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Characterization of sugar accumulation dynamics in grapes and the factors influencing this process at local scale
Get PDFDetermining the sugar concentration in grape berries is essential for winegrowers, as it enables them to estimate the alcohol content in the final wine and optimize the harvest date. In the face of climate change and rising temperatures, understanding the factors affecting sugar accumulation dynamics is crucial, to adapt viticultural practices and maintain wine quality. This study aims to analyze the growth and environmental factors involved in sugar accumulation in grapes, using data collected in Saint-Émilion, Pomerol, and their satellite appellations (Bordeaux, France)
Freshwater quality modeling in Aotearoa New Zealand: Current practice and future directions
Get PDFWater quality modeling at the catchment scale is vital for addressing environmental and societal challenges. In two workshops preceding this article, we revealed issues in current modeling practices leveraging New Zealand as a case study. Predominant were low trust in models, lack of transparency, and models unfit for purpose. This article uses a root-cause analysis to explore these issues, identify causes, and propose solutions. We find that current best practices and research are a good foundation but insufficient to fulfill our freshwater research and management needs. We advocate for long-term national strategies with centralized funding, standardized documentation, data, models, evaluation techniques, and communication methods, along with a centralized open-access platform for collaboration. Our vision is to streamline modeling projects, enhance the accessibility and reliability of models, and foster more effective decision-making processes for the sustainable management of freshwater ecosystems
Temporal stability of preferences: The case of COVID-19 vaccines in Australia and New Zealand
Get PDFThis paper introduces a novel two-level Latent Class (LC) structure to investigate the temporal stability of preferences, allowing individuals to switch classes over time. The model is used to investigate the temporal stability of COVID–19 vaccine preferences in Australia (AUS) and New Zealand (NZ) during 2020-2021. Through online experiments on vaccine choices, stated choice data is collected across three waves from the general population in both countries. The LC estimation identifies three distinct preference classes: an “Impatient” group, with greater sensitivity to waiting time (AUS: 46%, NZ: 31%), a “Price Sensitive” group (AUS: 41%, NZ: 56%), and a “Vaccine Hesitant” group (AUS: 13%, NZ: 13%). Across waves, preferences for COVID-19 vaccines remain stable, with the probability of respondents remaining in the same class over three waves being 0.62 for Australia and 0.61 for NZ. Changes in preferences are significantly linked to variations in individuals’ socioeconomic status and COVID–19 policy responses during the survey period
Beyond the enclave: Workforce mobility and livelihoods in New Caledonia
No full textRoundtable: Mining, Mobility, and Social Change in Melanesia and the Andean Region: Comparative
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Characterisation of the ovine KRTAP36-1 gene in Chinese tan lambs and its impact on selected wool traits
Get PDFWool has distinctive biological, physical, and chemical properties that contribute to its value both for the sheep and in global fibre and textile markets. Its fibres are primarily composed of proteins, principally keratin and keratin-associated proteins (KAPs). To better comprehend the genes that underpin key wool traits, this study examined the keratin-associated protein 36-1 gene (KRTAP36-1) in Chinese Tan lambs. We identified three previously reported alleles of the gene (named A, B and C) that were present in the lambs studied, with genotype frequencies as follows: 2.0% (n = 5; AA), 6.9% (n = 17; AB), 13.8% (n = 34; AC), 8.9% (n = 22; BB), 33.4% (n = 82; BC) and 35.0% (n = 86; CC). The frequencies of the individual alleles in the Chinese Tan lambs were 12.4%, 29.1% and 58.5% for alleles A, B and C, respectively. The three alleles were in Hardy–Weinberg Equilibrium. In an association analysis, it was revealed that allele C was associated with variation in the mean fibre curvature of the fine wool of the Chinese Tan lambs, but this association was not observed in their heterotypic hair fibres. This finding suggests that KRTAP36-1 might be differentially expressed in the wool follicles that produce the two fibre types, and that along with other KRTAP genes, it may be involved in determining fibre curvature and the distinctive curly coat of the lambs
Pastoral hazardscapes in Aotearoa New Zealand: gender, land dispossession, and dairying in a warming climate
Get PDFThe impacts of climate change are exposing vast stretches of dairy farms in the Waikato region of Aotearoa New Zealand to floods, droughts, and seawater inundation. This article describes how the Waikato ‘hazardscape’—co-created through processes of land dispossession, dairy intensification, and climate change—shapes the vulnerabilities and capacities of different dairy farming groups, specifically women, intergenerational, and Indigenous Māori farmers. Our findings show that while contemporary Māori owned dairy farms are sometimes situated on sub-optimal land as a result of decades of land dispossession, their size and collective ownership structures can support greater flexibility, diversification, and adaptive decision-making processes. The longevity and financial security of many non-Indigenous intergenerational dairy farms means they are also more able to invest in long-term adaptation decisions, albeit often tied to the continuation of dairying. Furthermore, within these farm units, dairy farm women make a significant contribution to adaptation goals, yet their unique adaptation strategies and requirements are often overlooked, particularly in industry-run settings. The article foregrounds how achieving equitable adaptation in Aotearoa New Zealand’s agricultural landscape will require more attention to the gendered impacts of climate change, and the ways in which access to land (or lack thereof) supports or creates barriers to flexible adaptation. We call for more diverse and inclusive platforms for adaptation planning that are receptive to envisioning alternative, more equitable, and ultimately lower risk ways of co-existing with hazards, while managing productive lan
Understanding university students' AI adoption and usage: Key determinants and policy implications
No full textAs artificial intelligence (AI) becomes increasingly embedded in higher education, students are adopting AI tools to support their learning, yet little is known about the determinants of this engagement. This study draws on survey data from universities in China, Indonesia, and New Zealand to examine demographic, social, and academic factors influencing AI adoption and usage intensity. Findings highlight critical disparities shaped by age, gender, discipline, and digital access. This session will examine the pedagogical and ethical implications of AI in higher education and offer evidence-based recommendations for embedding AI literacy and promoting equitable, inclusive engagement with AI across discipline
Enhancing sampling of dissolved N₂O in aquatic systems: Field-deployable automated gas bag collection system
Get PDFMeasuring dissolved nitrous oxide (N₂O), a potent greenhouse gas and contributor to ozone depletion, is essential for understanding its aquatic dynamics and informing climate mitigation and emission estimates. Dissolved N₂O concentration measurements typically involve headspace equilibration of water samples in sealed containers, followed by gas chromatography analysis. This manual method is labor-intensive and often requires toxic preservatives. Alternatively, air-water exchangers coupled with laser analyzers provide high-precision continuous measurements but lack sample storage capabilities and require frequent relocation and setup to capture spatiotemporal variations. We developed an automated gas bag (AGB) collection system for collecting N₂O samples (AGB-N₂O) from discrete water samples, which could then be analyzed for concentration using laser analyzers. This method combines the field-friendly sample collection and storage of the manual method with the precision of exchangers and laser analyzers. Field experiments tested four setups of exchangers with varying internal volumes (2 L vs. 1 L) and water flow rates (small nozzle: 0.75 L min¯¹ vs. medium nozzle: 3 L min¯¹) at sites with low vs. high N₂O concentrations (13 nM vs. 95 nM). The 2-L exchanger with a medium nozzle achieved the fastest equilibration times of 2.25 and 0.08 min for high and low N₂O sites, respectively. The AGB-N₂O showed comparable results to the manual method for measuring dissolved N₂O concentrations (p > 0.05). However, the AGB-N₂O demonstrated significantly lower standard deviations, indicating higher precision and consistency. These findings demonstrate the suitability of the AGB-N₂O for diverse aquatic environments, offering reliable and efficient N₂O measurements
Artificial intelligence marketing and leadership commitment: A solution for resource-constrained e-commerce firms
No full textThis study aims to investigate how implementation barriers impede the development of AI-driven marketing agility in e-commerce SMEs, with a particular focus on the moderating role of leadership commitment. Drawing on dynamic capabilities theory (DCT), we examined the relationships between technical complexity, cost implications, talent gaps, organizational resistance and marketing agility while exploring how leadership commitment moderates these relationships in the context of Chinese e-commerce SMEs.
Design/methodology/approach
We employed a mixed-methods approach combining two state-of-the-art methods: partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) analysis. Data were collected through a structured questionnaire from 317 marketing managers in Chinese e-commerce SMEs. The proposed research model was first validated using PLS-SEM to test the hypothesized relationships, followed by ANN analysis to explore nonlinear patterns and the relative importance of the implementation barriers
Findings
Largely in line with existing understanding, technical complexity and organizational resistance demonstrate the strongest negative effects on marketing agility development. However, leadership commitment significantly moderates all hypothesized relationships, weakening the negative impacts of implementation barriers. Triangulated ANN analysis has confirmed the hierarchical importance of these barriers and revealed nonlinear patterns in their relationships with marketing agility, with technical complexity emerging as the most influencial factor.
Originality/value
By reconceptualizing dynamic capabilities in the AI era, the research has revealed that the entire capability development process operates under different laws in technologically discontinuous contexts and introduced a new theoretical lens for understanding digital leadership in technology adoption contexts. Our theoretical advances enable precision interventions for organizations navigating AI implementation challenges in marketing operations
Thermal adaptation of bacterial and fungal growth in a geothermally influenced soil transect
No full textNumerous studies have investigated microbial adaptation to increasing soil temperature, but limitations in experimental design hinder comprehensive understanding. These include short‐term laboratory studies with constant environmental conditions and field studies with few distinct temperature treatments. Here, we utilized a long‐term natural soil geothermal gradient in Aotearoa, New Zealand, ranging in mean annual soil temperature (MAT) from 17°C to 42°C to explore thermal adaptation of microbial growth rates. We collected soil from 28 locations along the gradient and measured bacterial growth rate (via leucine incorporation) at eight temperatures (4°C–45°C) and fungal growth rate (via Ac‐in‐ergosterol) at two temperatures (16°C and 39°C). We then fit Macromolecular Rate Theory and the Ratkowsky equation to estimate the temperature minimum (), optimum (), and inflection point () for bacterial growth, and a temperature sensitivity index to compare relative fungal and bacterial growth rates. We found predictable changes in thermal adaptation of bacterial growth along the geothermal gradient with temperature response curves shifting 0.22°C–0.27°C per 1°C increase in MAT regardless of the temperature metric (i.e., , , and ) used. Thermal adaptation of bacterial and fungal growth increased roughly in parallel. We also compared the bacterial growth results to published temperature response data of microbial respiration (with added glucose) from this geothermal gradient. Rates of thermal adaptation for bacterial growth and microbial respiration were similar, suggesting synchronicity across microbial processes. The less than 1°C change in all measured temperatures metrics per degree increase in MAT resulted in microbial growth and activity closer to in situ temperatures at high soil temperatures and lower than in situ temperatures under non‐elevated soil temperatures. Overall, our results highlight the use of geothermal gradients and appropriate temperature models in studying thermal adaptation of soil microbial processes; the predictability of results also underscores potential for incorporating microbial thermal adaptation into soil carbon modeling effort