Reliability of map accuracy assessments: A comment on Hunter <i>et al</i>. (2016)

Roff, Adam; Lyons, Mitchell; Jones, H. C.; Thonell, Jillian

doi:10.1111/emr.12213

Cited by 2 publications

(23 citation statements)

References 11 publications

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“…Our work demonstrates that incorporating spe-cies height and removing rare species ensures that quantitative community classification is conceptually consistent with approaches used to identify and describe landscape patterns. This provides a tighter linkage between plot-based classifications and remotely sensed maps, allowing more robust mapping validations (Roff et al 2016) and greater confidence of land managers in both the classification and maps.…”

Section: Discussionmentioning

confidence: 99%

When rare species are not important: linking plot-based vegetation classifications and landscape-scale mapping in Australian savanna vegetation

et al. 2018

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Plant communities in extensive landscapes are often mapped remotely using detectable patterns based on vegetation structure and canopy species with a high relative cover. A plot-based classification which includes species with low relative canopy cover and ignores vegetation structure, may result in plant communities not easily reconcilable with the landscape patterns represented in mapping. In our study, we investigate the effects on classification outcomes if we (1) remove rare species based on canopy cover, and (2) incorporate vegetation structure by weighting species' cover by different measures of vegetation height. Using a dataset of 101 plots of savanna vegetation in north-eastern Australia we investigated first, the effect of removing rare species using four cover thresholds (1, 5, 8 and 10% contribution to total cover) and second, weighting species by four height measures including actual height as well as continuous and categorical transformations. Using agglomerative hierarchical clustering we produced a classification for each dataset and compared them for differences in: patterns of plot similarity, clustering, species richness and evenness, and characteristic species. We estimated the ability of each classification to predict species cover using generalised linear models. We found removing rare species at any cover threshold produced characteristic species appearing to correspond to landscape scale changes and better predicted species cover in grasslands and shrublands. However, in woodlands it made no difference. Using actual height of vegetation layer maintained vegetation structure, emphasised canopy and then sub-canopy species in clustering, and predicted species cover best of the height-measures tested. Thus, removing rare species and weighting species by height are useful techniques for identifying plant communities from plot-based classifications which are conceptually consistent with those in landscape scale mapping. This increases the confidence of end-users in both the classifications and the maps, thus enhancing their use in land management decisions.Abbreviations: ALL-dataset consisting of the full species pool; C>1-dataset with species contributing >1% to TFC included; C>5 -dataset with species contributing >5%; C>8 -dataset with species contributing >8%; C>10 -dataset with species contributing >10% to TFC included; IS -Indicator Species; ISA -Indicator Species Analysis; TFC -Total Foliage Cover.

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Section: Discussionmentioning

confidence: 99%

When rare species are not important: linking plot-based vegetation classifications and landscape-scale mapping in Australian savanna vegetation

et al. 2018

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“…Roff et al . () appropriately question the methodology used by the Hunter () validation of the GHMv4 mapping (Sivertsen et al . ).…”

Section: Introductionmentioning

confidence: 99%

“…() call into question whether Roff et al . () have presented a balanced viewpoint. The discussion presented by Roff et al .…”

Section: Introductionmentioning

confidence: 99%

“…The discussion presented by Roff et al . () tackles only one aspect of the list of errors presented by Hunter and Hawes () and Hunter (, , ). Roff et al .…”

Section: Introductionmentioning

confidence: 99%

“…Roff et al . () did not discuss (i) the limited accuracy of modelled communities, limited and biased on‐ground sampling, and the inability of the automated segmentation process to deal with nonwoody vegetation and disturbance classes and (ii) the limited number of recognised communities. Such errors have restricted the use of the product without extensive expert postprocessing and/or modification.…”

Section: Introductionmentioning

confidence: 99%

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Reliability of map accuracy assessments: A reply to Roff et al. (2016)

Hunter¹,

Lechner²

2016

Eco Management Restoration

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Summary Roff et al. (Ecological Management and Restoration, 17, 2016, 000) provide a discussion of the criteria expected for the best approach to validation of mapping programs and uses Hunter (Ecological Management & Restoration 17, 2016, 40) to highlight issues involved. While we support the general principles outlined, we note that the review does not apply the same standards to Sivertsen et al. (Greater Hunter Native Vegetation Mapping Geodatabase Guide (Version 4.0). Office of Environment and Heritage, Department of the Premier and Cabinet, Sydney, Australia, 2011), the original document critiqued by Hunter (Ecological Management & Restoration 17, 2016, 40). The Hunter (Ecological Management & Restoration 17, 2016, 40) validation was based on a larger sample size, greater sampling within mapping units and greater representation of landscapes than Sivertsen et al. (Greater Hunter Native Vegetation Mapping Geodatabase Guide (Version 4.0). Office of Environment and Heritage, Department of the Premier and Cabinet, Sydney, Australia, 2011). Survey and validation sites being placed along public roads and lands are common to both the general Office of Environment and Heritage (OEH) and Hunter (Ecological Management & Restoration 17, 2016, 40) validation methodologies. Thus, the criticisms of Roff et al. (Ecological Management and Restoration, 17, 2016, 000) of the Hunter (Ecological Management & Restoration 17, 2016, 40) approach apply equally, if not more, to Sivertsen et al. (Greater Hunter Native Vegetation Mapping Geodatabase Guide (Version 4.0). Office of Environment and Heritage, Department of the Premier and Cabinet, Sydney, Australia, 2011). We outline in the article how the Roff et al. (Ecological Management and Restoration, 17, 2016, 000) critique was selective and in some cases incorrect in its analysis of issues presented in Hunter (Ecological Management & Restoration 17, 2016, 40) and did not apply the same criteria to their own work. We conclude by discussing future directions for validating and mapping vegetation communities.

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Reliability of map accuracy assessments: A comment on Hunter et al. (2016)

Cited by 2 publications

References 11 publications

When rare species are not important: linking plot-based vegetation classifications and landscape-scale mapping in Australian savanna vegetation

When rare species are not important: linking plot-based vegetation classifications and landscape-scale mapping in Australian savanna vegetation

Reliability of map accuracy assessments: A reply to Roff et al. (2016)

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