A global meta-analysis on the effects of organic and inorganic fertilization on grasslands and croplands.

A central role for nature-based solution is to identify optimal management practices to address environmental challenges, including carbon sequestration and biodiversity conservation. Inorganic fertilization increases plant aboveground biomass but often causes a tradeoff with plant diversity loss. It remains unclear, however, whether organic fertilization, as a potential nature-based solution, could alter this tradeoff by increasing aboveground biomass without plant diversity loss. Here we compile data from 537 experiments on organic and inorganic fertilization across grasslands and croplands worldwide to evaluate the responses of aboveground biomass, plant diversity, and soil organic carbon (SOC). Both organic and inorganic fertilization increase aboveground biomass by 56% and 42% relative to ambient, respectively. However, only inorganic fertilization decreases plant diversity, while organic fertilization increases plant diversity in grasslands with greater soil water content. Moreover, organic fertilization increases SOC in grasslands by 19% and 15% relative to ambient and inorganic fertilization, respectively. The positive effect of organic fertilization on SOC increases with increasing mean annual temperature in grasslands, a pattern not observed in croplands. Collectively, our findings highlight organic fertilization as a potential nature-based solution that can increase two ecosystem services of grasslands, forage production, and soil carbon storage, without a tradeoff in plant diversity loss.

Nitrogen addition delays the emergence of an aridity-induced threshold for plant biomass.

Crossing certain aridity thresholds in global drylands can lead to abrupt decays of ecosystem attributes such as plant productivity, potentially causing land degradation and desertification. It is largely unknown, however, whether these thresholds can be altered by other key global change drivers known to affect the water-use efficiency and productivity of vegetation, such as elevated CO2 and nitrogen (N). Using >5000 empirical measurements of plant biomass, we showed that crossing an aridity (1-precipitation/potential evapotranspiration) threshold of ∼0.50, which marks the transition from dry sub-humid to semi-arid climates, led to abrupt declines in aboveground biomass (AGB) and progressive increases in root:shoot ratios, thus importantly affecting carbon stocks and their distribution. N addition significantly increased AGB and delayed the emergence of its aridity threshold from 0.49 to 0.55 (P < 0.05). By coupling remote sensing estimates of leaf area index with simulations from multiple models, we found that CO2 enrichment did not alter the observed aridity threshold. By 2100, and under the RCP 8.5 scenario, we forecast a 0.3% net increase in the global land area exceeding the aridity threshold detected under a scenario that includes N deposition, in comparison to a 2.9% net increase if the N effect is not considered. Our study thus indicates that N addition could mitigate to a great extent the negative impact of increasing aridity on plant biomass in drylands. These findings are critical for improving forecasts of abrupt vegetation changes in response to ongoing global environmental change.

Non-symmetric responses of leaf onset date to natural warming and cooling in northern ecosystems.

The northern hemisphere has experienced regional cooling, especially during the global warming hiatus (1998-2012) due to ocean energy redistribution. However, the lack of studies about the natural cooling effects hampers our understanding of vegetation responses to climate change. Using 15,125 ground phenological time series at 3,620 sites since the 1950s and 31-year satellite greenness observations (1982-2012) covering the warming hiatus period, we show a stronger response of leaf onset date (LOD) to natural cooling than to warming, i.e. the delay of LOD caused by 1°C cooling is larger than the advance of LOD with 1°C warming. This might be because cooling leads to larger chilling accumulation and heating requirements for leaf onset, but this non-symmetric LOD response is partially offset by warming-related drying. Moreover, spring greening magnitude, in terms of satellite-based greenness and productivity, is more sensitive to LOD changes in the warming area than in the cooling. These results highlight the importance of considering non-symmetric responses of spring greening to warming and cooling when predicting vegetation-climate feedbacks.

Global pattern of soil priming effect intensity and its environmental drivers.

The microbial priming effect-the decomposition of soil organic carbon (SOC) induced by plant inputs-has long been considered an important driver of SOC dynamics, yet we have limited understanding about the direction, intensity, and drivers of priming across ecosystem types and biomes. This gap hinders our ability to predict how shifts in litter inputs under global change can affect climate feedbacks. Here, we synthesized 18,919 observations of CO2 effluxes in 802 soils across the globe to test the relative effects (i.e., log response ratio [RR]) of litter additions on native SOC decomposition and identified the dominant environmental drivers in natural ecosystems and agricultural lands. Globally, litter additions enhanced native SOC decomposition (RR = 0.35, 95% CI: 0.32-0.38), with greater priming effects occurring with decreasing latitude and more in agricultural soils (RR = 0.43) than in uncultivated soils (RR = 0.28). In natural ecosystems, soil pH and microbial community composition (e.g., bacteria: fungi ratio) were the best predictors of priming, with greater effects occurring in acidic, bacteria-dominated sandy soils. In contrast, the substrate properties of plant litter and soils were the most important drivers of priming in agricultural systems since soils with high C:N ratios and those receiving large inputs of low-quality litter had the highest priming effects. Collectively, our results suggest that, though different factors may control priming effects, the ubiquitous nature of priming means that alterations of litter quality and quantity owing to global changes will likely have consequences for global C cycling and climate forcing.

Lagged precipitation effect on plant productivity is influenced collectively by climate and edaphic factors in drylands.

Lagged precipitation effect explains a large proportion of annual aboveground net primary productivity in some dryland ecosystems. Using satellite-derived plant productivity and precipitation datasets in the Northern Hemisphere drylands during 2000-2018, we identify 1111 pixels mainly located in the Tibetan Plateau, the western US, and Kazakhstan where productivities are significantly correlated with previous-year precipitation (hereafter, the lagged type). Differences in climatic and edaphic factors between the lagged and unlagged (pixels where productivities are not correlated with previous-year precipitation) types are evaluated. Permutational multivariate analysis of variance shows that the two types differ significantly regarding six climatic and edaphic factors. Compared to unlagged type, water availability, soil organic carbon, total nitrogen, field capacity, silt content and radiation are more sensitive to changes in precipitation in lagged type. Water availability is the most important factor for distinguishing the two types, followed by soil organic carbon, total nitrogen, field capacity, soil texture, and radiation. Our study suggests that the altered sensitivities of several climatic and edaphic factors to precipitation collectively affect the lagged effect of precipitation on productivity in drylands.

Unaltered soil microbial community composition, but decreased metabolic activity in a semiarid grassland after two years of passive experimental warming.

Soil microbial communities regulate soil carbon feedbacks to climate warming through microbial respiration (i.e., metabolic rate). A thorough understanding of the responses of composition, biomass, and metabolic rate of soil microbial community to warming is crucial to predict soil carbon stocks in a future warmer climate. Therefore, we conducted a field manipulative experiment in a semiarid grassland on the Loess Plateau of China to evaluate the responses of the soil microbial community to increased temperature from April 2015 to December 2017. Soil temperature was 2.0°C higher relative to the ambient when open-top chambers (OTCs) were used. Warming did not affect microbial biomass or the composition of microbial functional groups. However, warming significantly decreased microbial respiration, directly resulting from soil pH decrease driven by the comediation of aboveground biomass increase, inorganic nitrogen increase, and moisture decrease. These findings highlight that the soil microbial community structure of semiarid grasslands resisted the short-term warming by 2°C, although its metabolic rate declined.

Legacy effects of precipitation amount and frequency on the aboveground plant biomass of a semi-arid grassland.

Precipitation is known to have legacy effects on plant diversity and production of many terrestrial ecosystems. Precipitation regimes are expected to become more variable with increasing extreme precipitation events. However, how previous-year precipitation regimes affect the current-year aboveground biomass (AGB) remains largely unknown. Here we measured long-term (2004-2017) AGB in a semi-arid grassland of the Chinese Loess Plateau to evaluate the impact of previous-year precipitation amount on current-year AGB. Furthermore, to assess the response of current-year AGB to previous-year precipitation regimes, we conducted a field manipulation experiment that included three precipitation regimes during 2014-2017: (i) ambient precipitation, (ii) monthly added four 5 mm rain events, and (iii) monthly added one 20 mm event. Both the long-term (2004-2017) observations under ambient precipitation and short-term (2014-2017) measurements under manipulative treatments showed significant positive effects of previous-year precipitation on current-year AGB. Our path analysis suggested that previous-year precipitation frequency had negative effects on the current-year density and mean height of grass (Leymus secalinus) while had positive effects on forb (Artemisia capillaris). The forb had much smaller height and AGB (65% and 53% less, respectively) than the grass. Consequently, the AGB reduced in the weekly small events treatment, causing the sensitivity of AGB to precipitation to decrease. Therefore, our findings indicated that the impacts of precipitation regimes on plant community dynamics should be taken into consideration while assessing the precipitation legacy effect on ecosystem production.

Increasing microbial carbon use efficiency with warming predicts soil heterotrophic respiration globally.

The degree to which climate warming will stimulate soil organic carbon (SOC) losses via heterotrophic respiration remains uncertain, in part because different or even opposite microbial physiology and temperature relationships have been proposed in SOC models. We incorporated competing microbial carbon use efficiency (CUE)-mean annual temperature (MAT) and enzyme kinetic-MAT relationships into SOC models, and compared the simulated mass-specific soil heterotrophic respiration rates with multiple published datasets of measured respiration. The measured data included 110 dryland soils globally distributed and two continental to global-scale cross-biome datasets. Model-data comparisons suggested that a positive CUE-MAT relationship best predicts the measured mass-specific soil heterotrophic respiration rates in soils distributed globally. These results are robust when considering models of increasing complexity and competing mechanisms driving soil heterotrophic respiration-MAT relationships (e.g., carbon substrate availability). Our findings suggest that a warmer climate selects for microbial communities with higher CUE, as opposed to the often hypothesized reductions in CUE by warming based on soil laboratory assays. Our results help to build the impetus for, and confidence in, including microbial mechanisms in soil biogeochemical models used to forecast changes in global soil carbon stocks in response to warming.

Multifunctionality debt in global drylands linked to past biome and climate.

Past vegetation and climatic conditions are known to influence current biodiversity patterns. However, whether their legacy effects affect the provision of multiple ecosystem functions, that is, multifunctionality, remains largely unknown. Here we analyzed soil nutrient stocks and their transformation rates in 236 drylands from six continents to evaluate the associations between current levels of multifunctionality and legacy effects of the Last Glacial Maximum (LGM) desert biome distribution and climate. We found that past desert distribution and temperature legacy, defined as increasing temperature from LGM, were negatively correlated with contemporary multifunctionality even after accounting for predictors such as current climate, soil texture, plant species richness, and site topography. Ecosystems that have been deserts since the LGM had up to 30% lower contemporary multifunctionality compared with those that were nondeserts during the LGM. In addition, ecosystems that experienced higher warming rates since the LGM had lower contemporary multifunctionality than those suffering lower warming rates, with a ~9% reduction per extra degree Celsius. Past desert distribution and temperature legacies had direct negative effects, while temperature legacy also had indirect (via soil sand content) negative effects on multifunctionality. Our results indicate that past biome and climatic conditions have left a strong "functionality debt" in global drylands. They also suggest that ongoing warming and expansion of desert areas may leave a strong fingerprint in the future functioning of dryland ecosystems worldwide that needs to be considered when establishing management actions aiming to combat land degradation and desertification.

Impacts of climate change and human activities on grassland vegetation variation in the Chinese Loess Plateau.

China initiated the "Grain for Green Project" in 1999 to mitigate soil erosion. The vegetation cover of the Chinese Loess Plateau, one of the most erosive regions in the world, has been greatly increased. However, studies on quantitatively investigating the climate change and human activities on vegetation coverage change were rare. In this study, spatio-temporal changes in vegetation coverage were investigated using MODIS normalized difference vegetation index (NDVI) data over 2000-2016. And a new method was introduced using Net Primary Productivity (NPP) model and relationship between NPP and NDVI to quantitatively and spatially distinguish the NDVI affected by climate change and human activities. Results showed that mean NDVI value over 2009-2016 were 14.46% greater than that over 2000-2007. In order to quantify the contribution of climate change and human activities to vegetation change, an NPP model suitable for the grassland of the Chinese Loess Plateau was identified using biomass observations from field survey and literature. The NDVI affected by climate change (NDVIclimate) was estimated by the NPP model and the relationship between NPP and NDVI. And the NDVI affected by human activities (NDVIhuman) was calculated by actual NDVI minus NDVIclimate. Comparison of the two stages showed that human activities and climate change contributed 42.35% and 57.65% respectively to the ΔNDVI on grassland in the Loess Plateau. After analysis of numerous NDVIhuman related factors, the slopes restored by the "Grain for Green Project" was considered the main influence factor of human activities.

Under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear?

Understanding under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear is useful for accurately predicting the response of ecosystem function to global environmental change. Using long-term (2000-2016) net primary productivity (NPP)-precipitation datasets derived from satellite observations, we identify >5600pixels in the North Hemisphere landmass that fit either linear or nonlinear temporal NPP-precipitation relationships. Differences in climate (precipitation, radiation, ratio of actual to potential evapotranspiration, temperature) and soil factors (nitrogen, phosphorous, organic carbon, field capacity) between the linear and nonlinear types are evaluated. Our analysis shows that both linear and nonlinear types exhibit similar interannual precipitation variabilities and occurrences of extreme precipitation. Permutational multivariate analysis of variance suggests that linear and nonlinear types differ significantly regarding to radiation, ratio of actual to potential evapotranspiration, and soil factors. The nonlinear type possesses lower radiation and/or less soil nutrients than the linear type, thereby suggesting that nonlinear type features higher degree of limitation from resources other than precipitation. This study suggests several factors limiting the responses of plant productivity to changes in precipitation, thus causing nonlinear NPP-precipitation pattern. Precipitation manipulation and modeling experiments should combine with changes in other climate and soil factors to better predict the response of plant productivity under future climate.

Seasonal responses of soil respiration to warming and nitrogen addition in a semi-arid alfalfa-pasture of the Loess Plateau, China.

Responses of soil respiration (Rs) to increasing nitrogen (N) deposition and warming will have far-reaching influences on global carbon (C) cycling. However, the seasonal (growing and non-growing seasons) difference of Rs responses to warming and N deposition has rarely been investigated. We conducted a field manipulative experiment in a semi-arid alfalfa-pasture of northwest China to evaluate the response of Rs to nitrogen addition and warming from March 2014 to March 2016. Open-top chambers were used to elevate temperature and N was enriched at a rate of 4.42g m-2yr-1 with NH4NO3. Results showed that (1) N addition increased Rs by 14% over the two-year period; and (2) warming stimulated Rs by 15% in the non-growing season, while inhibited it by 5% in the growing season, which can be explained by decreased plant coverage and soil water. The main effect of N addition did not change with time, but that of warming changed with time, with the stronger inhibition observed in the dry year. When N addition and warming were combined, an antagonistic effect was observed in the growing season, whereas a synergism was observed in the non-growing season. Overall, warming and N addition did not affect the Q10 values over the two-year period, but these treatments significantly increased the Q10 values in the growing season compared with the control treatment. In comparison, combined warming and nitrogen addition significantly reduced the Q10 values compared with the single factor treatment. These results suggest that the negative indirect effect of warming-induced water stress overrides the positive direct effect of warming on Rs. Our results also imply the necessity of considering the different Rs responses in the growing and non-growing seasons to climate change to accurately evaluate the carbon cycle in the arid and semi-arid regions.

A mechanistic-bioclimatic modeling analysis of the potential impact of climate change on biomes of the Tibetan Plateau.

The Tibetan Plateau (TP) is experiencing high rates of climatic change. We present a novel combined mechanistic-bioclimatic modeling approach to determine how changes in precipitation and temperature on the TP may impact net primary production (NPP) in four major biomes (forest, shrub, grass, desert) and if there exists a maximum rain use efficiency (RUE(MAX)) that represents Huxman et al.'s "boundary that constrain[s] site-level productivity and efficiency." We used a daily mechanistic ecosystem model to generate 40-yr outputs using observed climatic data for scenarios of decreased precipitation (25-100%); increased air temperature (1 degrees - 6 degrees C); simultaneous changes in both precipitation (+/- 50%, +/- 25%) and air temperature (+1 to +6 degrees C) and increased interannual variability (IAV) of precipitation (+1 sigma to +3 sigma, with fixed means, where sigma is SD). We fitted model output from these scenarios to Huxman et al.'s RUE(MAX) bioclimatic model, NPP = alpha + RUE x PPT (where alpha is the intercept, RUE is rain use efficiency, and PPT is annual precipitation). Based on these analyses, we conclude that there is strong support (when not explicit, then trend-wise) for Huxman et al.'s assertion that biomes converge to a common RUE(MAX) during the driest years at a site, thus representing the boundary for highest rain use efficiency; the interactive effects of simultaneously decreasing precipitation and increasing temperature on NPP for the TP is smaller than might be expected from additive, single-factor changes in these drivers; and that increasing IAV of precipitation may ultimately have a larger impact on biomes of the Tibetan Plateau than changing amounts of rainfall and air temperature alone.