Proteomics and ß-hydroxybutyrylation Modification Characterization in the Hearts of Naturally Senescent Mice.

Aging is widely accepted as an independent risk factor for cardiovascular disease (CVD), which contributes to increasing morbidity and mortality in the elderly population. Lysine ß-hydroxybutyrylation (Kbhb) is a novel post-translational modification (PTM), wherein ß-hydroxybutyrate is covalently attached to lysine ε-amino groups. Recent studies have revealed that histone Kbhb contributes to tumor progression, diabetic cardiomyopathy progression, and postnatal heart development. However, no studies have yet reported a global analysis of Kbhb proteins in aging hearts or elucidated the mechanisms underlying this modification in the process. Herein, we conducted quantitative proteomics and Kbhb PTM omics to comprehensively elucidate the alterations of global proteome and Kbhb modification in the hearts of aged mice. The results revealed a decline in grip strength and cardiac diastolic function in 22-month-old aged mice compared to 3-month-old young mice. High-throughput liquid chromatogram-mass spectrometry analysis identified 1710 ß-hydroxybutyrylated lysine sites in 641 proteins in the cardiac tissue of young and aged mice. Additionally, 183 Kbhb sites identified in 134 proteins exhibited significant differential modification in aged hearts (fold change (FC) > 1.5 or <1/1.5, p < 0.05). Notably, the Kbhb-modified proteins were primarily detected in energy metabolism pathways, such as fatty acid elongation, glyoxylate and dicarboxylate metabolism, tricarboxylic acid cycle, and oxidative phosphorylation. Furthermore, these Kbhb-modified proteins were predominantly localized in the mitochondria. The present study, for the first time, provides a global proteomic profile and Kbhb modification landscape of cardiomyocytes in aged hearts. These findings put forth novel possibilities for treating cardiac aging and aging-related CVDs by reversing abnormal Kbhb modifications.

Multispecies coexistence in fragmented landscapes.

Spatial dynamics have long been recognized as an important driver of biodiversity. However, our understanding of species' coexistence under realistic landscape configurations has been limited by lack of adequate analytical tools. To fill this gap, we develop a spatially explicit metacommunity model of multiple competing species and derive analytical criteria for their coexistence in fragmented heterogeneous landscapes. Specifically, we propose measures of niche and fitness differences for metacommunities, which clarify how spatial dynamics and habitat configuration interact with local competition to determine coexistence of species. We parameterize our model with a Bayesian approach using a 36-y time-series dataset of three Daphnia species in a rockpool metacommunity covering >500 patches. Our results illustrate the emergence of interspecific variation in extinction and recolonization processes, including their dependencies on habitat size and environmental temperature. We find that such interspecific variation contributes to the coexistence of Daphnia species by reducing fitness differences and increasing niche differences. Additionally, our parameterized model allows separating the effects of habitat destruction and temperature change on species extinction. By integrating coexistence theory and metacommunity theory, our study provides platforms to increase our understanding of species' coexistence in fragmented heterogeneous landscapes and the response of biodiversity to environmental changes.

High-throughput DNA synthesis for data storage.

With the explosion of digital world, the dramatically increasing data volume is expected to reach 175 ZB (1 ZB = 1012 GB) in 2025. Storing such huge global data would consume tons of resources. Fortunately, it has been found that the deoxyribonucleic acid (DNA) molecule is the most compact and durable information storage medium in the world so far. Its high coding density and long-term preservation properties make itself one of the best data storage carriers for the future. High-throughput DNA synthesis is a key technology for "DNA data storage", which encodes binary data stream (0/1) into quaternary long DNA sequences consisting of four bases (A/G/C/T). In this review, the workflow of DNA data storage and the basic methods of artificial DNA synthesis technology are outlined first. Then, the technical characteristics of different synthesis methods and the state-of-the-art of representative commercial companies, with a primary focus on silicon chip microarray-based synthesis and novel enzymatic DNA synthesis are presented. Finally, the recent status of DNA storage and new opportunities for future development in the field of high-throughput, large-scale DNA synthesis technology are summarized.

DNA Framework-Programmed Nanoscale Enzyme Assemblies.

Multienzyme assemblies mediated by multivalent interaction play a crucial role in cellular processes. However, the three-dimensional (3D) programming of an enzyme complex with defined enzyme activity in vitro remains unexplored, primarily owing to limitations in precisely controlling the spatial topological configuration. Herein, we introduce a nanoscale 3D enzyme assembly using a tetrahedral DNA framework (TDF), enabling the replication of spatial topological configuration and maintenance of an identical edge-to-edge distance akin to natural enzymes. Our results demonstrate that 3D nanoscale enzyme assemblies in both two-enzyme systems (glucose oxidase (GOx)/horseradish peroxidase (HRP)) and three-enzyme systems (amylglucosidase (AGO)/GOx/HRP) lead to enhanced cascade catalytic activity compared to the low-dimensional structure, resulting in ∼5.9- and ∼7.7-fold enhancements over homogeneous diffusional mixtures of free enzymes, respectively. Furthermore, we demonstrate the enzyme assemblies for the detection of the metabolism biomarkers creatinine and creatine, achieving a low limit of detection, high sensitivity, and broad detection range.

LSD1 in drug discovery: From biological function to clinical application.

Lysine-specific demethylase 1 (LSD1) is a flavin adenine dinucleotide (FAD) dependent monoamine oxidase (MAO) that erases the mono-, and dimethylation of histone 3 lysine 4 (H3K4), resulting in the suppression of target gene transcriptions. Besides, it can also demethylate some nonhistone substrates to regulate their biological functions. As reported, LSD1 is widely upregulated and plays a key role in several kinds of cancers, pharmacological or genetic ablation of LSD1 in cancer cells suppresses cell aggressiveness by several distinct mechanisms. Therefore, numerous LSD1 inhibitors, including covalent and noncovalent, have been developed and several of them have entered clinical trials. Herein, we systemically reviewed and discussed the biological function of LSD1 in tumors, lymphocytes as well as LSD1-targeting inhibitors in clinical trials, hoping to benefit the field of LSD1 and its inhibitors.

Microfluidic Digital Immunoassay for Point-of-Care Detection of NT-proBNP from Whole Blood.

The high prevalence and economic burden of heart failure remain a challenge to global health. This lifelong disease leads to a buildup of permanent heart damage, making early detection and frequent monitoring crucial for effective treatment. N-terminal proBNP (NT-proBNP) is an important biomarker for monitoring the disease state, but current commercial and research NT-proBNP assays require phlebotomy and bulky equipment or do not satisfy clinical requirements such as sensitivity and detection thresholds. Here, we report a point-of-care (POC) compatible microfluidic digital immunoassay that can quantify the NT-proBNP concentration in a small volume of whole blood. Our automated microfluidic device takes whole blood samples mixed with biotinylated detection antibodies and passes through a plasma filter to react with a capture antibody-functionalized sensor surface. Streptavidin-coated gold nanoparticles (GNPs) are then released to mark the surface-bound single NT-proBNP immunocomplexes and recorded with bright-field microscopy. NT-proBNP concentrations in the sample are quantified via a hybrid digital/analog calibration curve. Digital counts of bound GNPs are used as readout signal at low concentrations for high sensitivity detection, and GNP pixel occupancies are used at high concentrations for extended dynamic range. With this approach, we detected NT-proBNP in the range of 8.24-10 000 pg/mL from 7 µL of whole blood in 10 min, with a limit of detection of 0.94 pg/mL. Finally, the method was validated with 15 clinical serum samples, showing excellent linear correlation (r = 0.998) with Roche's Elecsys proBNP II assay. This evidence indicates that this method holds promise for decentralized monitoring of heart failure.

Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.

Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recently, plasmonic-based electrochemical impedance microscopy (P-EIM) was demonstrated for the label-free mapping of the ignition and propagation of action potentials in neuron cells with subcellular resolution. However, limited by the signal-to-noise ratio in the high-speed P-EIM video, action potential mapping was achieved by averaging 90 cycles of signals. Such extensive averaging is not desired and may not always be feasible due to factors such as neuronal desensitization. In this study, we utilized advanced signal processing techniques to detect action potentials in P-EIM extracted signals with fewer averaged cycles. Matched filtering successfully detected action potential signals with as few as averaging five cycles of signals. Long short-term memory (LSTM) recurrent neural network achieved the best performance and was able to detect single-cycle stimulated action potential successfully [satisfactory area under the receiver operating characteristic curve (AUC) equal to 0.855]. Therefore, we show that deep learning-based signal processing can dramatically improve the usability of P-EIM mapping of neuronal electrical signals.

Mapping Endocytic Vesicular Acidification with a pH-Responsive DNA Nanomachine.

Mapping the endocytic vesicular acidification process is of prior importance to better understand the health and pathological processes of cells. Herein, by integrating a pH-sensitive i-motif and a pair of fluorescence resonance energy transfer (FRET) into a tetrahedral DNA framework (TDF), we develop a pH-responsive DNA nanomachine, allowing for efficient sensing of pH from 7.0 to 5.5 via the pH-triggered spatial proximity modulation of FRET. The inheriting endo-lysosome-targeting ability of TDF enables spatiotemporal tracking of endocytic vesicle acidification during the endosomal maturation process. Analysis of pH-dependent FRET response at single fluorescent spot level reveals the significant difference of endocytic vesicular acidification between normal and cancer cells. The performance of pH-responsive DNA nanomachine underlines its potential for studies on vesicle acidification-related pathologies as a universal platform.

Temporal asynchrony of plant and soil biota determines ecosystem multifunctional stability.

The role of plant biodiversity in stabilizing ecosystem multifunctionality has been extensively studied; however, the impact of soil biota biodiversity on ecosystem multifunctional stability, particularly under multiple environmental changes, remains unexplored. By conducting an experiment with environmental changes (adding water and nitrogen to a long-term grazing experiment) and an experiment without environmental changes (an undisturbed site) in semi-arid grasslands, our research revealed that environmental changes-induced changes in temporal stability of both above- and belowground multifunctionality were mainly impacted by plant and soil biota asynchrony, rather than by species diversity. Furthermore, changes in temporal stability of above- and belowground multifunctionality, under both experiments with and without environmental changes, were mainly associated with plant and soil biota asynchrony, respectively, suggesting that the temporal asynchrony of plant and soil biota has independent and non-substitutable effects on multifunctional stability. Our findings emphasize the importance of considering both above- and belowground biodiversity or functions when evaluating the stabilizing effects of biodiversity on ecosystem functions.

The neglected roles of adjacent natural ecosystems in maintaining bacterial diversity in agroecosystems.

A central aim of community ecology is to understand how local species diversity is shaped. Agricultural activities are reshaping and filtering soil biodiversity and communities; however, ecological processes that structure agricultural communities have often overlooked the role of the regional species pool, mainly owing to the lack of large datasets across several regions. Here, we conducted a soil survey of 941 plots of agricultural and adjacent natural ecosystems (e.g., forest, wetland, grassland, and desert) in 38 regions across diverse climatic and soil gradients to evaluate whether the regional species pool of soil microbes from adjacent natural ecosystems is important in shaping agricultural soil microbial diversity and completeness. Using a framework of multiscales community assembly, we revealed that the regional species pool was an important predictor of agricultural bacterial diversity and explained a unique variation that cannot be predicted by historical legacy, large-scale environmental factors, and local community assembly processes. Moreover, the species pool effects were associated with microbial dormancy potential, where taxa with higher dormancy potential exhibited stronger species pool effects. Bacterial diversity in regions with higher agricultural intensity was more influenced by species pool effects than that in regions with low intensity, indicating that the maintenance of agricultural biodiversity in high-intensity regions strongly depends on species present in the surrounding landscape. Models for community completeness indicated the positive effect of regional species pool, further implying the community unsaturation and increased potential in bacterial diversity of agricultural ecosystems. Overall, our study reveals the indubitable role of regional species pool from adjacent natural ecosystems in predicting bacterial diversity, which has useful implication for biodiversity management and conservation in agricultural systems.

Pressure Induced Nonmonotonic Evolution of Superconductivity in 6R-TaS_{2} with a Natural Bulk Van der Waals Heterostructure.

The natural bulk Van der Waals heterostructure compound 6R-TaS_{2} consists of alternate stacking 1T- and 1H-TaS_{2} monolayers, creating a unique system that incorporates charge-density-wave (CDW) order and superconductivity (SC) in distinct monolayers. Here, after confirming that the 2D nature of the lattice is preserved up to 8 GPa in 6R-TaS_{2}, we documented an unusual evolution of CDW and SC by conducting high-pressure electronic transport measurements. Upon compression, we observe a gradual suppression of CDW within the 1T layers, while the SC exhibits a dome-shaped behavior that terminates at a critical pressure P_{c} around 2.9 GPa. By taking account of the fact that the substantial suppression of SC is concomitant with the complete collapse of CDW order at P_{c}, we argue that the 6R-TaS_{2} behaves like a stack of Josephson junctions and thus the suppressed superconductivity can be attributed to the weakening of Josephson coupling associated with the presence of CDW fluctuations in the 1T layers. Furthermore, the SC reversely enhances above P_{c}, implying the development of emergent superconductivity in the 1T layers after the melting of T-layer CDW orders. These results show that the 6R-TaS_{2} not only provides a promising platform to explore emergent phenomena but also serves as a model system to study the complex interactions between competing electronic states.

Recent advances in selective mono-/dichalcogenation and exclusive dichalcogenation of C(sp2)-H and C(sp3)-H bonds.

Organochalcogen compounds are prevalent in numerous natural products, pharmaceuticals, agrochemicals, polymers, biological molecules and synthetic intermediates. Direct chalcogenation of C-H bonds has evolved as a step- and atom-economical method for the synthesis of chalcogen-bearing compounds. Nevertheless, direct C-H chalcogenation severely lags behind C-C, C-N and C-O bond formations. Moreover, compared with the C-H monochalcogenation, reports of selective mono-/dichalcogenation and exclusive dichalcogenation of C-H bonds are relatively scarce. The past decade has witnessed significant advancements in selective mono-/dichalcogenation and exclusive dichalcogenation of various C(sp2)-H and C(sp3)-H bonds via transition-metal-catalyzed/mediated, photocatalytic, electrochemical or metal-free approaches. In light of the significance of both mono- and dichalcogen-containing compounds in various fields of chemical science and the critical issue of chemoselectivity in organic synthesis, the present review systematically summarizes the advances in these research fields, with a special focus on elucidating scopes and mechanistic aspects. Moreover, the synthetic limitations, applications of some of these processes, the current challenges and our own perspectives on these highly active research fields are also discussed. Based on the substrate types and C-H bonds being chalcogenated, the present review is organized into four sections: (1) transition-metal-catalyzed/mediated chelation-assisted selective C-H mono-/dichalcogenation or exclusive dichalcogenation of (hetero)arenes; (2) directing group-free selective C-H mono-/dichalcogenation or exclusive dichalcogenation of electron-rich (hetero)arenes; (3) C(sp3)-H dichalcogenation; (4) dichalcogenation of both C(sp2)-H and C(sp3)-H bonds. We believe the present review will serve as an invaluable resource for future innovations and drug discovery.

Association of air pollution and risk of chronic kidney disease: A systematic review and meta-analysis.

Although epidemiological studies have evaluated the association between ambient air pollution and chronic kidney disease (CKD), the results remain mixed. To clarify the nature of the association, we conducted a comprehensive systematic review and meta-analysis to assess the global relationship between air pollution and CKD. The Web of Science, PubMed, Embase and Cochrane Library databases systematically were searched for studies published up to July 2023 and included 32 studies that met specific criteria. The random effects model was used to derive overall risk estimates for each pollutant. The meta-analysis estimated odds ratio (ORs) of risk for CKD were 1.42 (95% confidence interval [CI]: 1.31-1.54) for each 10 µg/m3 increase in PM2.5 ; 1.20 (95% CI: 1.14-1.26) for each 10 µg/m3 increase in PM10 ; 1.07 (95% CI: 1.05-1.09) for each 10 µg/m3 increase in NO2 ; 1.03 (95% CI: 1.02-1.03) for each 10 µg/m3 increase in NOX ; 1.07 (95% CI: 1.01-1.12) for each 1 ppb increase in SO2 ; 1.03 (95% CI: 1.00-1.05) for each 0.1 ppm increase in CO. Subgroup analysis showed that this effect varied by gender ratio, age, study design, exposure assessment method, and income level. Furthermore, PM2.5 , PM10 , and NO2 had negative effects on CKD even within the World Health Organization-recommended acceptable concentrations. Our results further confirmed the adverse effect of air pollution on the risk of CKD. These findings can contribute to enhance the awareness of the importance of reducing air pollution among public health officials and policymakers.

Integrated metabolomics and phosphoproteomics reveal the protective role of exosomes from human umbilical cord mesenchymal stem cells in naturally aging mouse livers.

BACKGROUND: Aging is characterized by a general decline in cellular function, which ultimately affects whole body homeostasis. This study aimed to investigate the effects and underlying mechanisms of exosomes derived from human umbilical cord mesenchymal stem cells (hUCMSC-exos) on the livers of naturally aging mice. METHOD: Twenty-two-month-old C57BL6 mice were used as a natural aging animal model, divided into a saline-treated wild-type aged control group (WT-AC) and a hUCMSC-exo-treated group (WT-AEX), and then detected by morphology, metabolomics and phosphoproteomics. RESULTS: Morphological analysis showed that hUCMSC-exos ameliorated structural disorder and decreased markers of senescence and genome instability in aging livers. Metabolomics showed that hUCMSC-exos decreased the contents of saturated glycerophospholipids, palmitoyl-glycerols and eicosanoid derivatives associated with lipotoxicity and inflammation, consistent with the decreased phosphorylation of metabolic enzymes, such as propionate-CoA ligase (Acss2), at S267 detected by phosphoproteomics. Moreover, phosphoproteomics indicated that hUCMSC-exos reduced the phosphorylation of proteins participating in nuclear transport and cancer signaling, such as heat shock protein HSP90-beta (Hsp90ab1) at S226 and nucleoprotein TPR (Tpr) at S453 and S379, while increasing those involved in intracellular communication, such as calnexin (Canx) at S563 and PDZ domain-containing protein 8 (Pdzd8). Finally, phosphorylated HSP90ß and Tpr were verified predominantly in hepatocytes. CONCLUSION: HUCMSC-exos improved metabolic reprogramming and genome stability mainly associated with phosphorylated HSP90ß in hepatocytes in natural aging livers. This work provides a comprehensive resource of biological data by omics to support future investigations of hUCMSC-exos in aging.

Efficacy and safety of intravitreal injections of conbercept for the treatment of idiopathic choroidal neovascularization.

BACKGROUND: To determine the efficacy and safety of intravitreally injected conbercept, a vascular endothelial growth factor receptor fusion protein, for the treatment of idiopathic choroidal neovascularization (ICNV). METHODS: This retrospective study analyzed outcomes in 40 patients (40 eyes) with ICNV who received intravitreal injections of conbercept 0.5 mg (0.05 ml) and were followed up for at least 12 months. All patients underwent full ophthalmic examinations, including best-corrected vision acuity (BCVA), intraocular pressure (IOP), slit-lamp examination, color fundus photography, optical coherence tomography angiography, multifocal electroretinogram, and fundus fluorescence angiography, if necessary, at baseline and after 1, 3, 6, and 12 months. BCVA, macular central retinal thickness (CRT), IOP, CNV blood flow area, thickness of the CNV-pigment epithelial detachment complex, thickness of the retinal nerve fiber layer (RNFL), and the first positive peak (P1) amplitude density in ring 1 before and after treatment were compared. RESULTS: Mean baseline BCVA (logMAR), CRT, CNV blood flow area, and CNV-pigment epithelial detachment complex thickness were significantly lower 1, 3, 6, and 12 months after than before conbercept treatment (P < 0.05 each). IOP and baseline RNFL thickness were unaffected by conbercept treatment. P1 amplitude density was significantly higher 1, 3, 6, and 12 months after than before conbercept treatment (P < 0.05 each). None of the 40 eyes showed obvious ocular adverse reactions, such as endophthalmitis, glaucoma, cataract progression, and retinal detachment, and none of the patients experienced systemic adverse events, such as cardiovascular and cerebrovascular accidents. CONCLUSIONS: Intravitreal injection of conbercept is beneficial to eyes with ICNV, inducing the recovery of macular structure and function and improving BCVA, while not damaging the neuroretina. Intravitreal conbercept is safe and effective for the treatment of ICNV.

Color Duplex Ultrasonography for the Evaluation of Innominate, Subclavian, and Common Carotid Artery Stenosis.

OBJECTIVE: This study aimed to validate the efficiency of Doppler ultrasonography for predicting the innominate, subclavian, and common carotid artery stenosis. METHODS: This retrospective multicenter study between 2013 and 2022 enrolled 636 patients who underwent carotid Doppler ultrasonography and subsequent digital subtraction angiography. And 58 innominate artery stenosis, 147 common carotid artery stenosis, and 154 subclavian artery stenosis were included. The peak systolic velocity at innominate, subclavian, and common carotid artery, and velocity ratios of innominate artery to common carotid artery, innominate artery to subclavian artery, and common carotid artery to internal carotid artery were measured or calculated. The threshold values were determined using receiver operating characteristic analysis. RESULTS: The threshold values of innominate artery stenosis were peak systolic velocity >206 cm/s (sensitivity: 82.8%; specificity: 91.4%) to predict ≥50% stenosis and >285 cm/s (sensitivity: 89.2%; specificity: 94.9%) to predict ≥70% stenosis. The threshold values of common carotid artery stenosis were peak systolic velocity >175 cm/s (sensitivity: 78.2%; specificity: 91.9%) to predict ≥50% stenosis and >255 cm/s (sensitivity: 87.1%; specificity: 87.2%) to predict ≥70% stenosis. The threshold values of subclavian artery stenosis were peak systolic velocity >200 cm/s (sensitivity: 68.2%; specificity: 84.4%) to predict ≥50% stenosis and >305 cm/s (sensitivity: 57.9%; specificity: 91.4%) to predict ≥70% stenosis. CONCLUSIONS: Symptomatic patients with ultrasonic parameters of velocity at innominate artery ≥206 cm/s, velocity at common carotid artery ≥175 cm/s, or velocity at subclavian artery ≥200 cm/s need to be considered for further verification and whether revascularization is necessary.

Metapopulation capacity determines food chain length in fragmented landscapes.

Metapopulation capacity provides an analytic tool to quantify the impact of landscape configuration on metapopulation persistence, which has proven powerful in biological conservation. Yet surprisingly few efforts have been made to apply this approach to multispecies systems. Here, we extend metapopulation capacity theory to predict the persistence of trophically interacting species. Our results demonstrate that metapopulation capacity could be used to predict the persistence of trophic systems such as prey-predator pairs and food chains in fragmented landscapes. In particular, we derive explicit predictions for food chain length as a function of metapopulation capacity, top-down control, and population dynamical parameters. Under certain assumptions, we show that the fraction of empty patches for the basal species provides a useful indicator to predict the length of food chains that a fragmented landscape can support and confirm this prediction for a host-parasitoid interaction. We further show that the impact of habitat changes on biodiversity can be predicted from changes in metapopulation capacity or approximately by changes in the fraction of empty patches. Our study provides an important step toward a spatially explicit theory of trophic metacommunities and a useful tool for predicting their responses to habitat changes.

An alfalfa MYB-like transcriptional factor MsMYBH positively regulates alfalfa seedling drought resistance and undergoes MsWAV3-mediated degradation.

Drought is a major threat to alfalfa (Medicago sativa L.) production. The discovery of important alfalfa genes regulating drought response will facilitate breeding for drought-resistant alfalfa cultivars. Here, we report a genome-wide association study of drought resistance in alfalfa. We identified and functionally characterized an MYB-like transcription factor gene (MsMYBH), which increases the drought resistance in alfalfa. Compared with the wild-types, the biomass and forage quality were enhanced in MsMYBH overexpressed plants. Combined RNA-seq, proteomics and chromatin immunoprecipitation analysis showed that MsMYBH can directly bind to the promoters of MsMCP1, MsMCP2, MsPRX1A and MsCARCAB to improve their expression. The outcomes of such interactions include better water balance, high photosynthetic efficiency and scavenge excess H2O2 in response to drought. Furthermore, an E3 ubiquitin ligase (MsWAV3) was found to induce MsMYBH degradation under long-term drought, via the 26S proteasome pathway. Furthermore, variable-number tandem repeats in MsMYBH promoter were characterized among a collection of germplasms, and the variation is associated with promoter activity. Collectively, our findings shed light on the functions of MsMYBH and provide a pivotal gene that could be leveraged for breeding drought-resistant alfalfa. This discovery also offers new insights into the mechanisms of drought resistance in alfalfa.

Animal and plant space-use drive plant diversity-productivity relationships.

Plant community productivity generally increases with biodiversity, but the strength of this relationship exhibits strong empirical variation. In meta-food-web simulations, we addressed if the spatial overlap in plants' resource access and animal space-use can explain such variability. We found that spatial overlap of plant resource access is a prerequisite for positive diversity-productivity relationships, but causes exploitative competition that can lead to competitive exclusion. Space-use of herbivores causes apparent competition among plants, resulting in negative relationships. However, space-use of larger top predators integrates sub-food webs composed of smaller species, offsetting the negative effects of exploitative and apparent competition and leading to strongly positive diversity-productivity relationships. Overall, our results show that spatial overlap of plants' resource access and animal space-use can greatly alter the strength and sign of such relationships. In particular, the scaling of animal space-use effects opens new perspectives for linking landscape processes without effects on biodiversity to productivity patterns.

Will a large complex system be productive?

While the relationship between food web complexity and stability has been well documented, how complexity affects productivity remains elusive. In this study, we combine food web theory and a data set of 149 aquatic food webs to investigate the effect of complexity (i.e. species richness, connectance, and average interaction strength) on ecosystem productivity. We find that more complex ecosystems tend to be more productive, although different facets of complexity have contrasting effects. A higher species richness and/or average interaction strength increases productivity, whereas a higher connectance often decreases it. These patterns hold not only between realized complexity and productivity, but also characterize responses of productivity to simulated declines of complexity. Our model also predicts a negative association between productivity and stability along gradients of complexity. Empirical analyses support our predictions on positive complexity-productivity relationships and negative productivity-stability relationships. Our study provides a step forward towards reconciling ecosystem complexity, productivity and stability.