Vulnerable Marine Ecosystems Indicator Taxa Research Articles

Identifying vulnerable marine ecosystems: an image-based vulnerability index for the Southern Ocean seafloor

Abstract A significant proportion of Southern Ocean seafloor biodiversity is thought to be associated with fragile, slow growing, long-lived, and habitat-forming taxa. Minimizing adverse impact to these so-called vulnerable marine ecosystems (VMEs) is a conservation priority that is often managed by relying on fisheries bycatch data, combined with threshold-based conservation rules in which all “indicator” taxa are considered equal. However, VME indicator taxa have different vulnerabilities to fishing disturbance and more consideration needs to be given to how these taxa may combine to form components of ecosystems with high conservation value. Here, we propose a multi-criteria approach to VME identification that explicitly considers multiple taxa identified from imagery as VME indicator morpho-taxa. Each VME indicator morpho-taxon is weighted differently, based on its vulnerability to fishing. Using the “Antarctic Seafloor Annotated Imagery Database”, where 53 VME indicator morpho-taxa were manually annotated generating >40000 annotations, we computed an index of cumulative abundance and overall richness and assigned it to spatial grid cells. Our analysis quantifies the assemblage-level vulnerability to fishing, and allows assemblages to be characterized, e.g. as highly diverse or highly abundant. The implementation of this quantitative method is intended to enhance VME identification and contextualize the bycatch events.

True Size Matters for Conservation: A Robust Method to Determine the Size of Deep-Sea Coral Reefs Shows They Are Typically Small on Seamounts in the Southwest Pacific Ocean

Protection of vulnerable marine ecosystems (VME) is a critical goal for marine conservation. Yet, in many deep-sea settings, where quantitative data are typically sparse, it is challenging to correctly identify the location and size of VMEs. Here we assess the sensitivity of a method to identify coral reef VMEs based on bottom cover and abundance of the stony coral Solenosmilia variabilis on deep seamounts, using image data from a 2018 large survey off Tasmania, Australia. Whilst there was some detectable influence of varying coral cover and the abundance of live coral heads, the distribution of coral reef VMEs was not substantially shifted by changing these criteria or altering the attributes of a moving window used to spatially aggregate coral patches. Whilst applying stricter criteria for classifying VMEs predictably produced smaller areas of coral reef VME, these differences are not sizeable and were often negligible. A model prediction of the area of suitable habitat for coral reef in the Tasmanian area was much greater than that estimated in this study. Coral reef VMEs formed large contiguous ‘blankets’, mainly on the peaks and flanks of seamounts, but were absent from the continental slope where S. variabilis occurred at low abundance (cover) and/or had no living colonies. The true size of the Tasmanian coral reef VMEs ranged from 0.02 to 1.16 km2; this was relatively large compared to reefs of S. variabilis mapped on New Zealand seamounts, but is small compared to the scales used for regional model predictions of suitable habitat (typically 1 km2 grid cell), much smaller than the smallest units of management interest (100s – 1000s km²). That the method is not overly sensitive to the choice of criteria is highly encouraging in the context of designing spatial conservation measures that are robust, although its broader application, including to other VME indicator taxa, needs to be substantiated by scenario testing in different environments. Importantly, it should encourage uptake by the broader community (e.g. fishing and mining sectors) and forms the basis for better predictive VME models at larger spatial scales and beyond single taxa.

Cold-Water Corals and Other Vulnerable Biological Structures on a North Pacific Seamount After Half a Century of Fishing

Addressing growing threats of overexploitation to the world’s oceans is especially challenging in the High Seas, where limited data and international jurisdiction make it difficult to determine where and when conservation measures are necessary. Of particular concern are vulnerable marine ecosystems (VMEs)—special habitats on the seafloor that are highly sensitive to disturbance and slow to recover. To ensure the long-term conservation and sustainable use of marine resources, regional fisheries management organizations are committed to identifying the locations of VMEs and responding to prevent significant adverse impacts (SAIs). For over 50 years, Cobb Seamount—a shallow underwater volcanic mountain in the Northeast Pacific Ocean—has been commercially fished by multiple nations using various types of gear. Here we have assimilated data from fisheries records and a recent visual survey on the seamount. Our findings show a variety of habitat-forming emergent biological structures widely distributed on Cobb Seamount and generally depth-stratified into high-density assemblages (≥1 m-2). Our spatial analyses show that fishing has also been widely distributed, overlapping the habitat of the biological structures. We found fewer cold-water corals, sponges, and other biological structures in areas with higher recent fishing effort and documented evidence of fishing impacts, such as extensive mats of coral rubble and a high abundance of derelict fishing gear entangled with dead or damaged organisms. Based on the average density of “lost” gear (2,785±1,003 km-2), we can confidently estimate that hundreds of thousands of items of derelict fishing gear are currently entangled with the seafloor of Cobb Seamount and that these pose an ongoing threat to biological structures, the biogenic habitats they create, and the species they support. Such impacts can persist for decades or centuries to come. This study contributes and discusses new information on the condition and distribution of biological structures, VME indicator taxa, physically complex biogenic ecosystems, and human impacts on Cobb Seamount. These data will be necessary to identify the location(s) of potential VMEs and SAIs on this heavily fished seamount in the High Seas.

Application of association analysis for identifing indicator taxa of vulnerable marine ecosystems in the Emperor Seamounts area, North Pacific Ocean

Reflecting the growing interest in ecosystem-based fishery management, deep sea bottom fisheries are being called upon to minimize adverse impacts on vulnerable marine ecosystems (VMEs), communities of marine organisms susceptible to anthropogenic disturbance. Many fishery management organizations have introduced indicator-based management measures for VME conservation, such as encounter protocols, in which VME indicator species and bycatch weight thresholds are assigned. If the bycatch amount of the indicator species in a fishing operation exceeds the predetermined threshold, the fishing vessel halts the fishing operation and moves a certain distance away from the encounter point. However, the representativeness of VME indicator taxa has not been evaluated quantitatively. In this study, we analyzed the co-occurrence of benthic animals collected by scientific bottom tow-net surveys in the Emperor Seamounts area, North Pacific Ocean, to characterize benthic communities in the area and to examine the ability of six candidate indicator taxa (gorgonians, Alcyonacea excluding gorgonians, Antipatharia, Scleractinia, Stylasterina, and Porifera) to represent the local benthic communities. Cluster analysis revealed four clusters of benthic communities, each of which includes both sessile and mobile benthos: (1) gorgonians-Scleractinia community with many mobile benthic taxa and Pisces; (2) Porifera-Stylasterina community with Polychaeta and Bivalvia; (3) Antipatharia-Alcyonacea (excluding gorgonians) community with Cephalopoda; and (4) Zoanthidea-Pennatulacea community with Crinoidae and Holothuroidea. The first cluster included the largest number of taxa and showed strong tendencies of co-occurrence, possibly reflecting the habitat-providing function of gorgonians and Scleractinia as well as the common environmental preferences of filter feeders, which constitute major components of the cluster. We used association analysis to identify VME indicator species in the study area. Association analysis reveals relationships between items in the form of association rules, where the occurrence of an “antecedent” {A} implies the co-occurrence of a “consequent” {B}; {A} and {B} contain items, in this case, taxa. Association analysis applied to the co-occurrence data extracted many effective association rules that include gorgonians or Scleractinia as the consequent and many benthic taxa as antecedents. These results demonstrate that gorgonians and Scleractinia are effective VME indicators in the study area because they co-occur with many other benthic animals and represent VME characteristics such as functional significance as habitat and structural complexity as well as fragility and slow recovery from physical damage.

Kernel density surface modelling as a means to identify significant concentrations of vulnerable marine ecosystem indicators.

The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME) from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO) produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE) to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify “significant concentrations” of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores), and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here and elsewhere.