Designing forest biodiversity experiments

general considerations illustrated by a new large experiment in subtropical China

Helge Bruelheide*, Karin Nadrowski, Thorsten Assmann, Juergen Bauhus, Sabine Both, Francois Buscot, Xiao-Yong Chen, Bingyang Ding, Walter Durka, Alexandra Erfmeier, Jessica L. M. Gutknecht, Dali Guo, Liang-Dong Guo, Werner Haerdtle, Jin-Sheng He, Alexandra-Maria Klein, Peter Kuehn, Yu Liang, Xiaojuan Liu, Stefan Michalski & 18 others Pascal A. Niklaus, Kequan Pei, Michael Scherer-Lorenzen, Thomas Scholten, Andreas Schuldt, Gunnar Seidler, Stefan Trogisch, Goddert von Oheimb, Erik Welk, Christian Wirth, Tesfaye Wubet, Xuefei Yang, Mingjian Yu, Shouren Zhang, Hongzhang Zhou, Markus Fischer, Keping Ma, Bernhard Schmid

*Corresponding author for this work

Research output: Contribution to journalArticle

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Abstract

1. 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.

2. 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 25.8x25.8m each.

3. 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.

4. 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.

5. 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.

Original languageEnglish
Pages (from-to)74-89
Number of pages16
JournalMethods in Ecology and Evolution
Volume5
Issue number1
Early online date22 Nov 2013
DOIs
Publication statusPublished - Jan 2014

Keywords

  • BEF-China
  • ecoscape
  • genetic diversity
  • planting pattern
  • random partitions design
  • species richness
  • trait-oriented extinction sequence
  • experimental grassland communities
  • ecological field experiments
  • leaf economics spectrum
  • plant-species richness
  • ecosystem services
  • environmental heterogeneity
  • limiting similarity
  • tree plantation
  • central-Europe
  • diversity

Cite this

Designing forest biodiversity experiments : general considerations illustrated by a new large experiment in subtropical China. / Bruelheide, Helge; Nadrowski, Karin; Assmann, Thorsten; Bauhus, Juergen; Both, Sabine; Buscot, Francois; Chen, Xiao-Yong; Ding, Bingyang; Durka, Walter; Erfmeier, Alexandra; Gutknecht, Jessica L. M.; Guo, Dali; Guo, Liang-Dong; Haerdtle, Werner; He, Jin-Sheng; Klein, Alexandra-Maria; Kuehn, Peter; Liang, Yu; Liu, Xiaojuan; Michalski, Stefan; Niklaus, Pascal A.; Pei, Kequan; Scherer-Lorenzen, Michael; Scholten, Thomas; Schuldt, Andreas; Seidler, Gunnar; Trogisch, Stefan; von Oheimb, Goddert; Welk, Erik; Wirth, Christian; Wubet, Tesfaye; Yang, Xuefei; Yu, Mingjian; Zhang, Shouren; Zhou, Hongzhang; Fischer, Markus; Ma, Keping; Schmid, Bernhard.

In: Methods in Ecology and Evolution, Vol. 5, No. 1, 01.2014, p. 74-89.

Research output: Contribution to journalArticle

Bruelheide, H, Nadrowski, K, Assmann, T, Bauhus, J, Both, S, Buscot, F, Chen, X-Y, Ding, B, Durka, W, Erfmeier, A, Gutknecht, JLM, Guo, D, Guo, L-D, Haerdtle, W, He, J-S, Klein, A-M, Kuehn, P, Liang, Y, Liu, X, Michalski, S, Niklaus, PA, Pei, K, Scherer-Lorenzen, M, Scholten, T, Schuldt, A, Seidler, G, Trogisch, S, von Oheimb, G, Welk, E, Wirth, C, Wubet, T, Yang, X, Yu, M, Zhang, S, Zhou, H, Fischer, M, Ma, K & Schmid, B 2014, 'Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China', Methods in Ecology and Evolution, vol. 5, no. 1, pp. 74-89. https://doi.org/10.1111/2041-210X.12126
Bruelheide, Helge ; Nadrowski, Karin ; Assmann, Thorsten ; Bauhus, Juergen ; Both, Sabine ; Buscot, Francois ; Chen, Xiao-Yong ; Ding, Bingyang ; Durka, Walter ; Erfmeier, Alexandra ; Gutknecht, Jessica L. M. ; Guo, Dali ; Guo, Liang-Dong ; Haerdtle, Werner ; He, Jin-Sheng ; Klein, Alexandra-Maria ; Kuehn, Peter ; Liang, Yu ; Liu, Xiaojuan ; Michalski, Stefan ; Niklaus, Pascal A. ; Pei, Kequan ; Scherer-Lorenzen, Michael ; Scholten, Thomas ; Schuldt, Andreas ; Seidler, Gunnar ; Trogisch, Stefan ; von Oheimb, Goddert ; Welk, Erik ; Wirth, Christian ; Wubet, Tesfaye ; Yang, Xuefei ; Yu, Mingjian ; Zhang, Shouren ; Zhou, Hongzhang ; Fischer, Markus ; Ma, Keping ; Schmid, Bernhard. / Designing forest biodiversity experiments : general considerations illustrated by a new large experiment in subtropical China. In: Methods in Ecology and Evolution. 2014 ; Vol. 5, No. 1. pp. 74-89.
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title = "Designing forest biodiversity experiments: general considerations illustrated by a new large experiment in subtropical China",
abstract = "1. 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.2. 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 25.8x25.8m each.3. 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.4. 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.5. 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.",
keywords = "BEF-China, ecoscape, genetic diversity, planting pattern, random partitions design, species richness, trait-oriented extinction sequence, experimental grassland communities, ecological field experiments, leaf economics spectrum, plant-species richness, ecosystem services, environmental heterogeneity, limiting similarity, tree plantation, central-Europe, diversity",
author = "Helge Bruelheide and Karin Nadrowski and Thorsten Assmann and Juergen Bauhus and Sabine Both and Francois Buscot and Xiao-Yong Chen and Bingyang Ding and Walter Durka and Alexandra Erfmeier and Gutknecht, {Jessica L. M.} and Dali Guo and Liang-Dong Guo and Werner Haerdtle and Jin-Sheng He and Alexandra-Maria Klein and Peter Kuehn and Yu Liang and Xiaojuan Liu and Stefan Michalski and Niklaus, {Pascal A.} and Kequan Pei and Michael Scherer-Lorenzen and Thomas Scholten and Andreas Schuldt and Gunnar Seidler and Stefan Trogisch and {von Oheimb}, Goddert and Erik Welk and Christian Wirth and Tesfaye Wubet and Xuefei Yang and Mingjian Yu and Shouren Zhang and Hongzhang Zhou and Markus Fischer and Keping Ma and Bernhard Schmid",
note = "Funded by German Research Foundation. Grant Number: DFG FOR 891/1 and 2 National Natural Science Foundation of China. Grant Numbers: NSFC 30710103907, 30930005, 31170457 , 31210103910 Swiss National Science Foundation (SNSF) Sino-German Centre for Research Promotion in Beijing",
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T1 - Designing forest biodiversity experiments

T2 - general considerations illustrated by a new large experiment in subtropical China

AU - Bruelheide, Helge

AU - Nadrowski, Karin

AU - Assmann, Thorsten

AU - Bauhus, Juergen

AU - Both, Sabine

AU - Buscot, Francois

AU - Chen, Xiao-Yong

AU - Ding, Bingyang

AU - Durka, Walter

AU - Erfmeier, Alexandra

AU - Gutknecht, Jessica L. M.

AU - Guo, Dali

AU - Guo, Liang-Dong

AU - Haerdtle, Werner

AU - He, Jin-Sheng

AU - Klein, Alexandra-Maria

AU - Kuehn, Peter

AU - Liang, Yu

AU - Liu, Xiaojuan

AU - Michalski, Stefan

AU - Niklaus, Pascal A.

AU - Pei, Kequan

AU - Scherer-Lorenzen, Michael

AU - Scholten, Thomas

AU - Schuldt, Andreas

AU - Seidler, Gunnar

AU - Trogisch, Stefan

AU - von Oheimb, Goddert

AU - Welk, Erik

AU - Wirth, Christian

AU - Wubet, Tesfaye

AU - Yang, Xuefei

AU - Yu, Mingjian

AU - Zhang, Shouren

AU - Zhou, Hongzhang

AU - Fischer, Markus

AU - Ma, Keping

AU - Schmid, Bernhard

N1 - Funded by German Research Foundation. Grant Number: DFG FOR 891/1 and 2 National Natural Science Foundation of China. Grant Numbers: NSFC 30710103907, 30930005, 31170457 , 31210103910 Swiss National Science Foundation (SNSF) Sino-German Centre for Research Promotion in Beijing

PY - 2014/1

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N2 - 1. 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.2. 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 25.8x25.8m each.3. 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.4. 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.5. 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.

AB - 1. 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.2. 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 25.8x25.8m each.3. 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.4. 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.5. 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.

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KW - planting pattern

KW - random partitions design

KW - species richness

KW - trait-oriented extinction sequence

KW - experimental grassland communities

KW - ecological field experiments

KW - leaf economics spectrum

KW - plant-species richness

KW - ecosystem services

KW - environmental heterogeneity

KW - limiting similarity

KW - tree plantation

KW - central-Europe

KW - diversity

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DO - 10.1111/2041-210X.12126

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VL - 5

SP - 74

EP - 89

JO - Methods in Ecology and Evolution

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