bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.07.12.738111

The ecology of remembering and forgetting: quantity-quality trade-offs in the spatiotemporal memory of a forager

Abstract

One way that animals can cope with the challenge of locating ephemeral food in time and space is by tracking elapsed time and planning revisits to these resources. These abilities likely evolved under constraints of memory capacity. We expect that during evolution a trade-off emerged between a large memory size (quantity) and high accuracy (quality) of information. We used computer simulations of a forager moving through space and time to investigate how timing accuracy, memory size, and forgetting affect foraging efficiency across environmental conditions, and how foragers should trade off the quantity against quality of memorised information. Memory in general paid off, as it improved foraging efficiency. However, surprisingly, the largest accuracy and size were not always most beneficial. In resource-poor, heterogeneous, and highly dynamic environments, extensive memory was even detrimental, as individuals likely became trapped in overexploited familiar areas. This suggests that under certain environmental conditions, a hidden, non-energetic cost of memory can arise. Furthermore, environmental structure shaped a quantity-quality trade-off such that a minimal memory size and higher timing accuracy were favoured in resource-poor, temporally stable and homogenous environments. Finally, forgetting was beneficial when memory was constrained, and environments were poor, heterogenous and dynamic. Forgetting limited the benefits of increased memory size, highlighting that memory costs can emerge from how it shapes movement patterns and foraging decisions. Overall, our results highlight that larger and more accurate memory is not necessarily better and that forgetting can be adaptive. This study takes a first step toward the theoretical consideration of memory trade-offs in order to research how they shape, and are shaped, by foraging pressures. Author summaryHow can we explain foraging memory abilities differences in animals? In this study, we make an attempt to elucidate the current patterns of temporal memory using a computational model that was inspired by realistic environmental and cognitive mechanisms. Building on our previous theoretical and empirical investigations of the causes and consequences of spatiotemporal memory, we provide new insights into the ecological drivers of temporal memory, how they shape an accuracy-size trade off, and its consequences for movement behaviour. We show that a larger memory is favoured, at the cost of accuracy, in resource-rich and dynamic environments. Our results highlight that while memory is generally beneficial, a larger and more accurate memory is not necessarily better. Moreover, our model suggests that such constraints of memory stem from a hidden cost of how memory restricts movement and instigates local overexploitation. Our findings contribute to a broader understanding of how cognition evolves in response to ecological conditions.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ozturk, K. C. D., van Pinxteren, B. O. C. M., Janmaat, K. R. L., Robira, B.. 2026-07-17. The ecology of remembering and forgetting: quantity-quality trade-offs in the spatiotemporal memory of a forager. https://doi.org/10.64898/2026.07.12.738111

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Deconstructing Boldness: Latent behavioural structure across novelty, predation, and exploration in an endangered species translocation program

Risk-related behaviours including neophobia, exploration, and predator avoidance are often assumed to covary along a general boldness axis. Although some translocation studies have linked one or more of these behaviours with fitness, it is possible that the underlying behavioural structure varies under different selective environments. Conservation breeding programs provide a unique opportunity to evaluate the structure of behavioural correlations in a non-domestic species under artificial conditions. We tested whether risk-related behaviours represent a unified boldness syndrome in a captive population of the endangered Attwaters prairie chicken (APC; Tympanuchus cupido attwateri). We quantified the repeatable behaviours of 257 juveniles and compared 11 models of behavioural covariation structure using multivariate mixed models and confirmatory factor analysis. There was no support for a single risk-taking axis; instead, we found three dimensions representing responses to novelty and environmental stimuli (Engagement), predator avoidance (Threat Response), and maze exploration (Maze Progression). Our results indicate that these risk-related behaviours are not organized along a single axis in captive APCs, challenging assumptions that risk-taking represents a universal behavioural syndrome. To anticipate post-release success accurately, conservation managers should understand the exact behavioural architecture of the captive population rather than assume that the classical bold-shy structure occurs in all contexts.

animal behavior and cognition↗

Shared brain transcriptome signatures of social evolution and plasticity in shell-dwelling cichlid fishes

Inter-individual variability in phenotypic traits is widespread in nature both across and within species, with similar patterns of variation often occurring between and within species. Given that these two types of variation are generated by evolutionary and plasticity processes respectively, it raises the question to what extent the causal mechanisms underlying such variability at these two different levels are shared or not. To address this question, we studied the variation in brain transcriptomes in Tanganyikan cichlids that exhibit both intra- and interspecific variation in social behavior. We compared two facultatively social cichlid species, each containing naturally occurring solitary and social-living individuals, with a closely related obligatory solitary resembling the ancestral state. Differential gene expression and Gene Set Enrichment Analyses were performed in the telencephalon and diencephalon transcriptomes to investigate the molecular basis of both behavioral plasticity and the evolution of sociality. Behavioral plasticity involved few differentially expressed genes but extensive changes in biological pathways, supporting a highly polygenic architecture of social behavior. Across both species, social-living individuals consistently upregulated pathways involved in translation, protein homeostasis, and energy metabolism, whereas solitary individuals showed enrichment of neuronal morphogenesis, cell adhesion, and structural plasticity. Remarkably, these same functional programs were associated with the independent evolution of sociality, revealing a strong overlap between evolutionary and plastic transcriptional responses. This convergence was largely restricted to the telencephalon, while the diencephalon showed limited and inconsistent functional signatures. Together, our results support the repeated recruitment of gene regulatory programs during the evolution of sociality and demonstrate that behavioral plasticity and evolutionary transitions share common neurogenomic responses, consistent with a conserved genetic toolkit for social behavior.

animal behavior and cognition↗

Inductive bias anchors a scaling law for biological learning

The speed of animal learning varies substantially across individuals and task domains, and does not always track intuitive notions of task complexity. A nominally simple binary decision task can take thousands of rewards to reach proficiency, whereas seemingly complex naturalistic tasks can be learned within dozens. A long-standing explanation is that learning speed reflects the alignment between an animal's inductive biases and the task at hand. However, without a precise notion of alignment, it is difficult to translate this idea into quantitative predictions. Here, modeling an animal as a Bayesian learner that improves through iterative reward feedback, we use statistical learning theory to derive a scaling law for biological learning. The law makes two predictions. First, inductive bias multiplicatively sets the speed of learning through a single quantity, the effective complexity. This quantity measures how well the task aligns with the animal's prior, and corresponds to the number of bits required to represent the task solution under that prior. We demonstrate this multiplicative scaling in a human motor learning dataset, where behavioral measurements before learning can precisely predict subsequent learning speed. Second, task performance improves as a power law in experience. We validate this power law in a large-scale mouse learning dataset and show that a two-parameter rescaling collapses individual learning curves onto a universal function predicted by the theory. These results suggest that behavioral measurements before learning can be used to predict task-dependent learning speeds, and they explain why learning speed reflects alignment with prior knowledge rather than nominal task complexity.

animal behavior and cognition↗