General discussion
7.2 Developing a generic framework to benchmark production of feed-crop livestock systems quantitatively
7.2.1 Discussion of the main findings
A generic method to benchmark livestock production quantitatively was not available at the start of this PhD project. To provide such a generic method, concepts of production ecology for livestock were defined in more detail in Chapter 2, building on the work of Van de Ven et al. (2003). Two major additions to the work of Van de Ven
et al. (2003) are the identification of the units and the proper system level suited to
benchmark livestock production under different agro-ecological conditions. Feed efficiency (kg animal-source food (ASF) per kg feed intake) at herd level was used to benchmark livestock systems, whereas production of ASF per hectare per year was used to benchmark feed-crop livestock systems (Fig. 7.1). Expressing livestock production per unit area is essential in the context of sustainable intensification. In literature, the production per animal (per year) is widely used as a benchmark for livestock production. This is useful to assess the scope to increase production of similar animals (e.g. kg milk per cow per year). The production per animal, however, does not account for the different life stages and purposes of animals in a herd. In addition, livestock production per farm can increase with an equal production per animal, but an increased feed efficiency, which indicates that feed efficiency at herd or flock level is a better benchmark to assess the scope to increase livestock production in relation to global food production (Gerssen-Gondelach et al., 2015). Benchmarking the scope to increase livestock production must account for feed production and feed intake of all animals in a herd, and not account for animals in specific life stages or animals with specific purposes only. Hence, the herd or flock level is most suited to investigate the scope to increase livestock production, as this level accounts for all animals within herds or flocks. The importance of accounting for feed intake fully has been emphasized in several descriptions of cattle models (Sanders and Cartwright, 1979, Naazie et al., 1997, Pang et al., 1999, Tess and Kolstad, 2000, Rufino et al., 2009). The concept of the smallest ‘herd unit’ was used to scale up from individual animals to the herd level. In Chapter 2, a herd unit was defined as one reproductive animal and its offspring, minus the replacement offspring (e.g. a heifer replacing a cow).
After the conceptual framework to assess the bio-physical scope to increase livestock production per unit area was laid out in Chapter 2 (Fig. 7.1), it was subsequently applied to beef production systems in the Charolais region of France. The diet used to calculate potential beef production of feed-crop livestock systems was defined as
Figure 7.1 Conceptual framework to quantify yield gaps of feed-crop livestock systems, as
defined in Chapter 2. Solid lines indicate the potential production of both feed crops and livestock production. Dashed lines indicate the actual production of feed crops and livestock. The green area indicates the actual production of animal-source food (ASF) per hectare. DM = dry matter.
an ad libitum diet consisting of 65% wheat and 35% hay. This diet was assumed to sustain potential growth of cattle. Potential production per hectare was calculated based on potential wheat and hay yields, and metabolisable energy requirements of cattle herds. The theoretical scope to increase beef production per unit area was defined as the difference between the potential and actual beef production per unit area in Chapter 2 (Fig. 7.1).
Applying concepts of production ecology to beef production in the Charolais region of France showed that yield gaps in feed-crop livestock systems were 79% of the potential beef production per hectare for an extensive cow-calf system, and 72% for a cow-calf-fattener system. These estimates were the first in literature for yield gaps of feed-crop livestock systems based on concepts of production ecology. Their
0 0 Li ves toc k pr oduc tion at her d lev el (k g ASF t -1 D M f eed)
Feed crop production (t DM ha-1 year-1)
Potential production (kg ASF ha-1 year-1)
Actual production (kg ASF ha-1 year-1)
The simple calculations in Chapter 2 did not account for the climate, feed quality, and available feed quantity. Since these factors are essential in livestock production, livestock modelling is required to assess the scope to increase livestock production more generically.
7.2.2 Limitations of the generic framework
Production levels and yield gaps of feed-crop livestock systems were expressed quantitatively in Chapter 2, but product quality (beef quality) was neglected. Nevertheless, trade-offs between product quantity and product quality exist in beef production systems. For example, potential production was estimated with higher culling rates than under actual production in Chapter 2. These higher culling rates resulted in a larger beef production per hectare compared to lower culling rates. In addition, higher culling rates resulted in a higher proportion of live weight derived from cows compared to lower culling rates. Live weight prices of Charolais cows, which reflect beef quality, are lower than live weight prices of calves (Réseaux d’Élevage Charolais, 2014). Hence, increasing culling rates increases the beef production per hectare, but may not necessarily increase beef quality. Another example is beef production from Angus cattle, which are kept for their high quality beef rather than their high beef production (Casey and Holden, 2006). Accounting for the trade-offs between beef quantity and quality is not straightforward, as assessing beef quality remains a complicated issue, despite its many quantitative indicators. Production levels and yield gaps were expressed as beef production per hectare per year, which accounts for beef production only. Beef farms in the Charolais region receive significant amounts of environmental subsidies for nature conservation and maintenance of landscapes (Veysset et al., 2005, Réseaux d’Élevage Charolais, 2014, Veysset et al., 2015). Landscape outputs, however, are not taken into account in the generic framework. In addition, cattle can have multiple outputs and functions, especially in tropical farming systems (Oosting et al., 2014, Udo et al., 2016). Examples of outputs are milk, beef, and manure, but also transport and traction. Livestock can even provide social status, and serve as an insurance or as a capital asset in regions where banks are inaccessible or unreliable (Udo et al., 2016). A method to account for multiple outputs is presented, therefore, in Section 7.5.2 of this chapter.