Monitoring ecological recovery of reclaimed wellsites: Protocols for quantifying recovery on forested lands.

We developed a scientifically robust and financially sustainable monitoring protocol to enable a consistent assessment of ecological recovery of physical, chemical, and biological indicators at certified reclaimed industrial wellsites in forested lands in noutheastern Alberta. Using the developed protocols, data can be generated from measurement of soil, vegetation, and landscape indicators at reclaimed wellsites and adjacent reference sites. We selected the appropriate vegetation, soil, and habitat indicators for a long-term reclamation monitoring program and have provided sampling protocols for the selected indicators here. The protocols may be used to identify and prioritize indicators of reduced ecosystem health and to track ecological recovery of reclaimed sites over time. The development of these integrated monitoring protocols is a first step towards successful and consistent long-term monitoring to assess ecological recovery of certified wellsites in Alberta. These protocols can be applied to wellsites and other similar sized disturbances in other forested regions too.

A framework for adaptive monitoring of the cumulative effects of human footprint on biodiversity.

Effective ecological monitoring is imperative in a human-dominated world, as our ability to manage functioning ecosystems will depend on understanding biodiversity responses to anthropogenic impacts. Yet, most monitoring efforts have either been narrowly focused on particular sites, species and stressors - thus inadequately considering the cumulative effects of multiple, interacting impacts at scales of management relevance - or too unfocused to provide specific guidance. We propose a cumulative effects monitoring framework that integrates multi-scaled surveillance of trends in biodiversity and land cover with targeted evaluation of hypothesized drivers of change. The framework is grounded in a flexible conceptual model and uses monitoring to generate and test empirical models that relate the status of diverse taxonomic groups to the nature and extent of human "footprint" and other landscape attributes. An adaptive cycle of standardized sampling, model development, and model evaluation provides a means to learn about the system and guide management. Additional benefits of the framework include standardized data on status and trend for a wide variety of biodiversity elements, spatially explicit models for regional planning and scenario evaluation, and identification of knowledge gaps for complementary research. We describe efforts to implement the framework in Alberta, Canada, through the Alberta Biodiversity Monitoring Institute, and identify key challenges to be addressed.

Achieving conservation when opportunity costs are high: optimizing reserve design in Alberta's oil sands region.

Recent studies have shown that conservation gains can be achieved when the spatial distributions of biological benefits and economic costs are incorporated in the conservation planning process. Using Alberta, Canada, as a case study we apply these techniques in the context of coarse-filter reserve design. Because targets for ecosystem representation and other coarse-filter design elements are difficult to define objectively we use a trade-off analysis to systematically explore the relationship between conservation targets and economic opportunity costs. We use the Marxan conservation planning software to generate reserve designs at each level of conservation target to ensure that our quantification of conservation and economic outcomes represents the optimal allocation of resources in each case. Opportunity cost is most affected by the ecological representation target and this relationship is nonlinear. Although petroleum resources are present throughout most of Alberta, and include highly valuable oil sands deposits, our analysis indicates that over 30% of public lands could be protected while maintaining access to more than 97% of the value of the region's resources. Our case study demonstrates that optimal resource allocation can be usefully employed to support strategic decision making in the context of land-use planning, even when conservation targets are not well defined.