海洋透光率仪的设计及其在初级生产力研究中的应用*

海洋浮游植物光合作用固碳在全球碳循环中扮演着极为重要的角色, 获取不同光衰减对应的海水深度, 对于采集水样用于海洋初级生产力的研究具有重要意义。本研究于国际上首次开发了无缆便携式海洋透光率仪, 特殊的光学结构设计和光谱滤光技术使得光谱响应在波段400~700nm范围内超过了同类海洋传感器, 特定光衰减下对应的深度误差小于0.5m。将本设备应用于南海中尺度涡旋初级生产力的研究中, 在采样率和自动化方面验证了仪器的便携性; 通过对涡旋中初级生产力的空间分布规律进行分析, 检验了仪器数据结果的可靠性。海洋透光率仪在价格、准确性、可靠度和操作的便携性上具有不可比拟的优势, 将在未来海洋生态环境的研究中发挥重要作用。     

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.     

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.     

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.     

全球二叠系顶部白云岩与沉积相关系统计及其白云石化机制的意义

本文对全球范围内23个典型的研究程度较高的晚长兴期露头进行了研究,逐一检查了晚长兴期白云岩前身沉积的沉积相,结果发现所有白云岩的前身都是浅水相的(除汉中梁山一个剖面外)。相反,目前已经研究的深水相上二叠统碳酸盐沉积物都没有发生白云岩化。这一结果表明,世界范围内上二叠统顶部白云岩的形成机制可能都与海平面下降有关,很可能是蒸发成因的浓缩卤水使沉积物发生白云岩化。据此推断,四川盆地东北部长兴组白云岩也应当是此种成因。     

重庆马槽坝-黑楼门地区上石炭统黄龙组白云岩储层类型及其控制因素

根据钻井岩心、薄片、物性等数据资料,对四川盆地东部马槽坝-黑楼门地区白云岩储层特征进行分析,并探讨沉积相及成岩作用对储层形成的控制作用。研究区白云岩储层的岩石类型主要为颗粒白云岩、微晶白云岩、粉-细晶白云岩。储集空间以次生粒间及粒内溶孔为主,并伴生有超大溶孔。研究区黄龙组储层总体上属于低孔低渗储层,以小孔-中细喉组合为主。白云石化作用、重结晶作用、破裂作用、古岩溶作用是有利于储层发育的成岩作用,其中白云石化作用是最普遍也是最重要的成岩作用。粒屑浅滩、潮道是有利于储层发育的沉积环境。     

四川盆地震旦系灯影组葡萄状白云岩成因

四川盆地震旦系灯影组发育巨厚的白云岩,其中灯影组二段和四段发育大量具有各种形态的葡萄状白云岩,其直径最长可达75cm,有的平行于层面,有的穿层。剖面资料表明,葡萄状白云岩发育多期等厚环边胶结物,中部残留大量未充填的不规则洞穴,这成为与岩溶喀斯特作用相关的地下溶蚀作用的证据。围岩泥晶白云石为早期海水中原生结晶的产物,后来的胶结物可划分为4期: (1)自泥晶化白云石(部分样品中可见)作为最早的一期胶结物,由于各种生物化学作用和生物作用的影响而紧贴着围岩发育;(2)第2期胶结物纤维状白云石可能为海水中直接沉淀的产物,经历后期成岩作用后,具有完全有序的结构,晶胞参数接近理想值;(3)细—中晶白云石为第3期胶结物,包含纤维状白云石溶蚀残余,形成于构造抬升之后的近地表大气淡水环境;(4)第4期胶结物中—粗晶白云石为埋藏环境下直接结晶的产物,充填了孔洞中心,残留部分未充填孔洞。灯影组受到了岩溶喀斯特作用、胶结作用以及白云石化作用等成岩作用的影响,其中与葡萄状白云岩有关的岩溶喀斯特作用对于灯影组储集层的发育至关重要。对灯影组葡萄状白云岩的研究,不仅有助于深入探讨灯影组储集层成因和演化及灯影组白云岩的成因,而且有助于指导四川盆地前寒武系油气勘探。