Food-washing monkeys recognize the law of diminishing returns

  1. Jessica E Rosien
  2. Luke D Fannin
  3. Justin D Yeakel
  4. Suchinda Malaivijitnond
  5. Nathaniel J Dominy  Is a corresponding author
  6. Amanda Tan  Is a corresponding author
  1. Department of Anthropology, Dartmouth College, United States
  2. Department of Biological Sciences, Dartmouth College, United States
  3. Ecology, Evolution, Environment & Society, Dartmouth College, United States
  4. Department of Life and Environmental Sciences, University of California, Merced, United States
  5. The Santa Fe Institute, United States
  6. Department of Biology, Chulalongkorn University, Thailand
  7. National Primate Research Center of Thailand, Chulalongkorn University, Thailand
  8. Department of Anthropology, Durham University, United Kingdom
5 figures, 2 videos and 7 additional files

Figures

Figure 1 with 1 supplement
Variation in the mineral and physical properties of quartz particles on food surfaces.

(a) Particle sizes followed a bimodal distribution, with most particles featuring metal inclusions. Nearly half the sample is <25 µm, the ‘grittiness threshold’ of the human oral cavity (Imai et al., 1995). (b) Circularity is a dimensionless shape factor (range: 0–1) based on two-dimensional microscopy and estimates for the projected area and perimeter of a given particle. Some examples are illustrated; overall, it is a convenient but imperfect proxy for sphericity, or deviations from spherical (Grace and Ebneyamini, 2021). Here, circularity varied as a function of mean Feret diameter, suggesting that larger particles hold greater potential for damaging attack angles during particle–enamel contact.

Figure 1—figure supplement 1
Comparison of cleaning effectiveness.

JER simulated the brushing and washing behaviors of our study animals using the same three treatments of cucumber slices in our experiment. Each simulation was replicated three times (n = 18 simulations). We found that brushing was less efficient than washing across all treatments, eliminating an average of 76 ± 7% vs. 93 ± 4% of surface sands, respectively.

Box 1—figure 1
Raccoons (Procyon lotor) tend to live in wooded habitats near waterways, where they can be seen dousing foods before ingestion (photograph by Markus Zindl, reproduced with permission).
Figure 2 with 4 supplements
Experimental design and results.

(a) To elicit food-cleaning behaviors, we put sliced cucumbers in trays representing three treatments—food surfaces with low (x¯ = 0.2 ± 0.2 mg mm−2), intermediate (x¯ = 0.9 ± 0.1 mg mm−2), and high (x¯ = 1.8 ± 0.9 mg mm−2) concentrations of sand—positioned 1.5 m apart and 15 m from the ocean. (b) Monkeys brushed the sandier treatments for longer durations [χ2 (2, n = 575 food-handling bouts) = 194.7, p<0.0001] with no effect of dominance rank or sex (Figure 2—figure supplement 1). (c) Monkeys washed the sandier treatments for longer durations [χ2 (2, n = 362 food-handling bouts) = 69.7, p<0.0001], and we found an interaction effect with rank independent of sex [χ2 = 19.3, p<0.0001; Figure 2—figure supplement 1]. (d) Energy intake rates also varied as function dominance rank [ANOVA, (LN-transformed); F2,104 = 10.0; p<0.0001]. Symbols represent mean values and whiskers ± 1 s.e. Photos by Amanda Tan.

Figure 2—figure supplement 1
Interindividual variation in mean brushing time, washing time, and energy intake.

(a) Monkeys put more time into brushing sandier treatments, χ2 (2, n = 575 food-brushing events) = 194.7, p<0.0001 with no difference across either dominance ranks or sex. (b) Monkeys put more time into washing sandier treatments, χ2 (2, n = 362 food-washing events) = 69.7, p<0.0001, but we also detected an interaction effect with dominance rank that was independent of sex, χ2 = 19.3, p<0.0001. (c) Energy intake rates (kJ min-1) also varied across dominance ranks (ANOVA, LN-Transformed); F2,104 = 10.0, p<0.0001.

Figure 2—figure supplement 2
Standardized residual diagnostic plots for the brushing generalized linear mixed models (GLMM) simulated using DHARMa.

(a) A qq-plot depicting deviations in the simulated standardized residuals from the overall expected distribution of the model. (b) Standardized simulated model residuals plotted against the predicted values of the model (rank transformed). Model outliers are represented by red stars. In both plots, no notable deviations were detected.

Figure 2—figure supplement 3
Standardized residual diagnostic plots for the washing generalized linear mixed models (GLMM), with ordinal rank modeled as a quadratic term, simulated using DHARMa.

(a) A qq-plot depicting deviations in the simulated standardized residuals from the overall expected distribution of the model. (b) Standardized simulated model residuals plotted against the predicted values of the model (rank transformed). Model outliers are represented by red stars. In both plots, no notable deviations were detected.

Figure 2—figure supplement 4
Standardized residual diagnostic plots for the washing generalized linear mixed models (GLMM), with ordinal rank modeled as a linear term, simulated using DHARMa.

(a) A qq-plot depicting deviations in the simulated standardized residuals from the overall expected distribution of the model. (b) Standardized simulated model residuals plotted against the predicted values of the model (rank transformed). Model outliers are represented by red stars. In both plots, no notable deviations were detected.

Figure 3 with 1 supplement
Predicted and observed cleaning times.

(a) Mean predicted time (large filled points vs. observed times [violin plots] for brushing and washing food [note log scale]). The vertical line associated with predicted times represents the 5–95% CI. (b) Predicted cleaning time as a function of cleaning inefficiency c, and handling time h, with mean predicted values (black points) for brushing and washing based on observed cleaning inefficiencies and handling times. The colored points (as in panel a) represent observed cleaning times. The trade-off between longer food handling times and efficient cleaning (oceanside food-washing; region I) and shorter handling times and inefficient cleaning (immediate food-brushing; region II) is depicted by the black curve.

Figure 3—figure supplement 1
Predicted and observed cleaning times.

Mean predicted time (large filled points vs. observed times [violin plots] for brushing and washing food [note log scale]). The vertical line associated with predicted includes uncertainty in handling time h and represents the 5–95% CI.

Box 2—figure 1
The Aérospatiale-BAC Concorde 102 is an iconic aircraft manufactured from 1965 to 1979.

This photo shows British Airways flight 002 on the eve of its final commercial flight on October 24, 2003 (photograph by Richard Vandervord, reproduced with permission).

Videos

Video 1
Experimental design.

Video footage of our experimental setting, including our study animals and their cleaning behaviors.

Video 2
Examples of overcleaning.

Monkeys allocated excess time to washing and brushing—by factors of 1.5 and 3.0, respectively—beyond that predicted by the optimization of sand removal.

Additional files

Supplementary file 1

Summarized fixed effects for the food brushing GLMM (n = 575 events by animals with known rank) as an analysis of deviance table (Type II Wald Chi Square Tests).

https://cdn.elifesciences.org/articles/98520/elife-98520-supp1-v1.docx
Supplementary file 2

Summarized fixed effects for the food washing GLMM (n = 362 events by animals with known rank) as an analysis of deviance table (Type II Wald Chi Square Tests) for the model that included both quadratic and linear ordinal rank terms.

https://cdn.elifesciences.org/articles/98520/elife-98520-supp2-v1.docx
Supplementary file 3

Summarized fixed effects for the food washing GLMM (n = 362 events by animals with known rank) as an analysis of deviance table (Type II Wald Chi Square Tests) for the model that included just a linear ordinal rank term.

https://cdn.elifesciences.org/articles/98520/elife-98520-supp3-v1.docx
Supplementary file 4

Full model fixed effects and confidence intervals for the food brushing GLMM.

Modeled as a zero-inflated Poisson (ZIP) (n = 575 observations).

https://cdn.elifesciences.org/articles/98520/elife-98520-supp4-v1.docx
Supplementary file 5

Full model fixed effects and confidence intervals for the food washing GLMM fixed effects with both a quadratic and linear ordinal rank term.

Modeled as a zero-inflated Conway-Maxwell Poisson (ZICMP) (n = 362 observations).

https://cdn.elifesciences.org/articles/98520/elife-98520-supp5-v1.docx
Supplementary file 6

Full model fixed effects and confidence intervals for the food washing GLMM fixed effects with only a linear ordinal rank term.

Modeled as a zero-inflated Conway-Maxwell Poisson (ZICMP) (n = 362 observations).

https://cdn.elifesciences.org/articles/98520/elife-98520-supp6-v1.docx
MDAR checklist
https://cdn.elifesciences.org/articles/98520/elife-98520-mdarchecklist1-v1.pdf

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  1. Jessica E Rosien
  2. Luke D Fannin
  3. Justin D Yeakel
  4. Suchinda Malaivijitnond
  5. Nathaniel J Dominy
  6. Amanda Tan
(2025)
Food-washing monkeys recognize the law of diminishing returns
eLife 13:RP98520.
https://doi.org/10.7554/eLife.98520.4