Proximate cues to phases of movement in a highly dispersive waterfowl, Anas superciliosa

BACKGROUND: Waterfowl can exploit distant ephemeral wetlands in arid environments and provide valuable insights into the response of birds to rapid environmental change, and behavioural flexibility of avian movements. Currently much of our understanding of behavioural flexibility of avian movement comes from studies of migration in seasonally predictable biomes in the northern hemisphere. We used GPS transmitters to track 20 Pacific black duck (Anas superciliosa) in arid central Australia. We exploited La Niña conditions that brought extensive flooding, so allowing a rare opportunity to investigate how weather and other environmental factors predict initiation of long distance movement toward freshly flooded habitats. We employed behavioural change point analysis to identify three phases of movement: sedentary, exploratory and long distance oriented movement. We then used random forest models to determine the ability of meteorological and remote sensed landscape variables to predict initiation of these phases. RESULTS: We found that initiation of exploratory movement phases is influenced by fluctuations in local weather conditions and accumulated rainfall in the landscape. Initiation of long distance movement phases was found to be highly individualistic with minor influence from local weather conditions. CONCLUSIONS: Our study reveals how individuals utilise local conditions to respond to changes in resource distribution at broad scales. Our findings suggest that individual movement decisions of dispersive birds are informed by the integration of multiple weather cues operating at different temporal and spatial scales

Will Wallace's Line save Australia from avian influenza?

Australia is separated from the Asian faunal realm by Wallace’s Line, across which there is relatively little avian migration. Although this does diminish the risk of high pathogenicity avian influenza of Asian origin arriving with migratory birds, the barrier is not complete. Migratory shorebirds, as well as a few landbirds, move through the region on annual migrations to and from Southeast Asia and destinations further north, although the frequency of infection of avian influenza in these groups is low. Nonetheless, high pathogenicity H5N1 has recently been recorded on the island of New Guinea in West Papua in domestic poultry. This event increases interest in the movements of birds between Wallacea in eastern Indonesia, New Guinea, and Australia, particularly by waterbirds. There are frequent but irregular movements of ducks, geese, and other waterbirds across Torres Strait between New Guinea and Australia, including movements to regions in which H5N1 has occurred in the recent past. Although the likelihood of avian influenza entering Australia via an avian vector is presumed to be low, the nature and extent of bird movements in this region is poorly known. There have been five recorded outbreaks of high pathogenicity avian influenza in Australian poultry flocks, all of the H7 subtype. To date, Australia is the only inhabited continent not to have recorded high pathogenicity avian influenza since 1997, and H5N1 has never been recorded. The ability to map risk from high pathogenicity avian influenza to Australia is hampered by the lack of quantitative data on the extent of bird movements between Australia and its northern neighbors. Recently developed techniques offer the promise to fill this knowledge gap

Cues, strategies, and outcomes:How migrating vertebrates track environmental change

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Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data

Aim Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert-based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert-based information with detailed empirical evidence. Here, we compared expert-based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individuals from 49 mammal species. Location Worldwide. Time period 1998-2021. Major taxa studied Forty-nine terrestrial mammal species. Methods Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types. Results IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively. Main conclusions We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data

Bird biometrics condition and disease database

Contains biometric measurements (tarsus length, bill length, total head length, body mass) of birds caught at various locations in Australia (though mainly South Australia and Victoria), including data on the viral (mainly Avian Influenza Virus) analysis of cloacal and oropharyngeal swabs, serology of sera samples, and additional data on metabolites and parasite prevalence in swabs, blood cells and sera. Approximately 1500 birds (mainly waterbirds) are sampled annually.<br /

A simple parametric method for reducing sample sizes in gut passage time trials

Seed dispersal is now regularly analyzed using spatially explicit models, relying in part on frugivore gut passage times to produce model outputs. In determining species-specific gut passage times, there is a trade-off in sample size between minimizing collection effort and maintaining statistical reliability. Here we demonstrate that a two-parameter lognormal parametric distribution reliably fits empirical gut passage time distributions and is easily parameterized using relatively small data sets of approximately 30 defecations. We suggest this approach as a statistically reliable substitute for larger empirical gut passage data sets in seed dispersal modeling, and also as a way of using published gut passage data sets to parameterize new models.<br /

Biogeographic models of gene flow in two waterfowl of the Australo-Papuan tropics

There are many large, easy-to-observe anseriform birds (ducks, geese, and swans) in northern Australia and New Guinea and they often gather in large numbers. Yet, the structure of their populations and their regional movements are poorly understood. Lac

Spatial patterns of a southern bell frog litoria raniformis population in an agricultural landscape

We investigated changes in the spatial organization of individuals within a population of endangered Southern Bell Frogs Litoria raniformis over an eight-month period. Our results identified strong temporal changes in both spatial organization and the apparent location of L. raniformis within the study site. Ripley\u27s K Function analyses showed that the position of individuals relative to one another shifted from random immediately after the study site was flooded (p &lt; 0.005), to strongly clustered at spatial scales between 0-1 500 m during the peak breeding period (p &lt; 0.005). The majority of flooded areas were dry by April and May and individuals again became aggregated within the remaining waterbodies.<br /