Christopher M. Baker

The lexicon of 6-month-olds is comprised of names and body part words. Unlike names, body part words do not often occur in isolation in the input. This presents a puzzle: How have infants been able to pull out these words from the continuous stream of speech at such a young age? We hypothesize that caregivers’ interactions directed at and on the infant’s body may be at the root of their early acquisition of body part words. Anartificial language segmentation study shows that experimenter-provided synchronous tactile cues help 4-month-olds to find words in continuous speech. A follow-up study suggests that this facilitation cannot be reduced to the highly social situation in which the directed interaction occurs. Taken together, these studies suggests that direct caregiver-infant interaction, exemplified in this study by touch cues, may play a key rolein infants’ ability to find word boundaries and suggests that words linked with caregiver touches may comprise early vocabulary items.

The detection and surveillance of emergency animal disease outbreaks play a crucial role in their management. However, monitoring such diseases can often rely on farmers self‐reporting animal infection. If there are disincentives for farmers to report disease, this can lead to delayed reporting, which could negatively impact outbreak management outcomes. To understand the range of impacts farmer reporting rates could have on the spread and management of outbreaks, we model the spread of animal disease using an agent‐based model. We investigate how varying the reporting rate for infected properties can impact firstly the total number of properties depopulated for various management strategies and secondly which strategy is optimal. Our model considers disease transmission occurring both within a property, through animal‐to‐animal transmission and between properties, through fomite dispersal and random movement of animals. Using this model, we compare the number of properties depopulated under four strategies: depopulating infected properties and animal movement restrictions combined with (1) ring culling, (2) ring testing, (3) ring vaccination (with a perfect vaccine) and (4) ring vaccination (with an imperfect vaccine). Given our assumptions and model structure, we find that outbreaks spread in clusters around an initially infected property, with additional clusters being seeded early by the random movement of animals between properties. We simulate the impact of reporting rates on a range of outbreak indicators, and we find it has the biggest impact on the time to detection. This time decreases as we increase the reporting rate, but with diminishing returns. We find the timing of outbreak detection impacts the total properties depopulated under all management strategies similarly, as outbreaks detected earlier ultimately lead to smaller outbreaks. As such, we find that varying the reporting rate had minimal impact on which strategy was optimal for a given simulation. Our modelling demonstrates how human behaviour, such as reporting rates, can impact the outcomes from managing emergency animal disease outbreaks. While exact behaviour cannot be predicted for future outbreaks, we can prepare for the next outbreak of emergency animal disease by investigating which management strategies can be robust to a variety of human behaviours.

Monitoring is essential for nature conservation, but many programmes are criticized for lacking purpose. We argue that monitoring delivers impact only when grounded in a clear theory of how activities lead to change. We clarify and categorize 15 distinct reasons to monitor within a theory-of-change framework, outlining how these can guide decisions about where to invest effort. These reasons fall into five groups: basic and applied research aimed at causal evaluation; monitoring integrated with on-ground actions; monitoring to inform policy; monitoring that strengthens enabling conditions for conservation; and curiosity-driven monitoring. Efforts to quantify the benefits of monitoring often focus on narrow, intervention-specific purposes, typically within adaptive management or evidence-based conservation approaches. However, much ecological monitoring serves functions beyond these frameworks. A broader perspective reveals additional, often overlooked, reasons to monitor, especially those that build the enabling conditions required for effective policy and practice. The benefits of these reasons for monitoring have rarely been articulated or quantified. Before designing a monitoring programme, conservation organizations should articulate a theory of change that makes their reasons for monitoring explicit. We provide a checklist of 15 reasons to support transparent logic, intentional design and clear links between monitoring information and improved policy or management outcomes.

Introduction: Following widespread exposure to Omicron variants, SARS-CoV-2 has transitioned to endemic circulation. Populations now have diverse infection and vaccination histories, resulting in heterogeneous immune landscapes. Careful consideration of the value of ongoing vaccination is required through the post-Omicron phase of COVID-19 management to minimise disease burden. We demonstrate the utility of a modelling approach to address this question, supporting recommendations for targeted vaccine use across different country settings. Methods: We integrated immunological, transmission, clinical and cost-effectiveness models and simulated populations with different characteristics and immune landscapes over the early post-Omicron period. We calculated the expected number of infections, hospitalisations and deaths for different vaccine scenarios. Costs (from a healthcare perspective) were estimated for exemplar country income-level groupings in the Western Pacific Region using pandemic-era vaccine prices and healthcare-seeking behaviour assumptions. We assessed the impact and cost-effectiveness of targeted vaccination strategies. Results are reported as incremental costs and disability-adjusted life years averted compared with no additional vaccination. Parameter and stochastic uncertainty were captured through scenario and sensitivity analysis. Results: Across different population demographics and income levels, we consistently found that annual elder-targeted boosting strategies are most likely to be cost-effective or cost-saving (>75% probability of being cost-effective among older, high-income settings; >50% probability of being cost-effective in younger, middle-income settings), while paediatric programmes are unlikely to be cost-effective. Results remained broadly consistent while accounting for uncertainties in the epidemiological and economic models, although they were sensitive to the cost of home-based care and vaccination. Use of pandemic-era vaccine prices may underestimate current vaccine prices available in upper-middle-income and high-income settings, potentially overestimating the cost-effectiveness of boosting in these settings. Half-yearly boosting may only be cost-effective in higher income settings with older population demographics and higher cost-effectiveness thresholds. Conclusion: Competing health priorities and resource constraints mean COVID-19 vaccine allocation needs to be carefully considered in context. These results, reflecting modelling conducted on the early post-Omicron period, demonstrate the value of continued booster vaccinations to protect against severe COVID-19 disease outcomes across high-income and middle-income settings and show that the biggest health gains relative to vaccine costs are achieved by targeting older age groups.

Marine invasive species can cause irreparable change in new environments, though not all non‐native species inevitably cause negative impacts to recipient ecosystems. Knowing which non‐native species could establish and have harmful impacts is vital to ensure the efficient use of limited resources for monitoring and surveillance, especially in less accessible regions such as the Southern Ocean. We used ensemble ecosystem modelling to predict an ensemble of plausible future scenarios of introduction and potential establishment of marine non‐native species to a known food web near Casey Station, East Antarctica. These scenarios explore potential impacts of successful invasions by five non‐native species. Non‐native species varied in their capacity to establish in the current food web following a single introduction event, though all could establish in at least some scenarios. Where the non‐native species did establish, their abundances mostly increased by between 10 and 1000 times, though some scenarios resulted in a million‐fold increase. Although most scenarios showed native species abundances only changed within 10% of the initial abundance, the establishment of an invasive species could plausibly cause substantial abundance declines to all native species. Synthesis and applications. This analysis helps us to better understand the potential range of impacts on native species and aids in developing strategies to help prevent or manage their introduction. We highlight the need for rapid detection methods, such as eDNA, to ensure any non‐native species are identified quickly in this ecosystem, particularly for those species we identified as having a high potential for negative impacts and fast population growth.

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

The rise of globalization has led to a sharp increase in international trade with high volumes of containers, goods, and items moving across the world. Unfortunately, these trade pathways also facilitate the movement of unwanted pests, weeds, diseases, and pathogens. Each item could contain biosecurity risk material, but it is impractical to inspect every item. Instead, inspection efforts typically focus on high‐risk items. However, low risk does not imply no risk. It is crucial to monitor the low‐risk pathways to ensure that they are and remain low risk. To do so, many approaches would seek to estimate the risk to some precision, but increasingly lower risks require more samples. On a low‐risk pathway that can be afforded only limited inspection resources, it makes more sense to assign fewer samples to the lower risk activities. We approach the problem by introducing two thresholds. Our method focuses on letting us know whether the risk is below certain thresholds, rather than estimating the risk precisely. This method also allows us to detect a significant change in risk. Our approach typically requires less sampling than previous methods, while still providing evidence to regulators to help them efficiently and effectively allocate inspection effort.

Background: Since the emergence of SARS-CoV-2 (COVID-19), there have been multiple waves of infection and multiple rounds of vaccination rollouts. Both prior infection and vaccination can prevent future infection and reduce severity of outcomes, combining to form hybrid immunity against COVID-19 at the individual and population level. Here, we explore how different combinations of hybrid immunity affect the size and severity of near-future Omicron waves. Methods: To investigate the role of hybrid immunity, we use an agent-based model of COVID-19 transmission with waning immunity to simulate outbreaks in populations with varied past attack rates and past vaccine coverages, basing the demographics and past histories on the World Health Organization Western Pacific Region. Results: We find that if the past infection immunity is high but vaccination levels are low, then the secondary outbreak with the same variant can occur within a few months after the first outbreak; meanwhile, high vaccination levels can suppress near-term outbreaks and delay the second wave. Additionally, hybrid immunity has limited impact on future COVID-19 waves with immune-escape variants. Conclusions: Enhanced understanding of the interplay between infection and vaccine exposure can aid anticipation of future epidemic activity due to current and emergent variants, including the likely impact of responsive vaccine interventions.

The invasive emerald ash borer ( Agrilus planipennis ) causes damage to street trees which is estimated to reach US$ 900 million over the next 30 years. Although millions of dollars are spent annually to control this species, spatiotemporal management plans are often based on rules of thumb that ignore future pest dispersal. Here, we reveal an optimal management strategy to protect urban trees in North America from A. planipennis . To achieve this, we embedded a pest dispersal model within a mixed integer programming framework. We discovered that optimized strategies consistently outperformed those based on rules of thumb, potentially resulting in the protection of an additional nearly 1 million street trees and savings of $ 629 million. Critically, the best management strategies always relied on quarantines and biological control (constituting 98–99% and 1–2% of the project budget, respectively), in contrast with current practices, where federal spending has been diverted to biological control. Our findings serve to inform future pest control efforts and can help protect many more trees from this invasive species.