Assessing availability and greenhouse gas emissions of lignocellulosic biomass feedstock supply – case study for a catchment in England

© 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.Feedstocks from lignocellulosic biomass (LCB) include crop residues and dedicated per¬ennial biomass crops. The latter are often considered superior in terms of climate change mitigation potential. Uncertainty remains over their availability as feedstocks for biomass provision and the net greenhouse gas emissions (GHG) during crop production. Our objective was to assess the optimal land allocation to wheat and Miscanthus in a specific case study located in England, to increase bio¬mass availability, improve the carbon balance (and reduce the consequent GHG emissions), and mini¬mally constrain grain production losses from wheat. Using soil and climate variables for a catchment in east England, biomass yields and direct nitrogen emissions were simulated with validated process-based models. A ‘Field to up-stream factory gate’ life-cycle assessment was conducted to estimate indirect management-related GHG emissions. Results show that feedstock supply from wheat straw can be supplemented beneficially with LCB from Miscanthus grown on selected low-quality soils. In our study, 8% of the less productive arable land area was dedicated to Miscanthus, increasing total LCB provision by about 150%, with a 52% reduction in GHG emission per ton LCB delivered and only a minor effect on wheat grain production (−3%). In conclusion, even without considering the likely carbon sequestration in impoverished soils, agriculture should embrace the opportunities to provide the bioeconomy with LCB from dedicated, perennial crops.Peer reviewe

Impact of extreme weather events frequency and intensity in shaping phytoplankton communities

Lake habitats and communities can often be correlated with general morphometric and geographic characteristics such as depth, latitude, altitude, or watershed area. Further, communities are typically correlated with average environmental conditions such as seasonal temperature and nutrient levels. The frequency and intensity of extreme weather events (rain and wind) are typically not encompassed by average environmental descriptors, yet, can modify the physical habitats of lakes, significantly influencing phytoplankton growth and survival. We tested the hypothesis that lakes with a higher frequency and intensity of extreme weather events have a functionally different phytoplankton assemblage from lakes with a lower frequency of extreme weather events. We compiled long-term (mean = 20±13 years, range 0.6-44 years) phytoplankton datasets for 22 lakes across a wide gradient of altitude, latitude, depth, and trophic state. We classified the phytoplankton genera into morpho-functional groups and C-S-R strategists, and compared among lake phytoplankton assemblages’ characteristics across the gradient of wind and rain conditions experienced by the lakes. We discuss how the frequency of extreme weather events can affect phytoplankton functional groups, the dominance of differing life history strategies and ultimately community structure. The frequency and intensity of extreme events is expected to increase with climate change, with the potential to drive shifts in phytoplankton composition

A global dataset on weather, lake physics, and phytoplankton dynamics

We compiled data from over 30 lakes across the globe to address how storms influence thermal structure and phytoplankton community dynamics mediated by lake conditions and functional traits. In addition to (generally) fortnightly phytoplankton samples (mean ± SD temporal coverage across all lakes = 20 ± 13 years), the dataset includes limnological variables from standard long-term monitoring programs (24 ± 15 years coverage), daily weather observations (16 ± 10 years coverage) and, when available, high-frequency lake water temperature and water chemistry profiles (12 ± 7 years coverage). All data have been standardized to similar formats and include complete metadata. We used the dataset to develop an R-package (“algaeClassify”), which assigns phytoplankton genus/species information to multiple functional trait groups, and here we provide a summary of ongoing research using the dataset to investigate: 1) the influence of storm events on seasonal phytoplankton succession, 2) the impact of storms on lake thermal structure, and 3) whether lake phytoplankton communities are shaped by long-term patterns in disturbance frequency and intensity. We give an overview on how to access these data, and we further highlight the opportunities the dataset provides for asking both basic and applied questions in limnology, ecology, climate change, and lake management

Quantifying pelagic phosphorus regeneration using three methods in lakes of varying productivity

Phosphorus (P) is often a limiting nutrient in freshwater ecosystems, and understanding P dynamics in lakes is critical for eutrophication management. Pelagic P regeneration can support a large fraction of primary production in stratified freshwaters. Various techniques have been used to quantify pelagic P regeneration including (1) P mass balance supply–demand, (2) regression using total P as a predictor, and, more recently, (3) whole-lake metabolism calculated from high-frequency dissolved oxygen (DO) data. To our knowledge no study comparing these methods in multiple lakes has been performed. To compare these 3 approaches, we investigated 3 Global Lake Ecological Observatory Network (GLEON) lakes that differ in productivity: Acton, a Midwestern USA hypereutrophic reservoir; and 2 Northeastern USA glacial lakes, oligotrophic Giles and mesotrophic/dystrophic Lacawac. In Acton, we used all 3 methods, but for Giles and Lacawac we used only the total P regression and metabolism techniques. Our results show the best agreement among methods in the mesotrophic lake, whereas the metabolism approach underestimated regeneration in the oligotrophic lake and overestimated regeneration in the hypereutrophic reservoir compared with other methods. P regeneration rates for the hypereutrophic reservoir were the most sensitive to the metabolism-based input parameters. Our study illustrates a novel use of high-frequency DO data, which are commonly collected on many GLEON buoys, to understand lake nutrient dynamics

Training macrosystems scientists requires both interpersonal and technical skills

Macrosystems science strives to integrate patterns and processes that span regional to continental scales. The scope of such research often necessitates the involvement of large interdisciplinary and/or multi-institutional teams composed of scientists across a range of career stages, a diversity that requires researchers to hone both technical and interpersonal skills. We surveyed participants in macrosystems projects funded by the US National Science Foundation to assess the perceived importance of different skills needed in their research, as well as the types of training they received. Survey results revealed a mismatch between the skills participants perceive as important and the training they received, particularly for interpersonal and management skills. We highlight lessons learned from macrosystems training case studies, explore avenues for further improvement of undergraduate and graduate education, and discuss other training opportunities for macrosystems scientists. Given the trend toward interdisciplinary research beyond the macrosystems community, these insights are broadly applicable for scientists involved in diverse, collaborative projects.https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/fee.228

Greenhouse gas emission associated with sugar production in southern Brazil

<p>Abstract</p> <p>Background</p> <p>Since sugarcane areas have increased rapidly in Brazil, the contribution of the sugarcane production, and, especially, of the sugarcane harvest system to the greenhouse gas emissions of the country is an issue of national concern. Here we analyze some data characterizing various activities of two sugarcane mills during the harvest period of 2006-2007 and quantify the carbon footprint of sugar production.</p> <p>Results</p> <p>According to our calculations, 241 kg of carbon dioxide equivalent were released to the atmosphere per a ton of sugar produced (2406 kg of carbon dioxide equivalent per a hectare of the cropped area, and 26.5 kg of carbon dioxide equivalent per a ton of sugarcane processed). The major part of the total emission (44%) resulted from residues burning; about 20% resulted from the use of synthetic fertilizers, and about 18% from fossil fuel combustion.</p> <p>Conclusions</p> <p>The results of this study suggest that the most important reduction in greenhouse gas emissions from sugarcane areas could be achieved by switching to a green harvest system, that is, to harvesting without burning.</p