COVID-19 pandemic-related drugs and microplastics from mask fibers jointly affect soil functions and processes.

The COVID-19 pandemic has led to an unprecedented increase in pharmaceutical drug consumption and plastic waste disposal from personal protective equipment. Most drugs consumed during the COVID-19 pandemic were used to treat other human and animal diseases. Hence, their nearly ubiquitous presence in the soil and the sharp increase in the last 3 years led us to investigate their potential impact on the environment. Similarly, the compulsory use of face masks has led to an enormous amount of plastic waste. Our study aims to investigate the combined effects of COVID-19 drugs and microplastics from FFP2 face masks on important soil processes using soil microcosm experiments. We used three null models (additive, multiplicative, and dominative models) to indicate potential interactions among different pharmaceutical drugs and mask MP. We found that the multiple-factor treatments tend to affect soil respiration and FDA hydrolysis more strongly than the individual treatments. We also found that mask microplastics when combined with pharmaceuticals caused greater negative effects on soil. Additionally, null model predictions show that combinations of high concentrations of pharmaceuticals and mask MP have antagonistic interactions on soil enzyme activities, while the joint effects of low concentrations of pharmaceuticals (with or without MP) on soil enzyme activities are mostly explained by null model predictions. Our study underscores the need for more attention on the environmental side effects of pharmaceutical contamination and their potential interactions with other anthropogenic global change factors.

Limiting Resources Define the Global Pattern of Soil Microbial Carbon Use Efficiency.

Microbial carbon (C) use efficiency (CUE) delineates the proportion of organic C used by microorganisms for anabolism and ultimately influences the amount of C sequestered in soils. However, the key factors controlling CUE remain enigmatic, leading to considerable uncertainty in understanding soil C retention and predicting its responses to global change factors. Here, we investigate the global patterns of CUE estimate by stoichiometric modeling in surface soils of natural ecosystems, and examine its associations with temperature, precipitation, plant-derived C and soil nutrient availability. We found that CUE is determined by the most limiting resource among these four basic environmental resources within specific climate zones (i.e., tropical, temperate, arid, and cold zones). Higher CUE is common in arid and cold zones and corresponds to limitations in temperature, water, and plant-derived C input, while lower CUE is observed in tropical and temperate zones with widespread limitation of nutrients (e.g., nitrogen or phosphorus) in soil. The contrasting resource limitations among climate zones led to an apparent increase in CUE with increasing latitude. The resource-specific dependence of CUE implies that soils in high latitudes with arid and cold environments may retain less organic C in the future, as warming and increased precipitation can reduce CUE. In contrast, oligotrophic soils in low latitudes may increase organic C retention, as CUE could be increased with concurrent anthropogenic nutrient inputs. The findings underscore the importance of resource limitations for CUE and suggest asymmetric responses of organic C retention in soils across latitudes to global change factors.

Oligotrophic microbes are recruited to resist multiple global change factors in agricultural subsoils.

An increasing number of anthropogenic pressures can have negative effects on biodiversity and ecosystem functioning. However, our understanding of how soil microbial communities and functions in response to multiple global change factors (GCFs) is still incomplete, particularly in less frequently disturbed subsoils. In this study, we examined the impact of different levels of GCFs (0-9) on soil functions and bacterial communities in both topsoils (0-20 cm) and subsoils (20-40 cm) of an agricultural ecosystem, and characterized the intrinsic factors influencing community resistance based on microbial life history strategy. Our experimental results showed a decline in soil multifunctionality, bacterial diversity, and community resistance as the number of GCFs increased, with a more drastic reduction in community resistance of subsoils. Specifically, we observed a significantly positive relationship between the oligotroph/copiotroph ratio and community resistance in subsoils, which was also verified by the negative correlation between 16S rRNA operon (rrn) copy number and community resistance. Structural equation modeling further revealed the direct effects of community resistance in promoting the ecosystem functioning, regardless of top- and subsoils. Therefore, these results suggested that subsoils may recruit more oligotrophic microbes to enhance their originally weaker community resistance under multiple GCFs, which was essential for maintaining sustainable agroecological functions and services. Overall, our study represents a significant advance in linking microbial life history strategy to the resistance of belowground microbial community and functionality.

Challenges in upscaling laboratory studies to ecosystems in soil microbiology research.

Soil microbiology has entered into the big data era, but the challenges in bridging laboratory-, field-, and model-based studies of ecosystem functions still remain. Indeed, the limitation of factors in laboratory experiments disregards interactions of a broad range of in situ environmental drivers leading to frequent contradictions between laboratory- and field-based studies, which may consequently mislead model development and projections. Upscaling soil microbiology research from laboratory to ecosystems represents one of the grand challenges facing environmental scientists, but with great potential to inform policymakers toward climate-smart and resource-efficient ecosystems. The upscaling is not only a scale problem, but also requires disentangling functional relationships and processes on each level. We point to three potential reasons for the gaps between laboratory- and field-based studies (i.e., spatiotemporal dynamics, sampling disturbances, and plant-soil-microbial feedbacks), and three key issues of caution when bridging observations and model predictions (i.e., across-scale effect, complex-process coupling, and multi-factor regulation). Field-based studies only cover a limited range of environmental variation that must be supplemented by laboratory and mesocosm manipulative studies when revealing the underlying mechanisms. The knowledge gaps in upscaling soil microbiology from laboratory to ecosystems should motivate interdisciplinary collaboration across experimental, observational, theoretic, and modeling research.

Rapid evolution generates synergism between multiple stressors: Linking theory and an evolution experiment.

Global change encompasses many co-occurring anthropogenic stressors. Understanding the interactions between these multiple stressors, whether they be additive, antagonistic or synergistic, is critical for ecosystem managers when prioritizing which stressors to mitigate in the face of global change. While such interactions between stressors appear prevalent, it remains unclear if and how these interactions change over time, as the majority of multiple-stressor studies rarely span multiple generations of study organisms. Although meta-analyses have reported some intriguing temporal trends in stressor interactions, for example that synergism may take time to emerge, the mechanistic basis for such observations is unknown. In this study, by analysing data from an evolution experiment with the rotifer Brachionus calyciflorus (~35 generations and 31,320 observations), we show that adaptation to multiple stressors shifts stressor interactions towards synergism. We show that trade-offs, where populations cannot optimally perform multiple tasks (i.e. adapting to multiple stressors), generate this bias towards synergism. We also show that removal of stressors from evolved populations does not necessarily increase fitness and that there is variation in the evolutionary trajectories of populations that experienced the same stressor regimes. Our results highlight outstanding questions at the interface between evolution and global change biology, and illustrate the importance of considering rapid adaptation when managing or restoring ecosystems subjected to multiple stressors under global change.

Airborne signals and abiotic factors: the neglected side of the plant communication.

A relevant number of reports have examined the role of airborne signals in plant-plant communication, indicating that volatile organic compounds (VOCs) can prime neighboring plants against pathogen and/or herbivore attacks. Conversely, there is very limited information available on the possibility of the emission of VOCs by emitter plants under abiotic stress conditions, which may alert neighboring unstressed plants and prime these individuals (receivers) against the same stressors. The present opinion paper briefly reviews a few reports examining the effect of infochemicals produced by emitters on receiver plants subjected to abiotic stresses typical of global climate change. The ecological implications of these dynamics, as well as some concerns related to the potential roles of inter-plant communication in environmentally controlled experiments, have arisen. Some possible inter-plant communications applications (biomonitoring and biostimulation), mediated by airborne signals, and some directions for future studies on this topic, are also provided.

Towards a unified study of multiple stressors: divisions and common goals across research disciplines.

Anthropogenic environmental changes, or 'stressors', increasingly threaten biodiversity and ecosystem functioning worldwide. Multiple-stressor research is a rapidly expanding field of science that seeks to understand and ultimately predict the interactions between stressors. Reviews and meta-analyses of the primary scientific literature have largely been specific to either freshwater, marine or terrestrial ecology, or ecotoxicology. In this cross-disciplinary study, we review the state of knowledge within and among these disciplines to highlight commonality and division in multiple-stressor research. Our review goes beyond a description of previous research by using quantitative bibliometric analysis to identify the division between disciplines and link previously disconnected research communities. Towards a unified research framework, we discuss the shared goal of increased realism through both ecological and temporal complexity, with the overarching aim of improving predictive power. In a rapidly changing world, advancing our understanding of the cumulative ecological impacts of multiple stressors is critical for biodiversity conservation and ecosystem management. Identifying and overcoming the barriers to interdisciplinary knowledge exchange is necessary in rising to this challenge. Division between ecosystem types and disciplines is largely a human creation. Species and stressors cross these borders and so should the scientists who study them.