| 1. |
- Jutfelt, Fredrik, et al.
(author)
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Two-current choice flumes for testing avoidance and preference in aquatic animals
- 2017
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In: Methods in Ecology and Evolution. - : John Wiley & Sons. - 2041-210X. ; 8:3, s. 379-390
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Research review (peer-reviewed)abstract
- Aquatic chemical ecology is an important and growing field of research that involves understanding how organisms perceive and respond to chemical cues in their environment. Research assessing the preference or avoidance of a water source containing specific chemical cues has increased in popularity in recent years, and a variety of methods have been described in the scientific literature. Two-current choice flumes have seen the greatest increase in popularity, perhaps because of their potential to address the broadest range of research questions.Here, we review the literature on two-current choice flumes and show that there is a clear absence of standardized methodologies that make comparisons across studies difficult. Some of the main issues include turbulent flows that cause mixing of cues, inappropriate size of choice arenas for the animals, short experiments with stressed animals, failure to report how experiment and researcher biases were eliminated, general underreporting of methodological details, underutilization of collected data and inappropriate data analyses.In this review, we present best practice guidelines on how to build, test and use two-current choice flumes to measure the behavioural responses of aquatic animals to chemical cues, and provide blueprints for flume construction. The guidelines include steps that can be taken to avoid problems commonly encountered when using two-current choice flumes and analysing the resulting data.This review provides a set of standards that should be followed to ensure data quality, transparency and replicability in future studies in this field.
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| 2. |
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| 3. |
- Malmaeus, Mikael, et al.
(author)
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Basic Income and Social Sustainability in Post-Growth Economies
- 2020
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In: Basic Income Studies. - : Walter de Gruyter GmbH. - 2194-6094 .- 1932-0183. ; 15:1
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Journal article (peer-reviewed)abstract
- A central task in efforts to identify pathways to ecologically and socially sustainable economies is to reduce inequality and poverty while reducing material consumption, which has recently inspired future post-growth scenarios. We build a model to explore the potential of a universal basic income (UBI) to serve these objectives. Starting from the observation that post-growth trajectories can take very different forms we analyze UBI in two scenarios advanced in the literature. Comparing UBI in a "local self-sufficiency" economy to a UBI in an "automation" economy, we show that although both scenarios satisfy central sustainability criteria, the impact of a UBI would differ greatly between these contexts. Our analysis shows that a UBI is less compatible with a labor-intensive local self-sufficiency economy than a capital-intensive, high tech economy. We conclude that the feasibility and attractiveness of a UBI in a post-growth scenario depends greatly on the specific characteristics of the economy.
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| 4. |
- Quesada Montano, Beatriz, et al.
(author)
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Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?
- 2018
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In: Hydrological Processes. - : WILEY. - 0885-6087 .- 1099-1085. ; 32:6, s. 830-846
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Journal article (peer-reviewed)abstract
- Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, such as Central America, hydrological models are an alternative for reproducing historical streamflow series. Additional types of informationto locally observed dischargecan be used to constrain model parameter uncertainty for ungauged catchments. Given the strong influence that climatic large-scale processes exert on streamflow variability in the Central American region, we explored the use of climate variability knowledge as process constraints to constrain the simulated discharge uncertainty for a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty, we first rejected parameter relationships that disagreed with our understanding of the system. Then, based on this reduced parameter space, we applied the climate-based process constraints at long-term, inter-annual, and intra-annual timescales. In the first step, we reduced the initial number of parameters by 52%, and then, we further reduced the number of parameters by 3% with the climate constraints. Finally, we compared the climate-based constraints with a constraint based on global maps of low-flow statistics. This latter constraint proved to be more restrictive than those based on climate variability (further reducing the number of parameters by 66% compared with 3%). Even so, the climate-based constraints rejected inconsistent model simulations that were not rejected by the low-flow statistics constraint. When taken all together, the constraints produced constrained simulation uncertainty bands, and the median simulated discharge followed the observed time series to a similar level as an optimized model. All the constraints were found useful in constraining model uncertainty for anassumed to beungauged basin. This shows that our method is promising for modelling long-term flow data for ungauged catchments on the Pacific side of Central America and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.
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| 5. |
- Quesada Montano, Beatriz, et al.
(author)
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Characterising droughts in Central America with uncertain hydro-meteorological data
- 2019
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In: Journal of Theoretical and Applied Climatology. - : Springer Science and Business Media LLC. - 0177-798X .- 1434-4483. ; 137:3-4, s. 2125-2138
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Journal article (peer-reviewed)abstract
- Central America is frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation, monitoring and forecasting are potentially useful to support water resource management. Drought indices are designed for these purposes, but their ability to characterise droughts depends on the characteristics of the regional climate and the quality of the available data. Local comprehensive and high-quality observational networks of meteorological and hydrological data are not available, which limits the choice of drought indices and makes it important to assess available datasets. This study evaluated which combinations of drought index and meteorological dataset were most suitable for characterising droughts in the region. We evaluated the standardised precipitation index (SPI), a modified version of the deciles index (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), the CRN073 dataset, the Climate Research Unit (CRU), ECMWF Reanalysis (ERA-Interim) and a regional station dataset, and temperature from the CRU and ERA-Interim datasets. The gridded meteorological precipitation datasets were compared to assess how well they captured key features of the regional climate. The performance of all the drought indices calculated with all the meteorological datasets was then evaluated against a drought index calculated using river discharge data. Results showed that the selection of database was more important than the selection of drought index and that the best combinations were the EDI and DI calculated with CHIRPS and CRN073. Results also highlighted the importance of including indices like SPEI for drought assessment in Central America.
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| 6. |
- Samuelsson, Oscar, et al.
(author)
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Gaussian process regression for monitoring and fault detection of wastewater treatment processes
- 2017
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In: Water Science and Technology. - UK : IWA Publishing. - 0273-1223 .- 1996-9732. ; 75:12, s. 2952-2963
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Journal article (peer-reviewed)abstract
- Monitoring and fault detection methods are increasingly important to achieve a robust and resource efficient operation of wastewater treatment plants (WWTPs). The purpose of this paper was to evaluate a promising machine learning method, Gaussian process regression (GPR), at WWTP monitoring applications. We evaluated GPR at two WWTP monitoring problems: estimate missing data in a flow rate signal (simulated data), and detect a drift in an ammonium sensor (real data). We showed that GPR with the standard estimation method, maximum likelihood estimation (GPR-MLE), suffered from local optima during estimation of kernel parameters, and did not give satisfactory results in a simulated case study. However, GPR with a state-of-the-art estimation method based on sequential Monte Carlo estimation (GPR-SMC) gave good predictions and did not suffer from local optima. Comparisons with simple standard methods revealed that GPR-SMC performed better than linear interpolation in estimating missing data in a noisy flow rate signal. We conclude that GPR-SMC is both a general and powerful method for monitoring full-scale WWTPs. However, this paper also shows that it does not always pay off to use more sophisticated methods. New methods should be critically compared against simpler methods, which might be good enough for some scenarios.
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| 7. |
- Schmidt, Lisa, 1958-, et al.
(author)
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Utilizing occupational health services in small-scale enterprises : a 10-year perspective
- 2016
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In: Small Enterprise Research. - : Taylor & Francis Group. - 1321-5906 .- 1175-0979. ; 23:2, s. 101-115
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Journal article (peer-reviewed)abstract
- The aim of this study was to explore how small-scale enterprises (SSEs) utilize occupational health services (OHS) and how the possibility of OHS providers to support occupational health and safety management (OHSM) has developed over a 10-year period. Qualitative interviews were carried out with four OHS providers and their SSE clients, with follow-up interviews being conducted with three of the four OHS providers and their clients after 10 years. The decade saw a change in market conditions for the OHS providers with each becoming larger and developing more effective marketing tools. Despite these changes, the OHS providers had not developed more collaborative or closer relationships with their small enterprise clients. Rather than increasing, the utilization of OHS had declined, with health examinations remaining the most purchased service. In addition, the three OHS providers had not improved their support for OHSM in small enterprises during the decade.
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| 8. |
- Westerberg, Ida, et al.
(author)
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Perceptual models of uncertainty for socio-hydrological systems : a flood risk change example
- 2017
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In: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 62:11, s. 1705-1713
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Journal article (other academic/artistic)abstract
- Characterizing, understanding and better estimating uncertainties are key concerns for drawing robust conclusions when analyzing changing socio-hydrological systems. Here we suggest developing a perceptual model of uncertainty that is complementary to the perceptual model of the socio-hydrological system and we provide an example application to flood risk change analysis.Such a perceptual model aims to make all relevant uncertainty sources - and different perceptions thereof - explicit in a structured way. It is a first step to assessing uncertainty in system outcomes that can help to prioritize research efforts and to structure dialogue and communication about uncertainty in interdisciplinary work.
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