Dynamic Land Cover Dataset version 2: 2001-now&amp;#x2026;a land cover odyssey

Lymburner, Leo; Tan, Peter J.; McIntyre, A.; Lewis, Adam; Thankappan, Medhavy

doi:10.1109/igarss.2013.6723532

Cited by 12 publications

(13 citation statements)

References 1 publication

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“…A noisy signal could therefore be expected from older records in areas which no longer have suitable vegetation conditions. Nevertheless, we analysed the 2000–2008 land cover type (Lymburner et al., 2010) for all occurrence records and found that the percentage of records in likely unsuitable land cover types (e.g. herbaceous vegetation, woody shrubs or cleared land) was negligible.…”

Section: Discussionmentioning

confidence: 99%

Dealing with sampling bias and inferring absence data to improve distribution models of a widely distributed vulnerable marsupial

Brizuela‐Torres,

Elith,

Guillera‐Arroita

et al. 2024

Austral Ecology

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Species distribution models are widely used to identify potential and high‐quality habitat of endangered species to inform conservation decisions. However, their usefulness is constrained by the amount and quality of biodiversity data and the approaches for dealing with data deficiencies. Presence‐only data, used in presence/background modelling methods, are widely available but are often affected by sampling bias. Presence/absence modelling methods are less affected by biases, but data are less common. We modelled the distribution of a widely distributed, endangered species from Australia – the greater glider – and tested how predictions were influenced by data treatment and modelling framework. We collated available species data and fitted generalized linear models and boosted regression trees using presence/absence data, as well as using an augmented dataset that included additional presences alongside absences inferred from survey data. We also fitted presence/background models, adopting three common strategies for bias correction. We compared model performance quantitatively through evaluation metrics calculated internally and on held out data, and qualitatively by identifying areas of agreement of spatial predictions. We found that presence/background models with bias correction performed better than not corrected, though evaluation metrics did not favour a single strategy. Presence/absence models outperformed presence/background models in comparable metrics and delivered different spatial predictions. Importantly, differences in spatial predictions between models had the potential to substantially alter decisions about where to protect high‐quality habitat. The approach to inferring absences proved useful, as models fitted with these outperformed all other models. Dealing with sampling bias requires additional time and data management strategies, but we found that the time invested allowed improvement of models and more reliable predictions. Our results suggest that ancillary occurrence data and careful data handling can improve both presence/background and presence/absence models.

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Section: Discussionmentioning

confidence: 99%

Dealing with sampling bias and inferring absence data to improve distribution models of a widely distributed vulnerable marsupial

Brizuela‐Torres,

Elith,

Guillera‐Arroita

et al. 2024

Austral Ecology

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“…Range data polygons for each species were downloaded from the IUCN Red List (IUCN, 2020a) and information on elevation and habitat preferences (where present) was noted. Australian Land Cover Classifications (Lymburner et al., 2015) were grouped to match the IUCN Habitat Classifications (IUCN, 2012) as closely as possible (Supporting Information S1). Contour data for Australia were obtained from Geoscience Australia (2004) to provide elevation information, and shapefiles that captured the intersection of range data, elevation, and habitat preferences were generated using Geographic Information System software, providing an AOH map for each species.…”

Section: Methodsmentioning

confidence: 99%

A consumption‐based analysis of extinction risk in Australia

Irwin

Geschke

2023

Conservation Letters.

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Australia has an important role to play in protecting biodiversity, yet has a poor track record in preventing species extinctions. While invasive species and fire regimes are significant contributors to extinction risk in Australia, many species are threatened by habitat loss and other activities that support demand for products and services. Here, we connect the direct impact on in-scope species to the final consumption ultimately supported by those activities, quantifying a territorial and consumption extinction-risk footprint for each economic sector, state, territory, and local government area. We identify consumption of goods and services provided by the construction sector as the most significant consumption driver of extinction risk and show that 30% of Australia's extinction-risk footprint is exported. Our findings highlight the importance of local government as the last line of defense against species extinctions and suggest that programs that influence consumption behavior may be required to reduce extinction risk in Australia.

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“…Landscape properties were extracted from the Dynamic Land Cover Dataset (DLCD) sourced from Lymburner et al (2010) using ArcGIS 10.6 (ESRI, 2017). Data on three landscape properties; landscape composition, edge density, and connectivity were assessed at the spatial scales of 250, 500, 1000, 2500, and 5000 m radii from the field center.…”

Section: Methodsmentioning

confidence: 99%

Continent‐wide evidence that landscape context can mediate the effects of local habitats on in‐field abundance of pests and natural enemies

Akter

Rizvi

Haque³

et al. 2023

Ecology and Evolution

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Landscape‐scale factors known to influence in‐field abundance of pest herbivores and their natural enemies, but little is known about effects that operate through the shorter‐range influences exerted by habitats immediately adjacent to crop fields. This study first compared the abundance of brassica insect pests and their natural enemy arthropods in 24 spatially independent brassica vegetable fields across southern Australia. An ‘edge effect’ index was used to compare the abundance of each taxon in the field center with abundance in areas of the crop adjacent to differing habitats. Then, three landscape properties: landscape composition, edge density, and connectivity of diverse crop and non‐crop habitats were analyzed at five scales up to 5 km from these focal field centers to assess longer‐range influences on arthropod abundances in field centers and on the edge effects. Edge effect of adjacent woody vegetation promoted ladybirds and reduced diamondback moth and whiteflies. Conversely, the presence of crops and pastures immediately adjacent to focal crop fields reduced whiteflies and aphids but with no effect on natural enemies. Effect of landscape composition and connectivity on arthropod abundance at field center found promotion of aphids (cabbage aphid and green peach aphid) by woodland in the landscape. Effect of landscape properties on the edge effects of adjacent habitats was contrasting; strengthened (landscape composition and edge density on edge effect of crops, pasture and woody vegetation in reducing diamondback moth and whiteflies) as well as weakened (edge density and landscape connectivity on edge effect of crops, pasture and woody vegetation in reducing diamondback moth on diamondback moth, whiteflies and aphids, and promoting ladybirds). Synthesis and applications: Findings of this geographically extensive study help define the level of pest risk associated with sites as well as suggest potential interventions such as establishment or restorations of woody vegetation adjacent to crop fields that could reduce risk.

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Dynamic Land Cover Dataset version 2: 2001-now…a land cover odyssey

Cited by 12 publications

References 1 publication

Dealing with sampling bias and inferring absence data to improve distribution models of a widely distributed vulnerable marsupial

Dealing with sampling bias and inferring absence data to improve distribution models of a widely distributed vulnerable marsupial

A consumption‐based analysis of extinction risk in Australia

Continent‐wide evidence that landscape context can mediate the effects of local habitats on in‐field abundance of pests and natural enemies

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