Humans are exploiting biological resources since thousands of years. Exploitation of biological resources has become particularly intense since the beginning of the 20th century and the steep increase in the worldwide human population size. Marine and freshwater fishes are not exception to that rule, and they have been (and continue to be) strongly harvested as a source of proteins for humans. For some species, fishery has been so intense that natural stocks have virtually collapsed in only a few decades. The worst example begin that of the Northwest Atlantic cod that has declined by more than 95% of its historical biomasses in only 20-30 years of intensive exploitation (Frank et al. 2005). These rapid and steep changes in biomasses have huge impacts on the entire ecosystems since species targeted by fisheries are often at the top of trophic chains (Frank et al. 2005). 

Beyond demographic impacts, fisheries also have evolutionary impacts on populations, which can also indirectly alter ecosystems (Uusi-Heikkilä et al. 2015; Palkovacs et al. 2018). Fishermen generally focus on the largest specimens, and hence exert a strong selective pressure against these largest fish (which is called “harvest selection”). There is now ample evidence that harvest selection can lead to rapid evolutionary changes in natural populations toward small individuals (Kuparinen & Festa-Bianchet 2017). These evolutionary changes are of course undesirable from a human perspective, and have attracted many scientific questions. Nonetheless, the consequence of harvest selection is not always observable in natural populations, and there are cases in which no phenotypic change (or on the contrary an increase in mean body size) has been observed after intense harvest pressures. In a conceptual Essay, Edeline and Loeuille (Edeline & Loeuille 2020) propose novel ideas to explain why the evolutionary consequences of harvest selection can be so diverse, and how a cross talk between ecological and evolutionary dynamics can explain patterns observed in natural stocks.

 The general and novel concept proposed by Edeline and Loeuille is actually as old as Darwin’s book; The Origin of Species (Darwin 1859). It is based on the simple idea that natural selection acting on harvested populations can actually be strong, and counter-balance (or on the contrary reinforce) the evolutionary consequence of harvest selection. Although simple, the idea that natural and harvest selection are jointly shaping contemporary evolution of exploited populations lead to various and sometimes complex scenarios that can (i) explain unresolved empirical patterns and (ii) refine predictions regarding the long-term viability of exploited populations. 

The Edeline and Loeuille’s crafty inspiration is that natural selection acting on exploited populations is itself an indirect consequence of harvest (Edeline & Loeuille 2020). They suggest that, by modifying the size structure of populations (a key parameter for ecological interactions), harvest indirectly alters interactions between populations and their biotic environment through competition and predation, which changes the ecological theatre and hence the selective pressures acting back to populations. They named this process “size-dependent eco-evolutionary feedback loops” and develop several scenarios in which these feedback loops ultimately deviate the evolutionary outcome of harvest selection from expectation. The scenarios they explore are based on strong theoretical knowledge, and range from simple ones in which a single species (the harvest species) is evolving to more complex (and realistic) ones in which multiple (e.g. the harvest species and its prey) species are co-evolving.

I will not come into the details of each scenario here, and I will let the readers (re-)discovering the complex beauty of biological life and natural selection. Nonetheless, I will emphasize the importance of considering these eco-evolutionary processes altogether to fully grasp the response of exploited populations. Edeline and Loeuille convincingly demonstrate that reduced body size due to harvest selection is obviously not the only response of exploited fish populations when natural selection is jointly considered (Edeline & Loeuille 2020). On the contrary, they show that –under some realistic ecological circumstances relaxing exploitative competition due to reduced population densities- natural selection can act antagonistically, and hence favour stable body size in exploited populations. Although this seems further desirable from a human perspective than a downsizing of exploited populations, it is actually mere window dressing as Edeline and Loeuille further showed that this response is accompanied by an erosion of the evolvability –and hence a lowest probability of long-term persistence- of these exploited populations.

Humans, by exploiting biological resources, are breaking the relative equilibrium of complex entities, and the response of populations to this disturbance is itself often complex and heterogeneous. In this Essay, Edeline and Loeuille provide –under simple terms- the theoretical and conceptual bases required to improve predictions regarding the evolutionary responses of natural populations to exploitation by humans (Edeline & Loeuille 2020). An important next step will be to generate data and methods allowing confronting the empirical reality to these novel concepts (e.g. (Monk et al. 2021), so as to identify the most likely evolutionary scenarios sustaining biological responses of exploited populations, and hence to set the best management plans for the long-term sustainability of these populations.

References

Darwin, C. (1859). On the Origin of Species by Means of Natural Selection. John Murray, London.

Edeline, E. & Loeuille, N. (2021) Size-dependent eco-evolutionary feedbacks in fisheries. bioRxiv, 2020.04.03.022905, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: https://doi.org/10.1101/2020.04.03.022905

Frank, K.T., Petrie, B., Choi, J. S. & Leggett, W.C. (2005). Trophic Cascades in a Formerly Cod-Dominated Ecosystem. Science, 308, 1621–1623. doi: https://doi.org/10.1126/science.1113075

Kuparinen, A. & Festa-Bianchet, M. (2017). Harvest-induced evolution: insights from aquatic and terrestrial systems. Philos. Trans. R. Soc. B Biol. Sci., 372, 20160036. doi: https://doi.org/10.1098/rstb.2016.0036

Monk, C.T., Bekkevold, D., Klefoth, T., Pagel, T., Palmer, M. & Arlinghaus, R. (2021). The battle between harvest and natural selection creates small and shy fish. Proc. Natl. Acad. Sci., 118, e2009451118. doi: https://doi.org/10.1073/pnas.2009451118 

Palkovacs, E.P., Moritsch, M.M., Contolini, G.M. & Pelletier, F. (2018). Ecology of harvest-driven trait changes and implications for ecosystem management. Front. Ecol. Environ., 16, 20–28. doi: https://doi.org/10.1002/fee.1743

Uusi-Heikkilä, S., Whiteley, A.R., Kuparinen, A., Matsumura, S., Venturelli, P.A., Wolter, C., et al. (2015). The evolutionary legacy of size-selective harvesting extends from genes to populations. Evol. Appl., 8, 597–620. doi: https://doi.org/10.1111/eva.12268

Along with the generalization of open-access practices, large, heterogeneous datasets are becoming increasingly available to ecologists (Farley et al. 2018). While such data offer exciting opportunities for unveiling original patterns and trends, they also raise new challenges regarding how to extract relevant information and actually improve our knowledge of complex ecological systems, beyond purely descriptive correlations (Dietze 2017, Farley et al. 2018).

In this work, Caumette et al. (2024) develop an original ecoinformatics approach to relate multi-scale environmental factors to the temporal dynamics of a major pest in mango orchards. Their method relies on the recent tree-boosting method GPBoost (Sigrist 2022) to hierarchize the influence of environmental factors of heterogeneous nature (e.g., orchard composition and management; landscape structure; climate) on the emergence date of the oriental fruit fly, Bactrocera dorsalis. As boosting methods allows the analysis of high-dimensional data, they are particularly adapted to the exploration of such datasets, to uncover unexpected, potentially complex dependencies between ecological dynamics and multiple environmental factors (Farley et al. 2018). In this article, Caumette et al. (2024) make a special effort to guide the reader step by step through their complex analysis pipeline to make it broadly understandable to the average ecologist, which is no small feat. I particularly welcome this commitment, as making new, cutting-edge analytical methods accessible to a large community of science practitioners with varying degrees of statistical or programming expertise is a major challenge for the future of quantitative ecology. 

The main result of Caumette et al. (2024) is that temperature and humidity conditions both at the local and regional scales are the main predictors of B. dorsalis emergence date, while orchard management practices seem to have relatively little influence. This suggests that favourable climatic conditions may allow the persistence of small populations of B. dorsalis over the dry season, which may then act as a propagule source for early re-infestations. However, as the authors explain, the resulting regression model is not designed for predictive purposes and should not at this stage be used for decision-making in pest management. Its main interest rather resides in identifying potential key factors favoring early infestations of B. dorsalis, and help focusing future experimental field studies on the most relevant levers for integrated pest management in mango orchards.

In a wider perspective, this work also provides a convincing proof-of-concept for the use of boosting methods to identify the most influential factors in large, multivariate datasets in a variety of ecological systems. It is also crucial to keep in mind that the current exponential growth in high-throughput environmental data (Lucivero 2020) could quickly come into conflict with the need to reduce the environmental footprint of research (Mariette et al. 2022). In this context, robust and accessible methods for extracting and exploiting all the information available in already existing datasets might prove essential to a sustainable pursuit of science.

References
 
Caumette C, Diatta P, Piry S, Chapuis M-P, Faye E, Sigrist F, Martin O, Papaïx J, Brévault T, Berthier K. 2024. Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards. bioRxiv 2023.11.10.566583, ver. 3 peer-reviewed and recommended by Peer Community in Ecology.  https://doi.org/10.1101/2023.11.10.566583

Dietze MC. 2017. Ecological Forecasting. Princeton University Press
 
Farley SS, Dawson A, Goring SJ, Williams JW. 2018. Situating Ecology as a Big-Data Science: Current Advances, Challenges, and Solutions. BioScience, 68, 563–576, https://doi.org/10.1093/biosci/biy068
 
Lucivero F. 2020. Big Data, Big Waste? A Reflection on the Environmental Sustainability of Big Data Initiatives. Science and Engineering Ethics 26, 1009–1030. https://doi.org/10.1007/s11948-019-00171-7

Mariette J, Blanchard O, Berné O, Aumont O, Carrey J, Ligozat A-L, Lellouch E, Roche P-E, Guennebaud G, Thanwerdas J, Bardou P, Salin G, Maigne E, Servan S, Ben-Ari T 2022. An open-source tool to assess the carbon footprint of research. Environmental Research: Infrastructure and Sustainability, 2022. https://dx.doi.org/10.1088/2634-4505/ac84a4
 
Sigrist F. 2022. Gaussian process boosting. The Journal of Machine Learning Research, 23, 10565-10610. https://jmlr.org/papers/v23/20-322.html
 

In 2015, Brockmeyer et al. [1] suggested that mandrills (Mandrillus sphinx) may accept additional ranging costs to avoid heavily parasitized areas. Following this paper, Bicca-Marques and Calegaro-Marques [2] questioned this interpretation and presented other hypotheses. To summarize, whilst Brockmeyer et al. [1] proposed that elevated daily path length may be a consequence of elevated parasite richness, Bicca-Marques and Calegaro-Marques [2] viewed it as a cause. In this current paper, Charpentier and Kappeler [3] respond to some of the criticisms by Bicca-Marques and Calegaro-Marques and discuss the putative parsimony of the two competing scenarios. The manuscript is interesting and focuses on an important question concerning the discussion about the social organization and home range use in wild mandrills. This answer helps to move this debate forward and should stimulate more empirical studies of the role of environmentally-transmitted parasites in shaping ranging and movement patterns of wild vertebrates. Given the elements this paper brings to the topics, it should have been published in American Journal of Primatology, the journal that published the two previous articles.

References

[1] Brockmeyer, T., Kappeler, P. M., Willaume, E., Benoit, L., Mboumba, S., & Charpentier, M. J. E. (2015). Social organization and space use of a wild mandrill (Mandrillus sphinx) group. American Journal of Primatology, 77(10), 1036–1048. doi: 10.1002/ajp.22439
[2] Bicca-Marques, J. C., & Calegaro-Marques, C. (2016). Ranging behavior drives parasite richness: A more parsimonious hypothesis. American Journal of Primatology, 78(9), 923–927. doi: 10.1002/ajp.22561
[3] Charpentier, M. J., & Kappeler, P. M. (2018). A reply to “Ranging Behavior Drives Parasite Richness: A More Parsimonious Hypothesis.” ArXiv:1805.08151v2 [q-Bio]. Retrieved from http://arxiv.org/abs/1805.08151

 Understanding the effects of environmental perturbations on coexistence is a key challenge in ecology, and models have played an important role in structuring our ideas and generating predictions, leading to quantitative hypotheses. In such models, environmental perturbations are often captured by changes in parameter values, such as the intrinsic growth rates of species (1–3). The question then becomes how much one can change these parameters without breaking coexistence and thus losing species (4). 
 
An intuitively appealing approach to address this question is to calculate a model’s feasibility domain (5–7). Loosely defined, it is the fraction of parameter settings leading to the coexistence of all species. Mathematically speaking, it is a high-dimensional triangle, of which one can calculate the size, just as for plain two-dimensional triangles. Parameter settings outside of this triangle break coexistence. Thus, it seems logical that greater feasibility domains would make for more robust ecosystems. However, careful interpretation is key: a greater feasibility domain merely implies that across many attempts at running a model with different random parameter settings, coexistence will be more frequent. It does not necessarily inform us how much one can perturb the parameters of a community with a predefined parameter setting. To get this information, we also need to know the shape of the triangle (7): perturbations more easily knock the parameter setting out of a flat triangle than out of an equilateral triangle. 
 
Desaillais et al. (8) develop a new theory that sheds light on what drives the shape of the feasibility domain. Specifically, they present the probability distribution that tells how close to the edge of the feasibility domain the parameter settings in that domain tend to be. For example, all points in a very flat triangle are close to its edge, while in an equilateral triangle, most points are safely stowed inside. The results show how, in a Lotka-Volterra model, the matrix of species interactions fully defines this distribution, which makes the technique empirically applicable in so far as one can estimate these interactions. The analysis then continues to explore the role of specific species in putative loss of coexistence. Desaillais et al. identify two species-level quantities: the first measures the total influence of the surrounding community on a focal species, while the second is a proxy for how close that focal species is to being lost, should a perturbation occur. While these two quantities are not mathematically independent, their correlation is not perfect, allowing one to categorize species into distinct ecological roles. A dataset of plant communities with different compositions illustrates how to apply this idea and gain some additional insight into the robustness of coexistence. These results pave the way for a number of potentially rewarding applications. How does the robustness of coexistence differ across network types? For which network types do we find back a more diverse set of ecological roles for species, i.e. for which networks are the two quantities least correlated? 

References

1. Baert, J.M., Janssen, C.R., Sabbe, K., and De Laender, F. (2016). Per capita interactions and stress tolerance drive stress-induced changes in biodiversity effects on ecosystem functions. Nat. Commun. 7, 12486. https://doi.org/10.1038/ncomms12486

2. Pásztor, L., Botta-Dukat, Z., Magyar, G., Czaran, T., and Meszéna, G. (2016). Theory-based ecology: A Darwinian approach 1st ed. (Oxford University Press).

3. Cenci, S., Montero-Castaño, A., and Saavedra, S. (2018). Estimating the effect of the reorganization of interactions on the adaptability of species to changing environments. J. Theor. Biol. 437, 115–125. https://doi.org/10.1016/j.jtbi.2017.10.016

4. Spaak, J.W., Baert, J.M., Baird, D.J., Eisenhauer, N., Maltby, L., Pomati, F., Radchuk, V., Rohr, J.R., Van den Brink, P.J., and De Laender, F. (2017). Shifts of community composition and population density substantially affect ecosystem function despite invariant richness. Ecol. Lett. 20, 1315–1324. https://doi.org/10.1111/ele.12828

5. Meszéna, G., Gyllenberg, M., Pásztor, L., and Metz, J.A.J. (2006). Competitive exclusion and limiting similarity: A unified theory. Theor. Popul. Biol. 69, 68–87. https://doi.org/10.1016/j.tpb.2005.07.001

6. Saavedra, S., Rohr, R.P., Bascompte, J., Godoy, O., Kraft, N.J.B., and Levine, J.M. (2017). A structural approach for understanding multispecies coexistence. Ecol. Monogr. 87, 470–486. https://doi.org/10.1002/ecm.1263

7. Grilli, J., Adorisio, M., Suweis, S., Barabás, G., Banavar, J.R., Allesina, S., and Maritan, A. (2017). Feasibility and coexistence of large ecological communities. Nat. Commun. 8. https://doi.org/10.1038/ncomms14389

8. Desallais M, Loreau M, Arnoldi J.F. (2024) The distribution of distances to the edge of species coexistence. bioRxiv, ver.4 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2024.01.21.575550

Polygyny is assumed to have led to the evolution of strong sexual size dimorphism (SSD) in mammals, males often being heavier or showing more developed armaments than females (Weckerly 1998; Loison et al. 1999; Pérez‐Barbería et al. 2002).  SSD generally increases with the degree of polygyny of the species. However, the degree of SSD, and particularly of sexual mass dimorphism, is not fixed for each species, and differences exist between populations (Blanckenhorn et al. 2006; Cox & Calsbeek 2010) or even between seasons within populations (Rughetti & Festa‐Bianchet 2011).

In this study, Hewison et al. propose that studying seasonal variation in sexual mass dimorphism and how this can be affected by winter harshness and latitude allows us to better assess the energetic costs associated with the eco-evolutionary constraints acting on each sex. To achieve their goal, Hewison et al. use a formidable, long-term dataset of over 7,000 individuals, in five roe deer populations (Capreolus capreolus), from south-west France and Sweden.

According to the authors, sexual mass dimorphism should be at its lowest in early spring in this species due to a stronger trade-off between antler growth and body weight maintenance in males over winter than in females. Furthermore, harsher conditions, varying both in time and space (i.e., Sweden vs. France), should increase winter weight loss, and thus, mass change differences between the sexes should be stronger and show more variation in Sweden than in France.

Their results support their hypotheses. In the two Swedish populations, males lost more mass than females. In the three French populations, males maintain their body mass while females gain some over the winter. Because of these sex-dependent loss/gain in body mass, sexual dimorphism was stronger early in the winter and null at the onset of spring. Furthermore, sexual dimorphism was stronger in southern than in northern populations. In France, males weighed about 10% more than females, while they weighed about 5% more in Sweden. Roe deer, however, do not show any dimorphism early in the spring, when males start defending their territory. 

The authors also found more variation in mass change among years in Swedish than in French roe deer, suggesting a stronger effect of winter severity on the dynamics of mass change in northern than in southern populations. The authors interpret the decrease in sexual dimorphism throughout the winter by the fact that, during this period, the energetic cost paid by males associated with the growth of their antlers and the effort of establishing their mating territory. They thus attribute the greater mass change in males to the competitive allocation of resources to antler growth or body mass. They also discuss the low probability that such sex differences in mass change could be caused by females’ gestation in this species.

Interestingly, Hewison et al. found that individual differences represented more than 70% of the total variation in body mass, and the low estimated among-individual variance in slopes with time might indicate that, despite a lower SSD, selection pressures on body mass can still be maintained at times when body mass may play an important role, such as in spring with territorial defense or later during mating (Vanpé et al. 2010). 

I recommend this article because it produces strong results, which show, without a shadow of a doubt, sex differences in their seasonal mass changes, resulting in a marked seasonal variation in SSD. The differences observed between southern and northern populations confirm the idea that the severity of the winters endured by these populations acts as a constraint on the deer's patterns of mass change. I hope this study will encourage more examinations of how eco-evolutionary constraints affect the sexual size dimorphism.

References

Blanckenhorn, W. U., Stillwell, R. C., Young, K. A., Fox, C. W., & Ashton, K. G. (2006). When Rensch meets Bergmann: does sexual size dimorphism change systematically with latitude? Evolution, 60(10), 2004-2011. https://doi.org/10.1554/06-110.1

Cox, R. M., & Calsbeek, R. (2010). Sex-specific selection and intraspecific variation in sexual size dimorphism. Evolution, 64(3), 798-809. https://doi.org/10.1111/j.1558-5646.2009.00851.x

Hewison M, Bonnot N, Gaillard JM, Kjellander P, Lemaitre J-F, Morellet N. and Pellerin M (2024) Body mass change over winter is consistently sex-specific across roe deer (Capreolus capreolus) populations. bioRxiv, ver.4 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2022.09.09.507329

Loison, A., Gaillard, J. M., Pélabon, C., & Yoccoz, N. G. (1999). What factors shape sexual size dimorphism in ungulates? Evolutionary Ecology Research, 1(5), 611-633. https://www.evolutionary-ecology.com/issues/v01n05/jjar1019.pdf

Pérez‐Barbería, F. J., Gordon, I. J., & Pagel, M. (2002). The origins of sexual dimorphism in body size in ungulates. Evolution, 56(6), 1276-1285. https://doi.org/10.1111/j.0014-3820.2002.tb01438.x

Rughetti, M., & Festa‐Bianchet, M. (2011). Seasonal changes in sexual size dimorphism in northern chamois. Journal of Zoology, 284(4), 257-264. https://doi.org/10.1111/j.1469-7998.2011.00800.x

Vanpé, C., Gaillard, J. M., Kjellander, P., Liberg, O., Delorme, D., & Hewison, A. M. (2010). Assessing the intensity of sexual selection on male body mass and antler length in roe deer Capreolus capreolus: is bigger better in a weakly dimorphic species? Oikos, 119(9), 1484-1492. https://doi.org/10.1111/j.1600-0706.2010.18312.x

Weckerly, F. W. (1998). Sexual-size dimorphism: influence of mass and mating systems in the most dimorphic mammals. Journal of Mammalogy, 79(1), 33-52. https://doi.org/10.2307/1382840