Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.

Seasonal Geophysical Monitoring of Biogenic Gases in a Northern Peatland: Implications for Temporal and Spatial Variability in Free Phase Gas Production Rates

A set of high resolution surface ground penetrating radar (GPR) surveys, combined with elevation rod ( to monitor surface deformation) and gas flux measurements, were used to investigate in situ biogenic gas dynamics within a northern peatland (Caribou Bog, Maine). Gas production rates were directly estimated from the time series of GPR measurements. Spatial variability in gas production was also investigated by comparing two sites with different geological and ecological attributes, showing differences and/or similarities depending on season. One site characterized by thick highly humified peat deposits (5-6 m), wooded heath vegetation and open pools showed large ebullition events during the summer season, with estimated emissions (based on an assumed range of CH(4) concentration) between 100 and 172 g CH(4) m(-2) during a single event. The other site characterized by thinner less humified peat deposits (2-3 m) and shrub vegetation showed much smaller ebullition events during the same season (between 13 and 23 g CH(4) m(-2)). A consistent period of free-phase gas (FPG) accumulation during the fall and winter, enhanced by the frozen surficial peat acting as a confining layer, was followed by a decrease in FPG after the snow/ice melt that released estimated fluxes between 100 and 200 g CH(4) m(-2) from both sites. Estimated FPG production rates during periods of biogenic gas accumulation ranged between 0.22 and 2.00 g CH(4) m(3) d(-1) and reflected strong seasonal and spatial variability associated with differences in temperature, peat soil properties, and/or depositional attributes (e. g., stratigraphy). Periods of decreased atmospheric pressure coincided with short-period increases in biogenic gas flux, including a very rapid decrease in FPG content associated with an ebullition event that released an estimated 39 and 67 g CH(4) m(-2) in less than 3.5 hours. These results provide insights into the spatial and seasonal variability in production and emission of biogenic gases from northern peatlands.

Spatial Patterns in Seasonal and Interannual Variability of Chlorophyll and Sea Surface Temperature in the California Current

Physical forcing and biological response within the California Current System (CCS) are highly variable over a wide range of scales. Satellite remote sensing offers the only feasible means of quantifying this variability over the full extent of the CCS. Using six years (1997-2003) of daily SST and chlorophyll imagery, we map the spatial dependence of dominant temporal variability at resolutions sufficient to identify recurrent mesoscale circulation and local pattern associated with coastal topography. Here we describe mean seasonal cycles and interannual variation; intraseasonal variability is left to a companion paper ( K. R. Legaard and A. C. Thomas, manuscript in preparation, 2006). Coastal upwelling dictates seasonality along north-central California, where weak cycles of SST fluctuate between spring minima and late summer maxima and chlorophyll peaks in early summer. Off northern California, chlorophyll maxima are bounded offshore by the seasonally recurrent upwelling jet. Seasonal cycles differ across higher latitudes and in the midlatitude Southern California Bight, where upwelling winds are less vigorous and/or persistent. Seasonality along south-central Baja is strongly affected by processes other than upwelling, despite year-round upwelling-favorable winds. Interannual variation is generally dominated by El Nino and La Nina conditions. Interannual SST variance is greatest along south-central Baja, although interannual variability constitutes a greater fraction of total variance inshore along southern Oregon and much of California. Patterns of interannual chlorophyll variance are consistent with dominant forcing through the widespread depression and elevation of the nutricline during El Nino and La Nina, respectively. Interannual variability constitutes a greater fraction of total chlorophyll variance offshore.

Spatial Patterns of Intraseasonal Variability of Chlorophyll and Sea Surface Temperature in the California Current

Six years of daily satellite data are used to quantify and map intraseasonal variability of chlorophyll and sea surface temperature (SST) in the California Current. We define intraseasonal variability as temporal variation remaining after removal of interannual variability and stationary seasonal cycles. Semivariograms are used to quantify the temporal structure of residual time series. Empirical orthogonal function (EOF) analyses of semivariograms calculated across the region isolate dominant scales and corresponding spatial patterns of intraseasonal variability. The mode 1 EOFs for both chlorophyll and SST semivariograms indicate a dominant timescale of similar to 60 days. Spatial amplitudes and patterns of intraseasonal variance derived from mode 1 suggest dominant forcing of intraseasonal variability through distortion of large scale chlorophyll and SST gradients by mesoscale circulation. Intraseasonal SST variance is greatest off southern Baja and along southern Oregon and northern California. Chlorophyll variance is greatest over the shelf and slope, with elevated values closely confined to the Baja shelf and extending farthest from shore off California and the Pacific Northwest. Intraseasonal contributions to total SST variability are strongest near upwelling centers off southern Oregon and northern California, where seasonal contributions are weak. Intraseasonal variability accounts for the majority of total chlorophyll variance in most inshore areas save for southern Baja, where seasonal cycles dominate. Contributions of higher EOF modes to semivariogram structure indicate the degree to which intraseasonal variability is shifted to shorter timescales in certain areas. Comparisons of satellite-derived SST semivariograms to those calculated from co-located and concurrent buoy SST time series show similar features.

Soil, snow, weather, and sub-surface storage data from a mountain catchment in the rain-snow transition zone

A comprehensive hydroclimatic data set is presented for the 2011 water year to improve understanding of hydrologic processes in the rain-snow transition zone. This type of dataset is extremely rare in scientific literature because of the quality and quantity of soil depth, soil texture, soil moisture, and soil temperature data. Standard meteorological and snow cover data for the entire 2011 water year are included, which include several rain-on-snow events. Surface soil textures and soil depths from 57 points are presented as well as soil texture profiles from 14 points. Meteorological data include continuous hourly shielded, unshielded, and wind corrected precipitation, wind speed, air temperature, relative humidity, dew point temperature, and incoming solar and thermal radiation data. Sub-surface data included are hourly soil moisture data from multiple depths from 7 soil profiles within the catchment, and soil temperatures from multiple depths from 2 soil profiles. Hydrologic response data include hourly stream discharge from the catchment outlet weir, continuous snow depths from one location, intermittent snow depths from 5 locations, and snow depth and density data from ten weekly snow surveys. Though it represents only a single water year, the presentation of both above and below ground hydrologic condition makes it one of the most detailed and complete hydro-climatic datasets from the climatically sensitive rain-snow transition zone for a wide range of modeling and descriptive studies.

Spatial distribution of isotopic compositions of Globigerina bulloides and Neogloboquadrina pachyderma (dex.) and the faunal assemblages of planktic foraminifera in surface sediment samples along the Chilean continental slope between 23°S and 44°S

We report on the spatial distribution of isotopic compositions of the two planktic foraminifera species Globigerina bulloides and Neogloboquadrina pachyderma (dex.), and the faunal assemblages of planktic foraminifera in 91 surface sediment samples along the Chilean continental slope between 23°S and 44°S. Both d13C and d18O data of N. pachyderma (dex.) show little variability in the study area. North of 39°S, the isotopic values of N. pachyderma (dex.) are heavier than those of G. bulloides, whereas south of 39°S, this relation inverses. This is indicative for a change from a well-mixed, deep thermocline caused by coastal upwelling north of 39°S to well-stratified water masses in a non-upwelling environment south of 39°S. In addition, the faunal composition of planktic foraminifera marks this change by transition from an upwelling assemblage north of 39°S to a high-nutrient-non-upwelling assemblage south of 39°S, which is characterized by decreased contributions of upwelling indicators such as G. bulloides, N. pachyderma (sin.), and Globigerinita glutinata. In general, we can conclude that food and light rather than temperature are the primary control of the planktic foraminiferal assemblage between 23°S and 44°S off Chile. Our data point to higher marine productivity at upwelling centers north of 25°S and at 30-33°S. South of 39°S, significant supply of nutrients by fluvial input most likely boosts the productivity.

Surface temperature measurements near Ny-Ålesund, Svalbard, Norway in 2008 with links to data files

The ground surface temperature is one of the key parameters that determine the thermal regime of permafrost soils in arctic regions. Due to remoteness of most permafrost areas, monitoring of the land surface temperature (LST) through remote sensing is desirable. However, suitable satellite platforms such as MODIS provide spatial resolutions, that cannot resolve the considerable small-scale heterogeneity of the surface conditions characteristic for many permafrost areas. This study investigates the spatial variability of summer surface temperatures of high-arctic tundra on Svalbard, Norway. A thermal imaging system mounted on a mast facilitates continuous monitoring of approximately 100 x 100 m of tundra with a wide variability of different surface covers and soil moisture conditions over the entire summer season from the snow melt until fall. The net radiation is found to be a control parameter for the differences in surface temperature between wet and dry areas. Under clear-sky conditions in July, the differences in surface temperature between wet and dry areas reach up to 10K. The spatial differences reduce strongly in weekly averages of the surface temperature, which are relevant for the soil temperature evolution of deeper layers. Nevertheless, a considerable variability remains, with maximum differences between wet and dry areas of 3 to 4K. Furthermore, the pattern of snow patches and snow-free areas during snow melt in July causes even greater differences of more than 10K in the weekly averages. Towards the end of the summer season, the differences in surface temperature gradually diminish. Due to the pronounced spatial variability in July, the accumulated degree-day totals of the snow-free period can differ by more than 60% throughout the study area. The terrestrial observations from the thermal imaging system are compared to measurements of the land surface temperature from the MODIS sensor. During periods with frequent clear-sky conditions and thus a high density of satellite data, weekly averages calculated from the thermal imaging system and from MODIS LST agree within less than 2K. Larger deviations occur when prolonged cloudy periods prevent satellite measurements. Futhermore, the employed MODIS L2 LST data set contains a number of strongly biased measurements, which suggest an admixing of cloud top temperatures. We conclude that a reliable gap filling procedure to moderate the impact of prolonged cloudy periods would be of high value for a future LST-based permafrost monitoring scheme. The occurrence of sustained subpixel variability of the summer surface temperature is a complicating factor, whose impact needs to be assessed further in conjunction with other spatially variable parameters such as the snow cover and soil properties.

Heat fluxes and surface radiation measurements from Samoylov Island, Lena Delta, Siberia, April to September 2007

In this article, we present a study on the surface energy balance of a polygonal tundra landscape in northeast Siberia. The study was performed during half-year periods from April to September in each of 2007 and 2008. The surface energy balance is obtained from independent measurements of the net radiation, the turbulent heat fluxes, and the ground heat flux at several sites. Short-wave radiation is the dominant factor controlling the magnitude of all the other components of the surface energy balance during the entire observation period. About 50% of the available net radiation is consumed by the latent heat flux, while the sensible and the ground heat flux are each around 20 to 30%. The ground heat flux is mainly consumed by active layer thawing. About 60% of the energy storage in the ground is attributed to the phase change of soil water. The remainder is used for soil warming down to a depth of 15 m. In particular, the controlling factors for the surface energy partitioning are snow cover, cloud cover, and the temperature gradient in the soil. The thin snow cover melts within a few days, during which the equivalent of about 20% of the snow-water evaporates or sublimates. Surface temperature differences of the heterogeneous landscape indicate spatial variabilities of sensible and latent heat fluxes, which are verified by measurements. However, spatial differences in the partitioning between sensible and latent heat flux are only measured during conditions of high radiative forcing, which only occur occasionally.