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It is hard for current time series reconstruction methods to achieve the balance of high-precision time series reconstruction and explanation of the model mechanism. The goal of this paper is to improve the reconstruction accuracy with a well-explained time series model. Thus, we developed a function-based model, the CCTM (Continuous Change Tracker Model) model, that can achieve high precision in time series reconstruction by tracking the time series variation rate. The goal of this paper is to provide a new solution for high-precision time series reconstruction and related applications. To test the reconstruction effects, the model was applied to four types of datasets: normalized difference vegetation index (NDVI), gross primary productivity (GPP), leaf area index (LAI), and MODIS surface reflectance (MSR). Several new observations are as follows. First, the CCTM model is well explained and based on the second-order derivative theorem, which divides the yearly time series into four variation types including uniform variations, decelerated variations, accelerated variations, and short-periodical variations, and each variation type is represented by a designed function. Second, the CCTM model provides much better reconstruction results than the Harmonic model on the NDVI, GPP, MSR, and LAI datasets for the seasonal segment reconstruction. The combined use of the Savitzky–Golay filter and the CCTM model is better than the combinations of the Savitzky–Golay filter with other models. Third, the Harmonic model has the best trend-fitting ability on the yearly time series dataset, with the highest R-Square and the lowest RMSE among the four function fitting models. However, with seasonal piecewise fitting, the four models all achieved high accuracy, and the CCTM performs the best. Fourth, the CCTM model should also be applied to time series image compression, two compression patterns with 24 coefficients and 6 coefficients respectively are proposed. The daily MSR dataset can achieve a compression ratio of 15 by using the 6-coefficients method. Finally, the CCTM model also has the potential to be applied to change detection, trend analysis, and phenology and seasonal characteristics extractions. [ABSTRACT FROM AUTHOR]

Remote sensing fractional vegetation cover (FVC) requires both finer-resolution and high-frequency in climate and ecosystem research. The increasing availability of finer-resolution (≤ 30 m) remote sensing data makes this possible. However, data from different satellites have large differences in spatial resolution, spectral response function, and so on, making joint use difficult. Herein, we showed that the vegetation index (VI)-based mixture model with the appropriate VI values of pure vegetation (Vv) and bare soil (Vs) from the MODIS BRDF product via the multi-angle VI method (MultiVI) was feasible to estimate FVC with multiple satellite data. Analyses of the spatial resolution and spectral response function differences for MODIS and other satellites including Landsat 8, Chinese GF 1, and ZY 3 predicted that (1) the effect of Vv and Vs downscaling on FVC estimation uncertainty varied from satellite to satellite due to the positioning differences, and (2) after spectral normalization, the uncertainty (RMSDs) for FVC estimation decreased by ~2.6% compared with the results without spectral normalization. FVC estimation across multiple satellite data will help to improve the spatiotemporal resolution of FVC products, which is an important development for numerous biophysical applications. Herein, we proved that the VI-based mixture model with Vv and Vs from MultiVI is a strong candidate. [ABSTRACT FROM AUTHOR]

The Bidirectional Reflectance Distribution Function (BRDF) is usually used to describe the reflectance anisotropy of a non-Lambertian surface and estimate surface parameters. Among the BRDF models, the kernel-driven models have been extensively used due to their simple form and powerful fitting ability, and their reliability has been validated in some studies. However, existing validation efforts used in situ measurements or limited satellite data, which may be subject to inadequate observational conditions or quality uncertainties. A recently released high-quality BRDF database from Polarization and Directionality of the Earth's Reflectances (POLDER) provides an opportunity to revisit the performance of the kernel-driven models. Therefore, in order to evaluate the fitting ability of the kernel-driven models under different observational conditions and explore their application direction in the future, we use the filtered high-quality BRDF database to evaluate the fitting ability of the kernel-driven model represented by the RossThick-LiSparseR (RTLSR) kernels in this paper. The results show that the RTLSR model performs well, which shows small fitting residuals under most observational conditions. However, the applicability of the RTLSR model performed differently across land cover types; the RTLSR model exhibited larger fitting residuals, especially over non-vegetated surfaces. Under different sun-sensor geometries, the fitting residuals show a strong positive correlation with the Solar Zenith Angle. The above two factors cause the RTLSR model to exhibit a poorer fitting ability at high latitudes. As an exploration, we designed a model combination strategy that combines the advantages of different models and achieved a better performance at high latitudes. We believe that this study provides a better understanding of the RTLSR model. [ABSTRACT FROM AUTHOR]

Habitat quality is an important indicator for evaluating the biodiversity provided by ecosystem. Estimating and scenario-simulating the dynamic evolution and future development trends of habitat quality under the influence of land-use change is significant in regional biodiversity conservation, formulating land-use planning, and maintaining the ecological environmental sustainability. In this article, we included the Huaihe River Economic Belt as the area of study because of its vital location in China and applied the CA–Markov and InVEST models to analyze the spatio-temporal evolution of habitat quality and to simulate the future development trends of habitat quality under three different land-use scenarios: fast urban growth scenario, farmland conservation-oriented scenario, and ecological conservation-oriented scenario. The results showed that the land-use change in the Huaihe River Economic Belt was mostly represented by the continuous increase of the built-up area, whereas other land types all declined in area from 1995 to 2015. The land-use changes under these three abovementioned alternative future scenarios with different development orientations were considerably different. The built-up area has been shown to expand rapidly to occupy other land types on a large scale under the fast urban growth scenario. Urban land increased slightly and a large area of rural residential land would be converted into farmland under the farmland conservation-oriented scenario. The built-up area and farmland might decrease while woodland, grassland and water would increase in extent of areas under the ecological conservation-oriented scenario. Habitat quality has been shown to be generally poor, continuing to decline from 1995 to 2015, while its spatial distribution was higher in the southwest and northeast areas and lower in the central regions. The future habitat quality would display a downward trend under the fast urban growth and farmland conservation-oriented scenarios with a further deterioration of the ecological environment, while the ecological conservation-oriented scenario predicted the converse trend that the ecological environment would be improved productively. This study may be useful for understanding the impact of land-use dynamics on biodiversity. The research results can provide a scientific basis for the decision-makers to formulate biodiversity conservation and land management policies. [ABSTRACT FROM AUTHOR]

We performed a detailed analysis of Earth Polychromatic Imaging Camera (EPIC) spectral data. We found that the vector composed of blue and near‐infrared (NIR) reflectance follows a counterclockwise closed‐loop trajectory from 0 to 24 UTC as Earth rotates. This nonlinear relationship was not observed by any other satellites due to limited spatial or temporal coverage of either low Earth orbit or geostationary satellites. We found that clouds play an important role in determining the nonlinear relationship in addition to the well‐known cloud‐free land‐ocean reflectance contrast in the two bands. The nonlinear relationship is the result of three factors: (1) a much larger cloud‐free land‐ocean contrast in the NIR band compared to the blue band, (2) significantly larger difference between cloudy land and cloudy ocean reflectance in the NIR band compared to the blue band, and (3) the periodic variation of fractions of clear land, clear ocean, cloudy land, and cloudy ocean in the sunlit hemisphere as Earth rotates. We found that the green vegetation contributes significantly to the NIR global average reflectance when the South and North Americas appear and disappear in the EPIC's field of view. The blue and NIR relationship can be useful for exoplanet research. Clouds impose a strong impact on global spectral reflectance, and the reflectance response to a change in cloud cover depends on whether the change is over land or over the ocean. On average, an increase of 0.1 in cloud coverage will lead to a 7% increase in spectrally integrated global average reflectance. Key Points: Blue and NIR reflectance relationship from EPIC and clouds play an important role in determining such relationshipThe response of the global reflectance to a change in cloud fraction is quantifiedThe blue and NIR relationship can be useful for exoplanet research [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) absorbed by vegetation have been successfully generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) data since early 2000. As the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard, the Suomi National Polar-orbiting Partnership (SNPP) has inherited the scientific role of MODIS, and the development of a continuous, consistent, and well-characterized VIIRS LAI/FPAR data set is critical to continue the MODIS time series. In this paper, we build the radiative transfer-based VIIRS-specific lookup tables by achieving minimal difference with the MODIS data set and maximal spatial coverage of retrievals from the main algorithm. The theory of spectral invariants provides the configurable physical parameters, i.e., single scattering albedos (SSAs) that are optimized for VIIRS-specific characteristics. The effort finds a set of smaller red-band SSA and larger near-infrared-band SSA for VIIRS compared with the MODIS heritage. The VIIRS LAI/FPAR is evaluated through comparisons with one year of MODIS product in terms of both spatial and temporal patterns. Further validation efforts are still necessary to ensure the product quality. Current results, however, imbue confidence in the VIIRS data set and suggest that the efforts described here meet the goal of achieving the operationally consistent multisensor LAI/FPAR data sets. Moreover, the strategies of parametric adjustment and LAI/FPAR evaluation applied to SNPP-VIIRS can also be employed to the subsequent Joint Polar Satellite System VIIRS or other instruments. [ABSTRACT FROM AUTHOR]

The operational Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) algorithm has been successfully implemented for Visible Infrared Imager Radiometer Suite (VIIRS) observations by optimizing a small set of configurable parameters in Look-Up-Tables (LUTs). Our preliminary evaluation showed reasonable agreement between VIIRS and MODIS LAI/FPAR retrievals. However, there is a need for a more comprehensive investigation to assure continuity of multi-sensor global LAI/FPAR time series, as the preliminary evaluation was spatiotemporally limited. In this study, we use a multi-year (2012-2016) global LAI/FPAR product generated from VIIRS and MODIS to evaluate for spatiotemporal consistency. We also quantify uncertainty of the product by utilizing available ground measurements. For both consistency and uncertainty evaluation, we account for variations in biome type and temporal resolution. Our results indicate that the LAI/FPAR retrievals from VIIRS and MODIS are consistent at different spatial (i.e., global and site) and temporal (i.e., 8-day, seasonal and annual) scales. The estimate of mean discrepancy (-0.006 ± 0.013 for LAI and -0.002 ± 0.002 for FPAR) meets the stability requirement for long-term LAI/FPAR Earth System Data Records (ESDRs) from multi-sensors as suggested by the Global Climate Observing System (GCOS). It is noteworthy that the rate of retrievals from the radiative transfer-based main algorithm is also comparable between two sensors. However, a relatively larger discrepancy over tropical forests was observed due to reflectance saturation and an unexpected interannual variation of main algorithm success was noticed due to instability in input surface reflectances. The uncertainties/relative uncertainties of VIIRS and MODIS LAI (FPAR) products assessed through comparisons to ground measurements are estimated to be 0.60/42.2% (0.10/24.4%) and 0.55/39.3% (0.11/26%), respectively. Note that the validated LAI were only distributed in low domains (~2.5), resulting in large relative uncertainty. Therefore, more ground measurements are needed to achieve a more comprehensive evaluation result of product uncertainty. The results presented here generally imbue confidence in the consistency between VIIRS and MODIS LAI/FPAR products and the feasibility of generating long-term multi-sensor LAI/FPAR ESDRs time series. [ABSTRACT FROM AUTHOR]

Scale effect, which is caused by a combination of model nonlinearity and surface heterogeneity, has been of interest to the remote sensing community for decades. However, there is no current analysis of scale effect in the ground-based indirect measurement of leaf area index (LAI), where model nonlinearity and surface heterogeneity also exist. This paper examines the scale effect on the indirect measurement of LAI. We built multiscale data sets based on realistic scenes and field measurements. We then implemented five representative methods of indirect LAI measurement at scales (segment lengths) that range from meters to hundreds of meters. The results show varying degrees of deviation and fluctuation that exist in all five methods when the segment length is shorter than 20 m. The retrieved LAI from either Beer's law or the gap-size distribution method shows a decreasing trend with increasing segment lengths. The length at which the LAI values begin to stabilize is about a full period of row in row crops and 100 m in broadleaf or coniferous forests. The impacts of segment length on the finite-length averaging method, the combination of gap-size distribution and finite-length methods, and the path-length distribution method are relatively small. These three methods stabilize at the segment scale longer than 20 m in all scenes. We also find that computing the average LAI of all of the short segment lengths, which is commonly done, is not as good as merging these short segments into a longer one and computing the LAI value of the merged one. [ABSTRACT FROM AUTHOR]

Fractional vegetation cover (FVC) is one of the most important criteria for surface vegetation status. This criterion corresponds to the complement of gap fraction unity at the nadir direction and accounts for the amount of horizontal vegetation distribution. This study aims to directly validate the accuracy of FVC products over crops at coarse resolutions (1 km) by employing field measurements and high-resolution data. The study area was within an oasis in the Heihe Basin, Northwest China, where the Heihe Watershed Allied Telemetry Experimental Research was conducted. Reference FVC was generated through upscaling, which fitted field-measured data with spaceborne and airborne data to retrieve high-resolution FVC, and then high-resolution FVC was aggregated with a coarse scale. The fraction of green vegetation cover product (i.e., GEOV1 FVC) of SPOT/VEGETATION data taken during the GEOLAND2 project was compared with reference data. GEOV1 FVC was generally overestimated for crops in the study area compared with our estimates. Reference FVC exhibits a systematic uncertainty, and GEOV1 can overestimate FVC by up to 0.20. This finding indicates the necessity of reanalyzing and improving GEOV1 FVC over croplands. [ABSTRACT FROM PUBLISHER]

This paper presents a simple radiative transfer model based on spectral invariant properties (SIP). The canopy structure parameters, including the leaf angle distribution and multi-angular clumping index, are explicitly described in the SIP model. The SIP model has been evaluated on its bidirectional reflectance factor (BRF) in the angular space at the radiation transfer model intercomparison platform, and in the spectrum space by the PROSPECT+SAIL (PROSAIL) model. The simulations of BRF by SIP agreed well with the reference values in both the angular space and spectrum space, with a root-mean-square-error (RMSE) of 0.006. When compared with the widely-used Soil-Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model on fPAR, the RMSE was 0.006 and the R2 was 0.99, which shows a high accuracy. This study also suggests the newly proposed vegetation index, the near-infrared (NIR) reflectance of vegetation (NIRv), was a good linear approximation of the canopy structure parameter, the directional area scattering factor (DASF), with an R2 of 0.99. NIRv was not influenced much by the soil background contribution, but was sensitive to the leaf inclination angle. The sensitivity of NIRv to canopy structure and the robustness of NIRv to the soil background suggest NIRv is a promising index in future biophysical variable estimations with the support of the SIP model, especially for the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) observations near the hot spot directions. [ABSTRACT FROM AUTHOR]

With the continual development of deep learning, the image processing in Internet of Things is the key technology. Nevertheless, many deep learning methods cannot deal with the special needs of Internet of Things, for example, the Internet of vehicles and ships for the traffic haze image. Particularly, haze removal in the water area, because of the influence of water vapor, is more difficult than that in the ordinary scene. And the dehazing of water area has practical value in shipping and aerial photography. Sensible dehazing effect can even ensure the safety of navigation. In this paper, a compensation textures dehazing method is presented for water alike scene. The motivation of this paper comes from the following observations. Dark channel haze removal method has a very real dehazing effect for ordinary scenes. However, due to the principle of the dark channel method, this dehazing method has a large deviation in the water alike area. Therefore, based on the classical dark channel method, this paper proposes three innovations. First, a dynamic priority method is designed. This method can calculate the priority order of patches according to the characteristics of the processed subject. Second, a compensation textures method is designed, which can compensate the special area according to the proposed priority method. Third, a new haze removal method is designed, which can effectively remove the haze of water area according to the proposed compensation textures method. The results of visual and quality experiment show that proposed method has a state-of-the-art dehazing result in the water alike area. [ABSTRACT FROM AUTHOR]

Objective: Ribosome-associated protein Quality Control (RQC), comprising several well-organized processes and crucial factors, provides translational surveillance in cells by recognizing and degrading aberrant nascent proteins arising from ribosome stalling. Although rapid progress has been made in RQC, a bibliographic analysis of RQC-related literature studies for the overall trends and research progress, particularly the correlation of RQC with diseases, is absent., Methods: We obtained scientific outputs of global RQC between 1999 and 2022 by Web of Science Core Collection (WoSCC). CiteSpace, VOSviewer, and a package of R called bibliometrix were applied to explore the current research status, hotspots, and the relationship between RQC and diseases., Results: A total of 429 articles have been included in this study, and the number of published studies increases annually. The United States and Germany have been found to lead in this field. An analysis of the keywords has shown "initiation", "aggregation", "structure basis", "elongation", and "degradation" to be the emerging themes of RQC. Keywords co-occurrence has shown E3 ubiquitin ligase to bridge RQC and neurodegeneration., Conclusion: Through a summary of the current studies on RQC, our study has provided evolutionary trends and frontiers in this field by mathematical analysis and visualization, implying the potential of RQC in neurodegeneration and other diseases., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Introduction: Asthenoteratozoospermia is one of the most common causes of male infertility. Several genes have been identified as genetic causative factors, but there is a considerable genetic heterogeneity underlying asthenoteratozoospermia. In this study, we performed a genetic analysis of two brothers from a consanguineous Uighur family in China to identify gene mutations causative for asthenoteratozoospermia-related male infertility., Methods: Two related patients with asthenoteratozoospermia from a large consanguineous family were sequenced by whole-exome sequencing and Sanger sequencing to identify disease-causing genes. Scanning and transmission electron microscopy analysis revealed ultrastructural abnormalities of spermatozoa. Quantitative real-time PCR (qRT-PCR) analysis and immunofluorescence (IF) analysis were used to assess the expression of the mutant messenger RNA (mRNA) and protein., Results: A novel homozygous frameshift mutation (c.2823dupT, p.Val942Cysfs*21) in DNAH6 was identified in both affected individuals and was predicted to be pathogenic. Papanicolaou staining and electron microscopy revealed multiple morphological and ultrastructural abnormalities of affected spermatozoa. qRT-PCR and IF analysis showed abnormal expression of DNAH6 in affected sperm, probably due to premature termination code and decay of abnormal 3' untranslated region (UTR) region of mRNA. Furthermore, intracytoplasmic sperm injection could achieve successful fertilization in infertile men with DNAH6 mutations., Discussion: The novel frameshift mutation identified in DNAH6 may contribute to asthenoteratozoospermia. These findings expand the spectrum of genetic mutations and phenotypes associated with asthenoteratozoospermia and may be useful for genetic and reproductive counseling in male infertility., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Huang, Zeng, Liu, Zhang, Liang, Gao, Yan, Shi, Chen, Song and Huang.)

Introduction: Human zona pellucida (ZP) plays an important role in reproductive process. Several rare mutations in the encoding genes ( ZP1 , ZP2 , and ZP3 ) have been demonstrated to cause women infertility. Mutations in ZP2 have been reported to cause ZP defects or empty follicle syndrome. We aimed to identify pathogenic variants in an infertile woman with a thin zona pellucida (ZP) phenotype and investigated the effect of ZP defects on oocyte gene transcription., Methods: We performed whole-exome sequencing and Sanger sequencing of genes were performed for infertilite patients characterized by fertilization failure in routine in vitro fertilization (IVF). Immunofluorescence (IF) and intracytoplasmic sperm injection (ICSI) were used in the mutant oocytes. Single-cell RNA sequencing was used to investigate transcriptomes of the gene-edited ( Zp2 mut/mut ) rat model. Biological function enrichment analysis, quantitative real-time PCR (qRT-PCR), and IF were performed., Results: We identified a novel homozygous nonsense mutation of ZP2 (c.1924C > T, p.Arg642X) in a patient with non-consanguineous married parents. All oocytes showed a thin or no ZP under a light microscope and were fertilized after ICSI. The patient successfully conceived by receiving the only two embryos that developed to the blastocyst stage. The immunofluorescence staining showed an apparently abnormal form of the stopped oocytes. We further demonstrated a total of 374 differentially expressed genes (DEGs) in the transcriptome profiles of Zp2 mut/mut rats oocytes and highlighted the signal communication between oocytes and granulosa cells. The pathway enrichment results of DEGs showed that they were enriched in multiple signaling pathways, especially the transforming growth factor-β (TGF-β) signaling pathway in oocyte development. qRT-PCR, IF, and phosphorylation analysis showed significantly downregulated expressions of Acvr2b, Smad2, p38MAPK, and Bcl2 and increased cleaved-caspase 3 protein expression., Discussion: Our findings expanded the known mutational spectrum of ZP2 associated with thin ZP and natural fertilization failure. Disruption of the integrity of the ZP impaired the TGF-β signaling pathway between oocytes and surrounding granulosa cells, leading to increased apoptosis and decreased developmental potential of oocytes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zeng, Sun, Zhang, Wu, Wang, Quan, Song, Guo, Wang, Chen, Xiao and Huang.)

Net ecosystem productivity (NEP), which is considered an important indicator to measure the carbon source/sink size of ecosystems on a regional scale, has been widely studied in recent years. Since China's terrestrial NEP plays an important role in the global carbon cycle, it is of great significance to systematically examine its spatiotemporal pattern and driving factors. Based on China's terrestrial NEP products estimated by a data-driven model from 1981 to 2018, the spatial and temporal pattern of China's terrestrial NEP was analyzed, as well as its response to climate change. The results demonstrate that the NEP in China has shown a pattern of high value in the west and low value in the east over the past 40 years. NEP in China from 1981 to 2018 showed a significantly increasing trend, and the NEP change trend was quite different in two sub-periods (i.e., 1981-1999 and 2000-2018). The temporal and spatial changes of China's terrestrial NEP in the past 40 years were affected by both temperature and precipitation. However, the area affected by precipitation was larger. Our results provide a valuable reference for the carbon sequestration capacity of China's terrestrial ecosystem., Competing Interests: The authors declare no conflicts of interest.

The world has increasingly relied on protected areas (PAs) to rescue highly valued ecosystems from human activities, but whether PAs will fare well with bioinvasions remains unknown. By analyzing three decades of seven of the largest coastal PAs in China, including World Natural Heritage and/or Wetlands of International Importance sites, we show that, although PAs are achieving success in rescuing iconic wetlands and critical shorebird habitats from once widespread reclamation, this success is counteracted by escalating plant invasions. Plant invasions were not only more extensive in PAs than non-PA controls but also undermined PA performance by, without human intervention, irreversibly replacing expansive native wetlands (primarily mudflats) and precluding successional formation of new native marshes. Exotic species are invading PAs globally. This study across large spatiotemporal scales highlights that the consequences of bioinvasions for humanity’s major conservation tool may be more profound, far reaching, and critical for management than currently recognized.

Background: The Clubiona zilla -group is a relatively small species group, distributed exclusively in East Asia, with only three species clearly documented so far., New Information: Clubiona hooda Dong & Zhang, 2016, which was previously placed in the C. trivialis -group, is assigned to the C. zilla -group in the present paper. A new spider of the C. zilla -group from Jiugong Mountain in China is described under the name of C. jiugong sp. nov. Detailed descriptions and photographs of the new species are provided., (Zuxian Zeng, Da Wang, Wanjuan Song, Hao Yu, Yang Zhong.)

Soil respiration ( R s ) represents the largest flux of CO 2 from terrestrial ecosystems to the atmosphere, but its spatial and temporal changes as well as the driving forces are not well understood. We derived a product of annual global R s from 2000 to 2014 at 1 km by 1 km spatial resolution using remote sensing data and biome-specific statistical models. Different from the existing view that climate change dominated changes in R s , we showed that land-cover change played a more important role in regulating R s changes in temperate and boreal regions during 2000-2014. Significant changes in R s occurred more frequently in areas with significant changes in short vegetation cover (i.e., all vegetation shorter than 5 m in height) than in areas with significant climate change. These results contribute to our understanding of global R s patterns and highlight the importance of land-cover change in driving global and regional R s changes., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)