Environmental control on the structure of echinoid assemblages in the Bellingshausen Sea (Antarctica)

Moyá, Francina; Saucède, Thomas; Manjón‐Cabeza, María Eugenia

doi:10.1007/s00300-012-1176-5

Cited by 13 publications

(11 citation statements)

References 40 publications

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“…In contrast, important changes are predicted in sea ice cover and seafloor temperatures (IPCC, ). They both are important drivers of SO communities (Peck, ; Waller, Worland, Convey, & Barnes, ) that determine the abundance, richness, and diversity of species assemblages (Moya, Saucede, & Manjón‐Cabeza, ). Sea ice cover also acts as a protection for benthic organisms by reducing potential UV‐B‐induced damage on organisms, particularly for those with planktonic larval stages (Gutt et al, ; Lister, Lamare, & Burritt, ).…”

Section: Discussionmentioning

confidence: 99%

“…In contrast, important changes are predicted in sea ice cover and seafloor temperatures (IPCC, 2018). They both are important drivers of SO communities (Peck, 2005;Waller, Worland, Convey, & Barnes, 2006) that determine the abundance, richness, and diversity of species assemblages (Moya, Saucede, & Manjón-Cabeza, 2012).…”

Section: In Total Antarctic Echinoid Species Distributed South Of Thmentioning

confidence: 99%

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Benthic ecoregionalization based on echinoid fauna of the Southern Ocean supports current proposals of Antarctic Marine Protected Areas under IPCC scenarios of climate change

Fabri‐Ruiz

Danis

Navarro

et al. 2020

Global Change Biology

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The Southern Ocean (SO) is among the regions on Earth that are undergoing regionally the fastest environmental changes. The unique ecological features of its marine life make it particularly vulnerable to the multiple effects of climate change. A network of Marine Protected Areas (MPAs) has started to be implemented in the SO to protect marine ecosystems. However, considering future predictions of the Intergovernmental Panel on Climate Change (IPCC), the relevance of current, static, MPAs may be questioned under future scenarios. In this context, the ecoregionalization approach can prove promising in identifying well‐delimited regions of common species composition and environmental settings. These so‐called ecoregions are expected to show similar biotic responses to environmental changes and can be used to define priority areas for the designation of new MPAs and the update of their current delimitation. In the present work, a benthic ecoregionalization of the entire SO is proposed for the first time based on abiotic environmental parameters and the distribution of echinoid fauna, a diversified and common member of Antarctic benthic ecosystems. A novel two‐step approach was developed combining species distribution modeling with Random Forest and Gaussian Mixture modeling from species probabilities to define current ecoregions and predict future ecoregions under IPCC scenarios RCP 4.5 and 8.5. The ecological representativity of current and proposed MPAs of the SO is discussed with regard to the modeled benthic ecoregions. In all, 12 benthic ecoregions were determined under present conditions, they are representative of major biogeographic patterns already described. Our results show that the most dramatic changes can be expected along the Antarctic Peninsula, in East Antarctica and the sub‐Antarctic islands under both IPCC scenarios. Our results advocate for a dynamic definition of MPAs, they also argue for improving the representativity of Antarctic ecoregions in proposed MPAs and support current proposals of Conservation of Antarctic Marine Living Resources for the creation of Antarctic MPAs.

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Section: Discussionmentioning

confidence: 99%

Section: In Total Antarctic Echinoid Species Distributed South Of Thmentioning

confidence: 99%

Benthic ecoregionalization based on echinoid fauna of the Southern Ocean supports current proposals of Antarctic Marine Protected Areas under IPCC scenarios of climate change

Fabri‐Ruiz

Danis

Navarro

et al. 2020

Global Change Biology

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“…The four selected species are known by a sufficient number of presence records to perform robust species distribution models. These four species are common on the Kerguelen Plateau and constitute substantial representatives of Antarctic benthic ecosystems (De Ridder, David, & Larrain, 1992;Díaz, Féral, David, Saucède, & Poulin, 2011;Hardy et al, 2011;Linse et al, 2008;Moya, Saucède, & Manjón-Cabeza, 2012;Poulin & Féral, 1995). Namely, we selected Abatus cordatus and Brisaster antarcticus, two species endemic to sub-Antarctic regions, and Ctenocidaris nutrix and Sterechinus diadema that present broader distribution ranges in the Southern Ocean ( Figure 1).…”

Section: Biological Recordsmentioning

confidence: 99%

Benthic species of the Kerguelen Plateau show contrasting distribution shifts in response to environmental changes

Guillaumot

Fabri‐Ruiz

Martin

et al. 2018

Ecology and Evolution

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Marine life of the Southern Ocean has been facing environmental changes and the direct impact of human activities during the past decades. Benthic communities have particularly been affected by such changes although we only slowly understand the effect of environmental changes on species physiology, biogeography, and distribution. Species distribution models (SDM) can help explore species geographic responses to main environmental changes. In this work, we modeled the distribution of four echinoid species with contrasting ecological niches. Models developed for [2005–2012] were projected to different time periods, and the magnitude of distribution range shifts was assessed for recent‐past conditions [1955–1974] and for the future, under scenario RCP 8.5 for [2050–2099]. Our results suggest that species distribution shifts are expected to be more important in a near future compared to the past. The geographic response of species may vary between poleward shift, latitudinal reduction, and local extinction. Species with broad ecological niches and not limited by biogeographic barriers would be the least affected by environmental changes, in contrast to endemic species, restricted to coastal areas, which are predicted to be more sensitive.

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“…Baroni‐Urbani & Buser's () index (hereafter Baroni for short) is broadly used in species distributional clustering and biotic regionalization (Márquez et al . ; Real, Olivero & Vargas ; Olivero, Real & Márquez ; Moya, Saucède & Manjón‐Cabeza ; Olivero, Márquez & Real ). It accounts for both shared presences and shared absences, but gives greater weight to presences.…”

Section: Calculating Fuzzy Similaritymentioning

confidence: 99%

fuzzySim: applying fuzzy logic to binary similarity indices in ecology

2015

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Summary1. Binary similarity indices are widely used in ecology, for example for detecting associations between species occurrence patterns, comparing regional and temporal species assemblages, and assessing beta diversity patterns, including spatial and temporal species loss and turnover. Such indices have widespread applications in biogeography, global change biology and biodiversity conservation. 2. Similarity indices are commonly calculated upon binary presence/absence (or sometimes modelled suitable/ unsuitable) data, which are generally incomplete and more categorical than their underlying natural patterns. Probable false absences are disregarded, amplifying the effects of data deficiencies and the scale dependence of the results. 3. Fuzzy occurrence data, with a degree of uncertainty attributed to localities where presence or absence cannot be safely assigned, could better reflect species distributions, compensating for incomplete knowledge and methodological errors. Similarity indices would therefore also benefit from accommodating such fuzzy data directly. 4. This study proposes fuzzy versions of the binary similarity indices most commonly used in ecology, so that they can be directly applied to continuous (fuzzy) rather than binary occurrence values, thus producing more realistic similarity assessments. Fuzzy occurrence can be obtained with several methods, some of which are also provided. The procedure is robust to data source disparities, gaps or other errors in species occurrence records, even for restricted species for which slight inaccuracies can affect substantial parts of their range. 5. The method is implemented in a free and open-source software package, fuzzySim, which is available for the R statistical software and under implementation for the QGIS geographic information system. It is provided with sample data and an illustrated tutorial suitable for non-experienced users.

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Environmental control on the structure of echinoid assemblages in the Bellingshausen Sea (Antarctica)

Cited by 13 publications

References 40 publications

Benthic ecoregionalization based on echinoid fauna of the Southern Ocean supports current proposals of Antarctic Marine Protected Areas under IPCC scenarios of climate change

Benthic ecoregionalization based on echinoid fauna of the Southern Ocean supports current proposals of Antarctic Marine Protected Areas under IPCC scenarios of climate change

Benthic species of the Kerguelen Plateau show contrasting distribution shifts in response to environmental changes

fuzzySim: applying fuzzy logic to binary similarity indices in ecology

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