Prioritizing landscapes for restoration based on spatial patterns of ecosystem controls and plant–plant interactions

Jomar M. Barbosa, Gregory P. Asner

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The widespread degradation of natural ecosystems requires cost-efficient restoration techniques that minimize risk and consider context-specific restoration conditions. However, meeting these demands can be difficult because information on ecosystem-level factors controlling vegetation and continuous spatial data on species interactions are often lacking. Using airborne light detection and ranging (LiDAR) data from a Hawaiian dry forest, we delineated crowns and assessed the 3D structure of more than 700 000 shrubs and trees. We used Random Forest machine learning to assess the relative importance of resource availability, environmental conditions, and disturbance regimes on canopy density. We then modelled and scaled up plant–plant interactions (i.e. potential nursery effects) to landscape units using a LiDAR-derived Canopy Coalescence (CC) index. We used the relative importance of ecosystem factors, canopy cover, and CC index to prioritize landscapes for restoration. Here, we demonstrate a methodological framework that prioritizes landscapes in need of restoration (i.e. planting woody species) using two ecological perspectives: (i) ecosystem-level controls on remnant woody vegetation, and (ii) potential interactions between established canopies and seedlings (e.g. nursery effect, competition). Our results highlight the heterogeneous nature of ecosystem-level drivers affecting forest structure along elevation gradients. Consequently, the degree of potential nursery interactions between established canopies and seedlings at the landscape-scale was context-specific. Synthesis and applications. Our study provides a methodological approach that prioritizes landscapes for restoration by identifying the main controls on tree spatial distribution and by inferring the favourable conditions for seedlings. This approach can guide land managers to define cost-efficient restoration strategies for large ecological areas.

Original languageEnglish (US)
Pages (from-to)1459-1468
Number of pages10
JournalJournal of Applied Ecology
Volume54
Issue number5
DOIs
StatePublished - Oct 2017
Externally publishedYes

Fingerprint

canopy
ecosystem
seedling
coalescence
environmental disturbance
vegetation
dry forest
resource availability
cost
spatial data
restoration
shrub
environmental conditions
spatial distribution
index
effect
detection

Keywords

  • Carnegie Airborne Observatory
  • facilitation
  • forest regrowth
  • landscape ecology
  • LiDAR
  • plant–plant interactions
  • Random Forest machine learning
  • remote sensing
  • restoration ecology

ASJC Scopus subject areas

  • Ecology

Cite this

Prioritizing landscapes for restoration based on spatial patterns of ecosystem controls and plant–plant interactions. / Barbosa, Jomar M.; Asner, Gregory P.

In: Journal of Applied Ecology, Vol. 54, No. 5, 10.2017, p. 1459-1468.

Research output: Contribution to journalArticle

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