Month: September 2024
Potential negative impacts of climate change outweigh opportunities for the Colombian Pacific Ocean Shrimp Fishery
Abstract
Climate change brings a range of challenges and opportunities to shrimp fisheries globally. The case of the Colombian Pacific Ocean (CPO) is notable due the crucial role of shrimps in the economy, supporting livelihoods for numerous families. However, the potential impacts of climate change on the distribution of shrimps loom large, making it urgent to scrutinize the prospective alterations that might unfurl across the CPO. Employing the Species Distribution Modeling approach under Global Circulation Model scenarios, we predicted the current and future potential distributions of five commercially important shrimps (Litopenaeus occidentalis, Xiphopenaeus riveti, Solenocera agassizii, Penaeus brevirostris, and Penaeus californiensis) based on an annual cycle, and considering the decades 2030 and 2050 under the Shared Socioeconomic Pathways SSP 2.6, SSP 4.5, SSP 7.0, and SSP 8.5. The Bathymetric Projection Method was utilized to obtain spatiotemporal ocean bottom predictors, giving the models more realism for reliable habitat predictions. Six spatiotemporal attributes were computed to gauge the changes in these distributions: area, depth range, spatial aggregation, percentage suitability change, gain or loss of areas, and seasonality. L. occidentalis and X. riveti exhibited favorable shifts during the initial semester for both decades and all scenarios, but unfavorable changes during the latter half of the year, primarily influenced by projected modifications in bottom salinity and bottom temperature. Conversely, for S. agassizii, P. brevirostris, and P. californiensis, predominantly negative changes surfaced across all months, decades, and scenarios, primarily driven by precipitation. These changes pose both threats and opportunities to shrimp fisheries in the CPO. However, their effects are not uniform across space and time. Instead, they form a mosaic of complex interactions that merit careful consideration when seeking practical solutions. These findings hold potential utility for informed decision-making, climate change mitigation, and adaptive strategies within the context of shrimp fisheries management in the CPO.
Evaluation of accuracy for satellites rainfall datasets compared in ground stations: a case study of duhok governorate, Northern Iraq
Abstract
Providing accurate and reliable rainfall data that can be used and applied in various climate and hydrological studies is essential. This paper aims to assess the accuracy of monthly rainfall data for satellites (climate engine, NASA-POWER) and corresponding data for ground stations, and through spatial mapping and linear measurement of rainfall indicators in Duhok Governorate in northern Iraq. The data evaluation process included the use of some statistical and cartographic methods available within the Jeffrey Amazing Statistics Program (JASP) and Origin Pro software, the evaluation and statistical analysis were conducted during the period from 2003 to 2022. The analysis results indicate that the relationship of ground stations with the climate engine recorded good values (Pbias = 1.24, NSE = 0.93, R = 0.97, Slope = 0.99, KGE = 0.72). However, these values are lower when compared with NASA-POWER (Pbias = 14.09, NSE = 0.55, R = 0.94, Slope = 0.34, KGE = -12.9). Both results indicate a positive relationship between the satellite and the ground data, and in general, all climate stations recorded a high correlation factor in monthly rainfall forecasting. Furthermore, the climate engine’s data were characterized by high rainfall accuracy and quality and were relatively consistent with the observed scale data (ground stations). This study provides new ideas about the methods for selecting rainfall products for climatic and hydrological studies.
Addressing the contradiction between water supply and demand: a study on multi-objective regional water resources optimization allocation
Abstract
As a result of economic development, population growth, accelerated urbanization and the frequent occurrence of extreme weather events, the contradiction between the supply and demand for water resources between regions has become increasingly acute. In order to solve the problem of regional water shortage and irrational utilization, the optimal allocation of water resources has become one of the research hotspots in recent years. In this study, firstly a multi-objective integrated allocation model of regional water resources is constructed by introducing social, economic, and environmental objective functions to address the complex uncertainties in the water resources system. Secondly, the standard whale algorithm is optimized and improved by introducing chaotic population initialization, chaotic convergence factor, adaptive Lévy flight and improved positive cosine mechanism. The model parameters, including the 2025 water resource demand and supply, pollutant discharge content, and unit water supply cost coefficients, are set by consulting the Shanxi Water Resources Bulletin 2022, the Shanxi Provincial Department of Water Resources, and the Report on the Work of the Shanxi Provincial Government 2023. Subsequently, the improved whale algorithm is utilized for the optimization of the predicted water resources for various target years in the future in the lower reaches of the Fen River in Shanxi Province, China. This ultimately yields optimized allocation results independently from both supply and demand sides. The experimental results demonstrate that the framework for water resource optimization using the improved whale algorithm is feasible, providing a reference scheme for regional multi-objective water resource optimization. Finally, the proposed policy recommendations emphasize the necessity of strengthening water diversion planning and management, promoting virtual water and water-saving initiatives, and highlighting water recycling and environmental protection in order to ensure the sustainable allocation of water resources in the downstream Fen River basin.
Compliance with kauri forest protection in New Zealand’s regional parks: the mediating role of trust on local versus visitor populations
Abstract
Realising behavioural change in long invested environmental practices is often difficult to achieve, especially when scientific understanding of the issues is still unfolding. Having confidence in one’s action requires knowledge that actions will be effective in improving environmental outcomes. Currently, we know little about the role of social trust in mediating complex and uncertain knowledge of environmental problems and the required actions needed to address them. In this quantitative study, we surveyed 472 users of endangered kauri forests in New Zealand to better explore the role of trust in relation to pro-environmental behaviours (PEB) designed to mitigate effects of the devastating plant disease, kauri dieback. Findings show uncertainty about the scientific knowledge of the issue, recommended actions and efficacy of proposed solutions significantly influenced PEB for both residents and visitors of forests; however, this relationship was partially mediated by trust, particularly among locals residing within 5 km of infected forest areas. These findings indicate the need for closer engagement with local residents to develop institutional and scientific trust in kauri dieback interventions. We outline activities that may help build trust and recommend new areas of research to support higher compliance with environmental protection initiatives.
The impact of coronavirus disease 2019 (COVID-19) pandemic experiences on attitudes towards vaccinations: on the social, cultural and political determinants of preferred vaccination organization models in Poland
Abstract
Background
The article describes attitudes towards vaccinations in Poland in relation to issues such as voluntary versus compulsory vaccinations, the method of financing vaccinations, the method of organizing and carrying out vaccinations, the cognitive and educational aspect of vaccines (how to obtain knowledge about vaccines) and the preferred model of work and research on new vaccines. Taking into account these issues, the authors have created four ideal models of preferred vaccination policies: (a) the market model; (b) the state model; (c) the vaccine hesitancy model; and (d) the civic–social model. This perspective makes it possible to better understand and learn about the various motives behind the attitudes of anti-vaccination movements, as well as to notice cracks and divisions among vaccination supporters and their attitudes towards the financing and organization of vaccinations.
Methods
The study was carried out using the CATI method on a representative random-quota sample of Polish society of 1000 people aged 18 and over. The study took age, sex, education and the size of the place of residence into account.
Additionally, in the Socio-demographic factors influencing attitudes towards vaccination practices in Poland section, we used the chi-squared test and regression analysis of factors influencing vaccination practices in Poland. PASW Statistics 18 (a version of SPSS) software was used for statistical analysis. Significant correlations were demonstrated at a significance level of 0.05% Pearson.
Results
This article has shown that attitudes towards vaccinations are embedded in broader divisions and orientations related to the vision of the social order: the role of the state, the organization of healthcare and payments for vaccinations and medical services, as well as preferred ways of knowledge production in society and work on new vaccines. The political sympathies and the age of the respondents were the most important variables influencing vaccination behaviour. The education of the respondents was less important.
Conclusions
A few years after the peak of the pandemic, the scope of anti-vaccination attitudes in Polish society ranges from 20% of the population (dogmatic anti-vaxxers) to 30% (vaccine hesitancy occurring depending on attitudes towards vaccinations).
International governance of advancing artificial intelligence
Abstract
New technologies with military applications may demand new modes of governance. In this article, we develop a taxonomy of technology governance forms, outline their strengths, and red-team their weaknesses. In particular, we consider the challenges and opportunities posed by advancing artificial intelligence, which is likely to have substantial dual-use properties. We conclude that subnational governance, though prevalent and mitigating some risks, is insufficient when the individual rewards from societally harmful actions outweigh normative sanctions, as is likely to be the case with AI. Nationally enforced standards are promising ways to govern AI deployment, but they are less viable in the “race-to-the-bottom” environments that are becoming common. When it comes to powerful technologies with military implications, there is only one multilateral option with a strong historical precedent: a non-proliferation plus norms-of-use regime, which we call NPT+. We believe that a non-proliferation regime may, therefore, be the necessary foundation for AI governance. However, AI may exhibit characteristics that would make a non-proliferation regime less effective than it has proven for nuclear weapons. As an alternative, verification-backed restrictions on AI development and use would address more risks, but they face challenges in the case of advanced AI, and we show how these challenges may not have technical solutions. Perhaps more importantly, we show that there is no clear example of major powers restricting the development of a powerful military technology when that technology lacks a ready substitute. We, therefore, turn to a final alternative, International Monopoly, which was the preferred solution of many scholars and policymakers in the early nuclear era. It should be considered again for governing AI: a monopoly would require less-invasive monitoring, though at the possible cost of eroding national sovereignty. Ultimately, we conclude that it is too soon to tell whether a non-proliferation regime, a verification-based regime, or an International Monopoly is most feasible for governing AI. Nonetheless, a variety of policies would yield a high return across all three scenarios, and we conclude by identifying some of these steps that could be taken today.