Methane (CH4) is a powerful greenhouse gas with ongoing efforts aiming to quantify and map emissions from natural and managed ecosystems. Wetlands play a significant role in the global CH4 budget, but uncertainties in their total emissions remain large, due to a combined lack of CH4 data and fuzzy boundaries between mapped ecosystem categories. European floodplain meadows are anthropogenic ecosystems that originated due to traditional management for hay cropping. These ecosystems are seasonally inundated by river water, and straddle the boundary between grassland and wetland ecosystems; however, an understanding of their CH4 function is lacking. Here, we established a replicated outdoor floodplain-meadow mesocosm experiment to test how water table depth (45, 30, 15 cm below the soil surface) and plant composition affect CH4 fluxes over an annual cycle. Water table was a major controller on CH4, with significantly higher fluxes (overall mean 9.3 mg m-2 d-1) from the high (15 cm) water table treatment. Fluxes from high water table mesocosms with bare soil were low (mean 0.4 mg m-2 d-1), demonstrating that vegetation drove high emissions. Larger emissions came from high water table mesocosms with aerenchymatous plant species (e.g. Alopecurus pratensis, mean 12.8 mg m-2 d-1), suggesting a role for plant-mediated transport. However, at low (45 cm) water tables A. pratensis mesocosms were net CH4 sinks, suggesting that there is plasticity in CH4 exchange if aerenchyma are present. Plant cutting to simulate a hay harvest had no effect on CH4, further supporting a role for plant-mediated transport. Upscaling our CH4 fluxes to a UK floodplain meadow using hydrological modelling showed that the meadow was a net CH4 source because oxic periods of uptake were outweighed by flooding-induced anoxic emissions. Our results show that floodplain meadows can be either small sources or sinks of CH4 over an annual cycle. Their CH4 exchange appears to respond to soil temperature, moisture status and community composition, all of which are likely to be modified by climate change, leading to uncertainty around the future net contribution of floodplain meadows to the CH4 cycle.

Attention Restoration Theory proposes that exposure to natural environments helps to restore attention. For sustained attention-the ongoing application of focus to a task, the effect appears to be modest, and the underlying mechanisms of attention restoration remain unclear. Exposure to nature may improve attention performance through many means: modulation of alertness and one\'s connection to nature were investigated here, in two separate studies. In both studies, participants performed the Sustained Attention to Response Task (SART) before and immediately after viewing a meadow, ocean, or urban image for 40 s, and then completed the Perceived Restorativeness Scale. In Study 1 (n = 68), an eye-tracker recorded the participants\' tonic pupil diameter during the SARTs, providing a measure of alertness. In Study 2 (n = 186), the effects of connectedness to nature on SART performance and perceived restoration were studied. In both studies, the image viewed was not associated with participants\' sustained attention performance; both nature images were perceived as equally restorative, and more restorative than the urban image. The image viewed was not associated with changes in alertness. Connectedness to nature was not associated with sustained attention performance, but it did moderate the relation between viewing the natural images and perceived restorativeness; participants reporting a higher connection to nature also reported feeling more restored after viewing the nature, but not the urban, images. Dissociation was found between the physiological and behavioral measures and the perceived restorativeness of the images. The results suggest that restoration associated with nature exposure is not associated with modulation of alertness but is associated with connectedness with nature.

Maize and alfalfa (Medicago sativa L.) have been used extensively in the animal husbandry to compensate for the lack of livestock and fodder yields in the chilly northeast of China. Little is known, however, about the impact on soil characteristics of consecutive plantings in various crops and alfalfa. In this research, the soil characteristics, bacterial community diversity, and structure of the meadow, maize, and alfalfa continuous cropping fields (i.e., 6, 10, 14, 20, and 30 years) were measured. The results showed that maize cropping and continuous cropping of alfalfa increased the soil bacterial alpha diversity compared with meadow cropping, and alpha diversity of alfalfa increased with the continuous planting years. Soil pH, total phosphorus (TP), available P, total potassium (TK), and nitrate nitrogen (NO3 -) content were soil variables significantly impacting the structure of soil bacterial communities in different plant types and different alfalfa continuous cropping systems. In addition, the relative abundance of some beneficial microbial species, such as Arthrobacter and Gaiellales, in the cropping maize and continuous cropping of alfalfa was much higher than that in the meadow field. Moreover, the networks differ among different plant types, and also differ among different continuous cropping years of alfalfa, and topologies of the networks suggested that continuous planting of alfalfa promotes cooperation between bacteria, which facilitates the long growth of alfalfa and is beneficial to the soil.

Microorganisms participate in the soil biogeochemical cycle. Therefore, investigating variations in microbial biomass, composition, and functions can provide a reference for improving soil ecological quality due to the sensitivity of microorganisms to vegetation coverage changes. However, the differences in soil microorganisms between shrubland and meadow have not been investigated in ecologically vulnerable subalpine areas. This study aimed to investigate the biochemical composition and functions of the soil microbial community under two shrublands and a meadow at high altitudes (3,400-3,550 m). Three sites under two shrublands, Rhododendron thymifolium (RHO) and Potentilla fruticosa (POT), and one meadow dominated by Kobresia myosuroides (MEA), were selected on the southern slope of the Qilian Mountains on the northeastern edge of the Qinghai-Tibetan Plateau, China. Soil physicochemical properties, the microbial community composition expressed by the phospholipid fatty acid (PLFA) biomarker, and enzyme activities were analyzed as well as their relationships. The results showed that water holding capacity and the soil carbon, nitrogen, and potassium content in RHO and POT were higher than those in the MEA. Moreover, the soil active carbon, dissolved organic carbon, total nitrogen, and dissolved total nitrogen content in RHO were higher than those in POT. The abundance of total PLFAs, bacteria, and fungi beneath the shrublands was considerably higher than that in the MEA. The PLFA abundance in RHO was significantly higher than that in POT. The fungal-to-bacterial ratio of RHO and POT was significantly higher than that in the MEA. The activities of β-glucosidase, cellobiohydrolase, and leucine aminopeptidase were the highest in RHO among the three vegetation types, followed by POT and MEA. The redundancy analysis indicated that the biochemical composition of the soil microorganisms and enzyme activities were driven by total nitrogen, dissolved organic carbon, water holding capacity, and soil organic carbon. Therefore, shrublands, which have higher biomass, can improve soil moisture status, increase soil carbon and nitrogen content (especially active carbon and active nitrogen), and further increase the abundance of total PLFAs, bacteria, and fungi. The increase of microbial biomass indirectly enhances the activity of relevant soil enzymes. The variations in PLFA abundance and enzyme activities can be attributed to shrub species, especially evergreen shrubs, which create more favorable conditions for soil microorganisms. This study provides a theoretical basis for investigating the soil biogeochemical cycle and a scientific basis for soil management and vegetation restoration in the subalpine regions.

Manual assessment of flower abundance of different flowering plant species in grasslands is a time-consuming process. We present an automated approach to determine the flower abundance in grasslands from drone-based aerial images by using deep learning (Faster R-CNN) object detection approach, which was trained and evaluated on data from five flights at two sites. Our deep learning network was able to identify and classify individual flowers. The novel method allowed generating spatially explicit maps of flower abundance that met or exceeded the accuracy of the manual-count-data extrapolation method while being less labor intensive. The results were very good for some types of flowers, with precision and recall being close to or higher than 90%. Other flowers were detected poorly due to reasons such as lack of enough training data, appearance changes due to phenology, or flowers being too small to be reliably distinguishable on the aerial images. The method was able to give precise estimates of the abundance of many flowering plant species. In the future, the collection of more training data will allow better predictions for the flowers that are not well predicted yet. The developed pipeline can be applied to any sort of aerial object detection problem.

Soil biological nitrogen fixation (BNF) represents a major pathway through which nitrogen enters pristine peatlands. Many peatlands have been undergoing human-induced changes in environmental factors, while environmental changes dramatically affect the community composition and activity of nitrogen-fixing prokaryotes (i.e., diazotrophs). However, the impact of peatland degradation on soil BNF remains unclear. By carrying out a field campaign, we examined how soil BNF varies along a natural gradient from pristine marshes to moderately-degraded meadows and sandy meadows on the Zoige Plateau. Plant and topsoil samples from four pristine marshes, three moderately-degraded meadows, and three sandy meadows were collected to determine the potential rate of nitrogen fixation (RNfix), abundance of the nifH gene, diazotrophic community composition, and soil and plant characteristics. Our results showed that topsoil RNfix varied in the range 0.018-3.00 μmol N g d.w.-1 day-1 (i.e. 21.74-1632.37 mg N m-2 day-1) across the ten sites, being lowest in sandy meadows and highest in pristine marshes. Topsoil RNfix and diazotrophic abundance were positively correlated with soil water content, sedge cover, plant biomass, soil organic carbon content, and total nitrogen and phosphorus contents. Soil water content, which affected most plant and soil characteristics, had dominant influences on the abundance and community structure of diazotrophs. The RNfix was closely correlated with the abundance of dominant diazotroph groups. The community composition of diazotrophs differed markedly among sites of different degradation levels. Proteobacteria was the most abundant diazotrophic phylum across the ten sites. Heterotrophic diazotrophs acted as the major contributor to BNF, especially in pristine marshes and moderately-degraded meadows. We conclude that soil water content was the main factor driving the depressed soil BNF during peatland degradation in Zoige, due to soil water effects on plant cover and biomass, soil organic carbon and total phosphorus, and the abundance and community structure of diazotrophs.

Tadham Moor in Somerset, England, is an exceptionally rich wetland site which has been mown for hay for many years, with stock grazing the aftermath, but with no history of any fertilizer use. A randomized blocks field experiment (1986-1989) was used to study the effects of five levels of nitrogen input treatments: 0 = control, 25, 50, 100 and 200 kg of N fertilizer per ha per yr. In Phase II of the experiment (1990-1993), each plot was split into two subplots. The allocated fertilizer treatment for the plot was continued in one, randomly selected, subplot but the treatment was discontinued in the other subplot. The experiment not only identified and quantified the changes occurring in the vegetation of hay meadows under different levels of N input, it also provided valuable insight into the dynamics of the sward upon the discontinuance of the treatments. The data for Phase II were used to estimate the time required by the changed vegetation (under different nitrogen treatments) to revert to a state comparable to that prevailing in the control plots. A method for estimating reversion times is described. The main difficulties in estimating the reversion times are identified, the choice of robust vegetation variables being critical. Reversion time estimation methods are presented and used to obtain working estimates for the four nitrogen treatments, applied for 5 yr. These estimates are 3, 5, 7 and 9 yr respectively. The validity of the estimates of 3 yr for the lowest nitrogen input treatment (25 kg /ha/yr) was checked using the available post cessation data.

Despite the crucial importance of arbuscular mycorrhizal fungi (AMF) for numerous processes within terrestrial ecosystems, knowledge of the determinants of AMF community structure still is limited, mainly because of the limited scope of the available individual case studies which often only include a few environmental variables. Here, we describe the AMF diversity of mid-European meadows (mown or regularly cut grasslands, or recently abandoned lands where grasslands established spontaneously) within a considerably heterogeneous landscape over a scale of several hundred kilometers with regard to macroclimatic, microclimatic, and soil parameters. We include data describing the habitat (including vegetation type), geography, and climate, and test their contribution to the structure of the AMF communities at a regional scale. We amplified and sequenced the ITS 2 region of the ribosomal DNA operon of the AMF from soil samples using nested PCR and Illumina pair-end amplicon sequencing. Habitat (especially soil pH) and geographical parameters (spatial distance, altitude, and longitude) were the main determinants of the structure of the AMF communities in the meadows at a regional scale, with the abundance of genera Septoglomus, Paraglomus, Archaeospora, Funneliformis, and Dominikia driving the main response. The effects of climate and vegetation type were not significant and were mainly encompassed within the geography and/or soil pH effects. This study illustrates how important it is to have a large set of environmental metadata to compare the importance of different factors influencing the AMF community structure at large spatial scales.

BACKGROUND: Global warming is going to affect both agricultural production and carbon storage in soil worldwide. Given the complexity of the soil-plant-atmosphere continuum, in situ experiments of climate warming are necessary to predict responses of plants and emissions of greenhouse gases (GHG) from soils. Arrays of infrared (IR) heaters have been successfully applied in temperate and tropical agro-ecosystems to produce uniform and large increases in canopy surface temperature across research plots. Because this method had not yet been tested in the Arctic where consequences of global warming on GHG emission are expected to be largest, the objective of this work was to test hexagonal arrays of IR heaters to simulate a homogenous 3 °C warming of the surface, i.e. canopy and visible bare soil, of five 10.5-m2 plots in an Arctic meadow of northern Norway.
RESULTS: Our results show that the IR warming setup was able to simulate quite accurately the target + 3 °C, thereby enabling us to simulate the extension of the growing season. Meadow yield increased under warming but only through the lengthening of the growing season. Our research also suggests that, when investigating agricultural systems on the Arctic, it is important to start the warming after the vegetation is established,. Indeed, differential emergence of meadow plants impaired the homogeneity of the warming with patches of bare soil being up to 9.5 °C warmer than patches of vegetation. This created a pattern of soil crusting, which further induced spatial heterogeneity of the vegetation. However, in the Arctic these conditions are rather rare as the soil exposed by snow melt is often covered by a layer of senescent vegetation which shelters the soil from direct radiation.
CONCLUSIONS: Consistent continuous warming can be obtained on average with IR systems in an Arctic meadow, but homogenous spatial distribution requires that the warming must start after canopy closure.

BACKGROUND: Most carabid beetles are particularly sensitive to local habitat characteristics. Although in China grasslands account for more than 40% of the national land, their biodiversity is still poorly known. The aim of this paper is to identify the main environmental characteristics influencing carabid diversity in different types of grassland in northern China.
METHODS: We investigated the influence of vegetation (plant biomass, cover, density, height and species richness), soil (bulk density, above ground litter, moisture and temperature) and climate (humidity, precipitation and temperature) on carabid community structure (species richness, species composition and functional diversity-measured as body size, movement and total diversity) in three types of grasslands: desert, typical and meadow steppes. We used Canonical correspondence analysis to investigate the role of habitat characteristics on species composition and eigenvector spatial filtering to investigate the responses of species richness and functional diversities.
RESULTS: We found that carabid community structure was strongly influenced by local habitat characteristics and particularly by climatic factors. Carabids in the desert steppe showed the lowest richness and functional diversities. Climate predictors (temperature, precipitation and humidity) had positive effects on carabid species richness at both regional and ecosystem levels, with difference among ecosystems. Plant diversity had a positive influence on carabid richness at the regional level. Soil compaction and temperature were negatively related to species richness at regional level. Climatic factors positively influenced functional diversities, whereas soil temperature had negative effects. Soil moisture and temperature were the most important drivers of species composition at regional level, whereas the relative importance of the various environmental parameters varied among ecosystems.
CONCLUSIONS: Carabid responses to environmental characteristics varied among grassland types, which warns against generalizations and indicates that management programs should be considered at grassland scale. Carabid community structure is strongly influenced by climatic factors, and can therefore be particularly sensitive to ongoing climate change.