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

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 cree', '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 on management actions that protect the critical habitats identified in the model. A multi-scale  approach to the modelling process is recommended whereby a spatially explicit model is first generated using landscape variables extracted from a GIS, and a second model at site level is developed using fine-scale habitat variables measured on the ground. Where there are constraints on the time and cost involved in measuring finer scale variables, the first step alone can be used for conservation planning.

Landscape characteristics associated with species richness and occurrence of small native mammals inhabiting a coastal heathland: a spatial modelling approach

In the coastal region of south-western Victoria, Australia, populations of native small mammal species are restricted to patches of suitable habitat in a highly fragmented landscape. The size and spatial arrangement of these patches is likely to influence both the occupancy and richness of species at a location. Geographic Information System (GIS)-based habitat models of the species richness of native small mammals, and individual species  occurrences, were developed to produce maps displaying the spatial  configuration of suitable habitat. Models were generated using either generalised linear Poisson regression (for species richness) or logistic regression (for species occurrences) with species richness or  presence/absence as the dependent variable and landscape variables, extracted from both GIS data layers and multi-spectral digital imagery, as the predictor variables. A multi-model inference approach based on the Akaike Information Criterion was used and the resulting model was applied in a GIS framework to extrapolate predicted richness/likelihood of occurrence across the entire area of the study. A negative association between species  richness and elevation, habitat complexity and sun index indicated that richness within the study area decreases with increasing altitude, vertical vegetation structure and exposure to solar radiation. Landform  characteristics were important (to varying degrees) in determining habitat occupancy for all of the species examined, while the influence of habitat complexity was important for only one of the species. Performance of all but one of the models generated using presence/absence data was high, as indicated by the area under the curve of a receiver-operating characteristic plot. The effective conservation of the small mammal species in the area of concern is likely to depend on management actions that promote the protection of the critical habitats identified in the models.

Modelling habitat suitability of the swamp antechinus (Antechinus minimus maritimus) in the coastal heathlands of southern Victoria, Australia

In recent years, predictive habitat distribution models, derived by combining multivariate statistical analyses with Geographic Information System (GIS) technology, have been recognised for their utility in conservation planning. The size and spatial arrangement of suitable habitat can influence the long-term persistence of some faunal species. In southwestern Victoria, Australia, populations of the rare swamp antechinus (Antechinus minimus maritimus) are threatened by further fragmentation of suitable habitat. In the current study, a spatially explicit habitat suitability model was developed for A. minimus that incorporated a measure of vegetation structure. Models were generated using logistic regression with species presence or absence as the dependent variable and landscape variables, extracted from both GIS data layers and multi-spectral digital imagery, as the predictors. The most parsimonious model, based on the Akaike Information Criterion, was spatially extrapolated in the GIS. Probability of species presence was used as an index of habitat suitability. A negative association between A. minimus presence and both elevation and habitat complexity was evidenced, suggesting a preference for relatively low altitudes and a vegetation structure of low vertical complexity. The predictive performance of the selected model was shown to be high (91%), indicating a good fit of the model to the data. The proportion of the study area predicted as suitable habitat for A. minimus (Probability of occurrence greater-or-equal, slanted0.5) was 11.7%. Habitat suitability maps not only provide baseline information about the spatial arrangement of potentially suitable habitat for a species, but they also help to refine the search for other populations, making them an important conservation tool.

Estimates of Heterozostera tasmanica, Zostera muelleri and Ruppia megacarpa distribution and biomass in the Hopkins Estuary, western Victoria, by GIS

Knowledge of the spatial arrangement of the seagrass distribution and biomass within the Hopkins Estuary is an essential step towards gaining an understanding of the functioning of the estuarine ecosystem. This study marks the first attempt to map seagrass distribution and model seagrass biomass and epiphyte biomass along depth gradients by the use of global positioning system (GPS) and geographical information system (GIS) technologies in the estuary. For mapping seagrass in small estuaries, ground-surveying the entire system is feasible. Three species of seagrasses, Heterozostera tasmanica (Martens ex Aschers), Zostera muelleri (Irmisch ex Aschers) and Ruppia megacarpa (Mason), were identified in the Hopkins Estuary. All beds investigated contained a mixed species relationship. Three harvest techniques were trialed in a pilot study, with the 25 × 25-cm quadrat statistically most appropriate. Biomass of seagrasses and epiphytes was found to vary significantly with depth, but not between sites. The average estimate of biomass for total seagrasses and their epiphytes in the estuary in January 2000 was 222.7 g m^–2 (dry weight). Of the total biomass, 50.6% or 112.7 g m^–2 (dry weight) was contributed by seagrasses and 49.4% of the biomass (110.0 g m^–2) were epiphytes. Of the 50.6% of the total biomass represented by seagrasses, 39.3% (87.5 g m^–2) were leaves and 11.3% (25.2 g m^–2) were rhizomes. The total area of seagrasses present in the Hopkins Estuary was estimated to be 0.4 ± 0.005 km², with the total area of the estuary estimated to be 1.6 ± 0.02 km² (25% cover). The total standing crop of seagrasses and epiphytes in the Hopkins Estuary in January 2000 was estimated to be 102.3 ± 57 t in dry weight, 56% (56.9 ± 17 t, dry weight) seagrasses and 44% (45.4 ± 19 t, dry weight) epiphytes. Of the seagrass biomass, 39% (39.7 ± 13 t, dry weight) was contributed by leaves and 17% (17.3 ± 7 t, dry weight) by rhizomes.

Fire and the conservation of the avifauna of mallee ecosystems

This research demonstrates that in mallee ecosystems the bird community changes with time-since-fire and is influenced by the spatial arrangement of landscape mosaics comprised of different post-fire-age vegetation. Fire alters vegetation structure and food availability for birds. The management of fire is critical for the conservation of mallee birds.

Illusions vary because of the types of decorations at bowers, not male skill at arranging them, in great bowerbirds

Many animals use extended phenotypes to attract mates, but the availability of suitable resources in the environment can affect the size and form of these signals, with unknown consequences for honest signalling. In some populations of the great bowerbird, Ptilonorhynchus nuchalis, males arrange decorations by size, with smaller decorations placed closer to the bower entrance than larger decorations. This may create a more even background pattern from the female's viewpoint within the bower than if decorations were arranged randomly. Males show consistent, individual variation in the size-distance gradient, which could reflect variation among males in the cognitive skills needed to arrange decorations. We examined whether individual consistency in gradient characteristics is related to a male's skill at decoration arrangement or the types of decorations at bowers. We paired 18 males and switched bower decorations between pairs. We measured gradient characteristics before switching and 4 and 8 days after switching. Gradient characteristics after switching were related to those of the bower from which decorations were received, not to those of the male's own bower before switching. Gradient characteristics were also related to the types of decorations received, including bones and snail shells. These results suggest that variation among males in the size-distance gradient is explained by differences in the availability of decorations at bowers, not the cognitive skills required to arrange decorations. Although variation in gradient characteristics could indicate the male's ability to locate and transport particular decorations, it could also reflect local availability of objects, with no relationship to male quality.

Setting conservation priorities for migratory networks under uncertainty

Conserving migratory species requires protecting connected habitat along the pathways they travel. Despite recent improvements in tracking animal movements, migratory connectivity remains poorly resolved at a population level for the vast majority of species, hampering conservation prioritisation. In the face of these data limitations, we develop a novel approach to spatial prioritisation based on a model of potential connectivity, derived from empirical data on species abundance and distances travelled between sites while on migration. Applying this approach to migratory shorebirds using the East Asian-Australasian Flyway, we demonstrate that conservation strategies that prioritise sites based on connectivity and abundance together, outperform strategies that only prioritise sites based on the abundance of birds. The conservation value of a site is therefore dependent on both its capacity to support migratory animals and its position within the migratory pathway, with the loss of crucial sites leading to partial or total population collapse. We suggest that strategies prioritising conservation action at sites supporting large populations of migrants should, where possible, be augmented using data or models on the spatial arrangement of sites.