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22 May 2019
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Sex makes them sleepy: host reproductive status induces diapause in a parasitoid population experiencing harsh winters

The response of interacting species to biotic seasonal cues

Recommended by and based on reviews by Anne Duplouy and 1 anonymous reviewer

In temperate regions, food abundance and quality vary greatly throughout the year, and the ability of organisms to synchronise their phenology to these changes is a key determinant of their reproductive success. Successful synchronisation requires that cues are perceived prior to change, leaving time for physiological adjustments.
But what are the cues used to anticipate seasonal changes? Abiotic factors like temperature and photoperiod are known for their driving role in the phenology of a wide range of plant an animal species [1,2] . Arguably though, biotic cues directly linked to upcoming changes in food abundance could be as important as abiotic factors, but the response of organisms to these cues remains relatively unexplored.
Biotic cues may be particularly important for higher trophic levels because of their tight interaction with the hosts or preys they depend on. In this study Tougeron and colleagues [3] address this topic using interacting insects, namely herbivorous aphids and the parasitic wasps (or parasitoids) that feed on them. The key finding of the study by Tougeron et al. [3] is that the host morph in which parasitic wasp larvae develop is a major driver of diapause induction. More importantly, the aphid morph that triggers diapause in the wasp is the one that will lay overwintering eggs in autumn at the onset of harsh winter conditions. Its neatly designed experimental setup also provides evidence that this response may vary across populations as host-dependent diapause induction was only observed in a wasp population that originated from a cold area. As the authors suggests, this may be caused by local adaptation to environmental conditions because, relative to warmer regions, missing the time window to enter diapause in colder regions may have more dramatic consequences. The study also shows that different aphid morphs differ greatly in their chemical composition, and points to particular types of metabolites like sugars and polyols as specific cues for diapause induction.
This study provides a nice example of the complexity of biological interactions, and of the importance of phenological synchrony between parasites and their hosts. The authors provide evidence that phenological synchrony is likely to be achieved via chemical cues derived from the host. A similar approach was used to demonstrate that the herbivorous beetle Leptinotarsa decemlineata uses plant chemical cues to enter diapause [4]. Beetles fed on plants exposed to pre-wintering conditions entered diapause in higher proportions than those fed on control plants grown at normal conditions. As done by Tougeron et al. [3], in [4] the authors associated diapause induction to changes in the composition of metabolites in the plant. In both studies, however, the missing piece is to unveil the particular chemical involved, an answer that may be provided by future experiments.
Latitudinal clines in diapause induction have been described in a number of insect species [5]. Correlative studies, in which the phenology of different trophic levels has been monitored, suggest that these clines may in part be governed by lower trophic levels. For example, Phillimore et al. [6] explored the relative contribution of temperature and of host plant phenology on adult flight periods of the butterfly Anthocharis cardamines. Tougeron et al. [3], by using aphids and their associated parasitoids, take the field further by moving from observational studies to experiments. Besides, aphids are not only a tractable host-parasite system in the laboratory, they are important agricultural pests. Improving our basic knowledge of their ecological interactions may ultimately contribute to improving pest control techniques. The study by Tougeron et al. [3] exemplifies the multiple benefits that can be gained from addressing fundamental questions in species that are also directly relevant to society.

References

[1] Tauber, M. J., Tauber, C. A., and Masaki, S. (1986). Seasonal Adaptations of Insects. Oxford, New York: Oxford University Press.
[2] Bradshaw, W. E., and Holzapfel, C. M. (2007). Evolution of Animal Photoperiodism. Annual Review of Ecology, Evolution, and Systematics, 38(1), 1–25. doi: 10.1146/annurev.ecolsys.37.091305.110115
[3] Tougeron, K., Brodeur, J., Baaren, J. van, Renault, D., and Lann, C. L. (2019b). Sex makes them sleepy: host reproductive status induces diapause in a parasitoid population experiencing harsh winters. bioRxiv, 371385, ver. 6 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/371385
[4] Izzo, V. M., Armstrong, J., Hawthorne, D., and Chen, Y. (2014). Time of the season: the effect of host photoperiodism on diapause induction in an insect herbivore, Leptinotarsa decemlineata. Ecological Entomology, 39(1), 75–82. doi: 10.1111/een.12066
[5] Hut Roelof A., Paolucci Silvia, Dor Roi, Kyriacou Charalambos P., and Daan Serge. (2013). Latitudinal clines: an evolutionary view on biological rhythms. Proceedings of the Royal Society B: Biological Sciences, 280(1765), 20130433. doi: 10.1098/rspb.2013.0433
[6] Phillimore, A. B., Stålhandske, S., Smithers, R. J., and Bernard, R. (2012). Dissecting the Contributions of Plasticity and Local Adaptation to the Phenology of a Butterfly and Its Host Plants. The American Naturalist, 180(5), 655–670. doi: 10.1086/667893

Sex makes them sleepy: host reproductive status induces diapause in a parasitoid population experiencing harsh wintersTougeron K., Brodeur J., van Baaren J., Renault D. and Le Lann C.<p>When organisms coevolve, any change in one species can induce phenotypic changes in traits and ecology of the other species. The role such interactions play in ecosystems is central, but their mechanistic bases remain underexplored. Upper troph...Coexistence, Evolutionary ecology, Experimental ecology, Host-parasite interactions, PhysiologyAdele Mennerat2018-07-18 18:51:03 View
08 Jan 2020
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Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits

Nitrate or not nitrate. That is the question

Recommended by based on reviews by Vincent Maire and 1 anonymous reviewer

The article by Legay et al. [1] addresses two main issues: the links between belowground and aboveground plant traits and the links between plant strategies (as defined by these traits) and the capacity to absorb nitrate and ammonium. I recommend this work because these are important and current issues. The literature on plant traits is extremely rich and the existence of a leaf economic spectrum linked to a gradient between conservative and acquisitive plants is now extremely well established [2-3]. Many teams are now working on belowground traits and possible links with the aboveground gradients [4-5]. It seems indeed that there is a root economic spectrum but this spectrum is apparently less pronounced than the leaf economic spectrum. The existence of links between the two spectrums are still controversial and are likely not universal as suggested by discrepant results and after all a plant could have a conservative strategy aboveground and an acquisitive strategy belowground (or vice-versa) because, indeed, constraints are different belowground and aboveground (for example because in given ecosystem/vegetation type light may be abundant but not water or mineral nutrients). The various results obtained also suggest that we do not full understand the diversity of belowground strategies, what is at stake with these strategies, and the links with root characteristics.
Each time I give a conference on the work we are carrying out on African grasses that likely absorb ammonium preferentially because they inhibit nitrification [6-7], somebody asks me a question about the fact that plant essentially absorb nitrate because ammonium is toxic and nitrate more available in the soil. The present article confirms that this is not the case and that, though there are currently some teams working on the subject, we do not really know for the moment whether plants absorb nitrate or ammonium, in which proportion, how plastic this proportion is within individuals and within species. This subject seems to me crucial because it is linked to (1) the capacity of ecosystems to conserve nitrogen [8], because nitrate, much more than ammonium, goes out of ecosystems through leaching and denitrification, (2) to carbon cycling and plant energy budget because absorbing nitrate requires spending mucho more energy than absorbing ammonium because nitrate must be reduced before being incorporated in plant biomass, which is very energy costly. These two issues are naturally very relevant to develop efficient cropping systems in terms of carbon and nitrogen.
Interestingly, the present article, comparing three grass species in different sites, suggests that there is no trade-off between the absorption of nitrate and ammonium: more acquisitive individuals tend to absorb more ammonium and nitrate. This is contrary to hypotheses we made to predict the outcome of competition between plants absorbing nitrate and ammonium in different proportions [9] but should be tested in the future comparing many different types of plants. The results also suggest that more conservative plants absorb relatively more ammonium, which makes sense because this allows them to spare the energy necessary to reduce nitrate. This leads to the question of the effect of these strategies on nitrogen retention within the ecosystem. If nitrification is high (low), absorbing ammonium is not efficient and likely leads to high (low) nitrogen losses. This should be tested in the future. Moreover, the authors have measured the absorption of nitrate and ammonium through measurements at the root scale on cut roots. This should be complemented by measurements at the whole plant scale.

References

[1] Legay, N., Grassein, F., Arnoldi, C., Segura, R., Laîné, P., Lavorel, S. and Clément, J.-C. (2020). Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits. bioRxiv, 372235, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/372235
[2] Shipley, B., Lechowicz, M.J., Wright, I. & Reich, P.B. (2006) Fundamental trade-offs generating the worldwide leaf economics spectrum. Ecology, 87, 535-541. doi: 10.1890/05-1051
[3] Reich, P.B. (2014) The world-wide ‘fast-slow’ plant economics spectrum: a traits manifesto. J. Ecol., 102, 275-301. doi: 10.1111/1365-2745.12211
[4] Maire, V., Gross, N., Pontes, L.D.S., Picon-Cochard, C. & Soussana, J.F. (2009) Trade-off between root nitrogen acquisition and shoot nitrogen utilization across 13 co-occurring pasture grass species. Func. Ecol., 23, 668-679. doi: 10.1111/j.1365-2435.2009.01557.x
[5] Roumet, C., Birouste, M., Picon-Cochard, C., Ghestem, M., Osman, N., Vrignon-Brenas, S., Cao, K.F. & Stokes, A. (2016) Root structure-function relationships in 74 species: evidence of a root economics spectrum related to carbon economy. New. Phytol., 210, 815-826. doi: 10.1111/nph.13828
[6] Lata, J.-C., Degrange, V., Raynaud, X., Maron, P.-A., Lensi, R. & Abbadie, L. (2004) Grass populations control nitrification in savanna soils. Funct. Ecol., 18, 605-611. doi: 10.1111/j.0269-8463.2004.00880.x
[7] Srikanthasamy, T., Leloup, J., N’Dri, A.B., Barot, S., Gervaix, J., Koné, A.W., Koffi, K.F., Le Roux, X., Raynaud, X. & Lata, J.-C. (2018) Contrasting effects of grasses and trees on microbial N-cycling in an African humid savanna. Soil Biol. Biochem., 117, 153-163. doi: 10.1016/j.soilbio.2017.11.016
[8] Boudsocq, S., Lata, J.C., Mathieu, J., Abbadie, L. & Barot, S. (2009) Modelling approach to analyze the effects of nitrification inhibition on primary production. Func. Ecol., 23, 220-230. doi: 10.1111/j.1365-2435.2008.01476.x
[9] Boudsocq, S., Niboyet, A., Lata, J.-C., Raynaud, X., Loeuille, N., Mathieu, J., Blouin, M., Abbadie, L. & Barot, S. (2012) Plant preference for ammonium versus nitrate: a neglected determinant of ecosystem functioning? Am. Nat., 180, 60-69. doi: 10.1086/665997

Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traitsLegay Nicolas, Grassein Fabrice, Arnoldi Cindy, Segura Raphaël, Laîné Philippe, Lavorel Sandra, Clément Jean-Christophe<p>The leaf economics spectrum (LES) is based on a suite of leaf traits related to plant functioning and ranges from resource-conservative to resource-acquisitive strategies. However, the relationships with root traits, and the associated belowgro...Community ecology, Physiology, Terrestrial ecologySébastien Barot2018-07-19 14:22:28 View
25 Oct 2021
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The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakes

The difficult interpretation of species co-distribution

Recommended by based on reviews by Anthony Maire and Emilie Macke

Ecology is the study of the distribution of organisms in space and time and their interactions. As such, there is a tradition of studies relating abiotic environmental conditions to species distribution, while another one is concerned by the effects of consumers on the abundance of their resources.  Interestingly, joining the dots appears more difficult than it would suggest: eluding the effect of species interactions on distribution remains one of the greatest challenges to elucidate nowadays (Kissling et al. 2012). Theory suggests that yes, species interactions such as predation and competition should influence range limits (Godsoe et al. 2017), but the common intuition among many biogeographers remains that over large areas such as regions and continents, environmental drivers like temperature and precipitation overwhelm their local effects. Answering this question is of primary importance in the context where species are moving around with climate warming.  Inconsistencies in food web structure may arise with asynchronized movements of consumers and their resources, leading to a major disruption in regulation and potentially ecosystem functioning. Solving this problem, however, remains very challenging because we have to rely on observational data since experiments are hard to perform at the biogeographical scale. 

The study of St-Gelais is an interesting step forward to solve this problem. Their main objective was to assess the strength of the association between phytoplankton and zooplankton communities at a large spatial scale, looking at the spatial covariation of both taxonomic and functional composition. To do so, they undertook a massive survey of more than 100 lakes across three regions of the boreal region of Québec. Species and functional composition were recorded, along with a set of abiotic variables. Classic community ecology at this point. The difficulty they faced was to disentangle the multiple causal relationships involved in the distribution of both trophic levels. Teasing apart bottom-up and top-down forces driving the assembly of plankton communities using observational data is not an easy task. On the one hand, both trophic levels could respond to variations in temperature, nutrient availability and dissolved organic carbon. The interpretation is fairly straightforward if the two levels respond to different factors, but the situation is much more complicated when they do respond similarly. There are potentially three possible underlying scenarios. First, the phyto and zooplankton communities may share the same environmental requirements, thereby generating a joint distribution over gradients such as temperature and nutrient availability. Second, the abiotic environment could drive the distribution of the phytoplankton community, which would then propagate up and influence the distribution of the zooplankton community. Alternatively, the abiotic environment could constrain the distribution of the zooplankton, which could then affect the one of phytoplankton. In addition to all of these factors, St-Gelais et al also consider that dispersal may limit the distribution, well aware of previous studies documenting stronger dispersal limitations for zooplankton communities. 

Unfortunately, there is not a single statistical approach that could be taken from the shelf and used to elucidate drivers of co-distribution. Joint species distribution was once envisioned as a major step forward in this direction (Warton et al. 2015), but there are several limits preventing the direct interpretation that co-occurrence is linked to interactions (Blanchet et al. 2020). Rather, St-Gelais used a variety of multivariate statistics to reveal the structure in their observational data. First, using a Procrustes analysis (a method testing if the spatial variation of one community is correlated to the structure of another community), they found a significant correlation between phytoplankton and zooplankton communities, indicating a taxonomic coupling between the groups. Interestingly, this observation was maintained for functional composition only when interaction-related traits were considered. At this point, these results strongly suggest that interactions are involved in the correlation, but it's hard to decipher between bottom-up and top-down perspectives. A complementary analysis performed with a constrained ordination, per trophic level, provided complementary pieces of information. First observation was that only functional variation was found to be related to the different environmental variables, not taxonomic variation. Despite that trophic levels responded to water quality variables, spatial autocorrelation was more important for zooplankton communities and the two layers appear to respond to different variables. 

It is impossible with those results to formulate a strong conclusion about whether grazing influence the co-distribution of phytoplankton and zooplankton communities. That's the mere nature of observational data. While there is a strong spatial association between them, there are also diverging responses to the different environmental variables considered. But the contrast between taxonomic and functional composition is nonetheless informative and it seems that beyond the idiosyncrasies of species composition, trait distribution may be more informative and general. Perhaps the most original contribution of this study is the hierarchical approach to analyze the data, combined with the simultaneous analysis of taxonomic and functional distributions. Having access to a vast catalog of multivariate statistical techniques, a careful selection of analyses helps revealing key features in the data, rejecting some hypotheses and accepting others. Hopefully, we will see more and more of such multi-trophic approaches to distribution because it is now clear that the factors driving distribution are much more complicated than anticipated in more traditional analyses of community data. Biodiversity is more than a species list, it is also all of the interactions between them, influencing their distribution and abundance (Jordano 2016).

References

Blanchet FG, Cazelles K, Gravel D (2020) Co-occurrence is not evidence of ecological interactions. Ecology Letters, 23, 1050–1063. https://doi.org/10.1111/ele.13525

Godsoe W, Jankowski J, Holt RD, Gravel D (2017) Integrating Biogeography with Contemporary Niche Theory. Trends in Ecology & Evolution, 32, 488–499. https://doi.org/10.1016/j.tree.2017.03.008

Jordano P (2016) Chasing Ecological Interactions. PLOS Biology, 14, e1002559. https://doi.org/10.1371/journal.pbio.1002559

Kissling WD, Dormann CF, Groeneveld J, Hickler T, Kühn I, McInerny GJ, Montoya JM, Römermann C, Schiffers K, Schurr FM, Singer A, Svenning J-C, Zimmermann NE, O’Hara RB (2012) Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents. Journal of Biogeography, 39, 2163–2178. https://doi.org/10.1111/j.1365-2699.2011.02663.x

St-Gelais NF, Vogt RJ, Giorgio PA del, Beisner BE (2021) The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakes. bioRxiv, 373332, ver. 4 peer-reviewed and recommended by Peer community in Ecology. https://doi.org/10.1101/373332

Warton DI, Blanchet FG, O’Hara RB, Ovaskainen O, Taskinen S, Walker SC, Hui FKC (2015) So Many Variables: Joint Modeling in Community Ecology. Trends in Ecology & Evolution, 30, 766–779. https://doi.org/10.1016/j.tree.2015.09.007

Wisz MS, Pottier J, Kissling WD, Pellissier L, Lenoir J, Damgaard CF, Dormann CF, Forchhammer MC, Grytnes J-A, Guisan A, Heikkinen RK, Høye TT, Kühn I, Luoto M, Maiorano L, Nilsson M-C, Normand S, Öckinger E, Schmidt NM, Termansen M, Timmermann A, Wardle DA, Aastrup P, Svenning J-C (2013) The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling. Biological Reviews, 88, 15–30. https://doi.org/10.1111/j.1469-185X.2012.00235.x

The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakesNicolas F St-Gelais, Richard J Vogt, Paul A del Giorgio, Beatrix E Beisner<p>Strong trophic interactions link primary producers (phytoplankton) and consumers (zooplankton) in lakes. However, the influence of such interactions on the biogeographical distribution of the &nbsp;taxa and functional traits of planktonic organ...Biogeography, Community ecology, Species distributionsDominique Gravel2018-07-24 15:01:51 View
10 Jan 2019
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Inferring macro-ecological patterns from local species' occurrences

Upscaling the neighborhood: how to get species diversity, abundance and range distributions from local presence/absence data

Recommended by ORCID_LOGO based on reviews by Kevin Cazelles and 1 anonymous reviewer

How do you estimate the biodiversity of a whole community, or the distribution of abundances and ranges of its species, from presence/absence data in scattered samples?
It all starts with the collector's dilemma: if you double the number of samples, you will not get double the number of species, since you will find many of the same common species, and only a few new rare ones.
This non-additivity has prompted many ecologists to study the Species-Area Relationship. A common theoretical approach has been to connect this spatial pattern to the overall distribution of how common or rare a species can be. At least since Fisher's celebrated log-series [1], ecologists have been trying to, first, infer the shape of the Species Abundance Distribution, and then, use it to predict how many species should be found in a given area or a given number of samples. This has found many applications, from microbial communities to tropical forests, from estimating the number of yet-unknown species to predicting how much biodiversity may be lost if a fraction of the habitat is removed.
In this elegant work, Tovo et al. [2] propose a method that starts only from presence/absence data over a number of samples, and provides the community's diversity, as well as its abundance and range size distributions. This method is simple, analytically explicit, and accurate: the authors test it on the classic Pasoh and Barro Colorado Island tropical forest datasets, and on simulated data. They make a very laudable effort in both explaining its theoretical underpinnings, and proposing a straightforward step-by-step guide to applying it to data.
The core of Tovo et al's method is a simple property: the scale invariance of the Negative Binomial (NB) distribution. Subsampling from a NB gives another NB, where a single parameter has changed. Therefore, if the Species Abundance Distribution is close enough to some NB (which is flexible enough to accommodate all the data here), we can estimate how this parameter changes when going from (1) a single sample to (2) all the available samples, and from there, extrapolate to (3) the entire community.
This principle was first applied by the authors in a previous study [3] that required abundance data in the samples, rather than just presence/absence. Given that binary occurrence data is far more available in a variety of empirical settings, this extension is worthwhile (including its new predictions on range size distributions), and it deserves to be widely known and tested.

ADDITIONAL COMMENTS

1) To explain the novelty of the authors' contribution, it is useful to look at competing techniques.
Some ""parametric"" approaches try to infer the whole-community Species Abundance Distribution (SAD) by guessing its functional form (Gaussian, power-law, log-series...) and fitting its parameters from sampled data. The issue is that this distribution shape may not remain in the same family as we increase the sampling effort or area, so the regression problem may not be well-defined. This is where the Negative Binomial's scale invariance is useful.
Other ""non-parametric"" approaches have renounced guessing the whole SAD: they simply try to approximate of its tail of rare species, by looking at how many species are found in only one (or a few) samples. From this, they derive an estimate of biodiversity that is agnostic to the rest of the SAD. Tovo et al. [2] show the issue with these approaches: they extrapolate from the properties of individual samples to the whole community, but do not properly account for the bias introduced by the amount of sampling (the intermediate scale (2) in the summary above).

2) The main condition for all such approaches to work is well-mixedness: each sample should be sufficiently like a lot drawn from the same skewed lottery. As long as that condition applies, finding the best approach is a theoretical matter of probabilities and combinatorics that may, in time, be given a definite answer.
The authors also show that ""well-mixed"" is not as restrictive as it sounds: the method works both on real data (which is never perfectly mixed) and on simulations where species are even more spatially clustered than the empirical data. In addition, the Negative Binomial's scale invariance entails that, if it works well enough at some spatial scale, it will also work at all higher scales (until one reaches the edges of the sufficiently-well-mixed community)

3) One may ask: why the Negative Binomial as a Species Abundance Distribution?
If one wishes for some dynamical explanation, the Negative Binomial can be derived from neutral birth and death process with immigration, as shown by the authors in [3]. But to be applied to data, it should only be able to approximate the empirical distribution well enough (at all relevant scales). Depending on one's taste, this type of probabilistic approaches can be interpreted as:
- purely phenomenological, describing only the observational process of sampling from an existing state of affairs, not the ecological processes that gave rise to that state.
- a null model, from which everything in practice is expected to deviate to some extent.
- or a way to capture the statistical forces that tend to induce stable relationships between different patterns (as long as no ecological process opposes them strongly enough).

References

[1] Fisher, R. A., Corbet, A. S., & Williams, C. B. (1943). The relation between the number of species and the number of individuals in a random sample of an animal population. The Journal of Animal Ecology, 42-58. doi: 10.2307/1411
[2] Tovo, A., Formentin, M., Suweis, S., Stivanello, S., Azaele, S., & Maritan, A. (2019). Inferring macro-ecological patterns from local species' occurrences. bioRxiv, 387456, ver. 2 peer-reviewed and recommended by PCI Ecol. doi: 10.1101/387456
[3] Tovo, A., Suweis, S., Formentin, M., Favretti, M., Volkov, I., Banavar, J. R., Azaele, S., & Maritan, A. (2017). Upscaling species richness and abundances in tropical forests. Science Advances, 3(10), e1701438. doi: 10.1126/sciadv.1701438

Inferring macro-ecological patterns from local species' occurrencesAnna Tovo, Marco Formentin, Samir Suweis, Samuele Stivanello, Sandro Azaele, Amos Maritan<p>Biodiversity provides support for life, vital provisions, regulating services and has positive cultural impacts. It is therefore important to have accurate methods to measure biodiversity, in order to safeguard it when we discover it to be thre...Macroecology, Species distributions, Statistical ecology, Theoretical ecologyMatthieu Barbier2018-08-09 16:44:09 View
31 Jan 2019
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Do the more flexible individuals rely more on causal cognition? Observation versus intervention in causal inference in great-tailed grackles

From cognition to range dynamics: advancing our understanding of macroecological patterns

Recommended by based on reviews by 2 anonymous reviewers

Understanding the distribution of species on earth is one of the fundamental challenges in ecology and evolution. For a long time, this challenge has mainly been addressed from a correlative point of view with a focus on abiotic factors determining a species abiotic niche (classical bioenvelope models; [1]). It is only recently that researchers have realized that behaviour and especially plasticity in behaviour may play a central role in determining species ranges and their dynamics [e.g., 2-5]. Blaisdell et al. propose to take this even one step further and to analyse how behavioural flexibility and possibly associated causal cognition impacts range dynamics.
The current preregistration is integrated in an ambitious long-term research plan that aims at addressing the above outlined question and focuses specifically on investigating whether more behaviourally flexible individuals are better at deriving causal inferences. The model system the authors plan on using are Great-tailed Grackles which have expanded their range into North America during the last century. The preregistration by Blaisdell et al. is a great example of the future of scientific research: it includes conceptual models, alternative hypotheses and testable predictions along with a sound sampling and analysis plan and embraces the principles of Open Science. Overall, the research the authors propose is fascinating and of highest relevance, as it aims at bridging scales from the microscopic mechanisms that underlie animal behaviour to macroscopic, macroecological consequences (see also [3]). I am very much looking forward to the results the authors will report.

References
[1] Elith, J. & Leathwick, J. R. 2009. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 40: 677-697. doi: 10.1146/annurev.ecolsys.110308.120159
[2] Kubisch, A.; Degen, T.; Hovestadt, T. & Poethke, H. J. (2013) Predicting range shifts under global change: the balance between local adaptation and dispersal. Ecography 36: 873-882. doi: 10.1111/j.1600-0587.2012.00062.x
[3] Keith, S. A. & Bull, J. W. (2017) Animal culture impacts species' capacity to realise climate-driven range shifts. Ecography, 40: 296-304. doi: 10.1111/ecog.02481
[4] Sullivan, L. L.; Li, B.; Miller, T. E.; Neubert, M. G. & Shaw, A. K. (2017) Density dependence in demography and dispersal generates fluctuating invasion speeds. Proc. Natl. Acad. Sci. USA, 114: 5053-5058. doi: 10.1073/pnas.1618744114
[5] Fronhofer, E. A.; Nitsche, N. & Altermatt, F. (2017) Information use shapes the dynamics of range expansions into environmental gradients. Glob. Ecol. Biogeogr. 26: 400-411. doi: 10.1111/geb.12547

Do the more flexible individuals rely more on causal cognition? Observation versus intervention in causal inference in great-tailed gracklesAaron Blaisdell, Zoe Johnson-Ulrich, Luisa Bergeron, Carolyn Rowney, Benjamin Seitz, Kelsey McCune, Corina LoganThis PREREGISTRATION has undergone one round of peer reviews. We have now revised the preregistration and addressed reviewer comments. The DOI was issued by OSF and refers to the whole GitHub repository, which contains multiple files. The specific...Behaviour & Ethology, Preregistrations, ZoologyEmanuel A. Fronhofer2018-08-20 11:09:48 View
04 Sep 2019
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Gene expression plasticity and frontloading promote thermotolerance in Pocillopora corals

Transcriptomics of thermal stress response in corals

Recommended by based on reviews by Mar Sobral

Climate change presents a challenge to many life forms and the resulting loss of biodiversity will critically depend on the ability of organisms to timely respond to a changing environment. Shifts in ecological parameters have repeatedly been attributed to global warming, with the effectiveness of these responses varying among species [1, 2]. Organisms do not only have to face a global increase in mean temperatures, but a complex interplay with another crucial but largely understudied aspect of climate change: thermal fluctuations. Understanding the mechanisms underlying adaptation to thermal fluctuations is thus a timely and critical challenge.
Coral reefs are among the most threaten ecosystems in the context of current global changes [3]. Brener-Raffalli and colleagues [4] provided a very complete study digging into the physiological, symbiont-based and transcriptomic mechanisms underlying response of corals to temperature changes. They used an experimental approach, following the heat stress response of coral colonies from different species of the genus Pocillopora. While the symbiont community composition did not significantly change facing exposure to warmer temperatures, the authors provided evidence for transcriptomic changes especially linked to stress response genes that may underlie plastic responses to heat stress.
The authors furthermore investigated the thermal stress response of corals originating from two sites differing in their natural thermal regimes, and found that they differ in the extent and nature of plastic response, including the expression of gene regulation factors and the basal expression level of some genes. These two sites also differ in a variety of aspects, including the focal coral species, which precludes from concluding about the role of thermal regime adaptation into the differences observed. However, these results still highlight a very interesting and important direction deserving further investigation [5], and point out the importance of variability in thermal stress response among localities [6] that might potentially mediate global warming consequences on coral reefs.

References

[1] Parmesan, C., & Yohe, G. (2003). A globally coherent fingerprint of climate change impacts across natural systems. Nature, 421(6918), 37–42. doi: 10.1038/nature01286
[2] Menzel, A., Sparks, T. H., Estrella, N., Koch, E., Aasa, A., Ahas, R., … Zust, A. (2006). European phenological response to climate change matches the warming pattern. Global Change Biology, 12(10), 1969–1976. doi: 10.1111/j.1365-2486.2006.01193.x
[3] Bellwood, D. R., Hughes, T. P., Folke, C., & Nyström, M. (2004). Confronting the coral reef crisis. Nature, 429(6994), 827–833. doi: 10.1038/nature02691
[4] Brener-Raffalli, K., Vidal-Dupiol, J., Adjeroud, M., Rey, O., Romans, P., Bonhomme, F., Pratlong, M., Haguenauer, A., Pillot, R., Feuillassier, L., Claereboudt, M., Magalon, H., Gélin, P., Pontarotti, P., Aurelle, D., Mitta, G. and Toulza, E. (2019). Gene expression plasticity and frontloading promote thermotolerance in Pocillopora corals. BioRxiv, 398602, ver 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/398602
[5] Kenkel, Carly D., and Matz, M. V. (2017). Gene expression plasticity as a mechanism of coral adaptation to a variable environment. Nature Ecology and Evolution, 1(1), 0014. doi: 10.1038/s41559-016-0014
[6] Kenkel, C. D., Meyer, E., and Matz, M. V. (2013). Gene expression under chronic heat stress in populations of the mustard hill coral (Porites astreoides) from different thermal environments. Molecular Ecology, 22(16), 4322–4334. doi: 10.1111/mec.12390

Gene expression plasticity and frontloading promote thermotolerance in Pocillopora coralsK. Brener-Raffalli, J. Vidal-Dupiol, M. Adjeroud, O. Rey, P. Romans, F. Bonhomme, M. Pratlong, A. Haguenauer, R. Pillot, L. Feuillassier, M. Claereboudt, H. Magalon, P. Gélin, P. Pontarotti, D. Aurelle, G. Mitta, E. Toulza<p>Ecosystems worldwide are suffering from climate change. Coral reef ecosystems are globally threatened by increasing sea surface temperatures. However, gene expression plasticity provides the potential for organisms to respond rapidly and effect...Climate change, Evolutionary ecology, Marine ecology, Molecular ecology, Phenotypic plasticity, SymbiosisStaffan Jacob2018-08-29 10:46:55 View
14 May 2019
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Field assessment of precocious maturation in salmon parr using ultrasound imaging

OB-GYN for salmon parrs

Recommended by ORCID_LOGO based on reviews by Hervé CAPRA and 1 anonymous reviewer

Population dynamics and stock assessment models are only as good as the data used to parameterise them. For Atlantic salmon (Salmo salar) populations, a critical parameter may be frequency of precocious maturation. Indeed, the young males (parrs) that mature early, before leaving the river to reach the ocean, can contribute to reproduction but have much lower survival rates afterwards. The authors cite evidence of the potentially major consequences of this alternate reproductive strategy. So, to be parameterised correctly, it needs to be assessed correctly. Cue the ultrasound machine.

Through a thorough analysis of data collected on 850 individuals [1], over three years, the authors clearly show that the non-invasive examination of the internal cavity of young fishes to look for gonads, using a portable ultrasound machine, provides reliable and replicable evidence of precocious maturation. They turned into OB-GYN for salmons (albeit for male salmons!) and it worked. While using ultrasounds to detect fish gonads is not a new idea (early attempts for salmonids date back to the 80s [2]), the value here is in the comparison with the classic visual inspection technique (which turns out to be less reliable) and the fact that ultrasounds can now easily be carried out in the field.

Beyond the potentially important consequences of this new technique for the correct assessment of salmon population dynamics, the authors also make the case for the acquisition of more reliable individual-level data in ecological studies, which I applaud.

References.

[1] Nevoux M, Marchand F, Forget G, Huteau D, Tremblay J, and Destouches J-P. (2019). Field assessment of precocious maturation in salmon parr using ultrasound imaging. bioRxiv 425561, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/425561
[2] Reimers E, Landmark P, Sorsdal T, Bohmer E, Solum T. (1987). Determination of salmonids’ sex, maturation and size: an ultrasound and photocell approach. Aquaculture Magazine.13:41-44.

Field assessment of precocious maturation in salmon parr using ultrasound imagingMarie Nevoux, Frédéric Marchand, Guillaume Forget, Dominique Huteau, Julien Tremblay, Jean-Pierre Destouches<p>Salmonids are characterized by a large diversity of life histories, but their study is often limited by the imperfect observation of the true state of an individual in the wild. Challenged by the need to reduce uncertainty of empirical data, re...Conservation biology, Demography, Experimental ecology, Freshwater ecology, Life history, Phenotypic plasticity, Population ecologyJean-Olivier Irisson2018-09-25 17:24:59 View
26 Mar 2019
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Is behavioral flexibility linked with exploration, but not boldness, persistence, or motor diversity?

Probing behaviors correlated with behavioral flexibility

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

Behavioral plasticity, which is a subset of phenotypic plasticity, is an important component of foraging, defense against predators, mating, and many other behaviors. More specifically, behavioral flexibility, in this study, captures how quickly individuals adapt to new circumstances. In cases where individuals disperse to new environments, which often occurs in range expansions, behavioral flexibility is likely crucial to the chance that individuals can establish in these environments. Thus, it is important to understand how best to measure behavioral flexibility and how measures of such flexibility might vary across individuals and behavioral contexts and with other measures of learning and problem solving.
In this preregistration, Logan and colleagues propose to use a long-term study of the great-tailed grackle to measure how much they can manipulate behavioral flexibility in a reversal learning task, how much behavioral flexibility in one task predicts flexibility in another task and in problem solving a new task, and how robust these patterns are within individuals and across tasks. Logan and colleagues lay out their hypotheses and predictions for each experiment in a clear and concise manner. They also are very clear about the details of their study system, such as how they determined the number of trials they use in their learning reversal experiments, and how those details have influenced their experimental design. Further, given that the preregistration uses RMarkdown and is stored on GitHub (as are other studies in the larger project), their statistical code and its history of modification are easily available. This is a crucial component of making research more reproducible, which is a recent emphasis in behavioral sciences more broadly.
Reviewers of this preregistration found the study of substantial merit. The authors have responded to the reviewers' comments and their revisions have made the preregistration much clearer and cogent. I am happy to recommend this preregistration.

Is behavioral flexibility linked with exploration, but not boldness, persistence, or motor diversity?Kelsey McCune, Carolyn Rowney, Luisa Bergeron, Corina LoganThis is a PREREGISTRATION. The DOI was issued by OSF and refers to the whole GitHub repository, which contains multiple files. The specific file we are submitting is g_exploration.Rmd, which is easily accessible at GitHub at https://github.com/cor...Behaviour & Ethology, Preregistrations, ZoologyJeremy Van Cleve2018-09-27 03:35:12 View
01 Apr 2019
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The inherent multidimensionality of temporal variability: How common and rare species shape stability patterns

Diversity-Stability and the Structure of Perturbations

Recommended by ORCID_LOGO and based on reviews by Frederic Barraquand and 1 anonymous reviewer

In his 1972 paper “Will a Large Complex System Be Stable?” [1], May challenges the idea that large communities are more stable than small ones. This was the beginning of a fundamental debate that still structures an entire research area in ecology: the diversity-stability debate [2]. The most salient strength of May’s work was to use a mathematical argument to refute an idea based on the observations that simple communities are less stable than large ones. Using the formalism of dynamical systems and a major results on the distribution of the eigen values for random matrices, May demonstrated that the addition of random interactions destabilizes ecological communities and thus, rich communities with a higher number of interactions should be less stable. But May also noted that his mathematical argument holds true only if ecological interactions are randomly distributed and thus concluded that this must not be true! This is how the contradiction between mathematics and empirical observations led to new developments in the study of ecological networks.
Since 1972, the theoretical corpus of ecology has advanced, building on the formalism of dynamical systems, ecologists have revealed that ecological interactions are indeed not randomly distributed [3,4], but general rules are still missing and we are far from understanding what determine the exact network topology of a given community. One promising avenue is to understand the relationship between different facets of the concept of stability [5,6]. Indeed, the classical approach to determine whether a system is stable is qualitative: if a system returns to its equilibrium when it is slightly moved away from it, then the system is considered stable. But there are several other aspects that are worth scrutinizing. For instance, when a system returns to its equilibrium, one can characterize the corresponding transient dynamics [7,8], that is asking fundamental questions such as: what is the trajectory of return? How long does it take to return to the equilibrium? Another fundamental question is whether the system remains qualitatively stable when the distributions of interactions strengths change? From a biological standpoint, all of these questions matter as all these aspects of stability may partially explain the actual structure of ecological networks, and hence, frameworks that integrate several facets of stability are much needed.
The study by Arnoldi et al. [9] is a significant step towards such a framework. The strength of their formalism is threefold. First, instead of considering separately the system and its perturbations, they considering the fluctuations of a perturbed ecological systems and thus, perturbations are parts of the ecological system. Second, they use of a broad definition of perturbation that encompasses the types of perturbations (whether the individual respond synchronously or not), their intensity and their direction (how the perturbations are correlated across species). Third, they quantify the instability of the system using variability which integrates the consequences of perturbations over the whole set of species of a community: such a measure is comparable across communities and accounts for the trivial effect of the perturbations on the system dynamics.
Using this framework, the authors show that interactions within a stable community leads to a general relationship between variability and the abundance of individually perturbed species: if individuals of species respond in synchrony to a perturbation, then the more abundant the species perturbed the higher the variability of the system, but the relationship is reverse when individual respond asynchronously. A direct implications of these results for the classical debate is that the diversity-stability relationship is negative for the former type of perturbations (as in May’s seminal paper) but positive for the latter type. Hence, the rigorous work of Arnoldi and colleagues sheds a new light upon the classical debate: the nature of the perturbation regime prevailing within a community affects the slope of the diversity-stability relationships and given the vast diversity of ecological communities, this may very well be one of the reasons why the debate still endures.
From a historical perspective, it is interesting that ecologists have gone from looking at random webs to structured webs and now, in a sense, Arnoldi et al. are unpacking the role of differentially structured perturbations. The work they achieved will doubtlessly be followed by further theoretical investigations. One natural research avenue is to revisit the role of the topology of ecological networks with this framework: how the distribution of interactions and their strength affect the general relationship they unravel? Finally, this study demonstrate that the impact of the abundance of a species on the variability of the system depends on the nature of the perturbation regime and so the distribution of species abundances within a community should be determined by the prevailing perturbation regime which is a prediction that remains to be tested.

References

[1] May, Robert M (1972). Will a Large Complex System Be Stable? Nature 238, 413–414. doi: 10.1038/238413a0
[2] McCann, Kevin Shear (2000). The Diversity–Stability Debate. Nature 405, 228–233. doi: 10.1038/35012234
[3] Rooney, Neil, Kevin McCann, Gabriel Gellner, and John C. Moore (2006). Structural Asymmetry and the Stability of Diverse Food Webs. Nature 442, 265–269. doi: 10.1038/nature04887
[4] Jacquet, Claire, Charlotte Moritz, Lyne Morissette, Pierre Legagneux, François Massol, Philippe Archambault, and Dominique Gravel (2016). No Complexity–Stability Relationship in Empirical Ecosystems. Nature Communications 7, 12573. doi: 10.1038/ncomms12573
[5] Donohue, Ian, Helmut Hillebrand, José M. Montoya, Owen L. Petchey, Stuart L. Pimm, Mike S. Fowler, Kevin Healy, et al. (2016). Navigating the Complexity of Ecological Stability. Ecology Letters 19, 1172–1185. doi: 10.1111/ele.12648
[6] Arnoldi, Jean-François, and Bart Haegeman (2016). Unifying Dynamical and Structural Stability of Equilibria. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science 472, 20150874. doi: 10.1098/rspa.2015.0874
[7] Caswell, Hal, and Michael G. Neubert (2005). Reactivity and Transient Dynamics of Discrete-Time Ecological Systems. Journal of Difference Equations and Applications 11, 295–310. doi: 10.1080/10236190412331335382
[8] Arnoldi, J-F., M. Loreau, and B. Haegeman (2016). Resilience, Reactivity and Variability: A Mathematical Comparison of Ecological Stability Measures. Journal of Theoretical Biology 389, 47–59. doi: 10.1016/j.jtbi.2015.10.012
[9] Arnoldi, Jean-Francois, Michel Loreau, and Bart Haegeman. (2019). The Inherent Multidimensionality of Temporal Variability: How Common and Rare Species Shape Stability Patterns.” BioRxiv, 431296, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/431296

The inherent multidimensionality of temporal variability: How common and rare species shape stability patternsJean-François Arnoldi, Michel Loreau, Bart Haegeman<p>Empirical knowledge of ecosystem stability and diversity-stability relationships is mostly based on the analysis of temporal variability of population and ecosystem properties. Variability, however, often depends on external factors that act as...Biodiversity, Coexistence, Community ecology, Competition, Interaction networks, Theoretical ecologyKevin Cazelles2018-10-02 14:01:03 View
05 Apr 2019
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Using a large-scale biodiversity monitoring dataset to test the effectiveness of protected areas at conserving North-American breeding birds

Protected Areas effects on biodiversity: a test using bird data that hopefully will give ideas for much more studies to come

Recommended by based on reviews by Willson Gaul and 1 anonymous reviewer

In the face of worldwide declines in biodiversity, evaluating the effectiveness of conservation practices is an absolute necessity. Protected Areas (PA) are a key tool for conservation, and the question “Are PA effective” has been on many a research agenda, as the introduction to this preprint will no doubt convince you. A challenge we face is that, until now, few studies have been explicitly designed to evaluate PA, and despite the rise of meta-analyses on the topic, our capacity to quantify their effect on biodiversity remains limited.
This study by Cazalis et al. [1] uses the rich dataset of the North-American Breeding Bird Survey and a sound paired design to investigate how PA change bird assemblages. The methodological care brought to the study in itself is worth the read, and the results are insightful. I will not spoil too much by revealing here that things are “complicated”, and that effects – or lack thereof – depend on the type of ecosystem, and the type of species considered.
If you are interested in conservation, bird communities, species life-history, or like beautiful plots: go and read it.

References

[1] Cazalis, V., Belghali, S., & Rodrigues, A. S. (2019). Using a large-scale biodiversity monitoring dataset to test the effectiveness of protected areas at conserving North-American breeding birds. bioRxiv, 433037, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/433037

Using a large-scale biodiversity monitoring dataset to test the effectiveness of protected areas at conserving North-American breeding birdsVictor Cazalis, Soumaya Belghali, Ana S.L. Rodrigues<p>Protected areas currently cover about 15% of the global land area, and constitute one of the main tools in biodiversity conservation. Quantifying their effectiveness at protecting species from local decline or extinction involves comparing prot...Biodiversity, Conservation biology, Human impact, Landscape ecology, MacroecologyPaul Caplat2018-10-04 08:43:34 View