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21 Dec 2020
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Influence of local landscape and time of year on bat-road collision risks

Assessing bat-vehicle collision risks using acoustic 3D tracking

Recommended by ORCID_LOGO based on reviews by Mark Brigham and ?

The loss of biodiversity is an issue of great concern, especially if the extinction of species or the loss of a large number of individuals within populations results in a loss of critical ecosystem services. We know that the most important threat to most species is habitat loss and degradation (Keil et al., 2015; Pimm et al., 2014); the latter can be caused by multiple anthropogenic activities, including pollution, introduction of invasive species and fragmentation (Brook et al., 2008; Scanes, 2018). Roads are a major cause of habitat fragmentation, isolating previously connected populations and being a direct source of mortality for animals that attempt to cross them (Spellberg, 1998).
While most studies have focused on the effect of roads on larger mammals (Bartonička et al., 2018; Litvaitis and Tash, 2008), in recent years many researchers have grown increasingly concerned about the risk of collision between bats and vehicles (Fensome and Mathews, 2016). For example, a recent publication by Medinas et al. (2021) found 509 bat casualties along a 51-km-long transect during a period of 3 years. Their study provides extremely valuable information to asses which factors primarily drive bat mortality on roads, yet it required a substantial investment of time coupled with the difficulty of detecting bat carcasses. Other studies have used acoustic monitoring as a proxy to gauge risk of collision based on estimates of bat density along roads (reviewed in Fensome and Mathews 2016); while the results of such studies are valuable, the number of passes recorded does not necessarily equal collision risk, as many species may simply avoid crossing the roads. Understanding the risk of collisions is of vital importance for adequate planning of road construction, particularly for key sites that harbor threatened bat species or unusually large populations, especially if these are already greatly impacted by other anthropogenic activities (e.g. wind turbines; Kunz et al. 2007) or unusually deadly pathogens (e.g. white-nose syndrome; Blehert et al. 2009).
The study by Roemer et al. (2020) titled “Influence of local landscape and time of year on bat-road collision risks”, is a welcome addition to our understanding of bat collision risk as it employs a more accurate assessment of bat collision risk based on acoustic monitoring and tracking of flight paths. The goal of the study of Roemer and collaborators, which was conducted at 66 study sites in the Mediterranean region, is to provide an assessment of collision risk based on bat activity near roads. They collected a substantial amount of information for several species: more than 30,000 estimated flight trajectories for 21+ species, including Barbastella barbastellus, Myotis spp., Plecotus sp., Rhinolophus ferrumequinum, Miniopterus schreibersii, Pipistrellus spp., Nyctalus leisleri, and others. They assess risk based on estimates of 1) species abundance from acoustic monitoring, 2) direction of flight paths along roads, and 3) bat-vehicle co-occurrence.
Their findings suggest that risk is habitat, species, guild, and season-specific. Roads within forested habitats posed the largest threats for most species, particularly since most flights within these habitats occurred at the zone of collision risk. They also found that bats typically fly parallel to the road axis regardless of habitat type, which they argue supports the idea that bats may use roads as corridors. The results of their study, as expected, also show that the majority of bat passes were detected during summer or autumn, depending on species, yet they provide novel findings of an increase in risky behaviors during autumn, when the number of passes at the zone of collision risk increased significantly. Their results also suggest that mid-range echolocators, a classification that is based on call design and parameters (Frey-Ehrenbold et al., 2013), had a larger portion of flights in the zone at risk, thus potentially making them more susceptible than short and long-range echolocators to collisions with vehicles.
The methods employed by Roemer et al. (2020) could further help us determine how roads pose species and site-specific threats in a diversity of places without the need to invest a significant amount of time locating bat carcasses. Their findings are also important as they could provide valuable information for deciding where new roads should be constructed, particularly if the most vulnerable species are abundant, perhaps due to the presence of important roost sites. They also show how habitats near larger roads could increase threats, providing an important first step for recommendations regarding road construction and maintenance. As pointed out by one reviewer, one possible limitation of the study is that the results are not supported by the identification of carcasses. For example, does an increase in the number of identified flights at the zone of risk really translate into an increase in the number of collisions? Regardless of the latter, the paper’s methods and results are very valuable and provide an important step towards developing additional tools to assess bat-vehicle collision risks.

References

[1] Bartonička T, Andrášik R, Duľa M, Sedoník J, Bíl M (2018) Identification of local factors causing clustering of animal-vehicle collisions. The Journal of Wildlife Management, 82, 940–947. https://doi.org/10.1002/jwmg.21467
[2] Blehert DS, Hicks AC, Behr M, Meteyer CU, Berlowski-Zier BM, Buckles EL, Coleman JTH, Darling SR, Gargas A, Niver R, Okoniewski JC, Rudd RJ, Stone WB (2009) Bat White-Nose Syndrome: An Emerging Fungal Pathogen? Science, 323, 227–227. https://doi.org/10.1126/science.1163874
[3] Brook BW, Sodhi NS, Bradshaw CJA (2008) Synergies among extinction drivers under global change. Trends in Ecology & Evolution, 23, 453–460. https://doi.org/10.1016/j.tree.2008.03.011
[4] Fensome AG, Mathews F (2016) Roads and bats: a meta-analysis and review of the evidence on vehicle collisions and barrier effects. Mammal Review, 46, 311–323. https://doi.org/10.1111/mam.12072
[5] Frey‐Ehrenbold A, Bontadina F, Arlettaz R, Obrist MK (2013) Landscape connectivity, habitat structure and activity of bat guilds in farmland-dominated matrices. Journal of Applied Ecology, 50, 252–261. https://doi.org/10.1111/1365-2664.12034
[6] Keil P, Storch D, Jetz W (2015) On the decline of biodiversity due to area loss. Nature Communications, 6, 8837. https://doi.org/10.1038/ncomms9837
[7] Kunz TH, Arnett EB, Erickson WP, Hoar AR, Johnson GD, Larkin RP, Strickland MD, Thresher RW, Tuttle MD (2007) Ecological impacts of wind energy development on bats: questions, research needs, and hypotheses. Frontiers in Ecology and the Environment, 5, 315–324. https://doi.org/10.1890/1540-9295(2007)5[315:EIOWED]2.0.CO;2
[8] Litvaitis JA, Tash JP (2008) An Approach Toward Understanding Wildlife-Vehicle Collisions. Environmental Management, 42, 688–697. https://doi.org/10.1007/s00267-008-9108-4
[9] Medinas D, Marques JT, Costa P, Santos S, Rebelo H, Barbosa AM, Mira A (2021) Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns. Journal of Environmental Management, 277, 111412. https://doi.org/10.1016/j.jenvman.2020.111412
[10] Pimm SL, Jenkins CN, Abell R, Brooks TM, Gittleman JL, Joppa LN, Raven PH, Roberts CM, Sexton JO (2014) The biodiversity of species and their rates of extinction, distribution, and protection. Science, 344. https://doi.org/10.1126/science.1246752
[11] Roemer C, Coulon A, Disca T, Bas Y (2020) Influence of local landscape and time of year on bat-road collision risks. bioRxiv, 2020.07.15.204115, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2020.07.15.204115
[12] Scanes CG (2018) Chapter 19 - Human Activity and Habitat Loss: Destruction, Fragmentation, and Degradation. In: Animals and Human Society (eds Scanes CG, Toukhsati SR), pp. 451–482. Academic Press. https://doi.org/10.1016/B978-0-12-805247-1.00026-5
[13] Spellerberg I (1998) Ecological effects of roads and traffic: a literature review. Global Ecology & Biogeography Letters, 7, 317–333. https://doi.org/10.1046/j.1466-822x.1998.00308.x

Influence of local landscape and time of year on bat-road collision risksCharlotte Roemer, Aurélie Coulon, Thierry Disca, and Yves Bas<p>Roads impact bat populations through habitat loss and collisions. High quality habitats particularly increase bat mortalities on roads, yet many questions remain concerning how local landscape features may influence bat behaviour and lead to hi...Behaviour & Ethology, Biodiversity, Conservation biology, Human impact, Landscape ecologyGloriana Chaverri2020-07-20 10:56:29 View
10 Jan 2019
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Inferring macro-ecological patterns from local species' occurrences

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

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

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

ADDITIONAL COMMENTS

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

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

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

References

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

Inferring macro-ecological patterns from local species' occurrencesAnna Tovo, Marco Formentin, Samir Suweis, Samuele Stivanello, Sandro Azaele, Amos Maritan<p>Biodiversity provides support for life, vital provisions, regulating services and has positive cultural impacts. It is therefore important to have accurate methods to measure biodiversity, in order to safeguard it when we discover it to be thre...Macroecology, Species distributions, Statistical ecology, Theoretical ecologyMatthieu Barbier2018-08-09 16:44:09 View
11 Aug 2023
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Implementing Code Review in the Scientific Workflow: Insights from Ecology and Evolutionary Biology

A handy “How to” review code for ecologists and evolutionary biologists

Recommended by ORCID_LOGO based on reviews by Serena Caplins and 1 anonymous reviewer

Ivimey Cook et al. (2023) provide a concise and useful “How to” review code for researchers in the fields of ecology and evolutionary biology, where the systematic review of code is not yet standard practice during the peer review of articles. Consequently, this article is full of tips for authors on how to make their code easier to review. This handy article applies not only to ecology and evolutionary biology, but to many fields that are learning how to make code more reproducible and shareable. Taking this step toward transparency is key to improving research rigor (Brito et al. 2020) and is a necessary step in helping make research trustable by the public (Rosman et al. 2022).

References

Brito, J. J., Li, J., Moore, J. H., Greene, C. S., Nogoy, N. A., Garmire, L. X., & Mangul, S. (2020). Recommendations to enhance rigor and reproducibility in biomedical research. GigaScience, 9(6), giaa056. https://doi.org/10.1093/gigascience/giaa056

Ivimey-Cook, E. R., Pick, J. L., Bairos-Novak, K., Culina, A., Gould, E., Grainger, M., Marshall, B., Moreau, D., Paquet, M., Royauté, R., Sanchez-Tojar, A., Silva, I., Windecker, S. (2023). Implementing Code Review in the Scientific Workflow: Insights from Ecology and Evolutionary Biology. EcoEvoRxiv, ver 5 peer-reviewed and recommended by Peer Community In Ecology. https://doi.org/10.32942/X2CG64

Rosman, T., Bosnjak, M., Silber, H., Koßmann, J., & Heycke, T. (2022). Open science and public trust in science: Results from two studies. Public Understanding of Science, 31(8), 1046-1062. https://doi.org/10.1177/09636625221100686

Implementing Code Review in the Scientific Workflow: Insights from Ecology and Evolutionary BiologyEdward Ivimey-Cook, Joel Pick, Kevin Bairos-Novak, Antica Culina, Elliot Gould, Matthew Grainger, Benjamin Marshall, David Moreau, Matthieu Paquet, Raphaël Royauté, Alfredo Sanchez-Tojar, Inês Silva, Saras Windecker<p>Code review increases reliability and improves reproducibility of research. As such, code review is an inevitable step in software development and is common in fields such as computer science. However, despite its importance, code review is not...Meta-analyses, Statistical ecologyCorina Logan2023-05-19 15:54:01 View
28 Aug 2023
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Implementing a rapid geographic range expansion - the role of behavior changes

Behavioral changes in the rapid geographic expansion of the great-tailed grackle

Recommended by ORCID_LOGO based on reviews by Francois-Xavier Dechaume-Moncharmont, Pizza Ka Yee Chow and 1 anonymous reviewer

While many species' populations are declining, primarily due to human-related impacts (McKnee et al., 2014), certain species have thrived by utilizing human-influenced environments, leading to their population expansion (Muñoz & Real, 2006). In this context, the capacity to adapt and modify behaviors in response to new surroundings is believed to play a crucial role in facilitating species' spread to novel areas (Duckworth & Badyaev, 2007). For example, an increase in innovative behaviors within recently established communities could aid in discovering previously untapped food resources, while a decrease in exploration might reduce the likelihood of encountering dangers in unfamiliar territories (e.g., Griffin et al., 2016). To investigate the contribution of these behaviors to rapid range expansions, it is essential to directly measure and compare behaviors in various populations of the species.

The study conducted by Logan et al. (2023) aims to comprehend the role of behavioral changes in the range expansion of great-tailed grackles (Quiscalus mexicanus). To achieve this, the researchers compared the prevalence of specific behaviors at both the expansion's edge and its middle. Great-tailed grackles were chosen as an excellent model due to their behavioral adaptability, rapid geographic expansion, and their association with human-modified environments. The authors carried out a series of experiments in captivity using wild-caught individuals, following a detailed protocol. The study successfully identified differences in two of the studied behavioral traits: persistence (individuals participated in a larger proportion of trials) and flexibility variance (a component of the species' behavioral flexibility, indicating a higher chance that at least some individuals in the population could be more flexible). Notably, individuals at the edge of the population exhibited higher values of persistence and flexibility, suggesting that these behavioral traits might be contributing factors to the species' expansion. Overall, the study by Logan et al. (2023) is an excellent example of the importance of behavioral flexibility and other related behaviors in the process of species' range expansion and the significance of studying these behaviors across different populations to gain a better understanding of their role in the expansion process.

Finally, it is important to underline that this study is part of a pre-registration that received an In Principle Recommendation in PCI Ecology (Sebastián-González 2020) where objectives, methodology, and expected results were described in detail. The authors have identified any deviation from the original pre-registration and thoroughly explained the reasons for their deviations, which were very clear. 

References

Duckworth, R. A., & Badyaev, A. V. (2007). Coupling of dispersal and aggression facilitates the rapid range expansion of a passerine bird. Proceedings of the National Academy of Sciences, 104(38), 15017-15022. https://doi.org/10.1073/pnas.0706174104

Griffin, A.S., Guez, D., Federspiel, I., Diquelou, M., Lermite, F. (2016). Invading new environments: A mechanistic framework linking motor diversity and cognition to establishment success. Biological Invasions and Animal Behaviour, 26e46. https://doi.org/10.1017/CBO9781139939492.004

Logan, C. J., McCune, K., LeGrande-Rolls, C., Marfori, Z., Hubbard, J., Lukas, D. 2023. Implementing a rapid geographic range expansion - the role of behavior changes. EcoEvoRxiv, ver. 3 peer-reviewed and recommended by PCI Ecology. https://doi.org/10.32942/X2N30J

McKee, J. K., Sciulli, P. W., Fooce, C. D., & Waite, T. A. (2004). Forecasting global biodiversity threats associated with human population growth. Biological Conservation, 115(1), 161-164. https://doi.org/10.1016/S0006-3207(03)00099-5

Muñoz, A. R., & Real, R. (2006). Assessing the potential range expansion of the exotic monk parakeet in Spain. Diversity and Distributions, 12(6), 656-665. https://doi.org/10.1111/j.1472-4642.2006.00272.x

Sebastián González, E. (2020) The role of behavior and habitat availability on species geographic expansion. Peer Community in Ecology, 100062. https://doi.org/10.24072/pci.ecology.100062. Reviewers: Caroline Nieberding, Tim Parker, and Pizza Ka Yee Chow.

Implementing a rapid geographic range expansion - the role of behavior changesLogan CJ, McCune KB, LeGrande-Rolls C, Marfori Z, Hubbard J, Lukas D<p>It is generally thought that behavioral flexibility, the ability to change behavior when circumstances change, plays an important role in the ability of species to rapidly expand their geographic range. Great-tailed grackles (<em>Quiscalus mexi...Behaviour & Ethology, Preregistrations, ZoologyEsther Sebastián González2023-04-12 11:00:42 View
06 Oct 2020
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Implementing a rapid geographic range expansion - the role of behavior and habitat changes

The role of behavior and habitat availability on species geographic expansion

Recommended by ORCID_LOGO based on reviews by Caroline Marie Jeanne Yvonne Nieberding, Pizza Ka Yee Chow, Tim Parker and 1 anonymous reviewer

Understanding the relative importance of species-specific traits and environmental factors in modulating species distributions is an intriguing question in ecology [1]. Both behavioral flexibility (i.e., the ability to change the behavior in changing circumstances) and habitat availability are known to influence the ability of a species to expand its geographic range [2,3]. However, the role of each factor is context and species dependent and more information is needed to understand how these two factors interact. In this pre-registration, Logan et al. [4] explain how they will use Great-tailed grackles (Quiscalus mexicanus), a species with a flexible behavior and a rapid geographic range expansion, to evaluate the relative role of habitat and behavior as drivers of the species’ expansion [4]. The authors present very clear hypotheses, predicted results and also include alternative predictions. The rationales for all the hypotheses are clearly stated, and the methodology (data and analyses plans) are described with detail. The large amount of information already collected by the authors for the studied species during previous projects warrants the success of this study. It is also remarkable that the authors will make all their data available in a public repository, and that the pre-registration in already stored in GitHub, supporting open access and reproducible science. I agree with the three reviewers of this pre-registration about its value and I think its quality has largely improved during the review process. Thus, I am happy to recommend it and I am looking forward to seeing the results.

References

[1] Gaston KJ. 2003. The structure and dynamics of geographic ranges. Oxford series in Ecology and Evolution. Oxford University Press, New York.

[2] Sol D, Lefebvre L. 2000. Behavioural flexibility predicts invasion success in birds introduced to new zealand. Oikos. 90(3): 599–605. https://doi.org/10.1034/j.1600-0706.2000.900317.x

[3] Hanski I, Gilpin M. 1991. Metapopulation dynamics: Brief history and conceptual domain. Biological journal of the Linnean Society. 42(1-2): 3–16. https://doi.org/10.1111/j.1095-8312.1991.tb00548.x

[4] Logan CJ, McCune KB, Chen N, Lukas D. 2020. Implementing a rapid geographic range expansion - the role of behavior and habitat changes (http://corinalogan.com/Preregistrations/gxpopbehaviorhabitat.html) In principle acceptance by PCI Ecology of the version on 16 Dec 2021 https://github.com/corinalogan/grackles/blob/0fb956040a34986902a384a1d8355de65010effd/Files/Preregistrations/gxpopbehaviorhabitat.Rmd.

Implementing a rapid geographic range expansion - the role of behavior and habitat changesLogan CJ, McCune KB, Chen N, Lukas D<p>It is generally thought that behavioral flexibility, the ability to change behavior when circumstances change, plays an important role in the ability of a species to rapidly expand their geographic range (e.g., Lefebvre et al. (1997), Griffin a...Behaviour & Ethology, Biological invasions, Dispersal & Migration, Foraging, Habitat selection, Human impact, Phenotypic plasticity, Preregistrations, ZoologyEsther Sebastián GonzálezAnonymous, Caroline Marie Jeanne Yvonne Nieberding, Tim Parker2020-05-14 11:18:57 View
16 Oct 2018
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Impact of group management and transfer on individual sociality in Highland cattle (Bos Taurus)

How empirical sciences may improve livestock welfare and help their management

Recommended by based on reviews by Alecia CARTER and 1 anonymous reviewer

Understanding how livestock management is a source of social stress and disturbances for cattle is an important question with potential applications for animal welfare programs and sustainable development. In their article, Sosa and colleagues [1] first propose to evaluate the effects of individual characteristics on dyadic social relationships and on the social dynamics of four groups of cattle. Using network analyses, the authors provide an interesting and complete picture of dyadic interactions among groupmates. Although shown elsewhere, the authors demonstrate that individuals that are close in age and close in rank form stronger dyadic associations than other pairs. Second, the authors take advantage of some transfers of animals between groups -for management purposes- to assess how these transfers affect the social dynamics of groupmates. Their central finding is that the identity of transferred animals is a key-point. In particular, removing offspring strongly destabilizes the social relationships of mothers while adding a bull into a group also profoundly impacts female-female social relationships, as social networks before and after transfer of these key-animals are completely different. In addition, individuals, especially the young ones, that are transferred without familiar conspecifics take more time to socialize with their new group members than individuals transferred with familiar groupmates, generating a potential source of stress. Interestingly, the authors end up their article with some thoughts on the implications of their findings for animal welfare and ethics. This study provides additional evidence that empirical science has a major role to play in providing recommendations regarding societal questions such as livestock management and animal wellbeing.

References

[1] Sosa, S., Pelé, M., Debergue, E., Kuntz, C., Keller, B., Robic, F., Siegwalt-Baudin, F., Richer, C., Ramos, A., & Sueur C. (2018). Impact of group management and transfer on individual sociality in Highland cattle (Bos Taurus). arXiv:1805.11553v4 [q-bio.PE] peer-reviewed and recommended by PCI Ecol. https://arxiv.org/abs/1805.11553v4

Impact of group management and transfer on individual sociality in Highland cattle (Bos Taurus)Sebastian Sosa, Marie Pelé, Elise Debergue, Cedric Kuntz, Blandine Keller, Florian Robic, Flora Siegwalt-Baudin, Camille Richer, Amandine Ramos, Cédric SueurThe sociality of cattle facilitates the maintenance of herd cohesion and synchronisation, making these species the ideal choice for domestication as livestock for humans. However, livestock populations are not self-regulated, and farmers transfer ...Behaviour & Ethology, Social structureMarie Charpentier2018-05-30 14:05:39 View
02 Jun 2021
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Identifying drivers of spatio-temporal variation in survival in four blue tit populations

Blue tits surviving in an ever-changing world

Recommended by ORCID_LOGO based on reviews by Ana Sanz-Aguilar and Vicente García-Navas

How long individuals live has a large influence on a number of biological processes, both for the individuals themselves as well as for the populations they live in. For a given species, survival is often summarized in curves showing the probability to survive from one age to the next. However, these curves often hide a large amount of variation in survival. Variation can occur from chance, or if individuals have different genotypes or phenotypes that can influence how long they might live, or if environmental conditions are not the same across time or space. Such spatiotemporal variations in the conditions that individuals experience can lead to complex patterns of evolution (Kokko et al. 2017) but because of the difficulties to obtain the relevant data they have not been studied much in natural populations.
 
In this manuscript, Bastianelli and colleagues (2021) identify which environmental and population conditions are associated with variation in annual survival of blue tits. The analyses are based on an impressive dataset, tracking a total of almost 5500 adults in four populations studied for at least 19 years. The authors describe two core results. First, average annual survival is lower in deciduous forests compared to evergreen forests. The differences in average annual survival between the forest types link with previously described differences, with individuals having larger clutches (Charmantier et al. 2016) and higher aggression (Dubuc-Messier et al. 2017) in the populations where adult survival is lower. Second, there are huge fluctuations from one year to the next in the percentage of individuals surviving which occur similarly in all populations. Even though survival covaried across the four populations, this variation was not associated with any of the local or global climate indices the authors investigated.
 
Studies like these are fundamental to our understanding of population change. They are important from an applied side as they can reveal the sustainability of populations and inform potential management options. On a basic research side, they reveal how evolution operates in populations. Theoretical studies predict that individuals are often not adapted to average conditions they experience, but either selected to balance the extremes they encounter  or to make the best during harsh conditions when it really matters (Lewontin & Cohen 1969).
 
This study also opens the door to new research, highlighting that demographic studies should pay attention to variation in survival and other life history traits. For blue tits specifically, the study shows that in order to understand the demography of populations we need a better mechanistic understanding of the environmental and physiological pressures influencing whether individuals die or not to make predictions whether and how climate or other ecological effects shape variation in survival.
 
References
 
Bastianelli O, Robert A, Doutrelant C, Franceschi C de, Giovannini P, Charmantier A (2021) Identifying drivers of spatio-temporal variation in survival in four blue tit populations. bioRxiv, 2021.01.28.428563, ver. 4 peer-reviewed and recommended by Peer community in Ecology. https://doi.org/10.1101/2021.01.28.428563

Charmantier A, Doutrelant C, Dubuc-Messier G, Fargevieille A, Szulkin M (2016) Mediterranean blue tits as a case study of local adaptation. Evolutionary Applications, 9, 135–152. https://doi.org/10.1111/eva.12282

Dubuc-Messier G, Réale D, Perret P, Charmantier A (2017) Environmental heterogeneity and population differences in blue tits personality traits. Behavioral Ecology, 28, 448–459. https://doi.org/10.1093/beheco/arw148

Kokko H, Chaturvedi A, Croll D, Fischer MC, Guillaume F, Karrenberg S, Kerr B, Rolshausen G, Stapley J (2017) Can Evolution Supply What Ecology Demands? Trends in Ecology & Evolution, 32, 187–197. https://doi.org/10.1016/j.tree.2016.12.005

Lewontin RC, Cohen D (1969) On Population Growth in a Randomly Varying Environment. Proceedings of the National Academy of Sciences, 62, 1056–1060. https://doi.org/10.1073/pnas.62.4.1056

Identifying drivers of spatio-temporal variation in survival in four blue tit populationsOlivier Bastianelli, Alexandre Robert, Claire Doutrelant, Christophe de Franceschi, Pablo Giovannini, Anne Charmantier<p style="text-align: justify;">In a context of rapid climate change, the influence of large-scale and local climate on population demography is increasingly scrutinized, yet studies are usually focused on one population. Demographic parameters, i...Climate change, Demography, Evolutionary ecology, Life history, Population ecologyDieter Lukas2021-01-29 15:24:23 View
11 Oct 2023
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Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis

Disentangling microbial exopolymer dynamics in intertidal sediments

Recommended by and ORCID_LOGO based on reviews by 2 anonymous reviewers

The 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.
 
In this study, Hubas et al. [4] compare the carbon and nitrogen isotope ratios in EPS with the carbon isotope ratios of fatty acid biomarkers to identify the main EPS producers in intertidal sediments. The authors find pronounced differences in the diversity, composition, isotope signatures, and production/consumption dynamics of EPS between muddy and sandy environments. While the contribution of diatoms was highest in the bound fraction of EPS in muddy environments, diatom contribution was highest in the colloidal fraction of EPS in sandy environments. These differences between sites likely reflect the functional differences in EPS dynamics of epipelic and episammic sediment communities.
 
Taken together, the innovative approach of the authors provides insights into the diversity and origin of EPS in microphytobenthic communities and highlights the importance of different microbial groups in EPS production. These findings are vital for understanding EPS dynamics in microbial interactions and their role in the functioning of coastal ecosystems.

References

  1. Flemming, H.-C. (2016) EPS-then and now. Microorganisms 4, 41 https://doi.org/10.3390/microorganisms4040041
  2. Wolfaardt, G.M. et al. (1999) Function of EPS. In Microbial Extracellular Polymeric Substances, pp. 171–200, Springer Berlin Heidelberg https://doi.org/10.1007/978-3-642-60147-7
  3. Flemming, H.-C. et al. (2007) The EPS matrix: the “house of biofilm cells.” J. Bacteriol. 189, 7945–7947 https://doi.org/10.1128/jb.00858-07
  4. Hubas, C. et al. (2022) Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.12.02.516908
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<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 ecologyUte Risse-Buhl2022-12-06 14:13:11 View
02 Oct 2018
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How optimal foragers should respond to habitat changes? On the consequences of habitat conversion.

Optimal foraging in a changing world: old questions, new perspectives

Recommended by ORCID_LOGO based on reviews by Frederick Adler, Andrew Higginson and 1 anonymous reviewer

Marginal value theorem (MVT) is an archetypal model discussed in every behavioural ecology textbook. Its popularity is largely explained but the fact that it is possible to solve it graphically (at least in its simplest form) with the minimal amount of equations, which is a sensible strategy for an introductory course in behavioural ecology [1]. Apart from this heuristic value, one may be tempted to disregard it as a naive toy model. After a burst of interest in the 70's and the 80's, the once vivid literature about optimal foraging theory (OFT) has lost its momentum [2]. Yet, OFT and MVT have remained an active field of research in the parasitoidologists community, mostly because the sampling strategy of a parasitoid in patches of hosts and its resulting fitness gain are straightforward to evaluate, which eases both experimental and theoretical investigations [3].
This preprint [4] is in line with the long-established literature on OFT. It follows two theoretical articles [5,6] in which Vincent Calcagno and co-authors assessed the effect of changes in the environmental conditions on optimal foraging strategy. This time, they did not modify the shape of the gain function (describing the diminishing return of the cumulative intake as a function of the residency time in a patch) but the relative frequencies of good and bad patches. At first sight, that sounds like a minor modification of their earlier models. Actually, even the authors initially were fooled by the similarities before spotting the pitfalls. Here, they genuinely point out the erroneous verbal prediction in their previous paper in which some non-trivial effects of the change in patch frequencies have been overlooked. The present study indeed provides a striking example of ecological fallacy, and more specifically of Simpson's paradox which occurs when the aggregation of subgroups modifies the apparent pattern at the scale of the entire population [7,8]. In the case of MVT under constraints of habitat conversion, the increase of the residency times in both bad and good patches can result in a decrease of the average residency time at the level of the population. This apparently counter-intuitive property can be observed, for instance, when the proportion of bad quality patches strongly increases, which increases the probability that the individual forages on theses quickly exploited patches, and thus decreases its average residency time on the long run.
The authors thus put the model on the drawing board again. Proper assessment of the effect of change in the frequency of patch quality is more mathematically challenging than when one considers only changes in the shape of the gain function. The expected gain must be evaluated at the scale of the entire habitat instead of single patch. Overall, this study, which is based on a rigorous formalism, stands out as a warning against too rapid interpretations of theoretical outputs. It is not straightforward to generalize the predictions of previous models without careful evaluating their underlying hypotheses. The devil is in the details: some slight, seemingly minor, adjustments of the assumptions may have some major consequences.
The authors discussed the general conditions leading to changes in residency times or movement rates. Yet, it is worth pointing out again that it would be a mistake to blindly consider these theoretical results as forecasts for the foragers' behaviour in natura. OFT models has for a long time been criticized for sweeping under the carpet the key questions of the evolutionary dynamics and the maintenance of the optimal strategy in a population [9,10]. The distribution of available options is susceptible to change rapidly due to modifications of the environmental conditions or, even more simply, the presence of competitors which continuously remove the best options from the pool of available options [11]. The key point here is that the constant monitoring of available options implies cognitive (neural tissue is one of the most metabolically expensive tissues) and ecological costs: assessment and adjustment to the environmental conditions requires time, energy, and occasional mistakes (cost of naiveté, [12]). While rarely considered in optimal analyses, these costs should severely constraint the evolution of the subtle decision rules. Under rapidly fluctuating conditions, it could be more profitable to maintain a sub-optimal strategy (but performing reasonably well on the long run) than paying the far from negligible costs implied by the pursuit of optimal strategies [13,14]. For instance, in the analysis presented in this preprint, it is striking how close the fitness gains of the plastic and the non-plastic forager are, particularly if one remembers that the last-mentioned cognitive and ecological costs have been neglected in these calculations.
Yet, even if one can arguably question its descriptive value, such models are worth more than a cursory glance. They still have normative value insofar that they provide upper bounds for the response to modifications of the environmental conditions. Such insights are precious to design future experiments on the question. Being able to compare experimentally measured behaviours with the extremes of the null model (stubborn non-plastic forager) and the optimal strategy (only achievable by an omniscient daemon) informs about the cognitive bias or ecological costs experienced by real life foragers. I thus consider that this model, and more generally most OFT models, are still a valuable framework which deserves further examination.

References

[1] Fawcett, T. W. & Higginson, A. D. 2012 Heavy use of equations impedes communication among biologists. Proc. Natl. Acad. Sci. 109, 11735–11739. doi: 10.1073/pnas.1205259109
[2] Owens, I. P. F. 2006 Where is behavioural ecology going? Trends Ecol. Evol. 21, 356–361. doi: 10.1016/j.tree.2006.03.014
[3] Louâpre, P., Fauvergue, X., van Baaren, J. & Martel, V. 2015 The male mate search: an optimal foraging issue? Curr. Opin. Insect Sci. 9, 91–95. doi: 10.1016/j.cois.2015.02.012
[4] Calcagno, V., Hamelin, F., Mailleret, L., & Grognard, F. (2018). How optimal foragers should respond to habitat changes? On the consequences of habitat conversion. bioRxiv, 273557, ver. 4 peer-reviewed and recommended by PCI Ecol. doi: 10.1101/273557
[5] Calcagno, V., Grognard, F., Hamelin, F. M., Wajnberg, É. & Mailleret, L. 2014 The functional response predicts the effect of resource distribution on the optimal movement rate of consumers. Ecol. Lett. 17, 1570–1579. doi: 10.1111/ele.12379
[6] Calcagno, V., Mailleret, L., Wajnberg, É. & Grognard, F. 2013 How optimal foragers should respond to habitat changes: a reanalysis of the Marginal Value Theorem. J. Math. Biol. 69, 1237–1265. doi: 10.1007/s00285-013-0734-y
[7] Galipaud, M., Bollache, L., Wattier, R., Dechaume-Moncharmont, F.-X. & Lagrue, C. 2015 Overestimation of the strength of size-assortative pairing in taxa with cryptic diversity: a case of Simpson's paradox. Anim. Behav. 102, 217–221. doi: 10.1016/j.anbehav.2015.01.032
[8] Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J. & Borsboom, D. 2013 Simpson's paradox in psychological science: a practical guide. Front. Psychol. 4, 513. doi: 10.3389/fpsyg.2013.00513
[9] Bolduc, J.-S. & Cézilly, F. 2012 Optimality modelling in the real world. Biol. Philos. 27, 851–869. doi: 10.1007/s10539-012-9333-3
[10] Pierce, G. J. & Ollason, J. G. 1987 Eight reasons why optimal foraging theory is a complete waste of time. Oikos 49, 111–118. doi: 10.2307/3565560
[11] Dechaume-Moncharmont, F.-X., Brom, T. & Cézilly, F. 2016 Opportunity costs resulting from scramble competition within the choosy sex severely impair mate choosiness. Anim. Behav. 114, 249–260. doi: 10.1016/j.anbehav.2016.02.019
[12] Snell-Rood, E. C. 2013 An overview of the evolutionary causes and consequences of behavioural plasticity. Anim. Behav. 85, 1004–1011. doi: 10.1016/j.anbehav.2012.12.031
[13] Fawcett, T. W., Fallenstein, B., Higginson, A. D., Houston, A. I., Mallpress, D. E. W., Trimmer, P. C. & McNamara, J. M. 2014 The evolution of decision rules in complex environments. Trends Cogn. Sci. 18, 153–161. doi: 10.1016/j.tics.2013.12.012
[14] Marshall, J. A. R., Trimmer, P. C., Houston, A. I. & McNamara, J. M. 2013 On evolutionary explanations of cognitive biases. Trends Ecol. Evol. 28, 469-473. doi: 10.1016/j.tree.2013.05.013

How optimal foragers should respond to habitat changes? On the consequences of habitat conversion.Vincent Calcagno, Frederic Hamelin, Ludovic Mailleret, Frederic GrognardThe Marginal Value Theorem (MVT) provides a framework to predict how habitat modifications related to the distribution of resources over patches should impact the realized fitness of individuals and their optimal rate of movement (or patch residen...Behaviour & Ethology, Dispersal & Migration, Foraging, Landscape ecology, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecologyFrancois-Xavier Dechaume-Moncharmont2018-03-05 10:42:11 View
19 Mar 2024
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How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach

Gene flow in the city. Unravelling the mechanisms behind the variability in urbanization effects on genetic patterns.

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

Worldwide, city expansion is happening at a fast rate and at the same time, urbanists are more and more required to make place for biodiversity. Choices have to be made regarding the area and spatial arrangement of suitable spaces for non-human living organisms, that will favor the long-term survival of their populations. To guide those choices, it is necessary to understand the mechanisms driving the effects of land management on biodiversity.

Research results on the effects of urbanization on genetic diversity have been very diverse, with studies showing higher genetic diversity in rural than in urban populations (e.g. Delaney et al. 2010), the contrary (e.g. Miles et al. 2018) or no difference (e.g. Schoville et al. 2013). The same is true for studies investigating genetic differentiation. The reasons for these differences probably lie in the relative intensities of gene flow and genetic drift in each case study, which are hard to disentangle and quantify in empirical datasets.

In their paper, Savary et al. (2024) used an elegant and powerful simulation approach to better understand the diversity of observed patterns and investigate the effects of dispersal limitation on genetic patterns (diversity and differentiation). Their simulations involved the landscapes of 325 real European cities, each under three different scenarios mimicking 3 virtual urban tolerant species with different abilities to move within cities while genetic drift intensity was held constant across scenarios. The cities were chosen so that the proportion of artificial areas was held constant (20%) but their location and shape varied. This design allowed the authors to investigate the effect of connectivity and spatial configuration of habitat on the genetic responses to spatial variations in dispersal in cities. 

The main results of this simulation study demonstrate that variations in dispersal spatial patterns, for a given level of genetic drift, trigger variations in genetic patterns. Genetic diversity was lower and genetic differentiation was larger when species had more difficulties to move through the more hostile components of the urban environment. The increase of the relative importance of drift over gene flow when dispersal was spatially more constrained was visible through the associated disappearance of the pattern of isolation by resistance. Forest patches (usually located at the periphery of the cities) usually exhibited larger genetic diversity and were less differentiated than urban green spaces. But interestingly, the presence of habitat patches at the interface between forest and urban green spaces lowered those differences through the promotion of gene flow. 

One other noticeable result, from a landscape genetic method point of view, is the fact that there might be a limit to the detection of barriers to genetic clusters through clustering analyses because of the increased relative effect of genetic drift. This result needs to be confirmed, though, as genetic structure has only been investigated with a recent approach based on spatial graphs. It would be interesting to also analyze those results with the usual Bayesian genetic clustering approaches. 

Overall, this study addresses an important scientific question about the mechanisms explaining the diversity of observed genetic patterns in cities. But it also provides timely cues for connectivity conservation and restoration applied to cities.  
 
References

Delaney, K. S., Riley, S. P., and Fisher, R. N. (2010). A rapid, strong, and convergent genetic response to urban habitat fragmentation in four divergent and widespread vertebrates. PLoS ONE, 5(9):e12767.
https://doi.org/10.1371/journal.pone.0012767
 
Miles, L. S., Dyer, R. J., and Verrelli, B. C. (2018). Urban hubs of connectivity: Contrasting patterns of gene flow within and among cities in the western black widow spider. Proceedings of the Royal Society B, 285(1884):20181224. https://doi.org/10.1098/rspb.2018.1224
 
Savary P., Tannier C., Foltête J.-C., Bourgeois M., Vuidel G., Khimoun A., Moal H., and Garnier S. (2024). How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach. EcoEvoRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/X2JS41.
 
Schoville, S. D., Widmer, I., Deschamps-Cottin, M., and Manel, S. (2013). Morphological clines and weak drift along an urbanization gradient in the butterfly, Pieris rapae. PLoS ONE, 8(12):e83095.
https://doi.org/10.1371/journal.pone.0083095

How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approachPaul Savary, Cécile Tannier, Jean-Christophe Foltête, Marc Bourgeois, Gilles Vuidel, Aurélie Khimoun, Hervé Moal, Stéphane Garnier<p><em>Context and objectives</em></p> <p>Although urbanization is a major driver of biodiversity erosion, it does not affect all species equally. The neutral genetic structure of populations in a given species is affected by both genetic drift a...Biodiversity, Conservation biology, Dispersal & Migration, Eco-evolutionary dynamics, Human impact, Landscape ecology, Molecular ecology, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Terrestrial ecologyAurélie Coulon2023-07-25 19:09:16 View