Author |
Bruelheide, H.; Nadrowski, K.; Assmann, T.; Bauhus, J.; Both, S.; Buscot, F.; Chen, X.-Y.; Ding, B.Y.; Durka, W.
; Erfmeier, A.; Gutknecht, J.L.M.; Guo, D.L.; Guo, L.-D.; Härdtle, W.; He, J.-S.; Klein, A.-M.; Kühn, P.; Liang, Y.; Liu, X.J.; Michalski, S.; Niklaus, P.A.; Pei, K.Q.; Scherer-Lorenzen, M.; Scholten, T.; Schuldt, A.; Seidler, G.; Trogisch, S.; von Oheimb, G.; Welk, E.; Wirth, C.; Wubet, T.
; Yang, X.F.; Yu, M.J.; Zhang, S.R.; Zhou, H.Z.; Fischer, M.; Ma, K.P.; Schmid, B. |
Abstract |
- Biodiversity–ecosystem
functioning (BEF) experiments address ecosystem-level consequences of
species loss by comparing communities of high species richness with
communities from which species have been gradually eliminated. BEF
experiments originally started with microcosms in the laboratory and
with grassland ecosystems. A new frontier in experimental BEF research
is manipulating tree diversity in forest ecosystems, compelling
researchers to think big and comprehensively.
- We present and
discuss some of the major issues to be considered in the design of BEF
experiments with trees and illustrate these with a new forest
biodiversity experiment established in subtropical China (Xingangshan,
Jiangxi Province) in 2009/2010. Using a pool of 40 tree species,
extinction scenarios were simulated with tree richness levels of 1, 2,
4, 8 and 16 species on a total of 566 plots of 25·8 × 25·8 m each.
- The
goal of this experiment is to estimate effects of tree and shrub
species richness on carbon storage and soil erosion; therefore, the
experiment was established on sloped terrain. The following important
design choices were made: (i) establishing many small rather than fewer
larger plots, (ii) using high planting density and random mixing of
species rather than lower planting density and patchwise mixing of
species, (iii) establishing a map of the initial ‘ecoscape’ to
characterize site heterogeneity before the onset of biodiversity effects
and (iv) manipulating tree species richness not only in random but also
in trait-oriented extinction scenarios.
- Data management and
analysis are particularly challenging in BEF experiments with their
hierarchical designs nesting individuals within-species populations
within plots within-species compositions. Statistical analysis best
proceeds by partitioning these random terms into fixed-term contrasts,
for example, species composition into contrasts for species richness and
the presence of particular functional groups, which can then be tested
against the remaining random variation among compositions.
- We
conclude that forest BEF experiments provide exciting and timely
research options. They especially require careful thinking to allow
multiple disciplines to measure and analyse data jointly and
effectively. Achieving specific research goals and synergy with previous
experiments involves trade-offs between different designs and requires
manifold design decisions.
|
Bruelheide, H., Nadrowski, K., Assmann, T., Bauhus, J., Both, S., Buscot, F., Chen, X.-Y., Ding, B.Y., Durka, W., Erfmeier, A., Gutknecht, J.L.M., Guo, D.L., Guo, L.-D., Härdtle, W., He, J.-S., Klein, A.-M., Kühn, P., Liang, Y., Liu, X.J., Michalski, S., Niklaus, P.A., Pei, K.Q., Scherer-Lorenzen, M., Scholten, T., Schuldt, A., Seidler, G., Trogisch, S., von Oheimb, G., Welk, E., Wirth, C., Wubet, T., Yang, X.F., Yu, M.J., Zhang, S.R., Zhou, H.Z., Fischer, M., Ma, K.P., Schmid, B. (2014):
Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China
Methods Ecol. Evol. 5 (1), 74 - 89 |