INTRODUCTION

Seabed impacts resulting from fish farm activities in the Marlborough Sounds, New Zealand, are currently determined by measuring chemical properties of sediment and changes in macro-infaunal diversity. These parameters are incorporated into the Enrichment Stage (ES) index (Keeley et al. 2012a, b, 2013), which provides regulators and producers with a measure of environmental impact at a specific site. The biological information included in the ES index includes a variety of statistics that are commonly used to describe benthic macrofauna assemblages (e.g. richness, diversity). Although very effective, this approach is expensive and slow, requires a high-level of taxonomic expertise, which is an area of shrinking capability worldwide, and hence imposes considerable and increasing costs to industry.

This project focuses on Objective 1 of a larger proposal to Seafood Innovations Ltd, which seeks to develop and implement a Next-Generation Sequencing (NGS) monitoring tool for the New Zealand fish farming industry. Objective 1 aims to improve knowledge on the spatio-temporal ecology of foraminifera. These micro-organisms (Protozoa) are extremely abundant and diverse in marine sediment and their small size, relatively uniform distribution and differing sensitivity to a range of pollutants make them very amenable for use in a molecular-based biomonitoring tool (Pawlowski et al. 2014; Pochon et al. in review). Our long-term goal is to develop a NGS-based 'Foraminiferal Community Index (FCI)' that may replace expensive and time-consuming macrobenthic infauna collection and identification. The tasks forming the objectives were as follows:

1.DNA/RNA sequencing and bioinformatics analysis. This task consisted of: i) generating foraminiferal-specific sequencing libraries from co-extracted environmental DNA and RNA molecules, ii) sequencing the libraries simultaneously using NGS IlluminaTM MiSeq technology, and iii) using bioinformatics tools to identify and enumerate the foraminiferal taxa present

2.Spatio-temporal statistical analysis of foraminiferal diversity. This task used data generated in Objective 1 and statistical techniques to investigate spatio-temporal changes or stability in foraminiferal communities along benthic enrichment gradients at four salmon farms over two years and from two locations (Marlborough Sounds and Stewart Island). These data were used to identify key bioindicator taxa.

Specifically, we aimed to answer the following questions:

1. How similar are foraminiferal communities among fish farms, regions, and years? 　

2. Do data generated using DNA provide the same answer as RNA?

3. Are the same key bioindicator foraminiferal species (Pawlowski et al. 2014; Pochon et al. in review) found at different farms?