Standardization of monitoring data reassesses spatial distribution of aquatic microplastics concentrations worldwide.

Microplastics are found in continental and oceanic waters worldwide, but their spatial distribution shows an intricate pattern. Their driving factors remain difficult to identify and widely discussed due to insufficient and unstandardized monitoring data. Here, based on in situ experiments and hundreds of river samples from the Qinghai-Tibet Plateau, we formulate a model to standardize aquatic microplastic measurements. The model was applied to existing data on a global scale. These data are standardized to a 20 µm mesh size, resulting in a new spatial distribution of aquatic microplastic densities, with average concentrations of 554.93 ± 1352.42 items/m3 in Europe, 2558.90 ± 4799.62 in North America and 1741.94 ± 3225.09 in Asia. Excessive contaminations (microplastic concentration > 104 items/m3) are in the Yangtze River, the Charleston Harbor Estuary, the Bodega Bay and the Winyah Bay. We show that, based on these standardized concentrations, new driving factors could be used to predict the global or regional microplastic distribution in continental waters, such as the Human Development Index with a correlation of 75.86% on a global scale, the nighttime lights with a correlation of 37.26 ± 0.30% in Europe and 39.02 ± 0.54% in Asia, and the Mismanagement Plastic Waste with a correlation of 61.21 ± 19.86% in North America. Mapping standardized concentrations of aquatic microplastics enables a better comparison of contamination levels between regions and reveals more accurate hotspots to better adapt remediation efforts and future plastic pollution scenarios.

Optimized multilateral crop trade patterns can effectively mitigate phosphorus imbalance among the involved countries.

Phosphorus imbalance for cropland can greatly influence environmental quality and productivity of agricultural systems. Resolving cropland phosphorus imbalance may be possible with more efficient multilateral crop trade within the involved trading countries; however, the driving mechanisms are unclear. This study calculates phosphorus budgets in China and five central Asian countries and proposes two optimal multilateral crop trade models to mitigate the phosphorus imbalance. Results show that the current trading pattern between China and Central Asia is causing a phosphorus imbalance intensification. Phosphorus surpluses in China and Uzbekistan are 41.7 and 8.9 kg/ha, while Kazakhstan, Kyrgyzstan, Tajikistan, and Turkmenistan exhibit phosphorus deficits with the negative value of -0.7, -1.2, -0.8, and -0.8 kg/ha, respectively. However, under the optimal multilateral crop trade patterns, phosphorus budget of China and Central Asia will become balanced. Phosphorus imbalance intensification for China is reduced to -2525 and -2472 kt under the single- and bilevel-objective-based crop trades. In Kyrgyzstan, it will drop 61.5 % and 50.0 % and change to 321 and 417 kt under the two optimal crop trades. Moreover, changes of phosphorus imbalance mitigations for other central Asian countries range from 11.9 % to 28.2 %. This provides a scientific basis when establishing policies for strengthening optimal multilateral crop trading across the world to promote global phosphorus management.

Horizontally acquired fungal killer protein genes affect cell development in mosses.

The moss Physcomitrium patens is crucial for studying plant development and evolution. Although the P. patens genome includes genes acquired from bacteria, fungi and viruses, the functions and evolutionary significance of these acquired genes remain largely unclear. Killer protein 4 (KP4) is a toxin secreted by the phytopathogenic fungus Ustilago maydis that inhibits the growth of sensitive target strains by blocking their calcium uptake. Here, we show that KP4 genes in mosses were acquired from fungi through at least three independent events of horizontal gene transfer. Two paralogous copies of KP4 (PpKP4-1 and PpKP4-2) exist in P. patens. Knockout mutants ppkp4-1 and ppkp4-2 showed cell death at the protonemal stage, and ppkp4-2 also exhibited defects in tip growth. We provide experimental evidence indicating that PpKP4-1/2 affects P. patens protonemal cell development by mediating cytoplasmic calcium and that KP4 genes are functionally conserved between P. patens and fungi. The present study provides additional insights into the role of horizontal gene transfer in land plant development and evolution.

Parallel evolution of two AIM24 protein subfamilies and their conserved functions in ER stress tolerance in land plants.

Despite decades of efforts in genome sequencing and functional characterization, some important protein families remain poorly understood. In this study, we report the classification, evolution, and functions of the largely uncharacterized AIM24 protein family in plants, including the identification of a novel subfamily. We show that two AIM24 subfamilies (AIM24-A and AIM24-B) are commonly distributed in major plant groups. These two subfamilies not only have modest sequence similarities and different gene structures but also are of independent bacterial ancestry. We performed comparative functional investigations on the two AIM24 subfamilies using three model plants: the moss Physcomitrium patens, the liverwort Marchantia polymorpha, and the flowering plant Arabidopsis thaliana. Intriguingly, despite their significant differences in sequence and gene structure, both AIM24 subfamilies are involved in ER stress tolerance and the unfolded protein response (UPR). In addition, transformation of the AIM24-A gene from P. patens into the AIM24-B null mutant of A. thaliana could at least partially rescue ER stress tolerance and the UPR. We also discuss the role of AIM24 genes in plant development and other cellular activities. This study provides a unique example of parallel evolution in molecular functions and can serve as a foundation for further investigation of the AIM24 family in plants.

Further mitigating carbon footprint pressure in urban agglomeration by enhancing the spatial clustering.

The increasing environmental pressure of anthropogenic CO2 emissions is impeding the sustainability of urban agglomerations (UAs). Recent research has shown that the spatial clustering of UA elements reduces CO2 emissions but underestimates its impact on vegetation carbon sequestration. Using an extended IPAT equation analysis framework and the Logarithmic Mean Divisia Index decomposition approach, this study revealed the positive effects of the economy and population spatial clustering on carbon footprint pressure (CFP) mitigation. Specifically, improving economic spatial clustering mitigated the rise in UA's CFP caused by affluence and population growth. Furthermore, population clustering in core cities effectively mitigated CFP in neighboring cities. Additionally, we found that the efficiency improvement, i.e., the decrease in the ratio of carbon emissions and gross domestic product, should be the dominant driver of CFP mitigation, followed by improved vegetation carbon sequestration. However, these drivers have limited future potential. We believe that by improving UA's spatial clustering of the economy and population, future urban environmental pressures and climate risks will be mitigated.

Analysis of the relationship between water and energy in China based on a multi-regional input-output method.

The shortage of water and energy are hindering the rapid development of the regional economy in recent years. Therefore, exploring the synergy of water and energy and managing the two resources comprehensively is conducive to the sustainable development of the economy. Based on the multi-regional input-output (MRIO) model, this study proposed a new assessment framework for investigating the water-energy (WE) relationship. We used this novel framework to identify the relationships in different sectors. The achieved results are as follows. First, water and energy are closely related in many sectors, including agriculture, extractive sector, petroleum, coking, and nuclear fuel processing sector, and other sectors. However, the construction sector, textile and clothing sector, and wood processing and furniture manufacturing sector showed low correlation (p > 0.05). Second, on the whole, the WE relationship has been improving. Among the eight regions, the relationship varies greatly, and the Southern coastal region has the best relationship (r = 0.78). Third, the spatial distribution of water and energy footprints shows high agreement. Although the virtual water and energy flows alleviated the energy pressure in Coastal areas, it has aggravated the water and energy shortages in Central areas. Therefore, identification of key sectors and construction of suitable policies may help alleviate the contradiction between water and energy shortages and drive regional economic development.

Water environmental pressure assessment in agricultural systems in Central Asia based on an Integrated Excess Nitrogen Load Model.

Agricultural runoff is the main source of water pollution in Central Asia. Excessive nitrogen (N) inputs from overuse of chemical fertilizers are threatening regional water resources. However, the scarcity of quantitative data and simplified empirical models limit the reliability of grey water footprint (GWF), particularly in undeveloped regions. In this study, we developed an Integrated Excess Nitrogen Load Model (IENLM) to calculate excess N load and evaluate its potential water environmental pressure in Central Asia. The model optimized the biological N fixation and atmospheric N deposition modules by involving more environmental variables and human activities. Results showed that N fertilizer application contributed over 60% to total N input and was mainly responsible for 42.9% increase of total GWF from 101.5 to 145.0 billion m3 during 1992 - 2018. Water pollution level (WPL) increased from 0.55 in 1992 to 2.41 in 2018 and the pollution assimilation capacity of water systems has been fully consumed just by N load from agriculture since 2005. GWF intensity and grey water pollution - efficiency types in all Central Asian countries have improved in recent years except for Turkmenistan. N fertilizer application and agricultural economy development were the main driving factors induced N pollution. Results were validated by riverine nitrate concentrations and the estimates from prior studies. In future, combining the N fertilizer reduction with other farm management practices were projected to effectively improve the WPL. The modeling framework is favorable for N pollution research in data-scarce regions and provides a scientific basis for decision-making for agriculture and water resource managements.

Impact of thermal condition on vegetation feedback under greening trend of China.

In China, an unambiguous greening trend was observed over the last three decades. The feedback induced by vegetation growth can affect regional climate. Here, we investigated how vegetation feeds back to land surface temperature (LST) in temperature zones and land-use types in China using 18-years (2001-2018) of Moderate Resolution Imaging Spectroradiometer (MODIS) LST and Normalized Difference Vegetation Index (NDVI) data. We first showed that vegetation feedback was significantly negative (p < 0.1, t-test) in most parts of China. Specifically, we discovered a downtrend of vegetation feedback from the coldest temperature zone to the hottest temperature zone. Moreover, vegetation feedback and thermal condition showed an inverse relationship among temperature zones. The inverse relationship clarified that vegetation growth can cool most parts of China during climate change. In the end, we showed the pattern of vegetation feedback among land-use types. Due to the expansion of grassland, vegetation feedback may temporarily positive. Suitable vegetation coverage in urban land, banning deforestation, and cultivating land reasonably can decrease the local temperature by inducing negative vegetation feedback.

Vegetation response to climate zone dynamics and its impacts on surface soil water content and albedo in China.

Extensive research has focused on the response of vegetation to climate change, including potential mechanisms and resulting impacts. Although many studies have explored the relationship between vegetation and climate change in China, research on spatiotemporal distribution changes of climate regimes using natural vegetation as an indicator is still lacking. Further, limited information is available on the response of vegetation to shifts in China's regional climatic zones. In this study, we applied Mann-Kendall, and correlation analysis to examine the variabilities in temperature, precipitation, surface soil water, normalised difference vegetation index (NDVI), and albedo in China from 1982 to 2012. Our results indicate significant shifts in the distribution of Köppen-Geiger climate classes in China from 12.08% to 18.98% between 1983 and 2012 at a significance level of 0.05 (MK). The percentage areas in the arid and continental zones expanded at a rate of 0.004%/y and 0.12%/y, respectively, while the percentage area in the temperate and alpine zones decreased by -0.05%/y and - 0.07%/y. Sensitivity fitting results between simulated and observed changes identified temperature to be a dominant control on the dynamics of temperate (r2 = 0.98) and alpine (r2 = 0.968) zones, while precipitation was the dominant control on the changes of arid (r2 = 0.856) and continental (r2 = 0.815) zones. The response of the NDVI to albedo infers a more pronounced radiative response in temperate (r = -0.82, p < .01) and alpine (r = -0.476, p < .05) compared to arid and continental zones. Furthermore, we identified more pronounced monthly increasing trends in NDVI and soil water, corresponding to weak changes in albedo during vegetation growing periods. Our results suggest that climate zone shifting has considerable impacts on the vegetation in China and will have larger ecological impacts through radiative or non-radiative feedback mechanisms in future warming scenarios.

Author Correction: A mycorrhizae-like gene regulates stem cell and gametophore development in mosses.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A mycorrhizae-like gene regulates stem cell and gametophore development in mosses.

Plant colonization of land has been intimately associated with mycorrhizae or mycorrhizae-like fungi. Despite the pivotal role of fungi in plant adaptation, it remains unclear whether and how gene acquisition following fungal interaction might have affected the development of land plants. Here we report a macro2 domain gene in bryophytes that is likely derived from Mucoromycota, a group that includes some mycorrhizae-like fungi found in the earliest land plants. Experimental and transcriptomic evidence suggests that this macro2 domain gene in the moss Physcomitrella patens, PpMACRO2, is important in epigenetic modification, stem cell function, cell reprogramming and other processes. Gene knockout and over-expression of PpMACRO2 significantly change the number and size of gametophores. These findings provide insights into the role of fungal association and the ancestral gene repertoire in the early evolution of land plants.

The hornwort genome and early land plant evolution.

Hornworts, liverworts and mosses are three early diverging clades of land plants, and together comprise the bryophytes. Here, we report the draft genome sequence of the hornwort Anthoceros angustus. Phylogenomic inferences confirm the monophyly of bryophytes, with hornworts sister to liverworts and mosses. The simple morphology of hornworts correlates with low genetic redundancy in plant body plan, while the basic transcriptional regulation toolkit for plant development has already been established in this early land plant lineage. Although the Anthoceros genome is small and characterized by minimal redundancy, expansions are observed in gene families related to RNA editing, UV protection and desiccation tolerance. The genome of A. angustus bears the signatures of horizontally transferred genes from bacteria and fungi, in particular of genes operating in stress-response and metabolic pathways. Our study provides insight into the unique features of hornworts and their molecular adaptations to live on land.

The effects of climate factors and human activities on net primary productivity in Xinjiang.

Net primary productivity (NPP) is an index of the increase in plant biomass. Plant biomass is an important component of the global carbon cycle that indicates the health of an ecosystem. Environmental restoration has recently received much attention in Xinjiang, and it is thus important to quantify the dynamic effects of the drivers of NPP in the region. NPP was calculated for the annual growing season from 1982 to 2013 using the Carnegie-Ames-Stanford Approach (CASA) model. The effects of climate factors on NPP were analyzed, and the relationships between NPP and climate factors as well as human activity were quantified. Additionally, an innovative method based on partial derivatives and residual error was proposed to calculate the contributions of climate factors and human activities. The results show that average annual NPP in Xinjiang was 57.45 g C m-2 from 1982 to 2013 and that the average increase in annual NPP was 0.23 g C m-2 year-1. The average increases in annual NPP due to temperature, precipitation, and solar radiation were 0.0095, 0.2679, and 0.2541 g C m-2 year-1; the average decreases were respectively - 0.0133, - 0.0521, and - 0.0725 g C m-2 year-1. Precipitation and solar radiation influence NPP more than temperature. Precipitation had the greatest effect on NPP in the first 19 years, but solar radiation became more influential after 2000. Climate conditions were favorable for increase in NPP before 2000. The environmental restoration also occurred in Xinjiang during that period, and human activity slightly decreased NPP. Human activity increased and had a greater effect on NPP after 2000.

Multi-criteria decision analysis of optimal planting for enhancing phytoremediation of trace heavy metals in mining sites under interval residual contaminant concentrations.

As one of the most cost-effective and sustainable methods for contaminants' removal, sequestration and/or detoxification, phytoremediation has already captured comprehensive attention worldwide. Nevertheless, the accurate effects of various spatial pattern in enhancing phytoremediation efficiency is not yet clear, especially for the polluted mining areas. This study designed nine planting patterns (monocropping, double intercropping and triple intercropping) of three indigenous plant species (Setaria viridis (L.), Echinochloa crus-galli (L.) and Phragmites australis (Cav.) Trin. ex Steud.) to further explore the effects of plants spatial pattern on phytoremediation efficiency. Considering the uncertainties of the residual contaminants' concentration (RCC) caused by soil anisotropy, permeability and land types, the interval transformation was introduced into the plant uptake model to simulate the remediation efficiency. Then multi-criteria decision analysis (MCDA) were applied to optimal the planting patterns, with the help of criteria of (a) the amount of heavy metal absorption; (b) the concentration of residual contaminant in soil; (c) root tolerance of heavy metals; (d) the total investment cost. Results showed that (1) the highest concentrations of Zn, Cd, and Pb of the polluted area were 7320.02, 14.30, 1650.51 mg kg-1 (2) During the 180 days simulation, the highest RMSE of residue trace metals in soil are 3.02(Zn), 2.67(Pb), 2.89(Cd), respectively. (3) The result of IMCDA shows that the planting patterns of Setaria viridis, Echinochloa crus-galli and Phragmites australis in alternative a9 (269 mg kg-1 year-1) had the highest absorption rate of heavy metals compared with a7 (235 mg kg-1 year-1) and a2 (240 mg kg-1 year-1). After 20 years of remediation, the simulated RCC in a9 is far below the national standard, and the root toxicity is 0.12 (EC ≤ EC20). In general, the optimal alternative derived from interval residual contaminant concentration can effectively express the dynamic of contaminant distribution and then can be effectively employed to evaluate the sustainable remediation methods.

Trace metal element pollution of soil and water resources caused by small-scale metallic ore mining activities: a case study from a sphalerite mine in North China.

Trace metal element contamination in mining areas is always a huge environmental challenge for the global mining industry. In this study, an abandoned sphalerite mine near the Yanshan Mountains was selected as subject to evaluate the soil and water contamination caused by small-scale mining. The results show that (1) Pearson correlation matrix and principal component analysis (PCA) results reveal that Zn, Cu, Cd, and Pb were greatly affected by the operation of mines, especially mineral tailings. The contents of trace metal elements decrease with the increase of the distance from the mining area. Zinc, Pb, and Cd were discovered in almost all soil samples, and Zn accounted for about 80% of pollution of the topsoil. (2) The trace element pollution levels in the topsoil of the three villages were ranked as follows: Cd > Cu > Pb~Zn. The potential ecological risk of farmland around the mine ranges from lower to higher, with Cd being the most harmful. (3) Human health risk assessment results show that trace elements in the mining area pose obvious non-carcinogenic health risks to children while the risks to adults are not equally obvious. The carcinogenic risk of Cd and Cr is within a safe range and does not pose an obvious cancer risk to the population.

Genome of Crucihimalaya himalaica, a close relative of Arabidopsis, shows ecological adaptation to high altitude.

Crucihimalaya himalaica, a close relative of Arabidopsis and Capsella, grows on the Qinghai-Tibet Plateau (QTP) about 4,000 m above sea level and represents an attractive model system for studying speciation and ecological adaptation in extreme environments. We assembled a draft genome sequence of 234.72 Mb encoding 27,019 genes and investigated its origin and adaptive evolutionary mechanisms. Phylogenomic analyses based on 4,586 single-copy genes revealed that C. himalaica is most closely related to Capsella (estimated divergence 8.8 to 12.2 Mya), whereas both species form a sister clade to Arabidopsis thaliana and Arabidopsis lyrata, from which they diverged between 12.7 and 17.2 Mya. LTR retrotransposons in C. himalaica proliferated shortly after the dramatic uplift and climatic change of the Himalayas from the Late Pliocene to Pleistocene. Compared with closely related species, C. himalaica showed significant contraction and pseudogenization in gene families associated with disease resistance and also significant expansion in gene families associated with ubiquitin-mediated proteolysis and DNA repair. We identified hundreds of genes involved in DNA repair, ubiquitin-mediated proteolysis, and reproductive processes with signs of positive selection. Gene families showing dramatic changes in size and genes showing signs of positive selection are likely candidates for C. himalaica's adaptation to intense radiation, low temperature, and pathogen-depauperate environments in the QTP. Loss of function at the S-locus, the reason for the transition to self-fertilization of C. himalaica, might have enabled its QTP occupation. Overall, the genome sequence of C. himalaica provides insights into the mechanisms of plant adaptation to extreme environments.

Gene refashioning through innovative shifting of reading frames in mosses.

Early-diverging land plants such as mosses are known for their outstanding abilities to grow in various terrestrial habitats, incorporating tremendous structural and physiological innovations, as well as many lineage-specific genes. How these genes and functional innovations evolved remains unclear. In this study, we show that a dual-coding gene YAN/AltYAN in the moss Physcomitrella patens evolved from a pre-existing hemerythrin gene. Experimental evidence indicates that YAN/AltYAN is involved in fatty acid and lipid metabolism, as well as oil body and wax formation. Strikingly, both the recently evolved dual-coding YAN/AltYAN and the pre-existing hemerythrin gene might have similar physiological effects on oil body biogenesis and dehydration resistance. These findings bear important implications in understanding the mechanisms of gene origination and the strategies of plants to fine-tune their adaptation to various habitats.

Carbon Monoxide Interacts with Auxin and Nitric Oxide to Cope with Iron Deficiency in Arabidopsis.

To clarify the roles of carbon monoxide (CO), nitric oxide (NO), and auxin in the plant response to iron deficiency (-Fe), and to establish how the signaling molecules interact to enhance Fe acquisition, we conducted physiological, genetic, and molecular analyses that compared the responses of various Arabidopsis mutants, including hy1 (CO deficient), noa1 (NO deficient), nia1/nia2 (NO deficient), yuc1 (auxin over-accumulation), and cue1 (NO over-accumulation) to -Fe stress. We also generated a HY1 over-expression line (named HY1-OX) in which CO is over-produced compared to wild-type. We found that the suppression of CO and NO generation using various inhibitors enhanced the sensitivity of wild-type plants to Fe depletion. Similarly, the hy1, noa1, and nia1/nia2 mutants were more sensitive to Fe deficiency. By contrast, the yuc1, cue1, and HY1-OX lines were less sensitive to Fe depletion. The hy1 mutant with low CO content exhibited no induced expression of the Fe uptake-related genes FIT1 and FRO2 as compared to wild-type plants. On the other hand, the treatments of exogenous CO and NO enhanced Fe uptake. Likewise, cue1 and HY1-OX lines with increased endogenous content of NO and CO, respectively, also exhibited enhanced Fe uptake and increased expression of bHLH transcriptional factor FIT1as compared to wild-type plants. Furthermore, we found that CO affected auxin accumulation and transport in the root tip by altering the PIN1 and PIN2 proteins distribution that control lateral root structure under -Fe stress. Our results demonstrated the integration of CO, NO, and auxin signaling to cope with Fe deficiency in Arabidopsis.

Transcriptome sequencing of Crucihimalaya himalaica (Brassicaceae) reveals how Arabidopsis close relative adapt to the Qinghai-Tibet Plateau.

The extreme environment of the Qinghai-Tibet Plateau (QTP) provides an ideal natural laboratory for studies on adaptive evolution. Few genome/transcriptome based studies have been conducted on how plants adapt to the environments of QTP compared to numerous studies on vertebrates. Crucihimalaya himalaica is a close relative of Arabidopsis with typical QTP distribution, and is hoped to be a new model system to study speciation and ecological adaptation in extreme environment. In this study, we de novo generated a transcriptome sequence of C. himalaica, with a total of 49,438 unigenes. Compared to five relatives, 10,487 orthogroups were shared by all six species, and 4,286 orthogroups contain putative single copy gene. Further analysis identified 487 extremely significantly positively selected genes (PSGs) in C. himalaica transcriptome. Theses PSGs were enriched in functions related to specific adaptation traits, such as response to radiation, DNA repair, nitrogen metabolism, and stabilization of membrane. These functions are responsible for the adaptation of C. himalaica to the high radiation, soil depletion and low temperature environments on QTP. Our findings indicate that C. himalaica has evolved complex strategies for adapting to the extreme environments on QTP and provide novel insights into genetic mechanisms of highland adaptation in plants.