214 resultados para temporal sampling
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Fruit flies require protein for reproductive development and actively feed upon protein sources in the field. Liquid protein baits mixed with insecticide are used routinely to manage pest fruit flies, such as Bactrocera tryoni (Froggatt). However, there are still some gaps in the underpinning science required to improve the efficacy of bait spray technology. The spatial and temporal foraging behaviour of B. tryoni in response to protein was investigated in the field. A series of linked trials using either wild flies in the open field or laboratory-reared flies in field cages and a netted orchard were undertaken using nectarines and guavas. Key questions investigated were the fly's response to protein relative to: height of protein within the canopy, fruiting status of the tree, time of day, season and size of the experimental arena. Canopy height had a significant response on B. tryoni foraging, with more flies foraging on protein in the mid to upper canopy. Fruiting status also had a significant effect on foraging, with most flies responding to protein when applied to fruiting hosts. B. tryoni demonstrated a repeatable diurnal response pattern to protein, with the peak response being between 12:00–16:00 h. Season showed significant but unpredictable effects on fruit fly response to protein in the subtropical environment where the work was undertaken. Relative humidity, but not temperature or rainfall, was positively correlated with protein response. The number of B. tryoni responding to protein decreased dramatically as the spatial scale increased from field cage through to the open field. Based on these results, it is recommend that, to be most effective, protein bait sprays should be applied to the mid to upper canopies of fruiting hosts. Overall, the results show that the protein used, an industry standard, has very low attractancy to B. tryoni and that further work is urgently needed to develop more volatile protein baits.
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This book describes the mortality for all causes of death and the trend in major causes of death since 1970s in Shandong Province, China.
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Historically a significant gap between male and female wages has existed in the Australian labour market. Indeed this wage differential was institutionalised in the 1912 arbitration decision which determined that the basic female wage would be set at between 54 and 66 per cent of the male wage. More recently however, the 1969 and 1972 Equal Pay Cases determined that male/female wage relativities should be based upon the premise of equal pay for work of equal value. It is important to note that the mere observation that average wages differ between males and females is not sine qua non evidence of sex discrimination. Economists restrict the definition of wage discrimination to cases where two distinct groups receive different average remuneration for reasons unrelated to differences in productivity characteristics. This paper extends previous studies of wage discrimination in Australia (Chapman and Mulvey, 1986; Haig, 1982) by correcting the estimated male/female wage differential for the existence of non-random sampling. Previous Australian estimates of male/female human capital basedwage specifications together with estimates of the corresponding wage differential all suffer from a failure to address this issue. If the sample of females observed to be working does not represent a random sample then the estimates of the male/female wage differential will be both biased and inconsistent.
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As the world’s population is growing, so is the demand for agricultural products. However, natural nitrogen (N) fixation and phosphorus (P) availability cannot sustain the rising agricultural production, thus, the application of N and P fertilisers as additional nutrient sources is common. It is those anthropogenic activities that can contribute high amounts of organic and inorganic nutrients to both surface and groundwaters resulting in degradation of water quality and a possible reduction of aquatic life. In addition, runoff and sewage from urban and residential areas can contain high amounts of inorganic and organic nutrients which may also affect water quality. For example, blooms of the cyanobacterium Lyngbya majuscula along the coastline of southeast Queensland are an indicator of at least short term decreases of water quality. Although Australian catchments, including those with intensive forms of land use, show in general a low export of nutrients compared to North American and European catchments, certain land use practices may still have a detrimental effect on the coastal environment. Numerous studies are reported on nutrient cycling and associated processes on a catchment scale in the Northern Hemisphere. Comparable studies in Australia, in particular in subtropical regions are, however, limited and there is a paucity in the data, in particular for inorganic and organic forms of nitrogen and phosphorus; these nutrients are important limiting factors in surface waters to promote algal blooms. Therefore, the monitoring of N and P and understanding the sources and pathways of these nutrients within a catchment is important in coastal zone management. Although Australia is the driest continent, in subtropical regions such as southeast Queensland, rainfall patterns have a significant effect on runoff and thus the nutrient cycle at a catchment scale. Increasingly, these rainfall patterns are becoming variable. The monitoring of these climatic conditions and the hydrological response of agricultural catchments is therefore also important to reduce the anthropogenic effects on surface and groundwater quality. This study consists of an integrated hydrological–hydrochemical approach that assesses N and P in an environment with multiple land uses. The main aim is to determine the nutrient cycle within a representative coastal catchment in southeast Queensland, the Elimbah Creek catchment. In particular, the investigation confirms the influence associated with forestry and agriculture on N and P forms, sources, distribution and fate in the surface and groundwaters of this subtropical setting. In addition, the study determines whether N and P are subject to transport into the adjacent estuary and thus into the marine environment; also considered is the effect of local topography, soils and geology on N and P sources and distribution. The thesis is structured on four components individually reported. The first paper determines the controls of catchment settings and processes on stream water, riverbank sediment, and shallow groundwater N and P concentrations, in particular during the extended dry conditions that were encountered during the study. Temporal and spatial factors such as seasonal changes, soil character, land use and catchment morphology are considered as well as their effect on controls over distributions of N and P in surface waters and associated groundwater. A total number of 30 surface and 13 shallow groundwater sampling sites were established throughout the catchment to represent dominant soil types and the land use upstream of each sampling location. Sampling comprises five rounds and was conducted over one year between October 2008 and November 2009. Surface water and groundwater samples were analysed for all major dissolved inorganic forms of N and for total N. Phosphorus was determined in the form of dissolved reactive P (predominantly orthophosphate) and total P. In addition, extracts of stream bank sediments and soil grab samples were analysed for these N and P species. Findings show that major storm events, in particular after long periods of drought conditions, are the driving force of N cycling. This is expressed by higher inorganic N concentrations in the agricultural subcatchment compared to the forested subcatchment. Nitrate N is the dominant inorganic form of N in both the surface and groundwaters and values are significantly higher in the groundwaters. Concentrations in the surface water range from 0.03 to 0.34 mg N L..1; organic N concentrations are considerably higher (average range: 0.33 to 0.85 mg N L..1), in particular in the forested subcatchment. Average NO3-N in the groundwater has a range of 0.39 to 2.08 mg N L..1, and organic N averages between 0.07 and 0.3 mg N L..1. The stream bank sediments are dominated by organic N (range: 0.53 to 0.65 mg N L..1), and the dominant inorganic form of N is NH4-N with values ranging between 0.38 and 0.41 mg N L..1. Topography and soils, however, were not to have a significant effect on N and P concentrations in waters. Detectable phosphorus in the surface and groundwaters of the catchment is limited to several locations typically in the proximity of areas with intensive animal use; in soil and sediments, P is negligible. In the second paper, the stable isotopes of N (14N/15N) and H2O (16O/18O and 2H/H) in surface and groundwaters are used to identify sources of dissolved inorganic and organic N in these waters, and to determine their pathways within the catchment; specific emphasis is placed on the relation of forestry and agriculture. Forestry is predominantly concentrated in the northern subcatchment (Beerburrum Creek) while agriculture is mainly found in the southern subcatchment (Six Mile Creek). Results show that agriculture (horticulture, crops, grazing) is the main source of inorganic N in the surface waters of the agricultural subcatchment, and their isotopic signature shows a close link to evaporation processes that may occur during water storage in farm dams that are used for irrigation. Groundwaters are subject to denitrification processes that may result in reduced dissolved inorganic N concentrations. Soil organic matter delivers most of the inorganic N to the surface water in the forested subcatchment. Here, precipitation and subsequently runoff is the main source of the surface waters. Groundwater in this area is affected by agricultural processes. The findings also show that the catchment can attenuate the effects of anthropogenic land use on surface water quality. Riparian strips of natural remnant vegetation, commonly 50 to 100 m in width, act as buffer zones along the drainage lines in the catchment and remove inorganic N from the soil water before it enters the creek. These riparian buffer zones are common in most agricultural catchments of southeast Queensland and are indicated to reduce the impact of agriculture on stream water quality and subsequently on the estuary and marine environments. This reduction is expressed by a significant decrease in DIN concentrations from 1.6 mg N L..1 to 0.09 mg N L..1, and a decrease in the �15N signatures from upstream surface water locations downstream to the outlet of the agricultural subcatchment. Further testing is, however, necessary to confirm these processes. Most importantly, the amount of N that is transported to the adjacent estuary is shown to be negligible. The third and fourth components of the thesis use a hydrological catchment model approach to determine the water balance of the Elimbah Creek catchment. The model is then used to simulate the effects of land use on the water balance and nutrient loads of the study area. The tool that is used is the internationally widely applied Soil and Water Assessment Tool (SWAT). Knowledge about the water cycle of a catchment is imperative in nutrient studies as processes such as rainfall, surface runoff, soil infiltration and routing of water through the drainage system are the driving forces of the catchment nutrient cycle. Long-term information about discharge volumes of the creeks and rivers do, however, not exist for a number of agricultural catchments in southeast Queensland, and such information is necessary to calibrate and validate numerical models. Therefore, a two-step modelling approach was used to calibrate and validate parameters values from a near-by gauged reference catchment as starting values for the ungauged Elimbah Creek catchment. Transposing monthly calibrated and validated parameter values from the reference catchment to the ungauged catchment significantly improved model performance showing that the hydrological model of the catchment of interest is a strong predictor of the water water balance. The model efficiency coefficient EF shows that 94% of the simulated discharge matches the observed flow whereas only 54% of the observed streamflow was simulated by the SWAT model prior to using the validated values from the reference catchment. In addition, the hydrological model confirmed that total surface runoff contributes the majority of flow to the surface water in the catchment (65%). Only a small proportion of the water in the creek is contributed by total base-flow (35%). This finding supports the results of the stable isotopes 16O/18O and 2H/H, which show the main source of water in the creeks is either from local precipitation or irrigation waters delivered by surface runoff; a contribution from the groundwater (baseflow) to the creeks could not be identified using 16O/18O and 2H/H. In addition, the SWAT model calculated that around 68% of the rainfall occurring in the catchment is lost through evapotranspiration reflecting the prevailing long-term drought conditions that were observed prior and during the study. Stream discharge from the forested subcatchment was an order of magnitude lower than discharge from the agricultural Six Mile Creek subcatchment. A change in land use from forestry to agriculture did not significantly change the catchment water balance, however, nutrient loads increased considerably. Conversely, a simulated change from agriculture to forestry resulted in a significant decrease of nitrogen loads. The findings of the thesis and the approach used are shown to be of value to catchment water quality monitoring on a wider scale, in particular the implications of mixed land use on nutrient forms, distributions and concentrations. The study confirms that in the tropics and subtropics the water balance is affected by extended dry periods and seasonal rainfall with intensive storm events. In particular, the comprehensive data set of inorganic and organic N and P forms in the surface and groundwaters of this subtropical setting acquired during the one year sampling program may be used in similar catchment hydrological studies where these detailed information is missing. Also, the study concludes that riparian buffer zones along the catchment drainage system attenuate the transport of nitrogen from agricultural sources in the surface water. Concentrations of N decreased from upstream to downstream locations and were negligible at the outlet of the catchment.
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Background: Measurement accuracy is critical for biomechanical gait assessment. Very few studies have determined the accuracy of common clinical rearfoot variables between cameras with different collection frequencies. Research question: What is the measurement error for common rearfoot gait parameters when using a standard 30Hz digital camera compared to 100Hz camera? Type of study: Descriptive. Methods: 100 footfalls were recorded from 10 subjects ( 10 footfalls per subject) running on a treadmill at 2.68m/s. A high-speed digital timer, accurate within 1ms served as an external reference. Markers were placed along the vertical axis of the heel counter and the long axis of the shank. 2D coordinates for the four markers were determined from heel strike to heel lift. Variables of interest included time of heel strike (THS), time of heel lift (THL), time to maximum eversion (TMax), and maximum rearfoot eversion angle (EvMax). Results: THS difference was 29.77ms (+/- 8.77), THL difference was 35.64ms (+/- 6.85), and TMax difference was 16.50ms (+/- 2.54). These temporal values represent a difference equal to 11.9%, 14.3%, and 6.6% of the stance phase of running gait, respectively. EvMax difference was 1.02 degrees (+/- 0.46). Conclusions: A 30Hz camera is accurate, compared to a high-frequency camera, in determining TMax and EvMax during a clinical gait analysis. However, relatively large differences, in excess of 12% of the stance phase of gait, for THS and THL variables were measured.
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Background: Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. Results: Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,1 the Poisson model,1 the double logarithmic model2 and the compound model3 - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. Conclusions: This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.
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Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.
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Nitrous oxide emissions from soil are known to be spatially and temporally volatile. Reliable estimation of emissions over a given time and space depends on measuring with sufficient intensity but deciding on the number of measuring stations and the frequency of observation can be vexing. The question of low frequency manual observations providing comparable results to high frequency automated sampling also arises. Data collected from a replicated field experiment was intensively studied with the intention to give some statistically robust guidance on these issues. The experiment had nitrous oxide soil to air flux monitored within 10 m by 2.5 m plots by automated closed chambers under a 3 h average sampling interval and by manual static chambers under a three day average sampling interval over sixty days. Observed trends in flux over time by the static chambers were mostly within the auto chamber bounds of experimental error. Cumulated nitrous oxide emissions as measured by each system were also within error bounds. Under the temporal response pattern in this experiment, no significant loss of information was observed after culling the data to simulate results under various low frequency scenarios. Within the confines of this experiment observations from the manual chambers were not spatially correlated above distances of 1 m. Statistical power was therefore found to improve due to increased replicates per treatment or chambers per replicate. Careful after action review of experimental data can deliver savings for future work.
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Acoustic sensors can be used to estimate species richness for vocal species such as birds. They can continuously and passively record large volumes of data over extended periods. These data must subsequently be analyzed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced surveyors can produce accurate results; however the time and effort required to process even small volumes of data can make manual analysis prohibitive. This study examined the use of sampling methods to reduce the cost of analyzing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilizing five days of manually analyzed acoustic sensor data from four sites, we examined a range of sampling frequencies and methods including random, stratified, and biologically informed. We found that randomly selecting 120 one-minute samples from the three hours immediately following dawn over five days of recordings, detected the highest number of species. On average, this method detected 62% of total species from 120 one-minute samples, compared to 34% of total species detected from traditional area search methods. Our results demonstrate that targeted sampling methods can provide an effective means for analyzing large volumes of acoustic sensor data efficiently and accurately. Development of automated and semi-automated techniques is required to assist in analyzing large volumes of acoustic sensor data. Read More: http://www.esajournals.org/doi/abs/10.1890/12-2088.1
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Smart Card data from Automated Fare Collection system has been considered as a promising source of information for transit planning. However, literature has been limited to mining travel patterns from transit users and suggesting the potential of using this information. This paper proposes a method for mining spatial regular origins-destinations and temporal habitual travelling time from transit users. These travel regularity are discussed as being useful for transit planning. After reconstructing the travel itineraries, three levels of Density-Based Spatial Clustering of Application with Noise (DBSCAN) have been utilised to retrieve travel regularity of each of each frequent transit users. Analyses of passenger classifications and personal travel time variability estimation are performed as the examples of using travel regularity in transit planning. The methodology introduced in this paper is of interest for transit authorities in planning and managements
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Nitrous oxide emissions from intensive, fertilised agricultural systems have been identified as significant contributors to both Australia's and the global greenhouse gas (GHG) budget. This is expected to increase as rates of agriculture intensification and land use change accelerate to support population growth and food production. Limited data exists on N2O trace gas fluxes from subtropical or tropical tree cropping soils critical for the development of effective mitigation strategies.This study aimed to quantify GHG emissions over two consecutive years (March 2007 to March 2009) from a 30 year (lychee) orchard in the humid subtropical region of Australia. GHG fluxes were measured using a combination of high temporal resolution automated sampling and manually sampled chambers. No fertiliser was added to the plots during the 2007 measurement season. A split application of nitrogen fertiliser (urea) was added at the rate of 265kgNha-1 during the autumn and spring of 2008. Emissions of N2O were influenced by rainfall events and seasonal temperatures during 2007 and the fertilisation events in 2008. Annual N2O emissions from the lychee canopy increased from 1.7kgN2O-Nha-1yr-1 for 2007, to 7.6kgN2O-Nha-1yr-1 following fertiliser application in 2008. This represented an emission factor of 1.56%, corrected for background emissions. The timing of the split application was found to be critical to N2O emissions, with over twice as much lost following an application in spring (2.44%) compared to autumn (EF: 1.10%). This research suggests that avoiding fertiliser application during the hot and moist spring/summer period can reduce N2O losses without compromising yields.
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This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.
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Background The Environments for Healthy Living (EFHL) study is a repeated sample, longitudinal birth cohort in South East Queensland, Australia. We describe the sample characteristics and profile of maternal, household, and antenatal exposures. Variation and data stability over recruitment years were examined. Methods Four months each year from 2006, pregnant women were recruited to EFHL at routine antenatal visits on or after 24 weeks gestation, from three public maternity hospitals. Participating mothers completed a baseline questionnaire on individual, familial, social and community exposure factors. Perinatal data were extracted from hospital birth records. Descriptive statistics and measures of association were calculated comparing the EFHL birth sample with regional and national reference populations. Data stability of antenatal exposure factors was assessed across five recruitment years (2006–2010 inclusive) using the Gamma statistic for ordinal data and chi-squared for nominal data. Results Across five recruitment years 2,879 pregnant women were recruited which resulted in 2904 live births with 29 sets of twins. EFHL has a lower representation of early gestational babies, fewer still births and a lower percentage of low birth weight babies, when compared to regional data. The majority of women (65%) took a multivitamin supplement during pregnancy, 47% consumed alcohol, and 26% reported having smoked cigarettes. There were no differences in rates of a range of antenatal exposures across five years of recruitment, with the exception of increasing maternal pre-pregnancy weight (p=0.0349), decreasing rates of high maternal distress (p=0.0191) and decreasing alcohol consumption (p<0.0001). Conclusions The study sample is broadly representative of births in the region and almost all factors showed data stability over time. This study, with repeated sampling of birth cohorts over multiple years, has the potential to make important contributions to population health through evaluating longitudinal follow-up and within cohort temporal effects.
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Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.
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Background Commercially available instrumented treadmill systems that provide continuous measures of temporospatial gait parameters have recently become available for clinical gait analysis. This study evaluated the level of agreement between temporospatial gait parameters derived from a new instrumented treadmill, which incorporated a capacitance-based pressure array, with those measured by a conventional instrumented walkway (criterion standard). Methods Temporospatial gait parameters were estimated from 39 healthy adults while walking over an instrumented walkway (GAITRite®) and instrumented treadmill system (Zebris) at matched speed. Differences in temporospatial parameters derived from the two systems were evaluated using repeated measures ANOVA models. Pearson-product-moment correlations were used to investigate relationships between variables measured by each system. Agreement was assessed by calculating the bias and 95% limits of agreement. Results All temporospatial parameters measured via the instrumented walkway were significantly different from those obtained from the instrumented treadmill (P < .01). Temporospatial parameters derived from the two systems were highly correlated (r, 0.79–0.95). The 95% limits of agreement for temporal parameters were typically less than ±2% of gait cycle duration. However, 95% limits of agreement for spatial measures were as much as ±5 cm. Conclusions Differences in temporospatial parameters between systems were small but statistically significant and of similar magnitude to changes reported between shod and unshod gait in healthy young adults. Temporospatial parameters derived from an instrumented treadmill, therefore, are not representative of those obtained from an instrumented walkway and should not be interpreted with reference to literature on overground walking.