Fungi attack plants – insects respond!

As she was preparing to do her dissertation research on the interactions between the Asian chestnut gall wasp, the chestnut blight disease and the European chestnut, Pilar Fernandez-Conradi read a lot of papers about fungal-insect-plant interactions.  She was impressed by the diversity of outcomes that resulted when plants were attacked by both insects and fungi, and wondered whether there were any generalities to glean from these research findings. She asked two basic questions. First, if a plant is infected by a fungus, is it more or less likely to be attacked by insects than is an uninfected plant?  Second, does an insect that attacks a fungal-infected plant perform better or worse than it would have on an uninfected plant?

D. Kuriphilus+Gnomo

Three-way interaction between the chestnut tree, the chestnut gall wasp, and the fungus Gnomopsis castanea. Female wasps induce the plant to create galls, which house developing larvae. Green globular galls (with a hint of rose-color) have not been infected by a fungus, while the very dark tissue is the the remains of a gall that was attacked by the fungus. Credit: Pilar Fernandez-Conradi.

Fernandez-Conradi and her colleagues thought they were more likely to discover a negative effect of fungal infection on the preference and performance of herbivorous insects.  Several studies had shown that nutrient quantity and quality of host plants is reduced by fungal infection, so it makes sense that insects would avoid infected plants.  But the researchers also knew that fungal infection can, in some cases, actually increase the sugar concentration of some plants, so insects might prefer those plants and also develop more rapidly on them. In addition, fungal infection can induce chemical defenses in plants that might make them less palatable to insects, or alternatively, fungal infection could weaken plant defenses making them more palatable to attacking insects.

To resolve this conundrum, Fernandez-Conradi and her colleagues did a meta-analysis, of the existing literature, identifying 1113 case studies based on 101 papers.  To be considered in the meta-analysis, all of the studies had to meet the following criteria: (1) report insect preference or performance on fungal-infected vs. uninfected plants, (2) report the Genus or species of the plant, fungus and insect, (3) report the mean response and a measure of variation (standard error, standard deviation or variance). The measure of variation allows researchers to calculate the effect size, which calculates the strength of the relationship that is being explored. The researchers found that, in general, insects avoid and perform worse on infected plants than they do on uninfected plants.

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Mean effect size of insect preference and performance (combined) in response to fungal infection infection.  Error bars are 95% confidence intervals (CIs).  In this graph, and the next two graphs as well, a solid data point indicates a statistically significant effect.  You can also visually test for statistical significance by noting that the error bar does not cross the dashed vertical line that represents no effect (at the 0.0 value). The negative value indicates that insects respond negatively to fungal infection.

Fernandez-Conradi and her colleagues then broke down the data to explore several questions in more detail. For example, they wondered if the type of fungus mattered.  For their meta-analysis, they considered three types of fungi with different lifestyles: (1) biotrophic pathogens that develop on and extract nutrients from living plant tissues, (2) necrotrophic pathogens that secrete enzymes that kill plant cells, so they can develop and feed on the dead tissue, and (3) endophytes that live inside living plant tissue without causing visible disease symptoms.

Fernandez-conradiFig1

Effect of fungus lifestyle on insect performance.  k = the number of studies.  Different letters to the right of CIs indicate significant differences among the variables (lifestyles).

The meta-analysis showed an important fungus-lifestyle effect (see the graph to your left).  Insect performance was strongly reduced in biotrophic pathogens and endophytes, but not in necrotrophic pathogens, where insect performance actually improved slightly (but not significantly). The researchers point out that biotrophic pathogens and endophytes both develop in living plant tissues, while necrotrophic pathogens release cell-wall degrading enzymes which can cause the plant to release sugars and other nutrients.  These nutrients obviously benefit the fungus, but can additionally benefit insects that feed on the plants.

To further explore this lifestyle effect, Fernandez-Conradi and her colleagues broke down insect response into performance and preference, focusing on chewing insects, for which there were the most data. Insects showed lower performance on and reduced preference (i.e. increased avoidance) for plants infected with biotrophic pathogens. They also performed equally poorly on endophyte-infected plants, but did not avoid endophyte-infected plants (see graph below). This was surprising since you would expect natural selection to favor insects that can choose the best plants to feed on. The problem for insects may be that endophytic infection is basically symptomless, so the insects may, in many cases, be unable to tell that the plant is infected, and likely to be less nutritionally rewarding.

Fernandez-conradiFig2

Effects of fungal infection on preference and performance of chewing insects.  k = the number of studies.  Different letters to the right of CIs indicate significant differences among the variables. Variables that share one letter have similar effect sizes. 

Many ecological studies deal with two interacting species: a predator and a prey, or a parasite and its host.  Fernandez-Conradi and her colleagues remind us that though two-species interactions are much easier to study, many important real-world interactions involve three or more species. Their meta-analysis highlights that plant infection by pathogenic and endophytic fungi reduces the performance and preference of insects that feed on these plants. But fungus lifestyle plays an important role, and may have different effects on performance and preference. Their meta-analysis also suggests other related avenues for research.  For example, how are plant-fungus-insect interactions modified by other species, such as viruses, bacteria and parasitoids (an animal that lives on or inside an insect, and feeds on its tissues)? Or, what are the underlying molecular (hormonal) mechanisms that determine the response of the plant to fungal infection, and to insect attack?  Finally, how does time influence both plant and insect response?  If a plant is recently infected by a fungus, does it have a different effect on insect performance and preference than does a plant that has suffered from chronic infection.  There are very few data on these (and other) questions, but they are more likely to get pursued now that some basic relationships have been uncovered.

note: the paper that describes this research is from the journal Ecology. The reference is Fernandez‐Conradi, P., Jactel, H., Robin, C., Tack, A.J. and Castagneyrol, B., 2018. Fungi reduce preference and performance of insect herbivores on challenged plants. Ecology, 99(2), pp.300-311. Thanks to the Ecological Society of America for allowing me to use figures from the paper. Copyright © 2018 by the Ecological Society of America. All rights reserved.

Predators and livestock – “stayin’ alive.”

President Donald Trump was elected on a platform that included building a great wall whose purpose was to keep out unwanted intruders from the south, and that would be paid for (apparently magically) by these same intruders.  The idea of building a great wall has been around for a long time; the Great Wall of China was constructed over a time period of almost two thousand years to keep out unwanted intruders (this time from the north). Not surprisingly, the cost of that Great Wall was not borne by the unwanted intruders. More recently, in the 1880s, the government of Australia constructed a 5500 km fence designed to keep unwanted dingoes away from sheep that pasture in southeastern Australia. As Lily van Eeden describes, the Australian government spends about $10 million dollars per year to maintain the fence but there are almost no data to compare livestock losses on either side of the fence. Thus she and her colleagues decided to look at what was being done globally to evaluate the effectiveness of different methods of protecting livestock.

DingoFencePeter Woodard

The Dingo fence across southeastern Australia. Credit Peter Woodard.

The researchers grouped livestock protection approaches into five different categories: lethal control, livestock guardian animals such as dogs, llamas and alpacas, fencing, shepherding and deterrents. Lethal control includes using poison baits and systematic culling of populations of top predators. Deterrents include aversive conditioning of problem predators, chemical, auditory or visual repellents, and protection devices such as livestock protection collars.

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A guardian dog emerges from the midst of its flock in Bulgaria. Credit: Sider Sedefchev.

Van Eeden and her colleagues then did a meta-analysis to see which approach worked best. You can check out my blog from Aug. 2, 2017 (“Meta-analysis measures multiple mycorrhizal benefits to plants”) for a more detailed discussion of meta-analyses. Very briefly a meta-analysis is a systematic analysis of data collected by many other researchers. This is challenging because each study uses slightly different techniques and has different levels of rigor. For this meta-analysis, van Eeden and her colleagues used only two types of studies. One type is a before/after design, in which researchers kept data on livestock loss before the mitigation treatment as well as after. The second type is a control-impact design, in which there was a control group set aside, which did not receive the mitigation treatment. Each study also needed sample sizes (number of herds and/or number of years), means and standard deviations, and had to be run for at least two months to be used in the meta-analysis.

The researchers searched several databases (Web of Science, SCOPUS and European Commission LIFE project), Google Scholar, and also used more informal sources, to collect a total of more than 3300 records. However, after imposing the requirements for types of experimental design and data output, only 40 studies remained for the meta-analysis. Based on these data, all five mitigation approaches reduced predation on livestock. The effect size in the figure below compares livestock loss with the treatment to livestock loss without the treatment, so that a negative value indicates that the treatment is associated with reduced livestock loss. The researchers conclude that all five approaches are somewhat effective, but the large confidence intervals (the whiskers in the graph) make it difficult to unequivocally recommend one approach over another. The effectiveness of lethal control was particularly variable (hence the huge confidence interval), as three studies showed an increase in livestock loss associated with lethal control.

van EedenFig2

Mean effect size (Hedges’ d) and confidence intervals for five methods used to mitigate conflict between predators and livestock.  More negative effect size indicates a more effective treatment. Numbers in parentheses are number of studies used for calculating mean effect size.

Finding that non-lethal management is as effective (or possibly more effective) than lethal control tells us that we should probably be very careful about intentionally killing large carnivores, since, in addition to being cool animals that deserve a right to exist, they also perform some important ecosystem services. For example, in Australia, there are probably more dingoes northwest of the fence than there are south of the fence, so exclusion may  be working. However there is some evidence that there are also more kangaroos and rabbits south of the fence, which could be an unintended consequence of fewer predatory dingoes. Kangaroos and rabbits eat lots of grass, so keeping dingoes away could ultimately be harming the sheep populations. Dingoes may also kill or compete with invasive foxes and feral cats, which have both been shown to drive native species to extinction, so excluding dingoes may increase foxes and cats, threatening native species.  Van Eeden and her colleagues argue that different mitigation approaches work in different contexts, but that we desperately need evidence in the form of standardized evaluative studies to understand which approach is most suitable in a particular context.

van Eeden Fig.3

Context-specific approach to managing the co-exstence of predators and livestock.

In all contexts, cultural and economic factors interact in mitigating conflict between humans and carnivores. The dingo is officially labeled as a wild dog, which invaded Australia relatively recently (about 4000 years ago), so the public perception is that this species has a limited historical role. Other cultures may have a different view of their predators. For example, the Lion Guardian project in Kenya, which trains and supports community members to protect lions, has successfully built tolerance for lions by incorporating Maasai community cultural values and belief systems.

To use a phrase that President Trump recently forbade the Centers for Disease Control to use in their reports, our decisions about predator mitigation should be “evidence-based.” We need more controlled studies that address the success of different mitigation approaches in particular contexts. We also must understand the costs of removing predators from an ecosystem, as predator removal can initiate a cascade of unintended consequences.

note: the paper that describes this research is from the journal Conservation Biology. The reference is van Eeden, L. M., Crowther, M. S., Dickman, C. R., Macdonald, D. W., Ripple, W. J., Ritchie, E. G. and Newsome, T. M. (2018), Managing conflict between large carnivores and livestock. Conservation Biology, 32: 26–34. doi:10.1111/cobi.12959. Thanks to the Society for Conservation Biology for allowing me to use figures from the paper. Copyright © 2018 by the Society for Conservation Biology. All rights reserved.

Meta-analysis measures multiple mycorrhizal benefits to plants

Plants and fungi sometimes live together in peace and harmony. Arbuscular mycorrhizal associations are associations between plant roots and fungi, in which the fungal hyphae (usually branched tubular structures) grow between root cells, penetrating some cells with a network of branches or arbuscules.  Oftentimes these are mutualistic associations with both the plants and the fungi benefiting from living together. Though plants with arbuscular mycorrhizal fungi (AMF) tend to grow better than plants without AMF, it not always clear what causes them to do so.

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Kura clover, Trifolium ambiguum, grown with AMF (left) and without AMF (right). Credit: Liz Koziol.

Ecologists have traditionally viewed arbuscular mycorrhizal associations as a straightforward nutrient-carbon exchange. Fungal hyphae, with their vast surface area, pick up nutrients (such as nitrogen and phosphorus compounds) from the soil, which they deliver to the root cells in exchange for plant-produced carbon molecules.

But recently researchers have identified numerous other potential ways that the fungi help the plants, including the following: (1) promoting water uptake and transport, (2) helping to spread allelochemicals – toxic chemicals that some plants release to rid themselves of nearby competitors, (3) inducing chemical defenses against herbivores, (4) enhancing disease resistance, and (5) promoting soil aggregation or clumping, which stabilizes the soil near the roots, reduces erosion and promotes stable water flow.

Ecology Fig1

Camille Delavaux and her colleagues wondered whether these other plant benefits might actually be more important than we originally thought. Delavaux was planning to write a review paper for a 1 credit independent study, but she found so many papers on this topic that she decided to collaborate with fellow students Lauren Smith-Ramesh and Sara Kuebbing on a full-scale meta-analysis.

A meta-analysis is a systematic analysis of data collected by many other researchers. Delavaux and her colleagues used the Web of Science database to find 4410 studies on how AMF supplied plants with nutrients and 1239 studies on how AMF provided other plant benefits. That’s a lot of studies! But for the meta-analysis, the authors only used a small fraction of these studies because they set certain restrictions. For example, to be used in the meta-analysis the authors required each study to show some measure of variation for the data (such as standard deviation or standard error). In addition, the authors required each study to compare plants grown under two conditions: with AMF and without AMF.  In many studies the researchers collected soil, which they sterilized in a hot oven, and then set up a test group, which they inoculated with AMF spores or a plug of soil or root fragments that contained AMF. In addition, these studies also had a control group of plants that received only sterilized soil with no AMF added.

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A collection of eight different species of AMF spores. Credit: Liz Koziol.

Delavaux and her colleagues compared how plants performed with and without an AMF. Because each study was different, one might only have been looking at the effects of AMF on nitrogen uptake performance, while a second study might consider how AMF influenced soil aggregation. Effect size (Hedges d+) compares mean performance of the AMF plant to mean performance of non-AMF plants for a particular variable (such as nitrogen uptake or soil aggregation). A positive effect size means that the AMF plant did better. Of course we need to know how much better is biologically meaningful, so for each variable the researchers calculated the 95% confidence intervals of the mean effect size. If the 95% confidence intervals were positive, then Delavaux and her colleagues could be 95% confident that there was a biologically important effect of AMF on plants for that particular measure of performance.

As expected, the researchers found a positive effect of AMF on plant nitrogen uptake. The mean effect size was 0.674 with a 95% confidence interval of 0.451- 0.912. We can interpret this to mean that we are 95% confident that the true mean effect size on nitrogen uptake is between 0.451 and 0.912. But the greatest effect of AMF on plants was on soil aggregation (mean effect size = 1.645, 95% confidence interval = 1.032 – 2.248). AMF also had significant positive effects on phosphorus uptake, water flow and disease resistance.

EcologyFig2

Mean effect size (Hedges’ d+) of AMF on different factors considered in the meta-analysis.  The horizontal error bars are the 95% confidence intervals. n = number of observations.  If the error bars do not cross zero, inoculation with AMF had a significant positive effect relative to plants without AMF.

This meta-analysis shows that AMF help plants in many different ways. Researchers knew about the AMF impact on nitrogen and phosphorus uptake, but may be surprised to learn of equally strong effects on water flow, disease resistance and soil aggregation. Consequently, AMF may be very useful for forest management, agriculture, conservation and habitat restoration. As examples, conservation biologists and forest managers may need to consider adding AMF to soils that have suffered severe burns from fires, which may kill the existing soil fungi. Or agriculturalists intent on growing a particular crop may want to inoculate the soil with a specific group of AMF spores that enhance soil aggregation and water uptake, so their crop may thrive in a habitat that might otherwise not be suitable.

More than 3/4 of land plants form associations with AMF. Consequently, any attempts to restore habitats or to maintain high levels of species diversity in existing ecosystems require understanding what types of AMF inhabit the soils, and how these AMF influence ecosystem functioning.

note: the paper that describes this research is from the journal Ecology. The reference is Delavaux, C. S., Smith-Ramesh, L. M. and Kuebbing, S. E. (2017), Beyond nutrients: a meta-analysis of the diverse effects of arbuscular mycorrhizal fungi on plants and soils. Ecology, 98: 2111–2119. doi:10.1002/ecy.1892. Thanks to the Ecological Society of America for allowing me to use figures from the paper. Copyright © 2017 by the Ecological Society of America. All rights reserved.