Biological assessment of western USA sandy bottom rivers based on modeling historical and current fish and macroinvertebrate data.

Biological monitoring is important for assessing the ecological condition of surface waters. However, there are challenges in determining what constitutes reference conditions, what assemblages should be used as indicators, and how assemblage data should be converted into quantitative indicator scores. In this study, we developed and applied biological condition gradient (BCG) modeling to fish and macroinvertebrate data previously collected from large, sandy bottom southwestern USA rivers. Such rivers are particularly vulnerable to altered flow regimes resulting from dams, water withdrawals and climate change. We found that sensitive ubiquitous taxa for both fish and macroinvertebrates had been replaced by more tolerant taxa, but that the condition assessment ratings based on fish and macroinvertebrate assemblages differed. We conclude that the BCG models based on both macroinvertebrate and fish assemblage condition were useful for classifying the condition of southwestern USA sandy bottom rivers. However, our fish BCG model was slightly more sensitive than the macroinvertebrate model to anthropogenic disturbance, presumably because we had historical fish data, and because fish may be more sensitive to dams and altered flow regimes than are macroinvertebrates.

A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms.

The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions, and the benefits that healthy coral reef ecosystems provide for many economies and societies. We developed a numeric (quantitative) BGC model for the coral reefs of Puerto Rico and the US Virgin Islands to transparently facilitate ecologically meaningful management decisions regarding these fragile resources. Here, reef conditions range from natural, undisturbed conditions to severely altered or degraded conditions. Numeric decision rules were developed by an expert panel for scleractinian corals and other benthic assemblages using multiple attributes to apply in shallow-water tropical fore reefs with depths <30 m. The numeric model employed decision rules based on metrics (e.g., % live coral cover, coral species richness, pollution-sensitive coral species, unproductive and sediment substrates, % cover by Orbicella spp.) used to assess coral reef condition. Model confirmation showed the numeric BCG model predicted the panel's median site ratings for 84% of the sites used to calibrate the model and 89% of independent validation sites. The numeric BCG model is suitable for adaptive management applications and supports bioassessment and criteria development. It is a robust assessment tool that could be used to establish ecosystem condition that would aid resource managers in evaluating and communicating current or changing conditions, protect water and habitat quality in areas of high biological integrity, or develop restoration goals with stakeholders and other public beneficiaries.

A biological condition gradient for coral reefs in the US Caribbean Territories: Part I. Coral narrative rules.

As coral reef condition and sustainability continue to decline worldwide, losses of critical habitat and their ecosystem services have generated an urgency to understand and communicate reef response to management actions, environmental contamination, and natural disasters. Increasingly, coral reef protection and restoration programs emphasize the need for robust assessment tools for protecting high-quality waters and establishing conservation goals. Of equal importance is the need to communicate assessment results to stakeholders, beneficiaries, and the public so that environmental consequences of decisions are understood. The Biological Condition (BCG) model provides a structure to evaluate the condition of a coral reef in increments of change along a gradient of human disturbance. Communication of incremental change, regardless of direction, is important for decision makers and the public to better understand what is gained or lost depending on what actions are taken. We developed a narrative (qualitative) Biological Condition Gradient (BCG) from the consensus of a diverse expert panel to provide a framework for coral reefs in US Caribbean Territories. The model uses narrative descriptions of biological attributes for benthic organisms to evaluate reefs relative to undisturbed or minimally disturbed conditions. Using expert elicitation, narrative decision rules were proposed and deliberated to discriminate among six levels of change along a gradient of increasing anthropogenic stress. Narrative rules for each of the BCG levels are presented to facilitate the evaluation of benthic communities in coral reefs and provide specific narrative features to detect changes in coral reef condition and biological integrity. The BCG model can be used in the absence of numeric, or quantitative metrics, to evaluate actions that may encroach on coral reef ecosystems, manage endangered species habitat, and develop and implement management plans for marine protected areas, watersheds, and coastal zones. The narrative BCG model is a defensible model and communication tool that translates scientific results so the nontechnical person can understand and support both regulatory and non-regulatory water quality and natural resource programs.