Search Results (414)

This study evaluated the seasonal greenhouse gas (GHG) emissions and carbon assimilation of Bambusa edulis under four soil amendment treatments—control (C), biochar (B), fertilizer using vermicompost (F), and biochar plus fertilizer (B + F)—in a coastal shelterbelt system in south-western Taiwan. Over a 12-month period, CO₂ and N₂O fluxes and photosynthetic carbon uptake were measured. The control (C) treatment served as the baseline, exhibiting the lowest greenhouse gas (GHG) emissions and carbon assimilation. Its summer N₂O emissions were 39.54 ± 20.79 g CO₂ e m⁻², and its spring carbon assimilation was 13.2 ± 0.84 kg CO₂ clump⁻¹. In comparison, the amendment treatments significantly enhanced both emissions and carbon uptake. The fertilizer-only (F) treatment resulted in the highest levels, with peak summer N₂O emissions increasing by 306.5% (to 160.73 ± 96.22 g CO₂ e m⁻²) and spring carbon assimilation increasing by 40.2% (to 18.5 ± 0.62 kg CO₂ clump⁻¹). An increase in these values was also observed in the combined biochar and fertilizer (B + F) treatment, although the magnitude was less than that of the F treatment alone. In the B + F treatment, summer N₂O emissions increased by 130.3% (to 91.1 ± 62.51 g CO₂ e m⁻²), while spring carbon assimilation increased by 17.4% (to 15.5 ± 0.36 kg CO₂ clump⁻¹). Soil CO₂ flux was significantly correlated with atmosphere temperature (r = 0.63, p < 0.01) and rainfall (r = 0.45, p < 0.05), while N₂O flux had a strong positive correlation with rainfall (r = 0.71, p < 0.001). The findings highlight a trade-off between nutrient-driven productivity and GHG intensity and demonstrate that optimized organic and biochar applications can enhance photosynthetic carbon gain while mitigating emissions. The results support bamboo’s role in climate mitigation and carbon offset strategies within nature-based solution frameworks. Full article

The primary strata of western Taiwan are Cenozoic sedimentary rocks. Characterized by low cementation and high porosity, these rocks exhibit a pronounced wetting–softening effect. Long-term exposure to warm, humid tropical and subtropical climates significantly degrades their engineering geological properties due to weathering. This study, based on a sandstone-shale interbedded highway slope in central Taiwan that has repeatedly collapsed, investigated the slope’s failure mechanism using remote-sensing image interpretation of previous landslides, surface geological surveys, kinematic analysis, photogrammetric mapping, laboratory artificial weathering experiments, and Distinct Element Method (DEM) simulations. The study revealed that the fundamental cause of collapse on this type of oblique-slope interbedded sandstone-shale is the sliding and toppling of sandstone blocks, driven by weathering and erosion of the shale. Based on artificial weathering experiments, the strength loss rate of the shale in the Kuantaoshan Sandstone Member of the Kueichulin Formation after weathering is 6.6 times that of the sandstone. The estimated collapse area from the two-dimensional Distinct Element Method analysis is consistent with the actual value from the photogrammetric model. This type of landslide caused by rock weathering always forms stepped surface where sandstone overhangs above shale. A shale erosion amount of 0.78–0.91 of the spacing of the joint approximately parallel to the slope surface was found to be the critical erosion before collapse and can serve as the early warning indicator. Full article

Shrimp populations are threatened by overfishing and climate change. Despite this, there are limited studies on the variations in biomass, number, and size of Eastern Neptune rose shrimp, Parapenaeus fissuroides, in different fishing grounds across seasons in the Southern Yellow and East China Seas of China, as well as habitat area change under different climate scenarios. In this study, the data was obtained from the bottom trawling surveys conducted from November 2018 to September 2019 at 26.5–35° N 120–127° E. We found that the major cohorts were concentrated at depths of 70–110 m in spring and summer, 80–90 m in autumn, and 60–100 m in winter. The greatest abundance was observed at sea bottom temperatures of 18–20 °C in spring, 18–21 °C in summer, 19–22 °C in autumn, and 17–19 °C in winter; and sea bottom salinity levels of 34–35 across all four seasons, indicating the influence of high-salinity Taiwan Warm Current and Yellow Sea Warm Current. The annual mean catch per unit effort in weight and number were 16,623.65 g·h⁻¹ and 4304.525 ind·h⁻¹, respectively. Climate variations may negatively impact the habitat area range of P. fissuroides. For migration route, P. fissuroides concentrates in Yushan and Yuwai for the upcoming spawning season in spring, with offspring occurring in high-temperature and high-salinity waters of Zhouwai and Yuwai in summer. The newborn recruited cohorts remained in Yushan, Wentai, and Mindong for nursery grounds in autumn and winter. We suggested a seasonal closure from August to November in Yushan, Yuwai, Zhouwai, and Mindong to protect and conserve P. fissuroides populations. Full article

Amid rising global energy demand and Taiwan’s transition toward a non-nuclear and low-carbon future, identifying an optimal renewable energy (RE) mix has become essential. This study analyzes eight RE sources using a three-model framework—Pearson correlation, Stepwise Regression Analysis (SRA), and Principal Component Analysis (PCA)—based on 60 monthly observations from 2019 to 2023. The results show that geothermal energy (GE) and solar photovoltaics (SP) exhibit strong positive correlations with total RE generation. Both SRA and PCA consistently identify conventional hydropower (CH), SP, and offshore wind power (OSW) as Taiwan’s most effective RE combination, while PCA provides superior predictive performance and reduces multicollinearity. In contrast, OWP, SB, BG, and WTE show limited contribution to overall RE output. Policy recommendations suggest prioritizing SP under resource constraints, and jointly expanding CH, SP, and OSW when resources permit, to achieve a balanced and sustainable RE structure. Full article

Global warming has increasingly reduced winter chill accumulation in traditional fruit-growing regions, disrupting dormancy release and bloom synchrony in deciduous fruit crops such as peach (Prunus persica). To evaluate adaptation potential under subtropical conditions, a three-year field study was conducted in central Taiwan using two low-chill cultivars, ‘Tainung No.4 Ruby’ (~100 chilling units, CU) and ‘Tainung No. 7 HongLing’ (~77 CU). Our results demonstrate that both cultivars produced long shoots (>34 nodes), completed vegetative growth by October, and reached natural leaf fall by mid-November. Nonlinear Gompertz and Logistic models accurately described shoot elongation dynamics and growth cessation. Flowering began in mid-January for ‘Tainung No. 7 HongLing’ and mid-February for ‘Tainung No. 4 Ruby’. Seasonal chill accumulation strongly influenced the onset of flower budbreak between apical and basal buds: in the milder 2023–2024 winter (~120 CU), apical–basal onset lags were wider (22 days in ‘Tainung No. 7 HongLing’), whereas in the colder 2024–2025 winter (~280 CU), these lags shortened (14 days). Notably, ‘Tainung No. 4 Ruby’ maintained a consistent apical–basal onset lag between seasons, indicating greater positional stability under variable chilling. Field-estimated CU thresholds for flower budbreak exceeded the reported chilling requirements, suggesting reduced chilling efficiency under fluctuating subtropical winter temperatures. These results demonstrate that integrating shoot growth, leaf fall timing, and chill–heat accumulation provides a phenology-informed framework for cultivar selection and orchard scheduling, thereby enhancing climate resilience of peach production in warm-winter regions. Full article

Trifolium repens L. is a protein-rich, versatile Leguminous lawn plant that is widely distributed across global temperate and subtropical regions. As an invasive species originating in Europe, its distribution in China extends from Xinjiang in the West to Taiwan and the Yangtze River Delta in the East, and is widespread throughout Northeast and Central China. However, in recent years, the distribution pattern of T. repens has become increasingly patchy and irregular. Therefore, unraveling the potential distribution and key environmental drivers of T. repens is critical for understanding its ecological role. This study utilized current species distribution data of T. repens and employed the MaxEnt model to simulate its potentially suitable niches across present and future climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) in China. This study identified Bio2 (mean diurnal temperature range) and Bio14 (precipitation of driest month) as the key drivers shaping the distribution of T. repens. Its current suitable habitats are primarily concentrated in the coastal, central, and Taiwan regions of China. Under future climates, these areas are projected to contract overall and shift toward lower latitudes and higher longitudes, with substantial suitable areas remaining only in the Eastern, Southern, and Taiwan regions. This study quantitatively assessed the ecological niche breadth of T. repens and its future spatial distribution under climate change, thereby laying a theoretical foundation for describing the ecological characteristics of this invasive species, conducting monitoring, and implementing further invasion risk management. Full article

Kinmen Island, historically known as Quemoy, holds significant historical and geopolitical importance due to its strategic location in the Taiwan Strait, just a few kilometers from the Chinese mainland. This study presents the first comprehensive assessment of soil erosion and deposition on Kinmen, providing a scientific foundation for future land conservation and sustainable development initiatives. It also addresses the underrepresentation of small-island environments in soil erosion modeling by adapting the Revised Universal Soil Loss Equation (RUSLE) and Unit-Stream-Power-based Erosion Deposition (USPED) models for coarse-textured soils under limited rainfall conditions, offering insights into the reliability and limitations of these models in such contexts. The rainfall–runoff erosivity factor (${\mathrm{R}}_{\mathrm{m}}$) was derived from precipitation data at four stations, while soil samples from ten locations were analyzed for the Soil Erodibility Factor (${\mathrm{K}}_{\mathrm{m}}$). Topographic factors, including the Slope Length and Steepness ($\mathrm{LS}$) and the Topographic Sediment Transport (${\mathrm{LS}}_{\mathrm{T}}$) factors, were computed from a 20 m DEM (Digital Elevation Model), and the Cover-Management Factor ($\mathrm{C}$) was obtained from land use classification. The RUSLE estimated a mean soil erosion rate of 2.17 Mg ha⁻¹ year⁻¹, while the USPED results varied with parameterization, ranging from 0.87 to 3.79 Mg ha⁻¹ year⁻¹ for erosion and 1.39 to 6.51 Mg ha⁻¹ year⁻¹ for deposition. The results were compared with studies from the neighboring Fujian Province and contextualized through two field expeditions. This pioneering research advances the understanding of erosion and deposition processes in a strategically located island environment and supports evidence-based policies for land conservation, contributing to SDG 15 (Life on Land) and SDG 13 (Climate Action). Full article

Avian influenza (AI) is a highly contagious viral disease affecting both domestic and wild birds, posing a significant threat to poultry farming worldwide. This study aims to analyze the key landscape and population factors associated with H7 avian influenza outbreaks across the Euro-Asian continent and to identify high-risk areas in Russia for the virus’s introduction and subsequent spread. Two models were developed using the Maximum Entropy algorithm (MaxEnt): An introduction model predicting the likelihood of avian influenza presence based on climatic, landscape, wild waterfowl and semiaquatic bird population density data; and a spread model estimating outbreak risk in poultry farms using data on synanthropic birds, poultry flock density, and proximity to wild bird habitats. The first model was trained via maximum likelihood using data from H7 avian influenza outbreaks in Europe (Italy, Germany, France, Denmark, Lithuania, the Netherlands) and Southeast Asia (China, Hong Kong, Taiwan, Japan, Cambodia, North Korea, South Korea, Vietnam). The second model was trained using output from the first model. Specifically, areas with a predicted probability of H7 outbreak between 0.9 and 1.0 were used as occurrence points for the model in Russia. The results demonstrated that both models achieved high predictive reliability for avian influenza outbreaks in the Russian Federation: the introduction model (AUC = 0.855) and the spread model (AUC = 0.993). Areas with a high probability of disease occurrence were identified in the Central, Southern, North Caucasian, and Volga Federal Districts. These findings underscore the necessity of enhanced disease surveillance in these regions, as well as in the border areas of the Ural, Siberian, and Far Eastern Federal Districts. The authors recommend strengthening biosecurity measures, enhancing wild bird monitoring in high-risk areas, and maintaining stocks of relevant vaccines to timely contain the outbreaks. Full article

Coral reefs, with their high biodiversity and ecological service functions, face significant threats due to climate change, overfishing, and pollution. The South China Sea (SCS) hosts rich coral biodiversity, particularly Acropora hyacinthus, a critical species for reef restoration. However, the region’s coral reefs are increasingly degraded, highlighting the urgent need for conservation efforts. In the present study, the genetic diversity and population structure of A. hyacinthus were examined based on two types of data: double-digest restriction-site-associated DNA (ddRAD) sequencing data and mitochondrial putative control region DNA (mtCR) sequences. Coral tissue samples were collected from 74 colonies inhabiting two inshore reefs (Sanya) and three offshore reefs (Xisha islands), and 748 single nucleotide polymorphisms (SNPs) and 74 mtCR sequences were obtained and utilized for downstream analysis. The results were consistent in analyses and did not cluster into two geographical groups for the inshore and offshore sites. Phylogenetic analysis showed that individuals of A. hyacinthus inhabiting the five detected sites were likely cryptic species HyaD. Furthermore, AMOVA and pairwise F_ST estimations based on both data types revealed no differentiation among five populations and between inshore and offshore reefs, which could be due to the reproductive mode of broadcast spawning for this species. However, a prevalent low level of genetic diversity was observed when compared with nearby Taiwan regions and Japan, and the geographic history results showed that the effective population size (N_e) had been decreasing for the past 300 years. Thus, we speculated that the populations of A. hyacinthus inhabiting the SCS lack the potential to cope with future climate change adequately, and multiple conservation measures should be implemented based on considering genetic diversity. Full article

This study investigates landslide occurrence in Taiwan, a region highly susceptible to landslides due to steep mountains and frequent typhoons (TYPs). The primary objective is to understand how both geomorphological factors and TYP characteristics contribute to landslide occurrence, which is essential for improving hazard prediction and risk management. The research analyzed landslide events that occurred during the TYP seasons of 2019 and 2023. The methodology involved using satellite-derived landslide inventories from SPOT imagery for events larger than 0.1 hectares, tropical cyclone track and intensity data from IBTrACS v4 (classified by Saffir–Simpson Hurricane Scale), and detailed topographic variables (elevation, slope, aspect, Stream Power Index) extracted from a 30 m Shuttle Radar Topography Mission Digital Elevation Model (SRTM-DEM). Land use and land cover classifications were based on Landsat imagery. To establish a timeline, landslides were matched with TYPs within a ±3-day window, and proximity was analyzed using buffer zones ranging from 50 to 500 km around storm centers. Key findings revealed that landslide susceptibility results from a complex interplay of meteorological, topographic, and land cover factors. The critical controls identified include elevations above 2000 m, slope angles between 30 and 45 degrees, southeast- and south-facing aspects, and low Stream Power Index values typical of headwater and upper slope locations. Landslides were most frequent during Category 3 TYPs and were concentrated 300 to 350 km from storm centers, where optimal rainfall conditions for slope failures exist. Interestingly, despite the stronger storms in 2023, the number of landslides was higher in 2019. This emphasizes the importance of interannual variability and terrain preparedness. These findings support sustainable disaster risk reduction and climate-resilient development, aligning with Sustainable Development Goals 11 (Sustainable Cities and Communities) and 13 (Climate Action). Furthermore, they provide a foundation for improving hazard assessment and risk mitigation in Taiwan and similar mountainous, TYP-prone regions. Full article

This study investigates how climate change literacy (CCL) and institutional contexts shape the climate-related behaviors of Taiwan’s public officials. Drawing on a 2024 national survey of 1940 civil servants, we apply hierarchical and comparative regression analyses to examine the relative influence of knowledge, affective dispositions, and organizational supports. Results show that solution-oriented knowledge exerts greater behavioral influence than factual awareness. At the same time, affective resources—particularly self-efficacy and environmental identity—are the strongest and most consistent drivers of engagement. Institutional factors further condition these relationships: central officials’ behaviors are shaped by departmental mandates and bureaucratic constraints, whereas local officials rely more on supervisor support and prior project involvement. These findings integrate literacy research with institutional perspectives, demonstrating that effective climate governance requires both individual agency and enabling organizational contexts. Policy implications include strengthening leadership training, creating experiential learning opportunities, and streamlining administrative structures across governance levels to accelerate climate action. Full article

Soil respiration (Rs), the second largest carbon flux in terrestrial ecosystems, critically regulates the turnover of soil carbon pools. However, its seasonal and annual responses to extreme events in monsoon forests remain unclear. This study used a continuous multichannel automated chamber system to monitor Rs over three years of drought (2019–2021) in an Asian monsoon forest in Taiwan. We assessed seasonal and annual Rs patterns and examined how drought influenced autotrophic (Rr) and heterotrophic (Rh) respiration through changes in soil temperature and moisture. Results showed Rs declined from 5.20 ± 2.08 to 3.86 ± 1.20 μmol CO₂ m⁻² s⁻¹, and Rh from 3.36 ± 1.21 to 3.15 ± 0.98 μmol CO₂ m⁻² s⁻¹ over the study period. Spring Rr values dropped significantly—by 29.3% in 2020 and 62.2% in 2021 compared to 2019 (p < 0.05), while Rh remained unchanged (p > 0.05). These results suggest that spring drought strongly suppresses autotrophic respiration but has minimal effect on Rh. Incorporating these dynamics into carbon models could improve predictions of carbon cycling under climate change. Our findings demonstrate that spring drought exerts a strong influence on soil carbon fluxes in Asian monsoon forests. Full article

Taiwan, located in a subtropical region, has experienced continuous warming in recent years, making the Urban Heat Island (UHI) effect one of its most pressing environmental challenges. Importantly, UHI is not confined to Taipei, the most populous city, but is also present in other metropolitan areas. This study investigates UHI effects in the five largest cities in Taiwan and examines climate-related news attention using web crawling. Cross-city comparisons are further conducted through Urban Heat Island Intensity (UHII) and correlation analysis. The results reveal that Taipei records the highest number of UHI-related news reports, particularly during summer, and its UHII is about 1.5 °C to 3 °C higher than in the other four cities. In addition, UHII in Taipei shows a marked increase between 2021 and 2023, suggesting a worsening impact on citizens’ living conditions. Meanwhile, news coverage in Taipei dominates nationwide attention, creating a spatially uneven distribution of media focus. This imbalance may undermine efforts to promote UHI mitigation and adaptation strategies in cities outside Taipei. Overall, this study highlights that UHI is not solely a problem of Taipei but a widespread issue across Taiwan’s urban areas. The findings provide useful references for policymakers and government agencies, emphasizing the need for equitable attention and broader public engagement through media channels to raise awareness and foster comprehensive climate adaptation actions. Full article

Climate change continues to threaten global biodiversity, making it essential to assess how keystone species may shift their distributions and to use these findings to inform conservation planning. This study evaluated the current and future habitat suitability of D. macropodum, an important tree species within subtropical evergreen broad-leaved forests in China, using 354 occurrence records and a suite of environmental variables. A parameter-optimized MaxEnt model (calibrated with ENMeval; RM = 4, FC = QHPT) was applied to simulate the species’ present distribution and projected changes under three climate scenarios (SSP126, SSP245, SSP585). The main factors influencing distribution were determined to be moisture and temperature seasonality, with the precipitation of the coldest quarter (Bio19, 36.3%), the mean diurnal range (Bio2, 37.5%), and the precipitation of the warmest quarter (Bio18, 14.2%) jointly contributing 88.0% of the total influence. The model projections indicated a 40.1% reduction in the total number of suitable habitats under high-emission scenarios (SSP585) by the 2090s, including a loss of over 80% of highly suitable areas. Centroid movements also diverged across the scenarios: a southwestern shift under SSP126 and SSP245 contrasted with a southeastern shift under SSP585, with each accompanied by significant habitat fragmentation. Key climate refugia were identified primarily in central Taiwan Province and the mountainous zones of Zhejiang and Fujian Provinces, which should be prioritized for conservation activities. These insights offer a foundational understanding for the conservation of D. macropodum and other ecologically similar subtropical evergreen species. However, direct extrapolation to other taxa should be made cautiously, as specific responses may vary based on differing ecological tolerances and dispersal capacities. Further research is needed to test the generalizability of these patterns across diverse plant functional types. Full article

Red bricks serve as an important material for load-bearing or enclosing structures in traditional architecture and are widely used in construction projects both domestically and internationally. Fujian red bricks, due to geographical, trade, and immigration-related factors, have spread to Taiwan and various regions in Southeast Asia, giving rise to distinctive red brick architectural complexes. To further investigate the types of damage, such as cracking and missing bricks, that occur in traditional red brick buildings due to multiple factors, including climate and human activities, this study takes Fujian red brick buildings as its research subject. It employs the YOLOv12 rapid detection method to conduct technical support research on structural assessment, type detection, and damage localization of surface damage in red brick building materials. The experimental model was conducted through the following procedures: on-site photo collection, slice marking, creation of an image training set, establishment of an iterative model training, accuracy analysis, and experimental result verification. Based on this, the causes of damage types and corresponding countermeasures were analyzed. The objective of this study is to attempt to utilize computer vision image recognition technology to provide practical, automated detection and efficient identification methods for damage types in red brick building brick structures, particularly those involving physical and mechanical structural damage that severely threaten the overall structural safety of the building. This research model will reduce the complex manual processes typically involved, thereby improving work efficiency. This enables the development of customized intervention strategies with minimal impact and enhanced timeliness for the maintenance, repair, and preservation of red brick buildings, further advancing the practical application of intelligent protection for architectural heritage. Full article