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1.
BMC Ecol Evol ; 24(1): 90, 2024 Jul 03.
Article in English | MEDLINE | ID: mdl-38956464

ABSTRACT

BACKGROUND: Assessing the historical dynamics of key food web components is crucial to understand how climate change impacts the structure of Arctic marine ecosystems. Most retrospective stable isotopic studies to date assessed potential ecosystem shifts in the Arctic using vertebrate top predators and filter-feeding invertebrates as proxies. However, due to long life histories and specific ecologies, ecosystem shifts are not always detectable when using these taxa. Moreover, there are currently no retrospective stable isotopic studies on various other ecological and taxonomic groups of Arctic biota. To test whether climate-driven shifts in marine ecosystems are reflected in the ecology of short-living mesopredators, ontogenetic changes in stable isotope signatures in chitinous hard body structures were analysed in two abundant squids (Gonatus fabricii and Todarodes sagittatus) from the low latitude Arctic and adjacent waters, collected between 1844 and 2023. RESULTS: We detected a temporal increase in diet and habitat-use generalism (= opportunistic choice rather than specialization), trophic position and niche width in G. fabricii from the low latitude Arctic waters. These shifts in trophic ecology matched with the Atlantification of the Arctic ecosystems, which includes increased generalization of food webs and higher primary production, and the influx of boreal species from the North Atlantic as a result of climate change. The Atlantification is especially marked since the late 1990s/early 2000s. The temporal patterns we found in G. fabricii's trophic ecology were largely unreported in previous Arctic retrospective isotopic ecology studies. Accordingly, T. sagittatus that occur nowadays in the high latitude North Atlantic have a more generalist diet than in the XIXth century. CONCLUSIONS: Our results suggest that abundant opportunistic mesopredators with short life cycles (such as squids) are good candidates for retrospective ecology studies in the marine ecosystems, and to identify ecosystem shifts driven by climate change. Enhanced generalization of Arctic food webs is reflected in increased diet generalism and niche width in squids, while increased abundance of boreal piscivorous fishes is reflected in squids' increased trophic position. These findings support opportunism and adaptability in squids, which renders them as potential winners of short-term shifts in Arctic ecosystems.


Subject(s)
Climate Change , Decapodiformes , Ecosystem , Food Chain , Animals , Arctic Regions , Climate Change/history , Carbon Isotopes/analysis , Nitrogen Isotopes/analysis , Diet/history
2.
Animals (Basel) ; 12(24)2022 Dec 15.
Article in English | MEDLINE | ID: mdl-36552473

ABSTRACT

Cephalopods are important in Arctic marine ecosystems as predators and prey, but knowledge of their life cycles is poor. Consequently, they are under-represented in the Arctic ecosystems assessment models. One important parameter is the change in ecological role (habitat and diet) associated with individual ontogenies. Here, the life history of Gonatus fabricii, the most abundant Arctic cephalopod, is reconstructed by the analysis of individual ontogenetic trajectories of stable isotopes (δ13C and δ15N) in archival hard body structures. This approach allows the prediction of the exact mantle length (ML) and mass when the species changes its ecological role. Our results show that the life history of G. fabricii is divided into four stages, each having a distinct ecology: (1) epipelagic squid (ML < 20 mm), preying mostly on copepods; (2) epi- and occasionally mesopelagic squid (ML 20−50 mm), preying on larger crustaceans, fish, and cephalopods; (3) meso- and bathypelagic squid (ML > 50 mm), preying mainly on fish and cephalopods; and (4) non-feeding bathypelagic gelatinous females (ML > 200 mm). Existing Arctic ecosystem models do not reflect the different ecological roles of G. fabricii correctly, and the novel data provided here are a necessary baseline for Arctic ecosystem modelling and forecasting.

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