Spatiotemporal variations of water use efficiency and its driving factors in Inner Mongolia from 2001 to 2020

Water use efficiency (WUE) is an important variable to explore coupled relationships in carbon and water cycles. In this study, we first compared the spatial variations of annual gross primary productivity (GPP) and evapotranspiration (ET) using four GPP and ET products. Second, we selected the products closest to the flux towers data to estimate WUE. Finally, we quantitatively analyzed the impact of climate change and soil water content on WUE. The results showed that: (1) Four GPP and ET products provided good performance, with GOSIF-GPP and FLDAS-ET exhibiting a higher correlation and the smallest errors with the flux tower data. (2) The spatial pattern of WUE is consistent with that of GPP and ET, gradually decreasing from the northeast to the southwest. Higher WUE values appeared in the northeast forest ecosystem, and lower WUE values occurred in the western Gobi Desert, with a value of 0.28 gC m^?2 mm^?1. The GPP and ET products showed an increasing trend, while WUE showed a decreasing trend (55.15%) from 2001 to 2020. (3) The spatial relationship between WUE and driving factors reveal the variations in WUE of Inner Mongolia are mainly affected by soil moisture between 0 and 10 cm (SM0-10cm), vapor pressure deficit (VPD), and precipitation, respectively. (4) In arid regions, VPD and precipitation exhibit a major influence on WUE. An increase in VPD and precipitation has a negative and positive effect on WUE, with threshold values of approximately 0.36 kPa and 426 mm, respectively. (5) In humid regions, SM0-10cm, VPD, SM10-40cm, and SM40-100cm exert a significant impact on WUE, especially SM0-10cm, and weakens with increasing soil depths, these differences may be related to physiological structure and living characteristics of vegetation types in different climate regimes. Our results emphasize the importance of VPD and soil moisture in regional variability in WUE.     

Elevation,slope aspect and integrated nutrient management effects on crop productivity and soil quality in North-west Himalayas,India

On farm bio-resource recycling has been given greater emphasis with the introduction of conservation agriculture specifically withclimate change scenarios in the mid-hills of the north-west Himalaya region（NWHR）. Under this changing scenario, elevation, slope aspect and integrated nutrient management（INM） may affect significantly soil quality and crop productivity. A study was conducted during 2009-2010 to 2010-2011 at the Ashti watershed of NWHR in a rainfed condition to examine the influence of elevation, slope aspect and integrated nutrient management（INM） on soil resource and crop productivity. Two years of farm demonstration trials indicated that crop productivity and soil quality is significantly affected by elevation, slope aspect and INM. Results showed that wheat equivalent yield（WEY） of improved technology increased crop productivity by -20%-37% compared to the conventional system. Intercropping of maize with cowpea and soybean enhanced yield by another 8%-17%. North aspect and higher elevation increased crop productivity by 15%-25% compared to south aspect and low elevation（except paddy）. Intercropping of maize with cowpea and soybean enhanced yield by another 8%-15%. Irrespective of slope, elevation and cropping system, the WEY increased by -30% in this region due to INMtechnology. The influence of elevation, slope aspect and INM significantly affected soil resources（SQI） and soil carbon change（SCC）. SCC is significantly correlated with SQI for conventional（R2 = 0.65＊）, INM technology（R2 = 0.81＊） and for both technologies（R2 = 0.73＊）. It is recommended that at higher elevation.（except for paddy soils） with a north facing slope, INM is recommended for higher crop productivity; conservation of soil resources is recommended for the mid hills of NWHR; and single values of SCC are appropriate as a SQI for this region.     

1961–2005年中国陆地生态系统净初级生产力模拟（英文）

Net primary productivity(NPP) is the most important index that represents the structure and function of the ecosystem.NPP can be simulated by dynamic global vegetation models(DGVM),which are designed to represent vegetation dynamics relative to environmental change.This study simulated the NPP of China's ecosystems based on the DGVM Integrated Biosphere Simulator(IBIS) with data on climate,soil,and topography.The applicability of IBIS in the NPP simulation of China's terrestrial ecosystems was verified first.Comparison with other relevant studies indicates that the range and mean value of simulations are generally within the limits of observations;the overall pattern and total annual NPP are close to the simulations conducted with other models.The simulations are also close to the NPP estimations based on remote sensing.Validation proved that IBIS can be utilized in the large-scale simulation of NPP in China's natural ecosystem.We then simulated NPP with climate change data from 1961 to 2005,when warming was particularly striking.The following are the results of the simulation.(1) Total NPP varied from 3.61 GtC/yr to 4.24 GtC/yr in the past 45 years and exhibited minimal significant linear increase or decrease.(2) Regional differences in the increase or decrease in NPP were large but exhibited an insignificant overall linear trend.NPP declined in most parts of eastern and central China,especially in the Loess Plateau.(3) Similar to the fluctuation law of annual NPP,seasonal NPP also displayed an insignificant increase or decrease;the trend line was within the general level.(4) The regional differences in seasonal NPP changes were large.NPP declined in spring,summer,and autumn in the Loess Plateau but increased in most parts of the Tibetan Plateau.     

The Soil Moisture and Net Primary Production Affected by CO_2 and Climate Change Using a Coupled Model

In this paper, a coupled model was used to estimate the responses of soil moisture and net primary production of vegetation （NPP） to increasing atmospheric CO2 concentration and climate change. The analysis uses three experiments simulated by the second-generation Earth System Model （CanESM2） of the Canadian Centre for Climate Modelling and Analysis （CCCma）, which are part of the phase 5 of the Coupled Model Intercomparison Project （CMIP5）. The authors focus on the magnitude and evolution of responses in soil moisture and NPP using simulations modeled by CanESM, in which the individual effects of increasing CO2 concentration and climate change and their combined effect are separately accounted for. When considering only the single effect of climate change, the soil moisture and NPP have a linear trend of 0.03 kg m^-2 yr^-1 and-0.14 gC m^- 2 yr^-2, respec- tively. However, such a reduction in the global NPP results from the decrease of NPP at lower latitudes and in the Southern Hemisphere, although increased NPP has been shown in high northern latitudes. The largest negative trend is located in the Amazon basin at -1.79 gC m^-2 yr^-2. For the individual effect of increasing CO2 concentration, both soil moisture and NPP show increases, with an elevated linear trend of 0.02 kg m^-2 yr^-1 and 0.84 gC m^-2 yr^-2, respectively. Most regions show an increasing NPP, except Alaska. For the combined effect of increasing atmospheric CO2 and climate change, the increased soil moisture and NPP exhibit a linear trend of 0.04 kg m^2 yr^-1 and 0.83 gC m^2 yr^-2 at a global scale. In the Amazon basin, the higher reduction in soil moisture is illustrated by the model, with a linear trend of-0.39 kg m^-2 yr^-1, for the combined effect. Such a change in soil moisture is caused by a weakened Walker circulation simulated by this coupled model, compared with the single effect of increasing CO2 concentration （experiment M2）, and a consequence of the reduction in NPP is also shown in this area, with a linear trend of-     

Seasonality of oceanic primary production and its interannual variability from 1998 to 2007

The seasonality of primary productivity plays an important role in nutrient and carbon cycling. We quantify the seasonality of satellite-derived, oceanic net primary production (NPP) and its interannual variability during the first decade of the SeaWiFS mission (1998 to 2007) using a normalized seasonality index (NSI). The NSI, which is based upon production half-time, t(1/2), generally becomes progressively more episodic with increasing latitude in open ocean waters, spanning from a relatively constant rate of primary productivity throughout the year (mean t(1/2) ~5 months) in subtropical waters to more pulsed events (mean t(1/2) ~3 months) in subpolar waters. This relatively gradual, poleward pattern in NSI differs from recent estimates of phytoplankton bloom duration, another measure of seasonality, at lower latitudes (~40°S–40°N). These differences likely reflect the temporal component of production assessed by each metric, with NSI able to more fully capture the irregular nature of production characteristic of waters in this zonal band. The interannual variability in NSI was generally low, with higher variability observed primarily in frontal and seasonal upwelling zones. The influence of the El Niño–Southern Oscillation on this variability was clearly evident, particularly in the equatorial Pacific, where primary productivity was anomalously episodic from the date line east to the coast of South America in 1998. Yearly seasonality and the magnitude of annual production were generally positively correlated at mid-latitudes and negatively correlated at tropical latitudes, particularly in a region bordering the Pacific equatorial divergence. This implies that increases of annual production in the former region are attained over the course of a year by shorter duration but higher magnitude NPP events, while in the latter areas it results from an increased frequency or duration of similar magnitude events. Statistically significant trends in the seasonality, both positive and negative, were detected in various patches. We suggest that NSI be used together with other phenomenological characteristics of phytoplankton biomass and productivity, such as the timing of bloom initiation and duration, as a means to remotely quantify phytoplankton seasonality and monitor the response of the oceanic ecosystem to environmental variability and climate change.     

山东荣成天鹅湖大叶藻形态和生长的季节性变化研究

2012年8月至2013年7月,作者逐月对天鹅湖大叶藻(Zostera marina L.)的形态特征、植株密度、生物量和生产力进行了监测。结果表明,大叶藻周年株高最高值和最低值分别出现在7月和1月;叶鞘高度、叶鞘宽度和叶宽的最高值均出现在7月,叶鞘高度最低值出现在1月,叶鞘宽度和叶宽最低值均出现在2月;大叶藻顶枝、侧枝和花枝的周年密度最大值分别出现在6月、4月和5月,最小值分别出现在1月、8月和7月;单株生物量和地上部分生物量最大值均出现在7月,地下部分出现在10月,而单株生物量和地上部分生物量最小值均出现在1月,地下部分生物量最小值出现在3月;单株地上和地下生产力最大值均出现在6月,最小值则分别出现在1月和2月。分析显示,大叶藻在冬季由于水温较低导致生长缓慢,且植株较小,在春季随水温上升,生长开始加快。水温在夏初达到大叶藻的最适生长水温,大叶藻的生物量和初级生产力达到最高值,而夏末和初秋由于水温过高导致大叶藻个体生物量、密度和初级生产力开始降低。这种季节性变化与水温的季节性变化密切相关。     

The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation

Remote sensing of vegetation gross primary production (GPP) is an important step to analyze terrestrial carbon (C) cycles in response to changing climate. The availability of global networks of C flux measurements provides a valuable opportunity to develop remote sensing based GPP algorithms and test their performances across diverse regions and plant functional types (PFTs). Using 70 global C flux measurements including 24 non-forest (NF), 17 deciduous forest (DF) and 29 evergreen forest (EF), we present the evaluation of an upscaled remote sensing based greenness and radiation (GR) model for GPP estimation. This model is developed using enhanced vegetation index (EVI) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and global course resolution radiation data from the National Center for Environmental Prediction (NCEP). Model calibration was achieved using statistical parameters of both EVI and LST fitted for different PFTs. Our results indicate that compared to the standard MODIS GPP product, the calibrated GR model improved the GPP accuracy by reducing the root mean square errors (RMSE) by 16%, 30% and 11% for the NF, DF and EF sites, respectively. The standard MODIS and GR model intercomparisons at individual sites for GPP estimation also showed that GR model performs better in terms of model accuracy and stability. This evaluation demonstrates the potential use of the GR model in capturing short-term GPP variations in areas lacking ground measurements for most of vegetated ecosystems globally.     

Mapping and modelling trade-offs and synergies between grazing intensity and ecosystem services in rangelands using global-scale datasets and models

Vast areas of rangelands across the world are grazed with increasing intensity, but interactions between livestock production, biodiversity and other ecosystem services are poorly studied. This study explicitly determines trade-offs and synergies between ecosystem services and livestock grazing intensity on rangelands. Grazing intensity and its effects on forage utilization by livestock, carbon sequestration, erosion prevention and biodiversity are quantified and mapped, using global datasets and models. Results show that on average 4% of the biomass produced annually is consumed by livestock. On average, erosion prevention is 10% lower in areas with a high grazing intensity compared to areas with a low grazing intensity, whereas carbon emissions are more than four times higher under high grazing intensity compared to low grazing intensity. Rangelands with the highest grazing intensity are located in the Sahel, Pakistan, West India, Middle East, North Africa and parts of Brazil. These high grazing intensities result in carbon emissions, low biodiversity values, low capacity for erosion prevention and unsustainable forage utilization. Although the applied models simplify the processes of ecosystem service supply, our study provides a global overview of the consequences of grazing for biodiversity and ecosystem services. The expected increasing future demand for livestock products likely increase pressures on rangelands. Global-scale models can help to identify targets and target areas for international policies aiming at sustainable future use of these rangelands.     

Molecular and stable carbon isotopic compositions of saturated fatty acids within one sedimentary profile in the Shenhu,northern South China Sea: Source implications

This study examined the distributions and stable carbon isotopic compositions of saturated fatty acids (SaFAs) in one 300 cm long sedimentary profile, which was named as Site4B in Shenhu, northern South China Sea. The concentrations of total SaFAs in sediments ranged from 1.80 to 10.16 μg/g (μg FA/g dry sediment) and showed an even-over-odd predominance in the carbon chain of C₁₂ to C₃₂, mostly with n-C₁₆ and n-C₁₈ being the two major components. The short-chain fatty acids (ScFAs; n-C₁₂ to n-C₁₈) mainly from marine microorganisms had average δ¹³C values of −26.7‰ to −28.2‰, whereas some terrigenous-sourced long-chain fatty acids (LcFAs; n-C₂₁ to n-C₃₂) had average δ¹³C values of −29.6‰ to −34.1‰. The other LcFAs (n-C₂₄ & n-C₂₆ ∼ n-C₂₈; average δ¹³C values are −26.1‰ to −28.0‰) as well as n-C₁₉ and n-C₂₀ SaFAs (average δ¹³C values are −29.1‰ and −29.3‰, respectively) showed a mixed signal of carbon isotope compositions.The relative bioproductivity calculation (marine vs. terrigenous) demonstrated that most of organic carbon accumulation throughout the sedimentary profile was contributed by marine organism. The high marine productivity in Shenhu, South China Sea may be related to the hydrocarbon seepage which evidenced by diapiric structures. Interestingly, there is a sever fluctuation of terrigenous inputs around the depth of 97 cm below the seafloor (bsf), probably resulting from the influence of the Dansgaard–Oeschger events and the Younger Dryas event as revealed by ¹⁴C age measurements.     

熔融制样波长色散X射线荧光光谱法测定白云石中钙镁硅铁铝

白云石属碳酸盐矿物,应用熔融制样X射线荧光光谱法测定其中主次量组分钙、镁、硅、铁、铝时,由于白云石灼烧减量大,在试料片制备过程中,如果以干基试料制备试料片,除灼烧减量外还有少量其他组分被分解出的大量CO₂带走,导致试料损失,测定结果偏低;如果以灼烧基试料制备试料片,由于灼烧后的试料极易吸收空气中的水分和CO₂,同样使测定结果偏低。基于质量守恒原理,本文直接以灼烧减量测量后的灼烧基试料质量作为试料量(即灼烧减量测定所称量的干基试料量扣除灼烧减量的量),以四硼酸锂为熔剂,5%碘化铵溶液为脱模剂,试料与熔剂的稀释比为1:10,于1050℃熔融15 min以上制备的试料片透彻、玻璃化程度高。以白云石标准物质和标准样品作为标准试料,制作各组分的标准曲线的相关系数在0.9940~0.9994之间;方法检出限为0.011%~0.48%;标准物质和标准样品的测定值与认定值基本一致,各组分的相对标准偏差(RSD,n=11)在0.5%~1.7%之间,方法具有较好的重现性。本方法以1050℃灼烧后的试样作为试料制备XRF分析样片,最大限度地降低了灼烧减量因素(空气中的水分和CO₂)对测定结果的影响,适用于白云石及其煅烧物中钙、镁、硅、铁、铝等组分的同时测定。