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Predicting the speed of biological invasions and native species migrations requires an understanding of the ecological and evolutionary dynamics of spreading populations. Theory predicts that evolution can accelerate species' spread velocity, but how landscape patchiness—an important control over traits under selection—influences this process is unknown. We manipulated the response to selection in populations of a model plant species spreading through replicated experimental landscapes of varying patchiness. After six generations of change, evolving populations spread 11% farther than nonevolving populations in continuously favorable landscapes and 200% farther in the most fragmented landscapes. The greater effect of evolution on spread in patchier landscapes was consistent with the evolution of dispersal and competitive ability. Accounting for evolutionary change may be critical when predicting the velocity of range expansions.

Understanding the movement of species’ ranges is a classic ecological problem that takes on urgency in this era of global change. Historically treated as a purely ecological process, range expansion is now understood to involve eco-evolutionary feedbacks due to spatial genetic structure that emerges as populations spread.We synthesize empirical and theoretical work on the eco-evolutionary dynamics of range expansion, with emphasis on bridging directional, deterministic processes that favor evolved increases in dispersal and demographic traits with stochastic processes that lead to the random fixation of alleles and traits. We develop a framework for understanding the joint influence of these processes in changing the mean and variance of expansion speed and its underlying traits. Our synthesis of recent laboratory experiments supports the consistent role of evolution in accelerating expansion speed on average, and highlights unexpected diversity in how evolution can influence variability in speed: results not well predicted by current theory. We discuss and evaluate support for three classes of modifiers of eco-evolutionary range dynamics (landscape context, trait genetics, and biotic interactions), identify emerging themes, and suggest new directions for future work in a field that stands to increase in relevance as populations move in response to global change.

Background. Although vaccination with trivalent inactivated influenza vaccine (TIV) is recommended for all pregnant women, no vaccine effectiveness (VE) studies of TIV in pregnant women have assessed laboratory-confirmed influenza outcomes. Methods. We conducted a case-control study over 2 influenza seasons (2010–2011 and 2011–2012) among Kaiser Permanente health plan members in 2 metropolitan areas in California and Oregon. We compared the proportion vaccinated among 100 influenza cases (confirmed by reverse transcription polymerase chain reaction) with the proportions vaccinated among 192 controls with acute respiratory illness (ARI) who tested negative for influenza and 200 controls without ARI (matched by season, site, and trimester). Results. Among influenza cases, 42% were vaccinated during the study season compared to 58% and 63% vaccinated among influenza-negative controls and matched ARI-negative controls, respectively. The adjusted VE of the current season vaccine against influenza A and B was 44% (95% confidence interval [CI], 5%–67%) using the influenza-negative controls and 53% (95% CI, 24%–72%) using the ARI-negative controls. Receipt of the prior season's vaccine, however, had an effect similar to receipt of the current season's vaccine. As such, vaccination in either or both seasons had statistically similar adjusted VE using influenza-negative controls (VE point estimates range = 51%–76%) and ARI-negative controls (48%–76%). Conclusions. Influenza vaccination reduced the risk of ARI associated with laboratory-confirmed influenza among pregnant women by about one-half, similar to VE observed among all adults during these seasons.

ObjectivesTo examine the potential for bias in the estimate of under-5 mortality due to birth defects recently produced by the WHO and the Maternal and Child Epidemiology Estimation research group.DesignSystematic analysis.MethodsWe examined the estimated number of under-5 deaths due to birth defects, the birth defect specific under-5 mortality rate, and the per cent of under-5 mortality due to birth defects, by geographic region, national income and under-5 mortality rate for three age groups from 2000 to 2019.ResultsThe under-5 deaths per 1000 live births from birth defects fell from 3.4 (95% uncertainty interval (UI) 3.1–3.8) in 2000 to 2.9 (UI 2.6–3.3) in 2019. The per cent of all under-5 mortality attributable to birth defects increased from 4.6% (UI 4.1%–5.1%) in 2000 to 7.6% (UI 6.9%–8.6%) in 2019. There is significant variability in mortality due to birth defects by national income level. In 2019, the under-5 mortality rate due to birth defects was less in high-income countries than in low-income and middle-income countries, 1.3 (UI 1.2–1.3) and 3.0 (UI 2.8–3.4) per 1000 live births, respectively. These mortality rates correspond to 27.7% (UI 26.6%–28.8%) of all under-5 mortality in high-income countries being due to birth defects, and 7.4% (UI 6.7%–8.2%) in low-income and middle-income countries.ConclusionsWhile the under-5 mortality due to birth defects is declining, the per cent of under-5 mortality attributable to birth defects has increased, with significant variability across regions globally. The estimates in low-income and middle-income countries are likely underestimated due to the nature of the WHO estimates, which are based in part on verbal autopsy studies and should be taken as a minimum estimate. Given these limitations, comprehensive and systematic estimates of the mortality burden due to birth defects are needed to estimate the actual burden.

Background Adverse birth outcomes (ABOs) cause significant infant morbidity and mortality in resource-limited settings. Many of the maternal risk factors associated with ABOs can be prevented. We present the prevalence, trends, and risk factors of selected ABOs from a hospital-based birth defects surveillance program in Kampala, Uganda. Methods We analyzed data for all mothers with singleton deliveries collected from four urban hospitals between 2015 and 2022. Prevalence of preterm birth [PTB], low birth weight [LBW], small for gestational age [SGA], and stillbirth [SB] and maternal HIV seroprevalence were calculated among 222,427 births. SB was defined as infant born without life ≥ 28 weeks of gestation, LBW as term live birth weighing < 2500 g and PTB as live birth born < 37 weeks of gestation. Time trends of ABOs by maternal HIV status and age were computed using quasi-Poisson regression model and presented graphically. Risk factor associations were estimated using robust Poisson models adjusting for infant sex, hospital of delivery, and birth year. Results Prevalence of PTB, LBW, SGA, and SB were 14.8%, 4.3%, 17.8%, and 3.1%, respectively. Maternal HIV seroprevalence was 7.7%. Compared to mothers aged 25–34 years, young adolescents 10–18 years was associated with PTB (adjusted risk ratio [aRR]: 1.44, 95% confidence interval (CI): 1.38–1.50); LBW (1.65,1.51–1.81); and SGA (1.18; 1.12–1.24). HIV seropositivity was associated with PTB (1.18; 1.14–1.22), LBW (1.54; 1.43–1.65), and SGA (1.28; 1.23–1.33). Compared to starting ANC in the first trimester, no antenatal care (ANC) was associated with PTB (2.44; 2.33–2.56), LBW (1.80; 1.55–2.09), SGA (1.37; 1.27–1.49), and SB (3.73; 3.32–4.15) and late attendance with LBW (1.09; 1.02–1.16), SGA (1.26; 1.22–1.30), and SB (1.09; 1.02–1.17). Our findings also indicate a rising trend in PTB among adolescent and young women aged 10–24 years, and a declining trend in LBW and SGA over time (ptrend < 0.05 for all). Conclusions Young maternal age, maternal HIV, and late or no ANC attendance were associated with ABO. Childbearing in the ages 25–34, preventing HIV in women, and supporting early and frequent ANC attendance are important in improving birth outcomes.

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas

Integral projection models (IPMs) are increasingly being applied to study size-structured populations. Here we call attention to a potential problem in their construction that can have important consequences for model results. IPMs are implemented using an approximating matrix and bounded size range. Individuals near the size limits can be unknowingly \"evicted\" from the model because their predicted future size is outside the range. We provide simple measures for the magnitude of eviction and the sensitivity of the population growth rate (λ) to eviction, allowing modelers to assess the severity of the problem in their IPM. For IPMs of three plant species, we found that eviction occurred in all cases and caused underestimation of the population growth rate (λ) relative to eviction-free models; it is likely that other models are similarly affected. Models with frequent eviction should be modified because eviction is only possible when size transitions are badly mis-specified. We offer several solutions to eviction problems, but we emphasize that the modeler must choose the most appropriate solution based on an understanding of why eviction occurs in the first place. We recommend testing IPMs for eviction problems and resolving them, so that population dynamics are modeled more accurately.

1. One of the key components of an organism's life history is the delay of reproduction until it reaches or returns to an optimal size. While we know climate can influence vital rates that shape life-history strategies, it is also critical to understand the effects of climate change on rapid life history evolution, which might modify the influence of climate change on population dynamics. 2. We asked how realistic changes in temperature and precipitation influence vital rates, costs of reproduction, and ultimately, evolutionarily stable (ES) flowering size in a long-lived perennial plant, Orchis purpurea. We also explored how evolution of flowering size could influence population persistence under changing climate. 3. Our approach combined model selection methods to characterize climate dependence in vital rates, stochastic integral projection models to integrate vital rates into an estimate of fitness, and adaptive dynamics to identify ES flowering sizes. 4. Vital rates responded uniquely to seasonal temperature and precipitation, with the largest response in the size-dependent probability of flowering. The predicted ES flowering size closely matched that observed, and responded strongly to adjusting the frequencies of extreme climate years. For example, increasing the frequency of extreme drought conditions was predicted to favour smaller reproductive sizes (and hence a shorter reproductive delay), despite observation that smaller plants were less likely to flower in dry years. This apparent discrepancy stems from a smaller payoff to delaying reproduction due to lower costs of reproduction in dry years. 5. The model of stochastic population dynamics predicted long-term persistence of the focal populations, even under the most extreme climate scenarios, while incorporating rapid life history evolution into predictions reduced the sensitivity of population growth to changing climate. 6. Synthesis. Our results illustrate that long-lived organisms can exhibit complex demographic responses to changing climate regimes. Additionally, they highlight that long-term evolutionary responses may be in opposing directions from short-term plastic responses to climate and emphasize the need for demographic models to integrate ecological and evolutionary influences of climate across the life cycle.

Machupo virus (MACV), a member of the Arenaviridae family and causative agent of Bolivian hemorrhagic fever, results in lethality rates of 25–35% in humans. Mice lacking the signal transducer and activator of transcription 1 (STAT-1−/−) have previously been shown to succumb to MACV infection within 7–8 days via the intraperitoneal route. Despite these reports, we observed partial lethality in STAT-1−/− mice following challenge with wild-type MACV. Serial sampling studies to evaluate the temporal progression of infection and pathologic changes after challenge revealed a two-phase disease course. The first phase was characterized by viral load and pathological lesions in the spleen, liver, and kidney followed by a second, lethal phase, defined by high viral titers and inflammation in the brain and spinal cord resulting in neurological manifestations and subsequent mortality. Tissue adaptation in the brains of challenged STAT-1−/− mice resulted in a fully lethal model in STAT-1−/− mice (mouse-adapted; maMACV). A similar two-phase disease course was observed following maMACV challenge, but more rapid dissemination of the virus to the brain and overall pathology in this region was observed. The outcome of these studies is a lethal small rodent model of MACV that recapitulates many aspects of human disease.

Life‐history theory makes several key predictions about reproductive strategies on the basis of demographic vital rates, particularly the relationship between juvenile and adult survival. Two such predictions concern the optimal time to begin reproducing and whether semelparity or iteroparity is favored. I tested these life‐history predictions and explored how they might differ between the native and introduced ranges of the monocarpic perennialCyno glossum officinale. I first compared vital rates between ranges. I then used these vital rates to parameterize integral projection models to calculate the population growth rate (λ) and net reproductive rate ( \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $R_{0}$ \\end{document} ) as surrogates for fitness to compare strategies within and between ranges. I found that both survival and growth were higher in the introduced range, where size at flowering was larger and iteroparity was much more common than in the native range. The observed and predicted strategies for size at flowering were similar in the native range. In the introduced range, however, even though plants flowered at a larger size, the observed size was not as large as the optimum predicted by λ or the higher optimum predicted by \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $R_{0}$ \\end{document} . Iteroparity conferred higher fitness in both ranges, as measured by both fitness metrics, suggesting that severe constraints, potentially specialist herbivores, prevent this strategy from becoming more common in the native range.