No abstract
Marine benthic habitats are modified by a number of human-related disturbances. When these disturbances occur at large scales over areas of high environmental variability, it is difficult to assess impacts using metrics such as species richness or individual species distributions because of varying species-specific responses to environmental drivers (e.g., exposure, sediment, temperature). Impact assessment can also be problematic when assessed at broad spatial scales because of regional heterogeneity of species pools. Even when effects on individual species can be detected, it is difficult to upscale from individual species to ecosystem scale effects. Here, we use a functional group approach to assess broad scale patterns in ecological processes with respect to fishing and environmental drivers. We used data from field surveys of benthic communities from two large, widely separated areas in New Zealand's EEZ (Chatham Rise and Challenger Plateau). We assigned 828 taxonomic units (most identified to species) into functional groups related to important ecosystem processes and likely sensitivity to, and recovery from, fishing disturbance to the seafloor. These included: opportunistic early colonists; substrate stabilisers (e.g., tube mat formers); substrate destabilisers; shell hash-creating species; emergent epifauna; burrowers; and predators and scavengers. Effects of fishing disturbance on benthic functional composition were observed, even at this broad spatial scale. Responses varied between functional groups, with some being tolerant of fishing impacts and others showing rapid declines with minimal fishing effort. The use of a functional group approach facilitates assessment of impacts across regions and species, allowing for improved generalisations of impacts to inform management and decision making.
To support ongoing marine spatial planning in New Zealand, a numerical environmental classification using Gradient Forest models was developed using a broad suite of biotic and high-resolution environmental predictor variables. Gradient Forest modeling uses species distribution data to control the selection, weighting and transformation of environmental predictors to maximise their correlation with species compositional turnover. A total of 630,997 records (39,766 unique locations) of 1,716 taxa living on or near the seafloor were used to inform the transformation of 20 gridded environmental variables to represent spatial patterns of compositional turnover in four biotic groups and the overall seafloor community. Compositional turnover of the overall community was classified using a hierarchical procedure to define groups at different levels of classification detail. The 75-group level classification was assessed as representing the highest number of groups that captured the majority of the variation across the New Zealand marine environment. We refer to this classification as the New Zealand “Seafloor Community Classification” (SCC). Associated uncertainty estimates of compositional turnover for each of the biotic groups and overall community were also produced, and an added measure of uncertainty – coverage of the environmental space – was developed to further highlight geographic areas where predictions may be less certain owing to low sampling effort. Environmental differences among the deep-water New Zealand SCC groups were relatively muted, but greater environmental differences were evident among groups at intermediate depths in line with well-defined oceanographic patterns observed in New Zealand’s oceans. Environmental differences became even more pronounced at shallow depths, where variation in more localised environmental conditions such as productivity, seafloor topography, seabed disturbance and tidal currents were important differentiating factors. Environmental similarities in New Zealand SCC groups were mirrored by their biological compositions. The New Zealand SCC is a significant advance on previous numerical classifications and includes a substantially wider range of biological and environmental data than has been attempted previously. The classification is critically appraised and considerations for use in spatial management are discussed.
Underwater Television (UWTV) surveys provide fishery-independent stock size estimations of the Norway lobster (Nephrops norvegicus), based directly on burrow counting using the survey assumption of “one animal = one burrow”. However, stock size may be uncertain depending on true rates of burrow occupation. For the first time, 3055 video transects carried out in several Functional Units (FUs) around Ireland were used to investigate this uncertainty. This paper deals with the discrimination of burrow emergence and door-keeping diel behaviour in Nephrops norvegicus, which is one of the most commercially important fisheries in Europe. Comparisons of burrow densities with densities of visible animals engaged in door-keeping (i.e. animals waiting at the tunnel entrance) behaviour and animals in full emergence, were analysed at time windows of expected maximum population emergence. Timing of maximum emergence was determined using wave-form analysis and GAM modelling. The results showed an average level of 1 visible Nephrops individual per 10 burrow systems, depending on sampling time and depth. This calls into question the current burrow occupancy assumption which may not hold true in all FUs. This is discussed in relation to limitations of sampling methodologies and new autonomous robotic technological solutions for monitoring.
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