The three major axes of terrestrial ecosystem function.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Recently constructed hydropower dams were associated with reduced economic production, population, and greenness in nearby areas.

Hydropower dams produce huge impacts on renewable energy production, water resources, and economic development, particularly in the Global South, where accelerated dam construction has made it a global hotspot. We do not fully understand the multiple impacts that dams have in the nearby areas from a global perspective, including the spatial differentiations. In this study, we examined the impacts of hydropower dam construction in nearby areas. We first found that more than one-third of global gross domestic production (GDP) and almost one-third of global population fall within 50 km of the world's 7,155 hydropower dams (<10% of the global land area sans the Antarctic). We further analyzed impacts of 631 hydropower dams (≥1-megawatt capacity) constructed since 2001 and commissioned before 2015 for their effects on economy, population, and environment in nearby areas and examined the results in five regions (i.e., Africa, Asia, Europe, North America, and South America) and by different dam sizes. We found that recently constructed dams were associated with increased GDP in North America and urban areas in Europe but with decreased GDP, urban land, and population in the Global South and greenness in Africa in nearby areas. Globally, these dams were linked with reduced economic production, population, and greenness of areas within 50 km of the dams. While large dams were related with reduced GDP and greenness significantly, small and medium dams were coupled with lowered population and urban land substantially, and large and medium dams were connected to diminished nighttime light noticeably in nearby areas.

Multi-omics provides new insights into the domestication and improvement of dark jute (Corchorus olitorius).

Jute (Corchorus sp.) is the most important bast fiber crop worldwide; however, the mechanisms underlying domestication and improvement remain largely unknown. We performed multi-omics analysis by integrating de novo sequencing, resequencing, and transcriptomic and epigenetic sequencing to clarify the domestication and improvement of dark jute Corchorus olitorius. We demonstrated that dark jute underwent early domestication and a relatively moderate genetic bottleneck during improvement breeding. A genome-wide association study of 11 important agronomic traits identified abundant candidate loci. We characterized the selective sweeps in the two breeding stages of jute, prominently, soil salinity differences played an important role in environmental adaptation during domestication, and the strongly selected genes for improvement had an increased frequency of favorable haplotypes. Furthermore, we speculated that an encoding auxin/indole-3-acetic acid protein COS07g_00652 could enhance the flexibility and strength of the stem to improve fiber yield. Our study not only provides valuable genetic resources for future fiber breeding in jute, but also is of great significance for reviewing the genetic basis of early crop breeding.

Transcriptomic and metabolomic analyses reveal the differential accumulation of phenylpropanoids and terpenoids in hemp autotetraploid and its diploid progenitor.

BACKGROUND: Cannabis sativa, a dioecious plant that has been cultivated worldwide for thousands of years, is known for its secondary metabolites, especially cannabinoids, which possess several medicinal effects. In this study, we investigated the autopolyploidization effects on the biosynthesis and accumulation of these metabolites, transcriptomic and metabolomic analyses were performed to explore the gene expression and metabolic variations in industrial hemp autotetraploids and their diploid progenitors. RESULTS: Through these analyses, we obtained 1,663 differentially expressed metabolites and 1,103 differentially expressed genes. Integrative analysis revealed that phenylpropanoid and terpenoid biosynthesis were regulated by polyploidization. No substantial differences were found in the cannabidiol or tetrahydrocannabinol content between tetraploids and diploids. Following polyploidization, some transcription factors, including nine bHLH and eight MYB transcription factors, affected the metabolic biosynthesis as regulators. Additionally, several pivotal catalytic genes, such as flavonol synthase/flavanone 3-hydroxylase, related to the phenylpropanoid metabolic pathway, were identified as being modulated by polyploidization. CONCLUSIONS: This study enhances the overall understanding of the impact of autopolyploidization in C. sativa and the findings may encourage the application of polyploid breeding for increasing the content of important secondary metabolites in industrial hemp.

3D error calibration of spatial spots based on dual position-sensitive detectors.

In this paper, a dual position-sensitive detector-based vision measurement system camera is built instead of a traditional CCD camera. The 3D position information for the light point is calculated according to the 2D coordinate information of a certain light point in the space illuminated on the two position-sensitive detector (PSD) photosensitive surfaces, which is used for position detection of the spatial light point. In addition, the positioning model for 2D PSDs with different spot sizes in the Gaussian spot mode is derived by the mathematical model of Lucovsky's differential equation for a PSD. For the nonlinear distortion of the PSD, a nonlinear error calibration method using a particle swarm combined with a back propagation neural network is proposed to correct the errors in the measured values through the relationship between the input and output values, to obtain the predicted value that approximates the real coordinates. Then, by comparing the influence of different spot sizes on the positioning accuracy, we conclude that the smaller the spot formed by the convergence of the beam under the optical lens, the higher the positioning accuracy. We believe this conclusion can help improve the accuracy of PSD measurements. Finally, a red LED light spot is set up, and the 3D position measurement and error calibration of the light spot is done by dual PSD cameras, which better solves the position detection problem of a space light spot under close-range conditions because it is fast, reliable, and easy to implement. It also provides an effective method to detect the motion trajectory of a moving light spot in space.

A new open-path eddy covariance method for nitrous oxide and other trace gases that minimizes temperature corrections.

Low-power, open-path gas sensors enable eddy covariance (EC) flux measurements in remote areas without line power. However, open-path flux measurements are sensitive to fluctuations in air temperature, pressure, and humidity. Laser-based, open-path sensors with the needed sensitivity for trace gases like methane (CH4 ) and nitrous oxide (N2 O) are impacted by additional spectroscopic effects. Corrections for these effects, especially those related to temperature fluctuations, often exceed the flux of gases, leading to large uncertainties in the associated fluxes. For example, the density and spectroscopic corrections arising from temperature fluctuations can be one or two orders of magnitude greater than background N2 O fluxes. Consequently, measuring background fluxes with laser-based, open-path sensors is extremely challenging, particularly for N2 O and gases with similar high-precision requirements. We demonstrate a new laser-based, open-path N2 O sensor and a general approach applicable to other gases that minimizes temperature-related corrections for EC flux measurements. The method identifies absorption lines with spectroscopic effects in the opposite direction of density effects from temperature and, thus, density and spectroscopic effects nearly cancel one another. The new open-path N2 O sensor was tested at a corn (Zea mays L.) field in Southwestern Michigan, United States. The sensor had an optimal precision of 0.1 ppbv at 10 Hz and power consumption of 50 W. Field trials showed that temperature-related corrections were 6% of density corrections, reducing EC random errors by 20-fold compared to previously examined lines. Measured open-path N2 O EC fluxes showed excellent agreement with those made with static chambers (m = 1.0 ± 0.3; r2  = .96). More generally, we identified absorption lines for CO2 and CH4  flux measurements that can reduce the temperature-related corrections by 10-100 times compared to existing open-path sensors. The proposed method provides a new direction for future open-path sensors, facilitating the expansion of accurate EC flux measurements.

Assessment of Climate Change and Human Activities on Vegetation Development in Northeast China.

Vegetation in Northeast China (NEC) has faced dual challenges posed by climate change and human activities. However, the factors dominating vegetation development and their contribution remain unclear. In this study, we conducted a comprehensive evaluation of the response of vegetation in different land cover types, climate regions, and time scales to water availability from 1990 to 2018 based on the relationship between normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). The effects of human activities and climate change on vegetation development were quantitatively evaluated using the residual analysis method. We found that the area percentage with positive correlation between NDVI and SPEI increased with time scales. NDVI of grass, sparse vegetation, rain-fed crop, and built-up land as well as sub-humid and semi-arid areas (drylands) correlated positively with SPEI, and the correlations increased with time scales. The negatively correlated area was concentrated in humid areas or areas covered by forests and shrubs. Vegetation water surplus in humid areas weakens with warming, and vegetation water constraints in drylands enhance. Moreover, potential evapotranspiration had an overall negative effect on vegetation, and precipitation was a controlling factor for vegetation development in semi-arid areas. A total of 53% of the total area in NEC showed a trend of improvement, which is mainly attributed to human activities (93%), especially through the implementation of ecological restoration projects in NEC. The relative role of human activities and climate change in vegetation degradation areas were 56% and 44%, respectively. Our findings highlight that the government should more explicitly consider the spatiotemporal heterogeneity of the influence of human activities and water availability on vegetation under changing climate and improve the resilience of regional water resources. The relative proportions and roles map of climate change and human activities in vegetation change areas provide a basis for government to formulate local-based management policies.

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales.

While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

Gene coexpression network analysis and tissue-specific profiling of gene expression in jute (Corchorus capsularis L.).

BACKGROUND: Jute (Corchorus spp.), belonging to the Malvaceae family, is an important natural fiber crop, second only to cotton, and a multipurpose economic crop. Corchorus capsularis L. is one of the only two commercially cultivated species of jute. Gene expression is spatiotemporal and is influenced by many factors. Therefore, to understand the molecular mechanisms of tissue development, it is necessary to study tissue-specific gene expression and regulation. We used weighted gene coexpression network analysis, to predict the functional roles of gene coexpression modules and individual genes, including those underlying the development of different tissue types. Although several transcriptome studies have been conducted on C. capsularis, there have not yet been any systematic and comprehensive transcriptome analyses for this species. RESULTS: There was significant variation in gene expression between plant tissues. Comparative transcriptome analysis and weighted gene coexpression network analysis were performed for different C. capsularis tissues at different developmental stages. We identified numerous tissue-specific differentially expressed genes for each tissue, and 12 coexpression modules, comprising 126 to 4203 genes, associated with the development of various tissues. There was high consistency between the genes in modules related to tissues, and the candidate upregulated genes for each tissue. Further, a gene network including 21 genes directly regulated by transcription factor OMO55970.1 was discovered. Some of the genes, such as OMO55970.1, OMO51203.1, OMO50871.1, and OMO87663.1, directly involved in the development of stem bast tissue. CONCLUSION: We identified genes that were differentially expressed between tissues of the same developmental stage. Some genes were consistently up- or downregulated, depending on the developmental stage of each tissue. Further, we identified numerous coexpression modules and genes associated with the development of various tissues. These findings elucidate the molecular mechanisms underlying the development of each tissue, and will promote multipurpose molecular breeding in jute and other fiber crops.

Construction of a high-resolution genetic map and identification of quantitative trait loci for salt tolerance in jute (Corchous spp.).

BACKGROUND: Jute (Corchorus spp.) is the most important natural fiber crop after cotton in terms of cultivation area and production. Salt stress greatly restricts plant development and growth. A high-density genetic linkage map is the basis of quantitative trait locus (QTLs) mapping. Several high-density genetic maps and QTLs mapping related to salt tolerance have been developed through next-generation sequencing in many crop species. However, such studies are rare for jute. Only several low-density genetic maps have been constructed and no salt tolerance-related QTL has been mapped in jute to date. RESULTS: We developed a high-density genetic map with 4839 single nucleotide polymorphism markers spanning 1375.41 cM and an average distance of 0.28 cM between adjacent markers on seven linkage groups (LGs) using an F2 jute population, LGs ranged from LG2 with 299 markers spanning 113.66 cM to LG7 with 1542 markers spanning 350.18 cM. In addition, 99.57% of gaps between adjacent markers were less than 5 cM. Three obvious and 13 minor QTLs involved in salt tolerance were identified on four LGs explaining 0.58-19.61% of the phenotypic variance. The interval length of QTL mapping varied from 1.3 to 20.2 cM. The major QTL, qJST-1, was detected under two salt stress conditions that explained 11.81 and 19.61% of the phenotypic variation, respectively, and peaked at 19.3 cM on LG4. CONCLUSIONS: We developed the first high-density and the most complete genetic map of jute to date using a genotyping-by-sequencing approach. The first QTL mapping related to salt tolerance was also carried out in jute. These results should provide useful resources for marker-assisted selection and transgenic breeding for salt tolerance at the germination stage in jute.

Development of an InDel polymorphism database for jute via comparative transcriptome analysis.

Jute (Corchorus spp.) is one of the most commercially important bast fiber crops in the world. However, molecular markers and high-density genetic maps are still lacking on jute compared with other crops. Insertion/deletion (InDel) markers, one of the most abundant sources of DNA/RNA variations in plant genomes, can easily be distinguished among different accessions using high-throughput sequencing. Using three transcriptome datasets, we identified and developed InDel markers. Altogether, 51 172 InDel sites in 18 800 unigenes were discovered, and the number of InDel loci per unigene varied from 1 to 31. Further, we found 94 InDel types, varying from 1 to 159 bp; the most common were single-nucleotide (23 028), binucleotide (9824), and trinucleotide (9182). In total, 49 563 InDels in 18 445 transcripts were discovered in the comparison between TC and YG, followed by 48 934 InDels in 18 408 transcripts between NY and YG, and 3570 InDels in 2701 unigenes between NY and TC. Additionally, there were 1273 InDel sites in 1129 unigenes with polymorphisms between any two of the three accessions. Twenty-nine (58%) primer pairs represented polymorphisms when compared to the jute accessions, and PIC varied from 0.340 to 0.680, with an average of 0.491.

Legacy effects of land use on soil nitrous oxide emissions in annual crop and perennial grassland ecosystems.

Land use conversions into and out of agriculture may influence soil-atmosphere greenhouse gas fluxes for many years. We tested the legacy effects of land use on cumulative soil nitrous oxide (N2 O) fluxes for 5 yr following conversion of 22-yr-old Conservation Reserve Program (CRP) grasslands and conventionally tilled agricultural fields (AGR) to continuous no-till corn, switchgrass, and restored prairie. An unconverted CRP field served as a reference. We assessed the labile soil C pool of the upper 10 cm in 2009 (the conversion year) and in 2014 using short-term soil incubations. We also measured in situ soil N2 O fluxes biweekly from 2009 through 2014 using static chambers except when soils were frozen. The labile C pool was approximately twofold higher in soils previously in CRP than in those formerly in tilled cropland. Five-year cumulative soil N2 O emissions were approximately threefold higher in the corn system on former CRP than on former cropland despite similar fertilization rates (~184 kg N·ha-1 ·yr-1 ). The lower cumulative emissions from corn on former cropland were similar to emissions from switchgrass that was fertilized less (~57 kg N·ha-1 ·yr-1 ), regardless of former land use, and lowest emissions were observed from the unfertilized restored prairie and reference systems. Findings support the hypothesis that soil labile carbon levels modulate the response of soil N2 O emissions to nitrogen inputs, with soils higher in labile carbon but otherwise similar, in this case reflecting land use history, responding more strongly to added nitrogen.

Assessing the interplay between canopy energy balance and photosynthesis with cellulose δ18O: large-scale patterns and independent ground-truthing.

There are few whole-canopy or ecosystem scale assessments of the interplay between canopy temperature and photosynthesis across both spatial and temporal scales. The stable oxygen isotope ratio (δ18O) of plant cellulose can be used to resolve a photosynthesis-weighted estimate of canopy temperature, but the method requires independent confirmation. We compare isotope-resolved canopy temperatures derived from multi-year homogenization of tree cellulose δ18O to canopy-air temperatures weighted by gross primary productivity (GPP) at multiple sites, ranging from warm temperate to boreal and subalpine forests. We also perform a sensitivity analysis for isotope-resolved canopy temperatures that showed errors in plant source water δ18O lead to the largest errors in canopy temperature estimation. The relationship between isotope-resolved canopy temperatures and GPP-weighted air temperatures was highly significant across sites (p < 0.0001, R2 = 0.82), thus offering confirmation of the isotope approach. The previously observed temperature invariance from temperate to boreal biomes was confirmed, but the greater elevation of canopy temperature above air temperature in the boreal forest was not. Based on the current analysis, we conclude that canopy temperatures in the boreal forest are as warm as those in temperate systems because day-time-growing-season air temperatures are similarly warm.

Nature-based solutions for resilient landscapes and cities.

Nature-based solutions (NBS) are increasingly applied to guide the design of resilient landscapes and cities to enable them to reach economic development goals with beneficial outcomes for the environment and society. The NBS concept is closely related to other concepts including sustainability, resilience, ecosystem services, coupled human and environment, and green (blue) infrastructure; however, NBS represent a more efficient and cost-effective approach to development than traditional approaches. The European Commission is actively engaged in investing in NBS as a driver in developing ecosystem services-based approaches throughout Europe and the world. The pool of knowledge and expertise presented in this Special Issue of Environmental Research highlights the applications of NBS as 'living' and adaptable tools to boost the capacity of landscapes and cities to face today's critical environmental, economic and societal challenges. Based on the literature and papers of this Special Issue, we propose five specific challenges for the future of NBS.

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

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 (r(2) = 0.90) and GPP recovery after a fire disturbance in South Dakota (r(2) = 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.

Grazing effects on surface energy fluxes in a desert steppe on the Mongolian Plateau.

Quantifying the surface energy fluxes of grazed and ungrazed steppes is essential to understand the roles of grasslands in local and global climate and in land use change. We used paired eddy-covariance towers to investigate the effects of grazing on energy balance (EB) components: net radiation (Rn ), latent heat (LE), sensible heat (H), and soil heat (G) fluxes on adjacent grazed and ungrazed areas in a desert steppe of the Mongolian Plateau for a two-year period (2010-2012). Near 95% of Rn was partitioned as LE and H, whereas the contributions of G and other components of the EB were 5% at an annual scale. H dominated the energy partitioning and shared ~50% of Rn . When comparing the grazed and the ungrazed desert steppe, there was remarkably lower Rn and a lower H, but higher G at the grazed site than at the ungrazed site. Both reduced available energy (Rn - G) and H indicated a "cooling effect" feedback onto the local climate through grazing. Grazing reduced the dry year LE but enhanced the wet year LE. Energy partitioning of LE/Rn was positively correlated with the canopy conductivity, leaf area index, and soil moisture. H/Rn was positively correlated with the vapor pressure deficit but negatively correlated with the soil moisture. Boosted regression tree results showed that LE/Rn was dominated by soil moisture in both years and at both sites, while grazing shifted the H/Rn domination from temperature to soil moisture in the wet year. Grazing not only caused an LE shift between the dry and the wet year, but also triggered a decrease in the H/Rn because of changes in vegetation and soil properties, indicating that the ungrazed area had a greater resistance while the grazed area had a greater sensitivity of EB components to the changing climate.

Nature-based solutions for urban landscapes under post-industrialization and globalization: Barcelona versus Shanghai.

Using Barcelona and Shanghai as case studies, we examined the nature-based solutions (NBS) in urban settings-specifically within cities experiencing post-industrialization and globalization. Our specific research questions are: (1) What are the spatiotemporal changes in urban built-up land and green space in Barcelona and Shanghai? (2) What are the relationships between economic development, exemplified by post-industrialization, globalization, and urban green space? Urban land use and green space change were evaluated using data derived from a variety of sources, including satellite images, landscape matrix indicators, and a land conversion matrix. The relationships between economic development, globalization, and environmental quality were analyzed through partial least squares structural equation modeling based on secondary statistical data. Both Barcelona and Shanghai have undergone rapid urbanization, with urban expansion in Barcelona beginning in the 1960s-1970s and in Shanghai in the last decade. While Barcelona's urban green space and green space per capita began declining between the 1950s and 1990s, they increased slightly over the past two decades. Shanghai, however, has consistently and significantly improved urban green space and green space per capita over the past six decades, especially since the economic reform in 1978. Economic development has a direct and significant influence on urban green space for both cities and post-industrialization had served as the main driving force for urban landscape change in Barcelona and Shanghai. Based on secondary statistical and qualitative data from on-site observations and interviews with local experts, we highlighted the institution's role in NBS planning. Furthermore, aspiration to become a global or globalizing city motivated both cities to use NBS planning as a place-making tool to attract global investment, which is reflected in various governing policies and regulations. The cities' effort to achieve a higher status in the global city hierarchy may have contributed to the increase in total green space and urban green per capita. In addition, various institutional shifts, such as land property rights in a market economy vs. a transitional economy, may also have contributed to the differences in efficiency when expanding urban green space in Barcelona and Shanghai.

Grassland productivity and carbon sequestration in Mongolian grasslands: The underlying mechanisms and nomadic implications.

BACKGROUND: Quantifying carbon (C) dioxide exchanges between ecosystems and the atmosphere and the underlying mechanism of biophysical regulations under similar environmental conditions is critical for an accurate understanding of C budgets and ecosystem functions. METHODS: For the first time, a cluster of four eddy covariance towers were set up to answer how C fluxes shift among four dominant ecosystems in Mongolia - meadow steppe (MDW), typical steppe (TPL), dry typical steppe (DRT) and shrubland (SHB) during two growing seasons (2014 and 2015). RESULTS: Large variations were observed for the annual net ecosystem exchange (NEE) from 59 to 193gCm-2, though all four sites acted as a C source. During the two growing seasons, MDW acted as a C sink, TPL and DRT were C neutral, while SHB acted as a C source. MDW to SHB and TPL conversions resulted in a 2.6- and 2.2-fold increase in C release, respectively, whereas the TPL to SHB conversion resulted in a 1.1-fold increase at the annual scale. C assimilation was higher at MDW than those at the other three ecosystems due to its greater C assimilation ability and longer C assimilation times during the day and growing period. On the other hand, C release was highest at SHB due to significantly lower photosynthetic production and relatively higher ecosystem respiration (ER). A stepwise multiple regression analysis showed that the seasonal variations in NEE, ER and gross ecosystem production (GEP) were controlled by air temperature at MDW, while they were controlled mainly by soil moisture at TPL, DRT and SHB. When air temperature increased, the NEE at MDW and TPL changed more dramatically than at DRT and SHB, suggesting not only a stronger C release ability but also a higher temperature sensitivity at MDW and TPL. CONCLUSIONS: The ongoing and predicted global changes in Mongolia likely impact the C exchange at MDW and TPL more than at DRT and SHB in Mongolia. Our results suggest that, with increasing drought and vegetation type succession, a clear trend for greater CO2 emissions may result in further global warming in the future. This study implies that diverse grassland ecosystems will respond differently to climate change in the future and can be seen as nature-based solutions (NBS) supporting climate change adaptation and mitigation strategies.

A novel soil manganese mechanism drives plant species loss with increased nitrogen deposition in a temperate steppe.

Loss of plant diversity with increased anthropogenic nitrogen (N) deposition in grasslands has occurred globally. In most cases, competitive exclusion driven by preemption of light or space is invoked as a key mechanism. Here, we provide evidence from a 9-yr N-addition experiment for an alternative mechanism: differential sensitivity of forbs and grasses to increased soil manganese (Mn) levels. In Inner Mongolia steppes, increasing the N supply shifted plant community composition from grass-forb codominance (primarily Stipa krylovii and Artemisia frigida, respectively) to exclusive dominance by grass, with associated declines in overall species richness. Reduced abundance of forbs was linked to soil acidification that increased mobilization of soil Mn, with a 10-fold greater accumulation of Mn in forbs than in grasses. The enhanced accumulation of Mn in forbs was correlated with reduced photosynthetic rates and growth, and is consistent with the loss of forb species. Differential accumulation of Mn between forbs and grasses can be linked to fundamental differences between dicots and monocots in the biochemical pathways regulating metal transport. These findings provide a mechanistic explanation for N-induced species loss in temperate grasslands by linking metal mobilization in soil to differential metal acquisition and impacts on key functional groups in these ecosystems.