4.6 Review

Toward managing mixed-species stands: from parametrization to prescription

Journal

FOREST ECOSYSTEMS
Volume 4, Issue -, Pages -

Publisher

SPRINGER HEIDELBERG
DOI: 10.1186/s40663-017-0105-z

Keywords

-

Categories

Funding

  1. European Union
  2. Bavarian State Ministry for Nutrition, Agriculture, and Forestry [7831-22209-2013]
  3. German Science Foundation [PR 292/12-1]
  4. National Institute of Food and Agriculture/Pennsylvania Agriculture Experiment Station project [PEN 04516]

Ask authors/readers for more resources

A better understanding and a more quantitative design of mixed-species stands will contribute to more integrative and goal-oriented research in mixed-species forests. Much recent work has indicated that the structure and growth of mixed species forests may fundamentally differ from monocultures. Here we suggest how to progress from the present accumulation of phenomenological findings to a design of mixed-species stands and advanced silvicultural prescriptions by means of modelling. First, the knowledge of mixing effects on the structure and growth at the stand, species, and individual tree level is reviewed, with a focus on those findings that are most essential for suitable modelling and silvicultural designs and the regulation of mixed stands as opposed to monocultures. Then, the key role of growth models, stand simulators, and scenario assessments for designing mixed species stands is discussed. The next section illustrates that existing forest stand growth models require some fundamental modifications to become suitable for both monocultures and mixed-species stands. We then explore how silvicultural prescriptions derived from scenario runs would need to be both quantified and simplified for transfer to forest management and demonstrated in training plots. Finally, we address the main remaining knowledge gaps that could be remedied through empirical research.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available