Building a soil spectral library for Tajikistan comparing local and global modeling approaches

Over the last ~20 years, soil spectral libraries storing near-infrared reflectance (NIR) spectra from diverse soil samples have been built for many places, since almost 10 years also for Tajikistan. Many calibration approaches have been reported and used for prediction from large and heterogeneous libraries, but most are hampered by the high diversity of the soils, where the mineral background is heavily influencing spectral features. In such cases, local learning strategies have the advantage of building locally adapted calibrations, which can deal better with nonlinearities. Therefore, it was our major aim to identify the most efficient approach to develop an accurate and stable locally weigthed calibration model using a spectral library compiled over the past years. Keywords: Tajikistan, Near-Infrared spectroscopy (NIRS), soil organic carbon, locally weighted regression, regional and local spectral library.

MODELING REACTIVE GAS UPTAKE, TRANSPORT, AND TRANSFORMATION IN AGGREGATED SOILS

Gas diffusion research in soils covers, to a large extent, the transport behavior of practically insoluble gases. We extend the mathematical description of gas transport to include reactive gaseous components that hydrolyze in water such as SO2 and CO2. The path between the free atmosphere and the microporous niches is modeled by assuming penetration through gas-filled macropores, air-water phase transfer, and diffusion and speciation in the liquid phase. For hydrolyzable gases, the rate of mass transfer into and the total absorption capacity of the soil solution may be high. Both the capacity and the transfer rate are influenced by the soil-solution pH; for high pH, they become extremely high for SO2. The soil absorption of such gases is also influenced by soil structure. Well-aerated, near-neutral soils are a potentially important sink for SO2.

Influence of the background wind on the local soil moisture-precipitation feedback

The importance of soil moisture anomalies on airmass convection over semiarid regions has been recognized in several studies. The underlying mechanisms remain partly unclear. An open question is why wetter soils can result in either an increase or a decrease of precipitation (positive or negative soil moisture–precipitation feedback, respectively). Here an idealized cloud-resolving modeling framework is used to explore the local soil moisture–precipitation feedback. The approach is able to replicate both positive and negative feedback loops, depending on the environmental parameters. The mechanism relies on horizontal soil moisture variations, which may develop and intensify spontaneously. The positive expression of the feedback is associated with the initiation of convection over dry soil patches, but the convective cells then propagate over wet patches where they strengthen and preferentially precipitate. The negative feedback may occur when the wind profile is too weak to support the propagation of convective features from dry to wet areas. Precipitation is then generally weaker and falls preferentially over dry patches. The results highlight the role of the midtropospheric flow in determining the sign of the feedback. A key element of the positive feedback is the exploitation of both low convective inhibition (CIN) over dry patches (for the initiation of convection) and high CAPE over wet patches (for the generation of precipitation).

Modeling tree water deficit from microclimate: an approach to quantifying drought stress

Tree water deficit estimated by measuring water-related changes in stem radius (DeltaW) was compared with tree water deficit estimated from the output of a simple, physiologically reasonable model (DeltaW(E)), with soil water potential (Psi(soil)) and atmospheric vapor pressure deficit (VPD) as inputs. Values of DeltaW were determined by monitoring stem radius changes with dendrometers and detrending the results for growth, We followed changes in DeltaW and DeltaW(E) in Pinus sylvestris L. and Quercus pubescens Willd. over 2 years at a dry site (2001-2002; Salgesch, Wallis) and in Picea abies (L.) Karst. for 1 year at a wet site (1998; Davos, Graubuenden) in the Swiss Alps. The seasonal courses of DeltaW in deciduous species and in conifers at the same site were similar and could be largely explained by variation in DeltaW(E). This finding strongly suggests that DeltaW, despite the known species-specific differences in stomatal response to microclimate, is mainly explained by a combination of atmospheric and soil conditions. Consequently, we concluded that trees are unable to maintain any particular DeltaW. Either Psi(soil) or VPD alone provided poorer estimates of AWthan a model incorporating both factors. As a first approximation of DeltaW(E), Psi(soil) can be weighted so that the negative mean Psi(soil) reaches 65 to 75% of the positive mean daytime VPD over a season (Q. pubescens: similar to65%, P abies: similar to70%, P sylvestris: similar to75%). The differences in DeltaW among species can be partially explained by a different weighting of Psi(soil) against VPD. The DeltaW of P. sylvestris was more dependent on Psi(soil) than that of Q. pubescens, but less than that of P. abies, and was less dependent on VPD than that of P. abies and Q. pubescens. The model worked well for P. abies at the wet site and for Q. pubescens and P. sylvestris at the dry site, and may be useful for estimating water deficit in other tree species.

Biotic and Abiotic Properties Mediating Plant Diversity Effects on Soil Microbial Communities in an Experimental Grassland

Plant diversity drives changes in the soil microbial community which may result in alterations in ecosystem functions. However, the governing factors between the composition of soil microbial communities and plant diversity are not well understood. We investigated the impact of plant diversity (plant species richness and functional group richness) and plant functional group identity on soil microbial biomass and soil microbial community structure in experimental grassland ecosystems. Total microbial biomass and community structure were determined by phospholipid fatty acid (PLFA) analysis. The diversity gradient covered 1, 2, 4, 8, 16 and 60 plant species and 1, 2, 3 and 4 plant functional groups (grasses, legumes, small herbs and tall herbs). In May 2007, soil samples were taken from experimental plots and from nearby fields and meadows. Beside soil texture, plant species richness was the main driver of soil microbial biomass. Structural equation modeling revealed that the positive plant diversity effect was mainly mediated by higher leaf area index resulting in higher soil moisture in the top soil layer. The fungal-to-bacterial biomass ratio was positively affected by plant functional group richness and negatively by the presence of legumes. Bacteria were more closely related to abiotic differences caused by plant diversity, while fungi were more affected by plant-derived organic matter inputs. We found diverse plant communities promoted faster transition of soil microbial communities typical for arable land towards grassland communities. Although some mechanisms underlying the plant diversity effect on soil microorganisms could be identified, future studies have to determine plant traits shaping soil microbial community structure. We suspect differences in root traits among different plant communities, such as root turnover rates and chemical composition of root exudates, to structure soil microbial communities.

Modeling postglacial vegetation dynamics of temperate forests on the Olympic Peninsula (WA, USA) with special regard to snowpack

Past and future forest composition and distribution in temperate mountain ranges is strongly influenced by temperature and snowpack. We used LANDCLIM, a spatially explicit, dynamic vegetation model, to simulate forest dynamics for the last 16,000 years and compared the simulation results to pollen and macrofossil records at five sites on the Olympic Peninsula (Washington, USA). To address the hydrological effects of climate-driven variations in snowpack on simulated forest dynamics, we added a simple snow accumulation-and-melt module to the vegetation model and compared simulations with and without the module. LANDCLIM produced realistic present-day species composition with respect to elevation and precipitation gradients. Over the last 16,000 years, simulations driven by transient climate data from an atmosphere-ocean general circulation model (AOGCM) and by a chironomid-based temperature reconstruction captured Late-glacial to Late Holocene transitions in forest communities. Overall, the reconstruction-driven vegetation simulations matched observed vegetation changes better than the AOGCM-driven simulations. This study also indicates that forest composition is very sensitive to snowpack-mediated changes in soil moisture. Simulations without the snow module showed a strong effect of snowpack on key bioclimatic variables and species composition at higher elevations. A projected upward shift of the snow line and a decrease in snowpack might lead to drastic changes in mountain forests composition and even a shift to dry meadows due to insufficient moisture availability in shallow alpine soils.