Search

Analysis of the spatial and temporal variation patterns of surface evapotranspiration is important for understanding global climate change, promoting scientific deployment of regional water resources, and improving crop yield and water productivity. Based on Landsat 8 OIL_TIRS data and remote sensing image data of the lower Yangtze River urban cluster for the same period of 2016–2021, combined with soil and meteorological data of the study area, this paper constructed a multiple linear regression (MLR) model and an extreme learning machine (ELM) inversion model with evapotranspiration as the target and, based on the model inversion, quantitatively and qualitatively analyzed the spatial and temporal variability in surface evapotranspiration in the study area in the past six years. The results show that both models based on feature factors and spectral indices obtained a good inversion accuracy, with the fusion of feature factors effectively improving the inversion ability of the model for ET. The best model for ET in 2016, 2017, and 2021 was MLR, with an R2 greater than 0.8; the best model for ET in 2018–2019 was ELM, with an R2 of 0.83 and 0.62, respectively. The inter-annual ET in the study area showed a "double-peak" dynamic variation, with peaks in 2018 and 2020; the intra-annual ET showed a single-peak cycle, with peaks in July–August. Seasonal differences were obvious, and spatially high-ET areas were mainly found in rural areas north of the Yangtze River and central and western China where agricultural land is concentrated. The net solar radiation, soil heat flux, soil temperature and humidity, and fractional vegetation cover all had significant positive effects on ET, with correlation coefficients ranging from 0.39 to 0.94. This study can provide methodological and scientific support for the quantitative and qualitative estimation of regional ET. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) released by the receptive syconia of Ficus species play a vital role in attracting highly species-specific pollinating fig wasps. The components of VOCs vary considerably among Ficus species, but are generally dominated by a few common terpenoid compounds or specific proportions of several compounds. Terpene synthase (TPS) is the main source of specific and diverse terpenoids, but the evolution of the TPS gene family in Ficus and the potential functions of the TPS genes in species-specific pollination remain largely unelucidated. In this study, using transcriptomes of ostiole bracts of receptive male figs from 24 Ficus species collected from South China and Southeast Asia, we comprehensively scanned and investigated the composition and evolutionary characteristics of all TPS genes in all 24 species. We identified 248 TPS genes, including 33 orthologous genes and six singletons. Sequence and phylogenetic analysis showed that a majority of the 248 TPSs contained the DDXXD and DTE motifs, rather than the DXDD motif, and involved all subfamilies (TPS-a,b,c,e/f and g) known in other angiosperm genomes, suggesting a very diverse and complex composition of class I TPSs during the receptive phase. In addition, compared to TPS-a, which is generally the largest subfamily in some plants, the TPS-b subfamily contained the highest number of genes in Ficus species. Expression profile comparison showed that the distribution and expression levels of different TPSs among different Ficus species differed considerably, but a few TPS genes were common across most species. Positive selection analysis showed that the Ficus TPS genes were mainly under purifying selection, with only four genes having positive selection signals and two genes having positive selection sites, and two genes having relatively fast-evolving rates. The present study demonstrates the basic evolutionary characteristics of TPS genes in Ficus and reveals the roles of TPSs in shaping the diversity and specificity of the fig–fig wasp symbiotic relationship. [ABSTRACT FROM AUTHOR]