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1.
Glob Chang Biol ; 26(4): 2161-2180, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31919925

RESUMO

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.

2.
Ecol Evol ; 8(12): 6210-6225, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29988407

RESUMO

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.

3.
Zookeys ; (697): 1-20, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29134013

RESUMO

This database includes over 7,100 georeferenced occurrence records of sea urchins (Echinodermata: Echinoidea) obtained from samples collected in the Southern Ocean (+180°W/+180°E; -35°/-78°S) during oceanographic cruises led over 150 years, from 1872 to 2015. Echinoids are common organisms of Southern Ocean benthic communities. A total of 201 species is recorded, which display contrasting depth ranges and distribution patterns across austral provinces and bioregions. Echinoid species show various ecological traits including different nutrition and reproductive strategies. Information on taxonomy, sampling sites, and sampling sources are also made available. Environmental descriptors that are relevant to echinoid ecology are also made available for the study area (-180°W/+180°E; -45°/-78°S) and for the following decades: 1955-1964, 1965-1974, 1975-1984, 1985-1994 and 1995-2012. They were compiled from different sources and transformed to the same grid cell resolution of 0.1° per pixel. We also provide future projections for environmental descriptors established based on the Bio-Oracle database (Tyberghein et al. 2012).

4.
Zookeys ; (630): 1-17, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27917039

RESUMO

The present dataset provides a case study for species distribution modelling (SDM) and for model testing in a poorly documented marine region. The dataset includes spatially-explicit data for echinoid (Echinodermata: Echinoidea) distribution. Echinoids were collected during oceanographic campaigns led around the Kerguelen Plateau (+63°/+81°E; -46°/-56°S) since 1872. In addition to the identification of collection specimens from historical cruises, original data from the recent campaigns POKER II (2010) and PROTEKER 2 to 4 (2013-2015) are also provided. In total, five families, ten genera, and 12 echinoid species are recorded in the region of the Kerguelen Plateau. The dataset is complemented with environmental descriptors available and relevant for echinoid ecology and SDM. The environmental data was compiled from different sources and was modified to suit the geographic extent of the Kerguelen Plateau, using scripts developed with the R language (R Core Team 2015). Spatial resolution was set at a common 0.1° pixel resolution. Mean seafloor and sea surface temperatures, salinity and their amplitudes, all derived from the World Ocean Database (Boyer et al. 2013) are made available for the six following decades: 1955-1964, 1965-1974, 1975-1984, 1985-1994, 1995-2004, 2005-2012. Future projections are provided for several parameters: they were modified from the Bio-ORACLE database (Tyberghein et al. 2012). They are based on three IPCC scenarii (B1, AIB, A2) for years 2100 and 2200 (IPCC, 4th report).

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