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The producer-scrounger game is a key element of foraging ecology in many systems. Producing and scrounging typically covary negatively, but partitioning this covariance into contributions of individual plasticity and consistent between individual differences is key to understanding population-level consequences of foraging strategies. Furthermore, little is known about the role cognition plays in the producer-scrounger game. We investigated the role of cognition in these alternative foraging tactics in wild mixed-species flocks of great tits and blue tits, using a production learning task in which we measured individuals' speed of learning to visit the single feeder in an array that would provide them with a food reward. We also quantified the proportion of individuals' feeds that were scrounges ('proportion scrounged'); scrounging was possible if individuals visited immediately after a previous rewarded visitor. Three learning experiments-initial and two reversal learning-enabled us to estimate the repeatability and covariance of each foraging behaviour. First, we examined whether individuals learned to improve their scrounging success (i.e. whether they obtained food by scrounging when there was an opportunity to do so). Second, we quantified the repeatability of proportion scrounged, and asked whether proportion scrounged affected production learning speed among individuals. Third, we used multivariate analyses to partition within- and among-individual components of covariance between proportion scrounged and production learning speed. Individuals improved their scrounging success over time. Birds with a greater proportion scrounged took longer to learn their own rewarding feeder. Although multivariate analyses showed that covariance between proportion scrounged and learning speed was driven primarily by within-individual variation, that is, by behavioural plasticity, among-individual differences also played a role for blue tits. This is the first demonstration of a cognitive trait influencing producing and scrounging in the same wild system, highlighting the importance of cognition in the use of alternative resource acquisition tactics. The results of our covariance analyses suggest the potential for genetic differences in allocation to alternative foraging tactics, which are likely species- and system-dependent. They also point to the need to control for different foraging tactics when studying individual cognition in the wild.

Natal body mass is a key predictor of viability and fitness in many animals. While variation in body mass and therefore juvenile viability may be explained by genetic and environmental factors, emerging evidence points to the gut microbiota as an important factor influencing host health. The gut microbiota is known to change during development, but it remains unclear whether the microbiome predicts fitness, and if it does, at which developmental stage it affects fitness traits.We collected data on two traits associated with fitness in wild nestling great tits (Parus major): weight and survival to fledging. We characterised the gut microbiome using 16S rRNA sequencing from nestling faeces and investigated temporal associations between the gut microbiome and fitness traits across development at day 8 (D8) and day 15 (D15) post-hatching. We also explored whether particular microbial taxa were ‘indicator species’ that reflected whether nestlings survived or not.There was no link between mass and microbial diversity on D8 or D15. However, we detected a time-lagged relationship where weight at D15 was negatively associated with the microbial diversity at D8, controlling for weight at D8, therefore reflecting relative weight gain over the intervening period.Indicator species analysis revealed that specificity values were high and fidelity values were low, suggesting that indicator taxa were primarily detected within either the survived or not survived groups, but not always detected in birds that either survived or died. Therefore these indicator taxa may be sufficient, but not necessary for determining either survival or mortality, perhaps owing to functional overlap in microbiota.We highlight that measuring microbiome-fitness relationships at just one time point may be misleading, especially early in life. Instead, microbial-host fitness effects may be best investigated longitudinally to detect critical development windows for key microbiota and host traits associated with neonatal weight. Our findings should inform future hypothesis testing to pinpoint which features of the gut microbial community impact on host fitness, and when during development this occurs. Such confirmatory research will shed light on population level processes and could have the potential to support conservation.