Supervised versus un‐supervised classification: a quantitative comparison of plant communities in savanna vegetation

Addicott, Eda, and Laurance, Susan G.W. (2019) Supervised versus un‐supervised classification: a quantitative comparison of plant communities in savanna vegetation. Applied Vegetation Science, 22. pp. 373-382.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website: https://doi.org/10.1111/avsc.12442
 
3
4


Abstract

Question: What are the differences between plant communities recognised using supervised versus un‐supervised methods?

Location: Northeastern Australia.

Methods: Two classifications of savanna plant communities were formed independently with two different approaches: supervised and un‐supervised (using agglomerative hierarchical clustering). Each approach used the same vegetation datasets and, importantly, classification criteria. The communities occur on two different landscapes, with differing environmental gradients, covering an area of 53,500 km2. We compared the internal characteristics of plant communities between approaches and landscapes using four evaluation criteria: identifiability, distinctiveness, similarity of internal heterogeneity and predictability of species foliage cover. Additionally, we compared the central floristic concepts and compositional boundaries of communities identified by each approach.

Results: Supervised and un‐supervised approaches recognised similar floristic community concepts. Compositional boundaries between communities were similar on the landscape with steeper environmental gradients but significantly different on the landscape with gradual environmental gradients. However, communities distinguished using supervised methods were significantly less distinct and identifiable, worse at predicting species foliage cover and significantly more variable in species composition than those identified using un‐supervised methods.

Conclusions: Using supervised rather than un‐supervised approaches to distinguish plant communities can result in less recognisable communities, possibly reducing their usefulness for land management planning. Importantly, we found a large disparity between the two approaches in delineating compositional boundaries between communities on landscapes with gradual environmental gradients. This is particularly relevant to communities in biomes such as the savanna which comprises 20% of the Earth's landmass. Ecologists can be more confident using a supervised approach on landscapes with steep environmental gradients but should target landscapes with gradual environmental gradients for un‐supervised classification.

Item ID: 60439
Item Type: Article (Research - C1)
ISSN: 1654-109X
Related URLs:
Additional Information:

A version of this publication was included as Chapter 5 of the following PhD thesis: Addicott, Eda Patricia (2019) A new classification approach: improving the regional ecosystem classification system in Queensland, Australia. PhD thesis, James Cook University, which is available Open Access in ResearchOnline@JCU. Please see the Related URLs for access.

Funders: Australian Research Council (ARC)
Projects and Grants: ARC Future Fellowship FT130101319
Date Deposited: 09 Oct 2019 04:14
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410404 Environmental management @ 30%
31 BIOLOGICAL SCIENCES > 3103 Ecology > 310302 Community ecology (excl. invasive species ecology) @ 70%
SEO Codes: 96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960501 Ecosystem Assessment and Management at Regional or Larger Scales @ 100%
Downloads: Total: 4
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page