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Quantifying the effects of climate change and human activities on runoff changes is the focus of climate change and hydrological research. This paper presents an integrated method employing the Budyko-based Fu model, hydrological modeling, and climate elasticity approaches to separate the effects of the two driving factors on surface runoff in the Luan River basin, China. The Budyko-based Fu model and the double mass curve method are used to analyze runoff changes during the period 1958~2009. Then two types of hydrological models (the distributed Soil and Water Assessment Tool model and the lumped SIMHYD model) and seven climate elasticity methods (including a nonparametric method and six Budyko-based methods) are applied to estimate the contributions of climate change and human activities to runoff change. The results show that all quantification methods are effective, and the results obtained by the nine methods are generally consistent. During the study period, the effects of climate change on runoff change accounted for 28.3~46.8% while those of human activities contributed with 53.2~71.7%, indicating that both factors have significant effects on the runoff decline in the basin, and that the effects of human activities are relatively stronger than those of climate change.

Warmer temperatures significantly influence crop yields, which are a critical determinant of food supply and human well-being. In this study, a probabilistic approach based on bivariate copula models was used to investigate the dependence (described by joint distribution) between crop yield and growing season temperature (TGS) in the major producing provinces of China for three staple crops (i.e., rice, wheat, and maize). Based on the outputs of 12 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under Shared Socioeconomic Pathway 5–8.5, the probability of yield reduction under 1.5 °C and 2 °C global warming was estimated, which has great implications for agricultural risk management. Results showed that yield response to TGS varied with crop and region, with the most vulnerable being rice in Sichuan, wheat in Sichuan and Gansu, and maize in Shandong, Liaoning, Jilin, Nei Mongol, Shanxi, and Hebei. Among the selected five copulas, Archimedean/elliptical copulas were more suitable to describe the joint distribution between TGS and yield in most rice-/maize-producing provinces. The probability of yield reduction was greater in vulnerable provinces than in non-vulnerable provinces, with maize facing a higher risk of warming-driven yield loss than rice and wheat. Compared to the 1.5 °C global warming, an additional 0.5 °C warming would increase the yield loss risk in vulnerable provinces by 2–17%, 1–16%, and 3–17% for rice, wheat, and maize, respectively. The copula-based model proved to be an effective tool to provide probabilistic estimates of yield reduction due to warming and can be applied to other crops and regions. The results of this study demonstrated the importance of keeping global warming within 1.5 °C to mitigate the yield loss risk and optimize agricultural decision-making in vulnerable regions.

Myeloid cell leukemia-1 (Mcl-1) plays an important role in various cell survival pathways. Some studies indicated that the expression of Mcl-1 was upregulated in host cells during infection with the virulent Mycobacterium tuberculosis strain, H37Rv. The present study was designed to investigate the effect of inhibiting Mcl-1 expression both in vivo and in vitro on apoptosis of host macrophages infected with M. tuberculosis using a small hairpin (sh)RNA. Mcl-1 expression was detected by the real time-polymerase chain reaction, western blotting, and immunohistochemistry. Flow cytometry and transmission electron microscopy were used to measure host macrophage apoptosis. We found elevated Mcl-1 levels in host macrophages infected with M. tuberculosis H37Rv. The expression of Mcl-1 was downregulated efficiently in H37Rv-infected host macrophages using shRNA. Knockdown of Mcl-1 enhanced the extent of apoptosis in H37Rv-infected host macrophages significantly. The increased apoptosis correlated with a decrease in M. tuberculosis colony forming units recovered from H37Rv-infected cells that were treated with Mcl-1-shRNA. Reducing Mcl-1 accumulation by shRNA also reduced accumulation of the anti-apoptotic gene, Bcl-2, and increased expression of the pro-apoptotic gene, Bax, in H37Rv-infected host macrophages. Our results showed that specific knockdown of Mcl-1 expression increased apoptosis of host macrophages significantly and decreased the intracellular survival of a virulent strain of M. tuberculosis. These data indicate that interference with Mcl-1 expression may provide a new avenue for tuberculosis therapy.