Search Results (60)

Grazing shapes rangelands globally, but it is difficult to study. Acoustic monitoring enables grazing to be described in terms of jaw movements, which are fundamental to how herbivores interact with their foraging environment. In an observational study on Mediterranean herbaceous rangeland, 10 beef cattle cows were monitored continuously over multiple days in two seasons. The algorithm used to analyze the acoustic signal furnished (without classification) a data sample of ≈5 M ingestive and ruminatory jaw movements. These were analyzed as between-event intervals and as minutely rates. The rumination displayed a consistent, strong rhythm and pattern of jaw movements. In contrast, there was no single “signature” jaw movement pattern for grazing (i.e., non-rumination). Although the underlying natural rhythm of rumination dominated non-rumination, it was intermittently and irregularly interrupted by longer intervals, whose size scaled logarithmically. There was evidence of further substructure, with a degree of separation between “grazing” and “resting” in the conventional sense. Three broad grazing styles emerged. In the “intense” style, animals sustained long runs of jaw movements in the natural rhythm, with relatively few interruptions. In the “regular” style, comprising the majority of non-rumination jaw activity, the natural rhythm still dominated, but was punctuated at irregular intervals by eruptions of somewhat longer intervals. The “diffuse” style comprised shorter runs in the natural rhythm, punctuated by highly erratic intervals spanning orders of magnitude. When the jaw movement events were viewed as minutely rates, the non-rumination population showed strong bimodality in the distribution of non-zero rates, with peaks at ≈60 and ≈15 jaw movements min⁻¹, suggesting two modes of grazing. The results strongly support the notion of behavioral grazing intensity and call into question the approach of viewing grazing as a binary state or expecting measures of grazing time to be strongly indicative of intake rate. Rate- and interval-based analyses of information at the jaw movement level can yield a penetrating profile of how an animal interacts with its foraging environment, epitomized in a graphical formulation termed the time accumulation curve. These results strengthen the case for the further development of this sensor technology. Full article

The arid region of Northwest China (ARNC) is responsive to global climate change, and drought events have occurred frequently in recent decades. However, studies about the effect of meteorological and drought stress on vegetation change in the ARNC are still insufficient. In this study, we analyzed the spatiotemporal trends of meteorological factors (temperature, TMP; precipitation, PRE; standardized precipitation evapotranspiration index, SPEI), drought stress factors (vapor pressure deficit, VPD; soil moisture, SM), and vegetation (normalized difference vegetation index, NDVI) during 1982–2021. We also investigated the characteristics of drought events by the run theory, including drought times, drought duration, drought severity, and drought intensity. The impacts of meteorological and drought stress factors on the vegetation were explored using Pearson correlation analysis and the structural equation model (SEM). We found that the annual and growing season TMP, PRE, VPD, SM, and NDVI showed an increasing trend in the ARNC during 1982–2021. In contrast, SPEI exhibited a decreasing trend in the annual and growing season. In addition, the characteristics of the drought events varied significantly in the ARNC. The drought events primarily occurred in the Tarim River Basin, Turpan-Hami Basin, and the Hexi Corridor. The Pearson correlation analysis and SEM results consistently demonstrated that TMP and SM exerted greater impacts on vegetation growth than PRE, VPD, and SPEI. The factors that determine vegetation change were TMP and PRE. Exploration of meteorological and drought stress factors that influence vegetation change is essential for comprehending the influence of dominant factors on vegetation change. Full article

The study of regional drought characteristics is vital for identifying drought patterns and offering scientifically informed guidance for drought warnings. This research focuses on the Sichuan Basin, where the Standardized Precipitation Evapotranspiration Index (SPEI) was calculated across various time scales using meteorological data from 1963 to 2022. Wavelet analysis was applied to examine the periodic fluctuations of the SPEI across different time scales. Drought events were identified using run-length theory and spatially visualized with ArcGIS 10.7 interpolation techniques to elucidate the temporal and spatial dynamics of drought occurrences. The findings are as follows: (1) Over nearly 60 years, the SPEI in the Sichuan Basin fluctuated between −1.5 and 1, with an insignificant annual downward trend but a significant downward trend in autumn (p < 0.05). (2) The SPEI displayed a primary cycle of 6 years in spring, autumn, and winter, while the summer cycle matched the annual SPEI cycle of 8 years. (3) Drought events were more frequent in the eastern part of the basin compared to the west. The area with high drought frequency shifted counterclockwise from east to north, northwest, west, and south with the changing seasons. (4) Drought duration was longer in the western and northern regions of the basin than in the east. Severe drought events were mainly concentrated in the Chengdu Plain and the Central Sichuan Hilly Region, although the drought intensity index was lowest in the Chengdu Plain and Chongqing in eastern Sichuan. The peak values of drought showed an insignificant decreasing trend, indicating a potential expansion in the extreme impacts of drought disasters in the study area. Full article

Liaoning Province, a crucial agricultural region in Northeast China, has endured frequent drought disasters in recent years, significantly affecting both agricultural production and the ecological environment. Conducting drought research is of paramount importance for formulating scientific drought monitoring and prevention strategies, ensuring agricultural production and ecological safety. This study developed a Comprehensive Joint Drought Index (CJDI) using the empirical Copula function to systematically analyze drought events in Liaoning Province from 1981 to 2020. Through the application of MK trend tests, Morlet wavelet analysis, and run theory, the spatiotemporal variation patterns and recurrence characteristics of drought in Liaoning Province were thoroughly investigated. The results show that, compared to the three classic drought indices, Standardized Precipitation Index (SPI), Evaporative Demand Drought Index (EDDI), and Standardized Precipitation Evapotranspiration Index (SPEI), CJDI has the highest accuracy in monitoring actual drought events. From 1981 to 2020, drought intensity in all regions of Liaoning Province (east, west, south, and north) exhibited an upward trend, with the western region experiencing the most significant increase, as evidenced by an MK test Z-value of −4.53. Drought events in Liaoning Province show clear seasonality, with the most significant periodic fluctuations in spring (main cycles of 5–20 years, longer cycles of 40–57 years), while the frequency and variability of drought events in autumn and winter are lower. Mild droughts frequently occur in Liaoning Province, with joint and co-occurrence recurrence periods ranging from 1.0 to 1.8 years. Moderate droughts have shorter joint recurrence periods in the eastern region (1.2–1.4 years) and longer in the western and southern regions (1.4–2.2 years), with the longest co-occurrence recurrence period in the southern region (3.0–4.0 years). Severe and extreme droughts are less frequent in Liaoning Province. This study provides a scientific foundation for drought monitoring and prevention in Liaoning Province and serves as a valuable reference for developing agricultural production strategies to adapt to climate change. Full article

Recent increases in extreme events, especially those near and beyond previous records, are a new index for Arctic and global climate change. They vary by type, location, and season. These record-shattering events often have no known historical analogues and suggest that other climate surprises are in store. Twenty-six unprecedented events from 2022, 2023, and early 2024 include record summer temperatures/heatwaves, storms, major Canadian wildfires, early continental snow melt, Greenland melt, sea temperatures of 5–7 °C above normal, drought in Iceland, and low northern Alaskan salmon runs. Collectively, such diverse extremes form a consilience, the principle that evidence from independent, unrelated sources converge as a strong indicator of ongoing Arctic change. These new behaviors represent emergent phenomenon. Emergence occurs when multiple processes interact to produce new properties, such as the interaction of Arctic amplification with the normal range of major weather events. Examples are typhon Merbok that resulted in extensive coastal erosion in the Bering Sea, Greenland melt, and record temperatures and melt in Svalbard. The Arctic can now be considered to be in a different state to before fifteen years ago. Communities must adapt for such intermittent events to avoid worst-case scenarios. Full article

Ungulates are terrestrial herbivores, basically adapted to running fast on the ground; tree-climbing behavior has been reported only in seven species, and five of them live in open habitats (Capra hircus, C. aegagrus, C. falconeri, C. cylindricornis, Oreotragus oreotragus). Tree-climbing behavior may also be evolved in ungulates inhabiting dense forests with abundant trees; however, this has rarely been reported in such species (Moschus leucogaster, M. moschiferus), probably due to the difficulty of observing in the wild. The numerous publicly available records in social networks hold potentially valuable information on the atypical behaviors of wild ungulates. Here, we explored the tree-climbing behavior of a forest-dwelling ungulate, the Formosan serow in Taiwan, a subtropical island, by extracting information from online social media platforms. We researched images and videos of Formosan serows through Facebook and YouTube and collected a total of 15 tree-climbing events. In these materials, Formosan serows climbed 10 tree species, including evergreen coniferous and broad-leaved trees, and a variety of parts, ranging in height from 0.6 to 4 m, and from branches of shrubs to trunks of tall trees. Tree-climbing behavior was recorded throughout Taiwan and from lowlands to subalpine zones, suggesting that tree climbing may be a common behavior in this species. Foraging while climbing trees was frequently observed (53.3%), suggesting that the purpose or benefit for climbing is to obtain additional food other than plants growing near the ground surface. In contrast to other tree-climbing ungulates, Formosan serows climbed trees not only in winter, but also in other seasons, when food is relatively abundant. This is the first scientific report of tree-climbing behavior in the Formosan serow that is typically a forest dweller. Full article

This study examines the representation of blocking events in the Southeast Pacific and Southwest Atlantic regions using a set of 13 global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Historical runs were employed to analyze blocking conditions in the recent past climate, spanning from 1985 to 2014, with ERA5 data utilized to represent observed blocking events. The majority of CMIP6 models underestimate the total number of blocking events in the Southeast Pacific. The MPI–ESM1–2–HR and MPI–ESM1–2–LR models come closest to replicating the number of blocking events observed in ERA5, with underestimations of approximately −10% and −9%, respectively. Nonetheless, these models successfully capture the seasonality and overall duration of blocking events, as well as accurately represent the position of blocking heights over the Southeast Pacific. Conversely, CMIP6 models perform poorly in representing blocking climatology in the Southwest Atlantic. These models both overestimate and underestimate the total number of blocking events by more than 25% compared to ERA5. Furthermore, they struggle to reproduce the seasonal distribution of blockings and face challenges in accurately representing the duration of blocking events observed in ERA5. Full article

It is crucial to identify drought characteristics and determine drought severity in response to climate change. Aiming at the increasingly serious drought situation in the Yellow River Basin, this study firstly selected the standardized precipitation index (SPI) and streamflow drought index (SDI) to analyze the characteristics of drought seasons, then identified the frequency, duration, and intensity of drought based on the run theory, and finally recognized the abrupt changing and driving factors of major drought events in specific years by the Mann–Kendall trend test. The conclusions showed the following: (1) The drought in the downstream of the Yellow River Basin was more severe than that in the upstream. The drought characteristics showed significant regional differentiation and deterioration. (2) The drought intensity and duration had an obvious spatial correlation. Compared with the other seasons, the drought duration and severity in spring and autumn were the most serious, and in winter, they showed an aggravating trend. (3) According to a time series analysis of drought conditions in the Yellow River Basin, the worst drought occurred in 1997–2001 with the least rainfall on record and a sudden rise in temperatures. This study could provide a scientific reference for agricultural drought disaster prevention and mitigation. Full article

A series of typhoons and tropical storms have produced extreme precipitation events in Vietnam during the first part of the 2020 monsoon season: events of this magnitude pose significant challenges to remote sensing Quantitative Precipitation Estimation (QPE) techniques. The weather-monitoring needs of modern human activities require that these challenges be overcome. In order to address this issue, in this work, seven precipitation products were validated with high spatial and temporal detail against over 1200 rain gauges in Vietnam during six case studies tailored around the most intense events of 2020. The data sources included the Vietnamese weather radar network, IMERG Early run and Final run, the South Korean GEO-KOMPSAT-2A and Chinese FengYun-4A geostationary satellites, DPR on board the GPM-Core Observatory, and European ERA5-Land reanalysis. All products were resampled to a standardized 0.02° grid and compared at hourly scale with ground stations measurements. The results indicated that the radars product was the most capable of reproducing the information collected by the rain gauges during the selected extreme events, with a correlation coefficient of 0.70 and a coefficient of variation of 1.38. However, it exhibited some underestimation, approximately 30%, in both occurrence and intensity. Conversely, geostationary products tended to overestimate moderate rain rates (FY-4A) and areas with low precipitation (GK-2A). More complex products such as ERA5-Land and IMERG failed to capture the highest intensities typical of extreme events, while GPM-DPR showed promising results in detecting the highest rain rates, but its capability to observe isolated events was limited by its intermittent coverage. Full article

Introduction: Wildfires impact large populations worldwide with increasing frequency and severity. In Canada, the fire season has affected more areas this year with potential implications for individuals’ well-being and quality of life (QoL). Objective: This study aimed to explore data related to the well-being and QoL of individuals living in areas impacted by wildfires in two Canadian provinces. Methodology: A cross-sectional survey was used to collect data from the residents in the two provinces who subscribed to the Text4Hope mental health support service. Descriptive and inferential statistics were applied using World Health Organization Well-Being Index (WHO-5). Results: Out of 1802 Text4Hope subscribers, 298 responded to the baseline surveys, yielding a response rate of (16.5%). The mean score of QoL was (40.8/100 ± 20.7). Most respondents were from Alberta (84.2%), 40 years old or below (28.3%), females (85.2%), Caucasian (83.5%), in a relationship (56.4%), employed (63.6%), received diagnoses of depression (56.6%), and anxiety (52.9%).The overall prevalence of low QoL was (67.3%; 95% CI: 61.2–73.1%) that was mostly reported among subscribers who were from Nova Scotia (70.5%), 40 years old or younger (71.2%), other gender (83.3%), Black/Hispanic and other ethnicity (85.7% each), having high-school or less education (70.3%), not in a relationship (74.1%), and unemployed (73.6%). In terms of clinical factors, low QoL was most prevalent among those who received the diagnoses of depression (74%) and anxiety (74.3%), and those who have been receiving antidepressants (71.8%) or benzodiazepines (93.3%). Regarding wildfire-related factors, the highest prevalence of low QoL was reported among those living in a region that has recently been impacted by the wildfires (74.7%) and those who have been less frequently watching television images about the devastation caused by the recent wildfires (72.6%). The multivariate logistic regression analysis model predicting the low QoL including the various variables was statistically significant; Χ² (df = 19; n = 254) = 31.69, p = 0.03. It was found that living in a region impacted by wildfires (37.9%) was the only significant predictor of low QoL (adjusted OR: 1.96; 95% CI: 1.05–3.65). Conclusions: The impact of wildfire on the QoL and well-being among people living in impacted regions is significant. It is empirical for the health authorities to support those who are disadvantaged by wildfire via running of screening programs to early identify mental health symptoms and addressing the living conditions of the survivors, along with the provision of innovative means of mental health support. This necessitates enhanced planning of the governments and health authorities to overcome such adverse psychological consequences of these events. Full article

The Lancang-Mekong River Basin (LMRB) is one of the major transboundary basins globally, facing ongoing challenges due to flood and drought disasters. Particularly in the past two decades, the basin has experienced an increased frequency of meteorological drought events, posing serious threats to the local socio-economic structures and ecological systems. Thus, this study aimed to analyze the meteorological drought characteristics in the LMRB and identify the impact and correlation of atmospheric circulation on the meteorological drought in the basin. Specifically, the different levels of meteorological drought events were defined using the Run Theory based on the seasonal and annual SPEI from 1980 to 2018. The time lag correlation between meteorological drought events and the EI Nino-Southern Oscillation (ENSO), Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO), were analyzed in the LMRB. Our results indicated that, from a temporal perspective, the period from November to April of the following year was particularly prone to meteorological droughts in the basin. In terms of spatial distribution, the primary agricultural regions within the basin, including Thailand, Eastern Cambodia, and Vietnam, were highly susceptible to meteorological droughts. Further analysis revealed a teleconnection between drought events in the LMRB and atmospheric circulation factors. The sensitivity of the basin’s drought timing to its response decreased in the order of the ENSO > AO > NAO > PDO. In general, the ENSO had the most substantial influence on drought events in the basin, with the strongest response relationship, while the upper reaches of the basin displayed the most significant response to the AO; the occurrence and progression of meteorological droughts in this area synchronized with the AO. These findings enhance our understanding of drought-prone areas in the LMRB, including the meteorological factors and driving mechanisms involved. This information is valuable for effectively mitigating and managing drought risks in the region. Full article

The sustainability of tourism activities faces many challenges. Furthermore, in the context of the Sustainable Development Goals (SDGs) and their overall slow progress, tourism-related goals and targets are underachieved. To address these challenges, this study has recognized sporting events as an opportunity to enhance the socio-economic activities in tourism destinations during off-season periods. More specifically, the aim of this study is to explore the dynamics of off-season destination resilience through small-scale running events, focusing on three key aspects: the strategies employed by organizers, the synergy created within the community, and the sustainable outcomes. Drawing on insights from qualitative interviews with twenty-five running event organizers across Greece, supported by the Delphi method to confirm and validate the results, their perceptions of the economic and socio-cultural dimensions are explored. This study identifies a number of strategies that enrich running events and can contribute to the sustainability of off-peak destinations. Additionally, the concept of synergy is identified and explored, emphasizing the importance of local engagement, participant encouragement, and community collaborations. These findings provide a comprehensive understanding of how these factors can influence the sustainability of off-peak destinations. To further validate and extend these findings, the second part of this study performs a quantitative analysis using PLS-SEM, involving eighty local authorities in Greece. The results highlight the mediating role of small-scale event enrichment strategies on the relationship between synergy and destination sustainability. This multifaceted approach indicates the dynamics of sustainable tourism, by examining the case of small-scale running events in the off-peak season. The impact of this balanced approach on the broader achievement of relevant SDGs is also supported. The implications of this research, in terms of its strategic and stakeholder orientation for tourism professionals and government agencies, are also discussed. Full article

The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change. Full article

Much of the Southeastern United States (SeUS) has experienced an increasing number of extreme precipitation events in recent decades. Characterizing these extreme precipitation events is critical for assessing risk from future hydroclimatic extremes and potential flash flooding. A threshold of one inch per hour (1IPH) was used to indicate an extreme precipitation event. Non-parametric tests were run to identify trends in 1IPH event frequency and locate time series change points. In the last 20 years, 1IPH events increased by 53 percent in the SeUS, and 21/61 stations recorded significant increasing trends. A change point is identified in 15/61 stations. June, July, and August are generally the peak time for 1IPH events, but Florida, Louisiana, and Mississippi recorded longer peak seasons. For the time between events, 17/61 stations recorded significant decreasing trends, implying that 1IPH events are increasing in frequency. Four teleconnection indices were positively correlated with 1IPH events. The SeUS experiences considerable tropical cyclone-induced extreme precipitation, yet only seven percent of 1IPH events overlapped with tropical cyclones. Therefore, the increasing frequency of 1IPH events is likely the result of a combination of baroclinic frontal zones or regional and mesoscale convective features. Causes for the increasing frequency of 1IPH events require further research. Full article

Landform evolution modelling (LEM) provides an avenue for simulating how a landscape may evolve over extended time periods of thousands of years. CAESAR-Lisflood LEM which includes a hydrologic model (TOPMODEL) and a hydraulic model (Lisflood) can be used to assess the proposed final landform morphology of a mine site by simulating how the mine landform and the landscape would evolve over a 1000-year period. The accuracy of future simulations depends on the calibration and validation of the model to past and present events. Calibration and validation of the model involve finding a combination of parameters of the model which when applied and simulated gives model outputs similar to those observed for the real site scenario for corresponding input data. Calibrating the sediment output of the CAESAR-Lisflood model at the catchment level and using it for studying the equilibrium conditions of the landform is an area that has yet to be explored. Therefore, the aim of this study was to calibrate the CAESAR-Lisflood model and then validate it. To achieve this, the model was run for a rainfall event with a set of parameters, plus discharge and sediment data for the input point of the catchment, to analyse how similar the model output would behave when compared with the discharge and sediment data for the output point of the catchment. The model parameters were then adjusted until the model closely approximated the real site values of the catchment. The model was then validated by running it for a different set of events and checking that the model gave similar results to the real site values. The outcomes demonstrated that while the model can be calibrated to a greater extent for hydrology (discharge output) throughout the year, sediment output calibration may be slightly improved via the ability to change parameters to take into account the seasonal vegetation growth during the start and end of the wet season. This study is important for designing and testing post-mining rehabilitated landscape systems that assess hydrology and sediment movement in seasonal biomes. Full article