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Abstract Modelling spatial and temporal patterns in ecology is imperative to understand the complex processes inherent in ecological phenomena. Log‐Gaussian Cox processes are a popular choice among ecologists to describe the spatiotemporal distribution of point‐referenced data. In addition, point pattern models where events instigate others nearby (i.e., self‐exciting behaviour) are becoming increasingly popular to infer the contagious nature of events (e.g., animal sightings). While there are existing R packages that facilitate fitting spatiotemporal point processes and, separately, self‐exciting models, none incorporate both. We present an R package, stelfi, that fits spatiotemporal self‐exciting and log‐Gaussian Cox process models using Template Model Builder through a range of custom‐written C++ templates. We illustrate the use of stelfi's functions fitting models to Sasquatch (bigfoot) sightings data within the USA. The structure of these data is typical of many seen in ecology studies. We show, from a temporal Hawkes process to a spatiotemporal self‐exciting model, how the models offered by the package enable additional insights into the temporal and spatial progression of point pattern data. We present extensions to these well‐known models that include spatiotemporal self‐excitation and joint likelihood models, which are better suited to capture the complex mechanisms inherent in many ecological data. The package stelfi offers user‐friendly functionality, is open source, and is available from CRAN. It offers the implementation of complex spatiotemporal point process models in R for applications even beyond the field of ecology.

For years Georgia's HOPE Scholarship program provided full tuition scholarships to high-achieving students. State budgetary shortfalls reduced its generosity in 2011. Under the new rules, only students meeting more rigorous merit-based criteria would retain the original scholarship covering full tuition, now called the Zell Miller Scholarship, with other students seeing aid reductions of approximately 15 percent. We exploit the fact that two of the criteria were high school grade point average and SAT/ACT score, which students could not manipulate when the change took place. We compare already-enrolled students just above and below these cutoffs, making use of advances in multi-dimensional regression discontinuity, to estimate effects of partial aid loss. We show that, after the changes, aid flowed disproportionately to wealthier students and find no evidence that the financial aid reduction affected persistence or graduation for these students. The results suggest that high-achieving students, particularly those already in college, may be less price-sensitive than their peers.

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

The establishment of marine non-indigenous species (NIS) in new locations can degrade environmental, socio-cultural, and economic values. Vessels arriving from international waters are the main pathway for the entry of marine NIS, via exposure due to ballast water discharge (hereafter, ballast discharge) and biofouling. We developed a systematic statistical likelihood-based methodology to investigate port-level marine NIS propagule pressure from ballast discharge and biofouling exposure using a combination of techniques, namely k-Nearest-Neighbour and random forest algorithms. Vessel characteristics and travel patterns were assessed as candidate predictors. For the ballast discharge analysis, the predictors used for model building were vessel type, dead weight tonnage, and the port of first arrival; the predictors used for the biofouling analysis were days since last antifouling paint, mean vessel speed, dead weight tonnage, and hull niche area. Propagule pressure for both pathways was calculated at a voyage, port and annual level, which were used to establish the relative entry score for each port. The model was applied to a case study for New Zealand. Biosecurity New Zealand has commissioned targeted marine surveillance at selected ports since 2002 to enable early detection of newly arrived marine NIS (Marine High-Risk Site Surveillance, MHRSS). The reported methodology was used to compare contemporary entry likelihoods between New Zealand ports. The results suggested that Tauranga now receives the highest volume of discharged ballast water and has the second most biofouling exposure compared to all other New Zealand ports. Auckland was predicted to receive the highest biofouling mass and was ranked tenth for ballast discharge exposure. Lyttelton, Napier, and New Plymouth also had a high relative ranking for these two pathways. The outputs from this study will inform the refinement of the MHRSS programme, facilitating continued early detection and cost-effective management to support New Zealand’s wider marine biosecurity system. More generally, this paper develops an approach for using statistical models to estimate relative likelihoods of entry of marine NIS.

In this article, the authors document the educational pedigrees of faculty at the top 96 economics programs in the United States. They use roster data of 96 top U.S. economics departments to provide a comprehensive update and expansion on data regarding the academic origins—both undergraduate and doctoral—of tenure-track faculty. Nearly 60 percent of their sample attended a top-15 university for their PhD; over a third attended a top-6 university for their PhD; the mean (median) ranking of faculty doctoral alma maters is 15 (10). The authors also find that over a third of faculty with U.S. undergraduate degrees received them at a top-15 university. [ABSTRACT FROM AUTHOR]

Incubation of an empty nest is a rarely detected phenomenon in birds but has been documented in a diversity of species. The causes of this breeding anomaly are unclear, but previous accounts have occurred in regions with elevated air pollution. We provide a detailed account of a female Black-throated Blue Warbler (Setophaga caerulescens) incubating an empty nest for 8 d at the Hubbard Brook Experimental Forest, New Hampshire, USA, May–June 2023, and explore possible explanations based on a literature review of this breeding anomaly. Our observation coincided with the presence of smoke from widespread wildfires in Quebec, Canada. The fires were caused by record temperatures and dry conditions. Wildfire smoke increased air particle pollution. We found 231 published accounts of 11 species incubating empty nests. Cavity-nesters in Europe comprised 45% of species (5 of 11) and 96% of accounts (225 of 231). Although many accounts lacked a clear explanation, the most common factors hypothesized to explain incubating empty nests were exposure to environmental pollution (81% of accounts, 167 of 206), calcium deficiency from environmental acidification (19% of accounts, 40 of 206), and disease and/or infertility (4% of accounts, 8 of 206). Our synthesis of published observations highlights the need for more data on individuals expressing this unusual behavior. Such data would improve our understanding of how egg laying and reproductive success respond to intrinsic and environmental factors, including wildfire emissions, which are forecasted to increase with climate change. [ABSTRACT FROM AUTHOR]

Anthropogenic activities can lead to changes in animal behavior. Predicting population consequences of these behavioral changes requires integrating short-term individual responses into models that forecast population dynamics across multiple generations. This is especially challenging for long-lived animals, because of the different time scales involved. Beaked whales are a group of deep-diving odontocete whales that respond behaviorally when exposed to military mid-frequency active sonar (MFAS), but the effect of these nonlethal responses on beaked whale populations is unknown. Population consequences of aggregate exposure to MFAS was assessed for two beaked whale populations that are regularly present on U.S. Navy training ranges where MFAS is frequently used. Our approach integrates a wide range of data sources, including telemetry data, information on spatial variation in habitat quality, passive acoustic data on the temporal pattern of sonar use and its relationship to beaked whale foraging activity, into an individual-based model with a dynamic bioenergetic module that governs individual life history. The predicted effect of disturbance from MFAS on population abundance ranged between population extinction to a slight increase in population abundance. These effects were driven by the interaction between the temporal pattern of MFAS use, baseline movement patterns, the spatial distribution of prey, the nature of beaked whale behavioral response to MFAS and the top-down impact of whale foraging on prey abundance. Based on these findings, we provide recommendations for monitoring of marine mammal populations and highlight key uncertainties to help guide future directions for assessing population impacts of nonlethal disturbance for these and other long-lived animals.

Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree, a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.

Teachers of literature often have students read works of fiction to learn important truths about the world. But, it is not clear how looking at a work of fiction can tell us about the actual world. This article examines whether and how this can be done.

Using restricted-access "Survey of Earned Doctorates" data, we investigate which attributes of a doctoral institution predict the share of its undergraduate BAs that will earn a PhD. We use truncation-correction to account for PhD receipt post-sample. Across the fields of humanities, physical, natural, and social sciences, PhD production is positively related to the number of an institution's highly-ranked PhD programs, suggesting such departments may play a role in both producing PhDs and encouraging undergraduates to earn PhDs themselves. It is negatively related to total students and the share of BAs received in the field, and positively related to test scores.

Avian eggs develop outside of the female body, and therefore embryonic development is subject to multiple internal (physiological) and external (ecological) factors. Embryonic developmental rate has important consequences for survival. Within species, embryos that develop too quickly often experience deformities, disorders, or mortality, while embryos that develop slowly risk inviability and increase the time they are exposed to various sources of mortality in the nest. These contrasting forces may lead to interspecific variation in developmental rates. We investigated potential factors affecting embryonic heart rate (EHR), a proxy of development, across 14 passerine species in the field. More specifically, we investigated if nest predation risk, clutch size, seasonality, and egg volume influenced EHR. From previous research, we expected, and found, that EHR was positively associated with embryonic age and egg temperature. Species with greater nest predation risk had higher EHR, shorter incubation periods, and lower nest temperature variance. EHR increased as the season progressed and with egg volume, while EHR declined with clutch size. Bird species exhibit varying strategies to increase nestling and fledgling survival in response to predation risk, and these results suggest that variation in embryonic development may be related to species‐specific differences in nest predation risk. [ABSTRACT FROM AUTHOR]