The study titled “General mechanisms for a top-down origin of the predator-prey power law” provides a fresh perspective on the classic predator-prey biomass relationship often observed in ecological communities. Traditionally, predator-prey dynamics have been examined through a bottom-up lens, where prey biomass and energy availability dictate predator populations. However, this study, which instead explores the possibility of a top-down origin for predator-prey power laws, offers a new dimension to our understanding of ecosystem regulation and raises questions about how predator-driven interactions might influence biomass scaling laws independently of prey abundance.

Ecologists have long noted that ecosystems often exhibit sublinear scaling between predator and prey biomasses. This pattern implies that predator biomass does not increase proportionally with prey biomass but at a slower rate, leading to a power-law relationship. Traditional explanations, such as those discussed by Peters (1983) and McGill (2006), have linked this to bottom-up processes, suggesting that increases in prey availability support, but do not fully translate to, larger predator populations due to energy losses in the trophic cascade. However, these explanations assume prey abundance as the principal driver. This new work raises an intriguing question: could density-dependent predator interactions, such as competition and interference, be equally or more important in creating this observed power law?

The authors hypothesized that density-dependent predator interactions might independently control predator biomass, even when prey is abundant. To test this, they combined predator and prey biomass dynamics equation based on a modified Lotka-Volterra model with agent-based models (ABMs) on a spatial grid, simulating predator-prey populations under varying environmental gradients and density-dependent conditions. These models allowed them to incorporate predator-specific factors, such as intraspecific competition (predator self-regulation) and predation interference, offering a quantitative framework to observe whether these top-down dynamics could indeed explain the observed biomass scaling independently of prey population changes.

Their results show that density-dependent predator dynamics, particularly at high predator densities, can yield sublinear scaling in predator-prey biomass relationships. This aligns well with empirical data, such as African mammalian ecosystems where predators seem to self-regulate under high prey availability by competing amongst themselves rather than expanding in direct proportion to prey biomass. Such findings support a shift from bottom-up perspectives to a model where top-down processes drive population regulation and biomass scaling.

I think that the work by Mazzarisi and collaborators (2024) offers a thought-provoking twist on predator-prey dynamics and suggests that our traditional frameworks may benefit from a broader, more predator-centered focus.

References

1. Onofrio Mazzarisi, Matthieu Barbier, Matteo Smerlak (2024) General mechanisms for a top-down origin of the predator-prey power law. bioRxiv, ver.2 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2024.04.04.588057

2. Peters, R. H. (1986). The ecological implications of body size (Vol. 2). Cambridge university press.

3. McGill, B. J. (2006). “A renaissance in the study of abundance.” Science, 314(5801), 770-772. https://doi.org/10.1126/science.1134920

In a recent paper published in PNAS, Fayet et al. [1] reported scarce field observations of two Atlantic puffins (four years apart) apparently scratching their bodies using sticks, which was interpreted by the authors as evidence of tool use in this species. In a short response, Benjamin Farrar [2] raises serious concerns about this interpretation and proposes simpler, more parsimonious, mechanisms explaining the observed behaviour: a textbook case of Morgan's canon.
In virtually all introductory lectures on animal behaviour, students are advised to exercise caution when interpreting empirical data and weighting alternative explanations. We are sometimes prisoner of our assumptions: our desire of beliefs in advanced cognitive skills in non-human species make us more receptive to facts confirming our preconceptions than to simpler, less exciting, interpretations (a phenomenon known as "confirmation bias" in psychology). We must resist the temptation to accept appealing explanations without enough critical thinking. Our students are thus taught to apply the Lloyd Morgan's canon, a variant of one of the most important heuristics in Science, the principle of parsimony or Occam's razor, rephrased by Morgan [3, page 53] in the context of animal behaviour: "In no case may we interpret an action as the outcome of a higher psychical faculty, if it can be interpreted as the outcome of the exercise of one that stands lower in the psychological scale". In absence of evidence to the contrary, one should postulate the simplest cognitive skill consistent with the observed behaviour. While sometimes criticized from an epistemological point of view [4-6], it remains an essential and largely accepted framework of animal cognition. It has repeatedly proved to be a useful guide in the minefield of comparative psychology. Classical ethology questions related to the existence of, for instance, meta-cognition [7], intentionality or problem solving [8] have been convincingly investigated using this principle.
Yet, there is a downside to this conservative approach. Blind reference to Morgan's canon may narrow our theoretical thinking about animal cognition [7,9]. It could be counter-productive to systematically deny advanced cognitive skills in animals. On the contrary, keeping our mind open to unplanned observations, unexpected discoveries, or serendipity [10], and being prepared to accept new hypotheses, sometimes fairly remote from the dominant paradigm, may be a fruitful research strategy. To quote Darwin's famous letter to Alfred Wallace: "I am a firm believer, that without speculation there is no good and original observation" [11]. Brief notes in specialized scientific journals, or even in grey literature (by enthusiast amateur ornithologists, ichthyologists, or entomologists), constitutes a rich array of anecdotal observations. For instance, Sol et al. [12] convincingly compared the innovation propensity across bird species by screening ornithology literature using keywords like 'never reported', 'not seen before', 'first report', 'unusual' or 'novel'. Even if "the plural of anecdote is not data" as the saying goes, such descriptions of novel behaviours, even single-subject observations, are indisputably precious: taxonomic ubiquity of a behaviour is a powerful argument in favour of evolutionary convergence. Of course, a race to the bottom, amplified by the inevitable media hypes around scientific articles questioning human exceptionalism, is another possible scientific trap for behavioural biologists in search of skills characteristic of so-called advanced species, but never described so far in supposedly cognitively simpler organisms. As stated by Franz de Waal [9]: "I have nothing against anecdotes, especially if they have been caught on camera or come from reputable observers who know their animals; but I do view them as a starting point of research, never an end point".
In the case of the two video observations of puffins apparently using sticks as scratching tool, it must be considered as a mere anecdote unless scientists systematically investigate this behaviour. In his constructive criticism of Fayet et al.'s paper, Benjamin Farrar [2] proposes interesting directions of research and testable predictions. A correlation between the background rate of stick picking and the rate of stick preening would indicate that this behaviour was more likely explained by fluke than genuine innovation in this species.

References

[1] Fayet, A. L., Hansen, E. S., and Biro, D. (2020). Evidence of tool use in a seabird. Proceedings of the National Academy of Sciences, 117(3), 1277–1279. doi: 10.1073/pnas.1918060117
[2] Farrar, B. G. (2020). Evidence of tool use in a seabird? PsyArXiv, 463hk, ver. 5 recommended and peer-reviewed by Peer Community In Ecology. doi: 10.31234/osf.io/463hk
[3] Morgan, C. L. (1894). An introduction to comparative psychology. London, UK: Walter Scott, Ltd. Retrieved from https://archive.org/details/introductiontoco00morg/page/53/mode/2up
[4] Meketa, I. (2014). A critique of the principle of cognitive simplicity in comparative cognition. Biology and Philosophy, 29(5), 731–745. doi: 10.1007/s10539-014-9429-z
[5] Fitzpatrick, S. (2017). Against Morgan's Canon. In K. Andrews and J. Beck (Eds.), The Routledge handbook of philosophy of animal minds (pp. 437–447). London, UK: Routledge, Taylor and Francis Group. doi: 10.4324/9781315742250.ch42
[6] Starzak, T. (2017). Interpretations without justification: a general argument against Morgan's Canon. Synthese, 194(5), 1681–1701. doi: 10.1007/s11229-016-1013-4
[7] Arbilly, M., and Lotem, A. (2017). Constructive anthropomorphism: a functional evolutionary approach to the study of human-like cognitive mechanisms in animals. Proceedings of the Royal Society B: Biological Sciences, 284(1865), 20171616. doi: 10.1098/rspb.2017.1616
[8] Taylor, A. H., Knaebe, B., and Gray, R. D. (2012). An end to insight? New Caledonian crows can spontaneously solve problems without planning their actions. Proceedings of the Royal Society B: Biological Sciences, 279(1749), 4977–4981. doi: 10.1098/rspb.2012.1998
[9] de Waal, F. (2016). Are we smart enough to know how smart animals are? New-York, USA: W. W. Norton and Company.
[10] Scheffer, M. (2014). The forgotten half of scientific thinking. Proceedings of the National Academy of Sciences, 111(17), 6119–6119. doi: 10.1073/pnas.1404649111
[11] Darwin, C. R. (1857). Letter to A. R. Wallace, 22 December 1857. Retrieved 30 January 2020, from https://www.darwinproject.ac.uk/letter/DCP-LETT-2192.xml
[12] Sol, D., Lefebvre, L., and Rodríguez-Teijeiro, J. D. (2005). Brain size, innovative propensity and migratory behaviour in temperate Palaearctic birds. Proceedings of the Royal Society B: Biological Sciences, 272(1571), 1433–1441. doi: 10.1098/rspb.2005.3099

In the preprint "From Fear to Food: Predation Risk Shapes Deer Behaviour, Their Resources, and Forest Vegetation", Martin et al. provide a comprehensive examination of the intricate interplay between predation risk, deer behavior, and forest ecosystems. The study offers notable insights into the "ecology of fear," as it takes advantage of an extensive dataset that reflects decades of dedicated research effort. The authors’ approach combines behavioral ecology, plant community analysis, and stable isotope studies, making this work a significant contribution to our understanding of complex ecological phenomena.

One of the most striking aspects of this study is the scale and richness of the dataset. The authors used data collected over multiple decades, spanning various experimental contexts, including islands with and without predators, hunting, and culling histories. These datasets are invaluable, as such long-term, geographically diverse studies are rare. The inclusion of both behavioral observations (e.g., flight initiation distances) and ecological outcomes (e.g., vegetation recovery) underscores the effort to provide a holistic understanding of these ecological interactions.

The results are not only scientifically robust but also conceptually significant. They challenge simplistic assumptions about predator-prey relationships by illustrating how both the presence and absence of predation risk can have lasting effects on ecosystems. For example, the findings that culling restores vegetation but creates behavioral shifts in deer populations emphasize the complexity of ecological restoration efforts. These results invite further exploration into how behavioral adaptations to predation risk may alter long-term ecosystem trajectories.

In conclusion, Martin et al.'s preprint represents a significant advancement in understanding predator-prey interactions and their cascading effects on ecosystems. The study’s comprehensive dataset and integrative approach provide a model for future research in ecological and behavioral sciences. It is a commendable contribution to the field, with implications for both theoretical ecology and practical conservation.

References

Jean-Louis Martin, Simon Chamaillé-Jammes, Anne Salomon, Devana Veronica Gomez Pourroy, Mathilde Schlaeflin, Soizic Le Saout, Annick Lucas, Ilham Bentaleb, Simon Chollet, Jake Pattison, Soline Martin-Blangy , Anthony J. Gaston (2024) From fear to food: predation risk shapes deer behaviour, their resources and forest vegetation . HAL, ver.6 peer-reviewed and recommended by PCI Ecology https://hal.science/hal-04381108v5

The spatial distribution of a species is driven by both biotic and abiotic factors that may change over time (Soberón & Nakamura, 2009; Paquette & Hargreaves, 2021).  Therefore, species ranges are dynamic, especially in humanized landscapes where changes occur at high speeds (Sirén & Morelli, 2020). The distribution of many species is being reduced because of human impacts; however, some species are expanding their distributions, even over their niche (Lustenhouwer & Parker, 2022). One of the factors that may lead to a geographic niche expansion is behavioral flexibility (Mikhalevich et al., 2017), but the mechanisms determining range expansion through behavioral changes are not fully understood. 

The PCI Ecology study by Summers et al. (2023) uses a very large database on the current and historic distribution of two species of grackles that have shown different trends in their distribution. The great-tailed grackle has largely expanded its range over the 20th century, while the range of the boat-tailed grackle has remained very similar. They take advantage of this differential response in the distribution of the two species and run several analyses to test whether it was a change in habitat availability, in the realized niche, in habitat connectivity or in in the other traits or conditions that previously limited the species range, what is driving the observed distribution of the species. The study finds a change in the niche of great-tailed grackle, consistent with the high behavioral flexibility of the species.

The two reviewers and I have seen a lot of value in this study because 1) it addresses a very timely question, especially in the current changing world; 2) it is a first step to better understanding if behavioral attributes may affect species’ ability to change their niche; 3) it contrasts the results using several complementary statistical analyses, reinforcing their conclusions; 4) it is based on the preregistration Logan et al (2021), and any deviations from it are carefully explained and justified in the text and 5) the limitations of the study have been carefully discussed. It remains to know if the boat-tailed grackle has more limited behavioral flexibility than the great-tailed grackle, further confirming the results of this study.
 
References

Logan CJ, McCune KB, Chen N, Lukas D (2021) Implementing a rapid geographic range expansion - the role of behavior and habitat changes. http://corinalogan.com/Preregistrations/gxpopbehaviorhabitat.html

Lustenhouwer N, Parker IM (2022) Beyond tracking climate: Niche shifts during native range expansion and their implications for novel invasions. Journal of Biogeography, 49, 1481–1493. https://doi.org/10.1111/jbi.14395

Mikhalevich I, Powell R, Logan C (2017) Is behavioural flexibility evidence of cognitive complexity? How evolution can inform comparative cognition. Interface Focus, 7, 20160121. https://doi.org/10.1098/rsfs.2016.0121

Paquette A, Hargreaves AL (2021) Biotic interactions are more often important at species’ warm versus cool range edges. Ecology Letters, 24, 2427–2438. https://doi.org/10.1111/ele.13864

Sirén APK, Morelli TL (2020) Interactive range-limit theory (iRLT): An extension for predicting range shifts. Journal of Animal Ecology, 89, 940–954. https://doi.org/10.1111/1365-2656.13150

Soberón J, Nakamura M (2009) Niches and distributional areas: Concepts, methods, and assumptions. Proceedings of the National Academy of Sciences, 106, 19644–19650. https://doi.org/10.1073/pnas.0901637106

Summers JT, Lukas D, Logan CJ, Chen N (2022) The role of climate change and niche shifts in divergent range dynamics of a sister-species pair. EcoEvoRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/osf.io/879pe

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