Fertilization of two genetic groups of Pinus patula Schiede ex Schltdl. & Cham. in a four-year progeny trial

Introduction: Genetic improvement and nutritional management are used to increase productive capacity. Objective: To analyze the effect of traditional and controlled-release fertilizers, as well as the way to define the doses (technically or empirically), on growth of 20 tree families of Pinus patulaSchiede ex Schltdl. & Cham. Materials and methods: Four fertilization treatments were applied: 1) control; 2) “technical”, based on foliar analysis; 3) controlled release (18-6-12 + 2CaO + 3.5 Mg + 2.1 Si + microelements); and 4) mixture of agricultural fertilizers in nutrient concentrations similar to the controlled-release treatment. Height, diameter, biomass index, number of whorls, leaf mass, and growth initiation and cessation were evaluated in a group of 10 superior and 10 inferior three-year old families in Chignahuapan, Puebla. Data were analyzed with the MIXED procedure of SAS. Results and discussion: Trees showed no significant differences in growth, biomass production and growth initiation by fertilization effect, but showed significant differences by genetic quality (P ≤ 0.05). The genotype*fertilization interaction was significant; after one year of controlled-release fertilizer application, inferior genotypes had the highest values of relative rates of biomass production, diameter at root collar and height. Conclusions: Controlled-release fertilizers at appropriate doses and environmental conditions are a viable option to promote growth of young P. patula trees in the field.

Water Deficit Modulates the CO2 Fertilization Effect on Plant Gas Exchange and Leaf-Level Water Use Efficiency: A Meta-Analysis

Elevated atmospheric CO2 concentrations ([eCO2]) and soil water deficits significantly influence gas exchange in plant leaves, affecting the carbon-water cycle in terrestrial ecosystems. However, it remains unclear how the soil water deficit modulates the plant CO2 fertilization effect, especially for gas exchange and leaf-level water use efficiency (WUE). Here, we synthesized a comprehensive dataset including 554 observations from 54 individual studies and quantified the responses for leaf gas exchange induced by e[CO2] under water deficit. Moreover, we investigated the contribution of plant net photosynthesis rate (Pn) and transpiration rates (Tr) toward WUE in water deficit conditions and e[CO2] using graphical vector analysis (GVA). In summary, e[CO2] significantly increased Pn and WUE by 11.9 and 29.3% under well-watered conditions, respectively, whereas the interaction of water deficit and e[CO2] slightly decreased Pn by 8.3%. Plants grown under light in an open environment were stimulated to a greater degree compared with plants grown under a lamp in a closed environment. Meanwhile, water deficit reduced Pn by 40.5 and 37.8%, while increasing WUE by 24.5 and 21.5% under ambient CO2 concentration (a[CO2]) and e[CO2], respectively. The e[CO2]-induced stimulation of WUE was attributed to the common effect of Pn and Tr, whereas a water deficit induced increase in WUE was linked to the decrease in Tr. These results suggested that water deficit lowered the stimulation of e[CO2] induced in plants. Therefore, fumigation conditions that closely mimic field conditions and multi-factorial experiments such as water availability are needed to predict the response of plants to future climate change.

Nitrate fertilization may delay autumn leaf senescence, while amino acid treatments do not

Fertilization with nitrogen (N)-rich compounds leads to increased growth, but may compromise phenology and winter survival of trees in boreal regions. During autumn, N is remobilized from senescing leaves and stored in other parts of the tree to be used in the next growing season. However, the mechanism behind the N fertilization effect on winter survival is not well understood and it is unclear how N levels or forms modulate autumn senescence. We performed fertilization experiments and showed that treating Populus saplings with high or low levels of inorganic nitrogen resulted in a delay in senescence. In addition, by using precise delivery of solutes into the xylem stream of Populus trees in their natural environment, we found that delay of autumn senescence was dependent on the form of N administered: inorganic N (NO3-1) delayed senescence but amino acids (Arg, Glu, Gln, and Leu) did not. Metabolite profiling of leaves showed that the levels of tricarboxylic acids (TCA), arginine catabolites (ammonium, ornithine), glycine, glycine-serine ratio and overall carbon-to-nitrogen (C/N) ratio were affected differently by the way of applying NO3-1 and Arg treatments. In addition, the onset of senescence did not coincide with soluble sugar accumulation in any of the treatments. Taken together, metabolomic rearrangement under different N forms or experimental setups could modulate senescence process, but not initiation and progression in Populus. We propose that the different regulation of C and N status through direct molecular signaling of NO3-1 could account for the contrasting effects of NO3-1 and Arg on senescence.

Climatic factors influencing New Zealand pasture resilience under scenarios of future climate change

New Zealand’s intensively managed pastoral agricultural systems are vulnerable to climate change because of their dependence on grazing livestock and pasture as the primary feed supply. Drawing from recent modelling results, annual pasture yields in New Zealand are projected to be robust to a changing climate due to more favourable growing conditions in winter and early spring and increased plant efficiencies from the CO2 fertilization effect. However, growth is also expected to become more variable and unpredictable, particularly in water-limited regions. A combination of short-term, incremental changes (already part of current practice) and longer-term strategic interventions will be necessary to maintain consistent feed supply under future climate change.

Plant Functional Types Differ in Their Long-term Nutrient Response to eCO2 in an Extensive Grassland

Increasing atmospheric CO2 enhances plant biomass production and may thereby change nutrient concentrations in plant tissues. The objective of this study was to identify the effect of elevated atmospheric CO2 concentrations on nutrient concentrations of grassland biomass that have been grown for 16 years (1998–2013). The grassland biomass grown at the extensively managed Giessen FACE experiment, fumigated with ambient and elevated CO2 (aCO2; eCO2; +20%) was harvested twice annually. Concentrations of C, N, P, K, Ca, Mg, Mn, Fe, Cu and Zn were determined separately for grasses, forbs and legumes. Under eCO2, the concentration of N was reduced in grasses, Ca was reduced in grasses and forbs, P was reduced in grasses but increased in legumes, Mg concentration was reduced in grasses, forbs and legumes and K was reduced in grasses but increased in forbs. The nutrient yield (in g nutrient yield of an element per m−2) of most elements indicated negative yield responses at a zero biomass response to eCO2 for grasses. K and Zn nutrient yields responded positively to eCO2 in forbs and Mn and Fe responded positively in forbs and legumes. The results suggest that under eCO2 the nutrient concentrations were not diluted by the CO2 fertilization effect. Rather, altered plant nutrient acquisitions via changed physiological mechanisms prevail for increased C assimilation under eCO2. Furthermore, other factors such as water or nutrient availability affected plant nutrient concentrations under eCO2.

The response of the Amazon ecosystem to the photosynthetically active radiation fields: integrating impacts of biomass burning aerosol and clouds in the NASA GEOS Earth system model

The Amazon experiences fires every year, and the resulting biomass burning aerosols, together with cloud particles, influence the penetration of sunlight through the atmosphere, increasing the ratio of diffuse to direct photosynthetically active radiation (PAR) reaching the vegetation canopy and thereby potentially increasing ecosystem productivity. In this study, we use the NASA Goddard Earth Observing System (GEOS) model with coupled aerosol, cloud, radiation, and ecosystem modules to investigate the impact of Amazon biomass burning aerosols on ecosystem productivity, as well as the role of the Amazon's clouds in tempering this impact. The study focuses on a 7-year period (2010–2016) during which the Amazon experienced a variety of dynamic environments (e.g., La Niña, normal years, and El Niño). The direct radiative impact of biomass burning aerosols on ecosystem productivity – called here the aerosol diffuse radiation fertilization effect – is found to increase Amazonian gross primary production (GPP) by 2.6 % via a 3.8 % increase in diffuse PAR (DFPAR) despite a 5.4 % decrease in direct PAR (DRPAR) on multiyear average during burning seasons. On a monthly basis, this increase in GPP can be as large as 9.9 % (occurring in August 2010). Consequently, the net primary production (NPP) in the Amazon is increased by 1.5 %, or ∼92 Tg C yr−1 – equivalent to ∼37 % of the average carbon lost due to Amazon fires over the 7 years considered. Clouds, however, strongly regulate the effectiveness of the aerosol diffuse radiation fertilization effect. The efficiency of this fertilization effect is the highest in cloud-free conditions and linearly decreases with increasing cloud amount until the cloud fraction reaches ∼0.8, at which point the aerosol-influenced light changes from being a stimulator to an inhibitor of plant growth. Nevertheless, interannual changes in the overall strength of the aerosol diffuse radiation fertilization effect are primarily controlled by the large interannual changes in biomass burning aerosols rather than by changes in cloudiness during the studied period.

Divergent historical GPP trends among state-of-the-art multi-model simulations and satellite-based products

Understanding historical changes in gross primary productivity (GPP) is essential for better predicting the future global carbon cycle. However, the historical trends of terrestrial GPP, owing to the CO2 fertilization effect, climate, and land-use change, remain largely uncertain. Using long-term satellite-based near-infrared radiance of vegetation (NIRv), a proxy for GPP, and multiple GPP datasets derived from satellite-based products, Dynamic Global Vegetation Model (DGVM) simulations, and machine learning techniques, here we comprehensively investigated their trends and analyzed the causes for any discrepancies during 1982–2015. Although spatial patterns of climatological annual GPP from all products and NIRv are highly correlated (r > 0.84), the spatial correlation coefficients of trends between DGVM GPP and NIRv significantly decreased (with the ensemble mean of r = 0.49) and even the spatial correlation coefficients of trends between other GPP products and NIRv became negative. By separating the global land into the tropics plus extra-tropical southern hemisphere (Trop+SH) and extra-tropical northern hemisphere (NH), we found that, during 1982–2015, simulated GPP from most of the models showed a stronger increasing trend over Trop+SH than NH. In contrast, the satellite-based GPP products indicated a substantial increase over NH. Mechanistically, model sensitivity experiments indicated that the increase of annual GPP was dominated by the CO2 fertilization effect (Global: 83.9 %), albeit a large uncertainty in magnitude among individual simulations. However, the spatial distribution of inter-model spreads of GPP trends resulted mainly from climate and land-use change rather than CO2 fertilization effect. Trends after 2000 were different from the full time-series, showing that satellite-based GPP products suggested weakened rising trends over NH and even significantly decreasing trends over Trop+SH, while the trends from DGVMs kept increasing. The inconsistencies are very likely caused by the contrasting performances between satellite-derived and DGVM simulated vegetation structure parameter (leaf area index, LAI). Therefore, the uncertainty in satellite-based GPP products induced by highly uncertain LAI data in the tropics undermines their roles in assessing the performance of DGVM simulations and understanding the changes of global carbon sinks.