Old-growth forests have traditionally been considered negligible as carbon sinks because carbon uptake has been thought to be balanced by respiration. We show that the top 20-centimeter soil layer in preserved old-growth forests in southern China accumulated atmospheric carbon at an unexpectedly high average rate of 0.61 megagrams of carbon hectare-1 year-1 from 1979 to 2003. This study suggests that the carbon cycle processes in the belowground system of these forests are changing in response to the changing environment. The result directly challenges the prevailing belief in ecosystem ecology regarding carbon budget in old-growth forests and supports the establishment of a new, nonequilibrium conceptual framework to study soil carbon dynamics.
Abstract:The rapid and non-destructive monitoring of the canopy leaf nitrogen concentration (LNC) in crops is important for precise nitrogen (N) management. Nowadays, there is an urgent need to identify next-generation bio-physical variable retrieval algorithms that can be incorporated into an operational processing chain for hyperspectral satellite missions. We assessed six retrieval algorithms for estimating LNC from canopy reflectance of winter wheat in eight field experiments. These experiments represented variations in the N application rates, planting densities, ecological sites and cultivars and yielded a total of 821 samples from various places in Jiangsu, China over nine consecutive years. Based on the reflectance spectra and their first derivatives, six methods using different numbers of wavelengths were applied to construct predictive models for estimating wheat LNC, including continuum removal (CR), vegetation indices (VIs), stepwise multiple linear regression (SMLR), partial least squares regression (PLSR), artificial neural networks (ANNs), and support vector machines (SVMs). To assess the performance of these six methods, we provided a systematic evaluation of the estimation OPEN ACCESS Remote Sens. 2015, 7 14940 accuracies using the six metrics that were the coefficients of determination for the calibration (R 2 C) and validation (R 2 V) sets, the root mean square errors of prediction (RMSEP) for the calibration and validation sets, the ratio of prediction to deviation (RPD), the computational efficiency (CE) and the complexity level (CL). The following results were obtained: (1) For the VIs method, SAVI(R1200, R705) produced a more accurate estimation of the LNC than other indices, with R² C, R² V, RMSEP, RPD and CE values of 0.844, 0.795, 0.384, 2.005 and 0.10 min, respectively; (2) For the SMLR, PLSR, ANNs and SVMs methods, the SVMs using the first derivative canopy spectra (SVM-FDS) offered the best accuracy in terms of R² C, R² V, RMSEP, RPD, and CE, at 0.96, 0.78, 0.37, 2.02, and 21.17, respectively; (3) The PLSR-FDS, ANN-OS and SVM-FDS methods yield similar accuracies if the CE and CL are not considered, however, ANNs and SVMs performed better on calibration set than the validation set which indicate that we should take more caution with the two methods for over-fitting. Except PLS method, the performance for most methods did not enhance when the spectrum were operated by the first derivative. Moreover, the evaluation of the robustness demonstrates that SVM method may be better suited than the other methods to cope with potential confounding factors for most varieties, ecological site and growth stage; (4) The prediction accuracy was found to be higher when more wavelengths were used, though at the cost of a lower CE. The findings are of interest to the remote sensing community for the development of improved inversion schemes for hyperspectral applications concerning other types of vegetation. The examples provided in this paper may also serve to illustrate the advantages and shortcomings...
While electroporation has been widely used as a physical method for gene transfection in vitro and in vivo, its application in gene therapy of cardiovascular cells remains challenging. Due to the high concentration of ion-transport proteins in the sarcolemma, conventional electroporation of primary cardiomyocytes tends to cause ion-channel activation and abnormal ion flux, resulting in low transfection efficiency and high mortality. In this work, we report a high-throughput nano-electroporation technique based on a nanochannel array platform, which enables massively parallel delivery of genetic cargo (microRNA, plasmids) into mouse primary cardiomyocytes in a controllable, highly efficient and benign manner. A simple ‘dewetting’ approach was implemented to precisely position a large number of cells on the nano-electroporation platform. With dosage control, our device precisely titrated the level of miR-29, a potential therapeutic agent for cardiac fibrosis, and determined the minimum concentration of miR-29 causing side effects in mouse primary cardiomyocytes. Moreover, the dose-dependent effect of miR-29 on mitochondrial potential and homeostasis was monitored. Altogether, our nanochannel array platform provides efficient trapping and transfection of primary mouse cardiomyocyte, which could improve the quality control for future microRNA therapy in heart diseases.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.