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AbstractBiodiversity offsets are increasingly adopted to mitigate the negative impacts of development activities on biodiversity. However, in practice, there are inconsistencies in how biodiversity offsets are understood and implemented. Based on interviews with environmental practitioners, the study sought to explore the conceptual understanding of biodiversity offsets among personnel involved in the design and implementation of offset schemes in Uganda. The study employed a 'technical use analysis' to seek personal interpretation and operationalization of the concept of biodiversity offsets. The results revealed that the concept tends to be simplified and adjusted to individual, project, and country contexts. The respondents had varied perceptions of biodiversity offsets in practice as compared to the theoretical concept. Biodiversity offsets were classified under five terms: trade-offs, payments, substitutes, compensations, and mitigation measures. The terms were derived from perceived inability of the measure to attain no net loss, and similarities of biodiversity components and services across impact and offset sites. Biodiversity offsets were thus considered no different from ordinary environmental conservation measures, contributing nothing unique to the conservation agenda. The study concludes that widespread implementation of biodiversity offsets under prevailing perceptions will escalate biodiversity loss. The study recommends emphasis on attaining no net loss through implementing outcome-based offsets as opposed to purpose-based offsets, that require delivering of 'no net loss' gains prior to projects being considered biodiversity offsets.

AbstractIncreasing farmers' adoption of sustainable nitrogen management practices is crucial for improving water quality. Yet, research to date provides ambiguous results about the most important farmer-level drivers of adoption, leaving high levels of uncertainty as to how to design policy interventions that are effective in motivating adoption. Among others, farmers' engagement in outreach or educational events is considered a promising leverage point for policy measures. This paper applies a Bayesian belief network (BBN) approach to explore the importance of drivers thought to influence adoption, run policy experiments to test the efficacy of different engagement-related interventions on increasing adoption rates, and evaluate heterogeneity of the effect of the interventions across different practices and different types of farms. The underlying data comes from a survey carried out in 2018 among farmers in the Central Valley in California. The analyses identify farm characteristics and income consistently as the most important drivers of adoption across management practices. The effect of policy measures strongly differs according to the nitrogen management practice. Innovative farmers respond better to engagement-related policy measures than more traditional farmers. Farmers with small farms show more potential for increasing engagement through policy measures than farmers with larger farms. Bayesian belief networks, in contrast to linear analysis methods, always account for the complex structure of the farm system with interdependencies among the drivers and allow for explicit predictions in new situations and various kinds of heterogeneity analyses. A methodological development is made by introducing a new validation measure for BBNs used for prediction.