Can meta-analysis be used as a decision-making tool for developing scenarios and causal chains in eco-hydrological systems? Case study in Florida

To date, there are a high volume of studies concerning climate change impact assessments in ecosystems. Meta-analysis, scenario development, and causal chains/loops have been used as tools in these assessments as well as in decision making either individually or combined in pairs. There exists a need to develop decision support tools that improve the linkage between climate-impacts research and planning, management, adaptation, and mitigation decisions by providing quantitative and timely information to stakeholders and managers. The overall goal is to address this need. A specific objective was to develop a decision support tool in eco-hydrological applications that combine three components: meta-analysis, scenario development, and causal chains/loop. The developed tool is novel, warranted, and timely. The use of the tool is demonstrated for Florida. The meta-analysis of 32 studies revealed precipitation changes ranged between +30% and -40%, and temperature changes ranged from +6 degrees C to -3 degrees C for Florida. Seven incremental scenarios were developed at 10% increments in the precipitation change range and nine scenarios with 1 degrees C increments in the temperature change range (driving forces). The causal chains/loops were developed using Driver-Pressure-State-Impact-Response framework for selected ecosystems and environment (e.g., agroecosystem, mangroves, water resources, and sea turtles) in Florida. The driving force puts pressure on the ecosystem or environment impacting their state, which in turn had a response (e.g., mitigation and adaptation strategies). The framework used indicators selected from studies on climate impact assessments (meta-analysis and others) for the selected ecosystems as well as author expertise on the topic to develop the chains/loops. The decision tool is applicable to stakeholders and any ecosystem within and outside of Florida.