Modeling biomass flows at the farm level: a discussion support tool for farmers

Abstract

-Many simulation models that are used to assess the impact of mixed farming systems have a high level of complexity that is not suitable for teaching farmers about the impacts of their practices. In this paper, we present a model that was developed and used with farmers as a discussion support tool to address the impacts of farming management strategies on farm resources. We assumed that the characterization of biomass flows at the farm level would provide a simple framework for designing a discussion support tool for farmers. The study was carried out in the semi-arid region of Brazil, where areas of native vegetation of the Caatinga Biome have been reduced in recent decades due to population pressure. In this region, simulation models are not used to discuss the impact of practices. We decided that a model for this purpose should: (1) be simple enough to be used by farmers, (2) be consistent with existing data, and (3) take into account the three main biomass management strategies. The model we built simulates biomass exports (harvest, animal intake, clearing vegetation of Caatinga), imports (purchase of fodder), and returns (animal manure) for farms with different vegetation types (Cenchrus ciliaris, Sorghum bicolour, Opuntia sp. and Caatinga native vegetation). We used the model to compare three management strategies over a 15-year period and found that the strategy that allows for the preservation of Caatinga vegetation is less sensitive to bad years but results in a reduced herd size. We validated the use of this model by testing it with farmers. We found that farmers were interested in using the model as a learning (38%), management (33%), or prospective tool (24%). This study shows that the dynamic modeling of biomass flows provides a simple and operational framework to analyze the impact of farming systems on farm resources with farmers. Contrary to current dynamic biophysical models that are based on extensive experimental data, this model does not give accurate predictions but allows both farmers and researchers to learn the impacts of farming systems. The complexity of the model should be increased progressively as farmers improve their understanding of the underlying processes. mixed crop-livestock farming systems / simulation model / Caatinga / sustainable development

Effects of potassium application on soil ecological resistance to Verticillium wilt of cotton (Gossypium hirsutum L.)

“…Previous studies indicated that the root exudates of resistant watermelon cultivars could inhibit spore germination and mycelium growth of Fusarium wilt, while the susceptible cultivars can increase the density of the pathogen (Wu et al 2010). This conclusion was also verified in this study, that is, under the same K application treatment, the disease index of V-wilt of resistant cotton varieties was lower than that of susceptible cotton varieties.…”

“…The root exudates played important roles in the occurrence and development of plant diseases, especially soil-borne disease. On the one hand, the exudates or some parts of them affected the growth and development of the pathogen directly (Wu et al 2006(Wu et al , 2010. On the other hand, the root exudation serves as an important carbon and energy source for microorganisms contained in the rhizosphere (Cheng et al 1996;Quian et al 1997;Yin et al 2009).…”

Validating a Whole Farm Modelling with Stakeholders: Evidence from a West African Case

“…Outputs of the model have an exploratory rather than a predictive interest, which would require a high level of precision. The comparison of magnitudes and trends between scenarios can support the farmer's reflexion and analysis regarding the changes to be implemented on the farm (Andrieu & Nogueira, 2010;Lisson et al, 2010). Nevertheless, reliable data sources must be used when the constants of the model are being set.…”

Supporting strategic thinking of smallholder dairy farmers using a whole farm simulation tool

“…This study provides insights on how simulation tools may be included in both participatory action research and advisory processes not only to test or promote innovative technologies, but also to help farmers redesign their production systems according to their own objectives. Rather than providing a close representation of reality, the objective is to nourish discussions between the farmer and researcher based on trends calculated for a given scenario, as was carried out by Andrieu and Nogueira (2010). Strategic decisions are taken under many uncertainties that are beyond the farmer's control, such as the economic context and climate.…”