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Embolism resistance drives the distribution of Amazonian rainforest tree species along hydro-topographic gradients
Oliveira, Rafael S. ; Costa, Flavia R.C. ; Baalen, Emma van; Jonge, Arjen de; Bittencourt, Paulo R. ; Almanza, Yanina ; V. Barros, Fernanda de; Cordoba, Edher C. ; Fagundes, Marina V. ; Garcia, Sabrina ; Guimaraes, Zilza T.T.M. ; Hertel, Mariana ; Schietti, Juliana ; Rodrigues-Souza, Jefferson ; Poorter, Lourens - \ 2018
New Phytologist (2018). - ISSN 0028-646X - 9 p.
drought vulnerability - forest resilience - functional ecology - hydrological niches - P - phosphorus - tropical forests - water table

Species distribution is strongly driven by local and global gradients in water availability but the underlying mechanisms are not clear. Vulnerability to xylem embolism (P50) is a key trait that indicates how species cope with drought and might explain plant distribution patterns across environmental gradients. Here we address its role on species sorting along a hydro-topographical gradient in a central Amazonian rainforest and examine its variance at the community scale. We measured P50 for 28 tree species, soil properties and estimated the hydrological niche of each species using an indicator of distance to the water table (HAND). We found a large hydraulic diversity, covering as much as 44% of the global angiosperm variation in P50. We show that P50: contributes to species segregation across a hydro-topographic gradient in the Amazon, and thus to species coexistence; is the result of repeated evolutionary adaptation within closely related taxa; is associated with species tolerance to P-poor soils, suggesting the evolution of a stress-tolerance syndrome to nutrients and drought; and is higher for trees in the valleys than uplands. The large observed hydraulic diversity and its association with topography has important implications for modelling and predicting forest and species resilience to climate change.

Response of natural cyanobacteria and algae assemblages to a nutrient pulse and elevated temperature
Lürling, Miquel ; Mello, Mariana Mendese ; Oosterhout, Frank van; Senerpont Domis, Lisette de; Marinho, Marcelo M. - \ 2018
Frontiers in Microbiology 9 (2018)AUG. - ISSN 1664-302X
Blooms - Climate change - Competition - Global warming - Optimum growth

Eutrophication (nutrient over-enrichment) is the primary worldwide water quality issue often leading to nuisance cyanobacterial blooms. Climate change is predicted to cause further rise of cyanobacteria blooms as cyanobacteria can have a competitive advantage at elevated temperatures. We tested the hypothesis that simultaneous rise in nutrients and temperature will promote cyanobacteria more than a single increase in one of the two drivers. To this end, controlled experiments were run with seston from 39 different urban water bodies varying in trophic state from mesotrophic to hypertrophic. These experiments were carried out at two different temperatures, 20°C (ambient) and 25°C (warming scenario) with or without the addition of a surplus of nutrients (eutrophication scenario). To facilitate comparisons, we quantified the effect size of the different treatments, using cyanobacterial and algal chlorophyll a concentrations as a response variable. Cyanobacterial and algal chlorophyll a concentrations were determined with a PHYTO-PAM phytoplankton analyzer. Warming caused an 18% increase in cyanobacterial chlorophyll-α, while algal chlorophyll-α concentrations were on average 8% higher at 25°C than at 20°C. A nutrient pulse had a much stronger effect on chlorophyll-α concentrations than warming. Cyanobacterial chlorophyll-α concentrations in nutrient enriched incubations at 20 or 25°C were similar and 9 times higher than in the incubations without nutrient pulse. Likewise, algal chlorophyll-α concentrations were 6 times higher. The results of this study confirm that warming alone yields marginally higher cyanobacteria chlorophyll-α concentrations, yet that a pulse of additional nutrients is boosting blooms. The responses of seston originating from mesotrophic waters seemed less strong than those from eutrophic waters, which indicates that nutrient control strategies -catchment as well as in-system measures- could increase the resilience of surface waters to the negative effects of climate change.

Simultaneous production of antioxidants and starch from the microalga Chlorella sorokiniana
Petruk, Ganna ; Gifuni, Imma ; Illiano, Anna ; Roxo, Mariana ; Pinto, Gabriella ; Amoresano, Angela ; Marzocchella, Antonio ; Piccoli, Renata ; Wink, Michael ; Olivieri, Giuseppe ; Monti, Daria M. - \ 2018
Algal Research 34 (2018). - ISSN 2211-9264 - p. 164 - 174.
Antioxidants - C. elegans - Chlorella sorokiniana - Eukaryotic cells - Microalgae

In recent years, microalgae have gained considerable importance as potential source of biofuels and bioplastics. However, these markets are still developing, as the high costs of cultivation ask for exploiting microalgae into new areas and with a biorefinery approach towards a multicomponent cascade extraction process. Here, a sequential processing strategy was used to extract starch with high yield from Chlorella sorokiniana under biocompatible conditions. The extract residue was then tested as a potential source of antioxidants. We found a strong protective activity of the extract residue towards oxidative stress in vitro on human colon cancer cells and in vivo on Caenorhabditis elegans nematodes, by inhibiting ROS production and activating DAF-16/FOXO transcription factor pathway. A pool of molecules from three different classes (fatty acids, photosynthetic pigments and carotenoids) was identified as responsible for the antioxidant activity. To our knowledge, this is the first report on the obtainment, from a “waste” fraction, of high value products endowed with antioxidant activity tested in cell-based models and in vivo.

Sustainable intensification of dairy production can reduce forest disturbance in Kenyan montane forests
Brandt, Patric ; Hamunyela, Eliakim ; Herold, Martin ; Bruin, Sytze De; Verbesselt, Jan ; Rufino, Mariana C. - \ 2018
Agriculture, Ecosystems and Environment 265 (2018). - ISSN 0167-8809 - p. 307 - 319.
Increasing demand for food and the shortage of arable land call for sustainable intensification of farming, especially in Sub-Saharan Africa where food insecurity is still a major concern. Kenya needs to intensify its dairy production to meet the increasing demand for milk. At the same time, the country has set national climate mitigation targets and has to implement land use practices that reduce greenhouse gas (GHG) emissions from both agriculture and forests. This study analysed for the first time the drivers of forest disturbance and their relationship with dairy intensification across the largest montane forest of Kenya. To achieve this, a forest disturbance detection approach was applied by using Landsat time series and empirical data from forest disturbance surveys. Farm indicators and farm types derived from a household survey were used to test the effects of dairy intensification on forest disturbance for different farm neighbourhood sizes (r = 2–5 km). About 18% of the forest area was disturbed over the period 2010–2016. Livestock grazing and firewood extraction were the dominant drivers of forest disturbance at 75% of the forest disturbance spots sampled. Higher on-farm cattle stocking rates and firewood collection were associated with 1–10% increased risk of forest disturbance across farm neighbourhood sizes. In contrast, higher milk yields, increased supplementation with concentrated feeds and more farm area allocated to fodder production were associated with 1–7 % reduced risk of forest disturbance across farm neighbourhood sizes. More intensified farms had a significantly lower impact on forest disturbance than small and resource-poor farms, and large and inefficient farms. Our results show that intensification of smallholder dairy farming leads to both farm efficiency gains and reduced forest disturbance. These results can inform agriculture and forest mitigation policies which target options to reduce GHG emission intensities and the risk of carbon leakage.
Energy-Efficient Ammonia Recovery in an Up-Scaled Hydrogen Gas Recycling Electrochemical System
Kuntke, Philipp ; Rodrigues, Mariana ; Sleutels, Tom ; Saakes, Michel ; Hamelers, Hubertus V.M. ; Buisman, Cees J.N. - \ 2018
ACS sustainable chemistry & engineering 6 (2018)6. - ISSN 2168-0485 - p. 7638 - 7644.
Ammonia recovery - Electrochemical system - Hydrogen recycling - Up-scaling

Nutrient and energy recovery is becoming more important for a sustainable future. Recently, we developed a hydrogen gas recycling electrochemical system (HRES) which combines a cation exchange membrane (CEM) and a gas-permeable hydrophobic membrane for ammonia recovery. This allowed for energy-efficient ammonia recovery, since hydrogen gas produced at the cathode was oxidized at the anode. Here, we successfully up-scaled and optimized this HRES for ammonia recovery. The electrode surface area was increased to 0.04 m2 to treat up to 11.5 L/day (∼46 gN/day) of synthetic urine. The system was operated stably for 108 days at current densities of 20, 50, and 100 A/m2. Compared to our previous prototype, this new cell design reduced the anode overpotential and ionic losses, while the use of an additional membrane reduced the ion transport losses. Overall, this reduced the required energy input from 56.3 kJ/gN (15.6 kW h/kgN) at 50 A/m2 (prototype) to 23.4 kJ/gN (6.5 kW h/kgN) at 100 A/m2 (this work). At 100 A/m2, an average recovery of 58% and a TAN (total ammonia nitrogen) removal rate of 598 gN/(m2 day) were obtained across the CEM. The TAN recovery was limited by TAN transport from the feed to concentrate compartment.

Climate-smart land use requires local solutions, transdisciplinary research, policy coherence and transparency
Carter, Sarah ; Arts, Bas ; E. Giller, Ken ; Soto Golcher, Cinthia ; Kok, Kasper ; Koning, Jessica De; Noordwijk, Meine Van; Reidsma, Pytrik ; Rufino, Mariana C. ; Salvini, Giulia ; Verchot, Louis ; Wollenberg, Eva ; Herold, Martin - \ 2018
Carbon Management (2018). - ISSN 1758-3004 - p. 291 - 301.
Successfully meeting the mitigation and adaptation targets of the Paris Climate Agreement (PA) will depend on strengthening the ties between forests and agriculture. Climate-smart land use can be achieved by integrating climate-smart agriculture (CSA) and REDD+. The focus on agriculture for food security within a changing climate, and on forests for climate change mitigation and adaptation, can be achieved simultaneously with a transformational change in the land-use sector. Striving for both independently will lead to competition for land, inefficiencies in monitoring and conflicting agendas. Practical solutions exist for specific contexts that can lead to increased agricultural output and forest protection. Landscape-level emissions accounting can be used to identify these practices. Transdisciplinary research agendas can identify and prioritize solutions and targets for integrated mitigation and adaptation interventions. Policy coherence must be achieved at a number of levels, from international to local, to avoid conflicting incentives. Transparency must lastly be integrated, through collaborative design of projects, and open data and methods. Climate-smart land use requires all these elements, and will increase the likelihood of successful REDD+ and CSA interventions. This will support the PA as well as other initiatives as part of the Sustainable Development Goals.
The contribution of sectoral climate change mitigation options to national targets: a quantitative assessment of dairy production in Kenya
Brandt, Patric ; Herold, Martin ; Rufino, Mariana C. - \ 2018
Environmental Research Letters 13 (2018)3. - ISSN 1748-9326 - 14 p.
Reducing greenhouse gas (GHG) emissions from agriculture has become a critical target in national climate change policies. More than 80% of the countries in Sub-Saharan Africa (SSA) refer to the reduction of agricultural emissions, including livestock, in their nationally determined contribution (NDC) to mitigate climate change. The livestock sector in Kenya contributes largely to the gross domestic product and to GHG emissions from the land use sector. The government has recently pledged in its NDC to curb total GHG emissions by 30% by 2030. Quantifying and linking the mitigation potential of farm practices to national targets is required to support realistically the implementation of NDCs. Improvements in feed and manure management represent promising mitigation options for dairy production. This study aimed (i) to assess mitigation and food production benefits of feed and manure management scenarios, including land use changes covering Kenya's entire dairy production region and (ii) to analyse the contribution of these practices to national targets on milk production and mitigation, and their biophysical feasibility given the availability of arable land. The results indicate that improving forage quality by increasing the use of Napier grass and supplementing dairy concentrates supports Kenya's NDC target, reduces emission intensities by 26%–31%, partially achieves the national milk productivity target for 2030 by 38%–41%, and shows high feasibility given the availability of arable land. Covering manure heaps may reduce emissions from manure management by 68%. In contrast, including maize silage in cattle diets would not reduce emission intensities due to the risk of ten-fold higher emissions from the conversion of land required to grow additional maize. The shortage of arable land may render the implementation of these improved feed practices largely infeasible. This assessment provides the first quantitative estimates of the potential of feed intensification and manure management to mitigate GHG emissions and to increase milk yields at sectoral-level and at a high spatial resolution for an SSA country. The scientific evidence is tailored to support actual policy and decision-making processes at the national level, such as 'Nationally Appropriate Mitigation Actions'. Linking feed intensification and manure management strategies with spatially-explicit estimates of mitigation and food production to national targets may help the sector to access climate financing while contributing to food security.
Archetypes of Climate Vulnerability : a Mixed-method Approach Applied in the Peruvian Andes
Vidal Merino, Mariana ; Sietz, Diana ; Jost, Francois ; Berger, Uta - \ 2018
Climate and Development (2018). - ISSN 1756-5529 - 17 p.
adaptive capacity - agro-ecological zones - Andean agriculture - pattern analysis - sustainable livelihoods
Farm household systems (FHSs) in the Andes handle climate-related hazards such as frost and droughts with risk-coping and risk-management strategies based on the adaptive capital available to them. Nevertheless, a higher frequency of climatic stressors observed during the last few decades is challenging their capacity to adapt at a pace fast enough to keep up with the changes in external conditions. This increases the demand on the scientific community from policy and decision makers to investigate climate impacts and propose viable adaptation pathways at the local and regional scales. Better understanding heterogeneity in climate vulnerability is an important step towards addressing this demand. We present here a mixed-method approach to assessing archetypes or patterns of climate vulnerability that combines qualitative tools from participatory rural assessment approaches and quantitative techniques including cluster analysis. We illustrate this by looking at a case study of the Central Andes of Peru. The operationalization of the methods revealed differential factors for climate vulnerability, allowing us to categorize FHS archetypes according to the differences in those underlying factors. The archetypes differed mainly according to farm area, agro-ecological zones, irrigation, off-farm employment and climate-related damages. The results suggest that the approach is useful for explaining vulnerability as a function of recurrent internal and external determinants of vulnerability and developing related adaptive strategies.
Species Distribution Modelling: Contrasting presence-only models with plot abundance data
Gomes, Vitor H.F. ; Ijff, Stéphanie D. ; Raes, Niels ; Amaral, Iêda Leão ; Salomão, Rafael P. ; Coelho, Luiz De Souza ; Matos, Francisca Dionízia De Almeida ; Castilho, Carolina V. ; Filho, Diogenes De Andrade Lima ; López, Dairon Cárdenas ; Guevara, Juan Ernesto ; Magnusson, William E. ; Phillips, Oliver L. ; Wittmann, Florian ; Carim, Marcelo De Jesus Veiga ; Martins, Maria Pires ; Irume, Mariana Victória ; Sabatier, Daniel ; Molino, Jean François ; Bánki, Olaf S. ; Guimarães, José Renan Da Silva ; Pitman, Nigel C.A. ; Piedade, Maria Teresa Fernandez ; Mendoza, Abel Monteagudo ; Luize, Bruno Garcia ; Venticinque, Eduardo Martins ; de Leão Novo, E.M.M. ; Vargas, Percy Núñez ; Silva, Thiago Sanna Freire ; Manzatto, Angelo Gilberto ; Terborgh, John ; Reis, Neidiane Farias Costa ; Montero, Juan Carlos ; Montero, Juan Carlos ; Casula, Katia Regina ; Marimon, Beatriz S. ; Marimon, Ben Hur ; Honorio Coronado, Euridice N. ; Feldpausch, Ted R. ; Duque, Alvaro ; Zartman, Charles Eugene ; Arboleda, Nicolás Castaño ; Killeen, Timothy J. ; Mostacedo, Bonifacio ; Vasquez, Rodolfo ; Schöngart, Jochen ; Assis, Rafael L. ; Medeiros, Marcelo Brilhante ; Simon, Marcelo Fragomeni ; Andrade, Ana ; Laurance, William F. ; Camargo, José Luís ; Demarchi, Layon O. ; Laurance, Susan G.W. ; Farias, Emanuelle De Sousa ; Nascimento, Henrique Eduardo Mendonça ; Revilla, Juan David Cardenas ; Quaresma, Adriano ; Costa, Flavia R.C. ; Vieira, Ima Célia Guimarães ; Cintra, Bruno Barçante Ladvocat ; Cintra, Bruno Barçante Ladvocat ; Castellanos, Hernán ; Brienen, Roel ; Stevenson, Pablo R. ; Feitosa, Yuri ; Duivenvoorden, Joost F. ; Aymard, Gerardo A.C. ; Mogollón, Hugo F. ; Targhetta, Natalia ; Comiskey, James A. ; Vicentini, Alberto ; Lopes, Aline ; Damasco, Gabriel ; Dávila, Nállarett ; García-Villacorta, Roosevelt ; Levis, Carolina ; Levis, Carolina ; Schietti, Juliana ; Souza, Priscila ; Emilio, Thaise ; Alonso, Alfonso ; Neill, David ; Dallmeier, Francisco ; Ferreira, Leandro Valle ; Araujo-Murakami, Alejandro ; Praia, Daniel ; Amaral, Dário Dantas Do; Carvalho, Fernanda Antunes ; Souza, Fernanda Coelho De - \ 2018
Scientific Reports 8 (2018)1. - ISSN 2045-2322
Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.
Agriculture-driven deforestation in the tropics from 1990 to-2015: emissions, trends and uncertainties
Carter, Sarah ; Herold, Martin ; Avitabile, Valerio ; Bruin, Sytze de; Sy, Veronique de; Kooistra, Lammert ; Rufino, Mariana C. - \ 2018
Environmental Research Letters 13 (2018)1. - ISSN 1748-9326
Limited data exists on emissions from agriculture-driven deforestation, and available data are typically uncertain. In this paper, we provide comparable estimates of emissions from both all deforestation and agriculture-driven deforestation, with uncertainties for 91 countries across the tropics between 1990 and 2015. Uncertainties associated with input datasets (activity data and emissions factors) were used to combine the datasets, where most certain datasets contribute the most. This method utilizes all the input data, while minimizing the uncertainty of the emissions estimate. The uncertainty of input datasets was influenced by the quality of the data, the sample size (for sample-based datasets), and the extent to which the timeframe of the data matches the period of interest. Area of deforestation, and the agriculture-driver factor (extent to which agriculture drives deforestation), were the most uncertain components of the emissions estimates, thus improvement in the uncertainties related to these estimates will provide the greatest reductions in uncertainties of emissions estimates. Over the period of the study, Latin America had the highest proportion of deforestation driven by agriculture (78%), and Africa had the lowest (62%). Latin America had the highest emissions from agriculture-driven deforestation, and these peaked at 974 ± 148 Mt CO2 yr−1 in 2000–2005. Africa saw a continuous increase in emissions between 1990 and 2015 (from 154 ± 21–412 ± 75 Mt CO2 yr−1), so mitigation initiatives could be prioritized there. Uncertainties for emissions from agriculture-driven deforestation are ± 62.4% (average over 1990–2015), and uncertainties were highest in Asia and lowest in Latin America. Uncertainty information is crucial for transparency when reporting, and gives credibility to related mitigation initiatives. We demonstrate that uncertainty data can also be useful when combining multiple open datasets, so we recommend new data providers to include this information.
A study of the origin of chloramphenicol isomers in honey
Yanovych, Dmytro ; Berendsen, Bjorn ; Zasadna, Zvenyslava ; Rydchuk, Mariana ; Czymai, Tobias - \ 2018
Drug Testing and Analysis 10 (2018)3. - ISSN 1942-7603 - p. 416 - 422.
Chiral LC-MS/MS - Chloramphenicol isomers - Dextramycin - Drug residues - Honey
Due to the unexpected detection of chloramphenicol isomer residues in honey, we have studied the hypothesis of unauthorized or unintended use of unregistered veterinary drug preparations. First, we have investigated honey samples in which a discrepancy was observed between the results of the immunological screening methods and the confirmatory liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. In all samples, previously identified to be contaminated with the banned antibiotic chloramphenicol according to LC-MS/MS only, the presence of dextramycin (SS-para isomer of chloramphenicol) was detected by chiral LC-MS/MS. The source of dextramycin in honey was investigated by studying the preparations utilized in apiaries from which the above non-compliant honey samples have been received. In all these preparations (beehive strips applied against the mite Varroa destructor) chloramphenicol was detected in the concentrations ranging from 33 to 34,400 μg kg-1. Chiral LC-MS/MS demonstrated the presence of chloramphenicol and dextramycin in different ratios, and it was concluded that these preparations can be the source of chloramphenicol and dextramycin residues in honey. These preparations were of foreign production and are not officially registered in accordance with current legislation.
How to target climate-smart agriculture? Concept and application of the consensus-driven decision support framework “targetCSA”
Brandt, Patric ; Kvakić, Marko ; Butterbach-Bahl, Klaus ; Rufino, Mariana C. - \ 2017
Agricultural Systems 151 (2017). - ISSN 0308-521X - p. 234 - 245.
Planning for agricultural adaptation and mitigation has to lean on informed decision-making processes. Stakeholder involvement, consensus building and the integration of comprehensive and reliable information represent crucial, yet challenging, pillars for successful outcomes. The spatially-explicit multi-criteria decision support framework “targetCSA” presented here aims to aid the targeting of climate-smart agriculture (CSA) at the national level. This framework integrates quantitative, spatially-explicit information such as vulnerability indicators (e.g. soil organic matter, literacy rate and market access) and proxies for CSA practices (e.g. soil fertility improvement, water harvesting and agroforestry) as well as qualitative opinions on these targeting criteria from a broad range of stakeholders. The analytic hierarchy process and a goal optimization approach are utilized to quantify collective, consensus-oriented stakeholder preferences on vulnerability indicators and CSA practices. Spatially-explicit vulnerability and CSA data are aggregated and coupled with stakeholder preferences deriving vulnerability and CSA suitability indices. Based on these indices, relevant regions with the potential to implement CSA practices are identified. “targetCSA” was exemplarily applied in Kenya exploring group-specific and overall consensus-based solutions of stakeholder opinions on vulnerability and CSA under different consensus scenarios. In this example, 32 experts from four stakeholder groups who participated in two surveys were included. The subsequent analyses not only revealed consistently regions with high CSA potential but also highlighted different high potential areas depending on the applied consensus scenario. Thus, this framework allows stakeholders to explore the consequences of scenarios that reflect opinions of the majority and minority or are based on a balance between them. “targetCSA” and the application example contribute valuable insights to the development of policy and planning tools to consensually target and implement CSA.
AntiSMASH 4.0 - improvements in chemistry prediction and gene cluster boundary identification
Blin, Kai ; Wolf, Thomas ; Chevrette, Marc G. ; Lu, Xiaowen ; Schwalen, Christopher J. ; Kautsar, Satria A. ; Suarez Duran, Hernando G. ; Los Santos, Emmanuel L.C. De; Kim, Hyun Uk ; Nave, Mariana ; Dickschat, Jeroen S. ; Mitchell, Douglas A. ; Shelest, Ekaterina ; Breitling, Rainer ; Takano, Eriko ; Lee, Sang Yup ; Weber, Tilmann ; Medema, Marnix H. - \ 2017
Nucleic Acids Research 45 (2017)W1. - ISSN 0305-1048 - p. W36 - W41.
Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the â € antibiotics and secondary metabolite analysis shell - antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.
Hydrogen Gas Recycling for Energy Efficient Ammonia Recovery in Electrochemical Systems
Kuntke, Philipp ; Rodríguez Arredondo, Mariana ; Widyakristi, Laksminarastri ; Heijne, Annemiek ter; Sleutels, Tom H.J.A. ; Hamelers, Hubertus V.M. ; Buisman, Cees J.N. - \ 2017
Environmental Science and Technology 51 (2017)5. - ISSN 0013-936X - p. 3110 - 3116.

Recycling of hydrogen gas (H2) produced at the cathode to the anode in an electrochemical system allows for energy efficient TAN (Total Ammonia Nitrogen) recovery. Using a H2 recycling electrochemical system (HRES) we achieved high TAN transport rates at low energy input. At a current density of 20 A m-2, TAN removal rate from the influent was 151 gN m-2 d-1 at an energy demand of 26.1 kJ gN -1. The maximum TAN transport rate of 335 gN m-2 d-1 was achieved at a current density of 50 A m-2 and an energy demand of 56.3 kJ gN -1. High TAN removal efficiency (73-82%) and recovery (60-73%) were reached in all experiments. Therefore, our HRES is a promising alternative for electrochemical and bioelectrochemical TAN recovery. Advantages are the lower energy input and lower risk of chloride oxidation compared to electrochemical technologies and high rates and independence of organic matter compared to bioelectrochemical systems. (Chemical Equation Presented).

Load ratio determines the ammonia recovery and energy input of an electrochemical system
Rodríguez Arredondo, Mariana ; Kuntke, Philipp ; Heijne, Annemiek Ter; Hamelers, Hubertus V.M. ; Buisman, Cees J.N. - \ 2017
Water Research 111 (2017). - ISSN 0043-1354 - p. 330 - 337.
Complete removal and recovery of total ammonia nitrogen (TAN) from wastewaters in (bio)electrochemical systems has proven to be a challenge. The system performance depends on several factors, such as current density, TAN loading rate and pH. The interdependence among these factors is not well understood yet: insight is needed to achieve maximum ammonium recovery at minimal energy input. The aim of this study was to investigate the influence of current density and TAN loading rate on the recovery efficiency and energy input of an electrochemical cell (EC). We therefore defined the load ratio, which is the ratio between the applied current and the TAN loading rate. The system consisted of an EC coupled to a membrane unit for the recovery of ammonia. Synthetic wastewater, with TAN concentration similar to urine, was used to develop a simple model to predict the system performance based on the load ratio, and urine was later used to evaluate TAN transport in a more complex wastewater. High fluxes (up to 433 gN m−2 d−1) and recovery efficiencies (up to 100%) were obtained. The simple model presented here is also suited to predict the performance of similar systems for TAN recovery, and can be used to optimize their operation.
Reducing emissions from agriculture to meet the 2 °C target
Wollenberg, Eva ; Richards, Meryl ; Smith, Pete ; Havlík, Petr ; Obersteiner, Michael ; Tubiello, Francesco N. ; Herold, Martin ; Gerber, Pierre ; Carter, Sarah ; Reisinger, Andrew ; Vuuren, Detlef P. van; Dickie, Amy ; Neufeldt, Henry ; Sander, Björn O. ; Wassmann, Reiner ; Sommer, Rolf ; Amonette, James E. ; Falcucci, Alessandra ; Herrero, Mario ; Opio, Carolyn ; Roman-cuesta, Rosa Maria ; Stehfest, Elke ; Westhoek, Henk ; Ortiz-Monasterio, Ivan ; Sapkota, Tek ; Rufino, Mariana C. ; Thornton, Philip K. ; Verchot, Louis V. ; West, Paul C. ; Soussana, Jean-François ; Baedeker, Tobias ; Sadler, Marc ; Vermeulen, Sonja ; Campbell, Bruce M. - \ 2016
Global Change Biology 22 (2016)12. - ISSN 1354-1013 - p. 3859 - 3864.
More than 100 countries pledged to reduce agricultural greenhouse gas (GHG) emissions in the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change. Yet technical information about how much mitigation is needed in the sector vs. how much is feasible remains poor. We identify a preliminary global target for reducing emissions from agriculture of ~1 GtCO2e yr−1 by 2030 to limit warming in 2100 to 2 °C above pre-industrial levels. Yet plausible agricultural development pathways with mitigation cobenefits deliver only 21–40% of needed mitigation. The target indicates that more transformative technical and policy options will be needed, such as methane inhibitors and finance for new practices. A more comprehensive target for the 2 °C limit should be developed to include soil carbon and agriculture-related mitigation options. Excluding agricultural emissions from mitigation targets and plans will increase the cost of mitigation in other sectors or reduce the feasibility of meeting the 2 °C limit.
Rhizobacteria and plant symbiosis in heavy metal uptake and its implications for soil bioremediation
Sobariu, Dana Luminita ; Fertu, Daniela Ionela Tudorache ; Diaconu, Mariana ; Pavel, Lucian Vasile ; Hlihor, Raluca Maria ; Drăgoi, Elena Niculina ; Curteanu, Silvia ; Lenz, Markus ; Corvini, Philippe François Xavier ; Gavrilescu, Maria - \ 2016
New Biotechnology 39 (2016). - ISSN 1871-6784 - p. 125 - 134.
Azotobacter sp. - Cadmium - Chromium - Lepidium sativum - Rhizobacteria - Tolerance

Certain species of plants can benefit from synergistic effects with plant growth-promoting rhizobacteria (PGPR) that improve plant growth and metal accumulation, mitigating toxic effects on plants and increasing their tolerance to heavy metals. The application of PGPR as biofertilizers and atmospheric nitrogen fixators contributes considerably to the intensification of the phytoremediation process. In this paper, we have built a system consisting of rhizospheric . Azotobacter microbial populations and . Lepidium sativum plants, growing in solutions containing heavy metals in various concentrations. We examined the ability of the organisms to grow in symbiosis so as to stimulate the plant growth and enhance its tolerance to Cr(VI) and Cd(II), to ultimately provide a reliable phytoremediation system. The study was developed at the laboratory level and, at this stage, does not assess the inherent interactions under real conditions occurring in contaminated fields with autochthonous microflora and under different pedoclimatic conditions and environmental stresses. . Azotobacter sp. bacteria could indeed stimulate the average germination efficiency of . Lepidium sativum by almost 7%, average root length by 22%, average stem length by 34% and dry biomass by 53%. The growth of . L. sativum has been affected to a greater extent in Cd(II) solutions due its higher toxicity compared to that of Cr(VI). The reduced tolerance index (TI, %) indicated that plant growth in symbiosis with PGPR was however affected by heavy metal toxicity, while the tolerance of the plant to heavy metals was enhanced in the bacteria-plant system.A methodology based on artificial neural networks (ANNs) and differential evolution (DE), specifically a neuro-evolutionary approach, was applied to model germination rates, dry biomass and root/stem length and proving the robustness of the experimental data. The errors associated with all four variables are small and the correlation coefficients higher than 0.98, which indicate that the selected models can efficiently predict the experimental data.

Multi-gas and multi-source comparisons of six land use emission datasets and AFOLU estimates in the Fifth Assessment Report, for the tropics for 2000–2005
Roman-Cuesta, Rosa Maria ; Herold, Martin ; Rufino, Mariana C. ; Rosenstock, Todd S. ; Houghton, Richard A. ; Rossi, Simone ; Butterbach-Bahl, Klaus ; Ogle, Stephen ; Poulter, Benjamin ; Verchot, Louis ; Martius, Christopher ; Bruin, Sytze de - \ 2016
Biogeosciences 13 (2016)20. - ISSN 1726-4170 - p. 5799 - 5819.
The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20–25 % of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates, however, remain highly uncertain, jeopardizing the mitigation effectiveness of this sector. Comparisons of global AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding of the reasons behind these differences. Here we compare a variety of AFOLU emission datasets and estimates given in the Fifth Assessment Report for the tropics (2000–2005) to identify plausible explanations for the differences in (i) aggregated gross AFOLU emissions, and (ii) disaggregated emissions by sources and gases (CO2, CH4, N2O). We also aim to (iii) identify countries with low agreement among AFOLU datasets to navigate research efforts. The datasets are FAOSTAT (Food and Agriculture Organization of the United Nations, Statistics Division), EDGAR (Emissions Database for Global Atmospheric Research), the newly developed AFOLU “Hotspots”, “Houghton”, “Baccini”, and EPA (US Environmental Protection Agency) datasets. Aggregated gross emissions were similar for all databases for the AFOLU sector: 8.2 (5.5–12.2), 8.4, and 8.0 Pg CO2 eq. yr−1 (for Hotspots, FAOSTAT, and EDGAR respectively), forests reached 6.0 (3.8–10), 5.9, 5.9, and 5.4 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and agricultural sectors were with 1.9 (1.5–2.5), 2.5, 2.1, and 2.0 Pg CO2 eq. yr−1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating the emissions by sources, continents, and gases, particularly for the forest sector, with fire leading the differences. Agricultural emissions were more homogeneous, especially from livestock, while those from croplands were the most diverse. CO2 showed the largest differences among the datasets. Cropland soils and enteric fermentation led to the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (carbon-only vs. multi-gas assessments, definitions, land use vs. land cover, etc.), in methods (tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc.) and in assumptions (carbon neutrality of certain emissions, instantaneous emissions release, etc.) which call for more complete and transparent documentation for all the available datasets. An enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.
Limited coalescence and Ostwald ripening in emulsions stabilized by hydrophobin HFBII and milk proteins
Dimitrova, Lydia M. ; Boneva, Mariana P. ; Danov, Krassimir D. ; Kralchevsky, Peter A. ; Basheva, Elka S. ; Marinova, Krastanka G. ; Petkov, Jordan T. ; Stoyanov, Simeon D. - \ 2016
Colloids and Surfaces. A: Physicochemical and Engineering Aspects 509 (2016). - ISSN 0927-7757 - p. 521 - 538.
Drop size distribution - Emulsification - Emulsion stability - HFBII hydrophobin - Ostwald ripening

Hydrophobins are proteins isolated from filamentous fungi, which are excellent foam stabilizers, unlike most of the proteins. In the present study, we demonstrate that hydrophobin HFBII can also serve as excellent emulsion stabilizer. The HFBII adsorption layers at the oil/water interface solidify similarly to those at the air/water interface. The thinning of aqueous films sandwiched between two oil phases ends with the formation of a 6 nm thick protein bilayer, just as in the case of foam films, which results in strong adhesive interactions between the emulsion drops. The drop-size distribution in hydrophobin stabilized oil-in-water emulsions is investigated at various protein concentrations and oil volume fractions. The data analysis indicates that the emulsification occurs in the Kolmogorov regime or in the regime of limited coalescence, depending on the experimental conditions. The emulsions with HFBII are very stable – no changes in the drop-size distributions are observed after storage for 50 days. However, these emulsions are unstable upon stirring, when they are subjected to the action of shear stresses. This instability can be removed by covering the drops with a second adsorption layer from a conventional protein, like β-lactoglobulin. The HFBII surface layer is able to suppress the Ostwald ripening in the case when the disperse phase is oil that exhibits a pronounced solubility in water. Hence, the hydrophobin can be used to stabilize microcapsules of fragrances, flavors, colors or preservatives due to its dense adsorption layers that block the transfer of oil molecules.

Hotspots of gross emissions from the land use sector: patterns, uncertainties, and leading emission sources for the period 2000–2005 in the tropics
Roman-cuesta, Rosa Maria ; Rufino, Mariana C. ; Herold, Martin ; Butterbach-bahl, Klaus ; Rosenstock, Todd S. ; Herrero, Mario ; Ogle, Stephen ; Li, Changsheng ; Poulter, Benjamin ; Verchot, Louis ; Martius, Christopher ; Stuiver, John ; Bruin, Sytze De - \ 2016
Biogeosciences 13 (2016)14. - ISSN 1726-4170 - p. 4253 - 4269.
According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) contributes roughly a quarter ( ∼  10–12 Pg CO2e yr−1) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice, and livestock. In spite of the importance of this sector, it is unclear where the regions with hotspots of AFOLU emissions are and how uncertain these emissions are. Here we present a novel, spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO2, CH4, N2O), associated uncertainties, and leading emission sources, in a spatially disaggregated manner (0.5°) for the tropics for the period 2000–2005. Our data highlight the following: (i) the existence of AFOLU emissions hotspots on all continents, with particular importance of evergreen rainforest deforestation in Central and South America, fire in dry forests in Africa, and both peatland emissions and agriculture in Asia; (ii) a predominant contribution of forests and CO2 to the total AFOLU emissions (69 %) and to their uncertainties (98 %); (iii) higher gross fluxes from forests, which coincide with higher uncertainties, making agricultural hotspots appealing for effective mitigation action; and (iv) a lower contribution of non-CO2 agricultural emissions to the total gross emissions (ca. 25 %), with livestock (15.5 %) and rice (7 %) leading the emissions. Gross AFOLU tropical emissions of 8.0 (5.5–12.2) were in the range of other databases (8.4 and 8.0 Pg CO2e yr−1 in FAOSTAT and the Emissions Database for Global Atmospheric Research (EDGAR) respectively), but we offer a spatially detailed benchmark for monitoring progress in reducing emissions from the land sector in the tropics. The location of the AFOLU hotspots of emissions and data on their associated uncertainties will assist national policy makers, investors, and other decision-makers who seek to understand the mitigation potential of the AFOLU sector.
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