Increasing diversity of COVID-19 strains: insights into evolutionary divergence and public health

 To be clear, I am not a virologist, nor am I a public health expert. But I do know how to analyze patterns of evolutionary diversity. Research into the SARS-CoV-2 virus that has given rise to the COVID-19 pandemic has greatly enhanced our understanding of global disease dynamics, mRNA vaccines and public health responses to a global crisis. But the COVID-19 pandemic also has the potential to provide fundamental insights into basic ecological and evolutionary processes. 

While a lot has been written about how COVID-19 lock-downs have had noticeable repercussions on air quality and wildlife in cities, the virus lends itself as a microcosm into natural world dynamics. SARS-CoV-2 is now the most studied non-human organism on Earth, and we've witnessed its spread across the globe (which provides insights into invasion biology), it has spread exponentially in populations at times (showcasing the power of models to predict spread), and its rapid diversification is evolution in real time.

Understanding how SARS-CoV-2 strain diversity is generated is of fundamental importance for public health policies. And SARS-CoV-2 is evolving and diversifying. In Ontario, Canada, we have a wonderful resource from Public Health Ontario that publishes data on the evolution of strain diversity and provides a wonderful graphical interface. This interface focuses on the SARS-CoV-2 phylogeny (that is the evolutionary family tree connecting strains to their ancestors) in Ontario.

An example phylogeny

Using their open data, I addressed a simple question, is the evolutionary diversity (measured by the distances separating strains) increasing over time?

To test this, I calculated a statistical measure called the standardized effect size of the mean pairwise distances (SES.MPD) which quantifies the average distances separating strains standardized by random permutations (in this case 500 randomizations) so that a SES.MPD value of 0 means that the evolutionary diversity of a group of strains is no different than a same number of strains randomly selected from the phylogeny. Negative values mean that strains are more closely related on the phylogeny than you expect by chance (referred to as under-dispersed), and positive values mean strains are more distantly related (over-dispersed). I did these calculations for each month since the pandemic hit Ontario (March 2020) and for the seven different regions of Ontario.

Analysis of the standardized effect size of the mean pairwise distances (SES.MPD) of SARS-CoV-2 strains across the seven regions in Ontario since the start of the pandemic. The dashed horizontal line indicates a value of 0 (no different than random expectation) and points outside of the grey box are statistically significantly different than random.

What I found was that early on in the pandemic, the strains were under-dispersed, meaning that they were more closely related and genetically similar than expected by chance. But over time the dissimilarity between strains increases and by May 2021 (the last data in the graphs), many of Ontario's regions had significantly over-dispersed strains. This means that strains found in the populations in May 2021 were generally more dissimilar from one another than early on.

Why this matters is that vaccines and other treatments are typically developed on a single strain or from samples collected at a specific time point. If strains are relatively genetically similar, then it is highly probable that treatments will be successful across the strains. However, as strains diversify and become more dissimilar, then treatments might become less effective overall. 

Had the spreading infection been dominated by single strains, with very few newer strains replacing older ones, we would expect that the SES.MPD values remain below zero, and would make it easier to track strains and adapt treatments.

These patterns are also valuable for insights into ecology and evolution. We often look at SES.MPD values to interpret how different processes structure diversity (like competition, predation, pollution, etc.), but we often don't have good evidence of how historical evolutionary processes can drive SES.MPD differences. The plots above show that rapid evolutionary diversification results in linearly increasing SES.MPD values.

Experimental macroevolution at microscales

Sometimes I find myself defending the value of microcosms and model organisms for ecological research. Research systems do not always have to involve a perfect mimicry of nature to provide useful information. A new paper in Evolution is a great example of how microcosms provide information that may not be accessible in any other system, making them a valuable tool in ecological research.

For example, macroevolutionary hypotheses are generally only testable using observational data. They suffer from the obvious problem that they generally relate to processes of speciation and extinction that occurred millions of years ago. The exception is the case of short generation, fast evolving microcosms, in which experimental macroevolution is actually possible. Which makes them really cool :-) In a new paper, Jiaqui Tan, Xian Yang and Lin Jiang showing that “Species ecological similarity modulates the importance of colonization history for adaptive radiation”. The question of how ecological factors such as competition and predation impact evolutionary processes such as the rapid diversification of a lineage (adaptive radiation) is an important one, but generally difficult to address (Nuismer & Harmon, 2015; Gillespie, 2004). Species that arrive to a new site will experience particular abiotic and biotic conditions that in turn may alter the likelihood that adaptive radiation will occur. Potentially, arriving early—before competitors are present—could maximize opportunities for usage of niche space and so allow adaptive radiation. Arriving later, once competitors are established, might suppress adaptive radiation.

More realistically, arrival order will interact with resident composition, and so the effects of arriving earlier or later are modified by the identities of the other species present in a site. After all, competitors may use similar resources, and compete less, or have greater resource usage and so compete more. Although hypotheses regarding adaptive radiation are often phrased in terms of a vague ‘niche space’, they might better be phrased in terms of niche differences and fitness differences. Under such a framework, simply having species present or not present at a site does not provide information about the amount of niche overlap. Using coexistence theory, Tan et al. produced a set of hypotheses predicting when adaptive radiation should be expected, given the biotic composition of the site (Figure below). In particular, they predicted that colonization history (order of arrival) would be less important in cases where species present interacted very little. Equally, when species had large fitness differences, they predicted that one species would suppress the other, and the order in which they arrived would be immaterial. ­

From Tan et al. 2017

The authors tested this using a bacterial microcosm with 6 bacterial competitors and a focal species – Pseudomonas fluorescens SBW25. SBW25 is known for its rapid evolution, which can produce genetically distinct phenotypes. Microcosm patches contained 2 species, SBW25 and one competitor species, and their order of arrival was varied. After 12 days, the phenotypic richness of SBW25 was measured in all replicates.

From Tan et al. 2017. Competitor order of arrival in general altered the final phenotypic richness of SBW25.

Both order of arrival and the identity of the competitor did indeed matter as predictors of final phenotypic richness (i.e. adaptive radiation) of SBW25. Further, these two variables interacted to significantly. Arrival order was most important when the 2 species were strong competitors (similar niche and fitness differences), in which case late arrival of SBW25 suppressed its radiation. On the other hand, when species interact weakly, arrival order had little affect on radiation. The effect of different interactions were not entirely simple, but particularly interesting to me was that fitness differences, rather than niche differences, often had important effects (see Figure below). The move away from considering the adaptive radiation hypothesis in terms of niche space, and restating it more precisely, here allowed important insights into the underlying mechanisms. Especially as researchers are developing more complex models of macroevolution, which incorporate factors such as evolution, having this kind of data available to inform them is really important.

Interaction between final phenotype richness and arrival order for B) niche differences and D) fitness differences. S-C refers to arrival of SWB25 first, C-S refers to its later arrival. 

The future of community phylogenetics

Community phylogenetics has received plenty of criticism over the last ten years (e.g. Mayfield and Levine, 2010; Gerhold et al. 2015). Much of the criticism is tied to concerns about pattern-based inference, the use of proxy variables, and untested assumptions. These issues are hardly unique to community phylogenetics, and I think that few ideas are solely ''good or solely 'bad'. They are useful in moulding our thinking as ecologists and inspiring new directions of thought. Many influential ideas in ecology have bobbled in confidence through time, but remain valuable nonetheless [e.g. interspecific competition, character displacement (Schoener 1982; Strong 1979)]. But still, it can be hard to see exactly how to use phylogenetic distances to inform community-level analyses in a rigorous way. Fortunately, there is research showing exactly this. The key, to me at least, to avoid treating a phylogeny as just another matrix to analyze, but to consider and test the mechanisms that might link the outcome of millions of years of evolution to community-level interactions.

A couple of potential approaches to move forward questions about community phylogenetics are discussed below. The first is to consider the mechanisms behind the pattern-inference analyses and ask whether assumptions hold.

1) Phylogenies and traits - testing assumptions about proxy value
As you know, if you have read the introductory paragraph of many community phylogenetic papers, Charles Darwin was the first to highlight that two closely related species might have different interactions than two distantly related species. People have tested this hypothesis in many ways in various systems, with mixed results. The most important directions forward is to make explicit the assumptions behind such ideas and experimentally test them. I.e. Do phylogenetic distances/divergence between species capture trait and ultimately ecological divergence between species?

From Kelly et al. 2015 Fig 1b.

Because evolutionary divergence should relate to feature divergence (sensu Faith), the most direct question to ask is how functionally important trait differences increase with increasing phylogenetic distances. For example, Kelly et al. (2014) found that “close relatives share more features than distant relatives but beyond a certain threshold increasingly more distant relatives are not more divergent in phenotype”, although in a limited test based only on patristic distances. This suggests that at short distances, phylogenetic distances may be a reasonable proxy for feature divergence, but that the relationship is not useful for making predictions about distant relatives.

Phylogenies and coexistence/competition. Ecological questions about communities may not be interested in traits alone. The key assumption behind many early analyses was that closely related species shared more similar *niches*, and so competed more strongly than distantly related species. Thus the question is one step removed from trait evolution, asking instead how phylogenetic divergence correlates into fitness differences or interaction strength. Not surprisingly, current papers suggest there is a fairly mixed, less predictable relationship between phylogenetic relatedness and competitive outcomes.

Recent findings have varied from “Stabilising niche differences were unrelated to phylogenetic distance, while species’ average fitness showed phylogenetic structure” (California grassland plants, Godoy et al. 2014); to, there is no signal in fitness or niche differences (algae species, Narwani et al. 2013); to, when species are sympatric, both stabilizing and fitness differences increase with phylogenetic distance (mediterranean annual plants; Germain et al. 2016). Given constraints, tradeoffs and convergence of strategies, it is really not surprising that the idea of simply inferring the importance of competition from patterns along a phylogenetic tree is not generally possible (Kraft et al. 2015; blogpost).

2) Phylogenies and the regional species pool
Really more interesting than testing for proxy value is to think about the mechanisms that tie evolution and community dynamics together. A key role for evolution in questions about community ecology is to ask what we can learn about the regional species pool—from which local communities are assembled. What information about the history of the lineages in a regional species pool informs the composition of local composition?

The character of the regional species pool is determined in part by the evolutionary history of the region, and this can in turn greatly constrain the evolutionary history of the community (Bartish et al. 2010). The abundance of past habitat types may alter the species pool, while certain communities may act as 'museums' harbouring particular clades. For example, Bartish et al. 2016 found that the lineages represented in different habitat types in a region differ in the evolutionary history they represent, with communities in dry habitats disproportionately including lineages from dry epochs and similar for wet habitats. Here, considering the phylogeny provides insight into the evolutionary component of an ecological idea like 'environmental filtering'.

Similarly, species pools are formed by both ecological processes (dispersal and constraints on dispersal) and evolutionary ones (extinctions, speciation in situ), and one suggestion is that appropriate null models for communities may need to consider both ecological and evolutionary processes (Pigot and Etienne, 2015).
Invasive species also should be considered in the context of evolution and ecology. Gallien et al. 2016 found that “currently invasive species belong to lineages that were particularly successful at colonizing new regions in the past.”

I think using phylogenies in this way is philosophically in line with ideas like Robert Ricklef's 'regional community' concept. The recognition is that a single time scale may be limiting in terms of understanding ecological communities.

References:

1. Mayfield, Margaret M., and Jonathan M. Levine. "Opposing effects of competitive exclusion on the phylogenetic structure of communities." Ecology letters 13.9 (2010): 1085-1093.
2. Gerhold, Pille, et al. "Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better)." Functional Ecology 29.5 (2015): 600-614.
3. Schoener, Thomas W. "The controversy over interspecific competition: despite spirited criticism, competition continues to occupy a major domain in ecological thought." American Scientist 70.6 (1982): 586-595. 
4. Strong Jr, Donald R., Lee Ann Szyska, and Daniel S. Simberloff. "Test of community-wide character displacement against null hypotheses." Evolution(1979): 897-913. 
5. Kelly, Steven, Richard Grenyer, and Robert W. Scotland. "Phylogenetic trees do not reliably predict feature diversity." Diversity and distributions 20.5 (2014): 600-612.
6. Godoy, Oscar, Nathan JB Kraft, and Jonathan M. Levine. "Phylogenetic relatedness and the determinants of competitive outcomes." Ecology Letters17.7 (2014): 836-844.
7. Narwani, Anita, et al. "Experimental evidence that evolutionary relatedness does not affect the ecological mechanisms of coexistence in freshwater green algae." Ecology Letters 16.11 (2013): 1373-1381.
8. Rachel M. Germain, Jason T. Weir, Benjamin Gilbert. Species coexistence: macroevolutionary relationships and the contingency of historical interactions. Proc. R. Soc. B 2016 283 20160047
9. Nathan J. B. Kraft, Oscar Godoy, and Jonathan M. Levine. Plant functional traits and the multidimensional nature of species coexistence. 2015. PNAS.
10. Bartish, Igor V., et al. "Species pools along contemporary environmental gradients represent different levels of diversification." Journal of Biogeography 37.12 (2010): 2317-2331.
11. IV Bartish, WA Ozinga, MI Bartish, GW Wamelink, SM Hennekens. 2016. Different habitats within a region contain evolutionary heritage from different epochs depending on the abiotic environment. Global Ecology and Biogeography
12. Pigot, Alex L., and Rampal S. Etienne. "A new dynamic null model for phylogenetic community structure." Ecology letters 18.2 (2015): 153-163.
13. Gallien, L., Saladin, B., Boucher, F. C., Richardson, D. M. and Zimmermann, N. E. (2016), Does the legacy of historical biogeography shape current invasiveness in pines?. New Phytol, 209: 1096–1105.

Pulling a fast one: getting unscientific nonsense into scientific journals. (or, how PLOS ONE f*#ked up)

The basis of all of science is that we can explain the natural world through observation and experiments. Unanswered questions and unsolved riddles are what drive scientists, and with every observation and hypothesis test, we are that much closer to understanding the universe. However, looking to supernatural causes for Earthly patterns is not science and has no place in scientific inquiry. If we relegate knowledge to divine intervention, then we fundamentally lose the ability to explain phenomena and provide solutions to real world problems.

Publishing in science is about leaping over numerous hurdles. You must satisfy the demands of reviewers and Editors, who usually require that methodologies and inferences satisfy strict and ever evolving criteria -science should be advancing. But sometimes people are able to 'game the system' and get junk science into scientific journals. Usually, this happens by improper use of the peer review systems or inventing data, but papers do not normally get into journals while concluding that simple patterns conform to divine intervention.

Such is the case in a recent paper published in the journal PLOS ONE. This is a fairly pedestrian paper about human hand anatomy and they conclude that anatomical structures provide evidence of a Creator. They conclude that since other primates show a slight difference in tendon connections, a Creator must be responsible for the human hand (well at least the slight, minor modification from earlier shared ancestors). Obviously this lazy science and an embarrassment to anyone that works as an honest scientist. But more importantly, it calls into question the Editor who handled this paper (Renzhi Han, Ohio State University Medical Center), but also PLOS ONE's publishing model. PLOS ONE handles thousands of papers and requires authors to pay for the costs of publishing. This may just be an aberration, a freak one-off, but the implications of this seismic f$@k up, should cause the Editors of PLOS to re-evaluate their publishing model.  

Ecology in evolutionary times

Ecological and evolutionary perspectives on community assembly. 2015. Gary G. Mittelbach, Douglas W. Schemske. Trends in Ecology and Evolution.

Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better). 2015. Pille Gerhold, James F. Cahill Jr, Marten Winter, Igor V. Bartish and Andreas Prinzing. Functional Ecology

Community assembly has always provided some of the most challenging puzzles for ecologists. Communities are complex, vaguely delimited, involve multi-species interactions, and assemble with seemingly immense variation. Thousands of papers have been dedicated to understanding community assembly, and many have proposed different approaches understanding communities. These range from the ever popular abiotic/biotic filtering concept, functional traits, coexistence theory, island biogeography, metacommunity theory, neutral theory, and phylogenetic patterns. It is probably fair to say that no one existing approach is adequate to completely describe or predict community assembly.

One response to this problem is the growing demand to expand the lens of “community” to cover greater spatial and temporal scales. This owes a lot, directly and indirectly, to Robert Ricklefs’ influential Sewall Wright Award lecture on the Disintegration of the Ecological Community. There is also a strong trend towards re-integrating evolutionary history into studies of community ecology. Coincidentally, or perhaps not, this is occurring as so-called ‘eco-phylogenetic’ approaches have been increasingly criticised. If nothing else, eco-phylogenetics provided a path for, and popularized, the idea of reintegrating evolution into community ecology.

I’ll highlight two particular papers that address this re-integration in surprisingly convergent ways. Both have macroevolution slants (that is, they focus on the impacts and drivers of speciation and extinction, sympatry, allopatry, etc), and an interest in the feedbacks between community interactions and these processes. The first, from Pille Gerhold, James F. Cahill Jr, Marten Winter, Igor V. Bartish and Andreas Prinzing, positions itself as the phoenix from the ashes of eco-phylogenetics (as seen in their particularly enthusiastic title :) ). Evolutionary history, captured by phylogenies, was originally of interest to ecologists not for what it was, but because it could (sometimes, maybe) act as a proxy for species traits and niches. This paper does an excellent job of laying out the various hypotheses that went behind this type of approach and showing why they are not reliably true. If for no other reason, it is worth reading the paper for its clear critique of the foundation of eco-phylogenetics. Using patterns in phylogenies as proxies for the outcomes of particular ecological processes being clearly suspect, the authors argue that explicitly thinking of phylogenetic patterns as the result of both ecological and evolutionary processes is far more informative. [I’ll return to this in a bit with their examples below].

The second paper is written by two big names in their respective fields: Gary Mittlebach (ecology) and Doug Schemske (evolution). The title is a bit vague (“Ecological and evolutionary perspectives on community assembly”), but it turns out that they too have converged on the importance of considering evolutionary history in order to understand community assembly. In particular they focus on the problematic nature of the species pool: species pools are nearly always treated as a static object changing little through time or space and are notoriously difficult to define. However, the species pool underlies null model approaches used to test communities for differences from a random expectation. So defining it correctly is important.

From the early days, Elton and others defined the species pool as the group of species that can disperse to and colonize a community. However, the species pool may be dynamic, and they note “To date, relatively little attention has been focused on the feedback that occurs between local community species composition, biotic interactions, and the diversification processes that generate regional species pools.”

This paper does an excellent job of explaining how macroevolutionary processes can alter a regional species pool. The most obvious example is the process of adaptive radiation in island-like systems, where competition for resources drives ecological divergence and speciation. Darwin’s finches, Anolis lizards, and cichlid fishes provide well-known examples of this rapid expansion of the species pool through inter-specific interactions. On mainland systems, speciation may be more likely to occur in allopatry, and the rate limiting step for range expansion (leading to secondary sympatry and only then increasing a species pool) is often interspecific interactions. One study found that secondary sympatry took 7my on average, though speciation alone took only 3my. So the species pool is the outcome of constant feedbacks between species interactions and evolutionary processes.

From Mittlebach & Schemske. Figure illustrating the feedbacks between evolution and ecological interactions, in producing the species pool.

Both papers provide useful examples of how such incorporating evolution into community ecology may prove useful. As a simple example, Mittlebach and Schemske point out that evolution can greatly alter the utility of Island Biogeography Theory: given enough time, speciation events including adaptive radiations, greatly increase the (non-mainland) species pool and would strongly alter predictions of diversity, especially for distant islands.

The Gerhold et al. paper provides the below illustrations as additional possibilities for how evolution and community interactions may feedback.

From Gerhold et al. Two examples of how evolution and communities might interact.

It is certainly interesting to see this shift towards how we envision and study communities. The historical focus on local space and time no doubt reflects ecologists' attempt to limit the problem to a manageable frame. But there is some logic behind expanding our definition of communities to larger spatial scales and greater time periods, especially since there are usually no true boundaries defining communities in space and time. Answering which specific time scales and spatial scales most useful to understanding communities is difficult: if we increase the time or space we consider, how and when does the additional information provided decline? The next step is to consider evolution in this fashion for real organisms, and evaluate the true utility of this approach.  

The fruits of our labour: the evolution of crops

#Guest post by Francesco Janzen.

Have you ever wondered how much work and time has been put into producing the food you eat today: that juicy apple, or that fresh loaf of bread? In modern times, we can easily recognize fruits and vegetables such as tomatoes, corn, and bananas, but would it surprise you that these foods have not always looked the way they do? Like all parts of the living world, food crops have changed much over time, and this change is directly linked to human efforts (Purseglove, 1965; Allaby et al., 2015). 

Agriculture began approximately 11,000-12,000 years ago, and has originated in several parts of the world (National Geographic, 2015). Humans domesticated wheat in the Fertile Crescent, or Near East approximately 8,000-9,000 years ago. (Nevo, 2014; National Geographic, 2015). In China, rice is proposed to have been domesticated 10,000-20,000 years ago (Gross & Zhao, 2014; National Geographic, 2015). Across the ocean, squash was domesticated about 10,000 years ago in what is known today as Mexico, and the beginning of sunflower cultivation began in North America around 5,000 years ago (Janick, 2013; National Geographic, 2015). All of these domestications began with wild progenitors of today’s crop species (Gross et al., 2014; Allaby et al., 2015).  

But how did the wild crops of ancient times develop into the modern ones we know today? John William Purseglove, a former tropical agricultural officer and director of the Singapore Botanic Gardens, discussed the ways in which humans have changed crop species over time in a chapter of “The Genetics of Colonizing Species” (1965). In his chapter, “The Spread of Tropical Crops”, Purseglove (1965) states that humans would have begun the first agricultural crops with a subset of desired plants from the original wild population. This subset would not possess the genetic diversity of the original population, essentially producing a genetic bottleneck effect (Purseglove, 1965). Furthermore, certain desired traits would be selected for in this new population, so breeding strategies would overtime change the traits expressed, such as larger fruit, seedless fruit, lack of defense mechanisms, etc. (Purseglove, 1965). Although they benefit humans, these changes could potentially decrease the competitive ability of these new plants. This intrinsically ties their survival to human assistance (Purseglove, 1965). 

Humans have not only changed the physical characteristics of crop plants; they have altered their geographic distributions as well. Compared to their wild ancestors, most crop plants are now grown in areas far removed from their origin, such as with vanilla (Vanilla planifolia). Vanilla originated in Mexico, but is now grown in large numbers in Madagascar (Purseglove, 1965). In fact, vanilla and most other crops are much more successful in their new environments, but why is this so? Purseglove (1965) proposed that by moving a crop plant into a new habitat where predators or disease are absent, little would control population sizes, and increase crop yields. 

Visible difference between a wild strawberry (Fragaria virginiana, left) and a domestic strawberry (Fragaria x ananassa, right), from http://www.jamesandthegiantcorn.com/tag/domestication/. 

The new environments that domestic crops are exposed to may further increase the genetic gap with their wild ancestors. Under new, adverse environmental conditions, a population of a crop may be culled, save for a few individuals possessing recessive genes that confer a benefit to coping with the altered conditions (Purseglove, 1965). The remaining individuals reproduce, which shifts the next generation’s genotypic frequency (Purseglove, 1965). In addition, this can effectively expand the range of the domestic crop, whereas the wild type remains restricted to its original range (Purseglove, 1965). 

Science has come a long way since Purseglove proposed his ideas 50 years ago, and the advent of DNA has helped improve our understanding of evolution. With respect to the evolution of crops, DNA allows for testing of certain theories proposed, one such being the bottleneck effect. A study conducted by Gross et al. (2014) investigated whether perennial crop species, specifically the apple (Malus x domestica) showed a decrease in genetic diversity when compared to closely related wild species. They expected that there would have been a narrowing of genetic diversity at two moments in history. Firstly, during a domestication bottleneck, similar to that proposed by Purseglove (1965), and secondly during an improvement bottleneck, where desirable traits in the crop species were selected for to produce elite cultivars (Gross et al., 2014). 

A visual depiction of the bottleneck effect, where the bottleneck represents stochastic (random) events, from http://bio1151.nicerweb.com/Locked/media/ch23/bottleneck.html. 

By sequencing specific DNA regions of 11 varieties of apple cultivar (both ancient and modern), and that of three wild species, Gross et a. (2014) sought to demonstrate that domesticated cultivars show less genetic diversity than wild species. The regions selected were areas where each species show a variable amount of repeated sequence length, known as microsatellites, allowing for easy comparison of genetic quality (Gross et al., 2014). What they found, contrary to what was expected, was that domestic apples have not undergone a significant reduction of genetic diversity, either at the domestication or improvement phases (Gross et al., 2014). This evidence shows that not all theories produced 50 or more years ago withstand the test of time, especially when new tools to test these theories become available.   

So how does any of this information impact management practice of controlling invasive species? Purseglove (1965) stated in his chapter that by understanding the evolution of crop species, we gain insight into the success of introduced weed species. Although weeds do not require any human assistance in survival, the forces acting on them may be the similar to those acting on agricultural crops. Just as crops experience a release from predators and disease when removed from their native habitats, weeds may also undergo this release, contributing to their widespread success (Purseglove, 1965). This parallel could be quite useful in the understanding and management of weedy species.  

References: 

Allaby, R.G., Gutaker R., Clarke, A.C., Pearson, N., Ware, R., Palmer, S.A., Kitchen, 

J.L., and Smith, O. 2015. Using archaeogenomic and computational approaches to unravel the history of local adaptation in crops. Philosophical Transactions Royal Society  370: 20130377.

Gross, B.L., Henk, A.D., Richards, C.M., Fazio, G., and Volk, G.M. 2014. Genetic 

diversity in Malus × Domestica (Rosaceae) through time in response to domestication. American Journal of Botany 101(10): 1770-1779.   

Gross, B.L. & Zhao, Z. 2014. Archaeological and genetic insights into the origins of 

domesticated rice. Proceedings of the National Academy of Sciences 111(17): 6190-6197. 

Janick, J. 2013. Development of New World crops by indigenous Americans. 

Horticultural Science 48(4): 406-412.   

National Geographic Society. 2015. The development of agriculture. Retrieved from 

https://genographic.nationalgeographic.com/development-of-agriculture/. 

Nevo, E. 2014. Evolution of wild emmer wheat and crop improvement. Journal of 

Systematics and Evolution 52(6): 673-696. 

Purseglove, J.W. (1965). The spread of tropical crops. In H.G. Baker, and G.L Stebbins 

(Eds.). The Genetics of Colonizing Species. New York: Academic Press.

Going natural: biological control of insect pests

*Guest post by Sheena Fry

Damage caused by agriculture pests is one of the most important factors of crop yield reduction (Cramer, 1967; Oerke et al., 1994) and can cause billions of dollars worth of damage each year (e.g. in Brazil, insect pests cause up to US$ 17.7 billon year^-1 of damage, Oliveira et al., 2014). Due to its economic impact, controlling pest populations is a priority for agricultural scientists. Chemical control is the primary method of pest management due to its relatively low costs and high effectiveness (Cooper and Dobson, 2007). Despite the widespread use of chemical controls, the health and environmental risks associated with their use are well known (Pimentel et al. 1992; Pimentel, 2005). The risks associated with pesticide use, as well as the evolution of pesticide resistance, has lead to a surge in interest in the use of biological control for pest management over the past 50 years.

The most important decision to be made in a biological control program is which biological control agent to use against a pest. Success rates for biological control of insects are low, with only 24-35% resulting in the establishment of the introduced species (Hall and Ehler 1979, van Lentern, 1983) and only 16% resulting in complete control of pest species (Hall et al., 1980). What determines the success of colonization and establishment is a key question in biological control research and must be answered in order to make predictions about establishment and success of introduced species. In 1965, Debach attempted to identify characteristics of successful colonizers but found that neither success nor failure could be explained by the presence or absence of a common characteristic. Over the past 50 years, several attempts have been made to list characteristics of successful invaders (e.g. Murdoch et al., 1985) and while they seem logical, there are too many exceptions for them to be used as a reliable indicator of a species’ potential to colonize and establish in a new area. DeBach saw “no possibility of predicting the fate of a purposely colonized imported entomophagous insect” and at present it remains an elusive goal (Fischbein and Corley, 2015).

Paul Debach 1914-1992

The environmental and health risks associated with chemical controls of insects (see references above) are not an issue when using biological controls. In addition to this, successfully established biological control species will be able to maintain stable populations without the need for additional investment by humans (unlike chemical controls, which must be applied each season). Despite the obvious benefits of biological control, there are also risks associated with the use of insects in biological control, such as the risk to non-targeted species (Simberloff and Stiling, 1996) or host switching. In order to make decisions about biological control we need to understand the evolution of introduced species in new environments, which can increase the efficiency of biological control (through post-colonization adaptation) or can increase the risk to non-targeted species. “The Genetics of Colonizing Species” (1965) brought together evolutionary biologists and ecologists (theoretical and applied) to discuss the evolution of introduced species. In DeBach’s chapter, he focused on colonizing entomophagous insects and, using biological control case studies, looked at the relative influence of pre- and post colonization adaptation, a key question in evolutionary biology. One such case study was the introduction of a parasitoid wasp (Comperiella bifasciata Howard, Figure 1), which was introduced to control a citrus pest, the California red scale (Aonidiella aurantii Maskell). The parasitoid wasp was released throughout southern California but initially was only able to establish at one location. It slowly spread and increased in abundance and, by 1957 was found at various locations throughout southern California. DeBach interpreted the poor initial establishment of the parasite followed by intense colonization as an indication that genetic adaptation had occurred.

Figure 1. A female parasitic wasp (Comperiella bifasciata Howard) infesting a California red scale (Aonidiella aurantii Maskell), from Forester et al. (1995).

Fifty years have passed since the publication of “The Genetics of Colonizing Species” (1965) and understanding the relative effects of pre- and post-colonization adaptation has remained an important issue. Phillips and colleagues (2008) examined the relative effects of genetic drift and selection in the frequencies of two asexually reproducing, genetically distinct parasitoid biotypes. This South American parasitoid wasp (Micrictonus hyperidae Loan, Figure 2) was introduced as a biological control for a pasture pest (Listronotus bonariensis Kuschel, Figure 2) in New Zealand in 1992. Phillips and colleagues recorded the relative frequencies of each biotype over a 10-year period and found that changes in biotype frequency were consistent with strong directional selection, favouring one of the parasitoid biotypes. This resulted in parasitoid populations being better adapted to New Zealand conditions than those originally released. 

Figure 2. A female parasitic wasp (Micrictonus hyperidae Loan, right) infesting a South American weevil (Listronotus bonariensis Kuschel, left). © Copyright AgResearch

There have been significant advance in the tools (statistical and molecular) available for the study of post-colonization success and adaptation since the publication of “The Genetics of Colonizing Species” (1965). These tools allow for better understanding of the post-colonization process of introduced species but, despite these advances, there has been little progress towards being able to predict the success of introduced species.

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