Aboveground Biomass Of Grasses Research Articles

Shifting Mountain Tree Line Increases Soil Organic Carbon Stability Regardless of Land Use.

Climate and land use changes are causing trees line to shift up into mountain meadows. The effect of this vegetation change on the partitioning of soil carbon (C) between the labile particulate organic matter (POM-C) and stable mineral-associated organic matter (MAOM-C) pools is poorly understood. Therefore, we assessed these C pools in a 10 cm topsoil layer along forest-meadow ecotones with different land uses (reserve and pasture) in the Northwest Caucasus of Russia using the size fractionation technique (POM 0.053-2.00 mm, MAOM < 0.053 mm). Potential drivers included the amount of C input from aboveground grass biomass (AGB) and forest litter (litter quantity) and their C/N ratios, aromatic compound content (litter quality), and soil texture. For both land uses, the POM-C pool showed no clear patterns of change along forest-meadow ecotones, while the MAOM-C pool increased steadily from meadow to forest. Regardless of land use, the POM-C/MAOM-C ratio decreased threefold from meadow to forest in line with decreasing grass AGB (R2 = 0.75 and 0.29 for reserve and pasture) and increasing clay content (R2 = 0.63 and 0.36 for reserve and pasture). In pastures, an additional negative relationship was found with respect to plant litter aromaticity (R2 = 0.48). Therefore, shifting the mountain tree line in temperate climates could have a positive effect on conserving soil C stocks by increasing the proportion of stable C pools.

Plant biomass of grasses in actively restored grasslands shows stronger association with eco‐physiological properties than in degraded native grasslands

AbstractGrassland degradation levels determine plant eco‐physiological properties, and thus influences ecosystem function. However, how land degradation affects the relationship between plant biomass and eco‐physiological properties of native and artificially restored grasslands is insufficiently understood. Here, we evaluated aboveground biomass (AGB), plant photosynthetic capacity, as well as soil texture, in a series of native grasslands (non‐degraded, slightly degraded, moderately degraded, heavily degraded, and extremely degraded) and artificially restored grasslands with different growth times (5, 9, 11, 14 and 17 years) within the alpine grassland ecosystem of the Qinghai–Tibet Plateau during the plant growing season. Results showed that, in native grasslands, land degradation significantly decreased the nitrogen (N) concentration and AGB of grasses but did not impact the phosphorus (P) concentration. In actively restored grasslands, the AGB, photosynthetic rate (Pn), N and P of grasses decreased significantly after 9 years or longer of replanting time. Furthermore, the AGB of grasses in actively restored grasslands showed stronger association with eco‐physiological properties than in native grasslands. In native grasslands, degradation affected AGB directly, but also indirectly through Pn. In actively restored grasslands, degradation affected AGB directly, but also indirectly through Pn, N and P. Our findings suggest that the mechanisms by which grass species respond to degradation differ between native and actively restored grasslands. Also, compared to native grasslands, the eco‐physiological properties of grasses are more sensitive to changing environmental conditions in actively restored grasslands. More importantly, the differing response mechanisms are likely to alter the plant community dynamics and future ecosystem stability.

Integrating the PROSAIL and SVR Models to Facilitate the Inversion of Grassland Aboveground Biomass: A Case Study of Zoigê Plateau, China

Grasslands play a vital role in the global ecosystem. Efficient and reproducible methods for estimating the grassland aboveground biomass (AGB) are crucial for understanding grassland growth, promoting sustainable development, and assessing the carbon cycle. Currently, the available methods are limited by their computational inefficiency, model transfer, and sampling scale. Therefore, in this study, the estimation of grassland AGB over a large area was achieved by coupling the PROSAIL model with the support vector machine regression (SVR) method. The ill-posed inverse problem of the PROSAIL model was mitigated through kernel-based regularization using the SVR model. The Zoigê Plateau was used as the case study area, and the results demonstrated that the estimated biomass accurately reproduced the reference AGB map generated by zooming in on on-site measurements (R2 = 0.64, RMSE = 43.52 g/m2, RRMSE = 15.13%). The estimated AGB map also maintained a high fitting accuracy with field sampling data (R2 = 0.69, RMSE = 44.07 g/m2, RRMSE = 14.21%). Further, the generated time-series profiles of grass AGB for 2022 were consistent with the trends in local grass growth dynamics. The proposed method combines the advantages of the PROSAIL model and the regression algorithm, reduces the dependence on field sampling data, improves the universality and repeatability of grassland AGB estimation, and provides an efficient approach for grassland ecosystem construction and planning.

Comparing the Utility of Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) on Sentinel-2 MSI to Estimate Dry Season Aboveground Grass Biomass

Grasslands are biomes of significant fiscal, social and environmental value. Grassland or rangeland management often monitors and manages grassland productivity. Productivity is determined by various biophysical parameters, one such being grass aboveground biomass. Advancements in remote sensing have enabled near-real-time monitoring of grassland productivity. Furthermore, the increase in sophisticated machine learning algorithms has provided a powerful tool for remote sensing analytics. This study compared the performance of two neural networks, namely, Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN), in predicting dry season aboveground biomass using open-access Sentinel-2 MSI data. Sentinel-2 spectral bands and derived vegetation indices were used as input data for the two algorithms. Overall, findings in this study showed that the deep CNN outperformed the ANN in estimating aboveground biomass with an R2 of 0.83, an RMSE of 3.36 g/m2 and an RMSE% of 6.09. In comparison, the ANN produced an R2 of 0.75, an RMSE of 5.78 g/m2 and an RMSE% of 8.90. The sensitivity analysis suggested that the blue band, Green Chlorophyll Index (GCl), and Green Normalised Difference Vegetation Index (GNDVI) were the most significant for model development for both neural networks. This study can be considered a pilot study as it is one of the first to compare different neural network performances using freely available satellite data. This is useful for more rapid biomass estimation, and this study exhibits the great potential of deep learning for remote sensing applications.

Influence of weather conditions and elements of harvest structure on yield of spring triticale cultivated in organic agriculture on southern chernozem of northern Kazakhstan

The article presents the results of research on the influence of weather conditions and organic fertilizers on the elements of the crop structure and the productivity of spring triticale. The studies were carried out in the LLP " SPCGF named after A. Barayev" on southern carbonate chernozems in 2018-2021. Triticale was cultivated according to the falow. Dry above-ground mass of sweet clover, sainfoin, alfalfa, brome and wheatgrass was introduced into the fallow field as organic fertilizers. An annual decrease in the grain yield of spring triticale was noted over the years of research from 1.95 t/ha in 2018 to 1.01 t/ha in 2021. The weight of 1000 grains did not change significantly over the years of the study and ranged from 37.0-45.7 g. The number of triticale grains per unit area gradually decreased over the years of the study from a maximum in 2018 of 6951 pieces/m2 to a minimum in 2021 of 2739 pcs/m2. Variants of application of aboveground biomass of various perennial grasses as organic fertilizers had an equivalent effect on the yield of triticale and crop structure elements in comparison with the control (aboveground biomass of sweet clover). A positive correlation was obtained between the yield of triticale and HTC (according to Selyaninov) for the months of June and August, where the dependence on the variants of the experiment changed from medium to high (with June r=0.62 ... 0.94, with August r=0.64 ... 0.80). A moderate correlation was obtained between the grain yield and the HTC (according to Selyaninov) for the period June-August (r=0.59…0.78). The influence of the mass of 1000 grains on the yield was ambiguous, in some cases the relationship was weak (r=-0.21 ... -0.27) in others - medium (r=0.33 ... 0.36). A positive correlation was established between the grain yield and the number of grains per 1 m2 (r=0.61…0.94).

Grazing exclusion alters soil methane flux and methanotrophic and methanogenic communities in alpine meadows on the Qinghai-Tibet Plateau.

Grazing exclusion (GE) is an effective measure for restoring degraded grassland ecosystems. However, the effect of GE on methane (CH4) uptake and production remains unclear in dominant bacterial taxa, main metabolic pathways, and drivers of these pathways. This study aimed to determine CH4 flux in alpine meadow soil using the chamber method. The in situ composition of soil aerobic CH4-oxidizing bacteria (MOB) and CH4-producing archaea (MPA) as well as the relative abundance of their functional genes were analyzed in grazed and nongrazed (6 years) alpine meadows using metagenomic methods. The results revealed that CH4 fluxes in grazed and nongrazed plots were -34.10 and -22.82 μg‧m-2‧h-1, respectively. Overall, 23 and 10 species of Types I and II MOB were identified, respectively. Type II MOB comprised the dominant bacteria involved in CH4 uptake, with Methylocystis constituting the dominant taxa. With regard to MPA, 12 species were identified in grazed meadows and 3 in nongrazed meadows, with Methanobrevibacter constituting the dominant taxa. GE decreased the diversity of MPA but increased the relative abundance of dominated species Methanobrevibacter millerae from 1.47 to 4.69%. The proportions of type I MOB, type II MOB, and MPA that were considerably affected by vegetation and soil factors were 68.42, 21.05, and 10.53%, respectively. Furthermore, the structural equation models revealed that soil factors (available phosphorus, bulk density, and moisture) significantly affected CH4 flux more than vegetation factors (grass species number, grass aboveground biomass, grass root biomass, and litter biomass). CH4 flux was mainly regulated by serine and acetate pathways. The serine pathway was driven by soil factors (0.84, p < 0.001), whereas the acetate pathway was mainly driven by vegetation (-0.39, p < 0.05) and soil factors (0.25, p < 0.05). In conclusion, our findings revealed that alpine meadow soil is a CH4 sink. However, GE reduces the CH4 sink potential by altering vegetation structure and soil properties, especially soil physical properties.

Effects of Long-Term Exclosure on Main Plant Functional Groups and Their Biochemical Properties in a Patchily Degraded Alpine Meadow in the Source Zone of the Yellow River, West China

This study aimed to understand the response of vegetation community characteristics in the degraded alpine meadow of the Source Zone of the Yellow River to exclosure of various lengths. Artificial fences were erected to prevent livestock grazing and let the degraded meadow recover naturally as a means of restoration. The research focused on a typical degraded alpine meadow in which four plots were fenced off for three periods of 1 year (E1), 4 years (E4), and 10 years (E10), plus a freely grazed plot as the control. The study compared and analyzed the differences in plant community characteristics, carbon (C), nitrogen (N), and phosphorus (P) reserves, as well as the stoichiometric characteristics of main functional groups in the alpine meadow over different exclosure durations. The results indicated that E10 long-term exclosure significantly increased the aboveground biomass of gramineous plants but reduced the aboveground biomass of miscellaneous grasses. However, when compared to E4 short-term exclosure, E10 resulted in a reduction in the aboveground biomass of Cyperaceae plants. On the other hand, E4 medium-term exclosure significantly increased the aboveground biomass of Gramineae and Cyperaceae. Exclosure significantly increased the nitrogen (N) and phosphorus (P) reserves of the aboveground plant communities. Among these communities, the plant communities in the E10 long-term exclosure had the highest N and P reserves. However, this exclosure length also led to a significant reduction in plant diversity. Furthermore, except for Cyperaceae, all functional groups were observed in E10 and E4 plots. The carbon–nitrogen ratio and carbon–phosphorus ratio of these groups were significantly lower than those of groups G and E1. Medium-term exclosure (E4) has a positive impact on the aboveground biomass as well as plants’ nitrogen and phosphorus reserves. However, long-term exclosure (E10) has been observed to decrease species diversity and nutrient utilization efficiency of alpine meadow vegetation, which can be detrimental to the sustainable development of the alpine meadow ecosystem. Therefore, it is not recommended to implement long-term exclosure. Instead, a moderate level of grazing should be adopted after 4 years of exclosure.

Effect of grazing management strategies on the vegetation parameters and soil nutrients in alpine Kobresia pygmaea meadow on the northeastern Qinghai–Tibetan Plateau

Understanding the impact of grazing management strategies on alpine meadow is of fundamental importance for grassland conservation. However, the vegetation and soil properties in response to the different grazing management strategies implemented on Kobresia pygmaea meadow remains elusive. In this study, a medium-term field experiment with three grazing management strategies (free grazing, FG; no grazing, NG; and reduced grazing, RG) was conducted. The results revealed that the total aboveground biomass (AGB), vegetation cover and litter biomass increased significantly under NG treatment, whereas the total belowground biomass (BGB) decreased significantly in NG plot. Furthermore, the responses of plant functional groups to different grazing management strategies were varied. The AGB of grass increased remarkably under NG treatment compared to FG plot, whereas there were no obvious change in AGB of the sedge, legume, and forb groups. The concentrations of the soil available phosphorus (AP) and ammonia nitrogen (NH4+-N) of RG and FG were considerably different at the 0–5 cm soil layers. In contrast, the soil C:N ratios in all soil layers were similar among the three grazing management strategies. It is worth noting that the soil AP concentration was positively correlated with the total AGB. More importantly, the results supported the functional equilibrium hypothesis for AGB versus BGB, which is based on the unique biological characteristics of K. pygmaea meadow. Our study provides valuable insights into the response of alpine meadow to grazing management strategies and can thus provide guidance for designing management strategies for degraded alpine meadow.

Quantifying Aboveground Grass Biomass Using Space-Borne Sensors: A Meta-Analysis and Systematic Review

Recently, the move from cost-tied to open-access data has led to the mushrooming of research in pursuit of algorithms for estimating the aboveground grass biomass (AGGB). Nevertheless, a comprehensive synthesis or direction on the milestones achieved or an overview of how these models perform is lacking. This study synthesises the research from decades of experiments in order to point researchers in the direction of what was achieved, the challenges faced, as well as how the models perform. A pool of findings from 108 remote sensing-based AGGB studies published from 1972 to 2020 show that about 19% of the remote sensing-based algorithms were tested in the savannah grasslands. An uneven annual publication yield was observed with approximately 36% of the research output from Asia, whereas countries in the global south yielded few publications (&lt;10%). Optical sensors, particularly MODIS, remain a major source of satellite data for AGGB studies, whilst studies in the global south rarely use active sensors such as Sentinel-1. Optical data tend to produce low regression accuracies that are highly inconsistent across the studies compared to radar. The vegetation indices, particularly the Normalised Difference Vegetation Index (NDVI), remain as the most frequently used predictor variable. The predictor variables such as the sward height, red edge position and backscatter coefficients produced consistent accuracies. Deciding on the optimal algorithm for estimating the AGGB is daunting due to the lack of overlap in the grassland type, location, sensor types, and predictor variables, signalling the need for standardised remote sensing techniques, including data collection methods to ensure the transferability of remote sensing-based AGGB models across multiple locations.

Short-term Macrochloa tenacissima response understory Pinus halepensis Mill forest after early prescribed burns in a semi-arid landscape

Climate change has led to altered fire patterns in the Mediterranean basin due to rising temperatures and greenhouse gas emissions, diminishing the resilience of forest ecosystems. To address this threat, forest management increasingly employs preventive measures like controlled burns, aiming to mitigate wildfire damage. However, understanding the impact of prescribed burns on vegetation remains crucial.Our study focuses on assessing the ecological effects of early-season prescribed burns on Macrochloa tenacissima communities within Pinus halepensis Mill forests on the Iberian Peninsula. These forests, with southeast-facing slopes and arid soils, heavily rely on alpha grass for post-fire recovery, acting as a shield against runoff and erosion. Yet, the presence of highly flammable resprouting species can lead to rapid combustible material accumulation. We evaluated parameters like coverage, floral diversity (α-diversity), aboveground plant biomass, photosynthetic activity, and chemical leaf properties of alpha grass, a year after a low-intensity controlled burn. Comparing burnt and unburnt areas revealed significant changes in α-diversity and ecophysiology of Macrochloa tenacissima due to early-season prescribed burns. These short-term shifts underscore the need for further exploration of underlying mechanisms.Our analysis also showed distinct shifts in alpha grass leaf chemical composition between the two plot types, potentially impacting post-fire recovery strategies. Although prescribed burning might not be optimal for reducing fire risk in resprouting species-dominated forests, it conserves native plants and enhances ecosystem diversity, providing valuable ecological benefits.In conclusion, our research deepens our understanding of early-season burning's repercussions on flammable vegetation dynamics and combustible material availability in semi-arid landscapes. It contributes to standardized management protocols, aiding effective forest service administration and wildfire risk reduction.

Choose Local: Dung Addition from Native Herbivores Can Produce Substantial Positive Effects on the Growth of Native Grasses Compared to Livestock Dung

Livestock grazing and dung deposition can increase soil nutrients, contributing to the dominance of exotic species. Recent research suggests that native herbivore grazing has positive effects on native vegetation and soil health. However, little is known about the effects of native herbivore dung on plant growth and its potential implications for the restoration of degraded grasslands. This study examined the effects of dung addition from a native herbivore, kangaroo (Macropus giganteus), and ruminant livestock, sheep (Ovis aries), on biomass production and nutrient uptake of the native perennial wallaby grass (Rytidosperma auriculatum) and the annual exotic wild oat (Avena barbata), two of the most abundant grasses from the temperate grasslands of southern Australia. We conducted a glasshouse experiment, adding each type of dung to each plant species grown without competition in pots containing soil with a nutrient composition similar to that of old fields. Kangaroo dung produced higher wallaby grass aboveground biomass than other treatments and less wild oat aboveground biomass than the control. Kangaroo dung affected nutrient uptake but not nutrient concentration. Sheep dung had no effect. We demonstrated that native herbivores and livestock dung can have different effects on the biomass of native and invasive grasses. The higher nutrient uptake in wallaby grass appeared to be a consequence of the higher biomass production, suggesting that the effects produced by kangaroo dung could be related to its chemical and biological characteristics rather than its nutrient composition. Incorporating native herbivores’ dung or facilitating their presence can improve restoration outcomes in degraded grasslands.

Determining fire frequency and its relationship with rangeland aboveground grass biomass using MODIS and Landsat imagery

ABSTRACT High frequency burned area (BA) images provide an opportunity to monitor rangeland fire frequency (FF). This study related grass aboveground biomass (AGB) to FF in a 4800 ha biodiversity conservation savannah-grassland rangeland. Archived (2000–2021), 500 m resolution MODIS burned area monthly images were used. Following Boolean coding (fire event pixel = 1, no-fire pixel = 0), addition GIS overlay analysis yielded total fires per pixel location. Fire detection accuracy was assessed using 2018–2021 management fire event records. Sample grass AGB data were obtained at the end of the 2020 and 2021 growing seasons from widely dispersed sampling sites with wide grass cover uniformity, where a 1 m quadrat was tossed randomly in a 20 m × 20 m plot up to three times. The quadrat-enclosed grass was harvested to soil level, air-dried, and weighed to generate site average AGB values, which were correlated with vegetation index (VI) values from sampling near-concurrent surface reflectance (L2SP) Landsat-8 OLI images. Four biomass-sensitive VIs utilising Landsat sensor spectral ranges were tested. The Enhanced Vegetation Index (EVI) yielded the strongest relationship (r = 0.410, p < 0.01). A linear model predicting grass AGB from EVI values was developed using 58% of sample data for training (R 2 = 0.3062, p < 0.01) and 42% for validation (R 2 = 0.5225, p < 0.001). Using the model, sampling site historical grass AGB values were predicted on same season, L2SP Landsat (TM, ETM+, OLI) images from 2000, 2002, 2006, 2009, 2013 and 2016, whose dates were selected by comparing rainfall. The MODIS images detected 73% of fires larger than 25 ha (one pixel). Most sites experienced long-term AGB gains, at faster rates in high FF (4–5 fires), low grazing sites. Most fires occurred as ecologically undesired late burns, indicating the utility of archived high-frequency BA images for rangeland management.

Near-Term Effects of Perennial Grasses on Soil Carbon and Nitrogen in Eastern Nebraska

Incorporating native perennial grasses adjacent to annual row crop systems managed on marginal lands can increase system resiliency by diversifying food and energy production. This study evaluated (1) soil organic C (SOC) and total N stocks (TN) under warm-season grass (WSG) monocultures and a low diversity mixture compared to an adjacent no-till continuous-corn system, and (2) WSG total above-ground biomass (AGB) in response to two levels of N fertilization from 2012 to 2017 in eastern Nebraska, USA. The WSG treatments consisted of (1) switchgrass (SWG), (2) big bluestem (BGB), and (3) low-diversity grass mixture (LDM; big bluestem, Indiangrass, and sideoat grama). Soils were sampled at fixed depth increments (0–120 cm) in the WSG plots and in the adjacent corn experiment in 2012 and 2017. Soil stocks (Mg ha−1) of SOC and TN were calculated on an equivalent soil mass (ESM) basis and compared within the three WSG treatments as well as between experiments (corn compared to the mean of all WSGs). Soil organic C and TN stocks within soil layers and cumulative stocks responded to the main effect of WSG (PWSG &lt; 0.05) but were no different when comparing the WSGs to corn (Pexpt = NS). Both SOC/TN stocks and cumulative stocks were generally greater in the LDM compared to the BGB. Neither SOC nor TN changed over time under either the WSGs or corn. Warm-season grass AGB responded to a three-way interaction of year, N rate, and WSG (p = 0.0007). Decreases in AGB over time were significant across WSGs and N levels except for SWG at 56 kg N ha−1 and LDM at 112 kg N ha−1. Above-ground biomass was generally greater in the LDM after the first harvest year (2013). Results suggest that incorporating WSGs into marginal cropland can maintain SOC and TN stocks while providing a significant source of biomass to be used in energy production or in integrated livestock systems.

Random forest method for analysis of remote sensing inversion of aboveground biomass and grazing intensity of grasslands in Inner Mongolia, China

ABSTRACT The quantification of grassland above-ground biomass (AGB) and grazing intensity (GI) and their distribution in space is of great significance to grassland management and eco-conservation. Remote-sensing technology is widely applied, but it is difficult to measure accurately when monitoring GI. In this study, the neural network, random forest and statistical function models of the relationship between Landsat NDVI and AGB were constructed by field survey and literature data collection in Inner Mongolia grassland, China. By comparing the accuracy among the three models, we constructed a remote-sensing retrieving model of grass AGB. We also estimated the grassland AGB during the peak growing season (August) for Inner Mongolia. Frequency histograms were then made to identify AGB thresholds under four GI levels (light or ungrazed, moderate grazing, overgrazing and extreme grazing) for each of three grassland types (meadow steppe, typical steppe and desert steppe). This study shows that the random forest model simulates grass AGB more accurately than other models. The spatial distribution of AGB in Inner Mongolia grasslands showed a tendency of decreasing from southeast to northwest, with an increasing trend in the last 10 years. The four GI levels in 2021 accounted for 18%, 25%, 36% and 21% of the grasslands in Inner Mongolia, respectively, and over the last 10 years the GI first improved and then deteriorated. This study provides a guideline to remote monitoring for grassland AGB and GI, and supplies scientific support for sustainable management and grassland restoration of large-scale grasslands.

Effects of intra-annual precipitation patterns on grassland productivity moderated by the dominant species phenology.

Phenology and productivity are important functional indicators of grassland ecosystems. However, our understanding of how intra-annual precipitation patterns affect plant phenology and productivity in grasslands is still limited. Here, we conducted a two-year precipitation manipulation experiment to explore the responses of plant phenology and productivity to intra-annual precipitation patterns at the community and dominant species levels in a temperate grassland. We found that increased early growing season precipitation enhanced the above-ground biomass of the dominant rhizome grass, Leymus chinensis, by advancing its flowering date, while increased late growing season precipitation increased the above-ground biomass of the dominant bunchgrass, Stipa grandis, by delaying senescence. The complementary effects in phenology and biomass of the dominant species, L. chinensis and S. grandis, maintained stable dynamics of the community above-ground biomass under intra-annual precipitation pattern variations. Our results highlight the critical role that intra-annual precipitation and soil moisture patterns play in the phenology of temperate grasslands. By understanding the response of phenology to intra-annual precipitation patterns, we can more accurately predict the productivity of temperate grasslands under future climate change.

Whole-soil warming shifts species composition without affecting diversity, biomass and productivity of the plant community in an alpine meadow.

The structure and function of plant communities in alpine meadow ecosystems are potentially susceptible to climate warming. Here, we utilized a unique field manipulation experiment in an alpine meadow on the Qinghai-Tibetan Plateau and investigated the responses of plant species diversity, composition, biomass, and net primary productivity (NPP) at both community and functional group levels to whole-soil-profile warming (3-4 °C across 0-100cm) during 2018-2021. Plant species diversity, biomass and NPP (both above- and belowground) at the community level showed remarkable resistance to warming. However, plant community composition gradually shifted over time. Over the whole experimental warming period, aboveground biomass of legumes significantly decreased by 45%. Conversely, warming significantly stimulated aboveground biomass of forbs by 84%, likely because of better growth and competitive advantages from the warming-induced stimulation of soil water and other variables. However, warming showed minor effects on aboveground biomass of grasses and sedges. Overall, we emphasize that experimental warming may significantly affect plant community composition in a short term by triggering adjustments in plant interspecific competition or survival strategies, which may cause potential changes in plant productivity over a more extended period and lead to changes in carbon source-sink dynamics in the alpine meadow ecosystem.

Efficacy of Pendimethalin Rates on Barnyard Grass (Echinochloa crus-galli (L.) Beauv) and Their Effect on Photosynthetic Performance in Rice

Pendimethalin herbicide toxicity to rice plants and barnyard grass invasion have increasingly affected the productivity of direct-seeded rice (DSR) in the fields. Whether and how to promote DSR productivity and sustain weed management depend on the appropriate pre-emergence herbicide application rate to minimise its toxicity in the rice ecosystem. Pot experiments were conducted to determine the effects of pendimethalin rates (1.5, 1.75, 2.0 kg a.i. ha−1, two control treatments include the untreated control and the treated control with 1.5 kg a.i. ha−1 S-metolachlor) on barnyard grass (Echinochloa crus-galli (L.) Beaux) and their potential toxicity risk to photosynthetic performances of rice (Topaz and Sen pidao). All the pendimethalin treatments provided excellent control of barnyard grass. Among the treatments, 1.5, 1.75, 2.0 kg a.i. ha−1 pendimethalin and 1.5 kg a.i. ha−1 S-metolachlor (treated control) decreased leaf area of barnyard grass significantly by 38.9, 49.6, 49.6 and 46.2%, respectively, compared with the untreated control at 40 days after sowing (DAS). The above-ground biomass of barnyard grass significantly decreased by 40% (1.48 g plant−1) with 2.0 kg a.i. ha−1 pendimethalin and by 46.2% (1.33 g plant−1) when 1.5 kg a.i. ha−1S-metolachlor was applied at 40 DAS compared with the untreated pots. Higher pendimethalin rates increased toxicity in Topaz and Sen pidao varieties, and 2.0 kg a.i. ha−1 pendimethalin significantly reduced effective quantum yield (light-adapted) of photosystem (PS) II by 18% (0.58) and 19% (0.52), respectively, compared with the untreated control. Application of 2.0 kg a.i. ha−1 pendimethalin rate significantly decreased the maximum quantum yield (dark-adapted) of Sen pidao (0.66) compared with 1.5 kg a.i. ha−1 pendimethalin (0.68) including the untreated control. All pendimethalin treatments suppressed above-ground biomass at 55 DAS, but above-ground biomass of barnyard grass significantly decreased by 59.9% when 2.0 kg a.i. ha−1 pendimethalin was applied compared with the untreated control. Although application of 1.5 kg a.i. ha−1 pendimethalin rates reduced the effective quantum yield (light-adapted) of photosystem II of Sen pidao (0.55) by a small percentage (8%) than Topaz (0.65), it was non-toxic for both varieties compared with 2.0 kg a.i. ha−1 pendimethalin. Therefore, the use of 1.5 kg a.i. ha−1 pendimethalin can be used for effective weed management in the direct seeding of rice at an early growth stage.

Grasshopper abundance and offtake increase after prescribed fire in semi-arid grassland

Background Fire modulates herbivore dynamics in open ecosystems. While extensive work demonstrates the interaction between fire and vertebrate grazers, less research describes how grasshopper herbivory dynamics respond to fire. Aim We examined how fire increased grass crude protein content and increased the density of and offtake by grasshoppers relative to unburned mixed-grass prairie. Methods We deployed grasshopper exclusion cages to determine grasshopper offtake of aboveground plant biomass, counted grasshopper abundance throughout the study period, and measured crude protein content of aboveground grass biomass. Key results Offtake and density were higher in burned versus unburned plots. Burned plot grasshopper density increased over time, with greater rates of increase in recently burned plots, while density remained constant in unburned locations. Conclusions We present a potential mechanism by which fire interacts with grasshoppers in open ecosystems. It is likely that greater grasshopper offtake and density in recently-burned plots is at least partially attributable to higher crude protein content, as grass in these plots has a much higher proportion of recent growth after fire removed senesced material. Implications Grasshopper herbivory likely acts as a multiplier of livestock herbivory in burned rangeland. Restoring fire regimes can balance direct negative effects of heating against nutritional benefits.

Interactions between soil water and plant community during vegetation succession in the restored grasslands on the Loess Plateau of China

AbstractPlant–soil water relations are important for understanding the development of plant communities, especially in arid and semiarid areas. However, the interactions between vegetation characteristics and soil water dynamics in the restored grasslands along succession chronosequence were limitedly understood. In this study, we measured the functional traits of dominant species, plant community characteristics and soil water dynamics in grasslands restored for 5, 15, and 30 years (RG5, RG15 and RG30, respectively), and investigated the linkage between plant traits and soil water at the community/plot scale. The results showed that soil water content was high at RG5, while soil water storage increment at RG5 was low. With soil water content highest at RG5 (16.25%), decreased at RG15 (14.81%), and then recovered in some degree at RG30 (15.2%), dominant plant species changed from pioneer species Artemisia capillaries to perennial legume Lespedesa davurica with high specific leaf area, and finally to perennial forb Stipa bungeana with low specific leaf area and low shoot/root ratio. Plant community characteristics including aboveground biomass, vegetation coverage, species diversity all increased with restoration and reached the highest value at RG15 or RG30. Aboveground biomass of perennial grass, as well as species richness showed a significantly positive relationship with soil water recharge and soil water storage increment at deeper layers (10–120 cm and 40–120 cm). Species diversity had positive correlations with soil water content in 0–10 cm layer, a negative correlation with soil water storage increment in 0–10 cm layer and no correlation in 10–20 cm layer. Our findings suggested that changes in soil water content might enhance perennial grass species in semiarid grasslands, and time lag also existed in the plant–soil water interactions.

Effects of Land Use Changes on the Plant Community Characteristics in the Wetlands of the Semi-Arid Regions

Human disturbance is the main driving factor of wetland vegetation degradation, and plant community changes can directly characterize the process of wetland degradation. The wetlands in semi-arid region of Songnen Plain perform the important ecological functions, especially the habitat of waterbirds. Recently, the succession of wetland plant community has been accelerated by land use changes. In this study, we investigated the variations of plant community in wetlands undergoing land use changes (natural, mowing, light grazing + mowing, moderate grazing and heavy grazing wetlands) in the western Songnen Plain. The results showed that the plant communities were significantly affected by land use changes. The typical wetland plant Calamagrostis angustifolia was the dominant species in natural wetlands, and its dominance was gradually decreased in mowing or grazing wetlands in where Carex spp. or Artemisia selengensis acting as the dominant species. The height, density, and biomass in natural wetlands were significantly higher than those in other wetlands, whereas the species diversity and richness in natural wetlands were significantly lower. The similarity index of plant community in wetlands undergoing land use changes to natural wetlands ranged from 17.7–45.1%, being the highest in mowed wetlands and the lowest in heavily grazed wetlands. The linear regression further indicated that the plant diversity index was negatively correlated with the aboveground biomass of grasses and positively correlated with the aboveground biomass of forbs. Therefore, the land use changes in wetlands drove the replacement of dominant species of wetland vegetation and changed plant community characteristics and the species diversity, and the maintenance of species diversity is linked with the variability in plant functional strategies. The results of community variations and their relationships with functional changes can be used for assessing the effects of degradation and ecological function in response of land use changes in wetlands.