Digital exercise interventions for improving measures of central obesity: a systematic review

Objectives - We aimed to systematically review the potential benefits of digital exercise interventions for improving measures of central obesity including visceral adipose tissue (VAT) and anthropometric surrogates for VAT in overweight or centrally obese adults aged 18 or over. Methods - A systematic literature search was conducted in three databases up until March 2020 (PROSPERO registration nr CRD42019126764). Results - N = 5 studies including 438 participants (age 48–80) with body mass index ≥ 25 kg/m2 met the eligibility criteria and were included. The duration of the interventions ranged from 8 to 24 weeks. No study measured the primary outcome VAT, although in N = 4 studies, waist circumference (WC) decreased by between 1.3 and 5.6 cm in the intervention groups. Conclusions - This systematic review shows that there is no evidence for the effects of digital exercise on VAT, although digital exercise may decrease WC. These findings highlight the need for additional randomized controlled trials to confirm the findings with respect to WC, and to further investigate the effects of digital exercise on VAT. Together, this may have important implications for reducing the burden of physical inactivity and obesity

Ventilation of the Arctic Ocean: Mean ages and inventories of anthropogenic CO2 and CFC-11

The Arctic Ocean constitutes a large body of water that is still relatively poorly surveyed because of logistical difficulties, although the importance of the Arctic Ocean for global circulation and climate is widely recognized. For instance, the concentration and inventory of anthropogenic CO2 (C ant) in the Arctic Ocean are not properly known despite its relatively large volume of well-ventilated waters. In this work, we have synthesized available transient tracer measurements (e.g., CFCs and SF6) made during more than two decades by the authors. The tracer data are used to estimate the ventilation of the Arctic Ocean, to infer deep-water pathways, and to estimate the Arctic Ocean inventory of C ant. For these calculations, we used the transit time distribution (TTD) concept that makes tracer measurements collected over several decades comparable with each other. The bottom water in the Arctic Ocean has CFC values close to the detection limit, with somewhat higher values in the Eurasian Basin. The ventilation time for the intermediate water column is shorter in the Eurasian Basin (∼200 years) than in the Canadian Basin (∼300 years). We calculate the Arctic Ocean C ant inventory range to be 2.5 to 3.3 Pg-C, normalized to 2005, i.e., ∼2% of the global ocean C ant inventory despite being composed of only ∼1% of the global ocean volume. In a similar fashion, we use the TTD field to calculate the Arctic Ocean inventory of CFC-11 to be 26.2 ± 2.6 × 106 moles for year 1994, which is ∼5% of the global ocean CFC-11 inventor

The tundra phenology database: more than two decades of tundra phenology responses to climate change

Observations of changes in phenology have provided some of the strongest signals of the effects of climate change on terrestrial ecosystems. The International Tundra Experiment (ITEX), initiated in the early 1990s, established a common protocol to measure plant phenology in tundra study areas across the globe. Today, this valuable collection of phenology measurements depicts the responses of plants at the colder extremes of our planet to experimental and ambient changes in temperature over the past decades. The database contains 150 434 phenology observations of 278 plant species taken at 28 study areas for periods of 1\u201326 years. Here we describe the full data set to increase the visibility and use of these data in global analyses and to invite phenology data contributions from underrepresented tundra locations. Portions of this tundra phenology database have been used in three recent syntheses, some data sets are expanded, others are from entirely new study areas, and the entirety of these data are now available at the Polar Data Catalogue (https://doi.org/10.21963/13215)

Explaining Support Vector Machines: A Color Based Nomogram.

PROBLEM SETTING: Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models. OBJECTIVE: In this work, we investigate whether SVMs using linear, polynomial and RBF kernels can be explained such that interpretations for model-based decisions can be provided. We further indicate when SVMs can be explained and in which situations interpretation of SVMs is (hitherto) not possible. Here, explainability is defined as the ability to produce the final decision based on a sum of contributions which depend on one single or at most two input variables. RESULTS: Our experiments on simulated and real-life data show that explainability of an SVM depends on the chosen parameter values (degree of polynomial kernel, width of RBF kernel and regularization constant). When several combinations of parameter values yield the same cross-validation performance, combinations with a lower polynomial degree or a larger kernel width have a higher chance of being explainable. CONCLUSIONS: This work summarizes SVM classifiers obtained with linear, polynomial and RBF kernels in a single plot. Linear and polynomial kernels up to the second degree are represented exactly. For other kernels an indication of the reliability of the approximation is presented. The complete methodology is available as an R package and two apps and a movie are provided to illustrate the possibilities offered by the method

Physical and biogeochemical controls on the variability in surface pH and calcium carbonate saturation states in the Atlantic sectors of the Arctic and Southern Oceans

Polar oceans are particularly vulnerable to ocean acidification due to their low temperatures and reduced buffering capacity, and are expected to experience extensive low pH conditions and reduced carbonate mineral saturations states (Ω) in the near future. However, the impact of anthropogenic CO2 on pH and Ω will vary regionally between and across the Arctic and Southern Oceans. Here we investigate the carbonate chemistry in the Atlantic sector of two polar oceans, the Nordic Seas and Barents Sea in the Arctic Ocean, and the Scotia and Weddell Seas in the Southern Ocean, to determine the physical and biogeochemical processes that control surface pH and Ω. High-resolution observations showed large gradients in surface pH (0.10–0.30) and aragonite saturation state (Ωar) (0.2–1.0) over small spatial scales, and these were particularly strong in sea-ice covered areas (up to 0.45 in pH and 2.0 in Ωar). In the Arctic, sea-ice melt facilitated bloom initiation in light-limited and iron replete (dFe>0.2 nM) regions, such as the Fram Strait, resulting in high pH (8.45) and Ωar (3.0) along the sea-ice edge. In contrast, accumulation of dissolved inorganic carbon derived from organic carbon mineralisation under the ice resulted in low pH (8.05) and Ωar (1.1) in areas where thick ice persisted. In the Southern Ocean, sea-ice retreat resulted in bloom formation only where terrestrial inputs supplied sufficient iron (dFe>0.2 nM), such as in the vicinity of the South Sandwich Islands where enhanced pH (8.3) and Ωar (2.3) were primarily due to biological production. In contrast, in the adjacent Weddell Sea, weak biological uptake of CO2 due to low iron concentrations (dFe<0.2 nM) resulted in low pH (8.1) and Ωar (1.6). The large spatial variability in both polar oceans highlights the need for spatially resolved surface data of carbonate chemistry variables but also nutrients (including iron) in order to accurately elucidate the large gradients experienced by marine organisms and to understand their response to increased CO2 in the future

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

The tundra phenology database: More than two decades of tundra phenology responses to climate change

Observations of changes in phenology have provided some of the strongest signals of the effects of climate change on terrestrial ecosystems. The International Tundra Experiment (ITEX), initiated in the early 1990s, established a common protocol to measure plant phenology in tundra study areas across the globe. Today, this valuable collection of phenology measurements depicts the responses of plants at the colder extremes of our planet to experimental and ambient changes in temperature over the past decades. The database contains 150,434 phenology observations of 278 plant species taken at 28 study areas for periods of 1 to 26 years. Here we describe the full dataset to increase the visibility and use of these data in global analyses, and to invite phenology data contributions from underrepresented tundra locations. Portions of this tundra phenology database have been used in three recent syntheses, some datasets are expanded, others are from entirely new study areas, and the entirety of these data are now available at the Polar Data Catalogue (https://doi.org/10.21963/13215)

Blue Carbon Storage Capacity of Temperate Eelgrass (Zostera marina) Meadows

Despite the importance of coastal ecosystems for the global carbon budgets, knowledge of their carbon storage capacity and the factors driving variability in storage capacity is still limited. Here we provide an estimate on the magnitude and variability of carbon stocks within a widely distributed marine foundation species throughout its distribution area in temperate Northern Hemisphere. We sampled 54 eelgrass (Zostera marina) meadows, spread across eight ocean margins and 36° of latitude, to determine abiotic and biotic factors influencing organic carbon (Corg) stocks in Zostera marina sediments. The Corg stocks (integrated over 25‐cm depth) showed a large variability and ranged from 318 to 26,523 g C/m2 with an average of 2,721 g C/m2. The projected Corg stocks obtained by extrapolating over the top 1 m of sediment ranged between 23.1 and 351.7 Mg C/ha, which is in line with estimates for other seagrasses and other blue carbon ecosystems. Most of the variation in Corg stocks was explained by five environmental variables (sediment mud content, dry density and degree of sorting, and salinity and water depth), while plant attributes such as biomass and shoot density were less important to Corg stocks. Carbon isotopic signatures indicated that at most sites <50% of the sediment carbon is derived from seagrass, which is lower than reported previously for seagrass meadows. The high spatial carbon storage variability urges caution in extrapolating carbon storage capacity between geographical areas as well as within and between seagrass species