Spatial analysis of crop rotation practice in North-western Germany
von Susanne Stein
Datum der mündl. Prüfung:2020-07-14
Betreuer:Dr. Horst-Henning Steinmann
Gutachter:Prof. Dr. Johannes Isselstein
Gutachter:Dr. Horst-Henning Steinmann
EnglischThe aim of the present study was to detect patterns of crop rotation in an agricultural region in the North-western part of Germany. It was analysed if and how the spatial distribution of the crop rotation patterns depends on selected ecological and economical site variables. The question arises in the light of the fast increase of maize acreage due to a booming biogas production. This was a data-based study using crop information of all arable fields in Lower Saxony which were funded with direct payments of the European Union agricultural fund during the years 2005 till 2011. Information about the related farm was not included. For the spatial localization only the digital field map of the year 2011 was available. Due to that, fields which changed their size and frame and so changing their identification number were not detectable over all seven years. However, about 24% of the arable parcels (122,956 records) could be used for complete seven-year sequence analysis. In a first step, before analysing crop rotations, the field data of the year 2011 were used to enlighten the relationship of crops with selected site variables. A logistic regression analysis was used to build spatial clusters of crop patterns which were compared with clusters of the following site variables: arable farming potential, soil texture, slope, precipitation, biotope density, grassland proportion, cattle density, pig and poultry density and farm size. The comparison showed a stronger relationship of clustered crop pattern with clustered site pattern than the single crop-site relationship. Maize and Winter wheat showed the clearest relation to site variables, especially the soil variables, but with diverging preferences. To reveal crop rotation patterns out of the wealth of crop sequences a typification method was developed. This typification approach allows to group the crop sequences in two steps, i) by their number of different crops and their number of transitions from one crop to another, ii) by their amount of leaf crops and their amount of spring sown crops. The first step addressed the structural aspects of the sequences and the second addressed the arable functions of the crops in a rotation. The ten largest groups of crop sequence types derived by this method were cropped on 60% of the investigated arable area. Among these ten types we found types of low structural and functional diversity as well as the most diverse types in significant extent. The largest type group (9.6%) contains crop sequences with four crops and 6-5 transitions in seven years as well as 1-3 leaf crops and 1-4 spring crops. The second largest type group represents sequences which were permanently cropped with one cereal spring sown crop (8.1%), this was maize here, actually. So, in Lower Saxony we found both ends of the scale in a significant amount, the highly diverse crop sequences as well as the sequences of continuous maize cropping. Maize dominated the most simple sequences but played also an important role for the most diverse sequences and for the diversification of pure winter crop stands. In the Geest region in Lower Saxony a number of rotation pattern with pure cereal crop sequences showed that maize took the role of the winter leaf crop (Oil seed rape) in the rotation, e.g. Maize-Winter Wheat-Winter Barley. One third of the arable area was cropped with sequences with a moderate amount of leaf crops (1-3) and spring crops (1-4), but nearly 40% showed any leaf crop and 20% any spring crop. So, Lower Saxony showed a pleasingly high amount of diverse crop sequences on the one hand but on the other hand we had nearly one third of the arable area cropped with only one or two crops, which is alarming. The latter were strongly linked with a high cattle density and peaty soils. Generally, the ten largest types showed specific relationships with the site variables and a spatial distribution related to the distribution of the soil conditions in Lower Saxony. This allows the conclusion that the crop rotation practice in Lower Saxony is related to the site condition in the respective regions. The spatial distribution of the clustered crop patterns of one year showed concordance at the first view with the crop sequence patterns of the seven years. So, the third part of the study examined the spatial congruency of the seven-year sequence data with the field data from one year in a defined area around that sequence. All arable fields in one 2x2 km quadrant of a raster were compared with the temporal crop sequences within this quadrant, according to their amount of leaf crops and spring crops (equivalent to the second typification step). This analysis showed an overestimation of the amount of the diverse crop sequence types and an underestimation of the amount of simple crop sequence types in the one-year field data in comparison with the actual crop sequences. This applies in particular for regions with heterogenous crop patterns. So, the one-year crop statistic, which is commonly used to derive the actual crop rotations, is not a proper data source in any case. Summarizing the results of the data analysis it can be stated that most of the farmers in Lower Saxony grow their crops in patterns which are inspired by crop rotation rules and used in relation to the site conditions. Regions with less fertile soils and mixed farming are more heterogenous than regions with very low or very high profitable soils. There is the dense maize cropping of the livestock farming regions as well as the pure winter cereal rotations in the coast regions which may lead to phytosanitary problems in the future if no measures of diversification are implemented. Due to biogas production, the dense maize rotations are no longer only an issue for intensive livestock farming regions. It is important to strengthen the development and market conditions for neglected crops, especially legumes and summer cereals, to enhance the diversification of crop rotations in future.
Keywords: crop rotation; Lower Saxony; Maize; LPIS; IACS; spatial data