​​Research about the effects of climate change on ecological communities has been abundant in the last decades. In particular, studies about the effects of climate change on mountain ecosystems have been key for understanding and communicating the consequences of this global phenomenon. Alpine regions show higher increases in warming in comparison to low-altitude ecosystems and this trend is likely to continue. This warming has caused reduced snowfall and/or changes in the duration of snow cover. For example, Notarnicola (2020) reported that 78% of the world’s mountain areas have experienced a snow cover decline since 2000. In the same vein, snow cover has decreased by 10% compared with snow coverage in the late 1960s (Walther et al., 2002) and snow cover duration has decreased at a rate of 5 days/decade (Choi et al., 2010). These changes have impacted the dynamics of high-altitude plant and animal populations. Some impacts are changes in the hibernation of animals, the length of the growing season for plants and the soil microbial composition (Chávez et al. 2021).

Lenzi et al. (2023), give us an excellent study using long-term data on alpine amphibian populations. Authors show how climate change has impacted the reproductive phenology of Bufo bufo, especially the breeding season starts 30 days earlier than ~40 years ago. This earlier breeding is associated with the increasing temperatures and reduced snow cover in these alpine ecosystems. However, these changes did not occur in a linear trend but a marked acceleration was observed until mid-1990s with a later stabilization. Authors associated these nonlinear changes with complex interactions between the global trend of seasonal temperatures and site-specific conditions. 

Beyond the earlier breeding season, changes in phenology can have important impacts on the long-term viability of alpine populations. Complex interactions could involve positive and negative effects like harder environmental conditions for propagules, faster development of juveniles, or changes in predation pressure. This study opens new research opportunities and questions like the urgent assessment of the global impact of climate change on animal fitness. This study provides key information for the conservation of these populations.

References

Chávez RO, Briceño VF, Lastra JA, Harris-Pascal D, Estay SA (2021) Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images. Frontiers in Ecology and Evolution, 9. https://doi.org/10.3389/fevo.2021.643850

Choi G, Robinson DA, Kang S (2010) Changing Northern Hemisphere Snow Seasons. Journal of Climate, 23, 5305–5310. https://doi.org/10.1175/2010JCLI3644.1

Lenzi O, Grossenbacher K, Zumbach S, Lüscher B, Althaus S, Schmocker D, Recher H, Thoma M, Ozgul A, Schmidt BR (2022) Four decades of phenology in an alpine amphibian: trends, stasis, and climatic drivers.bioRxiv, 2022.08.16.503739, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.16.503739

Notarnicola C (2020) Hotspots of snow cover changes in global mountain regions over 2000–2018. Remote Sensing of Environment, 243, 111781. https://doi.org/10.1016/j.rse.2020.111781

The authors present a study typical of the field of belowground-aboveground interactions [1]. This framework has been extremely fruitful since the beginning of 2000s [2]. It has also contributed to bridge the gap between soil ecology and the rest of ecology [3]. The study also pertains to the rich field on the impacts of herbivores on soil functioning [4].

The study more precisely tested during two years the effect on nutrient cycling of the interaction between the type of grassland (along a gradient of biomass productivity) and the diet of the community of insect herbivores (5 treatments manipulating the grasshopper community on 1 m2 plots, with a gradient from no grasshopper to grasshoppers either specialized on forbs or grasses). What seems extremely interesting is that the study is based on a rigorous hypothesis-testing approach. They compare the predictions of two frameworks: (1) The “productivity model” predicts that in productive ecosystems herbivores consume a high percentage of the net primary production thus accelerating nutrient cycling. (2) The “diet model” distinguishes herbivores consuming exploitative plants from those eating conservative plants. The former (later) type of herbivores favours conservative (exploitative) plants therefore decelerating (accelerating) nutrient cycling. Interestingly, the two frameworks have similar predictions (and symmetrically opposite predictions) in two cases out of four combinations between ecosystem productivities and types of diet (see Table 1). An other merit of the study is to combine in a rather comprehensive way all the necessary measurements to test these frameworks in combination: grasshopper diet, soil properties, characteristics of the soil microbial community, plant traits, vegetation survey and plant biomass.

The results were in contradiction with the ‘‘diet model’’: microbial properties and nitrogen cycling did not depend on grasshopper diet. The productivity of the grasslands did impact nutrient cycling but not in the direction predicted by the “productivity model”: productive grasslands hosted exploitative plants that depleted N resources in the soil and microbes producing few extracellular enzymes, which led to a lower potential N mineralization and a deceleration of nutrient cycling. Because, the authors stuck to their original hypotheses (that were not confirmed), they were able to discuss in a very relevant way their results and to propose some interpretations, at least partially based on the time scales involved by the productivity and diet models.

Beyond all the merits of this article, I think that two issues remain largely open in relation with the dynamics of the studied systems, and would deserve future research efforts. First, on the ‘‘short’’ term (up to several decades), can we predict how the communities of plants, soil microbes, and herbivores interact to drive the dynamics of the ecosystems? Second, at the evolutionary time scale, can we understand and predict the interactions between the evolution of plant, microbe and herbivore strategies and the consequences for the functioning of the grasslands? The two issues are difficult because of the multiple feedbacks involved. One way to go further would be to complement the empirical approach with models along existing research avenues [5, 6]. 

References

[1] Ibanez S, Foulquier A, Brun C, Colace M-P, Piton G, Bernard L, Gallet C, Clément J-C (2022) The contrasted impacts of grasshoppers on soil microbial activities in function of primary production and herbivore diet. bioRxiv, 2022.07.04.497718, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.07.04.497718

[2] Hooper, D. U., Bignell, D. E., Brown, V. K., Brussaard, L., Dangerfield, J. M., Wall, D. H., Wardle, D. A., Coleman, D. C., Giller, K. E., Lavelle, P., Van der Putten, W. H., De Ruiter, P. C., et al. 2000. Interactions between aboveground and belowground biodiversity in terretrial ecosystems: patterns, mechanisms, and feedbacks. BioScience, 50, 1049-1061. https://doi.org/10.1641/0006-3568(2000)050[1049:IBAABB]2.0.CO;2

[3] Barot, S., Blouin, M., Fontaine, S., Jouquet, P., Lata, J.-C., and Mathieu, J. 2007. A tale of four stories: soil ecology, theory, evolution and the publication system. PLoS ONE, 2, e1248. https://doi.org/10.1371/journal.pone.0001248

[4] Bardgett, R. D., and Wardle, D. A. 2003. Herbivore-mediated linkages between aboveground and belowground communities. Ecology, 84, 2258-2268. https://doi.org/10.1890/02-0274

[5] Barot, S., Bornhofen, S., Loeuille, N., Perveen, N., Shahzad, T., and Fontaine, S. 2014. Nutrient enrichment and local competition influence the evolution of plant mineralization strategy, a modelling approach. J. Ecol., 102, 357-366. https://doi.org/10.1111/1365-2745.12200

[6] Schweitzer, J. A., Juric, I., van de Voorde, T. F. J., Clay, K., van der Putten, W. H., Bailey, J. K., and Fox, C. 2014. Are there evolutionary consequences of plant-soil feedbacks along soil gradients? Func. Ecol., 28, 55-64. https://doi.org/10.1111/1365-2435.12201

In this study, the authors report a new method for estimating the abundance of the Pyrenean brown bear population. Precisely, the methodology involved aims to apply Pollock's closed robust design (PCRD) capture-recapture models to estimate population abundance and trends over time. Overall, the results encourage the use of PCRD to study populations' demographic rates, while minimizing biases due to inter-individual heterogeneity in detection probabilities.

Estimating the size and trends of animal population over time is essential for informing conservation status and management decision-making (Nichols & Williams 2006). This is particularly the case when the population is small, geographically scattered, and threatened. Although several methods can be used to estimate population abundance, they may be difficult to implement when individuals are rare, elusive, solitary, largely nocturnal, highly mobile, and/or occupy large home ranges in remote and/or rugged habitats. Moreover, in such standard methods,

• the population is assumed to be closed both geographically (no immigration nor emigration) and demographically (no births nor deaths) and
• all individuals are assumed to have identical detection probabilities regardless of their individual attributes (e.g., age, body mass, social status) and habitat features (home-range location and composition) (Otis et al. 1978).

However, these conditions are rarely met in real populations, such as wild mammals (e.g., Bellemain et al. 2005; Solbert et al. 2006), and therefore the risk of underestimating population size can rapidly increase because the assumption of perfect detection of all individuals in the population is violated.

Focusing on the critically endangered Pyrenean brown bear that was close to extinction in the mid-1990s, the study by Vanpe et al. (2022), uses protocol and opportunistic data to describe a statistical modeling exercise to construct mark-recapture histories from 2008 to 2020. Among the data, the authors collected non-invasive samples such as a mixture of hair and scat samples used for genetic identification, as well as photographic trap data of recognized individuals. These data are then analyzed in RMark to provide detection and survival estimates. The final model (i.e. PCRD capture-recapture) is then used to provide Bayesian population estimates. Results show a five-fold increase in population size between 2008 and 2020, from 13 to 66 individuals. Thus, this study represents the first published annual abundance and temporal trend estimates of the Pyrenean brown bear population since 2008.

Then, although the results emphasize that the PCRD estimates were broadly close to the MRS counts and had reasonably narrow associated 95% Credibility Intervals, they also highlight that the sampling effort is different according to individuals. Indeed, as expected, the detection of an individual depends on

• the intraspecific home range size variation that results in individuals that move the most being most likely to be detected and
• the mortality rate which is higher on cubs than on adults and subadults (due to infanticide by males, predation, death of the mother, or abandonment).

Overall, the PCRD capture-recapture modelling approach, involved in this study, provides robust estimates of abundance and demographic rates of the Pyrenean brown bear population (with associated uncertainty) while minimizing and considering bias due to inter-individual heterogeneity in detection probabilities.

The authors conclude that mark-recapture provides useful population estimates and urge wildlife ecologists and managers to use robust approaches, such as the RDPC capture-recapture model, when studying large mammal populations. This information is essential to inform management decisions and assess the conservation status of populations.

References

Bellemain, E.V.A., Swenson, J.E., Tallmon, D., Brunberg, S. and Taberlet, P. (2005). Estimating population size of elusive animals with DNA from hunter-collected feces: four methods for brown bears. Cons. Biol. 19(1), 150-161. https://doi.org/10.1111/j.1523-1739.2005.00549.x

Nichols, J.D. and Williams, B.K. (2006). Monitoring for conservation. Trends Ecol. Evol. 21(12), 668-673. https://doi.org/10.1016/j.tree.2006.08.007

Otis, D.L., Burnham, K.P., White, G.C. and Anderson, D.R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs (62), 3-135.

Solberg, K.H., Bellemain, E., Drageset, O.M., Taberlet, P. and Swenson, J.E. (2006). An evaluation of field and non-invasive genetic methods to estimate brown bear (Ursus arctos) population size. Biol. Conserv. 128(2), 158-168. https://doi.org/10.1016/j.biocon.2005.09.025

Vanpé C, Piédallu B, Quenette P-Y, Sentilles J, Queney G, Palazón S, Jordana IA, Jato R, Elósegui Irurtia MM, de la Torre JS, and Gimenez O (2022) Estimating abundance of a recovering transboundary brown bear population with capture-recapture models. bioRxiv, 2021.12.08.471719, ver. 4 recommended and peer-reviewed by PCI Ecology. https://doi.org/10.1101/2021.12.08.471719

In this meta-analysis, Shivani et al. [1] investigate 1) whether dominance and reproductive success are generally associated across social mammals and 2) whether this relationship varies according to a) life history traits (e.g., stronger for species with large litter size), b) ecological conditions (e.g., stronger when resources are limited) and c) the social environment (e.g., stronger for cooperative breeders than for plural breeders). Generally, the results are consistent with their predictions, except there was no clear support for this relationship to be conditional on the ecological conditions. considered

As I have previously recommended the preregistration of this study [2,3], I do not have much to add here, as such recommendation should not depend on the outcome of the study. What I would like to recommend is the whole scientific process performed by the authors, from preregistration sent for peer review, to preprint submission and post-study peer review. It is particularly recommendable to notice that this project was a Masters student project, which shows that it is possible and worthy to preregister studies, even for such rather short-term projects. I strongly congratulate the authors for choosing this process even for an early career short-term project. I think it should be made possible for short-term students to conduct a preregistration study as a research project, without having to present post-study results. I hope this study can encourage a shift in the way we sometimes evaluate students’ projects.

I also recommend the readers to look into the whole pre- and post- study reviewing history of this manuscript and the associated preregistration, as it provides a better understanding of the process and a good example of the associated challenges and benefits [4]. It was a really enriching experience and I encourage others to submit and review preregistrations and registered reports!

References

[1] Shivani, Huchard, E., Lukas, D. (2022). The effect of dominance rank on female reproductive success in social mammals. EcoEvoRxiv, rc8na, ver. 10 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/osf.io/rc8na

[2] Shivani, Huchard, E., Lukas, D. (2020). Preregistration - The effect of dominance rank on female reproductive success in social mammals In principle acceptance by PCI Ecology of the version 1.2 on 07 July 2020. https://dieterlukas.github.io/Preregistration_MetaAnalysis_RankSuccess.html

[3] Paquet, M. (2020) Why are dominant females not always showing higher reproductive success? A preregistration of a meta-analysis on social mammals. Peer Community in Ecology, 100056. https://doi.org/10.24072/pci.ecology.100056

[4] Parker, T., Fraser, H., & Nakagawa, S. (2019). Making conservation science more reliable with preregistration and registered reports. Conservation Biology, 33(4), 747-750. https://doi.org/10.1111/cobi.13342

Sexual coercion can be defined as the use by a male of force, or threat of force, which increases the chances that a female will mate with him at a time when she is likely to be fertile, and/or decrease the chances that she will mate with other males, at some cost to the female (Smuts & Smuts 1993). It has been evidenced in a wide range of species and may play an important role in the evolution of sexual conflict and social systems. However, identifying sexual coercion in natural systems can be particularly challenging. Notably, while male behaviour may have immediate consequences on mating success (“harassment”), the mating benefits may be delayed in time (“intimidation”), and in such cases, evidencing coercion requires detailed temporal data at the individual level. Moreover, in some species male aggressive behaviours may be subtle or rare and hence hardly observed, yet still have important effects on female mating probability and fitness. Therefore, investigating the occurrence and consequences of sexual coercion in such species is particularly relevant but studying it in a statistically robust way is likely to require a considerable amount of time spent observing individuals.

In this paper, Smit et al. (2022) test three clear predictions of the sexual coercion hypothesis in a natural population of Mandrills, where severe male aggression towards females is rare: (1) male aggression is more likely on sexually receptive females than on females in other reproductive states, (2) receptive females are more likely to be injured and (3) male aggression directed towards females is positively related to subsequent probability of copulation between those dyads. They also tested an alternative hypothesis, the “aggressive male phenotype” under which the correlation between male aggression towards females and subsequent mating could be statistically explained by male overall aggressivity. In agreement with the three predictions of the sexual coercion hypothesis, (1) male aggression was on average 5 times more likely, and (2) injuries twice as likely, to be observed on sexually receptive females than on females in other reproductive states and (3) copulation between males and sexually receptive females was twice more likely to be observed when aggression by this male was observed on the female before sexual receptivity. There was no support for the aggressive male hypothesis.

The reviewers and I were highly positive about this study, notably regarding the way it is written and how the predictions are carefully and clearly stated, tested, interpreted, and discussed.

This study is a good illustration of a case where some behaviours may not be common or obvious yet have strong effects and likely important consequences and thus be clearly worth studying. More generally, it shows once more the importance of detailed long-term studies at the individual level for our understanding of the ecology and evolution of wild populations.

It is also a good illustration of the challenges faced, when comparing the likelihood of contrasting hypotheses means we need to alter sample sizes and/or the likelihood to observe at all some behaviours. For example, observing copulation within minutes after aggression (and therefore, showing statistical support for “harassment”) is inevitably less likely than observing copulations on the longer-term (and therefore showing statistical support for “intimidation”, when of course effort is put into recording such behavioural data on the long-term). Such challenges might partly explain some apparently intriguing results. For example, why are swollen females more aggressed by males if only aggression before the swollen period seems associated with more chances of mating? Here, the authors systematically provide effect sizes (and confidence intervals) and often describe the effects in an intuitive biological way (e.g., “Swollen females were, on average, about five times more likely to become injured”). This clearly helps the reader to not merely compare statistical significances but also the biological strengths of the estimated effects and the uncertainty around them. They also clearly acknowledge limits due to sample size when testing the harassment hypothesis, yet they provide precious information on the probability of observing mating (a rare behaviour) directly after aggression (already a rare behaviour!), that is, 3 times out of 38 aggressions observed between a male and a swollen female. Once again, this highlights how important it is to be able to pursue the enormous effort put so far into closely and continuously monitoring this wild population.

Finally, this study raises exciting new questions, notably regarding to what extent females exhibit “counter-strategies” in response to sexual coercion, notably whether there is still scope for female mate choice under such conditions, and what are the fitness consequences of these dynamic conflicting sexual interactions. No doubt these questions will sooner than later be addressed by the authors, and I am looking forward to reading their upcoming work.

References

Smit N, Baniel A, Roura-Torres B, Amblard-Rambert P, Charpentier MJE, Huchard E (2022) Sexual coercion in a natural mandrill population. bioRxiv, 2022.02.07.479393, ver. 5 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.02.07.479393

Smuts BB, Smuts R w. (1993) Male Aggression and Sexual Coercion of Females in Nonhuman Primates and Other Mammals: Evidence and Theoretical Implications. In: Advances in the Study of Behavior (eds Slater PJB, Rosenblatt JS, Snowdon CT, Milinski M), pp. 1–63. Academic Press. https://doi.org/10.1016/S0065-3454(08)60404-0