Winter is a harsh season for many organisms that have to cope with food shortage and potentially lethal temperatures. Many species have evolved avoidance strategies. Among them, diapause is a resistance stage many insects use to overwinter. For an insect, it is critical to avoid lethal winter temperatures and thus to initiate diapause before winter comes, while making the most of autumn suitable climatic conditions [1,2]. Several cues can be used to appreciate that winter is coming, including day length and temperature [3]. But climate changes, temperatures rise and become more variable from year to year, which imposes strong pressure upon insect phenology [4]. How can insects adapt to changes in the mean and variance of winter onset?
In this paper, Jens Joschinski and Dries Bonte [5] address this question by using a well conducted meta-analysis of 458 diapause reaction norms obtained from 60 primary studies. They first ask first if insect mean diapause timing is tuned to match winter onset. They further ask if insects adapt to climatic unpredictability through a bet-hedging strategy by playing it safe and avoid risk (conservative bet-hedging) or on the contrary by avoiding to put all their eggs in one basket and spread the risk among their offspring (diversified bet-hedging). From published papers, the authors extracted data on mean diapause timing and information on latitude from which they retrieved day length inducing diapause, the date of winter onset and the day length at winter onset.
They found a positive correlation between latitude and the day length inducing diapause. On the contrary they found positive but (very) weak correlation between the date of winter onset and the date of diapause, thus indicating that diapause timing is not as optimally adapted to local environments as expected, particularly at high latitudes. They only found weak correlations between climate unpredictability and variability in diapause timing, and no correlation between climate unpredictability and deviation from optimal diapause timing. Together, these findings go against the hypothesis that insects use diversified or conservative bet-hedging strategies to cope with uncertainty in climatic conditions.
This is what makes the study thought provoking: the results do not match the theory well. Not because of a lack of data or a narrow scope, but because diapause is a complex trait that is determined by a large array of physiological and ecological factors [3]. Determining what are these factors is of particular interest in the face of the current climate change. This study shows what does not determine the timing of insect diapause. Researchers now know where to look at to improve our understanding of this key aspect of insect adaptation to climatic conditions.

References

[1] Dyck, H. V., Bonte, D., Puls, R., Gotthard, K., and Maes, D. (2015). The lost generation hypothesis: could climate change drive ectotherms into a developmental trap? Oikos, 124(1), 54–61. doi: 10.1111/oik.02066
[2] Gallinat, A. S., Primack, R. B., and Wagner, D. L. (2015). Autumn, the neglected season in climate change research. Trends in Ecology & Evolution, 30(3), 169–176. doi: 10.1016/j.tree.2015.01.004
[3] Tougeron, K. (2019). Diapause research in insects: historical review and recent work perspectives. Entomologia Experimentalis et Applicata, 167(1), 27–36. doi: 10.1111/eea.12753
[4] Bale, J. S., and Hayward, S. a. L. (2010). Insect overwintering in a changing climate. Journal of Experimental Biology, 213(6), 980–994. doi: 10.1242/jeb.037911
[5] Joschinski, J., and Bonte, D. (2020). Diapause is not selected as a bet-hedging strategy in insects: a meta-analysis of reaction norm shapes. BioRxiv, 752881, ver. 3 recommended and peer-reviewed by PCI Ecology. doi: 10.1101/752881

The article by Legay et al. [1] addresses two main issues: the links between belowground and aboveground plant traits and the links between plant strategies (as defined by these traits) and the capacity to absorb nitrate and ammonium. I recommend this work because these are important and current issues. The literature on plant traits is extremely rich and the existence of a leaf economic spectrum linked to a gradient between conservative and acquisitive plants is now extremely well established [2-3]. Many teams are now working on belowground traits and possible links with the aboveground gradients [4-5]. It seems indeed that there is a root economic spectrum but this spectrum is apparently less pronounced than the leaf economic spectrum. The existence of links between the two spectrums are still controversial and are likely not universal as suggested by discrepant results and after all a plant could have a conservative strategy aboveground and an acquisitive strategy belowground (or vice-versa) because, indeed, constraints are different belowground and aboveground (for example because in given ecosystem/vegetation type light may be abundant but not water or mineral nutrients). The various results obtained also suggest that we do not full understand the diversity of belowground strategies, what is at stake with these strategies, and the links with root characteristics.
Each time I give a conference on the work we are carrying out on African grasses that likely absorb ammonium preferentially because they inhibit nitrification [6-7], somebody asks me a question about the fact that plant essentially absorb nitrate because ammonium is toxic and nitrate more available in the soil. The present article confirms that this is not the case and that, though there are currently some teams working on the subject, we do not really know for the moment whether plants absorb nitrate or ammonium, in which proportion, how plastic this proportion is within individuals and within species. This subject seems to me crucial because it is linked to (1) the capacity of ecosystems to conserve nitrogen [8], because nitrate, much more than ammonium, goes out of ecosystems through leaching and denitrification, (2) to carbon cycling and plant energy budget because absorbing nitrate requires spending mucho more energy than absorbing ammonium because nitrate must be reduced before being incorporated in plant biomass, which is very energy costly. These two issues are naturally very relevant to develop efficient cropping systems in terms of carbon and nitrogen.
Interestingly, the present article, comparing three grass species in different sites, suggests that there is no trade-off between the absorption of nitrate and ammonium: more acquisitive individuals tend to absorb more ammonium and nitrate. This is contrary to hypotheses we made to predict the outcome of competition between plants absorbing nitrate and ammonium in different proportions [9] but should be tested in the future comparing many different types of plants. The results also suggest that more conservative plants absorb relatively more ammonium, which makes sense because this allows them to spare the energy necessary to reduce nitrate. This leads to the question of the effect of these strategies on nitrogen retention within the ecosystem. If nitrification is high (low), absorbing ammonium is not efficient and likely leads to high (low) nitrogen losses. This should be tested in the future. Moreover, the authors have measured the absorption of nitrate and ammonium through measurements at the root scale on cut roots. This should be complemented by measurements at the whole plant scale.

References

[1] Legay, N., Grassein, F., Arnoldi, C., Segura, R., Laîné, P., Lavorel, S. and Clément, J.-C. (2020). Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits. bioRxiv, 372235, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/372235
[2] Shipley, B., Lechowicz, M.J., Wright, I. & Reich, P.B. (2006) Fundamental trade-offs generating the worldwide leaf economics spectrum. Ecology, 87, 535-541. doi: 10.1890/05-1051
[3] Reich, P.B. (2014) The world-wide ‘fast-slow’ plant economics spectrum: a traits manifesto. J. Ecol., 102, 275-301. doi: 10.1111/1365-2745.12211
[4] Maire, V., Gross, N., Pontes, L.D.S., Picon-Cochard, C. & Soussana, J.F. (2009) Trade-off between root nitrogen acquisition and shoot nitrogen utilization across 13 co-occurring pasture grass species. Func. Ecol., 23, 668-679. doi: 10.1111/j.1365-2435.2009.01557.x
[5] Roumet, C., Birouste, M., Picon-Cochard, C., Ghestem, M., Osman, N., Vrignon-Brenas, S., Cao, K.F. & Stokes, A. (2016) Root structure-function relationships in 74 species: evidence of a root economics spectrum related to carbon economy. New. Phytol., 210, 815-826. doi: 10.1111/nph.13828
[6] Lata, J.-C., Degrange, V., Raynaud, X., Maron, P.-A., Lensi, R. & Abbadie, L. (2004) Grass populations control nitrification in savanna soils. Funct. Ecol., 18, 605-611. doi: 10.1111/j.0269-8463.2004.00880.x
[7] Srikanthasamy, T., Leloup, J., N’Dri, A.B., Barot, S., Gervaix, J., Koné, A.W., Koffi, K.F., Le Roux, X., Raynaud, X. & Lata, J.-C. (2018) Contrasting effects of grasses and trees on microbial N-cycling in an African humid savanna. Soil Biol. Biochem., 117, 153-163. doi: 10.1016/j.soilbio.2017.11.016
[8] Boudsocq, S., Lata, J.C., Mathieu, J., Abbadie, L. & Barot, S. (2009) Modelling approach to analyze the effects of nitrification inhibition on primary production. Func. Ecol., 23, 220-230. doi: 10.1111/j.1365-2435.2008.01476.x
[9] Boudsocq, S., Niboyet, A., Lata, J.-C., Raynaud, X., Loeuille, N., Mathieu, J., Blouin, M., Abbadie, L. & Barot, S. (2012) Plant preference for ammonium versus nitrate: a neglected determinant of ecosystem functioning? Am. Nat., 180, 60-69. doi: 10.1086/665997

Ecosystems shelter a huge number of species, continuously interacting. Each species interact in various ways, with trophic interactions, but also non-trophic interactions, not mentioning the abiotic and anthropogenic interactions. In particular, pollination, competition, facilitation, parasitism and many other interaction types are simultaneously present at the same place in terrestrial ecosystems [1-2]. For this reason, we need today to improve our understanding of such complex interaction networks to later anticipate their responses. This program is a huge challenge facing ecologists and they today join their forces among experimentalists, theoreticians and modelers. While some of us struggle in theoretical and modeling dimensions [3-4], some others perform brilliant works to observe and/or experiment on the same ecological objects [5-6].
In this nice study [6], Magrach et al. succeed in studying relatively large plant-pollinator interaction networks in the field, in Mediterranean ecosystems. For the first time to my knowledge, they study community-wide interactions instead of traditional and easier accessible pairwise interactions. On the basis of a statistically relevant survey, they focus on plant reproductive success and on the role of pollinator interactions in such a success. A more reductionist approach based on simpler pairwise interactions between plants and pollinators would not be able to highlight the interaction network structure (the topology) possibly impacting its responses [1,5], among which the reproductive success of some (plant) species. Yet, such a network analysis requires a fine control of probable biases, as those linked to size or autocorrelation between data of various sites. Here, Magrach et al. did a nice work in capturing rigorously the structures and trends behind this community-wide functioning.
To grasp possible relationships between plant and pollinator species is a first mandatory step, but the next critical step requires understanding processes hidden behind such relationships. Here, the authors succeed to reach this step too, by starting interpreting the processes at stake in their studied plant-pollinator networks [7]. In particular, the niche complementarity has been demonstrated to play a determinant role in the plant reproductive success, and has a positive impact on it [6].
When will we be able to detect a community-wise process? This is one of my team’s objectives, and we developed new kind of models with this aim. Also, authors focus here on plant-pollinator network, but the next step might be to gather every kind of interactions into a huge ecosystem network which we call the socio-ecosystemic graph [4]. Indeed, why to limit our view to certain interactions only? It will take time to grasp the whole interaction network an ecosystem is sheltering, but this should be our next challenge. And this paper of Magrach et al. [6] is a first fascinating step in this direction.

References

[1] Campbell, C., Yang, S., Albert, R., and Shea, K. (2011). A network model for plant–pollinator community assembly. Proceedings of the National Academy of Sciences, 108(1), 197-202. doi: 10.1073/pnas.1008204108
[2] Kéfi, S., Miele, V., Wieters, E. A., Navarrete, S. A., and Berlow, E. L. (2016). How structured is the entangled bank? The surprisingly simple organization of multiplex ecological networks leads to increased persistence and resilience. PLoS biology, 14(8), e1002527. doi: 10.1371/journal.pbio.1002527
[3] Gaucherel, C. (2019). The Languages of Nature. When nature writes to itself. Lulu editions, Paris, France.
[4] Gaucherel, C., and Pommereau, F. Using discrete systems to exhaustively characterize the dynamics of an integrated ecosystem. Methods in Ecology and Evolution, 10(9), 1615-1627. doi: 10.1111/2041-210X.13242
[5] Bennett, J. M. et al. (2018). A review of European studies on pollination networks and pollen limitation, and a case study designed to fill in a gap. AoB Plants, 10(6), ply068. doi: 10.1093/aobpla/ply068
[6] Magrach, A., Molina, F. P., and Bartomeus, I. (2020). Niche complementarity among pollinators increases community-level plant reproductive success. bioRxiv, 629931, ver. 7 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/629931
[7] Bastolla, U., Fortuna, M. A., Pascual-García, A., Ferrera, A., Luque, B., and Bascompte, J. (2009). The architecture of mutualistic networks minimizes competition and increases biodiversity. Nature, 458(7241), 1018-1020. doi: 10.1038/nature07950

The preregistration "Investigating sex differences in genetic relatedness in great-tailed grackles in Tempe, Arizona to infer potential sex biases in dispersal" [1] presents the analysis plan that will be used to genetically and spatially investigate sex-biased dispersal in great-tailed grackles (Quiscalus mexicanus).
Several hypotheses implying mating systems, intrasexual competition or sex-related handicaps have been proposed to explain the diversity of dispersal patterns between or within species according to their ecological requirements, environmental factors such as seasonality [2], or individual characteristics such as age [3] or sex [4].
In birds, females are classically the dispersing sex, while males remain close to the place they were hatched [5], with potential benefits that males derive from knowing the local environment to establish territories [6].
In great-tailed grackles the males hold territories and the females choose which territory to place their nest in [7]. In this context, the main hypothesis is that females are the dispersing sex in this species. The authors of this preregistration plan to investigate this hypothesis and its 3 alternatives ((i) the males are the dispersing sex, (ii) both sexes disperse or (iii) neither of the two sexes disperse), investigating the spatial distribution of genetic relatives.
The authors plan to measure the genetic relatedness (using SNP markers) and geographic distances among all female dyads and among all male dyads in the fine geographic scale (Tempe campus, Arizona). If females disperse away from relatives, the females will be less likely to be found geographically close to genetic relatives.
This pre-registration shows that the authors are well aware of the possible limitations of their study, particularly in relation to their population of 57 individuals, on a small scale. But they will use methods that should be able to detect a signal. They were very good at incorporating the reviewers' comments and suggestions, which enabled them to produce a satisfactory and interesting version of the manuscript presenting their hypotheses, limitations and the methods they plan to use. Another point I would like to stress is that this pre-registration practice is a very good one that makes it possible to anticipate the challenges and the type of analyses to be carried out, in particular by setting out the working hypotheses and confronting them (as well as the methods envisaged) with peers from this stage. I therefore recommend this manuscript and thank all the contributors (authors and reviewers) for their work. I look forward to seeing the outcomes of this study.

References

[1] Sevchik A., Logan C. J., Folsom M., Bergeron L., Blackwell A., Rowney C., and Lukas D. (2019). Investigating sex differences in genetic relatedness in great-tailed grackles in Tempe, Arizona to infer potential sex biases in dispersal. In principle recommendation by Peer Community In Ecology. corinalogan.com/Preregistrations/gdispersal.html
[2] Fies, M. L., Puckett, K. M., and Larson-Brogdon, B. (2002). Breeding season movements and dispersal of Northern Bobwhites in fragmented habitats of Virginia. Vol. 5 , Article 35. Available at: trace.tennessee.edu/nqsp/vol5/iss1/35
[3] Marvá, M., and San Segundo, F. (2018). Age-structure density-dependent fertility and individuals dispersal in a population model. Mathematical biosciences, 300, 157-167. doi: 10.1016/j.mbs.2018.03.029
[4] Trochet, A., Courtois, E. A., Stevens, V. M., Baguette, M., Chaine, A., Schmeller, D. S., Clobert, J., and Wiens, J. J. (2016). Evolution of sex-biased dispersal. The Quarterly Review of Biology, 91(3), 297-320. doi: 10.1086/688097
[5] Greenwood, P. J., and Harvey, P. H. (1982). The natal and breeding dispersal of birds. Annual review of ecology and systematics, 13(1), 1-21. doi: 10.1146/annurev.es.13.110182.000245
[6] Greenwood, P. J. (1980). Mating systems, philopatry and dispersal in birds and mammals. Animal behaviour, 28(4), 1140-1162. doi: 10.1016/S0003-3472(80)80103-5
[7] Johnson, K., DuVal, E., Kielt, M., and Hughes, C. (2000). Male mating strategies and the mating system of great-tailed grackles. Behavioral Ecology, 11(2), 132-141. doi: 10.1093/beheco/11.2.132

In their pre-registered paper [1], McCune and colleagues propose a field-based study of social versus individual learning mechanisms in an avian species (great-tailed grackles) that has been expanding its geographic range. The study forms part of a longer-term project that addresses various aspects of this species’ behaviour and biology, and the experience of the team is clear from the preprint. Assessing variation in learning mechanisms in different sections of the grackles’ distribution range, the researchers will investigate how individual learning and social transmission may impact learning about novel challenges in the environment. Considering that this is a social species, the authors expect both individual learning and social transmission to occur, when groups of grackles encounter new challenges/ opportunities in the wild. This in itself is not a very unusual idea to test [2, 3], but the authors are rigorously distinguishing between imitation, emulation, local enhancement, and social enhancement. Such rigour is certainly valuable in studies of cognition in the wild.
Further, the authors predict that the contribution of individual versus social learning could vary between populations, as the core may contain fewer unfamiliar/novel stimuli than the edge, where artificial sources of water (for example) may be more common. They make an argument that the core, middle, and edge populations would experience differing levels of environmental predictability. If true, their field experiments could yield very novel results on how changes in environmental predictability affect social/individual learning in a single study species. Their data would then give unusual insights into the ecological value of individual learning and distinct forms of social learning – something that is not easy to test in wild animals. The authors consider a variety of alternative hypotheses that may ultimately explain their findings, and clarify their methods and analyses in fine detail. The authors also set out limitations clearly, and give a thorough account of their approaches and thinking.
The reviewers and I have a still-unanswered question, which is central to the study: what is the predictability or unpredictability of the core versus edge environments? Although the authors have explained similarities and distinctions between the different sections of the grackles’ range, their description feels a bit vague -- it's not as rigorous or well-defined as the rest of the paper. Such a lack of definition may be inevitable in the limitations of a preprint, but ultimately it does suggest that there may be real uncertainty about the qualitative differences between the core, edge, and middle environments. The authors do explain that a lack of variation in individual responses to the field experiments would preclude the testing of further hypothesis, but do not mention how a salient lack of variation in novelty/ predictability between the environments could impact their hypotheses.
An assessment/quantification of the rate at which the different populations of grackles encounter novel stimuli would be a cornerstone of the success of this proposed study. Certainly, the authors cannot address this in much more detail during the preprint stage, but they need to consider how to best assess/describe differences before starting the full study. Such an assessment could take the form of either a GIS desktop study (comparing, for example, rates of dam/canal construction in core versus edge sections of the distribution range), or observational/ movement data contrasting how frequently members of core versus edge populations encounter artificial sources of water/food in a given month/year. Considering the long-term nature of the larger project, it is possible that these data are already available, but I am speculating. I would highly recommend that such an assessment be undertaken, beyond the mere mention of expected differences. This would solidify the central idea that there are concrete differences between the environments.
Despite this concern, the authors attended well to the comments and recommendations of the two reviewers – both experts in cognitive ecology. It is a preprint showing clear thinking and a consideration of most of the challenges that may be encountered during the course of the study. My own opinion and the estimations of the two reviewers all underscore the originality and value of this project – this should be a very valuable and potentially novel study. I look forward to seeing the outcomes of the research.

References

[1] McCune, K. B., McElreath, R., and Logan, C. J. (2019). Investigating the use of learning mechanisms in a species that is rapidly expanding its geographic range. In principle recommendation by Peer Community In Ecology. corinalogan.com/Preregistrations/g_sociallearning.html
[2] Benson-Amram, S. and Holekamp, K. E. (2012). Innovative problem solving by wild spotted hyenas. Proceedings of the Royal Society B: Biological Sciences, 279(1744), 4087–4095. doi: 10.1098/rspb.2012.1450
[3] Federspiel, I. G., Boeckle, M., von Bayern, A. M. P. and Emery, N. J. (2019). Exploring individual and social learning in jackdaws (Corvus monedula). Learning & Behavior, 47(3), 258–270. doi: 10.3758/s13420-019-00383-8