Submit a preprint

Direct submissions to PCI Ecology from bioRxiv.org are possible using the B2J service

Latest recommendationsrsstwitter

IdTitle * Authors * Abstract * Picture * Thematic fields * RecommenderReviewers▲Submission date
07 Jun 2023
article picture

High intraspecific growth variability despite strong evolutionary heritage in a neotropical forest

Environmental and functional determinants of tree performance in a neotropical forest: the imprint of evolutionary legacy on growth strategies

Recommended by ORCID_LOGO based on reviews by David Murray-Stoker, Camille Girard and Jelena Pantel

The hyperdiverse tropical forests have long fascinated ecologists because the fact that so many species persist at a low density at a local scale remains hard to explain. Both niche-based and neutral hypotheses have been tested, primarily based on analyzing the taxonomic composition of tropical forest plots (Janzen 1970; Hubbell 2001). Studies of the functional and phylogenetic structure of tropical tree communities have further aimed to better assess the importance of niche-based processes. For instance, Baraloto et al. (2012) found that co-occurring species were functionally and phylogenetically more similar in a neotropical forest, suggesting a role of environmental filtering. Likewise, Schmitt et al. (2021) found the influence of environmental filtering on the functional composition of an Indian rainforest. Yet these studies evidenced non-random trait-environment association based on the composition of assemblages only (in terms of occurrences and abundances). A major challenge remains to further address whether and how tree performance varies among species and individuals in tropical forests.

Functional traits are related to components of individual fitness (Violle et al. 2007). Recently, more and more emphasis has been put on examining the relationship between functional trait values and demographic parameters (Salguero-Gómez et al. 2018), in order to better understand how functional trait values determine species population dynamics and abundances in assemblages. Fortunel et al. (2018) found an influence of functional traits on species growth variation related to topography, and less clearly to neighborhood density (crowding). Poorter et al. (2018) observed 44% of trait variation within species in a neotropical forest. Although individual trait values would be expected to be better predictors of performance than average values measured at the species level, Poorter et al still found a poor relationship.

Schmitt et al. (2023) examined how abiotic conditions and biotic interactions (considering neighborhood density) influenced the variation of individual potential tree growth, in a tropical forest plot located in French Guiana. They also considered the link between species-averaged values of growth potential and functional traits. Schmitt et al. (2023) found substantial variation in growth potential within species, that functional traits explained 40% of the variation of species-averaged growth and, noticeably, that the taxonomic structure (used as random effect in their model) explained a third of the variation in individual growth.

Although functional traits of roots, wood and leaves could predict a significant part of species growth potential, much variability of tree growth occurred within species. Intraspecific trait variation can thus be huge in response to changing abiotic and biotic contexts across individuals. The information on phylogenetic relationships can still provide a proxy of the integrated phenotypic variation that is under selection across the phylogeny, and determine a variation in growth strategies among individuals. The similarity of the phylogenetic structure suggests a joint selection of these growth strategies and related functional traits during events of convergent evolution. Baraloto et al. (2012) already noted that phylogenetic distance can be a proxy of niche overlap in tropical tree communities. Here, Schmitt et al. further demonstrate that evolutionary heritage is significantly related to individual growth variation, and plead for better acknowledging this role in future studies.

While the role of fitness differences in tropical tree community dynamics remained to be assessed, the present study provides new evidence that individual growth does vary depending on evolutionary relationships, which can reflect the roles of selection and adaptation on growth strategies. Therefore, investigating both the influence of functional traits and phylogenetic relationships on individual performance remains a promising avenue of research, for functional and community ecology in general.

REFERENCES

Baraloto, Christopher, Olivier J. Hardy, C. E. Timothy Paine, Kyle G. Dexter, Corinne Cruaud, Luke T. Dunning, Mailyn-Adriana Gonzalez, et al. 2012. « Using functional traits and phylogenetic trees to examine the assembly of tropical tree communities ». Journal of Ecology, 100: 690‑701.
https://doi.org/10.1111/j.1365-2745.2012.01966.x
 
Fortunel Claire, Lasky Jesse R., Uriarte María, Valencia Renato, Wright S.Joseph, Garwood Nancy C., et Kraft Nathan J. B. 2018. « Topography and neighborhood crowding can interact to shape species growth and distribution in a diverse Amazonian forest ». Ecology, 99(10): 2272-2283. https://doi.org/10.1002/ecy.2441
 
Hubbell, S. P. 2001. The Unified Neutral Theory of Biodiversity and Biogeography. 1 vol. Princeton and Oxford: Princeton University Press. https://www.jstor.org/stable/j.ctt7rj8w
 
Janzen, Daniel H. 1970. « Herbivores and the number of tree species in tropical forests ». American Naturalist, 104(940): 501-528. https://doi.org/10.1086/282687
 
Poorter, Lourens, Carolina V. Castilho, Juliana Schietti, Rafael S. Oliveira, et Flávia R. C. Costa. 2018. « Can traits predict individual growth performance? A test in a hyperdiverse tropical forest ». New Phytologist, 219 (1): 109‑21. https://doi.org/10.1111/nph.15206
 
Salguero-Gómez, Roberto, Cyrille Violle, Olivier Gimenez, et Dylan Childs. 2018. « Delivering the promises of trait-based approaches to the needs of demographic approaches, and vice versa ». Functional Ecology, 32 (6): 1424‑35. https://doi.org/10.1111/1365-2435.13148
 
Schmitt, Sylvain, Valérie Raevel, Maxime Réjou‐Méchain, Narayanan Ayyappan, Natesan Balachandran, Narayanan Barathan, Gopalakrishnan Rajashekar, et François Munoz. 2021. « Canopy and understory tree guilds respond differently to the environment in an Indian rainforest ». Journal of Vegetation Science, e13075. https://doi.org/10.1111/jvs.13075
 
Sylvain Schmitt, Bruno Hérault, et Géraldine Derroire. 2023. « High intraspecific growth variability despite strong evolutionary heritage in a neotropical forest ». bioRxiv, 2022.07.27.501745, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.07.27.501745
 
Violle, C., M. L. Navas, D. Vile, E. Kazakou, C. Fortunel, I. Hummel, et E. Garnier. 2007. « Let the concept of trait be functional! » Oikos, 116(5), 882-892. https://doi.org/10.1111/j.0030-1299.2007.15559.x

High intraspecific growth variability despite strong evolutionary heritage in a neotropical forestSylvain Schmitt, Bruno Hérault, Géraldine Derroire<p style="text-align: justify;">Individual tree growth is a key determinant of species performance and a driver of forest dynamics and composition. Previous studies on tree growth unravelled the variation in species growth as a function of demogra...Community ecology, Demography, Population ecologyFrançois Munoz Jelena Pantel, David Murray-Stoker2022-08-01 14:29:04 View
09 Aug 2024
article picture

Reconstructing prevalence dynamics of wildlife pathogens from pooled and individual samples

Pooled samples hold information about the prevalence of wildlife pathogens

Recommended by ORCID_LOGO based on reviews by Megan Griffiths and 2 anonymous reviewers

Although monitoring the prevalence of pathogens in wildlife is crucial, there are logistical constraints that make this difficult, costly, and unpractical. This problem is often compounded when attempting to measure the temporal dynamics of prevalence. To improve the detection rate, a commonly used technique is pooling samples, where multiple individuals are analyzed at once. Yet, this introduces further potential biases: low-prevalence samples are effectively diluted through pooling, creating a false negative risk; negative samples are masked by the inclusion of positive samples, possibly artificially inflating the estimate of prevalence (and masking the inter-sample variability).

In their contribution, Borremans et al. (2024) come up with a modelling technique to provide accurate predictions of prevalence dynamics using a mix of pooled and individual samples. Because this model represents the pooling of individual samples as a complete mixing process, it can accurately estimate the prevalence dynamics from pooled samples only.

It is particularly noteworthy that the model provides an estimation of the false negative rate of the test. When there are false negatives (or more accurately, when the true rate at which false negatives happens), the value of the effect coefficients for individual-level covariates are likely to be off, potentially by a substantial amount. But besides more accurate coefficient estimation, the actual false negative rate is important information about the overall performance of the infection test.

The model described in this article also allows for a numerical calculation of the probability density function of infection. It is worth spending some time on how this is achieved, as I found the approach relying on combinatorics to be particularly interesting. When pooling, both the number of individuals that are mixed is known, and so is the measurement made on the pooled samples. The question is to figure out the number of individuals that because they are infectious, contribute to this score. The approach used by the authors is to draw (with replacement) possible positive and negative test outcomes assuming a number of positive individuals, and from this to estimate a pathogen concentration in the positive samples. This pathogen concentration can be transformed into its test outcome, and this value taken over all possible combinations is a conditional estimate of the test outcome, knowing the number of pooled individuals, and estimating the number of positive ones.

This approach is where the use of individual samples informs the model: by providing additional corrections for the relative volume of sample each individual provides, and by informing the transformation of test values into virus concentrations.

The authors make a strong case that their model can provide robust estimates of prevalence even in the presence of common field epidemiology pitfalls, and notably incomplete individual-level information. More importantly, because the model can work from pooled samples only, it gives additional value to samples that would otherwise have been discarded because they did not allow for prevalence estimates.

References

Benny Borremans, Caylee A. Falvo, Daniel E. Crowley, Andrew Hoegh, James O. Lloyd-Smith, Alison J. Peel, Olivier Restif, Manuel Ruiz-Aravena, Raina K. Plowright (2024) Reconstructing prevalence dynamics of wildlife pathogens from pooled and individual samples. bioRxiv, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2023.11.02.565200

Reconstructing prevalence dynamics of wildlife pathogens from pooled and individual samplesBenny Borremans, Caylee A. Falvo, Daniel E. Crowley, Andrew Hoegh, James O. Lloyd-Smith, Alison J. Peel, Olivier Restif, Manuel Ruiz-Aravena, Raina K. Plowright<p style="text-align: justify;">Pathogen transmission studies require sample collection over extended periods, which can be challenging and costly, especially in the case of wildlife. A useful strategy can be to collect pooled samples, but this pr...Epidemiology, Statistical ecologyTimothée Poisot Joshua Hewitt2023-11-21 23:16:20 View
30 May 2024
article picture

Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons

Untangling Eutrophication Effects on Coastal Lagoon Ecosystems

Recommended by ORCID_LOGO based on reviews by Kaylee P. Smit, Matthew J. Pruden and Kendyl Wright

Disentangling 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

Jones et al. (2024) Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons bioRxiv, 2022.08.18.504439, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.18.504439

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 lagoonsAuriane 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 ecologyNathalie Niquil Matthew J. Pruden2023-09-08 11:26:01 View
09 Dec 2019
article picture

Niche complementarity among pollinators increases community-level plant reproductive success

Improving our knowledge of species interaction networks

Recommended by ORCID_LOGO based on reviews by Michael Lattorff, Nicolas Deguines and 3 anonymous reviewers

Ecosystems shelter a huge number of species, continuously interacting. Each species interact in various ways, with trophic interactions, but also non-trophic interactions, not mentioning the abiotic and anthropogenic interactions. In particular, pollination, competition, facilitation, parasitism and many other interaction types are simultaneously present at the same place in terrestrial ecosystems [1-2]. For this reason, we need today to improve our understanding of such complex interaction networks to later anticipate their responses. This program is a huge challenge facing ecologists and they today join their forces among experimentalists, theoreticians and modelers. While some of us struggle in theoretical and modeling dimensions [3-4], some others perform brilliant works to observe and/or experiment on the same ecological objects [5-6].
In this nice study [6], Magrach et al. succeed in studying relatively large plant-pollinator interaction networks in the field, in Mediterranean ecosystems. For the first time to my knowledge, they study community-wide interactions instead of traditional and easier accessible pairwise interactions. On the basis of a statistically relevant survey, they focus on plant reproductive success and on the role of pollinator interactions in such a success. A more reductionist approach based on simpler pairwise interactions between plants and pollinators would not be able to highlight the interaction network structure (the topology) possibly impacting its responses [1,5], among which the reproductive success of some (plant) species. Yet, such a network analysis requires a fine control of probable biases, as those linked to size or autocorrelation between data of various sites. Here, Magrach et al. did a nice work in capturing rigorously the structures and trends behind this community-wide functioning.
To grasp possible relationships between plant and pollinator species is a first mandatory step, but the next critical step requires understanding processes hidden behind such relationships. Here, the authors succeed to reach this step too, by starting interpreting the processes at stake in their studied plant-pollinator networks [7]. In particular, the niche complementarity has been demonstrated to play a determinant role in the plant reproductive success, and has a positive impact on it [6].
When will we be able to detect a community-wise process? This is one of my team’s objectives, and we developed new kind of models with this aim. Also, authors focus here on plant-pollinator network, but the next step might be to gather every kind of interactions into a huge ecosystem network which we call the socio-ecosystemic graph [4]. Indeed, why to limit our view to certain interactions only? It will take time to grasp the whole interaction network an ecosystem is sheltering, but this should be our next challenge. And this paper of Magrach et al. [6] is a first fascinating step in this direction.

References

[1] Campbell, C., Yang, S., Albert, R., and Shea, K. (2011). A network model for plant–pollinator community assembly. Proceedings of the National Academy of Sciences, 108(1), 197-202. doi: 10.1073/pnas.1008204108
[2] Kéfi, S., Miele, V., Wieters, E. A., Navarrete, S. A., and Berlow, E. L. (2016). How structured is the entangled bank? The surprisingly simple organization of multiplex ecological networks leads to increased persistence and resilience. PLoS biology, 14(8), e1002527. doi: 10.1371/journal.pbio.1002527
[3] Gaucherel, C. (2019). The Languages of Nature. When nature writes to itself. Lulu editions, Paris, France.
[4] Gaucherel, C., and Pommereau, F. Using discrete systems to exhaustively characterize the dynamics of an integrated ecosystem. Methods in Ecology and Evolution, 10(9), 1615-1627. doi: 10.1111/2041-210X.13242
[5] Bennett, J. M. et al. (2018). A review of European studies on pollination networks and pollen limitation, and a case study designed to fill in a gap. AoB Plants, 10(6), ply068. doi: 10.1093/aobpla/ply068
[6] Magrach, A., Molina, F. P., and Bartomeus, I. (2020). Niche complementarity among pollinators increases community-level plant reproductive success. bioRxiv, 629931, ver. 7 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/629931
[7] Bastolla, U., Fortuna, M. A., Pascual-García, A., Ferrera, A., Luque, B., and Bascompte, J. (2009). The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature, 458(7241), 1018-1020. doi: 10.1038/nature07950

Niche complementarity among pollinators increases community-level plant reproductive successAinhoa Magrach, Francisco P. Molina, Ignasi Bartomeus<p>Declines in pollinator diversity and abundance have been reported across different regions, with implications for the reproductive success of plant species. However, research has focused primarily on pairwise plant-pollinator interactions, larg...Ecosystem functioning, Interaction networks, Pollination, Terrestrial ecologyCédric Gaucherel Nicolas Deguines2019-05-07 17:03:23 View
24 May 2023
article picture

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. 

REFERENCES

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. https://doi.org/10.1101/2022.08.22.504761

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
10 Oct 2018
article picture

Detecting within-host interactions using genotype combination prevalence data

Combining epidemiological models with statistical inference can detect parasite interactions

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

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

References

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

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

Effects of water nutrient concentrations on stream macroinvertebrate community stoichiometry: a large-scale study

The influence of water phosphorus and nitrogen loads on stream macroinvertebrate community stoichiometry

Recommended by ORCID_LOGO based on reviews by Thomas Guillemaud, Jun Zuo and 1 anonymous reviewer

The manuscript by Beck et al. (2024) investigates the effects of water phosphorus and nitrogen loads on stream macroinvertebrate community stoichiometry across France. Utilizing data from over 1300 standardized sampling events, this research finds that community stoichiometry is significantly influenced by water phosphorus concentration, with the strongest effects at low nitrogen levels.

The results demonstrate that the assumptions of Ecological Stoichiometry Theory apply at the community level for at least two dominant taxa and across a broad spatial scale, with probable implications for nutrient cycling and ecosystem functionality.

This manuscript contributes to ecological theory, particularly by extending Ecological Stoichiometry Theory to include community-level interactions, clarifying the impact of nutrient concentrations on community structure and function, and informing nutrient management and conservation strategies.

In summary, this study not only addresses a gap in community-level stoichiometric research but also delivers crucial empirical support for advancing ecological science and promoting environmental stewardship.

References

Beck M, Billoir E, Usseglio-Polatera P, Meyer A, Gautreau E and Danger M (2024) Effects of water nutrient concentrations on stream macroinvertebrate community stoichiometry: a large-scale study. bioRxiv, 2024.02.01.574823, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2024.02.01.574823

Effects of water nutrient concentrations on stream macroinvertebrate community stoichiometry: a large-scale studyMiriam Beck, Elise Billoir, Philippe Usseglio-Polatera, Albin Meyer, Edwige Gautreau, Michael Danger<p>Basal resources generally mirror environmental nutrient concentrations in the elemental composition of their tissue, meaning that nutrient alterations can directly reach consumer level. An increased nutrient content (e.g. phosphorus) in primary...Community ecology, Ecological stoichiometryHuihuang Chen Thomas Guillemaud, Jun Zuo, Anonymous2024-02-02 10:14:01 View
03 Jan 2024
article picture

Diagnosis of planktonic trophic network dynamics with sharp qualitative changes

A new approach to describe qualitative changes of complex trophic networks

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

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

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

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

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

Reference

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

Diagnosis of planktonic trophic network dynamics with sharp qualitative changesCedric Gaucherel, Stolian Fayolle, Raphael Savelli, Olivier Philippine, Franck Pommereau, Christine Dupuy<p>Trophic interaction networks are notoriously difficult to understand and to diagnose (i.e., to identify contrasted network functioning regimes). Such ecological networks have many direct and indirect connections between species, and these conne...Community ecology, Ecosystem functioning, Food webs, Freshwater ecology, Interaction networks, Microbial ecology & microbiologyFrancis Raoul Tim Coulson2023-07-03 10:42:34 View
23 Oct 2023
article picture

The Moa the Merrier: Resolving When the Dinornithiformes Went Extinct

Are Moas ancient Lazarus species?

Recommended by ORCID_LOGO based on reviews by Tim Coulson and Richard Holdaway

Ancient human colonisation often had catastrophic consequences for native fauna. The North American Megafauna went extinct shortly after humans entered the scene and Madagascar suffered twice, before 1500 CE and around 1700 CE after the Malayan and European colonisation. Maoris colonised New Zealand by about 1300 and a century later the giant Moa birds (Dinornithiformes) sharply declined. But did they went extinct or are they an ancient example of Lazarus species, species thought to be extinct but still alive? Scattered anecdotes of late sightings of living Moas even up to the 20th century seem to suggest the latter. The quest for later survival has also a criminal aspect. Who did it, the Maoris or the white colonisers in the late 18th century?

The present work by Floe Foxon (2023) tries to settle this question. It uses a survival modelling approach and an assessment of the reliability of nearly 100 alleged sightings. The model favours the so-called overkill hypothesis, that Moas probably went extinct in the 15th century shortly after Maori colonisation. A small but still remarkable probability remained for survival up to 1770. Later sightings turned out to be highly unreliable.

The paper is important as it does not rely on subjective discussions of late sightings but on a probabilistic modelling approach with sensitivity testing prior applied to marsupials. As common in probabilistic approaches, the study does not finally settle the case. A probability of as much as 20% remained for late survival after 1450 CE. This is not improbable as New Zealand was sufficiently unexplored in those days to harbour a few refuges for late survivors. However, in this respect, it is a bit unfortunate that at the end of the discussion, the paper cites Heuvelmans, the founder of cryptozoology, and it mentions the ivory-billed woodpecker, which has recently been redetected. No Moa remains were found after 1450.

References

Foxon F (2023) The Moa the Merrier: Resolving When the Dinornithiformes Went Extinct. bioRxiv, 2023.08.07.552261, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.08.07.552261

The Moa the Merrier: Resolving When the Dinornithiformes Went ExtinctFloe Foxon<p style="text-align: justify;">The Moa (Aves: Dinornithiformes) are an extinct group of the ratite clade from New Zealand. The overkill hypothesis asserts that the first New Zealand settlers hunted the Moa to extinction by 1450 CE, whereas the st...Conservation biology, Human impact, Statistical ecology, ZoologyWerner Ulrich Tim Coulson, Richard Holdaway2023-08-08 17:14:30 View
20 Sep 2018
article picture

When higher carrying capacities lead to faster propagation

When the dispersal of the many outruns the dispersal of the few

Recommended by ORCID_LOGO based on reviews by Yuval Zelnik and 1 anonymous reviewer

Are biological invasions driven by a few pioneers, running ahead of their conspecifics? Or are these pioneers constantly being caught up by, and folded into, the larger flux of propagules from the established populations behind them?
In ecology and beyond, these two scenarios are known as "pulled" and "pushed" fronts, and they come with different expectations. In a pushed front, invasion speed is not just a matter of how good individuals are at dispersing and settling new locations. It becomes a collective, density-dependent property of population fluxes. And in particular, it can depend on the equilibrium abundance of the established populations inside the range, i.e. the species’ carrying capacity K, factoring in its abiotic environment and biotic interactions.
This realization is especially important because it can flip around our expectations about which species expand fast, and how to manage them. We tend to think of initial colonization and long-term abundance as two independent axes of variation among species or indeed as two ends of a spectrum, in the classic competition-colonization tradeoff [1]. When both play into invasion speed, good dispersers might not outrun good competitors. This is useful knowledge, whether we want to contain an invasion or secure a reintroduction.
In their study "When higher carrying capacities lead to faster propagation", Haond et al [2] combine mathematical analysis, Individual-Based simulations and experiments to show that various mechanisms can cause pushed fronts, whose speed increases with the carrying capacity K of the species. Rather than focus on one particular angle, the authors endeavor to demonstrate that this qualitative effect appears again and again in a variety of settings.
It is perhaps surprising that this notable and general connection between K and invasion speed has managed to garner so little fame in ecology. A large fraction of the literature employs the venerable Fisher-KPP reaction-diffusion model, which combines local logistic growth with linear diffusion in space. This model has prompted both considerable mathematical developments [3] and many applications to modelling real invasions [4]. But it only allows pulled fronts, driven by the small populations at the edge of a species range, with a speed that depends only on their initial growth rate r.
This classic setup is, however, singular in many ways. Haond et al [2] use it as a null model, and introduce three mechanisms or factors that each ensure a role of K in invasion speed, while giving less importance to the pioneers at the border.
Two factors, the Allee effect and demographic stochasticity, make small edge populations slower to grow or less likely to survive. These two factors are studied theoretically, and to make their claims stronger, the authors stack the deck against K. When generalizing equations or simulations beyond the null case, it is easy to obtain functional forms where the parameter K does not only play the role of equilibrium carrying capacity, but also affects dynamical properties such as the maximum or mean growth rate. In that case, it can trivially change the propagation speed, without it meaning anything about the role of established populations behind the front. Haond et al [2] avoid this pitfall by disentangling these effects, at the cost of slightly more peculiar expressions, and show that varying essentially nothing but the carrying capacity can still impact the speed of the invasion front.
The third factor, density-dependent dispersal, makes small populations less prone to disperse. It is well established empirically and theoretically that various biological mechanisms, from collective organization to behavioral switches, can prompt organisms in denser populations to disperse more, e.g. in such a way as to escape competition [5]. The authors demonstrate how this effect induces a link between carrying capacity and invasion speed, both theoretically and in a dispersal experiment on the parasitoid wasp, Trichogramma chilonis.
Overall, this study carries a simple and clear message, supported by valuable contributions from different angles. Although some sections are clearly written for the theoretical ecology crowd, this article has something for everyone, from the stray physicist to the open-minded manager. The collaboration between theoreticians and experimentalists, while not central, is worthy of note. Because the narrative of this study is the variety of mechanisms that can lead to the same qualitative effect, the inclusion of various approaches is not a gimmick, but helps drive home its main message. The work is fairly self-contained, although one could always wish for further developments, especially in the direction of more quantitative testing of these mechanisms.
In conclusion, Haond et al [2] effectively convey the widely relevant message that, for some species, invading is not just about the destination, it is about the many offspring one makes along the way.

References

[1] Levins, R., & Culver, D. (1971). Regional Coexistence of Species and Competition between Rare Species. Proceedings of the National Academy of Sciences, 68(6), 1246–1248. doi: 10.1073/pnas.68.6.1246
[2] Haond, M., Morel-Journel, T., Lombaert, E., Vercken, E., Mailleret, L., & Roques, L. (2018). When higher carrying capacities lead to faster propagation. BioRxiv, 307322. doi: 10.1101/307322
[3] Crooks, E. C. M., Dancer, E. N., Hilhorst, D., Mimura, M., & Ninomiya, H. (2004). Spatial segregation limit of a competition-diffusion system with Dirichlet boundary conditions. Nonlinear Analysis: Real World Applications, 5(4), 645–665. doi: 10.1016/j.nonrwa.2004.01.004
[4] Shigesada, N., & Kawasaki, K. (1997). Biological Invasions: Theory and Practice. Oxford University Press, UK.
[5] Matthysen, E. (2005). Density-dependent dispersal in birds and mammals. Ecography, 28(3), 403–416. doi: 10.1111/j.0906-7590.2005.04073.x

When higher carrying capacities lead to faster propagationMarjorie Haond, Thibaut Morel-Journel, Eric Lombaert, Elodie Vercken, Ludovic Mailleret & Lionel Roques<p>This preprint has been reviewed and recommended by Peer Community In Ecology (https://dx.doi.org/10.24072/pci.ecology.100004). Finding general patterns in the expansion of natural populations is a major challenge in ecology and invasion biology...Biological invasions, Colonization, Dispersal & Migration, Experimental ecology, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecologyMatthieu Barbier Yuval Zelnik2018-04-25 10:18:48 View