Dave Swain

An n-alkane proxy for the sedimentary input of submerged/floating freshwater aquatic macrophytes

Lipid analysis of aquatic plants from lakes on Mt. Kenya, E. Africa, revealed that non-emergent (submerged and floating-leaved) species displayed enhanced abundances of mid-chain length, C23 and C25 n-alkanes. In contrast, the emergent aquatic plants had n-alkane distributions similar to those of the terrestrial vegetation, typically dominated by the long-chain length homologues (>C29). A proxy ratio, Paq, has been formulated to reflect the non-emergent aquatic macrophyte input to lake sediments relative to that from the emergent aquatic and terrestrial plants. # 2000 Elsevier Science Ltd. All rights reserved.

Transforming Agriculture through Pervasive Wireless Sensor Networks

A large-scale, outdoor pervasive computing system uses static and animal-borne nodes to measure the state of a complex system comprising climate, soil, pasture, and animals. Agriculture faces many challenges, such as climate change, water shortages, labor shortages due to an aging urbanized population, and increased societal concern about issues such as animal welfare, food safety, and environmental impact. Humanity depends on agriculture and water for survival, so optimal, profitable, and sustainable use of our land and water resources is critical.

Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

Wireless ad hoc sensor and actuator networks on the farm

Agriculture accounts for a significant portion of the GDP in most developed countries. However, managing farms, particularly large-scale extensive farming systems, is hindered by lack of data and increasing shortage of labour. We have deployed a large heterogeneous sensor network on a working farm to explore sensor network applications that can address some of the issues identified above. Our network is solar powered and has been running for over 6 months. The current deployment consists of over 40 moisture sensors that provide soil moisture profiles at varying depths, weight sensors to compute the amount of food and water consumed by animals, electronic tag readers, up to 40 sensors that can be used to track animal movement (consisting of GPS, compass and accelerometers), and 20 sensor/actuators that can be used to apply different stimuli (audio, vibration and mild electric shock) to the animal. The static part of the network is designed for 24/7 operation and is linked to the Internet via a dedicated high-gain radio link, also solar powered. The initial goals of the deployment are to provide a testbed for sensor network research in programmability and data handling while also being a vital tool for scientists to study animal behavior. Our longer term aim is to create a management system that completely transforms the way farms are managed

Reconstruction of a subalpine grass-dominated ecosystem, Lake Rutundu, Mount Kenya: a novel multi-proxy approach

Palaeoecological reconstructions based on a single proxy are limited, but by combining pollen, biogeochemistry and grass cuticle analysis, ecosystem structure and function can be better understood. Lake Rutundu is a small, subalpine lake on the northeast flank of Mt Kenya. During the last glacial, pollen evidence suggests a shrub grassland dominated by Afroalpine taxa and Poaceae, representing a dry, cold, open environment. The δ13C values of terrestrial biomarkers imply a high proportion of C4 plants. Grass cuticle analysis allows resolution of the different C4 subtypes and shows that the vegetation was dominated by tall C4 panicoid grasses, prone to frequent fires. During the Holocene, Poaceae pollen declined while subalpine shrubs increased. The δ13C values of terrestrial biomarkers imply a C3-dominated vegetation. Together with an expansion of rainforest at lower altitudes, this suggests wetter conditions more favourable to C3 plants. Increased percentages of C3 pooid grass cuticles confirm a reduction in moisture stress.

Animal Behaviour Understanding using Wireless Sensor Networks

This paper presents research that is being conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) with the aim of investigating the use of wireless sensor networks for automated livestock monitoring and control. It is difficult to achieve practical and reliable cattle monitoring with current conventional technologies due to challenges such as large grazing areas of cattle, long time periods of data sampling, and constantly varying physical environments. Wireless sensor networks bring a new level of possibilities into this area with the potential for greatly increased spatial and temporal resolution of measurement data. CSIRO has created a wireless sensor platform for animal behaviour monitoring where we are able to observe and collect information of animals without significantly interfering with them. Based on such monitoring information, we can identify each animals behaviour and activities successfully

Tracking livestock using global positioning systems – are we still lost?

Since the late 1980s, satellite-based global positioning systems (GPS) have provided unique and novel data that have been used to track animal movement. Tracking animals with GPS can provide useful information, but the cost of the technology often limits experimental replication. Limitations on the number of devices available to monitor the behaviour of animals, in combination with technical constraints, can weaken the statistical power of experiments and create significant experimental design challenges. The present paper provides a review and synthesis of using GPS for livestock-based studies and suggests some future research directions. Wildlife ecologists working in extensive landscapes have pioneered the use of GPS-based devices for tracking animals. Wildlife researchers have focussed efforts on quantifying and addressing issues associated with technology limitations, including spatial accuracy, rate of data collection, battery life and environmental factors causing loss of data. It is therefore not surprising that there has been a significant number of methodological papers published in the literature that have considered technical developments of GPS-based animal tracking. Livestock scientists have used GPS data to inform them about behavioural differences in free-grazing experiments. With a shift in focus from the environment to the animal comes the challenge of ensuring independence of the experimental unit. Social facilitation challenges independence of the individual in a group. The use of spatial modelling methods to process GPS data provides an opportunity to determine the degree of independence of data collected from an individual animal within behavioural-based studies. By using location and movement information derived from GPS data, researchers have been able to determine the environmental impact of grazing animals as well as assessing animal responses to management activities or environmental perturbations. Combining satellite-derived remote-sensing data with GPS-derived landscape preference indices provides a further opportunity to identify landscape avoidance and selection behaviours. As spatial livestock monitoring tools become more widely used, there will be a greater need to ensure the data and associated processing methods are able to answer a broader range of questions. Experimental design and analytical techniques need to be given more attention if GPS technology is to provide answers to questions associated with free-grazing animals.

An altitudinal and stable carbon isotope survey of C3 and C4 graminoids on Mount Kenya

ABSTRACT An altitudinal survey of grasses and sedges was conducted on the Sirimon and Chogoria tracks on Mount Kenya to supplement previous surveys restricted to the Timau track. Thirty seven grasses and twenty three sedges were recorded and stable carbon isotope analysis was used to identify the photosynthetic pathway (C3 or C4) used by these species. The occurrence of a group of C4 graminoids was confirmed close above the tree line, and the literature suggests this may also hold for the Aberdares Range and other East African mountain massifs. Lower altitude graminoids are C3 forest species, and this distribution upsets the assumption that C4 gives way to C3 with increasing altitude. The significance of this is discussed in relation to the interpretation of palaeoenvironments through carbon stable isotope proxies.

Determining the effect of stocking rate on the spatial distribution of cattle for the subtropical savannas

With the commercial development of the global positioning system (GPS), it is now possible to monitor the distribution of free ranging cattle and derive measures to describe landscape use. Animal GPS data can be integrated with a geographic information system (GIS) detailing topography, vegetation, soil type and other landscape features. Combining GPS and GIS information is useful for understanding how animals respond to spatial variability. This study quantified land-type preferences for Brahman cross steers over three time periods, from October 2004 to March 2006 in a replicated trial, under heavy (4 ha/AE; animal equivalent of ~450 kg steer) and light (8 ha/AE) stocking in four, ~105 ha paddocks of subtropical semi-arid savanna near Charters Towers, Queensland, Australia. The grazing trail was conducted at a scale much less than would be found in commercial situations. Consequently, the spatial pattern of cattle reported here may not represent what occurs at a commercial scale and implications are discussed. Results were analysed in terms of the spatial distribution of steers fitted with GPS devices in each of the four paddocks and for each stocking rate to provide insight into cattle distribution and land-type preferences. Steers walked in excess of 6 km per day, regardless of stocking rate, and exhibited diurnal patterns of movement, with peak activity around dawn (0500–0700 hours) and dusk (1800–2000 hours). The spatial distribution of the collared steers was not uniform and appeared to be strongly influenced by the prevailing drought conditions and location of water points within each paddock. A hierarchy of drivers for distribution was identified. With the exception of drinking water location, land subtype based on soil-vegetation associations influenced animal distribution. Preference indices (ŵi) indicated that steers selected sites associated with heavy clay and texture contrast soils dominated by Eucalyptus coolabah Blakely & Jacobs (ŵi = 5.33) and Eucalyptus brownii Maiden & Cambage (ŵi = 3.27), respectively, and avoiding Eucalyptus melanophloia F.Muell. ridges (ŵi = 0.26) and Eucalyptus cambageana Maiden (ŵi = 0.12) on sodosols. The results suggest that spatial variation in cattle distribution within a paddock may be more critical than overall stocking rate in influencing the pattern of biomass utilisation. However, to quantifying the effects of different grazing land management practices on animal distribution on a commercial scale, additional studies in extensive paddocks are required.

Agent-based modelling of foraging behaviour: the impact of spatial heterogeneity on disease risks from faeces in grazing systems

Many of the most pervasive disease challenges to livestock are transmitted via oral contact with faeces (or by faecal-aerosol) and the current paper focuses on how disease risk may depend on: spatial heterogeneity, animal searching behaviour, different grazing systems and faecal deposition patterns including those representative of livestock and a range of wildlife. A spatially explicit agent-based model was developed to describe the impact of empirically observed foraging and avoidance behaviours on the risk of disease presented by investigative and grazing contact with both livestock and wildlife faeces. To highlight the role of spatial heterogeneity on disease risks an analogous deterministic model, which ignores spatial heterogeneity and searching behaviour, was compared with the spatially explicit agent-based model. The models were applied to assess disease risks in temperate grazing systems. The results suggest that spatial heterogeneity is crucial in defining the disease risks to which individuals are exposed even at relatively small scales. Interestingly, however, although sensitive to other aspects of behaviour such as faecal avoidance, it was observed that disease risk is insensitive to search distance for typical domestic livestock restricted to small field plots. In contrast disease risk is highly sensitive to distributions of faecal contamination, in that contacts with highly clumped distributions of wildlife contamination are rare in comparison to those with more dispersed contamination. Finally it is argued that the model is a suitable framework to study the relative inter- and intra-specific disease risks posed to livestock under different realistic management regimes.