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24 May 2022
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Controversy over the decline of arthropods: a matter of temporal baseline?

Don't jump to conclusions on arthropod abundance dynamics without appropriate data

Recommended by ORCID_LOGO based on reviews by Gabor L Lovei and 1 anonymous reviewer

Humans are dramatically modifying many aspects of our planet via increasing concentrations of carbon dioxide in the atmosphere, patterns of land-use change, and unsustainable exploitation of the planet’s resources. These changes impact the abundance of species of wild organisms, with winners and losers. Identifying how different species and groups of species are influenced by anthropogenic activity in different biomes, continents, and habitats, has become a pressing scientific question with many publications reporting analyses of disparate data on species population sizes. Many conclusions are based on the linear analysis of rather short time series of organismal abundances.
 
There has been particular interest in how arthropods are impacted by environmental change, with several recent papers reporting contradictory results. To investigate why these contradictions might arise, Duchenne et al. (2022) conducted an analysis of four published data sets along with a series of experimental analyses of simulated time series to examine the power of widely used statistical analyses to gain inference on temporal trends. Their important paper reveals that accurate inference on dynamics, particularly of species that exhibit large temporal fluctuations in abundance, requires time series that are substantially longer than are typically collected, as well as careful thought as to whether linear models are appropriate. Linear analyses of short time series are susceptible to providing unreliable inference as trends can be strongly influenced by points at either end of the time series. 
 
Duchenne et al.’s paper provides important insight on the conditions when strong inference on temporal trends of arthropod (and other species) abundances can be made, and when they should be treated with caution. They do not doubt that many insect and arachnid species are changing their abundances, and that patterns in these changes may vary spatially. What their results do say is that we should treat grand claims of population recovery or rapid declines apparently to extinction with caution when they are based on short time series, particularly of species that show significant boom and bust dynamics. In many ways, these results are not unexpected, but it is nice to see such careful and thoughtful analyses and interpretation. More data are required for most arthropod species before clear assessments of abundance trends can be made. Given our reliance on many arthropods for food, pollination, and numerous ecosystem services, and the ability of other species to spread devastating human diseases such as dengue and malaria, it is advisable that we slow our modification of their habitats while additional data are collected to allow us to better characterise the trajectory of arthropod populations to understand what the consequences of our actions on the natural world are likely to be.  
 
References

Duchenne F, Porcher E, Mihoub J-B, Loïs G, Fontaine C (2022) Controversy over the decline of arthropods: a matter of temporal baseline? bioRxiv, 2022.02.09.479422, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.02.09.479422

Controversy over the decline of arthropods: a matter of temporal baseline?François Duchenne, Emmanuelle Porcher, Jean-Baptiste Mihoub, Grégoire Loïs, Colin Fontaine<p style="text-align: justify;">Recently, a number of studies have reported somewhat contradictory patterns of temporal trends in arthropod abundance, from decline to increase. Arthropods often exhibit non-monotonous variation in abundance over ti...Conservation biologyTim Coulson2022-02-11 15:44:44 View
05 Nov 2019
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Crown defoliation decreases reproduction and wood growth in a marginal European beech population.

Defoliation induces a trade-off between reproduction and growth in a southern population of Beech

Recommended by based on reviews by 3 anonymous reviewers

Individuals ability to withstand abiotic and biotic stresses is crucial to the maintenance of populations at climate edge of tree species distribution. We start to have a detailed understanding of tree growth response and to a lesser extent mortality response in these populations. In contrast, our understanding of the response of tree fecundity and recruitment remains limited because of the difficulty to monitor it at the individual tree level in the field. Tree recruitment limitation is, however, crucial for tree population dynamics [1-2].
In their study Oddou-Muratorio et al. [3] use a new method that they recently developed that jointly estimate male and female effective fecundity in natural populations using naturally established seedlings [4]. Their method uses a spatially explicit Bayesian analysis based on molecular markers and parentage analyses (MEMM program [4]). They apply this method to an unmanaged Beech forest at the southern edge of Beech distribution, where tree defoliation – taken as an integrative indicator of tree abiotic and biotic stress – and growth have been monitored for all adult trees.
This allows the authors to explore alternative hypothesis about tree fecundity response to stress. In one hand, biotic and abiotic stresses are thought to negatively impact tree fecundity. In the other hand, management and studies of orchard fruit tree support the idea that stress could trigger a compensatory increase of fecundity at the cost of other performances such as growth and survival.
They show that both growth and female fecundity are negatively affected by defoliation. There was no evidence that stresses trigger a compensatory increase of fecundity. Yet, they also found that, for large highly defoliated trees, there was a trade-off between growth and female fecundity. Some individuals are able to mitigate stress impact on fecundity by decreasing their growth. It is difficult to understand with available data what is driving such divergent responses between defoliated individuals. This could be related to differences in micro-environmental conditions or genetic background of individual trees. Such individual-level difference in response to stress could be crucial to understand tree populations response to ongoing climate change. This study clearly opens exciting new perspectives to apply such new methods to understand the role of fecundity on tree population dynamics. For instance, could we apply this method across the species distribution to understand how effective fecundity and its response to abiotic stress change between southern edge populations, core populations, and northern edge populations? Using time-series retrieved from such analysis can we disentangle the effect of different climatic drivers? It would also be interesting to see how such results can contribute to analyses covering the full tree life cycle to understand the contribution of fecundity response to population and evolutionary.

References

[1] Clark, J. S. et al. (1999). Interpreting recruitment limitation in forests. American Journal of Botany, 86(1), 1-16. doi: 10.2307/2656950
[2] Petit, R. J., and Hampe, A. (2006). Some evolutionary consequences of being a tree. Annu. Rev. Ecol. Evol. Syst., 37, 187-214. doi: 10.1146/annurev.ecolsys.37.091305.110215
[3] Oddou-Muratorio, S., Petit, C., Journe, V., Lingrand, M., Magdalou, J. A., Hurson, C., Garrigue, J., Davi, H. and Magnanou, E. (2019). Crown defoliation decreases reproduction and wood growth in a marginal European beech population. bioRxiv, 474874, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/474874
[4] Oddou‐Muratorio, S. and Klein, E. K. (2008). Comparing direct vs. indirect estimates of gene flow within a population of a scattered tree species. Molecular Ecology, 17(11), 2743-2754. doi: 10.1111/j.1365-294X.2008.03783.x

Crown defoliation decreases reproduction and wood growth in a marginal European beech population.Sylvie Oddou-Muratorio, Cathleen Petit-Cailleux, Valentin Journé, Matthieu Lingrand, Jean-André Magdalou, Christophe Hurson, Joseph Garrigue, Hendrik Davi, Elodie Magnanou.<p>1. Although droughts and heatwaves have been associated to increased crown defoliation, decreased growth and a higher risk of mortality in many forest tree species, their impact on tree reproduction and forest regeneration still remains underst...Climate change, Eco-evolutionary dynamics, Molecular ecology, Physiology, Population ecologyGeorges Kunstler2018-11-20 13:29:42 View
01 Jun 2018
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Data-based, synthesis-driven: setting the agenda for computational ecology

Some thoughts on computational ecology from people who I’m sure use different passwords for each of their accounts

Recommended by based on reviews by Matthieu Barbier and 1 anonymous reviewer

Are you an ecologist who uses a computer or know someone that does? Even if your research doesn’t rely heavily on advanced computational techniques, it likely hasn’t escaped your attention that computers are increasingly being used to analyse field data and make predictions about the consequences of environmental change. So before artificial intelligence and robots take over from scientists, now is great time to read about how experts think computers could make your life easier and lead to innovations in ecological research. In “Data-based, synthesis-driven: setting the agenda for computational ecology”, Poisot and colleagues [1] provide a brief history of computational ecology and offer their thoughts on how computational thinking can help to bridge different types of ecological knowledge. In this wide-ranging article, the authors share practical strategies for realising three main goals: (i) tighter integration of data and models to make predictions that motivate action by practitioners and policy-makers; (ii) closer interaction between data-collectors and data-users; and (iii) enthusiasm and aptitude for computational techniques in future generations of ecologists. The key, Poisot and colleagues argue, is for ecologists to “engage in meaningful dialogue across disciplines, and recognize the currencies of their collaborations.” Yes, this is easier said than done. However, the journey is much easier with a guide and when everyone involved serves to benefit not only from the eventual outcome, but also the process.

References

[1] Poisot, T., Labrie, R., Larson, E., & Rahlin, A. (2018). Data-based, synthesis-driven: setting the agenda for computational ecology. BioRxiv, 150128, ver. 4 recommended and peer-reviewed by PCI Ecology. doi: 10.1101/150128

Data-based, synthesis-driven: setting the agenda for computational ecologyTimothée Poisot, Richard Labrie, Erin Larson, Anastasia RahlinComputational ecology, defined as the application of computational thinking to ecological problems, has the potential to transform the way ecologists think about the integration of data and models. As the practice is gaining prominence as a way to...Meta-analyses, Statistical ecology, Theoretical ecologyPhillip P.A. Staniczenko2018-02-05 20:51:41 View
04 Apr 2023
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Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study

Species Distribution Models: the delicate balance between signal and noise

Recommended by ORCID_LOGO based on reviews by Alejandra Zarzo Arias and 1 anonymous reviewer

Species Distribution Models (SDMs) are one of the most commonly used tools to predict where species are, where they may be in the future, and, at times, what are the variables driving this prediction. As such, applying an SDM to a dataset is akin to making a bet: that the known occurrence data are informative, that the resolution of predictors is adequate vis-à-vis the scale at which their impact is expressed, and that the model will adequately capture the shape of the relationships between predictors and predicted occurrence.

In this contribution, Lambert & Virgili (2023) perform a comprehensive assessment of different sources of complications to this process, using replicated simulations of two synthetic species. Their experimental process is interesting, in that both the data generation and the data analysis stick very close to what would happen in "real life". The use of synthetic species is particularly relevant to the assessment of SDM robustness, as they enable the design of species for which the shape of the relationship is given: in short, we know what the model should capture, and can evaluate the model performance against a ground truth that lacks uncertainty.

Any simulation study is limited by the assumptions established by the investigators; when it comes to spatial data, the "shape" of the landscape, both in terms of auto-correlation and in where the predictors are available. Lambert & Virgili (2023) nicely circumvent these issues by simulating synthetic species against the empirical distribution of predictors; in other words, the species are synthetic, but the environment for which the prediction is made is real. This is an important step forward when compared to the use of e.g. neutral landscapes (With 1997), which can have statistical properties that are not representative of natural landscapes (see e.g. Halley et al., 2004).

A striking point in the study by Lambert & Virgili (2023) is that they reveal a deep, indeed deeper than expected, stochasticity in SDMs; whether this is true in all models remains an open question, but does not invalidate their recommendation to the community: the interpretation of outcomes is a delicate exercise, especially because measures that inform on the goodness of the model fit do not capture the predictive quality of the model outputs. This preprint is both a call to more caution, and a call to more curiosity about the complex behavior of SDMs, while also providing a sensible template to perform future analyses of the potential issues with predictive models.


References

Halley, J. M., et al. (2004) “Uses and Abuses of Fractal Methodology in Ecology: Fractal Methodology in Ecology.” Ecology Letters, vol. 7, no. 3, pp. 254–71. https://doi.org/10.1111/j.1461-0248.2004.00568.x.

Lambert, Charlotte, and Auriane Virgili (2023). Data Stochasticity and Model Parametrisation Impact the Performance of Species Distribution Models: Insights from a Simulation Study. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.01.17.524386

With, Kimberly A. (1997) “The Application of Neutral Landscape Models in Conservation Biology. Aplicacion de Modelos de Paisaje Neutros En La Biologia de La Conservacion.” Conservation Biology, vol. 11, no. 5, pp. 1069–80. https://doi.org/10.1046/j.1523-1739.1997.96210.x.

Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation studyCharlotte Lambert, Auriane Virgili<p>Species distribution models (SDM) are widely used to describe and explain how species relate to their environment, and predict their spatial distributions. As such, they are the cornerstone of most of spatial planning efforts worldwide. SDM can...Biogeography, Habitat selection, Macroecology, Marine ecology, Spatial ecology, Metacommunities & Metapopulations, Species distributions, Statistical ecologyTimothée Poisot2023-01-20 09:43:51 View
07 Oct 2019
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Deer slow down litter decomposition by reducing litter quality in a temperate forest

Disentangling effects of large herbivores on litter decomposition

Recommended by based on reviews by 2 anonymous reviewers

Aboveground – belowground interactions is a fascinating field that has developed in ecology since about 20 years [1]. This field has been very fruitful as measured by the numerous articles published but also by the particular role it has played in the development of soil ecology. While soil ecology has for a long time developed partially independently from “general ecology” [2], the field of aboveground – belowground interactions has shown that all ecological interactions occurring within the soil are likely to impact plant growth and plant physiology because they have their roots within the soil. In turns, this should impact the aerial system of plants (higher or lower biomasses, changes in leaf quality…), which should cascade on the aboveground food web. Conversely, all ecological interactions occurring aboveground likely impact plant growth, which should cascade to their root systems, and thus to the soil functioning and the soil food web (through changes in the emission of exudates or inputs of dead roots…). Basically, plants are linking the belowground and aboveground worlds because, as terrestrial primary producers, they need to have (1) leaves to capture CO2 and exploit light and (2) roots to absorb water and mineral nutrients. The article I presently recommend [3] tackles this general issue through the prism of the impact of large herbivores on the decomposition of leaf litter.
This issue is a relatively old one [4, 5] but still deserves efforts because there have been relatively few studies on the subject and because the issue is relatively complex due to the diversity of mechanisms involved and the difficulty to disentangle them. I recommend this article because the authors have cleverly taken advantage of a ‘‘natural’’ long-term experiment, i.e. three islands with contrasted deer densities, to test whether these large mammals are able to impact leaf litter decomposition and whether they are able to do so through changes in litter quality (because they browse the vegetation) or through changes in soil characteristics (either physical or chemical characteristics or the composition of the decomposer community). They have found that deer decrease litter decomposition, mainly through a decrease in litter quality (increase in its C:N ratio). I particularly appreciate the combination of statistics achieved to test the different hypotheses and the fair and in-depth discussion of the results.
I have to confess that I have two small regrets with this work. First, all replications are implemented within the same three islands, so that it cannot be fully excluded that measured effects should not be attributed to any other possible difference between the three islands. I am fairly sure this is not the case (at least because the three islands have the same environments) but I hope that future studies or meta-analyses will be able analyse independent deer density treatments. Second, as a soil ecologist, I am eager to see results on the decomposer communities, both microorganisms and macrofauna, of the three islands.

References

[1] Hooper, D. U., Bignell, D. E., Brown, V. K., Brussard, L., Dangerfield, J. M., Wall, D. H. and Wolters, V. (2000). Interactions between Aboveground and Belowground Biodiversity in Terrestrial Ecosystems: Patterns, Mechanisms, and Feedbacks. BioScience, 50(12), 1049-1061. doi: 10.1641/0006-3568(2000)050[1049:ibaabb]2.0.co;2
[2] Barot, S., Blouin, M., Fontaine, S., Jouquet, P., Lata, J.-C., and Mathieu, J. (2007). A Tale of Four Stories: Soil Ecology, Theory, Evolution and the Publication System. PLOS ONE, 2(11), e1248. doi: 10.1371/journal.pone.0001248
[3] Chollet S., Maillard M., Schörghuber J., Grayston S. and Martin J.-L. (2019). Deer slow down litter decomposition by reducing litter quality in a temperate forest. bioRxiv, 690032, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/690032
[4] Wardle, D. A., Barker, G. M., Yeates, G. W., Bonner, K. I., and Ghani, A. (2001). Introduced browsing mammals in New Zealand natural forests: aboveground and belowground consequences. Ecological Monographs, 71(4), 587-614. doi: 10.1890/0012-9615(2001)071[0587:ibminz]2.0.co;2
[5] Bardgett, R. D., and Wardle, D. A. (2003). Herbivore-mediated linkages between aboveground and belowground communities. Ecology, 84(9), 2258-2268. doi: 10.1890/02-0274

Deer slow down litter decomposition by reducing litter quality in a temperate forest Simon Chollet, Morgane Maillard, Juliane Schorghuber, Sue Grayston, Jean-Louis Martin<p>In temperate forest ecosystems, the role of deer in litter decomposition, a key nutrient cycling process, remains debated. Deer may modify the decomposition process by affecting plant cover and thus modifying litter abundance. They can also alt...Community ecology, Ecosystem functioning, Herbivory, Soil ecologySébastien Barot2019-07-04 14:30:19 View
28 Dec 2022
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Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse

An experimental approach for understanding how terrestrial isopods respond to environmental stressors

Recommended by based on reviews by Aaron Yilmaz and Michael Morris

​​In this article, the authors discuss the results of their study investigating the effects of heat stress and moisture stress on a terrestrial isopod Armadilldium vulgare, the common woodlouse [1]. Specifically, the authors have assessed how increased temperature or decreased moisture affects life history traits (such as growth, survival, and reproduction) as well as physiological traits (immune cell parameters and \( beta \)-galactosidase activity). This article quantitatively evaluates the effects of the two stressors on woodlouse. Terrestrial isopods like woodlouse are sensitive to thermal and moisture stress [2; 3] and are therefore good models to test hypotheses in global change biology and for monitoring ecosystem health.

​An important feature of this study is the combination of experimental, laboratory, and analytical techniques. Experiments were conducted under controlled conditions in the laboratory by modulating temperature and moisture, life history and physiological traits were measured/analyzed and then tested using models. Both stressors had negative impacts on survival and reproduction of woodlouse, and result in premature ageing. Although thermal stress did not affect survival, it slowed woodlouse growth. Moisture stress did not have a detectable effect on woodlouse growth but decreased survival and reproductive success. An important insight from this study is that effects of heat and moisture stressors on woodlouse are not necessarily linear, and experimental approaches can be used to better elucidate the mechanisms and understand how these organisms respond to environmental stress.

​This article is timely given the increasing attention on biological monitoring and ecosystem health.​

References:

[1] Depeux C, Branger A, Moulignier T, Moreau J, Lemaître J-F, Dechaume-Moncharmont F-X, Laverre T, Pauhlac H, Gaillard J-M, Beltran-Bech S (2022) Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse. bioRxiv, 2022.09.26.509512., ver. 3 peer-reviewd and recommended by PCI Ecology. https://doi.org/10.1101/2022.09.26.509512

[2] ​Warburg MR, Linsenmair KE, Bercovitz K (1984) The effect of climate on the distribution and abundance of isopods. In: Sutton SL, Holdich DM, editors. The Biology of Terrestrial Isopods. Oxford: Clarendon Press. pp. 339–367.​

[3] Hassall M, Helden A, Goldson A, Grant A (2005) Ecotypic differentiation and phenotypic plasticity in reproductive traits of Armadillidium vulgare (Isopoda: Oniscidea). Oecologia 143: 51–60.​ https://doi.org/10.1007/s00442-004-1772-3

Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouseCharlotte Depeux, Angele Branger, Theo Moulignier, Jérôme Moreau, Jean-Francois Lemaitre, Francois-Xavier Dechaume-Moncharmont, Tiffany Laverre, Hélène Paulhac, Jean-Michel Gaillard, Sophie Beltran-Bech<p>We tested independently the influences of increasing temperature and decreasing moisture on life history and physiological traits in the arthropod <em>Armadillidium vulgare</em>. Both increasing temperature and decreasing moisture led individua...Biodiversity, Evolutionary ecology, Experimental ecology, Life history, Physiology, Terrestrial ecology, ZoologyAniruddha Belsare2022-09-28 13:13:47 View
10 Oct 2018
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Detecting within-host interactions using genotype combination prevalence data

Combining epidemiological models with statistical inference can detect parasite interactions

Recommended by based on reviews by Samuel Díaz Muñoz, Erick Gagne and 1 anonymous reviewer

There are several important topics in the study of infectious diseases that have not been well explored due to technical difficulties. One such topic is pursued by Alizon et al. in “Modelling coinfections to detect within-host interactions from genotype combination prevalences” [1]. Both theory and several important examples have demonstrated that interactions among co-infecting strains can have outsized impacts on disease outcomes, transmission dynamics, and epidemiology. Unfortunately, empirical data on pathogen interactions and their outcomes is often correlational making results difficult to decipher.
The analytical framework developed by Alizon et al. [1] infers the presence and strength of pathogen interactions through their impact on transmission dynamics using a novel application of Approximate Bayesian Computation (ABC)-regression to epidemiological data. Traditional analytic approaches identify pathogen interactions when the observed distribution of pathogens among hosts differ from ‘neutral’ expectations. However, deviations from this expectation are not only a result of inter-strain interactions but can be caused by many ecological interactions, such as heterogeneity in host contact networks. To overcome this difficulty, Alizon et al [1] develop an analytical framework that incorporates explicit epidemiological models to allow inference of interactions among strains of Human Papillomaviruses (HPV) even with other ecological interactions that impact the distribution of strains among hosts. Alizon et al also demonstrate that using more of the available data, including the specific combination of strains present in hosts and knowledge of the connectivity of the hosts (i.e., super-spreaders), leads to more accurate inferences of the strength and direction of within-host interactions among coinfecting strains. This method successfully identified data generated from models with high and moderate inter-strain interaction intensity when the host population was homogeneous and was only slightly less successful when the host population was heterogeneous (super-spreaders present). By comparison, some previously published analytical methods could identify only some inter-strain interactions in datasets generated from models with homogeneous host populations, but host heterogeneity obscured these interactions.
This manuscript makes seamless connections between basic viral biology and its epidemiological consequences by tying them together with realistic models, illustrating the fundamental utility of biological modeling. This analytical framework provides crucial tools for experimentalists, facilitating collaborations with theoreticians to better understand the epidemiological consequences of co-infections. In addition, the method is simple enough to be applied by a broad base of experimentalists to the many pathogens where co-infections are common. Thus, this paper has the potential to impact several research fields and public health practice. Those attempting to apply this method should note the potential limitations noted by the authors. For example, it is not designed to detect the mechanisms of inter-strain interactions (there is no within host component of the models) but to identify the existence of interactions through patterns indicative of these interactions while ruling out other sources that could cause the pattern. This approach is likely to be most accurate when strain identification within hosts is precise and unbiased - which is unlikely in many systems where samples are taken only from symptomatic cases and strain detection is not sufficiently sensitive – and when host contact networks can be reasonably estimated. Importantly, a priori knowledge of the set of possible epidemiological models is needed for accurate parameter estimates, which may be true for several prominent pathogens, but not be so for many other pathogens and symbionts. We look forward to future extensions of this framework where this restriction is relaxed. Alizon et al. [1] have provided a framework that will facilitate theoretical and empirical work on the impact of coinfections on infectious disease and should shape future public health data collection standards.

References

[1] Alizon, S., Murall, C.L., Saulnier, E., & Sofonea, M.T. (2018). Detecting within-host interactions using genotype combination prevalence data. bioRxiv, 256586, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/256586

Detecting within-host interactions using genotype combination prevalence dataSamuel Alizon, Carmen Lía Murall, Emma Saulnier, Mircea T Sofonea<p>Parasite genetic diversity can provide information on disease transmission dynamics but most methods ignore the exact combinations of genotypes in infections. We introduce and validate a new method that combines explicit epidemiological modelli...Eco-immunology & Immunity, Epidemiology, Host-parasite interactions, Statistical ecologyDustin Brisson Samuel Díaz Muñoz, Erick Gagne2018-02-01 09:23:26 View
03 Jan 2024
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Diagnosis of planktonic trophic network dynamics with sharp qualitative changes

A new approach to describe qualitative changes of complex trophic networks

Recommended by based on reviews by Tim Coulson and 1 anonymous reviewer

Modelling the temporal dynamics of trophic networks has been a key challenge for community ecologists for decades, especially when anthropogenic and natural forces drive changes in species composition, abundance, and interactions over time. So far, most modelling methods fail to incorporate the inherent complexity of such systems, and its variability, to adequately describe and predict temporal changes in the topology of trophic networks. 

Taking benefit from theoretical computer science advances, Gaucherel and colleagues (2024) propose a new methodological framework to tackle this challenge based on discrete-event Petri net methodology. To introduce the concept to naïve readers the authors provide a useful example using a simplistic predator-prey model.

The core biological system of the article is a freshwater trophic network of western France in the Charente-Maritime marshes of the French Atlantic coast. A directed graph describing this system was constructed to incorporate different functional groups (phytoplankton, zooplankton, resources, microbes, and abiotic components of the environment) and their interactions. Rules and constraints were then defined to, respectively, represent physiochemical, biological, or ecological processes linking network components, and prevent the model from simulating unrealistic trajectories. Then the full range of possible trajectories of this mechanistic and qualitative model was computed.

The model performed well enough to successfully predict a theoretical trajectory plus two trajectories of the trophic network observed in the field at two different stations, therefore validating the new methodology introduced here. The authors conclude their paper by presenting the power and drawbacks of such a new approach to qualitatively model trophic networks dynamics.

Reference

Cedric Gaucherel, Stolian Fayolle, Raphael Savelli, Olivier Philippine, Franck Pommereau, Christine Dupuy (2024) Diagnosis of planktonic trophic network dynamics with sharp qualitative changes. bioRxiv 2023.06.29.547055, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.06.29.547055

Diagnosis of planktonic trophic network dynamics with sharp qualitative changesCedric Gaucherel, Stolian Fayolle, Raphael Savelli, Olivier Philippine, Franck Pommereau, Christine Dupuy<p>Trophic interaction networks are notoriously difficult to understand and to diagnose (i.e., to identify contrasted network functioning regimes). Such ecological networks have many direct and indirect connections between species, and these conne...Community ecology, Ecosystem functioning, Food webs, Freshwater ecology, Interaction networks, Microbial ecology & microbiologyFrancis Raoul Tim Coulson2023-07-03 10:42:34 View
30 Jan 2020
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Diapause is not selected as a bet-hedging strategy in insects: a meta-analysis of reaction norm shapes

When to diapause or not to diapause? Winter predictability is not the answer

Recommended by based on reviews by Kévin Tougeron, Md Habibur Rahman Salman and 1 anonymous reviewer

Winter is a harsh season for many organisms that have to cope with food shortage and potentially lethal temperatures. Many species have evolved avoidance strategies. Among them, diapause is a resistance stage many insects use to overwinter. For an insect, it is critical to avoid lethal winter temperatures and thus to initiate diapause before winter comes, while making the most of autumn suitable climatic conditions [1,2]. Several cues can be used to appreciate that winter is coming, including day length and temperature [3]. But climate changes, temperatures rise and become more variable from year to year, which imposes strong pressure upon insect phenology [4]. How can insects adapt to changes in the mean and variance of winter onset?
In this paper, Jens Joschinski and Dries Bonte [5] address this question by using a well conducted meta-analysis of 458 diapause reaction norms obtained from 60 primary studies. They first ask first if insect mean diapause timing is tuned to match winter onset. They further ask if insects adapt to climatic unpredictability through a bet-hedging strategy by playing it safe and avoid risk (conservative bet-hedging) or on the contrary by avoiding to put all their eggs in one basket and spread the risk among their offspring (diversified bet-hedging). From published papers, the authors extracted data on mean diapause timing and information on latitude from which they retrieved day length inducing diapause, the date of winter onset and the day length at winter onset.
They found a positive correlation between latitude and the day length inducing diapause. On the contrary they found positive but (very) weak correlation between the date of winter onset and the date of diapause, thus indicating that diapause timing is not as optimally adapted to local environments as expected, particularly at high latitudes. They only found weak correlations between climate unpredictability and variability in diapause timing, and no correlation between climate unpredictability and deviation from optimal diapause timing. Together, these findings go against the hypothesis that insects use diversified or conservative bet-hedging strategies to cope with uncertainty in climatic conditions.
This is what makes the study thought provoking: the results do not match the theory well. Not because of a lack of data or a narrow scope, but because diapause is a complex trait that is determined by a large array of physiological and ecological factors [3]. Determining what are these factors is of particular interest in the face of the current climate change. This study shows what does not determine the timing of insect diapause. Researchers now know where to look at to improve our understanding of this key aspect of insect adaptation to climatic conditions.

References

[1] Dyck, H. V., Bonte, D., Puls, R., Gotthard, K., and Maes, D. (2015). The lost generation hypothesis: could climate change drive ectotherms into a developmental trap? Oikos, 124(1), 54–61. doi: 10.1111/oik.02066
[2] Gallinat, A. S., Primack, R. B., and Wagner, D. L. (2015). Autumn, the neglected season in climate change research. Trends in Ecology & Evolution, 30(3), 169–176. doi: 10.1016/j.tree.2015.01.004
[3] Tougeron, K. (2019). Diapause research in insects: historical review and recent work perspectives. Entomologia Experimentalis et Applicata, 167(1), 27–36. doi: 10.1111/eea.12753
[4] Bale, J. S., and Hayward, S. a. L. (2010). Insect overwintering in a changing climate. Journal of Experimental Biology, 213(6), 980–994. doi: 10.1242/jeb.037911
[5] Joschinski, J., and Bonte, D. (2020). Diapause is not selected as a bet-hedging strategy in insects: a meta-analysis of reaction norm shapes. BioRxiv, 752881, ver. 3 recommended and peer-reviewed by PCI Ecology. doi: 10.1101/752881

Diapause is not selected as a bet-hedging strategy in insects: a meta-analysis of reaction norm shapesJens Joschinski and Dries BonteMany organisms escape from lethal climatological conditions by entering a resistant resting stage called diapause, and it is essential that this strategy remains optimally timed with seasonal change. Climate change therefore exerts selection press...Maternal effects, Meta-analyses, Phenotypic plasticity, Terrestrial ecologyBastien Castagneyrol2019-09-20 11:47:47 View
12 Mar 2023
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Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities.

Processing environmental DNA samples in turbid waters from coastal lagoons

Recommended by based on reviews by David Murray-Stoker and Rutger De Wit

Coastal lagoons are among the most productive natural ecosystems on Earth. These relatively closed basins are important habitats and nursery for endemic and endangered species and are extremely vulnerable to nutrient input from the surrounding catchment; therefore, they are highly susceptible to anthropogenic influence, pollution and invasion (Pérez-Ruzafa et al., 2019). In general, coastal lagoons exhibit great spatial and temporal variability in their physicochemical water characteristics due to the sporadic mixing of freshwater with marine influx. One of the alternatives for monitoring communities or target species in aquatic ecosystems is the environmental DNA (eDNA), since overcomes some limitations from traditional methods and enables the investigation of multiple species from a single sample (Thomsen and Willerslev, 2015). In coastal lagoons, where the water turbidity is highly variable, there is a major challenge for monitoring the eDNA because filtering turbid water to obtain the eDNA is problematic (filters get rapidly clogged, there is organic and inorganic matter accumulation, etc.). 

The study by Turba et al. (2023) analyzes different ways of dealing with eDNA sampling and processing in turbid waters and sediments of coastal lagoons, and offers guidelines to obtain unbiased results from the subsequent sequencing using 12S (fish) and 16S (Bacteria and Archaea) universal primers. They analyzed the effect on taxa detection of: i) freezing or not prior to filtering; ii) freezing prior to centrifugation to obtain a sample pellet; and iii) using frozen sediment samples as a proxy of what happens in the water. The authors propose these different alternatives (freeze, do not freeze, sediment sampling) because they consider that they are the easiest to carry out. They found that freezing before filtering using a 3 µm pore size filter had no effects on community composition for either primer, and therefore it is a worthwhile approach for comparison of fish, bacteria and archaea in this kind of system. However, significantly different bacterial community composition was found for sediment compared to water samples. Also, in sediment samples the replicates showed to be more heterogeneous, so the authors suggest increasing the number of replicates when using sediment samples. Something that could be a concern with the study is that the rarefaction curves based on sequencing effort for each protocol did not saturate in any case, this being especially evident in sediment samples. The authors were aware of this, used the slopes obtained from each curve as a measure of comparison between samples and considering that the sequencing depth did not meet their expectations, they managed to achieve their goal and to determine which protocol is the most promising for eDNA monitoring in coastal lagoons. Although there are details that could be adjusted in relation to this item, I consider that the approach is promising for this type of turbid system.

References

Pérez-Ruzafa A, Campillo S, Fernández-Palacios JM, García-Lacunza A, García-Oliva M, Ibañez H, Navarro-Martínez PC, Pérez-Marcos M, Pérez-Ruzafa IM, Quispe-Becerra JI, Sala-Mirete A, Sánchez O, Marcos C (2019) Long-Term Dynamic in Nutrients, Chlorophyll a, and Water Quality Parameters in a Coastal Lagoon During a Process of Eutrophication for Decades, a Sudden Break and a Relatively Rapid Recovery. Frontiers in Marine Science, 6. https://doi.org/10.3389/fmars.2019.00026

Thomsen PF, Willerslev E (2015) Environmental DNA – An emerging tool in conservation for monitoring past and present biodiversity. Biological Conservation, 183, 4–18. https://doi.org/10.1016/j.biocon.2014.11.019

Turba R, Thai GH, Jacobs DK (2023) Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities. bioRxiv, 2022.06.17.495388, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.06.17.495388

Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities.Rachel Turba, Glory H. Thai, and David K Jacobs<p style="text-align: justify;">Coastal lagoons are an important habitat for endemic and threatened species in California that have suffered impacts from urbanization and increased drought. Environmental DNA has been promoted as a way to aid in th...Biodiversity, Community genetics, Conservation biology, Freshwater ecology, Marine ecology, Molecular ecologyClaudia Piccini David Murray-Stoker2022-06-20 20:31:51 View