No outbreeding depression at a regional scale for a habitat-forming intertidal alga with limited dispersal

Hormosira banksii is distributed throughout southern Australasia, but dispersal of propagules is thought to be limited. In the present study, the hypothesis that outbreeding depression occurs in H. banksii was tested by assessing fertilisation success and early development of embryos in crosses between populations at local to regional spatial scales. Hierarchical experiments were conducted at three spatial scales with nesting present within each scale: small scale (within a rocky shore population), intermediate scale (regions separated by 70 km) and large scale (450-km separation between two states: Victoria and Tasmania). In each experiment, eggs and sperm were crossed within and between each population located in the spatial scale of interest. There were no consistent patterns of variable fertilisation success and subsequent development within a population or at different spatial scales. It was concluded that outbreeding depression is not detected in analyses of fertilisation success or early development processes in H. banksii. The results suggest one of the following to be likely: (1) H. banksii is capable of longer distance dispersal than previously considered, thus maintaining gene flow between distant populations, (2) gene flow is restricted by limited dispersal, but populations have not been isolated for a sufficient length of time to cause genetic divergence or (3) outbreeding depression is manifested as effects on later life-history stages.

Distribution and habitat requirements of the Yellow-Footed Antechinus Antechinus flavipes at multiple scales: a review

This review synthesises present knowledge of the distribution patterns and habitat requirements of the Yellow-footed Antechinus Antechinus flavipes. Factors influencing the distribution of A. flavipes are examined at several spatial scales ranging from the broad climatic conditions prevalent over the species’ entire range to the characteristics of nest sites used by individual animals. Analysis of the literature suggests that: 1) at the broad-scale, A. flavipes distribution is largely determined by warm, dry climatic conditions, the distribution of dry forests and woodlands and competition with closely related species; 2) at the landscape-scale the determinants of A. flavipes distribution are largely unknown, although initial investigations suggest some tolerance of fragmented landscapes; and 3) at a local-scale the distribution of A. flavipes is largely determined by the presence of large diameter trees, tree hollows, coarse woody debris, rocky crevices and leaf-litter. Directions for future research are suggested throughout the review.

Estimating population size of the black-eared miner, with an assessment of landscape-scale habitat requirements

The decline of the Black-eared Miner Manorina melanotis has been caused primarily by habitat degradation and vegetation clearance. To better direct conservation actions for this species there was a need to assess habitat requirements on a regional-scale and to estimate the population size using quantitative methods. We used vegetation mapping and the current distribution of the Black-eared Miner to determine regional-scale habitat requirements. These findings were combined with the results of distance sampling to provide population estimates. The species is restricted to large tracts of intact mallee in the Murray Mallee of southeastern Australia that have not been burnt for at least 45 years. The density· of Black-eared Miners is highest in areas that are dominated by mallee- Triodia associations and have not been intensively grazed. The Bookmark Biosphere Reserve supports an estimated 501 (270-927, 95% CI) colonies, containing 3758 (2026-6954) phenotypically pure Black-eared Miners, 2255 (1 215-4170) hybrids and small numbers of Yellow-throated Miners Manorina flavigula. However, the effective population size is considerably smaller (390 Black-eared Miners '(21 0-726) and 234 hybrids (126-433)), due to a skewed adult sex ratio (1 female: 1.81 males) and complex social organization. A smaller population also persists in the Murray Sunset National Park containing 53 (32-85) Black-eared Miner/hybrid colonies. Both populations face a high risk of extinction from large-scale wildfire. The endangered status of the species under IUCN criteria remains warranted.

Habitat manipulation and rodent damage control: reducing rodent damage in Australian macadamia orchards

This paper examines the relationship between adjacent non-crop vegetation and rodent (Rattus rattus) damage in Australian macadamia (Macadamia integrifolia) orchard systems. Orchards adjacent to structurally diverse, non-crop vegetation dominated by woody weeds exhibited significantly higher damage when compared to orchards adjacent to managed grasslands. This relationship formed the basis for a rodent damage reduction strategy utilising habitat manipulation. Structurally diverse, non-crop habitats were modified to grasslands leading to a reduction in rodent damage of 65%. This strategy was cost-effective and has the potential to be long-term with minimal effort needed to maintain sites in a modified state. Habitat manipulation is a process whereby the resource load in a system is reduced and hence rodent densities cannot reach levels where they cause significant crop damage. This paper provides empirical evidence to support habitat manipulation as a practical, cost-effective control strategy for rodent pests.

Filtering mobile spam by support vector machine

Currently mobile spam has been a major menace to the development of wireless networks. In this paper, the mobile spam problem and its countermeasures are analysed. In particular, we propose a Support Vector Machine to filter mobile spam. This mobile spam filtering system can be deployed in current wireless networks and achieve good performance in protecting end users and operators from mobile spam. Legislation issues and challenges to defend mobile spam are also discussed in the latter part of this paper.

Mark-aided distributed filtering by using neural network for DDoS defense

Currently Distributed Denial of Service (DDoS) attacks have been identified as one of the most serious problems on the Internet. The aim of DDoS attacks is to prevent legitimate users from accessing desired resources, such as network bandwidth. Hence the immediate task of DDoS defense is to provide as much resources as possible to legitimate users when there is an attack. Unfortunately most current defense approaches can not efficiently detect and filter out attack traffic. Our approach is to find the network anomalies by using neural network, deploy the system at distributed routers, identify the attack packets, and then filter them. The marks in the IP header that are generated by a group of IP traceback schemes, Deterministic Packet Marking (DPM)/Flexible Deterministic Packet Marking (FDPM), assist this process of identifying attack packets. The experimental results show that this approach can be used to defend against both intensive and subtle DDoS attacks, and can catch DDoS attacks’ characteristic of starting from multiple sources to a single victim. According to results, we find the marks in IP headers can enhance the sensitivity and accuracy of detection, thus improve the legitimate traffic throughput and reduce attack traffic throughput. Therefore, it can perform well in filtering DDoS attack traffic precisely and effectively.

Spam filtering using ML algorithms

Spam is commonly defined as unsolicited email messages, and the goal of spam categorization is to distinguish between spam and legitimate email messages. Spam used to be considered a mere nuisance, but due to the abundant amounts of spam being sent today, it has progressed from being a nuisance to becoming a major problem. Spam filtering is able to control the problem in a variety of ways. Many researches in spam filtering has been centred on the more sophisticated classifier-related issues. Currently,  machine learning for spam classification is an important research issue at present. Support Vector Machines (SVMs) are a new learning method and achieve substantial improvements over the currently preferred methods, and behave robustly whilst tackling a variety of different learning tasks. Due to its high dimensional input, fewer irrelevant features and high accuracy, the  SVMs are more important to researchers for categorizing spam. This paper explores and identifies the use of different learning algorithms for classifying spam and legitimate messages from e-mail. A comparative analysis among the filtering techniques has also been presented in this paper.

Spam filtering based on preference ranking

When the average number of spam messages received is continually increasing exponentially, both the Internet service provider and the end user suffer. The lack of an efficient solution may threaten the usability of the email as a communication means. In this paper we present a filtering mechanism applying the idea of preference ranking. This filtering mechanism will distinguish spam emails from other email on the Internet. The preference ranking gives the similarity values for nominated emails and spam emails specified by users, so that the ISP/end users can deal with spam emails at filtering points. We designed three filtering points to classify nominated emails into spam email, unsure email and legitimate email. This filtering mechanism can be applied on both middleware and at the client-side. The experiments show that high precision, recall and TCR (total cost ratio) of spam emails can be predicted for the preference based filtering mechanisms.

An innovative spam filtering model based on support vector machine

Spam is commonly defined as unsolicited email messages and the goal of spam categorization is to distinguish between spam and legitimate email messages. Many researchers have been trying to separate spam from legitimate emails using machine learning algorithms based on statistical learning methods. In this paper, an innovative and intelligent spam filtering model has been proposed based on support vector machine (SVM). This model combines both linear and nonlinear SVM techniques where linear SVM performs better for text based spam classification that share similar characteristics. The proposed model considers both text and image based email messages for classification by selecting an appropriate kernel function for information transformation.

Robust parallel filtering for mobile agent tracking

In this paper we develop a robust method of target/mobile agent tracking involving two independent estimators with separate measurement systems. The outputs of the two estimators are combined using simple trigonometry (post-estimation data fusion) and provide a robust and reliable tracking path. We demonstrate that through the use of recent advances in robust set-value state estimation, our robust parallel filter approach performs well even when the individual filters do not. Brief comparisons with common data fusion methods are conducted in order to demonstrate the advantages of our parallel (post-estimation fusion) approach

Robust parallel filtering design of a swarm tracking system

Swarming networks of mobile autonomous agents require inter-agent position information in order perform various tasks. The primary control input for the majority of current control strategies is inter-agent distance information. In this paper we provide a robust parallel filter based tracking scheme that allows a mobile agent to track other multiple mobile agents. The distance, angle, and relative position is given in a direct target tracking output. This allows the mobile agent to decide which information is best suited for the particular objective

Paleobiogeographical extinction patterns of Permian brachiopods in the Asian-western Pacific region

Spatial and temporal variations in biological diversity are critical in understanding the role of biogeographical regulation (if any) on mass extinctions. An analysis based on a latest database of the stratigraphic ranges of 89 Permian brachiopod families, 422 genera, and 2059 species within the Boreal, Paleoequatorial, and Gondwanan Realms in the Asian–western Pacific region suggests two discrete mass extinctions, each possibly with different causes. Using species/family rarefaction analysis, we constructed diversity curves for late Artinskian–Kungurian, Roadian–Wordian, Capitanian, and Wuchiapingian intervals for filtering out uneven sampling intensities. The end-Changhsingian (latest Permian) extinction eliminated 87–90% of genera and 94–96% of species of Brachiopoda. The timing of the end-Changhsingian extinction of brachiopods in the carbonate settings of South China and southern Tibet indicates that brachiopods suffered a rapid extinction within a short interval just below the Permian/Triassic boundary.

In comparison, the end-Guadalupian/late Guadalupian extinction is less profound and varies temporally in different realms. Brachiopods in the western Pacific sector of the Boreal Realm nearly disappeared by the end-Guadalupian but experienced a relatively long-term press extinction spanning the entire Guadalupian in the Gondwanan Realm. The end-Guadalupian brachiopod diversity fall is not well reflected at the timescale used here in the Paleoequatorial Realm because the life-depleted early Wuchiapingian was overlapped by a rapid radiation phase in the late Wuchiapingian. The Guadalupian fall appears to be related to the dramatic reduction of habitat area for the brachiopods, which itself is associated with the withdrawal of seawater from continental Pangea and the closure of the Sino-Mongolian seaway by the and-Guadalupian.

Agricultural intensification and loss of matrix habitat over 23 years in the West Wimmera, south-eastern Australia

The global trend toward more intensive forms of agriculture is changing the nature of matrix habitat in agricultural areas. Removal of components of matrix habitat can affect native biota at the paddock and the landscape scale, particularly where intensification occurs over large areas. We identify the loss of paddock trees due to the proliferation of centre pivot irrigation in dryland farming areas as a potentially serious threat to the remnant biota of these areas. We used a region of south-eastern Australia as a case study to quantify land use change from grazing and dryland cropping to centre pivot irrigation over a 23-year period. We also estimated rates of paddock tree loss in 5 representative landscapes within the region over the same period. The total area affected by centre pivots increased from 0 ha in 1980 to nearly 9000 ha by 2005. Pivots were more likely to be established in areas which had originally been plains savannah and woodlands containing buloke (Allocasuarina luehmannii), a food source for an endangered bird. On average, 42% of paddock buloke trees present in 1982 were lost by 2005. In the two landscapes containing several centre pivots, the loss was 54% and 70%. This accelerated loss of important components of matrix habitat is likely to result in species declines and local extinctions. We recommend that measures to alleviate the likely negative impacts of matrix habitat loss on native biota be considered as part of regional planning strategies.

Marine benthic habitat mapping using multibeam data, georeferenced video and image classification techniques in Victoria, Australia

This paper contributes to a better understanding of geophysical characteristics and benthic communities in the Hopkins site in Victoria, Australia. An automated decision tree classification system was used to classify substrata and dominant biota communities. Geophysical sampling and underwater video data collected in this study reveals a complex bathymetry and biological structure which complements the limited information of benthic marine ecosystems in coastal waters of Victoria. The technique of combining derivative products from the backscatter and the bathymetry datasets was found to improve separability for broad biota and substrata categories over the use of either of these datasets alone.