Author: Sarah Marley

Persistence (and a bit of luck) pays off: Costs of reproduction in mountain ungulates

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Fitness costs of reproduction are expected when resources are limited. This can drive the evolution of life‐history strategies and can affect population dynamics, particularly if females change their allocation of resources to reproduction. Dr Marco Festa-Bianchet (Université de Sherbrooke) explains the value of long-term studies for understanding such trade-offs and gives the #StoryBehindThePaper for his recent synthesis article in the Journal of Animal Ecology.

Long-term studies that monitor marked individuals are a valuable source of information in wildlife ecology.  But how do they start, and how do they keep going?  Here is how we ended up with 104 population-years of data on mountain ungulates in Alberta, Canada, for our ‘Synthesis’ paper: Long-term studies of bighorn sheep and mountain goats reveal fitness costs of reproduction.

In 1971, provincial wildlife biologists drove two small cabins up a fire lookout road on Ram Mountain, and assembled a corral trap with walls built by inmates at a minimum-security prison.  They wanted to determine the feasibility of a hunting season on female bighorn sheep, and measure the survival of orphan lambs.  In 1981, I was given a dart gun, shown how to use it, and sent to the Sheep River Wildlife Sanctuary in southwestern Alberta. My mission was to investigate whether individual differences in the timing of seasonal migration by bighorn sheep affected lungworm infection and risk of pneumonia.  In 1989, provincial wildlife biologists set up traps on Caw Ridge, north of Jasper National Park, to capture mountain goats and determine whether low kid survival may explain a recent decline in many populations in the province.

Fast-forward to 2019.  Nearly 2,500 marked sheep and goats, about 200 scientific publications and over 150 field assistants and graduate students later, our studies of mountain ungulates have substantially advanced our understanding of population dynamics, life-history and evolutionary ecology. They also provided key evidence of the evolutionary effects of intense trophy hunting.  The long-term data were the raw material for dozens of graduate theses, led to collaborations among researchers from multiple universities, and have had profound influences on wildlife management.  They carried on through perseverance of the many people involved, support from funding agencies such as the Natural Sciences and Engineering Research Council of Canada, and sheer luck.  At one point, Caw Ridge was supposed to become a coal mine.  Forest fires threatened evacuations. Cougar predation came close to reducing each of the three populations to a size that would question the value of continued monitoring. Roads and trails were washed out, camps broken into, equipment stolen. Most ecologists agree on the value of long-term studies, but perhaps not many realize that a major factor in the success of these studies is secure access to study areas.  That access can be threatened by natural disasters, changes in land tenure and political decisions.

Shee-goatStudents

Some of the many ‘goat students’ from over the years!

Our ‘Synthesis’ paper focuses on the fitness costs of reproduction from these long-term studies.  Much of what we know stems from our ability to monitor individuals from birth to death, and the changes in ecological variables, from population age structure and density to the occurrence of disease and predation, over the years of monitoring.  It is a bit of a running joke among people with long-term data sets that we could at times produce contrasting results simply by cherry-picking a few years of data.  Our Synthesis paper emphasizes how individual differences affect allocation to reproduction and our ability to detect fitness costs.  Those differences are formidable obstacles for non-manipulative studies.

We partly accounted for those individual differences through repeated measurements of individuals.  Repeated measurements transform individual differences from a statistical problem to biological insight.  Often, long-term studies face the criticism of limited external validity: you found this here, but would it be the same elsewhere?   The comparison of three populations of animals with similar characteristics increases our confidence in how fitness costs become more evident in specific circumstances, such as at high population density or during disease episodes.  Our clearest result is that females mostly shift costs of reproduction to their offspring, presumably to avoid compromising their residual reproductive value.  That result was expected in these long-lived highly iteroparous mammals, where the residual reproductive value of females is likely much greater than that of offspring.  For males, we suggest that the greatest costs of reproduction are in trying to reproduce, which involves competition with other males and a risk of injury.

Many questions remain, such as a better quantification of cumulative reproductive costs over multiple years or the possible role of fathers in maternal allocation decisions.  As climate change increasingly affects many aspects of the ecology of our study species, we are well positioned to investigate its ecological and evolutionary consequences.  As the studies continue, we will again rely on perseverance, some luck, and people who enjoy (or at least tolerate) fieldwork in difficult conditions.

RamSnowman2017

Fieldwork funtimes!

More Info:

Festa‐Bianchet, Côté, Hamel, and Pelletier (2019). Long‐term studies of bighorn sheep and mountain goats reveal fitness costs of reproduction. Journal of Animal Ecology, 88(8): 1118-1133. DOI: 10.1111/1365-2656.13002

Birds in paradise: biogeography in the subtropics

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Biogeography is often more complicated than the species-area relationship as discussed in a Journal of Animal Ecology paper testing multiple extensions of island biogeography theory. Sam Ross, lead author of the study, is a PhD student at Trinity College Dublin studying ecological responses to global change. Sam has additional interests in community ecology and macroecology, and works closely with colleagues at the Okinawa Institute of Science and Technology Graduate University in Japan. Here, he describes how this work fits into the long history of biogeography research.

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Light-vented bulbul (Pycnonotus sinensis), one of the species of interest in the Ryūkyū archipelago (Photo: Sam Ross)

The species-area relationship is considered one of the only ‘rules’ in ecology. We have observed more species on larger ‘islands’ (whether true islands or simply some habitat patch of interest) in studies of different plants and animals all around the world. When MacArthur and Wilson (1967) proposed this pattern and the pioneering biogeographical principles which underpin it, they acknowledged that a piece of the puzzle was missing: species identity.

Biogeographers have since recognised that species aren’t randomly distributed across the globe. We now believe there to be ecological factors which predict where species occur. For example, predators can only live in habitats where their prey are sufficiently abundant, otherwise they’ll starve. This led Dominique Gravel and colleagues to predict that larger islands should have more complex food webs, since smaller islands support fewer prey species and so can in turn support fewer, if any, predators (Gravel et al. 2011). They then proposed that predators should be more influenced by island size than their prey, producing steeper species-area relationships for higher trophic levels. They called this idea the ‘trophic theory of island biogeography.’

We tested this empirically using checklists of bird sightings across the Ryūkyū archipelago running from southern mainland Japan to Taiwan. We separated birds by their trophic groups and found that contrary to the trophic theory of island biogeography, our predatory birds didn’t really differ in the slope of their species-area relationship from our herbivorous birds. This wasn’t really what we expected to find but the trophic theory hasn’t yet been tested across a range of different study systems, so our test helps us to understand whether communities may be structured by trophic level or not.

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Expectation versus reality of our test of the trophic theory of island biogeography with the birds of the Ryūkyū (Image: Sam Ross)

Another way species’ identities might structure communities is based on the idea of environmental filtering. These filters are thought to be strongest on small islands, where there is little opportunity to just scrape by. Small islands are harsh; there are many ways populations can go extinct on small islands, but particularly life on these islands is strongly affected by environmental conditions. This means that only species particularly suited to the environment are likely to survive and thrive on small islands. By expanding on the work of Claire Jacquet and colleagues (Jacquet et al. 2017), we could then predict that small islands would have species which are similar to each other and are all adapted to the local environment, whereas larger islands are more likely to contain random species from the regional pool of all species which could possibly live there.

Another longstanding idea predicts the opposite pattern. Because smaller islands have fewer resources, species must compete for those finite resources to survive. This means that on small islands, we might expect species to be widely different from each other to minimise competition for food and space. If there’s only one small grasshopper population on the island for example, it seems more likely that we’ll find five species of birds that all eat different things than five that are competing for the chance to eat this one grasshopper. So, we might expect that competition results in distinctive species on smaller islands and that as competitive pressure relaxes on larger islands, these islands again are more likely to contain a random assortment of species.

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Blue Rock Thrush (Monticola solitarius) pictured at Cape Zanpa, Okinawa—the edge of the island (Photo: Sam Ross)

We tested whether either of these two processes structured the bird communities of the Ryūkyūs by calculating the functional and phylogenetic diversity of birds on each island using two global databases. We used the global phylogeny of birds and a database of functional traits to measure the observed functional and phylogenetic diversity of birds on each of our study islands. We also tested whether this observed diversity was higher or lower than expected by random chance by shuffling the names of species on the phylogeny and functional trait matrix. Together, this meant we could test whether diversity was lower than expected by random on small islands and increasing to a random sample of the regional pool (trait-based assembly), or whether competitive assembly occurred, where diversity was higher than expected on small islands and closer to random on larger islands.

We found no clear overall pattern of either trait-based or competitive assembly of bird communities in the Ryūkyūs, but we did find some differences among our trophic groups in whether communities were structured randomly or not. The insectivorous intermediate predators showed patterns of trait-based community assembly since their phylogenetic and functional diversity was lower than expected on small islands and increased to random on larger islands.

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Community assembly processes across our trophic groups of birds. We found no clear patterns for apex predators or herbivores, but intermediate predators followed the predictions of trait scaling by Jacquet et al. (2017). (Image: Sam Ross)

Overall, we tested multiple extensions to the theory of island biogeography which have been rarely tested, and certainly not extensively across a range of study locations and focal species. In the subtropical Ryūkyū archipelago, we found that bird communities did not clearly conform to the theories laid out by recent extensions to island biogeography theory, but that some held true. For now, we encourage others to continue testing these hypotheses in a variety of study systems to see whether our subtropical bird communities show the same biogeographic patterns as animal communities around the world.

More Info:

Ross, Friedman, Janicki, & Economo (2019). A test of trophic and functional island biogeography theory with the avifauna of a continental archipelago. Journal of Animal Ecology. DOI: 10.1111/1365-2656.13029

Determinants of micro- and macroparasite diversity in birds: the fruits of comparing apples and oranges

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Identifying the factors shaping variation in parasite diversity among host species is crucial to understand wildlife diseases. A recent paper in Journal of Animal Ecology investigated the role of host life history and ecology in explaining the species richness of micro- and macro-parasites in birds world-wide. Lead author Dr Jorge Sanchez Gutierrez explains more about the study.

The phrase “comparing apples and oranges” is often used in ecological and evolutionary contexts to make the point that differences in the “basic biology” of different taxa make any comparison invalid. Like apples and oranges, haemosporidians (unicellular blood parasites causing malaria-like diseases in birds) and helminths (parasitic worms such as tapeworms, roundworms and flukes) are in different branches of the taxonomic tree. But are they that different?

Unlike the tiny mosquito-borne haemosporidians, helminths are usually visible to the naked eye and do not multiply directly within an infected individual. Instead they produce infective stages that usually pass out of the host before transmission to another host. Unlike blood parasites, helminths tend to produce weaker immune responses in infected birds. It is thus likely that the two classes of parasites would lead to different selection pressures on hosts, and vice versa.

Yet, despite obvious differences in their transmission modes and virulence, they often infect the same host—be it an individual, a population or a species. Surely then, there are valid comparisons that can be made? And would such a comparative approach also identify potential red herrings arising from single group-based approaches? A comparison between these parasitic apples and oranges could help illuminate whether and how bird traits shape the diversity of these two parasite groups.

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Cestode (Image: Jorge Sanchez Gutierrez)

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Avian malaria (Image: Jorge Sanchez Gutierrez)

To answer this question, I teamed up with my colleagues David Thieltges and Theunis Piersma, both senior researchers at the Royal Netherlands Institute for Sea Research with broad and complementary experience in the field of parasite/host ecology. In an earlier study, published in Journal of Biogeography in 2017 (https://onlinelibrary.wiley.com/doi/abs/10.1111/jbi.12956), we (together with Eldar Rakhimberdiev) examined the correlates of helminth richness in Charadriiform birds (waders, gulls, auks and allies). We found that birds that exploit diverse diets and habitats harbour more helminth species, that is, relative to specialist birds.

In the present study in the Journal of Animal Ecology we went one step further and investigated whether these and other host traits (for example, migration distance, longevity or coloniality) correlate with the species richness of helminths and haemosporidians in birds worldwide. Historically, this line of research has focused on mammals, since global databases encompassing both micro- and macroparasites were largely restricted to mammals.

This meant that I had to put my shoulders to the wheel and combined several global-scale datasets on traits of over 300 bird species and the numbers of their blood and worm parasites. After controlling for research effort—some bird species are better studied than others—and bird phylogeny, we found that helminth richness positively correlated with bird longevity, geographic range size, dietary breadth and migration distance. Overall, such results are consistent with epidemiological and biogeographical processes. To our surprise, however, the only factor that explained some variation in the richness of blood parasites was research effort!

Jorge Graphical Abstract

Perhaps the simplest explanation for this lack of association between haemosporidian richness and bird traits is that blood parasites may be more influenced by factors related to the ecology of the arthropod vectors than the traits of the host. Another possibility to explain the non-significant relationship between haemosporidian richness and bird longevity (which we predicted to be negative, as haemosporidians can lower survival rate) is that haemosporidian parasites may lead to effective immune defence strategies, the response destroying what would have initially been an association. On the contrary, we found a positive effect for less pathogenic helminths that seldom kill their host. It might well be that long host lifespans promote the diversity of helminth parasite assemblages over evolutionary time, ultimately resulting in richer helminth faunas.

Although from a statistical point of view it remains open whether there are actual differences between the two parasite groups in the role of host life history and ecology in determining parasite richness of birds, the presence of many significant correlates within helminths but none in haemosporidians is intriguing. We hope that this study will bring renewed attention to the factors that determine patterns of parasitic infections. While writing this blog-post from tropical West Africa, where parasitic helminths are among the most common chronic infections and malaria parasite infection the most deadly, I realize about the importance of investigating the drivers of global patterns of parasite diversity and distribution to anticipate disease emergence risks, in both humans and wildlife.

More info:

Gutiérrez, Piersma and Thieltges (2019) Micro- and macroparasite species richness in birds: the role of host life history and ecology. Journal of Animal Ecology.

The invisible interplay between herbivorous insects and their monitoring ants on a chemically diverse plant

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Plants exhibit impressive genetic and chemical diversity, and this variation is important for structuring ecological communities. A recent paper in the Journal of Animal Ecology investigated this with regard to aphids and their host-plant tansy. Lead author Dr Sharon Zytynska from the Technical University of Munich tells us more about this study.

The perennial tansy plant (Tanacetum vulgare) grows steadily throughout the spring, producing heads of bright yellow flowers in the summer. It is native to temperate Europe and Asia, but invasive in North America. It has a long history of cultivation for medicinal uses (although worries about its toxicity have reduced its use), and has even had a moment of fame in the popular Game of Thrones series as one ingredient of ‘moon tea’ used to prevent or abort pregnancies.

Tansy aphids

Tansy aphids feeding on plant leaves (left), the distinctive yellow flowers of this plant in summer (middle), and in the field collecting data (right) (Photos: S Zytynska)

Tansy plants synthesise many different chemical compounds known as essential oils, which are stored in specialised cells on the plant’s leaves. These compounds are released through evaporation into the air around the plant, in particular when the leaves are touched such that the storage cells are damaged – if you squish a tansy leaf between your fingers you can smell the chemical compounds, even detecting different bouquets among neighbouring plants.

The chemical diversity of the plant leads it to being a natural insect repellent, with both the agricultural Colorado potato beetle pest and the common tick avoiding leaves of the plants (Panasiuk 1984; Pålsson et al. 2008). However, not all insects are repelled by the plant. Three specialised aphid species (small, soft-bodied insects that feed on the plant sap) are commonly found on the plants. One of these species, Metopeurum fuscoviride, feeds almost exclusively on tansy and is found living in dense colonies on the upper parts of the plant stems. In the early part of the season, these aphids produce winged morphs that can disperse among plants within a field site and to other field sites. After 2-3 weeks, the majority of aphids are unwinged, limiting their feeding options to their current plant or perhaps the neighbouring plant. This aphid species doesn’t just need its tansy plant host to survive but is also an obligate myrmecophile, which means it also needs ants around for colony growth. As aphids feed on the sugary plant sap, they ingest more than is needed and expel the extra as honeydew droplets. Ants feed on this honeydew, and in return protect the aphids from predators. Without ants, the aphids can also become overwhelmed by the honeydew – often sticking themselves to the plant, becoming easy fodder for predators and an ideal breeding ground for fungi.

Our current paper in Journal of Animal Ecology (Zytynska et al. 2019), is the culmination of a DFG (German Research Foundation) funded project where we investigated the effect of tansy plant chemical variation on its specialised aphids and their mutualist ant partners in a field site located in Bavaria, South Germany. We began the project by following almost 200 individual plants in a field from April until October, where the plants grow in individual patches, forming ‘islands’ for its specialised insect herbivores among the other plants growing in the area. Every week we observed the presence of ants, colonisation and population growth of aphids, and the presence of different natural enemies (e.g. ladybirds, and parasitic wasps) on each plant (Senft, Weisser & Zytynska 2017). We found a strong influence of the ants on aphid colonisation, and that local extinction (at the level of the plant) could only be driven by natural enemies once the aphid population was already small. So, we hypothesised that plant chemical variation could influence aphid colonisation success and subsequent population growth rates, leading to larger or smaller populations of aphids on plants with different chemical profiles.

Collecting chemicals

Collecting the volatile chemicals released by the plants in the laboratory (left; photo: J-P Schnitzler) and in the field (middle left; photo: S Zytynska) using stir bar sorptive extraction (middle right; photo: S Zytynska). In the early season, variation in these plant volatile chemicals influences aphid colonisation whereas later in the season other plant compounds (from metabolomics studies) are more important (right; adapted from Clancy et al. (2018))

From our 200 field plants, we identified 22 volatile compounds that are continually released by the plant (i.e. not induced through stress responses). Each of our naturally-growing field plants had its own unique chemical profile, but we were able to group them into four major ‘chemotype’ classes, and showed these influenced the probability of a plant being colonised by early-season winged aphids (Clancy et al. 2016). A further study using untargeted metabolomics grouped plants by their non-volatile compounds, and we found these could also influence aphid colonisation, and population growth rates of unwinged aphid colonies through the season (Clancy et al. 2018). A semi-natural field experiment then empirically confirmed that different chemical profiles of plants could alter aphid population growth, the number of ants on a plant that are tending the aphids, and also the abundance of predators on the different plants (Senft et al. 2019).

In the current paper, we wanted to also look at variation within the aphids themselves as this can affect colony growth rates but moreover if it can influence their choice of host-plant (reviewed in Zytynska & Weisser 2016). Aphids were collected across two years from each plant and genotyped using 18 specially-designed microsatellite loci. We identified six main genetic groups of aphids (genotypes) at our field site, with surprisingly high levels of genetic variation for an insect that reproduces asexually in the warm summer months. We found that the distribution of aphid genotypes was not random, but that certain aphid genotypes were found more often on certain plant chemotypes/metabotypes. Not only do aphids choose preferred plant chemotypes (or metabotypes) but that different genotypes of aphids show different preferences. Moreover, preferences of the ants for different plant variants also impacted the distribution of aphids with some ‘aphid genotype – plant chemotype’ combinations being enhanced by similar aphid and ant host preferences. Therefore, rather than a generic mass of green in a field, aphids can decipher which are their host plants and show a preference to the particular type of host plant they want to live on; perhaps similar to my preference for broccoli over cauliflower – same plant species (Brassica oleracea), but different variants.

So, as you take walks out into the countryside over the coming summer months, remember that these small insects are quietly getting on with their lives deciding where to feed, reproducing to increase their colony sizes, being poked by ants, and generally trying to avoid getting eaten by predators.

 

More information

Clancy, M.V., Zytynska, S.E., Moritz, F., Witting, M., Schmitt-Kopplin, P., Weisser, W.W. & Schnitzler, J.P. (2018) Metabotype variation in a field population of tansy plants influences aphid host selection. Plant Cell and Environment, 41, 2791-2805.

Clancy, M.V., Zytynska, S.E., Senft, M., Weisser, W.W. & Schnitzler, J.-P. (2016) Chemotypic variation in terpenes emitted from storage pools influences early aphid colonisation on tansy. Scientific Reports, 6, 38087.

Pålsson, K., Jaenson, T.G., Bæckström, P. & Borg-Karlson, A.-K. (2008) Tick repellent substances in the essential oil of Tanacetum vulgare. Journal of medical entomology, 45, 88-93.

Panasiuk, O. (1984) Response of Colorado potato beetles, Leptinotarsa decemlineata (Say), to volatile components of tansy, Tanacetum vulgare. Journal of chemical ecology, 10, 1325-1333.

Senft, M., Clancy, M.V., Weisser, W.W., Schnitzler, J.-P. & Zytynska, S.E. (2019) Additive effects of plant chemotype, mutualistic ants and predators on aphid performance and survival. Functional Ecology, 33, 139-151.

Senft, M., Weisser, W.W. & Zytynska, S.E. (2017) Habitat variation, mutualism and predation shape the spatio-temporal dynamics of tansy aphids. Ecol Entomology, 42, 389-401.

Zytynska, S.E., Guenay, Y., Sturm, S., Clancy, M.V., Senft, M., Schnitzler, J.P., Pophaly, S.D., Wurmser, C. & Weisser, W. (2019) Effect of plant chemical variation and mutualistic ants on the local population genetic structure of an aphid herbivore. Journal of Animal Ecology.

Zytynska, S.E. & Weisser, W.W. (2016) The effect of plant within-species variation on aphid ecology. Biology and Ecology of Aphids (ed. A. Vilcinskas), pp. 152-170. CRC Press.

Manipulation of gut microbiota during critical developmental windows affect host physiological performance and disease susceptibility across ontogeny

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Colonisation of gut microbiomes during early life can shape metabolism and immunity of adult animals. However, most data are derived from antibiotic‐treated or germ‐free laboratory mammals. Furthermore, few studies have explored how microbial colonization during critical windows influences a suite of other fitness‐related traits in wild animals. A recent study in the Journal of Animal Ecologytested whether hatching constitutes a critical development window for microbiome colonisation in wild-caught amphibians. Here, authors Robin Warne, Lucas Kirschman, and Lydia Zeglin present a summary of this work.

Our new study published in the Journal of Animal Ecology reveals the astounding and persistent effects that symbiotic gut bacteria can have on the development, growth, and health of their animal hosts. We found the bacterial community on the outside of eggs influences the microbiota that colonizes the guts of tadpoles as they hatch, and that differences in the bacteria during this initial colonization can have both positive and detrimental effects on the health of tadpoles as they grow into frogs.

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Wood frog tadpoles inoculated with differing bacterial communities at hatching exhibited differences in their gut microbiome that were associated with changes in development, growth, and metabolism. Changes in their gut microbiomes were also associated with differences in susceptibility to ranavirus (an emerging disease of amphibians) as well as variation in tail deformities. Tadpoles that were inoculated with random bacteria from the environment had more tail deformities (B) and were more susceptible to infection by ranavirus than tadpoles from other inoculation treatments.

In this experiment, we stripped the bacterial community on the eggs of wood frogs, and then inoculated them with microbes from differing sources, including from another species that differ in disease resistance and life history. We found tadpoles that received bacteria from the other species were more robust than controls, whereby they developed and grew faster, and trended towards being more resistant to a virus (ranavirus) that can be lethal to some amphibian tadpoles, especially wood frogs. By contrast, we found another group of tadpoles that were inoculated at hatching with random bacteria from the environment, were much less healthy. These tadpoles showed disrupted metabolic rates, high rates of tail deformities, and were more susceptible to the virus, which infects through the gut. These results suggest that variation in the types of symbiotic gut bacteria present at hatching influence the long-term health of their hosts.

The next step in our research is to explore the mechanisms by which gut bacteria influence their hosts. We think a likely way gut bacteria affect their hosts is via the metabolites or metabolic biproducts they produce, such as short chain fatty acids, essential nutrients like vitamins, and even hormone like compounds. These metabolites serve as energy substrates, essential nutrients, and potentially as signaling molecules that may directly influence their hosts through interfacing with hormone receptors in host tissues including the brain.

This experiment provides a great foundation for future experiments that explore these potential mechanisms, and these experiments could prove amphibians can be a valuable animal model for understanding microbiome effects on the health of hosts including in humans. This is because like our results in tadpoles, the mode of birth in humans (caesarian vs natural birth) can permanently shape the gut microbiome of adults, and have life-long effects on human health through affecting metabolic diseases and obesity.

This research could also inform conservation efforts of amphibians impacted by emerging diseases such as ranavirus and chytrid fungus, because researchers are exploring using bacterial inoculations and metabolites as a means to bioaugment amphibian resistance to such pathogens.

More Info:

Which GLM?

/ Sarah Marley / 1 Comment

Many papers refer to the use of GLMs in their analyses – but are you sure you know to which statistical approach they refer? Professor Daniel Blumstein and Associate Professor Noa Pinter-Wollman (University of California, Los Angeles) are here to clear up any confusion, and suggest a path going forwards…

Statistics have evolved rapidly and the proliferation of acronyms sometimes creates novel problems, particularly for those who use statistics as a tool rather than as their subject discipline. Two similar analyses now are abbreviated GLM: the general linear model and the generalized linear model. The use of the same acronym for two different statistical approaches creates confusion and miscommunication when reading methods sections of scientific papers.

Traditionally, the general linear model was viewed as broad term for linear regression, analysis of variance, or analysis of covariance, all of which minimize the sum of squares to explain variation in a continuous dependent variable as a function of categorical and/or continuous independent variables. Commercially produced statistical packages, like SPSS, give users a choice of fitting a GLM, or use different procedures to fit a regression or an ANOVA depending on the nature of the independent variables. In R, the lm() function produces identical results.

More recently, generalized linear models, also abbreviated GLM, extend general linear models by using maximum likelihood algorithms to fit models to data by specifying non-normal error distributions using a link function. Their use has become common due to the development of computationally intensive maximum likelihood techniques to fit statistical models and the availability of powerful personal computers. One of the functions in R that implements such models is glm().

We suggest that to avoid confusion, the original general linear model be referred to exclusively as LM, while the newer generalized linear model be referred to by the acronym GLM. By adopting this as tradition we will reduce the opportunity for statistical consumers trained in the Anthropocene to argue with their elders, trained in the Holocene, about which GLM is being used in a particular instance.

multicolored abacus photography

Photo by Skitterphoto on Pexels.com

Do spatial sampling scales influence the understanding of ant-plant interaction network architecture?

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Despite great interest in metrics to quantify the structure of ecological networks, the effects of sampling and scale remain poorly understood. However, a recent paper published in Journal of Animal Ecology seeks to change this! Lead author Dr Wesley Dáttilo (Instituto de Ecologia, Mexico) explains how studying ant-plant interaction networks helped develop a better understanding of spatial sampling scales.

We know that no single species is completely isolated in nature. Rather, each species is constantly interacting with other organisms in order to carry out their life cycles – for successful reproduction, development or survival.

The high diversity of biotic interactions over spatial and temporal gradients generates complex networks, where species are depicted as nodes and their interactions by links. Seminal studies dealing with the structure of ecological networks have assumed that observed patterns and structuring processes are scale-invariant. However, recent studies show that some descriptors of network structure are strongly affected by spatial sampling scales, which could lead to erroneous conclusions regarding the ecological and evolutionary dynamics of ecological networks. In fact, one of the most persistent challenges in ecology is the definition of suitable sampling scales at which to describe an ecological system.

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Wesley preparing his boat on the Juruena River to collect ant-plant interactions.

In our recently published paper in the Journal of Animal Ecology, we investigated for the first time whether the spatial sampling scale, from local to regional, affects our understanding of the structure of ant-plant interaction networks mediated by extrafloral nectaties in the southern Brazilian Amazon. In this biotic interaction, plants offer highly nutritive nectar, rich in sugar and amino acids to ants that protect their host plants against herbivores. We chose this type of mutualism as a study model because of its high diversity of interactions at small spatial scales within tropical environments.

Fig2

Workers of Crematogaster sp. (Myrmicinae) feeding on an extrafloral extrafloral nectar of Inga sp. (Mimosaceae).

The resulting database is one of the largest compiled to date in terms of species richness and number of ant-plant interactions. Specifically, we recorded ant-plant interactions in adjacent 25 x 30 m subplots (local sampling scale) nested within twelve 250 x 30 m plots (regional sampling scale). Moreover, we combined subplots with adjacent or random plots in order to increase the spatial sampling scales at the local and regional levels. We then calculated commonly used binary and quantitative network-level metrics for both sample scales (i.e., number of species and interactions, nestedness, specialization, and modularity), all of which encompass a wide array of structural patterns in interaction networks.

Fig1

Wesley Dáttilo and his field assitant Roberto sampling ant-plant interactions in the southern Brazilian Amazon.

In general, we observed that, despite the accumulation of species and links with increasing sampling scales, most network descriptors tended to be more constant at local compared to regional sampling scales. This cautions against pooling networks from different plots to describe ant-plant interactions, since they may influence metric values depending on the specific plot considered.

We collected the dataset used in this study during my master’s degree (under the guidance of my supervisor Dr. Thiago Izzo) while I was still living in Brazil. During my doctorate in Mexico, I completed an internship in Spain at Pedro Jordano’s Lab where I developed in depth the theoretical framework of this study and also worked with Jeferson Vizentin-Bugoni and Vanderlei J. Debastiani, two other young and promising Brazilian ecologists. After finishing my doctorate, I have been a researcher in the Instituto de Ecología A.C. in Mexico. Currently, my collaborators and I are seeking to understand how biological properties affect the structure and dynamics of plant-animal interaction networks at different levels. We are seeking to understand how species interactions vary through space-time, and how they are influenced by environmental perturbations in different ecosystems around the world (please visit: www.wesleydattilo.org).

Disentangling disease transmission in Madagascar fruit bats

/ Sarah Marley / Leave a comment

Bats can carry various diseases, including many which are transferable to humans. A recent study published in the Journal of Animal Ecology investigated disease extent, seasonality, and mechanisms of transmission among Malagasy fruit bats. Lead author Dr Cara Brook (Princeton University and UC Berkeley) explains more about the paper.

Bats (order Chiroptera) have received much attention in recent years for their roles as reservoirs for some of the world’s most virulent zoonoses—including Ebola and Marburg filoviruses and Hendra and Nipah henipaviruses (Calisher, Childs, Field, Holmes, & Schountz, 2006) —which they appear to host without experiencing disease. Numerous empirical studies have demonstrated seasonality in bat viral and immunological dynamics, which coincide with the annual chiropteran birth pulse and may underpin observed seasonality in cross-species emergence of bat-borne zoonoses  (Amman et al., 2012; Baker et al., 2014; Plowright et al., 2015, 2008; Schmidt et al., 2017). Previous theoretical work has attempted to recapture these seasonal dynamics using models encoding a suite of diverse transmission mechanisms, but application of these models to longitudinal field data has, to date, been rare. In a recent paper published in the Journal of Animal Ecology, we coupled field and modeling approaches to investigate the question of bat henipa- and filovirus seasonality on the Eighth Continent island nation of Madagascar.

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During the course of my PhD and in close collaboration with Christian Ranaivoson, a Malagasy doctoral student at the University of Antananarivo and the Institute Pasteur of Madagascar (and the second-author on this paper), we field-captured and serum-sampled over 800 fruit bats from three endemic Malagasy fruit bat species (Pteropus rufus, Eidolon dupreanum, and Rousettus madagascariensis) across all months of the year. From a subset of larger-bodied P. rufus and E. dupreanum, we extracted teeth under anesthesia, which were sliced and stained, with layers counted to determine each bat’s age. Serum underwent Luminex-based antibody assay against known filo- and henipavirus antigens.

Deciphering serology

Antibodies are memory proteins which the mammalian immune system uses to neutralize harmful viruses entering the body. Assays such as our Luminex measure the extent to which antibodies in serum bind the antigens against which they are challenged. The presence of antibodies specific to an antigen thus provides evidence of past exposure of the host from which the sample is taken to the viral antigen against which the sample is challenged.

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Our study reports the first evidence of Ebola “seropositivity” (antibody positivity) in any wild animal in Madagascar —specifically, in P. rufus and R. madagascariensis—in addition to the first evidence of Cedar virus (a bat-exclusive henipavirus) seropositivity in Madagascar—in E. dupreanum and R. madagascariensis. We further confirm previous records of seropositivity to Hendra and Nipah virus antigens in E. dupreanum and P. rufus (Iehlé et al., 2007) and additionally report the first evidence of Hendra and Nipah virus seropositivity in R. madagascariensis.

Because we lack specific antigens for viruses of Madagascar fruit bats, seropositivity was determined based on binding of Malagasy bat serum antibodies to antigens from African Ebola and Asian and Australian Nipah and Hendra viruses. As antibodies can sometimes bind antigens from similar viruses, it is possible that our seropositive fruit bats are, in actuality, hosting unique Ebola-, Hendra-, and/or Nipah-related viruses that have not yet been described. We are working actively to identify and isolate these viral genotypes to date.

Consistent with previous reports in the literature, we witnessed seasonal changes in population-level seroprevalence (the proportion of bats testing antibody positive) to Nipah virus in E. dupreanum and Ebola virus in P. rufus. Seroprevalence peaked at the height of the fruiting season and at the gestation/lactation transition for bats in our system. Data from individual E. dupreanum that were captured twice across our study supported population-level trends: female serotiters increased across gestation and declined post-lactation, while male serotiters increased throughout the fruiting season, then decreased across the dry season. Seasonal trends in body mass similarly mapped on to the reproductive calendar for females and the nutritional calendar for males.

Elucidating transmission

Traditionally, dynamical insights in disease ecology and public health have been largely derived via fitting of compartmental transmission models in the Susceptible-Infectious-Recovered (SIR) framework to times series of infectious cases. Under such a framework, hosts are classed into infection state categories (S-I-R), and parameters corresponding to transmission or recovery rates are optimized to produce the best recapitulation of the data. In the case of wildlife infections, where time series case data are difficult to obtain, we use tooth-derived age information, paired with serology (corresponding to the “recovered”, “R”-class) to improve modeling inference.

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For both Nipah virus in E. dupreanum and Ebola virus in P. rufus, seroprevalence was high in neonates, low in juveniles, increased with age across early adult years and finally waned again in older bats. Using a matrix-based approach, which enabled us to track bat ages within each infection state in our system, we were best able to recapitulate these data with an MSIRN model structure, by which bats passed from a state of maternally immune (M) to susceptible (S) to infectious (I) to recovered (R) before finally settling in to an “N”-class, representing “non-antibody-mediated immunity.” We modeled bats in this age class as antibody-negative via our Luminex but nonetheless immune to reinfection via some other immune-protective mechanism, consistent with some previously-reported experimental infections in the literature.

Our work greatly advances the conversation in bat virus disease ecology, but there remain many unanswered questions in this system and this field. For example, our MSIRN model assumes that the older bats become uniformly seronegative but nonetheless immunized for life—but we know from seasonal monitoring of serology that serotiters are dynamic for individual bats. It is possible then that older bats may go through seasonal cycles of seropositivity and/or actively shed virus in excretia, a process not explicitly modeled here. In the future, more finescale longitudinal sampling of recaptured individuals will facilitate construction of models incorporating within-host processes. This article represents the culmination of much of the work emerging from my PhD—but nonetheless launches me into a lifetime of questions and discoveries ahead.

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More Info:

Amman et al. (2012). Seasonal pulses of Marburg virus circulation in juvenile Rousettus aegyptiacus bats coincide with periods of increased risk of human infection. PLoS Pathogens, 8(10), e1002877. doi:10.1371/journal.ppat.1002877

Baker et al. (2014). Viral antibody dynamics in a chiropteran host. Journal of Animal Ecology, 83(2), 415–428. doi:10.1111/1365-2656.12153

Brook et al. (2019) Disentangling serology to elucidate henipa‐ and filovirus transmission in Madagascar fruit bats. Journal of Animal Ecology. doi:10.1111/1365-2656.12985

Calisher et al. (2006). Bats: Important reservoir hosts of emerging viruses. Clinical Microbiology Reviews, 19(3), 531–45. doi:10.1128/CMR.00017-06

Iehlé et al. (2007). Henipavirus and Tioman virus antibodies in Pteropodid bats, Madagascar. Emerging Infectious Diseases, 13(1), 159–161.

Plowright et al. (2015). Ecological dynamics of emerging bat virus spillover. Proceedings of the Royal Society B, 282(1798). doi:10.1098/rspb.2014.2124

Plowright et al. (2008). Reproduction and nutritional stress are risk factors for Hendra virus infection in little red flying foxes (Pteropus scapulatus). Proceedings of the Royal Society B: Biological Sciences, 275(1636), 861–9. doi:10.1098/rspb.2007.1260

Schmidt et al. (2017). Spatiotemporal fluctuations and triggers of Ebola virus spillover. Emerging Infectious Diseases, 23(3), 415–422. doi:10.3201/eid2303.160101

Lovers and fighters, and how their coexistence affects their evolution within an eco-evolutionary feedback loop

/ Sarah Marley / Leave a comment

Eco-evolutionary dynamics are well studied but the term is applied to a wide variety of effects and interactions. Yet comparing these different types of studies on eco-evolutionary dynamics will inform on how this field can move forward, which is precisely the aim of a recent British Ecological Society cross-journal Special Feature. Here,  Isabel Smallegange (an Associate Professor of Population Biology at the University of Amsterdam) discusses a study published within this Special Feature that investigates how an eco-evolutionary feedback loop between population dynamics and fighter expression affects the evolution of alternative reproductive tactics.

To contribute towards integrating the field of eco-evolutionary dynamics and move the field forward, scientific journals from the British Ecological Society, including the Journal of Animal Ecology, have recently published a cross-journal special feature entitled “The diversity of eco-evolutionary dynamics: comparing the feedbacks between ecology and evolution across scales”, edited by Franziska Brunner, Jacques Deere, Martijn Egas, Christophe Eizaguirre and Joost Raeymaekers *.

How evolutionary changes (like shifts in genotype and phenotype frequencies) and ecological changes (like the size, composition and growth of an animal or plant population) affect each other is a topic of intense and growing investigation in biology. Why? Because for a long time, ecologists ignored evolutionary processes as they were assumed to occur at much longer time scales (thousands to millions of years) compared to ecological processes (days to years). Vice versa, evolutionary biologists ignored ecological processes as these were assumed to occur at such short time scales that their effects would be unnoticeable at the long, evolutionary timescales. However, over the past decades, notions have changed from “nothing in biology makes sense except in the light of evolution” [1], to “nothing in evolutionary biology makes sense except in the light of ecology” [2], to finally “nothing in evolution or ecology makes sense except in the light of the other” [3].

Fig1

Figure 1 A summary of the findings of Yoshida et al. [4]: The ecological dynamics of predator and prey abundance in a rotifer-algae system differ, depending on whether or not prey can evolve in response to variation in predator abundance. Image: Isabel Smallegange

Yoshida and coworkers [4] provide an excellent example of how taking evolutionary processes into account, significantly affects ecological dynamics. They used a combination of experiments and theoretical modelling to study how the abundance of a rotifer predator and its algal prey varied over time. They found that if all prey are genetically the same, and thus the evolutionary process can be neglected, predator abundance peaked after a peak in prey abundance. After that, prey abundance declined, followed by a decline in predator abundance (Figure 1: top). However, when prey were genetically different, predator abundance peaked at the same time as prey abundance dipped, due to prey adapting to predator abundance (through a change in predator escape ability traits of prey) (Figure 1: bottom); a very different result than what was observed when evolution was halted.

Most studies on eco-evolutionary dynamics have focused on interactions between predators and their prey, like Yoshida and coworkers [4], or between parasites and their hosts. Surprisingly little is known about how eco-evolutionary interactions affect trait dynamics within single populations. Within single populations, it is likely that ecological and evolutionary variables are both the drivers and the objects of change. This means that we can distinguish an ecology-to-evolution pathway and an evolution-to-ecology pathway that together comprise an eco-evolutionary feedback loop (Figure 2).

Discrete alternative phenotypes that occur within single populations present ideal test beds to investigate how eco-evolutionary feedback loops operate. The reason for this is that the alternative phenotypes typically exhibit contrasting growth, reproduction or survival rates so that they are differentially affected by selection (the ecology-to-evolution pathway); in turn, an evolutionary shift in alternative phenotype expression would elicit an ecological response precisely because these alternative phenotypes differ in their demographic rates (the evolution-to-ecology pathway).

Fig2

Figure 2 The ecology-to-evolution pathway and the evolution-to-ecology pathway that comprise a closed, eco-evolutionary feedback loop. If the phenotype expressions of these genotypes have differential effects on survival and reproduction, the evolutionary change will feed back to affect the ecology of the population by affecting population size, density and / or structure in the evolution-to-ecology pathway. Image: Isabel Smallegange

Alternative reproductive tactics (ARTs) are an extreme form of discrete phenotype expression within single populations, and occur across many taxa. An excellent example are the male fighters and scramblers of my favourite study species, the bulb mite (Rhizoglyphus robini). Fighter bulb mites possess weapons for male-male competition over access to mates, whereas scramblers are defenceless. Fighters can also mortally injure conspecifics. This is also what my then Master student Jasper Croll found in 2015 in an experiment where he had observed that fighters are more likely to kill juveniles predisposed to develop into fighters [5]. Jasper next took on the challenge of using a population model to investigate if fighter expression can feed back to affect population size and structure, thereby altering the evolutionary dynamics of ART expression in an eco-evolutionary feedback loop.

Fig3

Image: Isabel Smallegange

Jasper found that the intraspecific killing by fighters can extend the conditions under which ARTs evolve because fighters that kill other fighters decreases fighter fitness. Importantly: this effect can be nullified when benefits from killing are incorporated, like increased reproduction through increased energy uptake. These results from Jasper’s work is now published in the Journal of Animal Ecology [6], and form part of a Special Feature entitled “The diversity of eco-evolutionary dynamics: comparing the feedbacks between ecology and evolution across scales”; a cross-journal special feature from the British Ecological Society, edited by Franziska Brunner, Jacques Deere, Martijn Egas, Christophe Eizaguirre and Joost Raeymaekers.

Are there still aspects of eco-evolutionary feedback loops that we do not understand? Yes! In my view, the next big challenge is to tease apart both pathways within an eco-evolutionary feedback loop. Key factors that are required to do so are (i) a solid understanding of how ecology (e.g. population density) affects trait distributions, (ii) a solid understanding of the developmental mechanism underlying trait expression, and (iii) a solid understanding of how evolutionary change affects ecological variables (e.g. population density).

And how can we use all this knowledge? It should lead to a solid understanding of how an environmental perturbation, such as a change in precipitation, temperature, predation pressure, etc., affects the two pathways of an eco-evolutionary loop: does a perturbation mainly affect ecological variables, with knock-on evolutionary consequences through the ecology-to-evolution pathway, or would it mainly result in an evolutionary shift in trait expression? Or perhaps both are affected simultaneously? These are essential insights to understand the dynamics of the natural world around us, and how they respond to the ever greater changes in the environment.

References

1 Dobzhansky, T. 1973. Nothing in biology makes sense except in the light of evolution. Am. Biol. Teach. 35: 125-129.

2 Grant P, Grant R. 2008. How and Why Species Multiply: The Radiation of Darwin’s Finches. Princeton Univ. Press, Princeton, NJ.

3 Pelletier F, Garant D, Hendry AP. 2009. Eco-evolutionary dynamics. Philos. Trans. R. Soc. B 364: 1483-1489.

4 Yoshida T, Jones LE, Ellner SP, Fussmann GF, Hairston NG Jr. 2003. Rapid evolution drives ecological dynamics in a predator-prey system. Nature 424: 303-306.

5 Smallegange IM, Fernandes RE, Croll JC. 2018. Population consequences of individual heterogeneity in life histories: overcompensation in response to harvesting of alternative reproductive tactics. Oikos 127: 738-749.

6 Croll JC, Egas M, Smallegange IM. Online. An eco-evolutionary feedback loop between population dynamics and fighter expression affects the evolution of alternative reproductive tactics. Journal of Animal Ecology. DOI 10.1111/1365-2656.12899

*A similar version of this post was posted on isabelsmallegange.com.

Urbanization alters predator‐avoidance behaviours

/ Sarah Marley / Leave a comment

Urbanisation is changing the natural landscape at a global scale. This obviously alters habitat structures, but what is the influence on predator-prey dynamics? A recent paper in the Journal of Animal Ecology studied two urban prey species to examine whether urbanisation changed their predator-avoidance behaviour. Lead author Dr Travis Gallo, an Urban Wildlife Postdoctoral Researcher at the Urban Wildlife Institute, Lincoln Park Zoo, tells us more. 

It’s easy to recognize that urban environments are quite different from the rural or natural landscapes ecologists have historically studied. Thus, urban ecologist have long stated that traditional ecological principles should be adjusted or fine-tuned to better fit urban ecosystems. For example, continuously maintained landscapes in cities stabilize primary productivity and reduce the ‘dynamic’ part of the well-studied principles of top-down and bottom-up trophic dynamics. Along those same lines, we became interested in the role that cities and their unique characteristics play in predator-prey dynamics.

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A coyote out in the open in Chicago (Photo: Julie Fuller)

In a study recently published in the Journal of Animal Ecology, we explored predator-avoidance behaviors of two common mammal species – eastern cottontail (Sylvilagus floridanus) and white-tailed deer (Odocoileus virginianus) in the highly urbanized landscape of Chicago, IL USA. Contrary to what one might expect, we found that coyotes (Canis latrans) – a natural predator – had little influence on predator-avoidance behaviors of either species in the more urbanized areas of Chicago.

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White-tailed deer doe and fawn (Photo: Urban Wildlife Institute)

But first let’s step back and offer a little context. Typically, the presence of a predator influences the distribution and behavior of prey species. One might expect that prey, if able, would first and foremost avoid habitat patches that contain predators. But our expectations for this outcome were derived from more natural systems — so how might this relationship change in a city? Habitat patches in urban environments are typically spaced far apart and embedded in a matrix of houses, businesses, and roads. The roads and buildings between habitat patches could restrict an animal’s ability to move between them. As a result, it may be all the more difficult for prey to ‘pack up and move’ if they so happen to encounter a predator. Therefore, we predicted that urban prey might be forced to occupy the same habitat patches as predators. If this were the case, we predicted that prey would change their daily activity schedules or increase their vigilance to avoid interactions with predators. But again, human development and human activity in and around an urban habitat patch might alter a species ability to perform such predator-avoidance behaviors.

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Remotely-triggered wildlife cameras around Chicago allowed a sneak peek into predator-prey dynamics of local wildlife (Photo: Urban Wildlife Institute)

Using photos collected from over 100 remotely triggered wildlife cameras placed across the greater Chicago region, we first assessed whether deer and cottontails were more likely to occupy the same habitat patches as coyotes – or were they avoiding them across the landscape? Additionally, we used the time of day each picture was taken to explore whether deer and cottontails changed their daily activity patterns when coyotes were present within a habitat patch. And finally, in each picture of deer and cottontail we identified whether the individual animal had their head up in a vigilance posture or down in foraging posture, and used that information to assess whether the presence of coyotes increased their rate of vigilance.

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An eastern cottontail displaying vigilance (Photo: Urban Wildlife Institute)

 

Contrary to our prediction – that prey species would likely be constrained to the same habitat patch as coyotes – we found no evidence of spatial aggregation, nor did we find any evidence of spatial avoidance. Both deer and cottontails were spatially distributed independent of where coyotes were present. Additionally, we found that neither species changed their daily activity schedules when coyotes were present. Our most interesting finding was that cottontails had their highest rates of vigilance when coyotes were absent from the most urban sites. Even when coyotes had a low probability of being at a site, cottontails were still on their toes! In Chicago, these highly urban habitat patches (e.g., city parks, golf courses, cemeteries) are often visited by people and in many cases people with their pets (sometimes untethered). While these urban green spaces may provide a refuge from coyote (i.e. a human-shield effect), they likely come with tradeoffs in the form of increased interactions with humans and their pets. As a result, their vigilance rates are high in urban areas even when coyotes are not around. Conversely, as sites became less urban we began to see a shift back to expected vigilance behaviors, and rabbits were more vigilant when coyotes were present in the less urban areas.

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Cemetaries are highly-urban habitat patches, regularly visited by people (Photo: Urban Wildlife Institute)

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As well as people, wildlife also come across pets (Photo: Urban Wildlife Institute)

These results indicate that urban ecosystems are still fear driven systems, but perhaps, the fear inducing agents are now anthropogenic in nature. Traditionally we think of predator-prey dynamics in the context of two interactions – predators and prey. But in urban ecosystems we must begin to think of it as a three-player game – predators, prey, and people. Thus, we should begin to explicitly consider people in our ecological equations – especially in urban ecosystems. Doing so will improve our predictions, advance our understanding of urban ecology, and increase our ability to conserve biodiversity on an urbanizing planet.

More Info:

Gallo et al. (2019) Urbanization alters predator‐avoidance behaviours. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.12967