Trends of land surface phenology derived from passive microwave and optical remote sensing systems and associated drivers across the dry tropics 1992–2012

Changes in vegetation phenology are among the most sensitive biological responses to global change. While land surface phenological changes in the Northern Hemisphere have been extensively studied from the widely used long-term AVHRR (Advanced Very High Resolution Radiometer) data, current knowledge on land surface phenological trends and the associated drivers remains uncertain for the tropics. This uncertainty is partly due to the well-known challenges of applying satellite-derived vegetation indices from the optical domain in areas prone to frequent cloud cover. The long-term vegetation optical depth (VOD) product from satellite passive microwaves features less sensitivity to atmospheric perturbations and measures different vegetation traits and functioning as compared to optical sensors. VOD thereby provides an independent and complementary data source for studying land surface phenology and here we performed a combined analysis of the VOD and AVHRR NDVI (Normalized Difference Vegetation Index) datasets for the dry tropics (25°N to 25°S) during 1992–2012. We find a general delay in the VOD derived start of season (SOS) and end of season (EOS) as compared to NDVI derived metrics, however with clear differences among land cover and continents. Pixels characterized by significant phenological trends (P < 0.05) account for up to 20% of the study area for each phenological metric of NDVI and VOD, with large spatial difference between the two sensor systems. About 50% of the pixels studied show significant phenological changes in either VOD or NDVI metrics. Drivers of phenological changes were assessed for pixels of high agreement between VOD and NDVI phenological metrics (serving as a means of reducing noise-related uncertainty). We find rainfall variability and woody vegetation change to be the main forcing variables of phenological trends for most of the dry tropical biomes, while fire events and land cover change are recognized as second-order drivers. Taken together, our study provides new insights on land surface phenological changes and the associated drivers in the dry tropics, as based on the complementary long-term data sources of VOD and NDVI, sensitive to changes in vegetation water content and greenness, respectively

Multiple genetic analyses to investigate the polymorphisms of Chinese Mongolian population with an efficient short tandem repeat panel

Aim To determine allele frequencies and forensic statistics of 22 autosomal short tandem repeat loci in Chinese Mongolian population. Methods Blood specimens were collected from 134 unrelated healthy Mongolian individuals, and 22 short tandem repeat loci were co-amplified and genotyped. Allele frequencies and forensic parameters were calculated, and population genetic differences were analyzed among Mongolian population and other eight Chinese populations: Northern Han, Guangdong Han, Chengdu Han, Xinjiang Hui, Xinjiang Uygur, Hainan Li, Qinghai Tibetan, and Hainan Han. Results All the loci were in the Hardy-Weinberg equilibrium, and after Bonferroni correction there was no linkage disequilibrium between them. The allele frequencies of these 22 loci were between 0.0037 and 0.3657. This panel had high discriminating power and genetic polymorphism in the Mongolian population, with combined power of discrimination of 0.999999999999999999999999998399 and combined probability of exclusion of 0.9999999999566925. Structure analysis showed no evidence that these nine Chinese populations had different component distribution. However, genetic distance analysis showed significant differences among them (P < 0.05). Conclusion The combined application of these 22 loci could be useful for forensic purposes in the Mongolian population. Mongolian population had smaller genetic distances from the populations in northern China (Northern Han, Xinjiang Uygur, and Xinjiang Hui) than from the populations in Hainan province (Hainan Han and Hainan Li populations)

Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph

Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in both training and inference. In contrast to the previous studies, we propose a fast and lightweight model named as PTPCG. In our model, we design a novel strategy for event argument combination together with a non-autoregressive decoding algorithm via pruned complete graphs, which are constructed under the guidance of the automatically selected pseudo triggers. Compared to the previous systems, our system achieves competitive results with 19.8\% of parameters and much lower resource consumption, taking only 3.8\% GPU hours for training and up to 8.5 times faster for inference. Besides, our model shows superior compatibility for the datasets with (or without) triggers and the pseudo triggers can be the supplements for annotated triggers to make further improvements. Codes are available at https://github.com/Spico197/DocEE .Comment: Accepted to IJCAI'202

Revisiting the coupling between NDVI trends and cropland changes in the Sahel drylands:a case study in western Niger

The impact of human activities via land use/cover changes on NDVI trends is critical for an improved understanding of satellite-observed changes in vegetation productivity in drylands. The dominance of positive NDVI trends in the Sahel, the so-called re-greening, is sometimes interpreted as a combined effect of an increase in rainfall and cropland expansion or agricultural intensification. Yet, the impact of changes in land use has yet to be thoroughly tested and supported by empirical evidence. At present, no studies have considered the importance of the different seasonal NDVI signals of cropped and fallowed fields when interpreting NDVI trends, as both field types are commonly merged into a single ‘cropland’ class. We make use of the distinctly different phenology of cropped and fallowed fields and use seasonal NDVI curves to separate these two field types. A fuzzy classifier is applied to quantify cropped and fallowed areas in a case study region in the southern Sahel (Fakara, Niger) on a yearly basis between 2000 and 2014. We find that fallowed fields have a consistently higher NDVI than unmanured cropped fields and by using two seasonal NDVI metrics (the amplitude and the decreasing rate) derived from the MODIS time series, a clear separation between classes of fields is achieved (r = 0.77). The fuzzy classifier can compute the percentage of a pixel (250 m) under active cultivation, thereby alleviating the problem of small field sizes in the region. We find a predominant decrease in NDVI over the period of analysis associated with an increased area of cropped fields at the expense of fallowed fields. Our findings couple cropping abandonment (more frequent fallow years) with positive NDVI trends and an increase in the percentage of the cropped area (fallow period shortening) with negative trends. These findings profoundly impact our understanding of greening and browning trends in agrarian Sahelian drylands and in other drylands of developing countries characterized by limited use of fertilizers

Mirror: A Universal Framework for Various Information Extraction Tasks

Sharing knowledge between information extraction tasks has always been a challenge due to the diverse data formats and task variations. Meanwhile, this divergence leads to information waste and increases difficulties in building complex applications in real scenarios. Recent studies often formulate IE tasks as a triplet extraction problem. However, such a paradigm does not support multi-span and n-ary extraction, leading to weak versatility. To this end, we reorganize IE problems into unified multi-slot tuples and propose a universal framework for various IE tasks, namely Mirror. Specifically, we recast existing IE tasks as a multi-span cyclic graph extraction problem and devise a non-autoregressive graph decoding algorithm to extract all spans in a single step. It is worth noting that this graph structure is incredibly versatile, and it supports not only complex IE tasks, but also machine reading comprehension and classification tasks. We manually construct a corpus containing 57 datasets for model pretraining, and conduct experiments on 30 datasets across 8 downstream tasks. The experimental results demonstrate that our model has decent compatibility and outperforms or reaches competitive performance with SOTA systems under few-shot and zero-shot settings. The code, model weights, and pretraining corpus are available at https://github.com/Spico197/Mirror .Comment: Accepted to EMNLP23 main conferenc

Population Genetic Diversity and Clustering Analysis for Chinese Dongxiang Group With 30 Autosomal InDel Loci Simultaneously Analyzed

In comparison with the most preferred genetic marker utilized in forensic science (STR), insertion/deletion analysis possesses further benefits, like absence of stutter peak, low mutation rate, and enabling mixed stain analysis. At present, a total of 169 unrelated healthy Dongxiang individuals dwelling in Dongxiang Autonomous county of Gansu province were recruited in our study to appraise the forensic usefulness of the panel including 30 autosomal diallelic genetic markers. The insertion allele frequencies were in the range of 0.1598 at HLD 111 to 0.8550 at HLD 118. The cumulative match of probability and the combined probability of exclusion were estimated based on independence of pairwise loci, with the values of 3.96 × 10-11 and 0.9886, respectively, which showed tremendous potential of this panel to be qualified for forensic personal identification in Chinese Dongxiang group. And it could also be used as a complementary tool for forensic parentage testing when combined with standard STR genetic markers. Furthermore, calculation of the DA distance and Fst values of pairwise populations, phylogenetic reconstruction, multidimensional scaling analysis, structure clustering analysis were also conducted to probe the genetic relationships between Dongxiang group and the other 30 reference populations. Results demonstrated that Dongxiang ethnic group might be genetically closer related with most Chinese populations involved in our study, especially Tibet groups, Xibe group, and several Han populations

Forensic characteristics and population genetics of Chinese Kazakh ethnic minority with an efficient STR panel

On the purpose of enhancing the forensic efficiency of CODIS STR loci, new STR loci have been gradually discovered and developed into some commercial multiplex systems. Recently, 22 STR loci including 18 non-CODIS STR loci and four CODIS STR loci were investigated in 501 unrelated healthy individuals of Kazakh ethnic group. Seven to 20 alleles at the different loci were identified and altogether 276 alleles for 22 selected loci were detected with the corresponding allelic frequencies ranging from 0.0010 to 0.3623. No significant deviation was observed from the Hardy–Weinberg equilibrium test for any of the 22 STRs. The value of cumulative power of discrimination in Kazakh group was 1-1.00E−28. Analyses of population differentiations and genetic distances between Kazakh and other Chinese groups presented that the Kazakh group with the Uygur group. These 22 STR loci evenly distributed on 22 different autosomal chromosomes were characterized by high genetic diversities and therefore could be utilized in the forensic cases to further increase the discrimination performance

Global assessment of sand and dust storms

The specific objectives of the assessment are to: 1) Synthesise and highlight the environmental and socio-economic causes and impacts of SDS, as well as available technical measures for their mitigation, at the local, regional and global levels; 2) Show how the mitigation of SDS can yield multiple sustainable development benefits; 3) Synthesize information on current policy responses for mitigating SDS and 4) Present options for an improved strategy for mitigating SDS at the local, regional and global levels, building on existing institutions and agreements

Mitigation of severe urban haze pollution by a precision air pollution control approach

Severe and persistent haze pollution involving fine particulate matter (PM_(2.5)) concentrations reaching unprecedentedly high levels across many cities in China poses a serious threat to human health. Although mandatory temporary cessation of most urban and surrounding emission sources is an effective, but costly, short-term measure to abate air pollution, development of long-term crisis response measures remains a challenge, especially for curbing severe urban haze events on a regular basis. Here we introduce and evaluate a novel precision air pollution control approach (PAPCA) to mitigate severe urban haze events. The approach involves combining predictions of high PM_(2.5) concentrations, with a hybrid trajectory-receptor model and a comprehensive 3-D atmospheric model, to pinpoint the origins of emissions leading to such events and to optimize emission controls. Results of the PAPCA application to five severe haze episodes in major urban areas in China suggest that this strategy has the potential to significantly mitigate severe urban haze by decreasing PM_(2.5) peak concentrations by more than 60% from above 300 μg m^(−3) to below 100 μg m^(−3), while requiring ~30% to 70% less emission controls as compared to complete emission reductions. The PAPCA strategy has the potential to tackle effectively severe urban haze pollution events with economic efficiency