Gross primary production responses to warming, elevated CO2 , and irrigation: quantifying the drivers of ecosystem physiology in a semiarid grassland

Belowground carbon allocation, root trait plasticity, and productivity during drought and warming in a pasture grass

Sustaining grassland production in a changing climate requires an understanding of plant adaptation strategies, including trait plasticity under warmer and drier conditions. However, our knowledge to date disproportionately relies on aboveground responses, despite the importance of belowground traits in maintaining aboveground growth, especially in grazed systems. We subjected a perennial pasture grass, Festuca arundinacea, to year-round warming (+3 °C) and cool-season drought (60% rainfall reduction) in a factorial field experiment to test the hypotheses that: (i) drought and warming increase carbon allocation belowground and shift root traits towards greater resource acquisition and (ii) increased belowground carbon reserves support post-drought aboveground recovery. Drought and warming reduced plant production and biomass allocation belowground. Drought increased specific root length and reduced root diameter in warmed plots but increased root starch concentrations under ambient temperature. Higher diameter and soluble sugar concentrations of roots and starch storage in crowns explained aboveground production under climate extremes. However, the lack of association between post-drought aboveground biomass and belowground carbon and nitrogen reserves contrasted with our predictions. These findings demonstrate that root trait plasticity and belowground carbon reserves play a key role in aboveground production during climate stress, helping predict pasture responses and inform management decisions under future climates.

The stimulatory effect of elevated CO2 on soil respiration is unaffected by N addition

Global atmospheric CO₂ keeps rising and brings about significant effects on ecosystem carbon (C) cycling by altering C processes in soils. Soil C responses to elevated CO₂ are highly uncertain, and how elevated CO₂ interacts with other factors, such as nitrogen (N) availability, to influence soil C flux comprises an important source of this uncertainty, especially for those under-studied ecosystems. By conducting a manipulated CO₂ concentration and N availability experiment on typical alpine grassland (4600 m asl), we combined the five-year in-situ measurement of soil respiration (SR) with an incubation experiment of microbial metabolic efficiency in the lab to explore the response of SR to elevated CO₂ and N availability. The results showed that elevated CO₂ at ambient N conditions and enriched N equally stimulated SR during the experimental period, whereas N supply had no significant effect. Elevated CO₂ enhanced soil dissolved organic C and enzyme activity, while had marginal effects on microbial biomass and C use efficiency (CUE). Strengthened microbial activity dominated SR stimulation under elevated CO₂. Enriched N boosted enzyme activity and microbial CUE. N availability played divergent roles in mediating SR. The negliable regulation of N supply on elevated CO₂ effects on SR was the offset consequences of the negative impacts of enhanced CUE and the positive contribution of heightened enzyme activity. Our findings suggest that rising CO₂ would accelerate soil C cycling of the alpine grassland under various N regimes by stimulating microbial activity instead of lowering microbial metabolic efficiency. Such results are crucial for understanding the role of alpine ecosystems in the global C cycle.

Elevated CO2, warming, N addition, and increased precipitation affect different aspects of the arbuscular mycorrhizal fungal community

The functional diversity of arbuscular mycorrhizal fungi (AMF) affects the resistance and resilience of plant communities to environmental stress. However, considerable uncertainty remains regarding how the complex interactions among elevated atmospheric CO₂ (eCO₂), nitrogen deposition (eN), precipitation (eP), and warming (eT) affect AMF communities. These global change factors (GCFs) do not occur in isolation, and their interactions likely affect AMF community structure and assembly processes. In this study, the interactive effects of these four GCFs on AMF communities were explored using an open-top chamber field experiment in a semiarid grassland. Elevated CO₂, eN, eT, eP, and their interactions did not affect AMF biomass. The relative abundance of Paraglomus increased with N addition across treatment combinations, whereas that of Glomus decreased with N addition, especially combined with eT and eCO₂. Precipitation, temperature (T), and N affected AMF phylogenetic α-diversity, and the three-way interaction among CO₂, T, and N affected taxonomic and phylogenetic α-diversity. N addition significantly affected the composition of AMF communities. Both variable selection and dispersal limitation played major roles in shaping AMF communities, whereas homogeneous selection and homogenizing dispersal had little effect on AMF community assembly. The contribution of variable selection decreased under eCO₂, eN and eT but not under eP. The contribution of dispersal limitation decreased under eCO₂, eT, and eP but increased under eN. The assembly of AMF communities under the sixteen GCF combinations was strongly affected by dispersal limitation, variable selection and ecological drift. Elevated CO₂, warming, N addition, and increased precipitation affected different aspects of AMF communities. The interactive effects of the four GCFs on AMF communities were limited. Overall, the results of this study suggest that AMF communities in semiarid grasslands can resist changes in global climate.

Non-structural carbohydrate dynamics associated with antecedent stem water potential and air temperature in a dominant desert shrub

Non-structural carbohydrates (NSCs) are necessary for plant growth and affected by plant water status, but the temporal dynamics of water stress impacts on NSC are not well understood. We evaluated how seasonal NSC concentrations varied with plant water status (predawn xylem water potential, Ψ) and air temperature (T) in the evergreen desert shrub Larrea tridentata. Aboveground sugar and starch concentrations were measured weekly or monthly for ~1.5 years on 6-12 shrubs simultaneously instrumented with automated stem psychrometers; leaf photosynthesis (A_net ) was measured monthly for 1 year. Leaf sugar increased during the dry, premonsoon period, associated with lower Ψ (greater water stress) and high T. Leaf sugar accumulation coincided with declines in leaf starch and stem sugar, suggesting the prioritization of leaf sugar during low photosynthetic uptake. Leaf starch was strongly correlated with A_net and peaked during the spring and monsoon seasons, while stem starch remained relatively constant except for depletion during the monsoon. Recent photosynthate appeared sufficient to support spring growth, while monsoon growth required the remobilization of stem starch reserves. The coordinated responses of different NSC fractions to water status, photosynthesis, and growth demands suggest that NSCs serve multiple functions under extreme environmental conditions, including severe drought.

Satellite-based global-scale irrigation water use and its contemporary trends

Irrigated agriculture is important for satisfying the increasing world food demand, but it interrupts the natural hydrological cycle by applying additional water to crops. Accurate information regarding irrigation water use (IWU) is a prerequisite to exploit land surface modeling and to quantify the uncertainty of climate projections. In this study, the global IWU was estimated for 2000-2015 by combining satellite-based soil moisture (SM) observations from the European Space Agency's Climate Change Initiative (ESA CCI) and the model estimated SM from European ReAnalysis-5 (ERA5). Considering irrigation as an unmodeled hydrological process in ERA5 and the ability of ESA CCI SM to capture the irrigation patterns, the global IWU was estimated by solving the water balance equations for ESA CCI and ERA5 SM. Owing to the global absence of ground-truth data for IWU, the IWU estimates were compared with the reported irrigation water withdrawals (IWWs) provided by Food and Agriculture Organization. The results indicated that satellite-based SM observations have the potential to identify global irrigation. All three ESA CCI products (active, passive, and merged) discerned the global irrigated areas satisfactorily, and the estimated IWU captured the pattern of the country-level IWWs (R = 0.77, 0.72, and 0.81 for active, passive, and merged products, respectively). However, the estimated IWU substantially underestimated the reported IWWs (bias of -76.55, -76.01, and -73.93 km³ for active, passive, and merged products, respectively) due to the coarse spatial resolution (0.25° × 0.25°) of the microwave remote sensing products and the inclusion of supplemental water in the IWWs, which was lost during distribution to crops. Trend analysis of the IWU indicated an increasing trend of the IWU in the first decade of the 21st century. However, in recent years the trend has reversed due to advances in agriculture technology and the adoption of water-efficient irrigation methods.

Legacies of more frequent drought in ponderosa pine across the western United States

Despite widespread interest in drought legacies-multiyear impacts of drought on tree growth-the key implication of reported drought legacies remains unaddressed: as impaired growth and slow recovery associated with drought legacies are pervasive across forest ecosystems, what is the impact of more frequent drought conditions? We investigated the assumption that either multiple drought years occurring during a short period (multiyear droughts), or droughts occurring during the recovery period from previous drought (compounded droughts), are detrimental to subsequent growth. There is evidence that drought responses may vary among populations of widespread species, leading us to examine regional differences in responses of the conifer Pinus ponderosa to historic drought frequency in the western United States. More frequent drought conditions incurred additional growth declines and shifts in growth-climate sensitivities in the years following drought relative to single-drought events, with 'triple-droughts' being worse than 'double-droughts'. Notably, prediction skill was not strongly reduced when ignoring compounded droughts, a consequence of the temporally comprehensive formulation of our stochastic antecedent model that accounts for the climatic memory of tree growth. We argue that incorporating drought-induced temporal variability in tree growth sensitivities can aid inference gained from statistical models, where more simplistic models could overestimate the severity of drought legacies. We also found regional differences in response to repeated drought, and suggest plastic post-drought sensitivities and climatic memory may represent beneficial physiological adjustments in interior regions. Within-species variability may thus mediate forest responses to increasing drought frequency under future climate change, but experimental approaches using more species are necessary to improve our understanding of the mechanisms that underlie drought legacy effects on tree growth.

Detecting global irrigated areas by using satellite and reanalysis products

Despite the importance of irrigation in meeting the world's food demand and as an essential human modification to water and energy cycles, the reliable extent and distribution of the global irrigated areas remain undefined. In this study, an intuitive method is proposed, based on the aftereffects of irrigation, to detect global irrigated areas by combining satellite and reanalysis datasets. The proposed methodology assumes that irrigation is an unmodeled land surface process, while satellite observations can effectively detect irrigation signals in near real-time. The spatial extents of irrigation were derived by calculating the difference between the remotely sensed and reanalysis datasets. To detect the irrigated areas, three irrigation-dependent variables, soil moisture (SM), land surface temperature (LST), and surface albedo (A_L), were used. In the absence of reliable ground truths, the proposed irrigation map was compared to the commonly used global irrigation maps, namely Global Map of Irrigated areas, Global Irrigated Area Map, and recently developed Global Irrigated Areas by Meier et al. (2018). Individual detection by SM, LST, and A_L has discrepancies in detecting irrigation signals in highly irrigated, urbanized, and semi-arid regions. However, by combining the individual detection maps, the proposed method showed reasonable agreement with the reference irrigated maps overlapping with approximately 70% of the irrigated areas. We believe that the proposed method, as stand-alone or in combination with the existing irrigation maps, will benefit the studies regarding water and energy balance closure in near-real time for large-scale land surface models by minimizing the uncertainties in model parameterization.

Evaluating and comparing remote sensing terrestrial GPP models for their response to climate variability and CO2 trends

Remote sensing (RS)-based models play an important role in estimating and monitoring terrestrial ecosystem gross primary productivity (GPP). Several RS-based GPP models have been developed using different criteria, yet the sensitivities to environmental factors vary among models; thus, a comparison of model sensitivity is necessary for analyzing and interpreting results and for choosing suitable models. In this study, we globally evaluated and compared the sensitivities of 14 RS-based models (2 process-, 4 vegetation-index-, 5 light-use-efficiency, and 3 machine-learning-based models) and benchmarked them against GPP responses to climatic factors measured at flux sites and to elevated CO₂ concentrations measured at free-air CO₂ enrichment experiment sites. The results demonstrated that the models with relatively high sensitivity to increasing atmospheric CO₂ concentrations showed a higher increasing GPP trend. The fundamental difference in the CO₂ effect in the models' algorithm either considers the effect of CO₂ through changes in greenness indices (nine models) or introduces the influences on photosynthesis (three models). The overall effects of temperature and radiation, in terms of both magnitude and sign, vary among the models, while the models respond relatively consistently to variations in precipitation. Spatially, larger differences among model sensitivity to climatic factors occur in the tropics; at high latitudes, models have a consistent and obvious positive response to variations in temperature and radiation, and precipitation significantly enhances the GPP in mid-latitudes. Compared with the results calculated by flux-site measurements, the model performance differed substantially among different sites. However, the sensitivities of most models are basically within the confidence interval of the flux-site results. In general, the comparison revealed that models differed substantially in the effect of environmental regulations, particularly CO₂ fertilization and water stress, on GPP, and none of the models performed consistently better across the different ecosystems and under the various external conditions.

Rainfall pulse response of carbon fluxes in a temperate grass ecosystem in the semiarid Loess Plateau

Rainfall pulses can significantly influence carbon cycling in water-limited ecosystems. The magnitude of carbon flux component responses to precipitation may vary depending on precipitation amount and antecedent soil moisture, associated with nonlinear responses of plants and soil microbes. The present study was carried out in a temperate grass ecosystem during 2013-2015 in the semiarid Loess Plateau of China, to examine the response of carbon fluxes to precipitation using the "threshold-delay" model. The unique contribution of environmental variables such as precipitation amount and antecedent soil moisture before rainfall (SWC_antecedent) to carbon fluxes in response to rainfall was also investigated. The lower threshold of effective rainfall was 6.6 mm for gross ecosystem production (GEP), 8.5 mm for net ecosystem production (NEP), and 4.5 mm for ecosystem respiration (RE); and the upper threshold of effective rainfall was 21.4 mm for GEP and NEP, and 16.8 mm for RE. Rainfall amount was positively affected the relative rainfall responses of GEP, NEP, and RE. However, SWC_antecedent at 20 cm soil depth offset the response of GEP to rainfall pulses, and SWC_antecedent at 5 cm soil depth offset the response of NEP and RE to rainfall pulses, with corresponding partial slopes of linear regressions of -0.50, -0.40, and -0.52. These results indicated that NEP was more sensitive to rainfall pulses and RE was more sensitive to SWC_antecedent. These results demonstrate the importance of rainfall events of <10 mm and that the negative effect of SWC_antecedent should also be considered when estimating ecosystem carbon fluxes in this semiarid region.

Elevated CO2 and Warming Altered Grassland Microbial Communities in Soil Top-Layers

As two central issues of global climate change, the continuous increase of both atmospheric CO₂ concentrations and global temperature has profound effects on various terrestrial ecosystems. Microbial communities play pivotal roles in these ecosystems by responding to environmental changes through regulation of soil biogeochemical processes. However, little is known about the effect of elevated CO₂ (eCO₂) and global warming on soil microbial communities, especially in semiarid zones. We used a functional gene array (GeoChip 3.0) to measure the functional gene composition, structure, and metabolic potential of soil microbial communities under warming, eCO₂, and eCO₂ + warming conditions in a semiarid grassland. The results showed that the composition and structure of microbial communities was dramatically altered by multiple climate factors, including elevated CO₂ and increased temperature. Key functional genes, those involved in carbon (C) degradation and fixation, methane metabolism, nitrogen (N) fixation, denitrification and N mineralization, were all stimulated under eCO₂, while those genes involved in denitrification and ammonification were inhibited under warming alone. The interaction effects of eCO₂ and warming on soil functional processes were similar to eCO₂ alone, whereas some genes involved in recalcitrant C degradation showed no significant changes. In addition, canonical correspondence analysis and Mantel test results suggested that NO₃-N and moisture significantly correlated with variations in microbial functional genes. Overall, this study revealed the possible feedback of soil microbial communities to multiple climate change factors by the suppression of N cycling under warming, and enhancement of C and N cycling processes under either eCO₂ alone or in interaction with warming. These findings may enhance our understanding of semiarid grassland ecosystem responses to integrated factors of global climate change.