Net primary production of major plant functional types in China: Vegetation classification and ecosystem simulation

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.

Reducing human activity promotes environmental restoration in arid and semi-arid regions: A case study in Northwest China

Human activities have adversely impacted grassland net primary productivity (NPP) across the world, and quantitative estimations of the anthropogenic impacts on NPP (HNPP) can be helpful to improve environmental protection and climate adaptation measures. However, disentangling the effects of climate variability and human activities on NPP is problematic and requires the calculation of potential net primary productivity (PNPP). In this study, we assessed the anthropogenic impacts on NPP in the Shiyang River basin-a typical arid and semi-arid region. We used the seasonal changes in NPP to identify the grids that were not affected by human activity and then proposed a method to calculate PNPP based on the leaf area index (LAI). We estimated the actual net primary productivity (ANPP) using the Carnegie-Ames-Stanford Approach (CASA) model, and the HNPP was then calculated as the difference between ANPP and PNPP. Our results showed that this method for PNPP calculation was reliable. From 2001 to 2016, the positive (90.85 gC·m^-2·a^-1) and negative effects (-130.21 gC·m^-2·a^-1) of human activities on NPP accounted for 32.68% and 46.84% of the ANPP, respectively, and the overall average HNPP was -39.36 g C·m²·a^-1. The implementation of ecological and environmental protection projects gradually mitigated the negative effects of human activity on NPP at a rate of 4.55 gC·m^-2·a^-1; however, negative HNPP values still occupied 55.39% of the entire region in 2016. In contrast with the prevailing views that climate change is the main factor accounting for vegetation recovery in arid and semi-arid regions, our results suggest that reducing human activities can significantly promote environmental restoration. The findings of this study suggest that policy makers and stakeholders can restore grassland ecosystems and promote environmental protection by reducing anthropogenic activities in arid and semi-arid regions.

Can more carbon be captured by grasslands? A case study of Inner Mongolia, China

Grasslands cover a large part of the Earth's surface and play an important role in the global carbon cycle. Previous studies have indicated that nearly half of the grassland vegetation cover has experienced degradation on a global scale; if this degradation is reversed, grasslands can act as potential carbon sinks. However, the question of how much more carbon (carbon gap) could be sequestrated by grassland vegetation by regulating human activities remains unanswered. Here, we present an innovative approach to assess the achievable carbon gap through focal analysis of long-term Moderate Resolution Imaging Spectroradiometer (MODIS) Net Primary Production (NPP) dataset or observed NPP (ONPP). In focal analysis, region segmentation was done to produce spatially homogeneous patches of the same types of soil, topography, and vegetation, referred to as S-T-V units, to minimize the variation in environmental conditions and their impacts on the NPP. Then, the ONPP within each S-T-V unit was rectified by offsetting the variations in potential NPP determined by the climate-oriented Miami NPP model. Hence, spatial variations in the climate-rectified ONPP (ONPP_CR) in an S-T-V unit were solely determined by different human activities across locations. In a case study of the Inner Mongolia grassland of China, three focal statistics, namely mean (Mean), 95% percentile threshold (95%PCT), and maximum (Max) within each S-T-V unit were computed for ONPP_CR for each year from 2000 to 2014 to assess the annual carbon uptake that was achievable by updating grassland management practices. The carbon gaps were assessed to be 11.8, 58.9, and 74.6 gC/m² per year based on Mean, 95%PCT, and Max, respectively, compared to 65.0 gC/m² per year based on the traditional pixel-based approach. We conclude that the carbon gap patterns identified from focal analysis are practically achievable and are more valuable in formulating policy-related decisions for grassland management. Implementing sustainable management practices that are currently being practiced at locations with high ONPP_CR in neighboring degraded areas is expected to increase the carbon sequestration by grassland vegetation by one-third.

Changes of vegetation carbon sequestration in the tableland of Loess Plateau and its influencing factors

The variations of vegetation carbon sequestration have become a gauge for evaluating the ecological effect of vegetation restoration. In this study, the spatiotemporal patterns of the net ecosystem production (NEP) were simulated using an improved CASA model and GSMSR model. It showed that the NEP markedly increased in the tableland of Loess Plateau during 2003-2012, with an annual average growth of 3.65 g C·m^-2 a^-1. The mixed broadleaf-conifer forest ranked first (127.23 g C·m^-2 a^-1) while the bare land and sparse vegetation presented the lowest carbon sequestration (14.64 g C·m^-2 a^-1). The NEP manifested a significantly uneven overall spatial distribution: high in the southwest and low in the northeast. The spatial variations of NEP resulted from the combined effects of geographic position, terrain, meteorology, and soil and vegetation, respectively. Quantitative isolation revealed that the most dominant factor of vegetation carbon sequestration was soil and vegetation, while terrain exerted insignificant impacts on the NEP.

Climate change risk to forests in China associated with warming

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021–2050) to 27.62% (2071–2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

Country-level net primary production distribution and response to drought and land cover change

Carbon sequestration by terrestrial ecosystems can offset emissions and thereby offers an alternative way of achieving the target of reducing the concentration of CO₂ in the atmosphere. Net primary production (NPP) is the first step in the sequestration of carbon by terrestrial ecosystems. This study quantifies moderate-resolution imaging spectroradiometer (MODIS) NPP from 2000 to 2014 at the country level along with its response to drought and land cover change. Our results indicate that the combined NPP for 53 countries represents >90% of global NPP. From 2000 to 2014, 29 of these 53 countries had increasing NPP trends, most notably the Central African Republic (23gC/m²/y). The top three and top 12 countries accounted for 30% and 60% of total global NPP, respectively, whereas the mean national NPP per unit area in the countries with the 12 lowest values was only around ~300gC/m²/y - the exception to this was Brazil, which had an NPP of 850gC/m²/y. Large areas of Russia, Argentina, Peru and several countries in southeast Asia showed a marked decrease in NPP (~15gC/m²/y). About 37% of the NPP decrease was caused by drought while ~55% of NPP variability was attributed to changes in water availability. Land cover change explained about 20% of the NPP variability. Our findings support the idea that government policies should aim primarily to improve water management in drought-afflicted countries; land use/land cover change policy could also be used as an alternative method of increasing NPP.