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

Changes in the spatial range of many species are one of the major consequences of the profound alteration of environmental conditions due to human activities. Some species expand, sometimes spectacularly during invasions; others decline; some shift. Because these changes result in local biodiversity loss (whether local species go extinct or are replaced by colonizing ones), understanding the factors driving spatial range dynamics appears crucial to predict biodiversity dynamics. Identifying the factors that shape individual movement is a main step towards such understanding. The study described in this preregistration (McCune et al. 2020) falls within this context by testing possible links between individual exploration behaviour and movements related to daily space use in an avian study model currently rapidly expanding, the great-tailed grackle (Quiscalus mexicanus).

Movement and exploration: which direction(s) for the link between exploration and dispersal?
Individuals are known to differ in their tendency to explore the environment (Réale et al. 2007; Wolf and Weissing 2012) and therefore in their motivation to move. Accordingly, exploration has been shown to relate to dispersal behaviour, i.e. movements between breeding sites (Dingemanse et al. 2003, Le Galliard et al. 2011, Rasmussen and Belk 2012; reviews in Cote et al. 2010, Ronce et al. 2012). Yet, the mechanisms underlying this link often remain unclear, due to the correlative nature of the data. A classical assumption is that dispersers may benefit from a high capacity to explore, allowing them to familiarize quicker with their new environment once reached, thus alleviating dispersal costs (Bonte et al. 2012). The association between dispersal and exploration would in this case result from selection for this combination of traits (Ronce et al. 2012), even though dispersal event itself may be independent from (and precede the effect of) exploration behaviour. Alternatively (but not exclusively), dispersal may simply be the final outcome of longer movements by individuals exploring larger ranges (Badyaev et al. 1996, Schliehe-Diecks et al. 2012). In the absence of easy ways to manipulate dispersal behaviour, on the one hand, and exploration tendency, on the other hand, investigating detailed, small-scale individual movements in relation to exploration should thus shed light on which processes may yield the observed relations between exploration as an individual personality trait and large-scale, long-term movements, such as dispersal, underlying species range dynamics.
In this project, the exploration behaviour of grackles will be measured in controlled conditions using standardized tests in captivity (McCune et al. 2019) before individuals are released and their daily space use behaviour will then be measured using remote tracking over long time periods (McCune et al. 2020). Importantly, these coupled measures will be obtained for individuals captured in three different populations: within the historical range of the species, in the middle of its expanding range and at the edge of the range (McCune et al. 2020). Therefore, the project will test (i) whether daily space use of individuals is linked to their intrinsic exploration tendency and (ii) whether space use differs between individuals from different populations along the expanding range. The preregistration echoes a complementary project by the same team that will focus on exploration and test (iii) whether exploration tendency differs between individuals from these different populations. Taken together, these three analyses will therefore provide solid background information to assess the role of exploration in the individuals’ decisions leading to movement and range dynamics in this species.
As underlined in the preregistration, previous studies addressing the links between individual exploration behaviour and movements have mostly focused on dispersal. A first type of studies have (as will be done here) measured exploration behaviour of individuals, often in captivity (Dingemanse et al. 2003, Korsten et al. 2013) but also in the wild (Rasmussen and Belk 2012, Debeffe et al. 2013), and related these measures to subsequent dispersal behaviour. The (often implicit) underlying assumption is that more exploratory individuals will be more likely to move further, explore different habitats and thus end up breeding farther than less explorative ones. In other words, exploration tendency precedes and drives dispersal. Sometimes, exploratory behaviour is measured on individuals of known dispersal status, i.e. after the dispersal event (Hoset et al. 2011), in which case selection for certain exploration phenotypes among dispersers may already have occurred. Besides this first approach, another type of studies have measured ‘exploration’ behaviour under the form of prospecting movements of individuals and linked these movements to subsequent dispersal (often in the context of habitat selection). While these studies were in the past based on direct thus potentially biased observations (Reed et al. 1999), they now rely more and more on technological advances using (miniaturized) remote tracking devices (Ponchon et al. 2013) that provide far more complete and unbiased movement data, and sometimes also complementary measures of individuals’ internal state. In this case, the implicit assumption is that individuals prospecting farther and/or in more habitat patches will be more likely to settle in a site located farther away from their departure site, because of a more exhaustive sampling of possible sites allowing individuals to identify higher-quality sites (Badyaev et al. 1996). In other words, exploration tendency would not directly lead to higher movements or longer distances, but would allow individuals to optimize their habitat choice among more numerous options, thus leading to an increased dispersal probability or distance; the relation between exploration and dispersal would thus be indirect. Prospecting studies address more closely the underlying mechanisms of movement; however, they cannot easily separate intrinsic individual exploratory tendency from the prospecting movements themselves, with potential feedback effects of the information already gathered on future exploration of other sites or patches, thus on subsequent movements.
By focusing on individual daily space use movements as a mechanistic approach to understand large-scale movements potentially involved in colonization and range expansion, the grackle study described in this preregistration (McCune et al. 2020) will thus contribute to bridge the knowledge gaps between exploration and dispersal. By linking exploration measures obtained from a battery of standardized tests conducted in controlled conditions to individual daily space use and movements recorded in the wild, the grackle project is set in between previous studies addressing the links between exploration and dispersal: it will document exploration in a separate and independent context with respect to the movements themselves, and it will use a mechanistic view of detailed movements by the same individuals in the wild to explore potential implications for dispersal and range expansion. Testing differences between the three study populations over the species range will indeed inform about potential large-scale, population implications of among-individual variation in the link between exploration and movements. Because this study will only measure already settled adult individuals whose previous history is unknown, there will nevertheless be no direct possible exploration of the link with either previous or subsequent dispersal behaviour. Thus, the potential links studied here relate more directly to post-dispersal benefits of exploration for an optimal exploitation of the new environment. Yet, if exploration is a life-long personality trait linked to daily movement patterns, it may also relate to natal dispersal movements in young individuals.

Evolutionary and conservation perspectives
If the results of the project reveal that exploration tendency and daily space use movements are indeed linked, and that individuals from populations across the species range differ in these traits, new questions will emerge. A first question would be whether such among-individual differences are at the origin of range expansion or rather one of its consequences since, again, we deal with correlative data here. In other words, individuals may differ in exploration tendency, and this may confer them different ability to move around, find and colonize new habitats; or individuals may show differences in exploration following arrival in a new habitat, either because more explorative individuals gain fitness benefits and are thus selected, or because of behavioural plasticity and post-colonization adjustment of exploration behaviour when facing new ecological and social conditions in the new environment. Another open question relates to the link between daily space use and dispersal: is dispersal a by-product of higher daily movements that allow individuals to discover new favorable places where to settle? Exploring this link could involve measuring just fledged individuals before natal dispersal occurs and/or individuals chosen according to their own dispersal history, and this would then imply long-term population monitoring as an efficient (but constraining) tool to address such questions. Finally, assessing the fitness consequences of the link between exploration and space use behaviour, and whether these consequences differ between populations along the range expansion, would also be needed to understand the contribution of this link to the invasion success of this species.
The study model chosen for this project is a rapidly expanding species. Importantly, however, and as emphasized in the preregistration, documenting links between exploration and daily space use patterns as well as differences between populations with different trajectories can provide crucial information in general to understand population persistence in response to global climate and landscape changes, both regarding invasion ability or extinction risk. The information should be key to assess the probability that a species may decline, persist or expand in studies addressing biodiversity and community dynamics in a changing world.

References

Badayev, A. V., Martin, T. E and Etges, W. J. 1996. Habitat sampling and habitat selection by female wild turkeys: ecological correlates and reproductive consequences. Auk 113: 636-646. doi: https://doi.org/10.2307/4088984
Bonte, D. et al. 2012. Costs of dispersal. Biological Reviews 87: 290-312. doi: https://doi.org/10.1111/j.1469-185X.2011.00201.x
Cote, J., Clobert, J., Brodin, T., Fogarty, S. and Sih, A. 2010. Personality-dependent dispersal: characterization, ontogeny and consequences for spatially structured populations. Philosophical Transactions of the Royal Society B 365: 4065-4576. doi: https://doi.org/10.1098/rstb.2010.0176
Debeffe, L., Morellet, N., Cargnelutti, B., Lourtet, B., Coulon, A., Gaillard, J.-M., Bon, R. and Hewison A. J. M. 2013. Exploration as a key component of natal dispersal: dispersers explore more than philopatric individuals in roe deer. Animal Behaviour 86: 143-151. doi: https://doi.org/10.1016/j.anbehav.2013.05.005
Dingemanse, N. J., Both, C., van Noordwijk, A. J., Rutten, A. L. and Drent, P. J. 2003. Natal dispersal and personalities in great tits (Parus major). Proceedings of the Royal Society B 270: 741-747. doi: https://doi.org/10.1098/rspb.2002.2300
Hoset, K. S., Ferchaud, A.-L., Dufour, F., Mersch, D., Cote, J. and Le Galliard, J.-F. 2011. Natal dispersal correlates with behavioral traits that are not consistent across early life stages. Behavioral Ecology 22: 176–183. doi: https://doi.org/10.1093/beheco/arq188
Korsten, P., van Overveld, T., Adriaensen, F. and Matthysen, E. 2013. Genetic integration of local dispersal and exploratory behaviour in a wild bird. Nature Communications 4: 2362. doi: https://doi.org/10.1038/ncomms3362
Le Galliard, J.-F., Rémy, A., Ims, R. A. and Lambin, X. 2011. Patterns and processes of dispersal behaviour in arvicoline rodents. Molecular Ecology 21: 505-523. doi: https://doi.org/10.1111/j.1365-294X.2011.05410.x
McCune K, Ross C, Folsom M, Bergeron L, Logan CJ. 2020. Does space use behavior relate to exploration in a species that is rapidly expanding its geographic range? http://corinalogan.com/Preregistrations/gspaceuse.html In principle acceptance by PCI Ecology of the version on 23 Sep 2020 https://github.com/corinalogan/grackles/blob/master/Files/Preregistrations/gspaceuse.Rmd.
McCune K, MacPherson M, Rowney C, Bergeron L, Folsom M, Logan CJ. 2019. Is behavioral flexibility linked with exploration, but not boldness, persistence, or motor diversity? (http://corinalogan.com/Preregistrations/gexploration.html) In principle acceptance by PCI Ecology of the version on 27 Mar 2019 https://github.com/corinalogan/grackles/blob/master/Files/Preregistrations/gexploration.Rmd
Ponchon, A., Grémillet, D., Doligez, B., Chambert, T., Tveraa, T., González-Solís, J. and Boulinier, T. 2013. Tracking prospecting movements involved in breeding habitat selection: insights, pitfalls and perspectives. Methods in Ecology and Evolution 4: 143-150. doi: https://doi.org/10.1111/j.2041-210x.2012.00259.x
Rasmussen, J. E. and Belk, M. C. 2012. Dispersal behavior correlates with personality of a North American fish. Current Zoology 58: 260–270. doi: https://doi.org/10.1093/CZOOLO%2F58.2.260
Réale, D., Reader, S. M., Sol, D., McDougall, P. T. and Dingemanse, N. J. 2007. Integrating animal temperament within ecology and evolution. Biological Reviews 82: 291-318. doi: https://doi.org/10.1111/j.1469-185x.2007.00010.x
Reed, J. M., Boulinier, T., Danchin, E. and Oring, L. W. 1999. Informed dispersal: prospecting by birds for breeding sites. Current Ornithology 15: 189-259. doi: https://doi.org/10.1007/978-1-4757-4901-4_5
Ronce, O. and Clobert, J. 2012. Dispersal syndromes. pp. 119-138 In Dispersal Ecology and Evolution (eds. Clobert, J., Baguette, M., Benton, T. G. and Bullock, J. M.), pp. 119-138. Oxford University Press.
Schliehe-Diecks, S., Eberle, M. and Kappeler, P. M. 2012. Walk the line - dispersal movements of gray mouse lemurs (Microcebus murinus). Behavioral Ecology and Sociobiology 66: 1175-1185. doi: https://dx.doi.org/10.1007%2Fs00265-012-1371-y
Wolf, M. and Weissing, F. J. 2012. Animal personalities: consequences for ecology and evolution. Trends in Ecology and Evolution 27: 452-461. doi: https://doi.org/10.1016/j.tree.2012.05.001

Species interactions are classically derived from the law of mass action: the probability that, for example, a predation event occurs is proportional to the product of the density of the prey and predator species. In order to describe how predator and prey species populations grow, is then necessary to introduce functional response, describing the intake rate of a consumer as a function of food (e.g. prey) density.
Linear functional responses shapes are typically introduced in the ecological modeling of population dynamics for both predator-prey and mutualistic systems [1,2]. Recently some works have proposed alternatives to the classic approach for mutualistic systems [3,4], both because cooperative interactions also model effect not directly related to mass action [3] and for analytical tractability [4,5].
In this work [6] the authors challenge the classic modeling of functional response also for predator-prey systems. In particular, they use a meta-analysis of several observational studies of predator-prey ecosystems to infer a generic predator functional response, fitting a phenomenological generalization of the mass-action law. Using advanced statistical analysis, they show that the functional response obtained from data is clearly different from the mass-action assumption. In fact, they found that it scales sub-linearly as the square root of the ratio between predator and prey biomass. They further argue that, from a macro-ecological point of view, using such a phenomenological relationship might be more valuable than relying on various mechanistic functional response formulations.
The manuscript thus provides an interesting different perspective on how to approach predator-prey modelling and for this reason, I have recommended the work for PCI Ecology.

References

[1] Volterra, V. (1928). Variations and Fluctuations of the Number of Individuals in Animal Species living together. ICES Journal of Marine Science, 3(1), 3–51. doi: 10.1093/icesjms/3.1.3
[2] 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
[3] Tu, C., Suweis, S., Grilli, J., Formentin, M., and Maritan, A. (2019). Reconciling cooperation, biodiversity and stability in complex ecological communities. Scientific Reports, 9(1), 1–10. doi: 10.1038/s41598-019-41614-2
[4] García-Algarra, J., Galeano, J., Pastor, J. M., Iriondo, J. M., and Ramasco, J. J. (2014). Rethinking the logistic approach for population dynamics of mutualistic interactions. Journal of Theoretical Biology, 363, 332–343. doi: 10.1016/j.jtbi.2014.08.039
[5] Suweis, S., Simini, F., Banavar, J. R., and Maritan, A. (2013). Emergence of structural and dynamical properties of ecological mutualistic networks. Nature, 500(7463), 449–452. doi: 10.1038/nature12438
[6] Barbier, M., Wojcik, L., and Loreau, M. (2020). A macro-ecological approach to predators’ functional response. BioRxiv, 832220, ver. 4 recommended and peer-reviewed by Peer Community in Ecology. doi: 10.1101/832220

Mammals show a very low level of variation in vertebral count, both among and within species, in comparison to other vertebrates [1]. Jordan’s rule for fishes states that the vertebral number among species increases with latitude, due to ambient temperatures during development [2]. Temperature has also been shown to influence vertebral count within species in fish [3], amphibians [4], and birds [5]. However, in mammals the count appears to be constrained, on the one hand, by a possible relationship between the development of the skeleton and the proliferations of cell lines with associated costs (neural malformations, cancer etc., [6]), and on the other by the cervical origin of the diaphragm [7].
Knight et al. [8] investigate the effect of intrauterine temperature variation on skeletal morphology during development, and focus on a particular mammal, Dasypus novemcinctus, or nine-banded armadillo. Armadillos (Xenarthra) and are characterized by relatively low body temperatures and low basal rates of metabolism. Dasypus novemcinctus is the only xenarthran mammal to have naturally expanded its range into the middle latitudes of the U.S., and one of the few mammals that invaded North America from South America. It is one of few placentals that withstand considerable decrease of body temperature without torpor. It presents a resting body temperature that is low and variable for a placental mammal of its size [9] and is the only vertebrate that gives birth to monozygotic quadruplets. Among 42 monotreme, marsupial and placental genera, Dasypus novemcinctus shows the highest variation of thoracolumbar vertebral count [10].
The particularities of Dasypus novemcinctus regarding vertebral count variation and ability to withstand variable temperature qualify it as a target organism for study of the relationship between skeleton morphology and temperature in mammals.
Knight et al. [8] explored variability in vertebral count within Dasypus novemcinctus to understand whether temperature during development determines skeleton morphology. To this end they experimented with 22 armadillos (19 with data) and litters from 12 pregnant females, in two environments, for three years — an impressive effort and experimental setup. Moreover, they used a wide variety of advanced experimental and analytical techniques. For example, they implanted intra-abdominal, long-term temperature recorders, which recorded data every 6 to 120 minutes for up to several months. They analysed body temperature periodicity by approximation of the recordings with Fourier series, and they CT-scanned fetuses.
All 19 individuals (from which data could be gathered) exhibited substantial daily variation in body temperature. Several intriguing results emerged such as the counter-intuitive finding that the mammals’ body temperature fluctuates more indoors than outdoors. Furthermore, three females (out of 12) were found to have offspring with atypical skeletons, and two of these mothers presented an extremely low internal temperature early in pregnancy. Additionally, genetically identical quadruplets differed skeletally among themselves within two litters.
Results are not yet definitive about the relationship of temperature during development and vertebral count in Dasypus novemcinctus. However, Knight et al. [8] demonstrated that nine-banded armadillos survive with high daily internal temperature fluctuations and successfully bring to term offspring which vary in skeletal morphology among and within genetically identical litters despite major temperature extremes.

References

[1] Hautier L, Weisbecker V, Sánchez-Villagra MR, Goswami A, Asher RJ (2010) Skeletal development in sloths and the evolution of mammalian vertebral patterning. Proceedings of the National Academy of Sciences, 107, 18903–18908. doi: 10.1073/pnas.1010335107
[2] Jordan, D.S. (1892) Relations of temperature to vertebrae among fishes. Proceedings of the United States National Museum, 1891, 107-120. doi: 10.5479/si.00963801.14-845.107
[3] Tibblin P, Berggren H, Nordahl O, Larsson P, Forsman A (2016) Causes and consequences of intra-specific variation in vertebral number. Scientific Reports, 6, 1–12. doi: 10.1038/srep26372
[4] Peabody RB, Brodie ED (1975) Effect of temperature, salinity and photoperiod on the number of trunk vertebrae in Ambystoma maculatum. Copeia, 1975, 741–746. doi: 10.2307/1443326
[5] Lindsey CC, Moodie GEE (1967) The effect of incubation temperature on vertebral count in the chicken. Canadian Journal of Zoology, 45, 891–892. doi: 10.1139/z67-099
[6] Galis F, Dooren TJMV, Feuth JD, Metz JAJ, Witkam A, Ruinard S, Steigenga MJ, Wunaendts LCD (2006) Extreme selection in humans against homeotic transformations of cervical vertebrae. Evolution, 60, 2643–2654. doi: 10.1111/j.0014-3820.2006.tb01896.x
[7] Buchholtz EA, Stepien CC (2009) Anatomical transformation in mammals: developmental origin of aberrant cervical anatomy in tree sloths. Evolution and Development, 11, 69–79. doi: 10.1111/j.1525-142X.2008.00303.x
[8] Knight F, Connor C, Venkataramanan R, Asher RJ. (2020). Body temperatures, life history, and skeletal morphology in the nine-banded armadillo (Dasypus novemcinctus). PCI-Ecology. doi: 10.17863/CAM.50971
[9] McNab BK (1980) Energetics and the limits to a temperate distribution in armadillos. Journal of Mammalogy, 61, 606–627. doi: 10.2307/1380307
[10] Asher RJ, Lin KH, Kardjilov N, Hautier L (2011) Variability and constraint in the mammalian vertebral column. Journal of Evolutionary Biology, 24, 1080–1090. doi: 10.1111/j.1420-9101.2011.02240.x

A predator can strongly influence the demography of its prey, which can have profound carryover effects on the trophic network; so-called density-mediated indirect interactions (DMII; Werner and Peacor 2003; Schmitz et al. 2004; Trussell et al. 2006). Furthermore, a novel predator can alter the phenotypes of its prey for traits that will change prey foraging efficiency. These trait-mediated indirect interactions may in turn have cascading effects on the demography and features of the basal resources consumed by the intermediate consumer (TMIII; Werner and Peacor 2003; Schmitz et al. 2004; Trussell et al. 2006), but very few studies have looked for these effects (Trusell et al. 2006). The study “Trophic cascade driven by behavioural fine-tuning as naïve prey rapidly adjust to a novel predator”, by Jolly et al. (2020) is therefore a much-needed addition to knowledge in this field. The authors have profited from a rare introduction of Northern quolls (Dasyurus hallucatus) on an Australian island, to examine both the density-mediated and trait-mediated indirect interactions with grassland melomys (Melomys burtoni) and the vegetation of their woodland habitat.
Jolly et al. (2020) compared melomys populations in four quoll-invaded and three quoll-free sites on the same island. Using capture-mark-recapture methods, they found a lower survival and decreased population size in quoll-invaded sites compared to quoll-free sites. Although they acknowledge that this decline could be attributable to either the direct effects of the predator or to a wildfire that occurred early in the experiment in the quoll-invaded sites, the authors argue that the wildfire alone cannot explain all of their results.
Beyond demographic effects, Jolly et al. (2020) also examined risk taking, foraging behaviour, and predator avoidance in melomys. Quoll presence was first associated with a strong decrease in risk taking in melomys, but the difference disappeared over the three years of study, indicating a possible adjustment by the prey. In quoll-invaded sites, though, melomys continued to be more neophobic than in the quoll-free sites throughout the study. Furthermore, in a seed (i.e. wheat) removal experiment, Jolly et al. (2020) measured how melomys harvested seeds in the presence or absence of predator scents. In both quoll-invaded and quoll-free sites, melomys density increased seed harvest efficiency. Melomys also removed less seeds in quoll-invaded sites than in quoll-free sites, supporting both the DMII and TMII hypotheses. However, in the quoll-invaded sites only, melomys foraged less on predator-scented seed patches than on unscented ones, trading foraging efficiency for an increased safety against predators, and this effect increased across the years. This last result indicates that predators can indirectly influence seed consumption through the trade-off between foraging and predator avoidance, strongly supporting the TMII hypothesis.
Ideally, the authors would have run a nice before-after, impact-control design, but nature does not always allow for ideal experimental designs. Regardless, the results of such an “experiment in the wild” predation study are still valuable, as they are very rare (Trussell et al. 2006), and they provide crucial information on the direct and indirect interactions along a trophic cascade. Furthermore, the authors have effectively addressed any concerns about potential confounding factors, and thus have a convincing argument that their results represent predator-driven demographic and behavioural changes.
One important question remains from an evolutionary ecology standpoint: do the responses of melomys to the presence of quolls represent phenotypically plastic changes or rapid evolutionary changes caused by novel selection pressures? Classically, TMII are assumed to be mostly caused by phenotypic plasticity (Werner and Peacor 2003), and this might be the case when the presence of the predator is historical. Phenotypic plasticity allows quick and reversible adjustments of the prey population to changes in the predator density. When the predator population declines, such rapid phenotypic changes can be reversed, reducing the cost associated with anti-predator behaviour (e.g., lower foraging efficiency) in the absence of predators. In the case of a novel predator, however, short-term evolutionary responses by the prey may play role in the TMII, as they would allow a phenotypic shift in prey’s traits along the trade-off between foraging efficiency and anti-predator response that will probably more advantageous over the longer term, if the predator does not disappear. The authors state that they could not rule out one or the other of these hypotheses. However, future work estimating the relative importance of phenotypic plasticity and evolutionary changes in the quoll-melomys system would be valuable. Phenotypic selection analysis, for example, by estimating the link between survival and the traits measured, might help test for a fitness advantage to altered behaviour in the presence of a predator. Common garden experiments, comparing the quoll-invaded and the quoll-free melomys populations, might also provide information on any potential evolutionary changes caused by predation. More work could also analyse the potential effects on the seed populations. Not only might the reduction in seed predation have consequences on the landscape in the future, as the authors mention, but it may also mean that the seeds themselves could be subject to novel selection pressures, which may affect their phenology, physiology or life history. Off course, the authors will have to switch from wheat to a more natural situation, and evaluate the effects of changes in the melomys population on the feature of the local vegetation and the ecosystem.
Finally, the authors have not yet found that the observed changes in the traits have translated into a demographic rebound for melomys. Here again, I can see an interesting potential for further studies. Should we really expect an evolutionary rescue (Bell and Gonzalez 2009) in this system? Alternatively, should the changes in behaviour be accompanied by permanent changes in life history, such as a slower pace-of-life (Réale et al. 2010) that could possibly lead to lower melomys density?
This paper provides nice in natura evidence for density- and trait-mediated indirect interactions hypotheses. I hope it will be the first of a long series of work on this interesting quoll-melomys system, and that the authors will be able to provide more information on the eco-evolutionary consequences of a novel predator on a trophic network.

References

-Bell G, Gonzalez A (2009) Evolutionary rescue can prevent extinction following environmental change. Ecology letters, 12(9), 942-948. https://doi.org/10.1111/j.1461-0248.2009.01350.x
-Jolly CJ, Smart AS, Moreen J, Webb JK, Gillespie GR, Phillips BL (2020) Trophic cascade driven by behavioural fine-tuning as naïve prey rapidly adjust to a novel predator. bioRxiv, 856997, ver. 6 peer-reviewed and recommended by PCI Ecology. https://doi.org/ 10.1101/856997
-Matassa C, Ewanchuk P, Trussell G (2018) Cascading effects of a top predator on intraspecific competition at intermediate and basal trophic levels. Functional Ecology, 32(9), 2241-2252. https://doi.org/10.1111/1365-2435.13131
-Réale D, Garant D, Humphries MM, Bergeron P, Careau V, Montiglio PO (2010) Personality and the emergence of the pace-of-life syndrome concept at the population level. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1560), 4051-4063. https://doi.org/10.1098/rstb.2010.0208
-Schmitz O, Krivan V, Ovadia O (2004) Trophic cascades: the primacy of trait‐mediated indirect interactions. Ecology Letters 7(2), 153-163. https://doi.org/10.1111/j.1461-0248.2003.00560.x
-Trussell G, Ewanchuk P, Matassa C (2006). Habitat effects on the relative importance of trait‐ and density‐mediated indirect interactions. Ecology Letters, 9(11), 1245-1252. https://doi.org/10.1111/j.1461-0248.2006.00981.x
-Werner EE, Peacor SD (2003) A review of trait‐mediated indirect interactions in ecological communities. Ecology, 84(5), 1083-1100. https://doi.org/10.1890/0012-9658(2003)084[1083:AROTII]2.0.CO;2