Despite the increasing refinement of statistical methods, a robust experimental design is still one of the most important cornerstones to answer ecological and evolutionary questions. However, there is a strong trade-off between a perfect design and its feasibility. A common mantra is that more data is always better, but how much is enough is complex to answer, specially when we want to capture the spatial and temporal variability of a given process. Gardarin and Valantin-Morison [1] make an effort to answer these questions for a practical case: How many pitfalls traps, of which type, and over which extent, do we need to detect shifts in arthropod community composition in agricultural landscapes. There is extense literature on how to approach these challenges using preliminary data in combination with simulation methods [e.g. 2], but practical cases are always welcomed to illustrate the complexity of the decisions to be made. A key challenge in this situation is the nature of simplified and patchy agricultural arthropod communities. In this context, small effect sizes are expected, but those small effects are relevant from an ecological point of view because small increases at low biodiversity may produce large gains in ecosystem functioning [3].
The paper shows that some variables are not important, such as the type of fluid used to fill the pitfall traps. This is good news for potential comparisons among studies using slightly different protocols. However, the bad news are that the sampling effort needed for detecting community changes is larger than the average effort currently implemented. A potential solution is to focus on Community Weighed Mean metrics (CWM; i.e. a functional descriptor of the community body size distribution) rather than on classic metrics such as species richness, as detecting changes on CWM requires a lower sampling effort and it has a clear ecological interpretation linked to ecosystem functioning.
Beyond the scope of the data presented, which is limited to a single region over two years, and hence it is hard to extrapolate to other regions and years, the big message of the paper is the need to incorporate statistical power simulations as a central piece of the ecologist's toolbox. This is challenging, especially when you face questions such as: Should I replicate over space, or over time? The recommended paper is accompanied by the statistical code used, which should facilitate this task to other researchers. Furthermore, we should be aware that some important questions in ecology are highly variable in space and time, and hence, larger sampling effort across space and time is needed to detect patterns. Larger and longer monitoring schemes require a large effort (and funding), but if we want to make relevant ecology, nobody said it would be easy.

References

[1] Gardarin, A. and Valantin-Morison, M. (2019). Which pitfall traps and sampling efforts should be used to evaluate the effects of cropping systems on the taxonomic and functional composition of arthropod communities? Zenodo, 3468920, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.5281/zenodo.3468920
[2] Johnson, P. C., Barry, S. J., Ferguson, H. M., and Müller, P. (2015). Power analysis for generalized linear mixed models in ecology and evolution. Methods in ecology and evolution, 6(2), 133-142. doi: 10.1111/2041-210X.12306
[3] Cardinale, B. J. et al. (2012). Biodiversity loss and its impact on humanity. Nature, 486(7401), 59-67. doi: 10.1038/nature11148

The metacommunity framework acknowledges that local sites are connected to other sites through dispersal, and that these connectivity patterns can influence local dynamics [1]. This framework is slowly moving from a framework that guides fundamental research to being actively applied in for instance a conservation context (e.g. [2]). Swan and Brown [3,4] analyzed the results of a suite of experimental manipulations in headwater and mainstem streams on invertebrate community structure in the context of the metacommunity concept. This was an important contribution to conservation ecology.
However, David Murray-Stoker [5] was not satisfied with their statistical analyses, and recreated, and more importantly, improved their original analyses in the peer-reviewed article. The new analyses are based on a combination of a more consistent site selection, checking the model assumptions, using different estimation procedures, and focusing more on effect size calculations versus statistical significance. This peer-reviewed article is thus the perfect example of the advantages of open research: the original authors making available both the data and their R script files, initially first updating the analyses and results themselves, followed by more in-depth analyses of the original data and question.
This peer reviewed went through a very in-depth process itself, with several rounds of questions and feedback that addressed both the statistical analyses, the interpretation of the results, and the conclusions. It also, however, addressed something that is often harder to provide feedback on, for instance the tone of the argument. I hope that scientists interested in these issues will not only read the final manuscript, but also the different steps of the peer review processes. These are very informative, I think, and provide a more complete picture of mainly the raison for certain decisions.
Not only does this provide the reader interested in stream conservation with the opportunity to make up their own mind on the appropriateness of these decisions, but it could potentially lead to more analyses of this important data set. For instance, maybe a formal meta-analysis that starts with the effect sizes of all the original studies might bring some new insights into this question?

References

[1] Leibold, M. A., Holyoak, M., Mouquet, N. et al. (2004). The metacommunity concept: a framework for multi‐scale community ecology. Ecology letters, 7(7), 601-613. doi: 10.1111/j.1461-0248.2004.00608.x
[2] Heino, J. (2013). The importance of metacommunity ecology for environmental assessment research in the freshwater realm. Biological Reviews, 88(1), 166-178. doi: 10.1111/j.1469-185X.2012.00244.x
[3] Swan, C. M., and Brown, B. L. (2017). Metacommunity theory meets restoration: isolation may mediate how ecological communities respond to stream restoration. Ecological Applications, 27(7), 2209-2219. doi: 10.1002/eap.1602
[4] Swan, C. M., and Brown, B. L. (2018). Erratum for: Metacommunity theory meets restoration: isolation may mediate how ecological communities respond to stream restoration. Ecological Applications 28:1370–1371. doi: 10.1002/eap.1738
[5] Murray-Stoker, D. (2020). On the efficacy of restoration in stream networks: comments, critiques, and prospective recommendations. bioRxiv, 611939, ver. 7 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/611939

Humans are dramatically modifying many aspects of our planet via increasing concentrations of carbon dioxide in the atmosphere, patterns of land-use change, and unsustainable exploitation of the planet’s resources. These changes impact the abundance of species of wild organisms, with winners and losers. Identifying how different species and groups of species are influenced by anthropogenic activity in different biomes, continents, and habitats, has become a pressing scientific question with many publications reporting analyses of disparate data on species population sizes. Many conclusions are based on the linear analysis of rather short time series of organismal abundances.
 
There has been particular interest in how arthropods are impacted by environmental change, with several recent papers reporting contradictory results. To investigate why these contradictions might arise, Duchenne et al. (2022) conducted an analysis of four published data sets along with a series of experimental analyses of simulated time series to examine the power of widely used statistical analyses to gain inference on temporal trends. Their important paper reveals that accurate inference on dynamics, particularly of species that exhibit large temporal fluctuations in abundance, requires time series that are substantially longer than are typically collected, as well as careful thought as to whether linear models are appropriate. Linear analyses of short time series are susceptible to providing unreliable inference as trends can be strongly influenced by points at either end of the time series. 
 
Duchenne et al.’s paper provides important insight on the conditions when strong inference on temporal trends of arthropod (and other species) abundances can be made, and when they should be treated with caution. They do not doubt that many insect and arachnid species are changing their abundances, and that patterns in these changes may vary spatially. What their results do say is that we should treat grand claims of population recovery or rapid declines apparently to extinction with caution when they are based on short time series, particularly of species that show significant boom and bust dynamics. In many ways, these results are not unexpected, but it is nice to see such careful and thoughtful analyses and interpretation. More data are required for most arthropod species before clear assessments of abundance trends can be made. Given our reliance on many arthropods for food, pollination, and numerous ecosystem services, and the ability of other species to spread devastating human diseases such as dengue and malaria, it is advisable that we slow our modification of their habitats while additional data are collected to allow us to better characterise the trajectory of arthropod populations to understand what the consequences of our actions on the natural world are likely to be.  
 
References

Duchenne F, Porcher E, Mihoub J-B, Loïs G, Fontaine C (2022) Controversy over the decline of arthropods: a matter of temporal baseline? bioRxiv, 2022.02.09.479422, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.02.09.479422

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

Individuals ability to withstand abiotic and biotic stresses is crucial to the maintenance of populations at climate edge of tree species distribution. We start to have a detailed understanding of tree growth response and to a lesser extent mortality response in these populations. In contrast, our understanding of the response of tree fecundity and recruitment remains limited because of the difficulty to monitor it at the individual tree level in the field. Tree recruitment limitation is, however, crucial for tree population dynamics [1-2].
In their study Oddou-Muratorio et al. [3] use a new method that they recently developed that jointly estimate male and female effective fecundity in natural populations using naturally established seedlings [4]. Their method uses a spatially explicit Bayesian analysis based on molecular markers and parentage analyses (MEMM program [4]). They apply this method to an unmanaged Beech forest at the southern edge of Beech distribution, where tree defoliation – taken as an integrative indicator of tree abiotic and biotic stress – and growth have been monitored for all adult trees.
This allows the authors to explore alternative hypothesis about tree fecundity response to stress. In one hand, biotic and abiotic stresses are thought to negatively impact tree fecundity. In the other hand, management and studies of orchard fruit tree support the idea that stress could trigger a compensatory increase of fecundity at the cost of other performances such as growth and survival.
They show that both growth and female fecundity are negatively affected by defoliation. There was no evidence that stresses trigger a compensatory increase of fecundity. Yet, they also found that, for large highly defoliated trees, there was a trade-off between growth and female fecundity. Some individuals are able to mitigate stress impact on fecundity by decreasing their growth. It is difficult to understand with available data what is driving such divergent responses between defoliated individuals. This could be related to differences in micro-environmental conditions or genetic background of individual trees. Such individual-level difference in response to stress could be crucial to understand tree populations response to ongoing climate change. This study clearly opens exciting new perspectives to apply such new methods to understand the role of fecundity on tree population dynamics. For instance, could we apply this method across the species distribution to understand how effective fecundity and its response to abiotic stress change between southern edge populations, core populations, and northern edge populations? Using time-series retrieved from such analysis can we disentangle the effect of different climatic drivers? It would also be interesting to see how such results can contribute to analyses covering the full tree life cycle to understand the contribution of fecundity response to population and evolutionary.

References

[1] Clark, J. S. et al. (1999). Interpreting recruitment limitation in forests. American Journal of Botany, 86(1), 1-16. doi: 10.2307/2656950
[2] Petit, R. J., and Hampe, A. (2006). Some evolutionary consequences of being a tree. Annu. Rev. Ecol. Evol. Syst., 37, 187-214. doi: 10.1146/annurev.ecolsys.37.091305.110215
[3] Oddou-Muratorio, S., Petit, C., Journe, V., Lingrand, M., Magdalou, J. A., Hurson, C., Garrigue, J., Davi, H. and Magnanou, E. (2019). Crown defoliation decreases reproduction and wood growth in a marginal European beech population. bioRxiv, 474874, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/474874
[4] Oddou‐Muratorio, S. and Klein, E. K. (2008). Comparing direct vs. indirect estimates of gene flow within a population of a scattered tree species. Molecular Ecology, 17(11), 2743-2754. doi: 10.1111/j.1365-294X.2008.03783.x