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Landscape research focuses on the often complex interplay between various landscape elements, integrating methods and expertise from different scientific disciplines, and considering long-term effects. To that end, ZALF started joint research and monitoring activities in the Quillow region, about 90 km north of Berlin, in the 1990s. Here arable fields prevail, but forested areas, wetlands and small lakes are quite abundant as well. The ZALF activities have since then been subsequently extended and continue doing so, covering aspects of agronomy, soil science, hydrology, biology and microbiology, socio-economics etc. at different temporal and spatial scales.

The study area comprises the Quillow catchment in Northeast Germany. The Quillow catchment has an area of about 170 km2 upstream of the confluence with the Strom stream which drains the adjacent catchment in the south. The topography is characterized by gently rolling hills, a so-called hummocky landscape. Altitude decreases from 110 m a.s.l. in the western part of the catchment, which is dominated by terminal moraines, to 20 m a.s.l. in the east, that is, the glacial valley of the receiving Ucker River close to the town of Prenzlau.

Climate

Meteorological data are available from the Dedelow Research Station in the northern part of the catchment. Mean values for the 1992–2013 periods were 8.6 °C for air temperature, and 563.8 mm of precipitation per year, corrected for wind and evaporation error.

Geology and geomorphology

The landscape has been massively reshaped during repeated advances and retreats of glaciation during the Pleistocene. This resulted in a complex setting of unconsolidated sediments with high textural heterogeneity. The sediments form a series of layered Pleistocene and Tertiary aquifers of about 100–150 m thickness with a 50-m-thick Oligocene marine clay layer as a lower confining bed. The complete series consists of permeable marine dominated sediments of upper Oligocene and the lower Miocene with a complex interplay between glacial deposits of the Pleistocene with a vertical extent of more than 100 m. These deposits, dominated by sediments from the main glaciations (Elster, Saalian and Weichselian), can be divided into different aquifers separated by till layers.

Topography and the related stream network are still far from maturity. Besides some large lakes, numerous small lakes and wetlands developed in drainless depressions. These natural ponds (<1 ha area each) are called kettle holes (Kalettka and Rudat 2006).

Soils

MyTitle: Soils
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MyTextfeld: <div class="ExternalClass97B28D2623B145F69968FD67721DBDCA"><p>The soil pattern of the Quillow catchment is related to topography and the heterogeneity of Pleistocenic deposits. Since the last centuries the natural soil pattern has been strongly modified by soil erosion (tillage, water) (Sommer et al. 2008, Gerke et al. 2012, Gerke et al. 2016, Koszinksi et al. 2013). Recently, only 20% of the arable land shows non-eroded soils (Albic Luvisols), mainly at lower midslopes. Extremely eroded soils (Calcaric Regosols) occur at convex landscape positions as well as steep slopes and strongly eroded soils (Calcic Luvisols) reaches from hilltops to upper midslopes. Footslopes and closed depressions comprise 20% of the landscape. Here, groundwater-influenced colluvial soils (Gleyic-Colluvic Regosols, partly overlying peat) have developed. Generally, the soil landscape reveals strong local gradients in wetness (< 100m distance). The soil texture is mainly loamy sand to sandy loam.</p><div> <img class="BildInAkkordeon" alt="Erosion-affected soil pattern in the Quillow catchment. Copyright: M. Wehrhan, ZALF" src="/de/struktur/eip/PublishingImages/ASLQ/ASLQ-Bodenmuster.jpg" /> <div class="ms-rteElement-Bildunterschrift">Erosion-affected soil pattern in the Quillow catchment: Light colours at hilltops indicate extremely eroded soils (a: Calcaric Regosols) by tillage erosion; brownish colours represent strongly eroded soils (b: Calcic Luvisols) affected by both, tillage and water erosion; brightish colour at lower midslopes indicate non-eroded soils (c: Albic Luvisols) and dark greyish areas indicate colluvial soils (d: Gleyic-Colluvic Regosols) in closed depressions. Quelle: © M. Wehrhan, ZALF.</div></div> <p>Soil erosion is the major process shaping soil landscapes and biogeochemical cycles. Recent research focusses on multi-proxy approaches to derive erosion and deposition rates over different time scales (Calitri et al. 2019, van der Meij et al., 2019). Special emphasis is further given to tillage erosion (Fiener et al. 2018) and feedbacks of soil erosion on C dynamics and C balances, i.e. the CO<sub>2</sub> sink/source functions of landscapes (Sommer et al. 2016, Hoffmann et al. 2017, 2018).</p></div>
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Soils

The soil pattern of the Quillow catchment is related to topography and the heterogeneity of Pleistocenic deposits. Since the last centuries the natural soil pattern has been strongly modified by soil erosion (tillage, water) (Sommer et al. 2008, Gerke et al. 2012, Gerke et al. 2016, Koszinksi et al. 2013). Recently, only 20% of the arable land shows non-eroded soils (Albic Luvisols), mainly at lower midslopes. Extremely eroded soils (Calcaric Regosols) occur at convex landscape positions as well as steep slopes and strongly eroded soils (Calcic Luvisols) reaches from hilltops to upper midslopes. Footslopes and closed depressions comprise 20% of the landscape. Here, groundwater-influenced colluvial soils (Gleyic-Colluvic Regosols, partly overlying peat) have developed. Generally, the soil landscape reveals strong local gradients in wetness (< 100m distance). The soil texture is mainly loamy sand to sandy loam.

Erosion-affected soil pattern in the Quillow catchment. Copyright: M. Wehrhan, ZALF

Erosion-affected soil pattern in the Quillow catchment: Light colours at hilltops indicate extremely eroded soils (a: Calcaric Regosols) by tillage erosion; brownish colours represent strongly eroded soils (b: Calcic Luvisols) affected by both, tillage and water erosion; brightish colour at lower midslopes indicate non-eroded soils (c: Albic Luvisols) and dark greyish areas indicate colluvial soils (d: Gleyic-Colluvic Regosols) in closed depressions. Quelle: © M. Wehrhan, ZALF.

Soil erosion is the major process shaping soil landscapes and biogeochemical cycles. Recent research focusses on multi-proxy approaches to derive erosion and deposition rates over different time scales (Calitri et al. 2019, van der Meij et al., 2019). Special emphasis is further given to tillage erosion (Fiener et al. 2018) and feedbacks of soil erosion on C dynamics and C balances, i.e. the CO₂ sink/source functions of landscapes (Sommer et al. 2016, Hoffmann et al. 2017, 2018).

Hydrology

MyTitle: Hydrology
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MyTextfeld: <div class="ExternalClassCCF1C41824E44840BFAE04A9EAC13CC9"><p>Interlayering of clayey till layers results in a system of layered aquifers that are not known in detail. However, some major features of the catchment’s hydrology can be inferred from merging information from different sources (Lischeid et al. 2017). In the eastern, downstream part of the catchments streams and kettle holes are hydraulically connected to a major aquifer. The aquifer extents to the western, upstream part of the catchment as well but being disconnected from the surface by an approximately horizontal confining bed. Here streams and kettle holes (small natural ponds) are connected to an overlying shallow aquifer. Groundwater flow direction in both aquifers follows the topographical gradient, approximately parallel to the main stream (Merz and Steidl 2015, Lischeid et al. 2017).</p><p>In general groundwater discharges into the kettle holes at one side and recharges to the aquifer at the other side. However, dense vegetation at the kettle holes’ shore, e.g., reed belts, bushes or trees, sustain high evapotranspiration even in dry periods. A model study has shown that groundwater flow direction in the “downstream” part of the kettle hole can reverse during dry periods. Depending on the texture and thickness of the shallow aquifer as well as on the meteorological boundary conditions, groundwater flow reversal can persist for some years.</p><p>Tile drains are very common in the riparian zone and in small depressions. In contrast, there is no evidence that surface runoff might play a major role for runoff generation. Long-term mean discharge 1972–1990 of the Quillow stream amounted to 143.6 mm per year (B. Stein and B. Hölzel, pers. comm. 1994). However, there are substantial uncertainties with respect to identifying the catchment boundaries for the different aquifers.</p></div>
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Hydrology

Interlayering of clayey till layers results in a system of layered aquifers that are not known in detail. However, some major features of the catchment’s hydrology can be inferred from merging information from different sources (Lischeid et al. 2017). In the eastern, downstream part of the catchments streams and kettle holes are hydraulically connected to a major aquifer. The aquifer extents to the western, upstream part of the catchment as well but being disconnected from the surface by an approximately horizontal confining bed. Here streams and kettle holes (small natural ponds) are connected to an overlying shallow aquifer. Groundwater flow direction in both aquifers follows the topographical gradient, approximately parallel to the main stream (Merz and Steidl 2015, Lischeid et al. 2017).

In general groundwater discharges into the kettle holes at one side and recharges to the aquifer at the other side. However, dense vegetation at the kettle holes’ shore, e.g., reed belts, bushes or trees, sustain high evapotranspiration even in dry periods. A model study has shown that groundwater flow direction in the “downstream” part of the kettle hole can reverse during dry periods. Depending on the texture and thickness of the shallow aquifer as well as on the meteorological boundary conditions, groundwater flow reversal can persist for some years.

Tile drains are very common in the riparian zone and in small depressions. In contrast, there is no evidence that surface runoff might play a major role for runoff generation. Long-term mean discharge 1972–1990 of the Quillow stream amounted to 143.6 mm per year (B. Stein and B. Hölzel, pers. comm. 1994). However, there are substantial uncertainties with respect to identifying the catchment boundaries for the different aquifers.

Land use

Land use is dominated by agriculture which covers about 74% of the catchment area where arable fields prevail. Grassland is found mainly close to the Quillow stream and in the eastern lowland parts of the catchment. In addition, small forest patches are located mainly in the western and southwestern part of the catchment. There are no major settlements in the catchment except for some small villages and single houses. Both settlement density and intensity of agricultural production have been rather stable over the last two decades.

Due to more fertile and less sandy soils compared to other regions in Northeast Germany this region has been intensively used by agriculture for centuries. However, a closer look at historical maps and reports revealed substantial changes at smaller spatial scales that are reflected in vegetation patterns until today (Wulf et al. 2016, 2017).

Research infrastructure

MyTitle: Research infrastructure
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MyTextfeld: <div class="ExternalClassF826D0FE630C47748D112319DCC847F0"><p>The <strong>Experimental Station Dedelow</strong> is located in the eastern part of the AgroScapeLab Quillow (near Prenzlau). On 42 ha of experimental fields (sandy loam) different agricultural cultivation systems are realized with modern experimental technology. In addition, there are various technical devices such as the TERENO lysimeters and the autonomous gas exchange measurements of "CARBO-ZALF". The staff of the station supports further numerous projects regarding the planning and implementation of measurement programs in cooperation with farmers.</p><p>At the <strong>CarboZALF-D experimental site</strong> near Dedelow (NE Germany) we quantify the magnitude, rates and mechanisms of soil C sequestration and release as well as plant growth, soil water and solute flux under controlled field conditions (Gerke et al. 2016; Hoffmann et al. 2017, 2018). A long-term manipulation experiment started in autumn 2010 with an artificial soil removal in sloping terrain. Since 2010 all carbon fluxes needed to derive a full carbon balance were measured at representative soils of the area (Sommer et al. 2016). The program includes a continuous CO<sub>2</sub> flux monitoring (net ecosystem exchange, NEE), a quantification of carbon exports by crop harvest as well as solute transport of organic (DOC) and inorganic carbon (DIC). Summing up all fluxes yields soil-specific full C balances which equals the change in soil organic carbon over time (= Δ SOC). After 6 years the SOC stock of the artificially eroded site (Calcic Luvisol) has increased by 0.9 kg C m<sup>-2</sup> in total. This effect has been described as "dynamic replacement" in the scientific literature. We observed surprisingly high mean annual C sequestration rates (144 g C m<sup>-2</sup> y<sup>-1</sup>) - comparable to natural peatlands.</p><p>To quantify the effects of fractional deep tillage on GHG and C dynamics a new field experiment was designed and established at the CarboZALF site. To measure highly dynamic GHG fluxes a modern gantry crane system was built (EFRE funding).</p><div> <img class="BildInAkkordeon" alt="Gantry crane system for GHG flux measurements at the CarboZALF experimental site. Copyright: M. Sommer, ZALF" src="/de/struktur/eip/PublishingImages/ASLQ/IMG_6238_300.JPG" /> <div class="ms-rteElement-Bildunterschrift">Gantry crane system for GHG flux measurements at the CarboZALF experimental site. Quelle: © M. Sommer, ZALF.</div></div></div>
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Research infrastructure

The Experimental Station Dedelow is located in the eastern part of the AgroScapeLab Quillow (near Prenzlau). On 42 ha of experimental fields (sandy loam) different agricultural cultivation systems are realized with modern experimental technology. In addition, there are various technical devices such as the TERENO lysimeters and the autonomous gas exchange measurements of "CARBO-ZALF". The staff of the station supports further numerous projects regarding the planning and implementation of measurement programs in cooperation with farmers.

At the CarboZALF-D experimental site near Dedelow (NE Germany) we quantify the magnitude, rates and mechanisms of soil C sequestration and release as well as plant growth, soil water and solute flux under controlled field conditions (Gerke et al. 2016; Hoffmann et al. 2017, 2018). A long-term manipulation experiment started in autumn 2010 with an artificial soil removal in sloping terrain. Since 2010 all carbon fluxes needed to derive a full carbon balance were measured at representative soils of the area (Sommer et al. 2016). The program includes a continuous CO₂ flux monitoring (net ecosystem exchange, NEE), a quantification of carbon exports by crop harvest as well as solute transport of organic (DOC) and inorganic carbon (DIC). Summing up all fluxes yields soil-specific full C balances which equals the change in soil organic carbon over time (= Δ SOC). After 6 years the SOC stock of the artificially eroded site (Calcic Luvisol) has increased by 0.9 kg C m^-2 in total. This effect has been described as "dynamic replacement" in the scientific literature. We observed surprisingly high mean annual C sequestration rates (144 g C m^-2 y^-1) - comparable to natural peatlands.

To quantify the effects of fractional deep tillage on GHG and C dynamics a new field experiment was designed and established at the CarboZALF site. To measure highly dynamic GHG fluxes a modern gantry crane system was built (EFRE funding).

Gantry crane system for GHG flux measurements at the CarboZALF experimental site. Copyright: M. Sommer, ZALF

Gantry crane system for GHG flux measurements at the CarboZALF experimental site. Quelle: © M. Sommer, ZALF.

Current research

MyTitle: Current research
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MyTextfeld: <div class="ExternalClass905BFC6073144F3593BE6A34EDEA950D"><p>Landscape research is based on numerous studies of single processes at single sites, scales, and during certain periods independent from each other. These findings are condensed in terms of general inferences that could be transferred to other regions, scales, and time periods, often via implementation in respective models. However, that approach systematically falls short of grasping unexpected relationships and feedbacks between the realms of different disciplines.</p><p>Revealing complex feedbacks between different "landscape elements" requires comprehensive data sets that describe various aspects of the same region in a coordinated way. This applies even for data acquisition of very different disciplines in order to enable detecting unexpected relationships. Only then the study region can be characterized in a high-dimensional phase-space (cf., Lischeid et al. 2016), i.e., yielding a comprehensive data cube, that could be analysed with powerful modern data mining approaches.</p><p>To that end, landscape research in the AgroScapeLab Quillow is based on four major pillars:</p><ol><li> <strong>Monitoring</strong>: Long-term systematic and continuous measuerments constitute the backbone of all research activities in the AgroScapeLab Quillow. These data are made available for other researchers and are complemented by additional data sets provided by external research partners, by authorities, via UAV (e.g., Wehrhan et al. 2016) and satellite remote sensing products, and the like. Monitoring comprises meteorological, hydrological, and biogeochemical data (Lischeid et al. 2016), land management and yield data, surveys of weeds, plant infestations and mycotoxins (Müller et al. 2010, Müller and Korn 2013), bird surveys (Brandt and Glemnitz 2014), etc.</li><li> <strong>Process studies</strong>: Single process studies as well as major projects with numerous partners (e.g., CarboZALF, SoilCan, TEROS, Landscales, BioMove, BIBS) focusing on single aspects of landscape processes benefit from the comprehensive background data. On the other hand, results from these studies help to optimize monitoring and modelling activities.</li><li> <strong>Landscape experiments</strong>: Based on comprehensive background data landscape experiments like in the CarboZALF project (Sommer et al. 2016) can be planned and interpreted.</li><li> <strong>Modelling and integrated data analysis</strong>: Long-term and consistent multivariate data sets are an ideal basis for developing and testing numerical models as well as for application and further development of modern data mining approaches in order to reveal complex interdependencies in landscapes.</li></ol></div>
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Current research

Landscape research is based on numerous studies of single processes at single sites, scales, and during certain periods independent from each other. These findings are condensed in terms of general inferences that could be transferred to other regions, scales, and time periods, often via implementation in respective models. However, that approach systematically falls short of grasping unexpected relationships and feedbacks between the realms of different disciplines.

Revealing complex feedbacks between different "landscape elements" requires comprehensive data sets that describe various aspects of the same region in a coordinated way. This applies even for data acquisition of very different disciplines in order to enable detecting unexpected relationships. Only then the study region can be characterized in a high-dimensional phase-space (cf., Lischeid et al. 2016), i.e., yielding a comprehensive data cube, that could be analysed with powerful modern data mining approaches.

To that end, landscape research in the AgroScapeLab Quillow is based on four major pillars:

Monitoring: Long-term systematic and continuous measuerments constitute the backbone of all research activities in the AgroScapeLab Quillow. These data are made available for other researchers and are complemented by additional data sets provided by external research partners, by authorities, via UAV (e.g., Wehrhan et al. 2016) and satellite remote sensing products, and the like. Monitoring comprises meteorological, hydrological, and biogeochemical data (Lischeid et al. 2016), land management and yield data, surveys of weeds, plant infestations and mycotoxins (Müller et al. 2010, Müller and Korn 2013), bird surveys (Brandt and Glemnitz 2014), etc.
Process studies: Single process studies as well as major projects with numerous partners (e.g., CarboZALF, SoilCan, TEROS, Landscales, BioMove, BIBS) focusing on single aspects of landscape processes benefit from the comprehensive background data. On the other hand, results from these studies help to optimize monitoring and modelling activities.
Landscape experiments: Based on comprehensive background data landscape experiments like in the CarboZALF project (Sommer et al. 2016) can be planned and interpreted.
Modelling and integrated data analysis: Long-term and consistent multivariate data sets are an ideal basis for developing and testing numerical models as well as for application and further development of modern data mining approaches in order to reveal complex interdependencies in landscapes.

Joining the AgroScapeLab Quillow

MyTitle: Joining the AgroScapeLab Quillow
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MyTextfeld: <div class="ExternalClass9F96F1C1669948BE8C3435FFAADDCC46"><p>The ASLQ is part of various research networks. In addition, <a title="List of publications - AgroScapeLab Quillow (ASLQ), 2016-05 / 2019" href="/en/struktur/eip/Documents/Literatur-AgroScapeLab-Quillow-2016-2019_en.pdf" target="_blank"><img class="ms-asset-icon ms-rtePosition-4" alt="PDF-Icon" src="/_layouts/15/images/icpdf.png" />results</a> <img class="mp_newTab_imgText" alt="new tab icon" src="/_layouts/15/images/zalfweb/IconNewTab_12.png" />, <a title="Open Research Data - The portal for freely accessible primary research data at ZALF" href="http://open-research-data-zalf.ext.zalf.de/ResearchData/Forms/All_Datasets.aspx" target="_blank"> existing data</a> <img class="mp_newTab_imgText" alt="new tab icon" src="/_layouts/15/images/zalfweb/IconNewTab_12.png" />, research infrastructure and research activities are shared with external partners and with anybody who likes to contribute to landscape research in the Quillow region. Please feel invited to contact us:</p><p>Concerning ASLQ in general, research concept, collaboration:</p><ul><li> <a title="Contact Gunnar Lischeid" href="/en/ueber_uns/mitarbeiter/Pages/Lischeid_g.aspx">Gunnar Lischeid</a></li><li> <a title="Contact Michael Sommer" href="/en/ueber_uns/mitarbeiter/Pages/sommer_m.aspx">Michael Sommer</a></li></ul><p>Concerning ASLQ data:</p><ul><li> <a title="ZALF Personensuche" href="/en/ueber_uns/mitarbeiter/Pages/default.aspx">Kristin Meier</a></li></ul><p>Concerning organisational or technical issues:</p><ul><li> <a title="Contact Gernot Verch" href="/en/ueber_uns/mitarbeiter/Pages/Verch_g.aspx">Gernot Verch</a></li></ul><p>Public relations:</p><ul><li> <a title="Contact Pressestelle" href="/en/aktuelles/presse/Pages/default.aspx">Pressestelle</a></li></ul></div>
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Joining the AgroScapeLab Quillow

The ASLQ is part of various research networks. In addition, results new tab icon , existing data , research infrastructure and research activities are shared with external partners and with anybody who likes to contribute to landscape research in the Quillow region. Please feel invited to contact us:

Concerning ASLQ in general, research concept, collaboration:

Concerning ASLQ data:

Kristin Meier

Concerning organisational or technical issues:

Gernot Verch

Public relations:

Pressestelle

References

MyTitle: References
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MyTextfeld: <div class="ExternalClassA9D9BA56339E454C83A3EB9F7F049778"><p>Brandt, K. L., Glemnitz, M. (2014). Assessing the regional impacts of increased energy maize cultivation on farmland birds. Environmental Monitoring and Assessment 186, 2, 679-697.</p><p>Calitri, F., Sommer, M., Norton, K., Temme, A., Brandova, D., Portes, R., Christl, M., Ketterer, M.E., Egli, M. (2019). Tracing the temporal evolution of soil redistribution rates in an agricultural landscape using 239+240Pu and 10Be. Earth Surface Processes and Landforms (accepted)</p><p>Fiener, P., Wilken, F., Aldana-Jague, E., Deumlich, D., Gómez, J. A., Guzmán, G., Hardy, R. A., Quinton, J. N., Sommer, M., Van Oost, K., Wexler, R. (2018) Uncertainties in assessing tillage erosion - how appropriate are our measuring techniques? Geomorphology 304, 214-225.</p><p>Gerke, H. H., Koszinski, S., Kalettka, T., Sommer, M. (2010). Structures and hydrologic function of soil landscapes with kettle holes using an integrated hydropedological approach. Journal of Hydrology 393, 1-2, 123-132.</p><p>Gerke, H. H., Hierold, W. (2012). Vertical bulk density distribution in C-horizons from marley till as indicator for erosion history in a hummocky post-glacial soil landscape. Soil & Tillage Research 125, 116-122.</p><p>Gerke, H. H., Rieckh, H., Sommer, M. (2016) Interactions between crop, water, and dissolved organic and inorganic carbon in a hummocky landscape with erosion-affected pedogenesis. Soil & Tillage Research 156, 230-244.</p><p>Hoffmann, M., Jurisch, N., Garcia Alba, D. J., Albiac Borraz, E., Schmidt, M., Huth, V., Rogasik, H., Rieckh, H., Verch, G., Sommer, M., Augustin, J. (2017) Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories. Biogeosciences 14, 4, 1003-1019.</p><p>Hoffmann, M., Pohl, M., Jurisch, N., Prescher, A.-K., Mendez Campa, E., Hagemann, U., Remus, R., Verch, G., Sommer, M., Augustin, J. (2018) Maize carbon dynamics are driven by soil erosion state and plant phenology rather than nitrogen fertilization form. Soil & Tillage Research 175, 255-266.</p><p>Koszinski, S., Gerke, H. H., Hierold, W., Sommer, M. (2013). Geophysical-based modeling of a kettle hole catchment of the morainic soil landscape. Vadose Zone Journal 12, 4.</p><p>Lischeid, G., Kalettka, T., Merz, C., Steidl, J. (2016). Monitoring the phase space of ecosystems: Concept and examples from the Quillow catchment, Uckermark. Ecological Indicators 65:55-65, DOI: 10.1016/j.ecolind.2015.10.067.</p><p>Lischeid, G., Balla, D., Dannowski, R., Dietrich, O., Kalettka, T., Merz, C., Schindler, U., Steidl, J. (2017). Forensic hydrology: what function tells about structure in complex settings. Environmental Earth Sciences 76, 1, Article: 40.</p><p>Merz, C., Steidl, J. (2015). Data on geochemical and hydraulic properties of a characteristic confined/unconfined aquifer system of the younger Pleistocene in northeast Germany. Earth System Science Data 7, 1, 109-116.</p><p>Müller, M.E.H., Korn, U. (2013). Alternaria mycotoxins in wheat – A 10 years survey in the Northeast of Germany. Food Control 34: 191-197.</p><p>Müller, M.E.H., Brenning, A., Verch, G., Koszinski, S., Sommer, M. (2010). Multifactorial spatial analysis of mycotoxin contamination of winter wheat at the field and landscape scale. Agriculture, Ecosystems and Environment 139: 245-254.</p><p>Sommer, M., Gerke, H. H., Deumlich, D. (2008). Modelling soil landscape genesis: A "time split" approach for hummocky agricultural landscapes. Geoderma 145, 3-4, 480-493.</p><p>Sommer, M., Augustin, J., Kleber, M. (2016). Feedbacks of soil erosion on SOC patterns and carbon dynamics in agricultural landscapes - the CarboZALF experiment. Soil & Tillage Research 156, 182-184.</p><p>van der Meij, W.M., Reimann, T., Vornehme, V.K., Temme A., Wallinga, J., van Beek, R., Sommer, M. (2019). Reconstructing rates and patterns of colluvial soil redistribution in an agrarian kettle hole. Earth Surface Processes and Landforms (accepted)</p><p>Wehrhan, M., Rauneker, P., Sommer, M. (2016). UAV-based estimation of carbon exports from heterogeneous soil landscapes - a case study from the CarboZALF experimental area. Sensors 16, 2, Article: 255.</p><p>Wulf, M., Jahn, U., Meier, K. (2016). Land cover composition determinants in the Uckermark (NE Germany) over a 220-year period. Regional Environmental Change 16, 6, 1793-1805.</p><p>Wulf, M., Jahn, U., Meier, K., Radtke, M. (2017). Tree species composition of a landscape in north-eastern Germany in 1780, 1890 and 2010. Forestry 90, 2, 174-186.</p></div>
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References

Brandt, K. L., Glemnitz, M. (2014). Assessing the regional impacts of increased energy maize cultivation on farmland birds. Environmental Monitoring and Assessment 186, 2, 679-697.

Calitri, F., Sommer, M., Norton, K., Temme, A., Brandova, D., Portes, R., Christl, M., Ketterer, M.E., Egli, M. (2019). Tracing the temporal evolution of soil redistribution rates in an agricultural landscape using 239+240Pu and 10Be. Earth Surface Processes and Landforms (accepted)

Fiener, P., Wilken, F., Aldana-Jague, E., Deumlich, D., Gómez, J. A., Guzmán, G., Hardy, R. A., Quinton, J. N., Sommer, M., Van Oost, K., Wexler, R. (2018) Uncertainties in assessing tillage erosion - how appropriate are our measuring techniques? Geomorphology 304, 214-225.

Gerke, H. H., Koszinski, S., Kalettka, T., Sommer, M. (2010). Structures and hydrologic function of soil landscapes with kettle holes using an integrated hydropedological approach. Journal of Hydrology 393, 1-2, 123-132.

Gerke, H. H., Hierold, W. (2012). Vertical bulk density distribution in C-horizons from marley till as indicator for erosion history in a hummocky post-glacial soil landscape. Soil & Tillage Research 125, 116-122.

Gerke, H. H., Rieckh, H., Sommer, M. (2016) Interactions between crop, water, and dissolved organic and inorganic carbon in a hummocky landscape with erosion-affected pedogenesis. Soil & Tillage Research 156, 230-244.

Hoffmann, M., Jurisch, N., Garcia Alba, D. J., Albiac Borraz, E., Schmidt, M., Huth, V., Rogasik, H., Rieckh, H., Verch, G., Sommer, M., Augustin, J. (2017) Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories. Biogeosciences 14, 4, 1003-1019.

Hoffmann, M., Pohl, M., Jurisch, N., Prescher, A.-K., Mendez Campa, E., Hagemann, U., Remus, R., Verch, G., Sommer, M., Augustin, J. (2018) Maize carbon dynamics are driven by soil erosion state and plant phenology rather than nitrogen fertilization form. Soil & Tillage Research 175, 255-266.

Koszinski, S., Gerke, H. H., Hierold, W., Sommer, M. (2013). Geophysical-based modeling of a kettle hole catchment of the morainic soil landscape. Vadose Zone Journal 12, 4.

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Müller, M.E.H., Brenning, A., Verch, G., Koszinski, S., Sommer, M. (2010). Multifactorial spatial analysis of mycotoxin contamination of winter wheat at the field and landscape scale. Agriculture, Ecosystems and Environment 139: 245-254.

Sommer, M., Gerke, H. H., Deumlich, D. (2008). Modelling soil landscape genesis: A "time split" approach for hummocky agricultural landscapes. Geoderma 145, 3-4, 480-493.

Sommer, M., Augustin, J., Kleber, M. (2016). Feedbacks of soil erosion on SOC patterns and carbon dynamics in agricultural landscapes - the CarboZALF experiment. Soil & Tillage Research 156, 182-184.

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Wehrhan, M., Rauneker, P., Sommer, M. (2016). UAV-based estimation of carbon exports from heterogeneous soil landscapes - a case study from the CarboZALF experimental area. Sensors 16, 2, Article: 255.

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Wulf, M., Jahn, U., Meier, K., Radtke, M. (2017). Tree species composition of a landscape in north-eastern Germany in 1780, 1890 and 2010. Forestry 90, 2, 174-186.