A Habitat-Based Framework for Communicating Natural Resource Condition

Progress in achieving desired environmental outcomes needs to be rigorously measured and reported for effective environmental management. Two major challenges in achieving this are, firstly, how to synthesize monitoring data in a meaningful way at appropriate temporal and spatial scales and, secondly, how to present results in a framework that allows for effective communication to resource managers and scientists as well as a broader general audience. This paper presents a habitat framework, developed to assess the natural resource condition of the urban Rock Creek Park (Washington, DC, USA), providing insight on how to improve future assessments. Vegetation and stream GIS layers were used to classify three dominant habitat types, Forest, Wetland, and Artificial-terrestrial. Within Rock Creek Park, Forest habitats were assessed as being in good condition (67% threshold attainment of desired condition), Wetland habitats to be in fair condition (49% attainment), and Artificial-terrestrial habitats to be in degraded condition (26% attainment), resulting in an assessed fair/good condition (60% attainment; weighted by habitat area) for all natural resources in Rock Creek Park. This approach has potential to provide assessment of resource condition for diverse ecosystems and provides a basis for addressing management questions across multiple spatial scales. 1. Introduction One of the key challenges of large-scale monitoring programs is to develop integrated and synthetic data products that can translate a multitude of diverse data into a format that can be readily communicated to decision-makers, policy developers, and the public [1–3]. Such timely syntheses of ecosystem condition can provide feedback to managers and stakeholders, so that the effectiveness of management actions as well as future management goals can be determined at multiple scales [4]. 1.1. Integrative Indices and Report Cards One approach to synthesizing data has been the development of multimetric indices to summarize the status of a community, such as stream fish, and then draw inferences on the status of the supporting ecosystem [5]. Metrics such as the fish index of biotic integrity (FIBI) and the benthic IBI have been widely applied, both internationally and regionally (e.g., streams in Maryland, USA). IBI metrics are seen as providing greater insight into ecosystem condition than physical measurements (e.g., water quality) alone, as biological communities provide an integrated summary of ecosystem condition over time [6–8]. However, in the absence of a rigorous process for