Using the Conservation Practice Effectiveness (CoPE) Database to assess adoption tradeoffs

Abstract

The newly published Conservation Practice Effectiveness (CoPE) Database compiles information on the effectiveness of a suite of conservation practices developed to treat contaminants in surface runoff and tile drainage water from agricultural landscapes. Traditional conservation practices such as no-tillage and conservation crop rotation are included in the CoPE Database, as well as novel practices such as drainage water management, blind inlets, and denitrification bioreactors. This will be particularly useful to conservation planners seeking new approaches to water quality problems associated with dissolved constituents, such as nitrate (NO 3) or soluble phosphorus (SP), and for researchers seeking to understand the circumstances in which such practices are most effective. Another novel feature of the database is the presentation of information on how individual conservation practices impact multiple water quality concerns. This information will be critical to enabling conservationists and policy makers to avoid (or at least be aware of) undesirable tradeoffs, whereby great efforts are made to improve water quality related to one resource concern (e.g., sediment) but exacerbate problems related to other concerns (e.g., NO 3 or SP). Finally, we note that the CoPE Database can serve as a source of the soft data needed to calibrate simulation models assessing the potential water quality tradeoffs of conservation practices, including those that are still being developed.

Addressing conservation practice limitations and trade‐offs for reducing phosphorus loss from agricultural fields

“…Conservation practices (CPs) are essential to reduce nutrient and soil loss from agricultural lands to protect water quality, especially when implemented as systems of practices, as demonstrated by the Conservation Effects Assessment Project (CEAP; Osmond et al., 2012). While CEAP and other field research confirm that CPs have benefited water quality in productive agricultural landscapes, CP effectiveness is also site‐specific and can result in unintended consequences or trade‐offs (Smith et al., 2019). Understanding and addressing the trade‐offs and unintended consequences of CPs are essential to the successful mitigation of watershed P losses.…”

An Overview of the Effectiveness of Agricultural Conservation Practices for Water Quality Improvement

“…Performance effectiveness is commonly calculated using the percent mass load and/or concentration reduction compared to a baseline (e.g., Smith et al, 2019;Chaubey et al, 2010). Ideally, both percent mass load and concentration should be evaluated because mass loads are intuitive and helpful for understanding the contributions of different sources to meeting federal total maximum daily load (TMDL) goals within a watershed, while nutrient concentrations are useful for assessing water quality criteria from human health and ecotoxicity perspectives.…”

Emerging nutrient management databases and networks of networks will have broad applicability in future machine learning and artificial intelligence applications in soil and water conservation

“…This special issue about the USDA ARS AgCROS/NUOnet features a series of papers that present data related to soil and water conservation efforts. These papers cover areas related to N balances (Sainju 2019); runoff and leaching (figure 3) (Vadas and Powell 2019); N management in different tillage systems (Balkcom 2019); nutrient distributions in grazed pastures (Franzluebbers et al 2019); runoff and nutrient losses from conventional and conservation tillage systems (Endale et al 2019); infiltration into saturated buffers (Jaynes and Isenhart 2019); a conservation planning and evaluation tool (White et al 2019); N sources and rates (Mikha et al 2019); the Conservation Practice Effectiveness (CoPE) Database (Smith et al 2019); and integration of data for a sustainable food system (Finley and Fukagawa 2019). Data from some of these papers have already been uploaded to NUOnet or to the USDA ARS National Agricultural Library.…”