The hemisessile lifestyle and feeding strategies of Iosactis vagabunda (Actiniaria, Iosactiidae), a dominant megafaunal species of the Porcupine Abyssal Plain

Iosactis vagabunda Riemann-Zürneck, 1997 (Actiniaria, Iosactiidae) is a small endomyarian anemone, recently quantified as the greatest contributor to megafaunal density (48%; 2372 individuals ha−1) on the Porcupine Abyssal Plain (PAP). We used time-lapse photography to observe 18 individuals over a period of approximately 20 months at 8-h intervals, and one individual over 2 weeks at 20-mine intervals, and report observations on its burrowing activity, and both deposit and predatory feeding behaviours. We recorded the apparent subsurface movement of an individual from an abandoned burrow to a new location, and burrow creation there. Raptorial deposit feeding on settled phytodetritus particles was observed, as was predation on a polychaete 6-times the estimated biomass of the anemone. Though essentially unnoticed in prior studies of the PAP, I. vagabunda may be a key component of the benthic community, and may make a critical contribution to the carbon cycling at the PAP long-term time-series study site

Subtle variation in abyssal terrain induces significant change in benthic megafaunal abundance, diversity, and community structure

Bathymetric gradients in the deep sea are known to affect key benthic community characteristics such as diversity. However, most studies investigate large-scale bathymetric variation, while habitat heterogeneity related to modest bathymetric variation has generally been overlooked because of limitations to sampling technology. We investigate the role of modest bathymetric variation (~10 m water depth intervals) on an abyssal hill, and horizontal variation at the 0.1–10 km scale, in the structuring of abyssal megafaunal assemblages. We assess numerical density, biomass density, diversity, and assemblage composition using seabed photographs captured with an autonomous underwater vehicle and sediment characteristics determined from cores. We detect significant differences in sediment particle size and organic carbon content, in relation to modest topographic elevation, with a greater fraction of fine particles and organic carbon on the abyssal plain than the hill. Total megafaunal numerical and biomass density, diversity, and the numerical densities of feeding groups were significantly different with modest topographic elevation; similarly, megafaunal composition varied significantly between ~10 m depth intervals. In relation to mesoscale horizontal variation, we also record significant differences between megabenthic communities in two abyssal plain areas with no significant differences in measured sedimentary characteristics and only a 2 m difference in water depth. Differences in these communities were detected in terms of dominance, assemblage composition by density and biomass, and numerical densities of feeding groups. These observations strongly indicate that previous general concepts of the abyssal environment greatly underestimate this mesoscale heterogeneity, such that beta- and gamma-diversity in the abyss may be higher than estimated. Importantly, these results also have clear implications for the design and interpretation of environmental survey and monitoring programmes in the abyss

Abyssal hills - hidden source of increased habitat heterogeneity, benthic megafaunal biomass and diversity in the deep sea

Abyssal hills are the most abundant landform on Earth, yet the ecological impact of the resulting habitat heterogeneity on the wider abyss is largely unexplored. Topographic features are known to influence food availability and the sedimentary environment in other deep-sea habitats, in turn affecting the species assemblage and biomass. To assess this spatial variation, benthic assemblages and environmental conditions were compared at four hill and four plain sites at the Porcupine Abyssal Plain. Here we show that differences in megabenthic communities on abyssal hills and the adjacent plain are related to environmental conditions, which may be caused by local topography and hydrodynamics. Although these hills may receive similar particulate organic carbon flux (food supply from the surface ocean) to the adjacent plain, they differ significantly in depth, slope, and sediment particle size distribution. We found that megafaunal biomass was significantly greater on the hills (mean 13.45 g m−2, 95% confidence interval 9.25–19.36 g m−2) than the plain (4.34 g m−2, 95% CI 2.08–8.27 g m−2; ANOVA F(1, 6) = 23.8, p < 0.01). Assemblage and trophic compositions by both density and biomass measures were significantly different between the hill and plain, and correlated with sediment particle size distributions. Hydrodynamic conditions responsible for the local sedimentary environment may be the mechanism driving these assemblage differences. Since the ecological heterogeneity provided by hills in the abyss has been underappreciated, regional assessments of abyssal biological heterogeneity and diversity may be considerably higher than previously thought

Inter-annual species-level variations in an abyssal polychaete assemblage (Sta. M, NE Pacific, 4000 m)

Understanding the dynamics of abyssal community structure and function has become increasingly important as deep-sea resource exploitation and climate change pressures are expected to ramp up. This time-series study investigates macrofaunal polychaete dynamics at a station in the North East Pacific (Sta. M; 35˚ N 123˚ W, 4000 m, 1991-2011). Infaunal polychaete species were identified and their proxy biomass and proxy energy use rate estimated. The assemblage comprised 167 species, having a composition consistent with other abyssal areas globally. Significant changes in univariate and multivariate parameters (rank abundance distribution, Simpson’s diversity index, and species and functional group composition) were detected across 1991-2011. However, no change in biomass or energy use rate was apparent through the time-series. The largest changes in the polychaete assemblage coincided with both an increase in sinking particulate organic carbon flux to the seafloor in 2007, and a 40 km relocation of the sampling location to a site 100 m shallower, preventing a conclusive assessment of which might drive the observed variation. Analyses prior to the change of sampling location showed that the polychaete assemblage composition dynamics were primary driven by food supply variation. Changes in several species were also lagged to changes in POC flux by 4 to 10 months. The polychaete fauna exhibited a significant positive relationship between total density and total energy use rate, suggesting population-level tracking of a common resource (e.g. POC flux food supply). Neither compensatory nor energetic zero-sum dynamics were detected among the polychaete assemblage, but the results suggest that the latter occur in the macrofaunal community as a whole. The results do indicate (a) potential control of species composition, and the density of individual key species, by food supply, when the time-series prior to the sampling location was analysed separately, and (b) generally sensitive detection of environmental change by species-level analysis of the abyssal polychaete assemblage

Response of deep-sea deposit-feeders to detrital inputs: A comparison of two abyssal time-series sites

Biological communities on the abyssal plain are largely dependent on detritus from the surface ocean as their main source of energy. Seasonal fluctuations in the deposition of that detritus cause temporal variations in the quantity and quality of food available to these communities, altering their structure and the activity of the taxa present. However, direct observations of energy acquisition in relation to detritus availability across megafaunal taxa in abyssal communities are few. We used time-lapse photography and coincident measurement of organic matter flux from water column sediment traps to examine the impact of seasonal detrital inputs on resource acquisition by the deposit feeding megafauna assemblages at two sites: Station M (Northeast Pacific, 4000 m water depth) and the Porcupine Abyssal Plain Sustained Observatory (PAP-SO, Northeast Atlantic 4850 m water depth). At Station M, studied over 18-months, the seasonal particle flux was followed by a salp deposition event. At that site, diversity in types of deposit feeding was related to seabed cover by detritus. At PAP-SO, studied over 30 months, the seasonal particle flux consisted of two peaks annually. While the two study sites were similar in mean flux (~8.0 mgC m−2 d−1), the seasonality in the flux was greater at PAP-SO. The mean overall tracking at PAP-SO was five times that of Station M (1.9 and 0.4 cm2 h−1, respectively); both are likely underestimated because tracking by some common taxa at both sites could not be quantified. At both sites, responses of deposit-feeding megafauna to the input of detritus were not consistent across the taxa studied. The numerically-dominant megafauna (e.g. echinoids, large holothurians and asteroids) did not alter their deposit feeding in relation to the seasonality in detrital supply. Taxa for which deposit feeding occurrence or rate were correlated to seasonality in particle flux were relatively uncommon (e.g. enteropneusta), known to cache food (e.g. echiurans), or to be highly selective for fresh detritus (e.g. the holothurian Oneirophanta mutabilis). Thus, the degree of seasonality in deposit feeding appeared to be taxon-specific and related to natural history characteristics such as feeding and foraging modes

Improving the estimation of deep-sea megabenthos biomass: dimension to wet weight conversions for abyssal invertebrates

Deep-sea megafaunal biomass has typically been assessed by sampling with benthic sledges and trawls, but non-destructive methods, particularly photography, are becoming increasingly common. Estimation of individual wet weight in seabed photographs has been achieved using equations obtained from measured trawl-caught specimens for a limited number of taxa. However, a lack of appropriate conversion factors has limited estimation across taxa encompassing whole communities. Here we compile relationships between measured body dimensions and preserved wet weights for a comprehensive catalogue of abyssal epibenthic megafauna, using ~47,000 specimens from the Porcupine Abyssal Plain (NE Atlantic) housed in the Discovery Collections. The practical application of the method is demonstrated using an extremely large dataset of specimen measurements from seabed photographs taken in the same location. We also collate corresponding field data on fresh wet weight, to estimate the impact of fixation in formalin and preservation in industrial denatured alcohol on the apparent biomass. Taxa with substantial proportions of soft tissues lose 35 to 60% of their wet weight during preservation, while those with greater proportions of hard tissues lose 10 to 20%. Our total estimated fresh wet weight biomass of holothurians and cnidarians in the photographic survey was ~20 times the previous estimates of total invertebrate biomass based on trawl catches. This dramatic uplift in megabenthic biomass has significant implications for studies of standing stocks, community metabolism, and numerical modelling of benthic carbon flows

A generalised volumetric method to estimate the biomass of photographically surveyed benthic megafauna

Biomass is a key variable for understanding the stocks and flows of carbon and energy in the environment. The quantification of megabenthos biomass (body size ≥ 1 cm) has been limited by their relatively low abundance and the difficulties associated with quantitative sampling. Developments in robotic technology, particularly autonomous underwater vehicles, offer an enhanced opportunity for the quantitative photographic assessment of the megabenthos. Photographic estimation of biomass has typically been undertaken using taxon-specific length-weight relationships (LWRs) derived from physical specimens. This is problematic where little or no physical sampling has occurred and/or where key taxa are not easily sampled. We present a generalised volumetric method (GVM) for the estimation of biovolume as a predictor of biomass. We validated the method using fresh trawl-caught specimens from the Porcupine Abyssal Plain Sustained Observatory (northeast Atlantic), and we demonstrated that the GVM has a higher predictive capability and a lower standard error of estimation than the LWR method. GVM and LWR approaches were tested in parallel on a photographic survey in the Celtic Sea. Among the 75% of taxa for which LWR estimation was possible, highly comparable biomass values and distribution patterns were determined by both methods. The biovolume of the remaining 25% of taxa increased the total estimated standing stock by a factor of 1.6. Additionally, we tested inter-operator variability in the application of the GVM, and we detected no statistically significant bias. We recommend the use of the GVM where LWRs are not available, and more generally given its improved predictive capability and its independence from the taxonomic, temporal, and spatial, dependencies known to impact LWRs

The Dynamical State and Mass-Concentration Relation of Galaxy Clusters

We use the Millennium Simulation series to study how the dynamical state of dark matter halos affects the relation between mass and concentration. We find that a large fraction of massive systems are identified when they are substantially out of equilibrium and in a particular phase of their dynamical evolution: the more massive the halo, the more likely it is found at a transient stage of high concentration. This state reflects the recent assembly of massive halos and corresponds to the first pericentric passage of recently-accreted material when, before virialization, the kinetic and potential energies reach maximum and minimum values, respectively. This result explains the puzzling upturn in the mass-concentration relation reported in recent work for massive halos; indeed, the upturn disappears when only dynamically-relaxed systems are considered in the analysis. Our results warn against applying simple equilibrium models to describe the structure of rare, massive galaxy clusters and urges caution when extrapolating scaling laws calibrated on lower-mass systems, where such deviations from equilibrium are less common. The evolving dynamical state of galaxy clusters ought to be carefully taken into account if cluster studies are to provide precise cosmological constraints.Comment: 8 Pages. Minor changes to match published versio

Automated classification of fauna in seabed photographs: The impact of training and validation dataset size, with considerations for the class imbalance

Machine learning is rapidly developing as a tool for gathering data from imagery and may be useful in identifying (classifying) visible specimens in large numbers of seabed photographs. Application of an automated classification workflow requires manually identified specimens to be supplied for training and validating the model. These training and validation datasets are generally generated by partitioning the available manual identified specimens; typical ratios of training to validation dataset sizes are 75:25 or 80:20. However, this approach does not facilitate the desired scalability, which would require models to successfully classify specimens in hundreds of thousands to millions of images after training on a relatively small subset of manually identified specimens. A second problem is related to the ‘class imbalance’, where natural community structure means that fewer specimens of rare morphotypes are available for model training. We investigated the impact of independent variation of the training and validation dataset sizes on the performance of a convolutional neural network classifier on benthic invertebrates visible in a very large set of seabed photographs captured by an autonomous underwater vehicle at the Porcupine Abyssal Plain Sustained Observatory. We tested the impact of increasing training dataset size on specimen classification in a single validation dataset, and then tested the impact of increasing validation set size, evaluating ecological metrics in addition to computer vision metrics. Computer vision metrics (recall, precision, F1-score) indicated that classification improved with increasing training dataset size. In terms of ecological metrics, the number of morphotypes recorded increased, while diversity decreased with increasing training dataset size. Variation and bias in diversity metrics decreased with increasing training dataset size. Multivariate dispersion in apparent community composition was reduced, and bias from expert-derived data declined with increasing training dataset size. In contrast, classification success and resulting ecological metrics did not differ significantly with varying validation dataset sizes. Thus, the selection of an appropriate training dataset size is key to ensuring robust automated classifications of benthic invertebrates in seabed photographs, in terms of ecological results, and validation may be conducted on a comparatively small dataset with confidence that similar results will be obtained in a larger production dataset. In addition, our results suggest that automated classification of less common morphotypes may be feasible, providing that the overall training dataset size is sufficiently large. Thus, tactics for reducing class imbalance in the training dataset may produce improvements in the resulting ecological metrics

Big in the benthos: future change of seafloor community biomass in a global, body size-resolved model

Deep-water benthic communities in the ocean are almost wholly dependent on near-surface pelagic ecosystems for their supply of energy and material resources. Primary production in sunlit surface waters is channelled through complex food webs that extensively recycle organic material, but lose a fraction as particulate organic carbon (POC) that sinks into the ocean interior. This exported production is further rarefied by microbial breakdown in the abyssal ocean, but a residual ultimately drives diverse assemblages of seafloor heterotrophs. Advances have led to an understanding of the importance of size (body mass) in structuring these communities. Here we force a size-resolved benthic biomass model, BORIS, using seafloor POC flux from a coupled ocean-biogeochemistry model, NEMO-MEDUSA, to investigate global patterns in benthic biomass. BORIS resolves 16 size-classes of metazoans, successively doubling in mass from approximately 1μg to 28mg. Simulations find a wide range of seasonal responses to differing patterns of POC forcing, with both a decline in seasonal variability, and an increase in peak lag times with increasing body size. However, the dominant factor for modelled benthic communities is the integrated magnitude of POC reaching the seafloor rather than its seasonal pattern. Scenarios of POC forcing under climate change and ocean acidification are then applied to investigate how benthic communities may change under different future conditions. Against a backdrop of falling surface primary production (-6.1%), and driven by changes in pelagic remineralisation with depth, results show that while benthic communities in shallow seas generally show higher biomass in a warmed world (+3.2%), deep-sea communities experience a substantial decline (-32%) under a high greenhouse gas emissions scenario. Our results underscore the importance for benthic ecology of reducing uncertainty in the magnitude and seasonality of seafloor POC fluxes, as well as the importance of studying a broader range of seafloor environments for future model development