Climate Change Mitigation - Soil Carbon: Science, Management and Policy for Multiple Benefits - page 126

SOC levels are often small, direct meas-
urement of SOC changes for an individual
field can require a large number of samples,
and thus a high cost. Efficient sampling de-
signs, which focus on repeated measure-
ments over time at relocatable benchmark
sites, can reduce greatly the sampling re-
quirements (and cost) for detecting SOC
change (Conant and Paustian, 2002; Lark,
2009; Spencer et al ., 2011). However, for
many smaller mitigation projects, particu-
larly in areas with highly heterogeneous
landscapes, quantifying SCS with direct soil
measurements alone is likely to be too costly.
Using model-based quantification sys-
tems, supported by a coordinated network
of 'on-farm' monitoring locations with direct
SOC measurements for representative soils
and management practices, has been pro-
posed as an approach that can reduce costs
significantly, while achieving acceptable ac-
curacy and precision, for the measurement
and monitoring required for agricultural op-
tions to be broadly accepted by C offset mar-
kets (Paustian et al ., 2011; Spencer et al .,
2011). This would enable monitoring at
field and farm scales to focus on reporting
of the practices that are occurring - when
and where on the landscape - which can be
accomplished using lower-cost methods
such as remote sensing and self-reporting by
the land users themselves (Paustian, 2012).
This type of approach could reduce dra-
matically the transaction costs for agricul-
tural mitigation projects and thus provide
more net compensation to incentivize land
users, potentially enabling a much broader
participation in agricultural mitigation pro-
grammes.
Other C accounting issues, specifically
additionality, permanence and leakage, pose
challenges to a broad participation of agri-
culture in current and future mitigation
policies. Further research and streamlined
policy designs can reduce impediments to
agricultural participation in GHG mitigation
efforts.
Additionality refers to the condition
that a mitigation project must produce re-
sults that would otherwise not be achieved
in the absence of an explicit mitigation
policy or effort - in other words, that the

mitigation results are additional to what
would have occurred with 'business as
usual' (BAU). This is particularly import-
ant for agricultural activities that would
not themselves be subject to mandatory
GHG emission regulations, but rather func-
tioning as an 'offset' to required emission
reductions in an industrial or energy-sector
business. Agricultural mitigation activities
need to be demonstrably 'additional' in
order to be viewed as of equal value to
emission reductions in other sectors of the
economy. Currently, most agriculturally re-
lated mitigation projects (indeed, projects
of all kinds), primarily involving voluntary
market systems, establish additionality on
a project-by-project basis, in which pro-
jects are tested by different criteria (e.g.
regulatory, financial, common practice) to
establish that the project activities do not
simply represent BAU.
Establishing additionality on a case-by-
case basis, as in the CDM and many voluntary
market standards, can entail development,
evaluation and verification costs. Alternatives
being explored are broader practice based or
'performance standards' that apply, for ex-
ample, for an entire class of projects within
a country or large region. However, setting
and applying performance standards also
faces significant challenges; first, in deter-
mining what constitutes an objective BAU
baseline, particularly in developing coun-
tries where information on current and past
land use and management practices is patchy
at best for many countries. Second, there
can be substantial variability for any set of
agricultural systems and practices viewed
at a regional or national scale, so setting a
too liberal performance standard will in-
crease the number of 'free riders', i.e. pro-
jects that are not really additional, whereas
too strict a performance standard will pre-
clude many projects with significant mitiga-
tion potential. Key to establishing workable
yet rigorous performance standards for po-
tential agricultural mitigation practices will
be more data and understanding of the
trends in the management practices that are
actually occurring on the landscape and
what the drivers are that influence manage-
ment choices.