Carbon net emission is a critical aspect of the environmental footprint in agricultural systems. However, the alternatives to describe soil organic carbon (SOC) changes associated with different agricultural management practices/land uses are limited. Here we provide an overview of carbon (C) stocks of non-forested areas of Uruguay to estimate SOC changes for different soil units affected by accumulated effects of crop and livestock production systems in the last decades. For this, we defined levels based on SOC losses relative to the original (reference) SOC stocks: 25% or less, between 25% and 50%, and 50% or more. We characterized the reference SOC stocks using three approaches: (1) an equation to derive the potential SOC capacity based on the clay and fine silt soil content, (2) the DayCent model to estimate the SOC stocks based on climate, soil texture and C inputs from the natural grasslands of the area, (3) an estimate of SOC using a proxy derived from remote sensing data (i.e., the Ecosystem Services Supply Index) that accounts for differences in C inputs. Depending on the used reference SOC, the soil units had different distributions of SOC losses within the zones defined by the thresholds. As expected, the magnitude of SOC changes observed for the different soil units was related to the relative frequency of annual crops, however, the high variability observed along the gradient of land uses suggests a wide space for increasing SOC with agricultural management practices. The assessment of the C stock preserved (CSP) belowground and the potential for increasing C accumulation or sequestration (CAP) are critical components of the C footprint of a given system. Thus, we propose a methodological road map to derive indicators of CSP and CAP at the farm level combining both, biogeochemical simulation models and conceptual models based on remote sensing data. We recognize at least three critical issues that require scientific and political consensus to implement the use of this propose: (1) how to define reference C stocks, (2) how to estimate current C stocks over large areas and in heterogeneous agricultural landscapes, and (3) what is a reasonable/acceptable threshold of C stocks reduction.
Identifying and assessing adaptation options are key pre-requisite steps to adaptation prioritization and effective adaptation planning. In this paper, we presented a systematic approach for adaptation stocktaking, combining a systematic mapping and an outcome-oriented and evidence-based assessment, illustrated using the case of The Gambia. This study systematically mapped 24 adaptation options that can potentially inform adaptation planning in The Gambia agriculture and food systems and assessed how the identified options contribute to the pillars of Climate-Smart Agriculture. Because of the paucity of evidence sources from The Gambia, we collated evidence from both The Gambia and the West Africa region. We found that many of the documented options, such as climate-resilient crop varieties, crop diversification, climate information use, and weather indexed-based insurance have the potential to increase agricultural productivity and income while building resilience to climate change. While several options, such as soil and water conservation practices can positively contribute to climate change mitigation, others such as manure and inorganic fertilizers can have no or negative impacts on mitigation. Agroforestry practices and System of Rice Intensification have the potential to make a triple impact. The paucity of evidence from The Gambia and the highly contextual and differential impacts of the identified adaptation options underscore the importance of careful consideration of barriers and enablers when developing and deploying policy and interventions to sustainably increase productivity and income while building resilience to climate risks and reducing GHGs emissions. Stakeholder engagement and participatory research action are crucial in selecting and testing the priority adaptation options which can maximize their potentials in specific agricultural and food system contexts, such as in The Gambia. Because of the heterogeneity in household vulnerability and socioecological circumstances, targeting options to the right contexts will also be crucial to avoid maladaptation. We highlighted key knowledge gaps in the understanding of the effectiveness and feasibility of the identified adaptation options in The Gambia. Beyond The Gambia, the approach can also be useful for and replicated in other least developed countries in the West African region, that are currently developing their National Adaptation Plan.