Catálogo de publicaciones - libros

This chapter explains the rationale for greenhouse gas emission estimation in tropical developing countries and why guidelines for smallholder farming systems are needed. It briefly highlights the innovations of the SAMPLES approach and explains how these advances fill a critical gap in the available quantification guidelines. The chapter concludes by describing how to use the guidelines.

This chapter presents a method for targeting landscapes with the objective of assessing mitigation options for smallholder agriculture. It presents alternatives in terms of the degree of detail and complexity of the analysis, to match the requirement of research and development initiatives. We address heterogeneity in land-use decisions that is linked to the agroecological characteristics of the landscape and to the social and economic profiles of the land users. We believe that as projects implement this approach, and more data become available, the method will be refined to reduce costs and increase the efficiency and effectiveness of mitigation in smallholder agriculture. The approach is based on the assumption that landscape classifications reflect differences in land productivity and greenhouse gas (GHG) emissions, and can be used to scale up point or field-level measurements. At local level, the diversity of soils and land management can be meaningfully summarized using a suitable typology. Field types reflecting small-scale fertility gradients are correlated to land quality, land productivity and quite likely to GHG emissions. A typology can be a useful tool to connect farmers’ fields to landscape units because it represents the inherent quality of the land and human-induced changes, and connects the landscape to the existing socioeconomic profiles of smallholders. The method is explained using a smallholder system from western Kenya as an example.

This chapter reviews methods and considerations for quantifying greenhouse gas (GHG) emissions and removals associated with changes in land-use and land-cover (LULC) in the context of smallholder agriculture. LULC change contributes a sizeable portion of global anthropogenic GHG emissions, accounting for 12.5 % of carbon emissions from 1990 to 2010 (Biogeosciences 9:5125–5142, 2012). Yet quantifying emissions from LULC change remains one of the most uncertain components in carbon budgeting, particularly in landscapes dominated by smallholder agriculture (Mitig Adapt Strateg Glob Chang 12:1001–1026, 2007; Biogeosciences 9:5125–5142, 2012; Glob Chang Biol 18:2089–2101, 2012). Current LULC monitoring methodologies are not well-suited for the size of land holdings and the rapid transformations from one land-use to another typically found in smallholder landscapes. In this chapter we propose a suite of methods for estimating the net changes in GHG emissions that specifically address the conditions of smallholder agriculture. We present methods encompassing a range of resource requirements and accuracy, and the trade-offs between cost and accuracy are specifically discussed. The chapter begins with an introduction to existing protocols, standards, and international reporting guidelines and how they relate to quantifying, analyzing, and reporting GHG emissions and removals from LULC change. We introduce general considerations and methodologies specific to smallholder agricultural landscapes for generating activity data, linking it with GHG emission factors and assessing uncertainty. We then provide methodological options, additional considerations, and minimum datasets required to meet the varying levels of reporting accuracy, ranging from low-cost high-uncertainty to high-cost low-uncertainty approaches. Technical step-by-step details for suggested approaches can be found in the associated website.

Standard methods for quantifying GHG emissions from soils tend to use either micrometeorological or chamber-based measurement approaches. The latter is the most widely used technique, since it can be applied at low costs and without power supply at remote sites to allow measurement of GHG exchanges between soils and the atmosphere for field trials. Instrumentation for micrometeorological measurements meanwhile is costly, requires power supply and a minimum of 1 ha homogeneous, flat terrain. In this chapter therefore we mainly discuss the closed chamber methodology for quantifying soil GHG fluxes. We provide detailed guidance on existing measurement protocols and make recommendations for selecting field sites, performing the measurements and strategies to overcome spatial variability of fluxes, and provide knowledge on potential sources of errors that should be avoided. As a specific example for chamber-based GHG measurements we discuss sampling and measurement strategies for GHG emissions from rice paddies.

Accurate measurement techniques are needed for determining greenhouse gas (GHG) emissions in order to improve GHG accounting estimates to IPCC Tiers 2 and 3 and enable the generation of carbon credits. Methane emissions from agriculture must be well defined, especially for ruminant production systems where national livestock inventories are generated. This review compares measurement techniques for determining methane production at different scales, ranging from in vitro studies to individual animal or herd measurements. Feed intake is a key driver of enteric methane production (EMP) and measurement of EMP in smallholder production systems face many challenges, including marked heterogeneity in systems and feed base, as well as strong seasonality in feed supply and quality in many areas of sub-Saharan Africa.

In vitro gas production studies provide a starting point for research into mitigation strategies, which can be further examined in respiration chambers or ventilated hood systems. For making measurements under natural grazing conditions, methods include the polytunnel, sulfur hexafluoride (SF), and open-path laser. Developing methodologies are briefly described: these include blood methane concentration, infrared thermography, pH, and redox balance measurements, methanogen population estimations, and indwelling rumen sensors.

This chapter presents methods to quantify carbon stocks and carbon stock changes in biomass of trees in agricultural landscapes. Specifically it assesses approaches for their applicability to smallholder farms and other tree enterprises in agricultural landscapes. Measurement techniques are evaluated across three criteria: accuracy, cost, and scale. We then recommend techniques appropriate for users looking to quantify carbon in tree biomass at the whole-farm and landscape scales. A basic understanding of the carbon cycle and the concepts of biomass assessment is assumed.

Smallholder agricultural systems in tropical and subtropical regions may have significantly contributed to greenhouse gas (GHG) emissions over the past number of decades. As a result, these systems currently offer large GHG mitigation potentials (e.g., soil organic carbon (SOC) sequestration), which can be realized through the implementation of good management and sustainable agricultural practices. In this chapter we synthesize current available methodologies designed to assess SOC stocks and stock changes. From this analysis, it becomes apparent that the design and subsequent implementation of any quantification and monitoring scheme envisaged for studies focusing solely on the soil component greatly differs from those developed for whole ecosystem accounting, not just in its approach, but also in the amount of resources needed to implement it within a given degree of accuracy. We provide analyses and recommendations on methods specifically dealing with quantification and assessment of SOC at both the individual farm and the landscape scale in smallholder agricultural systems.

Enhancing food security while contributing to mitigate climate change and preserving the natural resource base and vital ecosystem services requires the transition to agricultural production systems that are more productive, use inputs more efficiently, are more resilient to climate variability and emit fewer GHGs into the environment. Therefore, quantification of GHGs from agricultural production systems has been the subject of intensive scientific investigation recently to help researchers, development workers, and policy makers to understand how mitigation can be integrated into policy and practice. However, GHG quantification from smallholder production system should also take into account farm productivity to make such research applicable for smallholder farmers. Therefore, estimation of farm productivity should also be an integral consideration when quantifying smallholder mitigation potential. A wide range of methodologies have been developed to estimate crop yields from smallholder production systems. In this chapter, we present the synthesis of the state-of-the-art of crop yield estimation methods along with their advantages and disadvantages. Besides the plot level measurements and sampling, use of crop models and remote sensing are valuable tools for production estimation but detailed parameterization and validation of such tools are necessary before such tools can be used under smallholder production systems. The decision on which method to be used for a particular situation largely depends on the objective, scale of estimation, and desired level of precision. We emphasize that multiple approaches are needed to optimize the resources and also to have precise estimation at different scales.

Measurements of nutrient stocks and greenhouse gas (GHG) fluxes are typically collected at very local scales (<1 to 30 m) and then extrapolated to estimate impacts at larger spatial extents (farms, landscapes, or even countries). Translating point measurements to higher levels of aggregation is called . Scaling fundamentally involves conversion of data through integration or interpolation and/or simplifying or nesting models. Model and data manipulation techniques to scale estimates are referred to as scaling methods.

In this chapter, we first discuss the necessity and underlying premise of scaling and scaling methods. Almost all cases of agricultural GHG emissions and carbon (C) stock change research relies on disaggregated data, either spatially or by farming activity, as a fundamental input of scaling. Therefore, we then assess the utility of using empirical and process-based models with disaggregated data, specifically concentrating on the opportunities and challenges for their application to diverse smallholder farming systems in tropical regions. We describe key advancements needed to improve the confidence in results from these scaling methods in the future.

Trade-off analysis has become an increasingly important approach for evaluating system level outcomes of agricultural production and for prioritising and targeting management interventions in multi-functional agricultural landscapes. We review the strengths and weakness of different techniques available for performing trade-off analysis. These techniques, including mathematical programming and participatory approaches, have developed substantially in recent years aided by mathematical advancement, increased computing power, and emerging insights into systems behaviour. The strengths and weaknesses of the different approaches are identified and discussed, and we make suggestions for a tiered approach for situations with different data availability. This chapter is a modified and extended version of Klapwijk et al. (2014).