Visual fingerprints of the acoustic environment: The use of acoustic indices to characterise natural habitats

Acoustic recordings play an increasingly important role in monitoring terrestrial environments. However, due to rapid advances in technology, ecologists are accumulating more audio than they can listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings by calculating acoustic indices. These are statistics which describe the temporal-spectral distribution of acoustic energy and reflect content of ecological interest. We combine spectral indices to produce false-color spectrogram images. These not only reveal acoustic content but also facilitate navigation. An additional analytic challenge is to find appropriate descriptors to summarize the content of 24-hour recordings, so that it becomes possible to monitor long-term changes in the acoustic environment at a single location and to compare the acoustic environments of different locations. We describe a 24-hour ‘acoustic-fingerprint’ which shows some preliminary promise.

Structural, physiological and molecular characterisation of the Australian native resurrection grass Tripogon loliiformis (F.Meull) C.E.Hubb during dehydration and rehydration

There is an urgent need to develop crops that can withstand future climates. Results from this thesis demonstrated that a native Australian resurrection grass exhibits structural, physiological and metabolic strategies to tolerate drying. These strategies may be utilized for the generation of stress tolerant crops.

Error bounds for calculation of the Gittins indices

For a wide class of semi-Markov decision processes the optimal policies are expressible in terms of the Gittins indices, which have been found useful in sequential clinical trials and pharmaceutical research planning. In general, the indices can be approximated via calibration based on dynamic programming of finite horizon. This paper provides some results on the accuracy of such approximations, and, in particular, gives the error bounds for some well known processes (Bernoulli reward processes, normal reward processes and exponential target processes).

The Learning Component of Dynamic Allocation Indices

For a multiarmed bandit problem with exponential discounting the optimal allocation rule is defined by a dynamic allocation index defined for each arm on its space. The index for an arm is equal to the expected immediate reward from the arm, with an upward adjustment reflecting any uncertainty about the prospects of obtaining rewards from the arm, and the possibilities of resolving those uncertainties by selecting that arm. Thus the learning component of the index is defined to be the difference between the index and the expected immediate reward. For two arms with the same expected immediate reward the learning component should be larger for the arm for which the reward rate is more uncertain. This is shown to be true for arms based on independent samples from a fixed distribution with an unknown parameter in the cases of Bernoulli and normal distributions, and similar results are obtained in other cases.

Gittins indices and constrained allocation in clinical trials

We explore the use of Gittins indices to search for near optimality in sequential clinical trials. Some adaptive allocation rules are proposed to achieve the following two objectives as far as possible: (i) to reduce the expected successes lost, (ii) to minimize the error probability at the end. Simulation results indicate the merits of the rules based on Gittins indices for small trial sizes. The rules are generalized to the case when neither of the response densities is known. Asymptotic optimality is derived for the constrained rules. A simple allocation rule is recommended for one-stage models. The simulation results indicate that it works better than both equal allocation and Bather's randomized allocation. We conclude with a discussion of possible further developments.

Genetic Parameters for Physiological Characters in Merino Rams in Central and North West Queensland

Genetic and phenotypic parameters for respiration rate (RR) and rectal temperature (RT) are presented for weaner and hogget Merino rams, at Longreach and Julia Creek, Queensland. Heritability estimates for RT and RR at both sites and at both ages ranged from moderate to very high. Phenotypic and genetic correlations between these characters are also reported. AAABG 14th Conference; Proceedings of the Association for the Advancement of Animal Breeding and Genetics. AAABG

Climate response to physiological forcing of carbon dioxide simulated by the coupled Community Atmosphere Model (CAM3.1) and Community Land Model (CLM3.0)

Increasing concentrations of atmospheric CO2 decrease stomatal conductance of plants and thus suppress canopy transpiration. The climate response to this CO2-physiological forcing is investigated using the Community Atmosphere Model version 3.1 coupled to Community Land Model version 3.0. In response to the physiological effect of doubling CO2, simulations show a decrease in canopy transpiration of 8%, a mean warming of 0.1K over the land surface, and negligible changes in the hydrological cycle. These climate responses are much smaller than what were found in previous modeling studies. This is largely a result of unrealistic partitioning of evapotranspiration in our model control simulation with a greatly underestimated contribution from canopy transpiration and overestimated contributions from canopy and soil evaporation. This study highlights the importance of a realistic simulation of the hydrological cycle, especially the individual components of evapotranspiration, in reducing the uncertainty in our estimation of climatic response to CO2-physiological forcing. Citation: Cao, L., G. Bala, K. Caldeira, R. Nemani, and G.Ban-Weiss (2009), Climate response to physiological forcing of carbon dioxide simulated by the coupled Community Atmosphere Model (CAM3.1) and Community Land Model (CLM3.0).

Remote sensing of nitrogen and water stress in wheat

Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Developmental and physiological traits associated with high yield and stay-green phenotype in wheat

Water availability is a key limiting factor in wheat production in the northern grain belt of Australia. Varieties with improved adaptation to such conditions are actively sought. The CIMMYT wheat line SeriM82 has shown a significant yield advantage in multi-environment screening trials in this region. The objective of this study was to identify the physiological basis of the adaptive traits underpinning this advantage. Six detailed experiments were conducted to compare the growth, development, and yield of SeriM82 with that of the adapted cultivar, Hartog. The experiments were undertaken in field environments that represented the range of moisture availability conditions commonly encountered by winter crops grown on the deep Vertosol soils of this region. The yield of SeriM82 was 6-28% greater than that of Hartog, and SeriM82 exhibited a stay-green phenotype by maintaining green leaf area longer during the grain-filling period in all environments where yield was significantly greater than Hartog. However, where the availability of deep soil moisture was limited, SeriM82 failed to exhibit significantly greater yield or to express the stay-green phenotype. Thus, the stay-green phenotype was closely associated with the yield advantage of SeriM82. SeriM82 also exhibited higher mean grain mass than Hartog in all environments. It is suggested that small differences in water use before anthesis, or greater water extraction from depth after anthesis, could underlie the stay-green phenotype. The inability of SeriM82 to exhibit stay-green and higher yield where deep soil moisture was depleted indicates that extraction of deep soil moisture is important.

The physiological and metabolic impacts on sheep and cattle of feed and water deprivation before and during transport

Sheep and cattle are frequently subjected to feed and water deprivation (FWD) for about 12 h before, and then during, transport to reduce digesta load in the gastrointestinal tract. This FWD is marked by weight loss as urine and faeces mainly in the first 24 h but continuing at a reduced rate subsequently. The weight of rumen contents falls although water loss is to some extent masked by saliva inflow. FWD is associated with some stress, particularly when transportation is added. This is indicated by increased levels of plasma cortisol that may be partly responsible for an observed increase in the output of water and N in urine and faeces. Loss of body water induces dehydration that may induce feelings of thirst by effects on the hypothalamus structures through the renin-angiotensin-aldosterone system. There are suggestions that elevated cortisol levels depress angiotensin activity and prevent sensations of thirst in dehydrated animals, but further research in this area is needed. Dehydration coupled with the discharge of Na in urine challenges the maintenance of homeostasis. In FWD, Na excretion in urine is reduced and, with the reduction in digesta load, Na is gradually returned from the digestive tract to the extracellular fluid space. Control of enteropathogenic bacteria by normal rumen microbes is weakened by FWD and resulting infections may threaten animal health and meat safety. Recovery time is required after transport to restore full feed intake and to ensure that adequate glycogen is present in muscle pre-slaughter to maintain meat quality.

Growth and physiological response of six Australian rainforest tree species to a light gradient

An understanding of growth and photosynthetic potential of subtropical rainforest species to variations in light environment can be useful for determining the sequence of species introductions in rainforest restoration projects and mixed species plantations. We examined the growth and physiology of six Australian subtropical rainforest tree species in a greenhouse consisting of three artificial light environments (10%, 30%, and 60% full sunlight). Morphological responses followed the typical sun-shade dichotomy, with early and late secondary species (Elaeocarpus grandis, Flindersia brayleyana, Flindersia schottiana, and Gmelina leichhardtii) displaying higher relative growth rate (RGR) compared to mature stage species (Cryptocarya erythroxyion and Heritiera trifoliolatum). Growth and photosynthetic performance of most species reached a maximum in 30-60% full sunlight. Physiological responses provided limited evidence of a distinct dichotomy between early and late successional species. E. grandis and F brayleyana, provided a clear representation of early successional species, with marked increase in Am in high light and an ability to down regulate photosynthetic machinery in low light conditions. The remaining species (F. schottiana, G. leichhardtii, and H. trifoliolatum) were better represented as failing along a shade-tolerant continuum, with limited ability to adjust physiologically to an increase or decrease in light, maintaining similar A(max) across all light environments. Results show that most species belong to a shade-tolerant constituency, with an ability to grow and persist across a wide range of light environments. The species offer a wide range of potential planting scenarios and silvicultural options, with ample potential to achieve rapid canopy closure and rainforest restoration goals.