• Energy Research

Laboratory spectroscopy has proved its reliability for estimating soil organic carbon (SOC) by exploiting the relationship between electromagnetic radiation and key spectral features of organic carbon located in the VIS-NIR-SWIR (350–2500 nm) region. While this approach provides SOC estimates at specific sampling points, geo-statistical or interpolation techniques are required to infer continuous spatial information. UAS-based proximal or remote sensing has the potential to provide detailed and spatially explicit spectral sampling of the topsoil at the field or even watershed scale. However, the factors affecting the quality of spectral acquisition under outdoor conditions need to be considered. In this study, we investigate the capabilities of two portable hyperspectral sensors (STS-VIS and STS-NIR), and two small-form multispectral cameras with narrow bands in the VIS-NIR region (Parrot Sequoia and Mini-MCA6), to predict SOC content. We collected spectral data under both controlled laboratory and outdoor conditions, with the latter being affected by variable illumination and atmospheric conditions and sensor-sample distance. We also analysed the transferability of the prediction models between different measurement setups by aligning spectra acquired under different conditions (laboratory and outdoor) or by different instruments. Our results indicate that UAS-compatible small-form sensors can be used to reliably estimate SOC. The results show that: (i) the best performance for SOC estimation under outdoor conditions was obtained using the VIS-NIR range, while the addition of the SWIR region decreased the prediction accuracy; (ii) prediction models using only the narrow bands of multispectral cameras gave similar or better performances than those using continuous spectra from the STS hyperspectral sensors; and (iii) when used in outdoor conditions, the micro hyperspectral sensors substantially benefitted from a laboratory model calibration followed by a spectral transfer using an internal soil standard. Based on this analysis, we recommend VIS-NIR portable instruments for estimating spatially distributed SOC data. The integration of these sensors in UAS-mapping devices could represent a cost-effective solution for soil research and precision farming applications when high resolution data are required.

The negative effect of increasing atmospheric nitrogen (N) pollution on grassland biodiversity is now incontrovertible. However, the recent introduction of cleaner technologies in the UK has led to reductions in the emissions of nitrogen oxides, with concomitant decreases in N deposition. The degree to which grassland biodiversity can be expected to 'bounce back' in response to these improvements in air quality is uncertain, with a suggestion that long-term chronic N addition may lead to an alternative low biodiversity state. Here we present evidence from the 160-year-old Park Grass Experiment at Rothamsted Research, UK, that shows a positive response of biodiversity to reducing N addition from either atmospheric pollution or fertilizers. The proportion of legumes, species richness and diversity increased across the experiment between 1991 and 2012 as both wet and dry N deposition declined. Plots that stopped receiving inorganic N fertilizer in 1989 recovered much of the diversity that had been lost, especially if limed. There was no evidence that chronic N addition has resulted in an alternative low biodiversity state on the Park Grass plots, except where there has been extreme acidification, although it is likely that the recovery of plant communities has been facilitated by the twice-yearly mowing and removal of biomass. This may also explain why a comparable response of plant communities to reduced N inputs has yet to be observed in the wider landscape.

Abstract Last-century climate change has led to variable increases of the intrinsic water-use efficiency (W i; the ratio of net CO2 assimilation to stomatal conductance for water vapor) of trees and C3 grassland ecosystems, but the causes of the variability are not well understood. Here, we address putative drivers underlying variable W i responses in a wide range of grassland communities. W i was estimated from carbon isotope discrimination in archived herbage samples from 16 contrasting fertilizer treatments in the Park Grass Experiment, Rothamsted, England, for the 1915 to 1929 and 1995 to 2009 periods. Changes in W i were analyzed in relation to nitrogen input, soil pH, species richness, and functional group composition. Treatments included liming as well as phosphorus and potassium additions with or without ammonium or nitrate fertilizer applications at three levels. W i increased between 11% and 25% (P < 0.001) in the different treatments between the two periods. None of the fertilizers had a direct effect on the change of W i (ƊW i). However, soil pH (P < 0.05), species richness (P < 0.01), and percentage grass content (P < 0.01) were significantly related to ƊW i. Grass-dominated, species-poor plots on acidic soils showed the largest ƊW i (+14.7 μmol mol−1). The ƊW i response of these acidic plots was probably related to drought effects resulting from aluminum toxicity on root growth. Our results from the Park Grass Experiment show that W i in grassland communities consistently increased over a wide range of nutrient inputs, soil pH, and plant community compositions during the last century.