Effectiveness of regulatory policy in curbing deforestation in a biodiversity hotspot

Abstract

Recent rates of deforestation on private lands in Australia rival deforestation hotspots around the world, despite conservation policies in place to avert deforestation. This study uses causal impact estimation techniques to determine if a controversial conservation policy-the Vegetation Management Act (VMA)-has successfully reduced deforestation of remnant trees in the Brigalow Belt South, a 21.6 Mha biodiversity hotspot in Queensland. We use covariate matching to determine the regulatory effect of the policy on deforestation rates over time, compared to two counterfactual scenarios representing upper and lower estimates of policy impact. The VMA significantly reduced the rate of remnant deforestation in the highest impact scenario, saving 17, 729±1733 ha during 2000-2016. In the lowest scenario, 'panic clearing' before and after enactment of the VMA minimized the amount of remnant forests saved and may have marginally increased deforestation relative to the counterfactual (−404±617 ha). At peak effectiveness, the VMA successfully counteracted the amount of remnant deforestation during 2010-2012, but this only represents 4.78% of the 371, 252 ha of remnant forests cleared in the bioregion since enactment in 1999. Thus, while deforestation rates in the region have substantially reduced since the policy was enacted, our results of positive yet limited direct regulatory impact suggests the policy's effectiveness is strongly confounded by other deforestation drivers, like changing socio-economic or climate conditions, as well as new social signals provoked by the policy. The mechanisms through which the policy influences deforestation behavior must be further investigated to ensure real, desirable change is achieved.

The ecological outcomes of biodiversity offsets under “no net loss” policies: A global review

“…Our review identified just one study meeting our inclusion criteria that compared NNL outcomes with a robust counterfactual (Gibbons et al., ). Generally, the quality of impact evaluations for NNL appear to be lagging behind those applied in other areas of conservation and environmental policy, such as payments for ecosystem services (Pynegar, Jones, Gibbons, & Asquith, ), protected areas (Miteva, Pattanayak, & Ferraro, ), commodity sustainability certification (Carlson et al., ), and forest policy (Simmons et al., ). Recognizing that the true causal impact of conservation policies can be confounded by biases in those receiving conservation treatments, there is an increase in applications of experimental, quasi‐experimental, and matching methods to improve our causal understanding of policy effectiveness (Ferraro & Hanauer, ).…”

Estimating counterfactuals for evaluation of ecological and conservation impact: an introduction to matching methods

“…(2007) and Simmons et al . (2018)]. This approach is analogous to the procedure for selection of covariates described in Section IV.2.…”

Projected social costs of CO2 emissions from forest losses far exceed the sequestration benefits of forest gains under global change

“…We also assumed that the relatively strict vegetation clearing regulations observed between 2007 and 2014 influence clearing behaviour similarly throughout the projection period . While our analysis captures the effect of clearing regulations during the model calibration period (Evans, 2016;Marcos-Martinez et al, 2018), changes to such regulations could lead to forest cover changes well outside of the ranges presented here (Simmons et al, 2018c).…”