Page 254 - Microbial methane cycling in a warming world From biosphere to atmosphere Michiel H in t Zandt

Chapter 11. Integration and outlook
scenarios. For example, Q10 values are commonly used to assess the temperature sensitivity of an ecosystem. This sensitivity is determined by geochemical and biological parameters, but their implementation is complex and data points are often limited. In Chapter 7, we estimated Q10 values based on maximum rate changes upon temperature increase and substrate amendment. High initial Q10 values of 3.3-9.8 after 98 days of incubation indicated greater sensitivity upon direct warming, whereas a decrease in Q10 values to 0.9-1.1 in the long term indicated that these systems rapidly adapt to the climate change scenario. These values provide a valuable tool for both detailed and global comparisons, and climate models. However, limited datasets on Q10 values hamper further interpretation (Duc, Crill and Bastviken 2010; Sepulveda-Jauregui et al. 2018).
For feasible quantification of ecosystem contributions to the global greenhouse budget, we urgently need to find molecular proxies that can be used to estimate greenhouse gas fluxes and to categorize thermokarst lakes with regard to their greenhouse gas emission potential. We have to consider that the current molecular proxies might not be adequate and of sufficiently high throughput to detect all relevant microbial players. A fundamental question is whether we already know the microbial key players in the methane cycle of an ecosystem. Although in- depth 16S rRNA gene-based amplicon sequencing approaches together with full-metagenomic sequencing campaigns have helped to obtain microbial diversity datasets that are more detailed than ever (Chapter 4, 7 and 8), it is a lack in understanding microbial functions that provides a current bottleneck.
Investigations of minimally required datasets and correlating parameters can provide important steps forward in reducing costs and speeding up downstream analyses. In addition, valuable data can further be obtained through laboratory-based cultivation using micro-, meso-, and macrocosms, and especially bioreactors, in which environmental conditions can be even more precisely controlled than is often done today. The insights that can only be obtained from such efforts are essential for the interpretation of metagenomics sequencing datasets.
Peat provides an important role as global carbon sink
Peatlands play a dual role in the climate. In general, they are CO2 sinks and sequester atmospheric carbon in accumulating peat layers. However, most peatlands are also significant CH4 sources (Dean et al. 2018). Peatlands are found in permafrost environments, temperate,
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