Ecological quality is defined as the stability, adaptability and resilience of an ecosystem. Monitoring and assessing ecological quality are important bases for China's ecological civilization construction. The national key research and development program “Technologies and guidelines for monitoring ecological quality of terrestrial ecosystems in China”, launched in July 2017, includes plans to study the observation technologies and provide guidelines on the ecological in-situ observation, the regional biodiversity and ecosystem function monitoring and its applications, all of which contribute to national ecological quality assessment. A year after its implementation, some important progress has been achieved, such as building the indicator system for comprehensive monitoring of ecological quality and improvement of the methods, mass data transmission, infrared camera-based monitoring of biodiversity, multi-angle automatic spectral observation systems, and unmanned aerial vehicle (UAV) based desert monitoring. We have organized this special issue and attempted to introduce the monitoring techniques and assessment methods on ecological quality from different perspectives in order to further promote the development of ecology and its observation methods.
The accurate measurement of the dynamics of photosynthesis in China’s subtropical evergreen forest ecosystems is an important contribution to carbon (C) sink estimates in global terrestrial ecosystems and their responses to climate change. Eddy covariance has historically been the only direct method to assess C flux of whole ecosystems with high temporal resolution, but it suffers from limited spatial resolution. During the last decade, continuous global monitoring of plant primary productivity from spectroradiometer sensors on flux towers and satellites has extended the temporal and spatial coverage of C flux observations. In this study, we evaluated the performance of two physiological remote sensing indices, fluorescence reflectance index (FRI) and photochemical reflectance index (PRI), to measure the seasonal variations of photosynthesis in a subtropical evergreen forest ecosystem using continuous canopy spectral and flux measurements in the Dinghushan Nature Reserve in southern China. The more commonly used NDVI has been shown to be saturated and mainly affected by illumination (R2=0.88, p < 0.001), but FRI and PRI could better track the seasonal dynamics of plant photosynthetic functioning by comparison and are less affected by illumination (R2=0.13 and R2=0.51, respectively) at the seasonal scale. FRI correlated better with daily gross primary production (GPP) in the morning hours than in the afternoon hours, in contrast to PRI which correlated better with light-use efficiency (LUE) in the afternoon hours. Both FRI and PRI could show greater correlations with GPP and LUE respectively in the senescence season than in the recovery-growth season. When incident PAR was taken into account, the relationship between GPP and FRI was improved and the correlation coefficient increased from 0.22 to 0.69 (p < 0.001). The strength of the correlation increased significantly in the senescence season (R 2=0.79, p < 0.001). Our results demonstrate the application of FRI and PRI as physiological indices for the accurate measurement of the seasonal dynamics of plant community photosynthesis in a subtropical evergreen forest, and suggest these indices may be applied to carbon cycle models to improve the estimation of regional carbon budgets.
Fluctuations in soil greenhouse gas (GHG) are an important part of the terrestrial ecosystem carbon-nitrogen cycle, but uncertainties remain about the dynamic change and budget assessment of soil GHG flux. Using high frequency and consecutive soil GHG fluxes measured with an automatic dynamic chamber system, we tested the applicability of the current Forest-DNDC model in simulating soil CH4, CO2 and N2O fluxes in a temperate broad-leaved Korean pine forest at Changbai Mountain. The results showed that the Forest-DNDC model reproduced general patterns of environmental variables, however, simulated seasonal variation in soil temperature, snow melt processes and soil moisture partly deviated from measured variables, especially during the non-growing season. The modeled CH4 flux was close to the field measurement and co-varied mainly with soil temperature and snowpack. The modeled soil CO2 flux had the same seasonal trend to that of the observation along with variation in temperature, however, simulated CO2 flux in the growing season was underestimated. The modeled N2O flux attained a peak in summer due to the influence of temperature, which was apparently different from the observed peak of N2O flux in the freeze-thaw period. Meanwhile, both modeled CO2 flux and N2O flux were dampened by rainfall events. Apart from consistent estimation of annual soil CH4 flux, the annual accumulation of CO2 and N2O was underestimated. It is still necessary to further optimize model parameters and processes using long-term high-frequency observation data, especially transference of heat and water in soil and GHG producing mechanism. Continues work will improve modeling, ecosystem carbon-nitrogen budget assessment and estimation of soil GHGs flux from the site to the region.
Dynamic changes in solar radiation have an important influence on ecosystem carbon sequestration, but the effects of changes caused by sky conditions on net ecosystem CO2 exchange (NEE) are unclear. This study analyzed the effects of sunny, cloudy, and overcast sky conditions on NEE using carbon flux and meteorological data for a subtropical coniferous plantation in 2012. Based on one-year data, we found no seasonal variation in the light response curve under various sky conditions. Compared with sunny sky conditions, the apparent quantum yield (α) and potential photosynthetic rate at a light intensity of 150 and 750 W m-2 (P150 and P750) under cloudy sky conditions increased by an average of 82.3%, 217.7%, and 22.5%; α and P150 under overcast sky conditions increased by 118.5% and 301% on average. Moderate radiation conditions were more favorable for maximum NEE, while low radiation conditions inhibited NEE. In most cases, when the sunny NEE was used as a baseline for comparison, the relative change in NEE (%NEE) was positive under cloudy sky conditions and negative under overcast sky conditions. The average maximal %NEE under cloudy sky conditions was 42.4% in spring, 34.1% in summer, 1.6% in autumn and -87.3% in winter. This study indicates that cloudy sky conditions promote photosynthetic rates and NEE in subtropical coniferous plantations.
The priming effect is well acknowledged in soil systems but the effect of nitrogen (N) fertilization remains elusive. To explore how N modifies the priming effect in soil organic matter (SOM), one in situ experiment with 13C labeled glucose addition (0.4 mg C g-1 soil, 3.4 atom % 13C) was conducted on soil plots fertilized with three gradients of urea (0, 4 and 16 g N m-2 yr-1). After glucose addition, the soil CO2 concentration and phospholipid fatty acid (PLFA) were measured on day 3, 7, 21 and 35. The study found that N fertilization decreased soil CO2, PLFA and the fungi to bacteria ratio. Glucose triggered the strongest positive priming in soil at 0 g N m-2 yr-2, meanwhile N fertilization decreased SOM-derived CO2. Soil at 4 g N m-2 yr-2 released the largest amount of glucose-derived carbon (C), likely due to favorable nutrient stoichiometry between C and N. Stable microbial community biomass and composition during early sampling suggests “apparent priming” in this grassland. This study concludes that N fertilization inhibited soil priming in semi-arid grassland, and shifted microbial utilization of C substrate from SOM to added labile C. Diverse microbial functions might be playing a crucial role in soil priming and requires attention in future N fertilization studies.
We investigated soil respiration (Rs) dynamics and influencing factors under different nitrogen (N) addition levels (0, 2, 4, 8, 16, 32 g m-2 yr-1) on typical grassland plots in Inner Mongolia. We measured soil respiration, temperature, moisture and nutrients. We found that N addition did not change dynamic characteristics of Rs; daily and seasonal dynamics followed a single peak curve. N addition reduced Rs during the growing season. Rs under N2, N4, N8, N16 and N32 treatments decreased by 24.00%, 21.93%, 23.49%, 30.78% and 28.20% in the growing season, respectively, compared to the N0 treatment. However, Rs in the non-growing season was not different across treatments. Rs was significantly positively correlated with soil temperature and moisture and these two factors accounted for 72%-97% and 74%-82% of variation in Rs, respectively. The soil respiration temperature sensitivity (Q10) was between 2.27 and 4.16 and N addition reduced Q10 except in the N8 treatment.
Natural hay pastures in semi-arid pastoral areas produce the highest yields of hay in northern China. However, long-term continuous hay harvesting with no rest interval has resulted in severe degradation across widespread areas of these natural hay pastures. In addition, no clear data exist on the spatial distribution or degree of degradation occurring in natural hay pastures primarily because a nationally unified and normative evaluation standard is lacking. In view of the above problems, we employed an analytic hierarchy process to carry out screening and accuracy validation of evaluation indicators for natural hay pastures in north China grasslands (temperate meadow steppes, temperate steppes, mountain meadows, and lowland meadows). Our study identified seven easily measured indicators that reflect the state of natural hay pastures (average height, aboveground biomass, coverage, proportion of medium grasses, litter biomass, proportion of degradation-indicative plants, and proportion of bare spots and saline-alkali spots). A five-level scoring method was employed to delineate the threshold range for these indicators, The results of this study show that this method effectively solved the technical bottleneck for graded evaluation of degradation in natural hay pastures. This provides a theoretical basis for the scientific assessment of natural hay pasture degradation as well as important technical support for sustainable use of natural hay pastures and livestock production.
The acceleration of urbanization has led to the occupation of more cropland, especially higher quality cropland, which could pose a huge threat to food security and have other implications for the inadequate cropland resource supply in China. Though the spatial status of Chinese cropland quality has been assessed, its temporal changes since 2000 to 2015 are still not clear. An accumulated probability distribution method was used to determine the criteria of cropland quality using the net primary production data product (MOD17) from Moderate Resolution Imaging Spectroradiometer (MODIS). Then the cropland quality of higher, median and lower production was spatially mapped and its changes due to occupation by urbanization were analyzed through the land use changes (LUCC) data primarily from Landsat TM images in the three periods of 2000-2005, 2005-2010, and 2010-2015. The results showed that of the total cropland reduction area the proportion taken by urbanization increased from 47.29% in the early stage to 77.46% in the recent period. The quality of Chinese cropland was dominated by low- and medium-yield fields, accounting for 40.81% and 48.74%, respectively, with high-yield fields accounting for only 10.44% of the total cropland in the country in 2000. The high-yield areas have been seriously threatened by the expansion of construction land fields, with the ratio of high-yield area to total area occupied by urbanization increasing from 9.71% in 2000-2005 to 15.63% in 2010-2015. Spatially, this phenomenon has been moving from eastern and southern China to central and western China, especially in Northwest China where the ratio has arrived at the highest proportion, with 52.97% of high-yield cropland in the total land taken by the expansion by 2015. This study not only provides a method to assess cropland quality but also reveals the threatening trend from the expansion of urbanization on high-quality cropland. More attention should be paid to the latter in land use planning and policies made to prevent threats to food security from declines in both cropland quantity and quality.
Crop-residue return is a recommended practice for soil and nutrient management and is important in soil organic carbon (SOC) sequestration and CO2 mitigation. We applied a process-based Environmental Policy Integrated Climate (EPIC) model to simulate the spatial pattern of topsoil organic carbon changes from 2001 to 2010 under 4 crop-residue return scenarios in China. The carbon loss (28.89 Tg yr-1) with all crop-residue removal (CR0%) was partly reduced by 22.38 Tg C yr-1 under the status quo CR30% (30% of crop-residue return). The topsoil in cropland of China would become a net carbon sink if the crop-residue return rate was increased from 30% to 50%, or even 75%. The national SOC sequestration potential of cropland was estimated to be 25.53 Tg C yr-1 in CR50% and 52.85 Tg C yr-1 in CR75%, but with high spatial variability across regions. The highest rate of SOC sequestration potential in density occurred in Northwest and North China while the lowest was in East China. Croplands in North China tended to have stronger regional SOC sequestration potential in storage. During the decade, the reduced CO2 emissions from enhanced topsoil carbon in CR50% and CR75% were equivalent to 1.4% and 2.9% of the total CO2 emissions from fossil fuels and cement production in China, respectively. In conclusion, we recommend encouraging farmers to return crop-residue instead of burning in order to improve soil properties and alleviate atmospheric CO2 rises, especially in North China.
The dryland ecosystem is the dominant component of the global terrestrial ecosystem since arid regions occupy 45% of the earth’s land area and feed 38% of the world's population. The stability and sustainable development of the dryland ecosystem are critical for achieving the millennium development goal (MDG) in the arid and semiarid areas. However, there is still no scientific guideline for measuring and conserving the health and productivity of dryland ecosystems. Therefore, the purpose of this study is to develop the scientific conceptual framework of defining, monitoring and evaluating the ecological quality of dryland ecosystems. The ecological quality of dryland ecosystems is represented by a system of comprehensive indicators that are each extracted from the ecological elements, and structural and functional indices of the ecosystem. These indicators can be monitored by integrating satellites and unmanned aerial vehicles with ground-based sensor networks at the scale of either observational sites or regional scales. Finally, the ecological quality can be evaluated by evaluation models based on the normalized index values and their thresholds. This paper presents a conceptual framework for monitoring and evaluating the ecological quality of drylands, which provides a way of advancing the monitoring, diagnosis, and evaluation of the ecological quality of the dryland ecosystems.
Strong and rapid responses of soil microbial respiration to pulses, such as those from available soil organic matter (SOM) or water input from precipitation (especially in arid areas), are common. However, how soil microbes utilize new SOM inputs and the effects that temperature may have on their activities are unclear owing to the limitation in the application of traditional isotopic techniques at minute scales. In the present study, we developed a system of measuring 12CO2 and δ13C minutely and synchronously under controlled incubation temperatures, i.e., for 48 h at 7, 10, 15, 20, and 25 °C, to explore the carbon utilization strategies of soil microbes. We measured the respiration rates of soil microbes in response to different carbon sources, i.e., added glucose (Rg) and initial SOM (Rs), as well as the total respiration rate (Rt). All responses were rapid and characterized by unimodal curves. Furthermore, the characteristic values of these curves, such as the maximum of rate (R-max), the time required to achieve R-max, and the ratio of the duration of R-max to that of 1/2 R-max, were all dependent on incubation temperature. Interestingly, temperature greatly influenced the strategy that microorganisms employed to utilize different carbon sources. The effects of temperature on the intensity of the microbial respiratory response and the ratio of Rg/Rs are important for evaluating the effect of land-use changes or variations in seasonal temperature on SOM turnover and should be considered in ecological models in future studies.
Evapotranspiration is the key driving factor of the earth’s water cycle, and an important component of surface water and energy balances. Therefore, it also reflects the geothermal regulation function of ecohydrological process. The Qinghai-Tibet Plateau is the birthplace of important rivers such as the Yangtze River and the Yellow River. The regional water balance is of great significance to regional ecological security. In this study, ARTS, a dual- source remote sensing evapotranspiration model developed on a global scale, is used to evaluate the actual evapotranspiration (ET) in the Qinghai-Tibet Plateau from 1982 to 2014, using meteorological data interpolated from observations, as well as FPAR and LAI data obtained by satellite remote sensing. The characteristics of seasonal. interannual and dynamic changes of evapotranspiration were analyzed. The rates at which meteorological factors contribute to evapotranspiration are calculated by sensitivity analysis and multiple linear regression analysis, and the dominant factors affecting the change of evapotranspiration in the Qinghai-Tibet Plateau are discussed. The results show that: (1) The estimated values can explain more than 80% of the seasonal variation of the observed values (R2 = 0.80, P < 0.001), which indicates that the model has a high accuracy. (2) The evapotranspiration in the whole year, spring, summer and autumn show significant increasing trends in the past 30 years, but have significant regional differences. Whether in the whole year or in summer, the southern Tibetan Valley shows a significant decreasing trend (more than 20 mm per 10 years), while the Ali, Lhasa Valley and Haibei areas show increasing trends (more than 10 mm per 10 years). (3) Sensitivity analysis and multiple linear regression analysis show that the main factor driving the interannual change trend is climate warming, followed by the non-significant increase of precipitation. However, vegetation change also has a considerable impact, and together with climate factors, it can explain 56% of the interannual variation of evapotranspiration (multiple linear regression equation R2 = 0.56, P < 0.001). The mean annual evapotranspiration of low-cover grassland was 26.9% of high-cover grassland and 21.1% of medium-cover grassland, respectively. Considering significant warming and insignificant wetting in the Qinghai-Tibet Plateau, the increase of surface evapotranspiration will threaten the regional ecological security at the cost of glacial melting water. Effectively protecting the ecological security and maintaining the sustainable development of regional society are difficult and huge challenges.
Ecosystem services are spatially heterogeneous and temporal variability, which results in trade-offs, synergies and neutrality. The trade-off is a key problem in ecosystem management and requires optimized decision-making research. This paper reviews methods for identifying trade-offs and suggest future model developments. We conclude that (1) ecosystem service assessment depends on quantitative indicators and its modeling; (2) scenario analysis, multi-objective analysis and production possibility boundary are an effective means of ecosystem service trade-off decision-making; (3) future research needs to strengthen ecosystem service supply and demand flow and assist decision-making ecosystem mapping. Finally, integrated models should be developed to simulate and diagnose different scenarios and to optimize measures in land and ecosystem management for sustainability.
