In diesem Forschungsvorhaben sollen die Effekte von Habitatfragmentierung auf Nahrungsnetze untersucht werden. Als Modellsystem dient die trophische Kaskade 'Pflanze - Pilz/Blattschneiderameise - Prädator/Parasit' im Atlantischen Regenwald Brasiliens, eines der weltweit am stärksten gefährdeten Waldökosysteme. Seit langem wird eine Zunahme der Dichte und Diversität von Blattschneiderameisen (BSA) in gestörten Habitaten beobachtet. Die Gründe hierfür sind jedoch weitgehend ungeklärt. Die diesem Projekt zugrunde liegenden Arbeitshypothesen basieren auf der Annahme, dass sowohl die Kontrolle durch Resourcenqualität als auch durch Prädation und Parasitismus in fragmentierten Wäldern weniger effizient sind als in geschlossenen Waldsystemen. Zur Beurteilung der bottom-up-Kontrolle wird daher untersucht, ob (1) pflanzliche Abwehr, (2) BSA Nahrungsbreite, (3) -Aktionsradius und (4) -Herbivorierate in Waldfragmenten zunehmen. Die Effizienz der top-down Kontrolle wird darüber bestimmt ob (1) Prädationsrate sowie (2) Ameisen- und Pilzparasitierung in kontinuierlichen Wäldern zunehmen und (3) der Koloniegründungserfolg abnimmt. Die Evaluierung der einzelnen Parameter und ihrer relativen Bedeutung soll das Verständnis der funktionellen Rolle trophischer Interaktionen am Beispiel dieser Schlüsselarten neotropischer Ökosysteme verbessern
Raw data obtained from stable isotope analysis of δ13C and δ15N in beaks of the squids Gonatus fabricii (Lichtenstein, 1818) and Todarodes sagittatus (Lamarck, 1798) (Cephalopoda: Oegopsida), and primary analyses of these data. Squids sampled in the Baffin Bay, Davis Strait and Nordic Seas (1882-2010) and Iceland, Faroe Islands and Ireland (1844-2023), respectively. The beaks either come from the squids caught as bycatch, or from natural history museums, from stomach contents of predators.
Stable isotope analysis (SIA) has emerged as a valuable tool for understanding the trophic structure of the marine food web and gaining insights into trophic levels and niche. Researchers are increasingly utilizing SIA in studies focused on feeding ecology, particularly in estimating the long-term diets of meso- and bathypelagic fish. To facilitate this research, a global database of published data on stable isotopes, specifically δ13C and δ15N, of meso- and bathypelagic fish was created. The database was constructed by conducting a thorough search on Google Scholar and reviewing the references cited in the retrieved papers. The search primarily involved using popular terms such as stable isotope analysis or feeding ecology in combination with mesopelagic or bathypelagic fish. The resulting SIA database contains δ13C and δ15N values for 95 different species of meso- and bathypelagic fish, belonging to 27 families, with specimens collected between 2004 and 2015. Each entry in the database includes information on the sampling location, month and year of sample collection, taxonomic classifications (phylum, class, order, family), number of samples analyzed, as well as the reference and DOI of the original data source. This global SIA database holds significant potential as a valuable tool and data source for conducting large-scale meta-analyses.
Um das Akkumulationsverhalten umweltrelevanter Chemikalien unter realen Bedingungen zu untersuchen, wurden in vielen verschiedenen aquatischen Ökosystemen weltweit trophische Magnifikationsfaktoren (TMFs) abgeleitet. Der TMF ist definiert als eine Metrik, die die durch schnittliche trophische Anreicherung einer Chemikalie durch das analysierte Nahrungsnetz unter realistischen Umweltbedingungen beschreibt. TMFs sind nicht nur für Fragen der Risiko bewertung von Chemikalien interessant, sondern auch für bestimmte Aspekte der Überwachung von Stoffen im Kontext der Wasserrahmenrichtlinie (WRRL). Diese Untersuchung ist die erste TMF-Studie, die in einem deutschen Süßwasser-Ökosystem - dem Templiner See bei Potsdam - durchgeführt wurde. Ziel der Studie war es, die Nahrungsnetzanreicherung von Stoffen zu unter suchen und zuverlässige TMFs abzuleiten, die für regulatorische Zwecke verwendet werden können. Es wurde ein Satz von Nahrungsnetzproben gewonnen, der 15 Biota-Proben aus etwa drei trophischen Ebenen umfasst. Die Proben wurden nach standardisierten Protokollen der Umweltprobenbank des Bundes (UPB) aufgearbeitet und tiefgekühlt gelagert. Die erhaltenen Nahrungsnetzproben bilden somit ein "Nahrungsnetz auf Eis" und sind nun für eine Vielzahl von Analysen einsetzbar. In einem ersten Schritt wurde eine Plausibilitätsprüfung durchgeführt. Als Vergleichsmaßstab dienen persistente organische Schadstoffe (POPs), von denen bekannt ist, dass sie sich in Nahrungsnetzen anreichern und zudem nicht leicht metabolisiert werden. Von den hier analysierten POPs zeigen die meisten Stoffe TMFs signifikant über 1. In wenigen Fällen ist zwar auch eine Anreicherung zu erkennen, die jedoch statistisch nicht signifikant ist. Da nicht nur POPs mit lipophilen Akkumulationseigenschaften analysiert wurden, kann der Schluss gezogen werden, dass die archivierten Proben des "Nahrungsnetzes auf Eis" aus dem Templiner See zur Charakterisierung des trophischen Magnifikationspotentials weiterer in den Proben vorhandener Substanzen mit weniger untersuchten Bioakkumulationseigenschaften verwendet werden können. Zu diesem Zweck wurden mehrere PFAS, Arzneimittelwirkstoffe, Pestizide und Methylsiloxane in den Proben analysiert, um für diese TMFs abzuleiten. Quelle: Forschungsbericht
Sponge grounds are hotspots of biomass and biodiversity in the otherwise barren deep sea. It remains unknown how these ecosystems can thrive in such food limited environments, since organic matter settling from the surface ocean covers only small parts of their carbon demand. In this study, the food-web interactions and potential food sources of a North Atlantic deep-sea sponge reef were identified by bulk and compound-specific stable isotope analysis of amino and fatty acids. The elevated bulk δ15N values of sponges with relatively low abundance of associated microbes (LMA) is in line with a position at the top of the benthic food web, while the relatively high δ13C and intermediate δ15N values of high microbial abundance (HMA) sponges suggest considerable reliance on an alternate resource. Trophic positions based on amino acid δ15N values placed HMA sponges at the base of the food web. Fatty acid analysis of δ13C indicated transfer of sponge derived organic matter to the wider food web. Our results show that sponges drive both bottom-up and top-down processes, shunting organic carbon to higher trophic levels that would otherwise be inaccessible to other fauna. In this way, sponges are key to the sustenance of thriving deep-sea ecosystems.
We experimentally manipulated the presence of light and light intensity (F = 36.7 μmol m⁻² s⁻¹; D = 0 μmol m⁻² s⁻¹; L = 4.8 μmol m⁻² s⁻¹; M = 21.4 μmol m⁻² s⁻¹) and tested their effects on the vertical positioning of the freshwater jellyfish (Craspedacusta sowerbii) medusae. For the experiments, approximately 100 C. sowerbii medusae were collected in August 2017 in two lakes (Haager Weiher and Leitner Weiher) in Bavaria, Germany. Testing was carried out at Seeon Limnological Station in close vicinity to the collection site. The experimental columns were 7.4 cm in diameter and 170 cm high and were marked with horizontal lines every 5 cm for visual position estimation. Four replicates run in parallel. One C. sowerbii medusa was used in each experimental column. Data cover three light treatments, each run twice: 1) 16:8 h full light (F)–dark (D) light intensity cycles (nF = 716, nD = 428), 2) 16:8 h full light (F)–full dark (D) light intensity cycles complemented with low (L) and medium (M) light intensities (nF = 96, nM = 96, nL = 48, nD = 288), and 3) altered light intensities in approximately 2-hour periods randomly among dark, low, medium, and full light intensities (nF = 96, nM = 76, nL = 72, nD = 336). Results show that light alone was sufficient to trigger a vertical position change of jellyfish towards the water surface, especially high light.
Objective: Long-range transport of contaminants to the Arctic, the resulting exposures observed in Arctic human populations, and impacts of such exposures on human health have been the subject of considerable work in recent years, providing a baseline against which to compare future developments. Global climate change has the potential to remobilize environmental contaminants and alter contaminant transport pathways, fate, and routes of exposure in human populations. The Arctic is particularly sensitive to climate change and already exhibits clear impacts. Research into contaminant exposure and its effects on human health in the Arctic, in comparison with other exposed populations in Europe, presents an opportunity to gain insight into changes that may later impact other areas. The influence of climate change on contaminant spreading and transfer and the resultant risk to human populations in the Arctic and other areas of Europe will be studied by: - Research on the ways in which climate change will affect the long-range transport and fate of selected groups of contaminants, and possible implications for the re-distribution of contaminants (geographically and between relevant environmental media). This will involve modelling, utilizing the information base that exists on the distribution of such contaminants in the Arctic and other areas of Europe - Research on the impacts that changing pathways and climatic conditions will have on contaminant uptake and transfer within food webs, leading to foods consumed by humans. This will involve experimental work, process studies and targeted analytical studies, the latter focussed on supporting the modelling work and process studies related to human exposure to contaminants - Research focussing on human health, aimed at determining how climate-mediated changes in the environmental fate of selected groups of contaminants will result in changes in exposure of human populations, in the Arctic and in selected areas of Europe.
How will the current rate and spatial extent of environmental change affect the functioning of future ecosystems? Food webs are structurally diverse and are remarkably persistent despite multifaceted and spatially variable environmental change. Ecological theory posits that the structural complexity of food webs will help ecosystems weather environmental change, but few experiments have tested this idea. To truly understand how ecosystems and their constituent food webs will respond, we must explore, experimentally, how environmental change affects the structure of food webs, for example the number of species and the interactions among them, and, consequently, the the functioning of ecosystems, for example, the rates of biomass production, decomposition, and sequestration. Our proposed research focuses on the environmental changes associated with rising levels of dissolved organic carbon (DOC) in freshwater ecosystems, but also considers climate warming, eutrophication, and changes in biodiversity. As microbial communities closely regulate the decomposition of DOC, we propose to examine the effect of changes in the environment and in the architecture of food webs on the composition of microbial communities, including viruses and prokaryotes. In doing so, we can link the ecological structure and evolutionary dynamics of food webs to the biogeochemistry of ecosystems. We propose a series of experiments to test how environmental change affects the complex interactions between food web assemblages and ecosystem functioning. The experiments test predictions from three bodies of ecological theory, namely the theory of biodiversity and ecosystem functioning, the theory of evolving metacommunities, and the landscape theory of food-web structure. These theories provide a strong foundation for understanding interactions between environmental change, food-web architecture, and ecosystem functioning, but they fail to fully address the feedbacks between structural changes of food-webs at upper trophic levels (e.g. plankton and fish) and the biogeochemistry of ecosystems that is regulated by microbial communities. Our experiments bridge this gap, and will improve our ability to predict how entire ecosystems respond to environmental change.
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