Global contribution of invertebrates to forest litter decomposition.

Forest litter decomposition is an essential component of global carbon and nutrient turnover. Invertebrates play important roles in litter decomposition, but the regional pattern of their effects is poorly understood. We examined 476 case studies across 93 sites and performed a meta-analysis to estimate regional effects of invertebrates on forest litter decomposition. We then assessed how invertebrate diversity, climate and soil pH drive regional variations in invertebrate-mediated decomposition. We found that (1) invertebrate contributions to litter decomposition are 1.4 times higher in tropical and subtropical forests than in forests elsewhere, with an overall contribution of 31% to global forest litter decomposition; and (2) termite diversity, together with warm, humid and acidic environments in the tropics and subtropics are positively associated with forest litter decomposition by invertebrates. Our results demonstrate the significant difference in invertebrate effects on mediating forest litter decomposition among regions. We demonstrate, also, the significance of termites in driving litter mass loss in the tropics and subtropics. These results are particularly pertinent in the tropics and subtropics where climate change and human disturbance threaten invertebrate biodiversity and the ecosystem services it provides.

Transitioning from MODIS to VIIRS Global Water Reservoir Product.

Reservoirs play a crucial role in regulating water availability and enhancing water security. Here, we develop NASA's Visible Infrared Imaging Radiometer Suite (VIIRS) based Global Water Reservoir (GWR) product, consisting of measurements of reservoir area, elevation, storage, evaporation rate, and evaporation loss for 164 large global reservoirs. The dataset is available at 8-day and monthly temporal resolutions. Since the Moderate Resolution Imaging Spectroradiometer (MODIS) is close to the end of its life, we further evaluated the consistency between MODIS and VIIRS-based GWR to ensure continuity to the 20+ year MODIS GWR product. Independent assessment of VIIRS reservoir storage (8-day) retrievals against in-situ measurements shows an average of R2 = 0.84, RMSE = 0.47 km3, and NRMSE = 16.45%. The evaporation rate has an average of R2 = 0.56, RMSE = 1.32 mm/day, and NRMSE = 28.14%. Furthermore, results show good consistency (R2 ≥ 0.90) between the VIIRS and MODIS-based product components, confirming that long-term data continuity can be achieved. This dataset can provide valuable insights for long-term trend analysis, hydrological modeling, and understanding hydroclimatic extremes in the context of reservoirs.

Diminishing storage returns of reservoir construction.

Surface water reservoirs are increasingly being relied upon to meet rising demands in the context of growing population and changing climate. However, the amount of water available in reservoirs (and the corresponding trends) have not been well quantified at the global scale. Here we use satellite observations to estimate the storage variations of 7245 global reservoirs from 1999 to 2018. Total global reservoir storage has increased at a rate of 27.82 ± 0.08 km3/yr, which is mainly attributed to the construction of new dams. However, the normalized reservoir storage (NS)-the ratio of the actual storage to the storage capacity-has declined by 0.82 ± 0.01%. The decline of NS values is especially pronounced in the global south, while the global north mainly exhibits an NS increase. With predicted decreasing runoff and increasing water demand, these observed diminishing storage returns of reservoir construction will likely persist into the future.

Modeling knot features using branch scars from Mongolian oak (Quercus mongolica).

Wood quality is an important indicator for modern sawmills. Internal wood characteristics can be derived from their correlations with external appearances. In this study, we developed linear regression models to predict knot size from surface features of Mongolian oak (Quercus mongolica) using data collected from 53 trees. For this, manual measurements and X-ray computed tomography scanning technology was respectively used to obtain internal and external features of 1,297 knots. Our results showed that Mongolian oak knots were generally concentrated in the middle part of oak stems, with fewer knots observed at the top and base. The parameters of knot and scar showed significant correlations (P < 0.01), where length and diameter of the corresponding external scar increase with increasing the length and diameter of a knot. The corresponding external scar can be used as an effective indicator to predict the internal value of oak logs. The accuracy of our constructed model is more than 95% when assessed against independent test samples. These models thus can be applied to improve the practical production of oak timber and reduce commercial loss caused by knots. These additional data can improve the estimation of the influence of knots on wood quality and provide a theoretical foundation for investigating the characteristics of hardwood knots.

A Simple Label-Free Aptamer-Based Electrochemical Biosensor for the Sensitive Detection of C-Reactive Proteins.

The level of C-reactive protein (CRP) in the human body is closely associated with cardiovascular diseases and inflammation. In this study, a label-free functionalized aptamer sensor was attached to an electrode trimmed with in-gold nanoparticles and carboxylated graphene oxide (AuNPs/GO-COOH) to achieve sensitive measurements relative to CRP. Gold nanoparticles were selected for this study due to super stability, remarkably high electrical conductivity, and biocompatibility. In addition, carboxylated graphene oxide was utilized to promote the anchorage of inducer molecules and to increase detection accuracies. The sensing signal was recorded using differential pulse voltammetry (DPV), and it produced a conspicuous peak current obtained at approximately -0.4 V. Furthermore, the adapted sensor manifested a broad linear span from 0.001 ng/mL to 100 ng/mL. The results also demonstrated that this aptamer sensor had superior stability, specificity, and reproducibility. This aptamer-based electrochemical sensor has enormous potential in complex application situations with interfering substances.

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Developing outer crown profile prediction models of typical urban greening tree species will lay a foundation for the spatial allocation optimization of urban greening. In this study, Pinus tabuliformis, a typical greening tree species in Shenyang, was selected as the research object. Based on the Crown Window device, a total of 60 sample trees were selected to measure the crown shape, with power equation, segmented polynomial equation, and modified Kozak equation as the basic models. By introducing crown structure variables (the maximum crown radius) and neighbour competition variables (mean tree height, mean diameter at breast height, mean crown width, number for the neighbour trees, and mean crown contact height between sample trees and neighbour trees) through reparameterization, we constructed an outer crown shape model of P. tabuliformis that incorporates neighbour tree competition and maximum crown radius. The results showed that modified Kozak equation had the largest Ra2 and the smallest RMSE, as well as good stability. After introducing the maximum crown radius and the mean DBH of neighbour trees into the basic model through reparameterization, the Ra2 of the model increased by 0.0693 and the MSER was 14.4%. The maximum crown radius had a great influence on the crown shape, while the crown radius increased with the increases of the maximum crown radius. The influence of mean DBH of neighbour trees on crown shape was weaker than that of maximum crown radius. The upper part of crown increased and the lower part of crown decreased with increasing neighbour tree competition. In this study, the marginal regression outer crown profile model of P. tabuliformis coupled with neighbour tree competition and the maximum crown radius showed good goodness of fit and could reasonably simulate and predict the crown shape of planted P. tabuliformis.

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Crown width is a critical variable in reflecting the individual tree growth status and in developing forest growth and yield models. With the crown width base model as reference, we developed the crown width quantile regression models for different quantiles (0.50, 0.90, 0.93, 0.95, 0.96, 0.99) based on the data of 2763 Korean pines in 66 permanent plots from the 10-55 years old plantations in Dabiangou forest farm, mountainous areas of eastern Liaoning Province. We used the reparameterization method by introducing the single tree competition index (Rd) and used the dummy variable method by introducing stand density and forest layer variables. We then selected optimal quantile of maximum crown width in the stand by comparing our model developed routine to the traditional methods. The final crown width linear mixed effect quantile regression model was developed based on the optimal quantile at the plot level. The influence of each variable on crown width was analyzed to reflect the difference of crown width among individual trees in the stand. The models with different stand densities and forest layers had significant difference based on F statistical test: the Ra2 of the model increased by 0.0104, the root mean square error decreased by 0.0115 and the mean square error reduction was 7.4%, after the variables of forest layer, forest density, and competition being incorporated into the basic model. The developed quantile regression model performed better than that of the ordinary least square method in simulating the maximum crown width of a single tree in the forest stand. The selected best quantile of the quantile regression model for the upper forest layer and lower forest layer was 0.96 and 0.93, respectively. The linear quantile regression model with the mixed effect was superior to the traditional quantile regression model in Akaike, Bayesion and HQ information criterion and other evaluation para-meters, the standard error for the parameters of estimates was significantly reduced, and the introduced mixed effect well explained differences among different plots. For the upper forest layer and lower forest layer, the maximum crown width decreased with increasing stand density, increased with increasing relative diameters. The influence of stand density on the crown width of the lower forest layer was greater than that of the upper forest layer. The crown width would increase first and then decrease with the increases of DBH when the stand density was large enough. The mixed effect of the quantile regression model developed here could significantly improve the fitting stability of the model. The sustainable development of Korean pine plantation in the mountainous area of eastern Liaoning Pro-vince should be realized by adjusting stand density and moderate tending and thinning in the future.

Recent Advances in Aptamer-Based Nanopore Sensing at Single-Molecule Resolution.

Aptamers as the recognition element of the stochastic nanopore sensors have been under intense investigation. This paper reviews recent research advances in aptamer-based nanopore sensing techniques, including the classification and selection of nanopores (biological nanopores, solid-state nanopores, and nanopipettes), different strategies of aptamer-based nanopore sensing, and their values and outlook for applications in areas such as environmental analysis, precision diagnosis, pharmaceutical industry, and security. Furthermore, the single-molecule nanopore sensors have been applied to reveal the aptamer-target interactions, such as recognition orientation, binding sites, and conformational heterogeneity dissociation kinetics at the single-molecule level. In this review, recent research efforts to develop aptamer-based single-molecule nanopore sensors with high selectivity and sensitivity are highlighted, and some perspectives are drawn.

Evaporative water loss of 1.42 million global lakes.

The evaporative loss from global lakes (natural and artificial) is a critical component of the terrestrial water and energy balance. However, the evaporation volume of these water bodies-from the spatial distribution to the long-term trend-is as of yet unknown. Here, using satellite observations and modeling tools, we quantified the evaporation volume from 1.42 million global lakes from 1985 to 2018. We find that the long-term average lake evaporation is 1500 ± 150 km3 year-1 and it has increased at a rate of 3.12 km3 year-1. The trend attributions include an increasing evaporation rate (58%), decreasing lake ice coverage (23%), and increasing lake surface area (19%). While only accounting for 5% of the global lake storage capacity, artificial lakes (i.e., reservoirs) contribute 16% to the evaporation volume. Our results underline the importance of using evaporation volume, rather than evaporation rate, as the primary index for assessing climatic impacts on lake systems.

Effect of strip clear-cutting on the natural regeneration of Pinus tabuliformis plantations in northeastern China.

In this study, the effect of strip clear-cutting on the natural regeneration performance of mature Pinus tabuliformis plantations in the three locations in western part of the Liaoning Province was analyzed. Strip clear-cutting, with clear-cut and uncut strip widths of 15, 20, 25 m, and 10 and 18 m, respectively, was conducted in spring 2014, and control, in each study location. Field investigations were conducted in 2017. Fifteen sample plots with sizes of 4 m2 (2 m × 2 m) were established in each clear-cut strip, uncut strip, and control. One to four saplings were randomly selected to measure the current year increment, and the lengths and numbers for branch of the first whorl. Three saplings were randomly selected from the center of the strip to measure the photosynthetic rate. Three sample plots with sizes of 4 m2 (2 m × 2 m) and 1 m2 (1 m × 1 m) were developed in each strip and control to determine the biodiversity of shrubs and herbs as well as the water content of the decomposition and semi-decomposition layer. The results show that the current year increment and branch length of the first whorl can be ordered as follows: clear-cut strips > control > uncut strips. Number of the branches of the first whorl can be ordered as follows: clear-cut strips > uncut strips > control. Strip clear-cutting was a statistically significant treatment for the current year increment and length and number of branches of the first whorl. The saplings from the clear-cut strip with a width of 25 m have the largest photosynthetic capacity compared with those from the other strips and control. The transpiration rates of the large, medium, and small saplings from clear-cut strips are the largest and those of saplings from the control are the smallest. The water content of the decomposition and semi-decomposition layer in the control is the highest, but no significant difference was confirmed between the strip clear-cutting approaches.

Constructing Reservoir Area-Volume-Elevation Curve from TanDEM-X DEM Data.

Area-volume-elevation (AVE) curves are critical for reservoir operation rules. However, such curves are not publicly available for most global reservoirs. Here, we present a framework to derive reservoir AVE curves from TanDEM-X data, using Lake Mead (~600 km2) as an example. First, the maximum water extent from 1984 to 2018-provided by the global surface water (GSW) dataset-was used as a mask to obtain the TanDEM-X data. Then, the TanDEM-X water indication mask (WAM) was applied to the extracted TanDEM-X data to obtain the visible bathymetry, which represents the topography between the maximum extent (according to GSW) and the water extent from WAM. Last, the AVE curve was generated by integrating the volume values from the top to bottom layers. TanDEM-X also captures the elevation values of the transitional waters, which are defined as the difference between the highest and lowest water levels. The transitional waters were obtained by thresholding amplitude and coherence images, and their elevations were then added to the visible bathymetry to extend the AVE curves with an elevation range extending from 344-369 m to 341-369 m. Validation results against in situ lidar survey values suggest a high-accuracy of elevation-area (E-A) relationships with R 2 values of >0.99 and NRMSE values from 2.11% to 2.45%, and elevation-volume (E-V) relationships with R 2 values of 1 and NRMSE values from 1.11% to 1.29%. Results also show that TanDEM-X data can capture the interannual variations due to multiple acquisitions, and that the elevation measurements for the lake shore areas are reliable.

Effect of strip shelterwood-cuts on the crown morphology plasticity of natural regenerated Pinus tabuliformis saplings in northeastern China.

The study analysed the effect of shelterwood-cut strips on the outermost crown profiles and crown characteristics of naturally regenerated Pinus tabuliformis saplings in northeastern China. A total of 49 regenerated saplings from shelterwood-cut strips and 30 from uncut strips were collected. Nonlinear quantile regression was used to develop the outermost crown profile model for the saplings from the shelterwood-cut and uncut strips. The quantile value suitable for describing the outermost crown profiles of the two types of strips was selected using nonparametric boundary regression. The difference in crown morphologies between the shelterwood-cut strips and uncut strips was compared. The results showed that with the same diameter at breast height, the crown radii of the uncut strip saplings were larger than those of the shelterwood-cut strip saplings within the range of 0.2-1.0 for the relative depth into the crown. The largest crown radius of the saplings from the uncut strips was larger than that of the saplings from the shelterwood-cut strips. The inflection points of the shelterwood-cut strip sapling crowns were larger than those of the uncut strip sapling crowns. The crown volume of the small uncut strip saplings was larger than that of the shelterwood-cut strip saplings, and the difference in crown volume decreased with increasing sapling size. The saplings in the early stage of the uncut strips showed a greater growth rate than those of the shelterwood-cut strips, but their growth rate slowed over the long term according to branch-length annual growth. The present study provides a reference for forest management strategy decision making in promoting natural regeneration.

Automatic correction of contaminated images for assessment of reservoir surface area dynamics.

The potential of using Landsat for assessing long-term water surface dynamics of individual reservoirs at a global scale has been significantly hindered by contaminations from clouds, cloud shadows, and terrain shadows. A novel algorithm was developed towards the automatic correction of these contaminated image classifications. By applying this algorithm to the dataset by Pekel et al. (2016), time series of area values for 6817 global reservoirs (with an integrated capacity of 6099 km3) were generated from 1984 to 2015. The number of effective images that can be used in each time series has been improved by 81% on average. The long-term average area for these global reservoirs was corrected from 1.73×105 km2 to 3.94×105 km2. The results were proven to be robust through validation using observations, synthetic data, and visual inspection. This continuous reservoir surface area dataset can provide benefit to various applications (both at continental and local scales).

The Future of Earth Observation in Hydrology.

In just the past five years, the field of Earth observation has progressed beyond the offerings of conventional space agency based platforms to include a plethora of sensing opportunities afforded by CubeSats, Unmanned Aerial Vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically on the order of one billion dollars per satellite and with concept-to-launch timelines on the order of two decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturise sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist five years ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of the cost of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-meter resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen-scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the Internet of Things as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilise and exploit these new observing systems to enhance our understanding of the Earth and its linked processes.

Impacts of a Rapidly Declining Mountain Snowpack on Streamflow Timing in Canada's Fraser River Basin.

With its headwaters in the water towers of the western Cordillera of North America, the Fraser River is one of the continent's mightiest rivers by annual flows, supplies vital freshwater resources to populous downstream locations, and sustains the world's largest stocks of sockeye salmon along with four other salmon species. Here we show the Variable Infiltration Capacity (VIC) model's ability to reproduce accurately observed trends in daily streamflow for the Fraser River's main stem and six of its major tributaries over 1949-2006 when air temperatures rose by 1.4 °C while annual precipitation amounts remained stable. Rapidly declining mountain snowpacks and earlier melt onsets result in a 10-day advance of the Fraser River's spring freshet with subsequent reductions in summer flows when up-river salmon migrations occur. Identification of the sub-basins driving the Fraser River's most significant changes provides a measure of seasonal predictability of future floods or droughts in a changing climate.

Evaluation of Four Methods for Predicting Carbon Stocks of Korean Pine Plantations in Heilongjiang Province, China.

A total of 89 trees of Korean pine (Pinus koraiensis) were destructively sampled from the plantations in Heilongjiang Province, P.R. China. The sample trees were measured and calculated for the biomass and carbon stocks of tree components (i.e., stem, branch, foliage and root). Both compatible biomass and carbon stock models were developed with the total biomass and total carbon stocks as the constraints, respectively. Four methods were used to evaluate the carbon stocks of tree components. The first method predicted carbon stocks directly by the compatible carbon stocks models (Method 1). The other three methods indirectly predicted the carbon stocks in two steps: (1) estimating the biomass by the compatible biomass models, and (2) multiplying the estimated biomass by three different carbon conversion factors (i.e., carbon conversion factor 0.5 (Method 2), average carbon concentration of the sample trees (Method 3), and average carbon concentration of each tree component (Method 4)). The prediction errors of estimating the carbon stocks were compared and tested for the differences between the four methods. The results showed that the compatible biomass and carbon models with tree diameter (D) as the sole independent variable performed well so that Method 1 was the best method for predicting the carbon stocks of tree components and total. There were significant differences among the four methods for the carbon stock of stem. Method 2 produced the largest error, especially for stem and total. Methods 3 and Method 4 were slightly worse than Method 1, but the differences were not statistically significant. In practice, the indirect method using the mean carbon concentration of individual trees was sufficient to obtain accurate carbon stocks estimation if carbon stocks models are not available.

Modeling dry and wet deposition of sulfate, nitrate, and ammonium ions in Jiuzhaigou National Nature Reserve, China using a source-oriented CMAQ model: Part I. Base case model results.

A source-oriented Community Multiscale Air Quality (CMAQ) model driven by the meteorological fields generated by the Weather Research and Forecasting (WRF) model was used to study the dry and wet deposition of nitrate (NO3(-)), sulfate (SO4(2-)), and ammonium (NH4(+)) ions in the Jiuzhaigou National Nature Reserve (JNNR), China from June to August 2010 and to identify the contributions of different emission sectors and source regions that were responsible for the deposition fluxes. The model performance is evaluated in this paper and the source contribution analyses are presented in a companion paper. The results show that WRF is capable of reproducing the observed precipitation rates with a Mean Normalized Gross Error (MNGE) of 8.1%. Predicted wet deposition fluxes of SO4(2-) and NO3(-) at the Long Lake (LL) site (3100 m a.s.l.) during the three-month episode are 2.75 and 0.34 kg S(N) ha(-1), which agree well with the observed wet deposition fluxes of 2.42 and 0.39 kg S(N) ha(-1), respectively. Temporal variations in the weekly deposition fluxes at LL are also well predicted. Wet deposition flux of NH4(+) at LL is over-predicted by approximately a factor of 3 (1.60 kg N ha(-1)vs. 0.56 kg N ha(-1)), likely due to missing alkaline earth cations such as Ca(2+) in the current CMAQ simulations. Predicted wet deposition fluxes are also in general agreement with observations at four Acid Deposition Monitoring Network in East Asia (EANET) sites in western China. Predicted dry deposition fluxes of SO4(2-) (including gas deposition of SO2) and NO3(-) (including gas deposition of HNO3) are 0.12 and 0.12 kg S(N) h a(-1) at LL and 0.07 and 0.08 kg S(N) ha(-1) at Jiuzhaigou Bureau (JB) in JNNR, respectively, which are much lower than the corresponding wet deposition fluxes. Dry deposition flux of NH4(+) (including gas deposition of NH3) is 0.21 kg N ha(-1) at LL, and is also much lower than the predicted wet deposition flux. For both dry and wet deposition fluxes, predictions from the 12-km resolution nested domain are similar to those from the 36-km resolution parent domain.