Ocean colour data from the NASA Seaviewing Wide Field-of-view Sensor (SeaWiFS) was used to estimate chlorophyll a concentration around New Zealand on a monthly basis between September 1997 and May 2000. The performance of the SeaWiFS chlorophyll a algorithm (OC4v4) was investigated by comparing in situ measurements of the underwater light field with measurements of phytoplankton pigment concentration by High Performance Liquid Chromatography. The algorithm performed well for chlorophyll a concentrations below 0.6 mg m-3 but overestimated by a factor of two or more at higher concentrations. The average chlorophyll a concentration for New Zealand Exclusive Economic Zone was calculated as an indication of the overall productivity of the region and varied between 0.26 and 0.43 mg m-3 with no obvious relationship to the Southern Oscillation Index. New †

Around 30% of oceanic waters are high nitrate low chlorophyll (HNLC) where low iron levels limit algal growth. HNLC waters have mainly been studied using shipboard and lab experiments. Since 1997, remote‐sensing of phytoplankton via SeaWiFS Ocean Color has permitted monitoring of the constancy of this “HNLC condition,” i.e., spatial homogeneity and low temporal variability of chlorophyll over annual cycles. These trends can be exploited, as episodic iron inputs should be conspicuous by subsequent expression as iron‐elevated algal stocks. Subantarctic (SA) waters near New Zealand are HNLC, and the proximity of the arid Australian landmass, and the iron‐rich Subtropical Front, provide natural laboratories to detect episodic atmospheric and oceanic iron supply, respectively. Two approaches were used: Oceanic supply was inferred from episodic increases in chlorophyll concentrations in SA waters, detected using Ocean Color archives. Additional archives were used to confirm the oceanic provenance of iron supply, and identify supply mechanism(s). Atmospheric supply was assessed using data on source areas and loads for dust storms monitored in central Australia. Dust transport and its fate was assessed using air mass forward trajectories and SeaWiFS Ocean Color and Aerosol Optical Depth maps. During 1997–2001, episodic elevated chlorophyll events occurred in SA waters southeast of New Zealand. There was no evidence of these events being mediated by atmospheric iron supply; however, neither wind‐driven lateral advection or vertical mixing alone could account for these episodes. Dust storms, over this period sent plumes either into high iron SubTropical (ST) waters or into SA waters in early spring, when cells are probably light‐ rather than iron‐limited.

In October 2001, we observed a deep-ocean phytodetritus deposition event on Chatham Rise beneath the Subtropical Front (STF). The origin of this phytodetritus was probably an extensive phytoplankton bloom that occurred in the STF in the preceding weeks. We assessed the spatial distribution of the deposition event using video images from benthic lander and epibenthic trawl deployments and sediment pigment analyses at six sites on a north-south transect across Chatham Rise. High surficial sediment chlorophyll a concentrations were restricted spatially to the southern flank of Chatham Rise (350-1,200-m depth) with the highest values centered at ,750-m water depth (750 S). This southern 750 S site was also the only site where macroscopic phytodetritus was observed, coincident with elevated benthic biomass and sediment community respiration rates. At 750 S, phytodetritus resuspension was observed on video and corroborated by current meter, sediment trap, and optical 1 Corresponding author (s.nodder@niwa.co.nz). AcknowledgementsWe thank the officers and crew of RV Tangaroa, and numerous scientific personnel at NIOZ and NIWA, especially Henk Franken and Eilke Berghuis for lander support. Figures were drafted by Erika Mackay (NIWA). We appreciate the provision of unpublished organic carbon accumulation rates for Chatham Rise by Elisabeth Sikes (Rutgers University). We thank the SeaWiFS Project (Code 970.2) and the Distributed Active Archive Center (Code 902) at the Goddard Space Flight Center, Greenbelt, Maryland, for the production and distribution of the remotely sensed ocean color data, respectively. Thanks also to the two anonymous reviewers for their constructive comments.

We describe here the development of an ecosystem classification designed to underpin the conservation management of marine environments in the New Zealand region. The classification was defined using multivariate classification using explicit environmental layers chosen for their role in driving spatial variation in biologic patterns: depth, mean annual solar radiation, winter sea surface temperature, annual amplitude of sea surface temperature, spatial gradient of sea surface temperature, summer sea surface temperature anomaly, mean wave-induced orbital velocity at the seabed, tidal current velocity, and seabed slope. All variables were derived as gridded data layers at a resolution of 1 km. Variables were selected by assessing their degree of correlation with biologic distributions using separate data sets for demersal fish, benthic invertebrates, and chlorophyll-a. We developed a tuning procedure based on the Mantel test to refine the classification's discrimination of variation in biologic character. This was achieved by increasing the weighting of variables that play a dominant role and/or by transforming variables where this increased their correlation with biologic differences. We assessed the classification's ability to discriminate biologic variation using analysis of similarity. This indicated that the discrimination of biologic differences generally increased with increasing classification detail and varied for different taxonomic groups. Advantages of using a numeric approach compared with geographic-based (regionalisation) approaches include better representation of spatial patterns of variation and the ability to apply the classification at widely varying levels of detail. We expect this classification to provide a useful framework for a range of management applications, including providing frameworks for environmental monitoring and reporting and identifying representative areas for conservation.

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