Predicting the Distribution of Indicator Taxa of Vulnerable Marine Ecosystems in the Arctic and Sub-arctic Waters of the Nordic Seas

Burgos, Julian M.; Buhl‐Mortensen, Lene; Buhl-Mortensen, Pål; Ólafsdóttir, Steinunn H.; Steingrund, Pétur; Ragnarsson, Stefán Á.; Skagseth, Øystein

doi:10.3389/fmars.2020.00131

Cited by 47 publications

(39 citation statements)

References 137 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the framework of a full-scale baseline study of the region, an important component would be the assessment of the benthic communities, including the potential presence of vulnerable marine ecosystems (VMEs) (Burgos et al, 2020). VMEs are characterized by the uniqueness or rarity of the ecosystem, its fragility, the functional significance of its habitat, and the presence of key species with life-history traits that make recovery difficult and structural complexity (FAO, 2009).…”

Section: Discussionmentioning

confidence: 99%

Benthic Communities on the Mohn’s Treasure Mound: Implications for Management of Seabed Mining in the Arctic Mid-Ocean Ridge

et al. 2020

View full text Add to dashboard Cite

The Mohn's Treasure, described as an inactive sulfide mound, was discovered at 2,600m depth on the Arctic Mid-Ocean Ridge (AMOR) in 2002. In 2015, we conducted the first biological survey of Mohn's Treasure using remotely operated vehicle (ROV) photo transects and sampling. This site is covered by a thick layer of fine sediments, where hard substratum is only visible as rocky outcrops on ridges. The observed benthic community was typical of Arctic bathyal systems. A total of 46 species (identified as morphospecies) were recorded, with densities varying from 12.2 to 31.6 ind.m −2. The two most abundant phyla were Porifera and Echinodermata. The sediment is dominated by fields of the stalked crinoid Bathycrinus carpenterii, whereas areas of hard substratum were characterized by high abundances of several sponge species and associated fauna. Interest in commercial exploration and exploitation of minerals from massive sulfide deposits is rising globally, and the AMOR is being targeted for mineral exploration within Norwegian waters. Gathering baseline ecological data from these poorly known sites is thus urgent and essential if robust resource management measures are to be developed and implemented. The results of this ecological survey are discussed in relation to the designation of deep-sea vulnerable marine ecosystems (VMEs) and their implication in management and conservation of areas targeted by the emerging deep-sea mining industry.

show abstract

Section: Discussionmentioning

confidence: 99%

Benthic Communities on the Mohn’s Treasure Mound: Implications for Management of Seabed Mining in the Arctic Mid-Ocean Ridge

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In line with Burgos et al (2020) the following species were used as indicators of soft-bottom DSSAs in the study area: Hexadella cf. dedritifera, Geodia atlantica, Geodia barretti, Geodia macandrewii, Geodia sp., Steletta sp., and Stryphnus sp.…”

Section: Description Of Data and Data Processing Faunal Datamentioning

confidence: 99%

“…Also, we are interested to explore whether the presence of pre-selected species (as per a list of indicators, e.g., Burgos et al, 2020) is enough to isolate the target habitat, and we use the greater MarVid data to assess this question. Just what are these indicators indicative of, in terms of ecosystem structure and function?…”

Section: Introductionmentioning

confidence: 99%

Modeling the Distribution of Habitat-Forming, Deep-Sea Sponges in the Barents Sea: The Value of Data

et al. 2021

Self Cite

View full text Add to dashboard Cite

The use of species occurrence as a proxy for habitat type is widespread, probably because it allows the use of species distribution modeling (SDM) to cost-effectively map the distribution of e.g., vulnerable marine ecosystems. We have modeled the distribution of epibenthic megafaunal taxa typical of soft-bottom, Deep-Sea Sponge Aggregations (DSSAs), i.e., “indicators,” to discover where in the Barents Sea region this habitat is likely to occur. The following taxa were collectively modeled: Hexadella cf. dedritifera, Geodia spp., Steletta sp., Stryphnus sp. The data were extracted from MarVid, the video database for the Marine AREAl database for NOrwegian waters (MAREANO). We ask whether modeling density data may be more beneficial than presence/absence data, and whether using this list of indicator species is enough to locate the target habitat. We use conditional inference forests to make predictions of probability of presence of any of the target sponges, and total density of all target sponges, for an area covering a large portion of the Norwegian Barents Sea and well beyond the data’s spatial range. The density models explain <31% of the variance, and the probability models have high classificatory power (AUC > 0.88), depending on the variables/samples used to train the model. The predicted surfaces were then classified on the basis of a probability threshold (0.75) and a density threshold (13 n/100 m2) to obtain polygons of “core area” and “hotspots” respectively (zones). The DSSA core area comprises two main regions: the Egga shelf break/Tromsøflaket area, and the shelf break southwest of Røst bank in the Træna trench. Four hotspots are detected within this core area. Zones are evaluated in the light of whole-community data which have been summarized as taxon richness and density of all megafauna. Total megafaunal density was significantly higher inside the hotspots relative to the background. Richness was not different between zones. Hotspots appeared different to one another in their richness and species composition although no tests were possible. We make the case that the effectiveness of the indicator species approach for conservation planning rests on the availability of density data on the target species, and data on co-occurring species.

show abstract

“…Thus, we analyzed the variation inflation factors (VIFs) of environmental layers prior to its use in the modeling fitting procedure using a threshold of VIF = 10 to remove variables with strong collinearity. This VIF threshold was adopted in recent works, with positive results (Burgos et al, 2020;Morato et al, 2020). VIF analysis was done using the "usdm" package (Naimi et al, 2014).…”

Section: Selection Of Environmental Variablesmentioning

confidence: 99%

Predicted Shifts in the Distributions of Atlantic Reef-Building Corals in the Face of Climate Change

et al. 2021

View full text Add to dashboard Cite

Many species drive the diversity of ecosystems by adding structural complexity to the environment. In coral reefs, stony corals act as habitat-forming species, increasing niche availability for other organisms. Some coral species play key roles as reef builders due to their abundance or morpho-functional characteristics. Thus, changes in the distributions of these species can entail cascading effects in entire ecosystems. With climate change, many coral species are experiencing shifts in their distributions, threatening the preservation of coral reefs. Here, we projected the current and future distributions of three key reef builders of the Atlantic (Mussismilia hispida, Montastraea cavernosa, and the Siderastrea complex) under three relative concentration pathway scenarios: the most optimistic, the most pessimistic and one moderate scenario (RCP2.6, 4.5, and 8.5). Our models revealed that all the above species will undergo habitat loss in the future (2100) in the most pessimistic scenario, although new areas could become suitable, including regions in the eastern Atlantic Ocean. Additionally, when considering only its actual range of occurrence, M. hispida will lose habitats under all future scenarios. Moreover, in some regions of both the Tropical Northwestern Atlantic (TNA) and the Brazilian coast, these three species could disappear, with detrimental consequences for the associated communities. We highlight the need for an urgent change of course to guarantee functional reefs in the Atlantic in the future.

show abstract

Predicting the Distribution of Indicator Taxa of Vulnerable Marine Ecosystems in the Arctic and Sub-arctic Waters of the Nordic Seas

Cited by 47 publications

References 137 publications

Benthic Communities on the Mohn’s Treasure Mound: Implications for Management of Seabed Mining in the Arctic Mid-Ocean Ridge

Benthic Communities on the Mohn’s Treasure Mound: Implications for Management of Seabed Mining in the Arctic Mid-Ocean Ridge

Modeling the Distribution of Habitat-Forming, Deep-Sea Sponges in the Barents Sea: The Value of Data

Predicted Shifts in the Distributions of Atlantic Reef-Building Corals in the Face of Climate Change

Contact Info

Product

Resources

About