Methodology for Forecasting Fish Population Sizes Published in PNAS

The findings of a study conducted by Prof. Chih-Hao Hsieh along with an international team of scientists were published in the prestigious Proceedings of the National Academy of Sciences (April 17, 2013). The article, “Predicting climate effects on Pacific sardine,” presents a new analysis methodology for forecasting the influence of the associations between such non-linear variables as fishing, climate and ecological systems on fish populations. Prof. Chen conducts research at the Institute of Oceanography and the Institute of Ecology and Evolutionary Biology.

An urgent task involved in the effective operation and management of fisheries is to understand how the interactive effects between fishing and climate influence fish population sizes. Despite the large sums of money invested into research on this topic in the past, investigators had failed to come up with a reliable explanation.

Prof. Hsieh and his research partners believe the reason this problem has remained unsettled for decades is that scientists in the past researched the influences of only single variables, such as fishing activities and climate, separately on increases and decreases in fish populations, and that this created a major blind spot in their analyses. For instance, during the 1990s, research showed that increases in ocean temperatures led to rapid growth in sardine populations. However, the latest research from 2010 demonstrates that temperatures are not a major factor affecting population numbers and that the extrapolations of previous research were in fact incorrect or single-faceted misinterpretations.

The shortcomings of previous research stemmed from a failure to realize that associations between different variables emerge or dissolve spontaneously, sometimes producing positive effects and sometimes negative. That is to say, since a great variety of elements impact fish populations, we are unable to understand the problems confronting the sardine industry by using simply correlation analysis or modeling. It turns out that the impact of temperature on sardine populations can be positive and It can be negative; this depends on the interactive association between fish population conditions and the species.

Using this new methodology, Chen’s research team discovered that changes in sardine populations were influenced by the combined pressures of fishing, climate and variations in the ecological system. Prof. Chen and his partners conclude that investigators should not use single variables to infer their associations with population increases or decreases.

This new method avoids producing the abovementioned problem of single-sided explanations because it registers the dynamic relationships between all variables, not simply statistical correlations between pairs of variables. The team’s methodology can be utilized as a framework for researching variations in fish population sizes to understand the influences of the interactive associations between fishing activities, climate, ecological systems and species on the population of any single species.