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International audience; Tropical Asia has shown a strong greening trend in recent years. However, detailed knowledge about changes in carbon stocks remain uncertain as only few studies have used remotely sensed vegetation products for monitoring spatial and temporal changes of aboveground live biomass carbon (AGC) in that region. This study aims at evaluating optical- and microwave-based vegetation proxies (i.e., LAI, percent tree cover (PTC), L−/X-/C-band vegetation optical depths (VOD)) for understanding the spatio-temporal variations of tropical Asian AGC between 2013 and 2019. Our results indicated that the spatial distributions of L-VOD and PTC were highly spatially correlated with four benchmark AGC maps used for comparison (R > 0.79 and R > 0.75, respectively). By employing L-VOD as the reference data in assessing AGC dynamics, the X-/C-VOD showed advantages in capturing AGC changes for low-medium (20–40 Mg C/ha) carbon density vegetation, respectively, while other vegetation proxies showed limited capabilities. All proxies presented limitations in tracking AGC dynamics at high AGC density (> 60 Mg C/ha). Tropical Asian AGC stocks estimated using the L-VOD product indicated that tropical Asia accumulated carbon in biomass at a rate of +44+39+53 Tg C/yr between 2013 and 2019. This small sink is dominated by non-forest biomes (65.9%). The non-forest regions in southern India, southwest China, and southern Vietnam and southwest China showed a continuous AGC increase while forests in northern Laos, Malaysia, and central Indonesia experienced continuous decreases between 2013 and 2019 caused by deforestation.

Plant nuclear factor-Y (NF-Y) transcription factors (TFs) are key regulators of growth and stress resistance. However, the role of NF-Y TFs in poplar in response to biotic stress is still unclear. In this study, we cloned 26 PdbNF-Y encoding genes in the hybrid poplar P. davidiana × P. bollena, including 12 PdbNF-YAs, six PdbNF-YBs, and eight PdbNF-YCs. Their physical and chemical parameters, conserved domains, and phylogeny were subsequently analyzed. The protein–protein interaction (PPI) network showed that the three PdbNF-Y subunits may interact with NF-Y proteins belonging to two other subfamilies and other TFs. Tissue expression analysis revealed that PdbNF-Ys exhibited three distinct expression patterns in three tissues. Cis-elements related to stress-responsiveness were found in the promoters of PdbNF-Ys, and most PdbNF-Ys were shown to be differentially expressed under Alternaria alternata and hormone treatments. Compared with the PdbNF-YB and PdbNF-YC subfamilies, more PdbNF-YAs were significantly induced under the two treatments. Moreover, loss- and gain-of-function analyses showed that PdbNF-YA11 plays a positive role in poplar resistance to A. alternata. Additionally, RT‒qPCR analyses showed that overexpression and silencing PdbNF-YA11 altered the transcript levels of JA-related genes, including LOX, AOS, AOC, COI, JAZ, ORCA, and MYC, suggesting that PdbNF-YA11-mediated disease resistance is related to activation of the JA pathway. Our findings will contribute to functional analysis of NF-Y genes in woody plants, especially their roles in response to biotic stress.

Vegetation abundance is a critical indicator for measuring the status of vegetation.It is also important for revealing the rules of spatial change and evaluating the eco-environment of wetland.In this paper,vegetation abundance is estimated through a Linear Spectral Mixture Model(LSMM) using Landsat Thematic Mapper(TM) data within the Wild Duck Lake Wetland,a typical freshwater wetland in North China.Considering the biodiversity of wetland,it is necessary to select enough endmembers to characterize the spectral variability of features.However,a maximum of four endmembers is usually used in spectral mixture analysis when using Landsat TM data due to the high correlation coefficients among the three visible bands.Thus,the Normalized Difference Vegetation Index(NDVI),a widely used vegetation index,is included along with the six reflective bands of Landsat TM image,which extended the dimensionality of the TM data and allowed the use of five endmembers.After performed the Minimum Noise Fraction(MNF) transformation and Pixel Purity Index(PPI) algorithm,five endmembers are selected including Terrestrial plants,Aquatic plants,High albedo,Low albedo and Bare soil using n-Dimensional Visualizer Tool of ENVI software.At the same time,a four-endmember model which consists Plants,High albedo,Low albedo and Bare soil was established using the six reflective bands of Landsat TM data.For both four-and five-endmember model,we used a fully constrained LSMM algorithm to obtain the vegetation abundance of the study area.We modified our result using the pure water information of Wild Duck Lake Wetland,which was obtained by using NDVI and Normalized Difference Water Index(NDWI).The accuracy of vegetation abundance is validated by WorldView-2 multispectral image with a 1.8 meter spatial resolution through randomly selected 60 samples.The result showed that although the vegetation abundance extracted by four-and five-endmember model share almost the same spatial distribution,their values vary much from each other.Generally,the five-endmember model results a much higher value than the four-endmember model and it can reflect the vegetation abundance of aquatic plants better than the other.After the analysis of relationship between predicted and inspection values of both four-and five-endmember models,we found that the correlation coefficients are 0.8671 and 0.9023,respectively.Additionally,the Root Mean Square Error(RMSE) clearly showed that the five-endmember model can achieve a much better result than the other model: the former is 0.0939 and the latter is 0.1771.Our results suggest that it is feasible to improve the number of endmembers by extending the dimension of remote sensing image.By using NDVI as an additional data dimension along with the reflective bands of Landsat TM data,a five-endmember model can estimate vegetation abundance of Wild Duck Lake wetland better due to the inclusion of the fifth endmember.Moreover,four endmembers may be inadequate to spectrally characterize the heterogeneous landscapes of wetland.The use of five endmembers may further improve the representation of the spectral variability of land-cover types within the study area and thus potentially improve the accuracy for estimating vegetation abundance of wetlands.

Quantitative estimation of vegetation water content with remote sensing technique is of great significance for vegetation physiological status and growth trend monitoring. It also provides a theoretical foundation for actual application of vegetation water content diagnosis using remote sensing images in Wild Duck Lake wetland. In this paper the NDVIs and SRs calculated from simulation WorldVeiw-2 curves can be used to model and predict canopy water content of typical emerged plant. The NDVIs and SRs involving the additional spectral bands of WorldView-2, such as the red-edge and near infrared regions of the electromagnetic spectrum, improve the prediction accuracy compared with the traditional NDVIs and SRs.