DPSIR Framework

The DPSIR framework helps to structure complex human-environmental systems into a sequence from Driver, Pressure, State to Impact and Response (DPSIR). Due to its generic character, it can be used to investigate impacts of soil management on environmental and societal systems, to summarise existing knowledge of soil management research, and to detect research gaps. The DPSIR framework analytically links soil management (pressure) to soil functions (state) and its services (impact) that are assessed from the perspective of societal goals such as resource use efficiency or ecosystem services. Informed by the assessment results, society may react, governance may be adjusted (response) and steer soil management into a new direction (creating new drivers and restarting the sequence). 

The DPSIR framework describes a five-step causal relationship of human-nature interactions and was developed for the assessment of relations between human activities and the environment (Gabrielson and Bosch, 2003). It builds on the three-step PSI framework which was originally developed by the OECD (1993). The five analytical stages help to structure complex human-environmental systems in a sequence from Driver, Pressure, State to Impact and Response (DPSIR). For example, driving forces, such as human needs for specific nutrition or improved technological facilities, lead to particular human activities in soil management and biomass production. These activities exert pressures on the environment, e.g., soil, which might change its properties and processes (“state”) and corresponding functions. The potential environmental system changes have impacts on the societal system which are then evaluated by impact assessments. Informed by the valuation results, a societal response might take place that alters drivers and resets the causal chain of pressures, states, and impacts.

 

In this way, the DPSIR framework captures change and dynamic processes in human-nature interactions. It helps to integrate knowledge from different disciplines via indicators in a cycle of impact assessment (Tscherning et al., 2012; Helming et al., 2013). One key strength of the concept lies in its adaptability to various impact areas, objectives and scales of analysis (Tscherning et al., 2012). Potential enhancements of the framework could be designed to also consider interconnections between stages beyond the connection from preceding to following stage (Niemeijer & De Groot, 2008).

 

Figure 2: The DPSIR framework applied to soil functions in the socio-economic context, modified from Gabrielsen & Bosch (2003) 
The DPSIR framework analytically links soil management to soil functions and impacts on societal goals and value systems such as resource use efficiency or ecosystem services. Its perspective on human-nature interactions makes it possible to integrate scientific evidence from different disciplines into one joint framework, helping to develop comprehensive strategies for soil management that both sustain and improve soil functions. Finally, the integrated knowledge helps to provide scientific evidence for a multitude of societal groups and stakeholders involved in soil management (politicians, farmers, planners etc.) in order to support decision-making. 

Due to its generic character, the DPSIR framework can easily be applied to very different settings of soil research. A number of studies already use the framework to investigate impacts of soil management on environmental and societal systems. For example, DPSIR has been applied to analyse changes in agricultural management such as precision agriculture and manure input on different scales (Bouma et al., 2008), to illustrate how land degradation control could be more effective (Gislanddottir & Stocking, 2005), to analyse how salinity, acidity and erosion threaten the ecosystem services of food production and the regulation of water quality in Australia (Holland et al., 2015), and to detect co-evolution of soil and water conservation policy with human-environment linkages (Wang et al., 2015). Furthermore, studies that focus on particular stages of the framework or on the relationships between stages can be integrated into a full application of the DPSIR framework and a broader cause-effect relationship. For example, Smaling & Dixon (2006) investigate the state, impact and response of soil fertility and nutrient management in global farming systems.


Overall, DPSIR framework can be used to summarize existing knowledge of soil management research and to detect research gaps. A particular example that reviews and synthesises scientific evidence for all single analytical steps of the DPSIR framework is provided by Schjønning et al. (2015). Their thematic focus is the potential compaction of sub soil due to mechanical stress by agricultural machinery. In detail, they identify studies describing external and internal drivers of particular field traffic practices, e.g., technical improvement and saving of labour costs cause the use of bigger and heavier machinery. They cite further studies that show how the pressure by field traffic on soils increases and has consequences for soil processes, such as higher bulk density, less pore volume size and reduced root system. This change of the soil state again has impacts on selected soil functions such as reduced biomass production, less storing and filtering capacities for water and nutrients. Furthermore, Schjønning et al. (2015) present studies investigating the impact on the social system such as the calculation of the relation between yield loss and cost savings in machine operations (cost-effectiveness of alleviating or avoiding soil compaction). They present potential responses to desirable or undesirable impacts, ranging from provision of subsidies in the political system to farmers’ changes in soil management (e.g., increased application of nutrients or planting of taproot plants) to technical improvements towards smaller machinery.

Bouma J, de Vos JA, Sonneveld MPW, Heuvelink GBM, Stoorvogel JJ. 2008. The Role of Scientists in Multiscale Land Use Analysis: Lessons Learned from Dutch Communities of Practice. Advances in Agronomy 97: 175-237. DOI:10.1016/S0065-2113(07)00005-3


Gabrielsen P, Bosch P. 2003. Environmental Indicators: Typology and Use in Reporting European Environment Agency: Copenhagen, Denmark.

 

Gislanddottir G, Stocking M. 2005. Land degradation control and its global environmental benefits. Land Degradation & Development 16: 99-112. DOI:10.1002/ldr.687


Helming K, Diehl K, Geneletti D, Wiggering H. 2013. Mainstreaming ecosystem services in European policy impact assessment. Environmental Impact Assessment Review 40: 82-87. DOI:10.1016/j.eiar.2013.01.004


Holland JE, Luck GW, Finlayson CM. 2015. Threats to food production and water quality in the Murray-Darling Basin of Australia. Ecosystem Services 12: 55-70. DOI:10.1016/j.ecoser.2015.02.008


Niemeijer D, De Groot RS. 2008. Framing environmental indicators: moving from causal chains to causal networks. Environment, Development and Sustainability 10: 89-106. DOI:10.1007/s10668-006-9040-9


OECD-Organization for Economic Co-operation and Development. 1993. OECD core set of indicators for environmental performance reviews. Paris: OECD Environment Monographs No. 83.


Schjønning P, van den Akker JJH, Keller T, Greve MH, Lamandé M, Simojoki A, Stettler M, Arvidsson J, Breuning-Madsen H. 2015. Driver-Pressure-State-Impact-Response (DPSIR) Analysis and Risk Assessment for Soil Compaction-A European Perspective. Advances in Agronomy 133: 183-237. DOI:10.1016/bs.agron.2015.06.001


Smaling EMA, Dixon J. 2006. Adding a soil fertility dimension to the global farming systems approach, with cases from Africa. Agriculture Ecosystems & Environment 116: 15-26. DOI:10.1016/j.agee.2006.03.010


Tscherning K, Helming K, Krippner B, Sieber S, Paloma SG. 2012. Does research applying the DPSIR framework support decision making? Land Use Policy 29: 102-110. DOI:10.1016/j.landusepol.2011.05.009


Wang F, Mu X, Li R, Fleskens L, Stringer LC, Ritsema CJ. 2015. Co-evolution of soil and water conservation policy and human-environment linkages in the Yellow River Basis since 1949. Science of the Total Environment 508: 166-177. DOI:10.1016/j.scitotenv.2014.11.055