Ecological studies about marine benthic communities received a major leap from the application of a variety of non-destructive sampling and mapping techniques based on underwater image and video recording. The well-established scientific diving practice consists in the acquisition of single path or ‘round-trip’ over elongated transects, with the imaging device oriented in a nadir looking direction. As it may be expected, the application of automatic image processing procedures to data not specifically acquired for 3D modelling can be risky, especially if proper tools for assessing the quality of the produced results are not employed. This paper, born from an international cooperation, focuses on this topic, which is of great interest for ecological and monitoring benthic studies in Antarctica. Several video footages recorded from different scientific teams in different years are processed with an automatic photogrammetric procedure and salient statistical features are reported to critically analyse the derived results. As expected, the inclusion of oblique images from additional lateral strips may improve the expected accuracy in the object space, without altering too much the current video recording practices.

Abstract. The waters of Aotearoa New Zealand span over 4.2 million km2 of the South Pacific Ocean and harbour a rich diversity of seafloor associated taxa. Due to the immensity and remoteness of the area, there are significant gaps in the availability of data to quantify and map the distribution of seafloor and demersal biodiversity, limiting effective management. In this study, we describe the development and accessibility of an online atlas of seabed biodiversity that aims to fill these gaps. Species distribution models were developed for 579 taxa across four taxonomic groups: demersal fish, reef fish, subtidal invertebrates and macroalgae. Spatial layers for taxa distribution based on habitat suitability were statistically validated and then, as a further check, evaluated by taxonomic experts to provide measures of confidence to guide the future use of these layers. Spatially explicit uncertainty (SD) layers were also developed for each taxon distribution. We generated layer-specific metadata, including statistical and expert evaluation scores, which were uploaded alongside the accompanying spatial layers to the open access database Zonodo. This database provides the most comprehensive source of information on the distribution of seafloor taxa for Aotearoa New Zealand and is thus an invaluable resource for managers, researchers and the public that will guide the management and conservation of seafloor communities.

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Connected ecosystems can be detrimentally affected by the same stressor, such as occurs when excess fine sediment moves from streams into estuaries. However, no previous study has directly compared sedimentation effects across these ecosystems. Responses of benthic macroinvertebrate communities to sedimentation were predicted to vary between streams and estuaries, because of intersystem differences in the physical environment and representation of species traits. To compare these responses, fine terrigenous sediment was added simultaneously to replicated plots in stream-run habitats and the adjacent estuary. Although sediment addition to streams caused reduced invertebrate densities after 1 week, no changes in taxon richness or consistent changes in community structure were detected, and densities had recovered another week later. In contrast, sediment addition to estuarine sites caused large declines in invertebrate densities and changes in community structure, which remained evident at the innermost sites 16 days after addition. Across both systems, sedimentation effects were detectable only for some of the common taxa, and biological traits were not predictive of effects. The potential for more severe effects in estuaries should be considered when predicting the implications of land-use changes that may increase sedimentation, and when setting guidelines for maintaining stream and estuarine condition.

Generating spatial predictionsThe spatial distribution for each taxon was estimated using ensemble SDMs that were generated using the combined outputs from flexible machine learning Boosted Regression Tree (BRT) and Random Forest (RF) models. In subsequent sections we describe the biological data (from four biotic groups: demersal fish, reef fish, subtidal invertebrates and macroalgae), the spatially explicit environmental data, and how these were combined to predict the taxa distributions used in the atlas of seabed biodiversity of Aotearoa New Zealand. Biological samples Demersal fishFish species records (n = 391,198) (including information on research cruise identifier, gear type, date, minimum and maximum depth of trawl, and GPS location) from 1979 -2016 were extracted from the research trawl database 'TRAWL' (Niwa, 2014(Niwa, , 2018. The data were groomed to only keep those records identified to species level, collected using bottom trawls and within the Aotearoa New Zealand Exclusive Economic Zone (EEZ) and Territorial Sea (TS). To minimise the effect of spatial bias in the occurrence data, species records were aggregated spatially to a 1 km grid resolution (Stephenson et al., 2020). Because of difficulties in correcting for differences in trawl methods, all catch records were converted into presence (Lundquist et al., 2020). To ensure distribution models were robust, only demersal fish species with ≥ 50 unique spatial locations were retained for analysis. The final dataset included presence/absence records of 235 demersal fish taxa at 28,599 unique sampling locations. Reef FishThe relative abundance of reef fishes were obtained from 467 SCUBA dives made around the coast of Aotearoa New Zealand over an 18-year period from November 1986 to December 2004 (for detailed methodology see Smith et al. (2013)). The data were groomed for a previous study by Smith et al. (2013) and all records were provided to species level identification. Species records were aggregated (to presence/absence) spatially to a 250 m grid resolution and included observations of 160 species at 339 unique sampling locations. To ensure distribution models were robust, only reef fish species with ≥ 35 unique spatial locations were retained for analysis. The final dataset included presence/absence records of 51 reef fish taxa at 429 unique sampling locations. Subtidal InvertebratesSubtidal invertebrate occurrence records (n = 127,330) (including GPS location, species name, collection date, and sampling gear used) from 1896 -2019 were extracted from TRAWL (n = 56,841), NIWA invert (n = 59,144), Te Papa (n = 2943) and Auckland Museum (n = 8402) databases. Only those records that had been classified to at least genus level and included information on sampling gear were extracted. Each record included information on the date, GPS location, survey and collection method. Across the four databases, 208 different methods were used to sample subtidal invertebrates, although many of these were name variants of commonly used sampling gears. To accou...