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AbstractMany studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability.

AbstractIn a physiologically structured population model (PSPM) individuals are characterised by continuous variables, like age and size, collectively called their i-state. The world in which these individuals live is characterised by another set of variables, collectively called the environmental condition. The model consists of submodels for (i) the dynamics of the i-state, e.g. growth and maturation, (ii) survival, (iii) reproduction, with the relevant rates described as a function of (i-state, environmental condition), (iv) functions of (i-state, environmental condition), like biomass or feeding rate, that integrated over the i-state distribution together produce the output of the population model. When the environmental condition is treated as a given function of time (input), the population model becomes linear in the state. Density dependence and interaction with other populations is captured by feedback via a shared environment, i.e., by letting the environmental condition be influenced by the populations’ outputs. This yields a systematic methodology for formulating community models by coupling nonlinear input–output relations defined by state-linear population models. For some combinations of submodels an (infinite dimensional) PSPM can without loss of relevant information be replaced by a finite dimensional ODE. We then call the model ODE-reducible. The present paper provides (a) a test for checking whether a PSPM is ODE reducible, and (b) a catalogue of all possible ODE-reducible models given certain restrictions, to wit: (i) the i-state dynamics is deterministic, (ii) the i-state space is one-dimensional, (iii) the birth rate can be written as a finite sum of environment-dependent distributions over the birth states weighted by environment independent ‘population outputs’. So under these restrictions our conditions for ODE-reducibility are not only sufficient but in fact necessary. Restriction (iii) has the desirable effect that it guarantees that the population trajectories are after a while fully determined by the solution of the ODE so that the latter gives a complete picture of the dynamics of the population and not just of its outputs.

Harmful algal blooms threaten the water quality of many eutrophic and hypertrophic lakes and cause severe ecological and economic damage worldwide. Dense blooms often deplete the dissolved CO2 concentration and raise pH. Yet, quantitative prediction of the feedbacks between phytoplankton growth, CO2 drawdown and the inorganic carbon chemistry of aquatic ecosystems has received surprisingly little attention. Here, we develop a mathematical model to predict dynamic changes in dissolved inorganic carbon (DIC), pH and alkalinity during phytoplankton bloom development. We tested the model in chemostat experiments with the freshwater cyanobacterium Microcystis aeruginosa at different CO2 levels. The experiments showed that dense blooms sequestered large amounts of atmospheric CO2, not only by their own biomass production but also by inducing a high pH and alkalinity that enhanced the capacity for DIC storage in the system. We used the model to explore how phytoplankton blooms of eutrophic waters will respond to rising CO2 levels. The model predicts that (1) dense phytoplankton blooms in low- and moderately alkaline waters can deplete the dissolved CO2 concentration to limiting levels and raise the pH over a relatively wide range of atmospheric CO2 conditions, (2) rising atmospheric CO2 levels will enhance phytoplankton blooms in low- and moderately alkaline waters with high nutrient loads, and (3) above some threshold, rising atmospheric CO2 will alleviate phytoplankton blooms from carbon limitation, resulting in less intense CO2 depletion and a lesser increase in pH. Sensitivity analysis indicated that the model predictions were qualitatively robust. Quantitatively, the predictions were sensitive to variation in lake depth, DIC input and CO2 gas transfer across the air-water interface, but relatively robust to variation in the carbon uptake mechanisms of phytoplankton. In total, these findings warn that rising CO2 levels may result in a marked intensification of phytoplankton blooms in eutrophic and hypertrophic waters.

The aim of this work was to study the responses of aerobic granulation process to antibiotics and investigate the antibiotics and antibiotic-resistant bacteria (ARB) removal and transport. Results showed that aerobic granular sludge (AGS) was dominant in the bioreactor at day 45, and the relatively high protein content from tightly bound extracellular polymeric substances (TB-EPS) facilitated aerobic granulation and maintained biomass stabilization. The protein contents in EPS and TB-EPS were positively correlated with relative hydrophobicity, thereby improving the adsorption capacity among hydrophobic particles. The chemical oxygen demand (COD), NH3-N, and total N removal efficiencies were 98.0%, 97.0%, and 92.4%, respectively. Five antibiotics, including kanamycin, tetracycline, ciprofloxacin, ampicillin, and erythromycin, were examined in piggery wastewater, with concentrations up to the concentration range of 29.4-44.1 µg/l, and the total antibiotics removal rate reached up to 88.4% ± 4.5%. A total of 5.2% of the total antibiotics were discharged from bioreactor, and 62.5% of the total antibiotics were degraded, and 32.3% of total antibiotics were adsorbed by aerobic granules. The presence of antibiotics rarely exhibited an influence on AGS formation, and the relatively high microbial activity of aerobic granules was beneficial to antibiotics removal. The ARB removal rate increased up to 89.4% ± 3.3%, but a large amount of ARB was enriched in aerobic granules.

The production of hydrogen from biomass by fermentation is one of the routes that can contribute to a future sustainable hydrogen economy. Lignocellulosic biomass is an attractive feedstock because of its abundance, low production costs and high polysaccharide content.Batch cultures of Caldicellulosiruptor saccharolyticus and Thermotoga neapolitana produced hydrogen, carbon dioxide and acetic acid as the main products from soluble saccharides in Miscanthus hydrolysate. The presence of fermentation inhibitors, such as furfural and 5-hydroxylmethyl furfural, in this lignocellulosic hydrolysate was avoided by the mild alkaline-pretreatment conditions at a low temperature of 75 degrees C. Both microorganisms simultaneously and completely utilized all pentoses, hexoses and oligomeric saccharides up to a total concentration of 17 g l-1 in pH-controlled batch cultures. T. neapolitana showed a preference for glucose over xylose, which are the main sugars in the hydrolysate. Hydrogen yields of 2.9 to 3.4 mol H2 per mol of hexose, corresponding to 74 to 85% of the theoretical yield, were obtained in these batch fermentations. The yields were higher with cultures of C. saccharolyticus compared to T. neapolitana. In contrast, the rate of substrate consumption and hydrogen production was higher with T. neapolitana. At substrate concentrations exceeding 30 g l-1, sugar consumption was incomplete, and lower hydrogen yields of 2.0 to 2.4 mol per mol of consumed hexose were obtained.Efficient hydrogen production in combination with simultaneous and complete utilization of all saccharides has been obtained during the growth of thermophilic bacteria on hydrolysate of the lignocellulosic feedstock Miscanthus. The use of thermophilic bacteria will therefore significantly contribute to the energy efficiency of a bioprocess for hydrogen production from biomass.

Recent extreme weather events have resulted in an ongoing discussion on the issues of land use and compensation payments within Austrian agriculture. Building on a functional evaluation system for agricultural lands as developed within the Interreg IIIB project “ILUP”, the national project “Agriculture and Flooding” has as its goal to classify the flood-protection contribution and flood sensitivity of agricultural lands. This, in turn, enables the recommendation of targeted measures for potentially improving flood situations, as well as an estimate of their implementation costs. In addition to the digital soil map, other fundamental sources used for the project are the digital flood risk map, IACS land-use data and works by the Institute for Land and Water Management Research. Reference values and marginal returns sourced from the Federal Institute of Agricultural Economics also flow into the cost estimates for the recommended combination. The results will contribute to an understanding of the multifunctionality of agricultural lands and to the setting of priorities on a regional scale regarding packaged flood-prevention and damage-minimization. However, the results at hand can only serve as one step toward regional flood protection projects, whose development will require the cooperation of all interest groups.