Beauty in the eye of the beholder: a new species of gecko (Diplodactylidae: Lucasium) from inland north Queensland, Australia.

The Einasleigh Uplands bioregion of central north Queensland, Australia, harbours a unique suite of reptiles that have begun to receive significant attention in the last 20 years. This has resulted in a number of new reptile species being described, and recognition that others await description. We describe a new species of Lucasium Wermuth, 1965 from the western Einasleigh Uplands. Lucasium iris sp. nov. is genetically distinct and morphologically diagnosable from all congeners by its large size, long and narrow tail, nares in contact with rostral scale, homogeneous body scales, distinct vertebral stripe, and paired, enlarged, apical subdigital lamellae. It is known from low rocky hills in a localised area of the Gregory Range, has the most restricted known distribution of any Lucasium, and is the only Lucasium endemic to Queensland. The new species appears most closely related to L. steindachneri (Boulenger, 1885), based on mitochondrial DNA sequences, but has a colour-pattern more similar to L. immaculatum Storr, 1988. All three of these species occur in the Einasleigh Uplands, but only L. steindachneri is known to occur in sympatry with L. iris sp. nov. In addition to the description of the new species, we present records of Lucasium immaculatum from the Einasleigh Uplands, which represent a significant known range extension.

Correlates of Recent Declines of Rodents in Northern and Southern Australia: Habitat Structure Is Critical.

Australia has experienced dramatic declines and extinctions of its native rodent species over the last 200 years, particularly in southern Australia. In the tropical savanna of northern Australia significant declines have occurred only in recent decades. The later onset of these declines suggests that the causes may differ from earlier declines in the south. We examine potential regional effects (northern versus southern Australia) on biological and ecological correlates of range decline in Australian rodents. We demonstrate that rodent declines have been greater in the south than in the tropical north, are strongly influenced by phylogeny, and are consistently greater for species inhabiting relatively open or sparsely vegetated habitat. Unlike in marsupials, where some species have much larger body size than rodents, body mass was not an important predictor of decline in rodents. All Australian rodent species are within the prey-size range of cats (throughout the continent) and red foxes (in the south). Contrary to the hypothesis that mammal declines are related directly to ecosystem productivity (annual rainfall), our results are consistent with the hypothesis that disturbances such as fire and grazing, which occur in non-rainforest habitats and remove cover used by rodents for shelter, nesting and foraging, increase predation risk. We agree with calls to introduce conservation management that limits the size and intensity of fires, increases fire patchiness and reduces grazing impacts at ecological scales appropriate for rodents. Controlling feral predators, even creating predator-free reserves in relatively sparsely-vegetated habitats, is urgently required to ensure the survival of rodent species, particularly in northern Australia where declines are not yet as severe as those in the south.

Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1-100 ha) and landscape (100-1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes.

Projected changes in distributions of Australian tropical savanna birds under climate change using three dispersal scenarios.

Identifying the species most vulnerable to extinction as a result of climate change is a necessary first step in mitigating biodiversity decline. Species distribution modeling (SDM) is a commonly used tool to assess potential climate change impacts on distributions of species. We use SDMs to predict geographic ranges for 243 birds of Australian tropical savannas, and to project changes in species richness and ranges under a future climate scenario between 1990 and 2080. Realistic predictions require recognition of the variability in species capacity to track climatically suitable environments. Here we assess the effect of dispersal on model results by using three approaches: full dispersal, no dispersal and a partial-dispersal scenario permitting species to track climate change at a rate of 30 km per decade. As expected, the projected distributions and richness patterns are highly sensitive to the dispersal scenario. Projected future range sizes decreased for 66% of species if full dispersal was assumed, but for 89% of species when no dispersal was assumed. However, realistic future predictions should not assume a single dispersal scenario for all species and as such, we assigned each species to the most appropriate dispersal category based on individual mobility and habitat specificity; this permitted the best estimates of where species will be in the future. Under this "realistic" dispersal scenario, projected ranges sizes decreased for 67% of species but showed that migratory and tropical-endemic birds are predicted to benefit from climate change with increasing distributional area. Richness hotspots of tropical savanna birds are expected to move, increasing in southern savannas and southward along the east coast of Australia, but decreasing in the arid zone. Understanding the complexity of effects of climate change on species' range sizes by incorporating dispersal capacities is a crucial step toward developing adaptation policies for the conservation of vulnerable species.

Weather, not climate, defines distributions of vagile bird species.

BACKGROUND: Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species. METHODOLOGY: We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS) using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed "weather" models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality) from the three month, six month and one year period preceding each bird record over a 58 year period (1950-2008). These weather models were compared against models built using long-term (30 year) averages of the same climatic variables. CONCLUSIONS: Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages over-estimate availability of suitable habitat and species' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organism-appropriate temporal scales, improves understanding of species distributions.

Optimizing allocation of management resources for wildlife.

Allocating money for species conservation on the basis of threatened species listings is not the most cost-effective way of promoting recovery or minimizing extinction rates. Using ecological and social factors in addition to threat categories, we designed a decision-support process to assist policy makers in their allocation of resources for the management of native wildlife and to clarify the considerations leading to a priority listing. Each species is scored on three criteria at the scale of the relevant jurisdiction: (1) threat category, (2) consequences of extinction, and (3) potential for successful recovery. This approach provides opportunity for independent input by policy makers and other stakeholders (who weight the relative importance of the criteria) and scientists (who score the species against the criteria). Thus the process explicitly separates societal values from the technical aspects of the decision-making process while acknowledging the legitimacy of both inputs. We applied our technique to two Australian case studies at different spatial scales: the frogs of Queensland (1,728,000 km(2); 116 species) and the mammals of the Wet Tropics bioregion (18,500 km(2); 96 species). We identified 7 frog and 10 mammal species as priorities for conservation. The frogs included 1 of the 9 species classified as endangered under Queensland legislation, 3 of the 10 species classified as vulnerable, 2 of the 22 species classified as rare, and 1 of the 75 species classified as least concern. The mammals identified included 3 of the 6 species classified as endangered, 1 of the 4 species classified as vulnerable, 5 of the 11 species classified as rare, and 1 of the 75 species classified as least concern. The methods we used to identify species were robust to comparisons across the two taxonomic groups. We concluded that (1) our process facilitates comparisons of data required to make transparent, cost-effective, and strategic management decisions across taxonomic groups and (2) the process should be used to short-list species for further discussion rather than for allocating resources per se.