87 years ago, in ecology

Louis Emberger was an important French plant ecologist in the first half of the last century, known for his work on the assemblages of plants in the mediterranean.

For example, the plot below is his published diagram showing minimum temperature of the coolest month versus a 'pluviometric quotient' capturing several aspects of temperature and precipitation from:

Emberger; La végétation de la région méditerranienne. Rev. Gén. Bot., 42 (1930)

Note this wasn't an unappreciated or ignored paper - it received a couple hundred citations, up until present day. Further, updated versions have appeared in more recent years (see bottom).

So it's fascinating to see the eraser marks and crossed out lines, this visualisation of scientific uncertainty. The final message from this probably depends on your perspective and personality:

• Does it show that plant-environment modelling has changed a lot or that plant environmental modelling is still asking about the same underlying processes in similar ways?
• Does this highlight the value of expert knowledge (still cited) or the limitations of expert knowledge (eraser marks)? 

It's certainly a reminder of how lucky we are to have modern graphical software :)

E.g. updated in Hobbs, Richard J., D. M. Richardson, and G. W. Davis. "Mediterranean-type ecosystems: opportunities and constraints for studying the function of biodiversity." Mediterranean-Type Ecosystems. Springer Berlin Heidelberg, 1995. 1-42.











Thanks to Eric Garnier, for finding and sharing the original Emberger diagram and the more recent versions.

150 years of 'ecology'

The word ‘ecology’ was coined 150 years ago by Ernst Haeckel in his book Generelle Morphologie der Organismen published in 1866. Mike Begon gave a fascinating talk at the British Ecological Society meeting in Liverpool on what ecology as meant over these past 150 years and what it should mean in the future. The description of ecology that follows, is largely taken from Begon’s remarks.

Ernst Haeckel, 1860

Haeckel defined ecology as ‘the science of the relations of organism to its surrounding outside world (environment)’, which is in obvious contrast to the then burgeoning science of physiology, which was concerned with the world inside of an organism. Interestingly, the first 50 years of this new field of ecology was dominated by the study of plants. In America, Clements, while in the UK, Tansley, both saw ecology as the description of patterns of plant in relation to the outside world. In many ways, this conception of ecology was what Haeckel had envisioned.

Frederic Clements

However, by the 1960s, the domain of ecology began to grow rapidly. Ecologists like Odum used ‘ecology’ to mean the structure and function of ecosystems, while others focussed on the abundance and distribution of species. By this time ecology had grown to encapsulate all aspects of organismal patterns and functions in nature.

The post-60s period saw another expansion -namely the value of ecology. While Begon points out that text books, including his, focussed on the science of ecology in its pure form, many were ignoring the fact that ecology had/has important repercussions for how humanity will need to deal with the massive environmental impacts we’ve had on Earth’s natural systems. That is, the science of ecology can provide the foundation by which applied management solutions can be built. I personally believe that applied ecology has only just begun its ascension to being the most important element of ecological science (but I’m biassed -being the Executive Editor of the Journal of Applied Ecology). Just like how human physiology has become problem oriented, often focussed on human disease, ecology will too become more problem oriented and focus on our sick patients.

Begon went on to say what ecology should be in the near future. He juxtaposed the fact and truth based necessity of science to the post-truth Brexit/Trump era we now find ourselves in. If ecologists and scientists are to engage the public, and alter self-destructive behaviours, it cannot be with logic and evidence alone. He argued that we need to message like those post-truthers. Use metaphors, simple messages that are repeated, repeated, and repeated.

The first null model war in ecology didn't prevent the second one*

The most exciting advances in science often involve scientific conflict and debate. These can be friendly and cordial exchanges, or they can be acrimonious and personal. Scientists often wed themselves to their ideas and can be quite reluctant to admit that their precious idea was wrong. Students in ecology often learn about some of these classic debates (Clements v. Gleason; Diamond v. Simberloff and Connor), but often other debates fade from our collective memory. Scientific debates are important things to study, they tell us about how scientists function, how they communicate, but more importantly by studying them we are less likely to repeat them! Take for example the debate over species per genus ratios, which happened twice, first in the 1920s, then again in the 1940s. The second debate happened in ignorance of the first, with the same solution being offered!

To understand the importance of testing species-genus ratios we can start with a prediction from Darwin:

As species of the same genus have usually, though by no means invariably, some similarity in habits and constitution, and always in structure, the struggle will generally be more severe between species of the same genus, when they come into competition with each other, than between species of distinct genera (Darwin 1859)

To test this hypotheses, the Swiss botanist, Paul Jaccard (1901) created a ‘generic coefficient’ to describe biogeographical patterns and to measure the effects of competition on diversity. The generic coefficient was a form of the species-genus ratio (S/G), calculated as G/S x 100, and he interpreted a low S/G ratio (or high coefficient) to mean that competition between close relatives was high, and a high ratio (low coefficient) meant that there was a high diversity of ‘ecological conditions’ supporting closely related species in slightly different habitats (Jaccard 1922). At the same time as Jaccard was working on his generic coefficient, the Finnish botanist, Alvar Palmgren, compiled S/G patterns across the Aland Islands and inferred the low S/G values on distant islands to reflect random chance (Palmgren 1921). Over several years, Jaccard and Palmgren had a heated exchange in the literature (across different journals and languages!) about interpreting S/G ratios (e.g., Jaccard 1922, Palmgren 1925). Palmgren’s contention was that the S/G ratios he observed were related to the number of species occurring on the islands –an argument which later work vindicates. A few years after their exchange, another Swiss scientist, Arthur Maillefer, showed that Jaccard’s interpretation was not supported by statistical inference (Maillefer 1928, 1929). Maillefer created what is likely one of the first null model in ecology (Jarvinen 1982). He calculated the expected relationship between Jaccard’s generic coefficient and species richness from ‘chance’ communities that were randomly assembled (Fig. 1 –curve II). Maillefer rightly concluded that since the number of genera increase at a slower rate than richness, the ratio between the two couldn’t be independent of richness.

Jaccard’s generic coefficients plotted by Maillefer showing the relationship between the coefficients (calculated as Genera/Species x 100) and species richness (Maillefer 1929). The four curves depict different scenarios. Curve I shows the maximum values possible, and curve IV is the minimum. Curve III is when coefficients are calculated on sampled values from a flora, which stays on a mean value. Curve II represents the first null model in ecology, where species are randomly sampled (‘hasard’ is translated as chance or luck) and the coefficient was calculated from the random assemblages.

 This example is especially poignant because it foreshadowed another debate 20 years later –and not just in terms of using a null expectation, but that S/G ratios cannot be understood without comparison to the appropriate null. Elton (1946) examined an impressive set of studies to show that small assemblages tended to have low S/G ratios, which he thought indicated competitive interactions. Mirroring the earlier debate, Williams (1947), showed that S/G ratios were not independent of richness and that inferences about competition can only be supported if observed S/G values differed from expected null values. However, the error of inferring competition from S/G ratios without comparing them to null expectations continued into the 1960s (Grant 1966, Moreau 1966), until Dan Simberloff (1970) showed, unambiguously, that, independent of any ecological mechanism, lower S/G are expected on islands with fewer species. Because he compared observationed values to null expectations, Simberloff was able to show that assemblages actually tended to have higher S/G ratios than one would expect by chance (Simberloff 1970). So not only is competition not supported, but the available evidence indicated that perhaps there were more closely related species on islands, which Simberloff took to mean that close relatives prefer the same environments (Simberloff 1970).

Darwin, C. 1859. The origin of the species by means of natural selection. Murray, London.

Elton, C. S. 1946. Competition and the Structure of Ecological Communities. Journal of Animal Ecology 15:54-68.

Grant, P. R. 1966. Ecological Compatibility of Bird Species on Islands. The American Naturalist 100:451-462.

Jaccard, P. 1901. Etude comparative de la distribution florale dans une portion des Alpes et du Jura. Bulletin de la Societe Vaudoise des Sciences Naturelle 37:547-579.

Jaccard, P. 1922. La chorologie selective et sa signification pour la sociologie vegetale. Memoires de la Societe Vaudoise des Sciences Naturelle 2:81-107.

Jarvinen, O. 1982. Species-To-Genus Ratios in Biogeography: A Historical Note. Journal of Biogeography 9:363-370.

Maillefer, A. 1928. Les courbes de Willis: Repar- tition des especes dans les genres de diff6rente etendue. Bulletin de la Societe Vaudoise des Sciences Naturelle 56:617-631.

Maillefer, A. 1929. Le Coefficient générique de P. Jaccard et sa signification. Memoires de la Societe Vaudoise des Sciences Naturelle 3:9-183.

Moreau, R. E. 1966. The bird faunas of Africa and its islands. Academic Press, New York, NY.

Palmgren, A. 1921. Die Entfernung als pflanzengeographischer faktor. Series Acta Societatis pro Fauna et Flora Fennica 49:1-113.

Palmgren, A. 1925. Die Artenzahl als pflanzengeographischer Charakter sowie der Zufall und die säkulare Landhebung als pflanzengeographischer Faktoren. Ein pflanzengeographische Entwurf, basiert auf Material aus dem åländischen Schärenarchipel. Acta Botanica Fennica 1:1-143.

Simberloff, D. S. 1970. Taxonomic Diversity of Island Biotas. Evolution 24:23-47.

Williams, C. B. 1947. The Generic Relations of Species in Small Ecological Communities. Journal of Animal Ecology 16:11-18.

*This text has been modified from a forthcoming book on ecophylogenetics authored by Cadotte and Davies and published by Princeton University 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.

References:

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Protection- Estimated Losses in Major Food and Cash Crop. Elsevier Science: Amsterdam.

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economic impact of insect pests on Brazilian agriculture. Crop Protection, 56, 50-54.

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practice. The American Naturalist, 125, 344-366.

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J. M. (2008). Journal of Applied Ecology, 45, 948-956.

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