Distribution mechanisms of coral larvae support designation of marine conservation areas

Photo: Andreas Hallerbach / Flickr

Many marine organisms have mobile larvae and only at later life stages establish sessile colonies. Although several reseach projects on this topic exist, there is not much known about distribution mechanisms, which reflects there complexity and dependency on multiple factors such as age, survival rates und swimming speed of larvae but also on environmental conditionssuch as Position in the water body, lunar cycles and current. However, estimations based on models regarding the potential of distribution of marine organisms are essential in order to understand dynamics of meta-populations and their genetic structure, biodiversity and biogeography. A group of Australien scientists are convinced that the currently aplied parameters for modeling of distribution patterns have to be reconsidered, since they do not reflect time dynamics for survival rates and for the capacities to establish colonie of marine organisms. Until now models for the distribution of corals have used constant mortality rates and the assumption that larvae would attain and loose their colonizing competencies at the same time.

In order to refine those parameters the australian scientists conducted empirical studies of larvae of five different species of stone corals and thereby discovered interspecies variation as well as variations within the same colony. Due to these findings they created new models for the calculation / estimation of distribution capacities which included mortality rates, and the timeline for gain and loss of colonizing competencies.

Das Verständnis von Verbreitungsmechanismen ist grundlegend für die Beantwortung einer großen Bandbreite von ökologischen und evolutionären Fragen, sowie zur Abschätzung der Auswirkungen von Habitatfragmentation. Sie könnten auch dazu beitragen, die Struktur des Netzes von marinen Schutzgebieten zu verbessern. Dies ist ein gutes Beispiel dafür, wie taxonomische Forschung eine empirische Datengrundlage schafft, die mit Hilfe von Modellen dazu genutzt werden kann größere Zusammenhänge aufzudecken.

 

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