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Diatom abundance and assemblage data are presented for JPC43 - a ~12 m marine sediment core recovered from 576 m water depth in Neny Fjord, Marguerite Bay, Antarctic Peninsula (68.2571°S, 66.9617°W). The core was collected aboard the RVIB Nathanial B Palmer in 2002 during the NBP0201 scientific cruise (PI: Prof J B Anderson) to determine the timing of deglaciation in the fjords of the Antarctic Peninsula. The core record spans the Holocene with samples dated using an age model based on 5 reliable radiocarbon dates. Diatom concentrations and the contribution of Chaetoceros resting spores (CRS %) are calculated from counts (mean=474.4 valves) of the whole diatom assemblage - 'total counts' (n=81). The relevant methods are described and referenced in the associated publication (Allen et al. 2010).

California policy is incentivizing rapid adoption of zero emission electric vehicles for light duty and freight applications. In this project, we explored how locating charging facilities at California’s highway rest stops, might impact electricity demand, grid operation, and integration of renewables like solar and wind into California’s energy mix. Assuming a growing population of electric vehicles to meet state goals, we estimated state-wide growth of electricity demand, and identified the most attractive rest stop locations for siting chargers. Using a California-specific electricity dispatch model developed at ITS, we estimated how charging vehicles at these stations would impact renewable energy curtailment in California. We estimated the impacts of charging infrastructures on California’s electricity system and how they can be utilized to decrease the duck curve effect resulting from a large amount of solar energy penetration by 2050.

The purpose of this project is to determine if protein is less likely to create positive energy balance when added to the diet compared to carbohydrate. To do this, the investigators will take detailed measurements of participant's baseline metabolic rate to understand their energy requirements. Then, the investigators will feed participants all their meals for two weeks, Monday-Friday, and measure their food intake. During one of the week-long feeding periods, participants will consume a shake made of egg protein that is ~20% of their energy requirements. During the other week, participants will consume a shake made of carbohydrate that is ~20% of their energy requirements. Participants will drink the assigned shake at the beginning of each of their daily three meals, and then they will be offered a 'regular' meal of unlimited quantity. Participants will not know that the investigators are measuring the food consumed after drinking the shake. Participants will drink the protein shake for the first week and carb-based shake for the second week, and vice versa-- depending on the randomization order. To account for energy expenditure, participants will wear an activity monitor, an accelerometer. Energy balance, measured as participant energy intake minus energy expenditure, will be our main outcome for each treatment. However, because participants may change their behavior if made aware of the true research question, the investigators will tell participants that the purpose of the study is to see how low fiber and high fiber shakes affect mood. The hypothesis is that during the week when participants consume the protein shake, they will remain in energy balance, but during the week of carbohydrate shake consumption, participants will have positive energy balance.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.BCC.BCC-ESM1.amip' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The BCC-ESM 1 climate model, released in 2017, includes the following components: atmos: BCC_AGCM3_LR (T42; 128 x 64 longitude/latitude; 26 levels; top level 2.19 hPa), atmosChem: BCC-AGCM3-Chem, land: BCC_AVIM2, ocean: MOM4 (1/3 deg 10S-10N, 1/3-1 deg 10-30 N/S, and 1 deg in high latitudes; 360 x 232 longitude/latitude; 40 levels; top grid cell 0-10 m), seaIce: SIS2. The model was run by the Beijing Climate Center, Beijing 100081, China (BCC) in native nominal resolutions: atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 50 km, seaIce: 50 km.

Permafrost regions contain approximately half of the carbon stored in land ecosystems and have warmed at least twice as much as any other biome. This warming has influenced vegetation activity, leading to changes in plant composition, physiology, and biomass storage in aboveground and belowground components, ultimately impacting ecosystem carbon balance. Yet, little is known about the causes and magnitude of long-term changes in the above- to belowground biomass ratio of plants (η). Here, we analyzed η values based on 3,013 plots and 26,337 plant-specific measurements representing eight sites across the Tibetan Plateau from 1995 to 2021. Our analysis revealed distinct temporal trends in η for three vegetation types: a 17% increase in alpine wetlands, and a decrease of 26% and 48% in alpine meadows and alpine steppes, respectively. These trends were primarily driven by temperature-induced growth preferences rather than shifts in plant species composition. Our findings indicate that in wetter ecosystems climate warming promotes aboveground plant growth, while in drier ecosystems, such as alpine meadows and alpine steppes, plants allocate more biomass belowground. Four process-based biogeochemical models failed to simulate the observed changes in η, which highlights the importance of improved process understanding of the processes driving the response of biomass distribution to climate warming, which is crucial for predicting the future carbon trajectory of permafrost ecosystems.

These data record the results of processing otter trawl catches (OTSB14; Merrett & Marshall, 1980) from the National Oceanography Centre (NOC, UK) long-term study of the Porcupine Abyssal Plain (PAP), including the PAP-Sustained Observatory time-series. The data concern catches recovered during the RRS Challenger Cruise 142 in 1999. Billett, D.S.M. et al. (2000). RRS Challenger Cruise 142, 19 Apr-19 May 1999. Temporal and spatial variability of benthic communities at the Porcupine Abyssal Plain and in the Porcupine Seabight. Southampton Oceanography Centre Cruise Report, No. 30, 79pp.| https://www.bodc.ac.uk/resources/inventories/cruise_inventory/reports/ch142_99.pdf

This study will utilize a randomized, double-blind, cross-over design, comparing acute ingestion of the mixed flavonoid supplement (MF) compared to placebo control (PC) in healthy, non-obese, pre-menopausal women. The study will consist of two 24-hour study periods spent in the recently renovated indirect room calorimeter (i.e., metabolic chamber) at the University of North Carolina Chapel Hill Nutrition Research Institute (UNC NRI). The 24-hour study periods in the metabolic chamber will be 4 weeks apart. Primary outcome measures will be 24-hour energy expenditure (EE), resting metabolic rate (RMR), sleeping metabolic rate (SMR), substrate utilization from the respiratory quotient (RQ), and physical activity energy expenditure (AEE). Following recruitment and eligibility assessment, study participants will be randomly assigned to complete either the mixed flavonoid (MF) or the placebo control (PC) study day. After a 4-week washout, study participants will cross over and complete the alternative treatment. A method of randomly permuted blocks will be generated using web-based randomization software (www.randomization.com) resulting in 10 study participants receiving MF during the first week, and 10 study participants receiving the PC during the first week. Study participants will consume 2 MF or PC capsules 30 min before breakfast, and 2 MF or PC capsules 30 min before lunch. During both study days, study participants will be fed in energy balance (i.e., energy intake will be matched to energy expenditure). 2. Experimental Study Participants: Using data generated previously in the UNC NRI metabolic chamber, a sample size calculation with 80% power revealed that 15-20 study participants would be needed to detect a 50 kcal difference in 24-h EE. To account for attrition, 25 study participants will be recruited via mass advertisement throughout the local area. Pre-menopausal women will be chosen because this is a target population of the sponsor. 3. Pre-Study Baseline Testing Eligibility will be determined in the outpatient clinical suite at the UNC NRI. Body composition (fat mass and fat free mass (FFM)) will be determined via dual energy x-ray absorptiometry (DXA) (GE Lunar iDXA; Milwaukee, WI). Body mass index (BMI, kg/m2) will be calculated for measured height and weight. Resting metabolic rate (RMR) will be estimated using a FFM-based equation [418 + (20.3 FFM)] (J Appl Physiol 1993;75:2514-2520). This estimated RMR will be used to calculate total dietary energy intake while in the metabolic chamber: RMR x physical activity level (PAL) of 1.3, and then adjusted using measured data (details provided below). A small blood sample will be obtained at this time and T3, T4, and TSH levels assessed through the clinical lab at the Lab Corp (Burlington, NC). A urine pregnancy test will be performed. 4. Indirect calorimetry: The metabolic chamber at the Nutrition Research Institute in Kannapolis, NC is an open-circuit, whole room indirect calorimeter. The CO2 and O2 analysers are differential, with full scale readings set for 0%-1%. O2 consumption, CO2 production, EE and RQ are recorded each minute. EE is calculated using an abbreviated Weir's formula (VO2 X 3.941) + (VCO2 X 1.106), where VO2 is the volume of oxygen consumed in L/minute and VCO2 is the volume of carbon dioxide released in L/minute. RQ is calculated as VCO2/VO2. Area under the curve (AUC) will be calculated using RQ data for the four hours following breakfast, lunch and dinner as well as sleeping hours between midnight and 6:00 am. Spontaneous physical activity will be measured each minute using a total room sensor. To calculate resting metabolic rate (RMR), EE will be plotted against the activity motion sensor output (each averaged over 30 minutes), and the y-intercept of the linear regression taken as EE in the inactive state. RMR will be multiplied by 1440 minutes to extrapolate to 24 hours. Twenty-four hour sleeping metabolic rate (SMR) will be determined as the lowest mean EE (kJ/minute) measured over 3 consecutive hours between midnight and 6:30 am and multiplied by 1440 minutes. Diet induced thermogenesis (DIT) will be calculated by subtraction of SMR from RMR. Activity induced EE (AEE) will be calculated as the difference between 24 hour EE and RMR. 5. Metabolic chamber study day protocol. Subjects will arrive at the Nutrition Research Institute Building (500 Laureate Way) at 7:00 am. A urine pregnancy test will be performed. At 7:30 am, study participants will report to the metabolic chamber following an overnight fast (no food or beverages containing calories, alcohol, or caffeine from 11 pm). Study participants will be instructed on expectations of their stay and weighed in scrubs without shoes. At 8:00 am study participants will be sealed in the chamber. Except for a 2-minute interval each hour during which study participants will be requested to stand and stretch, study participants will remain seated or reclined, but awake throughout the day. Study participants will be asked to perform necessary daily activities during these 2-minute intervals. Breakfast (9:00 am), lunch (1:30 pm), and dinner (7:00 pm), will be served through an air-lock passage. Meals will be completed within 30 minutes of serving. Two MF capsules or placebo will be consumed 30 min before breakfast, and then again 30 minutes before lunch. At 10:30 pm, study participants will be asked to lie down for sleep. Study participants will be awakened at 6:30 am and allowed to move about the chamber to gather their belongings. At 7:15 am study participants will exit the chamber and be weighed. 6. Design of Metabolic Diets: Eucaloric diets will be designed to provide approximately 35% fat, 49% carbohydrates and 16% protein, reflecting current recommendations for this population group. Menus will be designed using a nutrient calculation and food management software, and consist of bagel, peanut butter, apple juice, whole-wheat bread, turkey, cheese, mayonnaise, buttery spread (10% kcal as fat), potato chips, lasagna, carrots, broccoli, rolls, and muffin. No beverages or foods containing caffeine will be served. The same foods will be served at both chamber visits. A baseline menu for each subject will be prepared based on calculated RMR X 1.3, reflecting the sedentary nature of the study day. To ensure energy balance conditions, the baseline menu of the first visit will be modified according to measured EE data at 3 hours (includes breakfast) and 7 hours (includes breakfast and lunch). Subsequent meals will be adjusted accordingly with 100 kcal peach muffins containing the same proportion of fat, carbohydrate and protein as the meals. Study participants will be fed an identical amount of the same meal at their second visit. 7. Statistical Analysis: Data will be analyzed using SAS (Cary, NC). To guard against any carryover effect from visit 1 to visit 2, a repeated measures regression with an unstructured correlation matrix within subject will be run with treatment (MF and PC) and visit (1 and 2) in the model along with an interaction term. If the interaction term is non-significant, then it will be removed and the model re-run. Two energy expenditure curves, one for the MF day, and one for the PC day, will be generated for each subject with the x axis representing time (min), and the y axis representing energy expenditure (kcal). The area under the energy expenditure curve for defined blocks of time will be calculated by using the trapezoid rule in the EXPAND procedure in SAS (SAS Institute, Inc., Cary, NC). A paired t-test on the log-transformed area will be performed to compare the energy expenditure of each period in the MF day with the corresponding period in the PC day. The Shapiro-Wilk test in the UNIVARIATE procedure in SAS will be used for normality check. The Benjamini-Hochberg method for false discovery rate correction in the MULTTEST procedure in SAS will be used for multiple testing corrections. SUPPLEMENT: The mixed flavonoid supplement and placebo capsules will look identical and be supplied by Reoxcyn Discoveries Group LLC (Salt Lake City, UT). Active ingredients in the flavonoid capsules include vitamin C, wild bilberry fruit extract, green tea leaf extract, quercetin, caffeine, and omega 3 fatty acids (see Appendix B). Capsule fill ingredients include Nu-Flow 70R (from powdered rice hulls), tapioca from cassava root, natural bamboo silica, and marshmallow root. Placebo capsules will contain only the fill ingredients (without the active ingredients). Two MF and PC capsules will be consumed 30 minutes before breakfast, and then again before lunch. The MF capsules will provide 658 mg flavonoids and 214 mg caffeine. The purpose of this study is to compare the effect of ingesting caffeine and mixed flavonoids (4 capsules, split between breakfast and lunch) on energy expenditure and fat oxidation in a metabolic chamber with 20 women (non-obese, healthy, ages 20-47 years, pre-menopausal). We hypothesize that based on the existing literature, ingestion of a double dose of the caffeine-mixed flavonoid supplement compared to placebo will increase fat oxidation and increase 24 h energy expenditure by about 75 kilocalories.