ArticleAmbio2021
A functional perspective on the analysis of land use and land cover data in ecology.
Article in Ambio, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Accuracy assessment of global land cover datasets for monitoring forest landscape restoration targets in Malawi.Environmental monitoring and assessment · 2026Article
- Modelling the global invasion potential of Pelagia noctiluca under climate change.Scientific reports · 2026Article
- Configurational heterogeneity drives songbird diversity at distinct spatial scales in managed boreal forests.Landscape ecology · 2026Article
- Identifying restoration priorities for habitat defragmentation: a case study in Alberta's oil sands.Landscape ecology · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Assessments of large-scale changes in habitat are a priority for management and conservation. Traditional approaches use land use and land cover data (LULC) that focus mostly on "structural" properties of landscapes, rather than "functional" properties related to specific ecological processes. Here, we contend that designing functional analyses of LULC can provide important and complementary information to traditional, structural analyses. We substantiate this perspective with an example of functional changes in habitat due to industrial anthropogenic footprints in Alberta's boreal forest, where there has been little overall forest loss (~ 6% structural change), but high levels of functional change (up to 93% functional change) for species' habitat, biodiversity, and wildfire ignition. We discuss the methods needed to achieve functional LULC analyses, when they are most appropriate to add to structural assessments, and conclude by providing recommendations for analyses of LULC in a future of increasingly high-resolution, dynamic remote sensing data.
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Registered trials
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