Ragnhild Sperstad

Lead Engineer

(+47) 476 34 369
ragnhild.sperstad@nibio.no

Place
Ås O43

Visiting address
Oluf Thesens vei 43, 1433 Ås

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Abstract

This paper reports soil development over time in different climates, on time-scales ranging from a few thousand to several hundred thousand years. Changes in soil properties over time, underlying soil-forming processes and their rates are presented. The paper is based on six soil chronosequences, i.e. sequences of soils of different age that are supposed to have developed under the similar conditions with regard to climate, vegetation and other living organisms, relief and parent material. The six soil chronosequences are from humid-temperate, Mediterranean and semi-arid climates. They are compared with regard to soil thickness increase, changes in soil pH, formation of pedogenic iron oxides (expressed as Fed/Fet ratios), clay formation, dust influx (both reflected in clay/silt ratios), and silicate weathering and leaching of base cations (expressed as (Ca+Mg+K+Na)/Al molar ratios) over time. This comparison reveals that the increase of solum thickness with time can be best described by logarithmic equations in all three types of climates. Fed/Fet ratios (proportion of pedogenic iron Fed compared to total iron Fet) reflects the transformation of iron in primary minerals into pedogenic iron. This ratio usually increases with time, except for regions, where the influx of dust (having low Fed/Fet ratios) prevails over the process of pedogenic iron oxide formation, which is the case in the Patagonian chronosequences. Dust influx has also a substantial influence on the time courses of clay/silt ratios and on element indices of silicate weathering. Using the example of a 730 ka soil chronosequence from southern Italy, the fact that soils of long chronosequences inevitably experienced major environmental changes is demonstrated, and, consequentially a modified definition of requirements for soil chronosequences is suggested. Moreover, pedogenic thresholds, feedback systems and progressive versus regressive processes identified in the soil chronosequences are discussed.

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Abstract

The first results of modeling soil development in marine sediments in S Norway using the model SoilGen are compared to measured properties of two soil chronosequences, on the western and eastern side of Oslofjord, respectively. The aim of this work is to test how well soil development under well-defined environmental conditions can be modeled. Such testing reveals to what degree soil-forming processes are understood, allowing formulation of adequate calculations reflecting these processes. The model predicts particle size distribution reasonably well, although clay depletion in the upper parts of the soils as a result of clay migration is overestimated. The model tends to underestimate contents of organic carbon and CEC in the A horizons: below, modeled CEC matches well with measured CEC. Base saturation is overestimated in the upper 40 cm and underestimated below. Apparently, leaching of bases proceeds less rapidly in reality than is predicted by the model, due to strong soil structure of the B horizons, causing preferential flow and base leaching around the aggregates, whereas bases inside the aggregates are only slightly affected by leaching. Difficulties and possibilities for improvements are identified, some related to model input data and some to the model itself. Input data could be improved by determining the amounts of organic carbon in organic surface horizons and by quantifying effects of bioturbation. A big challenge is the implementation of soil structure formation in the model. Quantitative data on the development of soil structure with time that can be included in a model are required. Amounts, distribution and connectivity of macro pores need to be defined for each stage of soil development, and zones of low and high base leaching need to be distinguished in the model for each time step. The long-term aim of this work is to model soil development with different sets of soil-forming factors, e.g. different climatic conditions in order to reliably predict soil development under different climate scenarios and related sets of soil-forming factors. The results of the first model runs and the identified possible improvements suggest that this aim is generally achievable.