RESUBMITTED to PCI Ecology

Files/Preregistrations/g_flexmanip.Rmd

@@ -12,17 +12,17 @@ author:
 date: '`r Sys.Date()`'
 always_allow_html: yes
 output:
+  pdf_document:
+    keep_tex: yes
+    latex_engine: xelatex
+  github_document: 
+    toc: true
   html_document: 
     toc: true
     toc_depth: 4
     toc_float: 
       collapsed: false
     code_folding: hide 
-  github_document: 
-    toc: true
-  pdf_document:
-    keep_tex: yes
-    latex_engine: xelatex
   md_document: 
     toc: true
 bibliography: MyLibrary.bib
@@ -49,7 +49,7 @@ library(formatR)
 knitr::opts_chunk$set(tidy.opts=list(width.cutoff=70),tidy=TRUE) 
 #Make code chunks wrap text so it doesn't go off the page when knitting to PDF
 
-knitr::opts_chunk$set(echo=T, include=T, results='asis', warning=F, message=F) 
+knitr::opts_chunk$set(echo=F, include=T, results='asis', warning=F, message=F) 
 #sets global options to display code along with the results https://exeter-data-analytics.github.io/LitProg/r-markdown.html
 #set echo=F for knitting to PDF (hide code), and echo=T for knitting to HTML (show code)
 ```
@@ -62,7 +62,7 @@ Aurélie Coulon (2019) Can context changes improve behavioral flexibility? Towar
 
 **Preregistration:** [html](http://corinalogan.com/Preregistrations/g_flexmanip.html), [pdf](https://github.com/corinalogan/grackles/blob/master/Files/Preregistrations/g_flexmanipPassedPreStudyPeerReview26Mar2019.pdf), [rmd](https://github.com/corinalogan/grackles/blob/d17a75c24df4b90aa607eda452f4fcc496ae9409/Files/Preregistrations/g_flexmanip.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](https://doi.org/10.32942/osf.io/5z8xs) at EcoEvoRxiv, [html](http://corinalogan.com/Preregistrations/g_flexmanip2.html), [rmd](https://github.com/corinalogan/grackles/blob/master/Files/Preregistrations/g_flexmanip.Rmd)
+**Post-study manuscript** (submitted to PCI Ecology for post-study peer review on 3 Jan 2022, underwent 4 rounds of revisions, R2 submitted Mar 2023, R3 submitted Apr 2023, R4 submitted May 2023): preprint [pdf](https://doi.org/10.32942/osf.io/5z8xs) at EcoEvoRxiv, [html](http://corinalogan.com/Preregistrations/g_flexmanip2.html), [rmd](https://github.com/corinalogan/grackles/blob/master/Files/Preregistrations/g_flexmanip.Rmd)
 
 
 ## ABSTRACT
@@ -102,7 +102,7 @@ If grackle flexibility is manipulable using serial reversals, this would provide
 
  - **P2:** Individuals that have improved their flexibility on a serial reversal learning task using shaded tubes (requiring fewer trials to reverse a preference as the number of reversals increases) are faster to switch between new methods of solving (latency to solve or attempt to solve a new way of accessing the food [locus]), and learn more new loci (higher total number of solved loci) on multi-access box flexibility tasks, and are faster to reverse preferences in a serial reversal task using a touchscreen than individuals in the control group where flexibility has not been manipulated. The positive correlation between reversal learning performance using shaded tubes and a touchscreen (faster birds have fewer trials) and the multi-access boxes (faster birds have lower latencies) indicates that all three tests measure the same ability even though the multi-access boxes require inventing new rules to solve new loci (while potentially learning a rule about switching: "when an option becomes non-functional, try a different option") while reversal learning requires switching between two rules ("choose light gray" or "choose dark gray") or learning the rule to "switch when the previously rewarded option no longer contains a reward". Serial reversals eliminate the confounds of exploration, inhibition, and persistence in explaining reversal learning speed because, after multiple reversals, what is being measured is the ability to learn one or more rules. If the manipulation works, this indicates that flexibility can be influenced by previous experience and might indicate that any individual has the potential to move into new environments (see relevant hypotheses in preregistrations on [genetics](http://corinalogan.com/Preregistrations/g_flexgenes.html) (R1) and [expansion](http://corinalogan.com/Preregistrations/g_expansion.html) (H1).
 
- - **P2 alternative 1:** If the manipulation does not work in that those individuals in the experimental condition do not decrease their reversal speeds more than control individuals, then this experiment elucidates whether general individual variation in flexibility relates to flexibility in new contexts (two distinct multi-access boxes and serial reversals on a touchscreen) as well as innovativeness (multi-access boxes). The prediction is the same as in P2, but in this case variation in flexibility is constrained by traits inherent to the individual [some of which are tested in @mccune2019exploration], which suggests that certain individuals will be more likely to move into new environments.
+ - **P2 alternative 1:** If the manipulation does not work in that those individuals in the experimental condition do not reverse faster than control individuals, then this experiment elucidates whether general individual variation in flexibility relates to flexibility in new contexts (two distinct multi-access boxes and serial reversals on a touchscreen) as well as innovativeness (multi-access boxes). The prediction is the same as in P2, but in this case variation in flexibility is constrained by traits inherent to the individual [some of which are tested in @mccune2019exploration], which suggests that certain individuals will be more likely to move into new environments.
 
  - **P2 alternative 2:** If there is no correlation between reversal learning speed (shaded tubes) and the latency to solve/attempt a new locus on the multi-access boxes, this could be because the latency to solve not only measures flexibility but also innovativeness. In this case, an additional analysis is run with the latency to solve as the response variable, to determine whether the fit of the model (as determined by the lower AIC value) with reversal learning as an explanatory variable is improved if motor diversity (the number of different motor actions used when attempting to solve the multi-access box) is included as an explanatory variable [see @diquelou2015role; @griffin2016invading]. If the inclusion of motor diversity improves the model fit, then this indicates that the latency to solve a new locus on the multi-access box is influenced by flexibility (reversal learning speed) and innovation (motor diversity). 
 
@@ -130,11 +130,11 @@ This study is based on a preregistration that received in principle acceptance a
 
 **Changes at the beginning of data collection**
 
-2) Reversal learning shaded tube choice criterion. At the beginning of the second bird’s initial discrimination in the reversal learning shaded tube experiment (October 2018), we revised the criterion for what counts as a choice from A) the bird’s head needs to pass an invisible line on the table that ran perpendicular to the the tube opening to B) the **bird needs to bend its body or head down to look in the tube** (see B demonstrated in Figure 3). Criterion A resulted in birds making more choices than the number of learning opportunities they were exposed to (because they could not see whether there was food in the tube unless they bent their head down to look in the tube) and appeared to result in slower learning. It is important that one choice equals one learning opportunity, therefore we revised the choice criterion to the latter. Anecdotally, this choice matters because the first three birds in the experiment (Tomatillo, Chalupa, and Queso) learned faster than the pilot birds (Empanada and Fajita) in their initial discriminations and first reversals. Thus, it was an important change to make at the beginning of the experiment (after testing the two pilot birds and before collecting any data that were included in analyses).
+2) Reversal learning shaded tube choice criterion. At the beginning of the second bird’s initial discrimination in the reversal learning shaded tube experiment (October 2018), we revised the criterion for what counts as a choice from A) the bird’s head needs to pass an invisible line on the table that ran perpendicular to the the tube opening to B) the **bird needs to bend its body or head down to look in the tube** (see B demonstrated in Figure 2). Criterion A resulted in birds making more choices than the number of learning opportunities they were exposed to (because they could not see whether there was food in the tube unless they bent their head down to look in the tube) and appeared to result in slower learning. It is important that one choice equals one learning opportunity, therefore we revised the choice criterion to the latter. Anecdotally, this choice matters because the first three birds in the experiment (Tomatillo, Chalupa, and Queso) learned faster than the pilot birds (Empanada and Fajita) in their initial discriminations and first reversals. Thus, it was an important change to make at the beginning of the experiment (after testing the two pilot birds and before collecting any data that were included in analyses).
 
 ![](g_flexmanip_figTzanatl1.png)
 
-**Figure 3.** Tzanatl preciosa bending down to look into the dark gray tube. 
+**Figure 2.** Tzanatl preciosa bending down to look into the dark gray tube. 
 
 3) Criterion to pass the control condition: Before collecting experimental data, we set the number of trials experienced by the birds in the control group as 1100 because this is how many trials it would have taken the pilot bird in the manipulated group, Fajita, to pass serial reversals 2-17 according to our revised serial reversal passing criterion. However, after 25 and 17 days (after Tomatillo and Queso’s first reversals, respectively) of testing the first two individuals in the control group, it became apparent that 1100 trials is impractical given the time constraints for how long we were permitted to keep each bird temporarily in captivity and would prevent birds from completing the test battery before their release. Additionally, after revising the choice criterion, it was going to be likely that birds in the manipulated group would require fewer than 1100 trials to meet the serial reversal passing criterion. Therefore, reducing the number of trials the control birds experience would result in a better match of experience with birds in the manipulated group. On 2 November 2018 we **set the number of trials control birds experience after their first (and only) reversal** to the number of trials it requires the first bird in the manipulated group to pass (the first bird had not passed yet, therefore we did not yet know what this number was). After more individuals in the manipulated group passed, we updated this number to the average number of trials to pass. This applied to all birds in the control condition, except Mofongo. Mofongo (control condition) was a slow participator and would not have finished his test battery by the time it got too hot to keep birds in the aviaries if we used the current average number of trials (420). Instead, we matched him with the fastest bird in the manipulated group (Habanero=290 trials) to make it more likely that Mofongo could get through the rest of the test battery in time.
 
@@ -179,7 +179,7 @@ Grackles were caught in the wild in Tempe, Arizona, USA for individual identific
 \	
 We stopped testing birds after we completed two full aviary seasons because the sample size was above the minimum suggested boundary of 15 (to detect a medium effect size) based on model simulations (see Supplementary Material 1).
 
-#### Summary of testing protocols (Figure 2)
+#### Summary of testing protocols (Figure 3)
 
 - **Reversal learning with shaded tubes:** One light gray and one dark gray tube were placed such that the openings were not visible (shades were pseudorandomized for side). One shade always contained a food reward. The individual had the opportunity to choose to look inside one tube per trial. Once the individual chose correctly on 17 out of the most recent 20 trials, they were considered to have a shade preference, and then the food was always placed in the previously non-rewarded shade and the same passing criterion was used to determine their reversal learning performance. Individuals were randomly placed in the manipulated condition (serial reversals until they passed two consecutive reversals in 50 trials or less) or the control condition (receive only one reversal and then a similar number of total trials to the manipulated individuals, but with two yellow tubes, both of which always had food).
 
@@ -191,7 +191,7 @@ We stopped testing birds after we completed two full aviary seasons because the
 
 ![](g_flexmanip_figPhotos.png)
 
-**Figure 2.** The experimental apparatuses: reversal learning using dark gray and light gray tubes or two different shapes on a touchscreen, and the wooden and plastic multi-access boxes (MAB). The wooden MAB has four loci, each containing food and each locus has a distinct way of being opened: lift up flap (A), swing open flap (B), pull out drawer (C), or push in flap (D). The plastic MAB has four loci that all provide access to one piece of food and each locus has a distinct way of being opened: open the window (left side), pull the string (top side), push the shovel (right side), or twist the shovel (bottom side).
+**Figure 3.** The experimental apparatuses: reversal learning using dark gray and light gray tubes (A) or two different shapes on a touchscreen (B), and the plastic (C) and wooden (D) multi-access boxes (MAB). The plastic MAB has four loci that all provide access to one piece of food and each locus has a distinct way of being opened: open the window (left side), pull the string (top side), push the shovel (right side), or twist the shovel (bottom side). The wooden MAB has four loci, each containing food and each locus has a distinct way of being opened: swing open flap (locus B), pull out drawer (locus C), push in flap (locus D), or lift up flap (locus A). 
 
 #### Open materials