Shuli Niu

Global patterns of the dynamics of soil carbon and nitrogen stocks following afforestation: a meta-analysis

• Afforestation has been proposed as an effective method of carbon (C) sequestration; however, the magnitude and direction of soil carbon accumulation following afforestation and its regulation by soil nitrogen (N) dynamics are still not well understood. • We synthesized the results from 292 sites and carried out a meta-analysis to evaluate the dynamics of soil C and N stocks following afforestation. • Changes in soil C and N stocks were significantly correlated and had a similar temporal pattern. Significant C and N stock increases were found 30 and 50 yr after afforestation, respectively. Before these time points, C and N stocks were either depleted or unchanged. Carbon stock increased following afforestation on cropland and pasture, and in tropical, subtropical and boreal zones. The soil N stock increased in the subtropical zone. The soil C stock increased after afforestation with hardwoods such as Eucalyptus, but did not change after afforestation with softwoods such as pine. Soil N stocks increased and decreased, respectively, after afforestation with hardwoods (excluding Eucalyptus) and pine. • These results indicate that soil C and N stocks both increase with time after afforestation, and that C sequestration through afforestation depends on prior land use, climate and the tree species planted.

Quantifying global soil carbon losses in response to warming

The majority of the Earth’s terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12–17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon–climate feedback that could accelerate climate change.

Photosynthetic overcompensation under nocturnal warming enhances grassland carbon sequestration

A mechanistic understanding of the carbon (C) cycle-climate change feedback is essential for projecting future states of climate and ecosystems. Here we report a novel field mechanism and evidence supporting the hypothesis that nocturnal warming in a temperate steppe ecosystem in northern China can result in a minor C sink instead of a C source as models have predicted. Nocturnal warming increased leaf respiration of two dominant grass species by 36.3%, enhanced consumption of carbohydrates in the leaves (72.2% and 60.5% for sugar and starch, respectively), and consequently stimulated plant photosynthesis by 19.8% in the subsequent days. Our experimental findings confirm previous observations of nocturnal warming stimulating plant photosynthesis through increased draw-down of leaf carbohydrates at night. The enhancement of plant photosynthesis overcompensated the increased C loss via plant respiration under nocturnal warming and shifted the steppe ecosystem from a minor C source (1.87 g C x m(-2) x yr(-1)) to a C sink (21.72 g C x m(-2) x yr(-1)) across the three growing seasons from 2006 to 2008. Given greater increases in daily minimum than maximum temperature in many regions, plant photosynthetic overcompensation may partially serve as a negative feedback mechanism for terrestrial biosphere to climate warming.

A global analysis of soil acidification caused by nitrogen addition

Nitrogen (N) deposition-induced soil acidification has become a global problem. However, the response patterns of soil acidification to N addition and the underlying mechanisms remain far from clear. Here, we conducted a meta-analysis of 106 studies to reveal global patterns of soil acidification in responses to N addition. We found that N addition significantly reduced soil pH by 0.26 on average globally. However, the responses of soil pH varied with ecosystem types, N addition rate, N fertilization forms, and experimental durations. Soil pH decreased most in grassland, whereas boreal forest was not observed a decrease to N addition in soil acidification. Soil pH decreased linearly with N addition rates. Addition of urea and NH4NO3 contributed more to soil acidification than NH4-form fertilizer. When experimental duration was longer than 20 years, N addition effects on soil acidification diminished. Environmental factors such as initial soil pH, soil carbon and nitrogen content, precipitation, and temperature all influenced the responses of soil pH. Base cations of Ca2+, Mg2+ and K+ were critical important in buffering against N-induced soil acidification at the early stage. However, N addition has shifted global soils into the Al3+ buffering phase. Overall, this study indicates that acidification in global soils is very sensitive to N deposition, which is greatly modified by biotic and abiotic factors. Global soils are now at a buffering transition from base cations (Ca2+, Mg2+ and K+) to non-base cations (Mn2+ and Al3+). This calls our attention to care about the limitation of base cations and the toxic impact of non-base cations for terrestrial ecosystems with N deposition.

Joint control of terrestrial gross primary productivity by plant phenology and physiology

Significance Terrestrial gross primary productivity (GPP), the total photosynthetic CO2 fixation at ecosystem level, fuels all life on land. However, its spatiotemporal variability is poorly understood, because GPP is determined by many processes related to plant phenology and physiological activities. In this study, we find that plant phenological and physiological properties can be integrated in a robust index—the product of the length of CO2 uptake period and the seasonal maximal photosynthesis—to explain the GPP variability over space and time in response to climate extremes and during recovery after disturbance. Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate–carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy–covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000–2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r2 = 0.90) and GPP recovery after a fire disturbance in South Dakota (r2 = 0.88). Additional analysis of the eddy–covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space.

Non-additive effects of water and nitrogen addition on ecosystem carbon exchange in a temperate steppe

Changes in precipitation and nitrogen (N) deposition can influence ecosystem carbon (C) cycling and budget in terrestrial biomes, with consequent feedbacks to climate change. However, little is known about the main and interactive effects of water and N additions on net ecosystem C exchange (NEE). In a temperate steppe of northern China, a field-manipulated experiment was conducted to evaluate the responses of NEE and its components to improve N and water availability from 2005 to 2008. The results showed that both water and N additions stimulated gross ecosystem productivity (GEP), ecosystem respiration (ER), and NEE. Water addition increased GEP by 17%, ER by 24%, and NEE by 11% during the experimental period, whereas N addition increased GEP by 17%, ER by 16%, and NEE by 19%. The main effects of both water and N additions changed with time, with the strongest water stimulation in the dry year and a diminishing N stimulation over time. When water and N were added in combination, there were non-additive effects of water and N on ecosystem C fluxes, which could be explained by the changes in species composition and the shifts of limiting resources from belowground (water or N) to aboveground (light). The positive water and N additions effects indicate that increasing precipitation and N deposition in the future will favor C sequestration in the temperate steppe. The non-additive effects of water and N on ecosystem C fluxes suggest that multifactor experiments are better able to capture complex interactive processes, thus improving model simulations and projections.

Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms.

• It is well established that individual organisms can acclimate and adapt to temperature to optimize their functioning. However, thermal optimization of ecosystems, as an assemblage of organisms, has not been examined at broad spatial and temporal scales. • Here, we compiled data from 169 globally distributed sites of eddy covariance and quantified the temperature response functions of net ecosystem exchange (NEE), an ecosystem-level property, to determine whether NEE shows thermal optimality and to explore the underlying mechanisms. • We found that the temperature response of NEE followed a peak curve, with the optimum temperature (corresponding to the maximum magnitude of NEE) being positively correlated with annual mean temperature over years and across sites. Shifts of the optimum temperature of NEE were mostly a result of temperature acclimation of gross primary productivity (upward shift of optimum temperature) rather than changes in the temperature sensitivity of ecosystem respiration. • Ecosystem-level thermal optimality is a newly revealed ecosystem property, presumably reflecting associated evolutionary adaptation of organisms within ecosystems, and has the potential to significantly regulate ecosystem-climate change feedbacks. The thermal optimality of NEE has implications for understanding fundamental properties of ecosystems in changing environments and benchmarking global models.

Global patterns and substrate-based mechanisms of the terrestrial nitrogen cycle

Nitrogen (N) deposition is impacting the services that ecosystems provide to humanity. However, the mechanisms determining impacts on the N cycle are not fully understood. To explore the mechanistic underpinnings of N impacts on N cycle processes, we reviewed and synthesised recent progress in ecosystem N research through empirical studies, conceptual analysis and model simulations. Experimental and observational studies have revealed that the stimulation of plant N uptake and soil retention generally diminishes as N loading increases, while dissolved and gaseous losses of N occur at low N availability but increase exponentially and become the dominant fate of N at high loading rates. The original N saturation hypothesis emphasises sequential N saturation from plant uptake to soil retention before N losses occur. However, biogeochemical models that simulate simultaneous competition for soil N substrates by multiple processes match the observed patterns of N losses better than models based on sequential competition. To enable better prediction of terrestrial N cycle responses to N loading, we recommend that future research identifies the response functions of different N processes to substrate availability using manipulative experiments, and incorporates the measured N saturation response functions into conceptual, theoretical and quantitative analyses.

Nitrogen regulation of the climate-carbon feedback: evidence from a long-term global change experiment

Modeling studies have shown that nitrogen (N) strongly regulates ecosystem responses and feedback to climate warming. However, it remains unclear what mechanisms underlie N regulation of ecosystem-climate interactions. To examine N regulation of ecosystem feedback to climate change, we have conducted a warming and clipping experiment since November 1999 in a tallgrass prairie of the Great Plains, USA. Infrared heaters were used to elevate soil temperature by an average of 1.96 degrees C at a depth of 2.5 cm from 2000 to 2008. Yearly biomass clipping mimicked hay or biofuel feedstock harvest. We measured carbon (C) and N concentrations, estimated their content and C:N ratio in plant, root, litter, and soil pools. Warming significantly stimulated C storage in aboveground plant, root, and litter pools by 17%, 38%, and 29%, respectively, averaged over the nine years (all P < 0.05) but did not change soil C content or N content in any pool. Plant C:N ratio and nitrogen use efficiency increased in the warmed plots compared to the control plots, resulting primarily from increased dominance of C4 plants in the community. Clipping significantly decreased C and N storage in plant and litter pools (all P < 0.05) but did not have interactive effects with warming on either C or N pools over the nine years. Our results suggest that increased ecosystem nitrogen use efficiency via a shift in species composition toward C4 dominance rather than plant N uptake is a key mechanism underlying warming stimulation of plant biomass growth.

The role of data assimilation in predictive ecology

In this rapidly changing world, improving the capacity to predict future dynamics of ecological systems and their services is essential for better stewardship of the earth system. Prediction relies on models that describe our understanding of the major processes that underlie system dynamics and data about these processes and the present state of ecosystems. Prediction becomes more effective when models are well informed by data. A technological revolution in the capacity to collect data now provides very different opportunities to test hypotheses and project future dynamics than when many standard statistical tests were first developed. Data assimilation is an emerging statistical approach to combine models with data in a rigorous way to constrain model parameters and system states, identify model error, and improve ecological prediction. In this paper, we illustrate how data assimilation can improve ecological prediction to support decision-making by reviewing applications of data assimilation across four different research fields: (1) emerging infectious disease, (2) fisheries, (3) fire, and (4) the terrestrial carbon cycle. Across these fields, data assimilation substantially improves prediction accuracy, highlighting its important role in enabling predictive ecology. Data assimilation with regional and global models faces major challenges, such as the large number of parameters to be estimated, high computational demands, the need to integrate multiple and heterogeneous data sets, and complex social-ecological interactions. Nevertheless, data assimilation provides an important statistical approach that has great potential to enhance the predictive capacity of ecological models in a changing climate.