Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Demographic signals of population decline and time to extinction in a seasonal, density-dependent model

Nearly all wild populations live in seasonal environments in which they experience regular fluctuations in environmental conditions that drive population dynamics. Recent empirical evidence from experimental populations of Drosophila suggests that demographic signals inherent in the counts of seasonal populations, including reproduction and survival, can indicate when in the annual cycle habitat loss occurred. However, it remains unclear whether these signatures of season-specific decline are detectable under a wider range of demographic conditions and rates of habitat loss. Here, we use a bi-seasonal Ricker model to examine season-specific signals of population decline induced by different rates of habitat loss in the breeding or non-breeding season and different strengths of density dependence. Consistent with the findings in Drosophila, breeding habitat loss was accompanied by reduced reproductive output and a density-dependent increase in survival during the subsequent non-breeding period. Non-breeding habitat loss resulted in reduced non-breeding survival and a density-dependent increase in reproduction in the following breeding season. These season-specific demographic signals of decline were present under a wide range of habitat loss rates (2–25% per generation) and different density-dependent regimes (weak, moderate, and strong). We show that stronger density dependence can negatively influence time to extinction when non-breeding habitat is lost, whereas the strength of density dependence does not influence time to extinction with breeding habitat loss (although, in all cases, density dependence itself was an important modulator of population dynamics). Our results illustrate the need to incorporate seasonality in theoretical models to better understand when populations are being driven to decline

An experimental test of the ecological mechanisms driving density-mediated carry-over effects in a seasonal population

Carry-over effects occur when past experience influences current individual performance. Although variation in conspecific density in one season has been shown to carry over to influence dynamics in the following season, the proximate ecological mechanisms driving these effects are unknown. One hypothesis is that high density decreases food availability, resulting in poor physiological condition, which in turn compromises performance the next season. Alternatively, high conspecific density could also lead to a high degree of antagonistic interactions, decreasing the amount of time individuals spend foraging. To investigate these hypotheses, we applied a factorial design where both conspecific density and per capita food availability during the non-breeding period were independently manipulated in seasonal populations of common fruit flies (Drosophila melanogaster Meigen, 1830). Individual condition at the beginning of the breeding period was influenced by per capita food availability but not density during the previous non-breeding period. In contrast, reproductive output was most strongly influenced by the interaction between per capita food availability and density in the previous non-breeding period, such that populations that experienced high non-breeding densities and low food availability had the lowest reproductive output. However, the strength of this effect was relatively weak. Our results demonstrate how environmental and social conditions in one part of the annual cycle can carry over to influence individual performance in subsequent periods.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Data from: Short distance migrants travel as far as long distance migrants in lesser black-backed gulls Larus fuscus

Migration strategies differ greatly among and within avian populations. The associated trade-offs and fitness consequences of diverse strategies and how they persist are pertinent questions in migration research. Migration is a costly endeavour, presumably compensated for by better survival conditions in the non-breeding area. One way to assess the cost of alternative strategies is to investigate the investment in movement across the entire annual cycle, an assessment made increasingly feasible with improvements in tracking technology. Our study focuses on lesser black-backed gulls, generalist seabirds that exploit a broad range of resources, exhibit diverse migration strategies and have potentially altered migration strategies in response to human activities and climate change. We used GPS tracking to quantify lesser black-backed gulls’ movement throughout their annual cycle and compare trade-offs among four migration strategies. The annual cumulative distance travelled by long distance migrants wintering in west Africa, over 4000 km from their breeding colony, did not differ significantly from individuals of the same breeding colony wintering only a few hundred kilometres away in Great Britain. Short distance migrants returned to the colony first, and long distance migrants returned last. Sex and wing length were not correlated with maximum range, cumulative distance travelled or timing. Individuals spent only a small proportion of their time in flight and spent on average 17% of their time at sea throughout an annual cycle, suggesting a reliance on inland resources for many individuals. Analysing movement throughout the annual cycle can change our perspective and understanding of consequences of different migration strategies. Our study shows that a range of migration strategies coexists and we propose that the long term costs and benefits of these strategies balance out. Diversity in migration strategies may contribute to the resilience of this species in the face of ongoing anthropogenic impact on the environment

Shamoun-Baranes et al. (2016)

This file includes the longitude and latitude data for each of the gulls included in our analyses, re-sampled at a 20 minute interval. Individuals are identified using a unique three digit code (BirdID) and bird-year subsets are each assigned a separate identifier (Subset). In addition to the coordinate data, cumulative distance travelled (CumulativeDistance) and distance from the colony (ColonyDistance) are also provided for each subset

Data from: Within-individual canalization contributes to age-related increases in trait repeatability: a longitudinal experiment in red knots

Abstract: Age-related increases in the repeatable expression of labile phenotypic traits are often assumed to arise from an increase in among-individual variance due to differences in developmental plasticity or by means of state-behaviour feedbacks. However, age-related increases in repeatability could also arise from a decrease in within-individual variance as a result of stabilizing trait expression, i.e. canalization. Here we describe age-related changes in within- and among-individual variance components in two correlated traits, gizzard mass and exploration behavior, in a medium-sized shorebird, the red knot (Calidris canutus). Increased repeatability of gizzard mass came about due to an increase in among-individual variance, unrelated to differences in developmental plasticity, together with decreases in within-individual variance, consistent with canalization. We also found canalization of exploration, but no age-related increase in overall repeatability, which suggests that showing predictable expression of exploration behaviour may be advantageous from a very young age onward. Contrasts between juveniles and adults in the first year after their capture provide support for the idea that environmental conditions play a key role in generating among-individual variation in both gizzard mass and exploration behavior. Our study shows that stabilization of traits occurs under constant conditions: with increased exposure to predictable cues, individuals may become more certain in their assessment of the environment allowing traits to become canalized

Data from: Ionome and elemental transport kinetics shaped by parallel evolution in threespine stickleback

Evidence that organisms evolve rapidly enough to alter ecological dynamics necessitates investigation of the reciprocal links between ecology and evolution. Data that link genotype to phenotype to ecology are needed to understand both the process and ecological consequences of rapid evolution. Here we quantified the suite of elements in individuals (i.e., ionome) and the fluxes of key nutrients across populations of threespine stickleback. We find that allelic variation associated with freshwater adaptation that controls bony plating is associated with changes in the ionome and nutrient recycling. More broadly, we find that adaptation of marine fish to freshwater conditions shifts the ionomes of natural populations and populations raised in common gardens. In both cases ionomic divergence between populations was primarily driven by differences in trace elements rather than elements typically associated with bone. These findings demonstrate the utility of ecological stoichiometry and the importance of ionome-wide data in understanding eco-evolutionary dynamics

Data from: Evolutionary design of a flexible, seasonally migratory, avian phenotype: why trade gizzard mass against pectoral muscle mass?

Migratory birds undergo impressive body remodelling over the course of an annual cycle. Prior to long-distance flights, red knots (Calidris canutus islandica) reduce gizzard mass while increasing body mass and pectoral muscle mass. Although body mass and pectoral muscle mass are functionally linked via their joint effects on flight performance, gizzard and pectoral muscle mass are thought to be independently regulated. Current hypotheses for observed negative within-individual covariation between gizzard and pectoral muscle mass in free-living knots are based on a common factor (e.g., migration) simultaneously affecting both traits, and/or protein limitation forcing allocation decisions. We used diet manipulations to generate within-individual variation in gizzard mass and test for independence between gizzard and pectoral muscle mass within-individuals outside the period of migration and under conditions of high protein availability. Contrary to our prediction, we observed a negative within-individual covariation between gizzard and pectoral muscle mass. We discuss this result as a potential outcome of an evolved mechanism underlying body remodelling associated with migration. Although our proposed mechanism requires empirical testing, this study echoes earlier calls for greater integration of studies of function and mechanism, and in particular, the need for more explicit consideration of the evolution of mechanisms underlying phenotypic design