Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.     

Fractal root system of Melica przewalskyi along different aspect in degraded grassland

Aims Fractal root system is phenotypic plasticity result of plant root architecture to respond to environmental heterogeneity, may reflect the growth strategy of plants to adapt to environmental conditions. Our objective was to explore the relationship between root fractal dimension and fractal abundance of fractal root system of Melica przewalskyi population in response to aspect variation in the northwest of China. Methods The study site was located in a degraded alpine grassland on the northern slope in Qilian Mountains, Gansu Province, China. Survey and sampling were carried out at 40 plots which were set up along four slope aspects transects with 20 m distance between adjacent plots. Handheld GPS was used to determine the elevation, longitude and latitude of each plot. ArcGIS was used to set up digital elevation model (DEM). Community traits were investigated and six individuals roots of M. przewalskyi were collected randomly at each plot. The samples were cleaned and divided into different organs, then scanning the root with the Win-RHIZO for measurements of fractal dimension and fractal abundance in laboratory, and their biomass were then measured after being dried at 80 °C in an oven. Important findings With the slope aspect turned from north to east, west, and south, the density, height and soil moisture content of the plant community displayed a pattern of initial decline, the height, density, root fractal abundance of M. przewalskyi increased and the root fractal dimension decreased. The root fractal dimension was negatively associated with the fractal abundance in all aspects, but the relationship varied along the slope aspects gradient; there was a highly significant negative correlation (p < 0.01) between the root fractal dimension and fractal abundance at north slope and south slope aspect, whereas the correlation only reached a significant level (p < 0.05) at the east slope aspect and west slope aspect; indicating that there is a trade-off between the root fractal dimension and fractal abundance. In addition, when the slope aspect changed from north to east, west and south, the standardized major axis (SMA) slope of the regression equation in the scaling relationships between root fractal dimension and fractal abundance increased (p < 0.05), indicating that the roots of M. przewalskyi at the droughty southern slope have less branch and more sparse in the same soil volume of root exploitation and utilization. Consequently, the resource allocation pattern on reasonable trade-off between root fractal dimension and fractal abundance in different slope aspect of M. przewalskyi, reflects the relationship between the income and the cost of construction of plant root architecture.     

Plant-derived smoke solutions stimulate the growth of Lycopersicon esculentum roots in vitro

Aqueous extracts of smoke, derived from Themeda triandra, a fire-climax grass, and Passerina vulgaris, a fynbos plant, stimulated the growth of primary root sections of tomato roots in suspension culture. The optimal dilution for both extracts was 1:2000. Several of the fractions obtained from TLC separation of the Themeda and the Passerina extracts significantly promoted primary root growth. The auxins naphthaleneacetic acid (NAA), indolebutyric acid (IBA) and indoleacetic acid (IAA) were found to stimulate the growth of the primary root axis, with IAA and NAA significantly promoting lateral root number. Similarly, the naturally occurring cytokinins, zeatin and its derivatives (zeatin-O-glucoside; dihydrozeatin and zeatin riboside) stimulated primary root length. Zeatin and dihydrozeatin promoted secondary root growth, but only at very low concentrations.     

Rice G protein γ subunit qPE9-1 modulates root elongation for phosphorus uptake by involving 14-3-3 protein OsGF14b and plasma membrane H+-ATPase

Heterotrimeric G protein is involved in plant growth and development, while the role of rice (Oryza sativa) G protein γ subunit qPE9-1 in response to low-phosphorus (LP) conditions remains unclear. The gene expression of qPE9-1 was significantly induced in rice roots under LP conditions. Rice varieties carrying the qPE9-1 allele showed a stronger primary root response to LP than the varieties carrying the qpe9-1 allele (mutant of the qPE9-1 allele). Transgenic rice plants with the qPE9-1 allele had longer primary roots and higher P concentrations than those with the qpe9-1 allele under LP conditions. The plasma membrane (PM) H⁺-ATPase was important for the qPE9-1-mediated response to LP. Furthermore, OsGF14b, a 14-3-3 protein that acts as a key component in activating PM H⁺-ATPase for root elongation, is also involved in the qPE9-1 mediation. Moreover, the overexpression of OsGF14b in WYJ8 (carrying the qpe9-1 allele) partially increased primary root length under LP conditions. Experiments using R18 peptide (a 14-3-3 protein inhibitor) showed that qPE9-1 is important for primary root elongation and H⁺ efflux under LP conditions by involving the 14-3-3 protein. In addition, rhizosheath weight, total P content, and the rhizosheath soil Olsen-P concentration of qPE9-1 lines were higher than those of qpe9-1 lines under soil drying and LP conditions. These results suggest that the G protein γ subunit qPE9-1 in rice plants modulates root elongation for phosphorus uptake by involving the 14-3-3 protein OsGF14b and PM H⁺-ATPase, which is required for rice P use.     

Rice straw decomposition in rice-field soil

Rice straw, buried in a rice-field during the dry season decomposed at a rate of 0.0075 day-1. Seventy five percent of the biomass, 70 percent carbon, 50 percent nitrogen and 30 percent phosphorus remained after 139 days of decomposition. Rice straw decomposition furnished 33% N and 8% P of the total nitrogen and phosphorus provided by man.     

Regulation of root hair density by phosphorus availability in Arabidopsis thaliana

We characterized the response of root hair density to phosphorus (P) availability in Arabidopsis thaliana. Arabidopsis plants were grown aseptically in growth media with varied phosphorus concentrations, ranging from 1 mmol m⁻³ to 2000 mmol m⁻³ phosphorus. Root hair density (number of root hairs per mm of root length) was analysed starting at 7 d of growth. Root hair density was highly regulated by phosphorus availability, increasing significantly in roots exposed to low-phosphorus availability. The initial root hairs produced by the radicle were not sensitive to phosphorus availability, but began to respond after 9 d of growth. Root hair density was about five times greater in low phosphorus (1 mmol m⁻³) than in high phosphorus (1000 mmol m⁻³) media. Root hair density decreased logarithmically in response to increasing phosphorus concentrations within that range. Root hair density also increased in response to deficiencies of several other nutrients, but not as strongly as to low phosphorus. Indoleacetic acid (IAA), the auxin transport inhibitor 2-(p-chlorophenoxy)-2-methylpropionic acid (CMPA), the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC), and the ethylene synthesis inhibitor amino-oxyacetic acid (AOA) all increased root hair density under high phosphorus but had very little effect under low phosphorus. Low phosphorus significantly changed root anatomy, causing a 9% increase in root diameter, a 31% decrease in the cross-sectional area of individual trichoblasts, a 40% decrease in the cross-sectional area of individual atrichoblasts, and 45% more cortical cells in cross-section. The larger number of cortical cells and smaller epidermal cell size in low phosphorus roots increased the number of trichoblast files from eight to 12. Two-thirds of increased root hair density in low phosphorus roots was caused by increased likelihood of trichoblasts to form hairs, and 33% of the increase was accounted for by changes in low phosphorus root anatomy resulting in an increased number of trichoblast files. These results show that phosphorus availability can fundamentally alter root anatomy, leading to changes in root hair density, which are presumably important for phosphorus acquisition.