Long-term monitoring is essential for environmental management, particularly for filling knowledge gap and improving predictive capabilities. However, through a pre-occupation with long-term monitoring, we may be putting unnecessary resources into filling knowledge gap that are already filled. Once monitoring provides a sufficiently high level of confidence in a tested hypothesis, resources should be reallocated to other management actions or monitoring objectives. But how can this decision be made?
We used a case study of Golden Perch (Macquaria ambigua) spawning in response to river discharge to demonstrate a method to determine when continued data collection yields little further understanding regarding a cause-effect relationship. We used three techniques to examine the contribution of additional data: a) a historical 8-year monitoring dataset to evaluate the value of cumulative monitoring, b) bootstrapping the existing dataset to verify whether the conclusion from (a) is robust across different datasets of different lengths, and c) simulating synthetic monitoring data to validate the conclusion from (b).
Results from the observed monitoring data indicate that the model only requires 4 years of data before additional data provides limited additional understanding of the relationship between discharge and spawning. However, bootstrapping the same dataset and simulating data suggests 8-12 years might be necessary. With the case-study program having now collected 10 years of monitoring data, we contend that understanding of the flow-spawning relationships is now “good enough”.
This case study demonstrates that monitoring might not need huge time series before making the decision to reallocate monitoring effort. The idea of using resampled or synthetic monitoring data to demonstrate the value of monitoring can be applied to other endpoints and other monitoring programs. This approach supports evidence-based decision-making by informing when it is appropriate to review and potentially reallocate resources to other monitoring priorities, ultimately contributing to more efficient environmental management.