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Latest recommendations
Id | Title * | Authors * | Abstract * ▼ | Picture * | Thematic fields * | Recommender | Reviewers | Submission date | |
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22 Nov 2021
When more competitors means less harvested resourceRecommended by François Munoz based on reviews by Francois Massol, Jeremy Van Cleve and 1 anonymous reviewerIn this paper, Alan R. Rogers (2021) examines the dynamics of foraging strategies for a resource that gains value over time (e.g., ripening fruits), while there is a fixed cost of attempting to forage the resource, and once the resource is harvested nothing is left for other harvesters. For this model, not any pure foraging strategy is evolutionary stable. A mixed equilibrium exists, i.e., with a mixture of foraging strategies within the population, which is still evolutionarily unstable. Nonetheless, Alan R. Rogers shows that for a large number of competitors and/or high harvesting cost, the mixture of strategies remains close to the mixed equilibrium when simulating the dynamics. Surprisingly, in a large population individuals will less often attempt to forage the resource and will instead “go fishing”. The paper also exposes an experiment of the game with students, which resulted in a strategy distribution somehow close to the theoretical mixture of strategies. The economist John F. Nash Jr. (1950) gained the Nobel Prize of economy in 1994 for his game theoretical contributions. He gave his name to the “Nash equilibrium”, which represents a set of individual strategies that is reached whenever all the players have nothing to gain by changing their strategy while the strategies of others are unchanged. Alan R. Rogers shows that the mixed equilibrium in the foraging game is such a Nash equilibrium. Yet it is evolutionarily unstable insofar as a distribution close to the equilibrium can invade. The insights of the study are twofold. First, it sheds light on the significance of Nash equilibrium in an ecological context of foraging strategies. Second, it shows that an evolutionarily unstable state can rule the composition of the ecological system. Therefore, the contribution made by the paper should be most significant to better understand the dynamics of competitive communities and their eco-evolutionary trajectories. References Nash JF (1950) Equilibrium points in n-person games. Proceedings of the National Academy of Sciences, 36, 48–49. https://doi.org/10.1073/pnas.36.1.48 Rogers AR (2021) Beating your Neighbor to the Berry Patch. bioRxiv, 2020.11.12.380311, ver. 8 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2020.11.12.380311
| Beating your neighbor to the berry patch | Alan R. Rogers | <p style="text-align: justify;">Foragers often compete for resources that ripen (or otherwise improve) gradually. What strategy is optimal in this situation? It turns out that there is no optimal strategy. There is no evolutionarily stable strateg... | Behaviour & Ethology, Evolutionary ecology, Foraging | François Munoz | Erol Akçay, Jorge Peña, Sébastien Lion, François Rousset, Ulf Dieckmann , Troy Day , Corina Tarnita , Florence Debarre , Daniel Friedman , Vlastimil Krivan , Ulf Dieckmann | 2020-12-10 18:38:49 | View | |
11 Oct 2023
Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysisCédric Hubas, Julie Gaubert-Boussarie, An-Sofie D’Hondt, Bruno Jesus, Dominique Lamy, Vona Meleder, Antoine Prins, Philippe Rosa, Willem Stock, Koen Sabbe https://doi.org/10.1101/2022.12.02.516908Disentangling microbial exopolymer dynamics in intertidal sedimentsRecommended by Ute Risse-Buhl and Nils Rädecker based on reviews by 2 anonymous reviewersThe secretion of extracellular polymeric substances (EPS) enables microorganisms to shape and interact with their environment [1]. EPS support cell adhesion and motility, offer protection from unfavorable conditions, and facilitate nutrient acquisition and transfer between microorganisms [2]. EPS production and consumption thus control the formation and structural organization of biofilms [3]. However, in marine environments, our understanding of the sources and composition of EPS is limited. References
| Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis | Cédric Hubas, Julie Gaubert-Boussarie, An-Sofie D’Hondt, Bruno Jesus, Dominique Lamy, Vona Meleder, Antoine Prins, Philippe Rosa, Willem Stock, Koen Sabbe | <p style="text-align: justify;">Extracellular polymeric substances (EPS) refer to a wide variety of high molecular weight molecules secreted outside the cell membrane by biofilm microorganisms. In the present study, EPS from marine microphytobenth... | Biodiversity, Ecological stoichiometry, Ecosystem functioning, Food webs, Marine ecology, Microbial ecology & microbiology, Soil ecology | Ute Risse-Buhl | 2022-12-06 14:13:11 | View | ||
25 May 2021
Clumpy coexistence in phytoplankton: The role of functional similarity in community assemblyCaio Graco-Roza, Angel M. Segura, Carla Kruk, Patricia Domingos, Janne Soininen, Marcelo M. Marinho https://doi.org/10.1101/869966Environmental heterogeneity drives phytoplankton community assembly patterns in a tropical riverine systemRecommended by Cédric Hubas and Eric Goberville based on reviews by Eric Goberville and Dominique LamyWhat predisposes two individuals to form and maintain a relationship is a fundamental question. Using facial recognition to see whether couples' faces change over time to become more and more similar, psychology researchers have concluded that couples tend to be formed from the start between people whose faces are more similar than average [1]. As the saying goes, birds of a feather flock together. And what about in nature? Are these rules of assembly valid for communities of different species? In his seminal contribution, Robert MacArthur (1984) wrote ‘To do science is to search for repeated patterns’ [2]. Identifying the mechanisms that govern the arrangement of life is a hot research topic in the field of ecology for decades, and an absolutely essential prerequisite to answer the outstanding question of what shape ecological patterns in multi-species communities such as species-area relationships, relative species abundances, or spatial and temporal turnover of community composition; amid others [3]. To explain ecological patterns in nature, some rely on the concept that every species - through evolutionary processes and the acquisition of a unique set of traits that allow a species to be adapted to its abiotic and biotic environment - occupies a unique niche: Species coexistence comes as the result of niche differentiation [4,5]. Such a view has been challenged by the recognition of the key role of neutral processes [6], however, in which demographic stochasticity contributes to shape multi-species communities and to explain why congener species coexist much more frequently than expected by chance [7,8]. While the niche-based and neutral theories appear seemingly opposed at first sight [9], the dichotomy may be more philosophical than empirical [4,5]. Many examples have come to support that both concepts are not incompatible as they together influence the structure, diversity and functioning of communities [10], and are simply extreme cases of a continuum [11]. From this perspective, extrinsic factors, i.e., environmental heterogeneity, may influence the location of a given community along the niche-neutrality continuum. The walk of species in nature is therefore neither random nor ecologically predestined. In microbial assemblages, the co-existence of these two antagonistic mechanisms has been shown both theoretically and empirically. It has been shown that a combination of stabilising (niche) and equalising (neutral) mechanisms was responsible for the existence of groups of coexistent species (clumps) in a phytoplankton rich community [12]. Analysing interannual changes (2003-2009) in the weekly abundance of diatoms and dinoflagellates located in a temperate coastal ecosystem of the Western English Channel, Mutshinda et al. [13] found a mixture of biomass dynamics consistent with the neutrality-niche continuum hypothesis. While niche processes explained the dynamic of phytoplankton functional groups (i.e., diatoms vs. dinoflagellates) in terms of biomass, neutral processes mainly dominated - 50 to 75% of the time - the dynamics at the species level within functional groups [13]. From one endpoint to another, defining the location of a community along the continuum is all matter of scale [4,11]. In their study, testing predictions made by an emergent neutrality model, Graco-Roza et al. [14] provide empirical evidence that neutral and niche processes joined together to shape and drive planktonic communities in a riverine ecosystem. Body size - the 'master trait' - is used here as a discriminant ecological dimension along the niche axis. From their analysis, they not only show that the specific abundance is organised in clumps and gaps along the niche axis, but also reveal that different clumps exist along the river course. They identify two main clumps in body size - with species belonging to three different morphologically-based functional groups - and characterise that among-species differences in biovolume are driven by functional redundancy at the clump level; species functional distinctiveness being related to the relative biovolume of species. By grouping their variables according to seasons (cold-dry vs. warm-wet) or river elevation profile (upper, medium and lower course), they hereby highlight how environmental heterogeneity contributes to shape species assemblages and their dynamics and conclude that emergent neutrality models are a powerful approach to explain species coexistence; and therefore ecological patterns. References [1] Tea-makorn PP, Kosinski M (2020) Spouses’ faces are similar but do not become more similar with time. Scientific Reports, 10, 17001. https://doi.org/10.1038/s41598-020-73971-8. [2] MacArthur RH (1984) Geographical Ecology: Patterns in the Distribution of Species. Princeton University Press. [3] Vellend M (2020) The Theory of Ecological Communities (MPB-57). Princeton University Press. [4] Wennekes PL, Rosindell J, Etienne RS (2012) The Neutral—Niche Debate: A Philosophical Perspective. Acta Biotheoretica, 60, 257–271. https://doi.org/10.1007/s10441-012-9144-6. [5] Gravel D, Guichard F, Hochberg ME (2011) Species coexistence in a variable world. Ecology Letters, 14, 828–839. https://doi.org/10.1111/j.1461-0248.2011.01643.x. [6] Hubbell SP (2001) The Unified Neutral Theory of Biodiversity and Biogeography (MPB-32). Princeton University Press. [7] Leibold MA, McPeek MA (2006) Coexistence of the Niche and Neutral Perspectives in Community Ecology. Ecology, 87, 1399–1410. https://doi.org/10.1890/0012-9658(2006)87[1399:COTNAN]2.0.CO;2. [8] Pielou EC (1977) The Latitudinal Spans of Seaweed Species and Their Patterns of Overlap. Journal of Biogeography, 4, 299–311. https://doi.org/10.2307/3038189. [9] Holt RD (2006) Emergent neutrality. Trends in Ecology & Evolution, 21, 531–533. https://doi.org/10.1016/j.tree.2006.08.003. [10] Scheffer M, Nes EH van (2006) Self-organized similarity, the evolutionary emergence of groups of similar species. Proceedings of the National Academy of Sciences, 103, 6230–6235. https://doi.org/10.1073/pnas.0508024103. [11] Gravel D, Canham CD, Beaudet M, Messier C (2006) Reconciling niche and neutrality: the continuum hypothesis. Ecology Letters, 9, 399–409. https://doi.org/10.1111/j.1461-0248.2006.00884.x. [12] Vergnon R, Dulvy NK, Freckleton RP (2009) Niches versus neutrality: uncovering the drivers of diversity in a species-rich community. Ecology Letters, 12, 1079–1090. https://doi.org/10.1111/j.1461-0248.2009.01364.x. [13] Mutshinda CM, Finkel ZV, Widdicombe CE, Irwin AJ (2016) Ecological equivalence of species within phytoplankton functional groups. Functional Ecology, 30, 1714–1722. https://doi.org/10.1111/1365-2435.12641. [14] Graco-Roza C, Segura AM, Kruk C, Domingos P, Soininen J, Marinho MM (2021) Clumpy coexistence in phytoplankton: The role of functional similarity in community assembly. bioRxiv, 869966, ver. 6 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/869966
| Clumpy coexistence in phytoplankton: The role of functional similarity in community assembly | Caio Graco-Roza, Angel M. Segura, Carla Kruk, Patricia Domingos, Janne Soininen, Marcelo M. Marinho | <p style="text-align: justify;">Emergent neutrality (EN) suggests that species must be sufficiently similar or sufficiently different in their niches to avoid interspecific competition. Such a scenario results in a transient pattern with clumps an... | Coexistence, Community ecology, Theoretical ecology | Cédric Hubas | 2020-01-23 16:11:32 | View | ||
03 Jun 2022
Evolutionary emergence of alternative stable states in shallow lakesAlice Ardichvili, Nicolas Loeuille, Vasilis Dakos https://doi.org/10.1101/2022.02.23.481597How to evolve an alternative stable stateRecommended by Tim Coulson based on reviews by Jean-François Arnoldi and 1 anonymous reviewerAlternative 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. References 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. https://doi.org/10.1101/2022.02.23.481597 | Evolutionary emergence of alternative stable states in shallow lakes | Alice 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 ecology | Tim Coulson | 2022-03-01 10:54:05 | View | ||
12 Sep 2023
Linking intrinsic scales of ecological processes to characteristic scales of biodiversity and functioning patternsYuval R. Zelnik, Matthieu Barbier, David W. Shanafelt, Michel Loreau, Rachel M. Germain https://doi.org/10.1101/2021.10.11.463913The impact of process at different scales on diversity and ecosystem functioning: a huge challengeRecommended by David Alonso based on reviews by Shai Pilosof, Gian Marco Palamara and 1 anonymous reviewerScale is a big topic in ecology [1]. Environmental variation happens at particular scales. The typical scale at which organisms disperse is species-specific, but, as a first approximation, an ensemble of similar species, for instance, trees, could be considered to share a typical dispersal scale. Finally, characteristic spatial scales of species interactions are, in general, different from the typical scales of dispersal and environmental variation. Therefore, conceptually, we can distinguish these three characteristic spatial scales associated with three different processes: species selection for a given environment (E), dispersal (D), and species interactions (I), respectively. From the famous species-area relation to the spatial distribution of biomass and species richness, the different macro-ecological patterns we usually study emerge from an interplay between dispersal and local interactions in a physical environment that constrains species establishment and persistence in every location. To make things even more complicated, local environments are often modified by the species that thrive in them, which establishes feedback loops. It is usually assumed that local interactions are short-range in comparison with species dispersal, and dispersal scales are typically smaller than the scales at which the environment varies (I < D < E, see [2]), but this should not always be the case. The authors of this paper [2] relax this typical assumption and develop a theoretical framework to study how diversity and ecosystem functioning are affected by different relations between the typical scales governing interactions, dispersal, and environmental variation. This is a huge challenge. First, diversity and ecosystem functioning across space and time have been empirically characterized through a wide variety of macro-ecological patterns. Second, accommodating local interactions, dispersal and environmental variation and species environmental preferences to model spatiotemporal dynamics of full ecological communities can be done also in a lot of different ways. One can ask if the particular approach suggested by the authors is the best choice in the sense of producing robust results, this is, results that would be predicted by alternative modeling approaches and mathematical analyses [3]. The recommendation here is to read through and judge by yourself. The main unusual assumption underlying the model suggested by the authors is non-local species interactions. They introduce interaction kernels to weigh the strength of the ecological interaction with distance, which gives rise to a system of coupled integro-differential equations. This kernel is the key component that allows for control and varies the scale of ecological interactions. Although this is not new in ecology [4], and certainly has a long tradition in physics ---think about the electric or the gravity field, this approach has been widely overlooked in the development of the set of theoretical frameworks we have been using over and over again in community ecology, such as the Lotka-Volterra equations or, more recently, the metacommunity concept [5]. In Physics, classic fields have been revised to account for the fact that information cannot travel faster than light. In an analogous way, a focal individual cannot feel the presence of distant neighbors instantaneously. Therefore, non-local interactions do not exist in ecological communities. As the authors of this paper point out, they emerge in an effective way as a result of non-random movements, for instance, when individuals go regularly back and forth between environments (see [6], for an application to infectious diseases), or even migrate between regions. And, on top of this type of movement, species also tend to disperse and colonize close (or far) environments. Individual mobility and dispersal are then two types of movements, characterized by different spatial-temporal scales in general. Species dispersal, on the one hand, and individual directed movements underlying species interactions, on the other, are themselves diverse across species, but it is clear that they exist and belong to two distinct categories. In spite of the long and rich exchange between the authors' team and the reviewers, it was not finally clear (at least, to me and to one of the reviewers) whether the model for the spatio-temporal dynamics of the ecological community (see Eq (1) in [2]) is only presented as a coupled system of integro-differential equations on a continuous landscape for pedagogical reasons, but then modeled on a discrete regular grid for computational convenience. In the latter case, the system represents a regular network of local communities, becomes a system of coupled ODEs, and can be numerically integrated through the use of standard algorithms. By contrast, in the former case, the system is meant to truly represent a community that develops on continuous time and space, as in reaction-diffusion systems. In that case, one should keep in mind that numerical instabilities can arise as an artifact when integrating both local and non-local spatio-temporal systems. Spatial patterns could be then transient or simply result from these instabilities. Therefore, when analyzing spatiotemporal integro-differential equations, special attention should be paid to the use of the right numerical algorithms. The authors share all their code at https://zenodo.org/record/5543191, and all this can be checked out. In any case, the whole discussion between the authors and the reviewers has inherent value in itself, because it touches on several limitations and/or strengths of the author's approach, and I highly recommend checking it out and reading it through. Beyond these methodological issues, extensive model explorations for the different parameter combinations are presented. Several results are reported, but, in practice, what is then the main conclusion we could highlight here among all of them? The authors suggest that "it will be difficult to manage landscapes to preserve biodiversity and ecosystem functioning simultaneously, despite their causative relationship", because, first, "increasing dispersal and interaction scales had opposing References [1] Levin, S. A. 1992. The problem of pattern and scale in ecology. Ecology 73:1943–1967. https://doi.org/10.2307/1941447 [2] Yuval R. Zelnik, Matthieu Barbier, David W. Shanafelt, Michel Loreau, Rachel M. Germain. 2023. Linking intrinsic scales of ecological processes to characteristic scales of biodiversity and functioning patterns. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2021.10.11.463913 [3] Baron, J. W. and Galla, T. 2020. Dispersal-induced instability in complex ecosystems. Nature Communications 11, 6032. https://doi.org/10.1038/s41467-020-19824-4 [4] Cushing, J. M. 1977. Integrodifferential equations and delay models in population dynamics [5] M. A. Leibold, M. Holyoak, N. Mouquet, P. Amarasekare, J. M. Chase, M. F. Hoopes, R. D. Holt, J. B. Shurin, R. Law, D. Tilman, M. Loreau, A. Gonzalez. 2004. The metacommunity concept: a framework for multi-scale community ecology. Ecology Letters, 7(7): 601-613. https://doi.org/10.1111/j.1461-0248.2004.00608.x [6] M. Pardo-Araujo, D. García-García, D. Alonso, and F. Bartumeus. 2023. Epidemic thresholds and human mobility. Scientific reports 13 (1), 11409. https://doi.org/10.1038/s41598-023-38395-0 | Linking intrinsic scales of ecological processes to characteristic scales of biodiversity and functioning patterns | Yuval R. Zelnik, Matthieu Barbier, David W. Shanafelt, Michel Loreau, Rachel M. Germain | <p style="text-align: justify;">Ecology is a science of scale, which guides our description of both ecological processes and patterns, but we lack a systematic understanding of how process scale and pattern scale are connected. Recent calls for a ... | Biodiversity, Community ecology, Dispersal & Migration, Ecosystem functioning, Landscape ecology, Theoretical ecology | David Alonso | 2021-10-13 23:24:45 | View | ||
01 Mar 2022
Dissimilarity of species interaction networks: quantifying the effect of turnover and rewiringTimothée Poisot https://doi.org/10.32942/osf.io/gxhu2How to evaluate and interpret the contribution of species turnover and interaction rewiring when comparing ecological networks?Recommended by François Munoz based on reviews by Ignasi Bartomeus and 1 anonymous reviewerA network includes a set of vertices or nodes (e.g., species in an interaction network), and a set of edges or links (e.g., interactions between species). Whether and how networks vary in space and/or time are questions often addressed in ecological research. Two ecological networks can differ in several extents: in that species are different in the two networks and establish new interactions (species turnover), or in that species that are present in both networks establish different interactions in the two networks (rewiring). The ecological meaning of changes in network structure is quite different according to whether species turnover or interaction rewiring plays a greater role. Therefore, much attention has been devoted in recent years on quantifying and interpreting the relative changes in network structure due to species turnover and/or rewiring. Poisot et al. (2012) proposed to partition the global variation in structure between networks, \( \beta_{WN} \) (WN = Whole Network) into two terms: \( \beta_{OS} \) (OS = Only Shared species) and \( \beta_{ST} \) (ST = Species Turnover), such as \( \beta_{WN} = \beta_{OS} + \beta_{ST} \). The calculation lays on enumerating the interactions between species that are common or not to two networks, as illustrated on Figure 1 for a simple case. Specifically, Poisot et al. (2012) proposed to use a Sorensen type measure of network dissimilarity, i.e., \( \beta_{WN} = \frac{a+b+c}{(2a+b+c)/2} -1=\frac{b+c}{2a+b+c} \) , where \( a \) is the number of interactions shared between the networks, while \( b \) and \( c \) are interaction numbers unique to one and the other network, respectively. \( \beta_{OS} \) is calculated based on the same formula, but only for the subnetworks including the species common to the two networks, in the form \( \beta_{OS} = \frac{b_{OS}+c_{OS}}{2a_{OS}+b_{OS}+c_{OS}} \) (e.g., Fig. 1). \( \beta_{ST} \) is deduced by subtracting \( \beta_{OS} \) from \( \beta_{WN} \) and represents in essence a "dissimilarity in interaction structure introduced by dissimilarity in species composition" (Poisot et al. 2012). Figure 1. Ecological networks exemplified in Fründ (2021) and discussed in Poisot (2022). a is the number of shared links (continuous lines in right figures), while b+c is the number of edges unique to one or the other network (dashed lines in right figures). Alternatively, Fründ (2021) proposed to define \( \beta_{OS} = \frac{b_{OS}+c_{OS}}{2a+b+c} \) and \( \beta_{ST} = \frac{b_{ST}+c_{ST}}{2a+b+c} \), where \( b_{ST}=b-b_{OS} \) and \( c_{ST}=c-c_{OS} \) , so that the components \( \beta_{OS} \) and \( \beta_{ST} \) have the same denominator. In this way, Fründ (2021) partitioned the count of unique \( b+c=b_{OS}+b_{ST}+c_{ST} \) interactions, so that \( \beta_{OS} \) and \( \beta_{ST} \) sums to \( \frac{b_{OS}+c_{OS}+b_{ST}+c_{ST}}{2a+b+c} = \frac{b+c}{2a+b+c} = \beta_{WN} \). Fründ (2021) advocated that this partition allows a more sensible comparison of \( \beta_{OS} \) and \( \beta_{ST} \), in terms of the number of links that contribute to each component. For instance, let us consider the networks 1 and 2 in Figure 1 (left panel) such as \( a_{OS}=2 \) (continuous lines in right panel), \( b_{ST} + c_{ST} = 1 \) and \( b_{OS} + c_{OS} = 1 \) (dashed lines in right panel), and thereby \( a = 2 \), \( b+c=2 \), \( \beta_{WN} = 1/3 \). Fründ (2021) measured \( \beta_{OS}=\beta_{ST}=1/6 \) and argued that it is appropriate insofar as it reflects that the number of unique links in the OS and ST components contributing to network dissimilarity (dashed lines) are actually equal. Conversely, the formula of Poisot et al. (2012) yields \( \beta_{OS}=1/5 \), hence \( \beta_{ST} = \frac{1}{3}-\frac{1}{5}=\frac{2}{15}<\beta_{OS} \). Fründ (2021) thus argued that the method of Poisot tends to underestimate the contribution of species turnover. To clarify and avoid misinterpretation of the calculation of \( \beta_{OS} \) and \( \beta_{ST} \) in Poisot et al. (2012), Poisot (2022) provides a new, in-depth mathematical analysis of the decomposition of \( \beta_{WN} \). Poisot et al. (2012) quantify in \( \beta_{OS} \) the actual contribution of rewiring in network structure for the subweb of common species. Poisot (2022) thus argues that \( \beta_{OS} \) relates only to the probability of rewiring in the subweb, while the definition of \( \beta_{OS} \) by Fründ (2021) is relative to the count of interactions in the global network (considered in denominator), and is thereby dependent on both rewiring probability and species turnover. Poisot (2022) further clarifies the interpretation of \( \beta_{ST} \). \( \beta_{ST} \) is obtained by subtracting \( \beta_{OS} \) from \( \beta_{WN} \) and thus represents the influence of species turnover in terms of the relative architectures of the global networks and of the subwebs of shared species. Coming back to the example of Fig.1., the Poisot et al. (2012) formula posits that \( \frac{\beta_{ST}}{\beta_{WN}}=\frac{2/15}{1/3}=2/5 \), meaning that species turnover contributes two-fifths of change in network structure, while rewiring in the subweb of common species contributed three fifths. Conversely, the approach of Fründ (2021) does not compare the architectures of global networks and of the subwebs of shared species, but considers the relative contribution of unique links to network dissimilarity in terms of species turnover and rewiring. Poisot (2022) concludes that the partition proposed in Fründ (2021) does not allow unambiguous ecological interpretation of rewiring. He provides guidelines for proper interpretation of the decomposition proposed in Poisot et al. (2012). References Fründ J (2021) Dissimilarity of species interaction networks: how to partition rewiring and species turnover components. Ecosphere, 12, e03653. https://doi.org/10.1002/ecs2.3653 Poisot T, Canard E, Mouillot D, Mouquet N, Gravel D (2012) The dissimilarity of species interaction networks. Ecology Letters, 15, 1353–1361. https://doi.org/10.1111/ele.12002 Poisot T (2022) Dissimilarity of species interaction networks: quantifying the effect of turnover and rewiring. EcoEvoRxiv Preprints, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/osf.io/gxhu2 | Dissimilarity of species interaction networks: quantifying the effect of turnover and rewiring | Timothée Poisot | <p style="text-align: justify;">Despite having established its usefulness in the last ten years, the decomposition of ecological networks in components allowing to measure their β-diversity retains some methodological ambiguities. Notably, how to ... | Biodiversity, Interaction networks, Theoretical ecology | François Munoz | 2021-07-31 00:18:41 | View | ||
12 Jan 2022
No Evidence for Long-range Male Sex Pheromones in Two Malaria MosquitoesSerge Bèwadéyir Poda, Bruno Buatois, Benoit Lapeyre, Laurent Dormont, Abdoulaye Diabaté, Olivier Gnankiné, Roch K. Dabiré, Olivier Roux https://doi.org/10.1101/2020.07.05.187542The search for sex pheromones in malaria mosquitoesRecommended by Niels Verhulst based on reviews by Marcelo Lorenzo and 1 anonymous reviewerPheromones are used by many insects to find the opposite sex for mating. Especially for nocturnal mosquitoes it seems logical that such pheromones exist as they can only partly rely on visual cues when flying at night. The males of many mosquito species form swarms and conspecific females fly into these swarms to mate. The two sibling species of malaria mosquitoes Anopheles gambiae s.s. and An. coluzzii coexist and both form swarms consisting of only one species. Although hybrids can be produced, these hybrids are rarely found in nature. In the study presented by Poda and colleagues (2022) it was tested if long-range sex pheromones exist in these two mosquito sibling species. In a previous study by Mozūraites et al. (2020), five compounds (acetoin, sulcatone, octanal, nonanal and decanal) were identified that induced male swarming and increase mating success. Interestingly these compounds are frequently found in nature and have been shown to play a role in sugar feeding or host finding of An. gambiae. In the recommended study performed by Poda et al. (2022) no evidence of long-range sex pheromones in A. gambiae s.s. and An. coluzzii was found. The discrepancy between the two studies is difficult to explain but some of the methods varied between studies. Mozūraites et al. (2020) for example, collected odours from mosquitoes in small 1l glass bottles, where swarming is questionable, while in the study of Poda et al. (2022) 50 x 40 x 40 cm cages were used and swarming observed, although most swarms are normally larger. On the other hand, some of the analytical techniques used in the Mozūraites et al. (2020) study were more sensitive while others were more sensitive in the Poda et al. (2022) study. Because it is difficult to prove that something does not exist, the authors nicely indicate that “an absence of evidence is not an evidence of absence” (Poda et al., 2022). Nevertheless, recently colonized species were tested in large cage setups where swarming was observed and various methods were used to try to detect sex pheromones. No attraction to the volatile blend from male swarms was detected in an olfactometer, no antenna-electrophysiological response of females to male swarm volatile compounds was detected and no specific male swarm volatile was identified. This study will open the discussion again if (sex) pheromones play a role in swarming and mating of malaria mosquitoes. Future studies should focus on sensitive real-time volatile analysis in mating swarms in large cages or field settings. In comparison to moths for example that are very sensitive to very specific pheromones and attract from a large distance, such a long-range specific pheromone does not seem to exist in these mosquito species. Acoustic and visual cues have been shown to be involved in mating (Diabate et al., 2003; Gibson and Russell, 2006) and especially at long distances, visual cues are probably important for the detection of these swarms. References Diabate A, Baldet T, Brengues C, Kengne P, Dabire KR, Simard F, Chandre F, Hougard JM, Hemingway J, Ouedraogo JB, Fontenille D (2003) Natural swarming behaviour of the molecular M form of Anopheles gambiae. Transactions of The Royal Society of Tropical Medicine and Hygiene, 97, 713–716. https://doi.org/10.1016/S0035-9203(03)80110-4 Gibson G, Russell I (2006) Flying in Tune: Sexual Recognition in Mosquitoes. Current Biology, 16, 1311–1316. https://doi.org/10.1016/j.cub.2006.05.053 Mozūraitis, R., Hajkazemian, M., Zawada, J.W., Szymczak, J., Pålsson, K., Sekar, V., Biryukova, I., Friedländer, M.R., Koekemoer, L.L., Baird, J.K., Borg-Karlson, A.-K., Emami, S.N. (2020) Male swarming aggregation pheromones increase female attraction and mating success among multiple African malaria vector mosquito species. Nature Ecology & Evolution, 4, 1395–1401. https://doi.org/10.1038/s41559-020-1264-9 Poda, S.B., Buatois, B., Lapeyre, B., Dormont, L., Diabate, A., Gnankine, O., Dabire, R.K., Roux, O. (2022) No evidence for long-range male sex pheromones in two malaria mosquitoes. bioRxiv, 2020.07.05.187542, ver. 6 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2020.07.05.187542 | No Evidence for Long-range Male Sex Pheromones in Two Malaria Mosquitoes | Serge Bèwadéyir Poda, Bruno Buatois, Benoit Lapeyre, Laurent Dormont, Abdoulaye Diabaté, Olivier Gnankiné, Roch K. Dabiré, Olivier Roux | <p style="text-align: justify;">Cues involved in mate seeking and recognition prevent hybridization and can be involved in speciation processes. In malaria mosquitoes, females of the two sibling species <em>Anopheles gambiae</em> s.s. and <em>An. ... | Behaviour & Ethology, Chemical ecology | Niels Verhulst | 2021-04-26 12:28:36 | View | ||
28 Jun 2024
Accounting for observation biases associated with counts of young when estimating fecundity: case study on the arboreal-nesting red kite (Milvus milvus)Sollmann Rahel, Adenot Nathalie, Spakovszky Péter, Windt Jendrik, Brady J. Mattsson https://doi.org/10.1101/2023.12.01.569571Accounting for observation biases associated with counts of young: you may count too many or too few...Recommended by Nigel Yoccoz based on reviews by Steffen Oppel and 1 anonymous reviewerMost species are hard to observe, and different methods are required to estimate demographic parameters such as the number of young individuals produced (one measure of breeding success) and survival. In the former case, and in particular for birds of prey, it often relies upon direct observations of breeding pairs on their nests. Two problems can then occur, that some young are missed and therefore the breeding success is underestimated (“false negatives”), but it is also possible that because for example of the nest structure or vegetation surrounding the nest, more young birds than in fact are present are counted (“false positives”). Sollmann et al. (2024) address this problem by using data where the truth is known as each nest was also accessed after climbing the tree, and a hierarchical model accounting for both undercounts and overcounts. Finally, they assess the impact of this correction on projected population size using simulations. This paper is a solid contribution to the panoply of methods and models that are available for monitoring populations, and has potential applications for many species for which both false positives and false negatives can be a problem. The results on the projected population sizes – showing that for growing populations correcting for bias can lead to large differences in population sizes after a few decades – may seem counterintuitive as population growth rate of long-lived species such as birds of prey is not very sensitive to a change in breeding success (as compared to adult survival). However, one should just be reminded that a small difference in population growth rate may translate to a large difference after many years – for example a growth rate of 1.05 after 50 years mean than population size is multiplied by 11.5, whereas a growth of 1.03 after 50 years mean a multiplication by 4.4, more than twice less individuals. Small differences may matter a lot if they are sustained, and a key aspect of management is to ensure that they are. Of course, management actions having an impact on survival may be more effective, but they might be harder to achieve than for example ensuring that birds of prey breed successfully. References Sollmann Rahel, Adenot Nathalie, Spakovszky Péter, Windt Jendrik, Mattsson Brady J. 2024. Accounting for observation biases associated with counts of young when estimating fecundity. bioRxiv, v. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.12.01.569571
| Accounting for observation biases associated with counts of young when estimating fecundity: case study on the arboreal-nesting red kite (*Milvus milvus*) | Sollmann Rahel, Adenot Nathalie, Spakovszky Péter, Windt Jendrik, Brady J. Mattsson | <p style="text-align: justify;">Counting the number of young in a brood from a distance is common practice, for example in tree-nesting birds. These counts can, however, suffer from over and undercounting, which can lead to biased estimates of fec... | Demography, Statistical ecology | Nigel Yoccoz | 2023-12-11 08:52:22 | View | ||
30 May 2024
Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoonsAuriane G. Jones, Gauthier Schaal, Aurélien Boyé, Marie Creemers, Valérie Derolez, Nicolas Desroy, Annie Fiandrino, Théophile L. Mouton, Monique Simier, Niamh Smith, Vincent Ouisse https://doi.org/10.1101/2022.08.18.504439Untangling Eutrophication Effects on Coastal Lagoon EcosystemsRecommended by Nathalie Niquil based on reviews by Kaylee P. Smit, Matthew J. Pruden and Kendyl WrightDisentangling the effects on ecosystem structure and functioning of natural and human-induced impacts in transitional waters is a great challenge in coast ecology. This is due to the observation that the ecosystems of transitional waters are naturally dynamic systems with characteristics of stressed systems. For example, the benthic communities present low species richness and high abundance of species with a high tolerance to variations, e.g., salinity. This general observation is known as the paradigm of the “Transitional Waters Quality Paradox” (Zaldívar et al., 2008) derived from the previously described “Estuarine Quality Paradox” (Elliott and Quintino, 2007). In Jones et al. (2024) “Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons”, a great diversity of lagoons is analyzed to disentangle the effects of eutrophication from those of natural environmental variability on benthic macroinvertebrates and understanding the links between environmental variables affecting benthic macroinvertebrates. These authors use a very elegant set of numerical approaches, including correlograms, linear models and variance partitioning. They apply this suite to a dataset of macrobenthic invertebrate abundances and environmental variables from 29 Mediterranean coastal lagoons in France. Through this suite of analyses, they demonstrate the strong complexity of the mechanisms interplaying in a situation of eutrophication on lagoon macrobenthos. The mechanisms involved are direct, like toxicity, or indirect, for example, through modifications of the sediment's biogeochemistry. Such a result on the different interactions involved is very important in the context of the search for indicators to define ecosystem status. Improving the definition of metrics is essential in environmental management decisions. References Elliott, M. and Quintino, V. (2007) The estuarine quality paradox, environmental homeostasis and the difficulty of detecting anthropogenic stress in naturally stressed areas. Marine Pollution Bulletin 54, 640–645. https://doi.org/10.1016/j.marpolbul.2007.02.003 Zaldívar, J. (2008). Eutrophication in transitional waters: an overview. https://doi.org/10.1285/I18252273V2N1P1 | Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons | Auriane G. Jones, Gauthier Schaal, Aurélien Boyé, Marie Creemers, Valérie Derolez, Nicolas Desroy, Annie Fiandrino, Théophile L. Mouton, Monique Simier, Niamh Smith, Vincent Ouisse | <p style="text-align: justify;">Coastal lagoons are transitional ecosystems that host a unique diversity of species and support many ecosystem services. Owing to their position at the interface between land and sea, they are also subject to increa... | Biodiversity, Community ecology, Ecosystem functioning, Marine ecology | Nathalie Niquil | Matthew J. Pruden | 2023-09-08 11:26:01 | View | |
12 Mar 2023
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 https://doi.org/10.1101/2022.06.17.495388Processing environmental DNA samples in turbid waters from coastal lagoonsRecommended by Claudia Piccini based on reviews by David Murray-Stoker and Rutger De WitCoastal 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 ecology | Claudia Piccini | David Murray-Stoker | 2022-06-20 20:31:51 | View |
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