Changes in morphology and physiology of an East Mediterranean sponge in different habitats

The sponge Tetilla sp. (Tetractinomorpha: Tetillidae) is a common species in the eastern Mediterranean. This sponge inhabits four different habitat types differing in wave impact and irradiance levels. Two of these habitats (a shallow cave and deep water) are characterized by relatively calm water, whereas the other two (shallow exposed site and tide pools) are in turbulent water with high energy flow. The present study examined the influence of physical (depth, illumination and water motion) and biotic factors on morphology, skeletal plasticity and reproductive traits among the four spatially separated populations. Sponges from tidal pools had significantly larger body volume than sponges from deep water and from shallow caves (ANOVA: tidal-deep P< 0.0001; tidal-shallow caves P< 0.05). Sponges from exposed habitats were significantly larger than deep-water sponges (ANOVA: P=0.01). In addition, individuals from tide pools and from the exposed habitat had a significantly higher proportion of structural silica than sponges from the calmer deep water and from the cave sites. Oxea spicules in sponges from the calm habitats were significantly shorter than in those from the tidal pools and the exposed habitats. The percentage of spicules out of a sponge's dry weight in individuals transplanted from deep (calm) to shallow (turbulent) water significantly increased by 21.9&PLUSMN; 12.9%. The new spicule percentage did not differ significantly from that of sponges originally from shallow water. Oocyte diameter differed significantly between habitats. The maximal size of mature eggs was found in deep-water sponges in June (97&PLUSMN; 5 μ m). In the shallow habitats, a smaller maximal oocyte diameter was found in the cave, in May (56.5&PLUSMN; 3 μ m). Furthermore, oocyte density in shallow-water sponges was highest in May and decreased in June (with 88.2&PLUSMN; 9 and 19.3&PLUSMN; 9 oocytes mm(-2), respectively). At the same time (June), oocyte density of deep-water sponges had just reached its maximum (155&PLUSMN; 33.7 oocytes mm(-2)). The difference in oocyte size and density between deep- and shallow-water individuals indicates an earlier gamete release in the shallow sponge population. The results suggest that plasticity in skeletal design of this sponge indicates a trade off between spicule production and investment in reproduction.

Degrees of freedom and motor planning in purposive movement

This paper presents empirical evidence suggesting that healthy humans can perform a two degree of freedom visuo-motor pursuit tracking task with the same response time delay as a one degree of freedom task. In contrast, the time delay of the response is influenced markedly by the nature of the motor synergy required to produce it. We suggest a conceptual account of this evidence based on adaptive model theory, which combines theories of intermittency from psychology and adaptive optimal control from engineering. The intermittent response planning stage has a fixed period. It possesses multiple optimal trajectory generators such that multiple degrees of freedom can be planned concurrently, without requiring an increase in the planning period. In tasks which require unfamiliar motor synergies, or are deemed to be incompatible, internal adaptive models representing movement dynamics are inaccurate. This means that the actual response which is produced will deviate from the one which is planned. For a given target-response discrepancy, corrective response trajectories of longer duration are planned, consistent with the principle of speed-accuracy trade-off. Compared to familiar or compatible tasks, this results in a longer response time delay and reduced accuracy. From the standpoint of the intermittency approach, the findings of this study help make possible a more integral and predictive account of purposive action. (c) 2005 Elsevier B.V. All rights reserved.

The value of a small microkernel for dreamy memory and the RAMpage memory hierarchy

This paper explores potential for the RAMpage memory hierarchy to use a microkernel with a small memory footprint, in a specialized cache-speed static RAM (tightly-coupled memory, TCM). Dreamy memory is DRAM kept in low-power mode, unless referenced. Simulations show that a small microkernel suits RAMpage well, in that it achieves significantly better speed and energy gains than a standard hierarchy from adding TCM. RAMpage, in its best 128KB L2 case, gained 11% speed using TCM, and reduced energy 14%. Equivalent conventional hierarchy gains were under 1%. While 1MB L2 was significantly faster against lower-energy cases for the smaller L2, the larger SRAM's energy does not justify the speed gain. Using a 128KB L2 cache in a conventional architecture resulted in a best-case overall run time of 2.58s, compared with the best dreamy mode run time (RAMpage without context switches on misses) of 3.34s, a speed penalty of 29%. Energy in the fastest 128KB L2 case was 2.18J vs. 1.50J, a reduction of 31%. The same RAMpage configuration without dreamy mode took 2.83s as simulated, and used 2.39J, an acceptable trade-off (penalty under 10%) for being able to switch easily to a lower-energy mode.

A new method for conservation planning for the persistence of multiple species

Although the aim of conservation planning is the persistence of biodiversity, current methods trade-off ecological realism at a species level in favour of including multiple species and landscape features. For conservation planning to be relevant, the impact of landscape configuration on population processes and the viability of species needs to be considered. We present a novel method for selecting reserve systems that maximize persistence across multiple species, subject to a conservation budget. We use a spatially explicit metapopulation model to estimate extinction risk, a function of the ecology of the species and the amount, quality and configuration of habitat. We compare our new method with more traditional, area-based reserve selection methods, using a ten-species case study, and find that the expected loss of species is reduced 20-fold. Unlike previous methods, we avoid designating arbitrary weightings between reserve size and configuration; rather, our method is based on population processes and is grounded in ecological theory.

Hierarchical indexing structure for efficient similarity search in video retrieval

With the rapid increase in both centralized video archives and distributed WWW video resources, content-based video retrieval is gaining its importance. To support such applications efficiently, content-based video indexing must be addressed. Typically, each video is represented by a sequence of frames. Due to the high dimensionality of frame representation and the large number of frames, video indexing introduces an additional degree of complexity. In this paper, we address the problem of content-based video indexing and propose an efficient solution, called the Ordered VA-File (OVA-File) based on the VA-file. OVA-File is a hierarchical structure and has two novel features: 1) partitioning the whole file into slices such that only a small number of slices are accessed and checked during k Nearest Neighbor (kNN) search and 2) efficient handling of insertions of new vectors into the OVA-File, such that the average distance between the new vectors and those approximations near that position is minimized. To facilitate a search, we present an efficient approximate kNN algorithm named Ordered VA-LOW (OVA-LOW) based on the proposed OVA-File. OVA-LOW first chooses possible OVA-Slices by ranking the distances between their corresponding centers and the query vector, and then visits all approximations in the selected OVA-Slices to work out approximate kNN. The number of possible OVA-Slices is controlled by a user-defined parameter delta. By adjusting delta, OVA-LOW provides a trade-off between the query cost and the result quality. Query by video clip consisting of multiple frames is also discussed. Extensive experimental studies using real video data sets were conducted and the results showed that our methods can yield a significant speed-up over an existing VA-file-based method and iDistance with high query result quality. Furthermore, by incorporating temporal correlation of video content, our methods achieved much more efficient performance.

Can non-directional male mating preferences facilitate honest female ornamentation?

Recent studies have demonstrated male mate choice for female ornaments in species without sex-role reversal. Despite these empirical findings, little is known about the adaptive dynamics of female signalling, in particular the evolution of male mating preferences. The evolution of traits that signal mate quality is more complex in females than in males because females usually provide the bulk of resources for the developing offspring. Here, we investigate the evolution of male mating preferences using a mathematical model which: (i) specifically accounts for the fact that females must trade-off resources invested in ornaments with reproduction; and (ii) allows male mating preferences to evolve a non-directional shape. The optimal adaptive strategy for males is to develop stabilizing mating preferences for female display traits to avoid females that either invests too many or too few resources in ornamentation. However, the evolutionary stability of this prediction is dependent upon the level of error made by females when allocating resources to either signal or fecundity.

Matching of catalogues by probabilistic pattern classification

We consider the statistical problem of catalogue matching from a machine learning perspective with the goal of producing probabilistic outputs, and using all available information. A framework is provided that unifies two existing approaches to producing probabilistic outputs in the literature, one based on combining distribution estimates and the other based on combining probabilistic classifiers. We apply both of these to the problem of matching the HI Parkes All Sky Survey radio catalogue with large positional uncertainties to the much denser SuperCOSMOS catalogue with much smaller positional uncertainties. We demonstrate the utility of probabilistic outputs by a controllable completeness and efficiency trade-off and by identifying objects that have high probability of being rare. Finally, possible biasing effects in the output of these classifiers are also highlighted and discussed.

Optimal eradication: when to stop looking for an invasive plant

The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. Eradication is commonly declared either on an ad hoc basis, on notions of seed bank longevity, or on setting arbitrary thresholds of 1% or 5% confidence that the species is not present. Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits. We develop theory that determines the number of years of absent surveys required to minimize the net expected cost. Given detection of a species is imperfect, the optimal stopping time is a trade-off between the cost of continued surveying and the cost of escape and damage if eradication is declared too soon. A simple rule of thumb compares well to the exact optimal solution using stochastic dynamic programming. Application of the approach to the eradication programme of Helenium amarum reveals that the actual stopping time was a precautionary one given the ranges for each parameter.

Cone photoreceptor oil droplet pigmentation is affected by ambient light intensity

The cone photoreceptors of many vertebrates contain spherical organelles called oil droplets. In birds, turtles, lizards and some lungfish the oil droplets are heavily pigmented and function to filter the spectrum of light incident upon the visual pigment within the outer segment. Pigmented oil droplets are beneficial for colour discrimination in bright light, but at lower light levels the reduction in sensitivity caused by the pigmentation increasingly outweighs the benefits generated by spectral tuning. Consequently, it is expected that species with pigmented oil droplets should modulate the density of pigment in response to ambient light intensity and thereby regulate the amount of light transmitted to the outer segment. In this study, microspectrophotometry was used to measure the absorption spectra of cone oil droplets in chickens (Gallus gallus domesticus) reared under bright (unfiltered) or dim (filtered) sunlight. Oil droplet pigmentation was found to be dependent on the intensity of the ambient light and the duration of exposure to the different lighting treatments. In adult chickens reared in bright light, the oil droplets of all cone types (except the violet-sensitive single cones, whose oil droplet is always non-pigmented) were more densely pigmented than those in chickens reared in dim light. Calculations show that the reduced levels of oil droplet pigmentation in chickens reared in dim light would increase the sensitivity and spectral bandwidth of the outer segment significantly. The density of pigmentation in the oil droplets presumably represents a trade-off between the need for good colour discrimination and absolute sensitivity. This might also explain why nocturnal animals, or those that underwent a nocturnal phase during their evolution, have evolved oil droplets with low pigment densities or no pigmentation or have lost their oil droplets altogether.

Optimizing Presence–Absence Surveys For Detecting Population Trends

Presence-absence surveys are a commonly used method for monitoring broad-scale changes in wildlife distributions. However, the lack of power of these surveys for detecting population trends is problematic for their application in wildlife management. Options for improving power include increasing the sampling effort or arbitrarily relaxing the type I error rate. We present an alternative, whereby targeted sampling of particular habitats in the landscape using information from a habitat model increases power. The advantage of this approach is that it does not require a trade-off with either cost or the Pr(type I error) to achieve greater power. We use a demographic model of koala (Phascolarctos cinereus) population dynamics and simulations of the monitoring process to estimate the power to detect a trend in occupancy for a range of strategies, thereby demonstrating that targeting particular habitat qualities can improve power substantially. If the objective is to detect a decline in occupancy, the optimal strategy is to sample high-quality habitats. Alternatively, if the objective is to detect an increase in occupancy, the optimal strategy is to sample intermediate-quality habitats. The strategies with the highest power remained the same under a range of parameter assumptions, although observation error had a strong influence on the optimal strategy. Our approach specifically applies to monitoring for detecting long-term trends in occupancy or abundance. This is a common and important monitoring objective for wildlife managers, and we provide guidelines for more effectively achieving it.

Review of the ecology of Australian urban fauna: A focus on spatially explicit processes

Cities have a major impact on Australian landscapes, especially in coastal regions, to the detriment of native biodiversity. Areas suitable for urban development often coincide with those areas that support high levels of species diversity and endemism. However, there is a paucity of reliable information available to guide urban conservation planning and management, especially regarding the trade-off between investing in protecting and restoring habitat at the landscape level, and investing in programmes to maintain the condition of remnant vegetation at the local (site) level. We review the literature on Australian urban ecology, focusing on urban terrestrial and aquatic vertebrate and invertebrate fauna. We identify four main factors limiting our knowledge of urban fauna: (i) a lack of studies focusing at multiple ecological levels; (ii) a lack of multispecies studies; (iii) an almost total absence of long-term (temporal) studies; and (iv) a need for stronger integration of research outcomes into urban conservation planning and management. We present a set of key principles for the development of a spatially explicit, long-term approach to urban fauna research. This requires an understanding of the importance of local-level habitat quality and condition relative to the composition, configuration and connectivity of habitats within the larger urban landscape. These principles will ultimately strengthen urban fauna management and conservation planning by enabling us to prioritize and allocate limited financial resources to maximize the conservation return.

Collaborative filtering on data streams

Collaborate Filtering is one of the most popular recommendation algorithms. Most Collaborative Filtering algorithms work with a static set of data. This paper introduces a novel approach to providing recommendations using Collaborative Filtering when user rating is received over an incoming data stream. In an incoming stream there are massive amounts of data arriving rapidly making it impossible to save all the records for later analysis. By dynamically building a decision tree for every item as data arrive, the incoming data stream is used effectively although an inevitable trade off between accuracy and amount of memory used is introduced. By adding a simple personalization step using a hierarchy of the items, it is possible to improve the predicted ratings made by each decision tree and generate recommendations in real-time. Empirical studies with the dynamically built decision trees show that the personalization step improves the overall predicted accuracy.