Description:
This study describes the use of landscape transition analysis as a means for effective basin management. Land cover transitions from 1995 to 2002 were analyzed using a cross-tabulation matrix for an important economic zone in south-west Victoria, Australia. Specifically, the matrix was used to determine whether the transitions were random or systematic. Random landscape transitions occur when a land cover replaces other land covers in proportion to their availability.
Description:
Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and intercatchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.
Description:
Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and intercatchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.
Description:
Objective: Prior to implementation of a Normal Labour and Birth Bundle (NLBB) at a regional maternity service in Victoria, Australia, this study aimed to understand clinician factors that may influence the uptake, acceptance and use of the NLBB. Design: This was a mixed methods study in which The Theory of Planned Behaviour (TPB) provided the framework for the conduct and analysis of the staff survey and focus groups. Descriptive and multiple regression were used to analyse the survey data and thematic analysis was used for the focus group data. Participants: Participants for the survey and focus groups included clinicians providing publicly funded care and management of labour for women birthing at the health service. Maternity care clinicians were invited to participate in both the survey and the focus groups. Findings: Seventy-six clinicians (88.8%) responded to the survey. Mean scores for TPB constructs were well above the mid-scale score of 4, indicating strong positive attitudes, high levels of self-efficacy and positive social pressure to use the NLBB and strong intentions to use it in the future. Self-efficacy was the strongest independent predictor (beta=0.45, p < 0.001) of intention to use the NLBB (overall model R2 = 0.38). A valued consequence of implementing standardised and objective guidelines, highlighted in the focus groups, was the positive impact on clinicians' confidence in their decision-making. Key conclusions: This study found that midwives and obstetricians were in favour of using a normal labour and birth care bundle and perceived the bundle to align with the expectations of work colleagues and the women they care for. The findings of this study show that clinicians at the health service had strong intentions to use the normal labour and birth care bundle in the future. Implications for practice: Implementation science is important in embedding and sustaining practice change. Understanding staff perceptions is an essential first step of this process. (c) 2018 Elsevier Ltd. All rights reserved.