Agricultural field margin plants, often referred to as “spontaneous” species, are key for the stabilization of several social-ecological processes related to crop production such as pollination or pest control (Tamburini et al. 2020). Because of its beneficial function, increasing the diversity of field margin flora becomes as important as crop diversity in process-based agricultures such as agroecology. Contrary, supply-dependent intensive agricultures produce monocultures and homogenized environments that might benefit their productivity, which generally includes the control or elimination of the field margin flora (Emmerson et al. 2016, Aligner 2018). Considering that different agricultural practices are produced by (and produce) different territories (Moore 2020) and that they are also been shaped by current climate change, we urgently need to understand how agricultural intensification constrains the potential of territories to develop agriculture more resilient to such change (Altieri et al., 2015). Thus, studies unraveling how agricultural practices' effects on agricultural field margin flora interact with those of climate change is of main importance, as plant strategies better adapted to such social-ecological processes may differ.        
 
In this vein, the study of Poinas et al. (2024) can be considered a key contribution. It exemplifies how agricultural intensification practiced in the context of climate change can constrain the potential of agricultural field margin flora to cope with climatic variations. The authors found that the incidence of plant strategies better adapted to climate change (conservative/stress-tolerant and Mediterranean species) increased with higher temperatures and lower soil moisture, and with lower intensity of margin management. In contrast, the incidence of ruderal species decreased with climate change. Thus, increasing or even maintaining current levels of agricultural intensification may affect the potential of French agriculture to move to sustainable process-based agricultures because of the reduction of plant diversity, particularly of vegetation better adapted to climate change. 
 
By using an impressive dataset spanning 9 years and 555 agricultural margins in continental France, Poinas et al. (2024) investigated temporal changes in climatic variables (temperature and soil moisture), agricultural practices (herbicide and fertilizers quantity, the frequency of margin mowing or grinding), plant taxonomical and functional diversity, plant strategies (Grime 1977, 1988) and relationships between these temporal changes. Temporal changes in plant strategies were associated with those observed in climatic variables and agricultural practices. Even such associations seem to be mediated by spatial changes, as described in the supplementary material and in their most recent article (Poinas et al. 2023), changes in climatic variables registered in a decade shaped plant strategies and therefore the diversity and functional potential of agricultural field margins. These results are clearly synthesized in Figures 6 and 7 of the present contribution.
 
As shown by Poinas et al. (2024), in the context of climate change, decreasing agricultural intensification will produce more diverse agricultural field margins by promoting the persistence of plant species better adapted to higher temperatures and lower soil moisture. Thus, adopting other agricultural practices (e.g., agroforestry, agroecology) will produce territories with a higher potential to move to sustainable processes-based agricultures that may better cope with climate change by harboring higher biocultural diversity (Altieri et al. 2015).

References

Alignier, A., 2018. Two decades of change in a field margin vegetation metacommunity as a result of field margin structure and management practice changes. Agric., Ecosyst. & Environ., 251, 1–10. https://doi.org/10.1016/j.agee.2017.09.013 

Altieri, M.A., Nicholls, C.I., Henao, A., Lana, M.A., 2015. Agroecology and the design of climate change-resilient farming systems. Agron. Sustain. Dev. 35, 869–890. https://doi.org/10.1007/s13593-015-0285-2

Emmerson, M., Morales, M. B., Oñate, J. J., Batary, P., Berendse, F., Liira, J., Aavik, T., Guerrero, I., Bommarco, R., Eggers, S., Pärt, T., Tscharntke, T., Weisser, W., Clement, L. & Bengtsson, J. (2016). How agricultural intensification affects biodiversity and ecosystem services. In Adv. Ecol. Res. 55, 43-97. https://doi.org/10.1016/bs.aecr.2016.08.005

Grime, J. P., 1977. Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. The American Naturalist, 111(982), 1169–1194. https://doi.org/10.1086/283244

Grime, J. P., 1988. The C-S-R model of primary plant strategies—Origins, implications and tests. In L. D. Gottlieb & S. K. Jain, Plant Evolutionary Biology (pp. 371–393). Springer Netherlands. https://doi.org/10.1007/978-94-009-1207-6_14

Moore, J., 2020. El capitalismo en la trama de la vida (Capitalism in The Web of Life). Traficantes de sueños, Madrid, Spain. 

Poinas, I., Fried, G., Henckel, L., & Meynard, C. N., 2023. Agricultural drivers of field margin plant communities are scale-dependent. Bas. App. Ecol. 72, 55-63. https://doi.org/10.1016/j.baae.2023.08.003

Poinas, I., Meynard, C. N., Fried, G., 2024. Functional trade-offs: exploring the temporal response of field margin plant communities to climate change and agricultural practices, bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.03.03.530956

Tamburini, G., Bommarco, R., Wanger, T.C., Kremen, C., Van Der Heijden, M.G., Liebman, M., Hallin, S., 2020. Agricultural diversification promotes multiple ecosystem services without compromising yield. Sci. Adv. 6, eaba1715. https://doi.org/10.1126/sciadv.aba1715

European farmland bird populations continue declining at an alarming rate, and some species require urgent action to avoid their demise (Silva et al. 2024). While factors such as climate change and urbanization also play an important role in driving the decline of farmland bird populations, its main driver seems to be linked with agricultural intensification (Rigal et al. 2023). Besides increased pesticide and fertilizer use, agricultural intensification often results in the homogenization of agricultural landscapes through the removal of seminatural linear features such as hedgerows, field margins, and grassy strips that can be beneficial for biodiversity. These features may be particularly important during the breeding season, when breeding farmland birds can benefit from patches of denser vegetation to conceal nests and improve breeding success. It is both important and timely to understand how landscape management can help to address the ongoing decline of farmland birds by identifying specific actions that can boost breeding success.

Perrot et al. 2023 contribute to this effort by exploring how red-legged partridges use linear features in an intensive agricultural landscape during the breeding season. Through a combination of targeted fieldwork and GPS tracking, the authors highlight patterns in home range size and habitat selection that provide insights for landscape management. Specifically, their results suggest that birds have smaller range sizes in the vicinity of traffic routes and seminatural features structured by both herbaceous and woody cover. Furthermore, they show that breeding birds tend to choose linear elements with herbaceous cover whereas non-breeders prefer linear elements with woody cover, underlining the importance of accounting for the needs of both breeding and non-breeding birds. In particular, the authors stress the importance of providing additional vegetation elements such as hedges, grassy strips or embankments in order to increase landscape heterogeneity. These landscape elements are usually found in the vicinity of linear infrastructures such as roads and tracks, but it is important they are available also in separate areas to avoid the risk of bird collision and the authors provide specific recommendations towards this end. Overall, this is an important study with clear recommendations on how to improve landscape management for these farmland birds.

References

Perrot, C., Séranne, L., Berceaux, A., Noel, M., Arroyo, B., & Bacon, L. (2023) "Use of linear features by red-legged partridges in an intensive agricultural landscape: implications for landscape management in farmland." bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology.
https://doi.org/10.1101/2023.07.27.550774
 
Rigal, S., Dakos, V., Alonso, H., Auniņš, A., Benkő, Z., Brotons, L., ... & Devictor, V. (2023) "Farmland practices are driving bird population decline across Europe." Proceedings of the National Academy of Sciences 120.21: e2216573120.
https://doi.org/10.1073/pnas.2216573120
 
Silva, J. P., Gameiro, J., Valerio, F., & Marques, A. T. (2024) "Portugal's farmland bird crisis requires action." Science 383.6679: 157-157.
https://doi.org/10.1126/science.adn1390

Community ecology usually concerns itself with understanding the causes and consequences of diversity at a given taxonomic resolution, most classically at the species level. Yet there is no doubt that diversity exists at all scales, and phenotypic variability within a taxon can be comparable to differences between taxa, as observed from bacteria to fish and trees. The question that motivates an active and growing body of work (e.g. Raffard et al 2019) is not so much whether intraspecific variability matters, but what we get wrong by ignoring it and how to incorporate it into our understanding of communities. There is no established way to think about diversity at multiple nested taxonomic levels, and it is tempting to summarize intraspecific variability simply by measuring species mean and variance in any trait and metric.

In this study, Girard-Tercieux et al (2023a) propose that, to understand its impact on community-level outcomes and in particular on species coexistence, we should carefully distinguish between two ways of thinking about intraspecific variability:

-"unstructured" variation, where every individual's features are like an independent random draw from a species-specific distribution, for instance, due to genetic lottery and developmental accidents

-"structured" variation that is due to each individual encountering a different but enduring microenvironment.

The latter type of variability may still appear complex and random-like when the environment is high-dimensional (i.e. multifaceted, with many different factors contributing to each individual's performance and development). Thus, it is not necessarily "structured" in the sense of being easily understood -- we may need to measure more aspects of the environment than is practical if we want to fully predict these variations.

What distinguishes this "structured" variability is that it is, in a loose sense, inheritable: individuals from the same species that grow in the same microenvironment will have the same performance, in a repeatable fashion. Thus, if each species is best at exploiting at least a fraction of environmental conditions, it is likely to avoid extinction by competition, except in the unlucky case of no propagule reaching any of the favorable sites.
By contrast, drawing each individual's preferences and performance randomly at each generation (from its own species distribution, but independently from other and past individuals) leads to stochastic dynamics, so-called ecological drift, that easily induce a large number of species extinctions.

The core intuition, that the complex spatial structure and high-dimensional nature of the environment plays a key explanatory role in species coexistence, is a running thread through several of the authors' work (e.g. Clark et al 2010), clearly inspired by their focus on tropical forests. This study, by tackling the question of intraspecific determinants of interspecific outcomes, makes a compelling addition to this line of investigation, coming as a theoretical companion to a more data-oriented study (Girard-Tercieux et al 2023b). But I believe it raises a question that is even broader in scope.

This kind of intraspecific variability, due to different individuals growing in different microenvironments, is perhaps most relevant for trees and other sessile organisms, but the distinction made here between "unstructured" and "structured" variability can likely be extended to many other ecological settings.

In my understanding, what matters most in "structured" variability is not so much it stemming from a fixed environment, but rather it being maintained across generations, rather than possibly lost by drift. This difference between variability in the form of "frozen" randomness and in the form of stochastic drift over time is highly relevant in other theoretical fields (e.g. in physics, where it is the difference between a disordered solid and a liquid), and thus, I expect that it is a meaningful distinction to make throughout community ecology.

References

James S. Clark, David Bell, Chengjin Chu, Benoit Courbaud, Michael Dietze, Michelle Hersh, Janneke HilleRisLambers et al. (2010) "High‐dimensional coexistence based on individual variation: a synthesis of evidence." Ecological Monographs 80, no. 4 : 569-608. https://doi.org/10.1890/09-1541.1

Camille Girard-Tercieux, Ghislain Vieilledent, Adam Clark, James S. Clark, Benoît Courbaud, Claire Fortunel, Georges Kunstler, Raphaël Pélissier, Nadja Rüger, Isabelle Maréchaux (2023a) "Beyond variance: simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure." bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.06.503032

Camille Girard‐Tercieux, Isabelle Maréchaux, Adam T. Clark, James S. Clark, Benoît Courbaud, Claire Fortunel, Joannès Guillemot et al. (2023b) "Rethinking the nature of intraspecific variability and its consequences on species coexistence." Ecology and Evolution 13, no. 3 : e9860. https://doi.org/10.1002/ece3.9860

Allan Raffard, Frédéric Santoul, Julien Cucherousset, and Simon Blanchet. (2019) "The community and ecosystem consequences of intraspecific diversity: A meta‐analysis." Biological Reviews 94, no. 2: 648-661. https://doi.org/10.1111/brv.12472

“Pattern, like beauty, is to some extent in the eye of the beholder” (Grant 1977 in Wiens, 1989)

Tick-borne diseases are an important burden on public health all over the globe, making accurate forecasts of tick population a key ingredient in a successful public health strategy. Over long time scales, tick populations can undergo complex dynamics, as they are sensitive to many non-linear effects due to the complex relationships between ticks and the relevant (numerical) features of their environment.

But luckily, capturing complex non-linear responses is a task that machine learning thrives on. In this contribution, Manley et al. (2023) explore the use of Gradient Boosted Trees to predict the distribution (presence/absence) and abundance of ticks across New York state.

This is an interesting modelling challenge in and of itself, as it looks at the same ecological question as an instance of a classification problem (presence/absence) or of a regression problem (abundance). In using the same family of algorithm for both, Manley et al. (2023) provide an interesting showcase of the versatility of these techniques. But their article goes one step further, by setting up a multi-class categorical model that estimates jointly the presence and abundance of a population. I found this part of the article particularly elegant, as it provides an intermediate modelling strategy, in between having two disconnected models for distribution and abundance, and having nested models where abundance is only predicted for the present class (see e.g. Boulangeat et al., 2012, for a great description of the later).

One thing that Manley et al. (2023) should be commended for is their focus on opening up the black box of machine learning techniques. I have never believed that ML models are more inherently opaque than other families of models, but the focus in this article on explainable machine learning shows how these models might, in fact, bring us closer to a phenomenological understanding of the mechanisms underpinning our observations.

There is also an interesting discussion in this article, on the rate of false negatives in the different models that are being benchmarked. Although model selection often comes down to optimizing the overall quality of the confusion matrix (for distribution models, anyway), depending on the type of information we seek to extract from the model, not all types of errors are created equal. If the purpose of the model is to guide actions to control vectors of human pathogens, a false negative (predicting that the vector is absent at a site where it is actually present) is a potentially more damaging outcome, as it can lead to the vector population (and therefore, potentially, transmission) increasing unchecked.

Boulangeat I, Gravel D, Thuiller W. Accounting for dispersal and biotic interactions to disentangle the drivers of species distributions and their abundances: The role of dispersal and biotic interactions in explaining species distributions and abundances. Ecol Lett. 2012;15: 584-593.
https://doi.org/10.1111/j.1461-0248.2012.01772.x

Manley W, Tran T, Prusinski M, Brisson D. (2023) Modeling tick populations: An ecological test case for gradient boosted trees. bioRxiv, 2023.03.13.532443, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.03.13.532443