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Animal movement patterns, whether related to dispersal, migration, or ranging behaviors, vary in time. Individual movements reflect the outcomes of interactions between an individual's condition and a multitude of underlying ecological processes. Theory predicts that when competition for breeding territories is high, individuals should arrive at breeding sites earlier than what would otherwise be optimal for breeding in the absence of competition. This is because priority at a site can confer significant competitive advantages leading to better breeding outcomes. Empirical data from long-distance migrants support this theory. However, it has not been tested within the context of fine-scale movements in nonmigratory populations. We assessed the effect of arrival time at a breeding site on reproductive outcomes in an intensively monitored resident population of Great Tits ( Parus major ). The population was monitored passively, via passive integrated transponder (PIT) tag loggers, and actively, via catching, during breeding and nonbreeding seasons. We developed new capture-recapture-resight models that use both data types to model breeding outcome conditional on the unknown individual arrival times. In accordance with theory, individuals arrived at the woods synchronously in waves that were large at the beginning of the nonbreeding season and small toward the end, with very few arrivals in the intervening period. There was a strong effect of arrival time on the probability of breeding; the earlier an individual arrived, the more likely it was to successfully establish a nest that reached the incubation period. However, once nests were established, they had equal probabilities of failing early, regardless of arrival time. Finally, there was moderate evidence of a negative effect of arrival time on the probability of successfully fledging nestlings. These empirical findings are consistent with theoretical models that suggest an important role for competition in shaping fine-scale seasonal movements. Our capture-recapture-resight models are extensible and suitable for a variety of applications, particularly when the goal is to estimate the effects of unobservable arrival times on subsequent ecological outcomes.

Conservation professionals are familiar with value‐driven research and practice. However, recent efforts to use strategic communication, specifically conservation messaging, to affect targeted behaviour change or influence values and attitudes towards conservation introduce new ethical dilemmas that conservation professionals may not have considered or are ill‐equipped to deal with. Drawing from strategic communication theory and professional guidelines, including from public relations, social marketing, advocacy, and the social sciences more broadly, we provide a framework and discuss important ethical considerations for conservation messaging. The considerations discussed include those that apply across all stages of conservation messaging (be reflexive, engage responsibly, and consider power), as well as those that apply when defining the problem (ensure fairness in audience targeting), designing the solution (use equitable messages and calls to action and use truthful messaging and authentic messengers), and considering outcomes (consider intended and unintended consequences). We present these considerations not as a fail‐safe checklist to prevent unethical conduct in conservation messaging, but rather as points of reflection to consider in the design of ethical conservation messages and campaigns. We present a series of prompting questions to guide this process. We believe taking the time to reflect in this way paves the way for more effective and ethical strategies for conservation messaging, leading to more open, trusting, and sustainable relationships with our audiences. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog.

The conservation profession is increasingly seeking effective ways to reduce societal impact on biodiversity, including through targeted behavior change interventions. Multiple conservation behavior change programs exist, but there is also great uncertainty regarding which behaviors are most strategic to target. Behavioral prioritization is a tool that has been used effectively to support behavior change decision‐making in other environmental disciplines and more recently for a small sub‐set of biodiversity behavior change challenges. Here, we use behavioral prioritization to identify individual behaviors that could be modified to achieve biodiversity benefits in the state of Victoria, Australia. We use an adapted nominal group technique method to identify potential biodiversity behaviors and, for each behavior, estimate the corresponding plasticity (or capacity for change) and positive impact on biodiversity outcomes. We elicited 27 behaviors that individuals could undertake to benefit or reduce their negative impact on biodiversity. This list was then used to prioritize 10 behaviors as determined by their likely effect(s) on biodiversity, plasticity, and current prevalence in Victoria. We take a first step in outlining a list of behaviors that can direct Victorian decision‐makers toward increasing positive and reducing negative impacts of society on biodiversity, guide motivated individuals to reduce their own biodiversity footprint, and more broadly, develop a behavior change research agenda for behaviors most likely to benefit biodiversity.

The provision of wild birds with supplementary food has increased substantially over recent decades. While it is assumed that provisioning birds is beneficial, supplementary feeding can have detrimental ‘carry-over’ effects on reproductive traits. Due to difficulties in monitoring individual feeding behaviour, assessing how individuals within a population vary in their exploitation of supplementary food resources has been limited. Quantifying individual consumption of supplementary food is necessary to understand the operation of carry-over effects at the individual level. We used Radio Frequency Identification (RFID) technology and automated feeders to estimate individual consumption of supplementary winter food in a large wild population of great tits Parus major and blue tits Cyanistes caeruleus. Using these data, we identified demographic factors that explained individual variation in levels of supplementary food consumption. We also tested for carry-over effects of supplementary food consumption on recruitment, reproductive success and a measure of survival. Individual variation in consumption of supplementary food was explained by differences between species, ages, sexes and years. Individuals were consistent across time in their usage of supplementary resources. We found no strong evidence that the extent of supplementary food consumption directly influenced subsequent fitness parameters. Such effects may instead result from supplementary food influencing population demographics by enhancing the survival and subsequent breeding of less competitive individuals, which reduce average breeding parameters and increase density-dependent competition. Carry-over effects of supplementary feeding are not universal and may depend upon the temporal availability of the food provided. Our study demonstrates how RFID systems can be used to examine individual-level behaviour with minimal effects on fitness.

Inferences drawn from long‐term field studies are vulnerable to biases in observability of different classes of individuals, which may lead to biases in the estimates of selection, or fitness. Population surveys that monitor breeding individuals can introduce such biases by not identifying individuals that fail early in their reproductive attempts. Here, we quantify how the standard protocol for detecting breeding females introduces bias in a long‐term population study of the great tit, Parus major. We do so by identifying females whose breeding attempts fail before they would normally be censused and explore whether this early failure can be predicted by a number of intrinsic and extrinsic factors. We investigate the effect of these biases on estimates of reproductive performance and selection. We show that females that go undetected by standard censusing because they fail early in their breeding attempt were less likely to have been previously trapped within our study site and were more likely to breed in poor‐quality habitats. Furthermore, we demonstrate that this bias sampling had lead previous studies on this population to overestimate the reproductive performance of unringed females, which are likely to be immigrants to the population. Finally, we show that these biases in detectability influence estimates of selection on a key life‐history trait. While these conclusions are specific to this study, we suggest that such effects are likely to be widespread and that more attention should be given to whether or not methods for surveying natural populations introduce systematic bias that will influence conclusions about ecological and evolutionary processes.

Social network analysis has become a popular tool for characterising the social structure of populations. Animal social networks can be built either by observing individuals and defining links based on the occurrence of specific types of social interactions, or by linking individuals based on observations of physical proximity or group membership, given a certain behavioural activity. The latter approaches of discovering network structure require splitting the temporal observation stream into discrete events given an appropriate time resolution parameter. This process poses several non-trivial problems which have not received adequate attention so far. Here, using data from a study of passive integrated transponder (PIT)-tagged great tits Parus major, we discuss these problems, demonstrate how the choice of the extraction method and the temporal resolution parameter influence the appearance and properties of the retrieved network and suggest a modus operandi that minimises observer bias due to arbitrary parameter choice. Our results have important implications for all studies of social networks where associations are based on spatio-temporal proximity, and more generally for all studies where we seek to uncover the relationships amongst a population of individuals that are observed through a temporal data stream of appearance records.