami University students. The first table displays the results of the total students surveyed. The following tables are the results for specific groups of students determined by the background surveys, i.e. male, naturalistic, urban, etc. In the first data column of the tables, the results are given for how many students rated a certain picture more cheerful that the other in the picture set. For example, in the first table, first row, seventeen of the sixty students surveyed rated Picture A more cheerful than Picture B. The next two columns in the tables display how many people rated a picture most cheerful and most depressing. For instance, in the first table, first row, four of the sixty students rated Picture A as the most cheerful while thirteen of the sixty students rated Picture A as most depressing. Note: a legend for the pictures is included at the end of the tables.
From studying this data from the “Total” table, we can draw many conclusions. First, we can easily see that the highest picked picture as most depressing was Picture C. Picture C was with a window with its blind drawn and in artificial light. Because a majority of people rated this picture as most depressing, we can say that it is because of either the lighting or the window blind. Artificial lighting and a blind-drawn window both portray shutting off natural light and using artificia

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