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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 Victorias 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.

Spatial models of population dynamics have been proposed as a useful method for predicting the impacts of environmental change on biodiversity. Here, we demonstrate advances in dynamic landscape metapopulation modelling and its use as a decision support tool for evaluating the impacts of forest management scenarios. This novel modelling framework incorporates both landscape and metapopulation model stochasticity and allows their relative contributions to model output variance to be characterized. It includes a detailed sensitivity analysis, allowing defensible uncertainty bounds and the prioritization of future data gathering to reduce model uncertainties. We demonstrate this framework by modelling the landscape-level impacts of eight forest management scenarios on the red-backed salamander (Plethodon cinereus (Green, 1818)) in the boreal forest of Ontario, Canada, using the RAMAS Landscape package. The 100 year forest management scenarios ranged in intensity of timber harvesting and fire suppression. All scenarios including harvesting predicted decreases in salamander population size and the current style of forest management is predicted to produce a 9%-17% decrease in expected minimum population size compared with scenarios without harvesting. This method is amenable to incorporating many forms of environmental change and allows a meaningful treatment of uncertainty. Resume: Les modeles spatialises de dynamique des populations sont consideres comme une methode utile pour la prediction des impacts des changements environnementaux sur la biodiversite. Dans cet article, nous montrons les progres recents en modelisation de dynamique de metapopulations a l'echelle du paysage et l'utilite de cette methode comme outil d'aide a la decision pour evaluer les impacts de differents scenarios d'amenagement forestier. Ce nouveau cadre de modelisation prend en compte a la fois la stochasticite des modeles de paysage et de metapopulations et il permet de caracteriser leur contribution relative a la variance des resultats du modele. Il inclut une analyse de sensibilite detaillee qui permet d'etablir des limites d'incertitude defendables et la priorisation de nouvelles collectes de donnees pour reduire l'incertitude du modele. Nous presentons un exemple de ce cadre en modelisant les impacts a l'echelle paysagere de huit scenarios d'amenagement forestier sur la salamandre rayee (Plethodon cinereus (Green, 1818)) dans la foret boreale ontarienne, au Canada, au moyen du progiciel RAMAS Landscape. Les scenarios d'amenagement forestier d'une duree de 100 ans comprenaient differentes intensites de recolte ligneuse et de protection contre le feu. Les modeles ont predit une diminution de la taille des populations de salamandres pour tous les scenarios impliquant la recolte de bois et ils indiquent que les pratiques courantes d'amenagement forestier provoqueront une baisse de 9%-17% de la taille minimale de population esperee comparativement aux scenarios sans recolte. Cette methode de modelisation offre la souplesse necessaire pour tenir compte de plusieurs types de changements environnementaux et permet de traiter adequatement l'incertitude. [Traduit par la Redaction], Introduction There has been an increasing emphasis on modelling species' response to environmental change with spatial habitat models (Thompson et al. 2003; Thomas et al. 2004). However, correlative models of [...]

Biodiversity offsetting involves trying to compensate for the damage to species and habitats caused by development such as expanding cities, constructing mines and building dams, by creating an 'ecologically equivalent' [...]