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A Data Guide for this study is available as a web page and for download. The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2008 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships. Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents. Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer. From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study. Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full pregnancy and fertility histories from both men and women, an educational history of dates of degrees and school attendance, contact with the criminal justice system, military service, and various employment events, including the date of first and current jobs, with respective information on occupation, industry, wages, hours, and benefits. Finally, physical measurements and biospecimens were also collected at Wave IV, and included anthropometric measures of weight, height and waist circumference, cardiovascular measures such as systolic blood pressure, diastolic blood pressure, and pulse, metabolic measures from dried blood spots assayed for lipids, glucose, and glycosylated hemoglobin (HbA1c), measures of inflammation and immune function, including High sensitivity C-reactive protein (hsCRP) and Epstein-Barr virus (EBV). Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample.; Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I.; Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later.; Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. ; For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent; Wave II: 88.6 percent; Wave III: 77.4 percent; Wave IV: 80.3 percent; Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States. audio computer-assisted self interview (ACASI) computer-assisted personal interview (CAPI) computer-assisted self interview (CASI) paper and pencil interview (PAPI) face-to-face interview

Fire has a long history in Australia and is a key driver of vegetation dynamics in the tropical savanna ecosystems that cover one quarter of the country. Fire reconstructions are required to understand ecosystem dynamics over the long term but these data are lacking for the extensive savannas of northern Australia. This paper presents a multiproxy palaeofire record for Marura sinkhole in eastern Arnhem Land, Northern Territory, Australia. The record is constructed by combining optical methods (counts and morphology of macroscopic and microscopic charcoal particles) and chemical methods (quantification of abundance and stable isotope composition of pyrogenic carbon by hydrogen pyrolysis). This novel combination of measurements enables the generation of a record of relative fire intensity to investigate the interplay between natural and anthropogenic influences. The Marura palaeofire record comprises three main phases: 4600–2800 cal BP, 2800–900 cal BP and 900 cal BP to present. Highest fire incidence occurs at ~4600–4000 cal BP, coinciding with regional records of high effective precipitation, and all fire proxies decline from that time to the present. 2800–900 cal BP is characterised by variable fire intensities and aligns with archaeological evidence of occupation at nearby Blue Mud Bay. All fire proxies decline significantly after 900 cal BP. The combination of charcoal and pyrogenic carbon measures is a promising proxy for relative fire intensity in sedimentary records and a useful tool for investigating potential anthropogenic fire regimes.

Taxonomic identification of archaeological fish bones provides important insights into the subsistence practices of ancient coastal peoples. However, it can be difficult to execute robust morphological identification of fish bones from species-rich fossil assemblages, especially from post-cranial material with few distinguishing features. Fragmentation, weathering and burning further impede taxonomic identification, resulting in large numbers of unidentifiable bones from archaeological sites. This limitation can be somewhat mitigated by taking an ancient DNA (aDNA) bulk-bone metabarcoding (BBM) approach to faunal identification, where DNA from non-diagnostic bone fragments is extracted and sequenced in parallel. However, a large proportion of fishing communities (both past and present) live in tropical regions that have sub-optimal conditions for long-term aDNA preservation. To date, the BBM method has never been applied to fish bones before, or to fossils excavated from an exposed context within a tropical climate. Here, we demonstrate that morphologically indistinct bulk fish bone from the tropics can be identified by sequencing aDNA extracted from 100 to 300 ya archaeological midden material in southwest Madagascar. Despite the biases of the approach, we rapidly obtained family, genus, and species-level assemblage information, and used this to describe a subset of the ichthyofauna exploited by an 18th century fishing community. We identified 23 families of fish, including benthic, pelagic, and coral-dwelling fishes, suggesting a reliance on a variety of marine and brackish habitats. When possible, BBM should be used alongside osteological approaches to address the limitations of both; however, this study highlights how genetic methods can nevertheless be a valuable tool for helping resolve faunal assemblages when morphological identification is hindered by taphonomic processes, lack of adequate comparative collections, and time constraints, and can provide a temporal perspective on fish biodiversity in the context of accelerated exploitation of the marine environment. Metabarcoding_DataTrimmed, quality filtered, chimera filtered, abundance filtered, and unique 12SrRNA metabarcoding reads for each DNA extract (including controls) sequenced.

The Southern Irumide Belt (SIB) records over one and a half billion years (c. 2000 to 500 Ma) of tectonic evolution along the southern Congo Craton margin. To understand this evolution we present U–Pb, Lu–Hf, rare earth element zircon and structural data for the SIB of Zambia, which are used to investigate its formation, evolution, and relationship to the Irumide Belt of the southern Congo Craton. Orthogneiss in the Chewore–Rufunsa and Chipata terranes yield ages between c. 2040 to 2000 Ma. This implies the presence of Palaeoproterozoic basement throughout the SIB, similar to basement rocks within the Irumide Belt. Detrital zircon data from the Chipata Terrane yield age populations and εHf(t) values that are equivalent to samples from other SIB terranes and the Irumide Belt. The similarities between basement units and overlying sedimentary sequences in the SIB and Irumide Belt indicate that the SIB formed an integral part of the southern Congo margin since the Palaeoproterozoic, rather than accreting to this margin during the late-Mesoproterozoic. Subsequent structural deformation in this region occurred as two phases, a N–S directed compression during the late-Neoproterozoic to Cambrian, and a weaker E–W directed compression during the Phanerozoic.

LOVECLIM transiently forced by changes in orbital parameters (Berger 1978), NH ice-sheet topography and albedo (Abe-Ouchi et al., 2013), and pCO2 (Luthi et al., 2008), as well as meltwater input in the North Atlantic to simulate D-O variability

2020-05-18 and 2020-05-25: Correction of depth values to meter (multiplication of prior values by 100), parameter set to "DEPTH, sediment/rock" (corrected meters composite depth) and "Depth, composite revised" (Equivalent depth of 339-U1385, corrected revised meters composite depth); update of PIs

A key tenant of risk reduction models in archaeology the world over is that changes in resource availability drove mobility increases and created a need for an extension of stone tool use life. This manuscript directly addresses the question, is retouch intensity of tools related to distance from freshwater, by using extant localities of major Gorges, Rivers and water holes in the southern Kimberley region of northern Australia. Previous research has argued that retouched stone points during the mid to late-Holocene were part of a risk minimisation strategy, within broader technological organisation models. Modelling the distance from primary water sources, in arid to semi-arid regions of the southern Kimberley, reduction intensity of points is found to increase with distance from water sources consistently. This research provides an appropriate test of existing risk minimisation models and highlights global significance for similar studies where retouch tool reduction and forager mobility are linked to environmental change.