Thinning increases tree growth by delaying drought-induced growth cessation in a Mediterranean evergreen oak coppice

Cabon, A., et al., 2018. Forest Ecology and Management

Original research (primary data)
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Abstract

The Mediterranean evergreen oak coppices of Southern Europe are increasingly vulnerable to drought because of both the ongoing climate change that increases drought length and intensity, and the lack of forest management that induces a structural aging of the stands. Decreasing stand density through thinning has been widely regarded as a means to improve the resistance of evergreen oak forests to climate change by decreasing the competition for water amongst the remaining stems. Data from a 30-years thinning experiment, that includes a control and four thinning intensity treatments (from 25% to 80% of basal area removed), in a coppiced holm oak (Quercus ilex L.) forest of southern France, was used to quantify the effects of thinning on stem growth. Building on the ‘sink limitation’ paradigm, which proposes that tree growth is controlled by phenology and climatic constraints and decoupled from carbon assimilation, we investigated if the effect of thinning on stem growth was explained by a delayed drought-induced growth cessation. Using a water balance model, we simulated the date of drought-induced growth cessation, previously found to correspond to the day of the year when water potential drops below a threshold of -1.1 MPa, and used it to predict growth in the different treatments of the thinning experiment. Thinning increased long-term growth at the stem level but decreased the wood biomass at the stand level. Decreasing stem density, and hence the leaf area index, was simulated to delay the date of drought-induced growth cessation. A growth model based on the date of growth cessation explained 85% of the effect of thinning on stem growth over the 30-year period of the study, and 95% for the first five years after thinning. The canopy density for which the effect of thinning is the most beneficial was found to maximize the growth duration without lifting completely the water limitation in summer. Moderate thinning had a sustained beneficial effect on the growth of all stem size classes, whereas stronger thinning intensities increased the size asymmetry of competition and their overall effect dropped faster. Our simple predictive model based on the simulation of the water balance as a function of stand density opens the way to providing management guidelines for the optimization of tree density as a function of water limitation in Mediterranean evergreen woodlands.

Case studies

Basic information

  • Case ID: INT-051-1
  • Intervention type: Management
  • Intervention description:

    Field experiment. Selective thinning from below (sensu Assman, 1970), which consists in removing the smallest stems to the benefit of the biggest ones; Five thinning intensities were applied where approximately 0%, 25%, 45%, 60% and 80% of the basal area was removed

  • Landscape/sea scape ecosystem management: No
  • Climate change impacts Effect of Nbs on CCI Effect measures
    Loss of timber production  No effect Tree growth: Mean annual stem Basal Area Increment wood production of the thinned plots (i.e. standing + extracted wood biomass)
  • Approach implemented in the field: Yes
  • Specific location:

    35 km northwest of Montpellier, Southern France, in the state forest of Puéchabon (43°44′29′′N, 3°35′45′′E, 270 m a.s.l)

  • Country: France
  • Habitat/Biome type: Mediterranean shrubs and Forests |
  • Issue specific term: Not applicable

Evidence

  • Notes on intervention effectivness: effectiveness compared to control (0% thinning plots)
  • Is the assessment original?: Yes
  • Broadtype of intervention considered: Not applicable
  • Compare effectivness?: No
  • Compared to the non-NBS approach: Not applicable
  • Report greenhouse gas mitigation?: No
  • Impacts on GHG: Not applicable
  • Assess outcomes of the intervention on natural ecosystems: No
  • Impacts for the ecosystem: Not reported
  • Ecosystem measures:
  • Assess outcomes of the intervention on people: No
  • Impacts for people: Not reported
  • People measures:
  • Considers economic costs: No
  • Economic appraisal conducted: No
  • Economic appraisal described:
  • Economic costs of alternative considered: No
  • Compared to an alternative: Not reported

Evaluation methodology

  • Type of data: Quantitative
  • Is it experimental: Yes
  • Experimental evalution done: In-situ/field
  • Non-experimental evalution done: Not applicable
  • Study is systematic: