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.

The evolution of the avian bill as a thermoregulatory organ.

The avian bill is a textbook example of how evolution shapes morphology in response to changing environments. Bills of seed-specialist finches in particular have been the focus of intense study demonstrating how climatic fluctuations acting on food availability drive bill size and shape. The avian bill also plays an important but under-appreciated role in body temperature regulation, and therefore in energetics. Birds are endothermic and rely on numerous mechanisms for balancing internal heat production with biophysical constraints of the environment. The bill is highly vascularised and heat exchange with the environment can vary substantially, ranging from around 2% to as high as 400% of basal heat production in certain species. This heat exchange may impact how birds respond to heat stress, substitute for evaporative water loss at elevated temperatures or environments of altered water availability, or be an energetic liability at low environmental temperatures. As a result, in numerous taxa, there is evidence for a positive association between bill size and environmental temperatures, both within and among species. Therefore, bill size is both developmentally flexible and evolutionarily adaptive in response to temperature. Understanding the evolution of variation in bill size however, requires explanations of all potential mechanisms. The purpose of this review, therefore, is to promote a greater understanding of the role of temperature on shaping bill size over spatial gradients as well as developmental, seasonal, and evolutionary timescales.

Bayesian classification of catchments using spatial data: a first step to improved modelling of catchment effects on stream ecological condition

A major challenge facing freshwater ecologists and managers is the development of models that link stream ecological condition to catchment scale effects, such as land use. Previous attempts to make such models have followed two general approaches. The bottom-up approach employs mechanistic models, which can quickly become too complex to be useful. The top-down approach employs empirical models derived from large data sets, and has often suffered from large amounts of unexplained variation in stream condition.

We believe that the lack of success of both modelling approaches may be at least partly explained by scientists considering too wide a breadth of catchment type. Thus, we believe that by stratifying large sets of catchments into groups of similar types prior to modelling, both types of models may be improved. This paper describes preliminary work using a Bayesian classification software package, ‘Autoclass’ (Cheeseman and Stutz 1996) to create classes of catchments within the Murray Darling Basin based on physiographic data.

Autoclass uses a model-based classification method that employs finite mixture modelling and trades off model fit versus complexity, leading to a parsimonious solution. The software provides information on the posterior probability that the classification is ‘correct’ and also probabilities for alternative classifications. The importance of each attribute in defining the individual classes is calculated and presented, assisting description of the classes. Each case is ‘assigned’ to a class based on membership probability, but the probability of membership of other classes is also provided. This feature deals very well with cases that do not fit neatly into a larger class. Lastly, Autoclass requires the user to specify the measurement error of continuous variables.

Catchments were derived from the Australian digital elevation model. Physiographic data werederived from national spatial data sets. There was very little information on measurement errors for the spatial data, and so a conservative error of 5% of data range was adopted for all continuous attributes. The incorporation of uncertainty into spatial data sets remains a research challenge.

The results of the classification were very encouraging. The software found nine classes of catchments in the Murray Darling Basin. The classes grouped together geographically, and followed altitude and latitude gradients, despite the fact that these variables were not included in the classification. Descriptions of the classes reveal very different physiographic environments, ranging from dry and flat catchments (i.e. lowlands), through to wet and hilly catchments (i.e. mountainous areas). Rainfall and slope were two important discriminators between classes. These two attributes, in particular, will affect the ways in which the stream interacts with the catchment, and can thus be expected to modify the effects of land use change on ecological condition. Thus, realistic models of the effects of land use change on streams would differ between the different types of catchments, and sound management practices will differ.

A small number of catchments were assigned to their primary class with relatively low probability. These catchments lie on the boundaries of groups of catchments, with the second most likely class being an adjacent group. The locations of these ‘uncertain’ catchments show that the Bayesian classification dealt well with cases that do not fit neatly into larger classes.

Although the results are intuitive, we cannot yet assess whether the classifications described in this paper would assist the modelling of catchment scale effects on stream ecological condition. It is most likely that catchment classification and modelling will be an iterative process, where the needs of the model are used to guide classification, and the results of classifications used to suggest further refinements to models.

Latitudinal gradients in abundance, and the causes of rarity in the tropics: a test using Australian honeyeaters (Aves: Meliphagidae)

Several studies have uncovered interspecific latitudinal gradients in abundance (population density) such that tropical species tend to be, on average, less abundant than species at higher latitudes. The causes of this relationship remain poorly studied, in contrast to the relative wealth of literature examining the relationship to latitude of other variables such as range size and body mass. We used a cross-species phylogenetic comparative approach and a spatial approach to examine three potential determining factors (distribution, reproductive output and climate) that might explain why abundance correlates with latitude, using data from 54 species of honeyeaters (Meliphagidae) in woodland environments in eastern Australia. There is a strong positive correlation between mean abundance and latitude in these birds. Reproductive output (clutch size) was positively linked to both abundance and latitude, but partial correlation analysis revealed that clutch size is not related to abundance once the effects of latitude are removed. A subsequent multiple regression model that also considered range size, clutch size and body mass showed that latitude is the only strong predictor of abundance in honeyeaters. In the separate spatial analysis, the climatic variables that we considered (temperature, rainfall and seasonality) were all strongly linked to latitude, but none served as a better predictor of abundance than latitude per se, either individually or collectively. The most intriguing result of our analyses was that the cross-species latitudinal pattern in abundance was not evident within species. This suggests an intrinsic cause of the pattern of ‘rarity in the tropics’ in Australian honeyeaters. We suggest that evolutionary age may provide a key to understanding patterns of abundance in these birds.

Temporal and spatial variability of breeding in Australian birds and the potential implications of climate change

Climate change has profound implications for biodiversity worldwide. To understand its effects on Australia's avifauna, we need to evaluate the effects of annual climatic variability and geographical climate gradients. Here, we use national datasets to examine variation in breeding of 16 species of common and widespread Australian landbirds, in relation to four variables: altitude, latitude, year and the Southern Oscillation Index. Analysis of 30 years of nesting records confirmed that breeding was generally later in colder altitudes and latitudes (geographic variation), but was not consistently related to year or the Southern Oscillation Index (temporal variation). However, power to detect expected temporal effects was low. The timing of breeding became significantly earlier with year only in south-eastern Australia. In contrast, an index of breeding activity (the proportion of atlas records for a species for which breeding was reported) increased with increasing winter values of the Southern Oscillation Index (generally wetter conditions) for all 16 species across Australia. This suggests that annual fluctuations in rainfall can have dramatic and immediate effects on breeding, even for largely sedentary, seasonally breeding species. If, as expected, climate change creates drier conditions over much of Australia, we predict a marked negative effect on bird breeding.

Spatial activity recognition in a smart home environment using a chemotactic model

Spatial activity recognition is challenging due to the amount of noise incorporated during video tracking in everyday environments. We address the spatial recognition problem with a biologically-inspired chemotactic model that is capable of handling noisy data. The model is based on bacterial chemotaxis, a process that allows bacteria to change motile behaviour in relation to environmental gradients. Through adoption of chemotactic principles, we propose the chemotactic model and evaluate its performance in a smart house environment. The model exhibits greater than 99% recognition performance with a diverse six class dataset and outperforms the Hidden Markov Model (HMM). The approach also maintains high accuracy (90-99%) with small training sets of one to five sequences. Importantly, unlike other low-level spatial activity recognition models, we show that the chemotactic model is capable of recognising simple interwoven activities.

Fine-scale spatial and temporal variations in diets of the pipefish Stigmatopora nigra within seagrass patches

Diets of the pipefish Stigmatopora nigra were analysed to determine if food availability was causing S. nigra to distribute according to habitat edge effects. Gut analysis found little difference in the diets of S. nigra at the edge and interior of seagrass patches, regardless of time of day or season. Fish diets did, however, vary with seagrass density: S. nigra in denser seagrass consumed more harpacticoid copepods and fewer planktonic copepods. The lack of difference in prey eaten by S. nigra at the edge and interior of patches suggests either that food was not determining S. nigra distribution patterns within patches or that differences in fish densities across patches meant that relative fish–prey densities were similar at edge and interior positions. Alternatively, any edge effects in diet might be masked by gradients in seagrass structure.