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Abstract In 1974, Sue Herring described the relationship between two important performance variables in the feeding system, bite force and gape. These variables are inversely related, such that, without specific muscular adaptations, most animals cannot produce high bite forces at large gapes for a given sized muscle. Despite the importance of these variables for feeding biomechanics and functional ecology, the paucity of in vivo bite force data in primates has led to bite forces largely being estimated through ex vivo methods. Here, we quantify and compare in vivo bite forces and gapes with output from simulated musculoskeletal models in two craniofacially distinct strepsirrhines:Eulemur, which has a shorter jaw and slower chewing cycle durations relative to jaw length and body mass compared toVarecia. Bite forces were collected across a range of linear gapes from 16 adult lemurs (suborder Strepsirrhini) at the Duke Lemur Center in Durham, North Carolina representing three species:Eulemur flavifrons(n = 6; 3F, 3M),Varecia variegata(n = 5; 3F, 2M), andVarecia rubra(n = 5; 5F). Maximum linear and angular gapes were significantly higher forVareciacompared toEulemur(p = .01) but there were no significant differences in recorded maximum in vivo bite forces (p = .88). Simulated muscle models using architectural data for these taxa suggest this approach is an accurate method of estimating bite force‐gape tradeoffs in addition to variables such as fiber length, fiber operating range, and gapes associated with maximum force. Our in vivo and modeling data suggestVareciahas reduced bite force capacities in favor of absolutely wider gapes compared toEulemurin relation to their longer jaws. Importantly, our comparisons validate the simulated muscle approach for estimating bite force as a function of gape in extant and fossil primates. 

Abstract Sleep spindles are a physiological marker of off-line memory consolidation. In young adults, sleep spindles are preferentially responsive to encoded information that is tagged as having future relevance. Older adults, on the other hand, show reduced capacity for future simulation and alterations in sleep physiology. Healthy young adults (n = 38) and older adults (n = 28) completed an adaptation night, followed by two in-laboratory polysomnography nights, in which they mentally simulated future events or remembered past events, recorded via written descriptions. We quantified the degree of future/past thinking using linguistic analysis of time orientation. In young adults, greater future thinking was linked to greater spindle density, even when controlling for gender, age, and word count (rp = .370, p = .028). The opposite was true for older adults, such that greater future thinking was associated with reduced spindle density (rp = −.431, p = .031). These patterns were selective to future thinking (not observed for past thinking). The collective findings implicate an impaired interaction between future relevance tagging and sleep physiology as a mechanism by which aging compromises sleep-dependent cognitive processing. 

Cool- and warm-season precipitation totals have been reconstructed on a gridded basis for North America using 439 tree-ring chronologies correlated with December–April totals and 547 different chronologies correlated with May–July totals. These discrete seasonal chronologies are not significantly correlated with the alternate season; the December–April reconstructions are skillful over most of the southern and western United States and north-central Mexico, and the May–July estimates have skill over most of the United States, southwestern Canada, and northeastern Mexico. Both the strong continent-wide El Niño–Southern Oscillation (ENSO) signal embedded in the cool-season reconstructions and the Arctic Oscillation signal registered by the warm-season estimates faithfully reproduce the sign, intensity, and spatial patterns of these ocean–atmospheric influences on North American precipitation as recorded with instrumental data. The reconstructions are included in the North American Seasonal Precipitation Atlas (NASPA) and provide insight into decadal droughts and pluvials. They indicate that the sixteenth-century megadrought, the most severe and sustained North American drought of the past 500 years, was the combined result of three distinct seasonal droughts, each bearing unique spatial patterns potentially associated with seasonal forcing from ENSO, the Arctic Oscillation, and the Atlantic multidecadal oscillation. Significant 200–500-yr-long trends toward increased precipitation have been detected in the cool- and warm-season reconstructions for eastern North America. These seasonal precipitation changes appear to be part of the positive moisture trend measured in other paleoclimate proxies for the eastern area that began as a result of natural forcing before the industrial revolution and may have recently been enhanced by anthropogenic climate change. 

Abstract Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap‐nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID‐19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site‐level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.