Detecting the Effects of Deep-Seabed Nodule Mining: Simulations Using Megafaunal Data From the Clarion-Clipperton Zone

Jeff A Ardron,Erik Simon-Lledó,Daniel O B Jones,Henry A Ruhl

doi:10.3389/fmars.2019.00604

Abstract

The International Seabed Authority is in the process of preparing exploitation regulations for deep-seabed mining (DSM). DSM has the potential to disturb the seabed over wide areas, yet there is little information on the ecological consequences, both at the site of mining and surrounding areas where disturbance such as sediment smothering could occur. Of critical regulatory concern is whether the impacts cause “serious harm” to the environment. Using metazoan megafaunal data from the Clarion-Clipperton Zone (northern equatorial Pacific), we simulate a range of disturbances from very low to severe, to determine the effect on community-level metrics. Two kinds of stressors were simulated: one that impacts organisms based on their affinity to nodules, and another that applies spatially stochastic stress to all organisms. These simulations are then assessed using power analysis to determine the amount of sampling required to distinguish the disturbances. This analysis is limited to modelling lethal impacts on megafauna. It provides a first indication of the effect sizes and ecological nature of mining impacts that might be expected across a broader range of taxa. To detect our simulated ‘tipping point’, power analyses suggest impact monitoring samples should each have at least 500-750 individual megafauna; and, at least five such samples, as well as control samples should be assessed. In the region studied, this translates to approximately 1500 – 2300 m2 seabed per impact monitoring sample; i.e., 7500 - 11 500 m2 in total for a given location and/or habitat. Detecting less severe disturbances requires more sampling. The numerical density of individuals and Pielou’s evenness of communities appear most sensitive to simulated disturbances and may provide suitable ‘early warning’ metrics for monitoring. To determine the sampling details for detecting the desired threshold(s) for harm, statistical effect sizes will need to be determined and validated. The determination of what constitutes serious harm is a legal question that will need to consider socially acceptable levels of long-term harm to deep-sea life, and may change as new information becomes available. Monitoring details, data, and results including power analyses should be made fully available, to facilitate independent review and evidence-based policy decisions.

Highlights

Proposed in the 1960s, commercial scale deep-seabed mining (DSM) has not yet occurred for a variety of economic, technological, and political reasons (e.g., Glasby, 2000)
The data are from a photographic survey of a 5500 km2 rectangular region of seafloor centred on 122◦ 55 W 17◦ 16 N within the southwest corner of an “Area of Particular Environmental Interest” (APEI) designated by the International Seabed Authority (ISA) as APEI-6
To reliably detect the impacts of polymetallic nodule mining, before serious harm occurs, our results suggest the use of impact monitoring sampling unit sizes of at least 500–750 individuals each and a minimum replication of five of such samples collected in both disturbed and control sites

Summary

Introduction

Proposed in the 1960s, commercial scale deep-seabed mining (DSM) has not yet occurred for a variety of economic, technological, and political reasons (e.g., Glasby, 2000). We look at possible effects from the mining one type of deep-sea mineral resource – polymetallic nodules – in the Clarion-Clipperton Zone (CCZ) of the northern equatorial Pacific. When looking at historical nodule mining simulations, most sites are still significantly depauperate in most faunal groups assessed over decadal time-scales (Jones et al, 2017). Organisms of different sizes and functional groups typically exhibit a different sensitivity to mining impact experiments (Jones et al, 2017), with suspension feeding megafauna usually showing the clearest responses to disturbance over decadal scales, both within the directly disturbed area and outside of it (Vanreusel et al, 2016; Simon-Lledó et al, 2019c). Assessing each aspect of potential harm will require statistically robust environmental monitoring that is designed beforehand to be able to answer regulatory concerns (Jones et al, 2017, 2018a) – a focus of this paper

Methods

Results

Conclusion