Mapping and explaining the productivity of Pinus radiata in New Zealand

Mapping Pinus radiata productivity for New Zealand not only provides useful information for forest owners, industry stakeholders and policy managers, but also enables current and future plantations to be visualised, quantified, and planned. Using an extensive set of permanent sample plots, split into fitting (n = 1,146) and validation (n = 618) datasets, models of P. radiata 300 Index (an index of volume mean annual increment) and Site Index (an index of height growth) were developed using a regression kriging technique. Spatial predictions were accurate and accounted for 61% and 70% of the variance for 300 Index and Site Index, respectively. Productivity predicted from these surfaces for the entire plantation estate averaged 27.4 m³ ha⁻¹ yr⁻¹ for the 300 Index and 30.4 m for Site Index. Surfaces showed wide regional variation in this productivity, which was attributable mainly to variation in air temperature and root-zone water storage from site to site

Fast Learning Neural Nets with Adaptive Learning Styles

There are many learning methods in artificial neural networks. Depending on the application, one learning or weight update rule may be more suitable than another, but the choice is not always clear-cut, despite some fundamental constraints, such as whether the learning is supervised or unsupervised. This paper addresses the learning style selection problem by proposing an adaptive learning style. Initially, some observations concerning the nature of adaptation and learning are discussed in the context of the underlying motivations for the research, and this paves the way for the description of an example system. The approach harnesses the complementary strengths of two forms of learning which are dynamically combined in a rapid form of adaptation that balances minimalist pattern intersection learning with Learning Vector Quantization. Both methods are unsupervised, but the balance between the two is determined by a performance feedback parameter. The result is a data-driven system that shifts between alternative solutions to pattern classification problems rapidly when performance is poor, whilst adjusting to new data slowly, and residing in the vicinity of a solution when performance is good

Snap-Drift: Real-time, Performance-guided Learning

A novel approach for real-time learning and mapping of patterns using an external performance indicator is described. The learning makes use of the 'snap-drift' algorithm based on the concept of fast, convergent, minimalist learning (snap) when the overall network performance has been poor and slower, cautious learning (drift towards user request input patterns) when the performance has been good, in a non-stationary environment where new patterns are being introduces over time. Snap is based on adaptive resonance; and drift is based on learning vector quantization (LVQ). The two are combined in a semi-supervised system that shifts its learning style whenever it receives a change in performance feedback. The learning is capable of rapidly relearning and reestablishing, according to changes in feedback or patterns. We have used this algorithm in the design of a modular neural network system, known as performance-guided adaptive resonance theory (P-ART). Simulation results show that it discovers alternative solutions in response to a significantly changed situation, in terms of the input vectors (patterns) and/or of the environment, which may require the patterns to be treated differently over time

Performance-guided Neural Network for Self-Organising Network Management

A neural network architecture is introduced for real-time learning of input sequences using external performance feedback. Some aspects of Adaptive Resonance Theory (ART) networks [1] are applied because they are able to function in a fast real-time adaptive active network environment where user requests and new proxylets (services) are constantly being introduced over time [2,3]. The architecture learns, self-organis es and self-stabilises in response to user requests, mapping the requests according to the types of proxylets available. However, in order make the neural networks respond to performance feedback, we introduce a modification to the original ART1 network in the form of the ‘snap-drift’ algorithm, that uses fast convergent, minimalist learning (snap) when the overall network performance is poor, and slow learning (drift towards user request input pattern) when the performance is good. Preliminary simulations evaluate the two-tiered architecture using a simple operating environment consisting of simulated training and test data

Extreme wet conditions coincident with Bronze Age abandonment of upland areas in Britain

Abandonment of farming systems on upland areas in southwest Britain during the Late Bronze Age – some 3000 years ago – is widely considered a ‘classic’ demonstration of the impact of deteriorating climate on the vulnerability of populations in such marginal environments. Here we test the hypothesis that climate change drove the abandonment of upland areas by developing new chronologies for human activity on upland areas during the Bronze Age across southwest Britain (Dartmoor, Exmoor and Bodmin Moor). We find Bronze Age activity in these areas spanned 3900–2950 calendar years ago with abandonment by 2900 calendar years ago. Holocene Irish bog and lake oak tree populations provide evidence of major shifts in hydroclimate across western Britain and Ireland, coincident with ice rafted debris layers recognized in North Atlantic marine sediments, indicating significant changes in the latitude and intensity of zonal atmospheric circulation across the region. We observe abandonment of upland areas in southwest Britain coinciding with a sustained period of extreme wet conditions that commenced 3100 calendar years ago. Our results are consistent with the view that climate change increased the vulnerability of these early farming communities and led to a less intensive use of such marginal environments across Britain

Fight or Flight: Parental Decisions about Predators at Nests of Northern Bobwhites (Colinus virginianus)

Patterns of nest defense against predators by ground-nesting bird species in the wild are poorly understood, largely because of a historical inability to directly monitor nests. Most nest-defense studies have observed responses elicited from artificial predators or human observers presented to nesting birds, and few have attempted to present these events in the context of predator—prey relationships found in the wild. We hypothesized that predator threat level (e.g., the threat posed to the clutch or to the clutch and the attending adult), parental characteristics, clutch investment, and future reproductive opportunities would influence avian nest-defense decisions. During 1999–2006, we examined predation events (n = 242) from 790 video-monitored Northern Bobwhite (Colinus virginianus) nests. We evaluated parental, predator, daily, and seasonal correlates that potentially contributed to patterns of nest defense by Northern Bobwhites using a model selection approach. The top model showed that nest defense was strongest at nests with larger predators that posed a threat to both adults and the clutch. This model also contained clutch size, but parameter estimates suggest that predator type was the only significant factor determining rates of nest defense. Our results suggest that Northern Bobwhites use the threat posed to the nest and the attending adult by the approaching predator as the primary cue in decisions to engage in nest defense

Potential for tree rings to reveal spatial patterns of past drought variability across western Australia

Proxy records have provided major insights into the variability of past climates over long timescales. However, for much of the Southern Hemisphere, the ability to identify spatial patterns of past climatic variability is constrained by the sparse distribution of proxy records. This is particularly true for mainland Australia, where relatively few proxy records are located. Here, we (1) assess the potential to use existing proxy records in the Australasian region—starting with the only two multi-century tree-ring proxies from mainland Australia—to reveal spatial patterns of past hydroclimatic variability across the western third of the continent, and (2) identify strategic locations to target for the development of new proxy records. We show that the two existing tree-ring records allow robust reconstructions of past hydroclimatic variability over spatially broad areas (i.e. > 3° × 3°) in inland north- and south-western Australia. Our results reveal synchronous periods of drought and wet conditions between the inland northern and southern regions of western Australia as well as a generally anti-phase relationship with hydroclimate in eastern Australia over the last two centuries. The inclusion of 174 tree-ring proxy records from Tasmania, New Zealand and Indonesia and a coral record from Queensland did not improve the reconstruction potential over western Australia. However, our findings suggest that the addition of relatively few new proxy records from key locations in western Australia that currently have low reconstruction skill will enable the development of a comprehensive drought atlas for the region, and provide a critical link to the drought atlases of monsoonal Asia and eastern Australia and New Zealand

Identification and Mitigation of Conducting Package Losses for Quantum Superconducting Devices

Low-loss superconducting microwave devices are required for quantum computation. Here, we present a series of measurements and simulations showing that conducting losses in the packaging of our superconducting resonator devices affect the maximum achievable internal quality factors (Qi) for a series of thin-film Al quarter-wave resonators with fundamental resonant frequencies varying between 4.9 and 5.8 GHz. By utilizing resonators with different widths and gaps, we sampled different electromagnetic energy volumes for the resonators affecting Qi. When the backside of the sapphire substrate of the resonator device is adhered to a Cu package with a conducting silver glue, a monotonic decrease in the maximum achievable Qi is found as the electromagnetic sampling volume is increased. This is a result of induced currents in large surface resistance regions and dissipation underneath the substrate. By placing a hole underneath the substrate and using superconducting material for the package, we decrease the ohmic losses and increase the maximum Qi for the larger size resonators

Patterns of Incubation Behavior in Northern Bobwhites (\u3ci\u3eColinus virginianus\u3c/i\u3e)

Patterns of incubation and nesting behavior for many species of birds, especially those with cryptic nests, have been difficult to obtain due to logistical and technological limitations. As a result, little is known about the daily attendance rhythms and behavioral patterns of many species, including the Northern Bobwhite (Colinus virginianus), despite this species being one of the most studied birds in the world. Incubation represents parental investment in offspring, and a multitude of factors may affect investment behaviors, including reproductive ecology, sex and age of parent, habitat quality, clutch age, and timing in the nesting season. Most Northern Bobwhite nests are incubated by a single adult, most often by females, but also by some males. We assessed the nest attendance patterns and parental investment in bob-white clutches (n 118) using continuous near-infrared video of nests being incubated by male or female bobwhites. We found that incubating parents took 0 –3 recesses per day. A single recess was most common for 87% of nest-days, and most of these were during mid-day to late afternoon (12:00 19:00). Mean total daily recess time was 182 min (95% CI: 98–264) for nests that hatched and 224 min (95% CI: 140–308) for nests that failed. We observed no difference between sexes in the number or length of recesses taken, but females initiated recess later in the day (median start time 15:00) than males (median start time 14:00). We found that nest recess length decreased as the clutch got older and increased as the nesting season progressed. Video surveillance systems proved to be a use-ful tool for observing and quantifying patterns of incubation behavior in a ground-nesting species with cryptic nests

A769662 inhibits insulin-stimulated akt activation in human macrovascular endothelial cells independent of AMP-activated protein kinase

Protein kinase B (Akt) is a key enzyme in the insulin signalling cascade, required for insulin-stimulated NO production in endothelial cells (ECs). Previous studies have suggested that AMP-activated protein kinase (AMPK) activation stimulates NO synthesis and enhances insulin-stimulated Akt activation, yet these studies have largely used indirect activators of AMPK. The effects of the allosteric AMPK activator A769662 on insulin signalling and endothelial function was therefore examined in cultured human macrovascular ECs. Surprisingly, A769662 inhibited insulin-stimulated NO synthesis and Akt phosphorylation in human ECs from umbilical veins (HUVECs) and aorta (HAECs). In contrast, the AMPK activators compound 991 and AICAR had no substantial inhibitory effect on insulin-stimulated Akt phosphorylation in ECs. Inhibition of AMPK with SBI-0206965 had no effect on the inhibition of insulin-stimulated Akt phosphorylation by A769662, suggesting the inhibitory action of A769662 is AMPK-independent. A769662 decreased IGF1-stimulated Akt phosphorylation yet had no effect on VEGF-stimulated Akt signalling in HUVECs, suggesting that A769662 attenuates early insulin/IGF1 signalling. The effects of A769662 on insulin-stimulated Akt phosphorylation were specific to human ECs, as no effect was observed in the human cancer cell lines HepG2 or HeLa, as well as in mouse embryonic fibroblasts (MEFs). A769662 inhibited insulin-stimulated Erk1/2 phosphorylation in HAECs and MEFs, an effect that was independent of AMPK in MEFs. Therefore, despite being a potent AMPK activator, A769662 has effects unlikely to be mediated by AMPK in human macrovascular ECs that reduce insulin sensitivity and eNOS activation