Spatial and temporal effects of grazing management and rainfall on the vertebrate fauna of a tropical savanna

Grazing by domestic livestock is one of the most widespread uses of the rangelands of Australia. There is limited information on the effects of grazing by domestic livestock on the vertebrate fauna of Australia and the establishment of a long-term grazing experiment in north-eastern Queensland at Wambiana provided an opportunity to attempt an examination of the changes in vertebrate fauna as a consequence of the manipulation of stocking rates. The aim was to identify what the relative effects of vegetation type, stocking rate and other landscape-scale environmental factors were on the patterns recorded. Sixteen 1-ha sites were established within three replicated treatments (moderate, heavy and variable stocking rates). The sites were sampled in the wet and dry seasons in 1999-2000 (T-0) and again in 2003-04 (T-1). All paddocks of the treatments were burnt in 1999. Average annual rainfall declined markedly between the two sampling periods, which made interpretation of the data difficult. A total of 127 species of vertebrate fauna comprising five amphibian, 83 bird, 27 reptile and 12 mammal species were recorded. There was strong separation in faunal composition from T-0 to T-1 although changes in mean compositional dissimilarity between the grazing stocking rate treatments were less well defined. There was a relative change in abundance of 24 bird, four mammal and five reptile species from T-0 to T-1. The generalised linear modelling identified that, in the T-1 data, there was significant variation in the abundance of 16 species explained by the grazing and vegetation factors. This study demonstrated that vertebrate fauna assemblage did change and that these changes were attributable to the interplay between the stocking rates, the vegetation types on the sites surveyed, the burning of the experimental paddocks and the decrease in rainfall over the course of the two surveys. It is recommended that the experiment is sampled again but that the focus should be on a rapid survey of abundant taxa (i.e. birds and reptiles) to allow an increase in the frequency of sampling and replication of the data. This would help to articulate more clearly the trajectory of vertebrate change due to the relative effects of stocking rates compared with wider landscape environmental changes. Given the increasing focus on pastoral development in northern Australia, any opportunity to incorporate the collection of data on biodiversity into grazing manipulation experiments should be taken for the assessment of the effects of land management on faunal species

Impact of Tail Loss on the Behaviour and Locomotor Performance of Two Sympatric Lampropholis Skink Species

Caudal autotomy is an anti-predator behaviour that is used by many lizard species. Although there is an immediate survival benefit, the subsequent absence of the tail may inhibit locomotor performance, alter activity and habitat use, and increase the individuals' susceptibility to future predation attempts. We used laboratory experiments to examine the impact of tail autotomy on locomotor performance, activity and basking site selection in two lizard species, the delicate skink (Lampropholis delicata) and garden skink (L. guichenoti), that occur sympatrically throughout southeastern Australia and are exposed to an identical suite of potential predators. Post-autotomy tail movement did not differ between the two Lampropholis species, although a positive relationship between the shed tail length and distance moved, but not the duration of movement, was observed. Tail autotomy resulted in a substantial decrease in sprint speed in both species (28–39%), although this impact was limited to the optimal performance temperature (30°C). Although L. delicata was more active than L. guichenoti, tail autotomy resulted in decreased activity in both species. Sheltered basking sites were preferred over open sites by both Lampropholis species, although this preference was stronger in L. delicata. Caudal autotomy did not alter the basking site preferences of either species. Thus, both Lampropholis species had similar behavioural responses to autotomy. Our study also indicates that the impact of tail loss on locomotor performance may be temperature-dependent and highlights that future studies should be conducted over a broad thermal range

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational approaches to Explainable Artificial Intelligence:Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.</p

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Eaten out of house and home:impacts of grazing on ground-dwelling reptiles in Australian grasslands and grassy woodlands

Large mammalian grazers can alter the biotic and abiotic features of their environment through their impacts on vegetation. Grazing at moderate intensity has been recommended for biodiversity conservation. Few studies, however, have empirically tested the benefits of moderate grazing intensity in systems dominated by native grazers. Here we investigated the relationship between (1) density of native eastern grey kangaroos, Macropus giganteus, and grass structure, and (2) grass structure and reptiles (i.e. abundance, richness, diversity and occurrence) across 18 grassland and grassy Eucalyptus woodland properties in south-eastern Australia. There was a strong negative relationship between kangaroo density and grass structure after controlling for tree canopy cover. We therefore used grass structure as a surrogate for grazing intensity. Changes in grazing intensity (i.e. grass structure) significantly affected reptile abundance, reptile species richness, reptile species diversity, and the occurrence of several ground-dwelling reptiles. Reptile abundance, species richness and diversity were highest where grazing intensity was low. Importantly, no species of reptile was more likely to occur at high grazing intensities. Legless lizards (Delma impar, D. inornata) were more likely to be detected in areas subject to moderate grazing intensity, whereas one species (Hemiergis talbingoensis) was less likely to be detected in areas subject to intense grazing and three species (Menetia greyii, Morethia boulengeri, and Lampropholis delicata) did not appear to be affected by grazing intensity. Our data indicate that to maximize reptile abundance, species richness, species diversity, and occurrence of several individual species of reptile, managers will need to subject different areas of the landscape to moderate and low grazing intensities and limit the occurrence and extent of high grazing

The HERMES Spectrometer

The HERMES experiment is collecting data on inclusive and semi-inclusive deep inelastic scattering of polarised positrons from polarised targets of Il, D, and He-3. These data give information on the spin structure of the nucleon. This paper describes the forward angle spectrometer built for this purpose. The spectrometer includes numerous tracking chambers (micro-strip gas chambers, drift and proportional chambers) in front of and behind a 1.3 T.m magnetic field, as well as an extensive set of detectors for particle identification (a lead-glass calorimeter, a pre-shower detector, a transition radiation detector, and a threshold Cherenkov detector). Two of the main features of the spectrometer are its good acceptance and identification of both positrons and hadrons, in particular pions. These characteristics, together with the purity of the targets, are allowing HERMES to make unique contributions to the understanding of how the spins of the quarks contribute to the spin of the nucleon. (C) 1998 Elsevier Science B.V. All rights reserved