FIMS: a free and open-source spatial database system                     for plant observation and mobile data collection

Trotter, Lewis; Robinson, Todd; Wardell‐Johnson, Grant; Grigg, A. H.; Luxton, Sarah

doi:10.1127/phyto/2018/0249

Cited by 2 publications

(2 citation statements)

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“…A floristic information management system was developed to prevent data corruption and data-entry error, and to ensure that future data additions fit system requirements (Trotter et al 2018). This included automating name updates through Max (the Western Australian Herbarium platform for sharing plant name updates, see https://www.dpaw.wa.gov.au/about-us/ science-and-research/publications-resources/113-max-a-speciesdatabase-helper-for-windows).…”

Section: Data Cleaningmentioning

confidence: 99%

“…A Mediterranean forest, the area has important commercial and conservation values, including as a major water catchment area for Perth (Petrone et al 2010;Hughes et al 2012;Wardell-Johnson et al 2015). Alcoa of Australia Ltd (Alcoa) have collected 30 000 plots of floristic data since the 1990s (see Trotter et al 2018 for full details). The dataset covers a restricted area at high resolution, enabling community mapping and comparison to the broad floristic formations currently used to set CAR conservation targets in the forest.…”

Section: Introductionmentioning

confidence: 99%

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Vegetation classification in south-western Australia’s Mediterranean jarrah forest: new data, old units, and a conservation conundrum

Luxton

Wardell‐Johnson

Sparrow³

et al. 2021

Aust. J. Bot.

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Conservation reserve selection is guided by vegetation classification and mapping. New survey data and improvements in the availability of archived data through online data-sharing platforms enable updated classifications and the critique of existing conservation criteria. In the Northern Jarrah Forest Region of south-western Australia, percentage-based targets using ‘forest ecosystem units’ (15% of each unit) and the systematic conservation planning principles of ‘comprehensiveness, adequacy and representativeness’ underpin the State’s reserve network. To assess the degree of community-level heterogeneity within the forest ecosystem units, new survey data for the forest (30000 plots) were classified using a non-hierarchical clustering algorithm. Results were assigned to the National Vegetation Information System, and community groups defined at the Association level (Level V). Significant community level heterogeneity was found, including 15 communities in the dominant ‘jarrah woodland’ unit, and 13 in the ‘shrub, herb and sedgelands’ unit. Overall, this research highlights limitations in the current reserve system, including the influence of scale on percentage-based targets and ‘representativeness’. A multi-scale approach to reserve selection, based on a quantitative, floristic, hierarchical classification system, would improve the level of scientific rigour underlying decision-making.

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Section: Data Cleaningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Vegetation classification in south-western Australia’s Mediterranean jarrah forest: new data, old units, and a conservation conundrum

Luxton

Wardell‐Johnson

Sparrow³

et al. 2021

Aust. J. Bot.

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Capitalising on the Floristic Survey as a Non-Destructive Line of Evidence for Mineral Potential Modelling: A Case Study of Bauxite in South-Western Australia

Trotter,

Wardell-Johnson,

Grigg

et al. 2024

Land

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While geobotanists have long used plant occurrence to locate subsurface resources, none have utilised floristic surveys as evidence in models of mineral potential. Here, we combine plant species distributions with terrain metrics to produce predictive models showing the probability of bauxite presence. We identified nineteen taxa with statistically significant associations with known bauxite deposits and identified eleven terrain metrics from previous studies. We grouped variables into three variable sets (floristic, topographic, and topo-flora) and produced mineral potential models for each using four algorithms or approaches: (a) a generalised linear model (GLM); (b) random forest (RF); (c) maxent (ME); and (d) a heterogenous stacking ensemble (GLM-RF-ME). Overall, the random forest model outperformed all algorithms including the ensemble based on the area under the curve (AUC) metric. The floristic set of variables outperformed the topographic set (AUC: 0.86 v 0.82). However, together they had the greatest predictive capacity (AUC: 0.89). Six taxa, including Banksia grandis, Leucopogon verticillatus, and Persoonia longifolia, were indicators of bauxite presence, while five other taxa, including Xanthorrhoea preissii and Hypocalymma angustifolium, were associated with bauxite absence. Important topographic variables were topographic wetness, landscape position, and valley depth, which characterised bauxite locations as being well drained, in the upper slope positions of subdued hills, and at some distance from valleys. The addition of floristic surveys provides a new line of evidence about the overlying botanical life that tolerates, accumulates, or avoids bauxite or associated minerals. As opposed to drilling, both datasets can be collected and interrogated at low cost and without impact to the surrounding environment. These data are valuable additions to future applications of mineral potential modelling.

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FIMS: a free and open-source spatial database system for plant observation and mobile data collection

Cited by 2 publications

References 1 publication

Vegetation classification in south-western Australia’s Mediterranean jarrah forest: new data, old units, and a conservation conundrum

Vegetation classification in south-western Australia’s Mediterranean jarrah forest: new data, old units, and a conservation conundrum

Capitalising on the Floristic Survey as a Non-Destructive Line of Evidence for Mineral Potential Modelling: A Case Study of Bauxite in South-Western Australia

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