Stronger Short-Term Effects of Mowing Than Extreme Summer Weather on a Subalpine Grassland

Mowing mitigated the sensitivity of ecosystem carbon fluxes responses to heat waves in a Eurasian meadow steppe

The heat waves (HW) will be more frequent and intense in the future with increased human activity and uncertain implications for ecosystem carbon fluxes. The semi-arid Eurasian grassland is sensitive to climate change and under frequent HWs attacks. Mowing as one of the most common human practices in this region, combining with HW can have comprehensive effects on plant communities, biomass, and nutrient cycling. Hence, a 3-year (2019-2021) field manipulation experiment was conducted to assess how mowing influenced the carbon cycling under HWs, and the interactions between HWs and mowing on carbon fluxes at the community and ecosystem levels in a Eurasian meadow steppe. Over the three years, HW significantly reduced net ecosystem CO₂ exchange (NEE) and gross ecosystem production (GEP) by 28 % and 8 % (P < 0.05), respectively, whereas ecosystem respiration (Re) did not show significant changes. Moderate mowing (stubble height was set at 6-8 cm) for harvest effectively mitigated ecosystem sensitivity to HWs and significantly increased ecosystem carbon fluxes (NEE, Re, and GEP), biomass and the number of species. Mowing reduced the negative impact of HWs on ecosystem carbon fluxes by about 15 % compared to HWs alone, contributing to the invasion of species such as Thalictrum squarrosum and Vicia amoena, and increased the indirect effect of HW on NEE in the structural equation model. In addition, the higher soil water content (SWC) was another effective way to reduce the impact of HWs. Therefore, mowing and higher SWC would be effective ways to counteract the negative effects of HWs on carbon fluxes in future grassland management.

Mowing enhances the positive effects of nitrogen addition on ecosystem carbon fluxes and water use efficiency in a semi-arid meadow steppe

Grasslands are now facing a continuously increasing supply of nitrogen (N) fertilizers, resulting in alterations in ecosystem functioning, including changes in carbon (C) and water cycling. Mowing, one of the most widely used grassland management techniques, has been shown to mitigate the negative impacts of increased N availability on species richness. However, knowledge of how N addition and mowing, alone and/or in combination, affect ecosystem-level C fluxes and water use efficiency (W_N) is still limited. We experimentally manipulated N fertilization (0 and 10 g N m^-2 yr^-1) and mowing (once per year at the end of the growing season) following a randomized block design in a meadow steppe characterized by salinization and alkalinization in northeastern China. We found that, compared to the control plots, N addition, mowing, and their interaction increased net ecosystem CO₂ exchange by 65.1%, 14.7%, and 133%, and W_N by 40.7%, 18.5%, and 96.1%, respectively. Nitrogen enrichment also decreased soil pH, which resulted in greater aboveground biomass (AGB). Moreover, N addition indirectly increased AGB by inducing changes in species richness. Our results indicate that mowing enhances the positive effects of N addition on ecosystem C fluxes and W_N. Therefore, appropriate grassland management practices are essential to improve ecosystem C sequestration, W_N, and mitigate future species diversity declines due to ecosystem eutrophication.

Estimating soil moisture content under grassland with hyperspectral data using radiative transfer modelling and machine learning

The monitoring of soil moisture content (SMC) at very high spatial resolution (<10m) using unmanned aerial systems (UAS) is of high interest for precision agriculture and the validation of large scale SMC products. Data-driven approaches are the most common method to retrieve SMC with UAS-borne data at water limited sites over non-disturbed agricultural crops. A major disadvantage of data-driven algorithms is the limited transferability in space and time and the need of a high number of ground reference samples. Physically-based approaches are less dependent on the amount of samples and are transferable in space and time. This study explores the potential of (1) a hybrid method targeting the soil brightness factor of the PROSAIL model using a variational heteroscedastic Gaussian Processes regression (VHGPR) algorithm, and (2) a data-driven method employing VHGPR for the retrieval of SMC over three grassland sites based on UAS-borne VIS-NIR (399-1001 nm) hyperspectral data. The sites were managed by mowing (Fendt), grazing (Grosses Bruch) and irrigation (Marquardt). With these distinct local pre-conditions we aimed to identify factors that favor and limit the retrieval of SMC. The hybrid approach presented encouraging results in Marquardt (RMSE = 1.5 Vol_%, R2 = 0.2). At the permanent grassland sites (Fendt, Grosses Bruch) the thatch layer jeopardized the application of the hybrid model. We identified the complex canopy structure of grassland as the main factor impacting the hybrid SMC retrieval. The data-driven approach showed high accuracy for Fendt (R2 = 0.84, RMSE = 8.66) and Marquardt (R2 = 0.4, RMSE = 10.52). All data-driven models build on the LAI-SMC relationship. However, this relationship was hampered by mowing (Fendt), leading to a lack of transferability in time. The alteration of plant traits by grazing prevents finding a relationship with SMC in Grosses Bruch. In Marquardt, we identified the timelag between changes in SMC and plant response as the main reason of decrease in model accuracy. Yet, the model performance is accurate in undisturbed and water-limited areas (Marquardt). The analysis points to challenges that need to be tackled in future research and opens the discussion for the development of robust models to retrieve high resolution SMC from UAS-borne remote sensing observations.

Mowing Facilitated Shoot and Root Litter Decomposition Compared with Grazing

Shoot and root litter are two major sources of soil organic carbon, and their decomposition is a crucial nutrient cycling process in the ecosystem. Altitude and land use could affect litter decomposition by changing the environment in mountain grassland ecosystems. However, few studies have investigated the effects of land use on litter decomposition in different altitudes. We examined how land-use type (mowing vs. grazing) affected shoot and root litter decomposition of a dominant grass (Bromus inermis) in mountain grasslands with two different altitudes in northwest China. Litterbags with 6 g of shoot or root were fixed in the plots to decompose for one year. The mass loss rate of the litter, and the environmental attributes related to decomposition, were measured. Litter decomposed faster in mowing than grazing plots, resulting from the higher plant cover and soil moisture but lower bulk density, which might promote soil microbial activities. Increased altitude promoted litter decomposition, and was positively correlated with soil moisture, soil organic carbon (SOC), and β-xylosidase activity. Our results highlight the diverse influences of land-use type on litter decomposition in different altitudes. The positive effects of mowing on shoot decomposition were stronger in lower than higher altitude compared to grazing due to the stronger responses of the plant (e.g., litter and aboveground biomass) and soil (e.g., soil moisture, soil bulk density, and SOC). Soil nutrients (e.g., SOC and soil total nitrogen) seemed to play essential roles in root decomposition, which was increased in mowing plots at lower altitude and vice versa at higher altitude. Therefore, grazing significantly decreased root mass loss at higher altitude, but slightly increased at lower altitude compared to mowing. Our results indicated that the land use might variously regulate the innate differences of the plant and edaphic conditions along an altitude gradient, exerting complex impacts in litter decomposition and further influencing carbon and nutrient cycling in mountain grasslands.

Effects of disturbances on aboveground biomass of alpine meadow in the Yellow River Source Zone, Western China

A field experiment quantifies the impacts of two external disturbances (mowing-simulated grazing and number of pika) on aboveground biomass (AGB) in the Yellow River Source Zone from 2018 to 2020. AGB was estimated from drone images for 27 plots subject to three levels of each disturbance (none, moderate, and severe). The three mowing severities bear a close relationship with AGB and its annual change. The effects of pika disturbance on AGB change were overwhelmed by the significantly different AGB at different mowing severities (-.471 < r < -.368), but can still be identified by inspecting each mowing intensity (-.884 < r < -.626). The impact of severe mowing on AGB loss was more profound than that of severe pika disturbance in heavily disturbed plots, and the joint effects of both severe disturbances had the most impacts on AGB loss. However, pika disturbance made little difference to AGB change in the moderate and non-mowed plots. Mowing intensity weakens the relationship between pika population and AGB change, but pika disturbance hardly affects the relationship between mowing severity and AGB change. The effects of both disturbances on AGB were further complexified by the change in monthly mean temperature. Results indicate that reducing mowing intensity is more effective than controlling pika population in efforts to achieve sustainable grazing of heavily disturbed grassland.

Improving Predictions of Climate Change-Land Use Change Interactions

Climate change and land use change often interact, altering biodiversity in unexpected ways. Research into climate change-land use change (CC-LUC) interactions has so far focused on quantifying biodiversity outcomes, rather than identifying the underlying ecological mechanisms, making it difficult to predict interactions and design appropriate conservation responses. We propose a risk-based framework to further our understanding of CC-LUC interactions. By identifying the factors driving the exposure and vulnerability of biodiversity to land use change, and then examining how these factors are altered by climate change (or vice versa), this framework will allow the effects of different interaction mechanisms to be compared across geographic and ecological contexts, supporting efforts to reduce biodiversity loss from interacting stressors.

Can mowing restore boreal rich-fen vegetation in the face of climate change?

Low-frequency mowing has been proposed to be an effective strategy for the restoration and management of boreal fens after abandonment of traditional haymaking. This study investigates how mowing affects long-term vegetation change in both oceanic and continental boreal rich-fen vegetation. This will allow evaluation of the effectiveness of mowing as a management and restoration tool in this ecosystem in the face of climate change. At two nature reserves in Central Norway (Tågdalen, 63° 03' N, 9° 05 E, oceanic climate and Sølendet, 62° 40' N, 11° 50' E, continental climate), we used permanent plot data from the two sites to compare plant species composition from the late 1960s to the early 1980s with that recorded in 2012-2015 in abandoned and mown fens. Changes in species composition and frequency were analysed by multivariate and univariate methods in relation to environmental variables and modelled climate and groundwater data. Mowing resulted in a decline in shrub and Molinia caerulea cover at the continental and oceanic sites respectively, and the total cover of specialist fen species had increased to a significantly greater extent in the mown plots than the unmown at the continental site. However, mowing did not have an effect on the cover of specialist bryophyte species, and some specialist species declined regardless of mowing treatment. Temperature sums had increased at both sites, but precipitation had not changed significantly. Mowing was shown to be the most important determinant of plant community composition at both sites, with local environmental conditions being of secondary importance. In conclusion, the abandonment of traditional management practices results in the loss of characteristic fen species. In order to encourage the restoration of typical rich-fen vegetation, particularly in oceanic areas, additional management measures, such as more intensive mowing, may be required.

Heavy mowing enhances the effects of heat waves on grassland carbon and water fluxes

Heat waves (HWs) are a type of extreme weather event that is of growing concern in the scientific community. Yet field data based on sound experiment on the variation of ecosystem CO₂ levels under HWs remain rare. Additionally, ecosystems react to HWs and the coupled human activities (such as grazing in grasslands) are unknown. Thus, a 3-year field experiment was conducted to simulate HWs in conjunction with different mowing intensities that mimicking grazing in a Stipa krylovii steppe on the Mongolian Plateau. HWs significantly decreased ecosystem exchange (NEE) of CO₂, ecosystem respiration (Re) and gross ecosystem productivity (GEP) by 31%, 5% and 16%, respectively, over the three years. Continuous HWs over multiple years produced cumulative effects by reducing NEE at 20%, 34% and 40% in the first, second and third HW years, respectively. During three pre-defined three periods of HWs (during HW period, after HW period in the same year, and after HW period in the next year), variations in water use efficiency indicated that the grassland ecosystem exhibited a strategy for adapting to the continuous HWs to a certain extent, by adjusting community structure or increasing litter biomass. Finally, mowing increased the effects of HWs by extending the legacy effect, such that restoration of the grassland required a greater amount of time under the combination of HWs and mowing.

Impact of droughts on water provision in managed alpine grasslands in two climatically different regions of the Alps

This study analyzes the impact of droughts, compared with average climatic conditions, on the supporting ecosystem service water provision in sub-watersheds in managed alpine grasslands in two climatically different regions of the Alps, Lautaret (French Alps) and Stubai (Austrian Alps). Soil moisture was modelled in the range of 0-0.3 m. At both sites, current patterns showed that the mean seasonal soil moisture was (1) near field capacity for grasslands with low management intensity and (2) below field capacity for grasslands with higher land-use intensity. Soil moisture was significantly reduced by drought at both sites, with lower reductions at the drier Lautaret site. At the sub-watershed scale, soil moisture spatial heterogeneity was reduced by drought. Under drought conditions, the evapotranspiration to precipitation ratios at Stubai was slightly higher than those at Lautaret, indicating a dominant 'water spending' strategy of plant communities. Regarding catchment water balance, deep seepage was reduced by drought at Stubai more strongly than at Lautaret. Hence, the observed 'water spending' strategy at Stubai might have negative consequences for downstream water users. Assessing the water provision service for alpine grasslands provided evidence that, under drought conditions, evapotranspiration was influenced not only by abiotic factors but also by the water-use strategy of established vegetation. These results highlight the importance of 'water-use' strategies in existing plant communities as predictors of the impacts of drought on water provision services and related ecosystem services at both the field and catchment scale.