ALBERT

Beschreibung: Simultaneous Fourier transform infrared (FTIR) extinction spectra and aerosol size distributions have been measured for some components of mineral dust aerosol including feldspars (albite, oligoclase) and diatomaceous earth, as well as more complex authentic dust samples that include Iowa loess and Saharan sand. Spectral simulations for single-component samples, derived from Rayleigh-theory models for characteristic particle shapes, better reproduce the experimental spectra including the peak position and band shape compared to Mie theory. The mineralogy of the authentic dust samples was inferred using analysis of FTIR spectra. This approach allows for analysis of the mineralogy of complex multicomponent dust samples. Extinction spectra for the authentic dust samples were simulated from the derived sample mineralogy using published optical constant data for the individual mineral constituents and assuming an external mixture. Nonspherical particle shape effects were also included in the simulations and were shown to have a significant effect on the results. The results show that the position of the peak and the shape of the band of the IR characteristic features in the 800 to 1400 cm−1 spectral range are not well simulated by Mie theory. The resonance peaks are consistently shifted by more than +40 cm−1 relative to the experimental spectrum in the Mie simulation. Rayleigh model solutions for different particle shapes better predict the peak position and band shape of experimental spectra, even though the Rayleigh condition may not be strictly obeyed in these experiments.

Beschreibung: [1]  Radiative transfer calculations as well as satellite and ground-based retrieval algorithms often use Mie theory to account for atmospheric mineral dust. However, the approximations used in Mie theory are often not appropriate for mineral dust and can lead to inaccuracies in modeling optical properties. Analytic models that are based on Rayleigh theory and account for particle shapes can offer significant advantages when used to model the IR extinction of mineral dust in the accumulation size mode. Here, we extend our investigations of the IR optical properties of mineral dust to include samples that have been processed with organic acids. In particular, we aerosolize several individual components of mineral dust with organic compounds that are common in the atmosphere. Through online and offline analysis of the resulting aerosol particles combining FTIR extinction spectroscopy, micro-Raman spectroscopy and scanning electron microscopy we have identified three distinct outcomes of the interactions, which depend on the nature of the mineral and the organic acid: reactions with segregation of the products within the particle; formation of a uniform coating on the particle; or a formation of external mixture when there is no significant chemical interaction. Analysis of FTIR extinction spectra of the different dust components that have undergone processing shows red shifts of the prominent IR resonance peaks. The extent of the red shift, which varies from 2 to 10 cm -1 , depends on the mineral and the nature of the interaction. Spectral simulations showed that the deviation from Mie theory becomes even more pronounced for these processed mineral dust aerosol components.

Beschreibung: In the high Arctic, recruitment of hard-bottom benthic organisms has been studied at single locations, but little is known about how it varies spatially or temporally, or how it is influenced by abiotic factors. In this study, settlement plates were simultaneously deployed at five locations in three Svalbard (Norway) fjords at depths ranging from 7 m to 215 m. Recruitment was significantly different among fjords and among locations within a fjord. Recruits at each site co-occurred randomly even though interspecific overgrowth was observed. This finding provides further evidence that there is not necessarily a relationship between non-random co-occurrence and interspecific competition, such as is traditionally assumed for other isolated, island-like habitats. We found significantly lower recruitment in an Arctic-influenced fjord than in more Atlantic-influenced fjords. The abundance and richness of recruits was significantly lower in fall-winter than in spring-summer, but the spirorbid Circeis armoricana recruited in high abundance in fall-winter. Both the abundance and taxonomic richness of recruits declined exponentially with depth, with the hydroid Stegopoma plicatile dominating at 215 m in an Atlantic-influenced fjord. The most abundant recruiting taxa ( C. armoricana , Semibalanus balanoides , Harmeria scutulata , Celleporella hyalina ) can be described as pioneer (early-succession) species. Crustose coralline algae, a slow-growing superior competitor, also recruited at one location. Recruitment in Svalbard is highly variable, both spatially and temporally, and our results show the influence of local factors such as adult species composition.

Beschreibung: Accurate maps of wetlands and riparian areas are critical for targeting conservation and monitoring efforts. However, detailed inventories in mountain regions are largely non-existent, as conventional mapping approaches are hindered by high costs, remoteness, and landscape variability. Contemporary modeling techniques can circumvent many of these issues, but are often difficult to interpret and tend to rely on specialized datasets that prevent their wider application. In this study, we used machine learning, Landsat 8 imagery and geomorphometric indices to map the distribution of wetlands and riparian areas in the Cache la Poudre River watershed, Colorado, USA. We used a presence-background approach to develop and compare predictions from three popular algorithms: boosted regression trees, MaxEnt and random forests. In addition, we developed the models within three elevation-based life zones to account for altitudinal changes in ecohydrology and land use. Our results showed strong predictive performance, with top-performing models achieving area under the curve values as high as 0.98 and correctly classifying up to 95% of test data. Model performance varied by elevation zone, and no algorithm consistently outperformed the others. The boosted regression trees approach was uniquely able to differentiate wetlands from irrigated agriculture and residential areas in lower elevations. Multi-seasonal greenness and wetness indices were highly influential predictors in all models, underscoring the importance of capturing local phenological characteristics and hydrological regimes. Dissection and roughness terrain metrics were key predictors for identifying valley bottom meadows and emergent wetlands in high-elevation forests. We demonstrate how integrating ecological interpretation into the modeling workflow can inform conventional accuracy statistics and help bridge field-based and remote sensing perspectives. We also show how continuous model outputs can facilitate this process by depicting nuances of the wetland-upland continuum. Our approach requires only public data that are widely available, and can be easily adapted to other heterogeneous mountain settings. We used machine learning, Landsat 8 imagery and geomorphometric indices to map the distribution of wetlands and riparian areas in a highly variable Rocky Mountain watershed. We used a presence-background approach to develop and compare predictions from three popular algorithms: boosted regression trees, MaxEnt and random forests. Results were highly accurate, with top-performing models achieving area under the curve values as high as 0.98 and correctly classifying up to 95% of test data. Multi-seasonal greenness and wetness indices were highly influential predictors in all models. Dissection and roughness terrain metrics were key predictors for identifying valley-bottom meadows and emergent wetlands in high-elevation forests. We demonstrate how integrating ecological interpretation into the modeling workflow can inform conventional accuracy statistics and help bridge field-based and remote sensing perspectives. Our approach requires only public data that are widely available, and can be easily adapted to other heterogeneous mountain settings.