{"id":9354,"date":"2024-07-01T14:41:04","date_gmt":"2024-07-01T13:41:04","guid":{"rendered":"https:\/\/www.idiv.de\/?page_id=9354"},"modified":"2024-12-09T15:57:42","modified_gmt":"2024-12-09T14:57:42","slug":"forschungsprojekte","status":"publish","type":"page","link":"https:\/\/www.idiv.de\/de\/forschung\/kernforschungsgruppen\/biodiversitaetstheorie\/forschungsprojekte\/","title":{"rendered":"Forschungsprojekte"},"content":{"rendered":"
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Forschungsprojekte<\/h1>

Wir analysieren \u00f6kologische Systeme<\/strong> als verschiedene Arten von Netzwerken, darunter trophische Netze<\/strong> von R\u00e4uber-Beute-Interaktionen und r\u00e4umliche Netzwerken<\/strong> von Habitatflecken. Diese Forschungsbereiche sind durch die allgemeine Verwendung allometrischer Skalierungsfunktionen<\/strong> verbunden, die Netzwerkparameter wie F\u00fctterungsst\u00e4rke oder Bewegungsraten mit den K\u00f6rpermassen der Arten in Beziehung setzen.<\/p>\n \n <\/div>\n <\/div>\n\n \n <\/div>\n\n <\/div>\n<\/div>\n\n

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Unsere Forschungen gliedern sich in die folgenden \u00fcbergreifenden Forschungsthemen<\/h2><\/div><\/div><\/div><\/div>\n\n
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R\u00e4uber-Beute-Interaktionen und trophische Netzwerke.<\/h3>\n

In diesem Forschungsbereich befassen wir uns damit, wie sich die K\u00f6rpermasse der Arten und Umweltvariablen wie die Temperatur auf die R\u00e4uber-Beute-Interaktionen und die komplexen trophischen Netzwerke nat\u00fcrlicher Gemeinschaften auswirken.<\/p>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n\n\n \n

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The earth’s ecosystems comprise millions of species that are engaged in billions of interactions. The organisation (who is feeding on whom) and the strength of these feeding interactions are critically important for community stability and maintaining biodiversity. However, the enormous number of interactions renders systematic empirical measurements of their strengths impossible, thus limiting our ability to understand the structure, dynamics, and stability of natural trophic networks.<\/p>\n<\/header>\n

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How can we obtain a generalized and predictive understanding of interactions between species?<\/h4>\n
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Our primary approach to understanding predator-prey interaction strengths is to focus on constraints by their body masses. We found systematic effects of body masses on feeding rates and functional response parameters (Rall et al. 2012, Kalinkat et al. 2013). The resulting non-random distributions of interaction strengths across species pairs yield a high system stability (Heckmann et al. 2012). Together, these findings show how body masses determine the structure, dynamics and stability of trophic networks in nature. Our current research comprises constraints on species-coexistence patterns in microbial networks, effects of space (habitat size) on interaction strengths and population dynamics and forecasting ecological dynamics.<\/p>\n <\/div>\n\n\n <\/div>\n <\/div>\n

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What are the consequences of climate warming for species‘ interactions and trophic networks?<\/h4>\n
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In systematic laboratory experiments, we analysed the increase in consumer feeding rates relative to their metabolism (Vucic-Pestic et al. 2011, Lang et al. 2012). In contrast to prior expectations, we found that the relatively weaker increase in feeding rates stabilises population oscillations at the risk of consumer starvation (Fussmann et al. 2014). Surprisingly, these destabilising warming effects can be buffered by nutrient enrichment (Binzer et al. 2016). In ongoing research projects, we address how global change affects interaction strengths <\/b>and ecosystem functioning.<\/p>\n <\/div>\n\n\n <\/div>\n <\/div>\n

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Binzer, A. et al. 2016. Interactive effects of warming, eutrophication and size structure: impacts on biodiversity and food-web structure. –\u00a0Glob. Change Biol.<\/i>\u00a022: 220\u2013227.<\/p>\n

Fussmann, K. E. et al. 2014. Ecological stability in response to warming. –\u00a0Nat. Clim. Change<\/i>\u00a04: 206\u2013210.<\/p>\n

Heckmann, L. et al. 2012. Interactive effects of body-size structure and adaptive foraging on\u00a0\u00a0 food-web stability. –\u00a0Ecol. Lett.<\/i>\u00a015: 243\u2013250.<\/p>\n

Kalinkat, G. et al. 2013. Body masses, functional responses and predator\u2013prey stability. –\u00a0Ecol. Lett.<\/i>\u00a016: 1126\u20131134.<\/p>\n

Lang, B. et al. 2012. Warming effects on consumption and intraspecific interference\u00a0\u00a0 competition depend on predator metabolism. –\u00a0J. Anim. Ecol.<\/i>\u00a081: 516\u2013523.<\/p>\n

Rall, B. C. et al. 2012. Universal temperature and body-mass scaling of feeding rates. –\u00a0Philos. Trans. R. Soc. B Biol. Sci.<\/i>\u00a0367: 2923\u20132934.<\/p>\n

Vucic-Pestic, O. et al. 2011. Warming up the system: higher predator feeding rates but lower energetic efficiencies. –\u00a0Glob. Change Biol.<\/i>\u00a017: 1301\u20131310.<\/p>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n\n\n \n <\/div>\n <\/div>\n <\/div>\n

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Bewegung, Meta-Lebensgemeinschaften und r\u00e4umliche Netzwerke<\/h3>\n

In diesem Forschungsbereich untersuchen wir, (1) wie Artenmerkmale wie K\u00f6rpermasse und Bewegungsmodus die Bewegungsmuster beeinflussen, (2) was die Stabilit\u00e4t von Metagemeinschaften bestimmt und (3) wie die Bewegung von Arten r\u00e4umliche Netzwerke von Lebensraumflecken schafft.<\/p>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n\n\n \n

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Many natural landscapes are characterized by a patchy distribution of habitats that are separated by a less-inhabitable landscape matrix. Examples of these spatial structures include (1) agricultural landscapes with forest fragments, ponds and small grasslands as patches within large areas that are dominated by intensively used fields or plantations; (2) lakes that are are surrounded by terrestrial ecosystems and (3) islands in the ocean. The local communities of these patches are not isolated but coupled by species dispersal. This yields metacommunities composed of the species across all habitat patches. Moreover, the habitat patches are linked by species movement creating spatial habitat networks.<\/p>\n

What constrains the movement of species?<\/h4>\n

Movement is one of the most fundamental processes of life linking individuals with their resources, mating partners and resting sites. Why are the movement rates so different between species? We analyze how this variance is explained by movement modes (running, flying, swimming) and species‘ body masses and how this yields systematic patterns in spatial networks.\u00a0 The movement theory is linked to natural movement trajectories by fitting Bayesian state-space models to unravel the importance of landscape characteristics for individual movement. Currently, the vast majority of movement trajectories is available for vertebrates. We aim at complementing this with data on invertebrate movement by employing camera systems in the laboratory (Dell et al. 2014) as well as passive sensor techniques in the field.<\/p>\n

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Dell, A. I. et al. 2014. Automated image-based tracking and its application in ecology. – Trends Ecol. Evol. 29: 417\u2013428.<\/p>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n\n\n \n <\/div>\n <\/div>\n <\/div>\n

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Experimentelle Meta-Lebensgemeinschaften und mikrobielle Netzwerke<\/h3>\n

In diesem Forschungsbereich testen wir die Vorhersagen der \u00f6kologischen Netzwerktheorie in mikrobiellen Mikrokosmen von Bakterien und ihren protistischen Konsumenten.<\/p>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n\n\n \n

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A big challenge in ecology is to link theory predictions obtained under simplifying assumptions to the complex patterns and processes found in natural ecosystems. For instance, natural communities are not only characterized by an entangled structure of inter- and intraspecific interactions between species but also by heterogeneous spatial distributions of habitat patches linked by species dispersal. The structure of these trophic and spatial networks constrains the diversity, dynamics and functioning of the communities. Therefore, experimental systems need to establish these types of networks under controlled and replicable conditions.<\/p>\n

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How can microbial networks help us to understand theory predictions?<\/h4>\n

Microbial networks comprising protists and bacteria have a long history in ecology. They have the big advantage that they are easy to manipulate, highly flexible and represent a great tool to test theoretical predictions in relatively short time. For example, it was generally assumed that global warming destabilizes natural systems due to an increased speed of life and accelerated oscillations. However, our microcosm experiments revealed that predator-prey (protozoa-bacteria) interactions are stabilized by warming due to dampened oscillations in population cycles, whereas extinctions due to predator starvation become more likely (Fussmann et al. 2014). Our current research investigates the processes driving coexistence in microbial networks comprising protists and bacteria on sugar resources.<\/p>\n

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Fussmann, K. E. et al. 2014. Ecological stability in response to warming. – Nat. Clim. Change 4: 206\u2013210.<\/p>\n<\/div>\n <\/div>\n

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