On the functional role of diversity and trophic interactions in litter decomposition of forest ecosystems

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With increasing biodiversity loss due to human-induced activities, one of the emerging priorities for science and society is to understand if and how changes in diversity and/or species composition impact ecosystem function. With a particular emphasis on forest ecosystems that provide habitat to over 65% of terrestrial biodiversity, my research program investigates the role of diversity on the ecosystem functions of litter decomposition and nutrient cycling. The long-term objective is to test theoretical predictions in biodiversity science by providing novel experimental evidence for increasingly complex multi-trophic models of forest floor communities in boreal, temperate and tropical forest ecosystems. To understand interactions between and among trophic levels in these forest floor communities, my lab will (1) quantify decomposition rates of leaf litter, root litter and coarse woody debris in primary and secondary forests, (2) characterize soil macrofauna communities (detritivores and predators) in these forests, (3) compile a functional trait database for detritus, detritivores and their soil predators to calculate functional diversity of these communities and (4) co-develop and test current theory on diversity and trophic interactions using a detritus-detrivore-predator experimental model. Incorporating trophic complexity in our understanding of biodiversity-ecosystem functioning is challenging, but recognized as the necessary next step for more relevant predictions of the consequences of biodiversity change for forest communities and ecosystems. This research program will provide new insight into the role of biodiversity in ecosystem function and provide society with a scientific basis to face growing environmental challenges in the current context of global change. Such fundamental research is necessary and directly relevant for informing policy on conservation of forest ecosystems. It will also provide novel experimental field data for improving forest biogeochemical models that all currently suffer severe limitations in their ability to accurately predict soil carbon. ******