Clarifying uncertainty in biogeochemical response to land management
Abstract
We examined the ability of contemporary simulation and empirical modeling tools to describe net greenhouse gas (GHG) emissions as a result of agricultural and forest ecosystem land management, and we looked at how key policy institutions use these tools. We focused on quantification of nitrous oxide (N2O) emissions from agricultural systems, as agriculture is the dominant source of anthropogenic N2O emissions. Agricultural management impact on N2O emissions is especially challenging because controls on N2O emissions (soil aerobic status, inorganic N availability, and C substrate availability) vary as a function of site soil type, climate, and cropping system; available measurements do not cover all relevant combinations of these controlling system features. Furthermore, N2O emissions are highly non-linear, and threshold values of controlling soil environmental conditions are not defined across most agricultural site properties. We also examined the multi-faceted challenges regarding the quantification of increased soil organic carbon (SOC) storage as a result of land management in both agricultural and forest systems. Quantifying changes in SOC resulting from land management is difficult because mechanisms of SOC stabilization are not fully understood, SOC measurements have been concentrated in the upper 30cm of soil, erosion is often ignored when estimating SOC, and few long-term studies exist to track system response to diverse management practices. Furthermore, the permanence of SOC accumulating management practices is not easily established. For instance, under the Regional Greenhouse Gas Initiative (RGGI), forest land managed for SOC accumulation must remain under permanent conservation easement to ensure that SOC accumulation is not reversed due to changes in land cover. For agricultural protocols, given that many farmers rent land and that agriculture is driven by an annual management time scale, the ability to ensure SOC-accumulating land management would be maintained indefinitely has delayed the implementation of SOC accumulating practices for compliance with the California Global Warming Solutions Act (AB 32). GHG accounting tools are increasingly applied to implement GHG reduction policies. In this policy context, data limitation has impacted the implementation of GHG accounting strategies. For example, protocol design in support of AB 32 initially sought to apply simulation models to determine N2O emissions across all major U.S. agricultural landscapes. After discussion with ecosystem scientists, the lack of observations and model validation in most U.S. arable landscapes led to protocol definition based on simple empirical models and limited to corn management in 12 states. The distribution of protocol participants is also a potential source of inaccuracy in GHG accounting. Land management protocols are often structured assuming that in the aggregate policy achieves an average improvement by promoting specific management. However it is unclear that current policy incentives promote participation from a truly random distribution of landscapes. Participation in policy development to support improved land management challenges ecosystem scientists with making recommendations based on best-available information while acknowledging that uncertainty limits accurate quantification of impacts via analysis using either observations or simulation modeling.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFMPA21B1878T
- Keywords:
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- 0485 BIOGEOSCIENCES Science policy;
- 0402 BIOGEOSCIENCES Agricultural systems;
- 6309 POLICY SCIENCES Decision making under uncertainty;
- 6329 POLICY SCIENCES Project evaluation