Memetics

From Wikipedia, the free encyclopedia

Memetics is a theory of mental content based on an analogy with Darwinian evolution, originating from the popularization of Richard Dawkins' 1976 book The Selfish Gene.^[1] Proponents describe memetics as an approach to evolutionary models of cultural information transfer.

The meme, analogous to a gene, was conceived as a "unit of culture" (an idea, belief, pattern of behaviour, etc.) which is "hosted" in the minds of one or more individuals, and which can reproduce itself, thereby jumping from mind to mind. Thus what would otherwise be regarded as one individual influencing another to adopt a belief is seen as an idea-replicator reproducing itself in a new host. As with genetics, particularly under a Dawkinsian interpretation, a meme's success may be due to its contribution to the effectiveness of its host.

Memetics is also notable for sidestepping the traditional concern with the truth of ideas and beliefs. Instead, it is interested in their success.^[2]

The Usenet newsgroup alt.memetics started in 1993 with peak posting years in the mid to late 1990s.^[3] The Journal of Memetics was published electronically from 1997 to 2005.^[4]

History

In his book The Selfish Gene (1976), the evolutionary biologist Richard Dawkins used the term meme to describe a unit of human cultural transmission analogous to the gene, arguing that replication also happens in culture, albeit in a different sense. Ted Cloak had briefly outlined a similar hypothesis in 1975, which Dawkins referenced. Cultural evolution itself is a much older topic, with a history that dates back to Darwin's era.

Dawkins (1976) contended that the meme is a unit of information residing in the brain and is the mutating replicator in human cultural evolution. It is a pattern that can influence its surroundings – that is, it has causal agency – and can propagate. This created great debate among sociologists, biologists, and scientists of other disciplines, because Dawkins himself did not provide a sufficient explanation of how the replication of units of information in the brain controls human behaviour and ultimately culture, since the principal topic of the book was genetics. Dawkins apparently did not intend to present a comprehensive theory of memetics in The Selfish Gene, but rather coined the term meme in a speculative spirit. Accordingly, the term "unit of information" came to be defined in different ways by many scientists.

The modern memetics movement dates from the mid-1980s. A January 1983 Metamagical Themas column^[5] by Douglas Hofstadter, in Scientific American, was influential as was his 1985 book of the same name. "Memeticist" was coined as analogous to "geneticist" originally in The Selfish Gene. Later Arel Lucas suggested that the discipline that studies memes and their connections to human and other carriers of them be known as memetics by analogy with 'genetics.'"^[6] Dawkins' The Selfish Gene has been a factor in drawing in people of disparate intellectual backgrounds. Another stimulus was the publication in 1991 of Consciousness Explained by Tufts University philosopher Daniel Dennett, which incorporated the meme concept into a theory of the mind. In his 1991^[7] essay "Viruses of the Mind", Richard Dawkins used memetics to explain the phenomenon of religious belief and the various characteristics of organised religions. By then, memetics had also become a theme appearing in fiction (e.g. Neal Stephenson's Snow Crash).

The idea of language as a virus had already been introduced by William S. Burroughs as early as 1962 in his book The Ticket That Exploded, and later in The Electronic Revolution, published in 1970 in The Job and is also explored in Media Virus by Douglas Rushkoff in 1995.

However, the foundation of memetics in full modern incarnation originates in the publication in 1996 of two books by authors outside the academic mainstream: Virus of the Mind: The New Science of the Meme by former Microsoft executive turned motivational speaker and professional poker player, Richard Brodie, and Thought Contagion: How Belief Spreads Through Society by Aaron Lynch, a mathematician and philosopher who worked for many years as an engineer at Fermilab. Lynch claimed to have conceived his theory totally independently of any contact with academics in the cultural evolutionary sphere, and apparently was not even aware of Dawkins' The Selfish Gene until his book was very close to publication.

Around the same time as the publication of the books by Lynch and Brodie the e-journal Journal of Memetics – Evolutionary Models of Information Transmission appeared on the web. It was first hosted by the Centre for Policy Modelling at Manchester Metropolitan University but later taken over by Francis Heylighen of the CLEA research institute at the Vrije Universiteit Brussel. The e-journal soon became the central point for publication and debate within the nascent memeticist community. (There had been a short-lived paper memetics publication starting in 1990, the Journal of Ideas edited by Elan Moritz.^[8]) In 1999, Susan Blackmore, a psychologist at the University of the West of England, published The Meme Machine, which more fully worked out the ideas of Dennett, Lynch, and Brodie and attempted to compare and contrast them with various approaches from the cultural evolutionary mainstream, as well as providing novel, and controversial, memetics-based theories for the evolution of language and the human sense of individual selfhood.

The term "meme"

The term "meme" derives from the Ancient Greek μιμητής (mimētḗs), meaning "imitator, pretender". The similar term "mneme" was used in 1904, by the German evolutionary biologist Richard Semon, best known for his development of the engram theory of memory, in his work Die mnemischen Empfindungen in ihren Beziehungen zu den Originalempfindungen, translated into English in 1921 as The Mneme. Until Daniel Schacter published Forgotten Ideas, Neglected Pioneers: Richard Semon and the Story of Memory in 2000, Semon's work had little influence, though it was quoted extensively in Erwin Schrödinger’s prescient 1956 Tarner Lecture “Mind and Matter”. Richard Dawkins (1976) apparently coined the word "meme" independently of Semon, writing this:

“Mimeme” comes from a suitable Greek root, but I want a monosyllable that sounds a bit like “gene”. I hope my classicist friends will forgive me if I abbreviate mimeme to meme. If it is any consolation, it could alternatively be thought of as being related to “memory”, or to the French word même.

Maturity

In 2005, the Journal of Memetics – Evolutionary Models of Information Transmission ceased publication and published a set of articles on the future of memetics. The website states that although "there was to be a relaunch...after several years nothing has happened".^[9] Susan Blackmore has left the University of the West of England to become a freelance science writer and now concentrates more on the field of consciousness and cognitive science. Derek Gatherer moved to work as a computer programmer in the pharmaceutical industry, although he still occasionally publishes on memetics-related matters. Richard Brodie is now climbing the world professional poker rankings. Aaron Lynch disowned the memetics community and the words "meme" and "memetics" (without disowning the ideas in his book), adopting the self-description "thought contagionist". Lynch lost his previous funding from a private sponsor and after his book royalties declined, he was unable to support himself as a private memetics/thought-contagion consultant.^{[citation needed]} He died in 2005.

Susan Blackmore (2002) re-stated the definition of meme as: whatever is copied from one person to another person, whether habits, skills, songs, stories, or any other kind of information. Further she said that memes, like genes, are replicators in the sense as defined by Dawkins.^[10] That is, they are information that is copied. Memes are copied by imitation, teaching and other methods. The copies are not perfect: memes are copied with variation; moreover, they compete for space in our memories and for the chance to be copied again. Only some of the variants can survive. The combination of these three elements (copies; variation; competition for survival) forms precisely the condition for Darwinian evolution, and so memes (and hence human cultures) evolve. Large groups of memes that are copied and passed on together are called co-adapted meme complexes, or memeplexes. In her definition, the way that a meme replicates is through imitation. This requires brain capacity to generally imitate a model or selectively imitate the model. Since the process of social learning varies from one person to another, the imitation process cannot be said to be completely imitated. The sameness of an idea may be expressed with different memes supporting it. This is to say that the mutation rate in memetic evolution is extremely high, and mutations are even possible within each and every interaction of the imitation process. It becomes very interesting when we see that a social system composed of a complex network of microinteractions exists, but at the macro level an order emerges to create culture.

Internalists and externalists

The memetics movement split almost immediately into two. The first group were those who wanted to stick to Dawkins' definition of a meme as "a unit of cultural transmission". Gibran Burchett, another memeticist responsible for helping to research and co-coin the term memetic engineering, along with Leveious Rolando and Larry Lottman, has stated that a meme can be defined, more precisely, as "a unit of cultural information that can be copied, located in the brain". This thinking is more in line with Dawkins' second definition of the meme in his book The Extended Phenotype. The second group wants to redefine memes as observable cultural artifacts and behaviors. However, in contrast to those two positions, Blackmore does not reject either concept of external or internal memes.^[11]

These two schools became known as the "internalists" and the "externalists." Prominent internalists included both Lynch and Brodie; the most vocal externalists included Derek Gatherer, a geneticist from Liverpool John Moores University, and William Benzon, a writer on cultural evolution and music. The main rationale for externalism was that internal brain entities are not observable, and memetics cannot advance as a science, especially a quantitative science, unless it moves its emphasis onto the directly quantifiable aspects of culture. Internalists countered with various arguments: that brain states will eventually be directly observable with advanced technology, that most cultural anthropologists agree that culture is about beliefs and not artifacts, or that artifacts cannot be replicators in the same sense as mental entities (or DNA) are replicators. The debate became so heated that a 1998 Symposium on Memetics, organised as part of the 15th International Conference on Cybernetics, passed a motion calling for an end to definitional debates. McNamara demonstrated in 2011 that functional connectivity profiling using neuroimaging tools enables the observation of the processing of internal memes (i-memes) in response to external e-memes.^[12]

An advanced statement of the internalist school came in 2002 with the publication of The Electric Meme, by Robert Aunger, an anthropologist from the University of Cambridge. Aunger also organised a conference in Cambridge in 1999, at which prominent sociologists and anthropologists were able to give their assessment of the progress made in memetics to that date. This resulted in the publication of Darwinizing Culture: The Status of Memetics as a Science, edited by Aunger and with a foreword by Dennett, in 2000.

Criticism

This evolutionary model of cultural information transfer is based on the concept that units of information, or "memes", have an independent existence, are self-replicating, and are subject to selective evolution through environmental forces.^[13] Starting from a proposition put forward in the writings of Richard Dawkins, it has since turned into a new area of study, one that looks at the self-replicating units of culture. It has been proposed that just as memes are analogous to genes, memetics is analogous to genetics.
Critics contend that some proponents' assertions are "untested, unsupported or incorrect."^[13] Luis Benitez-Bribiesca, a critic of memetics, calls it "a pseudoscientific dogma" and "a dangerous idea that poses a threat to the serious study of consciousness and cultural evolution" among other things. As factual criticism, he refers to the lack of a code script for memes, as the DNA is for genes, and to the fact that the meme mutation mechanism (i.e., an idea going from one brain to another) is too unstable (low replication accuracy and high mutation rate), which would render the evolutionary process chaotic.^[14]

Another criticism comes from semiotics, (e.g., Deacon,^[15] Kull^[16]) stating that the concept of meme is a primitivized concept of Sign. Meme is thus described in memetics as a sign without its triadic nature. In other words, meme is a degenerate sign, which includes only its ability of being copied. Accordingly, in the broadest sense, the objects of copying are memes, whereas the objects of translation and interpretation are signs.

Mary Midgley criticises memetics for at least two reasons:^[17] One, culture is not best understood by examining its smallest parts, as culture is pattern-like, comparable to an ocean current. Many more factors, historical and others, should be taken into account than only whatever particle culture is built from. Two, if memes are not thoughts (and thus not cognitive phenomena), as Daniel C. Dennett insists in "Darwin's Dangerous Idea", then their ontological status is open to question, and memeticists (who are also reductionists) may be challenged whether memes even exist. Questions can extend to whether the idea of "meme" is itself a meme, or is a true concept. Fundamentally, memetics is an attempt to produce knowledge through organic metaphors, which as such is a questionable research approach, as the application of metaphors has the effect of hiding that which does not fit within the realm of the metaphor. Rather than study actual reality, without preconceptions, memetics, as so many of the socio-biological explanations of society, believe that saying that the apple is like an orange is a valid analysis of the apple.^[18]

Like other critics, Maria Kronfeldner has criticized memetics for being based on an allegedly inaccurate analogy with the gene; alternately, she claims it is "heuristically trivial", being a mere redescription of what is already known without offering any useful novelty.^[19]

New developments

Dawkins responds in A Devil's Chaplain that there are actually two different types of memetic processes (controversial and informative). The first is a type of cultural idea, action, or expression, which does have high variance; for instance, a student of his who had inherited some of the mannerisms of Wittgenstein. However, he also describes a self-correcting meme, highly resistant to mutation. As an example of this, he gives origami patterns in elementary schools – except in rare cases, the meme is either passed on in the exact sequence of instructions, or (in the case of a forgetful child) terminates. This type of meme tends not to evolve, and to experience profound mutations in the rare event that it does.

Another definition, given by Hokky Situngkir, tried to offer a more rigorous formalism for the meme, memeplexes, and the deme, seeing the meme as a cultural unit in a cultural complex system. It is based on the Darwinian genetic algorithm with some modifications to account for the different patterns of evolution seen in genes and memes. In the method of memetics as the way to see culture as a complex adaptive system, he describes a way to see memetics as an alternative methodology of cultural evolution. However, there are as many possible definitions that are credited to the word "meme". For example, in the sense of computer simulation the term memetic algorithm is used to define a particular computational viewpoint.

The possibility of quantitative analysis of memes using neuroimaging tools and the suggestion that such studies have already been done was given by McNamara (2011).^[12] This author proposes hyperscanning (concurrent scanning of two communicating individuals in two separate MRI machines) as a key tool in the future for investigating memetics.

In 2013 Australian academic JT Velikovsky proposed the holon as the structure of the meme,^[20] synthesizing the major theories on memes of Richard Dawkins, Mihaly Csikszentmihalyi, E. O. Wilson, Frederick Turner (poet) and Arthur Koestler.

Memetics can be simply understood as a method for scientific analysis of cultural evolution. However, proponents of memetics as described in the Journal of Memetics (out of print since 2005^[21] ) – Evolutionary Models of Information Transmission believe that 'memetics' has the potential to be an important and promising analysis of culture using the framework of evolutionary concepts. Keith Henson who wrote Memetics and the Modular-Mind (Analog Aug. 1987)^[22] makes the case that memetics needs to incorporate evolutionary psychology to understand the psychological traits of a meme's host.^[23] This is especially true of time-varying, meme-amplification host-traits, such as those leading to wars.^[24][25]

Recently, Christopher diCarlo has developed the idea of 'memetic equilibrium' to describe a cultural compatible state with biological equilibrium. In "Problem Solving and Neurotransmission in the Upper Paleolithic" (in press), diCarlo argues that as human consciousness evolved and developed, so too did our ancestors' capacity to consider and attempt to solve environmental problems in more conceptually sophisticated ways. Understood in this way, problem solving amongst a particular group, when considered satisfactory, often produces a feeling of environmental control, stability, in short—memetic equilibrium. But the pay-off is not merely practical, providing purely functional utility—it is biochemical and it comes in the form of neurotransmitters. The relationship between a gradually emerging conscious awareness and sophisticated languages in which to formulate representations combined with the desire to maintain biological equilibrium, generated the necessity for memetic equilibrium to fill in conceptual gaps in terms of understanding three very important aspects in the Upper Paleolithic: causality, morality, and mortality. The desire to explain phenomena in relation to maintaining survival and reproductive stasis, generated a normative stance in the minds of our ancestors—Survival/Reproductive Value (or S-R Value).

Jan E.M. Houben has argued on several occasions that the well-attested, exceptional resilience of Vedic ritual and its interaction with a changing ecological and economic environment over several millennia (at least from the mid-second millennium B.C.) can be profitably dealt with in a ‘cultural evolution’ perspective in which the Vedic mantra is the ‘meme’ or unit of cultural replication.^[26] This renders superfluous attempts to explain the phenomenon of the millennia old tradition of Vedic ritual in genetic terms.^[27] The term ‘meme’ is here taken as a pointer to a rich analogy of biological-cultural parallelism (gene-meme) in a perspective of cultural evolution, which in itself does not suffice to turn ‘memetics’ into a ‘science’: with regard to Vedic ritual it is rather an extended metaphor useful to address both large-scale and micro-scale aspects of the phenomenon and their interrelation that remained hitherto out of view. The domain of Vedic ritual should nevertheless be able to fulfil to a large extent the three challenges posed to memetics by B. Edmonds (2002 and 2005).^[28]

Applications

Research methodologies that apply memetics go by many names: Viral marketing, cultural evolution, the history of ideas, social analytics, and more. Many of these applications do not make reference to the literature on memes directly but are built upon the evolutionary lens of idea propagation that treats semantic units of culture as self-replicating and mutating patterns of information that are assumed to be relevant for scientific study. For example, the field of public relations is filled with attempts to introduce new ideas and alter social discourse. One means of doing this is to design a meme and deploy it through various media channels. One historic example of applied memetics is the PR campaign conducted in 1991 as part of the build-up to the first Gulf War in the United States.^[29]

The application of memetics to a difficult complex social system problem, environmental sustainability, has recently been attempted at thwink.org. Using meme types and memetic infection in several stock and flow simulation models, Jack Harich has demonstrated several interesting phenomena that are best, and perhaps only, explained by memes. One model, The Dueling Loops of the Political Powerplace, argues that the fundamental reason corruption is the norm in politics is due to an inherent structural advantage of one feedback loop pitted against another. Another model, The Memetic Evolution of Solutions to Difficult Problems, uses memes, the evolutionary algorithm, and the scientific method to show how complex solutions evolve over time and how that process can be improved. The insights gained from these models are being used to engineer memetic solution elements to the sustainability problem.

Another application of memetics in the sustainability space is the crowdfunded Climate Meme Project conducted by Joe Brewer and Balasz Laszlo Karafiath in the spring of 2013. This study was based on a collection of 1000 unique text-based expressions gathered from Twitter, Facebook, and structured interviews with climate activists. The major finding was that the global warming meme is not effective at spreading because it causes emotional duress in the minds of people who learn about it. Five central tensions were revealed in the discourse about [climate change], each of which represents a resonance point through which dialogue can be engaged. The tensions were Harmony/Disharmony (whether or not humans are part of the natural world), Survival/Extinction (envisioning the future as either apocalyptic collapse of civilization or total extinction of the human race), Cooperation/Conflict (regarding whether or not humanity can come together to solve global problems), Momentum/Hesitation (about whether or not we are making progress at the collective scale to address climate change), and Elitism/Heretic (a general sentiment that each side of the debate considers the experts of its opposition to be untrustworthy.^[30]
Ben Cullen, in his book Contagious Ideas,^[31] brought the idea of the meme into the discipline of archaeology. He coined the term "Cultural Virus Theory", and used it to try to anchor archaeological theory in a neo-Darwinian paradigm. Archaeological memetics could assist the application of the meme concept to material culture in particular.

Francis Heylighen of the Center Leo Apostel for Interdisciplinary Studies has postulated what he calls "memetic selection criteria". These criteria opened the way to a specialized field of applied memetics to find out if these selection criteria could stand the test of quantitative analyses. In 2003 Klaas Chielens carried out these tests in a Masters thesis project on the testability of the selection criteria.

In Selfish Sounds and Linguistic Evolution,^[32] Austrian linguist Nikolaus Ritt has attempted to operationalise memetic concepts and use them for the explanation of long term sound changes and change conspiracies in early English. It is argued that a generalised Darwinian framework for handling cultural change can provide explanations where established, speaker centred approaches fail to do so. The book makes comparatively concrete suggestions about the possible material structure of memes, and provides two empirically rich case studies.

Australian academic S.J. Whitty has argued that project management is a memeplex with the language and stories of its practitioners at its core.^[33] This radical approach sees a project and its management as an illusion; a human construct about a collection of feelings, expectations, and sensations, which are created, fashioned, and labeled by the human brain. Whitty's approach requires project managers to consider that the reasons for using project management are not consciously driven to maximize profit, and are encouraged to consider project management as naturally occurring, self-serving, evolving process which shapes organizations for its own purpose.

Swedish political scientist Mikael Sandberg argues against "Lamarckian" interpretations of institutional and technological evolution and studies creative innovation of information technologies in governmental and private organizations in Sweden in the 1990s from a memetic perspective.^[34] Comparing the effects of active ("Lamarckian") IT strategy versus user–producer interactivity (Darwinian co-evolution), evidence from Swedish organizations shows that co-evolutionary interactivity is almost four times as strong a factor behind IT creativity as the "Lamarckian" IT strategy.

Terminology

• Memeplex – (an abbreviation of meme-complex) is a collection or grouping of memes that have evolved into a mutually supportive or symbiotic relationship.^[35] Simply put, a meme-complex is a set of ideas that reinforce each other. Meme-complexes are roughly analogous to the symbiotic collection of individual genes that make up the genetic codes of biological organisms. An example of a memeplex would be a religion.

• Meme pool – a population of interbreeding memes.

• Memetic engineering – The process of deliberately creating memes, using engineering principles.

• Memetic algorithms - an approach to evolutionary computation that attempts to emulate cultural evolution in order to solve optimization problems.

• Memotype – is the actual information-content of a meme.^[36]

• Memeoid – is a neologism for people who have been taken over by a meme to the extent that their own survival becomes inconsequential. Examples include kamikazes, suicide bombers and cult members who commit mass suicide. The term was apparently coined by H. Keith Henson in "Memes, L5 and the Religion of the Space Colonies," L5 News,September 1985 pp. 5–8,^[37] and referenced in the expanded second edition of Richard Dawkins' book The Selfish Gene (p. 330). But in the strict sense all people are essentially memeoid, since no distinction can be made if one uses language, or memes use their host. In The Electronic Revolution William S. Burroughs writes: "the word has not been recognised as a virus because it has achieved a state of stable symbiosis with the host."

• Memetic equilibrium – refers to the cultural equivalent of species biological equilibrium. It is that which humans strive for in terms of personal value with respect to cultural artefacts and ideas. The term was coined by Christopher diCarlo.^[38]

Dual inheritance theory

From Wikipedia, the free encyclopedia

Dual inheritance theory (DIT), also known as gene–culture coevolution or biocultural evolution,^[1] was developed in the late 1970s and early 1980s to explain how human behavior is a product of two different and interacting evolutionary processes: genetic evolution and cultural evolution. In DIT, culture is defined as information and behavior acquired through social learning. One of the theory's central claims is that culture evolves partly through a Darwinian selection process, which dual inheritance theorists often describe by analogy to genetic evolution.^[2]

Because genetic evolution is relatively well understood, most of DIT examines cultural evolution and the interactions between cultural evolution and genetic evolution.

Theoretical basis

DIT holds that genetic and cultural evolution interacted in the evolution of Homo sapiens. DIT recognizes that the natural selection of genotypes is an important component of the evolution of human behavior and that cultural traits can be constrained by genetic imperatives. However, DIT also recognizes that genetic evolution has endowed the human species with a parallel evolutionary process of cultural evolution. DIT makes three main claims:^[3]

Culture capacities are adaptations

The human capacity to store and transmit culture arose from genetically evolved psychological mechanisms. This implies that at some point during the evolution of the human species a type of social learning leading to cumulative cultural evolution was evolutionarily advantageous.

Culture evolves

Social learning processes give rise to cultural evolution. Cultural traits are transmitted differently from genetic traits and, therefore, result in different population-level effects on behavioral variation.

Genes and culture coevolve

Cultural traits alter the social and physical environments under which genetic selection operates. For example, the cultural adoptions of agriculture and dairying have, in humans, caused genetic selection for the traits to digest starch and lactose, respectively.^{[4][5][6][7][8][9]} As another example, it is likely that once culture became adaptive, genetic selection caused a refinement of the cognitive architecture that stores and transmits cultural information. This refinement may have further influenced the way culture is stored and the biases that govern its transmission.
DIT also predicts that, under certain situations, cultural evolution may select for traits that are genetically maladaptive. An example of this is the demographic transition, which describes the fall of birth rates within industrialized societies. Dual inheritance theorists hypothesize that the demographic transition may be a result of a prestige bias, where individuals that forgo reproduction to gain more influence in industrial societies are more likely to be chosen as cultural models.^[10][11]

View of culture

People have defined the word "culture" to describe a large set of different phenomena.^[12][13] A definition that sums up what is meant by "culture" in DIT is:

Culture is information stored in individuals' brains that is capable of affecting behavior and that got there through social learning.^[14][15]

This view of culture emphasizes population thinking by focusing on the process by which culture is generated and maintained. It also views culture as a dynamic property of individuals, as opposed to a view of culture as a superorganic entity to which individuals must conform.^[16] This view's main advantage is that it connects individual-level processes to population-level outcomes.^[17]

Genetic influence on cultural evolution

Genes have an impact on cultural evolution via psychological predispositions on cultural learning.^[18] Genes encode much of the information needed to form the human brain. Genes constrain the brain's structure and, hence, the ability of the brain to acquire and store culture. Genes may also endow individuals with certain types of transmission bias (described below).

Cultural influences on genetic evolution

Culture can profoundly influence gene frequencies in a population. One of the best known examples is the prevalence of the genotype for adult lactose absorption in human populations, such as Northern Europeans and some African societies, with a long history of raising cattle for milk. Other societies such as East Asians and Amerindians, retain the typical mammalian genotype in which the body shuts down lactase production shortly after the normal age of weaning. This implies that the cultural practice of raising cattle first for meat and later for milk led to selection for genetic traits for lactose digestion.^[19] Recently, analysis of natural selection on the human genome suggests that civilization has accelerated genetic change in humans over the past 10,000 years.^[20]

Mechanisms of cultural evolution

In DIT, the evolution and maintenance of cultures is described by five major mechanisms: natural selection of cultural variants, random variation, cultural drift, guided variation and transmission bias.

Natural selection

Cultural differences among individuals can lead to differential survival of individuals. The patterns of this selective process depend on transmission biases and can result in behavior that is more adaptive to a given environment.

Random variation

Random variation arises from errors in the learning, display or recall of cultural information, and is roughly analogous to the process of mutation in genetic evolution.

Cultural drift

Cultural drift is a process roughly analogous to genetic drift in evolutionary biology.^[21][22][23] In cultural drift, the frequency of cultural traits in a population may be subject to random fluctuations due to chance variations in which traits are observed and transmitted (sometimes called "sampling error").^[24] These fluctuations might cause cultural variants to disappear from a population. This effect should be especially strong in small populations.^[25] A model by Hahn and Bentley shows that cultural drift gives a reasonably good approximation to changes in the popularity of American baby names.^[24] Drift processes have also been suggested to explain changes in archaeological pottery and technology patent applications.^[23] Changes in the songs of song birds are also thought to arise from drift processes, where distinct dialects in different groups occur due to errors in songbird singing and acquisition by successive generations.^[26] Cultural drift is also observed in an early computer model of cultural evolution.^[27]

Guided variation

Cultural traits may be gained in a population through the process of individual learning. Once an individual learns a novel trait, it can be transmitted to other members of the population. The process of guided variation depends on an adaptive standard that determines what cultural variants are learned.

Biased transmission

Understanding the different ways that culture traits can be transmitted between individuals has been an important part of DIT research since the 1970s.^[28][29] Transmission biases occur when some cultural variants are favored over others during the process of cultural transmission.^[30] Boyd and Richerson (1985)^[30] defined and analytically modeled a number of possible transmission biases. The list of biases has been refined over the years, especially by Henrich and McElreath.^[31]

Content bias

Content biases result from situations where some aspect of a cultural variant's content makes them more likely to be adopted.^[32] Content biases can result from genetic preferences, preferences determined by existing cultural traits, or a combination of the two. For example, food preferences can result from genetic preferences for sugary or fatty foods and socially-learned eating practices and taboos.^[32] Content biases are sometimes called "direct biases."^[30]

Context bias

Context biases result from individuals using clues about the social structure of their population to determine what cultural variants to adopt. This determination is made without reference to the content of the variant. There are two major categories of context biases: (1) model-based biases, and (2) frequency-dependent biases.

Model-based biases

Model-based biases result when an individual is biased to choose a particular "cultural model" to imitate. There are four major categories of model-based biases: (1) prestige bias, (2) skill bias, (3) success bias, (4) similarity bias.^[3][33] A "prestige bias" results when individuals are more likely to imitate cultural models that are seen as having more prestige. A measure of prestige could be the amount of deference shown to a potential cultural model by other individuals. A "skill bias" results when individuals can directly observe different cultural models performing a learned skill and are more likely to imitate cultural models that perform better at the specific skill. A "success bias" results from individuals preferentially imitating cultural models that they determine are most generally successful (as opposed to successful at a specific skill as in the skill bias.) A "similarity bias" results when individuals are more likely to imitate cultural models that are perceived as being similar to the individual based on specific traits.

Frequency-dependent biases

Frequency-dependent biases result when an individual is biased to choose particular cultural variants based on their perceived frequency in the population. The most explored frequency-dependent bias is the "conformity bias." Conformity biases result when individuals attempt to copy the mean or the mode cultural variant in the population. Another possible frequency dependent bias is the "rarity bias." The rarity bias results when individuals preferentially choose cultural variants that are less common in the population. The rarity bias is also sometimes called a "nonconformist" or "anti-conformist" bias.

Social learning and cumulative cultural evolution

In DIT, the evolution of culture is dependent on the evolution of social learning. Analytic models show that social learning becomes evolutionarily beneficial when the environment changes with enough frequency that genetic inheritance can not track the changes, but not fast enough that individual learning is more efficient.^[34] While other species have social learning, and thus some level of culture, only humans, some birds and chimpanzees are known to have cumulative culture.^[35] Boyd and Richerson argue that the evolution of cumulative culture depends on observational learning and is uncommon in other species because it is ineffective when it is rare in a population.
They propose that the environmental changes occurring in the Pleistocene may have provided the right environmental conditions.^[36] Michael Tomasello argues that cumulative cultural evolution results from a "ratchet effect" that began when humans developed the cognitive architecture to understand others as mental agents.^[37] Furthermore Tomasello proposed in the 80s that there are some disparities between the observational learning mechanisms found in humans and great apes - which go some way to explain the observable difference between great ape traditions and human types of culture (see Emulation (observational learning)).

Cultural group selection

Although group selection is commonly thought to be nonexistent or unimportant in genetic evolution,^[38][39][40] DIT predicts that, due to the nature of cultural inheritance, it may be an important force in cultural evolution. The reason group selection is thought to operate in cultural evolution is because of conformist biases (see above section on transmission biases). Conformist biases make it difficult for novel cultural traits to spread through a population. Conformist bias also helps maintain variation between groups. These two properties, rare in genetic transmission, are necessary for group selection to operate.^[41] Based on an earlier model by Cavalli-Sforza and Feldman,^[42] Boyd and Richerson show that conformist biases are almost inevitable when traits spread through social learning,^[43] implying that group selection is common in cultural evolution. Analysis of small groups in New Guinea imply that cultural group selection might be a good explanation for slowly changing aspects of social structure, but not for rapidly changing fads.^[44] The ability of cultural evolution to maintain intergroup diversity is what allows for the study of cultural phylogenetics.^[45]

Historical development

The idea that human cultures undergo a similar evolutionary process as genetic evolution goes back at least to Darwin^[46] In the 1960s, Donald T. Campbell published some of the first theoretical work that adapted principles of evolutionary theory to the evolution of cultures.^[47] In 1976, two developments in cultural evolutionary theory set the stage for DIT. In that year Richard Dawkins's The Selfish Gene introduced ideas of cultural evolution to a popular audience. Although one of the best-selling science books of all time, because of its lack of mathematical rigor, it had little impact on the development of DIT. Also in 1976, geneticists Marcus Feldman and Luigi Luca Cavalli-Sforza published the first dynamic models of gene–culture coevolution.^[48] These models were to form the basis for subsequent work on DIT, heralded by the publication of three seminal books in the 1980s.

The first was Charles Lumsden and E.O. Wilson's Genes, Mind and Culture.^[49] This book outlined a series of mathematical models of how genetic evolution might favor the selection of cultural traits and how cultural traits might, in turn, affect the speed of genetic evolution. While it was the first book published describing how genes and culture might coevolve, it had relatively little impact on the further development of DIT.^[50] Some critics felt that their models depended too heavily on genetic mechanisms at the expense of cultural mechanisms.^[51] Controversy surrounding Wilson's sociobiological theories may also have decreased the lasting impact of this book.^[50]

The second 1981 book was Cavalli-Sforza and Feldman's Cultural Transmission and Evolution: A Quantitative Approach.^[22] Borrowing heavily from population genetics and epidemiology, this book built a mathematical theory concerning the spread of cultural traits. It describes the evolutionary implications of vertical transmission, passing cultural traits from parents to offspring; oblique transmission, passing cultural traits from any member of an older generation to a younger generation; and horizontal transmission, passing traits between members of the same population.

The next significant DIT publication was Robert Boyd and Peter Richerson's 1985 Culture and the Evolutionary Process.^[30] This book presents the now-standard mathematical models of the evolution of social learning under different environmental conditions, the population effects of social learning, various forces of selection on cultural learning rules, different forms of biased transmission and their population-level effects, and conflicts between cultural and genetic evolution. The book's conclusion also outlined areas for future research that are still relevant today.

Current and future research

In their 1985 book, Boyd and Richerson outlined an agenda for future DIT research. This agenda, outlined below, called for the development of both theoretical models and empirical research. DIT has since built a rich tradition of theoretical models over the past two decades.^[52] However, there has not been a comparable level of empirical work.
In a 2006 interview Harvard biologist E. O. Wilson expressed disappointment at the little attention afforded to DIT:

"...for some reason I haven't fully fathomed, this most promising frontier of scientific research has attracted very few people and very little effort." ^[53]

Kevin Laland and Gillian Brown attribute this lack of attention to DIT's heavy reliance on formal modeling.

"In many ways the most complex and potentially rewarding of all approaches, [DIT], with its multiple processes and cerebral onslaught of sigmas and deltas, may appear too abstract to all but the most enthusiastic reader. Until such a time as the theoretical hieroglyphics can be translated into a respectable empirical science most observers will remain immune to its message."^[54]

Economist Herbert Gintis disagrees with this critique, citing empirical work as well as more recent work using techniques from behavioral economics.^[55] These behavioral economic techniques have been adapted to test predictions of cultural evolutionary models in laboratory settings ^[56][57][58] as well as studying differences in cooperation in fifteen small-scale societies in the field.^[59]

Since one of the goals of DIT is to explain the distribution of human cultural traits, ethnographic and ethnologic techniques may also be useful for testing hypothesis stemming from DIT. Although findings from traditional ethnologic studies have been used to buttress DIT arguments,^[60][61] thus far there have been little ethnographic fieldwork designed to explicitly test these hypotheses.^[44][59][62]

Herb Gintis has named DIT one of the two major conceptual theories with potential for unifying the behavioral sciences, including economics, biology, anthropology, sociology, psychology and political science. Because it addresses both the genetic and cultural components of human inheritance, Gintis sees DIT models as providing the best explanations for the ultimate cause of human behavior and the best paradigm for integrating those disciplines with evolutionary theory.^[63] In a review of competing evolutionary perspectives on human behavior, Laland and Brown see DIT as the best candidate for uniting the other evolutionary perspectives under one theoretical umbrella.^[64]

Relation to other fields

Sociology and cultural anthropology

Two major topics of study in both sociology and cultural anthropology are human cultures and cultural variation. However, Dual Inheritance theorists charge that both disciplines too often treat culture as a static superorganic entity that dictates human behavior.^[65][66] Cultures are defined by a suite of common traits shared by a large group of people. DIT theoriests argue that this doesn't sufficiently explain variation in cultural traits at the individual level. By contrast, DIT models human culture at the individual level and views culture as the result of a dynamic evolutionary process at the population level.^[65][67]

Human sociobiology and evolutionary psychology

Human sociobiologists and evolutionary psychologists try to understand how maximizing genetic fitness, in either the modern era or past environments, can explain human behavior. When faced with a common and seemingly maladaptive trait, practitioners from these disciplines try to determine how the trait actually increases genetic fitness (maybe through kin selection or by speculating about early evolutionary environments). Dual Inheritance theorists, in contrast, will consider a variety of genetic and cultural processes in addition to natural selection on genes.

Human behavioral ecology

Human behavioral ecology (HBE) and DIT have a similar relationship to what ecology and evolutionary biology have in the biological sciences. HBE is more concerned about ecological process and DIT more focused on historical process. One difference is that human behavioral ecologists often assume that culture is a system that produces the most adaptive outcome in a given environment. This implies that similar behavioral traditions should be found in similar environments. However, this is not always the case. A study of African cultures showed that cultural history was a better predictor of cultural traits than local ecological conditions.^[68]

Memetics

Memetics, which comes from the meme idea described in Dawkins's The Selfish Gene, is similar to DIT in that it treats culture as an evolutionary process that is distinct from genetic transmission. However, there are some philosophical differences between memetics and DIT.^[69] One difference is that memetics' focus is on the selection potential of discrete replicators (memes), where DIT allows for transmission of both non-replicators and non-discrete cultural variants. DIT does not assume that replicators are necessary for cumulative adaptive evolution. DIT also more strongly emphasizes the role of genetic inheritance in shaping the capacity for cultural evolution. But perhaps the biggest difference is a difference in academic lineage. Memetics as a label is more influential in popular culture than in academia. Critics of memetics argue that it is lacking in empirical support or is conceptually ill-founded, and question whether there is hope for the memetic research program succeeding. Proponents point out that many cultural traits are discrete, and that many existing models of cultural inheritance assume discrete cultural units, and hence involve memes.^[70]

Criticisms

A number of criticisms of DIT have been put forward.^[71][72][73] From some points of view, use of the term ‘dual inheritance’ to refer to both what is transmitted genetically and what is transmitted culturally is technically misleading.^{[citation needed]} Many opponents cite horizontal transmission of ideas to be so "different" from the typical vertical transmission (reproduction) in genetic evolution that it is not evolution. However, 1) even genetic evolution uses non-vertical transmission through the environmental alteration of the genome during life by acquired circumstance: epigenetics, and 2) genetic evolution is also affected by direct horizontal transmission between separate species of plants and strains of bacteria: horizontal gene transfer. Other critics argue that there can be no "dual" inheritance without cultural inheritance being "sequestered" by the biotic genome^{[citation needed]}. Evidence for this process is scarce and controversial. Why this is a demand of critics, however, can be considered unclear as it refutes none of the central claims laid down by proponents of DIT.

More serious criticisms of DIT arise from the choice of Darwinian selection as an explanatory framework for culture. Some argue, cultural evolution does not possess the algorithmic structure of a process that can be modeled in a Darwinian framework as characterized by John von Neumann^[74] and used by John Holland to design the genetic algorithm.^[75] Forcing culture into a Darwinian framework gives a distorted picture of the process for several reasons. First, some argue Darwinian selection only works as an explanatory framework when variation is randomly generated.^{[citation needed]} To the extent that transmission biases are operative in culture, they mitigate the effect of Darwinian change, i.e. change in the distribution of variants over generations of exposure to selective pressures.^{[citation needed]} Second, since acquired change can accumulate orders of magnitude faster than inherited change, if it is not getting regularly discarded each generation, it quickly overwhelms the population-level mechanism of change identified by Darwin; it ‘swamps the phylogenetic signal’.^{[citation needed]} However, DIT proponents might reply that, 1) biotic evolution does not function only on randomly generated phenotypes either, since the phenotypes present in a population are the combined result of random and selective effects during the last generation; and 2)that transmission bias would quite often also reinforce "Darwinian change" since it is widely evidenced that Culture has adaptive value in increasing human fitness.

Another discord in opinion stems from DIT opponents' assertion that there exists some "creative force" that is applied to each idea as it is received and before it is passed on, and that this agency is so powerful that it can be stronger than the selective system of other individuals assessing what to teach and whether your idea has merit^{[citation needed]}. But if this criticism was valid then it would be comparatively much easier to argue an unpopular or incorrect concepts than it actually is. In addition, nothing about DIT runs counter to the idea that an internally selective process (some would call creativity) also determines the fitness of ideas received and sent. In fact this decision making is a large part of the territory embraced by DIT proponents but is poorly understood due to limitations in neurobiology (for more information see Neural Darwinism).

Related criticisms of the effort to frame culture in Darwinian terms have been leveled by Richard Lewontin,^[76] Niles Eldredge,^[77] and Stuart Kauffman.^[78]

Bees Matter

Written by Lee Townsend

 

Orignal link:  http://albertabuzzing.com/2015/02/beesmatter/

 

 

Last week a new website called “Beesmatter” was launched, and with it came an open letter to Ontarians titled “Getting the Facts Straight on Honey Bees”.  This was developed and released by Ontario farmers and the agricultural industry that supports them, and I think it is a great concept.  My understanding is that this will be a national awareness campaign meant to draw attention to the importance of honey bees.

I’d love to say that the beesmatter project is very similar to collaborations between beekeepers/farmers/agricultural industry that have taken place on the Canadian prairies, but sadly the Ontario Beekeepers Association (OBA) was not involved in this instance.  That is not due to Ontario farmers excluding the OBA, it’s due to the OBA board of directors being far too ignorant to work with the farmers and agricultural industry in Ontario.

Later in the week, the OBA released its response to the #beesmatter letter.  I’ve taken the time to read both letters and while both make valid points, both also omit facts in order to prove their points (more so the OBA).  I have a much bigger problem with the OBA’s response, as it is the prototypical environmental activist jargon that we’ve come to expect from that organization these days.

I’ll start with the #beesmatter letter.  I fully understand the purpose of the letter, and overall it was well done and well intentioned.  On the Canadian prairies, this kind of project would have been fully supported by the beekeeping industry.  As the beekeeping industry is quite small and very much an unknown commodity to most people, this is the kind of PR we dream of.  It is unfortunate though that certain media outlets and the OBA have labelled it “chemical company propaganda”, as I and most others realize that’s not the case.  There was a great deal of good information in it, but there were also important points left out of it.

Statistics Canada data demonstrates that in Ontario, honey bee colony numbers are up almost 60 per cent since 2003, when the use of neonicotinoid seed treatments were introduced. Honey production has increased by 29 per cent in the past year, and Ontario has a successful honey beekeeping industry which earned $30 million in 2014.

This statement is true because Ontario beekeepers did an exceptional job of not only replacing their winter dead outs but also increasing the number of colonies in that province.  In 2014 Ontario recorded the most colonies its ever had, which is something beekeepers there should be commended for.  What was left out though is that Ontario claimed losses of 58% in the spring of 2014 (which is up for debate, which I’ll go into more later).  A loss of that magnitude is difficult to recover from.  An increase in honey production/profits was also mentioned.  This may be true, as we noticed the same thing in Alberta, but like any form of Agriculture our production varies on a yearly basis.  We are also seeing some of the highest honey prices in our history.   

Health Canada recently released a report indicating that, in 2014, the number of honey bee incidents reported during planting was down 70 per cent from 2013. And, of the late season issues reported, 72 per cent were made by only three beekeepers out of 3,262.

This statement is a direct reflection of the PMRA report that was released on November 25, 2014.  Honestly, all anyone can go on is what the report states.  It does appear that the new dust-reducing seed flow lubricant as well as updated best management practices by the farmers during seeding accomplished what was intended.  There have been claims by the OBA board that this is indeed not the case, but there is little fact to back up their claims.

85 per cent of Canadian honey is produced in western Canada where there are no known honey bee colony health issues resulting from neonicotinoid seed treatment use.

This statement is true.  Bees on the Canadian prairies forage primarily on canola, which is treated with neonicotinoids.  Considering that 21 million acres (from what I understand) of canola was grown out west in 2014, if neonics were the issue that Ontario makes it out to be we should be seeing the ill-effects from it in our bees as well.  We aren’t.

Other countries, including England and Australia, that rely on science-based regulatory systems have concluded that any risk to honey bee populations from neonicotinoids is low and manageable.

I do not fully understand how the regulatory systems in other countries works, but there has been a ban on neonics in the EU since late 2013.  After this ban was implemented the EU released this report on the status of bee health in the EU.  According to it, bee populations have increased by 13% since 2008 and the main causes of overwintering losses were attributed to harsh weather and disease/pests.  It appears the neonic ban there was based on anecdotal evidence, but it will be interesting to see further data on this in 2015

Here in Ontario, real-world field level research consistently demonstrates that responsible use of neonicotinoid seed treatments does not result in honey bee colony health issues.

There has been some excellent work done by Cynthia Scott-Dupree from the University of Guelph on this subject in recent years (here and here and here).  You can read them for yourself, and I feel they were very well done.

The Ontario Ministry of Agriculture, Food and Rural Affairs changed the criteria for reporting colony mortality in the province, resulting in inflated reports of overwinter mortality losses in Ontario.

This has yet to be explained by the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA).  According to OMAFRA, the overwintering losses in Ontario were determined by a voluntary survey sent out to the provinces 247 registered commercial beekeepers.  Out of that 247, only 97 responded to the survey (39% completion rate).  Out of these 97 producers, 50 reported losses of higher than 50%.  These producers that claimed losses of over 50% only represent 20% of the commercial beekeepers in Ontario.  How OMAFRA extrapolated that data to read as a 58% loss province wide is still uncertain.  It is also important to note that these beekeepers “suspected” chronic pesticide damage contributed to their losses.  There have been few to no official lab reports released by these beekeepers to back up that claim to date.

The claim of a 58% winter loss in Ontario has also been questioned by the Canadian Association of Professional Apiculturists (CAPA).  In their 2014 “Wintering Loss” report, they noted that the preliminary analysis of mortality in Ontario indicates that a proportion of beekeepers had a much lower level of mortality (9 to 22%) compared to the provincial average.  To date the OBA nor OMAFRA have explained this discrepancy.

Something else that OMAFRA does differently is how they define a dead colony.  For the rest of Canada, a colony with 3 or less frames of bees and brood is considered dead.  But in Ontario, 4 frames or less of bees and brood is used to define a dead colony.  Considering that there are many beekeepers using 4 frame nucs (small colonies used for queen production, colony replacement, etc.), it becomes unclear as to just how many of the hives that were declared dead by OMAFRA and the beekeepers were indeed dead.  And beekeepers are masters at saving small and/or weak colonies.  Generally a colony with 3 frames or less is culled by the beekeeper, but one with 4 frames can be saved and built into a producing colony that year.

One explanation for this though could be due to OMAFRA’s  “Beekeeper Compensation Plan“.  This program was launched in 2014 and was recently extended for the 2015 season.  The program works by paying the beekeeper $105/hive once their losses exceed 40%.  This payment doesn’t cover the first 40% of losses, just losses after that.
One concern with this program is that there is a suspicion that some beekeepers increased their colony numbers in late 2014 with 4 frame nucs in order to trigger more overwintering loss claims this spring.

Now, lets look at the OBA response.  Like all press releases put out by the OBA in recent years, it is full of half-truths.

Last winter Ontario beekeepers lost 58% of their hives. The number of honey bee colonies (measured in mid summer) does not reflect the large number of colonies lost each winter, nor does it reflect the 30,000 queens or nearly 20,000 bee packages that beekeepers had to purchase to replace the unusually high number of colonies that failed in the winter and spring. We also want to stress that although honey bee colonies can be managed by beekeepers to sustain their numbers, reports indicate serious declines among wild bees and other pollinators.

I’m not sure what point the OBA is trying to make here.  Buying large numbers of packages and queens is nothing new to most beekeepers in Canada, and our industry is highly reliant on these imports in order to replace our overwintering losses and yearly colony number increases.  The OBA is making it sound like this is something new, and while they did have to buy more bee stock in 2014 than ever before, they’ve been doing it for a very long time. 
They used to deny it, but it has always been easy to see through that.  And they not only used these bee imports to replace their losses, but they also increased their colony numbers in 2014 by 15,300 from 2013.  For comparisons sake, Alberta only increased the number of colonies it had by 4,100 from 2013 to 2014.  I really have an issue with the OBA using “wild bees and other pollinators” in their reasoning.  Last I checked the OBA was representing the honeybee industry in Ontario, and were not experts on other pollinators. 

Fact: Honey production on a per colony basis is actually down by 40% since 2003. We’d also like to point out that ‘earnings’ are not the same as ‘profits’. Every spring Ontario beekeepers work diligently, and at great cost, to recover their winter losses and respond to the high demand for bees for blueberry pollination. Ontario’s beekeepers are producing less honey while incurring significant costs to restore their colony numbers. As well, although Canada is a net exporter of honey, Ontario experiences a honey trade deficit of nearly $15 million due to the lack of safe bee pasture and the inability of pesticide weakened colonies to meet current demand.

This is a very misleading statement.  While it’s true that the honey production per hive is down from 121 lbs/hive in 2003 to 73 lbs/hive in 2014, the OBA fails to mention how many colonies were used primarily for pollination services in 2014 compared to 2003.  Colonies used primarily for pollination services are still included in the honey production statistics, which will lower the production per colony.  Ontario has never been a large honey production province though, and a great deal of their income has depended on the pollination services they offer.  In fact, Ontario sent more hives into pollination in 2014 than ever before.  Also, Ontario had one of their harshest winters in history and that poor weather continued into the spring/summer.  Weather has a huge impact on honey production, and it can also be directly attributed to their 2014 production.

The OBA’s claim that a lack of bee safe pasture is a main cause of their losses is misleading as well .  What they fail to mention is that there are ways to find more suitable forage for bees, which is something that prairie beekeepers have done for decades.  But it requires a change in management practices by the beekeeper, which seems to be something the anti-pesticide group in Ontario refuses to consider.  There is a great deal of forage in western Ontario (clover, alfalfa, etc.), so all I’m hearing from the OBA is excuses instead of solutions.

Another misleading statement. The Health Canada report cited was an interim report. In fact, Ontario’s Ministry of Agriculture, Farming and Rural Affairs (OMAFRA) reported (see link to PA report below) that pesticide poisoning incidents were actually higher in 2014 (345) compared to 2013 (320) and 2012 (240). It’s also important to note that with 58% of colonies dying over the winter there were fewer colonies exposed to pesticides and, as well, due to the late planting

This statement, while backed by Ontario’s provincial apiculturist (PA), is vague.  It is common knowledge that the less progressive/modern beekeepers in Ontario now blame pesticides for all their bee losses.  Without evidence to back up the statement that (visual observations do not count), I put more stock in the PMRA report than the PA’s report.  Also, the claim that there were fewer colonies exposed to pesticides due to later seeding is not accurate. 
Unless the beekeepers waited until June to replace their losses, a great deal of their 2014 colonies were exposed to crop planting.  

Another misleading statement. Beekeepers have been able to manage mites, disease and pests for decades. Unfortunately, however, we are unable to avoid pesticide exposure. In Ontario, neonics are used to treat over 5 million acres of soy and corn, when even our own provincial crop specialists say that they are only needed on 10% – 20% of these acres. In addition to killing bees outright, neonicotinoids compromise bees’ immune systems, making them more vulnerable to viruses and making it more difficult to fight off varroa. It reduces their navigation skills, affecting the bees’ capacity to forage and communicate forage opportunities; and it compromise nutrition by reducing the availability of a diversity of uncontaminated plants.

This is by far the most comical of all the statements in the OBA’s response.  No beekeeper in Canada can claim to have mites/disease/pests under control to the degree the OBA leads you to believe.  Yes we all work diligently to control these problems, but we are limited in the number of tools we have to protect our bees against them.  You also have a great deal of beekeepers (hobby/small scale primarily) that have no clue how as to what proper “Integrated Pest Management” (IPM) practices are.  There are even “prominent” commercial beekeepers in Ontario that are lacking in proper IPM practices.  This statement is proven by this video the OBA released on YouTube last year.  You can clearly see a commercial beekeeper incorrectly treating his hives for the varroa mite.  He is using both formic acid and oxalic acid on his bees at the same time, in the late fall, and on hives that are quite small in size.  For any informed beekeeper, we fully understand that this is a great way to kill your hives.  The fact that the OBA board actively uses this video as an example of “proper” IPM, I really have to question their knowledge base.
The OBA also fails to mention how many incidents are reported to PMRA in Ontario each year by beekeepers due to bee kills from using formic acid.  But for those of you that are inquisitive, these formic acid bee kills can be found on the PMRA website.

As for the comment of “neonicotinoids” kill bees outright, that is not true.  As I stated above, honeybees on the prairies are exposed to a much higher volume of neonics than those in Ontario with no adverse effects being seen. From our experience, healthy honeybees are highly resilient to this kind of chemical exposure.  There have been instances where bees have been sprayed directly with products such as Matador® during canola bloom, and the effects have been devastating.  But with chemical treatments like neonics, there seem to be little to no adverse effects on healthy bees.  If the bees are already suffering from malnutrition, mites, diseases, pests, etc., neonics can become lethal.  Bees do not do well with multiple stresses, the[y] never have.

We disagree. Ontario has taken a bold step to protect honey bees by setting targets to reduce the use of neonicotinoid pesticides by 80% by 2017. This step, alone, will help honey bees. In the past three years we have seen excessive colony losses and an increase in the number of Ontario beekeepers reporting incidents of pesticide poisoning, leading to Health Canada to conclude in their 2013 report: “the current use of neonicotinoid pesticides on corn and soy is not sustainable”.  

The main issue with the “Pollinator Health” document released by OMAFRA in 2014 is the fact that there is ZERO mention of what beekeepers need to do in order to better their management practices so that these losses do not keep occurring.  The document lays all the responsibility for Ontario’s bee/pollinator health on the farmer and seed manufacturers.  As I explained earlier, there are many things the beekeepers can do in order to correct this problem as well.  And from our experiences in western Canada, reducing overwintering losses to 15% is an almost unrealistic goal.  The biggest reason for that is the weather, we can’t control it and it is the difference between a  10% loss and a  40% loss.  When you start talking about losses of 50% or higher, there is a beekeeper management problem at play.

As I read more of the comments between farmers and the eco-activists (OBA falls under that category) in Ontario, the more I realize the chance of a common solution being found that benefits both sides is virtually impossible.  That is disappointing due to the fact there was great potential for everyone to work together in order to fix this problem.  The farmers/seed manufacturers have been doing a very good job in finding ways to reduce neonic exposure to Ontario’s bees, but sadly the same can’t be said about the OBA board of directors.  That unwillingness to work together on a COMMON solution is working against the good beekeepers in that province, and their association fails to realize that.

What’s also been lost is the efforts of the Canadian Honey Council (CHC) during this debacle.  CHC formed a “Bee Incident Committee” in 2012 to deal with the problems in Ontario, but the OBA refused to work with them unless CHC demanded a neonic ban as well.  Then in early 2014, CHC helped spearhead the “National Bee Health Action Plan”.  Again the OBA thumbed its nose at the efforts of the CHC, and only recently begged to be included in the roundtable.  And in December of 2014 CHC and the Canadian Seed Trade Association announced plans to  greatly reduce the application rate of seed applied insecticides over the next two years.  Of course, the OBA scoffed at this
announcement.  Are you noticing a common theme here?

There isn’t anyone in Canadian agriculture that disagrees with reducing the amount of pesticides used during crop production.  Whether it be neonics or the miticides used by beekeepers, chemical dependence is not desirable.  The truth of the matter though is that these products will always be a part of modern agriculture, and all we can do as good stewards is find ways to reduce our usage of them.  But at the same time, we have to look in the mirror and admit our faults.  Many beekeepers have done that and learned from it, just as many farmers have done the same.  But until the OBA board and it’s followers do it, nothing will change.  Their bees will still die and they will blame everything but themselves.