ORCID Profile
0000-0002-7108-0787
Current Organisation
Deakin University Geelong - Waterfront Campus
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Elsevier BV
Date: 10-2016
Publisher: American Society of Civil Engineers (ASCE)
Date: 07-2017
Publisher: SAGE Publications
Date: 29-06-2023
DOI: 10.1177/87569728231180268
Abstract: There is a growing face-value acceptance of optimism bias as the primary cause of transport cost overruns. This article provides a timely review of literature on optimism bias and transport infrastructure project cost overruns. The article identifies significant gaps and unanswered questions about the relationship between optimism bias in project cost appraisal and cases of transport infrastructure cost overruns. The presence and nature of optimism bias in the complex institutional environment of project cost appraisal are largely understudied and not well understood. Consequently, this has significant implications for the development of effective mitigation strategies for improving transport project cost performance.
Publisher: Emerald
Date: 07-07-2020
DOI: 10.1108/ECAM-04-2019-0186
Abstract: Effective inter-organisational relationships are key to engendering innovation and ensuring the successful delivery of infrastructure projects. Relationship-based contracts are thus widely used to stimulate best-for-project ideals and attenuate the otherwise adversarial relationship that often exists between clients and contractors. This study examines the effectiveness and limitations of a project facilitation model as coaching tool for developing conducive inter-organisational relationships for construction project delivery. The study adopts a case-study approach using evidence from triangulated data sources of focus group workshops, semi-structured interviews and document analysis. (1) The facilitation model enabled an environment for psychological safety to be developed, which engendered a platform for effective cooperation for problem-solving and achieving quasi best-for-project ideals. (2) The model provides the mechanism to develop team behaviours that support enhanced performance and create an environment less adversarial and more collaborative than traditional contracting. The novelty of this research is that relationship-based principles have been utilised as part of a traditional design-bid-build contract with lump-sum payment arrangements.
Publisher: Elsevier BV
Date: 11-2018
Publisher: Informa UK Limited
Date: 05-01-2019
Publisher: Informa UK Limited
Date: 13-09-2018
Publisher: Edward Elgar Publishing
Date: 14-07-2023
Publisher: Wiley
Date: 08-12-2022
Abstract: In community ecology, unconstrained ordination can be used to indirectly explore drivers of community composition, while constrained ordination can be used to directly relate predictors to an ecological community. However, existing constrained ordination methods do not explicitly account for community composition that cannot be explained by the predictors, so that they have the potential to misrepresent community composition if not all predictors are available in the data. We propose and develop a set of new methods for ordination and joint species distribution modelling (JSDM) as part of the generalized linear latent variable model (GLLVM) framework, that incorporate predictors directly into an ordination. This includes a new ordination method that we refer to as concurrent ordination, as it simultaneously constructs unconstrained and constrained latent variables. Both unmeasured residual covariation and predictors are incorporated into the ordination by simultaneously imposing reduced rank structures on the residual covariance matrix and on fixed‐effects. We evaluate the method with a simulation study, and show that the proposed developments outperform canonical correspondence analysis (CCA) for Poisson and Bernoulli responses, and perform similar to redundancy analysis (RDA) for normally distributed responses, the two most popular methods for constrained ordination in community ecology. Two ex les with real data further demonstrate the benefits of concurrent ordination, and the need to account for residual covariation in the analysis of multivariate data. This article contextualizes the role of constrained ordination in the GLLVM and JSDM frameworks, while developing a new ordination method that incorporates the best of unconstrained and constrained ordination, and which overcomes some of the deficiencies of existing classical ordination methods.
Publisher: Wiley
Date: 04-05-2021
Abstract: It is common practice for ecologists to examine species niches in the study of community composition. The response curve of a species in the fundamental niche is usually assumed to be quadratic. The centre of a quadratic curve represents a species' optimal environmental conditions, and the width its ability to tolerate deviations from the optimum. Most multivariate methods assume species respond linearly to niche axes, or with a quadratic curve that is of equal width for all species. However, it is widely understood that some species have the ability to better tolerate deviations from their optimal environment (generalists) compared to other (specialist) species. Rare species often tolerate a smaller range of environments than more common species, corresponding to a narrow niche. We propose a new method, for ordination and fitting Joint Species Distribution Models, based on Generalized Linear Mixed‐effects Models, which relaxes the assumptions of equal tolerances. By explicitly estimating species maxima, and species optima and tolerances per ecological gradient, we can better explore how species relate to each other.
Publisher: Wiley
Date: 31-12-2019
DOI: 10.1111/GCB.14904
Abstract: Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to bio ersity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on in idual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
Publisher: Informa UK Limited
Date: 29-01-2019
Publisher: Emerald
Date: 07-04-2014
DOI: 10.1108/JFMPC-06-2013-0027
Abstract: – Drawing on mainstream arguments in the literature, the paper presents a coherent and holistic view on the causes of cost overruns, and the dynamics between cognitive dispositions, learning and estimation. A cost prediction model has also been developed using data mining for estimating final cost of projects. The paper aims to discuss these issues. – A mixed-method approach was adopted: a qualitative exploration of the causes of cost overrun followed by an empirical development of a final cost model using artificial neural networks. – A conceptual model to distinguish between the often conflated causes of underestimation and cost overruns on large publicly funded projects. The empirical model developed in this paper achieved an average absolute percentage error of 3.67 percent with 87 percent of the model predictions within a range of ±5 percent of the actual final cost. – The model developed can be converted to a desktop package for quick cost predictions and the generation of various alternative solutions for a construction project in a sort of what-if analysis for the purposes of comparison. The use of the model could also greatly reduce the time and resources spent on estimation. – A thorough discussion on the dynamics between cognitive dispositions, learning and cost estimation has been presented. It also presents a conceptual model for understanding two often conflated issues of cost overrun and under-estimation.
Publisher: Engineering Sciences Press
Date: 2018
Publisher: Elsevier BV
Date: 07-2018
Publisher: Authorea, Inc.
Date: 20-04-2022
DOI: 10.22541/AU.165045606.66517681/V1
Abstract: Understanding how population dynamics are influenced by species interactions and the surrounding community is crucial for addressing many ecological questions, but requires modelling of complex systems involving direct, indirect and often asymmetric species interactions. Progress in developing multispecies models that can tackle this task is being made in multiple subfields of ecology, often with varying approaches and end goals but also facing shared challenges. We review some of the main challenges and the ways in which they are being addressed, highlighting a wide variety of methods that can support the development of multispecies models for understanding population dynamics. The main challenges that we examine are estimation of species interactions from limited data, the necessity of simplifications, and handling uncertainty in complex, multispecies models. In addition to reviewing a wide variety of approaches and methods for dealing with these challenges, we discuss future directions and make suggestions for how we believe the development of multispecies models for understanding population dynamics can move forward more efficiently.
Publisher: American Society of Civil Engineers (ASCE)
Date: 12-2018
Publisher: Informa UK Limited
Date: 24-07-2014
Publisher: Elsevier BV
Date: 06-2017
Publisher: Cold Spring Harbor Laboratory
Date: 07-10-2020
DOI: 10.1101/2020.10.05.326199
Abstract: It is common practice for ecologists to examine species niches in the study of community composition. The response curve of a species in the fundamental niche is usually assumed to be quadratic. The center of a quadratic curve represents a species’ optimal environmental conditions, and the width its ability to tolerate deviations from the optimum. Most multivariate methods assume species respond linearly to the environment of the niche, or with a quadratic curve that is of equal width and height for all species. However, it is widely understood that some species are generalists who tolerate deviations from their optimal environment better than others. Rare species often tolerate a smaller range of environments than more common species, corresponding to a narrow niche. We propose a new method, for ordination and fitting Joint Species Distribution Models, based on Generalized Linear Mixed-Effects Models, which relaxes the assumptions of equal tolerances and equal maxima. By explicitly estimating species optima, tolerances, and maxima, per ecological gradient, we can better predict change in species communities, and understand how species relate to each other.
Publisher: American Society of Civil Engineers
Date: 13-05-2014
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Knut Anders Hovstad.