Mid-infrared spectroscopy as a potential tool for reconstructing lake salinity

Many aquatic ecosystems in Australia are impacted or threatened by salinisation; however, there is a paucity of records detailing the changes in salinity of individual water bodies that extend beyond a few decades. One way to overcome this issue is the use of inference models, which have typically been based on biological proxies. This pilot project investigates the potential for mid-infrared spectroscopy (MIRS) to provide an alternative method of reconstructing past salinity levels in Australian lakes. A small (19 lakes) calibration dataset was used to develop a MIRS-based lake water salinity inference model (measured vs. inferred salinity, based on leave-one-out cross-validation, R2 = 0.64). This model and a previously published diatom–salinity model were both used to infer salinity levels in Tower Hill Lake in south-eastern Australia, over the last 60 years. Comparisons between these reconstructions and measured salinity data from Tower Hill Lake indicate that salinities inferred by the MIRS model more closely resembled the measured values than those produced using the diatom model, predominantly in terms of the actual values inferred, but also with regard to the trends observed. This supports the hypothesis that MIRS can provide a valuable new tool for reconstructing lake salinity.Laura Cunningham, John Tibby, Sean Forrester, Cameron Barr and Jan Skjemsta

Only small changes in soil organic carbon and charcoal concentrations found one year after experimental slash-and-burn in a temperate deciduous forest

International audienceAnthropogenic fires affected the temperate deciduous forests of Central Europe over millennia. Biomass burning releases carbon to the atmosphere and produces charcoal, which potentially contributes to the stable soil carbon pools and is an important archive of environmental history. The fate of charcoal in soils of temperate deciduous forests, i.e. the processes of charcoal incorporation and transportation, and the effects on soil organic matter are still not clear. In a long-term experimental burning site, we investigated the effects of slash-and-burn and determined soil organic carbon, charcoal carbon and nitrogen concentrations and the soil lightness of colour (L*) in the topmost soil material (0?1, 1?2.5 and 2.5?5 cm depths) before, immediately after the fire and one year after burning. The main results are that (i) only few charcoal particles from the forest floor were incorporated into the soil matrix by soil mixing animals. In 0?1 cm and during one year, the charcoal C concentrations increased only by 0.4 g kg?1 and the proportion of charcoal C to SOC concentrations increased from 2.8 to 3.4%; (ii) the SOC concentrations did not show any significant differences; (iii) soil lightness significantly decreased in the topmost soil layer and correlated with the concentrations of charcoal C (r=-0.87**) and SOC (r=?0.94**) in samples 0?5 cm. We concluded that the soil colour depends on the proportion of aromatic charcoal carbon in total organic matter and that Holocene burning could have influenced soil charcoal concentrations and soil colour

Soil organic

[1] We quantified the effects of repeated, seasonal fires on soil organic carbon (SOC), black carbon (BC), and total N in controls and four fire treatments differing in frequency and season of occurrence in a temperate savanna. The SOC at 0-20 cm depth increased from 2044 g C m À2 in controls to 2393-2534 g C m À2 in the three treatments that included summer fire. Similarly, soil total N (0-20 cm) increased from 224 g N m À2 in the control to 251-255 g N m À2 in the treatments that included summer fire. However, winter fires had no effect on SOC or total N. Plant species composition coupled with lower d 13 C of SOC suggested that increased soil C in summer fire treatments was related to shifts in community composition toward greater relative productivity by C 3 species. Lower d 15 N of soil total N in summer fire treatments was consistent with a scenario in which N inputs > N losses. The BC storage was not altered by fire, and comprised 13-17% of SOC in all treatments. Results indicated that fire and its season of occurrence can significantly alter ecosystem processes and the storage of C and N in savanna ecosystems

Australian climate-carbon cycle feedback reduced by soil black carbon

Annual emissions of carbon dioxide from soil organic carbon are an order of magnitude greater than all anthropogenic carbon dioxide emissions taken together1. Global warming is likely to increase the decomposition of soil organic carbon, and thus the release of carbon dioxide from soils2,3,4,5, creating a positive feedback6,7,8,9. Current models of global climate change that recognize this soil carbon feedback are inaccurate if a larger fraction of soil organic carbon than postulated has a very slow decomposition rate. Here we show that by including realistic stocks of black carbon in prediction models, carbon dioxide emissions are reduced by 18.3 and 24.4% in two Australian savannah regions in response to a warming of 3 ∘C over 100 years1. This reduction in temperature sensitivity, and thus the magnitude of the positive feedback, results from the long mean residence time of black carbon, which we estimate to be approximately 1,300 and 2,600 years, respectively. The inclusion of black carbon in climate models is likely to require spatially explicit information about its distribution, given that the black carbon content of soils ranged from 0 to 82% of soil organic carbon in a continental-scale analysis of Australia. We conclude that accurate information about the distribution of black carbon in soils is important for projections of future climate change

Multi-objective calibration of RothC using measured carbon stocks and auxiliary data of a long-term experiment in Switzerland

Interactions between model parameters and low spatiotemporal resolution of available data mean that conventional soil organic carbon (SOC) models are often affected by equifinality, with consequent uncertainty in SOC forecasts. Estimation of belowground C inputs is another major source of uncertainty in SOC modelling. Models are usually calibrated on SOC stocks and fluxes from long‐term experiments (LTEs), whereas other point data are not used for constraining the model parameters. We used data from an agricultural long‐term (> 65 years) fertilization experiment to test a multi‐objective parameter estimation approach on the RothC model, combining SOC data from different fertilization treatments with microbial biomass, basal respiration and Zimmermann’s fractions data. We also compared two methods to estimate the belowground C inputs: a conventional scaling of belowground biomass from crop harvest yield and an alternative approach based on constant belowground C for cereals measured experimentally in the field. The resulting posterior parameter distributions still suffered from some equifinality; the most stable C pool kinetic constants and composition of exogenous organic matter were the most sensitive parameters. The use of fixed belowground C inputs for cereals improved the model performance, reducing the importance of treatment‐specific parameters and processes. The introduction of microbial biomass and basal respiration data was effective for increasing determination of the calibration, but also suggested a change in the model structure: the microbial biomass pool, which is proportional to the C inputs in the traditional models, could be represented by different microbial physiology functions