Data quality and the role of nutrients in forest carbon-use efficiency

2015 ◽  
Vol 5 (11) ◽  
pp. 959-960 ◽  
Author(s):  
Werner L. Kutsch ◽  
Pasi Kolari
Keyword(s):  
Data Quality ◽  
Forest Carbon ◽  
Carbon Use Efficiency ◽  
Use Efficiency

scholarly journals Reply to 'Uncertain effects of nutrient availability on global forest carbon balance' and 'Data quality and the role of nutrients in forest carbon-use efficiency'

2015 ◽  
Vol 5 (11) ◽  
pp. 960-961 ◽  
Author(s):  
M. Fernández-Martínez ◽  
S. Vicca ◽  
I. A. Janssens ◽  
J. Sardans ◽  
S. Luyssaert ◽  
...  
Keyword(s):  
Data Quality ◽  
Nutrient Availability ◽  
Carbon Balance ◽  
Forest Carbon ◽  
Carbon Use Efficiency ◽  
Use Efficiency

scholarly journals The role of alternative oxidase in modulating carbon use efficiency and growth during macronutrient stress in tobacco cells

2005 ◽  
Vol 56 (416) ◽  
pp. 1499-1515 ◽  
Author(s):  
Stephen M. Sieger ◽  
Brian K. Kristensen ◽  
Christine A. Robson ◽  
Sasan Amirsadeghi ◽  
Edward W. Y. Eng ◽  
...  
Keyword(s):  
Alternative Oxidase ◽  
Tobacco Cells ◽  
Carbon Use Efficiency ◽  
Use Efficiency

scholarly journals Forest carbon use efficiency: is respiration a constant fraction of gross primary production?

2007 ◽  
Vol 13 (6) ◽  
pp. 1157-1167 ◽  
Author(s):  
EVAN H. DeLUCIA ◽  
JOHN E. DRAKE ◽  
RICHARD B. THOMAS ◽  
MIQUEL GONZALEZ-MELER
Keyword(s):  
Primary Production ◽  
Gross Primary Production ◽  
Forest Carbon ◽  
Carbon Use Efficiency ◽  
Use Efficiency

Understanding the controls over forest carbon use efficiency on small spatial scales: Effects of forest disturbance and tree diversity

2019 ◽  
Vol 269-270 ◽  
pp. 136-144 ◽  
Author(s):  
Norbert Kunert ◽  
Tarek S. El-Madany ◽  
Luiza Maria T. Aparecido ◽  
Sebastian Wolf ◽  
Catherine Potvin
Keyword(s):  
Forest Disturbance ◽  
Spatial Scales ◽  
Tree Diversity ◽  
Forest Carbon ◽  
Carbon Use Efficiency ◽  
Use Efficiency

New insights on carbon use efficiency using calorespirometry – a bioenergetics-based model

2020 ◽  
Author(s):  
Arjun Chakrawal ◽  
Anke M. Herrmann ◽  
Stefano Manzoni
Keyword(s):  
Metabolic Pathways ◽  
Microbial Growth ◽  
Energy Content ◽  
Growth Yields ◽  
Balance Model ◽  
Organic C ◽  
Degree Of Reduction ◽  
Carbon Use Efficiency ◽  
Use Efficiency

<p>Soil organic carbon (SOC) represents both a source of energy (catabolism) and a building material for biosynthesis (anabolism) for microorganisms. Microbial carbon use efficiency (CUE) – the ratio of C used for biosynthesis over C consumed – measures the partitioning between anabolic and catabolic processes. While most work on CUE has been based on C mass flows, the role of SOC energy content, microbial energy demand, and general energy flows on CUE have been rarely considered. Thus, a bioenergetics perspective on CUE could provide new insights on how microorganisms utilize C substrates and ultimately allow C to be stabilized in soils.</p><p>The microbial growth reactions are generally associated with a negative enthalpy change, which results in heat dissipation from the system. This heat can be measured using an isothermal calorimeter, which is often coupled with respiration measurements. This coupled system allows studying energy and C exchanges, and calculating their ratio referred to as the calorespirometric ratio (CR). Here, we formulate a coupled mass and energy balance model for microbial growth and provide a generalized relationship between CUE and CR. In the model, we consider two types of organic C in soils, the added substrate (i.e., glucose) and the native SOC. Furthermore, we assume that glucose is taken up via aerobic (AE) and two fermentation metabolic pathways – glucose to ethanol (F1) and glucose to lactic acid (F2); for simplicity, only aerobic growth on the native SOC was adopted. We use this model as a framework to generalize previous formulations and generate hypotheses on the expected variations in CR as a function of substrate type, metabolic pathways, and microbial properties (specifically CUE). In turn, the same equations can be used to estimate CUE from measured CR.</p><p>Our results show that in a non-growing system, CR depends only on the rates of different metabolic pathways (AE, F1, and F2). While in growing systems, CR is a function of rates as well as growth yields for these metabolic pathways. Under purely aerobic conditions, our model predicts that CUE increases with increasing CR when the degree of reduction of the substrate is higher than that of the microbial biomass. Similarly, CUE decreases with increasing CR when the degree of reduction of substrate is lower than that of the biomass. In the case of combined metabolism – aerobic and fermentation simultaneously – CUE is not only a function of CR and the degree of reduction of substrates but also the rates and growth yields of all metabolic pathways involved. To summarize, in this contribution we illustrate how calorespirometry can become an efficient tool to evaluate CUE and the role of different metabolic pathways in soil systems.</p>

How relevant are microbial traits to understand soil biogeochemical cycles? 

2021 ◽  
Author(s):  
Tessa Camenzind ◽  
Johannes Lehmann ◽  
Anika Lehmann ◽  
Carlos A. Aguilar-Trigueros ◽  
Matthias C. Rillig
Keyword(s):  
Enzymatic Activity ◽  
Fungal Growth ◽  
Biogeochemical Cycles ◽  
Model Organisms ◽  
Soil System ◽  
Microbial Physiology ◽  
Carbon Use Efficiency ◽  
N Supply ◽  
Use Efficiency

<p>Our knowledge about the role of microbial organisms as drivers of soil biogeochemical cycles is mainly based on soil analyses, and the physiological information that exists for few microbial model organisms. In soil, measurements of process rates and element contents can be related to the apparent activity of the microbial community, though conclusions are often indirect - actual microbial physiology and diversity remains hidden. By contrast, analyses of microbial physiology under controlled conditions are hardly representative of the vast diversity of microorganisms in soil, and a transfer of these findings to complex soil systems is challenging. Thus, we argue that a better exchange among these ecological disciplines will lead to a valuable transfer of relevant questions, knowledge and improved understanding of the role of microbes in soil and its responses to environmental change. <br>Here, we provide examples of an evaluation of microbial parameters relevant in soil biogeochemical cycles, analysing traits in a collection of 31 saprobic fungi in response to varying substrate conditions. The large dataset allowed to test several assumptions and conclusions derived from soil system analyses exemplarily for soil fungi. Specifically, we (1) evaluated the optimum C:N:P (carbon:nitrogen:phosphorus) substrate ratio for fungal growth and activity, (2) assessed the responses in carbon-use efficiency and enzyme activity to N deficiency, (3) analyzed the relevance of C versus N supply for fungal growth and activity under varying substrate conditions and (4) tested the assumption of microbial stoichiometric homeostasis, that represents a basic principle in soil ecological stoichiometry. <br>Fungal responses to changes in N and C availability were partly consistent with expectations, e.g. regarding general nutrient demands, though as often discussed C availability appeared more relevant for growth especially in complex substrates. Enzymatic activity and respiration also positively correlated with N availability, resulting in decreased carbon-use efficiency at high N supply. These findings, for example, contradict certain conclusions in soil analyses, namely that N limitations will result in “N mining” (high enzymatic activity), while the excess of C causes “overflow respiration” and reduced CUE. Regarding fungal C:N:P ratios, those were only related to nutrient demands when growing in simple media, while in soil substrate such relations seem more complex. Contradicting the assumption of microbial homeostasis in soil, fungal individuals showed more flexible C:N:P ratios than expected, though the degree of flexibility varied among isolates. In general, the results also reveal a large trait variation among different isolates, with several traits showing a phylogenetic signal, indicating variations in microbial activity depending on community composition.<br>Finally, we want to raise and discuss several emerging questions: How relevant is a deeper understanding of microbial physiology to understand soil biogeochemical processes? How do we include the variability of traits in diverse soil communities – are average values informative, or can we proceed with useful categories? And how can methods in soil science and microbial ecology be merged best to allow fruitful knowledge transfer?</p>

Sign in / Sign up

Export Citation Format

Share Document