Diverse Climate Research Articles

Spatial downscaling of GRACE-derived groundwater storage changes across diverse climates and human interventions with Random Forests

The Gravity Recovery and Climate Experiment (GRACE) satellites launched in 2002, which were followed by the GRACE Follow-On mission in 2018, represented a significant advancement in global groundwater storage monitoring. However, the inherent limitation of a relatively low spatial resolution confines its applicability primarily to large river basins and aquifers. This study introduces a novel statistical downscaling approach using Random Forests (RF) to enhance the spatial resolution from 3° × 3° to 0.25° × 0.25° for GRACE-derived groundwater storage (GWS) changes. Focusing on sub-Saharan Africa, the Middle East, and South Asia across diverse climates and human interventions, the analysis spans from February 2003 to December 2022. Predictors encompass hydrological fluxes and their accumulation, including IMERG precipitation, GLEAM evapotranspiration, and GLDAS runoff, alongside GLDAS soil moisture and MODIS NDVI. RF models show robust performance across 114 aquifers, with a Pearson’s correlation coefficient (CC) exceeding 0.92 for training sets and 0.85 for validation sets. Validation against in-situ groundwater level observations from wells in India reveals satisfactory performance, with positive Spearman’s CC values between in-situ groundwater levels and downscaled terrestrial water storage anomaly (TWSA) for a majority of dug and bore wells. This study concludes with the generation of monthly downscaled GWS changes (0.25° × 0.25°) spanning from February 2003 to December 2022. These datasets serve as a foundation for facilitating finer-scale hydrological studies and formulating local groundwater management strategies.

Eco-Friendly Urban Design: Investigating Innovative Approaches and Sustainable Construction Practices Across Afghanistan’s Diverse Climate Zones

Eco-Friendly Urban Design: Investigating Innovative Approaches and Sustainable Construction Practices Across Afghanistan’s Diverse Climate Zones

Eco-Friendly Urban Design: Investigating Innovative Approaches and Sustainable Construction Practices Across Afghanistan’s Diverse Climate Zones

Climate change serves as a pervasive catalyst globally, significantly influencing urban growth and construction dynamics. The interplay of population growth, heightened consumption, increased waste production, and rising CO2 emissions presents a substantial threat to biodiversity and plant life. Creating vibrant, environmentally conscious cities requires integrating architectural, design, and landscape components into the urban development process. This study employs a descriptive approach to examine the intricate dynamics among urbanism, urbanization, and climate-responsive design across Afghanistan's diverse climatic zones. The findings reveal a significant shift from traditional to contemporary global standards, marking a significant evolution within the construction sector. However, there remains a notable lack of climate awareness, resulting in a gap between evolving construction features and climate-responsive methodologies. The Afghanistan National Environmental Protection Agency’s strategies are often too generalized, failing to address specific climatic requirements effectively. Unplanned urban growth has led to limited access to proper housing, increased poverty, and greater vulnerability to climate impacts. Key issues include uncontrolled carbon emissions from heating, transportation, waste management, and industrial activities, severely affecting precipitation patterns and living quality. The research emphasizes the necessity for tailored climate-responsive design and sustainable construction practices, advocating for integrating green technologies and enhancing regulatory frameworks to promote energy efficiency and reduce the environmental footprint of urban developments in Afghanistan.

Revolutionizing multifunctional electrolyte additive design and synthesis for high-voltage nickel-rich batteries in diverse climates

The high-voltage LiNi0.6Co0.2Mn0.2O2 (NCM622) cathode presents a promising avenue for advancing the energy density of lithium-ion batteries. Nevertheless, current limitations primarily arise from electrolyte systems unable to meet stringent criteria, including stable performance under elevated temperatures and efficient discharge at low temperatures. In this study, we address these challenges by designing a molecular structure incorporating boron oxygen functional groups, phenyl-, and fluorine moieties to simultaneously enhance ion conductivity and thermal stability under extreme voltages. A multifunctional electrolyte additive, 3, 4, 5-trifluorophenylboronic anhydride (TFPBA), has been successfully developed via synthesis. TFPBA plays a pivotal role in promoting the formation of a hierarchical cathode electrolyte interphase (CEI) through its preferential decomposition and oxidation processes. This CEI features a mechanically stable inner layer enriched with fluorophenyl- groups, crucial for high-temperature cycling, alongside an outer layer concentrated with BxOyFz complexes that significantly improve Li+ conductivity, ensuring superior performance under low-temperature conditions and at elevated rates. Moreover, TFPBA acts as an HF scavenger within the electrolyte, mitigating corrosive effects on the cathode surface, thereby curtailing CEI reformation and the transition metal dissolution. The Li/NCM622 half cells with TFPBA exhibit impressive capacity retention rates of 92.58%, 80.09%, and 81.77% after extensive cycling at temperatures of −20 °C, 25 °C, and 55 °C, respectively. Moreover, NCM622/graphite full cells with TFPBA achieve a remarkable capacity retention of 97.97% after 150 cycles at room temperature. Our findings highlight the exceptional electrochemical performance of NCM622 cathodes at elevated voltages across a wide temperature range, providing valuable insights for the development of advanced electrolytes in high-demand applications.

Assessing the role of habitat, climate, and anthropization gradients on terrestrial mammal diversity in the western Mediterranean basin.

Mammal species globally exhibit distribution patterns conditioned by environmental conditions and human impact. The Mediterranean basin provides an ideal system to study these effects due to its diverse climate, and habitat conditions. In this work, we aim to assess the impact of landscape heterogeneity and anthropization degree on terrestrial mammal diversity in this region. Accordingly, we deployed over 300 camera traps across 28 sites for 3 months. Detected mammal species (weighing more than 1kg) were classified as domestic carnivores, domestic ungulates, wild carnivores, wild ungulates, lagomorphs, and large rodents. Alpha and beta diversity were calculated for each group and all wild mammals. Simple linear regressions and multimodal analysis were conducted between mammal diversities and climate, environmental conditions, landscape heterogeneity, and anthropization degree variables. Redundancy analyses were performed to identify variables and species determining the mammalian community composition. Indexes measuring landscape heterogeneity, anthropization degree, and its 30-year change did not correlate with mammal diversity. However, the difference in elevation within sites and domestic carnivore abundance showed a significant positive correlation with some of the diversity indexes. Nonetheless, rainfall and mean elevation factors generally showed the highest correlation with mammal diversity. Instead, a few influential species, including generalists and open-habitat specialists, highlighted the importance of conserving open areas, as well as the importance of the Pyrenees region as a key habitat for certain species. Therefore, climatic variables emerged as the key determinants of mammal diversity, highlighting climate change as a potential threat to mammal diversity in this area.

Relationships among soil moisture at various depths under diverse climate, land cover and soil texture

Soil moisture is an important component of the hydrological cycle and a key mediator between land surface and atmospheric interactions. Although substantial progress has been made in remote sensing of soil moisture at different spatial scales, the shallow penetration depth of remote sensors greatly limits their utility for applications in meteorological modelling and hydrological studies where the critical variable of interest is the root-zone soil moisture content. Therefore, this study assesses the relationship between soil moisture at the surface (10 cm) and in lower soil layers (20, 40, 60, 80, 100, and 120 cm) under varying climates, soils, and crop types. Cross-correlation analysis is applied to daily in-situ soil moisture measurements from 4712 locations in agricultural lands across the contiguous United States. Our analysis demonstrates that zero-day lag always produced the highest correlation between 10 cm soil moisture and soil moisture in the lower layers. In addition, a positive and strong relationship between 10 and 20 cm soil moisture (r = 0.84) was observed, while the relationships between 10 and 40 cm soil moisture were moderate (r = 0.52). The decline in cross-correlation continued to the deeper soil layers, which indicated that, on a daily timescale, the surface soil moisture gradually becomes decoupled with soil moisture at greater depths. Therefore, our research suggests that the estimation of soil moisture in the soil layers up to 40 cm based on surface soil moisture is most promising. However, the influence of climate, crop type, and soil texture on the strength of relationships between surface and lower layers makes the prediction difficult. The comparatively weak relationship between precipitation and soil moisture (0.09–0.32), as well as the relationship between reference evapotranspiration (ETo) and soil moisture (−0.19–0.18), in this study can be attributed to scale mismatching from different data sources.

Construction of ecological security pattern of arid area based on landscape ecological risk assessment: a case study of the Wu-Chang-Shi urban agglomeration.

The construction of ecological security pattern (ESP) holds paramount importance in ensuring regional environment sustainability. This study introduces an innovative approach to ESP construction grounded in landscape ecological risk (LER) assessment, with Wu-Chang-Shi urban agglomeration in Xinjiang, China, serving as a case study. Initially, LER within the area was evaluated using the LER Index (LERI) method. Subsequently, the Geodetector model was employed to discern the relationship between multi-source data and LER. Furthermore, ecological resistance and corridors were delineated utilizing the minimum cumulative resistance (MCR) model. Lastly, the corridors were optimized using the gravity model, finalizing the ESP construction. Study results reveal that LER was always fluctuating from 1990 to 2010, and tended to stabilize from 2010 to 2020. Factor detection underscores the predominant influence of land use on LER, followed by elevation and vegetation distribution. The ESP shows the imperative for improving connectivity of the natural areas that are fragmented by urban land, highlighting the great significance of the woodland-originating corridors. Finally, strategies are proposed to enhance woodland and water coverage, boost landscape diversity in nature reserves, and prioritize ecological conservation in corridor regions. In summation, the study furnishes a framework for analyzing arid regions in Eurasia. Furthermore, the research idea of evaluation-analysis-remodeling also offers insights into environmental management in developing areas with more diverse climate types.

SARIMA Model-Based Monte Carlo Simulation of Option Contract Design for Maize Seasonal Heavy Precipitation in Shenyang

Agricultural production is highly dependent on weather conditions such as temperature, light, water and heat. The huge loss caused by extreme disaster weather makes the global insurance and reinsurance market overwhelmed, and seriously affects the enthusiasm of agricultural investment and the development of agricultural economy. With unique topography and vast territory, China is vulnerable to complex and diverse climate disasters. In recent years, the annual average economic loss caused by extreme weather disasters has reached about 200-300 billion yuan, among which floods caused by extreme heavy rainfall are the main agricultural disasters in China. In order to enhance the "farmer - insurance company - government" interest association to resist the risk of flood disaster caused by extreme heavy rainfall, financial hedging derivatives of weather disaster risk have gradually become a new hedging tool besides traditional insurance and reinsurance. This paper takes Shenyang, the main grain producing area in northeast China, as the sample of the study area, and uses the SARIMA model to obtain the distribution characteristics of seasonal rainfall time series. Different seasonal rainfall index option products (call option and put option contracts) are designed respectively, and the final option pricing is obtained by Monte Carlo stochastic simulation. The seasonal rainfall call option and put option contracts have opened up a new hedging model of agricultural extreme weather catastrophe outside the insurance and reinsurance market, which has enriched the varieties of weather financial derivatives market in China, reduced the severe impact of extreme weather disasters on agriculture, and enhanced the ability of agricultural stakeholders to resist the risk of extreme weather disasters.

Structural characteristics and physicomechanical properties of bamboo scrimber composite during natural weathering

Bamboo-based composite materials used outdoors are exposed to diverse natural climates, necessitating an understanding of their surface, physical, and mechanical properties for long-term use. This study evaluated changes in chemical composition, surface color, microstructure, and physicomechanical attributes of bamboo scrimber composite (BSC) manufactured from heat-treated moso bamboo bundles and phenol formaldehyde resin. Over two years of weathering, photodegradation affects bamboo and phenol formaldehyde resin, especially lignin, causing surface discoloration and cracking. Initial weathering stages reduced the width swelling rate, thickness swelling rate, and shear strength of BSC. Despite this, two-year weathered BSC meets the Chinese GB/T 30364-2013 standard for outdoor flooring and exhibits strong weather resistance.

Does Urbanization Exacerbate Asymmetrical Changes in Precipitation at Divergent Time Scales in China?

AbstractUrbanization alters the thermal and dynamic environment of the local climate system, resulting in significant impacts on precipitation in both urban and adjacent areas. Nevertheless, there remains a significant gap in our understanding of urbanization‐induced effects on asymmetrical, symmetrical, and other precipitation patterns in urban agglomerations (UAs) with divergent background climates and geographic regions at different timescales. Specifically, this asymmetrical change pattern is characterized by an increase in heavy (or light) rainfall and a decrease in light (or heavy) rainfall. Here, we assessed the effects of urbanization on precipitation patterns across 18 UAs situated in diverse background climates and geographical areas in China at different timescales. The results demonstrate that urbanization predominantly alters precipitation patterns in UAs located in the humid region. Specifically, urbanization amplified asymmetrical changes in Yangtze River Delta, Pearl River Delta, Beibu Gulf, Middle Yangtze River, and Guanzhong, but exacerbated symmetrical changes in precipitation in some regions such as Chengdu‐Chongqing. Notably, the urbanization effect demonstrates greater significance at the hourly scale, as exemplified in the Yangtze River Delta, Pearl River Delta, and Middle Yangtze River, where the urban impact is nearly twice as pronounced when compared to the daily scale. Moreover, urbanization had either no effect or has a negative impact on precipitation patterns in UAs located within continental and arid regions. This is related to the intensity of urbanization, background climate and complex topography. This finding implies that urban managers should consider the impact of urbanization on precipitation patterns in different contexts to provide scientific guidance for urban planning.

Supplemental Material for Culturally Responsive Teaching Self-Efficacy and Cultural Diversity Climate Are Positively Associated With the Academic and Psychological Adjustment of Immigrant and Nonimmigrant Students

Supplemental Material for Culturally Responsive Teaching Self-Efficacy and Cultural Diversity Climate Are Positively Associated With the Academic and Psychological Adjustment of Immigrant and Nonimmigrant Students

Organizational Diversity Climate as a Predictor of Employee Turnover Intention

Organizational Diversity Climate as a Predictor of Employee Turnover Intention

Adolescent Cultural Identity Development in Context: The Dynamic Interplay of the Identity Project With Classroom Cultural Diversity Climate in Italy and Germany

While both the classroom cultural diversity climate and curriculum-based interventions can promote cultural identity development, they have not been studied together. Drawing on theories of ethnic-racial identity development, the current study aimed to understand the dynamic interplay of a curriculum-based intervention (the Identity Project) with the classroom cultural diversity climate (heritage culture and intercultural learning, critical consciousness socialization and equal treatment) on cultural identity exploration and resolution. Our sample included 906 mid-adolescents in Italy (32.36% immigrant descent, Mage (SD) = 15.12 (0.68) years, 51.73% female), and 504 early adolescents in Germany (53.86% immigrant descent, Mage (SD) = 12.82 (0.89) years, 42.37% female). Bayesian multivariate linear models show that the Identity Project and a stronger critical consciousness climate in the classroom before the intervention promoted cultural identity exploration at post-test in both countries. However, effects of the intervention and facets of the diversity climate on subsequent resolution were only observed in Italy. There was some evidence that the intervention could alter the classroom cultural diversity climate in Germany, while the intervention could compensate for a less positive diversity climate in the slightly older sample in Italy. Thus, it seems promising to systematically build in opportunities to engage with students’ diverse heritage cultures and identities when developing new curricula, as well as to train teachers to implement such curricula.

Horticultural Food Plants in Traditional Herbal Medicine in the Mediterranean Basin: A Review

The Mediterranean Basin’s diverse climates and ecosystems have shaped a rich botanical heritage through centuries of selective cultivation, resulting in a wide array of horticultural plants with valuable therapeutic properties. The use of horticultural food plants as herbal remedies has become an integral part of traditional medicine in this geographical context. The present review aims to highlight the use of horticultural food plants (HFPs) in the context of traditional herbal medicine in the countries of the Mediterranean Basin and explore their traditional uses and therapeutic properties. A comprehensive ethnobotanical literature search was conducted on the food plants used as herbal medicine in the Mediterranean region using existing online scientific databases. Based on the literature review, 64 taxa used as medicinal plants by traditional users in the Mediterranean Basin were documented. Overall, horticultural plants are used in Mediterranean countries to treat a total of 573 ailments. Italy has the highest number of use reports (998), followed by Morocco (281) and Spain (193). Apiaceae (11 taxa), Cucurbitaceae (9 taxa), and Brassicaceae (8 taxa) are the most frequently cited families. The genus Allium is the most abundant in species (5).

SSR-BASED ASSESSMENT OF GENETIC DIVERSITY IN TOMATO CULTIVARS AND LINES GROWN IN KAZAKHSTAN

Tomato (Solanum lycopersicum L.) is a versatile crop known for its nutritional value and health benefits, thriving in diverse climates worldwide. Nevertheless, regional variations persist in tomato yield, with Kazakhstan serving as an example of lower productivity in contrast to global averages. Closing this disparity requires comprehensive genetic studies and breeding efforts. This study is focused on the genetic diversity of 49 tomato cultivars and hybrids sourced from Kazakh Research Institute of Fruit and Vegetable Growing (Almaty), employing 10 SSR markers associated with important agronomic traits. SSR genotyping unveiled polymorphisms across 6 markers with variable allele numbers. Genetic diversity metrics highlighted significant genetic diversity within both outdoor and greenhouse tomato cultivars and lines. Bayesian clustering, Neighbor-joining (NJ) clustering, and principal coordinate analysis (PCoA) delineated genetic differentiation between outdoor and greenhouse tomatoes with small admixture, indicating distinct breeding directions for these two types. Highly polymorphic SSRs (PIC > 0.5) associated with essential fruit traits emerge as promising targets for marker-assisted selection (MAS) that can be used to enhance tomato breeding efficiency in Kazakhstan. According to 8 SSRs, 22 out of 30 outdoor accessions and 8 greenhouse tomato accessions were genetically uniform. This study offers comprehensive insights into the genetic diversity and population structure of tomato cultivars and lines in Kazakhstan, laying the foundation for informed breeding endeavors aimed at bolstering yield and resilience in tomato crops.

Revealing accuracy in climate dynamics: enhancing evapotranspiration estimation using advanced quantile regression and machine learning models

This study examines the effectiveness of various quantile regression (QR) and machine learning (ML) methodologies developed for analyzing the relationship between meteorological parameters and daily reference evapotranspiration (ETref) across diverse climates in Iran spanning from 1987 to 2022. The analyzed models include D-vine copula-based quantile regression (DVQR), multivariate linear quantile regression (MLQR), Bayesian model averaging quantile regression (BMAQR), as well as machine learning algorithms such as extreme learning machine (ELM), random forest (RF), M5 model Tree (M5Tree), least squares support vector regression algorithm (LSSVR), and extreme gradient boosting (XGBoost). Additionally, empirical equations (EEs) such as Baier and Robertson (BARO), Jensen and Haise (JEHA), and Penman (PENM) models were considered. While the EEs demonstrated acceptable performance, the QR and ML models exhibited superior accuracy. Among these, the MLQR model displayed the highest accuracy compared to DVQR and BMAQR models. Moreover, LSSVR, XGBoost, and M5Tree models outperformed ELM and RF models. Notably, LSSVR, XGBoost, and MLQR models exhibited comparable performance (R2 and NSE > 0.92, MBE and RMSE < 0.5, and SI > 0.05) to M5Tree and BMAQR models across all climates. Importantly, these models significantly outperformed EEs, DVQR, ELM, and RF models in all climates. In conclusion, high-dimensional QR and ML models are recommended as promising alternatives for accurately estimating daily ETref in diverse global climate conditions.

Elevation Regulates the Response of Climate Heterogeneity to Climate Change

AbstractClimate change represents a profound threat to the diversity and stability of global climate zones. However, the complex interplay between climate change and elevation in shaping climate heterogeneity is not yet fully understood. Here, we combine Shannon's diversity index (SHDI) with the Köppen‐Geiger climate classification to explore the altitudinal distributions of global climate heterogeneity; and their responses to climate change. The study reveals a distinctive pattern: SHDI, a proxy for climate heterogeneity tends to slow down or decline at lower elevations with increasing temperatures, while at higher elevations, it continues to rise due to continuing cold conditions. Examination of climate simulations, both with and without anthropogenic forcing, confirms that observed changes in climate heterogeneity are primarily attributable to anthropogenic climate change within these high‐elevation regions. This study underscores the importance of high‐elevation regions as not only custodians of diverse climate types but also potential refuges for species fleeing warmer climates.

An update for Halyomorpha halys (Stål, 1855) (Hemiptera, Pentatomidae) distribution in Belgium

The brown marmorated stink bug, Halyomorpha halys, represents an important insect pest and subsequently an important agricultural threat due to its polyphagous feeding habits and adaptability to diverse climates. Native from East Asia, its recent establishment in various regions, including North America and Europe, has led to substantial yield losses and economic impacts, which highlight the need for comprehensive research efforts, based on data occurrence by combining those from expert entomologists and citizen scientists. We reported here 14 new occurrences of this insect pest in the three regions of Belgium. Then, these data were merged with data occurrences from other studies and GBIF datasets of Belgium. The combined dataset showed a peak of presence of Halyomorpha halys in October and a dominance of field observations from citizen scientists especially in the nothern part of Belgium, Flanders. Crowd-sourced data have provided valuable insights into the presence and distribution of Halyomorpha halys in Belgium. Given the importance of the generated dataset, it could be asserted that this pest is uniformly distributed across the entire country, which necessitates additional research to evaluate its impact on various crops.

What determines how governance indicators shape policy processes? Evidence from three environmental issues in India

AbstractGovernance indicators influence and shape policy processes. The need for exploring how governance indicators lead to efficient policy responses is a long‐drawn debate in the field of policy studies. While existing literature is mostly from developed world, there is a dearth of empirical evidence from developing countries like India. As cities continue to remain the fulcrum of economic growth despite the much‐argued development model practised across India, it remains to be seen how governance indicators determine policy processes in cities. Adapting United Nations Economic and Social Commission for Asia and the Pacific's (UNESCAP's) module on eight governance indicators we studied the policy process of three diverse climate change‐linked environmental issues ‐ air pollution, dengue, and extreme heat, from three urban Indian metropolis ‐ Delhi, Kolkata, and Ahmedabad, respectively. We used a semi‐structured questionnaire to interview 33 stakeholders. We coded interview findings and formulated a color‐coded matrix to highlight the importance of governance indicators by environmental issues. Transparency, accountability and participation played an important role in shaping policy processes. The importance of other governance indicators varied due to diversity in administrative structures across three cities. Our study's findings highlight a complex relationship between governance indicators and policy processes linked to the environmental issues. Our study shows that the relevance of governance indicators in shaping policies around environmental issues is determined by the nature of the environmental issue and the structure of governance. In addition, our study adds four new indicators, governance structures, capacity building, informality, and gender‐inclusivity, which influence policy processes.

The Use of the GWPCA-MGWR Model for Studying Spatial Relationships between Environmental Variables and Longline Catches of Yellowfin Tunas

The yellowfin tuna represents a significant fishery resource in the Pacific Ocean. Its resource endowment status and spatial variation mechanisms are intricately influenced by marine environments, particularly under varying climate events. Consequently, investigating the spatial variation patterns of dominant environmental factors under diverse climate conditions, and understanding the response of yellowfin tuna catch volume based on the spatial heterogeneity among these environmental factors, presents a formidable challenge. This paper utilizes comprehensive 5°×5° yellowfin tuna longline fishing data and environmental data, including seawater temperature and salinity, published by the Western and Central Pacific Fisheries Commission (WCPFC) and the Inter-American Tropical Tuna Commission (IATTC) for the period 2000–2021 in the Pacific Ocean. In conjunction with the Niño index, a multiscale geographically weighted regression model based on geographically weighted principal component analysis (GWPCA-MGWR) and spatial association between zones (SABZ) is employed for this study. The results indicate the following: (1) The spatial distribution of dominant environmental factors affecting the catch of Pacific yellowfin tuna is primarily divided into two types: seawater temperature dominates in the western Pacific Ocean, while salinity dominates in the eastern Pacific Ocean. When El Niño occurs, the area with seawater temperature as the dominant environmental factor in the western Pacific Ocean further extends eastward, and the water layers where the dominant environmental factors are located develop to deeper depths; when La Niña occurs, there is a clear westward expansion in the area with seawater salinity as the dominant factor in the eastern Pacific Ocean. This change in the spatial distribution pattern of dominant factors is closely related to the movement of the position of the warm pool and cold tongue under ENSO events. (2) The areas with a higher catch of Pacific yellowfin tuna are spatially associated with the dominant environmental factor of mid-deep seawater temperature (105–155 m temperature) to a greater extent than other factors, the highest correlation exceeds 70%, and remain relatively stable under different ENSO events. The formation of this spatial association pattern is related to the vertical movement of yellowfin tuna as affected by subsurface seawater temperature. (3) The GWPCA-MGWR model can fully capture the differences in environmental variability among subregions in the Pacific Ocean under different climatic backgrounds, intuitively reflect the changing areas and influencing boundaries from a macro perspective, and has a relatively accurate prediction on the trend of yellowfin tuna catch in the Pacific Ocean.