We show that globally declining fisheries catch trends cannot be explained by random processes and are consistent with declining stock abundance trends. Future projections are inherently uncertain but may provide a benchmark against which to assess the effectiveness of conservation measures. Marine reserves and fisheries closures are among those measures and can be equally effective in tropical and temperate areas-but must be combined with catch-, effort-, and gear restrictions to meet global conservation objectives.
What is the role and status of marine biodiversity in sustaining ocean ecosystem services such as food supply, water quality control, and ecosystem stability? In our recent study, we addressed this question using meta-analysis of published experimental data, historical time series, global catch trends, and studies of marine reserves and fisheries closures (1). We found that in all of these independent data sets, biodiversity was positively related to productivity, stability, and the supply of ecosystem services. The comments by Wilberg and Miller (2), Jaenike (3), and Hölker et al. (4) focus almost exclusively on our usage of catch trends and our projection of a possible fisheries collapse after accelerated biodiversity loss.First, Wilberg and Miller (2) argue that under certain assumptions, a random process may generate declining trajectories in the global catch data that are similar to observed trends. They hypothesize that the increasing proportion of time series that fall below 10% of the maximum catch (our operational definition of collapse) could be a simple, accumulating function of time. If this were the case, recovery after a collapse would certainly occur. Yet in reality, recoveries of collapsed stocks are often rare, as discussed below. Furthermore, their supporting formula assumes an independent, identically distributed (iid) times series. However, the assumption of independence among data points does not hold for the autocorrelated random series that they use in their simulations, nor for the catch data that we used in (1).Despite these shortcomings, we were able to test Wilberg and Miller's hypothesis that increasing length of time series is correlated with increasing likelihood of collapse across large marine ecosystems (LMEs). We used all available fisheries catch data from the catch database of the United Nations Food and Agriculture Organization (FAO) and other sources, as outlined in (1). Results show that for the 64 LMEs included in our original study, there is no relation between the average start year of a fishery and the likelihood of a collapse (Fig. 1A). This means that ecosystems that have been fished for longer do not necessarily show more frequent collapses. Furthermore, there is an inverse correlation between the average lifetime of a fishery (the length of time over which it produced catches) and the proportion of fisheries that are collapsed (Fig. 1B). This refutes the idea that longer catch series are more prone to collapse than shorter ones, as suggested in (2).Wilb...
