Australia’s savanna herbivores : bioclimatic distributions and an assessment of the potential impact of regional climate change

The future impacts of climate change are predicted to significantly affect the survival of many species. Recent studies indicate that even species that are relatively mobile and/or have large geographic ranges may be at risk of range contractions or extinction. An ecologically and evolutionary significant group of mammals that has been largely overlooked in this research is Australia’s large marsupial herbivores, the macropodids (kangaroos). The aims of our investigation were to define and compare the climatic conditions that influence the current distributions of four sympatric large macropodids in northern Australia (Macropus antilopinus, Macropus robustus, Macropus giganteus, and Macropus rufus) and to predict the potential future impact of climate change on these species. Our results suggest that contemporary distributions of these large macropodids are associated with well‐defined climatic gradients (tropical and temperate conditions) and that climatic seasonality is also important. Bioclimatic modeling predicted an average reduction in northern Australian macropodid distributions of in response to increases of 2.0°C. At this temperature, the distribution of M. antilopinus was reduced by . We predict that increases of 6.0°C may cause severe range reductions for all four macropodids ( ) in northern Australia, and this range reduction may result in the extinction of M. antilopinus.

Assessment of spatiotemporal varying relationships between rainfall, land cover and surface water area using geographically weighted regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R 2 and lower corrected Akaike information criterion (AICC). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R 2 and lower AICC. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.

Induced ordered weighted averaging operators

Since the introduction of the ordered weighted averaging operator [18], the OWA has received great attention with applications in fields including decision making, recommender systems [8, 21], classification [10] and data mining [16] among others. The most important step in the calculation of the OWA is the permutation of the input vector according to the size of its arguments. In some applications, it makes sense that the inputs be reordered by values different to those used in calculation. For instance, if we have a number of mobile sensor readings, we may wish to allocate more importance to the reading taken from the sensor closest to us at a given point in time, rather than the largest reading.

A weighted version of the Melbourne low-vision ADL index : a measure of disability impact

Objective. To develop a version of the Melbourne Low-Vision ADL Index that measures the personal impact of disability in activities of daily living (ADL's). Also, to determine the relationship between clinical measures of vision impairment and disability impact.

Methods. The Melbourne Low-Vision ADL Index (MLVAI) is a desk-based clinical assessment of disability in ADL's. Ability to perform each item is rated on a five-level descriptive scale from zero to four. In this study, the original version of the MLVAI was modified to measure disability impact. The simple modification involved weighting each item by the importance of that item to the person being tested. Importance was also rated on a five-level scale from zero to four. The validity and reliability of the Weighted Melbourne Low-Vision ADL Index (MLVAIW) was determined for 97 vision-impaired subjects in a cross-sectional study.

Results. Cronbach's alpha coefficient indicated an internal reliability of 0.94, and an intraclass correlation coefficient indicated an overall reliability of 0.88. The standard error of measurement was 24.7 points (out of a possible score of 400). There was a statistically significant difference in test scores between normal subjects and vision-impaired subjects. All vision measures had a high, statistically significant correlation with MLVAIW score. Near-word acuity had the strongest correlation (rs = 0.78, p < 0.001), followed by Melbourne Edge Test contrast sensitivity (rs = -0.72, p < 0.001). Visual field had the weakest correlation (rs = -0.52, p < 0.001). The best predictive model of MLVAIW score incorporated the variables age, near-word acuity, and visual field. Together, these variables accounted for 65.1% of the variance in MLVAIW score.

Conclusions. The MLVAI is highly valid and reliable when weighted by a scale that reflects the personal importance of ADL's. The MLVAIW can provide information over and above that obtained with the usual clinical vision measures and may be used to assess low-vision patients and to measure low-vision rehabilitation outcomes. It is suggested that the assessment of disability using the original MLVAI and the assessment of the impact of disability using the MLVAIW should be kept separate to facilitate the clear interpretation of the outcomes of low-vision rehabilitation.

An amoeboid algorithm for shortest path in fuzzy weighted networks

Taking the uncertainty existing in edge weights of networks into consideration, finding shortest path in such fuzzy weighted networks has been widely studied in various practical applications. In this paper, an amoeboid algorithm is proposed, combing fuzzy sets theory with a path finding model inspired by an amoeboid organism, Physarum polycephalum. With the help of fuzzy numbers, uncertainty is well represented and handled in our algorithm. What's more, biological intelligence of Physarum polycephalum has been incorporate into the algorithm. A numerical example on a transportation network is demonstrated to show the efficiency and flexibility of our proposed amoeboid algorithm.

An improved physarum centrality measure for weighted networks

Identification of the most central node within a network is one of the primary problems in network analysis. Among various centrality measures for weighted networks, most are based on the assumption that information only spreads through the shortest paths. Then, a mathematical model of an amoeboid organism has been used by Physarum centrality to relax the assumption. However, its computational complexity is relatively high by finding competing paths between all pairs of nodes in networks. In this paper, with the idea of a ground node, an improved Physarum centrality is proposed by maintaining the feature of original measure with the performance is greatly enhanced. Examples and applications are given to show the efficiency and effectiveness of our proposed measure in weighted networks.

Size-frequency distributions along a latitudinal gradient in middle permian fusulinoideans

Geographic gradients in body size within and among living species are commonly used to identify controls on the long-term evolution of organism size. However, the persistence of these gradients over evolutionary time remains largely unknown because ancient biogeographic variation in organism size is poorly documented. Middle Permian fusulinoidean foraminifera are ideal for investigating the temporal persistence of geographic gradients in organism size because they were diverse and abundant along a broad range of paleo-latitudes during this interval (~275–260 million years ago). In this study, we determined the sizes of Middle Permian fusulinoidean fossils from three different paleo-latitudinal zones in order to examine the relationship between the size of foraminifers and regional environment. We recovered the following results: keriothecal fusulinoideans are substantially larger than nonkeriothecal fusulinoideans; fusulinoideans from the equatorial zone are typically larger than those from the north and south transitional zones; neoschwagerinid specimens within a single species are generally larger in the equatorial zone than those in both transitional zones; and the nonkeriothecal fusulinoideans Staffellidae and Schubertellidae have smaller size in the north transitional zone. Fusulinoidean foraminifers differ from most other marine taxa in exhibiting larger sizes closer to the equator, contrary to Bergmann's rule. Meridional variation in seasonality, water temperature, nutrient availability, and carbonate saturation level are all likely to have favored or enabled larger sizes in equatorial regions. Temporal variation in atmospheric oxygen concentrations have been shown to account for temporal variation in fusulinoidean size during Carboniferous and Permian time, but oxygen availability appears unlikely to explain biogeographic variation in fusulinoidean sizes, because dissolved oxygen concentrations in seawater typically increase away from the equator due to declining seawater temperatures. Consequently, our findings highlight the fact that spatial gradients in organism size are not always controlled by the same factors that govern temporal trends within the same clade.

Probability distributions of number of children and maternal age at various order births using age-specific fertility rates by birth order

In this study, a simple analytical framework to find the probability distributions of number of children and maternal age at various order births by making use of data on age-specific fertility rates by birth order was proposed. The proposed framework is applicable to both the period and cohort fertility schedules. The most appealing point of the proposed framework is that it does not require stringent assumptions. The proposed framework has been applied to the cohort birth order-specific fertility schedules of India and its different regions and period birth order-specific fertility schedules, including the United States of America, Russia, and the Netherlands, to demonstrate its usefulness.