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The Shule River Basin (SRB) is a typical arid area in northwest China with a fragile ecology. Understanding vegetation dynamics and its response to climate change and human activities provides essential ecological and environmental resource management information. This study extracted fractional vegetation coverage (FVC) data from 2000 to 2019 using the Google Earth Engine platform and Landsat satellite images, employing trend analysis and other methods to examine spatiotemporal changes in vegetation in the SRB. Additionally, we used partial correlation and residual analyses to explore the response of FVC to climate change and human activities. The main results were: (1) The regional average FVC in the SRB showed a significant upward trend from 2000 to 2019, increasing by 1.3 × 10−3 a–1. The area within 1 km of roads experienced a higher increase of 3 × 10−3 a–1, while the roadless areas experienced a lower increase of 1.1 × 10−3 a–1. The FVC spatial heterogeneity in the SRB is significant. (2) Partial correlation analysis shows that the FVC correlates positively with precipitation and surface water area, with correlation coefficients of 0.575 and 0.744, respectively. A weak negative correlation exists between the FVC and land surface temperature (LST). FVC changes are more influenced by precipitation than by LST. (3) The contributions of climate change to vegetation recovery are increasing. Human activities, particularly agricultural practices, infrastructure development, and the conversion of farmland to grassland, significantly influence vegetation changes in densely populated areas. (4) The area changes of different land types are closely related to climate factors and human activities. Increased construction, agricultural activity, and converting farmland back to grassland have led to an increase in the area proportions of "impervious surfaces", "cropland", and "grassland". Climate changes, such as increased rainfall, have resulted in larger areas of "wetlands" and "sparse vegetation". These results provide valuable information for ecosystem restoration and environmental protection in the SRB. [ABSTRACT FROM AUTHOR]

The nitrogen isotopic composition (15N/14N ratio, or δ15N) of enameloid‐bound organic matter (δ15NEB) in shark teeth was recently developed to investigate the biogeochemistry and trophic structures (i.e., food webs) of the ancient ocean. Using δ15NEB, we present the first nitrogen isotopic evidence for trophic differences between shark taxa from a single fossil locality. We analyze the teeth of four taxa (Meristodonoides, Ptychodus, Scapanorhynchus, and Squalicorax) from the Late Cretaceous (83–84 Ma) Trussells Creek site in Alabama, USA, and compare the N isotopic findings with predictions from tooth morphology, the traditional method for inferring shark paleo‐diets. Our δ15NEB data indicate two distinct trophic groups, with averages separated by 6.1 ± 2.1‰. The lower group consists of Meristodonoides and Ptychodus, and the higher group consists of Scapanorhynchus and Squalicorax (i.e., lamniforms). This δ15NEB difference indicates a 1.5 ± 0.5 trophic‐level separation between the two groups, a finding that is in line with paleontological predictions of a higher trophic level for these lamniforms over Meristodonoides and Ptychodus. However, the δ15NEB of Meristodonoides is lower than suggested by tooth morphology, although consistent with mechanical tests suggesting that higher trophic‐level bony fishes were not a major component of their diet. Further, δ15NEB indicates that the two sampled lamniform taxa fed at similar trophic levels despite their different inferred tooth functions. These two findings suggest that tooth morphology alone may not always be a sufficient indicator of dietary niche. The large trophic separation revealed by the δ15NEB offset leaves open the possibility that higher trophic‐level lamniforms, such as those measured here, preyed upon smaller, lower trophic‐level sharks like Meristodonoides. [ABSTRACT FROM AUTHOR]

Studying the response and recovery of marine microbial communities during mass extinction events provides an evolutionary window through which to understand the adaptation and resilience of the marine ecosystem in the face of significant environmental disturbances. The goal of this study is to reconstruct changes in the marine microbial community structure through the Late Devonian Frasnian‐Famennian (F‐F) transition. We performed a multiproxy investigation on a drill core of the Upper Devonian New Albany Shale from the Illinois Basin (western Kentucky, USA). Aryl isoprenoids show green sulfur bacteria expansion and associated photic zone euxinia (PZE) enhancement during the F‐F interval. These changes can be attributed to augmented terrigenous influxes, as recorded collectively by the long‐chain/short‐chain normal alkane ratio, carbon preference index, C30 moretane/C30 hopane, and diahopane index. Hopane/sterane ratios reveal a more pronounced dominance of eukaryotic over prokaryotic production during the mass extinction interval. Sterane distributions indicate that the microalgal community was primarily composed of green algae clades, and their dominance became more pronounced during the F‐F interval and continued to rise in the subsequent periods. The 2α‐methylhopane index values do not show an evident shift during the mass extinction interval, whereas the 3β‐methylhopane index values record a greater abundance of methanotrophic bacteria during the extinction interval, suggesting enhanced methane cycling due to intensified oxygen depletion. Overall, the Illinois Basin during the F‐F extinction experienced heightened algal productivity due to intensified terrigenous influxes, exhibiting similarities to contemporary coastal oceans that are currently undergoing globalized cultural eutrophication. The observed microbial community shifts associated with the F‐F environmental disturbances were largely restricted to the extinction interval, which suggests a relatively stable, resilient marine microbial ecosystem during the Late Devonian. [ABSTRACT FROM AUTHOR]

Mapping river water quality at a basin scale with satellite image data represents a tremendous technical challenge, since traditional empirical remote sensing models calibrated for specific reaches of a river cannot be applied to all the rivers and streams in the basin with an adequate prediction accuracy. In this study, we developed a multi-predictor ensemble model to map and assess water turbidity for all rivers and streams in the Tombigbee River Basin with Landsat 8 multispectral images. Coincident with Landsat 8 satellite overpass on 2 May 2019, we conducted boat-based water quality data collection in the confluence area of Tombigbee River and Black Warrior River near the city of Demopolis, Alabama. Based on the coincident satellite image and field water samples, we calibrated and evaluated the multi-predictor ensemble model, which consists four component empirical models. Our evaluations suggest that the multi-predictor ensemble model can improve turbidity estimation accuracy by 79% in comparison with the best traditional empirical model. More importantly, our multi-predictor ensemble model can be applied to other river and stream reaches across three major sub-basins with a high prediction accuracy. With the multi-predictor ensemble model, we derived a turbidity map for all rivers and streams with a width greater than 90 m in the basin, by processing three Landsat 8 image scenes. This basin-wide turbidity map indicates that the turbidity of rivers and streams exhibits longitudinal gradients and distinct spatial trends within the basin, which were related to the basin land cover/land use, hydrometeorological condition, and the spatial distribution of dams. Owing to its strong spatial transferability and high prediction accuracy, the ensemble model, in conjunction with synoptic multispectral satellite image data, is recommended as an effective and efficient tool for mapping and monitoring river and stream water quality at a large basin or regional scale. [ABSTRACT FROM AUTHOR]