Actual Net Primary Productivity Research Articles

Temporal and spatial evolution of net primary productivity in the Three-River Headwaters Region under phenological changes and anthropogenic influence.

Understanding the spatiotemporal changes in net primary productivity (NPP) and the driving factors behind these changes in climate-vulnerable regions is crucial for ecological conservation. This study simulates the actual NPP (NPPA) and climate potential NPP (NPPC) in the Three-River Headwaters Region from 2000 to 2020. The Theil-Sen Median method and Mann-Kendall mutation analyses are employed to explore their spatiotemporal variation patterns, while geographic weighted regression and machine learning are used to investigate the influence of anthropogenic activities and climatic factors on NPPA, the results indicate that the average NPPA across the entire region over multiple years is 382.506 , which is 0.132 times the average annual NPPC over the past 21years, showing an overall distribution pattern of low in the northwest and high in the southeast. The annual increase in NPPA from 2000 to 2020 is approximately 1.034 . The source region of the Yangtze River shows the largest improvement in vegetation, with 74.1% of the area showing improvement. Between 2002 and 2003, the annual NPPA in the Three-River Headwaters Region experienced a sudden change, lagging behind the NPPC change by 1year, and after 2005, the upward trend in NPPA became more pronounced. The impact of anthropogenic activities on NPPA shifted from positive to negative to positive from 2000 to 2020, with significant impact areas mainly concentrated in the northeast and a few areas in the central and southern parts. The proportion of areas with extremely significant impact increased from 1.9% in 2000 to 3.7% in 2020. Over the past 21years, the main factors influencing NPPA changes in the Three-River Headwaters Region have been soil moisture and precipitation, with the influence of different climate factors on NPP changing over time. Additionally, NPP is more sensitive to changes in altitude in low-altitude areas. This study can provide more accurate theoretical support for ecological environment assessment and subsequent protection efforts in the Three-River Headwaters Region.

Spatiotemporal variation and prediction of NPP in Beijing-Tianjin-Hebei region by coupling PLUS and CASA models

Vegetation productivity is crucial for human production and livelihoods. Understanding net primary productivity (NPP) in historical contexts and predicting its future fluctuations is imperative for assessing the environmental sustainability of a region. However, relatively few researches have been conducted on predicting NPP, requiring further development and refinement of NPP prediction methods and models. This study introduces a novel approach that discretely couples the PLUS and CASA models for NPP prediction, and it validates the applicability of this approach in the research area. The objective of our study is to analyze the spatiotemporal patterns of NPP change in the Beijing-Tianjin-Hebei (BTH) region from 2001 to 2020, predict NPP under three different climate scenarios (SSP 1-2.6, SSP 2-4.5, SSP 5-8.5) in 2030, and identify an appropriate path for the future development of this region. The results indicate:(1) From 2001 to 2020, NPP in the research area has shown a gradual improvement trend and maintained a certain spatial distribution pattern in general. (2) The study discovered a correlation coefficient of 0.83 and an RMSE of 102.86 between predicted and actual NPP for 2020. This suggests that the method introduced in our study is suitable for predicting NPP in the research area. (3) NPP in the study area is predicted to decline in 2030 compared with 2020 under all three scenarios. Moreover, the SSP 1-2.6 scenario, representing a low-emission scenario, is suitable for the BTH region compared with other climate scenarios. This research sheds light on NPP variations in the BTH region over the past 20 years and the next 10 years, offering a scientific basis for relevant departments to formulate future policies.

Assessing the Distribution and Driving Effects of Net Primary Productivity along an Elevation Gradient in Subtropical Regions of China

Globally, forest ecosystems, especially subtropical forests, play a central role in biogeochemical cycles and climate regulation, demonstrating their irreplaceable function. The subtropical region of China, characterized by its unique forest ecosystem, complex terrain, climate heterogeneity, diverse vegetation types, and frequent human activities, underscores the importance of the in-depth study of its net primary productivity (NPP). This paper employs the eddy covariance–light use efficiency (EC-LUE) model to quantitatively estimate the gross primary productivity (GPP) of this region from 2001 to 2018, followed by an estimation of the actual net primary productivity (ANPP) using the carbon use efficiency (CUE). The results showed that over these 18 years, the annual average ANPP was 677.17 gC m−2 a−1, exhibiting an overall increasing trend, particularly in mountainous areas, reserves, and the cultivated lands of the northeastern plains, whereas a significant decrease was observed around the urban agglomerations on the southeast coast. Furthermore, the Thornthwaite memorial model was applied to calculate the potential net primary productivity (PNPP), and diverse scenarios were set to quantitatively evaluate the impact of climate change and human activities on the vegetation productivity in the study area. It was found that in areas where the ANPP increased, both human activities and climate change jointly influenced ANPP dynamics; in areas with a decreased ANPP, the impact of human activities was particularly significant. Additionally, the heterogeneous distribution of ANPP across different altitudinal gradients and the driving effects of various climatic factors were analyzed. Finally, a partial correlation analysis was used to examine the relationships between the temperature, precipitation, and ANPP. This study indicated that temperature and precipitation have a substantial impact on the growth and distribution of vegetation in the region, yet the extent of this influence shows considerable variation among different areas. This provides a robust scientific basis for further research and understanding of the carbon dynamics of subtropical forest ecosystems and their role in the global carbon cycle.

Grassland productivity increase was dominated by climate in Qinghai-Tibet Plateau from 1982 to 2020

Grassland areas occupy 60% of the Qinghai-Tibetan Plateau (QTP) and play a critical role in enhancing the ecological barrier functions of the QTP. Grassland ecosystems, and net primary productivity (NPP) in general, have dramatically changed in time and space since the 1980s, with climate warming and the intensification of human activities. Current research widely believes that climate and human activities are the common driving factors of grassland ecosystem changes on the QTP. However, there is still controversy over their dominant driving factors and their contribution rates, especially during different research periods. Therefore, this study calculated the relative contributions of climate change, human activities (except LUCC) and LUCC to actual NPP (aNPP) changes during the two periods from 1982 to 2000 to 2001–2020. This study simulated three kinds of NPPs, that is, actual NPP, potential NPP, and human-appropriated NPP, using climate productivity, the light use efficiency model, and the residual method, respectively. Moreover, the study area was divided into two parts, and then the contributions of the three factors were calculated objectively. The results showed that (1) the actual NPP (aNPP) of the QTP increased dramatically from 1982 to 2000 but did not change obviously from 2001 to 2020. (2) Comprehensive evaluation showed that climate was the dominant factor for the aNPP net increase, and its contribution rate dramatically increased from 36.3% during 1982–2000 to 224.2% during 2001–2020. Human activities changed from a positive contribution (53.3%) to a negative contribution (−124.8%) to the aNPP net increase. The contribution rate of LUCC to the aNPP increase significantly decreased from 10.4% to 0.6%. Therefore, finer grassland restoration measures and government policies must be implemented to increase NPP against the background of favorable warm-wet climate conditions for increasing grassland NPP in the QTP. These results benefit the scientific management of grassland resources and ecological barrier building on the QTP.

Impacts of Human Activities on the Net Primary Productivity of Vegetation in Chengde's Transitional Region from Plateau to Plain in the Context of Climate Change

Chengde's transitional region from plateau to plain is located in the transition zone of agriculture and livestock and is extremely sensitive to climate change and human activities. This study used the net primary productivity(NPP) of vegetation as an evaluation index to quantify the degree impacts of climate change and human activities on vegetation change in the region. The Thornthwaite Memorial model was used to calculate the potential NPP, and the actual NPP was obtained based on MODIS NPP remote sensing images, using the difference between the actual and potential NPPs to express the amount of change in NPP owing to human activities. We used the slope trend and coefficient of variation method to analyze the trend and stability distribution of the actual NPP, potential NPP, and NPP influenced by human activities, and the correlation between actual NPP and annual precipitation and annual average temperature was analyzed using the correlation coefficient method. Finally, we quantified the impact of climate change and human activities on vegetation change in the region. The results showed that 99.87% of the vegetation in the region was improved and changed steadily, and the proportions of the areas showing positive correlation between actual NPP and annual precipitation and annual average temperature were 99.87% and 91.66%, respectively. The potential NPP showed an increasing trend from northwest to southeast, whereas the trend and stability of the potential NPP both showed an increasing trend from west to east. The area where climate change and human activities played a role in vegetation improvement accounted for 99.71%, and that affected by climate change accounted for 0.14%, with the proportion of human activities leading to vegetation degradation being 0.15%.

Dynamic of Grassland Degradation and Its Driving Forces from Climate Variation and Human Activities in Central Asia

Central Asia is one of the most sensitive regions to climate changes in the world and the grassland degradation of this region has attracted considerable concern. Quantifying the driving force of grassland degradation is important for understanding the effects of climate variation and human activities on grassland. In this study, net primary productivity (NPP) was selected as an indicator to quantitatively evaluate the relative role of climate variation and human activities in Central Asia from 2000 to 2020. This study used the global NPP product MOD17A3 as actual NPP and estimated the potential NPP using the Thornthwaite memorial model. The potential NPP and the difference between the potential NPP and actual NPP were used to represent the influence of climate variation and human activities. The grassland degradation or restoration can be demonstrated by the slope of actual NPP (SA). A positive slope value (SA) suggested that restoration occurs, whereas a negative slope value suggested that degradation occurred. The results showed that 23.08% of the total grassland area experienced grassland degradation, whereas 2.51% of the whole grassland underwent grassland restoration. Furthermore, 53.8% of the degraded grassland areas were influenced by climate variation, and 14.5% were caused by human activities. By contrast, the relative roles of climate variation and human activities in grassland restoration were 25% and 47.9%, respectively. The NPP variation also could be calculated by assessing the effects of these factors and the results showed that 55.7% of the NPP decrease was caused by climate variation, whereas 9.6% was a result of human activities. On the contrary, climate variation and human activities resulted in 19.8% and 37.3% of grassland restoration, respectively. Therefore, climate variation was the dominant factor of grassland degradation, and human activities were the main driver of grassland restoration in Central Asia.

Contributions of climate change and human activities to grassland degradation and improvement from 2001 to 2020 in Zhaosu County, China

Grassland degradation poses a serious threat to biodiversity, ecosystem services, and human well-being. In this study, we investigated grassland degradation in Zhaosu County, China, between 2001 and 2020, and analyzed the impacts of climate change and human activities using the Miami model. The actual net primary productivity (ANPP) obtained with CASA (Carnegie-Ames-Stanford Approach) modeling, showed a decreasing trend, reflecting the significant degradation that the grasslands in Zhaosu County have experienced in the past 20 years. Grassland degradation was found to be highest in 2018, while the degraded area continuously decreased in the last 3 years (2018–2020). Climatic factors for found to be the dominant factor affecting grassland degradation, particularly the decrease in precipitation. On the other hand, human activities were found to be the main factor affecting improvement of grasslands, especially in recent years. This finding profoundly elucidates the underlying causes of grassland degradation and improvement and helps implement ecological conservation and restoration measures. From a practical perspective, the research results provide an important reference for the formulation of policies and management strategies for sustainable land use.

Untangling the effects of climate variation and human interference on grassland dynamics in North China

AbstractClimatic and anthropogenic disturbances play pivotal roles in shaping the dynamics of grassland. Quantifying their impacts on grassland variation is essential to ensure sustainable grassland management. In this study, we employed the Thornthwaite Memorial and Carnegie–Ames–Stanford‐approach (CASA) models to investigate the spatiotemporal effects of these two variables on grassland variation in northern China from 2000 to 2016, using the net primary productivity (NPP) as a measure. Our findings reveal that approximately 25.92% of the grassland in northern China experienced degradation, while restored grasslands occupied 45% of the total grassland area. The average grassland actual NPP (ANPP) and human‐induced NPP decreased at rates of −0.60 and −5.62 gC m−2 a−1, respectively. Conversely, potential NPP exhibited an upward trend with an average increase of 2.27 gC m−2 a−1. Furthermore, grassland ANPP showed a projected increase in most parts of northern China. Climate change emerged as the primary driver for grassland restoration in Xinjiang, Qinghai, and Inner Mongolia, leading to an increase of 21582.79 Gg C in grassland NPP. In contrast, human activities were the dominant catalysts for grassland degradation, resulting in a reduction of 51932.3 Gg C in grassland NPP. Human‐induced grassland degradation was ubiquitous in northwest and northeast China. With the exception of slope grassland, climate change primarily influenced the restoration of most grassland types, while human activities were the primary cause of degradation. Our analysis indicated a strong correlation between temperature and grassland degradation, while precipitation played a pivotal role in grassland restoration in northern China. Human interference demonstrated both positive and negative impacts on grassland changes. In conclusion, the increase in precipitation and the implementation of ecological restoration plans have effectively promoted the restoration of grasslands in northern China.

Change characteristics and influencing factors of grassland degradation in adjacent areas of the Qinghai-Tibet Plateau and suggestions for grassland restoration.

Natural grasslands are being progressively degraded around the world due to climate change and socioeconomic factors. Most of the drivers, processes, and consequences of grassland degradation are studied separately, and it is not yet clear whether the change characteristics and influence factors of adjacent areas of grassland are identical. We analyzed changes in grassland area and quality, and the influences of climate changes and socioeconomic factors from 1980-2018 in Maqu County, Xiahe County and Luqu County on the eastern Qinghai-Tibet Plateau (QTP). We found that areas with high and medium coverage grassland in Maqu County and Luqu County decreased continuously with time, while low coverage grassland areas increased in three counties. In Xiahe County, the medium coverage grassland area reduced with time (except for 2010), while the high and low coverage grassland areas increased. The actual net primary productivity of the three counties showed a downward trend. In Maqu County, the total grassland area had an extremely significant positive correlation with number of livestock going to market, commodity rate, gross domestic product (GDP), primary industry, tertiary industry, household density, and levels of junior middle school education and university education in the area. In Luqu County, the total grassland area high coverage grassland area were significantly negatively correlated with total number of livestock, secondary industry, levels of primary school education, and temperature. Ecological education was positively correlated with high coverage grassland, and negatively correlated with low coverage grassland in all three areas. The results of this study suggest that the best ways to restore the area and quality of grasslands in these areas would be to reduce the local cultivated land area and slow down the development of the primary and tertiary industries in Maqu County, and to control industry development and the total number of livestock in Luqu County. This study also suggests that improving education level and strengthening the level of ecological education are conducive to the restoration of grasslands.

Impacts of Climate Change and Anthropogenic Activities on the Net Primary Productivity of Grassland in the Southeast Tibetan Plateau

Climate change and anthropogenic activities have had a profound effect on the variation in grassland productivity in the Tibetan Plateau in recent decades. Quantifying the impacts of climatic and anthropogenic variables on grassland productivity is a necessary step in making the management policies of a sustainable grassland ecosystem. Net primary productivity (NPP) is an important part of the terrestrial carbon cycle and can be used to assess vegetation growth. Based on the Carnegie–Ames–Stanford Approach model and statistical analysis method, in this study we estimated the variations in grassland potential NPP (PNPP), actual NPP (ANPP) and human-induced NPP (HNPP) in the Northwest Sichuan Plateau (NWSP) of the Southeast Tibetan Plateau from 2001 to 2020. Also, we assessed the contribution of climatic change and anthropogenic activities to grassland ANPP. The results showed that the average values of grassland ANPP, PNPP and HNPP in the whole NWSP increased at the rates of 3.81, 9.14 and 7.18 g C m−2 a−1, respectively. Grassland ANPP increased in 91.7% of the total area. Climate-oriented impacts led grassland ANPP to increase in 82.6% of the area, and temperature increase was the dominant factor. Additionally, anthropogenic activity was the major reason for the grassland ANPP’s decline (5.4% of the total area). Overall, our findings are beneficial for the formulation of practical countermeasures regarding climate change adaption and damaged grassland recovering in the plateau.

Spatiotemporal variations and driving factors of global terrestrial vegetation productivity gap under the changing of climate, CO2, landcover and N deposition

Understanding the gap between potential productivity and the actual productivity of vegetation (vegetation productivity gap, VPG) is the basis to explore the potential productivity improvement and identify its constraints. In this study, we used the classification and regression tree model to simulate the potential net primary productivity (PNPP) based on the flux-observational maximum net primary productivity (NPP) across different vegetation types, that is, potential productivity. The actual NPP (ANPP) is obtained from the grid NPP averaged over five terrestrial biosphere models, and the VPG is subsequently calculated. On this basis, we used the variance decomposition method to separate the effects of climate change, land-use change, CO2, and nitrogen deposition on the trend and the interannual variability (IAV) of VPG from 1981 to 2010. Meanwhile, the spatiotemporal variation characteristics and influencing factors of VPG under future climate scenarios are analyzed. The results showed an increasing trend in PNPP and ANPP, while there was a decreasing trend of VPG in most parts of the world and this trend is more significant under representative concentration pathways (RCPs). The turning points (TP) of VPG variation are found under RCPs and the reduction trend of VPG before TP is more than that after TP. The VPG reduction in most regions was caused by the combined effects of PNPP and ANPP (41.68 %) from 1981 to 2010. However, the dominant factors of global VPG reduction are changing under RCPs, and the increment of NPP (39.71 % - 49.3 %) has become the dominating factor of VPG variation. CO2 plays a decisive role in the multi-year trend of VPG, while climate change is the main factor determining the IAV of VPG. Under changing climate, temperature and precipitation are negatively correlated with VPG in most parts of the world, and the relationship between radiation and VPG from weak negative to positive correlation.

黄河流域草地净初级生产力时空动态及其驱动机制

PDF HTML阅读 XML下载 导出引用 引用提醒 黄河流域草地净初级生产力时空动态及其驱动机制 DOI: 10.5846/stxb202108182295 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金课题（41701503，U21A2014）；中国博士后科学基金（2018M642736） Spatiotemporal dynamics of grassland net primary productivity and its driving mechanisms in the Yellow River Basin Author: Affiliation: Fund Project: The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:黄河流域是生态系统的敏感区，流域草地生态系统在气候变化和人类活动驱动下发生了显著变化。基于多源遥感影像和气象站点资料等，采用改进后的CASA模型估算2001-2018年黄河流域草地净初级生产力（NPP），评估定量反演结果精度，分析研究时段内流域草地净初级生产力时空动态，探讨气候要素和人类活动对流域草地净初级生产力的影响。结果表明：1）基于改进的CASA模型能够高精度模拟黄河流域草地NPP。2）2001-2018年黄河流域草地NPP呈增加趋势，且在2013年发生突变。2001-2013年气候和人类活动均促进流域草地NPP增加，而2013年后人类活动抑制流域草地NPP增加的作用明显增强，抑制区域面积较前一阶段增加34.89%。整体上，人类活动对草地NPP的影响强度低于气候要素影响强度。3）耕地和建设用地面积的变化，是驱动实际净初级生产力动态的重要人类活动要素。耕地和建设用地面积的增加与草地面积减少、实际净初级生产力增加速率的降低紧密相关。伴随经济发展，应坚持实施退耕还林还草政策，并加强对草地生态保护的监督。 Abstract:The Yellow River Basin (YRB) is a sensitive area for ecosystems. The grassland ecosystem in the YRB has changed significantly under climate change and human activities. Combing with multi-source remote sensing images and meteorological site data, we estimated the grassland net primary productivity (NPP) in the Yellow River Basin from 2001 to 2018 using the improved CASA model in this paper. After quantitatively evaluating the accuracy of simulated NPP data, we analyzed the spatiotemporal dynamics of grassland NPP and its responses to climate changes and human activities in the YRB. Results showed that 1) the improved CASA-based model could simulate the grassland NPP in the Yellow River Basin with high precision. 2) Grassland NPP in the YRB showed an increasing trend from 2001 to 2018, with a sudden change in 2013. Climate and human activities contributed to the increase of grassland NPP from 2001 to 2013. After 2013, the effect of human activities inhibiting the increase of grassland NPP increased significantly, and the area of the inhibited area increased by 34.89% over the previous period. Overall, the influence intensity of human activities on grassland NPP was lower than that of climate factors. 3) Change of cropland and built-up land area was the important human activity that drove the dynamics of actual NPP. The increase of cropland and built-up land closely related to the decrease of grassland area and the reduction of increase rate of actual NPP. With the development of the economy, the "Grain for Green" program should be persistently implemented, and the supervision of grassland ecological protection should be strengthened. 参考文献 相似文献 引证文献

Novel model for NPP prediction based on temperature and land use changes: A case in Sichuan and Chongqing, China

The net primary productivity (NPP) is a direct reflection of the productivity of vegetation communities; predicting changes in the NPP is important for assessing the sustainability of ecosystems. However, few studies have been conducted on the prediction of the NPP, and it is necessary to develop more prediction models. Therefore, in this study, a model based on temperature and land use/cover changes (LUCCs) was developed and applied to the Sichuan-Chongqing region, and the prediction results were obtained under the development scenarios composed of a shared socioeconomic pathway (SSP) and a representative concentration pathway (RCP). The results show that: (1) the NPP in the Sichuan-Chongqing region in 2020 simulated using the newly developed model to the actual NPP in 2020, and the kappa coefficient was 75.03%, which indicates that this model has a good applicability. (2) The total NPP increased in all five SSP-RCP scenarios (from high to low, SSP5-8.5, SSP4-6.0, SSP1-2.6, SSP2-4.5, and SSP3-7.0), but the SSP3-7.0 and SSP5-8.5 scenarios include uncontrolled urban expansion, leading to destruction of ecological areas. The SSP2-4.5 scenario continues the existing development pattern, with more moderate land use and NPP changes. The urban land use in the SSP1-2.6 and SSP4-6.0 scenarios is more intensive and the level of ecological protection is better. Simulating the LUCCs under different SSP-RCP scenarios and predicting the NPP changes can provide a theoretical basis for coping with future ecological changes and improving ecosystem stability.

Quantitative assessment of the contributions of climate change and human activities on vegetation degradation and restoration in typical ecologically fragile areas of China

Vegetation is a key component of terrestrial ecosystems, and its changes are very sensitive to climate change (CC) and human activities (HA), especially in ecologically fragile areas (EFA). However, the mechanism of relative contribution to vegetation degradation and restoration in EFA under the influence of CC and HA is still unclear. Based on the Carnegie-Ames-Stanford Approach (CASA) model and the Miami model, we estimated three key parameters of vegetation in China’s EFA: actual net primary productivity (ANPP), potential net primary productivity (PNPP), and human activity net primary productivity (HNPP). Using these variables, we quantitatively analyzed the relative contribution of CC and HA to vegetation restoration and degradation from 1982 to 2018 by the residual trend method. The results showed that the area ratio of vegetation restoration in China’s EFA was close to 71.6%, and the total ANPP increased by 174 Tg C, mainly concentrated in the Southwest Karst area and the Loess Plateau, but the Qinghai-Tibet Plateau showing a trend of degradation during 1982 to 2018. The climate background of each region was a key factor that can never be ignored to determine the positive or negative impact of regional CC and HA on vegetation activities. The CC and HA played a positive role in vegetation restoration areas, with a relative contribution of 59.1% and 16.4%, regional warming and humidification caused by the increase of temperature and precipitation was the main factor driving vegetation restoration. In vegetation degradation areas, The HA was the main driving force, especially the relative contribution of the Qinghai-Tibet Plateau, the arid and semi-arid areas and the Loess Plateau, which were as high as 96.8%, 83.3% and 80.2%, respectively. Finally, the annual average temperature (TEMP) and the annual solar radiation (SRAD) were relatively important and sensitive for the CASA model in the input environmental variables. This study provided a way to quantitatively understand the mechanism of climate change and human activities on the dynamic evolution of vegetation in EFA. In the future, the implementation of ecological protection and restoration projects need to fully consider the differences in climate background and strengthen the monitoring of the ecological environment.

Quantifying the Influence of Climate Change and Anthropogenic Activities on the Net Primary Productivity of China’s Grasslands

As one of China’s most common vegetation types, grasslands comprise about 27.5% of its terrestrial area and 41% of its carbon storage. Since climate change (CC) and human activities (HA) have a great effect on grasslands, quantifying the contributions of CC and HA on grassland net primary productivity (NPP) is crucial in understanding the mechanisms of grassland regional carbon balances. However, current approaches, including residual trend, biophysical model and environmental background-based methods, have limitations on different scales, especially on the national scale of China. To improve assessment accuracy, modifications to the environmental background-based method were introduced in calculating the CC and HA contributions to the actual NPP (ANPP). In this study, the grassland ANPP in national nature reserves was defined as the environmental background value (PNPP), which was only affected by CC and without HA. The pixel PNPP outside the nature reserves could be replaced by the pixel PNPP in the nature reserve with the most similar habitat in the same natural ecological geographical division. The impact of HA on grassland ANPP (HNPP) could be identified by calculating the difference between PNPP and ANPP. Finally, the contributions of CC and HA to ANPP changes were assessed by the trends of ANPP, PNPP, and HNPP. The results showed that the average grassland ANPP significantly increased from 2001 to 2020. CC contributed 71.0% to ANPP change, whereas HA contributed 29.0%. Precipitation was the main contributor to grassland growth among arid and semi-arid regions, while temperature inhibited productivity in these areas. HA was the major cause of degradation in China’s grasslands, although the effects have declined over time. The research could provide support support for government decisions. It could also provide a new and feasible research method for quantitatively evaluating grasslands and other ecosystems.

Contributions of Climatic and Anthropogenic Drivers to Net Primary Productivity of Vegetation in the Mongolian Plateau

Global warming and intense human activity are altering the net primary productivity (NPP) of vegetation in arid and semi-arid regions where vegetation ecosystems are sensitive to climate change, including the Mongolian Plateau (MP). To deepen the understanding of the dynamics of vegetation and its driving factors on the MP, the actual NPP (ANPP) of the MP from 2000 to 2019 was estimated based on a modified Carnegie–Ames–Stanford Approach (CASA) model. The Thornthwaite Memorial and Guangsheng Zhou models were applied concurrently to estimate the potential NPP of the vegetation, and different scenarios were constructed to evaluate quantitatively the impact of climate change and human activity on the vegetation productivity of our study area. The results showed that the carbon sequestration capacities of various vegetation types in the MP differ, with forest > cropland > grassland > wetland. The NPP increased significantly during 2000–2019. Most areas showed a continuous and stable change in vegetation ANPP, with the current trend in variation mainly reflected in the continuous improvement of vegetation. In general, restoration of vegetation was prominent in the MP, and human activities affected more than 30% of vegetation restoration. The ANPP was positively correlated with temperature and precipitation, the latter of which had a more significant effect. Desertification management, restoration of cropland to forest and grassland, afforestation and reasonable grazing activities were the main human activities performed to restore vegetation. This study is expected to advance the theoretical understanding of ecological protection and sustainable development in the MP.

The Different Impacts of Climate Variability and Human Activities on NPP in the Guangdong–Hong Kong–Macao Greater Bay Area

As two main drivers of vegetation dynamics, climate variability and human activities greatly influence net primary productivity (NPP) variability by altering the hydrothermal conditions and biogeochemical cycles. Therefore, studying NPP variability and its drivers is crucial to understanding the patterns and mechanisms that sustain regional ecosystem structures and functions under ongoing climate variability and human activities. In this study, three indexes, namely the potential NPP (NPPp), actual NPP (NPPa), and human-induced NPP (NPPh), and their variability from 2000 to 2020 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) were estimated and analyzed. Six main scenarios were generated based on change trends in the three indexes over the past 21 years, and the different relative impacts of climate variability and human activities on NPPa variability were quantitatively analyzed and identified. The results showed that the NPPp, NPPa, and NPPh had heterogeneous spatial distributions, and the average NPPp and NPPa values over the whole study area increased at rates of 3.63 and 6.94 gC·m−2·yr−1 from 2000 to 2020, respectively, while the NPPh decreased at a rate of −4.43 gC·m−2·yr−1. Climate variability and the combined effects of climate variability and human activities were the major driving factors of the NPPa increases, accounting for more than 72% of the total pixels, while the combined effects of the two factors caused the NPPa values to increase by 32–54% of the area in all cities expect Macao and across all vegetation ecosystems. Human activities often led to decreases in NPPa over more than 16% of the total pixels, and were mainly concentrated in the central cities of the GBA. The results can provide a reference for understanding NPP changes and can offer a theoretical basis for implementing ecosystem restoration, ecological construction, and conservation practices in the GBA.

Effects of climate change and human activities on net primary production of wetlands on the Zoige Plateau from 1990 to 2015

Wetlands are vulnerable to climate change and human activities. However, the past changes caused by climate and human activities on net primary production (NPP) were unclear on the Zoige Plateau, which is on the Qinghai-Tibet Plateau. In this study, the impact of climatic and anthropogenic pressure on the NPP of wetlands on the Zoige Plateau from 1990 to 2015 was explored. We assessed and quantified the effects of climatic and anthropogenic factors on NPP using a simulated process model (LPJ_WHyMe) and a remote sensing model (CASA). Our simulations suggested that the annual average potential net primary production (NPPp) fluctuated during the study period and peaked in 2008 (347.37 g C m-2 year-1), while the total wetland NPPp peaked in 2000 (1.75 Tg C year-1). The results also showed that the annual average actual net primary production (NPPa) reached the lowest value of 206.04 g C m-2 year-1 in 2000. The total wetland NPPa ranged from 0.97 to 1.15 Tg C year-1 and continuously decreased over the study period. Our research revealed that human activities accounted for 22.37–36.45% of wetland NPP reduction over the study period. These results suggested that reducing human interventions can improve the NPP of wetlands. However, some of the negative effects of human activities have been offset by ecological restoration projects. These results provide a reference and scientific support for wetland protection and sustainable development.

Quantifying and Mapping Human Appropriation of Net Primary Productivity in Qinghai Grasslands in China

Human appropriation of net primary productivity (HANPP) is an important indicator for assessing ecological sustainability. However, the spatiotemporal dynamics of HANPP in the Qinghai grasslands remain unclear. In this study, we used the spatially explicit Biome-BGCMuSo model to quantify and map HANPP in the Qinghai grasslands from 1979 to 2018. Generally, the actual net primary productivity (NPPact) was slightly lower than the potential net primary productivity (NPPpot), and the difference between the NPPpot and NPPact increased slightly over time. From 1979 to 2001, the NPPpot and NPPact were relatively stable; however, from 2001 to 2018, both showed significant fluctuating upward trends. From 1979 to 2018, HANPP showed a fluctuating upward trend from 6.36 to 31.85 gC/m2/yr, with an average increase of 2.14 gC/m2/yr. The average HANPP was 16.90 gC/m2/yr, which represented 18.80% of the NPPpot of Qinghai grasslands. High HANPP mainly occurred in eastern Qinghai, whereas it was low in central and western Qinghai. Conversely, from 1979 to 2018, the HANPP efficiency decreased in a fluctuating way from 98.28% to 72.05%, with an average annual decrease of 0.66%. The interannual variations in the HANPP efficiency and harvest were negatively correlated, with a correlation coefficient of −0.46 (p < 0.01). The average HANPP efficiency was 85.33%, and the values in most grids were between 80% and 100%, being relatively low in southern and eastern Qinghai. In rare cases, the HANPP efficiency was greater than 1. This study clarifies the details of spatiotemporal dynamics of HANPP in the Qinghai grasslands and indicates the need to optimize local management of grassland resources to ensure future ecological sustainability.

Assessment of ecological restoration projects under water limits: Finding a balance between nature and human needs

Revegetation has significantly contributed to improvements in ecosystem services, such as carbon sequestration and soil retention. Yet, vegetation expansion in water-limited regions may generate conflict of water demand between nature and humans. Present studies are still lacking when it comes to identifying the permissible vegetation capacity, i.e. net primary productivity (NPP) threshold, based on the local water resources limits, and further proposing adjustment and optimization strategies to keep water use balanced in anthropogenic-biological systems. Under such a circumstance, this study assesses the difference between the actual NPP and NPP thresholds at regional and ecosystem scales in China. The results show that 8 out of 31 provinces have their provincial actual NPP above the regional NPP thresholds, mainly concentrated in northern China between 400 and 800 mm iso-precipitation line, i.e. North China Plain (Beijing-Tianjin-Hebei), the middle reaches of the Yellow River Basin (Shaanxi and Henan provinces), and the Northeast China (Heilongjiang, Jilin and Liaoning). Forest ecosystems dominate the difference between the actual total woodland and grassland ecosystems NPP and the permissible NPP thresholds in these regions, ranging from 67% (Beijing) to 99% (Tianjin). If the current vegetation intensity in these regions remains unchanged, the areas of woodland and grassland ecosystems should be optimized 0–48% and 0–100% of their present areas to balance the water demand between the ecosystems and humans, without considering the potential consequence of climate change and soil erosion. Although 23 provinces have their regional actual NPP below their permissible NPP thresholds, 6 out of 23 provinces still have their woodland and grassland ecosystems NPP above the corresponding NPP thresholds, mainly focusing on the Northwestern China north over the 400 mm iso-precipitation line, including Inner Mongolia, Qinghai, Hainan, Shanxi, Gansu and Xinjiang. Forest ecosystems also dominate the negative NPP differences in these regions, ranging from 91% (Inner Mongolia) to 46% (Gansu). These reveal the hidden and potential pressure in the 6 provinces to balance limited water resources in the local anthropogenic-biological system. This study provides a method to assess the water-resources permissible NPP threshold and further proposes the specific adjustment and optimization plans for the areas with actual NPP above the corresponding NPP thresholds, which can provide guidance for ecological restoration program implementations in a more sustainable way.