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The age at first breeding is an important demographic parameter in determining maximum growth rate, population size and generation time and is a key parameter in calculating the potential biological removal of birds. Albatrosses and petrels do not begin breeding for many years, with some first breeding in their teens. This means that even long-term studies of birds banded as chicks may not last long enough to observe the entire process of recruitment to breeding. Estimates based only on observed data (the naive estimate) may be biased by imperfect observation, emigration, and study duration. Instead, modelling approaches should be used to estimate the mean age at first breeding, but these must be used carefully. Here, we show the large negative bias that may be caused by limited study duration and emigration when the naive estimate is used. Capture-mark-recapture methods combined with additional assumptions about emigration can alleviate the bias, provided that an appropriate model is used. Using these methods, we analysed data collected between 1991 and 2006 on 1,246 Gibson's albatrosses ('Diomedea gibsoni') banded as chicks (mostly banded from 1995 onwards) and 1,258 birds banded as adults. While 402 birds banded as chicks were observed returning to the study area, only 42 were observed breeding. With limited data, model-based approaches must be used, and assumptions about recruitment to breeding play an additional role in the estimate of the age at first breeding. In particular, the function chosen for recruitment to breeding for older age classes cannot be compared to data. Three recruitment functions are compared to show the large sensitivity of the estimated mean age at first breeding to the assumed functional form.

Decision theory provides an organised approach to decision making in natural resource conservation. The theory requires clearly stated objectives, decision alternatives and decision-outcome utilities, and thus allows for the separation of values (conservation and other societal objectives) from beliefs. Models express belief in the likely response of the system to conservation actions, and can range from simple, graphical representations to complex computer models. Models can be used to make predictions about likely decision-outcomes, and hence guide decision making. Decision making must account for uncertainty, which can be reduced but never eliminated. Uncertainty can be described via probabilities, which in turn can be used to compute the expected value of alternative decisions, averaging over all relevant sources of uncertainty. Reduction of uncertainty, where possible, improves decision making. Adaptive management involves the reduction of uncertainty via prediction under two or more alternative, structural models, comparison of model predictions to monitoring, and feedback via Bayes' Theorem into revising model weights, which in turn influences decision making. As part of a 3-day workshop on structured decision making (SDM) and adaptive resource management (ARM), we constructed a prototypical decision model for the recovery for Hector's dolphin ('Cephalorynchus hectori'), an endangered dolphin endemic to New Zealand coastal waters. Our model captures several steps in the process of building an SDM/ARM framework, and should be useful for managers wishing to apply these principles to dolphin conservation or other resources problems.

The Australian Wildlife Health Network (AWHN) is a national initiative of the Commonwealth Government and is managed under the Wildlife Exotic Disease Preparedness Program (WEDPP) of the Australian Department of Agriculture, Fisheries and Forestry. Its mission is to promote and facilitate collaborative links in the investigation and management of wildlife health in support of human and animal health, biodiversity and trade.

With the increasing use of ion-selective electrodes in environmental and health applications, it is important to know the precision of estimated concentrations. A Bayesian model for non-linear calibration is introduced which provides estimates of measurement precision by incorporating uncertainty in calibration parameters and inherent random noise in emf response. The analysis of lead in 17 soil samples demonstrates that large gains in precision are possible when calibrations are extended to include multiple electrodes and standard addition data. The results highlight the need for improved calibration and routine use of standard addition as ion selective electrodes become increasingly popular for demanding, real world applications.

In this paper it is demonstrated how the Bayesian parametric bootstrap can be adapted to models with intractable likelihoods. The approach is most appealing when the computationally efficient semi-automatic approximate Bayesian computation (ABC) summary statistics are selected. The parametric bootstrap approximation is used to form a proposal distribution in ABC algorithms to improve the computational efficiency. The new approach is demonstrated through the sequential Monte Carlo and the ABC importance and rejection sampling algorithms. We found efficiency gains in two simulation studies, the univariate g-and-k quantile distribution, a toggle switch model in dynamic bionetworks, and in a stochastic model describing expanding melanoma cell colonies.

Principal coordinates analysis (PCoA) is a statistical ordination technique commonly applied to morphology-based cladistic matrices to study macroevolutionary patterns, morphospace occupation, and disparity. However, PCoA-based morphospaces are dissociated from the original data; therefore, whether such morphospaces accurately reflect body-plan disparity or extrinsic factors, such as body size, remains uncertain. We collated nine character–taxon matrices of dinosaurs together with body-mass estimates for all taxa and tested for relationships between body size and both the principal axis of variation (i.e., PCo1) and the entire set of PCo scores. The possible effects of body size on macroevolutionary hypotheses derived from ordinated matrices were tested by reevaluating evidence for the accelerated accumulation of avian-type traits indicated by a strong directional shift in PCo1 scores in hypothetical ancestors of modern birds. Body mass significantly accounted for, on average, approximately 50% and 16% of the phylogenetically corrected variance in PCo1 and all PCo scores, respectively. Along the avian stem lineage, approximately 30% of the morphological variation is attributed to the reconstructed body masses of each ancestor. When the effects of body size are adjusted, the period of accelerated trait accumulation is replaced by a more gradual, additive process. Our results indicate that even at low proportions of variance, body size can noticeably affect macroevolutionary hypotheses generated from ordinated morphospaces. Future studies should thoroughly explore the nature of their character data in association with PCoA-based morphospaces and use a residual/covariate approach to account for potential correlations with body size.

Second-Harmonic Laser Microscopy promises to be a useful diagnostic modality for breast cancer. Statistical image analysis has provided key insights into the differences between images of normal, benign and malignant breast tissue. Spectral analysis of image features coupled with a support-vector machine classifier is demonstrated to accurately separate normal from tumour tissue. Further analysis of the tumour group using the multi-scale, multi-directional, steerable pyramid filter has revealed features that can be used to separate benign from malignant breast tissue. The classifier presented can serve as a prototype for devices developed to serve in a clinical setting.

Silvicultural practices such as thinning are performed both for commodity production and to help achieve fuel reduction and biodiversity goals. Although there are several studies that have examined effects of clearcut harvest techniques on forest songbirds, few have examined the effects of thinning. We studied the response of songbirds to different silvicultural approaches to forest management. We experimentally manipulated three 80 to 110 y-old Douglas-fir stands to evaluate influences of commercial thinning and clearcut harvest silvicultural systems on populations of diurnal breeding birds in southwestern Oregon. We conducted 10 to 12 bird point count surveys in each stand between 1992 and 1994 (prior to treatment), and point count surveys of birds 6 times each year from 1998 through 1999 (subsequent to treatment). We found that relative abundance and species richness were highest in the uncut control plots, slightly lower in the thinned plots, and lowest in the clearcut plots. A species-by-species analysis of those species with sufficient data showed marked negative short-term impacts of clearcutting on 12 of 16 species, potentially moderate negative impacts of thinning on 9 of 16 species, as well as positive impacts of thinning on at least 3 species.

The finite annual rate of population increase (λ) is a fundamental demographic parameter that characterizes the relative annual change in animal numbers. Uncertainty in the estimation of λ from demographic population viability analyses (PVAs) has been largely limited to sensitivity analysis, calculating a pseudo-distribution 'λ' using Monte Carlo methods, or by use of bootstrap methods. The delta method has been used and suggested by several researchers, but no one has provided the computational means to implement it. In this paper, we present 'Mathematica' code to calculate λ and its variance based on eigenvalue calculations of a Leslie transition matrix. We demonstrate the procedure using data from a Hawaiian hawk ('Buteo solitarius') study.

As part of the Cicerone Project's farmlet experiment, conducted on the Northern Tablelands of New South Wales, Australia, between July 2000 and December 2006, this study assessed the effects of varying soil fertility, pasture species and grazing management on the botanical composition of three 53-ha farmlets subjected to different management strategies. Starting with the same initial conditions, the farmlets were managed to reach different target levels of soil phosphorus (P) and sulfur (S); Farmlet A aimed at 60 mg/kg of Colwell P and 10 mg/kg S (KC₄₀) whereas Farmlets B and C both aimed at 20 and 6.5 mg/kg of P and S, respectively. Pastures were renovated on six out of eight paddocks on Farmlet A, but only one paddock of each of Farmlets B (typical management) and C (intensive rotational grazing) was renovated. Flexible rotational grazing was employed on Farmlets A and B (each of eight paddocks) while Farmlet C used intensive rotational grazing over its 17 major paddocks, which were further subdivided into 37 subpaddocks. This paper focuses on the botanical composition dynamics observed across all three farmlets and the explanatory variables associated with those changes. Eight assessments of botanical composition were carried out at approximately annual intervals across each of the 37 major paddocks distributed across the farmlets and the results for each of 49 species were aggregated into seven functional groups for analysis. The strongest correlation found was a negative curvilinear relationship between sown perennial grasses (SPG) and warm-season grasses (WSG). The most significant factors affecting the functional group changes were soil P, sowing phase, paddock and date. These factors led to significant increases in SPG and correspondingly lower levels of WSG on Farmlet A compared with Farmlet B. Farmlets B and C experienced similar, declining levels of SPG, and increasing levels of WSG suggesting that intensive rotational grazing did not lead to substantial changes in botanical composition, compared with flexible rotational grazing, in spite of the fact that intensive rotational grazing had much longer grazing rests and shorter graze periods than the other two farmlets. Soil P levels were also significantly associated with levels of cool-season annual grasses, legumes and herbs, especially on Farmlet A. In general, the largest differences in botanical composition were between Farmlet A and the other two farmlets; these differences were most closely associated with those plants categorised as sown, introduced, C₃pasture species. The levels of legume were generally low on all farmlets, due largely to the dry seasons experienced over most of the trial. Efforts to increase the legume composition on all farmlets were more successful on Farmlet A than on the other two farmlets due, presumably, to higher soil fertility on Farmlet A. Farmlet C, with its long rest periods and short graze periods, had a small proportion of legumes, due to the competitive effects of the accumulated tall grass herbage between grazings. The 'typical' management of Farmlet B also resulted in low levels of legume as well as increased 'patchiness' of the pastures and increased numbers of thistles.

Multivariate estimation fitting a common structure to estimates of genetic and environmental covariance matrices is examined in a simple simulation study. It is shown that such parsimonious estimation can considerably reduce sampling variation. However, if the assumption of similarity in structure does not hold at least approximately, bias in estimates of the genetic covariance matrix can be substantial. For small samples and more than a few traits, structured estimation is likely to reduce mean square error even if bias is quite large. Hence such models should be used cautiously.

Farming systems research conducted under dryland conditions is subject to the vagaries of the climate during the experimental period. Whether such an experiment experiences a representative series of climatic years must be examined in relation to the longer term climatic record. The Cicerone Project's farmlet experiment was conducted on the Northern Tablelands of New South Wales, Australia, to investigate the profitability and sustainability of three different management systems: one managed under typical, moderate-input conditions (farmlet B); a second which employed a higher level of pasture inputs and soil fertility (farmlet A); and a third which focussed on the use of moderate inputs and intensive rotational grazing (farmlet C). The climate experienced during the 6.5-year experimental period was compared with the 118-year climatic record, using a biophysical simulation model of grazed systems. The model utilised the long-term daily climate data as inputs and provided outputs that allowed comparison of parameters known to affect grazed pastures. Modelled soil-available water, the number of soil moisture stress days (SMSDs) limiting pasture growth, and growth indices over the experimental period (2000-06) were compared with data over the climatic record from 1890 to 2007. SMSDs were defined as when the modelled available soil moisture to a depth of 300 mm was <17% of water-holding capacity. In addition, minimum temperatures and, in particular, the frequency of frosts, were compared with medium-term (1981-2011) temperature records. Wavelet transforms of rainfall and modelled available soil water data were used to separate profile features of these parameters from the noise components of the data. Over the experimental period, both rainfall and available soil water were more commonly significantly below than above the 95% confidence intervals of both parameters. In addition, there was an increased frequency of severe frosting during the dry winters experienced over the 6.5-year period. These dry and cold conditions were likely to have limited the responses to the pasture and grazing management treatments imposed on the three farmlets. In particular, lower than average levels of available soil water were likely to have constrained pasture production, threatened pasture persistence, and reduced the response of the pasture to available soil nutrients and, as a consequence, livestock production and economic outcomes. Ideally, dryland field experimentation should be conducted over a representative range of climatic conditions, including soil moisture conditions both drier and wetter than average. The drier than average conditions, combined with a higher than normal frequency of severe frosts, mean that the results from the Cicerone Project's farmlet experiment need to be viewed in the context of the climate experienced over this 6.5-year period.

This paper focuses on the construction of computer-generated designs on irregularly-shaped, constrained regions. Overviews of the Fedorov exchange algorithm (FEA) and other exchange algorithms for the construction of D-optimal designs are given. A faster implementation of the FEA is presented, which is referred to as fast-FEA (denoted FFEA). The FFEA was applied to construct D-optimal designs for several published examples with constrained experimental regions. Designs resulting from the FFEA are more D-efficient than published designs, and provide benchmarks for future comparisons of design construction algorithms. The construction of G-optimal designs for constrained regions is also discussed and illustrated with a published example.

The high detection rates of acoustic- and radio-tagged fish greatly improve the ability of an investigator to obtain information on survival and movement of fish with fewer tags. The trade-off, though, is a greater dependence on the individual tag performance, as each tagged fish in a smaller study represents a greater proportion of the outcome. This reduction in release size, due to the increase in detection capability, places a greater emphasis on the need to accurately gauge the status of the tagged fish. Should a tag fail while a smolt is migrating through the study area, the release-recapture model cannot discern the difference between smolt death and tag failure. If the release-recapture models are not adjusted for the probability of tag failure, the estimates of smolt survival will therefore be negatively biased. This article presents a semiparametric approach for adjusting survival estimates from release-recapture studies for tag failure, and provides subsequent estimation of sampling variance and its contributing components.

Good information is invaluable for decision-making. With the explosion of computational power and digital data storage technologies, and more recently the huge increase in mobile communications devices, vast quantities of data are becoming available. But these data are unwieldy. Where data was once scarce, hard to gather, and therefore had to be subject to the very careful analytical processes familiar from mathematical statistics and probability theory, now data come in overwhelming quantity (Volume), at high speeds (velocity), and in many different forms (variety). The challenges and opportunities in Big Data arise from the attempt to use data effectively when it is available in massive Volume, at high Velocity, and in great Variety. This book brings together a number of works that explore a range of significant issues related to Big Data. At one end of the range is concern for gathering data, as seen in the chapter on web scraping, to issues in processing data, as seen in the chapter on national statistical institutes, to concerns for using and analysing data, as seen in several chapters related to teaching with Big Data.

Measurements made on pasture plots in field evaluation studies are affected by the spatial heterogeneity of the field due to local influences of paddock history, moisture drying order and fertility gradients. Statistical models to account for these inherent and ephemeral effects can markedly enhance the accuracy of comparisons among test lines or treatments so that interpretation of the results is objective, accurate and reliable. This paper reports on statistical methods for the field evaluation of white clover breeding lines in the development of locally adapted white clover cultivars for New South Wales dry-land pastures.

We investigate the potential for biosecurity regulators to design inspection regimes that reduce intervention and encourage importers to decrease the likelihood of biosecurity risk material being present in consignments. The interaction between a biosecurity regulator and a vertically integrated importer is framed as an inspection game. Our principal focus is a dynamic version of the game, which we use to assess whether regimes based on past compliance can encourage behaviours consistent with the regulatory objective. Our results suggest appropriate candidates for compliance-based inspection regimes are goods where there is access to cost-effective 'fixed' abatement technologies, and those with high costs associated with being inspected or failing inspection.

There is an increasing trend towards integrated research, in which several individuals or institutions pool their expertise and make use of common resources, collaborating towards a common set of scientific goals. Integrated research enables a larger number of factors to be investigated, and the most influential or important ones identified, providing information on how the different factors interact or fit together. Good experimental design is, however, required to ensure the aims can be achieved and resources spent wisely. Issues involved in the experimental design of the Australian Beef Cattle Cooperative Research Centre for Meat Quality are discussed. Theoretical results and simulation studies were used to determine optimal numbers of progeny per sire for estimating genetic parameters. For heritabilities of 0.2 and 0.5, the optima are respectively 21 and 9 progeny with recorded measurements. The curves surrounding the optima are quite flat, so aiming for 10-15 progeny with measurements per trait should provide reasonable accuracy in many situations. Estimates of heritabilities, genetic correlations and phenotypic variances have lower sampling correlations than genetic variances and covariances, suggesting that when results are pooled over different breeds or trials, it is better to pool estimates of heritabilities and genetic correlations than (co)variances. Using sires in more than one year increases the robustness of estimated sire effects and increases the accuracy of genetic parameter estimates for hard-to-measure traits (e.g. feed efficiency) that are not recorded on all animals. Unless sires can be chosen as a true random sample of the population, arrangements of link sires (and other effects such as treatments) should be chosen to provide accurate estimates when all terms in the model are fitted as fixed.

Very little is known about the cardiometabolic risk of migrants who settle in Australia. This study investigated differences in cardiometabolic risk markers among ethnic groups attending a tailored healthy lifestyle program in Queensland, Australia; and differences in these markers between those living in Australia for shorter versus longer periods of time. Baseline data collected between October 2014 and June 2017 from the Living Well Multicultural—Lifestyle Modification Program were used. People living in ethnic communities in Queensland who were ≥18 years old, and not underweight were eligible to participate. Independent variables were ethnicity and length of time in Australia. Outcomes were cardiometabolic risk markers including BMI, waist circumference, weight‐to‐height ratio (WHtR) and hypertension. Analyses were done separately for each independent variable. Linear and logistic regressions were run for continuous and binary outcomes with differences/Odds ratios reported respectively. Multivariable analyses showed that Burmese/Vietnamese had an average BMI lower than Afghani/Arabic (3.7 points), Somalian/Sudanese (4.7 points) and Pacific Islander (11.6 points) (p < 0.001) respectively. Differences in waist circumference between Burmese/Vietnamese with Sri Lankan/Bhutanese, Afghani/Arabic, Somalian/Sudanese and Pacific Islander were 6.3, 8.4, 9.1 and 24.0 cm (p < 0.01) respectively. Although Burmese/Vietnamese also had lower average WHtR compared to the others, the differences were not significant for Somalian/Sudanese. Moreover, Sri Lankan/Bhutanese and Pacific Islander were more likely to be hypertensive compared to Burmese/Vietnamese (p < 0.05). Immigrants living in Australia >5years had on average 1.2 points higher BMI, 2.4cm larger waist circumference, and 0.02 points higher WHtR (p < 0.05) compared to those living for ≤5 years. Long‐stay immigrants were also more likely to be hypertensive than short‐stay immigrants (p < 0.01). In conclusion, cardiometabolic risk is significantly different among ethnic groups in Queensland with Pacific Islanders having the highest risk. Immigrants living in Australia >5 years had higher risks compared to those living in Australia for shorter periods of time.

To address growing concern over the effects of fisheries non-target catch on elasmobranchs worldwide, the accurate reporting of elasmobranch catch is essential. This requires data on a combination of measures, including reported landings, retained and discarded non-target catch, and post-discard survival. Identification of the factors influencing discard versus retention is needed to improve catch estimates and to determine wasteful fishing practices. To do this, retention rates of elasmobranch non-target catch in a broad subset of fisheries throughout the world were compared by taxon, fishing country, and gear. A regression tree and random forest analysis indicated that taxon was the most important determinant of retention in this dataset, but all three factors together explained 59% of the variance. Estimates of total elasmobranch removals were calculated by dividing the Food and Agriculture Organization of the United Nations (FAO) global elasmobranch landings by average retention rates, and suggest that total elasmobranch removals may exceed FAO reported landings by as much as 400%. This analysis is the first effort to directly characterize global drivers of discards for elasmobranch non-target catch. The results highlight the importance of accurate quantification of retention and discard rates to improve assessments of the potential impacts of fisheries on these species.

Collective animal behavior is an emergent phenomenon arising from the local interactions of the members of animal groups. Considerable progress has been made in characterizing these interactions, particularly inferring rules that shape and guide the responses of animals to their near neighbors. To date, experimental work has focused on collective behavior within a single, stable context. We examine the individual and collective behavior of a schooling fish species, the x-ray tetra (Pristella maxillaris), identifying their response to changes in context produced by food cues or conspecific alarm cues. Fish exposed to alarm cues show pronounced, broad-ranging changes of behavior, including reducing speed and predictability in their movements. Alarmed fish also alter their responses to other group members, including enacting a smaller zone of repulsion and increasing their frequency of observation of, and responsiveness to, near neighbors. Fish subject to food cues increased speed as a function of neighbor positions and reduced encounter frequency with near neighbors. Overall, changes in individual behavior and the interactions among individuals in response to external cues coincide with changes in group-level patterns, providing insight into the adaptability of behavior to changes in context and interrelationship between local interactions and global patterns in collective behavior.

Many bird species are subject to human-caused mortality, either through direct harvest (e.g. game birds) or through incidental mortalities (e.g. fisheries-related bycatch of seabirds, impact with vehicles, wind turbines, or power lines). In order to assess the impact of additional mortalities on birds, both the number of birds killed and their ability to sustain those deaths must be estimated. Niel and Lebreton [Niel, C., Lebreton, J.-D., 2005. Using demographic invariants to detect overharvested bird populations from incomplete data. Conservation Biology 19, 826-835] applied a simple decision rule [Wade, P.R., 1998. Calculating limits to the allowable human-caused mortality of cetaceans and pinnipeds. Marine Mammal Science 14, 1-37] to estimate the level of additional human-caused mortality or potential biological removal (PBR) that can be sustained for bird species given only (1) estimates of the population size, adult survival, and age at first breeding, and (2) the current population status and management goals. We provide guidelines for appropriate use of the method and case studies comparing results from this method to other approaches. Particular focus is placed on applying the method to Procellariiformes. PBR limits may then be set without a population model and when monitoring levels are minimal, and in a computationally straightforward manner. While this approach has many advantages, there are limitations. The PBR rule was initially developed for cetaceans and pinnipeds and there have been no adaptations for the unique biology of birds which may need further consideration. Additionally, because this is a simplifying method that ignores differences in life stages, it may not be appropriate for very small populations or for those listed as 'critically endangered', and further work is needed for situations where mortalities have large gender or age bias.

Fisheries bycatch threatens populations of marine megafauna such as marine mammals, turtles, seabirds, sharks and rays, but fisheries impacts on non-target populations are often difficult to assess due to factors such as data limitation, poorly defined management objectives and lack of quantitative bycatch reduction targets. Limit reference points can be used to address these issues and thereby facilitate adoption and implementation of mitigation efforts. Reference points based on catch data and life history analysis can identify sustainability limits for bycatch with respect to defined population goals even when data are quite limited. This can expedite assessments for large numbers of species and enable prioritization of management actions based on mitigation urgency and efficacy. This paper reviews limit reference point estimators for marine megafauna bycatch, with the aim of highlighting their utility in fisheries management and promoting best practices for use. Different estimators share a common basic structure that can be flexibly applied to different contexts depending on species life history and available data types. Information on demographic vital rates and abundance is required; of these, abundance is the most data-dependent and thus most limiting factor for application. There are different approaches for handling management risk stemming from uncertainty in reference point and bycatch estimates. Risk tolerance can be incorporated explicitly into the reference point estimator itself, or probability distributions may be used to describe uncertainties in bycatch and reference point estimates, and risk tolerance may guide how those are factored into the management process. Either approach requires simulation-based performance testing such as management strategy evaluation to ensure that management objectives can be achieved. Factoring potential sources of bias into such evaluations is critical. This paper reviews the technical, operational, and political challenges to widespread application of reference points for management of marine megafauna bycatch, while emphasizing the importance of developing assessment frameworks that can facilitate sustainable fishing practices.

There is a trend towards integrated research, where experimenters aim to make the best possible use of available resources, and individuals or institutions pool their expertise, make use of common resources and collaborate towards a common set of scientific goals. This allows a larger number of factors to be investigated, enabling the most influential or important ones to be identified as well as providing information on how the different factors interact or fit together. The issues involved in generating complex multi-factor designs are described and discussed, using as examples the entire series of experiments in the Australian Beef Cattle CRC and a simpler experiment to estimate genetic marker effects. An algorithm to generate suitable designs is presented. For the genetic marker experiment, the resultant designs were up to 10% more efficient than less sophisticated designs. In the case of the Beef Cattle CRC, achieving the same accuracy of estimating treatment and sire effects without sophisticated designs would have required 5-10% more animals, at a cost of $150,000-300,000 for purchase, transport and feeding of animals. If all additional costs of experimentation were included, the total savings from use of efficient designs were estimated to lie between $0.5 and $1 million.

Fine-scale geographic interactions between Steller sea lion ('Eumetopias jubatus') abundance trends and the abundance of local fisheries and commercial fishing efforts from Southeast Alaska to the Aleutian Islands were assessed. Census counts of Steller sea lions from 1976 to 2002 at 53 different trend sites and rookeries were grouped into 33 locales with similar population trends. Localized estimates of commercial groundfish biomass densities for walleye pollock ('Theragra chalcogramma'), Pacific cod ('Gadus macrocephalus'), arrowtooth flounder ('Atheresthes stomias'), and Atka mackerel ('Pleurogrammus monopterygius') from 1983 to 2002 and localized estimates of commercial fishing effort from 1990 to 2002 were matched to the 33 locales. Generalized estimating equations methods found a negative relationship between Steller sea lion abundance trends and walleye pollock density (P < 0.10). However, the 4.8-fold change in walleye pollock density between 1984 and 2001 was estimated to change the rate of population change (λ) by only 0.029. The analysis estimated that elimination of all trawl fishing effort would increase λ by as little as 0.0056. Neither commercial groundfish abundance nor commercial fishing effort could explain the large historical declines in the rate of Steller sea lion population change observed.

1. An important problem encountered by ecologists in species distribution modelling (SDM) and in multivariate analysis is that of understanding why environmental responses differ across species, and how differences are mediated by functional traits. 2. We describe a simple, generic approach to this problem - the core idea being to fit a predictive model for species abundance (or presence/absence) as a function of environmental variables, species traits and their interaction. 3. We show that this method can be understood as a model-based approach to the fourth-corner problem - the problem of studying the environment-trait association using matrices of abundance or presence/absence data across species, environmental data across sites and trait data across species. The matrix of environment-trait interaction coefficients is the fourth corner. 4. We illustrate that compared with existing approaches to the fourth-corner problem, the proposed model-based approach has advantages in interpretability and its capacity to perform model selection and make predictions. 5. To illustrate the method we used a generalized linear model with a LASSO penalty, fitted to data sets from four different studies requiring different models, illustrating the flexibility of the proposed approach. 6. Predictive performance of the model is compared with that of fitting SDMs separately to each species, and in each case, it is shown that the trait model, despite being much simpler, had comparable predictive performance, even significantly outperforming separate SDMs in some cases.

In age-classified population models where all parameters are known, the generation time and growth rate are calculated in a straightforward manner. For many populations, some parameters, such as juvenile survival, are difficult to estimate accurately. In a simplified population model where fecundity and survival are constant from the onset of breeding, it is known that generation time may be calculated given only adult survival, age at first reproduction, and the population growth rate. However, the assumption of constant fecundity from the onset of breeding does not hold for many populations. An extended population model allows calculation of generation time with the additional knowledge of the ratio of age-specific fecundities compared to a maximum fecundity rate. When these relative fecundities are unknown, an ad hoc adjustment to the simplified model performs well. When the study population is in an ideal environment, the optimal generation time and maximum growth rate are linked, and both may be approximated knowing only adult survival, age at first reproduction, and the relative fecundities. The maximum growth rate has important conservation implications, and calculating it correctly is therefore important. Improper use of the simplified population model to calculate the maximum growth rate, combined with a simple decision rule, leads to an average overharvest of 36%, and >60% for three of six bird species studied, compared to the full population model. By comparison, using the approximation from the extended or adjusted models results in average overharvests of only 8% (extended model) and 5% (adjusted model), and <50% for all six species (either model).

The provenance or origin of a soil sample is of interest in soil forensics, archaeology, and biosecurity. In all of these fields, highly specialized and often expensive analysis is usually combined with expert interpretation to estimate sample origin. In this proof of concept study we apply rapid and non-destructive spectral analysis to the question of direct soil provenancing. This approach is based on one of the underlying tenets of soil science - that soil pedogenesis is spatially unique, and thus digital spectral signatures of soil can be related directly, rather than via individual soil properties, to a georeferenced location. We examine three different multivariate regression techniques to predict GPS coordinates in two nested datasets. With a minimum of data processing, we show that in most instances Eastings and Northings can be predicted to within 20% of the range of each within the dataset using the spectral signatures produced via portable x-ray fluorescence. We also generate 50 and 95% confidence intervals of prediction and express these as a range of GPS coordinates. This approach has promise for future application in soil and environmental provenancing.

A breeding project has developed a new synthetic white clover ('Trifolium repens L.') cultivar, Grasslands Trophy, that possesses tolerance of summer moisture stress in dryland pasture environments in the 850-1250 mm average annual rainfall temperate perennial pasture zone in eastern Australia. The breeding strategy used to develop Grasslands Trophy was an 'in situ' breeding cycle for: (i) identifying and selecting superior genotypes, (ii) crossing elite germplasm and (iii) progeny testing derived breeding lines for the expression of key agronomic and grazing value traits. The primary selection criteria were early vigour, herbage yield, persistence and seed yield potential. Parental selection was also applied for seed yield, uniformity of leaf size, uniform flowering pattern and freedom from disease and virus symptoms. Grasslands Trophy is medium-large in leaf size with stable leaf size, combines intermediate stolon density with intermediate stolon thickness, and expresses high stolon survival and strong autumn regrowth following summer moisture stress. Grasslands Trophy has mid-season flowering maturity, intensive flowering prolificacy and high seed yield capability. Agronomic results from trials in northern New South Wales and New Zealand indicate that Grasslands Trophy has broad adaptation, expresses high summer and winter growth activity, and is reliably persistent for at least 4 years.

Unfortunately most of Australia's flying-foxes are listed as vulnerable, largely due to habitat loss and colony destruction. Both of these lead to increased interaction with humans and, inevitably, result in injuries. Specific causes of injuries vary with the location and the time of year, however in Sydney alone, some typical per annum figures for the Grey-headed Flying-fox 'Pteropus poliocephalus' (GHFF) are: • power line 17% (78% fatal); • miscellaneous physical injury 17%; • net caught 17% (in country areas this is by barbed wire instead); • less than half are released and a quarter are euthanised.

The purpose of this book is to focus on a wide range of concepts and procedures which are available for analysing quantitative research data. These concepts and procedures are collectively considered to constitute the domain of statistics. It is an inescapable fact that in order to either read or conduct good business, behavioural and social science research, you must become acquainted with how such data are analysed. • Quantitative data necessarily require the application of specific statistical formulas, analytical sequences and computations which transform and condense raw numerical data (e.g. people's marks on a survey questionnaire or readings from an instrument) into forms that can be interpreted as telling particular stories or as supporting or not supporting a particular research question, hypothesis or prediction. • Qualitative data on the other hand, confront the researcher in non-numerical (often textual) form and this necessitates quite different analytical approaches to extracting meaning from the data and generating appropriate interpretations. However, in some circumstances, it may be appropriate to transform qualitative data into quantitative form, which means that there may be instances where qualitative research data can be usefully analysed using quantitative methods. This book should prove very useful to the reader in either case.

Intrinsic population growth rate (r max) is an important parameter for many ecological applications, such as population risk assessment and harvest management. However, r max can be a diffi cult parameter to estimate, particularly for long-lived species, for which appropriate life table data or abundance time series are typically not obtainable. We describe a method for improving estimates of r max for long-lived species by integrating life-history theory (allometric models) and population-specific demographic data (life table models). Broad allometric relationships, such as those between life history traits and body size, have long been recognized by ecologists. These relationships are useful for deriving theoretical expectations for r max , but r max for real populations may vary from simple allometric estimators for "archetypical" species of a given taxa or body mass. Meanwhile, life table approaches can provide population-specific estimates of r max from empirical data, but these may have poor precision from imprecise and missing vital rate parameter estimates. Our method borrows strength from both approaches to provide estimates that are consistent with both life-history theory and population-specific empirical data, and are likely to be more robust than estimates provided by either method alone. Our method uses an allometric constant: the product of r max and the associated generation time for a stable-age population growing at this rate. We conducted a meta-analysis to estimate the mean and variance of this allometric constant across well-studied populations from three vertebrate taxa (birds, mammals, and elasmobranchs) and found that the mean was approximately 1.0 for each taxon. We used these as informative Bayesian priors that determine how much to "shrink" imprecise vital rate estimates for a data-limited population toward the allometric expectation. The approach ultimately provides estimates of r max (and other vital rates) that reflect a balance of information from the individual studied population, theoretical expectation, and meta-analysis of other populations. We applied the method specifically to an archetypical petrel (representing the genus 'Procellaria') and to white sharks ('Carcharodon carcharias') in the context of estimating sustainable fishery bycatch limits.

This report considers how the department can use microeconomic theory, including the theory of incentive and information economics, to design intervention protocols that encourage participants to reduce the likelihood of biosecurity risk material entering Australia.
Changes to the rules of the biosecurity “game” may induce changes in behaviour from import-supply chain participants. Some rules might lead participants to take actions that potentially undermine the Australian Government’s biosecurity objective; other rules may lead participants to take actions that are beneficial to the national biosecurity objective. Economics provides a framework to test which policy settings (including rules, incentive structures, monitoring practices etc.) align the actions of import-supply chain participants with the objectives of government.
The project employed three strategies to inform the design of compliance-based inspection protocols to improve the alignment between government biosecurity objectives and the commercial objectives of import-supply chain participants, namely:
i. use of administrative data;
ii. interviews with relevant biosecurity stakeholders; and
iii. insights from economic theory.

The Internet is an example of a general physical problem dealing with motion near the speed of light relative to different time frames of reference. The second order differential equation (DE) takes the form of 'time diffusion' near the speed of light or alternatively, considered as a complex variable with real time and imaginary longitudinal components. Congestion waves are generated by peak global traffic from different time zones following the Earth's revolution defined by spherical harmonics and a day/night bias. The DE is essentially divided into space and time operators constrained by the speed of light c, band capacity w and a fractal dimension Z (Hausdorff dimension). This paper explores the relationship between the dynamics and the network including the addition of fractal derivatives to the DE for regional networks for 0 < Z < 1.

Dizziness and or unsteadiness, associated with episodes of loss of balance, are frequent complaints in those suffering from persistentproblems following a whiplash injury. Research has been inconclusive with respect to possible aetiology, discriminative tests and analysesused. The aim of this pilot research was to identify the test conditions and the most appropriate method for the analysis of sway that may differentiate subjects with persistent whiplash associated disorders (WAD) from healthy controls. The six conditions of the Clinical Test for Sensory Interaction in Balance was performed in both comfortable and tandem stance in 20 subjects with persistent WAD compared to 20 control subjects. The analyses were carried out using a traditional method of measurement, total sway distance, to results obtained from the use of wavelet analysis. Subjects withWAD were significantly less able to complete the tandem stance tests on a firm surface than controls. In comfortable stance, using wavelet analysis, significant differences between subjects withWAD and the control group were evident in total energy of the trace for all test conditions apart from eyes open on the firm surface. In contrast, the results of the analysis using total sway distance revealed no significant differences between groups across all six conditions. Wavelet analysis may be more appropriate for detecting disturbances inbalance in whiplash subjects because the technique allows separation of the noise from the underlying systematic effect of sway. Thesefindings will be used to direct future studies on the aeitiology of balance disturbances in WAD.

Learning management systems (LMS) are a necessary and important tool and well suited as a learning tool and activity in higher educational. Thus, the authors allege that most of the universities these days are using the LMS tools in their institute. However, each institute has different LMS tools that allow the users (management, instructors, and students) to use them for daily activity. This chapter discusses the main usefulness tools (Moodie, Blackboard, WebCT, and Sakai) and the most useful data analysis approaches (CB-SEM, PLS, GSCA, and NEUSREL) in order to clarify the advantages and disadvantages for each of them, which gives an easier decision for managements and researchers to choose the suitable LMS tool and data analysis approach for their institute and research.

Analysis of published experimental data on monomeric radical diffusion in the emulsion polymerisation of styrene shows that it can be quantitatively described equally well by non-equilibrium diffusion from particles, where all parameters are derived from properties of the discrete phase, or by steady-state diffusion where all parameters are derived from properties of the continuous phase. The non-equilibrium model better describes an observed experimental trend to a reduced desorption rate coefficient at higher weight fraction of polymer in the particles. The theoretical upper bound of the non-equilibrium model is also higher than the theoretical upper bound of the steady-state model allowing fits to experimental data which must be discarded as anomalous in the continuous phase model.

We consider the coverage rate of model-averaged confidence intervals for the treatment means in a factorial experiment, when we use a normal linear model in the analysis. Model-averaging provides a useful compromise between using the full model (containing all main effects and interactions) and a "best model" obtained by some model-selection process. Use of the full model guarantees perfect coverage, whereas use of a best model is known to lead to narrow intervals with poor coverage. Model-averaging allows us to achieve good coverage using intervals that are also narrower than those from the full model. We compare four information criteria that might be used for model-averaging in this setting: AIC, AICc , AIC*c and BIC. In this setting, if the full model is 'truth', all the criteria will have perfect coverage rates asymptotically. We use simulation to assess the coverage rates and interval widths likely to be achieved by a confidence interval with a nominal coverage of 95%. Our results suggest that AIC performs best in terms of coverage rate; across a wide range of scenarios and replication levels, it consistently provides coverage rates within 1.5% points of the nominal level, while also leading to reductions in interval-width of up to 30%, compared to the full model. AICc performed worst overall, with a coverage rate that was up to 5.2% points too low. We recommend that model-averaging become standard practise when summarising the results of a factorial experiment in terms of the treatment means, and that AIC be used to perform the model-averaging.

The main aim of this report is to assess the potential impact of fisheries on four New Zealand seabird species: Antipodean and Gibson's wandering albatross ('Diomedea antipodensis antipodensis' and 'Diomedea antipodensis gibsoni'); Black petrels ('Procellaria parkinsoni') and Southern royal albatross ('Diomedea epomophora'). In doing so, we review possible modelling approaches, the data available and the potential impact of other factors (particularly climate).

With the increased development of low-cost and miniature devices, sensors are increasingly being deployed as arrays of redundant sensors. However, little work has been done characterizing properties of these arrays. Here, we develop and test a Bayesian algorithm for estimating the limit of detection of sensor arrays. The algorithm is applicable for single sensors as well as sensor arrays, and works by reducing a vector in the signal domain to a univariate response in the measurand domain. We show that the new algorithm can reproduce results from a benchmark algorithm for single sensors, and then demonstrate the benefit of adding additional sensors to an array. Then, we provide guidelines that achieve numerical stability while minimising computational cost. Finally, we provide a real-world example using an array of ion-selective electrodes measuring carbonate in seawater. This application demonstrates how incorporation of a set of individual low-quality sensors into an array leads to a substantially reduced LOD that clearly meets the demands of the application.