Combination Of Climate Change Research Articles

Assessment of the coherence of groundwater levels in coastal aquifers with climate change and anthropogenic activity

This study aimed to assess the coherence between groundwater levels and various factors during two distinct periods, 2002–2020 and 2025–2050, in Miandoab aquifer in northwestern of the Iran. Partial wavelet coherence and multi-wavelet coherence analyses were employed to assess the coherence between individual parameters and their simultaneous coherence. The factors considered in the study were derived from remote sensing data, including Gravity Recovery and Climate Experiment data and Landsat data, which were utilized to examine water storage anomalies and anthropogenic activity, respectively. Additionally, General Circulation Models were employed to predict groundwater levels under future climate change scenarios via a feedforward neural network. To streamline the modeling process and categorize piezometers, with each group reflecting different patterns, clustering techniques were applied to group multiple piezometers. There were four final clusters, and representative piezometers from each cluster were chosen as targets for modeling and future predictions. Finally, the differences in coherence between past and future periods were compared and analyzed. The results revealed decreasing trends in groundwater level, precipitation and soil moisture index in 2025–2050; however, there were increasing trends in normalized difference vegetation index and temperature. In addition, wavelet analysis indicated that during the period 2025–2050, the delay in interaction between groundwater level and various factors decreased to 0–4 months, whereas longer delays were observed for the period 2002–2020. The analysis of multi- wavelet coherence showed that the combination of climate change and anthropogenic activity may have more significant coherence (0.9–1) with groundwater level than the combination of gravity recovery and climate experiment data and soil moisture index. The results highlight the greater significance of gravity recovery and climate experiment data in terms of coherence with groundwater levels compared to other factors.

Wildfire risk management in the era of climate change.

The August 8, 2023R Lahaina fire refocused attention on wildfires, public alerts, and emergency management. Wildfire risk is on the rise, precipitated through a combination of climate change, increased development in the wildland-urban interface (WUI), decades of unmitigated biomass accumulation in forests, and a long history of emphasis on fire suppression over hazard mitigation. Stemming the tide of wildfire death and destruction will involve bringing together diverse scientific disciplines into policy. Renewed emphasis is needed on emergency alerts and community evacuations. Land management strategies need to account for the impact of climate change and hazard mitigation on forest ecosystems. Here, we propose a long-term strategy consisting of integrating wildfire risk management in wider-scope forest land management policies and strategies, and we discuss new technologies and possible scientific breakthroughs.

Quantifying the spatial aggregation bias of urban heat data

Every year, high temperatures send people to the hospital and morgue, and the combination of climate change and urbanization will increase extreme heat exposure. Cities are searching for ways to determine the most affected areas to begin addressing this pervasive issue. While we are living through the “big data” revolution, policy makers are still uncertain about what level of data is most useful. We evaluate the data loss from using data at different spatial resolutions to evaluate heat vulnerability, as both the definition of intra-urban heat and the resolution of the data affect the area identified and targeted for mitigation. Variance-based metrics provide many advantages, but when data is aggregated, these metrics are less able to represent the full range of urban heat. Using the case of Bexar County (home to San Antonio, TX), we find that increasing data aggregation increases both false positive and false negative identification of intra-urban heat islands, leading to unreliable results. Misclassification increases as aggregation increases, indicating that decisions should be made at the finest spatial resolution possible.

Dynamic Change and Attribution Regarding Fractional Vegetation Coverage in Mengdong River Basin

The situation of rocky desertification in the southwestern part of China is very serious and has been included as one of three major ecological problems. In this study, using Landsat images as the data sources, we estimated the fractional vegetation coverage (FVC) in the Mengdong River Basin in the Hunan Province over the past 40 years, analyzed its spatio-temporal variation characteristics, and explored the driving mechanism (climate and anthropogenic) using the Mann–Kendall, Hurst index, and partial correlation methods. Specifically, the impact of ecological engineering on the recovery of vegetation cover in rocky desertification areas was analyzed and discussed in this study. The results demonstrate the following: (1) The changes in FVC in the study area before and after the rocky desertification management ecological project differed significantly, with a very small change in the rate of change in the mean value of FVC between 1987 and 1999 (<0.1%), while the FVC had a significant linear growth trend between 2000 and 2022 (>0.9%). (2) The Hurst index of FVC ranged from −0.233 to 2.476, with an average value of 0.864. The area with an H value greater than 0.75 accounted for 80.12%, indicating that the future trend in the vast majority of regions will develop in accordance with the current change trend. (3) The average partial correlation coefficients between FVC and precipitation and between FVC and temperature were −0.02 and 0.27, respectively, showing that FVC is more sensitive to temperature than precipitation. The combination of climate change and human activities is the main cause of FVC change. The contributions of climate change (precipitation and temperature) and human activities to FVC variation are about 30% and 70%, respectively. Ecological restoration projects have a significant positive effect on the recovery of vegetation in rocky desertification areas. The results of this study are intended to provide a scientific basis for analyzing the characteristics of vegetation restoration in existing rocky desertification areas and ecological management in future rocky desertification areas.

Are forest management practices to improve carbon balance compatible with maintaining bird diversity under climate change? A case study in Eastern North America

The combination of climate change and anthropogenic disturbance significantly impacts forest bird assemblages. Assessing the cumulative effects of forest management and climate change on biodiversity and ecosystem services, including carbon sequestration and storage and provisioning of wood products is key to informing forest management and conservation decision making. Specifically, we projected changes in forest composition and structure according to various forest management strategies under a changing climate using LANDIS-II for two case study areas of Quebec (Canada): a hemiboreal (Hereford Forest) and a boreal (Montmorency Forest) area. Then, we assessed projected bird assemblage changes, as well as sensitive and at-risk species. As part of an integrated assessment, we evaluated the best possible management measures aimed at preserving avian diversity and compared them with optimal options for mitigation of carbon emissions to the atmosphere. Forest management and climate change were projected to lead to significant changes in bird assemblages in both types of forest through changes in forest composition. We projected an increase in deciduous vegetation which favored species associated with mixed and deciduous stands to the detriment of species associated with older, coniferous forests. Changes were more pronounced in Hereford Forest than Montmorency Forest. In addition, Hereford’s bird assemblages were mainly affected by climate change, while those in Montmorency Forest were more impacted by forest management. We estimated that 25% of Hereford and 6% of Montmorency species will be sensitive to climate change, with projected abundance changes (positive or negative) exceeding 25%. According to the simulations, a decrease in the level of forest harvesting could benefit bird conservation and contribute to reduction of carbon emissions in the boreal forest area. Conversely, the hemiboreal forest area require trade-offs, as mitigation of carbon emissions is favored by more intensive forest management that stimulates the growth and carbon sequestration of otherwise stagnant stands.

A statewide, weather-regime based stochastic weather generator for process-based bottom-up climate risk assessments in California – Part II: Thermodynamic and dynamic climate change scenarios

This study is the second of a two-part series presenting a novel weather regime-based stochastic weather generator to support bottom-up climate vulnerability assessments of water systems in California. In Part 2 of this series, we present how the model is used to develop an ensemble of climate change scenarios based on both thermodynamic and dynamic signals of climate change. The ensemble includes a suite of 30 climate change scenarios, each consisting of 1000 years of simulated daily climate data (precipitation, maximum temperature, minimum temperature) at a 6 km resolution across the entire state of California. The 30 scenarios represent a range of plausible climate changes to temperature, average precipitation, and precipitation extremes that are reflective of thermodynamic responses of the atmosphere to warming. An additional two scenarios are also created that represent changes in the frequency of weather regimes (e.g., dynamic climate change). Results from these scenarios reveal that when the effects of anthropogenic climate change are combined with plausible realizations of natural climate variability, the severity of extremes in California is amplified significantly. In addition, recent changes in the frequency of large-scale patterns of atmospheric circulation can have impacts of similar magnitude to large (>10%) declines in average precipitation, particularly with respect to drought. The scenarios developed in this work are designed to allow water managers to systematically test the sensitivity of their water system to different combinations of climate change, so that key vulnerabilities can be discovered and then addressed through adaptation planning.

Variation of material fluxes in a large heterogenic subtropical river: A combination of climate change and human damming influences

Study regionThe West River, the main tributary of the Pearl River, China Study focusA hydrological model of the West River was successfully established and used to quantify the role of basin-wide spatiotemporal change of the impacts of climate change and human damming activities in the variation of material fluxes (water discharge and sediment load) at the river outlet at both interannual and seasonal time scales of the period from 1975 to 2017. New hydrological insights for the regionThe interannual variations of water discharge and sediment load were controlled by a single factor locally: runoff variation was positively correlated with the ENSO index (r = 0.56, p < 0.001) and the dams caused a 75.1% reduction of the annual sediment load in the post-dam period (2009–2017). Seasonally, climate change can alter the monthly water discharge by − 12–23% in the latter half of an abnormal year, while the dams caused a 4.6% reduction and a 12.4% increase in the summer and winter sediment load, respectively. There was a strong interaction between the two influencing factors seasonally, particularly during the wetter summer or drier winter, wherein the dominant driving mechanism in the monthly variation of material fluxes can switch. For the river basin, the impacts of climate change and dams are spatially variable. The basin-wide spatiotemporal change of the impacts of climate change and human damming activities can complicate the hydrological signal at the river outlet.

Monitoring Lake Level Changes in Bosten Lake from 2003-2021 based on Multi-source Satellite Altimetry Data

The investigation of freshwater lake water resource changes in arid regions is crucial for understanding the evolution of regional lake dynamics under climate change, given their value and limited availability. This study aims to overcome the limitations of traditional water level monitoring methods and address the practical need for monitoring water level changes in Lake Bosten, located in the arid and semi-arid regions of China. To this end, we employed ICESat, ICESat-2, and CryoSat-2 altimetry data, as well as Landsat 8-OLI optical remote sensing data, to obtain the water level information for Bosten Lake from 2003 to 2022. We analyzed the temporal variation of the lake level and discussed the response of the lake level to climate and human activities in the context of temperature, precipitation data, and human water use. The water level of Lake Bosten exhibited a decreasing and then increasing trend, with three rising and three falling intervals, respectively. The intra-year variation of the lake water level exhibited bimodal characteristics, and the fluctuation range of water level during abundant water periods was greater than that during dry periods. Finally, we correlated the extracted lake water level with the measured water level at the hydrological station and found a significant positive linear correlation between the observed water level of Bosten Lake based on satellite altimetry and the measured water level at the hydrological station, with an overall correlation coefficient of 0.896 and 0.934 (P &lt; 0.01), indicating high accuracy of the water level results obtained in this study. The dynamics of Lake Bosten are influenced by a combination of climate change, hydrological elements, and human activities, with a relatively weak relationship between climate change and lake volume and a strong influence of human activities. Multi-source altimetry satellites provide a powerful tool for monitoring lake water levels over a long time scale, which is critical for studying lake water level changes and their response to climate and the environment.

The impact of climate change and human activities to vegetation carbon sequestration variation in Sichuan and Chongqing

Exploring the vegetation carbon cycle and the factors influencing vegetation carbon sequestration in areas with complex plateau-basin topography and fragile ecosystems is crucial. In this study, spatial and temporal characteristics of carbon sequestration by vegetation in Sichuan and Chongqing from 2010 to 2020 and the influencing factors were investigated through simulations of net primary productivity (NPP) using the modified Carnegie-Ames-Stanford approach (CASA) and the Thornthwaite Memorial (TM) model and using chemical equations of photochemical reactions. The results indicated that: The spatial distribution of carbon sequestration capacity (CSC) trends showed an increase in the east (the most prominent increased trend along the mountainous areas of the basin) and a decrease in the west (western Sichuan plateau). Differences exist in the impact factors of CSC in different regions. In the basin margins and mountainous areas, where the proportion of forests was high, a combination of climate change and human activities contributed to the increase in CSC. The relatively warm and humid meteorological conditions in the hinterland of the basin were more conducive to the increase in CSC, and climate change also affected the region more significantly. In contrast, in the relatively high altitude of western Sichuan, controlled human activities were the key to improving CSC. The results of the study contribute to the understanding of the basic theory of vegetation carbon cycle in areas with complex plateau-basin topography and fragile ecosystems, as well as to provide suggestions for ecological shelter construction and ecological restoration in the upper Yangtze River.

Using multi-platform LiDAR to guide the conservation of the world's largest temperate woodland

Australia's Great Western Woodlands are the largest intact temperate woodland ecosystem on Earth, spanning an area the size of the average European country. These woodlands are part of one of the world's biodiversity hotspots and, despite subsisting on just 200–400 mm of rainfall a year, can store considerable amounts of carbon. However, they face growing pressure from a combination of climate change and increasingly frequent and large wildfires, which have burned over a third of these slow-growing, fire-sensitive woodlands in last 50 years alone. To develop conservation strategies that bolster the long-term resilience of this unique ecosystem, we urgently need to understand how much old-growth woodland habitat remains intact and where it is distributed across this vast region. To tackle this challenge, we brought together data from an extensive network of field plots distributed across the region and combined this with information on vegetation 3D structure derived from drone, airborne and spaceborne LiDAR. Using this unique dataset, we developed a novel modelling framework to generate the first high-resolution maps of woodland tree size and age structure across the entire region. We found that 41.2% of the woodland habitat is covered by old-growth stands, equivalent to an area of approximately 39,187 km2. Only 10% of these old-growth woodlands fall within current protected areas managed by the state government. Instead, most remaining old-growth woodlands are found either within the Ngadju Indigenous Protected Area (26.9%) or outside of formal protected areas on leaseholds and privately owned lands (57.2%). Our maps of woodland size and age structure will help guide the targeted management and conservation of the Great Western Woodlands. Moreover, by developing a robust pipeline for integrating LiDAR data from multiple platforms, our study paves the way for mapping the 3D structure and carbon storage of open and heterogeneous woodland ecosystems from space.

Quantifying the effects of nature-based solutions in reducing risks from hydrometeorological hazards: Examples from Europe

The combination of climate change and social and ecological factors will increase risks societies face from hydrometeorological hazards (HMH). Reducing these risks is typically achieved through the deployment of engineered (or grey) infrastructure but increasingly, nature-based solutions (NBS) are being considered. Most risk assessment frameworks do not allow capturing well the role NBS can play in addressing all components of risk, i.e., the hazard characteristics and the exposure and vulnerability of social-ecological systems. Recently, the Vulnerability and Risk assessment framework developed to allow the assessment of risks in the context of NBS implementation (VR-NBS framework) was proposed. Here, we carry out the first implementation of this framework using five case study areas in Europe which are exposed to various HMH. Our results show that we can demonstrate the effect NBS have in terms of risk reduction and that this can be achieved by using a flexible library of indicators that allows to capture the specificities of each case study hazard, social and ecological circumstances. The approach appears to be more effective for larger case study areas, but further testing is required in a broader variety of contexts.

The long-distance relationship between Dirofilaria and the UK: case report and literature review.

Over the last two decades, vector-borne pathogens (VBPs) have changed their distribution across the globe as a consequence of a variety of environmental, socioeconomic and geopolitical factors. Dirofilaria immitis and Dirofilaria repens are perfect exemplars of European VBPs of One Health concern that have undergone profound changes in their distribution, with new hotspots of infection appearing in previously non-endemic countries. Some areas, such as the United Kingdom, are still considered non-endemic. However, a combination of climate change and the potential spread of invasive mosquito species may change this scenario, exposing the country to the risk of outbreaks of filarial infections. Only a limited number of non-autochthonous cases have been recorded in the United Kingdom to date. These infections remain a diagnostic challenge for clinicians unfamiliar with these "exotic" parasites, which in turn complicates the approach to treatment and management. Therefore, this review aims to (i) describe the first case of D. repens infection in a dog currently resident in Scotland, (ii) summarise the available literature on Dirofilaria spp. infections in both humans and animals in the United Kingdom and (iii) assess the suitability of the United Kingdom for the establishment of these new VBPs.

Modeling the effects of spatially explicit patterns of climate and fire on future populations of a fire-dependent plant

Many plant species are likely to face population decline or even extinction in the coming century, especially those with a limited distribution and inadequate dispersal relative to the projected rates of climate change. The obligate seeding California endemic, Ceanothus perplexans is especially at risk, and depending on how climate change interacts with altered fire regimes in Southern California, certain populations are likely to be more at risk than others. To identify which areas within the species’ range might need conservation intervention, we modeled population dynamics of C. perplexans under various climate and fire regime change scenarios, focusing on spatially explicit patterns in fire frequency. We used a species distribution model to predict the initial range and potential future habitat, while adapting a density-dependent, stage-structured population model to simulate population dynamics. As a fire-adapted obligate seeder, simulated fire events caused C. perplexans seeds to germinate, but also killed all adults in the population. Our simulations showed that the total population would likely decline under any combination of climate change and fire scenario, with the species faring best at an intermediate fire return interval of around 30–50 years. Nevertheless, while the total population declines least with a 30–50 year fire return interval, the effect of individual subpopulations varies depending on spatially explicit patterns in fire simulations. Though climate change is a greater threat to most subpopulations, increased fire frequencies particularly threatened populations in the northwest of the species’ range closest to human development. Subpopulations in the mountainous southern end of the range are likely to face the sharpest declines regardless of fire. Through a combination of species distribution modeling, fire modeling, and spatially explicit demographic simulations, we can better prepare for targeted conservation management of vulnerable species affected by global change.

Downscaling global land-use/cover change scenarios for regional analysis of food, energy, and water subsystems

Integrated assessment models (IAMs) capture synergies between human development and natural ecosystems that have important implications for the food-energy-water (FEW) nexus. However, their lack of fine-scale representation of water regulatory structure and landscape heterogeneity impedes their application to FEW impact studies in water-limited basins. To address this limitation, we developed a framework for studying effects of global change on regional outcomes for food crops, bioenergy, hydropower, and instream flows. We applied the new methodology to the Columbia River Basin (CRB) as a case study. The framework uses the Demeter land-use and land-cover change (LULCC) downscaling tool, which we updated so that water rights are spatially integrated in the land allocation process. We downscaled two LULCC scenarios (SSP2-RCP 4.5 and SSP5-RCP 8.5) under three levels of irrigation expansion: no expansion (historical extent), moderate expansion (all land presently authorized by a water right is irrigated), and maximum expansion (new water rights are granted to cover all irrigable land). The downscaled scenarios were evaluated using a hydrology-cropping systems model and a reservoir model coupled in a linear fashion to quantify changes in food and bioenergy crop production, hydropower generation, and availability of instream flows for fish. The net changes in each sector were partitioned among climate, land use, and irrigation-expansion effects. We found that climate change alone resulted in approximately 50% greater production of switchgrass for bioenergy and 20% greater instream flow deficits. In the irrigation-expansion scenarios, the combination of climate change and greater irrigated extent increased switchgrass production by 76% to 256% at the cost of 42% to 165% greater instream flow deficits and 0% to 8% less hydropower generation. Therefore, while irrigation expansion increased bioenergy crop productivity, it also exacerbated seasonal water shortages, especially for instream use. This paper provides a general framework for assessing benchmark scenarios of global LULCC in terms of their regional FEW subsystem outcomes.

ENSEMBLING OF DECISION TREES, KNN, AND LOGISTIC REGRESSION WITH SOFT-VOTING METHOD FOR WILDFIRE SUSCEPTIBILITY MAPPING

Abstract. As a result of climate change, climatic catastrophes, such as wildfires, are likely to increase. Wildfires continue to occur frequently and spread with greater intensity due to extreme weather conditions. In recent years, explosive fire growths have been reported in the United States, Australia, and other parts of the world. A combination of climate change and human activity has caused the semi-arid forestry areas in Iran's northern provinces to become more desiccated, leading to an increase in wildfires. The accuracy of the resulting fire susceptibility maps (FSMs) will directly be related to the performance of the method classifier. In this study, we use an ensemble classifier to model the FSM for a selected forestry case study area in one of the northern provinces of this country. Therefore, FSM is generated based on established criteria using the ensemble model. With Decision Trees, K nearest neighbor, and Logistic Regression, the ensemble model was created using the soft-voting method. A forest fire inventory data is created based on data collected over five years using GPS and the MODIS thermal anomalies product for training and testing the applied approach. The K-fold method was used for validation, and the resulting FSM was validated using five accuracy assessment metrics. The best result from the area under the curve (AUC) yields 93% for fold 9, and the mean AUC for ten folds yields 88%.

祁连山国家公园植被时空变化及其对人类活动的响应

PDF HTML阅读 XML下载 导出引用 引用提醒 祁连山国家公园植被时空变化及其对人类活动的响应 DOI: 10.5846/stxb202107221990 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 甘肃省创新群体项目（20JR10RA038）；中国科学院"西部之光"交叉团队项目-重点实验室合作研究专项；国家重点研发计划项目（2019YFC0507401） Spatial and temporal changes in vegetation cover and response to human activities in Qilian Mountain National Park Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:祁连山国家公园地处青藏、蒙新、黄土三大高原交汇地带的祁连山北麓，作为国家公园体制试点之一，是我国重要的生态功能区、水源涵养地和生物多样性保护优先区域，其生态功能不可忽视。以祁连山国家公园2000-2019年归一化植被指数（NDVI）和净初级生产力（NPP）数据为基础，结合气温、降水、土地利用、矿产开采和旅游发展数据，利用泰尔-森趋势分析（Theil-Sen趋势分析）、曼-肯德尔检验（Mann-Kendall显著性检验）、土地转移概率矩阵和多元残差分析方法，分析该区域的植被时空分布特征、变化趋势特征及其对气候变化和人类活动的响应。结果表明：（1）2000-2019年祁连山国家公园内NDVI和NPP在空间上呈现出东南高西北低，由东南向西北递减的格局。时间上呈现上升趋势，上升速率分别为0.0053/a和0.0014/a；（2）祁连山国家公园内NPP提高、降低和稳定区域分别占总面积的87.29%、0.40%和12.30%。降低区域零星分布于整个国家公园，其中在走廊南山和冷龙岭交汇处，靠近甘青两省交界边缘分布最为集中。提高区域分布广泛，尤其以国家公园东部最为明显；（3）祁连山国家公园NDVI与气温呈现显著正相关区域约占40.18%，与降水呈现正相关区域约占25.70%，气温上升、降水增多促进了国家公园植被生长，适宜的水热组合对植被生长更有利；（4）人类活动对植被变化的影响具有两面性：约有28.91%矿业、旅游和水电站在整改、规范之后植被生长状况仍较差，生态环境没有明显恢复；退耕还林还草工程、生态林建设工程成效显著，近3年林地、草地面积增多。（5）祁连山国家公园大部分植被覆盖变化是由气候变化和人类活动共同导致。 Abstract:Qilian Mountain National Park is located in the north piedmont of Qilian Mountains at the intersection of Qinghai-Tibet, Mongolian-Xinjiang and Loess. As one of the national park system pilots, Qilian Mountain National park is an important ecological function area, a water retention area and a priority area for biodiversity conservation in China, and its ecological functions cannot be ignored. Based on the Normalized Difference Vegetation Index (NDVI) and Net Primary Productivity (NPP) of Qilian Mountain National Park from 2000-2019, combined with temperature, precipitation, land use, mineral extraction and tourism development data, we used the Theil-Sen slope estimation, Mann-Kendall test, land transfer matrix and multivariate residual analysis methods to analyze the spatial and temporal distribution characteristics of vegetation, change trend characteristics and its response to climate change and human activities. The results showed that (1) NDVI and NPP in Qilian Mountain National Park from 2000 to 2019 showed a spatial pattern of high in the southeast and low in the northwest, decreasing from southeast to northwest. Temporally, they showed an increasing trend, with an increase rate of 0.0053/a and 0.0014/a, respectively. (2) The improved, decreased and stable areas of NPP in Qilian Mountain National Park accounted for 87.29%, 0.40% and 12.30% of the total area, respectively. Decreased areas are scattered throughout the national park, with the most concentrated distribution at the intersection of Zoulang South Mountains and Lenglongling, near the border edge of Gansu and Qinghai provinces. The improved areas are widely distributed, especially the most obvious in the eastern part of the national park. (3) The NDVI of Qilian Mountain National Park shows a significant positive correlation with temperature in about 40.18% of the area, and a positive correlation with precipitation in about 25.70% of the area, the increase in temperature and precipitation promotes the growth of vegetation in the national park, and a suitable combination of hydrothermal conditions is more favorable to the growth of vegetation.(4) The impact of human activities on vegetation changes was two-sided:Approximately 28.91% of mining, tourism and hydroelectric power stations in the national park still had poor vegetation growth after rectification and regulation, and the ecological environment has not recovered significantly; The cropland to forest and grassland conversion projects and ecological forest projects have been effective, the area of forest and grassland has increased, in the past three years.(5) Most of the vegetation cover changes in Qilian Mountain National Park were caused by a combination of climate change and human activity. 参考文献 相似文献 引证文献

천성산 화엄늪의 형성연대와 그 가치

This study presents new evidence about the formation time of hwaeomneup (wetland) and discusses its value through comparison with previously studied mountainous wetlands in South Korea. For this, radiocarbon dating was performed on 9 samples from the wetland. As a result of the study, it was estimated that the wetland was not formed during the historical period of about 700 years ago, as previously known, but at least 2,800 years ago. The wetland was developed by the combination of climate change and geomorphic processes including weathering, hydrological and pedogenic processes. The highest growth rates were at AD. 600-1000, which corresponds to the medieval warm period. Since then, the wetland has grown slowly. This period corresponds to the Little Ice Age. Hwaeomnuep is an important source to research natural history in the late Holocene.

The Effects of Climate Change on Heading Type Chinese Cabbage (Brassica rapa L. ssp. Pekinensis) Economic Production in South Korea

Since Chinese cabbage is consumed fresh, its wholesale price varies with the total amount supplied on the market. However, in these days, climate variability presents a large threat to sustainable Chinese cabbage production in South Korea. To manage Chinese cabbage production well under unexpected weather conditions, it is important to study the impacts of climate variability on Chinese cabbage economic yields in South Korea. In this study, 2-year field trials were conducted in multiple locations across seven provinces in South Korea. The collected morphological data from 24 different varieties were used to develop a yield prediction model using a machine learning technique. Three Chinese cabbage groups were carried out through the clustering analysis, and a yield model was developed for each cluster group. The developed model was used to predict the cabbage economic yields under different combinations of climate change and cropping management plans. According to simulation results, Group 1 had the shortest growing degree days and produced higher yields than the other two groups. However, the overproduction of Group 1 led to a price reduction in the market of (USD(0.04–0.08) per kg), which suggested that producing Group 2 of (USD(0.31–0.96) per kg) is more beneficial to farmers. Based on the production results of the groups, their revenue varied by location and cropping management. The results of this study provide farmers with a better understanding of the relationship between production and economic benefits in future climate change scenarios.

Climate-induced small pelagic fish blooms in an overexploited marine ecosystem of the South China Sea

Marine ecosystems are a primary conservation concern because of the separate and synergistic effects of overfishing and climate change on their productivity and biodiversity. For the purpose of implementing ecosystem-based fisheries management, it is essential to understand how fish stocks respond to climate change in marine ecosystems, especially those that have been overexploited. The Beibu Gulf in the northwestern part of the South China Sea has long been one of China’s major fishing grounds. After the collapse of the demersal ecosystem in 1990 s, small pelagic fishes, including Japanese jack mackerel (Trachurus japonicus) and Japanese scad (Decapterus maruadsi), have occupied a more-important ecological niche in this gulf. However, insufficient research on how small pelagic fish respond to climate change creates great uncertainty for implementing the current management measures. This study used fish data of trawl surveys and environmental data to investigate possible mechanisms leading to dramatic fluctuations in small pelagic fish populations and their possible effects on the Beibu Gulf marine ecosystem. Abnormal blooms of small pelagic fish, especially T. japonicus and D. maruadsi, occurred following four La Niña events (in 2007/2008, 2010/2011, 2011/2012, and 2020/2021). Moreover, the dominant fish species shifted observably and regularly, Shannon–Wiener diversity and Pielou’s evenness decreased significantly in the northeastern coastal waters of the gulf, and the spatial pattern of the fish community was reorganized in this ecosystem. The small pelagic fish blooms in summers probably resulted from a combination of climate change, overfishing, and a summer fishing moratorium, which thereby caused a series of responses in the marine ecosystem. Fluctuations in the small pelagic fish populations after La Niña events seemed more dramatic after the collapse of demersal fish stocks. Therefore, we emphasize the need for implementing ecosystem-based, preventive, and adaptive fisheries management.

Vegetation coverage changes driven by a combination of climate change and human activities in Ethiopia, 2003–2018

Climate change often leads to the vulnerability of vegetation cover, while the impact of human activities on vegetation cover is undoubtedly more complex in this context, especially in Ethiopia. This paper analyzed the spatiotemporal dynamics of vegetation growth in Ethiopia from 2003 to 2018 by the enhanced vegetation index (EVI) based on different time scales and explored the coefficient of variation and driving factors of the fractional vegetation coverage (FVC). The results indicated that the EVI mainly presents a “double peak” pattern, with large spatiotemporal differences between quarters and months in Ethiopia. The FVC increased by 0.0005 per year, but vegetation showed a browning trend after 2013. The FVC degraded area accounted for 43.9% of the total area, of which the significantly degraded area accounted for 7.51% due to human activities, mainly in northern, central, and southern Ethiopia. The effects of precipitation and maximum temperature on vegetation differed on time scales. Spatially, the vegetation on the northwest side of the Main Ethiopian Rift Valley (MERV) was dominated by a combination of maximum temperature and precipitation, while vegetation on the southeast side of MERV was mainly influenced by precipitation. However, the spatial overlay analysis with degraded and healthy vegetation zones revealed that human activities were the key driver of vegetation cover change rather than climate change. This study provides support for further development of vegetation health conservation policies in Ethiopia and monitoring of vegetation dynamics in other countries around the world.