The Ocean Health Index

A healthy ocean sustainably delivers a range of benefits to people now and in the future. The Ocean Health Index is the comprehensive framework used to quantify ocean-derived benefits to humans and to help inform sustainable ocean management using the best available information. Assessments using the OHI framework require synthesizing existing data representing those benefits, using methods that are reproducible and repeatable. Repeated assessments using the same methods enable quantifiable comparison of changes in ocean health through time, which can be used to inform policy and track progress.

Visit ( for more about the science and methods behind the Ocean Health Index, or ( for an overview of the Ocean Health Index project.

Abstract of published paper

Drivers and implications of change in global ocean health over the past five years

Growing international and national focus on quantitatively measuring and improving ocean health has increased the need for comprehensive, scientific, and repeated indicators to track progress towards achieving policy and societal goals. The Ocean Health Index (OHI) is one of the few indicators available for this purpose. Here we present results from five years of annual global assessment for 220 countries and territories, evaluating potential drivers and consequences of changes and presenting lessons learned about the challenges of using composite indicators to measure sustainability goals.

Globally scores have shown little change, as would be expected. However, individual countries have seen notable increases or declines due in particular to improvements in the harvest and management of wild-caught fisheries, the creation of marine protected areas (MPAs), and decreases in natural product harvest. Rapid loss of sea ice and the consequent reduction of coastal protection from that sea ice was also responsible for declines in overall ocean health in many Arctic and sub-Arctic countries. The OHI performed reasonably well at predicting near-term future scores for many of the ten goals measured, but data gaps and limitations hindered these predictions for many other goals.

Ultimately, all indicators face the substantial challenge of informing policy for progress toward broad goals and objectives with insufficient monitoring and assessment data. If countries and the global community hope to achieve and maintain healthy oceans, we will need to dedicate significant resources to measuring what we are trying to manage.

OHI scores and average change in scores 2012-2016

The map below shows scores (or annual change in score) for the selected goal for the 220 coastal countries and regions included in the OHI, and the histogram shows the distribution of scores across the regions.

To view scores for the overall Index, choose a “score by year” and select “Index” under Ocean Health Goal. These figures correspond to Figure 1 A/B in the paper. Score 2012 - 2016: Scores for the overall Index and each of the OHI goals and subgoals displayed for each region, for 2012 to 2016. To view scores for each OHI goal, choose a year and a goal from the dropdown menus. These figures correspond to Figures B and C in the paper.

Annual change 2016: Map of the slope estimates from a linear regression model of the Index scores from 2012 to 2016 for each region, for the overall Index as well as for each of the OHI goals and subgoals. The Index figure corresponds to Figure 1C/D in the published paper, while the per-goal figures correspond to Figures D, E, and F in the supporting information.

Global trends from 2012-2016

This graphic shows the average annual change in global status for each goal and subgoal, unweighted (blue dots) and weighted by size of Exclusive Economic Zone (EEZ, orange dots). Solid circles indicate trends significantly different from zero; open circles indicate trends that are not statistically significant.

Large differences between unweighted and weighted values (e.g. natural products and fisheries) result from countries with large EEZs having scores significantly different from the global average.

This plot corresponds to Fig 2 in the published paper.

Relationship between score and annual change in score

This figure shows OHI scores for 2016 versus the trend over the past 5 years for each region. Each dot represents one OHI region, comparing its score in 2016 to its overall trend. Red dashed lines indicate no change over time (horizontal line) and the mean Index score across regions (vertical line); the dark red line is the linear regression slope.

Regions with higher Index scores in 2016 that improved through time are in the top-right quadrant, and countries with lower scores that declined through time are in the bottom-left. Choose a georegion to view the significant differences in scores and trends within and among georegions (P < 0.001).

This plot corresponds to Fig 3 from the published paper.

Drivers of change in OHI scores from 2012-2016

Changes to countries’ individual goal scores varied and influenced their overall Index score. This plot shows how score changes for each goal contributed to the overall Index change for every coastal country. When countries are filtered by “High-mid-low,” the plot includes the 15 regions with largest increases and decreases in scores and 10 representative regions in between (denoted by grey background).

The size of the colored bars represents the magnitude of change for that goal. If the colored area is to the right of the zero line, it had a positive impact on the score; if the bar is to the left, it had a negative impact. It is important to note that minor change in an Index score can occur due to a wide range of possible combinations of changes in goal scores.

This plot corresponds to Fig 4 from the published paper and Fig G from the supporting information.

Evaluating the OHI model using 5 years of data.

The Ocean Health Index score for a given goal includes the current status and a prediction of “likely future status,” based on recent trends, pressures, and resilience. These figures compare the performance of the OHI model in tracking and predicting changes in status and likely future status. Select “Index” to the left to evaluate the overall index score (corresponding to Fig 5 in the published paper), or individual goals to evaluate predicted changes vs. observed changes within each goal (corresponding to Fig H from the SI). Lighter red lines indicate a one-to-one relationship, while dark red lines indicate the estimate from a linear regression model.

  • Top: OHI scores in 2012 versus 2016; clustering around the 1:1 line and high R2 values show that past scores are a strong predictor future scores.
  • Middle: “Likely future status” in 2012 (i.e., a prediction of status for 2016) versus observed status in 2016. High R2 values show that predictions of future status (i.e. “likely future status” from 2012) correlate strongly with observed future status (i.e. current status 2016).
  • Bottom: expected change in status (OHI “likely future status” from 2012 scenario minus current status from 2012) and the observed change (status in 2016 minus status in 2012). It appears the predicted changes bear little relation to observed changes, with observed changes generally being quite small relative to predicted changes.

Relationship between change in OHI score and rank

Each dot on this plot refers to a coastal country. Where the dot falls on the plot indicates the change in that country’s OHI score and rank among all of the countries from 2012 to 2016. The dark red line shows the estimated average relationship between score change and rank change, based on a linear regression model.

In some cases, countries with roughly the same change in score, such as the Republique du Congo and Gilbert Islands (Kiribati) (-7.52 vs. -7.89, respectively), can have very different changes in rank (-12 vs. -78). In other cases, countries may have similar change in rank but very different changes in scores (e.g. Republique du Congo vs. Saint Kitts and Nevis). This is because scores are not uniformly distributed (see distributions on the “Score maps” tab); change in score within a tight cluster of scores will result in larger changes in rank than a similar change outside of such a cluster. This suggests that absolute values for goal scores are a more useful indicator of condition than rank order, especially when tracking change over time.

This plot corresponds to Fig 6 from the published paper and Figs I and J from the SI.