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Affiliations: 1) Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, 2) University of California Los Angeles, USA, 3) University of California Santa Barbara, USA, 4) Arizona State University, Tempe, AZ USA. *Corresponding author:


This is the post-study manuscript of the preregistration that was pre-study peer reviewed and received an In Principle Recommendation on 26 Mar 2019 by:

Aurélie Coulon (2019) Can context changes improve behavioral flexibility? Towards a better understanding of species adaptability to environmental changes. Peer Community in Ecology, 100019. 10.24072/pci.ecology.100019. Reviewers: Maxime Dahirel and Andrea Griffin

Preregistration: html, pdf, rmd

Post-study manuscript (submitted to PCI Ecology for post-study peer review on 3 Jan 2022, underwent 3 rounds of revisions, R2 submitted Mar 2023, R3 submitted Apr 2023): preprint pdf at EcoEvoRxiv, html, rmd


Behavioral flexibility, the ability to adapt behavior to new circumstances, is thought to play an important role in a species’ ability to successfully adapt to new environments and expand its geographic range. However, flexibility is rarely directly tested in a way that would allow us to determine how flexibility works to predict a species’ ability to adapt their behavior to new environments. We use great-tailed grackles (Quiscalus mexicanus; a bird species) as a model to investigate this question because they have recently rapidly expanded their range into North America. We attempted to manipulate grackle flexibility using shaded (light and dark gray) tube reversal learning to determine whether flexibility is generalizable across contexts (multi-access box), and what learning strategies grackles employ. We found that flexibility was manipulable: birds in the manipulated group took fewer trials to pass criterion with increasing reversal number, and they reversed a shade preference in fewer trials by the end of their serial reversals compared to control birds who had only one reversal. Birds that passed their last reversal faster were also more flexible (faster to switch between loci) and innovative (solved more loci) on a multi-access box. All grackles in the manipulated reversal learning group used one learning strategy (epsilon-decreasing) in all reversals, and none used a particular exploration or exploitation strategy earlier or later in their serial reversals. Understanding how flexibility causally relates to other traits will allow researchers to develop robust theory about what flexibility is and when to invoke it as a primary driver in a given context, such as a rapid geographic range expansion.


Behavioral flexibility, the ability to adapt behavior to new circumstances through packaging information and making it available to other cognitive processes (see Mikhalevich et al., 2017 for the theoretical background on this definition), is thought to play an important role in a species’ ability to successfully adapt to new environments and expand its geographic range (e.g., Lefebvre et al., 1997; Sol et al., 2002, 2005, 2007; Sol & Lefebvre, 2000). The behavioral flexibility (hereafter referred to as flexibility) of individuals is considered an important trait that facilitates the capacity for learning, which is then associated with problem solving ability (applying what one has learned about the world to then attempt to access a resource that is not readily accessible) (see review in Lea et al., 2020). It is hypothesized that, through flexibility, individuals can increase the diversity of their behaviors either via asocial learning (innovativeness) or social learning, leading to the establishment of the population in a new area (Wright et al., 2010).

It is predicted that flexibility should positively relate with innovativeness, the ability to create a new behavior or use an existing behavior in a new situation (Griffin & Guez, 2014). However, these predictions are based on species-level data and proxies for flexibility and for innovation (e.g., brain size, number of anecdotal reports of “novel” foods consumed) when examining such relationships (see Logan et al., 2018). Flexibility is rarely directly tested in species that are rapidly expanding their geographic ranges in a way that would allow us to determine how flexibility works and predict a species’ ability to adapt their behavior to new areas. Those investigations that examine the relationship between flexibility and innovation or problem solving in species that are expanding their range show mixed results, with these variables correlating positively (e.g., grey squirrels: Chow et al., 2016), negatively (e.g., Indian mynas: Griffin et al., 2013), or not at all (e.g., stick tool use and string pulling in great-tailed grackles: Logan, 2016). Problem solving in these contexts involves experimental assays that do not necessarily require innovativeness to solve (e.g., the ability to solve tasks using pre-trained behaviors: Griffin & Guez, 2014). However, none of these experiments manipulated flexibility.

Here, we take the first step to improving our understanding of whether and how flexibility relates to innovativeness by starting with one population and performing a manipulative experiment on one of the variables to determine whether there is an associated change in the other. Once this association is known, future research can then investigate whether flexibility and innovativeness are involved in a range expansion. Manipulative experiments go beyond correlations to infer a cause and effect relationship between the manipulated variable and the variable(s) measured after the manipulation (Hernán & Robins, 2006; McElreath, 2020). A manipulative experiment combined with the random assignment of subjects to a condition (manipulated group or control group), eliminates many confounds associated with internal and external variation (for example, season, motivation, sex, and so on). Such manipulative experiments in behavioral ecology have primarily been conducted in laboratory settings because of the increased feasibility, however such experiments are now also being conducted in wild settings (e.g., Aplin et al., 2015).

We focused our study on one population of great-tailed grackles (Quiscalus mexicanus, hereafter grackles), a bird species that is flexible (Logan, 2016). While they are originally from Central America, grackles have rapidly expanded their geographic range across the US since 1880 (Summers et al., 2023; Wehtje, 2003). We attempted to manipulate grackle flexibility using serial reversals of a shade (light or dark gray) preference to determine whether their flexibility is generalizable across additional experimental contexts (touchscreen reversal learning and multi-access box solution switching), whether improving flexibility also improves innovativeness (number of loci solved on a multi-access box), and what learning strategies grackles employ (Figure 1).

Reversal learning is a common way of measuring flexibility that has been used for many decades across many species, therefore lending itself well to comparative analyses and generalizations (see review in Lea et al., 2020). In this test, an individual learns to prefer the rewarded option, which differs from the non-rewarded option in shade/color, shape, space, or another discriminable feature. Once this initial preference is formed, the previously non-rewarded option becomes the rewarded option and vice versa, and the preference is reversed. Individuals who are faster to reverse their preference are considered more flexible - better able to change their behavior when the circumstances change. Serial reversal learning involves continuing to reverse the preference back and forth to determine whether individuals learn a “win-stay, lose-shift” rule that, when the reward no longer follows the expected option, they should switch to preferring the other option (Spence, 1936; J. Warren, 1965; J. M. Warren, 1965). Once this rule is learned, it can then be applied to new contexts and result in improved performance over individuals who have not learned this rule (J. M. Warren, 1965). We randomly assigned individuals to a manipulated or control condition and used serial reversals (for the manipulated group) to attempt to manipulate flexibility and determine whether the manipulated individuals were then more flexible and more innovative in other contexts.

If grackle flexibility is manipulable using serial reversals, this would provide us with a useful tool for investigating the relationship between flexibility and any number of other variables implicated in geographic range expansions. It would provide researchers with a way to examine the direct links between, for example, flexibility and exploration, to determine whether they are connected and in which direction, which could provide insights into how populations establish in a new location if cross-population manipulations were conducted. If the flexibility manipulation is not successful, this could indicate either that we did not manipulate the right aspect of flexibility (e.g., perhaps training them to solve a variety of different types of tasks quickly would be more effective) or that grackle flexibility is not a trait that is trainable.