Using ion-exchange resins to monitor nitrate fluxes in remote semiarid stream beds.

Monitoring in remote areas can represent a real challenge in environmental studies. Numerous techniques have been developed over the last decades to monitor nutrients and other elements in different systems. However, not all of them are suitable for field applications, particularly when the locations are difficult to access or its accessibility depends on seasonal climate conditions. This study was aimed to test the applicability and efficiency of resin samplers and resin bags to monitor nitrates fluxes (NO3-N) in two small semi-arid catchments in Northwestern Mexico. Resin samplers were installed in the hyporheic zone below the river bed in order to monitor the vertical fluxes of NO3-N and remained there for 5 months (during the summer rains). Resin bags were anchored in rock outcrops upstream of the resin samplers before the onset of the summer rainfall season and replaced every 2 weeks during 4 months to capture pulses of NO3-N in ephemeral streams. NO3-N pulses in the stream are a potential source of NO3-N that can infiltrate into the soil. Results of the resin samplers found a difference of up to 12 kg ha-1 season-1 between the two catchments. The resin bags showed a higher accumulation of NO3-N in the catchment with lower vegetation cover (160.3 mg L-1 season-1) compared to the one with higher vegetation (67.8 mg L-1 season-1). Measured nitrate fluxes at both sites responded to rainfall pulses recorded during the monitoring period. Resin samplers and resin bags can be used together, to assess nutrient fluxes on the surface and in the soil and can be tested in any type of ecosystem. In this particular case, these methods demonstrated an efficient way of determining spatio-temporal nitrate fluxes in semi-arid ecosystems in remote areas that are difficult to access, monitor, and collect data.

Orientation of tree rows in alley cropping systems matters - The "ShadOT" modelling tool for tree growth and shading effects.

Agroforestry systems have received a significant attention in recent years and can be considered as a potential strategy in agricultural production to respond to worsening climatic conditions. The decision-making process for farmers to design and implement agroforestry systems is complex due to time-consuming processes of planting, growing and management of trees, as well as the long-term impacts on the field and its productivity. The shading of the arable land by trees is a core issue and should be reduced through a north-south orientation of the tree rows. However, this orientation is often in conflict with other criteria. In order to consider future shading from different tree row orientations into the design process, the modelling tool "ShadOT" was developed. This tool can simulate tree growth and analyses spatial shading over variable time periods by using only a limited number of parameters. This tool was programmed exclusively with open source software and can therefore be easily extended. It offers an ideal platform for testing different agroforestry designs due to its simple approach and minimal parameterization. Two different designs (north-south and west-east orientation) were tested for a field and differences in the temporal and spatial distribution of shaded areas are presented.•Modelling tool for tree growth and shading effects is presented.•The tool is written in Python programming language, uses only open-source software and requires a limited number of inputs.•Identification of spatial-temporal shading patterns of different alley cropping scenarios.

Sustainable transformation of agriculture requires landscape experiments.

Transformation of agriculture to realise sustainable site-specific management requires comprehensive scientific support based on field experiments to capture the complex agroecological process, incite new policies and integrate them into farmers' decisions. However, current experimental approaches are limited in addressing the wide spectrum of sustainable agroecosystem and landscape characteristics and in supplying stakeholders with suitable solutions and measures. This review identifies major constraints in current field experimentation, such as a lack of consideration of multiple processes and scales and a limited ability to address interactions between them. It emphasizes the urgent need to establish a new category of landscape experimentation that empowers agricultural research on sustainable agricultural systems, aiming at elucidating interactions among various landscape structures and functions, encompassing both natural and anthropogenic features. It extensively discusses the key characteristics of landscape experiments and major opportunities to include them in the agricultural research agenda. In particular, simultaneously considering multiple factors, and thus processes at different scales and possible synergies or antagonisms among them would boost our understanding of heterogeneous agricultural landscapes. We also highlight that though various studies identified promising approaches with respect to experimental design and data analysis, further developments are still required to build a fully functional and integrated framework for landscape experimentation in agricultural settings.

Use of the term "landscape" in sustainable agriculture research: A literature review.

Finding consensus in definitions of commonly-used terms and concepts is a key requirement to enable cooperations between interdisciplinary scientists and practitioners in inter- or transdisciplinary projects. In research on sustainable agriculture, the term 'landscape' is emphasised in particular, being used in studies that range from biogeochemical to socio-economic topics. However, it is normally used in a rather unspecific manner. Moreover, different disciplines assign deviating meanings to this term, which impedes interdisciplinary understanding and synthesis. To close this gap, a systematic literature review from relevant disciplines was conducted to identify a common understanding of the term "landscape". Three general categories of landscape conceptualizations were identified. In a small subset of studies, "landscape" is defined by area size or by natural or anthropogenic borders. The majority of reviewed papers, though, define landscapes as sets of relationships between various elements. Selection of respective elements differed widely depending on research objects. Based on these findings, a new definition of landscape is proposed, which can be operationalized by interdisciplinary researchers to define a common study object and which allows for sufficient flexibility depending on specific research questions. It also avoids over-emphasis on specific spatio-temporal relations at the "landscape scale", which may be context-dependent. Agricultural landscape research demands for study-specific definitions which should be meticulously provided in the future.