Evaluating the impact of biodiversity offsetting on native vegetation| Global Change Biology | 2023 | Peer Reviewed | Original research | https://doi.org/10.1111/gcb.16801
Biodiversity offsetting is a globally influential policy mechanism for reconciling trade-offs between development and biodiversity loss. However, there is little robust evidence of its effectiveness. We evaluated the outcomes of a jurisdictional offsetting policy (Victoria, Australia). Offsets under Victoria’s Native Vegetation Framework (2002–2013) aimed to prevent loss and degradation of remnant vegetation, and generate gains in vegetation extent and quality. We categorised offsets into those with near-complete baseline woody vegetation cover (“avoided loss”, 2702 ha) and with incomplete cover (“regeneration”, 501 ha), and evaluated impacts on woody vegetation extent from 2008 to 2018. We used two approaches to estimate the counterfactual. First, we used statistical matching on biophysical covariates: a common approach in conservation impact evaluation, but which risks ignoring potentially important psychosocial confounders. Second, we compared changes in offsets with changes in sites that were not offsets for the study duration but were later enrolled as offsets, to partially account for self-selection bias (where landholders enrolling land may have shared characteristics affecting how they manage land). Matching on biophysical covariates, we estimated that regeneration offsets increased woody vegetation extent by 1.9%–3.6%/year more than non-offset sites (138–180 ha from 2008 to 2018) but this effect weakened with the second approach (0.3%–1.9%/year more than non-offset sites; 19–97 ha from 2008 to 2018) and disappeared when a single outlier land parcel was removed. Neither approach detected any impact of avoided loss offsets. We cannot conclusively demonstrate whether the policy goal of ‘net gain’ (NG) was achieved because of data limitations. However, given our evidence that the majority of increases in woody vegetation extent were not additional (would have happened without the scheme), a NG outcome seems unlikely. The results highlight the importance of considering self-selection bias in the design and evaluation of regulatory biodiversity offsetting policy, and the challenges of conducting robust impact evaluations of jurisdictional biodiversity offsetting policies.