Species composition and forest structure explain the temperature sensitivity patterns of productivity in temperate forests

Research output: Journal contributionsJournal articlesResearchpeer-review

Standard

Species composition and forest structure explain the temperature sensitivity patterns of productivity in temperate forests. / Bohn , Friedrich J. ; May, Felix; Huth, Andreas.
In: Biogeosciences, Vol. 15, No. 6, 26.03.2018, p. 1795 - 1813.

Research output: Journal contributionsJournal articlesResearchpeer-review

Harvard

APA

Vancouver

Bibtex

@article{cc06e46c51174dec97cd5eb2663756eb,
title = "Species composition and forest structure explain the temperature sensitivity patterns of productivity in temperate forests",
abstract = "Rising temperatures due to climate change influence the wood production of forests. Observations show that some temperate forests increase their productivity, whereas others reduce their productivity. This study focuses on how species composition and forest structure properties influence the temperature sensitivity of aboveground wood production (AWP). It further investigates which forests will increase their productivity the most with rising temperatures. We described forest structure by leaf area index, forest height and tree height heterogeneity. Species composition was described by a functional diversity index (Rao's Q) and a species distribution index (ΩAWP). ΩAWP quantified how well species are distributed over the different forest layers with regard to AWP. We analysed 370 170 forest stands generated with a forest gap model. These forest stands covered a wide range of possible forest types. For each stand, we estimated annual aboveground wood production and performed a climate sensitivity analysis based on 320 different climate time series (of 1-year length). The scenarios differed in mean annual temperature and annual temperature amplitude. Temperature sensitivity of wood production was quantified as the relative change in productivity resulting from a 1 ∘C rise in mean annual temperature or annual temperature amplitude. Increasing ΩAWP positively influenced both temperature sensitivity indices of forest, whereas forest height showed a bell-shaped relationship with both indices. Further, we found forests in each successional stage that are positively affected by temperature rise. For such forests, large ΩAWP values were important. In the case of young forests, low functional diversity and small tree height heterogeneity were associated with a positive effect of temperature on wood production. During later successional stages, higher species diversity and larger tree height heterogeneity were an advantage. To achieve such a development, one could plant below the closed canopy of even-aged, pioneer trees a climax-species-rich understorey that will build the canopy of the mature forest. This study highlights that forest structure and species composition are both relevant for understanding the temperature sensitivity of wood production.",
keywords = "Biology, Ecosystems Research",
author = "Bohn, {Friedrich J.} and Felix May and Andreas Huth",
note = "Publisher Copyright: {\textcopyright} Author(s) 2018.",
year = "2018",
month = mar,
day = "26",
doi = "10.5194/bg-15-1795-2018",
language = "English",
volume = "15",
pages = "1795 -- 1813",
journal = "Biogeosciences",
issn = "1726-4170",
publisher = "Copernicus Publications",
number = "6",

}

RIS

TY - JOUR

T1 - Species composition and forest structure explain the temperature sensitivity patterns of productivity in temperate forests

AU - Bohn , Friedrich J.

AU - May, Felix

AU - Huth, Andreas

N1 - Publisher Copyright: © Author(s) 2018.

PY - 2018/3/26

Y1 - 2018/3/26

N2 - Rising temperatures due to climate change influence the wood production of forests. Observations show that some temperate forests increase their productivity, whereas others reduce their productivity. This study focuses on how species composition and forest structure properties influence the temperature sensitivity of aboveground wood production (AWP). It further investigates which forests will increase their productivity the most with rising temperatures. We described forest structure by leaf area index, forest height and tree height heterogeneity. Species composition was described by a functional diversity index (Rao's Q) and a species distribution index (ΩAWP). ΩAWP quantified how well species are distributed over the different forest layers with regard to AWP. We analysed 370 170 forest stands generated with a forest gap model. These forest stands covered a wide range of possible forest types. For each stand, we estimated annual aboveground wood production and performed a climate sensitivity analysis based on 320 different climate time series (of 1-year length). The scenarios differed in mean annual temperature and annual temperature amplitude. Temperature sensitivity of wood production was quantified as the relative change in productivity resulting from a 1 ∘C rise in mean annual temperature or annual temperature amplitude. Increasing ΩAWP positively influenced both temperature sensitivity indices of forest, whereas forest height showed a bell-shaped relationship with both indices. Further, we found forests in each successional stage that are positively affected by temperature rise. For such forests, large ΩAWP values were important. In the case of young forests, low functional diversity and small tree height heterogeneity were associated with a positive effect of temperature on wood production. During later successional stages, higher species diversity and larger tree height heterogeneity were an advantage. To achieve such a development, one could plant below the closed canopy of even-aged, pioneer trees a climax-species-rich understorey that will build the canopy of the mature forest. This study highlights that forest structure and species composition are both relevant for understanding the temperature sensitivity of wood production.

AB - Rising temperatures due to climate change influence the wood production of forests. Observations show that some temperate forests increase their productivity, whereas others reduce their productivity. This study focuses on how species composition and forest structure properties influence the temperature sensitivity of aboveground wood production (AWP). It further investigates which forests will increase their productivity the most with rising temperatures. We described forest structure by leaf area index, forest height and tree height heterogeneity. Species composition was described by a functional diversity index (Rao's Q) and a species distribution index (ΩAWP). ΩAWP quantified how well species are distributed over the different forest layers with regard to AWP. We analysed 370 170 forest stands generated with a forest gap model. These forest stands covered a wide range of possible forest types. For each stand, we estimated annual aboveground wood production and performed a climate sensitivity analysis based on 320 different climate time series (of 1-year length). The scenarios differed in mean annual temperature and annual temperature amplitude. Temperature sensitivity of wood production was quantified as the relative change in productivity resulting from a 1 ∘C rise in mean annual temperature or annual temperature amplitude. Increasing ΩAWP positively influenced both temperature sensitivity indices of forest, whereas forest height showed a bell-shaped relationship with both indices. Further, we found forests in each successional stage that are positively affected by temperature rise. For such forests, large ΩAWP values were important. In the case of young forests, low functional diversity and small tree height heterogeneity were associated with a positive effect of temperature on wood production. During later successional stages, higher species diversity and larger tree height heterogeneity were an advantage. To achieve such a development, one could plant below the closed canopy of even-aged, pioneer trees a climax-species-rich understorey that will build the canopy of the mature forest. This study highlights that forest structure and species composition are both relevant for understanding the temperature sensitivity of wood production.

KW - Biology

KW - Ecosystems Research

UR - http://www.scopus.com/inward/record.url?scp=85044954010&partnerID=8YFLogxK

U2 - 10.5194/bg-15-1795-2018

DO - 10.5194/bg-15-1795-2018

M3 - Journal articles

VL - 15

SP - 1795

EP - 1813

JO - Biogeosciences

JF - Biogeosciences

SN - 1726-4170

IS - 6

ER -

DOI

Recently viewed

Publications

  1. Experiences of the Self between Limit, Transgression, and the Explosion of the Dialectical System
  2. Failure to Learn From Failure Is Mitigated by Loss-Framing and Corrective Feedback
  3. Towards an open question answering architecture
  4. Reading Comprehension as Embodied Action: Exploratory Findings on Nonlinear Eye Movement Dynamics and Comprehension of Scientific Texts
  5. New Labor, Old Questions: Practices of Collaboration with Robots
  6. Getting down to specifics on RCA [Resource Consumption Accounting]
  7. Visualization of the Plasma Frequency by means of a Particle Simulation using a Normalized Periodic Model
  8. Challenges in detecting proximal effects of existential threat on lie detection accuracy
  9. The professional context as a predictor for response distortion in the Adaption-Innovation-Inventory – An investigation using mixture-distribution item-response theory models
  10. Industrial applications using wavelet packets for gross error detection
  11. Introduction
  12. Systematic feature evaluation for gene name recognition
  13. A cognitive mapping approach to understanding public objection to energy infrastructure
  14. Public Value: rethinking value creation
  15. Predicate‐based model of problem‐solving for robotic actions planning
  16. Octanol-Water Partition Coefficient Measurement by a Simple 1H NMR Method
  17. Approximate tree kernels
  18. Mathematical Modeling for Robot 3D Laser Scanning in Complete Darkness Environments to Advance Pipeline Inspection
  19. Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems
  20. Metrics for Experimentation Programs: Categories, Benefits and Challenges
  21. Scholarly Question Answering Using Large Language Models in the NFDI4DataScience Gateway
  22. Application of design of experiments for laser shock peening process optimization
  23. A survey of empirical studies using transaction level data on exports and imports
  24. A Wavelet Packet Algorithm for Online Detection of Pantograph Vibrations
  25. Processing of CSR communication: insights from the ELM
  26. Experimentally established correlation of friction surfacing process temperature and deposit geometry
  27. Guest Editorial - ''Econometrics of Anonymized Micro Data''
  28. Performance Saga: Interview 01
  29. Active learning for network intrusion detection
  30. A Lyapunov based PI controller with an anti-windup scheme for a purification process of potable water
  31. Embarrassment as a public vs. private emotion and symbolic coping behaviour
  32. Intraspecific trait variation increases species diversity in a trait-based grassland model
  33. »HOW TO MAKE YOUR OWN SAMPLES«
  34. Imaginary practices as the nexus between continuity and disruptive change
  35. Polar Coordinates and Interactive Learning