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12 Apr 2023
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Feeding and growth variations affect δ13C and δ15N budgets during ontogeny in a lepidopteran larva

Refining our understanding how nutritional conditions affect 13C and 15N isotopic fractionation during ontogeny in a herbivorous insect

Recommended by based on reviews by Anton Potapov and 1 anonymous reviewer

Using stable isotope fractionation to disentangle and understand the trophic positions of animals within the food webs they are embedded within has a long tradition in ecology (Post, 2002; Scheu, 2002). Recent years have seen increasing application of the method with several recent reviews summarizing past advancements in this field (e.g. Potapov et al., 2019; Quinby et al., 2020).

In their new manuscript, Charberet and colleagues (2023) set out to refine our understanding of the processes that lead to nitrogen and carbon stable isotope fractionation by investigating how herbivorous insect larvae (specifically, the noctuid moth Spodoptera littoralis) respond to varying nutritional conditions (from starving to ad libitum feeding) in terms of stable isotopes enrichment. Though the underlying mechanisms have been experimentally investigated before in terrestrial invertebrates (e.g. in wolf spiders; Oelbermann & Scheu, 2002), the elegantly designed and adequately replicated experiments by Charberet and colleagues add new insights into this topic. Particularly, the authors provide support for the hypotheses that (A) 15N is disproportionately accumulated under fast growth rates (i.e. when fed ad libitum) and that (B) 13C is accumulated under low growth rates and starvation due to depletion of 13C-poor fat tissues. Applying this knowledge to field samples where feeding conditions are usually not known in detail is not straightforward, but the new findings could still help better interpretation of field data under specific conditions that make starvation for herbivores much more likely (e.g. droughts).

Overall this study provides important methodological advancements for a better understanding of plant-herbivore interactions in a changing world.


Charberet, S., Maria, A., Siaussat, D., Gounand, I., & Mathieu, J. (2023). Feeding and growth variations affect δ13C and δ15N budgets during ontogeny in a lepidopteran larva. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology.

Oelbermann, K., & Scheu, S. (2002). Stable Isotope Enrichment (δ 15N and δ 13C) in a Generalist Predator (Pardosa lugubris, Araneae: Lycosidae): Effects of Prey Quality. Oecologia, 130(3), 337–344.

Post, D. M. (2002). Using stable isotopes to estimate trophic position: Models, methods, and assumptions. Ecology, 83(3), 703–718.[0703:USITET]2.0.CO;2

Potapov, A. M., Tiunov, A. V., & Scheu, S. (2019). Uncovering trophic positions and food resources of soil animals using bulk natural stable isotope composition. Biological Reviews, 94(1), 37–59.

Quinby, B. M., Creighton, J. C., & Flaherty, E. A. (2020). Stable isotope ecology in insects: A review. Ecological Entomology, 45(6), 1231–1246.

Scheu, S. (2002). The soil food web: Structure and perspectives. European Journal of Soil Biology, 38(1), 11–20.

Feeding and growth variations affect δ13C and δ15N budgets during ontogeny in a lepidopteran larvaSamuel M. Charberet, Annick Maria, David Siaussat, Isabelle Gounand, Jérôme Mathieu<p style="text-align: justify;">Isotopes are widely used in ecology to study food webs and physiology. The fractionation observed between trophic levels in nitrogen and carbon isotopes, explained by isotopic biochemical selectivity, is subject to ...Experimental ecology, Food webs, PhysiologyGregor Kalinkat2022-11-16 15:23:31 View
26 Apr 2021
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Experimental test for local adaptation of the rosy apple aphid (Dysaphis plantaginea) during its recent rapid colonization on its cultivated apple host (Malus domestica) in Europe

A planned experiment on local adaptation in a host-parasite system: is adaptation to the host linked to its recent domestication?

Recommended by based on reviews by Sharon Zytynska, Alex Stemmelen and 1 anonymous reviewer

Local adaptation shall occur whenever selective pressures vary across space and overwhelm the effects of gene flow and local extinctions (Kawecki and Ebert 2004). Because the intimate interaction that characterizes their relationship exerts a strong selective pressure on both partners, host-parasite systems represent a classical example in which local adaptation is expected from rapidly evolving parasites adapting to more evolutionary constrained hosts (Kaltz and Shykoff 1998). Such systems indeed represent a large proportion of the study-cases in local adaptation research (Runquist et al. 2020). Biotic interactions intervene in many environment-related societal challenges, so that understanding when and how local adaptation arises is important not only for understanding evolutionary dynamics but also for more applied questions such as the control of agricultural pests, biological invasions, or pathogens (Parker and Gilbert 2004).

The exact conditions under which local adaptation does occur and can be detected is however still the focus of many theoretical, methodological and empirical studies (Blanquart et al. 2013, Hargreaves et al. 2020, Hoeksema and Forde 2008, Nuismer and Gandon 2008, Richardson et al. 2014). A recent review that evaluates investigations that examined the combined influence of biotic and abiotic factors on local adaptation reaches partial conclusions about their relative importance in different contexts and underlines the many traps that one has to avoid in such studies (Runquist et al. 2020). The authors of this review emphasize that one should evaluate local adaptation using wild-collected strains or populations and over multiple generations, on environmental gradients that span natural ranges of variation for both biotic and abiotic factors, in a theory-based hypothetico-deductive framework that helps interpret the outcome of experiments. These multiple targets are not easy to reach in each local adaptation experiment given the diversity of systems in which local adaptation may occur. Improving research practices may also help better understand when and where local adaptation does occur by adding controls over p-hacking, HARKing or publication bias, which is best achieved when hypotheses, date collection and analytical procedures are known before the research begins (Chambers et al. 2014). In this regard, the route taken by Olvera-Vazquez et al. (2021) is interesting. They propose to investigate whether the rosy aphid (Dysaphis plantaginea) recently adapted to its cultivated host, the apple tree (Malus domestica), and chose to pre-register their hypotheses and planned experiments on PCI Ecology (Peer Community In 2020). Though not fulfilling all criteria mentioned by Runquist et al. (2020), they clearly state five hypotheses that all relate to the local adaptation of this agricultural pest to an economically important fruit tree, and describe in details a powerful, randomized experiment, including how data will be collected and analyzed. The experimental set-up includes comparisons between three sites located along a temperature transect that also differ in local edaphic and biotic factors, and contrasts wild and domesticated apple trees that originate from the three sites and were both planted in the local, sympatric site, and transplanted to allopatric sites. Beyond enhancing our knowledge on local adaptation, this experiment will also test the general hypothesis that the rosy aphid recently adapted to Malus sp. after its domestication, a question that population genetic analyses was not able to answer (Olvera-Vazquez et al. 2020).


Blanquart F, Kaltz O, Nuismer SL, Gandon S (2013) A practical guide to measuring local adaptation. Ecology Letters, 16, 1195–1205.

Briscoe Runquist RD, Gorton AJ, Yoder JB, Deacon NJ, Grossman JJ, Kothari S, Lyons MP, Sheth SN, Tiffin P, Moeller DA (2019) Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis. The American Naturalist, 195, 412–431.

Chambers CD, Feredoes E, Muthukumaraswamy SD, Etchells PJ, Chambers CD, Feredoes E, Muthukumaraswamy SD, Etchells PJ (2014) Instead of “playing the game” it is time to change the rules: Registered Reports at <em>AIMS Neuroscience</em> and beyond. AIMS Neuroscience, 1, 4–17.

Hargreaves AL, Germain RM, Bontrager M, Persi J, Angert AL (2019) Local Adaptation to Biotic Interactions: A Meta-analysis across Latitudes. The American Naturalist, 195, 395–411.

Hoeksema JD, Forde SE (2008) A Meta‐Analysis of Factors Affecting Local Adaptation between Interacting Species. The American Naturalist, 171, 275–290.

Kaltz O, Shykoff JA (1998) Local adaptation in host–parasite systems. Heredity, 81, 361–370.

Kawecki TJ, Ebert D (2004) Conceptual issues in local adaptation. Ecology Letters, 7, 1225–1241.

Nuismer SL, Gandon S (2008) Moving beyond Common‐Garden and Transplant Designs: Insight into the Causes of Local Adaptation in Species Interactions. The American Naturalist, 171, 658–668.

Olvera-Vazquez SG, Remoué C, Venon A, Rousselet A, Grandcolas O, Azrine M, Momont L, Galan M, Benoit L, David G, Alhmedi A, Beliën T, Alins G, Franck P, Haddioui A, Jacobsen SK, Andreev R, Simon S, Sigsgaard L, Guibert E, Tournant L, Gazel F, Mody K, Khachtib Y, Roman A, Ursu TM, Zakharov IA, Belcram H, Harry M, Roth M, Simon JC, Oram S, Ricard JM, Agnello A, Beers EH, Engelman J, Balti I, Salhi-Hannachi A, Zhang H, Tu H, Mottet C, Barrès B, Degrave A, Razmjou J, Giraud T, Falque M, Dapena E, Miñarro M, Jardillier L, Deschamps P, Jousselin E, Cornille A (2020) Large-scale geographic survey provides insights into the colonization history of a major aphid pest on its cultivated apple host in Europe, North America and North Africa. bioRxiv, 2020.12.11.421644.

Olvera-Vazquez S.G., Alhmedi A., Miñarro M., Shykoff J. A., Marchadier E., Rousselet A., Remoué C., Gardet R., Degrave A. , Robert P. , Chen X., Porcher J., Giraud T., Vander-Mijnsbrugge K., Raffoux X., Falque M., Alins, G., Didelot F., Beliën T., Dapena E., Lemarquand A. and Cornille A. (2021) Experimental test for local adaptation of the rosy apple aphid (Dysaphis plantaginea) to its host (Malus domestica) and to its climate in Europe. In principle recommendation by Peer Community In Ecology., ver. 4.

Parker IM, Gilbert GS (2004) The Evolutionary Ecology of Novel Plant-Pathogen Interactions. Annual Review of Ecology, Evolution, and Systematics, 35, 675–700.

Peer Community In. (2020, January 15). Submit your preregistration to Peer Community In for peer review.

Richardson JL, Urban MC, Bolnick DI, Skelly DK (2014) Microgeographic adaptation and the spatial scale of evolution. Trends in Ecology & Evolution, 29, 165–176.

Experimental test for local adaptation of the rosy apple aphid (Dysaphis plantaginea) during its recent rapid colonization on its cultivated apple host (Malus domestica) in EuropeOlvera-Vazquez S.G., Alhmedi A., Miñarro M., Shykoff J. A., Marchadier E., Rousselet A., Remoué C., Gardet R., Degrave A. , Robert P. , Chen X., Porcher J., Giraud T., Vander-Mijnsbrugge K., Raffoux X., Falque M., Alins, G., Didelot F., Beliën T.,...<p style="text-align: justify;">Understanding the extent of local adaptation in natural populations and the mechanisms enabling populations to adapt to their environment is a major avenue in ecology research. Host-parasite interaction is widely se...Evolutionary ecology, PreregistrationsEric Petit2020-07-26 18:31:42 View
15 Jul 2023
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Evolution of dispersal and the maintenance of fragmented metapopulations

The spatial dynamics of habitat fragmentation drives the evolution of dispersal and metapopulation persistence

Recommended by based on reviews by Eva Kisdi, David Murray-Stoker, Shripad Tuljapurkar and 1 anonymous reviewer

​​​​​The persistence of populations facing the destruction of their habitat is a multifaceted question that has mobilized theoreticians and empiricists alike for decades. As an ecological question, persistence has been studied as the spatial rescue of populations via dispersal into remaining suitable habitats. The spatial aggregation of habitat destruction has been a key component of these studies, and it has been applied to the problem of coexistence by integrating competition-colonization tradeoffs. There is a rich ecological literature on this topic, both from theoretical and field studies (Fahrig 2003). The relationship between life-history strategies of species and their resilience to spatially structured habitat fragmentation is also an important component of conservation strategies through the management of land use, networks of protected areas, and the creation of corridors. In the context of environmental change, the ability of species to adapt to changes in landscape configuration and availability can be treated as an eco-evolutionary process by considering the possibility of evolutionary rescue (Heino and Hanski 2001; Bell 2017). However, eco-evolutionary dynamics considering spatially structured changes in landscapes and life-history tradeoffs remains an outstanding question. Finand et al. (2023) formulate the problem of persistence in fragmented landscapes over evolutionary time scales by studying models for the evolution of dispersal in relation to habitat fragmentation and spatial aggregation. Their simulations were conducted on a spatial grid where individuals can colonize suitable patch as a function of their competitive rank that decreases as a function of their (ii) dispersal distance trait. Simulations were run under fixed habitat fragmentation (proportion of unsuitable habitat) and aggregation, and with an explicit rate of habitat destruction to study evolutionary rescue.

Their results reveal a balance between the selection for high dispersal under increasing habitat fragmentation and selection for lower dispersal in response to habitat aggregation. This balance leads to the coexistence of polymorphic dispersal strategies in highly aggregated landscapes with low fragmentation where high dispersers inhabit aggregated habitats while low dispersers are found in isolated habitats. The authors then integrate the spatial rescue mechanism to the problem of evolutionary rescue in response to temporally increasing fragmentation. There they show how rapid evolution allows for evolutionary rescue through the evolution of high dispersal. They also show the limits to this evolutionary rescue to cases where both aggregation and fragmentation are not too high. Interestingly, habitat aggregation prevents evolutionary rescue by directly affecting the evolutionary potential of dispersal. The study is based on simple scenarios that ignore the complexity of relationships between dispersal, landscape properties, and species interactions. This simplicity is the strength of the study, revealing basic mechanisms that can now be tested against other life-history tradeoffs and species interactions. Finand et al. (2023) provide a novel foundation for the study of eco-evolutionary dynamics in metacommunities exposed to spatially structured habitat destruction. They point to important assumptions that must be made along the way, including the relationships between dispersal distance and fecundity (they assume a positive relationship), and the nature of life-history tradeoffs between dispersal rate and local competitive abilities. 


Bell, G. 2017. Evolutionary Rescue. Annual Review of Ecology, Evolution, and Systematics 48:605–627. 
Fahrig, L. 2003. Effects of Habitat Fragmentation on Biodiversity. Annual Review of Ecology, Evolution, and Systematics 34:487–515. 
Finand, B., T. Monnin, and N. Loeuille. 2023. Evolution of dispersal and the maintenance of fragmented metapopulations. bioRxiv, 2022.06.08.495260, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. 
Heino, M., and I. Hanski. 2001. Evolution of Migration Rate in a Spatially Realistic Metapopulation Model. The American Naturalist 157:495–511.

Evolution of dispersal and the maintenance of fragmented metapopulationsBasile Finand, Thibaud Monnin, Nicolas Loeuille<p>Because it affects dispersal risk and modifies competition levels, habitat fragmentation directly constrains dispersal evolution. When dispersal is traded-off against competitive ability, increased fragmentation is often expected to select high...Colonization, Competition, Dispersal & Migration, Eco-evolutionary dynamics, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecologyFrédéric Guichard2022-06-10 13:51:15 View
03 Jun 2022
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Evolutionary emergence of alternative stable states in shallow lakes

How to evolve an alternative stable state

Recommended by ORCID_LOGO based on reviews by Jean-François Arnoldi and 1 anonymous reviewer

Alternative stable states describe ecosystems that can persist in more than one configuration. An ecosystem can shift between stable states following some form of perturbation. There has been much work on predicting when ecosystems will shift between stable states, but less work on why some ecosystems are able to exist in alternative stable states in the first place. The paper by Ardichvili, Loeuille, and Dakos (2022) addresses this question using a simple model of a shallow lake. Their model is based on a trade-off between access to light and nutrient availability in the water column, two essential resources for the macrophytes they model. They then identify conditions when the ancestral macrophyte will diversify resulting in macrophyte species living at new depths within the lake. The authors find a range of conditions where alternative stable states can evolve, but the range is narrow. Nonetheless, their model suggests that for alternative stable states to exist, one requirement is for there to be asymmetric competition between competing species, with one species being a better competitor on one limiting resource, with the other being a better competitor on a second limiting resource. 

These results are interesting and add to growing literature on how asymmetric competition can aid species coexistence. Asymmetric competition may be widespread in nature, with closely related species often being superior competitors on different resources. Incorporating asymmetric competition, and its evolution, into models does complicate theoretical investigations, but Ardichvili, Loeuille, and Dakos’ paper elegantly shows how substantial progress can be made with a model that is still (relatively) simple.


Ardichvili A, Loeuille N, Dakos V (2022) Evolutionary emergence of alternative stable states in shallow lakes. bioRxiv, 2022.02.23.481597, ver. 3 peer-reviewed and recommended by Peer Community in Ecology.

Evolutionary emergence of alternative stable states in shallow lakesAlice Ardichvili, Nicolas Loeuille, Vasilis Dakos<p style="text-align: justify;">Ecosystems under stress may respond abruptly and irreversibly through tipping points. Although much is explored on the mechanisms that affect tipping points and alternative stable states, little is known on how ecos...Community ecology, Competition, Eco-evolutionary dynamics, Theoretical ecologyTim Coulson2022-03-01 10:54:05 View
24 May 2023
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Evolutionary determinants of reproductive seasonality: a theoretical approach

When does seasonal reproduction evolve?

Recommended by ORCID_LOGO based on reviews by Francois-Xavier Dechaume-Moncharmont, Nigel Yoccoz and 1 anonymous reviewer

Have you ever wondered why some species breed seasonally while others do not? You might think it is all down to lattitude and the harshness of winters but it turns out it is quite a bit more complicated than that. A consequence of this is that climate change may result in the evolution of the degree of seasonal reproduction, with some species perhaps becoming less seasonal and others more so even in the same habitat. 

Burtschell et al. (2023) investigated how various factors influence seasonal breeding by building an individual-based model of a baboon population from which they calculated the degree of seasonality for the fittest reproductive strategy. They then altered key aspects of their model to examine how these changes impacted the degree of seasonality in the reproductive strategy. What they found is fascinating. 

The degree of seasonality in reproductive strategy is expected to increase with increased seasonality in the environment, decreased food availability, increased energy expenditure, and how predictable resource availability is. Interestingly, neither female cycle length nor extrinsic infant mortality influenced the degree of seasonality in reproduction.

What this means in reality for seasonal species is more challenging to understand. Some environments appear to be becoming more seasonal yet less predictable, and some species appear to be altering their daily energy budgets in response to changing climate in quite complex ways. As with pretty much everything in biology, Burtschell et al.'s work reveals much nuance and complexity, and that predicting how species might alter their reproductive timing is fraught with challenges.

The paper is very well written. With a simpler model it may have proven possible to achieve analytical solutions, but this is a very minor gripe. The reviewers were positive about the paper, and I have little doubt it will be well-cited. 


Burtschell L, Dezeure J, Huchard E, Godelle B (2023) Evolutionary determinants of reproductive seasonality: a theoretical approach. bioRxiv, 2022.08.22.504761, ver. 2 peer-reviewed and recommended by Peer Community in Ecology.

Evolutionary determinants of reproductive seasonality: a theoretical approachLugdiwine Burtschell, Jules Dezeure, Elise Huchard, Bernard Godelle<p style="text-align: justify;">Reproductive seasonality is a major adaptation to seasonal cycles and varies substantially among organisms. This variation, which was long thought to reflect a simple latitudinal gradient, remains poorly understood ...Evolutionary ecology, Life history, Theoretical ecologyTim Coulson Nigel Yoccoz2022-08-23 21:37:28 View
01 Feb 2020
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Evidence of tool use in a seabird?

Touchy matter: the delicate balance between Morgan’s canon and open-minded description of advanced cognitive skills in the animal

Recommended by ORCID_LOGO based on reviews by Valérie Dufour and Alex Taylor

In a recent paper published in PNAS, Fayet et al. [1] reported scarce field observations of two Atlantic puffins (four years apart) apparently scratching their bodies using sticks, which was interpreted by the authors as evidence of tool use in this species. In a short response, Benjamin Farrar [2] raises serious concerns about this interpretation and proposes simpler, more parsimonious, mechanisms explaining the observed behaviour: a textbook case of Morgan's canon.
In virtually all introductory lectures on animal behaviour, students are advised to exercise caution when interpreting empirical data and weighting alternative explanations. We are sometimes prisoner of our assumptions: our desire of beliefs in advanced cognitive skills in non-human species make us more receptive to facts confirming our preconceptions than to simpler, less exciting, interpretations (a phenomenon known as "confirmation bias" in psychology). We must resist the temptation to accept appealing explanations without enough critical thinking. Our students are thus taught to apply the Lloyd Morgan's canon, a variant of one of the most important heuristics in Science, the principle of parsimony or Occam's razor, rephrased by Morgan [3, page 53] in the context of animal behaviour: "In no case may we interpret an action as the outcome of a higher psychical faculty, if it can be interpreted as the outcome of the exercise of one that stands lower in the psychological scale". In absence of evidence to the contrary, one should postulate the simplest cognitive skill consistent with the observed behaviour. While sometimes criticized from an epistemological point of view [4-6], it remains an essential and largely accepted framework of animal cognition. It has repeatedly proved to be a useful guide in the minefield of comparative psychology. Classical ethology questions related to the existence of, for instance, meta-cognition [7], intentionality or problem solving [8] have been convincingly investigated using this principle.
Yet, there is a downside to this conservative approach. Blind reference to Morgan's canon may narrow our theoretical thinking about animal cognition [7,9]. It could be counter-productive to systematically deny advanced cognitive skills in animals. On the contrary, keeping our mind open to unplanned observations, unexpected discoveries, or serendipity [10], and being prepared to accept new hypotheses, sometimes fairly remote from the dominant paradigm, may be a fruitful research strategy. To quote Darwin's famous letter to Alfred Wallace: "I am a firm believer, that without speculation there is no good and original observation" [11]. Brief notes in specialized scientific journals, or even in grey literature (by enthusiast amateur ornithologists, ichthyologists, or entomologists), constitutes a rich array of anecdotal observations. For instance, Sol et al. [12] convincingly compared the innovation propensity across bird species by screening ornithology literature using keywords like 'never reported', 'not seen before', 'first report', 'unusual' or 'novel'. Even if "the plural of anecdote is not data" as the saying goes, such descriptions of novel behaviours, even single-subject observations, are indisputably precious: taxonomic ubiquity of a behaviour is a powerful argument in favour of evolutionary convergence. Of course, a race to the bottom, amplified by the inevitable media hypes around scientific articles questioning human exceptionalism, is another possible scientific trap for behavioural biologists in search of skills characteristic of so-called advanced species, but never described so far in supposedly cognitively simpler organisms. As stated by Franz de Waal [9]: "I have nothing against anecdotes, especially if they have been caught on camera or come from reputable observers who know their animals; but I do view them as a starting point of research, never an end point".
In the case of the two video observations of puffins apparently using sticks as scratching tool, it must be considered as a mere anecdote unless scientists systematically investigate this behaviour. In his constructive criticism of Fayet et al.'s paper, Benjamin Farrar [2] proposes interesting directions of research and testable predictions. A correlation between the background rate of stick picking and the rate of stick preening would indicate that this behaviour was more likely explained by fluke than genuine innovation in this species.


[1] Fayet, A. L., Hansen, E. S., and Biro, D. (2020). Evidence of tool use in a seabird. Proceedings of the National Academy of Sciences, 117(3), 1277–1279. doi: 10.1073/pnas.1918060117
[2] Farrar, B. G. (2020). Evidence of tool use in a seabird? PsyArXiv, 463hk, ver. 5 recommended and peer-reviewed by Peer Community In Ecology. doi: 10.31234/
[3] Morgan, C. L. (1894). An introduction to comparative psychology. London, UK: Walter Scott, Ltd. Retrieved from
[4] Meketa, I. (2014). A critique of the principle of cognitive simplicity in comparative cognition. Biology and Philosophy, 29(5), 731–745. doi: 10.1007/s10539-014-9429-z
[5] Fitzpatrick, S. (2017). Against Morgan's Canon. In K. Andrews and J. Beck (Eds.), The Routledge handbook of philosophy of animal minds (pp. 437–447). London, UK: Routledge, Taylor and Francis Group. doi: 10.4324/9781315742250.ch42
[6] Starzak, T. (2017). Interpretations without justification: a general argument against Morgan's Canon. Synthese, 194(5), 1681–1701. doi: 10.1007/s11229-016-1013-4
[7] Arbilly, M., and Lotem, A. (2017). Constructive anthropomorphism: a functional evolutionary approach to the study of human-like cognitive mechanisms in animals. Proceedings of the Royal Society B: Biological Sciences, 284(1865), 20171616. doi: 10.1098/rspb.2017.1616
[8] Taylor, A. H., Knaebe, B., and Gray, R. D. (2012). An end to insight? New Caledonian crows can spontaneously solve problems without planning their actions. Proceedings of the Royal Society B: Biological Sciences, 279(1749), 4977–4981. doi: 10.1098/rspb.2012.1998
[9] de Waal, F. (2016). Are we smart enough to know how smart animals are? New-York, USA: W. W. Norton and Company.
[10] Scheffer, M. (2014). The forgotten half of scientific thinking. Proceedings of the National Academy of Sciences, 111(17), 6119–6119. doi: 10.1073/pnas.1404649111
[11] Darwin, C. R. (1857). Letter to A. R. Wallace, 22 December 1857. Retrieved 30 January 2020, from
[12] Sol, D., Lefebvre, L., and Rodríguez-Teijeiro, J. D. (2005). Brain size, innovative propensity and migratory behaviour in temperate Palaearctic birds. Proceedings of the Royal Society B: Biological Sciences, 272(1571), 1433–1441. doi: 10.1098/rspb.2005.3099

Evidence of tool use in a seabird?Benjamin G. FarrarFayet, Hansen and Biro (1) provide two observations of Atlantic puffins, *Fratercula arctica*, performing self-directed actions while holding a stick in their beaks. The authors interpret this as evidence of tool use as they suggest that the stick...Behaviour & EthologyFrancois-Xavier Dechaume-Moncharmont2020-01-22 11:55:27 View
18 Mar 2019
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Evaluating functional dispersal and its eco-epidemiological implications in a nest ectoparasite

Limited dispersal in a vector on territorial hosts

Recommended by based on reviews by Shelly Lachish and 1 anonymous reviewer

Parasitism requires parasites and hosts to meet and is therefore conditioned by their respective dispersal abilities. While dispersal has been studied in a number of wild vertebrates (including in relation to infection risk), we still have poor knowledge of the movements of their parasites. Yet we know that many parasites, and in particular vectors transmitting pathogens from host to host, possess the ability to move actively during at least part of their lives.
So... how far does a vector go – and is this reflected in the population structure of the pathogens they transmit? This is the question addressed by Rataud et al. [1], who provide the first attempt at using capture-mark-recapture to estimate not only functional dispersal, but also detection probability and survival in a wild parasite that is also a vector for other pathogens.
The authors find that (i) functional dispersal of soft ticks within a gull colony is very limited. Moreover, they observe unexpected patterns: (ii) experimental displacement of ticks does not induce homing behaviour, and (iii) despite lower survival, tick dispersal was lower in nests not containing hosts than in successful nests.
These results contrast with expectations based on the distribution of infectious agents. Low tick dispersal within the colony, combined with host territoriality during breeding and high site fidelity between years should result in a spatially structured distribution of infectious agents carried by ticks. This is not the case here. One possible explanation could be that soft ticks live for much longer than a breeding season, and that they disperse at other times of year to a larger extent than usually assumed.
This study represents one chapter of a story that will likely keep unfolding. It raises fascinating questions, and illustrates the importance of basic knowledge of parasite ecology and behaviour to better understand pathogen dynamics in the wild.

[1] Rataud A., Dupraz M., Toty C., Blanchon T., Vittecoq M., Choquet R. & McCoy K.D. (2019). Evaluating functional dispersal and its eco-epidemiological implications in a nest ectoparasite. Zenodo, 2592114. Ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.5281/zenodo.2592114

Evaluating functional dispersal and its eco-epidemiological implications in a nest ectoparasiteAmalia Rataud, Marlène Dupraz, Céline Toty, Thomas Blanchon, Marion Vittecoq, Rémi Choquet, Karen D. McCoy<p>Functional dispersal (between-site movement, with or without subsequent reproduction) is a key trait acting on the ecological and evolutionary trajectories of a species, with potential cascading effects on other members of the local community. ...Dispersal & Migration, Epidemiology, Parasitology, Population ecologyAdele Mennerat2018-11-05 11:44:58 View
14 Nov 2022
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Estimating abundance of a recovering transboundary brown bear population with capture-recapture models

A new and efficient approach to estimate, from protocol and opportunistic data, the size and trends of populations: the case of the Pyrenean brown bear

Recommended by based on reviews by Tim Coulson, Romain Pigeault and ?

In this study, the authors report a new method for estimating the abundance of the Pyrenean brown bear population. Precisely, the methodology involved aims to apply Pollock's closed robust design (PCRD) capture-recapture models to estimate population abundance and trends over time. Overall, the results encourage the use of PCRD to study populations' demographic rates, while minimizing biases due to inter-individual heterogeneity in detection probabilities.

Estimating the size and trends of animal population over time is essential for informing conservation status and management decision-making (Nichols & Williams 2006). This is particularly the case when the population is small, geographically scattered, and threatened. Although several methods can be used to estimate population abundance, they may be difficult to implement when individuals are rare, elusive, solitary, largely nocturnal, highly mobile, and/or occupy large home ranges in remote and/or rugged habitats. Moreover, in such standard methods,

  • the population is assumed to be closed both geographically (no immigration nor emigration) and demographically (no births nor deaths) and
  • all individuals are assumed to have identical detection probabilities regardless of their individual attributes (e.g., age, body mass, social status) and habitat features (home-range location and composition) (Otis et al. 1978).

However, these conditions are rarely met in real populations, such as wild mammals (e.g., Bellemain et al. 2005; Solbert et al. 2006), and therefore the risk of underestimating population size can rapidly increase because the assumption of perfect detection of all individuals in the population is violated.

Focusing on the critically endangered Pyrenean brown bear that was close to extinction in the mid-1990s, the study by Vanpe et al. (2022), uses protocol and opportunistic data to describe a statistical modeling exercise to construct mark-recapture histories from 2008 to 2020. Among the data, the authors collected non-invasive samples such as a mixture of hair and scat samples used for genetic identification, as well as photographic trap data of recognized individuals. These data are then analyzed in RMark to provide detection and survival estimates. The final model (i.e. PCRD capture-recapture) is then used to provide Bayesian population estimates. Results show a five-fold increase in population size between 2008 and 2020, from 13 to 66 individuals. Thus, this study represents the first published annual abundance and temporal trend estimates of the Pyrenean brown bear population since 2008.

Then, although the results emphasize that the PCRD estimates were broadly close to the MRS counts and had reasonably narrow associated 95% Credibility Intervals, they also highlight that the sampling effort is different according to individuals. Indeed, as expected, the detection of an individual depends on

  • the intraspecific home range size variation that results in individuals that move the most being most likely to be detected and
  • the mortality rate which is higher on cubs than on adults and subadults (due to infanticide by males, predation, death of the mother, or abandonment).

Overall, the PCRD capture-recapture modelling approach, involved in this study, provides robust estimates of abundance and demographic rates of the Pyrenean brown bear population (with associated uncertainty) while minimizing and considering bias due to inter-individual heterogeneity in detection probabilities.

The authors conclude that mark-recapture provides useful population estimates and urge wildlife ecologists and managers to use robust approaches, such as the RDPC capture-recapture model, when studying large mammal populations. This information is essential to inform management decisions and assess the conservation status of populations.



Bellemain, E.V.A., Swenson, J.E., Tallmon, D., Brunberg, S. and Taberlet, P. (2005). Estimating population size of elusive animals with DNA from hunter-collected feces: four methods for brown bears. Cons. Biol. 19(1), 150-161.

Nichols, J.D. and Williams, B.K. (2006). Monitoring for conservation. Trends Ecol. Evol. 21(12), 668-673.

Otis, D.L., Burnham, K.P., White, G.C. and Anderson, D.R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs (62), 3-135.

Solberg, K.H., Bellemain, E., Drageset, O.M., Taberlet, P. and Swenson, J.E. (2006). An evaluation of field and non-invasive genetic methods to estimate brown bear (Ursus arctos) population size. Biol. Conserv. 128(2), 158-168.

Vanpé C, Piédallu B, Quenette P-Y, Sentilles J, Queney G, Palazón S, Jordana IA, Jato R, Elósegui Irurtia MM, de la Torre JS, and Gimenez O (2022) Estimating abundance of a recovering transboundary brown bear population with capture-recapture models. bioRxiv, 2021.12.08.471719, ver. 4 recommended and peer-reviewed by PCI Ecology.

Estimating abundance of a recovering transboundary brown bear population with capture-recapture modelsCécile Vanpé, Blaise Piédallu, Pierre-Yves Quenette, Jérôme Sentilles, Guillaume Queney, Santiago Palazón, Ivan Afonso Jordana, Ramón Jato, Miguel Mari Elósegui Irurtia, Jordi Solà de la Torre, Olivier Gimenez<p>Estimating the size of small populations of large mammals can be achieved via censuses, or complete counts, of recognizable individuals detected over a time period: minimum detected (population) size (MDS). However, as a population grows larger...Conservation biology, Demography, Population ecologyNicolas BECH2022-01-20 10:49:59 View
30 Mar 2020
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Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America

Catching the fly in dystopian times

Recommended by based on reviews by 4 anonymous reviewers

Host-parasite interactions are ubiquitous on Earth. They are present in almost every conceivable ecosystem and often result from a long history of antagonist coevolution [1,2]. Recent studies on climate change have revealed, however, that modification of abiotic variables are often accompanied by shifts in the distributional range of parasites to habitats far beyond their original geographical distribution, creating new interactions in novel habitats with unpredictable consequences for host community structure and organization [3,4]. This situation may be especially critical for endangered host species having small population abundance and restricted distribution range. The infestation of bird species with larvae of the muscid fly genus Philornis is a case in point. At least 250 bird species inhabiting mostly Central and South America are infected by Philornis flies [5,6]. Fly larval development occurs in bird faeces, nesting material, or inside nestlings, affecting the development and nestling survival.
Recent reports indicate significant reduction of bird numbers associated with recent Philornis infection, the most conspicuous being Galapagos finches [7,8]. One way to prevent this potential effect consists in to examine the expected geographical shift of Philornis fly species under future climate change scenarios so that anticipatory conservation practices become implemented for endangered bird species. In this regard, Ecological Niche Modeling (ENM) techniques have been increasingly used as a useful tool to predict disease transmission as well as the species becoming infected under different climate change scenarios [9-11]. The paper of Cuervo et al. [12] is an important advance in this regard. By identifying for the first time the macro-environmental variables influencing the abiotic niche of species of the Philornis torquans complex in southern South America, the authors perform a geographical projection model that permits identification of the areas susceptible to be colonized by Philornis species in Argentina, Brazil, and Chile, including habitats where the parasitic fly is still largely absent at present. Their results are promissory for conservation studies and contribute to the still underdeveloped issue of the way climate change impacts on antagonistic ecological relationships.


[1] Thompson JN (1994) The Coevolutionary Process. University of Chicago Press.
[2] Poulin R (2007) Evolutionary Ecology of Parasites: (Second Edition). Princeton University Press. doi: 10.2307/j.ctt7sn0x
[3] Pickles RSA, Thornton D, Feldman R, Marques A, Murray DL (2013) Predicting shifts in parasite distribution with climate change: a multitrophic level approach. Global Change Biology, 19, 2645–2654. doi: 10.1111/gcb.12255
[4] Marcogliese DJ (2016) The distribution and abundance of parasites in aquatic ecosystems in a changing climate: More than just temperature. Integrative and Comparative Biology, 56, 611–619. doi: 10.1093/icb/icw036
[5] Dudaniec RY, Kleindorfer S (2006) Effects of the parasitic flies of the genus Philornis (Diptera: Muscidae) on birds. Emu - Austral Ornithology, 106, 13–20. doi: 10.1071/MU04040
[6] Antoniazzi LR, Manzoli DE, Rohrmann D, Saravia MJ, Silvestri L, Beldomenico PM (2011) Climate variability affects the impact of parasitic flies on Argentinean forest birds. Journal of Zoology, 283, 126–134. doi: 10.1111/j.1469-7998.2010.00753.x
[7] Fessl B, Sinclair BJ, Kleindorfer S (2006) The life-cycle of Philornis downsi (Diptera: Muscidae) parasitizing Darwin’s finches and its impacts on nestling survival. Parasitology, 133, 739–747. doi: 10.1017/S0031182006001089
[8] Kleindorfer S, Peters KJ, Custance G, Dudaniec RY, O’Connor JA (2014) Changes in Philornis infestation behavior threaten Darwin’s finch survival. Current Zoology, 60, 542–550. doi: 10.1093/czoolo/60.4.542
[9] Johnson EE, Escobar LE, Zambrana-Torrelio C (2019) An ecological framework for modeling the geography of disease transmission. Trends in Ecology and Evolution, 34, 655–668. doi: 10.1016/j.tree.2019.03.004
[10] Carvalho BM, Rangel EF, Ready PD, Vale MM (2015) Ecological niche modelling predicts southward expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), vector of Leishmania (Leishmania) amazonensis in South America, under climate change. PLOS ONE, 10, e0143282. doi: 10.1371/journal.pone.0143282
[11] Garrido R, Bacigalupo A, Peña-Gómez F, Bustamante RO, Cattan PE, Gorla DE, Botto-Mahan C (2019) Potential impact of climate change on the geographical distribution of two wild vectors of Chagas disease in Chile: Mepraia spinolai and Mepraia gajardoi. Parasites and Vectors, 12, 478. doi: 10.1186/s13071-019-3744-9
[12] Cuervo PF, Percara A, Monje L, Beldomenico PM, Quiroga MA (2020) Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America. bioRxiv, 839589, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/839589

Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South AmericaPablo F. Cuervo, Alejandro Percara, Lucas Monje, Pablo M. Beldomenico, Martín A. Quiroga<p>*Philornis* flies are the major cause of myasis in altricial nestlings of neotropical birds. Its impact ranges from subtle to lethal, being of major concern in endangered bird species with geographically-restricted, fragmented and small-sized p...Biogeography, Macroecology, Parasitology, Species distributionsRodrigo Medel2019-11-26 21:31:33 View
16 Jun 2020
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Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback framework

Stasis and the phenotypic gambit

Recommended by based on reviews by Jacob Johansson, Katja Räsänen and 1 anonymous reviewer

The preprint "Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback framework" by Coulson (2020) presents a general framework for evolutionary ecology, useful to interpret patterns of selection and evolutionary responses to environmental transitions. The paper is written in an accessible and intuitive manner. It reviews important concepts which are at the heart of evolutionary ecology. Together, they serve as a worldview which you can carry with you to interpret patterns in data or observations in nature. I very much appreciate it that Coulson (2020) presents his personal intuition laid bare, the framework he uses for his research and how several strong concepts from theoretical ecology fit in there. Overviews as presented in this paper are important to understand how we as researchers put the pieces together.
A main message of the paper is that resource detection and acquisition traits, broadly called "resource accrual traits" are at the core of evolutionary dynamics. These traits and the processes they are involved in often urge some degree of individual specialization. Not all traits are resource accrual traits all the time. Guppies are cited as an example, which have traits in high predation environments that make foraging easier for them, such as being less conspicuous to predators. In the absence of predators, these same traits might be neutral. Their colour pattern might then contribute much less to the odds of obtaining resources.
"Resource accrual" reminds me of discussions of resource holding potential (Parker 1974), which can be for example the capacity to remain on a bird feeder without being dislodged. However, the idea is much broader and aggression does not need to be important for the acquisition of resources. Evolutionary success is reserved for those steadily obtaining resources. This recalls the pessimization principle of Metz et al. (2008), which applies in a restricted set of situations and where the strategy which persists at the lowest resource levels systematically wins evolutionary contests. If this principle would apply universally, the world then inherently become the worst possible. Resources determine energy budgets and different life history strategies allocate these differently to maximize fitness. The fine grain of environments and the filtration by individual histories generate a lot of variation in outcomes. However, constraint-centered approaches (Kempes et al. 2019, Kooijman 2010) are mentioned but are not at the core of this preprint. Evolution is rather seen as dynamic programming optimization with interactions within and between species. Coulson thus extends life history studies such as for example Tonnabel et al. (2012) with eco-evolutionary feedbacks. Examples used are guppies, algae-rotifer interactions and others. Altogether, this makes for an optimistic paper pushing back the pessimization principle.
Populations are expected to spend most of the time in quasi-equilibrium states where the long run stochastic growth rate is close to zero for all genotypes, alleles or other chosen classes. In the preprint, attention is given to reproductive value calculus, another strong tool in evolutionary dynamics (Grafen 2006, Engen et al. 2009), which tells us how classes within a population contribute to population composition in the distant future. The expected asymptotic fitness of an individual is equated to its expected reproductive value, but this might require particular ways of calculating reproductive values (Coulson 2020). Life history strategies can also be described by per generation measures such as R0 (currently on everyone's radar due to the coronavirus pandemic), generation time etc. Here I might disagree because I believe that this focus in per generation measures can lead to an incomplete characterization of plastic and other strategies involved in strategies such as bet-hedging. A property at quasi-equilibrium states is precise enough to serve as a null hypothesis which can be falsified: all types must in the long run leave equal numbers of descendants. If there is any property in evolutionary ecology which is useful it is this one and it rightfully merits attention.
However, at quasi-equilibrium states, directional selection has been observed, often without the expected evolutionary response. The preprint aims to explain this and puts forward the presence of non-additive gene action as a mechanism. I don't believe that it is the absence of clonal inheritance which matters very much in itself (Van Dooren 2006) unless genes with major effect are present in protected polymorphisms. The preprint remains a bit unclear on how additive gene action is broken, and here I add from the sphere in which I operate. Non-additive gene action can be linked to non-linear genotype-phenotype maps (Van Dooren 2000, Gilchrist and Nijhout 2001) and if these maps are non-linear enough to create constraints on phenotype determination, by means of maximum or minimum phenotypes which cannot be surpassed for any combination of the underlying traits, then they create additional evolutionary quasi-equilibrium states, with directional selection on a phenotype such as body size. I believe Coulson hints at this option (Coulson et al. 2006), but also at a different one: if body size is mostly determined by variation in resource accrual traits, then the resource accrual traits can be under stabilizing selection while body size is not. This requires that all resource accrual traits affect other phenotypic or demographic properties next to body size. In both cases, microevolutionary outcomes cannot be inferred from inspecting body sizes alone, either resource accrual traits need to be included explicitly, or non-linearities, or both when the map between resource accrual and body size is non-linear (Van Dooren 2000).
The discussion of the phenotypic gambit (Grafen 1984) leads to another long-standing issue in evolutionary biology. Can predictions of adaptation be made by inspecting and modelling individual phenotypes alone? I agree that with strongly non-linear genotype-phenotype maps they cannot and for multivariate sets of traits, genetic and phenotypic correlations can be very different (Hadfield et al. 2007). However, has the phenotypic gambit ever claimed to be valid globally or should it rather be used locally for relatively small amounts of variation? Grafen (1984) already contained caveats which are repeated here. As a first approximation, additivity might produce quite correct predictions and thus make the gambit operational in many instances. When important individual traits are omitted, it may just be misspecified. I am interested to see cases where the framework Coulson (2020) proposes is used for very large numbers of phenotypic and genotypic attributes. In the end, these highly dimensional trait distributions might basically collapse to a few major axes of variation due to constraints on resource accrual.
I highly recommend reading this preprint and I am looking forward to the discussion it will generate.


[1] Coulson, T. (2020) Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback framework. bioRxiv, 509067, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/509067
[2] Coulson, T., Benton, T. G., Lundberg, P., Dall, S. R. X., and Kendall, B. E. (2006). Putting evolutionary biology back in the ecological theatre: a demographic framework mapping genes to communities. Evolutionary Ecology Research, 8(7), 1155-1171.
[3] Engen, S., Lande, R., Sæther, B. E. and Dobson, F. S. (2009) Reproductive value and the stochastic demography of age-structured populations. The American Naturalist 174: 795-804. doi: 10.1086/647930
[4] Gilchrist, M. A. and Nijhout, H. F. (2001). Nonlinear developmental processes as sources of dominance. Genetics, 159(1), 423-432.
[5] Grafen, A. (1984) Natural selection, kin selection and group selection. In: Behavioural Ecology: An Evolutionary Approach,2nd edn (JR Krebs & NB Davies eds), pp. 62–84. Blackwell Scientific, Oxford.
[6] Grafen, A. (2006). A theory of Fisher's reproductive value. Journal of mathematical biology, 53(1), 15-60. doi: 10.1007/s00285-006-0376-4
[7] Hadfield, J. D., Nutall, A., Osorio, D. and Owens, I. P. F. (2007). Testing the phenotypic gambit: phenotypic, genetic and environmental correlations of colour. Journal of evolutionary biology, 20(2), 549-557. doi: 10.1111/j.1420-9101.2006.01262.x
[8] Kempes, C. P., West, G. B., and Koehl, M. (2019). The scales that limit: the physical boundaries of evolution. Frontiers in Ecology and Evolution, 7, 242. doi: 10.3389/fevo.2019.00242
[9] Kooijman, S. A. L. M. (2010) Dynamic Energy Budget theory for metabolic organisation. University Press, third edition.
[10] Metz, J. A. J., Mylius, S.D. and Diekman, O. (2008) When does evolution optimize?. Evolutionary Ecology Research 10: 629-654.
[11] Parker, G. A. (1974). Assessment strategy and the evolution of fighting behaviour. Journal of theoretical Biology, 47(1), 223-243. doi: 10.1016/0022-5193(74)90111-8
[12] Tonnabel, J., Van Dooren, T. J. M., Midgley, J., Haccou, P., Mignot, A., Ronce, O., and Olivieri, I. (2012). Optimal resource allocation in a serotinous non‐resprouting plant species under different fire regimes. Journal of Ecology, 100(6), 1464-1474. doi: 10.1111/j.1365-2745.2012.02023.x
[13] Van Dooren, T. J. M. (2000). The evolutionary dynamics of direct phenotypic overdominance: emergence possible, loss probable. Evolution, 54(6), 1899-1914. doi: 10.1111/j.0014-3820.2000.tb01236.x
[14] Van Dooren, T. J. M. (2006). Protected polymorphism and evolutionary stability in pleiotropic models with trait‐specific dominance. Evolution, 60(10), 1991-2003. doi: 10.1111/j.0014-3820.2006.tb01837.x

Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback frameworkTim Coulson<p>I provide a general framework for linking ecology and evolution. I start from the fact that individuals require energy, trace molecules, water, and mates to survive and reproduce, and that phenotypic resource accrual traits determine an individ...Eco-evolutionary dynamics, Evolutionary ecologyTom Van Dooren2019-01-03 10:05:16 View