ABSTRACT
Intervening into agricultural systems necessarily includes risks, uncertainties, and ultimately unknown outcomes. Decision analysis embraces uncertainty through an interdisciplinary approach that involves relevant stakeholders in evaluating complex decisions. We applied decision analysis approaches to prioritize 21 farm management interventions, which could be considered in certification schemes for banana production. We estimated their contribution to climate change adaptation and mitigation as well as ecological outcomes. We used a general model that estimated the impacts of each intervention on adaptation (benefits minus costs), mitigation (global warming potential), ecological parameters (e.g., biodiversity and water and soil quality), and farming aspects (e.g., yield, implementation costs and production risks). We used expert and documented knowledge and presented uncertainties in the form of 90% confidence intervals to feed the model and forecast the changes in system outcomes caused by each intervention compared to a baseline scenario without the measure. By iterating the model function 10,000 times, we obtained probability distributions for each of the outcomes and farm management interventions. Our results suggest that interventions associated with nutrient management (e.g., composting and nutrient management plan) positively affect climate change adaptation, mitigation, and ecological aspects. Measures with no direct yield benefits (e.g., plastic reduction) correlate negatively with adaptation but have positive impacts on ecology. Creating buffer zones and converting low-productivity farmland (incl. unused land) also have positive ecological and adaptation outcomes. Decision analysis can help in prioritizing farm management interventions, which may vary considerably in their relationship with the expected outcomes. Additional work may be required to elaborate a comprehensive assessment of the underlying aspects modulating the impacts of a given measure on the evaluated outcome. Our analysis provides insights on the most promising interventions for banana plantations and may help practitioners and researchers in focusing further studies. Supplementary Information: The online version contains supplementary material available at 10.1007/s13593-022-00809-0.
ABSTRACT
Concentrations of arsenic and other trace elements in groundwater were examined at three villages (PT, POT and CHL) in the Kandal Province of Cambodia. Concentrations of arsenic in the groundwater ranged from 6.64 (in POT village) to 1543 microg/L (in PT village), with average and median concentrations of 552 and 353 microg/L, respectively. About 86% out of fifteen samples contained arsenic concentrations exceeding the WHO drinking water guidelines of 10 microg/L. Concentrations of arsenic (III) varied from 4 (in POT village) to 1334 microg/L (in PT village), with an average concentration of 470 microg/L. In addition, about 67%, 80% and 86% of the groundwater samples had higher concentrations for, respectively, barium, manganese and lead than the WHO drinking water guidelines. These results reveal that groundwater in Kandal Province is not only considerably contaminated with arsenic but also with barium, manganese and lead. A risk assessment study found that one sample (PT25) had a cumulative arsenic concentration (6758 mg) slightly higher than the threshold level (6750 mg) that could cause internal cancer in smelter workers with chronic exposure to arsenic from groundwater. High cumulative arsenic ingestion poses a health threat to the residents of Kandal Province.
