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Density‐dependent feedback is recognized as important regulatory mechanisms of population size. Considering the spatial scales over which such feedback operates has advanced our theoretical understanding of metapopulation dynamics. Yet, metapopulation models are rarely fit to time‐series data and tend to omit details of the natural history and behavior of long‐lived, highly mobile species such as colonial mammals and birds. Seabird metapopulations consist of breeding colonies that are connected across large spatial scales, within a heterogeneous marine environment that is increasingly affected by anthropogenic disturbance. Currently, we know little about the strength and spatial scale of density‐dependent regulation and connectivity between colonies. Thus, many important seabird conservation and management decisions rely on outdated assumptions of closed populations that lack density‐dependent regulation. We investigated metapopulation dynamics and connectivity in an exemplar seabird species, the Northern gannet (Morus bassanus), using more than a century of census data of breeding colonies distributed across the Northeast Atlantic. We developed and fitted these data to a novel hierarchical Bayesian state‐space model, to compare increasingly complex scenarios of metapopulation regulation through lagged, local, regional, and global density dependence, as well as different mechanisms for immigration. Models with conspecific attraction fit the data better than the equipartitioning of immigrants. Considering local and regional density dependence jointly improved model fit slightly, but importantly, future colony size projections based on different mechanistic regulatory scenarios varied widely: a model with local and regional dynamics estimated a lower metapopulation capacity (645,655 Apparently Occupied Site [AOS]) and consequently higher present saturation (63%) than a model with local density dependence (1,367,352 AOS, 34%). Our findings suggest that metapopulation regulation in the gannet is more complex than traditionally assumed, and highlight the importance of using models that consider colony connectivity and regional dynamics for conservation management applications guided by precautionary principles. Our study advances our understanding of metapopulation dynamics in long‐lived colonial species and our approach provides a template for the development of metapopulation models for colonially living birds and mammals. [ABSTRACT FROM AUTHOR]

The ability of individual animals to balance their energy budgets throughout the annual cycle is important for their survival, reproduction and population dynamics. However, the annual cycles of many wild, mobile animals are difficult to observe and our understanding of how individuals balance their energy budgets throughout the year therefore remains poor.We developed a hierarchical Bayesian state‐space model to investigate how key components of animal energy budgets (namely individual energy gain and storage) varied in space and time. Our model used biologger‐derived estimates of time‐activity budgets, locations and energy expenditure to infer year‐round time series of energy income and reserves. The model accounted for seasonality in environmental drivers such as sea surface temperature and daylength, allowing us to identify times and locations of high energy gain.Our study system was a population of common guillemots Uria aalge breeding at a western North Sea colony. These seabirds manage their energy budgets by adjusting their behaviour and accumulating fat reserves. However, typically during severe weather conditions, birds can experience an energy deficit over a sustained period, leading to starvation and large‐scale mortality events.We show that guillemot energy gain varied in both time and space. Estimates of guillemot body mass varied throughout the annual cycle and birds periodically experienced losses in mass. Mass losses were likely to have either been adaptive, or due to energetic bottlenecks, the latter leading to increased susceptibility to mortality. Guillemots tended to be lighter towards the edge of their spatial distribution.We describe a framework that combines biologging data, time‐activity budget analysis and Bayesian state‐space modelling to identify times and locations of high energetic reward or potential energetic bottlenecks in a wild animal population. Our approach can be extended to address ecological and conservation‐driven questions that were previously unanswerable due to logistical complexities in collecting data on wild, mobile animals across full annual cycles. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Background: It is often assumed that the population dynamics of the malaria vector Anopheles funestus, its role in malaria transmission and the way it responds to interventions are similar to the more elaborately characterized Anopheles gambiae. However, An. funestus has several unique ecological features that could generate distinct transmission dynamics and responsiveness to interventions. The objectives of this work were to develop a model which will: (1) reconstruct the population dynamics, survival, and fecundity of wild An. funestus populations in southern Tanzania, (2) quantify impacts of density dependence on the dynamics, and (3) assess seasonal fluctuations in An. funestus demography. Through quantifying the population dynamics of An. funestus, this model will enable analysis of how their stability and response to interventions may differ from that of An. gambiae sensu lato. Methods: A Bayesian State Space Model (SSM) based on mosquito life history was fit to time series data on the abundance of female An. funestus sensu stricto collected over 2 years in southern Tanzania. Prior values of fitness and demography were incorporated from empirical data on larval development, adult survival and fecundity from laboratory-reared first generation progeny of wild caught An. funestus. The model was structured to allow larval and adult fitness traits to vary seasonally in response to environmental covariates (i.e. temperature and rainfall), and for density dependency in larvae. The effects of density dependence and seasonality were measured through counterfactual examination of model fit with or without these covariates. Results: The model accurately reconstructed the seasonal population dynamics of An. funestus and generated biologically-plausible values of their survival larval, development and fecundity in the wild. This model suggests that An. funestus survival and fecundity annual pattern was highly variable across the year, but did not show consistent seasonal trends either rainfall or temperature. While the model fit was somewhat improved by inclusion of density dependence, this was a relatively minor effect and suggests that this process is not as important for An. funestus as it is for An. gambiae populations. Conclusion: The model's ability to accurately reconstruct the dynamics and demography of An. funestus could potentially be useful in simulating the response of these populations to vector control techniques deployed separately or in combination. The observed and simulated dynamics also suggests that An. funestus could be playing a role in year-round malaria transmission, with any apparent seasonality attributed to other vector species. [ABSTRACT FROM AUTHOR]

The contribution of interspecific competition to structuring population and community dynamics remains controversial and poorly tested. Interspecific competition has long been thought to influence the structure of migrant–resident bird communities in winter, yet experimental evidence remains elusive. The arrival of billions of songbirds into Neotropical habitats, where they co‐exist with residents, provides a unique opportunity to assess interspecific competition and its consequences. Working in 15 ha of Jamaican black mangrove forest, we used removal experiments to test whether dominant resident Yellow Warblers compete interspecifically with subordinate wintering American Redstarts; we also used observational evidence (interspecific territorial overlap) to understand whether this coexistence influences physical condition, spring departure dates or annual return rates. Consistent with interspecific competition, after experimental removal of the resident, yearling male Redstarts (but not females or adult males) immediately moved into vacated Yellow Warbler territories, increasing their overlap with the space by 7.3%. Yearling Redstarts also appeared to adjust their territorial space use by actively avoiding Yellow Warblers; for example, Redstarts departing the wintering grounds as yearlings and returning the following winter shifted such that their territories overlapped 32% less with those of Yellow Warblers. Adult Redstarts showed no such territorial flexibility. Adult male Redstarts also showed evidence supporting the consequences of coexistence: territorial overlap with Yellow Warblers was negatively correlated with body condition and annual return rates. Adult male Redstarts with <25% territorial overlap with Yellow Warblers were more than three times as likely to return between seasons than those with 100% overlap. We propose that the territorial inflexibility of adult male Redstarts produces these consequences, which may be due to their years‐long investment in that particular territory. More generally, the temporary nature of migrant–resident interspecific competition is likely what allows coexistence during winter, the most resource‐poor time of year. Interspecific competition and the consequences of coexistence are likely age‐ and sex‐specific and the product of intraspecific dominance hierarchy in Redstarts. Our observations suggest that interspecific coexistence has measurable consequences, and our experiments support the long‐held, but previously untested belief that resident birds compete interspecifically with wintering migrants. [ABSTRACT FROM AUTHOR]

The balance between economic growth and wildlife conservation is a priority for many governments. Enhancing realism in assessment of population‐level impacts of anthropogenic mortality can help achieve this balance. Population Viability Analysis (PVA) is commonly applied to investigate population vulnerability, but outcomes of PVA are sensitive to formulations of density‐dependence, environmental stochasticity and life history. Current practice in marine assessments is to use precautionary models that assume no compensation from density‐dependence or rescue‐effects via "re‐seeding" from other colonies. However, if we could empirically quantify regulatory population processes, the responses of populations to additional anthropogenic mortality may be assessed with more realism in PVA.Using Bayesian state‐space models fitted to population time series from three sympatric seabird populations, selected for varied life histories, we inferred the extent to which their dynamics are driven by environmental stochasticity and density‐dependence.Based on these inferences, we conducted an exhaustive PVA across credible parameterizations for intrinsic and extrinsic population regulation, simulated as a closed and re‐seeded system. Scenarios of anthropogenic mortality, along a sliding scale of precaution, were applied both proportionally and as a fixed quota using Potential Biological Removal (PBR).Baseline results from fitting revealed clear environmental regulation in two of our three species. Crucially, we found that for our empirically derived, realistic model parameterizations there are risks of decline to real populations even under very precautionary mortality scenarios. We find that PBR is dubious in application as a sustainable tool for population assessment when we account for regulation. Closed versus re‐seeded models showed a large divergence in outcomes, with sharper declines in closed simulations. Fixed‐quota mortality typically induced greater population declines comparative to proportional mortality, subject to regulation and re‐seeding.Synthesis and applications. Practitioners using arbitrary formulations of population regulation risk over‐precaution (economic constraint) or under‐precaution (endangering populations). The demands of increased economic development and preservation of wildlife require that methodologies apply techniques that confer reality and rigour to assessment. The current practice of employing models lacking density‐dependence and empirical environmental information imposes limitations in the efficacy of estimating impacts. Here, we provide a method to quantify the conditions that predominantly regulate a population and exacerbate the risk of decline from anthropogenic mortality. It is in the interests of both developers and conservationists to apply methods in population impact assessments that capture realism in the processes driving population dynamics. Practitioners using arbitrary formulations of population regulation risk over‐precaution (economic constraint) or under‐precaution (endangering populations). The demands of increased economic development and preservation of wildlife require that methodologies apply techniques that confer reality and rigour to assessment. The current practice of employing models lacking density‐dependence and empirical environmental information imposes limitations in the efficacy of estimating impacts. Here, we provide a method to quantify the conditions that predominantly regulate a population and exacerbate the risk of decline from anthropogenic mortality. It is in the interests of both developers and conservationists to apply methods in population impact assessments that capture realism in the processes driving population dynamics. Editor's Choice [ABSTRACT FROM AUTHOR]

The need to understand the impacts of land management for conservation, agriculture and disease prevention are driving demand for new predictive ecology approaches that can reliably forecast future changes in population size. Currently, although the link between habitat composition and animal population dynamics is undisputed, its function has not been quantified in a way that enables accurate prediction of population change in nature. Here, using 12 house sparrow colonies as a proof-of-concept, we apply recent theoretical advances to predict population growth or decline from detailed data on habitat composition and habitat selection. We show, for the first time, that statistical population models using derived covariates constructed from parametric descriptions of habitat composition and habitat selection can explain an impressive 92% of observed population variation. More importantly, they provide excellent predictive power under cross-validation, anticipating 81% of variability in population change. These models may be embedded in readily available generalized linear modelling frameworks, allowing their rapid application to field systems. Furthermore, we use optimization on our sample of sparrow colonies to demonstrate how such models, linking populations to their habitats, permit the design of practical and environmentally sound habitat manipulations for managing populations. [ABSTRACT FROM AUTHOR]

Animal aggregations occur in almost all taxa and can be strongly influential for consumer-resource dynamics and population health. Their adaptive value and underlying mechanisms are thus fundamental questions. Many animals use information about resource locations inadvertently broadcasted by other individuals through visual, acoustic, or olfactory cues. Such simple, involuntary information transfer is commonly employed in groups of social animals. However, it remains unknown whether public information use could have been the initial cause of social aggregations. Here, using agent-based modeling, in the absence of inclusive fitness benefits or direct conspecific attraction, we show that the use of ephemeral public information about resource locations can cause memory-based foragers to spontaneously and permanently aggregate into communal home ranges that take the form of movement circuits (also called traplines) along which individuals travel asynchronously. Even though experienced individuals only rely on their personal memory to inform their movement decisions, we find that the use of public information during the learning phase is very beneficial in the long term because the communal circuits are more efficient than those established by individuals that do not use public information. Our results reveal how simple, inadvertent information transfer between naïve, selfish foragers can cause the emergence of long-term aggregations, which are a prerequisite for the evolution of more complex social behaviors. They also suggest that individuals may not necessarily need to witness the entire sequences of actions performed by others to converge to the same behavioral routines. [ABSTRACT FROM AUTHOR]

Dynamic occupancy models are popular for estimating dynamic distribution rates (colonization and extinction) from repeated presence/absence surveys of unmarked animals. This approach assumes closure among repeated samples within primary periods, allowing estimation of dynamic rates between these periods. However, the impact of temporary emigration (TE; reversible changes in sampling availability) on dynamic rate estimates has not been tested., Using simulated data, we investigated the degree to which TE could mislead researchers interested in quantifying dynamics. We then compared results from three avian point count datasets to evaluate the likelihood that TE confounds estimates of dynamics for 19 species under a popular sampling protocol., Simulated experiments indicated that when secondary periods were open to TE, presence of dynamics was correctly identified ≥95.1% of the time, and dynamic rate estimates were accurate. However, dynamic rate estimates were biased when secondary periods were closed to TE. In empirical datasets, dynamic occupancy models had greater support than closed models for all species when secondary sampling periods occurred in immediate succession (i.e. 3 samples within 10 min); however, our results suggest that this is because dynamic estimates were heavily influenced by TE. When counts within a primary period were separated by 24-48 hr, we found evidence of dynamics for less than half of these species. We recommend an alternative sampling approach that allows accurate estimation of dynamic rates when TE is of no interest, and introduce a novel model for estimating both processes simultaneously in rare cases where they are both of biological interest., Concern for violating the occupancy modelling closure assumption has led to widespread recommendations that samples within primary periods be conducted extremely close in time. However, this may not be the best approach when interest is in quantifying dynamic rates. While dynamic occupancy models provide estimates of 'colonization' and 'extinction,' these values do not inherently represent dynamics unless TE has been explicitly modelled or accounted for with sampling design. Naiveté to this fact can result in incorrect conclusions about biological processes. [ABSTRACT FROM AUTHOR]

We develop a theory of generalist predation showing how alternative prey species are affected by changes in both mean abundance and variability (coefficient of variation) of their predator’s primary prey. The theory is motivated by the indirect effects of cyclic rodent populations on ground-breeding birds, and developed through progressive analytic simplifications of an empirically-based model. It applies nonetheless to many other systems where primary prey have fast life-histories and can become superabundant, thus facilitating impact on alternative prey species and generating highly asymmetric interactions. Our results suggest that predator effects on alternative prey should generally decrease with mean primary prey abundance, and increase with primary prey variability (low to high CV)—unless predators have strong aggregative responses, in which case these results can be reversed. Approximations of models including predator dynamics (general numerical response with possible delays) confirm these results but further suggest that negative temporal correlation between predator and primary prey is harmful to alternative prey. Finally, we find that measurements of predator numerical responses are crucial to predict–even qualitatively–the response of ecosystems to changes in the dynamics of outbreaking prey species. [ABSTRACT FROM AUTHOR]