Different Adaptive Strategies of Three Mangrove Species to Nutrient Enrichment: Revealed by Trait-based Analysis

Mangrove species are undergoing environmental changes from nutrient-poor to nutrient enrichment due to the large input of external nutrients. The potential difference in adaptive strategies between the slow- and fast-growing species may lead to great changes in species interaction and ecosystem functioning. This study aims to test whether the response strategies to soil nutrient availability differ between the slow- and fast-growing mangrove species. The comparison was carried out among three common mangrove species including two slow-growing species Aegiceras corniculata and Kandelia obovata, and one intrinsic fast-growing species Laguncularia racemosa. All tested species showed conservative strategies (such as slow-growing and high concentrations of leaf tolerance/resistance traits) when living in the nutrient-poor soils. But when soil nutrient increased, L. racemosa shifted to a fast-growing strategy, accompanied by a substantial reduction of tolerance traits including the concentrations of carbon, cellulose, total phenolics, and soluble sugar in leaves. In contrast, A. corniculatum and K. obovata maintained still conservative strategies even under nutrient enrichment. All the species increased leaf nitrogen, phosphorus, lipid, lignin and specific leaf area (SLA) with soil nutrient availability, but L. racemosa showed a greater nutrient acquisition capacity indicated by a steeper regression line of SLA vs. nutrient resorption efficiency than A. corniculatum. Further, the steeper regression line of SLA vs. leaf δ13C of L. racemosa indicated a higher water use efficiency than A. corniculatum. The dependence of the adaptive strategies of these species to soil nutrient status improved the standing of plant-plant interactions at different soil nutrient status.

Nutrient resorption tightens plant nitrogen and phosphorus coupling and decreases with sulfur deposition as mediated by interannual precipitation in a meadow

Purpose Sulfur (S) deposition as a global change issue causes worldwide soil acidification, nutrient mobilization and marked changes in plant nutrition. Here, we investigated how S deposition would affect leaf nutrient resorption and how this effect varies with yearly fluctuations in precipitation. Methods In a semiarid meadow exposed to S addition, we measured nitrogen (N), phosphorus (P) and S concentrations in green and senescent leaves of a grass and a sedge and calculated nutrient resorption efficiencies (NuRE) across two years with contrasting precipitation (13% higher and 27% lower than long-term mean annual precipitation). Results Concentrations of N, P, and S in green and senescent leaves generally increased with S addition across the two years, with the exception of N and P concentrations in green leaves of the grass that showed no response or even decreased with S addition. The coupling relationships between N and P concentrations showed interannual variations and tightened by nutrient resorption, as evidenced by stronger N and P correlations in senescent leaves than in green leaves in the wet year. Leaf NuRE convergently decreased with S addition across the two years congruent with soil acidification and increased soil N, P and S availability, while NuRE was higher in the wet year due to lower soil nutrient availability herein. Conclusions This study provides new evidence on the role of nutrient resorption in tightening stoichiometric N:P relationships, and a three-dimensional feedback framework that plant nutrient resorption was favored by higher precipitation to sharpen its tradeoff with soil nutrient availability.

Seasonal variation in AMF colonisation, soil and plant nutrient content in gypsum specialist and generalist species growing in P-poor soils

Aims Gypsum soils are P-limited atypical soils that harbour a rich endemic flora. These singular soils are usually found in drylands, where plant activity and soil nutrient availability are seasonal. No previous studies have analysed the seasonality of P nutrition and its interaction with the arbuscular mycorrhiza fungi (AMF) colonisation in gypsum plants. Our aim was to evaluate the seasonal changes in plant nutrient status, AMF colonisation and rhizospheric soil nutrient availability in gypsum specialist and generalist species. Methods We evaluated seasonal variation in the proportion of root length colonised by AMF structures (hyphae, vesicules and arbuscules), plant nutrient status (leaf C, N and P and fine root C and N) and rhizospheric soil content (P, organic matter, nitrate and ammonium) of three gypsum specialists and two generalists throughout a year. Results All species showed arbuscules within roots, including species of Caryophyllaceae and Brassicaceae. Root colonisation by arbuscules (AC) was higher in spring than in other seasons, when plants showed high leaf P-requirements. Higher AC was decoupled from inorganic N and P availability in rhizospheric soil, and foliar nutrient content. Generalists showed higher AC than specialists, but only in spring. Conclusions Seasonality was found in AMF colonisation, rhizospheric soil content and plant nutrient status. The mutualism between plants and AMF was highest in spring, when P-requirements are higher for plants, especially in generalists. However, AMF decoupled from plant demands in autumn, when nutrient availability increases in rhizospheric soil.

Unraveling the Influence of Land-Use Change on δ13C, δ15N, and Soil Nutritional Status in Coniferous, Broadleaved, and Mixed Forests in Southern China: A Field Investigation

Natural isotopic abundance in soil and foliar can provide integrated information related to the long-term alterations of carbon (C) and nitrogen (N) cycles in forest ecosystems. We evaluated total carbon (TC), total nitrogen (TN), and isotopic natural abundance of C (δ13C) and N (δ15N) in soil and foliar of coniferous plantation (CPF), natural broadleaved forest (NBF), and mixed forest stands at three different soil depths (i.e., 0–10, 10–20, and 20–40 cm). This study also explored how soil available nutrients are affected by different forest types. Lutou forest research station, located in Hunan Province, central China, was used as the study area. Results demonstrated that the topsoil layer had higher TC and TN content in the mixed forest stand, resulting in a better quality of organic materials in the topsoil layer in the mixed forest than NBF and CPF. In general, soil TC, TN, and δ15N varied significantly in different soil depths and forest types. However, the forest type did not exhibit any significant effect on δ13C. Overall, soil δ13C was significantly enriched in CPF, and δ15N values were enriched in mixed forest. Foliar C content varied significantly among forest types, whereas foliar N content was not significantly different. No big differences were observed for foliar δ15N and δ13C across forest types. However, foliar δ13C and δ15N were positively related to soil δ13C and δ15N, respectively. Foliar N, soil and foliar C:N ratio, soil moisture content (SMC), and forest type were observed as the major influential factors affecting isotopic natural abundance, whereas soil pH was not significantly correlated. In addition, forest type change and soil depth increment had a significant effect on soil nutrient availability. In general, soil nutrient availability was higher in mixed forest. Our findings implied that forest type and soil depth alter TC, TN, and soil δ15N, whereas δ13C was only driven by soil depth. Moreover, plantations led to a decline in soil available nutrient content compared with NBF and mixed forest stands.

Extent and distribution of surface soil acidity in the rainfed areas of Ethiopia

The soil acidity level is a key soil characteristic that determines soil nutrient availability, soil microbial activities and crop growth. However, studies on distribution and extent of soil acidity in Ethiopia are not available. This study was carried out to predict the extent and severity of soil acidity. The study used 88,265 soil pH samples collected from soil laboratories and 21,439 samples compiled from studies. Rainfall, altitude, slope gradient, soil, and land cover were considered to generate spatial autocorrelation and integrated into geospatial analysis to predict the soil pH. The performance of the kriging model was found to be satisfactory with a standard error of 0.77, RMSE of 0.51, and R2 of 0.74. The model estimates showed that 47% and 30.2% of the country’s total area and rainfed areas were acidic (pH<6.5), respectively. Out of the total area of the country, 3.7% is found to be extremely to strongly acidic (pH<5.5), 20.7% is moderately acidic (5.6