► Ten-year poplar plantation forest in Beijing of China was a strong carbon sink. ► Soil moisture suppressed carbon uptake more than respiration under drought. ► The timing and intensity of drought ...were the main causes of the variation in ecosystem CO2 fluxes.
Poplar plantations are widely used for timber production and ecological restoration in northern China, a region that experiences frequent droughts and water scarcity. An open-path eddy-covariance (EC) system was used to continuously measure the carbon, water, and energy fluxes in a poplar plantation during the growing season (i.e., April–October) over the period 2006–2008 in the Daxing District of Beijing, China. We examined the seasonal and inter-annual variability of gross ecosystem productivity (GEP), net ecosystem exchange (NEE), and ecosystem respiration (ER). Although annual total precipitation was the lowest in 2006, natural rainfall was amended by flood irrigation. In contrast, no supplementary water was provided during a severe drought in spring (i.e., April–June), 2007, resulting in a significant reduction in net ecosystem production (NEP=−NEE). This resulted from the combined effects of larger decrease in GEP than that in ER. Despite the drought – induced reduction in NEP, the plantation forest was a strong carbon sink accumulating 591±62, 641±71, and 929±75gCm−2year−1 for 2006, 2007, and 2008, respectively. The timing of the drought significantly affected the annual GEP. Severe drought during canopy development induced a lasting reduction in carbon exchange throughout the growing season, while the severe drought at the end of growing season did not significantly reduce carbon uptake. Additionally, irrigation reduced negative drought impacts on carbon sequestration. Overall, this fast growing poplar plantation is a strong carbon sink and is sensitive to the changes in environmental conditions.
Understanding the joint impact of anthropologic and climatic changes on ecosystem function and dynamics is among the frontiers in global environmental change studies. Carbon and water balances are ...especially crucial to the sustainable ecosystem and functional returns in sensitive regions such as the Mongolian Plateau. In this study, the significance of non-climatic component (NCC) on carbon and water use efficiency (CUE and WUE) is quantified among the ecosystem types on the Mongolian Plateau. We mapped the spatial gradients of carbon/water balance and delineated the hotspots of NCC-driven CUE and WUE for 2000-2013 using gross and net primary production (GPP and NPP) and evapotranspiration (ET) products derived from the MODIS databases. Significantly higher CUE and WUE values were found in Mongolia (MG) than in Inner Mongolia (IM) due to both climatic forcing (CF) and NCC. NCC was found to dominate the changes in CUE and WUE in the steppes on the plateau by over 16% and 22%, respectively, but with spatially uneven distributions. NCC-driven WUE values were much higher than those driven by CF. The hotspots for NCC-driven CUE did not overlap with those of WUE, with CUE hotspots concentrated in the east of MG and northeast of IM; WUE hotspots were found in the central and Khangai regions of MG and eastern regions of IM. The NCC-driven CUE area in MG was from population growth and the industrial shares in gross domestic product, while the NCC-driven WUE area was due to livestock growth in MG but driven by the growth of cultivated lands in IM. In sum, we conclude that NCC provoked substantial spatiotemporal changes on carbon and water use. CF and NCC effects on carbon and water balance varied in space, by ecosystem type, and between the two political entities.
Urban built-up area, one of the most important measures of an urban landscape, is an essential variable for understanding ecological and socioeconomic processes in urban systems. With an interest in ...urban development in transitional economies in Southeast Asia, we recognized a lack of high-to-medium resolution (<60 m) built-up information for countries in the region, including Vietnam, Laos, Cambodia and Myanmar. In this study, we combined multiple remote sensing data, including Landsat, DMSP/OLS night time light, MODIS NDVI data and other ancillary spatial data, to develop a 30-m resolution urban built-up map of 2010 for the above four countries. Following the trend analysis of the DMSP/OLS time series and the 2010 urban built-up extent, we also quantified the spatiotemporal dynamics of urban built-up areas from 1992 to 2010. Among the four countries, Vietnam had the highest proportion of urban built-up area (0.91%), followed by Myanmar (0.15%), Cambodia (0.12%) and Laos (0.09%). Vietnam was also the fastest in new built-up development (increased ~8.8-times during the 18-year study period), followed by Laos, Cambodia and Myanmar, which increased at 6.0-, 3.6- and 0.24-times, respectively.
Cannabis sativa, a dioecious plant that has been cultivated worldwide for thousands of years, is known for its secondary metabolites, especially cannabinoids, which possess several medicinal effects. ...In this study, we investigated the autopolyploidization effects on the biosynthesis and accumulation of these metabolites, transcriptomic and metabolomic analyses were performed to explore the gene expression and metabolic variations in industrial hemp autotetraploids and their diploid progenitors. Through these analyses, we obtained 1,663 differentially expressed metabolites and 1,103 differentially expressed genes. Integrative analysis revealed that phenylpropanoid and terpenoid biosynthesis were regulated by polyploidization. No substantial differences were found in the cannabidiol or tetrahydrocannabinol content between tetraploids and diploids. Following polyploidization, some transcription factors, including nine bHLH and eight MYB transcription factors, affected the metabolic biosynthesis as regulators. Additionally, several pivotal catalytic genes, such as flavonol synthase/flavanone 3-hydroxylase, related to the phenylpropanoid metabolic pathway, were identified as being modulated by polyploidization. This study enhances the overall understanding of the impact of autopolyploidization in C. sativa and the findings may encourage the application of polyploid breeding for increasing the content of important secondary metabolites in industrial hemp.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
As the two largest landlocked countries, Kazakhstan and Mongolia have similar biophysical conditions and socioeconomic roots in the former Soviet Union. Our objective is to investigate the direction, ...extent, and spatial variation of land cover change at three administrative levels over three decades (1990–2020). We selected three provinces from each country (Aktobe, Akmola, and Almaty province in Kazakhstan, and Arkhangai, Tov, and Dornod in Mongolia) to classify the land cover into forest, grassland, cropland, barren, and water. Altogether, 6964 Landsat images were used in pixel-based classification method with random forest model for image processing. Six thousand training data points (300 training points × 5 classes × 4 periods) for each province were collected for classification and change detection. Land cover changes at decadal and over the entire study period for five land cover classes were quantified at the country, provincial, and county level. High classification accuracy indicates localized land cover classification have an edge over the latest global land cover product and reveal fine differences in landscape composition. The vast steppe landscapes in these two countries are dominated by grasslands of 91.5% for Dornod in Mongolia and 74.7% for Aktobe in Kazakhstan during the 30-year study period. The most common land cover conversion was grassland to cropland. The cyclic land cover conversions between grassland and cropland reflect the impacts of the Soviet Union’s largest reclamation campaign of the 20th century in Kazakhstan and the Atar-3 agriculture re-development in Mongolia. Kazakhstan experienced a higher rate of land cover change over a larger extent of land area than Mongolia. The spatial distribution of land use intensity indicates that land use hotspots are largely influenced by policy and its shifts. Future research based on these large-scale land use and land cover changes should be focused the corresponding ecosystem and society functions.
The Mongolian Plateau hosts two different governments: the Mongolian People's Republic and the Inner Mongolia Autonomous Region, a provincial-level government of the People's Republic of China. The ...divergence between these governments has widened in the past century, mostly due to a series of institutional changes that generated different socioeconomic and demographic trajectories. Due to its high latitude and altitude, the Plateau has been highly sensitive to the rapid changes in global and regional climates that have altered the spatial and temporal distributions of energy and water. Based on a recent workshop to synthesize findings on the sustainability of the Plateau amidst socioeconomic and environmental change, we identify five critical issues facing the social-ecological systems (SES): (1) divergent and uncertain changes in social and ecological characteristics; (2) declining prevalence of nomadism; (3) consequences of rapid urbanization in transitional economies; (4) the unsustainability of large-scale afforestation efforts in the semi-arid and arid areas of Inner Mongolia; and (5) the role of institutional changes in shaping the SES on the Plateau. We emphasize that lessons learned in Inner Mongolia are valuable, but may not always apply to Mongolia. National land management policies and regulations have long-term effects on the sustainability of SES; climate change adaptation policies and practices must be tuned to local conditions and should be central to decision-making on natural resource management and socioeconomic development pathways.
The effects of land use policy and socioeconomic changes on urban landscape dynamics have been increasingly investigated around the world, but our knowledge of the underlying processes of these ...effects is still inadequate for sustainably managing urban ecosystems. Thus, the main goal of this study was to understand: (1) the changes in urban landscape, population, and economic conditions over a 36-year period, and (2) the coupled dynamics of land use policy, landscape structure, major demographic features, and three kinds of industries in one of the most dazzling modern cities of China—the Shenzhen special economic zone (SEZ). The landscape expansion index was used to explore the developed-land expansion under different land use policies while structural equation modeling (SEM) was used to analyze the relationship among three variables (Land Cover Change or LCC, Economy, and Population). We found that the urban expansion during the four periods (1973–1979, 1979–1995, 1995–2003, and 2003–2009) was not always at the expense of urban vegetation cover. The importance of each socioeconomic driver during the four periods was not consistent over time, with policy shifts as the primary driver. Our SEM showed that Economy played a more important role than Population in driving LCC in the Shenzhen SEZ. Meanwhile, the secondary and tertiary industries had a stronger influence than the primary industry; and the floating population had a greater effect than the registered permanent population.
•We upscaled AmeriFlux tower data to the conterminous United Stateswith and without considering the atmospheric CO2.•GPP/NEE difference between two models exhibits a great spatial and seasonal ...variability and an annual difference of 200gCm−2yr−1.•Air temperature played an important role in determining the atmospheric CO2 effects on carbon fluxes.•The simulation without considering CO2 effects failed to detect ecosystem responses to droughts in part of the US in 2006.
Quantitative understanding of regional gross primary productivity (GPP) and net ecosystem exchanges (NEE) and their responses to environmental changes are critical to quantifying the feedbacks of ecosystems to the global climate system. Numerous studies have used the eddy flux data to upscale the eddy covariance derived carbon fluxes from stand scales to regional and global scales. However, few studies incorporated atmospheric carbon dioxide (CO2) concentrations into those extrapolations. Here, we consider the effect of atmospheric CO2 using an artificial neural network (ANN) approach to upscale the AmeriFlux tower of NEE and the derived GPP to the conterminous United States. Two ANN models incorporating remote sensing variables at an 8-day time step were developed. One included CO2 as an explanatory variable and the other did not. The models were first trained, validated using eddy flux data, and then extrapolated to the region at a 0.05o×0.05o (latitude×longitude) resolution from 2001 to 2006. We found that both models performed well in simulating site-level carbon fluxes. The spatially-averaged annual GPP with and without considering the atmospheric CO2 were 789 and 788gCm−2yr−1, respectively (for NEE, the values were −112 and −109gCm−2yr−1, respectively). Model predictions were comparable with previous published results and MODIS GPP products. However, the difference in GPP between the two models exhibited a great spatial and seasonal variability, with an annual difference of 200gCm−2yr−1. Further analysis suggested that air temperature played an important role in determining the atmospheric CO2 effects on carbon fluxes. In addition, the simulation that did not consider atmospheric CO2 failed to detect ecosystem responses to droughts in part of the US in 2006. The study suggests that the spatially and temporally varied atmospheric CO2 concentrations should be factored into carbon quantification when scaling eddy flux data to a region.
We developed a water‐centric monthly scale simulation model (WaSSI‐C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand ...accounting model (WaSSI). The WaSSI‐C model was evaluated with basin‐scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE) estimates by multiple independent methods across 2103 eight‐digit Hydrologic Unit Code watersheds in the conterminous United States from 2001 to 2006. Our results indicate that WaSSI‐C captured the spatial and temporal variability and the effects of large droughts on key ecosystem fluxes. Our modeled mean (±standard deviation in space) ET (556 ± 228 mm yr−1) compared well to Moderate Resolution Imaging Spectroradiometer (MODIS) based (527 ± 251 mm yr−1) and watershed water balance based ET (571 ± 242 mm yr−1). Our mean annual GEP estimates (1362 ± 688 g C m−2 yr−1) compared well (R2 = 0.83) to estimates (1194 ± 649 g C m−2 yr−1) by eddy flux‐based EC‐MOD model, but both methods led significantly higher (25–30%) values than the standard MODIS product (904 ± 467 g C m−2 yr−1). Among the 18 water resource regions, the southeast ranked the highest in terms of its water yield and carbon sequestration capacity. When all ecosystems were considered, the mean NEE (−353 ± 298 g C m−2 yr−1) predicted by this study was 60% higher than EC‐MOD's estimate (−220 ± 225 g C m−2 yr−1) in absolute magnitude, suggesting overall high uncertainty in quantifying NEE at a large scale. Our water‐centric model offers a new tool for examining the trade‐offs between regional water and carbon resources under a changing environment.
Key Points
A monthly scale water‐centric model developed
Examined spatial and temporal dynamics of carbon and water fluxes
Growing season precipitation critical to GEP and NEE
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