We assembled data from a global network of automated lake observatories to test hypotheses regarding the drivers of ecosystem metabolism. We estimated daily rates of respiration and gross primary production (GPP) for up to a full year in each lake, via maximum likelihood fits of a free-water metabolism model to continuous highfrequency measurements of dissolved oxygen concentrations. Uncertainties were determined by a bootstrap analysis, allowing lake-days with poorly constrained rate estimates to be down-weighted in subsequent analyses. GPP and respiration varied considerably among lakes and at seasonal and daily timescales. Mean annual GPP and respiration ranged from 0.1 to 5.0 mg O 2 L 21 d 21 and were positively related to total phosphorus but not dissolved organic carbon concentration. Within lakes, significant day-to-day differences in respiration were common despite large uncertainties in estimated rates on some lake-days. Daily variation in GPP explained 5% to 85% of the daily variation in respiration after temperature correction. Respiration was tightly coupled to GPP at a daily scale in oligotrophic and dystrophic lakes, and more weakly coupled in mesotrophic and eutrophic lakes. Background respiration ranged from 0.017 to 2.1 mg O 2 L 21 d 21 and was positively related to indicators of recalcitrant allochthonous and autochthonous organic matter loads, but was not clearly related to an indicator of the quality of allochthonous organic matter inputs.Gross primary production (GPP) and respiration are perhaps the two most fundamental processes in ecosystems. At the cellular or organismal level, they describe biochemical pathways that make organic carbon molecules and energy available to cells. When these cellular processes are integrated across an entire ecosystem, the result-ecosystemlevel GPP, ecosystem respiration, or collectively ecosystem metabolism-describes biogeochemical and trophic processes occurring at the system level.There is substantial interest in understanding the controls on ecosystem metabolism in aquatic (Mulholland et al.
Skin sensors are of paramount importance for flexible wearable electronics, which are active in medical diagnosis and healthcare monitoring. Ultrahigh sensitivity, large measuring range, and high skin conformability are highly desirable for skin sensors. Here, an ultrathin flexible piezoresistive sensor with high sensitivity and wide detection range is reported based on hierarchical nanonetwork structured pressuresensitive material and nanonetwork electrodes. The hierarchical nanonetwork material is composed of silver nanowires (Ag NWs), graphene (GR), and polyamide nanofibers (PANFs). Among them, Ag NWs are evenly interspersed in a PANFs network, forming conductive pathways. Also, GR acts as bridges of crossed Ag NWs. The hierarchical nanonetwork structure and GR bridges of the pressure-sensitive material enable the ultrahigh sensitivity for the pressure sensor. More specifically, the sensitivity of 134 kPa −1 (0−1.5 kPa) and the low detection of 3.7 Pa are achieved for the pressure sensor. Besides, the nanofibers act as a backbone, which provides effective protection for Ag NWs and GR as pressure is applied. Hence, the pressure sensor possesses an excellent durability (>8000 cycles) and wide detection range (>75 kPa). Additionally, ultrathin property (7 μm) and nanonetwork structure provide high skin conformability for the pressure sensor. These superior performances lay a foundation for the application of pressure sensors in physiological signal monitoring and pressure spatial distribution detection.
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