Description: Commercial-scale mining for polymetallic nodules could have a major impact on the deepsea environment, but the effects of these mining activities on deep-sea ecosystems are very poorly known. The first commercial test mining for polymetallic nodules was carried out in 1970. Since then a number of small-scale commercial test mining or scientific disturbance studies have been carried out. Here we evaluate changes in faunal densities and diversity of benthic communities measured in response to these 11 simulated or test nodule mining disturbances using meta-analysis techniques. We find that impacts are often severe immediately after mining, with major negative changes in density and diversity of most groups occurring. However, in some cases, the mobile fauna and small-sized fauna experienced less negative impacts over the longer term. At seven sites in the Pacific, multiple surveys assessed recovery in fauna over periods of up to 26 years. Almost all studies show some recovery in faunal density and diversity for meiofauna and mobile megafauna, often within one year. However, very few faunal groups return to baseline or control conditions after two decades. The effects of polymetallic nodule mining are likely to be long term. Our analyses show considerable negative biological effects of seafloor nodule mining, even at the small scale of test mining experiments, although there is variation in sensitivity amongst organisms of different sizes and functional groups, which have important implications for ecosystem responses. Unfortunately, many past studies have limitations that reduce their effectiveness in determining responses. We provide recommendations to improve future mining impact test studies. Further research to assess the effects of test-mining activities will inform ways to improve mining practices and guide effective environmental management of mining activities.

Description: There is a strong economic interest in commercial deep‐sea mining of polymetallic nodules and therefore a need to define suitable preservation zones in the abyssal plain of the Clarion Clipperton Fracture Zone (CCZ). However, besides ship‐based multibeam data, only sparse continuous environmental information is available over large geographic scales. We test the potential of modelling meiofauna abundance and diversity on high taxonomic level on large geographic scale using a random forest approach. Ship‐based multibeam bathymetry and backscatter signal are the only sources for 11 predictor variables, as well as the modelled abundance of polymetallic nodules on the seafloor. Continuous meiofauna predictions have been combined with all available environmental variables and classified into classes representing abyssal habitats using k‐means clustering. Results show that ship‐based, multibeam‐derived predictors can be used to calculate predictive models for meiofauna distribution on a large geographic scale. Predicted distribution varies between the different meiofauna response variables. To evaluate predictions, random forest regressions were additionally computed with 1,000 replicates, integrating varying numbers of sampling positions and parallel samples per site. Higher numbers of parallel samples are especially useful to smoothen the influence of the remarkable variability of meiofauna distribution on a small scale. However, a high number of sampling positions is even more important, integrating a greater amount of natural variability of environmental conditions into the model. Synthesis and applications. Polymetallic nodule exploration contractors are required to define potential mining and preservation zones within their licence area. The biodiversity and the environment of preservation zones should be representative of the sites that will be impacted by mining. Our predicted distributions of meiofauna and the derived habitat maps are an essential first step to enable the identification of areas with similar ecological conditions. In this way, it is possible to define preservation zones not only based on expert opinion and environmental proxies but also integrating evidence from the distribution of benthic communities.