SOCIAL LEARNING THEORY


SOCIAL LEARNING THEORY
Social learning theory posits that learning is a cognitive process that takes place in a social context and can occur purely through observation or direct instruction, even in the absence of motor reproduction or direct reinforcement. In addition to the observation of behavior, learning also occurs through the observation of rewards and punishments, a process known as vicarious reinforcement. The theory expands on traditional behavioral theories, in which behavior is governed solely by reinforcements, by placing emphasis on the important roles of various internal processes in the learning individual.
HISTORY
Prior to 1960, published theories of learning were heavily influenced by theories of classic conditioning, operant conditioning, and the psychoanalytic concept of drives. In 1959, Noam Chomsky published his criticism of B.F. Skinner’s book Verbal Behavior. In his review, Chomsky stated that pure stimulus-response theories of behavior could not account for the process of language acquisition, an argument that contributed significantly to psychology’s cognitive revolution.
Within this context, Albert Bandura studied learning processes that occurred in interpersonal contexts and were not adequately explained by theories of operant conditioning or existing models of social learning, such as the work of Julian Rotter. Specifically, Bandura argued that “the weaknesses of learning approaches that discount the influence of social variables are nowhere more clearly revealed than in their treatment of the acquisition of novel responses.” Skinner’s explanation of the acquisition of new responses relied on the process of successive approximation, which required multiple trials, reinforcement for components of behavior, and gradual change. Rotter’s theory proposed that the likelihood of a behavior occurring was a function of the subjective expectancy and value of the reinforcement. This model assumed a hierarchy of existing responses and thus did not (according to Bandura account for a response that had not yet been learned. Bandura began to conduct studies of the rapid acquisition of novel behaviors via social observation, the most famous of which were the Bobo doll experiments.
BOBO DOLL EXPERIMENTS
In 1961, Bandura and colleagues published the first paper on the results of the now-famous Bobo doll experiments. The Bobo doll is a child-sized inflatable doll with a weighted bottom that causes it to pop back up after being knocked down. In the first iteration of these studies, preschool-aged children were divided into three groups: one group that observed an adult behaving aggressively towards the Bobo doll (punching, kicking, striking with a mallet, yelling), another group that observed the adult playing peacefully, and a control group.
To control for possible peer influences, each participant viewed their assigned scenario individually. Later, the child was allowed to play independently in the play room which contained a variety of aggressive and non-aggressive toys, including the Bobo doll. Participants’ acts of verbal and physical aggression toward the Bobo doll were then recorded. Results revealed significant group differences, such that children exposed to the aggressive model were more likely to imitate what they had seen and behave aggressively toward the doll. Bandura and colleagues argued that the results supported that children could rapidly acquire novel behaviors through the process of observation and imitation, and this occurred even in the absence of any kind of reinforcement.
Subsequent variations on the original experiment provided additional insights into the social nature of learning. In a 1963 paper, Bandura and colleagues demonstrated that children imitated aggressive behavior witnessed on video, in addition to live observation, and children also imitated aggressive behaviors enacted by a cartoon character. An additional study, published in 1965, showed that witnessing the model being punished for the aggressive behavior decreased the likelihood that children would imitate the behavior, a process he referred to as vicarious reinforcement.
THEORY
Social learning theory integrated behavioral and cognitive theories of learning in order to provide a comprehensive model that could account for the wide range of learning experiences that occur in the real world. As initially outlined by Bandura and Walters in 1963 and further detailed in 1977, key tenets of social learning theory are as follows:
1. Learning is not purely behavioral; rather, it is a cognitive process that takes place in a social context.
2. Learning can occur by observing a behavior and by observing the consequences of the behavior (vicarious reinforcement).
3. Learning involves observation, extraction of information from those observations, and making decisions about the performance of the behavior (observational learning or modeling). Thus, learning can occur without an observable change in behavior.
4. Reinforcement plays a role in learning but is not entirely responsible for learning.
5. The learner is not a passive recipient of information. Cognition, environment, and behavior all mutually influence each other (reciprocal determinism).
Social learning theory draws heavily on the concept of modeling, or learning by observing a behavior. Bandura outlined three types of modeling stimuli:
• Live model
in which an actual person is demonstrating the desired behavior
• Verbal instruction
in which an individual describes the desired behavior in detail and instructs the participant in how to engage in the behavior
• Symbolic
in which modeling occurs by means of the media, including movies, television, Internet, literature, and radio. Stimuli can be either real or fictional characters.
Exactly what information is gleaned from observation is influenced by the type of model, as well as a series of cognitive and behavioral processes, including:[3]
• Attention
In order to learn, observers must attend to the modeled behavior. Attention is impacted by characteristics of the observer (e.g., perceptual abilities, cognitive abilities, arousal, past performance) and characteristics of the behavior or event (e.g., relevance, novelty, affective valence, and functional value).
• Retention
In order to reproduce an observed behavior, observers must be able to remember features of the behavior. Again, this process is influenced by observer characteristics (cognitive capabilities, cognitive rehearsal) and event characteristics (complexity).
• Reproduction
To reproduce a behavior, the observer must organize responses in accordance with the model. Observer characteristics affecting reproduction include physical and cognitive capabilities and previous performance.
• Motivation
The decision to reproduce (or refrain from reproducing) an observed behavior is dependent on the motivations and expectations of the observer, including anticipated consequences and internal standards.
An important factor in social learning theory is the concept of reciprocal determinism. This notion states that just as an individual’s behavior is influenced by the environment, the environment is also influenced by the individual’s behavior.[11] In other words, a person’s behavior, environment, and personal qualities all reciprocally influence each other. For example, a child who plays violent video games will likely influence their peers to play as well, which then encourages the child to play more often. This could lead to the child becoming desensitized to violence, which in turn will likely affect the child’s real life behaviors.
APPLICATIONS
Criminology
Social learning theory has been used to explain the emergence and maintenance of deviant behavior, especially aggression. Criminologists Ronald Akers and Robert Burgess integrated the principles of social learning theory and operant conditioning with Edwin Sutherland’s Differential Association Theory to create a comprehensive theory of criminal behavior. Burgess and Akers emphasized that criminal behavior is learned in both social and nonsocial situations through combinations of direct reinforcement, vicarious reinforcement, explicit instruction, and observation. Both the probability of being exposed to certain behaviors and the nature of the reinforcement are dependent on group norms.
Developmental psychology
In her book Theories of Developmental Psychology, Patricia H. Miller lists both moral development and gender-role development as important areas of research within social learning theory. Social learning theorists emphasize observable behavior regarding the acquisition of these two skills. For gender-role development, the same-sex parent provides only one of many models from which the individual learns gender-roles. Social learning theory also emphasizes the variable nature of moral development due to the changing social circumstances of each decision: “The particular factors the child thinks are important vary from situation to situation, depending on variables such as which situational factors are operating, which causes are most salient, and what the child processes cognitively. Moral judgments involve a complex process of considering and weighing various criteria in a given social situation.”
For social learning theory, gender development has to do with the interactions of numerous social factors, involving all the interactions the individual encounters. For social learning theory, biological factors are important but take a back seat to the importance of learned, observable behavior. Because of the highly gendered society in which an individual might develop, individuals begin to distinguish people by gender even as infants. Bandura’s account of gender allows for more than cognitive factors in predicting gendered behavior: for Bandura, motivational factors and a broad network of social influences determine if, when, and where gender knowledge is expressed.
MANAGEMENT
Social Learning theory proposes that rewards aren’t the sole force behind creating motivation. Thoughts, beliefs, morals, and feedback all help to motivate us. Three other ways in which we learn are vicarious experience, verbal persuasion, and physiological states. Modeling, or the scenario in which we see someone’s behaviors and adopt them as our own, aide the learning process as well as mental states and the cognitive process.
Media violence
Principles of social learning theory have been applied extensively to the study of media violence. Akers and Burgess hypothesized that observed or experienced positive rewards and lack of punishment for aggressive behaviors reinforces aggression. Many research studies have discovered significant correlations between viewing violent television and aggression later in life, as well as playing violent video games and aggressive behaviors. The role of observational learning has also been cited as an important factor in the rise of rating systems for TV, movies, and video games.
Psychotherapy
Another important application of social learning theory has been in the treatment and conceptualization of anxiety disorders. The classical conditioning approach to anxiety disorders, which spurred the development of behavioral therapy and is considered by some to be the first modern theory of anxiety, began to lose steam in the late 1970s as researchers began to question its underlying assumptions. For example, the classical conditioning approach holds that pathological fear and anxiety are developed through direct learning; however, many people with anxiety disorders cannot recall a traumatic conditioning event, in which the feared stimulus was experienced in close temporal and spatial contiguity with an intrinsically aversive stimulus. Social learning theory helped salvage learning approaches to anxiety disorders by providing additional mechanisms beyond classical conditioning that could account for the acquisition of fear. For example, social learning theory suggests that a child could acquire a fear of snakes by observing a family member express fear in response to snakes. Alternatively, the child could learn the associations between snakes and unpleasant bites through direct experience, without developing excessive fear, but could later learn from others that snakes can have deadly venom, leading to a re-evaluation of the dangerousness of snake bites, and accordingly, a more exaggerated fear response to snakes.
SCHOOL PSYCHOLOGY
Many classroom and teaching strategies draw on principles of social learning to enhance students’ knowledge acquisition and retention. For example, using the technique of guided participation, a teacher says a phrase and asks the class to repeat the phrase. Thus, students both imitate and reproduce the teacher’s action, aiding retention. An extension of guided participation is reciprocal learning, in which both student and teacher share responsibility in leading discussions. Additionally, teachers can shape the classroom behavior of students by modelling appropriate behavior and visibly rewarding students for good behavior. By emphasizing the teacher’s role as model and encouraging the students to adopt the position of observer, the teacher can make knowledge and practices explicit to students, enhancing their learning outcomes.

REFERENCES
1. Bandura, Albert (1963). Social learning and personality development. New York: Holt, Rinehart, and Winston.
2. Albert Bandura (1971). “Social Learning Theory”. General Learning Corperation. Retrieved 25 December 2013.
3. Bandura, A. (1972). Parke, R.D., ed. Recent trends in social learning theory. New York: Academic Press, Inc.
4. Chomsky, Noam (1959). “A review of B. F. Skinner’s Verbal Behavior”. Language 35 (1): 26–58.
5. Skinner, B. F. (1957). Verbal behavior. New York: Appleton-Century-Crofts.
6. Skinner, B. F. (1963). Science and human behavior. New York: Appleton.
7. Rotter, Julian (1954). Social learning and clinical psychology. Englewood Cliffs, New Jersey: Prentice-Hall.
8. Bandura, A.; Ross, D.; Ross, S.A. (1961). “Transmission of aggression through the imitation of aggressive models”. Journal of Abnormal and Social Psychology 63 (3): 575–582. doi:10.1037/h0045925. PMID 13864605.
9. Bandura, A.; Ross, D; Ross, S.A. (1963). “Imitation of film-mediated aggressive models”. Journal of Abnormal and Social Psychology 66 (1): 3–11. doi:10.1037/h0048687.
10. Bandura, Albert (1965). “Influence of models’ reinforcement contingencies on the acquisition of imitative responses”. Journal of Personality and Social Psychology 1 (6): 589–595. doi:10.1037/h0022070.

IS GAMBLING A SIN, WHAT DOES THE BIBLE SAY ABOUT GAMBLING.


IS GAMBLING A SIN,
WHAT DOES THE BIBLE SAY ABOUT GAMBLING.
Surprisingly, the Bible contains no specific command to avoid gambling. However, the Bible does contain timeless principles for living a life pleasing to God and is filled with wisdom to deal with every situation, including gambling.
Throughout the Old and New Testaments, we read about people casting lots when a decision had to be made. In most instances, this was simply a way of determining something impartially:
Joshua then cast lots for them in Shiloh in the presence of the LORD, and there he distributed the land to the Israelites according to their tribal divisions. (Joshua 18:10, NIV)
Casting lots was common among many ancient cultures. Roman soldiers cast lots for Jesus’ garments at his crucifixion:
“Let’s not tear it,” they said to one another. “Let’s decide by lot who will get it.” This happened that the scripture might be fulfilled which said, “They divided my garments among them and cast lots for my clothing.” So this is what the soldiers did. (John 19:24, NIV)
Does the Bible Mention Gambling?
Although the words “gambling” and “gamble” do not appear in the Bible, we cannot assume that an activity is not a sin simply because it is not mentioned. Looking at pornography on the Internet and using illegal drugs are not mentioned either, but both violate God’s laws.
While casinos and lotteries promise thrills and excitement, obviously people gamble to try to win money. Scripture gives very specific instructions about what our attitude should be toward money:
Whoever loves money never has money enough; whoever loves wealth is never satisfied with his income. This too is meaningless. (Ecclesiastes 5:10, NIV)
“No servant can serve two masters. [Jesus said.] Either he will hate the one and love the other, or he will be devoted to the one and despise the other. You cannot serve both God and money.” (Luke 16:13, NIV)
For the love of money is a root of all kinds of evil. Some people, eager for money, have wandered from the faith and pierced themselves with many griefs. (1 Timothy 6:10, NIV)
Gambling is a way to bypass work, but the Bible counsels us to persevere and work hard:
Lazy hands make a man poor, but diligent hands bring wealth. (Proverbs 10:4, NIV)
One of the key principles in the Bible is that people should be wise stewards of everything God gives them, including their time, talent and treasure. Gamblers may believe they earn their money with their own labor and may spend it as they please, yet God gives people the talent and health to carry out their jobs, and their very life is a gift from him as well. Wise stewardship of extra money calls believers to invest it in the Lord’s work or to save it for an emergency, rather than lose it in games in which the odds are stacked against the player.
Gamblers covet more money, but they may also covet the things money can buy, such as cars, boats, houses, expensive jewelry and clothing. The Bible forbids a covetous attitude in the Tenth Commandment:
“You shall not covet your neighbor’s house. You shall not covet your neighbor’s wife, or his manservant or maidservant, his ox or donkey, or anything that belongs to your neighbor.” (Exodus 20:17, NIV)
Gambling also has the potential to turn into an addiction, like drugs or alcohol. According to the National Council on Problem Gambling, 2 million U.S. adults are pathological gamblers and another 4 to 6 million are problem gamblers. This addiction can destroy the stability of the family, lead to job loss, and cause a person to lose control of their life:
…for a man is a slave to whatever has mastered him. (2 Peter 2:19)
Some argue that gambling is nothing more than entertainment, no more immoral than going to a movie or concert. People who attend movies or concerts expect only entertainment in return, however, not money. They are not tempted to keep spending until they “break even.”
Finally, gambling provides a sense of false hope. Participants place their hope in winning, often against astronomical odds, instead of placing their hope in God. Throughout the Bible, we are constantly reminded that our hope is in God alone, not money, power, or position:
Find rest, O my soul, in God alone; my hope comes from him. (Psalm 62:5, NIV)
May the God of hope fill you with all joy and peace as you trust in him, so that you may overflow with hope by the power of the Holy Spirit. (Romans 15:13, NIV)
Command those who are rich in this present world not to be arrogant nor to put their hope in wealth, which is so uncertain, but to put their hope in God, who richly provides us with everything for our enjoyment. (1 Timothy 6:17, NIV)
Some Christians believe that church raffles, bingos and the like to raise funds for Christian education and ministries are harmless fun, a form of donation involving a game. Their logic is that, as with alcohol, an adult should act responsibly. In those circumstances, it seems unlikely someone would lose a large amount of money.
God’s Word is No Gamble
Every leisure activity is not a sin, but all sin is not clearly listed in the Bible. Added to that, God doesn’t just want us not to sin, but he gives us an even higher goal. The Bible encourages us to consider our activities in this way:
“Everything is permissible for me”—but not everything is beneficial. “Everything is permissible for me”—but I will not be mastered by anything. (1 Corinthians 6:12, NIV)
This verse appears again in 1 Corinthians 10:23, with the addition of this idea: “Everything is permissible”—but not everything is constructive.” When an activity is not distinctly described as sin in the Bible, we can ask ourselves these questions: “Is this activity beneficial for me or will it become my master? Will participation in this activity be constructive or destructive to my Christian life and witness?”
The Bible does not explicitly say, “Thou shalt not play blackjack.” Yet by gaining a thorough knowledge of the Scriptures we have a trustworthy guide for determining what pleases and displeases God.
BETTING
So I do not see anything wrong in betting weather you call it pool or online or offline betting as well as baba ijebu or lottery they are not sin.i say this because neither you nor the bookies knew about the outcome of the events you have placed bets on.it will be a sin when the outcome have been known and when bets are place one party is trying to cheat or defraud the other.
Valentine c. uwakwe
08033559733

Question: “Is gambling a sin? What does the Bible say about gambling?”

Answer: The Bible does not specifically condemn gambling, betting, or the lottery. The Bible does warn us, however, to stay away from the love of money (1 Timothy 6:10; Hebrews 13:5). Scripture also encourages us to stay away from attempts to “get rich quick” (Proverbs 13:11; 23:5; Ecclesiastes 5:10). Gambling most definitely is focused on the love of money and undeniably tempts people with the promise of quick and easy riches.

What is wrong with gambling? Gambling is a difficult issue because if it is done in moderation and only on occasion, it is a waste of money, but it is not necessarily evil. People waste money on all sorts of activities. Gambling is no more or less of a waste of money than seeing a movie (in many cases), eating an unnecessarily expensive meal, or purchasing a worthless item. At the same time, the fact that money is wasted on other things does not justify gambling. Money should not be wasted. Excess money should be saved for future needs or given to the Lord’s work, not gambled away.

While the Bible does not explicitly mention gambling, it does mention events of “luck” or “chance.” As an example, casting lots is used in Leviticus to choose between the sacrificial goat and the scapegoat. Joshua cast lots to determine the allotment of land to the various tribes. Nehemiah cast lots to determine who would live inside the walls of Jerusalem. The apostles cast lots to determine the replacement for Judas. Proverbs 16:33 says, “The lot is cast in the lap, but its every decision is from the Lord.”

What would the Bible say about casinos and lotteries? Casinos use all sorts of marketing schemes to entice gamblers to risk as much money as possible. They often offer inexpensive or even free alcohol, which encourages drunkenness, and thereby a decreased ability to make wise decisions. Everything in a casino is perfectly rigged for taking money in large sums and giving nothing in return, except for fleeting and empty pleasures. Lotteries attempt to portray themselves as a way to fund education and/or social programs. However, studies show that lottery participants are usually those who can least afford to be spending money on lottery tickets. The allure of “getting rich quick” is too great a temptation to resist for those who are desperate. The chances of winning are infinitesimal, which results in many peoples’ lives being ruined.

Can lotto/lottery proceeds please God? Many people claim to be playing the lottery or gambling so that they can give the money to the church or to some other good cause. While this may be a good motive, reality is that few use gambling winnings for godly purposes. Studies show that the vast majority of lottery winners are in an even worse financial situation a few years after winning a jackpot than they were before. Few, if any, truly give the money to a good cause. Further, God does not need our money to fund His mission in the world. Proverbs 13:11 says, “Dishonest money dwindles away, but he who gathers money little by little makes it grow.” God is sovereign and will provide for the needs of the church through honest means. Would God be honored by receiving donated drug money or money stolen in a bank robbery? Of course not. Neither does God need or want money that was “stolen” from the poor in the temptation for riches.

First Timothy 6:10 tells us, “For the love of money is a root of all kinds of evil. Some people, eager for money, have wandered from the faith and pierced themselves with many griefs.” Hebrews 13:5 declares, “Keep your lives free from the love of money and be content with what you have, because God has said, ‘Never will I leave you; never will I forsake you.’” Matthew 6:24 proclaims, “No one can serve two masters. Either he will hate the one and love the other, or he will be devoted to the one and despise the other. You cannot serve both God and Money.”

Gambling
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Gambling, or gaming, is the staking of money or other thing of value on the issue of a game of chance. It thus belongs to the class of aleatory contracts which the gain or loss of the parties depends on an uncertain event. It is not gambling, in the strict sense, if a bet is laid on the issue of a game of skill like billiards or football. The issue must depend on chance, as in dice, or partly on chance, partly on skill, as in whist. Moreover, in ordinary parlance, a person who plays for small stakes to give zest to the game is not said to gamble; gambling connotes playing for high stakes.
In its moral aspect, although gambling usually has a bad meaning, yet we may apply to it what was said about betting. On certain conditions, and apart from excess or scandal, it is not sinful to stake money on the issue of a game of chance any more than it is sinful to insure one’s property against risk, or deal in futures on the produce market. As I may make a free gift of my own property to another if I choose, so I may agree with another to hand over to him a sum of money if the issue of a game of cards is other than I expect, while he agrees to do the same in my favour in the contrary event.
Theologians commonly require four conditions so that gaming may not be illicit.
• What is staked must belong to the gambler and must be at his free disposal. It is wrong, therefore, for the lawyer to stake the money of his client, or for anyone to gamble with what is necessary for the maintenance of his wife and children.
• The gambler must act freely, without unjust compulsion.
• There must be no fraud in the transaction, although the usual ruses of the game may be allowed. It is unlawful, accordingly, to mark the cards, but it is permissible to conceal carefully from an opponent the number of trump cards one holds.
• Finally, there must be some sort of equality between the parties to make the contract equitable; it would be unfair for a combination of two expert whist players to take the money of a couple of mere novices at the game.
If any of these conditions be wanting, gambling becomes more or less wrong; and, besides, there is generally an element of danger in it which is quite sufficient to account for the bad name which it has. In most people gambling arouses keen excitement, and quickly develops into a passion which is difficult to control. If indulged in to excess it leads to loss of time, and usually of money; to an idle and useless life spent in the midst of bad company and unwholesome surroundings; and to scandal which is a source of sin and ruin to others. It panders to the craving for excitement and in many countries it has become so prevalent that it rivals drunkenness in its destructive effects on the lives of the people. It is obvious that the moral aspect of the question is not essentially different if for a game of chance is substituted a horse-race, a football or cricket match, or the price of stock or produce at some future date. Although the issue in these cases seldom depends upon chance, still the moral aspect of betting upon it is the same in so far as the issue is unknown or uncertain to the parties who make the contract. Time bargains, difference transactions, options, and other speculative dealings on the exchanges, which are so common nowadays, add to the malice of gambling special evils of their own. They lead to the disturbance of the natural prices of commodities and securities, do grave injury to producers and consumers of those commodities, and are frequently attended by such unlawful methods of influencing prices as the dissemination of false reports, cornering, and the fierce contests of “bulls” and “bears”, i.e. of the dealers who wish respectively to raise or lower prices.
Hitherto we have prescinded from positive law in our treatment of the question of gambling. It is, however, a matter on which both the civil and the canon law have much to say. In the United States the subject lies outside the province of the Federal Government, but many of the States make gambling a penal offence when the bet is upon an election, a horse-race, or a game of chance. Betting contracts and securities given upon a bet are often made void. In England the Gaming Act, 1845, voids contracts made by way of gaming and wagering; and the Gaming Act, 1892, renders null and void any promise, express or implied, to pay any person any sum of money under, or in respect of, any contract or agreement rendered null and void by the Gaming Act, 1845, or to pay any sum of money by way of commission, fee, reward, or otherwise, in respect of any such contract or agreement, or of any services in relation thereto or in connection therewith.
From very early times gambling was forbidden by canon law. Two of the oldest (41, 42) among the so-called canons of the Apostles forbade games of chance under pain of excommunication to clergy and laity alike. The 79th canon of the Council of Elvira (306) decreed that one of the faithful who had been guilty of gambling might be, on amendment, restored to communion after the lapse of a year. A homily (the famous “De Aleatoribus”) long ascribed by St. Cyprian, but by modern scholars variously attributed to Popes Victor I, Callistus I, and Melchiades, and which undoubtedly is a very early and interesting monument of Christian antiquity, is a vigorous denunciation of gambling. The Fourth Lateran Council (1215), by a decree subsequently inserted in the “Corpus Juris”, forbade clerics to play or to be present at games of chance. Some authorities, such as Aubespine, have attempted to explain the severity of the ancient canons against gambling by supposing that idolatry was often connected with it in practice. The pieces that were played with were small-sized idols, or images of the gods, which were invoked by the players for good luck. However, as Benedict XIV remarks, this can hardly be true, as in that case the penalties would have been still more severe.
Profane writers of antiquity are almost as severe in their condemnation of gambling as are the councils of the Christian Church. Tacitus and Ammianus Marcellinus tell us that by gambling men are led into fraud, cheating, lying, perjury, theft, and other enormities; while Peter of Blois says that dice is the mother of perjury, theft, and sacrilege. The old canonists and theologians remark that although the canons generally mention only dice by name, yet under this appellation must be understood all games of chance; and even those that require skill, if they are played for money.
The Council of Trent contented itself with ordering all the ancient canons on the subject to be observed, and in general prescribed that the clergy were to abstain from unlawful games. As Benedict XIV remarks, it was left to the judgment of the bishops to decide what games should be held to be unlawful according to the different circumstances of person, place, and time. St. Charles Borromeo, in the first Synod of Milan, put the Tridentine decree into execution, and drew up a list of games which were forbidden to the clergy, and another list of those that were allowed. Among those which he forbade were not only dicing in various forms, but also games something like our croquet and football. Other particular councils declared that playing at dice and cards was unbecoming and forbidden to clerics, and in general they forbade all games which were unbecoming to the clerical state. Thus, a council held at Bordeaux in 1583 decreed that the clergy were to abstain altogether from playing in public or in private at dice, cards, or any other forbidden and unbecoming game. The council held at Aix in 1585 forbade them to play at cards, dice or any other game of the like kind, and even to look on at the playing of such games. Another, held at Narbonne in 1609, decreed that clerics were not to play at dice, cards, or other unlawful and unbecoming games, especially in public.
There was some doubt as to whether chess was to be considered an unbecoming, and therefore, an unlawful, game for clerics. In the opinion of St. Peter Damian it was certainly unlawful. On one occasion he caught the Bishop of Florence playing chess, to while away the time when on a journey. The bishop tried to defend himself by saying that chess was not dice. The saint, however, refused to admit the distinction, especially as the bishop was playing in public. Scripture, he said, does not make express mention of chess, but it is comprised under the term dice. And Baronius defends the saint’s doctrine. Some sciolist, he remarks, may say that St. Peter Damian was under a delusion in classing chess under dice, since chess is not a game of chance but calls for the exercise of much skill and talent. Let that be as it may, he proceeds, priests must at any rate be guided in their conduct by the words of St. Paul, who declared that what is not expedient, what is not edifying, is not allowed.
Modern ecclesiastical law is less exacting in this matter. The provincial Councils of Westminster are content with prescribing that clerics must abstain from unlawful games. The Plenary School of Maynooth, held in 1900, says that since not a little time is occasionally lost, and idleness is fostered by playing cards, the priest should be on his guard against such games, especially where money is staked, lest he incur the reproach of being a gambler. He is also exhorted to deter the laity by word and example from betting at horse-races, especially when the stakes are high. The Second Plenary Council of Baltimore made a distinction between games which may not suitably be indulged in by a cleric, even when played in private, and games like cards which may be played for the sake of innocent recreation. It repeated the prohibition of the First Plenary Council of Baltimore that clerics are not to indulge in unlawful games, and only in moderation are to use those that are lawful, so as not to cause scandal. Nowadays, it is commonly held that positive ecclesiastical law only forbids games of chance, even to the clergy, when in themselves or for some extrinsic reason, such as loss of time or scandal, they are forbidden by the natural law.

Isn’t gambling a sin? How then can you Catholics justify playing bingo?–and in church yet!
Answer
First of all, the stereotype of bingo-playing Catholics is really overblown. The vast majority of parishes don’t even have a bingo night. Second, gambling is not in and of itself wrong. Read your Bible and you will not find gambling condemned anywhere in it.
The average gambler loses money, but the process is entertaining, so what gambling amounts to is paying money to be entertained, and there is nothing wrong with that.
Gambling becomes sinful only when one pays too much money for the entertainment. A person in a casino spending thousands of dollars that his family needs is committing a sin, and the Church is very firm about this (Catechism of the Catholic Church 2413). It would likewise be sinful for a person to spend thousands of dollars his family needed on other forms of entertainment, too, like limited edition books, movies, collector’s items, or whatever.
However, if you can afford it, there is nothing wrong with spending a few dollars for an evening of entertainment, whether it is bingo, the movies, or something else. In fact, spending a few dollars on an evening playing bingo in a church basement with a bunch of fellow Christians is probably a more wholesome activity than spending the same amount of money going to see a typical movie–or for that matter staying home and watching TV for free.

Nervous system


Nervous system
Nervous system

The Human Nervous System.
The nervous system is the part of an animal’s body that coordinates its voluntary and involuntary actions and transmits signals between different parts of its body. Nervous tissue first arose in wormlike organisms about 550 to 600 million years ago. In most animal species it consists of two main parts, the central nervous system (CNS) and the peripheral nervous system (PNS). The CNS contains the brain and spinal cord. The PNS consists mainly of nerves, which are enclosed bundles of the long fibers or axons, that connect the CNS to every other part of the body. The PNS includes motor neurons, mediating voluntary movement; the autonomic nervous system, comprising the sympathetic nervous system and the parasympathetic nervous system, which regulate involuntary functions, and the enteric nervous system, which functions to control the gastrointestinal system.
At the cellular level, the nervous system is defined by the presence of a special type of cell, called the neuron, also known as a “nerve cell”. Neurons have special structures that allow them to send signals rapidly and precisely to other cells. They send these signals in the form of electrochemical waves traveling along thin fibers called axons, which cause chemicals called neurotransmitters to be released at junctions called synapses. A cell that receives a synaptic signal from a neuron may be excited, inhibited, or otherwise modulated. The connections between neurons can form neural circuits and also neural networks that generate an organism’s perception of the world and determine its behavior. Along with neurons, the nervous system contains other specialized cells called glial cells (or simply glia), which provide structural and metabolic support.
Nervous systems are found in most multicellular animals, but vary greatly in complexity. The only multicellular animals that have no nervous system at all are sponges, placozoans and mesozoans, which have very simple body plans. The nervous systems of the radially symmetric organisms the ctenophores (comb jellies) and cnidarians (which include anemones, hydras, corals and jellyfish) consist of a diffuse nerve net. All other animal species, with the exception of a few types of worm, have a nervous system containing a brain, a central cord (or two cords running in parallel), and nerves radiating from the brain and central cord. The size of the nervous system ranges from a few hundred cells in the simplest worms, to around 100 billion cells in humans.
The central nervous system functions to send signals from one cell to others, or from one part of the body to others and to receive feedback. Malfunction of the nervous system can occur as a result of genetic defects, physical damage due to trauma or toxicity, infection or simply of ageing. The medical specialty of neurology studies disorders of the nervous system and looks for interventions that can prevent or treat them. In the peripheral nervous system, the most common problem is the failure of nerve conduction, which can be due to different causes including diabetic neuropathy and demyelinating disorders such as multiple sclerosis and amyotrophic lateral sclerosis.
Neuroscience is the field of science that focuses on the study of the nervous system.
Structure
The nervous system derives its name from nerves, which are cylindrical bundles of fibers (the axons of neurons), that emanate from the brain and spinal cord, and branch repeatedly to innervate every part of the body. Nerves are large enough to have been recognized by the ancient Egyptians, Greeks, and Romans, but their internal structure was not understood until it became possible to examine them using a microscope. A microscopic examination shows that nerves consist primarily of axons, along with different membranes that wrap around them and segregate them into fascicles. The neurons that give rise to nerves do not lie entirely within the nerves themselves—their cell bodies reside within the brain, spinal cord, or peripheral ganglia.
All animals more advanced than sponges have nervous systems. However, even sponges, unicellular animals, and non-animals such as slime molds have cell-to-cell signalling mechanisms that are precursors to those of neurons. In radially symmetric animals such as the jellyfish and hydra, the nervous system consists of a nerve net, a diffuse network of isolated cells. In bilaterian animals, which make up the great majority of existing species, the nervous system has a common structure that originated early in the Ediacaran period, over 550 million years ago.
Cells
The nervous system contains two main categories or types of cells: neurons and glial cells.
Neurons
The nervous system is defined by the presence of a special type of cell—the neuron (sometimes called “neurone” or “nerve cell”). Neurons can be distinguished from other cells in a number of ways, but their most fundamental property is that they communicate with other cells via synapses, which are membrane-to-membrane junctions containing molecular machinery that allows rapid transmission of signals, either electrical or chemical. Many types of neuron possess an axon, a protoplasmic protrusion that can extend to distant parts of the body and make thousands of synaptic contacts. Axons frequently travel through the body in bundles called nerves.
Even in the nervous system of a single species such as humans, hundreds of different types of neurons exist, with a wide variety of morphologies and functions. These include sensory neurons that transmute physical stimuli such as light and sound into neural signals, and motor neurons that transmute neural signals into activation of muscles or glands; however in many species the great majority of neurons receive all of their input from other neurons and send their output to other neurons.
Glial cells
Glial cells (named from the Greek for “glue”) are non-neuronal cells that provide support and nutrition, maintain homeostasis, form myelin, and participate in signal transmission in the nervous system. In the human brain, it is estimated that the total number of glia roughly equals the number of neurons, although the proportions vary in different brain areas. Among the most important functions of glial cells are to support neurons and hold them in place; to supply nutrients to neurons; to insulate neurons electrically; to destroy pathogens and remove dead neurons; and to provide guidance cues directing the axons of neurons to their targets. A very important type of glial cell (oligodendrocytes in the central nervous system, and Schwann cells in the peripheral nervous system) generates layers of a fatty substance called myelin that wraps around axons and provides electrical insulation which allows them to transmit action potentials much more rapidly and efficiently.

Anatomy in vertebrates

Diagram showing the major divisions of the vertebrate nervous system.
The nervous system of vertebrates (including humans) is divided into the central nervous system (CNS) and the peripheral nervous system (PNS).
The (CNS) is the major division, and consists of the brain and the spinal cord.[11] The spinal canal contains the spinal cord, while the head contains the brain. The CNS is enclosed and protected by the meninges, a three-layered system of membranes, including a tough, leathery outer layer called the dura mater. The brain is also protected by the skull, and the spinal cord by the vertebrae.
The peripheral nervous system (PNS) is a collective term for the nervous system structures that do not lie within the CNS. The large majority of the axon bundles called nerves are considered to belong to the PNS, even when the cell bodies of the neurons to which they belong reside within the brain or spinal cord. The PNS is divided into somatic and visceral parts. The somatic part consists of the nerves that innervate the skin, joints, and muscles. The cell bodies of somatic sensory neurons lie in dorsal root ganglia of the spinal cord. The visceral part, also known as the autonomic nervous system, contains neurons that innervate the internal organs, blood vessels, and glands. The autonomic nervous system itself consists of two parts: the sympathetic nervous system and the parasympathetic nervous system. Some authors also include sensory neurons whose cell bodies lie in the periphery (for senses such as hearing) as part of the PNS; others, however, omit them.

The vertebrate nervous system can also be divided into areas called grey matter (“gray matter” in American spelling) and white matter. Grey matter (which is only grey in preserved tissue, and is better described as pink or light brown in living tissue) contains a high proportion of cell bodies of neurons. White matter is composed mainly of myelinated axons, and takes its color from the myelin. White matter includes all of the nerves, and much of the interior of the brain and spinal cord. Grey matter is found in clusters of neurons in the brain and spinal cord, and in cortical layers that line their surfaces. There is an anatomical convention that a cluster of neurons in the brain or spinal cord is called a nucleus, whereas a cluster of neurons in the periphery is called a ganglion. There are, however, a few exceptions to this rule, notably including the part of the forebrain called the basal ganglia.
“Identified” neurons
A neuron is called identified if it has properties that distinguish it from every other neuron in the same animal—properties such as location, neurotransmitter, gene expression pattern, and connectivity—and if every individual organism belonging to the same species has one and only one neuron with the same set of properties. In vertebrate nervous systems very few neurons are “identified” in this sense—in humans, there are believed to be none—but in simpler nervous systems, some or all neurons may be thus unique. In the roundworm C. elegans, whose nervous system is the most thoroughly described of any animal’s, every neuron in the body is uniquely identifiable, with the same location and the same connections in every individual worm. One notable consequence of this fact is that the form of the C. elegans nervous system is completely specified by the genome, with no experience-dependent plasticity.
The brains of many molluscs and insects also contain substantial numbers of identified neurons. In vertebrates, the best known identified neurons are the gigantic Mauthner cells of fish. Every fish has two Mauthner cells, located in the bottom part of the brainstem, one on the left side and one on the right. Each Mauthner cell has an axon that crosses over, innervating neurons at the same brain level and then travelling down through the spinal cord, making numerous connections as it goes. The synapses generated by a Mauthner cell are so powerful that a single action potential gives rise to a major behavioral response: within milliseconds the fish curves its body into a C-shape, then straightens, thereby propelling itself rapidly forward. Functionally this is a fast escape response, triggered most easily by a strong sound wave or pressure wave impinging on the lateral line organ of the fish. Mauthner cells are not the only identified neurons in fish—there are about 20 more types, including pairs of “Mauthner cell analogs” in each spinal segmental nucleus. Although a Mauthner cell is capable of bringing about an escape response individually, in the context of ordinary behavior other types of cells usually contribute to shaping the amplitude and direction of the response.
Mauthner cells have been described as command neurons. A command neuron is a special type of identified neuron, defined as a neuron that is capable of driving a specific behavior individually. Such neurons appear most commonly in the fast escape systems of various species—the squid giant axon and squid giant synapse, used for pioneering experiments in neurophysiology because of their enormous size, both participate in the fast escape circuit of the squid. The concept of a command neuron has, however, become controversial, because of studies showing that some neurons that initially appeared to fit the description were really only capable of evoking a response in a limited set of circumstances.
Function
At the most basic level, the function of the nervous system is to send signals from one cell to others, or from one part of the body to others. There are multiple ways that a cell can send signals to other cells. One is by releasing chemicals called hormones into the internal circulation, so that they can diffuse to distant sites. In contrast to this “broadcast” mode of signaling, the nervous system provides “point-to-point” signals—neurons project their axons to specific target areas and make synaptic connections with specific target cells. Thus, neural signaling is capable of a much higher level of specificity than hormonal signaling. It is also much faster: the fastest nerve signals travel at speeds that exceed 100 meters per second.
At a more integrative level, the primary function of the nervous system is to control the body. It does this by extracting information from the environment using sensory receptors, sending signals that encode this information into the central nervous system, processing the information to determine an appropriate response, and sending output signals to muscles or glands to activate the response. The evolution of a complex nervous system has made it possible for various animal species to have advanced perception abilities such as vision, complex social interactions, rapid coordination of organ systems, and integrated processing of concurrent signals. In humans, the sophistication of the nervous system makes it possible to have language, abstract representation of concepts, transmission of culture, and many other features of human society that would not exist without the human brain.

Neurons and synapses

Major elements in synaptic transmission. An electrochemical wave called an action potential travels along the axon of a neuron. When the wave reaches a synapse, it provokes release of a small amount of neurotransmitter molecules, which bind to chemical receptor molecules located in the membrane of the target cell.
Most neurons send signals via their axons, although some types are capable of dendrite-to-dendrite communication. (In fact, the types of neurons called amacrine cells have no axons, and communicate only via their dendrites.) Neural signals propagate along an axon in the form of electrochemical waves called action potentials, which produce cell-to-cell signals at points where axon terminals make synaptic contact with other cells.
Synapses may be electrical or chemical. Electrical synapses make direct electrical connections between neurons, but chemical synapses are much more common, and much more diverse in function. At a chemical synapse, the cell that sends signals is called presynaptic, and the cell that receives signals is called postsynaptic. Both the presynaptic and postsynaptic areas are full of molecular machinery that carries out the signalling process. The presynaptic area contains large numbers of tiny spherical vessels called synaptic vesicles, packed with neurotransmitter chemicals. When the presynaptic terminal is electrically stimulated, an array of molecules embedded in the membrane are activated, and cause the contents of the vesicles to be released into the narrow space between the presynaptic and postsynaptic membranes, called the synaptic cleft. The neurotransmitter then binds to receptors embedded in the postsynaptic membrane, causing them to enter an activated state. Depending on the type of receptor, the resulting effect on the postsynaptic cell may be excitatory, inhibitory, or modulatory in more complex ways. For example, release of the neurotransmitter acetylcholine at a synaptic contact between a motor neuron and a muscle cell induces rapid contraction of the muscle cell. The entire synaptic transmission process takes only a fraction of a millisecond, although the effects on the postsynaptic cell may last much longer (even indefinitely, in cases where the synaptic signal leads to the formation of a memory trace).
Structure of a typical chemical synapse

Postsynaptic
density
Voltage-
gated Ca++
channel
Synaptic
vesicle
Neurotransmitter
transporter
Receptor
Neurotransmitter
Axon terminal
Synaptic cleft
Dendrite

There are literally hundreds of different types of synapses. In fact, there are over a hundred known neurotransmitters, and many of them have multiple types of receptors.[36] Many synapses use more than one neurotransmitter—a common arrangement is for a synapse to use one fast-acting small-molecule neurotransmitter such as glutamate or GABA, along with one or more peptide neurotransmitters that play slower-acting modulatory roles. Molecular neuroscientists generally divide receptors into two broad groups: chemically gated ion channels and second messenger systems. When a chemically gated ion channel is activated, it forms a passage that allows specific types of ion to flow across the membrane. Depending on the type of ion, the effect on the target cell may be excitatory or inhibitory. When a second messenger system is activated, it starts a cascade of molecular interactions inside the target cell, which may ultimately produce a wide variety of complex effects, such as increasing or decreasing the sensitivity of the cell to stimuli, or even altering gene transcription.
According to a rule called Dale’s principle, which has only a few known exceptions, a neuron releases the same neurotransmitters at all of its synapses. This does not mean, though, that a neuron exerts the same effect on all of its targets, because the effect of a synapse depends not on the neurotransmitter, but on the receptors that it activates. Because different targets can (and frequently do) use different types of receptors, it is possible for a neuron to have excitatory effects on one set of target cells, inhibitory effects on others, and complex modulatory effects on others still. Nevertheless, it happens that the two most widely used neurotransmitters, glutamate and GABA, each have largely consistent effects. Glutamate has several widely occurring types of receptors, but all of them are excitatory or modulatory. Similarly, GABA has several widely occurring receptor types, but all of them are inhibitory. Because of this consistency, glutamatergic cells are frequently referred to as “excitatory neurons”, and GABAergic cells as “inhibitory neurons”. Strictly speaking this is an abuse of terminology—it is the receptors that are excitatory and inhibitory, not the neurons—but it is commonly seen even in scholarly publications.
One very important subset of synapses are capable of forming memory traces by means of long-lasting activity-dependent changes in synaptic strength. The best-known form of neural memory is a process called long-term potentiation (abbreviated LTP), which operates at synapses that use the neurotransmitter glutamate acting on a special type of receptor known as the NMDA receptor. The NMDA receptor has an “associative” property: if the two cells involved in the synapse are both activated at approximately the same time, a channel opens that permits calcium to flow into the target cell. The calcium entry initiates a second messenger cascade that ultimately leads to an increase in the number of glutamate receptors in the target cell, thereby increasing the effective strength of the synapse. This change in strength can last for weeks or longer. Since the discovery of LTP in 1973, many other types of synaptic memory traces have been found, involving increases or decreases in synaptic strength that are induced by varying conditions, and last for variable periods of time. The reward system, that reinforces desired behaviour for example, depends on a variant form of LTP that is conditioned on an extra input coming from a reward-signalling pathway that uses dopamine as neurotransmitter. All these forms of synaptic modifiability, taken collectively, give rise to neural plasticity, that is, to a capability for the nervous system to adapt itself to variations in the environment.
Reflexes and other stimulus-response circuits

Simplified schema of basic nervous system function: signals are picked up by sensory receptors and sent to the spinal cord and brain, where processing occurs that results in signals sent back to the spinal cord and then out to motor neurons
The simplest type of neural circuit is a reflex arc, which begins with a sensory input and ends with a motor output, passing through a sequence of neurons connected in series. This can be shown in the “withdrawal reflex” causing a hand to jerk back after a hot stove is touched. The circuit begins with sensory receptors in the skin that are activated by harmful levels of heat: a special type of molecular structure embedded in the membrane causes heat to change the electrical field across the membrane. If the change in electrical potential is large enough to pass the given threshold, it evokes an action potential, which is transmitted along the axon of the receptor cell, into the spinal cord. There the axon makes excitatory synaptic contacts with other cells, some of which project (send axonal output) to the same region of the spinal cord, others projecting into the brain. One target is a set of spinal interneurons that project to motor neurons controlling the arm muscles. The interneurons excite the motor neurons, and if the excitation is strong enough, some of the motor neurons generate action potentials, which travel down their axons to the point where they make excitatory synaptic contacts with muscle cells. The excitatory signals induce contraction of the muscle cells, which causes the joint angles in the arm to change, pulling the arm away.
In reality, this straightforward schema is subject to numerous complications. Although for the simplest reflexes there are short neural paths from sensory neuron to motor neuron, there are also other nearby neurons that participate in the circuit and modulate the response. Furthermore, there are projections from the brain to the spinal cord that are capable of enhancing or inhibiting the reflex.
Although the simplest reflexes may be mediated by circuits lying entirely within the spinal cord, more complex responses rely on signal processing in the brain. For example, when an object in the periphery of the visual field moves, and a person looks toward it many stages of signal processing are initiated. The initial sensory response, in the retina of the eye, and the final motor response, in the oculomotor nuclei of the brain stem, are not all that different from those in a simple reflex, but the intermediate stages are completely different. Instead of a one or two step chain of processing, the visual signals pass through perhaps a dozen stages of integration, involving the thalamus, cerebral cortex, basal ganglia, superior colliculus, cerebellum, and several brainstem nuclei. These areas perform signal-processing functions that include feature detection, perceptual analysis, memory recall, decision-making, and motor planning.
Feature detection is the ability to extract biologically relevant information from combinations of sensory signals. In the visual system, for example, sensory receptors in the retina of the eye are only individually capable of detecting “points of light” in the outside world. Second-level visual neurons receive input from groups of primary receptors, higher-level neurons receive input from groups of second-level neurons, and so on, forming a hierarchy of processing stages. At each stage, important information is extracted from the signal ensemble and unimportant information is discarded. By the end of the process, input signals representing “points of light” have been transformed into a neural representation of objects in the surrounding world and their properties. The most sophisticated sensory processing occurs inside the brain, but complex feature extraction also takes place in the spinal cord and in peripheral sensory organs such as the retina.

Intrinsic pattern generation
Although stimulus-response mechanisms are the easiest to understand, the nervous system is also capable of controlling the body in ways that do not require an external stimulus, by means of internally generated rhythms of activity. Because of the variety of voltage-sensitive ion channels that can be embedded in the membrane of a neuron, many types of neurons are capable, even in isolation, of generating rhythmic sequences of action potentials, or rhythmic alternations between high-rate bursting and quiescence. When neurons that are intrinsically rhythmic are connected to each other by excitatory or inhibitory synapses, the resulting networks are capable of a wide variety of dynamical behaviors, including attractor dynamics, periodicity, and even chaos. A network of neurons that uses its internal structure to generate temporally structured output, without requiring a corresponding temporally structured stimulus, is called a central pattern generator.
Internal pattern generation operates on a wide range of time scales, from milliseconds to hours or longer. One of the most important types of temporal pattern is circadian rhythmicity—that is, rhythmicity with a period of approximately 24 hours. All animals that have been studied show circadian fluctuations in neural activity, which control circadian alternations in behavior such as the sleep-wake cycle. Experimental studies dating from the 1990s have shown that circadian rhythms are generated by a “genetic clock” consisting of a special set of genes whose expression level rises and falls over the course of the day. Animals as diverse as insects and vertebrates share a similar genetic clock system. The circadian clock is influenced by light but continues to operate even when light levels are held constant and no other external time-of-day cues are available. The clock genes are expressed in many parts of the nervous system as well as many peripheral organs, but in mammals all of these “tissue clocks” are kept in synchrony by signals that emanate from a master timekeeper in a tiny part of the brain called the suprachiasmatic nucleus.
Pathology
The central nervous system is protected by major physical and chemical barriers. Physically, the brain and spinal cord are surrounded by tough meningeal membranes, and enclosed in the bones of the skull and spinal vertebrae, which combine to form a strong physical shield. Chemically, the brain and spinal cord are isolated by the so-called blood–brain barrier, which prevents most types of chemicals from moving from the bloodstream into the interior of the CNS. These protections make the CNS less susceptible in many ways than the PNS; the flip side, however, is that damage to the CNS tends to have more serious consequences.
Although nerves tend to lie deep under the skin except in a few places such as the ulnar nerve near the elbow joint, they are still relatively exposed to physical damage, which can cause pain, loss of sensation, or loss of muscle control. Damage to nerves can also be caused by swelling or bruises at places where a nerve passes through a tight bony channel, as happens in carpal tunnel syndrome. If a nerve is completely transected, it will often regenerate, but for long nerves this process may take months to complete. In addition to physical damage, peripheral neuropathy may be caused by many other medical problems, including genetic conditions, metabolic conditions such as diabetes, inflammatory conditions such as Guillain–Barré syndrome, vitamin deficiency, infectious diseases such as leprosy or shingles, or poisoning by toxins such as heavy metals. Many cases have no cause that can be identified, and are referred to as idiopathic. It is also possible for nerves to lose function temporarily, resulting in numbness as stiffness—common causes include mechanical pressure, a drop in temperature, or chemical interactions with local anesthetic drugs such as lidocaine.
Physical damage to the spinal cord may result in loss of sensation or movement. If an injury to the spine produces nothing worse than swelling, the symptoms may be transient, but if nerve fibers in the spine are actually destroyed, the loss of function is usually permanent. Experimental studies have shown that spinal nerve fibers attempt to regrow in the same way as nerve fibers, but in the spinal cord, tissue destruction usually produces scar tissue that cannot be penetrated by the regrowing nerves.

FOOD CHAIN


FOOD CHAIN
A food chain is a linear sequence of links in a food web starting from a species that are called producers in the web and ends at a species that is called decomposers species in the web. A food chain also shows how the organisms are related with each other by the food they eat. A food chain differs from a food web, because the complex polyphagous network of feeding relations are aggregated into trophic species and the chain only follows linear monophagous pathways. A common metric used to quantify food web trophic structure is food chain length. In its simplest form, the length of a chain is the number of links between a trophic consumer and the base of the web and the mean chain length of an entire web is the arithmetic average of the lengths of all chains in a food web.
Food chains were first introduced by the African-Arab scientist and philosopher Al-Jahiz in the 9th century and later popularized in a book published in 1927 by Charles Elton, which also introduced the food web concept.
Food chain length
Food chains are directional paths of trophic energy or, equivalently, sequences of links that start with basal species, such as producers or fine organic matter, and end with consumer organisms.
The food chain’s length is a continuous variable that provides a measure of the passage of energy and an index of ecological structure that increases in value counting progressively through the linkages in a linear fashion from the lowest to the highest trophic (feeding) levels. Food chains are often used in ecological modeling (such as a three species food chain). They are simplified abstractions of real food webs, but complex in their dynamics and mathematical implications. Ecologists have formulated and tested hypotheses regarding the nature of ecological patterns associated with food chain length, such as increasing length increasing with ecosystem size, reduction of energy at each successive level, or the proposition that long food chain lengths are unstable. Food chain studies have had an important role in ecotoxicology studies tracing the pathways and biomagnification of environmental contaminants.
Food chains vary in length from three to six or more levels. A food chain consisting of a flower, a frog, a snake and an owl consists of four levels; whereas a food chain consisting of grass, a grasshopper, a rat, a snake and finally a hawk consists of five levels. Producers, such as plants, are organisms that utilize solar energy or heat energy to synthesize starch. All food chains must start with a producer. In the deep sea, food chains centered around hydrothermal vents exist in the absence of sunlight. Chemo-synthetic bacteria and archaea can use hydrogen sulfide from hydro-thermal vents as an energy source (just as plants use sunlight) to produce carbohydrates; they form the base of the food chain. Consumers are organisms that eat other organisms. All organisms in a food chain, except the first organism, are consumers.

FOOD WEBS


FOOD WEB
A food web (or food cycle) depicts feeding connections (what-eats-what) in an ecological community and hence is also referred to as a consumer-resource system. Ecologists can broadly lump all life forms into one of two categories called trophic levels: 1) the autotrophs, and 2) the heterotrophs. To maintain their bodies, grow, develop, and to reproduce, autotrophs produce organic matter from inorganic substances, including both minerals and gases such as carbon dioxide. These chemical reactions require energy, which mainly comes from the sun and largely by photosynthesis, although a very small amount comes from hydrothermal vents and hot springs. A gradient exists between trophic levels running from complete autotrophs that obtain their sole source of carbon from the atmosphere, to mixotrophs (such as carnivorous plants) that are autotrophic organisms that partially obtain organic matter from sources other than the atmosphere, and complete heterotrophs that must feed to obtain organic matter. The linkages in a food web illustrate the feeding pathways, such as where heterotrophs obtain organic matter by feeding on autotrophs and other heterotrophs. The food web is a simplified illustration of the various methods of feeding that links an ecosystem into a unified system of exchange. There are different kinds of feeding relations that can be roughly divided into herbivory, carnivory, scavenging and parasitism. Some of the organic matter eaten by heterotrophs, such as sugars, provides energy. Autotrophs and heterotrophs come in all sizes, from microscopic to many tonnes – from cyanobacteria to giant redwoods, and from viruses and bdellovibrio to blue whales.
Charles Elton pioneered the concept of food cycles, food chains, and food size in his classical 1927 book “Animal Ecology”; Elton’s ‘food cycle’ was replaced by ‘food web’ in a subsequent ecological text. Elton organized species into functional groups, which was the basis for Raymond Lindeman’s classic and landmark paper in 1942 on trophic dynamics. Lindeman emphasized the important role of decomposer organisms in a trophic system of classification. The notion of a food web has a historical foothold in the writings of Charles Darwin and his terminology, including an “entangled bank”, “web of life”, “web of complex relations”, and in reference to the decomposition actions of earthworms he talked about “the continued movement of the particles of earth”. Even earlier, in 1768 John Bruckner described nature as “one continued web of life”.
Food webs are limited representations of real ecosystems as they necessarily aggregate many species into trophic species, which are functional groups of species that have the same predators and prey in a food web. Ecologists use these simplifications in quantitative (or mathematical) models of trophic or consumer-resource systems dynamics. Using these models they can measure and test for generalized patterns in the structure of real food web networks. Ecologists have identified non-random properties in the topographic structure of food webs. Published examples that are used in meta analysis are of variable quality with omissions. However, the number of empirical studies on community webs is on the rise and the mathematical treatment of food webs using network theory had identified patterns that are common to all. Scaling laws, for example, predict a relationship between the topology of food web predator-prey linkages and levels of species richness.
TAXONOMY OF A FOOD WEB
Food webs are the road-maps through Darwin’s famous ‘entangled bank’ and have a long history in ecology. Like maps of unfamiliar ground, food webs appear bewilderingly complex. They were often published to make just that point. Yet recent studies have shown that food webs from a wide range of terrestrial, freshwater, and marine communities share a remarkable list of patterns.
Links in food webs map the feeding connections (who eats whom) in an ecological community. Food cycle is the antiquated term that is synonymous with food web. Ecologists can broadly lump all life forms into one of two trophic layers, the autotrophs and the heterotrophs. Autotrophs produce more biomass energy, either chemically without the suns energy or by capturing the suns energy in photosynthesis, than they use during metabolic respiration. Heterotrophs consume rather than produce biomass energy as they metabolize, grow, and add to levels of secondary production. A food web depicts a collection of polyphagous heterotrophic consumers that network and cycle the flow of energy and nutrients from a productive base of self-feeding autotrophs.
The base or basal species in a food web are those species without prey and can include autotrophs or saprophytic detritivores (i.e., the community of decomposers in soil, biofilms, and periphyton). Feeding connections in the web are called trophic links. The number of trophic links per consumer is a measure of food web connectance. Food chains are nested within the trophic links of food webs. Food chains are linear (noncyclic) feeding pathways that trace monophagous consumers from a base species up to the top consumer, which is usually a larger predatory carnivore.
Linkages connect to nodes in a food web, which are aggregates of biological taxa called trophic species. Trophic species are functional groups that have the same predators and prey in a food web. Common examples of an aggregated node in a food web might include parasites, microbes, decomposers, saprotrophs, consumers, or predators, each containing many species in a web that can otherwise be connected to other trophic species.
TROPHIC LEVELS
Food webs have trophic levels and positions. Basal species, such as plants, form the first level and are the resource limited species that feed on no other living creature in the web. Basal species can be autotrophs or detritivores, including “decomposing organic material and its associated microorganisms which we defined as detritus, micro-inorganic material and associated microorganisms (MIP), and vascular plant material.” Most autotrophs capture the sun’s energy in chlorophyll, but some autotrophs (the chemolithotrophs) obtain energy by the chemical oxidation of inorganic compounds and can grow in dark environments, such as the sulfur bacterium Thiobacillus, which lives in hot sulfur springs. The top level has top (or apex) predators which no other species kills directly for its food resource needs. The intermediate levels are filled with omnivores that feed on more than one trophic level and cause energy to flow through a number of food pathways starting from a basal species.
In the simplest scheme, the first trophic level (level 1) is plants, then herbivores (level 2), and then carnivores (level 3). The trophic level is equal to one more than the chain length, which is the number of links connecting to the base. The base of the food chain (primary producers or detritivores) is set at zero. Ecologists identify feeding relations and organize species into trophic species through extensive gut content analysis of different species. The technique has been improved through the use of stable isotopes to better trace energy flow through the web. It was once thought that omnivory was rare, but recent evidence suggests otherwise. This realization has made trophic classifications more complex.
TROPHIC DYNAMICS
The trophic level concept was introduced in a historical landmark paper on trophic dynamics in 1942 by Raymond L. Lindeman. The basis of trophic dynamics is the transfer of energy from one part of the ecosystem to another. The trophic dynamic concept has served as a useful quantitative heuristic, but it has several major limitations including the precision by which an organism can be allocated to a specific trophic level. Omnivores, for example, are not restricted to any single level. Nonetheless, recent research has found that discrete trophic levels do exist, but “above the herbivore trophic level, food webs are better characterized as a tangled web of omnivores.”
A central question in the trophic dynamic literature is the nature of control and regulation over resources and production. Ecologists use simplified one trophic position food chain models (producer, carnivore, decomposer). Using these models, ecologists have tested various types of ecological control mechanisms. For example, herbivores generally have an abundance of vegetative resources, which meant that their populations were largely controlled or regulated by predators. This is known as the top-down hypothesis or ‘green-world’ hypothesis. Alternatively to the top-down hypothesis, not all plant material is edible and the nutritional quality or antiherbivore defenses of plants (structural and chemical) suggests a bottom-up form of regulation or control. Recent studies have concluded that both “top-down” and “bottom-up” forces can influence community structure and the strength of the influence is environmentally context dependent. These complex multitrophic interactions involve more than two trophic levels in a food web.
Another example of a multi-trophic interaction is a trophic cascade, in which predators help to increase plant growth and prevent overgrazing by suppressing herbivores. Links in a food-web illustrate direct trophic relations among species, but there are also indirect effects that can alter the abundance, distribution, or biomass in the trophic levels. For example, predators eating herbivores indirectly influence the control and regulation of primary production in plants. Although the predators do not eat the plants directly, they regulate the population of herbivores that are directly linked to plant trophism. The net effect of direct and indirect relations is called trophic cascades. Trophic cascades are separated into species-level cascades, where only a subset of the food-web dynamic is impacted by a change in population numbers, and community-level cascades, where a change in population numbers has a dramatic effect on the entire food-web, such as the distribution of plant biomass.
ENERGY FLOW AND BIOMASS
The Law of Conservation of Mass dates from Antoine Lavoisier’s 1789 discovery that mass is neither created nor destroyed in chemical reactions. In other words, the mass of any one element at the beginning of a reaction will equal the mass of that element at the end of the reaction.

Left: Energy flow diagram of a frog. The frog represents a node in an extended food web. The energy ingested is utilized for metabolic processes and transformed into biomass. The energy flow continues on its path if the frog is ingested by predators, parasites, or as a decaying carcass in soil. This energy flow diagram illustrates how energy is lost as it fuels the metabolic process that transform the energy and nutrients into biomass.
Right: An expanded three link energy food chain (1. plants, 2. herbivores, 3. carnivores) illustrating the relationship between food flow diagrams and energy transformity. The transformity of energy becomes degraded, dispersed, and diminished from higher quality to lesser quantity as the energy within a food chain flows from one trophic species into another. Abbreviations: I=input, A=assimilation, R=respiration, NU=not utilized, P=production, B=biomass.

Food webs depict energy flow via trophic linkages. Energy flow is directional, which contrasts against the cyclic flows of material through the food web systems. Energy flow “typically includes production, consumption, assimilation, non-assimilation losses (feces), and respiration (maintenance costs).” In a very general sense, energy flow (E) can be defined as the sum of metabolic production (P) and respiration (R), such that E=P+R.
The mass (or biomass) of something is equal to its energy content. Mass and energy are closely intertwined. However, concentration and quality of nutrients and energy is variable. Many plant fibers, for example, are indigestible to many herbivores leaving grazer community food webs more nutrient limited than detrital food webs where bacteria are able to access and release the nutrient and energy stores. “Organisms usually extract energy in the form of carbohydrates, lipids, and proteins. These polymers have a dual role as supplies of energy as well as building blocks; the part that functions as energy supply results in the production of nutrients (and carbon dioxide, water, and heat). Excretion of nutrients is, therefore, basic to metabolism.” The units in energy flow webs are typically a measure mass or energy per m2 per unit time. Different consumers are going to have different metabolic assimilation efficiencies in their diets. Each trophic level transforms energy into biomass. Energy flow diagrams illustrate the rates and efficiency of transfer from one trophic level into another and up through the hierarchy.
It is the case that the biomass of each trophic level decreases from the base of the chain to the top. This is because energy is lost to the environment with each transfer as entropy increases. About eighty to ninety percent of the energy is expended for the organism’s life processes or is lost as heat or waste. Only about ten to twenty percent of the organism’s energy is generally passed to the next organism. The amount can be less than one percent in animals consuming less digestible plants, and it can be as high as forty percent in zooplankton consuming phytoplankton. Graphic representations of the biomass or productivity at each tropic level are called ecological pyramids or trophic pyramids. The transfer of energy from primary producers to top consumers can also be characterized by energy flow diagrams.
FOOD CHAIN
A common metric used to quantify food web trophic structure is food chain length. Food chain length is another way of describing food webs as a measure of the number of species encountered as energy or nutrients move from the plants to top predators. There are different ways of calculating food chain length depending on what parameters of the food web dynamic are being considered: connectance, energy, or interaction. In its simplest form, the length of a chain is the number of links between a trophic consumer and the base of the web. The mean chain length of an entire web is the arithmetic average of the lengths of all chains in a food web.
In a simple predator-prey example, a deer is one step removed from the plants it eats (chain length = 1) and a wolf that eats the deer is two steps removed (chain length = 2). The relative amount or strength of influence that these parameters have on the food web address questions about:
• the identity or existence of a few dominant species (called strong interactors or keystone species)
• the total number of species and food-chain length (including many weak interactors) and
• how community structure, function and stability is determined.[35][36]
Ecological pyramids

Top Left: A four level trophic pyramid sitting on a layer of soil and its community of decomposers. Top right: A three layer trophic pyramid linked to the biomass and energy flow concepts. Bottom: Illustration of a range of ecological pyramids, including top pyramid of numbers, middle pyramid of biomass, and bottom pyramid of energy. The terrestrial forest (summer) and the English Channel ecosystems exhibit inverted pyramids.Note: trophic levels are not drawn to scale and the pyramid of numbers excludes microorganisms and soil animals. Abbreviations: P=Producers, C1=Primary consumers, C2=Secondary consumers, C3=Tertiary consumers, S=Saprotrophs.
In a pyramid of numbers, the number of consumers at each level decreases significantly, so that a single top consumer, (e.g., a polar bear or a human), will be supported by a much larger number of separate producers. There is usually a maximum of four or five links in a food chain, although food chains in aquatic ecosystems are more often longer than those on land. Eventually, all the energy in a food chain is dispersed as heat.
Ecological pyramids place the primary producers at the base. They can depict different numerical properties of ecosystems, including numbers of individuals per unit of area, biomass (g/m2), and energy (k cal m−2 yr−1). The emergent pyramidal arrangement of trophic levels with amounts of energy transfer decreasing as species become further removed from the source of production is one of several patterns that is repeated amongst the planets ecosystems. The size of each level in the pyramid generally represents biomass, which can be measured as the dry weight of an organism. Autotrophs may have the highest global proportion of biomass, but they are closely rivaled or surpassed by microbes.
Pyramid structure can vary across ecosystems and across time. In some instances biomass pyramids can be inverted. This pattern is often identified in aquatic and coral reef ecosystems. The pattern of biomass inversion is attributed to different sizes of producers. Aquatic communities are often dominated by producers that are smaller than the consumers that have high growth rates. Aquatic producers, such as planktonic algae or aquatic plants, lack the large accumulation of secondary growth as exists in the woody trees of terrestrial ecosystems. However, they are able to reproduce quickly enough to support a larger biomass of grazers. This inverts the pyramid. Primary consumers have longer lifespans and slower growth rates that accumulates more biomass than the producers they consume. Phytoplankton live just a few days, whereas the zooplankton eating the phytoplankton live for several weeks and the fish eating the zooplankton live for several consecutive years. Aquatic predators also tend to have a lower death rate than the smaller consumers, which contributes to the inverted pyramidal pattern. Population structure, migration rates, and environmental refuge for prey are other possible causes for pyramids with biomass inverted. Energy pyramids, however, will always have an upright pyramid shape if all sources of food energy are included and this is dictated by the second law of thermodynamics.
MATERIAL FLUX AND RECYCLING
Many of the Earth’s elements and minerals (or mineral nutrients) are contained within the tissues and diets of organisms. Hence, mineral and nutrient cycles trace food web energy pathways. Ecologists employ stoichiometry to analyze the ratios of the main elements found in all organisms: carbon (C), nitrogen (N), phosphorus (P). There is a large transitional difference between many terrestrial and aquatic systems as C:P and C:N ratios are much higher in terrestrial systems while N:P ratios are equal between the two systems. Mineral nutrients are the material resources that organisms need for growth, development, and vitality. Food webs depict the pathways of mineral nutrient cycling as they flow through organisms. Most of the primary production in an ecosystem is not consumed, but is recycled by detritus back into useful nutrients. Many of the Earth’s microorganisms are involved in the formation of minerals in a process called biomineralization. Bacteria that live in detrital sediments create and cycle nutrients and biominerals. Food web models and nutrient cycles have traditionally been treated separately, but there is a strong functional connection between the two in terms of stability, flux, sources, sinks, and recycling of mineral nutrients.
KINDS OF FOOD WEBS
Food webs are necessarily aggregated and only illustrate a tiny portion of the complexity of real ecosystems. For example, the number of species on the planet are likely in the general order of 107, over 95% of these species consist of microbes and invertebrates, and relatively few have been named or classified by taxonomists. It is explicitly understood that natural systems are ‘sloppy’ and that food web trophic positions simplify the complexity of real systems that sometimes overemphasize many rare interactions. Most studies focus on the larger influences where the bulk of energy transfer occurs. “These omissions and problems are causes for concern, but on present evidence do not present insurmountable difficulties.”

There are different kinds or categories of food webs:
• Source web – one or more node(s), all of their predators, all the food these predators eat, and so on.
• Sink web – one or more node(s), all of their prey, all the food that these prey eat, and so on.
• Community (or connectedness) web – a group of nodes and all the connections of who eats whom.
• Energy flow web – quantified fluxes of energy between nodes along links between a resource and a consumer.
• Paleoecological web – a web that reconstructs ecosystems from the fossil record.
• Functional web – emphasizes the functional significance of certain connections having strong interaction strength and greater bearing on community organization, more so than energy flow pathways. Functional webs have compartments, which are sub-groups in the larger network where there are different densities and strengths of interaction. Functional webs emphasize that “the importance of each population in maintaining the integrity of a community is reflected in its influence on the growth rates of other populations.”
Within these categories, food webs can be further organized according to the different kinds of ecosystems being investigated. For example, human food webs, agricultural food webs, detrital food webs, marine food webs, aquatic food webs, soil food webs, Arctic (or polar) food webs, terrestrial food webs, and microbial food webs. These characterizations stem from the ecosystem concept, which assumes that the phenomena under investigation (interactions and feedback loops) are sufficient to explain patterns within boundaries, such as the edge of a forest, an island, a shoreline, or some other pronounced physical characteristic.
DETRITAL WEB
In a detrital web, plant and animal matter is broken down by decomposers, e.g., bacteria and fungi, and moves to detritivores and then carnivores. There are often relationships between the detrital web and the grazing web. Mushrooms produced by decomposers in the detrital web become a food source for deer, squirrels, and mice in the grazing web. Earthworms eaten by robins are detritivores consuming decaying leaves.
“Detritus can be broadly defined as any form of non-living organic matter, including different types of plant tissue (e.g. leaf litter, dead wood, aquatic macrophytes, algae), animal tissue (carrion), dead microbes, faeces (manure, dung, faecal pellets, guano, frass), as well as products secreted, excreted or exuded from organisms (e.g. extra-cellular polymers, nectar, root exudates and leachates, dissolved organic matter, extra-cellular matrix, mucilage). The relative importance of these forms of detritus, in terms of origin, size and chemical composition, varies across ecosystems.”
QUANTITATIVE FOOD WEBS
Ecologists collect data on trophic levels and food webs to statistically model and mathematically calculate parameters, such as those used in other kinds of network analysis (e.g., graph theory), to study emergent patterns and properties shared among ecosystems. There are different ecological dimensions that can be mapped to create more complicated food webs, including: species composition (type of species), richness (number of species), biomass (the dry weight of plants and animals), productivity (rates of conversion of energy and nutrients into growth), and stability (food webs over time). A food web diagram illustrating species composition shows how change in a single species can directly and indirectly influence many others. Microcosm studies are used to simplify food web research into semi-isolated units such as small springs, decaying logs, and laboratory experiments using organisms that reproduce quickly, such as daphnia feeding on algae grown under controlled environments in jars of water.
While the complexity of real food webs connections are difficult to decipher, ecologists have found mathematical models on networks an invaluable tool for gaining insight into the structure, stability, and laws of food web behaviours relative to observable outcomes. “Food web theory centers around the idea of connectance.” Quantitative formulas simplify the complexity of food web structure. The number of trophic links (tL), for example, is converted into a connectance value:
,
where, S(S-1)/2 is the maximum number of binary connections among S species. “Connectance (C) is the fraction of all possible links that are realized (L/S2) and represents a standard measure of food web complexity…” The distance (d) between every species pair in a web is averaged to compute the mean distance between all nodes in a web (D) and multiplied by the total number of links (L) to obtain link-density (LD), which is influenced by scale dependent variables such as species richness. These formulas are the basis for comparing and investigating the nature of non-random patterns in the structure of food web networks among many different types of ecosystems.
Scaling laws, complexity, choas, and patterned correlates are common features attributed to food web structure.
COMPLEXITY AND STABILITY
Food webs are complex. Complexity is a measure of an increasing number of permutations and it is also a metaphorical term that conveys the mental intractability or limits concerning unlimited algorithmic possibilities. In food web terminology, complexity is a product of the number of species and connectance. Connectance is “the fraction of all possible links that are realized in a network”.These concepts were derived and stimulated through the suggestion that complexity leads to stability in food webs, such as increasing the number of trophic levels in more species rich ecosystems. This hypothesis was challenged through mathematical models suggesting otherwise, but subsequent studies have shown that the premise holds in real systems.
At different levels in the hierarchy of life, such as the stability of a food web, “the same overall structure is maintained in spite of an ongoing flow and change of components.” The farther a living system (e.g., ecosystem) sways from equilibrium, the greater its complexity. Complexity has multiple meanings in the life sciences and in the public sphere that confuse its application as a precise term for analytical purposes in science. Complexity in the life sciences (or biocomplexity) is defined by the “properties emerging from the interplay of behavioral, biological, physical, and social interactions that affect, sustain, or are modified by living organisms, including humans”.
Several concepts have emerged from the study of complexity in food webs. Complexity explains many principals pertaining to self-organization, non-linearity, interaction, cybernetic feedback, discontinuity, emergence, and stability in food webs. Nestedness, for example, is defined as “a pattern of interaction in which specialists interact with species that form perfect subsets of the species with which generalists interact”, “—that is, the diet of the most specialized species is a subset of the diet of the next more generalized species, and its diet a subset of the next more generalized, and so on.” Until recently, it was thought that food webs had little nested structure, but empirical evidence shows that many published webs have nested subwebs in their assembly.
Food webs are complex networks. As networks, they exhibit similar structural properties and mathematical laws that have been used to describe other complex systems, such as small world and scale free properties. The small world attribute refers to the many loosely connected nodes, non-random dense clustering of a few nodes (i.e., trophic or keystone species in ecology), and small path length compared to a regular lattice. “Ecological networks, especially mutualistic networks, are generally very heterogeneous, consisting of areas with sparse links among species and distinct areas of tightly linked species. These regions of high link density are often referred to as cliques, hubs, compartments, cohesive sub-groups, or modules…Within food webs, especially in aquatic systems, nestedness appears to be related to body size because the diets of smaller predators tend to be nested subsets of those of larger predators (Woodward & Warren 2007; YvonDurocher et al. 2008), and phylogenetic constraints, whereby related taxa are nested based on their common evolutionary history, are also evident (Cattin et al. 2004).” “Compartments in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups. Theoretically, compartments increase the stability in networks, such as food webs.”
Food webs are also complex in the way that they change in scale, seasonally, and geographically. The components of food webs, including organisms and mineral nutrients, cross the thresholds of ecosystem boundaries. This has led to the concept or area of study known as cross-boundary subsidy. “This leads to anomalies, such as food web calculations determining that an ecosystem can support one half of a top carnivore, without specifying which end.” Nonetheless, real differences in structure and function have been identified when comparing different kinds of ecological food webs, such as terrestrial vs. aquatic food webs.
HISTORY OF FOOD WEBS
Food webs serve as a framework to help ecologists organize the complex network of interactions among species observed in nature and around the world. One of the earliest descriptions of a food chain was described by a medieval Afro-Arab scholar named Al-Jahiz: “All animals, in short, cannot exist without food, neither can the hunting animal escape being hunted in his turn.” The earliest graphical depiction of a food web was by Lorenzo Camerano in 1880, followed independently by those of Pierce and colleagues in 1912 and Victor Shelford in 1913. Two food webs about herring were produced by Victor Summerhayes and Charles Elton[86] and Alister Hardy[87] in 1923 and 1924. Charles Elton subsequently pioneered the concept of food cycles, food chains, and food size in his classical 1927 book “Animal Ecology”; Elton’s ‘food cycle’ was replaced by ‘food web’ in a subsequent ecological text.[88] After Charles Elton’s use of food webs in his 1927 synthesis,[89] they became a central concept in the field of ecology. Elton[88] organized species into functional groups, which formed the basis for the trophic system of classification in Raymond Lindeman’s classic and landmark paper in 1942 on trophic dynamics.[16][36][90] The notion of a food web has a historical foothold in the writings of Charles Darwin and his terminology, including an “entangled bank”, “web of life”, “web of complex relations”, and in reference to the decomposition actions of earthworms he talked about “the continued movement of the particles of earth”. Even earlier, in 1768 John Bruckner described nature as “one continued web of life”.[3][91][92][93]
Interest in food webs increased after Robert Paine’s experimental and descriptive study of intertidal shores[94] suggesting that food web complexity was key to maintaining species diversity and ecological stability. Many theoretical ecologists, including Sir Robert May[95] and Stuart Pimm,[96] were prompted by this discovery and others to examine the mathematical properties of food webs.

ECOLOGICAL NICHE


ECOLOGICAL NICHE
In ecology, a niche is a term with a variety of meanings related to the behavior of a species living under specific environmental conditions. The ecological niche describes how an organism or population responds to the distribution of resources and competitors (for example, by growing when resources are abundant, and when predators, parasites and pathogens are scarce) and how it in turn alters those same factors (for example, limiting access to resources by other organisms, acting as a food source for predators and a consumer of prey). “The type and number of variables comprising the dimensions of an environmental niche vary from one species to another…[and]…the relative importance of particular environmental variables for a species may vary according to the geographic and biotic contexts”.
The notion of ecological niche is central to ecological biogeography, which focuses on spatial patterns of ecological communities. “Species distributions and their dynamics over time result from properties of the species, environmental variation…, and interactions between the two — in particular the abilities of some species, especially our own, to modify their environments and alter the range dynamics of many other species.” Alteration of an ecological niche by its inhabitants is the topic of niche construction.
The majority of species exist in a standard ecological niche, but there are exceptions. A premier example of a non-standard niche filling species is the flightless, ground-dwelling kiwi bird of New Zealand, which feeds on worms and other ground creatures, and lives its life in a mammal niche. Island biogeography can help explain island species and associated unfilled niches.
GRINNELLIAN NICHE
The ecological meaning of niche comes from the meaning of niche as a recess in a wall for a statue, which itself is probably derived from the Middle French word nicher, meaning to nest. The term was coined by the naturalist Joseph Grinnell in 1917, in his paper “The niche relationships of the California Thrasher”. The Grinnellian niche concept embodies the idea that the niche of a species is determined by the habitat in which it lives and its accompanying behavioral adaptations. In other words, the niche is the sum of the habitat requirements and behaviors that allow a species to persist and produce offspring. For example, the behavior of the California Thrasher is consistent with the chaparral habitat it lives in—it breeds and feeds in the underbrush and escapes from its predators by shuffling from underbrush to underbrush. Its ‘niche’ is defined by the felicitous complementing of the thrasher’s behavior and physical traits (camouflaging color, short wings, strong legs) with this habitat.
This perspective of niche allows for the existence of both ecological equivalents and empty niches. An ecological equivalent to an organism is an organism from a different taxonomic group exhibiting similar adaptations in a similar habitat, an example being the different succulents found in American and African deserts, cactus and euphorbia. As another example, the Anolis lizards of the Greater Antilles are a rare example of convergent evolution, adaptive radiation, and the existence of ecological equivalents: the Anolis lizards evolved in similar microhabitats independently of each other and resulted in the same ecomorphs across all four islands.
ELTONIAN NICHE
In 1927 Charles Sutherland Elton, a British ecologist, defined a niche as follows: “The ‘niche’ of an animal means its place in the biotic environment, its relations to food and enemies.”
Elton classified niches according to foraging activities (“food habits”): “For instance there is the niche that is filled by birds of prey which eat small animals such as shrews and mice. In an oak wood this niche is filled by tawny owls, while in the open grassland it is occupied by kestrels. The existence of this carnivore niche is dependent on the further fact that mice form a definite herbivore niche in many different associations, although the actual species of mice may be quite different.”
HUTCHINSONIAN NICHE
The Hutchinsonian niche is an n-dimensional hypervolume, where the dimensions are environmental conditions and resources, that define the requirements of an individual or a species to practice “its” way of life, more particularly, for its population to persist. The “hypervolume” defines the multi-dimensional space of resources (e.g., light, nutrients, structure, etc.) available to (and specifically used by) organisms, and “all species other than those under consideration are regarded as part of the coordinate system.”
The niche concept was popularized by the zoologist G. Evelyn Hutchinson in 1957. Hutchinson wanted to know why there are so many types of organisms in any one habitat. His work inspired many others to develop models to explain how many and how similar coexisting species could be within a given community, and led to the concepts of ‘niche breadth’ (the variety of resources or habitats used by a given species), ‘niche partitioning’ (resource differentiation by coexisting species), and ‘niche overlap’ (overlap of resource use by different species).
Statistics were introduced into the Hutchinson niche by Robert MacArthur and Richard Levins using the ‘resource-utilization’ niche employing histograms to describe the ‘frequency of occurrence’ as a function of a Hutchinson coordinate. So, for instance, a Gaussian might describe the frequency with which a species ate prey of a certain size, giving a more detailed niche description than simply specifying some median or average prey size. One advantage in using statistics is illustrated in the figure, where it is clear that for the narrower distributions (top) there is no competition for prey between the extreme left and extreme right species, while for the broader distribution (bottom), niche overlap indicates competition exists between all species. For such a bell-shaped distribution, the position, width and form of the niche correspond to the mean, standard deviation and the actual distribution itself.
An organism free of interference from other species could use the full range of conditions (biotic and abiotic) and resources in which it could survive and reproduce which is called its fundamental niche. However, as a result of pressure from, and interactions with, other organisms (i.e. inter-specific competition) species are usually forced to occupy a niche that is narrower than this, and to which they are mostly highly adapted. This is termed the realized niche. Hutchinson used the idea of competition for resources as the primary mechanism driving ecology, but overemphasis upon this focus has proved to be a handicap for the niche concept.[13] In particular, overemphasis upon a species’ dependence upon resources has led to too little emphasis upon the effects of organisms on their environment, for instance, colonization and invasions.
The term adaptive zone was coined by the paleontologist George Gaylord Simpson to explain how a population could jump from one niche to another that suited it, jump to an ‘adaptive zone’, made available by virtue of some modification, or possibly a change in the food chain, that made the adaptive zone available to it without a discontinuity in its way of life because the group was ‘pre-adapted’ to the new ecological opportunity.
Hutchinson’s “niche” (a description of the ecological space occupied by a species) is subtly different from the “niche” as defined by Grinnell (an ecological role, that may or may not be actually filled by a species—see vacant niches).
A niche is a very specific segment of ecospace occupied by a single species. On the presumption that no two species are identical in all respects (called Hardin’s ‘axiom of inequality’ and the competitive exclusion principle, some resource or adaptive dimension will provide a niche specific to each species.[16] Species can however share a ‘mode of life’ or ‘autecological strategy’ which are broader definitions of ecospace. For example, Australian grasslands species, though different from those of the Great Plains grasslands, exhibit similar modes of life.
Once a niche is left vacant, other organisms can fill that position. For example, the niche that was left vacant by the extinction of the tarpan has been filled by other animals (in particular a small horse breed, the konik). Also, when plants and animals are introduced into a new environment, they have the potential to occupy or invade the niche or niches of native organisms, often outcompeting the indigenous species. Introduction of non-indigenous species to non-native habitats by humans often results in biological pollution by the exotic or invasive species.
The mathematical representation of a species’ fundamental niche in ecological space, and its subsequent projection back into geographic space, is the domain of niche modelling.
PARAMETERS
The different dimensions, or plot axes, of a niche represent different biotic and abiotic variables. These factors may include descriptions of the organism’s life history, habitat, trophic position (place in the food chain), and geographic range. According to the competitive exclusion principle, no two species can occupy the same niche in the same environment for a long time. The parameters of a realized niche are described by the realized niche width of that species.