Landscape gradients in Sphagnum peatlands: Nutrients, trace elements and diversity of free-living mites (Arthropoda: Acari) along a 1600 km transect on the West Siberian Plain

The West Siberian Plain holds special ecological significance as the largest peatland region of the world, which is expected to be affected by the climate change. We analysed water chemistry, chemical composition of Sphagnum tissues (total C, total N, K, P, and a range of trace elements) and biodiversity (abundance, species richness, community composition) of free-living mites (Oribatida and Mesostigmata) in twelve Sphagnum peatlands along the 1600 km transect (54°46′N to 67°29′N) on the West Siberian Plain. Mites were classified into two functional groups – “limnic” (Oribatida species which inhabit aquatic habitats), and “terrestrial” (all other species).

The results showed a latitudinal productivity gradient, with a consistent increase in nutrient content of Sphagnum and water pH from North to South; the northern-most site had lowest N and highest C:N ratio, indicating potential N limitation. There was an increase in levels of Cr, Zn, Ni and Sr in the Sphagnum tissues in proportion to the abundance of lithophile Ti on the southern end of the transect; however, in absolute terms, the concentrations of these elements were low. The abundance patterns of terrestrial and limnic mites reflected increasing nutrient load in Sphagnum bogs from North to South, as well as increasingly xeric conditions. Latitude and nutrients (P and C:N ratio) together explained 67.2 % variability in community composition of Oribatida and Mesostigmata. We found no effect of latitude or productivity on species richness; the main driver for species richness appeared to be the local micro-topography, with dryer areas colonised by a wider range of species. Our data help to elucidate landscape-scale patterns of productivity and biodiversity in West Siberian peatlands and provide a checkpoint in the timeline of global change. As sensitive intrazonal ecosystems, peatlands can act as useful early warning systems, offering insights about the effects of human activities on a large scale.