Evaluating restoration treatment effectiveness through a comparison of residual composition, structure, and spatial pattern with historical reference sites

Miles E. LeFevre, Derek J. Churchill, Andrew J. Larson, Sean M.A. Jeronimo, Jamie Bass, Jerry F. Franklin, Van R. Kane

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Forest-restoration efforts are increasing in the western United States in response to realized and expected changes in climate and disturbance regimes. Managers are challenged to find practical and defensible targets to shift forest composition, structure, and spatial pattern to a more resistant and resilient state. The Northeast Washington Forest Vision 2020 project on the Colville National Forest presented an opportunity to map and use previously uncaptured mesic stand-level historical reference conditions to a large restoration project. We reconstructed historical forest conditions in 12 plots across a range of plant-association groups and mapped five restoration treatment units after implementation. We evaluated treatment effectiveness both in terms of meeting the prescriptions' stated objectives and by similarity to observed reference conditions using metrics of density, species composition, clump-size patterns, and open-space patterns. We found that dry plant associations were historically dominated by distributed clumps of large shade-intolerant trees, whereas cold mesic plant associations were structured as a gap-matrix spatial pattern. Treatments were effective at meeting prescribed density and species-composition targets, but generally resulted in stands that were overly uniform or clumped compared to historical reference conditions. Study Implications: Collaborative forest-restoration efforts are enhanced by explicit prescription targets and objective monitoring of treatment implementation, which together enable adaptive management. Spatial aspects of forest stand structure are often intentionally manipulated in restoration treatments because of their known relations to ecological functions. Reference conditions can provide defensible starting-points from which to develop a treatment prescription and to evaluate monitoring data. This study provides a spatially explicit stand-level historical reference dataset for the northeast Washington region, including moist mixed-conifer forest types for which historical reference data were not previously available. This reference dataset is available to managers for use in creating reference targets for restoration treatments in stands of similar site conditions and plant-association groups. The methods we used for monitoring restoration treatments are easily applied in an adaptive management framework and can highlight where modifications to future prescriptions are needed to better align treatments with restoration objectives. Treatments in this study were found to have large (>30 tree) untreated patches of high-density forest that had no analog in the historical reference data. This highlights the need for explicit targets when spatial pattern is an objective of restoration treatments.

Original languageEnglish
Pages (from-to)578-588
Number of pages11
JournalForest Science
Volume66
Issue number5
DOIs
StatePublished - Oct 1 2020

Keywords

  • Frequent fire
  • Historical reconstruction
  • Reference conditions
  • Resilience
  • Spatial pattern

Fingerprint

Dive into the research topics of 'Evaluating restoration treatment effectiveness through a comparison of residual composition, structure, and spatial pattern with historical reference sites'. Together they form a unique fingerprint.

Cite this