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Writing differently in Management Learning
No full textWriting differently exemplifies the best of Management Learning and the creative, innovative, and provocative research that calls this journal home. We look at the special role the journal has played in fostering a place where writing differently can flourish, and the unique contributions it has made to the broader writing differently movement in management and organisation studies. We tell the story of writing differently in Management Learning in two oscillating narratives. These narratives can be read separately or together, as they tell a similar story but in unique ways. The first is a more academic exploration. The second is a series of personal reflections on our assorted experiences (as an author or co-author, an editor, a doctoral student, an early career researcher, and a professor), in the processes of writing differently with Management Learning. Ultimately, we hope this overview will inspire you to see where the words can take you
A framework for analysis of curriculum pendulum swings: Comparing curriculum reform in England, Wales, and New Zealand
No full text‘Pendulum swings’ from one vision of curriculum to another are increasingly frequent and are likely to rise in number, given the growing polarisation in society. However, such swings have rarely been the focus of academic discussion. We know little about the initiating conditions and the processes which characterise them, and there has been insufficient consideration of their effects. Our aim in this article is therefore to create an analytic frame for the study of curriculum pendulum swings. We develop this through an initial comparative study of recent curriculum reform in three jurisdictions—England, Wales, and Aotearoa New Zealand. We propose a framing through five axes to help think about rapid curricular reform and examine the extent to which these three jurisdictions ‘swung’ between these axes. Our analysis revealed some common features of these pendulum swings: (1) they were underpinned by an initial, oversimplified educational ‘crisis narrative’ that challenges the legitimacy of the extant curriculum; (2) solutions to this ‘crisis’ were framed in binary terms; and (3) social actors beyond the government (such as think tanks and teachers' professional organisations) often had significant influence, including at times, leading to a ‘counter-swing’. We conclude with some critical reflections, inviting others to strengthen or critique our initial framings and analysis to advance a new focus in curriculum studies
Under what climate conditions were the New Zealand subantarctic islands glaciated?
No full textMountain glaciers are highly sensitive to climatic changes, making them key indicators for reconstructing past climate conditions. This study focuses on the New Zealand subantarctic Auckland and Campbell archipelagos, where geomorphological evidence of past glaciation provides rare insights into past terrestrial climate in the Southern Ocean. Using a 2D glacier model, we explored the temperature, precipitation, and seasonality conditions necessary for different glaciation extents on these islands. Our findings suggest that the Auckland Islands, with higher topography and greater precipitation, are more prone to glaciation than Campbell Island. We find that the most recent period of glaciation occurred in a climate that was 6–7 °C below mid-20th century levels, while the islands were covered by ice caps at temperatures more than 8 °C lower (assuming present day precipitation). Increased temperature seasonality relative to present requires further temperature reductions to achieve equivalent ice volumes, underscoring the sensitivity of glacier mass balance to summer temperatures. Our results provide a refined understanding of glaciation in the southwest Pacific sector of the Southern Ocean and offer a framework for assessing global climate model simulations of past climates. However, the climatic implications of the glacial record in these islands remain uncertain without precise dating of past glaciation events
The Effects of Ecological Restoration on Nitrogen Partitioning in Wetland Ecosystems
No full textNitrogen (N) is essential for plant growth, but excessive inputs from fertilisers, livestock waste, and non-native N-fixing plants can overwhelm ecosystems. Wetlands, often referred to as “nature’s kidneys”, play a key role in buffering excess N. However, despite their importance, over 90% of New Zealand’s wetlands have been lost or degraded, and our understanding of how wetland condition influences N pools and fluxes remains limited. Ecological restoration is the process of repairing human-altered ecosystems to resemble their approximate natural structure and function. Research on N dynamics in restored wetlands, particularly those converted from agroecosystems, is sparse. Wetland swamp forests, despite having the highest N retention capacity among wetland types, also remain largely understudied. My thesis aimed to address these knowledge gaps by examining how ecological restoration affects N dynamics (pools and fluxes) across three wetland states: unrestored wetlands (actively disturbed by agriculture), restored wetlands (undergoing active restoration following agriculture), and remnant wetlands (mature swamp forest). I sampled soils, leaves, roots, wood, and bark from 19 wetlands across the Wairarapa region of New Zealand. Samples were analysed for percent N (%N) and δ¹⁵N values, with soils additionally analysed for mineral and microbial N. I hypothesised that (1) plant tissue %N would be highest in remnant wetlands, due to greater plant functional diversity and biomass; (2) soils in unrestored wetlands would have higher total N and mineral N content, but lower microbial N, due to different N source inputs, reduced plant biomass, and lower amounts of soil organic matter storing less N; (3) plant tissue δ¹⁵N values would be lowest in remnant wetlands, followed by restored and unrestored wetlands, mirroring dominant N source inputs; and (4) soil δ¹⁵N values would show the same pattern, with remnant wetlands having the lowest δ¹⁵N values due to greater soil organic matter and microbial diversity, which reduces ¹⁴N loss. I found total ecosystem N ranged from 504 g m⁻² (± 82.2 SE) in unrestored wetlands to 654 g m⁻² (± 156 SE) in restored wetlands and 906 g m⁻² (± 118 SE) in remnant wetlands. However, these differences were not statistically significant due to high variability among wetlands of each state. When total ecosystem N was partitioned, linear models showed remnant wetlands stored significantly more N in above-ground biomass (herb and canopy foliage) than restored and unrestored wetlands. Surprisingly, soil percent N and mineral N (nitrate (NO₃⁻) and ammonium (NH4+)) did not differ significantly among wetland states, but when bulk density of soil was accounted for, the soil mineral fraction NO₃⁻ was greatest in unrestored wetlands. Microbial N differed significantly by wetland state, with remnant wetlands holding more N in microbial biomass than unrestored and restored wetlands. Remnant wetlands had the lowest δ¹⁵N values in soil, coarse roots, fine roots, and canopy foliar N pools. Herb layer δ¹⁵N did not differ between remnant and restored wetlands but was significantly higher in unrestored wetlands. Soil and fine root δ¹⁵N values were similar between unrestored and restored wetlands. Overall, my findings highlight the complex responses of wetland N pools and fluxes to ecosystem state. Restoration increases N uptake and long-term N storage, but restored wetlands still hold less N than remnant wetlands, possibly indicating ongoing capacity for further uptake as restored wetlands mature. These results underscore the critical importance of protecting and restoring wetlands to remove excess N from landscapes, safeguarding freshwater and human health and enhancing landscape resilience.</p
Genetic Programming Hyper-Heuristic for Cost and Energy Efficient Container Allocation and Migration in Global Cloud Data Centres
No full textContainers have become a popular method for deploying software applications, especially in cloud data centres. Individuals and businesses can rent server space in these centres to run their containerised applications, and even configure them to automatically start or stop in response to fluctuating demand. The task of placing containers onto virtual machines (VMs), and VMs onto physical machines (PMs), is handled by cloud service providers rather than end users. These providers aim to minimise operational costs through efficient resource management. However, because a container’s resource requirements rarely align perfectly with those of a specific VM, careful decisions must be made about placement. Poor allocation can lead to underutilised resources and, as a result, increased energy costs.There are a number of existing methods to solve this Container allocation problem. However, they neglected two key aspects of real world data centres. First, many studies do not account for Containers shutting down and leaving the data centre and how this effects future Container allocations. Recent statistics have shown that many containers only run for a few hours at most before completing their task and shutting down. While some existing research considered migrating Containers between different VMs, this is rarely done for energy efficiency reasons. This aspect, combined with frequent container departures, creates an opportunity to migrate remaining containers into the newly freed space. This can help reduce the overall number of virtual VMs and PMs needed at any given time, hereby reducing the overall energy expenditure of cloud data centres.A second important but often overlooked aspect is the global distribution of data centres. Reducing the energy consumption of a given data centre is often the immediate approach to reducing the cost of running a set of containers. However power costs, specifically in the wholesale market, are variable and change throughout the day in any particular location and are often lower at night. Containers could be moved between data centres in response to different power prices to achieve a lower overall cost than using a single data centre.This thesis presents two novel Genetic Programming Hyper-Heuristic (GPHH) algorithms for energy- and cost-efficient container allocation and migration in cloud data centres. The first algorithm addresses dynamic resource allocation within a single data centre, incorporating real-world considerations such as containers leaving the system and energy-aware migration into newly freed resources. The second algorithm extends the model to a global setting, accounting for geographically distributed data centres with variable, time-dependent power costs. Both algorithms use three co-evolved GPHH trees to guide container-to-VM allocation, VM-to-PM placement, and container migration decisions. To support these innovations, we enhance existing datasets to include container lifetimes and develop a new dataset capturing regional electricity price fluctuations. A custom simulator is also constructed to evaluate dynamic scenarios involving container departures and inter-data-centre migrations. Experimental results demonstrate that our GPHH-based solutions significantly outperform several state-of-the-art methods in reducing energy usage and operational costs, offering practical benefits for real-world cloud infrastructure management.</p
Identifying potentially suitable and accessible refugia to mitigate impacts of an emerging disease on a rare tree
No full textIdentifying refugia from emerging threats is vital to ensure the persistence of rare and threatened species, but modeling habitat distribution for these species is challenging and the role of people in refuge management is rarely considered. Myrtle rust is an emerging infectious disease that represents a grave threat to the rare wetland tree species maire tawake (Syzygium maire) in Aotearoa New Zealand. We combined high-resolution hydrological modeling with integrated species distribution modeling of new and existing S. maire records to identify the extent of habitat in the capital city region available for conservation management. We mapped 2 myrtle rust infection risk scenarios throughout the region to identify areas of relatively low disease risk and used distance of S. maire habitat to the nearest road as a proxy for human accessibility to the area. We identified 1230 km2 of S. maire habitat (waterlogged areas) in the region. In these areas, 1–52 km2 were the most feasible for conservation because they were predicted to support high relative abundances of S. maire, were accessible by road, and offered lower disease risk. However, protecting trees only in low-risk or accessible refugia was predicted by the species distribution model (SDM) to be insufficient to maintain the regional population as the myrtle rust pandemic proceeds. Our highly local approach to refugia modeling enabled rapid collection of new records of a rare species for species distribution modeling and access to high-resolution topographical data for hydrological modeling. However, limitations to understanding the biophysical limits of myrtle rust and S. maire included model-based constraints on inference, poor spatial precision of historical species records, insufficient information on groundwater drainage, and uncertainty in quantifying disease risk. The success of regional conservation efforts for this species will likely depend on human intervention to increase S. maire occupancy in low-risk habitats and to manage myrtle rust. We therefore recommend leveraging human–nature interactions in areas to create, expand, and protect habitat for rare species in a rapidly changing world
Understanding Seasonality and Stock Structure in Snapper (Chrysophrys Auratus) From the West Coast of New Zealand
No full textFisheries management is very often supported by stock assessments. An adequate understanding of stock structure is key for accurately evaluating stock status with stock assessments. It is also important to understand the seasonal migration and connectivity patterns of substocks, as exposure and vulnerability to fishing pressure is likely to differ among substocks. The present research investigated seasonality and stock structure in snapper (Chrysophrys auratus) on the west coast of New Zealand using spatio-temporal models fitted to commercial fishery data implemented through the vector autoregressive spatio-temporal (VAST) modelling platform. We used Poisson-link delta models that combined models for fish numbers per unit of area and average weight per fish to predict snapper biomass-densities over time and space. Models were fitted to commercial bottom trawl biomass catch rate data separately for three seasons: spring (October–December), summer (January–April), and winter (May–September). The models included a fixed year effect, random effects for spatial and spatio-temporal variation, catchability covariates, and a vessel-year random effect. The models predicted snapper densities, which were used to produce summary metrics—including median log-density, interannual variability in log-density, and long-term abundance trend—as well as to conduct hierarchical clustering to group spatial areas into clusters. Results indicated clear seasonal differences in snapper dynamics between spring, summer, and winter. We also found noticeable differences between three spatial strata on the west coast of New Zealand, which is consistent with previous findings from stock assessments, genetic studies, and phenology studies.</p
Simulating Geomagnetically Induced Currents using Empirical Magnetotelluric Impedances in Aotearoa New Zealand
No full textThis thesis is a comprehensive guide outlining physics-based simulations performed to identify vulnerabilities in Aotearoa New Zealand’s power grid network during space weather events. A growing understanding of the influences of space weather on technological systems has captured the attention of scientists spanning disciplines from astrophysics, atmospheric sciences, and geophysics. Research within these fields have indicated that the risk of large scale magnetic storms to ground based infrastructure is, to a large degree, dependent on the geology, were regions underlain by rocks having high electrical resistivity are most at risk. The electric currents induced in infrastructure and man-made technology are referred to as geomagnetically induced currents (GIC). These can result in loss of communications, pipeline corrosion, and damage to transformers, and in extreme cases blackout occurrences. The role of improving the earth conductivity models in space weather hazard studies has been underway in Aotearoa New Zealand for several years with the increasing acquisition of long period magnetotelluric (MT) data.This work incorporates GIC calculations from 62 MT impedance measurements collected in the South Island. GIC were computed using the MT data for several historical geomagnetic storms where resulting time series are compared to the direct measurements made at transformers by Transpower Ltd. Thus far, results imply that the models using the long period MT data yield GIC proximal to the measured peak storm values, more so than the previous models. The validation of this technique is a fundamental step in carrying out the assessment of GIC in the northernmost North Island, a region where no MT measurements existed, until now. Recent acquisition of 55 MT sites spanning Northland to the Waikato region are used in con- junction with legacy MT data to calculate GIC in the North Island to assess which substation transformers are most at risk to space weather hazards.</p
Using water-isotope evidence from Antarctic ice cores to determine Last Interglacial ice sheet changes
No full textThe 21st Conference of the Parties (COP21) to the United Nations Framework Convention on Climate Change (UNFCCC) highlighted the critical thresholds of 1.5°C and 2°C global warming above pre-industrial levels (Hoegh-Guldberg et al., 2018) , emphasizing their significance for global climate stability. The Last Interglacial (LIG; 116–130 kyr BP [kilo years before present]) was approximately 1±1°C warmer than the preindustrial (PI) global surface air temperature (SAT) making it an excellent example to assess impacts of a Paris Agreement world. At the peak of the LIG, global mean sea level (GMSL) was 1.2-8.7 m higher than present level, with the Antarctic Ice Sheet (AIS) contributing substantially, potentially accounting for up to 7.7 m of GMSL rise. However, significant debate remains regarding the extent of AIS retreat and AIS elevation changes during the LIG, particularly in West Antarctica. Reconstructing past climates provides valuable insights to improve predictions of AIS morphology, the associated GMSL rise, and the implications for a warmer future. Aiming to progress the understanding of plausible AIS elevation changes from LIG to PI, stable water isotope 18O data are used here as a paleothermometer to assess the isotopic response to AIS elevation changes across a range of plausible scenarios. The water vapour is transported from open ocean regions onto the continent and deposited as precipitation, linking large-scale circulation and ice sheet surface conditions to the recorded isotopic signal. This work takes advantage of six available, well-dated East Antarctic cores and two unpublished West Antarctic ice cores to assess the isotopic relationship with elevation changes by using isotope-enabled simulations. The thesis specifically aims to address three scientific questions to investigate the evolution of AIS configurations during the LIG: 1. How did the change in AIS configuration impact 18O concentrations during the LIG?2. What is the most plausible AIS configuration for the LIG? 3. What are the differences in relationships between changes in 18O, elevation, and surface temperature across the LIG and last glacial maximum periods?To explore the isotopic responses to elevation changes, a series of isotope-enabled simulations were conducted using the HadCM3 general circulation model. Each experiment was initialized using plausible LIG AIS configurations from previous ice sheet modelling experiments. Through comparing the modelled LIG-to-PI Δ18O to the ice core measurements in Antarctica, the results show that these simulations capture less than 10% of core-mean Δ18O changes observed in East Antarctica. Even though these simulations cannot fully account for the observed 18O signals, they do capture the geographical pattern of Δ18O across Antarctica. The remaining discrepancies between the modelled and observed core-mean Δ18O reveal that LIG simulations need to consider a warmer Southern Ocean, with reduced Antarctic sea ice to reproduce and understand the observed 18O. In the next step, isotope-enabled simulations incorporating AIS elevations were used to explore the most plausible AIS configurations across the LIG. Conducting thousands of simulations for all published AIS morphologies is computationally prohibitive; therefore, a novel Gaussian Process (GP) emulator was developed, inspired by previous methodologies and its application to LGM AIS reconstruction. This study also accounted for the warmer Southern Ocean boundary conditions, which were crucial for reproducing the magnitude of LIG warming over Antarctica. A mathematical parameterization was applied to define AIS morphology and ocean conditions in HadCM3 simulations. Using the modelled Δ18O, the GP emulator was successfully constructed to predict 18O responses to elevation changes in Antarctica. 18O measurements from 130 to 121 ky at six Antarctic ice core sites were then used to constrain the emulator, deriving the most plausible AIS evolution across the LIG, which closely matched the observed isotopic signals. The evolution suggests higher WAIS topographies from 129 to 126 ky compared to previously published works, with ice sheet growth in East Antarctica. The estimated global mean sea level (GMSL) equivalent, considering only elevation changes, indicates two periods of WAIS lowering around 129 and 126 ky. During the early LIG, WAIS was the primary contributor to GMSL changes, while EAIS played a dominant role in the later LIG. However, as Glacial Isostatic Adjustment (GIA) was not considered, GMSL estimates may be incomplete or underestimated.Understanding the interactions between Δ18O, Δelevation, and ΔSAT is crucial for reconstructing past AIS changes and temperatures using isotopic measurements, particularly for the LIG and LGM periods. To further investigate the interpretation of 18O in the past, this study analysed changes in elevation, SAT, and 18O across different climates and regions using plausible and idealised LIG simulations (by HadCM3), as well as a subset of LGM simulations that shared AIS morphologies from a previously published study with the isotope-enabled ECHAM5 atmospheric and oceanic general circulation models (ECHAM5-wiso). Model–data comparisons of LGM-to-PI Δ18O show that HadCM3 underestimates the isotopic difference between the LGM and preindustrial periods, as compared to both ECHAM5-wiso simulations and ice core observations. This is likely due to a SAT warm bias over the Southern Ocean, which limits distillation, the progressive removal of heavy isotopes from water vapour as it cools and precipitates over the continent. The ECHAM5-wiso results suggest unusual isotopic behavior compared to its updated version, ECHAM6-wiso. To ensure consistency in modeled physics, the following analysis of Δelevation - ΔSAT - Δ18O relationships used all HadCM3 simulations. The relationship values remain relatively uniform at inland ice core sites, such as Vostok (VK), Dome Fuji (DF), EPICA Dome C, and EPICA Dronning Maud Land (EDML) but exhibit greater variability in coastal regions. Additionally, Δ18O–ΔSAT relationships differ between the EAIS and WAIS, with statistically steeper slopes in the west and shallower slopes in the east. These regional differences likely reflect variations in local climatic factors modulating the relationship at specific coastal sites. The use of LGM or modern Δelevation - ΔSAT - Δ18O relationships to LIG climate may lead to an overestimation of AIS changes inferred from measured 18O at ice core sites.</p
Do Obesity Classifications Create the Obesity Paradox? A Scoping Review of Obesity Definitions Applied in Sepsis Research
No full textObesity appears to be associated with improved health outcomes in patients with sepsis, a phenomenon termed the obesity paradox. However, the potential influence of varying operational definitions of obesity on clinical outcomes within this paradox remains inadequately characterised. This scoping review aimed to identify, analyse, and synthesise the methodological approaches to obesity definition employed in sepsis research. A systematic literature search was conducted in August 2023 across MEDLINE, Embase, CINAHL, and CENTRAL databases. This review included original articles, systematic reviews, and meta-analyses reporting on adult patients with both obesity and sepsis. After removing 60 duplicates, 430 citations were screened, and 68 met the inclusion criteria. Among studies on the obesity paradox, 90.5% supporting and 88.6% refuting it employed body mass index-based definitions, with approximately three-quarters using retrospective designs. Studies supporting the obesity paradox identified patients with obesity as younger, predominantly female, and with higher comorbidity rates. In contrast, studies refuting the paradox reported more diverse age and sex distributions, yet consistently noted elevated chronic disease prevalence in patients with obesity. Both groups found similar or higher illness severity scores among patients with obesity. The lack of methodological rigour in obesity definitions within clinical research may contribute to the obesity paradox. Future studies should critically evaluate measurement methods and definitional variability to clarify their impact on clinical outcomes
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