Choice of activity data

Mineral soils Tier 1

Cropland systems are classified by practices that influence soil C storage. The default management classification system is provided in Figure 5.1. Inventory compilers should use this classification to categorize management systems in a manner consistent with the default Tier 1 stock change factors. This classification may be further developed for Tiers 2 and 3 approaches. In general, practices that are known to increase C storage, such as irrigation, mineral fertilization, organic amendments, cover crops and high residue yielding crops, have higher inputs, while practices that decrease C storage, such as residue burning/removal, bare fallow, and low residue crop varieties, have lower inputs. These practices are used to categorize management systems and then estimate the change in soil organic C stocks. Practices should not be considered that are used in less than 1/3 of a given cropping sequence (i.e., crop rotation), which is consistent with the classification of experimental data used to estimate the default stock change factors. Rice production, perennial croplands, and set-aside lands (i.e., lands removed from production) are considered unique management systems (see below).

Each of the annual cropping systems (low input, medium input, high input, and high input w/organic amendment) are further subdivided based on tillage management. Tillage practices are divided into no-till (direct seeding without primary tillage and only minimal soil disturbance in the seeding zone; herbicides are typically used for weed control), reduced tillage (primary and/or secondary tillage but with reduced soil disturbance that is usually shallow and without full soil inversion; normally leaves surface with >30% coverage by residues at planting) and full tillage (substantial soil disturbance with full inversion and/or frequent, within year tillage operations, while leaving <30% of the surface covered by residues at the time of planting). It is good practice only to consider reduced and no-till if they are used continuously (every year) because even an occasional pass with a full tillage implement will significantly reduce the soil organic C storage expected under the reduced or no-till regimes (Pierce et al., 1994; Smith et al., 1998). Assessing the impact of rotational tillage systems (i.e., mixing reduced, no-till and/or full tillage practices) on soil C stocks will require a Tier 2 method.

The main types of land-use activity data are: i) aggregate statistics (Approach 1), ii) data with explicit information on land-use conversions but without specific geo-referencing (Approach 2), or iii) data with explicit information on land-use conversions and geo-referencing (Approach 3), such as land-use and management inventories making up a statistically-based sample of a country's land area (see Chapter 3 for discussion of approaches). At a minimum, globally available land-use and crop production statistics, such as FAO databases (http://faostat.fao.org/), provide annual compilations of total land area by major land-uses, select management data (e.g., irrigated vs. non-irrigated cropland), land area in 'perennial' crops (i.e., vineyards, perennial herbaceous crops, and tree-based crops such as orchards) and annual crops (e.g., wheat, rice, maize, sorghum, etc.). FAO databases would be an example of aggregate data (Approach 1).

Management activity data supplement the land-use data, providing information to classify management systems, such as crop types and rotations, tillage practices, irrigation, manure application, residue management, etc. These data can also be aggregate statistics (Approach 1) or information on explicit management changes (Approach 2 or 3). Where possible, it is good practice to determine the specific management practices for land areas associated with cropping systems (e.g., rotations and tillage practice), rather than only area by crop. Remote sensing data are a valuable resource for land-use and management activity data, and potentially, expert knowledge is another source of information for cropping practices. It is good practice to elicit expert knowledge using methods provided in Volume 1, Chapter 2 (eliciting expert knowledge).

National land-use and resource inventories, based on repeated surveys of the same locations, constitute activity data gathered using Approach 2 or 3, and have some advantages over aggregated land-use and cropland management data (Approach 1). Time series data can be more readily associated with a particular cropping system (i.e., combination of crop type and management over a series of years), and the soil type can be determined by sampling or by referencing the location to a suitable soil map. Inventory points that are selected based on an appropriate statistical design also enable estimates of the variability associated with activity data, which can be used as part of a formal uncertainty analysis. An example of a survey using Approach 3 is the National Resource Inventory in the U.S. (Nusser and Goebel, 1997).

Activity data require additional in-country information to stratify areas by climate and soil types. If such information has not already been compiled, an initial approach would be to overlay available land cover/land-use maps (of national origin or from global datasets such as IGBP_DIS) with soil and climate maps of national origin or global sources, such as the FAO Soils Map of the World and climate data from the United Nations Environmental Program. A detailed description of the default climate and soil classification schemes is provided in Chapter 3, Annex 3A.5. The soil classification is based on soil taxonomic description and textural data, while climate regions are based on mean annual temperatures and precipitation, elevation, occurrence of frost, and potential evapotranspiration.

Tier 2

Tier 2 approaches are likely to involve a more detailed stratification of management systems than in Tier 1 (see Figure 5.1) if sufficient data are available. This can include further subdivisions of annual cropping input categories (i.e., low, medium, high, and high with amendment), rice cultivation, perennial cropping systems, and set-asides. It is good practice to further subdivide default classes based on empirical data that demonstrates significant differences in soil organic C storage among the proposed categories. In addition, Tier 2 approaches can involve a finer stratification of climate regions and soil types.

Tier 3

For application of dynamic models and/or a direct measurement-based inventory in Tier 3, similar or more detailed data on the combinations of climate, soil, topographic and management data are needed, relative to the Tiers 1 and 2 methods, but the exact requirements will depend on the model or measurement design.

Organic soils

Tier 1

In contrast to the mineral soil method, croplands on organic soils are not classified into management systems under the assumption that drainage associated with all types of management for crops stimulates oxidation of organic matter previously built up under a largely anoxic environment. However, in order to apply the method described in Section 2.3.3.1 (Chapter 2), croplands do need to be stratified by climate region and soil type (see Chapter 3, Annex 3A.5 for guidance on soil and climate classifications).

Similar databases and approaches as those outlined for Mineral Soils in the Tier 1 discussion can be used for deriving area estimates. The land area with organic soils that are managed for Cropland can be determined using an overlay of a land-use map on climate and soils maps. Country-specific data on drainage projects combined with land-use surveys can be used to obtain a more refined estimate of the relevant areas.

Tier 2

Tier 2 approaches may involve a stratification of management systems if sufficient data are available. This can include subdivisions of annual cropping systems by drainage class, crop type (Freibauer, 2003) or tillage disturbance. In addition, Tier 2 approaches can involve a finer stratification of climate regions.

Tier 3

Tier 3 approaches for organic soils are likely to include more detailed data on climate, soil, topographic and management data, relative to the Tiers 1 and 2 methods, but the exact requirements will depend on the model or measurement design.

Figure 5.1 Classification scheme for cropland systems. In order to classify cropland management systems, the inventory compiler should start at the top and proceed through the diagram answering questions (move across branches if answer is yes) until reaching a terminal point on the diagram. The classification diagram is consistent with default stock change factors in Table 5.5. C input classes (i.e., low, medium, high and high with organic amendment) are further subdivided by tillage practice.

Figure 5.1 Classification scheme for cropland systems. In order to classify cropland management systems, the inventory compiler should start at the top and proceed through the diagram answering questions (move across branches if answer is yes) until reaching a terminal point on the diagram. The classification diagram is consistent with default stock change factors in Table 5.5. C input classes (i.e., low, medium, high and high with organic amendment) are further subdivided by tillage practice.

Note:

1: Does not typically include grazing of residues in the field. 2: e.g. cotton, vegetables and tobacco.

3: Practices that increase C input above the amount typically generated by the low residues yielding varieties such as using organic amendments, cover crops/green manures, and mixed crop/grass systems.

4: Practices that increase C input by enhancing residue production, such as using irrigation, cover crops/green manures, vegetated fallows, high residue yielding crops, and mixed crop/grass systems. 5 Perennial cover without frequent harvest.

Note: Only consider practices, such as irrigation, residue burning/removal, mineral fertilizers, N-fixing crops, organic amendment, cover crops/green manures, low residue crop, or fallow, if used in at least 1/3 of cropping rotation sequence.

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