Soil microbes comprise a large portion of the genetic diversity on Earth and influence a large number of important ecosystem processes. Increasing atmospheric nitrogen (N) deposition represents a major global change driver; however, it is still debated whether the impacts of N deposition on soil microbial biomass and respiration are ecosystem-type dependent. Moreover, the extent of N deposition impacts on microbial composition remains unclear. Here we conduct a global meta-analysis using 1408 paired observations from 151 studies to evaluate the responses of soil microbial biomass, composition, and function to N addition. We show that nitrogen addition reduced total microbial biomass, bacterial biomass, fungal biomass, biomass carbon, and microbial respiration. Importantly, these negative effects increased with N application rate and experimental duration. Nitrogen addition reduced the fungi to bacteria ratio and the relative abundances of arbuscular mycorrhizal fungi and gram-negative bacteria and increased gram-positive bacteria. Our structural equation modeling showed that the negative effects of N application on soil microbial abundance and composition led to reduced microbial respiration. The effects of N addition were consistent across global terrestrial ecosystems. Our results suggest that atmospheric N deposition negatively affects soil microbial growth, composition, and function across all terrestrial ecosystems, with more pronounced effects with increasing N deposition rate and duration.

Plants are key to the functionality of many ecosystem processes. The duration and intensity of water stress are anticipated to increase in the future; however, a detailed elucidation of the responses of plants to water stress remains incomplete. For this study, we present a meta-analysis derived from the 1,301 paired observations of 84 studies to evaluate the responses of plants to water stress. The results revealed that although water stress inhibited plant growth and photosynthesis, it increased reactive oxygen species (ROS), plasma membrane permeability, enzymatic antioxidants, and non-enzymatic antioxidants. Importantly, these responses generally increased with the intensity and duration of water stress, with a more pronounced decrease in ROS anticipated over time. Our findings suggested that the overproduction of ROS was the primary mechanism behind the responses of plants to water stress, where plants appeared to acclimatize to water stress, to some extent, over time. Our synthesis provides a framework for better understanding the responses and mechanisms of plants under drought conditions.

Estimating forest structural attributes of planted forests plays a key role in managing forest resources, monitoring carbon stocks, and mitigating climate change. High-resolution and low-cost remote-sensing data are increasingly available to measure three-dimensional (3D) canopy structure and model forest structural attributes. In this study, we compared two suites of point cloud metrics and the accuracies of predictive models of forest structural attributes using unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) and digital aerial photogrammetry (DAP) data, in a subtropical coastal planted forest of East China. A comparison between UAV-LiDAR and UAV-DAP metrics was performed across plots among different tree species, heights, and stem densities. The results showed that a higher similarity between the UAV-LiDAR and UAV-DAP metrics appeared in the dawn redwood plots with greater height and lower stem density. The comparison between the UAV-LiDAR and DAP metrics showed that the metrics of the upper percentiles (r for dawn redwood = 0.95–0.96, poplar = 0.94–0.95) showed a stronger correlation than the lower percentiles (r = 0.92–0.93, 0.90–0.92), whereas the metrics of upper canopy return density (r = 0.21–0.24, 0.14–0.15) showed a weaker correlation than those of lower canopy return density (r = 0.32–0.68, 0.31–0.52). The Weibull α parameter indicated a higher correlation (r = 0.70–0.72) than that of the Weibull β parameter (r = 0.07–0.60) for both dawn redwood and poplar plots. The accuracies of UAV-LiDAR (adjusted (Adj)R² = 0.58–0.91, relative root-mean-square error (rRMSE) = 9.03%–24.29%) predicted forest structural attributes were higher than UAV-DAP (Adj-R² = 0.52–0.83, rRMSE = 12.20%–25.84%). In addition, by comparing the forest structural attributes between UAV-LiDAR and UAV-DAP predictive models, the greatest difference was found for volume (ΔAdj-R² = 0.09, ΔrRMSE = 4.20%), whereas the lowest difference was for basal area (ΔAdj-R² = 0.03, ΔrRMSE = 0.86%). This study proved that the UAV-DAP data are useful and comparable to LiDAR for forest inventory and sustainable forest management in planted forests, by providing accurate estimations of forest structural attributes.

Deforestation poses a global threat to biodiversity and its capacity to deliver ecosystem services. Yet, the impacts of deforestation on soil biodiversity and its associated ecosystem services remain virtually unknown. We generated a global dataset including 696 paired-site observations to investigate how native forest conversion to other land uses affects soil properties, biodiversity, and functions associated with the delivery of multiple ecosystem services. The conversion of native forests to plantations, grasslands, and croplands resulted in higher bacterial diversity and more homogeneous fungal communities dominated by pathogens and with a lower abundance of symbionts. Such conversions also resulted in significant reductions in carbon storage, nutrient cycling, and soil functional rates related to organic matter decomposition. Responses of the microbial community to deforestation, including bacterial and fungal diversity and fungal guilds, were predominantly regulated by changes in soil pH and total phosphorus. Moreover, we found that soil fungal diversity and functioning in warmer and wetter native forests is especially vulnerable to deforestation. Our work highlights that the loss of native forests to managed ecosystems poses a major global threat to the biodiversity and functioning of soils and their capacity to deliver ecosystem services.

The CRISPR/Cas9 system (clustered regularly interspaced short palindromic repeat-associated protein 9) is a powerful genome-editing tool in animals, plants, and humans. This system has some advantages, such as a high on-target mutation rate (targeting efficiency), less cost, simplicity, and high-efficiency multiplex loci editing, over conventional genome editing tools, including meganucleases, transcription activator-like effector nucleases (TALENs), and zinc finger nucleases (ZFNs). One of the crucial shortcomings of this system is unwanted mutations at off-target sites. We summarize and discuss different approaches, such as dCas9 and Cas9 paired nickase, to decrease the off-target effects in plants. According to studies, the most effective method to reduce unintended mutations is the use of ligand-dependent ribozymes called aptazymes. The single guide RNA (sgRNA)/ligand-dependent aptazyme strategy has helped researchers avoid unwanted mutations in human cells and can be used in plants as an alternative method to dramatically decrease the frequency of off-target mutations. We hope our concept provides a new, simple, and fast gene transformation and genome-editing approach, with advantages including reduced time and energy consumption, the avoidance of unwanted mutations, increased frequency of on-target changes, and no need for external forces or expensive equipment.