Coastal resource planning system: Integrating evaluation of ecological integrity and ecosystem services valuation

Efficient and effective coastal management decisions rely on knowledge of the impact of human activities on ecosystem integrity, vulnerable species, and valued ecosystem services—collectively, human impact on environmental quality (EQ). Ecosystem-based management (EBM) is an emerging approach to address the dynamics and complexities of coupled social-ecological systems. EBM “is intended to directly address the long-term sustainable delivery of ecosystem services and the resilience of marine ecosystems to perturbations” (Rosenberg and Sandifer, 2009). The lack of a tool that integrates human choices with the ecological connections between contributing watersheds and nearshore areas, and that incorporates valuation of ecosystem services, is a critical missing piece needed for effective and efficient coastal management. To address the need for an integrative tool for evaluation of human impacts on ecosystems and their services, Battelle developed the EcoVal™ Environmental Quality Evaluation System. The EcoVal system is an updated (2009) version of the EQ Evaluation System for Water Resources developed by Battelle for the U.S. Bureau of Reclamation (Dee et al., 1972). The Battelle EQ evaluation system has a thirty-year history of providing a standard approach to evaluate watershed EQ. This paper describes the conceptual approach and methodology of the updated EcoVal system and its potential application to coastal ecosystems. (PDF contains 4 pages)

The EBM-DPSER conceptual model: integrating ecosystem services into the DPSIR framework

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers.

Real-time climate monitoring using an AVHRR-based vegetation index

A normalized difference vegetation index (NDVI) has been produced and archived on a 1° latitude by 1° longitude grid between 55°S and 75°N. The many sources of data errors in the NDVI include cloud contamination, scan angle biases, changes in solar zenith angle, and sensor degradation. Week-to-week variability, primarily caused by cloud contamination and scan angle biases, can be minimized by temporally filtering the data. Orbital drift and sensor degradation introduces interannual variability into the dataset. These trends make the usefulness of a long-term climatology uncertain and limit the usefulness of the NDVI. Elimination of these problems should produce an index that can be used for climate monitoring.