Simulated nitrogen deposition affects soil fauna from a semiarid Mediterranean ecosystem in central Spain

Nitrogen (N) deposition is a major threat to the semiarid Mediterranean ecosystems. We simulated a gradient of N deposition (0, 10, 20 and 50 kg N ha^?1 year^?1?+?6.4 kg N ha^?1 year^?1 ambient deposition) in a Mediterranean shrubland from central Spain. In autumn 2011 (after 4 years of experimental duration), soil cores were taken to extract the soil fauna. Acari (45.54%) and Collembola (44.00%) were the most represented taxonomical groups, and their abundance was negatively related to soil pH. Simulated N deposition had an impact on the total number of individuals in soil as well as on Collembola and Pauropoda abundance. Collembola abundance increased with N loads up to 20 kg N ha^-1 year^-1 and then decreased. This response was attributed to soil acidification (between 0 and 20 kg N ha^-1 year^-1) and increased soil ammonium (between 20 and 50 kg N ha^-1 year^-1). Pauropoda were favoured by additions of 50 kg N ha^-1 year^-1, and it was the only taxonomical group whose abundance was exclusively related to N deposition, suggesting their potential as bioindicators. Contrary to predictions, there was a negative relationship between soil faunal abundance and plant diversity. In conclusion, soil faunal communities from semiarid Mediterranean ecosystems in central Spain seem to be primarily influenced by soil chemistry (mainly pH) but are also susceptible to increased N deposition. The main drivers of change under increased N deposition scenarios seem to be soil acidification and increased ammonium in soils where nitrate is the dominant mineral N form.     

Testing the utility of abiotic surrogates for marine habitat mapping at scales relevant to management

Habitat mapping at the scale at which marine protected areas are designed and managed is essential for assessment of, and design for, representation. Most habitat mapping studies rely solely or in part on abiotic surrogates for patterns of biodiversity. The utility of abiotic variables in predicting biological distributions at the local scale (10 s of km) was tested in a remote video survey of macrobenthos in Moreton Bay, Australia. Habitat classifications of the same set of 41 sites based on 6 abiotic variables and abundances of 89 taxa and bioturbation indicators were compared using correlation, regression and ordination analyses. The concepts of false homogeneity (abiotically similar but biologically distinct) and false heterogeneity (abiotically distinct but biologically similar) were defined to describe types of errors associated with using abiotic surrogates to construct habitat maps, and quantified using two separate methods. Overall, the best prediction by abiotic surrogates explained less than 30% of the pattern of biological similarity. Errors of false homogeneity were between 20% and 62%, depending on the methods of estimation. Predictive capability of abiotic surrogates at the taxon level was poor, with only 6% of taxon/surrogate correlations significant. Abiotic variables did not discriminate sufficiently between different soft bottom communities to be a reliable basis for mapping. These results have implications for the widespread use of abiotic surrogates in marine habitat mapping to plan for, or assess, representation in marine protected areas. Little confidence can be placed in marine habitat classifications based solely or largely on abiotic surrogates without calibration by rigorous biological surveys at the appropriate scale. Therefore, it is questionable whether marine protected areas designed on this basis can have measurable benefits for conservation.     

Fate of xanthohumol and related prenylflavonoids from hops to beer

The fate of three prenylated flavonoids of the chalcone type, xanthohumol, desmethylxanthohumol, and 3'-geranylchalconaringenin, was monitored with LC/MS-MS from hops (Humulus lupulus L.) to beer in two brewing trials. The three prenylchalcones were largely converted into their isomeric flavanones, isoxanthohumol, prenylnaringenins, and geranylnaringenins, respectively, in the boiling wort. Losses of prenylflavonoids were due to incomplete extraction from the hops into the wort (13-25%), adsorption to insoluble malt proteins (18-26%), and adsorption to yeast cells (11-32%) during fermentation. The overall yield of xanthohumol, after lagering of the beer and largely in the form of isoxanthohumol, amounted to 22-30% of the hops' xanthohumol. About 10% of the hops' desmethylxanthohumol, completely converted into prenylnaringenins, remained in the beers. 3'-Geranylchalconaringenin behaved similarly to desmethylxanthohumol. Solubility experiments indicated that (1) malt carbohydrates form soluble complexes with xanthohumol and isoxanthohumol and (2) solubility does not dictate the isoxanthohumol levels of finished beers.     

Sources of nitrite in a permanent grassland soil

The objective of this study was to separate the observed nitrite (NO₂^–) concentration in a permanent grassland soil into process‐specific subpools. A laboratory experiment was carried out where either the nitrate and/or ammonium pool was labelled with ¹⁵N at 60 atom % excess. The main N transformations that occurred in this experiment were analysed with a ¹⁵N tracing model extended with a NO₂^– submodel. Techniques that have been used to date have been only able to identify NO₂^– subpools related to nitrification (NO₂^–_nit) and denitrification (NO₂^–_den). With the analysis presented here, we were able to quantify the size of an additional NO₂^– pool in the soil related to organic N turnover (NO₂^–_org). All transformations related to NO₂^– turnover of the three subpools occurred simultaneously. After non‐linear parameter optimization the model predicted that on average NO₂^–_den, NO₂^–_nit and NO₂^–_org pools contributed 57, 33 and 10% to the total soil NO₂^– concentration. The finding that heterotrophic processes can contribute to the NO₂^– dynamics in permanent grassland soils might also have important implications for the understanding of gaseous N production that are tightly linked to NO₂^– turnover. Further work is needed to find out how important the conversion of organic N to NO₂^– is in other soil‐based ecosystems and to identify the microbial groups responsible for this process.     

Discriminating soil crust type,development stage and degree of disturbance in semiarid environments from their spectral characteristics

Biological soil crusts (BSCs) are increasingly recognized as common features in arid and semiarid ecosystems and play an important role in the hydrological and ecological functioning of these ecosystems. However, BSCs are very vulnerable to, in particular, human disturbance. This results in a complex spatial pattern of BSCs in various stages of development. Such patterns, to a large extent, determine runoff and erosion processes in arid and semiarid ecosystems. In recent years, visible and near infrared (Vis‐NIR) diffuse reflectance spectroscopy has been used for large‐scale mapping of the distribution of BSCs. Our goals were (i) to demonstrate the efficiency of Vis‐NIR spectroscopy in discriminating vegetation, physical soil crusts, various developmental stages of BSCs, and various types of disturbance on BSCs and (ii) to develop a classification system for these types of ground cover based on Vis‐NIR spectroscopy. Spectral measurements were taken of vegetation, physical crusts and various types of BSCs prior to, and following, trampling or removal with a scraper in two semiarid areas in SE Spain. The main spectral differences were: (i) absorption by water at about 1450 nm, more intense in the spectra of vegetation than in those of physical crusts or BSCs, (ii) absorption features at about 500 and 680 nm for the BSCs, which were absent or very weak for physical crusts, (iii) a shallower slope between about 750 and 980 nm for physical crusts and early‐successional BSCs than for later‐successional BSCs and (iv) a steeper slope between about 680 and 750 nm for the most developed BSCs. A partial least squares regression‐linear discriminant analysis of the spectral data resulted in a reliable classification (Kappa coefficients over 0.90) of the various types of ground cover and types of BSC disturbance. The distinctive spectral features of vegetation, physical crusts and the various developmental stages of BSCs were used to develop a classification system. This will be a promising tool for mapping BSCs with hyperspectral remote sensing.