Biotic indicators of climate change in high altitude Tsoltak glacial lake of Ladakh Range, NW Trans-Himalaya, India

Coastal scientists postulate that salt marshes are significantly affected by dynamics of global climate. However, few studies have explicitly proposed a perspective that regards salt marshes as potential indicators of climate change. This review article evaluates the possibility of salt marshes as indicators of global climate change, focusing upon three major aspects: sedimentary, vegetation, and biogeochemical dynamics. The previous literature concerned with these aspects commonly argues that the primary impact of climate change on salt marshes occurs via sea-level variations, because hydrologic fluctuations regulate the frequency, duration, and depth of over-marsh flooding events. Sedimentary, floristic, and biogeochemical dynamics prove to be significantly influenced by sea-level changes regardless of climate zones, and hence, undoubtedly possess a potential for indicating climate signatures. However, where plant-plant interactions such as facilitation and competition are important, vegetation dynamics in salt marshes may not be an immediate, sole function of sea-level and climate variations. Also, specifically in the field of salt marsh biogeochemistry, enough long-term data have not been collected to convincingly conclude that biogeochemistry is a useful indicator of climate change. Therefore, while this review is concerned mainly with the possibility of salt marshes as indicators of climate change, their suitability or usefulness is a different matter to be resolved through further data collection and discussion in future investigations.

Glacial lakes are a critical water resource, an indicator of climate change, and a potential source for glacial lake outburst floods. Accurate and frequent mapping is important for understanding glacial lake dynamics and associated hazards, particularly in a changing climate. Many datasets and mapping techniques are currently used to delineate glacial lakes. This review offers a comprehensive analysis of the datasets and methods used for glacial lake mapping at regional and global scales, highlights their strengths and limitations, provides suggestions for choosing appropriate data and methods, and proposes potential future research directions. We find that field observations provide the most detailed information on glacial lakes. However, resource constraints limit field surveys, and remote sensing–based datasets and threshold-based approaches are the standard practice. Recently, machine learning models have become more common due to their ability to automatically delineate glacial lakes. Cloud computing has simplified the access to large remote sensing datasets and plays a vital role in the automation of glacial lake mapping. In the future, we recommend the establishment of standardized glacial lake definitions and a global glacial lake monitoring system based on deep learning models. Fostering interinstitutional and community collaborations is expected to help achieve these goals.

Discontinuation of glacial meltwater input reshapes the diversity and stability of eukaryotic planktonic microbial communities in glacial lakes.

A Torrent of Consequences

The detection of glacial lake change in the Himalayas, Nepal is extremely significant since the glacial lake change is one of the crucial indicators of global climate change in this area, where is the most sensitive area of the global climate changes. In the Himalayas, some of glacial lakes are covered by the dark mountains’ shadow because of their location. Therefore, these lakes can not be detected by conventional method such as Normalized Difference Water Index (NDWI), because the reflectance feature of shadowed glacial lake is different comparing to the ones which are located in the open flat area. The shadow causes two major problems: 1) glacial lakes which are covered by shadow completely result in underestimation of the number of glacial lakes; 2) glacial lakes which are partly identified are considered to undervalue the area of glacial lakes. The aim of this study is to develop a new model, named Detection of Shadowed Glacial Lakes (DSGL) model, to identify glacial lakes under the shadow environment by using Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) data in the Himalayas, Nepal. The DSGL model is based on integration of two different modifications of NDWI, namely NDWIs model and NDWIshe model. NDWIs is defined as integration of the NDWI and slope analysis and used for detecting non-shadowed lake in the mountain area. The NDWIshe is proposed as a new methodology to overcome the weakness of NDWIs on identifying shadowed lakes in highly elevated mountainous area such as the Himalayas. The first step of the NDWIshe is to enhance the data from ASTER 1B using the histogram equalization (HE) method, and its outcome product is named ASTERhe. We used the ASTERhe for calculating the NDWIhe and the NDWIshe. Integrated with terrain analysis using Digital Elevation Model (DEM) data, the NDWIshe can be used to identify the shadowed glacial lakes in the Himalayas. NDWIs value of 0.41 is used to identify the glacier lake (NDWIs ≥ 0.41), and 0.3 of NDWIshe is used to identify the shadowed glacier lake (NDWIshe ≤ 0.3). The DSGL model was proved to be able to classify the glacial lakes more accurately, while the NDWI model had tendency to underestimate the presence of actual glacial lakes. Correct classification rate regarding the products from NDWI model and DSGL model were 57% and 99%, respectively. The results of this paper demonstrated that the DSGL model is promising to detect glacial lakes in the shadowed environment at high mountains.

Glacial lakes are not only the important refresh water resources in alpine region, but also act as a trigger of many glacial hazards such as glacial lake outburst flood (GLOF) and debris flow. Therefore, glacial lakes play an important role on the cryosphere, climate change and alpine hazards. In this paper, the issues of glacial lake were systematically discussed, then from the view of glacial lake inventory and glacial lake hazards study, the glacial lake was defined as natural water mainly supplied by modern glacial meltwater or formed in glacier moraine’s depression. Furthermore, a complete classification system of glacial lake was proposed based on its formation mechanism, topographic feature and geographical position. Glacial lakes were classified as 6 classes and 8 subclasses, i.e., glacial erosion lake (including cirque lake, glacial valley lake and other glacial erosion lake), moraine-dammed lake (including end moraine-dammed lake, lateral moraine-dammed lake and moraine thaw lake), ice-blocked lake (including advancing glacier-blocked lake and other glacier-blocked lake), supraglacial lake, subglacial lake and other glacial lake. Meanwhile, some corresponding features exhibiting on remote sensing image and quantitative indices for identifying different glacial lake types were proposed in order to build a universal and operational classification system of glacial lake.

Glacial lakes are a sensitive indicator of regional climate change and one of the initiators of glacier disasters. It is of great significance to understand the spatial distribution and change characteristics of glacial lakes for exploring their response patterns to climate change and assessing the glacial lake outburst flood (GLOF) susceptibility. Based on Gaofen-1/6 PMS, Sentinel-2A/2B MSI and Landsat TM/ETM+/OLI images from 2000 to 2020, we integrated geographic information technology and mathematical and statistical methods to analyze the spatial and temporal distribution of glacial lakes in Nepal and their dynamic changes, and further discriminated and evaluated the GLOF susceptibility of glacial lakes. The results show that there were 2420 glacial lakes in Nepal in 2020, mainly distributed within the 4500~5500 m, with an area of 87.21 km2 and a water storage of 1921.72 × 106 m3. The number and area of glacial lakes with each area above 0.01 km2 in Nepal showed an increasing trend from 2000 to 2020, while 499 new glacial lakes were born, 139 lakes disappeared, the area and water storage increased by 19.46 km2, 403.07 × 106 m3, respectively. Glacial lakes at altitudes <3000 m were relatively stable, while the number and area of glacial lakes at altitudes within 4500~5500 m increased rapidly. We assessed the GLOF susceptibility of 40 moraine-dammed glacial lakes with an area above 0.2 km2 in Nepal, and found that there were 8, 12, 14 and 6 glacial lakes with low, medium, high and very high susceptibility, respectively. Among glacial lakes with very high GLOF susceptibility, potential GLOF events of Tsho Rolpa glacial lake, Lower Barun glacial lake and glacial lake with code of GL87091E27797N will cause great harm to downstream regions. GLOFs in Nepal will be in an active status in the future, therefore, the dynamics of glacial lakes and their surroundings should be continuously monitored.

The Niangmuco region on the east margin of the Eastern Himalayan Syntaxis features a large number of glacial lakes. The development process and stability classification of glacial lakes is of great significance to the study of seasonal glaciers in the eastern Himalayan margin, with implications for economic development and disaster prevention. Based on Landsat remote sensing image data from 2000 to 2021, this study analyzed the development and change characteristics of glacial lakes in the Niangmuco region during the past 21 years, and classified the stability of lakes with areas >0.02 km2 using the fuzzy consistent matrix method. In this area, 126 glacial lakes were identified within an elevation range of 3044–4156 m with a total area of 10.94 km2. These lakes primarily included glacial erosion lakes, valley lakes, tectonic lakes, and landslide dam lakes. Specifically, glacial erosion lakes accounted for 88.9% of the total number of lakes and 60.3% of the total lake area, followed by valley lakes with 6.3% and 23.7%, respectively. From 2000 to 2010, the total area of glacial lakes decreased from 10.53 km2 to 10.09 km2, which may be attributable to climate fluctuations. Subsequently, the area of lakes increased significantly to 10.94 km2 in 2021, an increase of 0.41 km2. Compared with 2000, among the lakes with a growth rate of 0.019 km2/a in 21 years, glacial erosion lakes exhibited the largest change. Among the classified glacial lakes in the study area, 95.7% were stable and relatively stable, mostly comprising glacial erosion lakes at high altitudes between 3468 and 4156 m. Only 4 unstable and extremely unstable glacial lakes were identified, and they were located near a fault zone. The findings show that the development and the change of glacial lakes in the area are primarily controlled by temperature and precipitation, and the topography and fault activity have important influences on the stability of glacial lakes.

冰湖作为区域气候变化的灵敏指示器和主要冰川灾害的启动器，认识其空间分布及变化特征对探讨冰湖对气候变化的响应规律及冰湖溃决危险性评估具有重要意义.基于1968-1980年地形图数据和1994-2016年Landsat TM/OLI遥感影像资料，综合利用RS、GIS技术和数理统计方法分析帕隆藏布流域面积≥ 0.01 km²冰湖时空分布及其动态变化，并对潜在危险性冰湖进行判别和评估.结果表明：2016年帕隆藏布流域共有冰湖351个，面积50.48 km²，且面积和数量分别以面积>1 km²和面积<0.1 km²的冰湖为主，这些冰湖主要分布于海拔2800~5400 m之间.近50年来帕隆藏布流域冰湖总体呈数量增多、面积增加态势；海拔<3000 m的冰湖相对稳定，而海拔>4500 m的冰湖数量和面积增加则相对迅速.近50年间帕隆藏布流域冰川面积减少591.34 km²，气候变暖导致的冰川末端退缩和冰川融水增加为冰湖形成和扩张提供了发育空间和物质来源.切毛措、光谢错等9个冰湖为潜在危险性冰湖，预计未来一段时间内帕隆藏布流域冰湖溃决可能处于活跃阶段，其形成和暴发也将更加频繁.;Glacial lake serves as a sensitive indicator of regional climate change and trigger of major glacial disasters. Understanding its spatial distribution and changing characteristics is of great significance for exploring the response of glacial lake to climate change and assessing the risk of glacial lake outburst. Based on the topographic maps in 1968-1980 and Landsat TM/OLI remote sensing images from 1994 to 2016, we analyzed the spatial-temporal distribution and dynamic changes of glacial lakes with an area larger than 0.01 km² in the Parlung Zangbo River Basin as well as identified and evaluated the potential dangerous glacial lakes using RS, GIS and mathematical statistics methods. The results showed that:In 2016, there were 351 glacial lakes with a total area of 50.48 km² in the Parlung Zangbo River Basin. Glacial lakes with areas >1 km² accounted for the largest area and <0.1 km² accounted for the biggest number. Glacial lakes were mainly concentrated in 2800-5400 m. In the past 50 years, the number and area of glacial lakes in this basin have increased. Among them, the number and area of glacial lakes below 3000 m were relatively stable, whereas those above 4500 m increased rapidly. Under the background of climate warming, the glacier area in the Parlung Zangbo River Basin has decreased by 591.34 km² in the past 50 years. The retreat of the glacier terminal and the increase of glacial meltwater provided development space and material source for the formation, expansion and area increase of glacial lakes. There were 9 potentially dangerous glacial lakes being identified in the Parlung Zangbo River Basin. It is expected that the glacial lake outburst will be in an active stage in the future.

Glacial lakes are highly sensitive indicators of global climate change. The accurate extraction of glacial lakes from image data is of great importance to the evaluation of the hydrological environment in high mountain regions. This paper demonstrates a systematic approach&amp;#x2014;TSCV (threshold and simplified C-V)&amp;#x2014;that integrates the advantages of the threshold segmentation method and the active contour model to improve the effect of glacial lake extraction, by overcoming the problems involved in the efficient extraction of small, overlooked glacial lakes and in the removal of some mountain shadows. Three typical areas of glacial lake development in High Asia were selected for glacial lake extraction from Landsat-8 imagery and the results were then compared with those obtained using the threshold segmentation method and the fuzzy clustering method (FCM). The values of the kappa coefficient (KC) and average extraction accuracy (AEA) shows that the TSCV (KC &amp;#x003D; 0.895, AEA &amp;#x003D; 0.739) performed superior than other two methods, especially for the small glacial lakes, but also that the threshold segmentation method (KC &amp;#x003D; 0.869, AEA &amp;#x003D; 0.631) requires the least time and that the FCM (KC &amp;#x003D; 871, AEA &amp;#x003D; 0.663) has the lowest commission error. Our findings lead to a new approach to improve the accuracy of glacial lake extraction in situation where a large proportion of the lakes are small and with a potential for automated glacial lake mapping in rugged mountain areas at a large scale.

Given the emergence of climate change and health risks, this review examined potential relationships between varying indicators of climate change, movement behaviors (ie,physical activity [PA], sedentary behavior, and sleep), and health. Seven databases were searched in March 2020, April 2023, and April 2024. To be included, studies must have examined indicators of climate change and at least one of the movement behaviors as either an exposure or a third variable (ie,mediator/moderator), and a measure of health as outcome. Evidence was summarized by the role (mediator/moderator) that either climate change or movement behavior(s) has with health measures. Relationships and directionality of each association, as well as the strength and certainty of evidence were synthesized. A total of 79 studies were eligible, representing 6,671,791 participants and 3137 counties from 25 countries (40% low- and middle-income countries). Of 98 observations from 17 studies that examined PA as a mediator, 34.7% indicated that PA mediated the relationship between climate change and health measure such that indicators of adverse climate change were associated with lower PA, and worse health outcome. Of 274 observations made from 46 studies, 28% showed that PA favorably modified the negative association between climate change and health outcome. Evidence was largely lacking and inconclusive for sedentary behavior and sleep, as well as climate change indicators as an intermediatory variable. PA may mitigate the adverse impact of climate change on health. Further evidence is needed to integrate PA into climate change mitigation, adaptation, and resilience strategies.

William Solecki,1,a Cynthia Rosenzweig,2,a Reginald Blake,3,a Alex de Sherbinin,4 Tom Matte,5 Fred Moshary,6 Bernice Rosenzweig,7 Mark Arend,6 Stuart Gaffin,8 Elie Bou-Zeid,9 Keith Rule,10 Geraldine Sweeny,11 and Wendy Dessy11 1City University of New York, CUNY Institute for Sustainable Cities, New York, NY. 2Climate Impacts Group, NASA Goddard Institute for Space Studies, Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 3Physics Department, New York City College of Technology, CUNY, Brooklyn, NY; Climate Impacts Group, NASA Goddard Institute for Space Studies. 4 Center for International Earth Science Information Network (CIESIN), Columbia University, Palisades, NY. 5New York City Department of Health and Mental Hygiene, New York, NY. 6NOAA CREST, City College of New York, CUNY, New York, NY. 7CUNY Environmental Crossroads, City College of New York, CUNY, New York, NY. 8Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 9Department of Civil & Environmental Engineering, Princeton University, Princeton, NJ. 10Princeton Plasma Physics Laboratory, Princeton, NJ. 11New York City Mayor’s Office of Operation, New York, NY

The study sought to ascertain awareness and differences in male and female extension workers perceptions of climate change. The study was carried out in Anambra state, Nigeria. A total of forty respondents (20 males and 20 females) purposively selected from four agricultural zones in the state were used for the study. Data were analysed using percentage, mean score and t- test. All( 100%) of males and 95% of the females were married. Majority (71.3%) of the males were in the age range of 45 to 54 years while majority(77.9%) of the females were in the age range of 40 . 49years. The mean ages were 45 years and 44 years for the male and female extension workers respectively. Majority of the male (60%) and female workers (68.5%) had HND/ degree certificate and had about 4 to 6 persons in the household. Females noticed and heard about climate change earlier than their male colleagues. Male extension workers sourced information on climate change mainly from radio (100%), newspaper (95%) and television (80%) while the female extension workers sourced mainly from radio (90%), fellow extension workers (85%) and friends/relations (70%). There were significant differences in their perception of swamp rice production (t= 2..4, p. 0.05), overgrazing of farmlands by livestock (t =- 2.7, p. 0.05) and high use of irrigation (t = - 2.2, p. 0.05) as causes of climate change. There were also significant differences in their perception of high humidity (t = 2.7, p. 0.05) as indicator of climate change and high incidence of weeds (t= -2.7, p. 0.05) as effect of climate change .Females perceived these factors more as causes, indicator and effects of climate change than males. The study emphasized on the need to educate/train both male and female extension workers generally on issues concerning climate change and specifically on the causes, indicators and effects of climate change that they are ignorant of. This is for onward Transmission to their clientele, enhanced agricultural productivity and encouraging future. Key words: awareness perceptions climate change extension workers

The subject of climate change in the areas of the Tibetan Plateau (TP) and the Himalayas has taken on increasing importance because of available water resources from their mountain glaciers. Many of these glaciers over the region have been retreating, while some are advancing and stable. Other studies report that some glaciers in the Himalayas show acceleration on their shrinkage. However, the causes of the glacier meltings are still difficult to grasp because of the complexity of climatic change and its influence on glacier issues. However, it is vital that we pursue further study to enable the future prediction on glacier changes.

An inventory of glacial lakes in the Third Pole region and their changes in response to global warming