How would a plant trait evolve if it is involved in interacting with both a pollinator and an herbivore species? The answer by Yacine and Loeuille is straightforward: it is not trivial, but it can explain many situations found in natural populations.

Yacine and Loeuille applied the well-known Adaptive Dynamics framework to a system with three interacting protagonists: a herbivore, a pollinator, and a plant. The evolution of a plant trait is followed under the assumption that it regulates the frequency of interaction with the two other species. As one can imagine, that is where problems begin: interacting more with pollinators seems good, but what if at the same time it implies interacting more with herbivores? And that's not a silly idea, as there are many cases where herbivores and pollinators share the same cues to detect plants, such as colors or chemical compounds.

They found that depending on the trade-off between the two types of interactions and their density-dependent effects on plant fitness, the possible joint ecological and evolutionary outcomes are numerous. When herbivory prevails, evolution can make the ménage-à-trois ecologically unstable, as one or even two species can go extinct, leaving the plant alone. Evolution can also make the coexistence of the three species more stable when pollination services prevail, or lead to the appearance of a second plant species through branching diversification of the plant trait when herbivory and pollination are balanced.

Yacine and Loeuille did not only limit themselves to saying "it is possible," but they also did much work evaluating when each evolutionary outcome would occur. They numerically explored in great detail the adaptive landscape of the plant trait for a large range of parameter values. They showed that the global picture is overall robust to parameter variations, strengthening the plausibility that the evolution of a trait involved in antagonistic interactions can explain many of the correlations between plant and animal traits or phylogenies found in nature.

Are we really there yet? Of course not, as some assumptions of the model certainly limit its scope. Are there really cases where plants' traits evolve much faster than herbivores' and pollinators' traits? Certainly not, but the model is so general that it can apply to any analogous system where one species is caught between a mutualistic and a predator species, including potential species that evolve much faster than the two others. And even though this limitation might cast doubt on the generality of the model's predictions, studying a system where a species' trait and a preference trait coevolve is possible, as other models have already been studied (see Fritsch et al. 2021 for a review in the case of evolution in food webs). We can bet this is the next step taken by Yacine and Loeuille in a similar framework with the same fundamental model, promising fascinating results, especially regarding the evolution of complex communities when species can accumulate after evolutionary branchings.

Relaxing another assumption seems more challenging as it would certainly need to change the model itself: interacting species generally do not play fixed roles, as being mutualistic or antagonistic might generally be density-dependent (Holland and DeAngelis 2010). How would the exchange of resources between three interacting species evolve? It is an open question.

References

Fritsch, C., Billiard, S., & Champagnat, N. (2021). Identifying conversion efficiency as a key mechanism underlying food webs adaptive evolution: a step forward, or backward? Oikos, 130(6), 904-930.
https://doi.org/10.1111/oik.07421
 
Holland, J. N., & DeAngelis, D. L. (2010). A consumer-resource approach to the density‐dependent population dynamics of mutualism. Ecology, 91(5), 1286-1295.
https://doi.org/10.1890/09-1163.1

Yacine, Y., & Loeuille, N. (2024) Attracting pollinators vs escaping herbivores: eco-evolutionary dynamics of plants confronted with an ecological trade-off. bioRxiv 2021.12.02.470900; doi: https://doi.org/10.1101/2021.12.02.470900

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

Stochastic Cellular Automata (SCA) are a popular modelling tool because in, spite of their simplicity, they can generate a variety of spatial patterns. This makes them particularly appreciated, for instance, to validate the insights of analytical or semi-analytical spatial models that make simplifying assumptions, e.g. moment equations models. A first limit to SCA are that as soon as details are added to the model, reproducibility issues may occur. Computation speed is also an issue, especially for large populations. The work by Génin et al. addresses these two issues through the development of an R package, chouca.

The use of the package is designed to be as smooth as possible: users only need to define the type of possible transitions along with their rates, the parameter values, the number of neighbours, and the initial state of the landscape. The main function returns the population dynamics of each state and even the final state of the landscape.

In addition to its flexibility, an asset of chouca resides in its use of the Rcpp package, which compiles the model designed by the user in C++. This allows for high computation speed, which can be further boosted by using parallelising options from R.

In their manuscript, the authors use ecological models to illustrate the more advanced possibilities opened by chouca, e.g. in terms of graphical interpretation or even to estimate parameter values by computing likelihood functions (the implementation in R does make it very appropriate for statistical inference in general). The package still has some limitations, and, for example, it currently only applied to 2D rectangular grids and it cannot include elaborate movement processes. However, some of these could be addressed in future releases and chouca already has the potential to become central for SCA modelling, both for beginners and expert users, especially in ecology.

References

Alexandre Génin, Guillaume Dupont, Daniel Valencia, Mauro Zucconi, M. Isidora Ávila-Thieme, Sergio A. Navarrete, Evie A. Wieters (2024) Easy, fast and reproducible Stochastic Cellular Automata with chouca. bioRxiv, ver.6 peer-reviewed and recommended by Peer Community in Ecology https://doi.org/10.1101/2023.11.08.566206

Agriculture in the XXI century faces the huge challenge of having to provide food to a rapidly growing human population, which is expected to reach 10.9 billion in 2100 (UUNN 2019), by means of practices and methods that guarantee crop sustainability, human health safety, and respect to the environment (UUNN 2015). Such regulation by the United Nations ultimately entails that agricultural scientists are urged to design strategies and methods that effectively minimize the use of harmful chemical products to control pest populations and to improve soil quality.
One of the most, if not the most, sustainable, safe, and environmentally friendly approach to apply against pests is Biological Pest Control (BPC, hereafter), that is, the use of natural enemies to control the populations of pest organisms. The concept of BPC is by no means new: long back to the 300 AC, Chinese farmers built bamboo bridges between citrus trees to facilitate the foraging of the ant species Oecophylla smaragdina to control lepidopteran citrus pests (Konishi and Ito, 1973); It is also nice to use this recommendation letter to recall and quote the words written in 1752 by the famous Swedish taxonomist, botanist and zoologist, Carl Linnaeus: "Every insect has its predator which follows and destroys it. Such predatory insects should be caught and used for disinfecting crop-plants" (Hörstadius (1974) apud Linnaeus 1752).
Acknowledging the many cases of successes from BPC along our recent history, it is also true that application of BPC strategies during the XX century suffered from wrong-doings, mainly when the introduced biological control agent (BCA, hereafter) was of exotic origin and with a generalist diet-breath; in some cases the release of exotic species resulted on global extinction, reduction in the range of distribution, reduction in the population abundance, and partial displacement, of native and functionally similar species, and interbreeding with them (reviewed in van Lenteren et al. 2006). One of the most famous cases is that of Harmonia axyridis, a coccinellid predator of Asian origin that caused important environmental damage in North America (reviewed in Koch & Galvan, 2008).
Fortunately, after the implementation of the Nagoya protocol (CBD, 2011) importation of exotic species for BPC use was severely restricted and controlled, worldwide. Consequently, companies and agricultural scientist were driven to reinforce their focus and interest on the exploitation of native natural enemies, via the mass-rearing and release of native candidates (augmentative BPC), the conservation of landscapes near the crops to provide resources for natural enemies (i.e. conservation biological pest control), or via the exploitation of the genetic variability of BCAs, to create strains performing better at regulating pest populations under specific biotic or abiotic negative circumstances. Some of these cases are cited in Lartigue et al. (2020). The genetic improvement of BCAs is a strategy still in its infancy, but there is no doubt that the interest for it has significantly increased over the last 5 years (Lommen et al 2017, Bielza 2020, Leung et al 2020).
In my humble opinion, what makes the paper of Lartigue et al. (2020) a remarkable contribution to the field of genetic breeding of BCAs is that it opens a new window of opportunities to the field, by exploring the possibilities for artificial selection of behavioral traits (Réale et al. 2007) to "create" strains of natural enemies displaying behavioral syndromes (Sih et al. 2004) that makes them better at regulating pest populations. The behavioral approach for breeding BCAs can then be extended by crossing it with known abiotic and/or biotic hostile environments (e.g. warm and drought environments, presence of predators/competitors to the BCA, respectively) and engineer strains more prompt to display particular behavioral syndromes to help them to overcome the overall hostility of specific environments. I strongly believe that the approach proposed in Lartigue et al. (2020) will influence the future management of agricultural systems, where strategies including the genetic breeding of BCAs’ behavior will contribute to create better guards and protectors of our crops.

References

Bielza, P., Balanza, V., Cifuentes, D. and Mendoza, J. E. (2020). Challenges facing arthropod biological control: Identifying traits for genetic improvement of predators in protected crops. Pest Manag Sci. doi: https://doi.org/10.1002/ps.5857
CBD - Convention on Biological Diversity, 2011. The Nagoya Protocol on Access and Benefit-sharing, https://www.cbd.int/abs/doc/protocol/nagoya-protocol-en.pdf
Hörstadius, S. (1974). Linnaeus, animals and man. Biological Journal of the Linnaean Society, 6, 269-275. doi: https://doi.org/10.1111/j.1095-8312.1974.tb00725.x
Koch, R.L. and Galvan, T.L. (2008). Bad side of a good beetle: the North American experience with Harmonia axyridis. BioControl 53, 23–35. doi: https://doi.org/10.1007/978-1-4020-6939-0_3
Konishi, M. and Ito, Y. (1973). Early entomology in East Asia. In: Smith, R.F., Mittler, T.E., Smith, C.N. (Eds.), History of Entomology, Annual Reviews Inc., Palo Alto, California, pp. 1-20.
Lartigue, S., Yalaoui, M., Belliard, J., Caravel, C., Jeandroz, L., Groussier, G., Calcagno, V., Louâpre, P., Dechaume-Moncharmont, F.-X., Malausa, T. and Moreau, J. (2020). Consistent variations in personality traits and their potential for genetic improvement of biocontrol agents: Trichogramma evanescens as a case study. bioRxiv, 2020.08.21.257881, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: https://doi.org/10.1101/2020.08.21.257881
Leung et al. (2020). Next-generation biological control: the need for integrating genetics and genomics. Biological Reviews, 95(6), 1838–1854. doi: https://doi.org/10.1111/brv.12641
Lommen, S. T. E., de Jong, P. W. and Pannebakker, B. A. (2017). It is time to bridge the gap between exploring and exploiting: prospects for utilizing intraspecific genetic variation to optimize arthropods for augmentative pest control – a review. Entomologia Experimentalis et Applicata, 162: 108-123. doi: https://doi.org/10.1111/eea.12510
Réale, D., Reader, S. M., Sol, D., McDougall, P. T. and Dingemanse, N. J. (2007). Integrating animal temperament within ecology and evolution. Biological Reviews, 82: 291-318. doi: https://doi.org/10.1111/j.1469-185X.2007.00010.x
Sih, A., Bell, A. and Johnson, J. C. (2004). Behavioral syndromes: an ecological and evolutionary overview. Trends in Ecology and Evolution, 19(7), 372–378. doi: https://doi.org/10.1016/j.tree.2004.04.009
UUNN. 2015. Transforming our world: the 2030 Agenda for Sustainable Development. report of the Open Working Group of the General Assembly on Sustainable Development Goals (A/68/970 and Corr.1; see also A/68/970/Add.1–3).
UUNN. 2019. World population prospects 2019. United Nations, Department of Economic and Social Affairs, Population Division: Highlights. ST/ESA/SER.A/423.
van Lenteren, J. C., Bale, J., Bigler, F., Hokkanen, H. M. T. and Loomans A. J. M. (2006). Assessing risks of releasing exotic biological control agents of arthropod pests. Annual Review of Entomology, 51: 609-634. doi: https://doi.org/10.1146/annurev.ento.51.110104.151129

Reproductive succes, as a surrogate of individual fitness, depends both on extrinsic and intrinsic factors [1]. Among the intrinsic factors, resource level or health are considered important potential drivers of fitness but exceedingly difficult to measure directly. Thus, a host of proxies have been suggested, known as condition indices [2]. The question arises whether all condition indices consistently measure the same "inner state" of individuals and whether all of them similarly correlate to individual fitness. In this preregistration, Berens and colleagues aim to answer this question for two common condition indices, fat score and scaled mass index (Fig. 1), using great-tailed grackles as a model system. Although this question is not new, it has not been satisfactorily solved and both reviewers found merit in the attempt to clarify this matter.  Figure 1. Hypothesized relationships between two condition indices and reproductive success. Single arrow heads indicate causal relationships; double arrow heads indicate only correlation. In a best case scenario, all relationships should be positive and linear. A problem in adressing this question with grackles is limited population, ergo sample, size and limited possibilites of recapture individuals. Some relationships can be missed due to low statistical power. Unfortunately, existing tools for power analysis fall behind complex designs and the one planned for this study. Thus, any potentially non significant relationship has to be taken cautiously. Nevertheless, even if grackles will not provide a definitive answer (they never meant to do it), this preregistration can inspire broader explorations of matches and mismatches across condition indices and species, as well as uncover non-linear relationships with reproductive success. **References** [1] Roff, D. A. (2001). Life history evolution. Oxford University Press, Oxford. [2] Labocha, M. K.; Hayes, J. P. (2012). Morphometric indices of body condition in birds: a review. Journal of Ornithology 153: 1–22. doi: [10.1007/s10336-011-0706-1](https://dx.doi.org/10.1007/s10336-011-0706-1)