Spatial model for predicting the presence of cinnamon fungus (<i>Phytophthora cinnamomi</i>) in sclerophyll vegetation communities in south‐eastern Australia

Wilson, Barbara A.; Lewis, Adam; Aberton, John

doi:10.1046/j.1442-9993.2003.01253.x

Cited by 30 publications

(14 citation statements)

References 18 publications

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“…We calculated slope (degrees) and aspect (degrees) for each plot using ArcGIS version 8.1 (Environmental Systems Research Institute, Inc., Redlands, CA) and a digital elevation model (DEM) with a horizontal grid spacing of 10 m. We used the Surface Analysis tool in the Spatial Analyst extension to create slope and aspect layers from the DEM. Because the combined effect of slope and aspect can influence how much solar radiation an area receives, which in turn can influence the phenology and water status of plants growing in these areas, we calculated a sun index (Wilson et al , ; Gibson et al ) for inclusion as a model variable using the following formula, modified for the Northern Hemisphere as follows:

Sun Index = - (cos [aspect] \times tan [slope] \times 100)

where aspect is in degrees from north, and slope is in degrees from horizontal in the direction of the steepest slope. South‐facing, steep slopes have positive (high) sun index values, whereas north‐facing, steep slopes have negative sun index values.…”

Section: Methodsmentioning

confidence: 99%

Relationship between habitat characteristics and densities of southern Idaho ground squirrels

et al. 2013

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Many wildlife species living in sagebrush‐steppe habitats of the Intermountain West of the United States have experienced population declines. Effective management of such species, especially restoration efforts, is contingent on understanding relationships between habitat characteristics and population densities of the target species. Unfortunately, even such basic information is often lacking. The goal of this 2‐year study was to determine the relationship between southern Idaho ground squirrel (Urocitellus endemicus) population densities and habitat variables: soils (texture), topography (slope, aspect), and vegetation (canopy cover, species diversity). We measured population density indirectly through burrow entrance counts and categorized them into high‐burrow and low‐burrow densities. We used logistic regression and Akaike's Information Criterion to identify a best subset of models. We employed model averaging and calculated odds ratios for averaged parameter estimates found in the best models. A high density of burrows was associated with greater percentages of silt; east‐facing aspects; greater plant species diversity; and greater cover of perennial grasses, perennial grasses and forbs, and native perennial forbs. Low burrow density was associated with greater percentages of sand; south‐facing aspects; greater cover of exotic annuals; and lesser plant species diversity. Management of southern Idaho ground squirrel habitat should focus on protecting areas with existing native vegetation and restoring native, perennial vegetation in areas that are infested with exotic annuals, especially in areas possessing suitable soil types and topographic features. © 2013 The Wildlife Society.

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Sun Index = - (cos [aspect] \times tan [slope] \times 100)

Section: Methodsmentioning

confidence: 99%

Relationship between habitat characteristics and densities of southern Idaho ground squirrels

et al. 2013

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“…(Wilson, Aberton & Reichl 2001; Wilson, Lewis & Aberton 2003). Sun index was used on the premise that the amount of solar radiation received at a site will be influenced by the steepness and orientation of the landscape at that site.…”

Section: Methodsmentioning

confidence: 99%

Spatial prediction of rufous bristlebird habitat in a coastal heathland: a GIS‐based approach

Gibson¹,

Wilson²,

Cahill³

et al. 2004

Journal of Applied Ecology

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182

146

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Summary 1.To develop a conservation management plan for a species, knowledge of its distribution and spatial arrangement of preferred habitat is essential. This is a difficult task, especially when the species of concern is in low abundance. In south-western Victoria, Australia, populations of the rare rufous bristlebird Dasyornis broadbenti are threatened by fragmentation of suitable habitat. In order to improve the conservation status of this species, critical habitat requirements must be identified and a system of corridors must be established to link known populations. A predictive spatial model of rufous bristlebird habitat was developed in order to identify critical areas requiring preservation, such as corridors for dispersal. 2. Habitat models generated using generalized linear modelling techniques can assist in delineating the specific habitat requirements of a species. Coupled with geographic information system (GIS) technology, these models can be extrapolated to produce maps displaying the spatial configuration of suitable habitat. 3. Models were generated using logistic regression, with bristlebird presence or absence as the dependent variable and landscape variables, extracted from both GIS data layers and multispectral digital imagery, as the predictors. A multimodel inference approach based on Akaike's information criterion was used and the resulting model was applied in a GIS to extrapolate predicted likelihood of occurrence across the entire area of concern. The predictive performance of the selected model was evaluated using the receiver operating characteristic (ROC) technique. A hierarchical partitioning protocol was used to identify the predictor variables most likely to influence variation in the dependent variable. Probability of species presence was used as an index of habitat suitability. 4. Negative associations between rufous bristlebird presence and increasing elevation, 'distance to creek', 'distance to coast' and sun index were evident, suggesting a preference for areas relatively low in altitude, in close proximity to the coastal fringe and drainage lines, and receiving less direct sunlight. A positive association with increasing habitat complexity also suggested that this species prefers areas containing high vertical density of vegetation. 5. The predictive performance of the selected model was shown to be high (area under the curve 0·97), indicating a good fit of the model to the data. Hierarchical partitioning analysis showed that all the variables considered had significant independent contributions towards explaining the variation in the dependent variable. The proportion of the total study area that was predicted as suitable habitat for the rufous bristlebird (using probability of occurrence at a ≥ 0·5 level) was 16%. 6. Synthesis and applications. The spatial model clearly delineated areas predicted as highly suitable rufous bristlebird habitat, with evidence of potential corridors linking coastal and inland populations via gullies. Conservation of this species will depend...

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“…cinnamomi is broadly distributed globally. At very small spatial scales (i.e.,~1 m 2 ), the pathogen appears to be somewhat randomly distributed; although it may be present within a given square meter soil patch, it is likely to be detected in only a fraction of samples collected within that patch [21][22][23]. Pathogen propagules are also capable of moving vertically within the soil profile, retreating to depth to survive inclement conditions [21,24].…”

Section: Introductionmentioning

confidence: 99%

“…Across broader spatial scales, P. cinnamomi is thought to be associated with moist soils at low topographic positions, such as drainages. Conversely, the pathogen is generally thought to be absent from higher and drier soils [22,23,25,26]. However, P. cinnamomi has been isolated from dry ridgetop soils in Australia [27] and eastern Kentucky [28], suggesting that environmental conditions limiting P. cinnamomi and its distribution are complex.…”

Section: Introductionmentioning

confidence: 99%

Phytophthora cinnamomi Colonized Reclaimed Surface Mined Sites in Eastern Kentucky: Implications for the Restoration of Susceptible Species

Sena

Yeager

Dreaden

et al. 2018

Forests

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Appalachian forests are threatened by a number of factors, especially introduced pests and pathogens. Among these is Phytophthora cinnamomi, a soil-borne oomycete pathogen known to cause root rot in American chestnut, shortleaf pine, and other native tree species. This study was initiated to characterize the incidence of P. cinnamomi on surface mined lands in eastern Kentucky, USA, representing a range of time since reclamation (10, 12, 15, and 20 years since reclamation). Incidence of P. cinnamomi was correlated to soil properties including overall soil development, as indicated by a variety of measured soil physical and chemical parameters, especially the accumulation of soil organic carbon. P. cinnamomi was detected in only two of the four sites studied, aged 15 and 20 years since reclamation. These sites were generally characterized by higher organic matter accumulation than the younger sites in which P. cinnamomi was not detected. These results demonstrate that P. cinnamomi is capable of colonizing reclaimed mine sites in Appalachia; additional research is necessary to determine the impact of P. cinnamomi on susceptible tree species at these sites.

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Spatial model for predicting the presence of cinnamon fungus (Phytophthora cinnamomi) in sclerophyll vegetation communities in south‐eastern Australia

Cited by 30 publications

References 18 publications

Relationship between habitat characteristics and densities of southern Idaho ground squirrels

Relationship between habitat characteristics and densities of southern Idaho ground squirrels

Spatial prediction of rufous bristlebird habitat in a coastal heathland: a GIS‐based approach

Phytophthora cinnamomi Colonized Reclaimed Surface Mined Sites in Eastern Kentucky: Implications for the Restoration of Susceptible Species

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