Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Area of Science:

• Ecological forecasting
• Environmental science
• Sustainability science

Background:

• Current ecological forecasts often focus on long timescales, limiting their utility for near-term environmental decision-making.
• There is a need for ecological forecasts that allow for iterative refinement based on new observational data to test scientific theories.
• Near-term forecasting is essential for adaptive management and addressing societal needs under environmental uncertainty.

Purpose of the Study:

• To identify the immediate scientific and societal needs for iterative near-term ecological forecasting.
• To outline the opportunities and challenges associated with developing and implementing near-term ecological forecasts.
• To emphasize the importance of an iterative, learning-by-doing approach to advance ecological prediction.

Main Methods:

• Review of current ecological forecasting practices and limitations.
• Identification of advancements in data availability and computational methods.
• Analysis of challenges in data interoperability, latency, and uncertainty quantification.
• Discussion of necessary changes in scientific training, culture, and institutions.

Main Results:

• Increased data volume and accessibility present opportunities but also challenges in data integration and uncertainty quantification.
• Advances in computational and statistical methods offer potential for improved forecasting.
• Iterative forecasting requires enhanced cyberinfrastructure, forecast-specific theory, and methods.
• Cultural and institutional shifts are needed to support a more predictive ecological science.

Conclusions:

• Iterative, near-term ecological forecasting is vital for societal relevance and sustainable decision-making.
• Addressing challenges in data, methods, and cyberinfrastructure is critical for advancing ecological prediction.
• A shift towards a learning-by-doing approach will accelerate progress in ecological forecasting and its application.
• The time is now to make ecology more predictive to address pressing environmental questions.