Contributions of natural and human factors to increases in vegetation productivity in China

Increasing trends in vegetation productivity have been identified for the last three decades for many regions in the northern hemisphere including China. Multiple natural and human factors are possibly responsible for the increases in vegetation productivity, while their relative contributions remain unclear. Here we analyzed the long-term trends in vegetation productivity in China using the satellite-derived normalized difference vegetation index (NDVI) and assessed the relationships of NDVI with a suite of natural (air temperature, precipitation, photosynthetically active radiation (PAR), atmospheric carbon dioxide (CO2) concentrations, and nitrogen (N) deposition) and human (afforestation and improved agricultural management practices) factors. Overall, China exhibited an increasing trend in vegetation productivity with an increase of 2.7%. At the provincial scale, eleven provinces exhibited significant increases in vegetation productivity, and the majority of these provinces are located within the northern half of the country. At the national scale, annual air temperature was most closely related to NDVI and explained 36.8% of the variance in NDVI, followed by afforestation (25.5%) and crop yield (15.8%). Altogether, temperature, total forest plantation area, and crop yield explained 78.1% of the variance in vegetation productivity at the national scale, while precipitation, PAR, atmospheric CO2 concentrations, and N deposition made no significant contribution to the increases in vegetation productivity. At the provincial scale, each factor explained a part of the variance in NDVI for some provinces, and the increases in NDVI for many provinces could be attributed to the combined effects of multiple factors. Crop yield and PAR were correlated with NDVI for more provinces than were other factors, indicating that both elevated crop yield resulting from improved agricultural management practices and increasing diffuse radiation were more important than other factors in increasing vegetation productivity at the provincial scale. The relative effects of the natural and human factors on vegetation productivity varied with spatial scale. The true contributions of multiple factors can be obscured by the correlation among these variables, and it is essential to examine the contribution of each factor while controlling for other factors. Future changes in climate and human activities will likely have larger influences on vegetation productivity in China

Drought events and their effects on vegetation productivity in China

Many parts of the world have experienced frequent and severe droughts during the last few decades. Most previous studies examined the effects of specific drought events on vegetation productivity. In this study, we characterized the drought events in China from 1982 to 2012 and assessed their effects on vegetation productivity inferred from satellite data. We first assessed the occurrence, spatial extent, frequency, and severity of drought using the Palmer Drought Severity Index (PDSI). We then examined the impacts of droughts on China\u27s terrestrial ecosystems using the Normalized Difference Vegetation Index (NDVI). During the period 1982–2012, China\u27s land area (%) experiencing drought showed an insignificant trend. However, the drought conditions had been more severe over most regions in northern parts of China since the end of the 1990s, indicating that droughts hit these regions more frequently due to the drier climate. The severe droughts substantially reduced annual and seasonal NDVI. The magnitude and direction of the detrended NDVI under drought stress varied with season and vegetation type. The inconsistency between the regional means of PDSI and detrended NDVI could be attributed to different responses of vegetation to drought and the timing, duration, severity, and lag effects of droughts. The negative effects of droughts on vegetation productivity were partly offset by the enhancement of plant growth resulting from factors such as lower cloudiness, warming climate, and human activities (e.g., afforestation, improved agricultural management practices)

Water use efficiency of China\u27s terrestrial ecosystems and responses to drought

Water use efficiency (WUE) measures the trade-off between carbon gain and water loss of terrestrial ecosystems, and better understanding its dynamics and controlling factors is essential for predicting ecosystem responses to climate change. We assessed the magnitude, spatial patterns, and trends of WUE of China’s terrestrial ecosystems and its responses to drought using a process-based ecosystem model. During the period from 2000 to 2011, the national average annual WUE (net primary productivity (NPP)/evapotranspiration (ET)) of China was 0.79 g C kg−1 H2O. Annual WUE decreased in the southern regions because of the decrease in NPP and the increase in ET and increased in most northern regions mainly because of the increase in NPP. Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. “Turning-points” were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE. The cumulative lagged effect of drought on monthly WUE varied by region. Our findings have implications for ecosystem management and climate policy making. WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity

Vegetation response to extreme climate events on the Mongolian Plateau from 2000 to 2010

Climate change has led to more frequent extreme winters (aka, dzud) and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000–2002 combined summer drought–dzud and 2010 dzud were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000–2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000–2001, 2005 and 2009) were characterized by negative anomalies with peak values between �1.5 and �0.5 and were statistically different (P \u3c 0:001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (p \u3c 0:001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI \u3c �1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (R2 D 65 and 60, p \u3c 0:05) than for the IM grassland biome (R2 D 53, p \u3c 0:05). Our results showed significant differences in the responses to extreme climatic events (summer drought and dzud) between the desert and grassland biomes on the Plateau

Satellite evidence for significant biophysical consequences of the “Grain for Green” Program on the Loess Plateau in China

Afforestation has been implemented worldwide as regional and national policies to address environmental problems and to improve ecosystem services. China\u27s central government launched the “Grain for Green” Program (GGP) in 1999 to increase forest cover and to control soil erosion by converting agricultural lands on steep slopes to forests and grasslands. Here a variety of satellite data products from the Moderate Resolution Imaging Spectroradiometer were used to assess the biophysical consequences of the GGP for the Loess Plateau, the pilot region of the program. The average tree cover of the plateau substantially increased because of the GGP, with a relative increase of 41.0%. The GGP led to significant increases in enhanced vegetation index (EVI), leaf area index, and the fraction of photosynthetically active radiation absorbed by canopies. The increase in forest productivity as approximated by EVI was not driven by elevated air temperature, changing precipitation, or rising atmospheric carbon dioxide concentrations. Moreover, the afforestation significantly reduced surface albedo, leading to a positive radiative forcing and a warming effect on the climate. The GGP also led to a significant decline in daytime land surface temperature and exerted a cooling effect on the climate. The GGP therefore has significant biophysical consequences by altering carbon cycling, hydrologic processes, and surface energy exchange and has significant feedbacks to the regional climate. The net radiative forcing on the climate depends on the offsetting of the negative forcing from carbon sequestration and higher evapotranspiration and the positive forcing from lower albedo

Aboveground net primary productivity of vegetation along a climate-related gradient in a Eurasian temperate grassland: spatiotemporal patterns and their relationships with climate factors

Accurate assessments of spatiotemporal patterns in net primary productivity and their links to climate are important to obtain a deeper understanding of the function, stability and sustainability of grassland ecosystems. We combined a satellite-derived NDVI time-series dataset and field-based samples to investigate spatiotemporal patterns in aboveground net primary productivity (ANPP), and we examined the effect of growing season air temperate (GST) and precipitation (GSP) on these patterns along a climaterelated gradient in an eastern Eurasian grassland. Our results indicated that the ANPP fluctuated with no significant trend during 2001-2012. The spatial distribution of ANPP was heterogeneous and decreased from northeast to southwest. The interannual changes in ANPP were mainly controlled by year-to-year GSP; a strong correlation of interannual variability between ANPP and GSP was observed. Similarly, GSP strongly influenced spatial variations in ANPP, and the slopes of fitted linear functions of the GSP-ANPP relationship increased from arid temperate desert grassland to humid meadow grassland. An exponential function could be used to fit the GSP-ANPP relationship for the entire region. An improved moisture index that combines the effects of GST and GSP better explained the variations in ANPP compared with GSP alone. In comparisons with the previous studies, we found that the relationships between spatiotemporal variations in ANPP and climate factors were probably scale dependent. We imply that the quantity and spatial range of analyzed samples contribute to these different results. Multi-scale studies are necessary to improve our knowledge of the response of grassland ANPP to climate change.ArticleENVIRONMENTAL EARTH SCIENCES.76(1):56(2017)journal articl

Impacts of Future Climate Change on Net Primary Productivity of Grassland in Inner Mongolia, China

Net Primary Productivity (NPP) of grassland is a key variable of terrestrial ecosystems and is an important parameter for characterizing carbon cycles in grassland ecosystems. In this research, the Inner Mongolia grassland NPP was calculated using the Miami Model and the impact of climate change on grassland NPP was subsequently analyzed under the Special Report on Emissions Scenarios (SRES) A2, B2, and A1B scenarios, which are inferred from Providing Regional Climates for Impacts Studies (PRECIS) climate model system. The results showed that: (1) the NPP associated with these three scenarios had a similar distribution in Inner Mongolia: the grassland NPP increased gradually from the western region, with less than 200 g/m2/yr, to the southeast region, with more than 800 g/m2/yr. Precipitation was the main factor determining the grassland NPP; (2) compared with the baseline (1961-1990), there would be an overall increase in grassland NPP during three time periods (2020s: 2011-2040, 2050s: 2041-2070, and 2080s: 2071-2100) under the A2 and B2 scenarios; (3) under the A1B scenario, there will be a decreasing trend at middle-west region during the 2020s and 2050s; while there will be a very significant decrease from the 2050s to 2080s for middle Inner Mongolia; and (4) grassland NPP under the A1B scenario would present the most significant increase among the three scenarios, and would have the least significant increase under the B2 scenario

An analysis of long-term effects of climate change and socioeconomic activities on grassland productivity of inner Mongolia

In recent years, researchers have recognized the complexity of the interactions between the ecological system and the economic development of human society. However, the complicated relationships overwhelm traditional statistical procedures and require an innovative approach to investigate their dynamics. We proposed this study to provide a unique perspective in analyzing the long-term causal relationships between the grassland productivity, climate change, and socioeconomic development of Inner Mongolia Autonomous Region (IMAR) of China. Our attempt began with acquiring remotely sensed satellite imagery, climatic variations, and aggregated annual reports of the socio-economy of the IMAR in vegetation growing seasons for 15 years. The spatial and temporal dissimilarities of the raw observations prevented us from exploiting the potential of this valuable dataset; thus, we interpolated and extrapolated the data to generate a panel dataset with consistent spatial and temporal resolutions. Then, we took another step to preprocess the panel data by applying a signal filter to isolate the long-term trend of change from the inter- and intra-annual cyclic patterns and used the trends as the input for a panel data model. The results from our statistical analysis indicated that the independent variables explained the variations in the dependent variable extremely well, while the polynomial terms of climatic variables were significant with limited marginal effect and most of the climatic variables showed negative linear impact on the grassland productivity. In the meantime, we found not all socioeconomic variables we attempted to include into the model significantly affected grassland productivity, especially the variables describing the financial status of the IMAR residents

A Global Assessment of Long-Term Greening and Browning Trends in Pasture Lands Using the GIMMS LAI3g Dataset

Pasture ecosystems may be particularly vulnerable to land degradation due to the high risk of human disturbance (e.g., overgrazing, burning, etc.), especially when compared with natural ecosystems (non-pasture, non-cultivated) where direct human impacts are minimal. Using maximum annual leaf area index (LAImax) as a proxy for standing biomass and peak annual aboveground productivity, we analyze greening and browning trends in pasture areas from 1982-2008. Inter-annual variability in pasture productivity is strongly controlled by precipitation (positive correlation) and, to a lesser extent, temperature (negative correlation). Linear temporal trends are significant in 23% of pasture cells, with the vast majority of these areas showing positive LAImax trends. Spatially extensive productivity declines are only found in a few regions, most notably central Asia, southwest North America, and southeast Australia. Statistically removing the influence of precipitation reduces LAImax trends by only 13%, suggesting that precipitation trends are only a minor contributor to long-term greening and browning of pasture lands. No significant global relationship was found between LAImax and pasture intensity, although the magnitude of trends did vary between cells classified as natural versus pasture. In the tropics and Southern Hemisphere, the median rate of greening in pasture cells is significantly higher than for cells dominated by natural vegetation. In the Northern Hemisphere extra-tropics, conversely, greening of natural areas is 2-4 times the magnitude of greening in pasture areas. This analysis presents one of the first global assessments of greening and browning trends in global pasture lands, including a comparison with vegetation trends in regions dominated by natural ecosystems. Our results suggest that degradation of pasture lands is not a globally widespread phenomenon and, consistent with much of the terrestrial biosphere, there have been widespread increases in pasture productivity over the last 30 years