Soil Polygons Research Articles

Topographic and bioclimatic controls on soil/paleosol morphogenesis in the Norra Storfjället Mountains, Sweden

Retreat of the Stabre Glacier in the Norra Storfjället Mountains of northern Sweden led to the emplacement of a broad expanse of glaciofluvial sediment, a virtual blanket of debris interspersed with recessional and push moraines. Episodic mass wasting of the glaciofluvial, moraine and loessic deposits yielded a pedostratigraphic succession of 14C-dated sub-Boreal and sub-Atlantic Cryosols in soliflucted sediment that provide weathering data related to Neoglacial perturbations, whereas weathering within polygonal complexes yielded single profile, one event, Cryosolic Gleysols of similar age. Both provide a database of paleosol extremes controlled by topography and bioclimate. Together, the paleosols provide a database of weathering of mixed amphibolitic gneiss, trachytic lavas and granite weathering under two variable redox conditions, one (soliflucted sediment) fully or partially aerated and free draining under a subaerial atmosphere with high redox potential; the other (polygonal soil) partly reduced under the influence of an active layer of sporadic permafrost. Paleosols dated to the Early Neoglacial (~3600–4200cal14CyrBP) have variable horizon development dependent upon landform associations, and provide maximum ages for the second oldest moraine stillstand of ice retreat into the highlands on the Arctic Circle of Sweden. The Cryosolic Gleysol yields surprisingly high extractable Fe and Al suggestive of considerable redox fluctuations over the time of morphogenesis.

Spatial disaggregation of complex soil map units: A decision-tree based approach in Bavarian forest soils

Detailed knowledge on the spatial distribution of soils is crucial for environmental monitoring, management, and modeling. However soil maps with a finite number of discrete soil map units are often the only available information about soils. Depending on the map scale or the detailing of the map legend this information could be too imprecise. We present a method for the spatial disaggregation of map units, namely the refinement of complex soil map units in which two or more soil types are aggregated. Our aim is to draw new boundaries inside the map polygons to represent a single soil type and no longer a mixture of several soil types. The basic idea for our method is the functional relationship between soil types and topographic position as formulated in the concept of the catena. We use a comprehensive soil profile database and topographic attributes derived from a 10m digital elevation model as input data for the classification of soil types with random forest models. We grouped all complex map units which have the same combination of soil types. Each group of map units is modeled separately. For prediction of the soil types we stratified the soil map into these groups and apply a specific random forest model only to the associated map units. In order to get reliable results we define a threshold for the predicted probabilities at 0.7 to assign a specific soil type. In areas where the probability is below 0.7 for every possible soil type we assign a new class “indifferent” because the model only makes unspecific classification there. Our results show a significant spatial refinement of the original soil polygons. Validation of our predictions was estimated on 1812 independent soil profiles which were collected subsequent to prediction in the field. Field validation gave an overall accuracy of 70%. Map units, in which shallow soils were grouped together with deep soils could be separated best. Also histosols could be predicted successful. Highest error rate were found in map units, in which Gleysoils were grouped together with deep soils or Anthrosols. To check for validity of our results we open the black box random forest model by calculating the variable importance for each predictor variable and plotting response surfaces. We found good confirmations of our hypotheses, that topography has a significant influence on the spatial arrangement of soil types and that these relationships can be used for disaggregation.

Spatially locating soil classes within complex soil polygons – Mapping soil capability for agriculture in Saskatchewan Canada

This paper proposes a simplified approach to mapping soil capability, as defined by the Canada Land Inventory (CLI), based on the hypothesis that the primary determinants of soil capability may be surrogated by Normalized Difference Vegetation Index (NDVI) derived from Earth Observation (EO) data integrated with other biophysical information. A case study in which a Decision Tree classification method with a boosting algorithm was used in spatially locating individual soil capability classes as estimated in the complex symbol of the CLI database was conducted in Saskatchewan Canada. The input metrics used for the classification include the first four principal components of the original NDVI images, phenological parameters, topographic factors, land cover and spatial dependence images. Validation showed high Kappa coefficients for the mapped soil capability classes within homogeneous soil polygons and high R-squares between the mapped soil area and CLI-estimated area within heterogeneous polygons. Results confirm the hypothesis that integrating parameters derived from the Moderate Resolution Imaging Spectro-radiometer (MODIS) 250m time-series Normalized Difference Vegetation Index (NDVI) with ancillary data may serve as a comprehensive tool for classification of soil capability.

Digital Mapping of Soil Drainage Classes Using Multitemporal RADARSAT-1 and ASTER Images and Soil Survey Data

Discriminant analysis classification (DAC) and decision tree classifiers (DTC) were used for digital mapping of soil drainage in the Bras-d’Henri watershed (QC, Canada) using earth observation data (RADARSAT-1 and ASTER) and soil survey dataset. Firstly, a forward stepwise selection was applied to each land use type identified by ASTER image in order to derive an optimal subset of soil drainage class predictors. The classification models were then applied to these subsets for each land use and merged to obtain a digital soil drainage map for the whole watershed. The DTC method provided better classification accuracies (29 to 92%) than the DAC method (33 to 79%) according to the land use type. A similarity measure (S) was used to compare the best digital soil drainage map (DTC) to the conventional soil drainage map. Medium to high similarities (0.6≤S<0.9) were observed for 83% (187 km2) of the study area while 3% of the study area showed very good agreement (S≥0.9). Few soil polygons showed very weak similarities (S<0.3). This study demonstrates the efficiency of combining radar and optical remote sensing data with a representative soil dataset for producing digital maps of soil drainage.

Disaggregation of legacy soil data using area to point kriging for mapping soil organic carbon at the regional scale

Legacy data in the form of soil maps, which often have typical property measurements associated with each polygon, can be an important source of information for digital soil mapping (DSM). Methods of disaggregating such information and using it for quantitative estimation of soil properties by methods such as regression kriging (RK) are needed. Several disaggregation processes have been investigated; preferred methods include those which include consideration of scorpan factors and those which are mass preserving (pycnophylactic) making transitions between different scales of investigation more theoretically sound. Area to point kriging (AtoP kriging) is pycnophylactic and here we investigate its merits for disaggregating legacy data from soil polygon maps. Area to point regression kriging (AtoP RK) which incorporates ancillary data into the disaggregation process was also applied. The AtoP kriging and AtoP RK approaches do not involve collection of new soil measurements and are compared with disaggregation by simple rasterization. Of the disaggregation methods investigated, AtoP RK gave the most accurate predictions of soil organic carbon (SOC) concentrations (smaller mean absolute errors (MAEs) of cross-validation) for disaggregation of soil polygon data across the whole of Northern Ireland.Legacy soil polygon data disaggregated by AtoP kriging and simple rasterization were used in a RK framework for estimating soil organic carbon (SOC) concentrations across the whole of Northern Ireland, using soil sample data from the Tellus survey of Northern Ireland and with other covariates (altitude and airborne radiometric potassium). This allowed direct comparison with previous analysis of the Tellus survey data. Incorporating the legacy data, whether from simple rasterization of the polygons or AtoP kriging, substantially reduced the MAEs of RK compared with previous analyses of the Tellus data. However, using legacy data disaggregated by AtoP kriging in RK resulted in a greater reduction in MAEs. A jack-knife procedure was also performed to determine a suitable number of additional soil samples that would need to be collected for RK of SOC for the whole of Northern Ireland depending on the availability of ancillary data. We recommend i) if only legacy soil polygon map data are available, they should be disaggregated using AtoP kriging, ii) if ancillary data are also available legacy data should be disaggregated using AtoP RK and iii) if new soil measurements are available in addition to ancillary and legacy soil map data, the legacy soil map data should be first disaggregated using AtoP kriging and these data used along with ancillary data as the fixed effects for RK of the new soil measurements.

Carbon sequestration potential of recommended management practices for paddy soils of China, 1980–2050

China's rice paddies, accounting for 19% of the world's total, play an important role in soil carbon (C) sequestration. In order to reduce uncertainties from upscaling spatial processes of the DeNitrification–DeComposition (DNDC) model for improving the understanding of C sequestration under recommended management practices (RMPs), we parameterized the DNDC model with a 1:1,000,000 polygonal soil database to estimate how RMPs influence potential C sequestration of the top 30 cm of Chinese paddy soils and to identify which management practices have the greatest potential to increase soil organic carbon (SOC) in these soils. These practices include reduced/no tillage, increasing crop residue return, and increasing manure applications. A baseline and eleven RMP scenarios were projected from 2009 to 2080, including traditional and conservation tillage, increasing crop residue return, increasing manure incorporation, and the combination of these practices. The results indicated that C sequestration potential under modeled RMPs increased compared to the baseline scenario, and varied greatly from 29.2 to 847.7 Tg C towards the end of the study period with an average rate of 0.7 to 20.2 Tg C yr − 1 . In general, increasing crop residue return was associated with higher rates of C sequestration when compared to increasing manure application or practicing conservation tillage. The simulations demonstrated that the most effective soil C sequestration strategy probably involves the implementation of a combination of RMPs, and that they vary by location.

Updating Conventional Soil Maps through Digital Soil Mapping

Conventional soil maps, as the major data source for information on the spatial variation of soil, are limited in terms of both the level of spatial detail and the accuracy of soil attributes. These soil maps, however, contain valuable knowledge on soil-environment relationships. Such knowledge can be extracted for updating conventional soil maps through the use of available high-quality data on environmental variables and data analysis techniques. We developed a method to update conventional soil maps using digital soil mapping techniques without additional field work, which can be used in situations where the study area contains no or few soil profile descriptions at points. The basis of the method is that soil polygons on a conventional soil map correspond to landscape units, which can be considered as combinations of environmental factors. Such environmental combinations were approximated through fuzzy clustering on the environmental factors. We extracted the knowledge on soil-environment relationships by relating the environmental combinations to the mapped soil types. The extracted knowledge was then used for soil mapping using the Soil Land Inference Model (SoLIM) framework. This method was demonstrated through a case study for updating a conventional 1:20,000 soil map of Wakefield, NB, Canada. The case study showed that the updated digital soil map contained much greater spatial detail than the conventional soil map. Field validation indicated that the accuracy of the updated soil map was much higher than the conventional soil map at the level of soil associations with drainage classes, indicating that the proposed method is an effective approach to updating conventional soil maps.

Regional Simulation of Soil Organic Carbon Dynamics for Dry Farmland in East China by Coupling a 1:500 000 Soil Database with the Century Model

Changes in soil organic carbon (SOC) in agricultural soils influence soil quality and greenhouse gas concentrations in the atmosphere. Dry farmland covers more than 70% of the whole cropland area in China and plays an important role in mitigating carbon dioxide (CO 2) emissions. In this study, 4 109 dry farmland soil polygons were extracted using spatial overlay analysis of the soil layer (1:500 000) and the land use layer (1:500 000) to support Century model simulations of SOC dynamics for dry farmland in Anhui Province, East China from 1980 to 2008. Considering two field-validation sites, the Century model performed relatively well in modeling SOC dynamics for dry farmland in the province. The simulated results showed that the area-weighted mean soil organic carbon density (SOCD) of dry farmland increased from 18.77 Mg C ha −1 in 1980 to 23.99 Mg C ha −1 in 2008 with an average sequestration rate of 0.18 Mg C ha −1 year −1. Approximately 94.9% of the total dry farmland area sequestered carbon while 5.1% had carbon lost. Over the past 29 years, the net SOC gain in dry farmland soils of the province was 19.37 Tg, with an average sequestration rate of 0.67 Tg C year −1. Augmentation of SOC was primarily due to increased consumption of nitrogen fertilizer and farmyard manure. Moreover, SOC dynamics were highly differentiated among dry farmland soil groups. The integration of the Century model with a fine-scale soil database approach could be conveniently utilized as a tool for the accurate simulation of SOC dynamics at the regional scale.

Upper-bound approach for analysis of cantilever retaining walls

The proposed method for the analysis of cantilever retaining walls is based on ultimate limit states, but in contrast to other methods, which are recognized worldwide, also considers the condition of vertical force equilibrium, which includes the wall unit weight and the vertical component of the soil–structure interaction. The two-dimensional analytical model with polygonal soil pressure distribution is based on two new characteristics: the parameter α and the passive pressure coefficient at the embedment depth, Kb. The kinematic approach of limit analysis is used to examine the limit equilibrium state of the cantilever retaining wall according to soil properties and other loadings. The failure mechanism, composed of a classical determination of the passive pressure in the embedded part of the wall and a kinematically admissible velocity field at the retained side of the wall, estimates the limiting value of the passive earth pressure at the embedment depth. The advantage of the proposed method is that it enables the design of more slender cantilever retaining walls, at which the comparable level of safety for geotechnical and structural bearing capacity limit states is reached, which is the basic condition for safe design of retaining structures.

Soil-Web: An online soil survey for California, Arizona, and Nevada

Digital soil survey products represent one of the largest and most comprehensive inventories of soils information currently available. The complex structure of these databases, intensive use of codes and scientific jargon make it difficult for non-specialists to utilize digital soil survey resources. A project was initiated to construct a web-based interface to digital soil survey products (STATSGO and SSURGO) for California, Arizona, and Nevada that would be accessible to the general public. A collection of mature, open source applications (including Mapserver, PostGIS and Apache Web Server) were used as a framework to support data storage, querying, map composition, data presentation, and contextual links to related materials. Application logic was written in the PHP language to “glue” together the many components of an online soil survey. A comprehensive website ( http://casoilresource.lawr.ucdavis.edu/map) was created to facilitate access to digital soil survey databases through several interfaces including: interactive map, Google Earth and HTTP-based application programming interface (API). Each soil polygon is linked to a map unit summary page, which includes links to soil component summary pages. The most commonly used soil properties, land interpretations and ratings are presented. Graphical and tabular summaries of soil profile information are dynamically created, and aid with rapid assessment of key soil properties. Quick links to official series descriptions (OSD) and other such information are presented. All terminology is linked back to the USDA-NRCS Soil Survey Handbook which contains extended definitions. The Google Earth interface to Soil-Web can be used to explore soils information in three dimensions. A flexible web API was implemented to allow advanced users of soils information to access our website via simple web page requests. Soil-Web has been successfully used in soil science curriculum, outreach activities, and current research projects. Although not the only online soil survey application, Soil-Web remains the simplest and most rapid means of accessing soils information for California, Arizona, and Nevada.

Soil Scientists Revisit a High-Intensity Soil Survey in Northwest Illinois with Electromagnetic Induction and Traditional Methods

Electromagnetic induction (EMI) and global positioning system (GPS) data were used with geographical information system (GIS) to improve a high intensity soil survey that was completed with traditional methods in northwest Illinois. Apparent conductivity (ECa) maps provided additional layers of information, which improved knowledge of soils and directed soil sampling. The information provided by ECa maps and additional soil sampling led soil scientists to recognize different soils and modify mapping concepts. Within the site, ECa maps assisted the identification and delineation of soil polygons and improved the quality of the high-intensity soil map. White spatial ECa patterns influenced the judgments of soil scientists, ECa maps were not accepted as a substitute for a high-intensity soil map.

Mapping soils using the fuzzy approach and regression-kriging case study from the Považský Inovec Mountains, Slovakia

The paper introduces a method of digital mapping of spatial distribution of soil typological units. It implements fuzzy k-means to classify the soil profile data (study area from the Považský Inovec Mountains, Slovakia) and regression-kriging with the selected digital terrain and remote sensing data to draw membership maps of soil typological units. Totally three soil typological units were identified: Haplic Cambisols (Skeletic, Dystric), Albic Stagnic Luvisols, and Haplic Stagnosols (Albic, Dystric). We analysed the membership values to these units with respect to terrain and remote sensing data. The membership values appeared as spatially smoothly dependant on the terrain gradients (linearly or exponentially) whereas the residua showed spatial autocorrelation. Based on regression and kriging analyses, the regression-kriging model was successfully deployed to draw raster membership maps. These maps yield coefficients of determination between R<sup>2</sup> = 56% (Albic Stagnic Luvisols) to R<sup>2</sup>= 79% (Haplic Cambisols (Skeletic, Dystric)) when evaluated by cross validation. The grid-based continuous soil map represents an alternative to the classical polygon soil maps and can offer a wide range of interpretations for landscape studies.

Patterns of bacterial diversity across a range of Antarctic terrestrial habitats

Although soil-borne bacteria represent the world's greatest source of biological diversity, it is not well understood whether extreme environmental conditions, such as those found in Antarctic habitats, result in reduced soil-borne microbial diversity. To address this issue, patterns of bacterial diversity were studied in soils sampled along a > 3200 km southern polar transect spanning a gradient of increased climate severity over 27 degrees of latitude. Vegetated and fell-field plots were sampled at the Falkland (51 degrees S), South Georgia (54 degrees S), Signy (60 degrees S) and Anchorage Islands (67 degrees S), while bare frost-sorted soil polygons were examined at Fossil Bluff (71 degrees S), Mars Oasis (72 degrees S), Coal Nunatak (72 degrees S) and the Ellsworth Mountains (78 degrees S). Bacterial 16S rRNA gene sequences were recovered subsequent to direct DNA extraction from soil, polymerase chain reaction amplification and cloning. Although bacterial diversity was observed to decline with increased latitude, habitat-specific patterns appeared to also be important. Namely, a negative relationship was found between bacterial diversity and latitude for fell-field soils, but no such pattern was observed for vegetated sites. The Mars Oasis site, previously identified as a biodiversity hotspot within this region, proved exceptional within the study transect, with unusually high bacterial diversity. In independent analyses, geographical distance and vegetation cover were found to significantly influence bacterial community composition. These results provide insight into the factors shaping the composition of bacterial communities in Antarctic terrestrial habitats and support the notion that bacterial diversity declines with increased climatic severity.

The cyanobacterial community of polygon soils at an inland Antarctic nunatak

Inland Antarctic terrestrial ecosystems and biodiversity are poorly understood in comparison with Antarctic coastal regions. Microorganisms, as primary colonists, are integral to Antarctic soil ecosystem development, essential for pedogenesis and structuring the soil, and providing the nutrients necessary for the subsequent establishment of macroorganisms. This study analysed the microbial communities present in polygon soils of Coal Nunatak (Alexander Island, at the southern limit of the maritime Antarctic). Soils were analysed across three polygons (centre and margins) and at three depths (0–1, 1–2, 2–5 cm). Cyanobacterial communities were characterised using two complementary molecular biological approaches, temperature gradient gel electrophoresis and clone library analysis. The three polygons exhibited conspicuous differences in community composition, both between different polygons and spatially (horizontally and vertically) within a single polygon. Comparison of our data with that from previous studies using classical culture and morphological identification techniques clearly shows the need for more intensive research on patterns of microbial diversity in terrestrial habitats throughout the Antarctic. The majority of the 17 cyanobacterial genera identified at Coal Nunatak are thought to have ubiquitous distributions, while none are known only from the Antarctic. Three of the genera present are also known to be capable of being lichen photobionts.

Residual soil nitrogen indicator for agricultural land in Canada

Residual soil nitrogen (RSN) is the amount of inorganic nitrogen that remains in the soil at the end of the growing season after crops have been harvested. RSN is an estimate of this quantity, calculated as the difference between all N inputs (fertilizer, manure-N, biological fixation, and atmospheric deposition) and all N outputs (N removed in crop harvest, N lost from ammonia volatilization and N lost from denitrification) assuming that mineralization and immobilization are generally balanced. RSN was calculated on a soil polygon level (scale 1:1 million) as well as on provincial and national levels for each of the 5 census years from 1981 to 2001. The Canadian average RSN values from 1981 to 1996 were fairly constant with a range of 12.9 to 13.9 kg N ha-1. However, RSN increased by 51% from 13.9 kg N ha-1 in 1996 to 21.0 kg N ha-1 in 2001. This dramatic increase was due to several factors including an increase in legume crop acreage (i.e., increased biological N2 fixation) and lower crop yields and reduced N uptake as a result of climatic constraints (droughts) which were prevalent in many regions in Canada in 2001. Key words: Nitrate, residual nitrogen, nitrogen balance, N indicator

A flexible approach to managing variability in grain yield and nitrate leaching at within-field to farm scales

We up-scaled the APSIM simulation model of crop growth, water and nitrogen dynamics to interpret and respond to spatial and temporal variations in soil, season and crop performance and improve yield and decrease nitrate leaching. Grain yields, drainage below the maximum root depth and nitrate leaching are strongly governed by interaction of plant available soil water storage capacity (PAWC), seasonal rainfall and nitrogen supply in the water-limited Mediterranean-type environment of Western Australia (WA). APSIM simulates the interaction of these key system parameters and the robustness of its simulations has been rigorously tested with the results of several field experiments covering a range of soil types and seasonal conditions in WA. We used yield maps, soil and weather data for farms at two locations in WA to determine spatial and temporal patterns of grain yield, drainage below the maximum root depth and nitrate leaching under a range of weather, soil and nitrogen management scenarios. On one farm, we up-scaled APSIM simulations across the whole farm using local weather and fertiliser use data and the average PAWC values of soil type polygons. On a 70 ha field on another farm, we used a linear regression of apparent soil electrical conductivity (ECa) measured by EM38 against PAWC to transform an ECa map of the field into a high resolution (5 m grid) PAWC map. We then used regressions of simulated yields, drainage below the maximum root depth and nitrate leaching on PAWC to upscale the APSIM simulations for a range of weather and fertiliser management scenarios. This continuous mapping approach overcame the weakness of the soil polygons approach, which assumed uniformity in soil properties and processes within soil type polygons. It identified areas at greatest financial and environmental risks across the field, which required focused management and simulated their response to management interventions. Splitting nitrogen applications increased simulated wheat yields at all sites across the field and decreased nitrate leaching particularly where the water storage capacity of the soil was small. Low water storage capacity resulted in both low wheat yields and large leaching loss. Another management option to decrease leaching may be to grow perennial vegetation that uses more water and loses less by drainage.

Prehistoric exploitation of Grevena highland zones: hunters and herders along the Pindus chain of western Macedonia (Greece)

The surveys and excavations carried out in the highland zone of the Grevena Pindus Mountains have revealed that the watershed that separates western Macedonia from Epirus was (seasonally) inhabited in different prehistoric times, from the Middle Palaeolithic to the Bronze Age. The highest concentration of ‘sites’ is known from the surroundings of the modern village of Samarina, which is rich in good-quality chert raw material outcrops. This territory is still nowadays heavily exploited by Vlach shepherds who seasonally carry out pastoral activities, moving their flocks from the eastern lowlands up to the high-altitude pastures. The excavations carried out at three different sites, all lying on a flysch substratum, revealed the presence of a redeposited lower sediment, characterized by a polygonal soil caused by ground freezing that was later effected by erosion canals produced by human interference in the landscape. The results so far obtained from a few charcoal radiocarbon dates indicate that this fact took place in at least three different periods from the middle Bronze Age to the seventh century ad.

La végétation des sols polygonaux aux étages alpin supérieur et subnival en Valais (Alpes centro-occidentales, Suisse)

Beguin Cl., Progin Sonney M. and Vonlanthen M. 2006. The vegetation of polygonal soils at the upper alpine and subnival belts in Switzerland. Bot. Helv. 116: 41–54. Polygonal soils are typical formations of arctic regions but occur locally at high elevation in the Alps. A vegetation survey of sites with polygonal patterning of soils in the Western Swiss Alps revealed a clear distinction between (1) periglacial polygonal soils, whose structure is created by frost action, and whose occurrence is limited to the subniveal belt (2700–3000 m a.s.l.) and (2) soils whose polygonal structures are mere contraction cracks created by desiccation, which are found in the alpine belt (2300–2750 m a.s.l). Two new plant associations characteristic of these sites are described: periglacial polygonal soils of the subniveal belt are colonized by the association Saxifrago oppositifoliae- Poetum alpinae ass. nov. of the alliance Drabion hoppeanae. Conversely, soils with polygonal contraction cracks shelter the association Epilobio anagallidifolii- Saginetum saginoidis ass. nov., which is related to the alliance Salicion herbaceae. We describe the particular geomorphological and climatic factors leading to the local formation of these soil types with their specialised vegetation. We conclude that their future existence is strongly threatened by climate warming.

VARIATION IN BIOGEOCHEMISTRY AND SOIL BIODIVERSITY ACROSS SPATIAL SCALES IN A POLAR DESERT ECOSYSTEM

Desert ecosystems are characterized by distinct spatial patterning in soil biogeochemistry and biodiversity. In the Antarctic Dry Valleys, soil polygons are prominent features of the landscape and may be key units for scaling local ecological information to the greater region. We examined polygon soils in each of the three basins of Taylor Valley, Antarctica. Our objectives were to characterize variability in soil biogeochemistry and biodiversity at local to regional scales, and to test the influence of soil properties upon invertebrate communities. We found that soil biogeochemical properties and biodiversity vary over multiple spatial scales from fine (<10 m) to broad (>10 km) scales. Differences in biogeochemistry were most pronounced at broad scales among the major lake basins of Taylor Valley corresponding to differences in geology and microclimate, while variation in invertebrate biodiversity and abundance occurred at landscape scales of 10–500 m, and within individual soil polygons. Variation in biogeochemistry and invertebrate communities across these scales reflects the influence of physical processes and landscape development over ecosystem structure in the dry valleys. The development of soil polygons influences the spatial patterning of soil properties such as soil organic matter, salinity, moisture, and invertebrate habitat suitability. Nematode abundance and life history data indicate that polygon interiors are more suitable habitats than soils in the troughs at the edges of polygons. These data suggest that physical processes (i.e., polygon development) and biogeochemistry are important influences on the spatial variability of biotic communities in dry valley soil ecosystems.

Seasonal periodicity of physical factors, inorganic nutrients and microalgae in Antarctic fellfields

Over 15 months between January 1990 and March 1991, a range of physical, chemical and biological parameters was monitored regularly in fellfield soils of frost-sorted polygons at four sites on Signy Island (South Orkney Islands, maritime Antarctica). These included inorganic nutrients (orthophosphate, available nitrate and, over a more limited period, ammonia), chlorophyll a (as a proxy measure of microalgal biomass) and a range of potential cryoprotectant compounds. Transects across soil polygons revealed neither intrapolygon gradients in concentrations of inorganic nutrients or chlorophyll a nor significant interpolygon differences, in contrast with previous studies. Nitrate was present in much lower concentrations than phosphate, supporting evidence that it is a limiting nutrient in these fellfield ecosystems. Spring snowmelt, although a potential source of nutrient input, was not associated with increased concentrations of inorganic nutrients in the soil, probably through isolation of the soil from overlaying snow by a surface layer of ice. Soil microalgae at the study sites must survive winter temperatures of at least −9°C, even when protected beneath up to 1 m of snow, and it has been proposed that they accumulate sugars and polyols as cryoprotectants. In support of this, concentrations of erythritol, glycerol, glucose, sucrose and trehalose in the soil (both absolute quantity and after correction for chlorophyll a concentration) increased as winter proceeded, suggesting that changes in sugar concentrations were due to accumulation within individual cells.