Low-elevation Zones Research Articles

Empirical Modeling of Soil Loss and Yield Utilizing RUSLE and SYI: A Geospatial Study in South Sikkim, Teesta Basin

Soil erosion and subsequent sedimentation pose significant challenges in the Sikkim Himalayas. In this study, we conducted an assessment of the impact of rainfall-induced soil erosion and sediment loss in South Sikkim, which falls within the Teesta Basin, employing Revised Universal Soil Loss Equation (RUSLE) and Sediment Yield Index (SYI) models. Leveraging mean annual precipitation data, a detailed soil map, geomorphological landforms, Digital Elevation Models (DEMs), and LANDSAT 8 OLI data were used to prepare the factorial maps of South Sikkim. The results of the RUSLE and SYI models revealed annual soil loss >200 t ha−1 yr−1, whereas mean values were estimated to be 93.42 t ha−1 yr−1 and 70.3 t ha−1 yr−1, respectively. Interestingly, both models displayed similar degrees of soil loss in corresponding regions under the various severity classes. Notably, low-severity erosion <50 t ha−1 yr−1 was predominantly observed in the valley sides in low-elevation zones, while areas with severe erosion rates >200 t ha−1 yr−1were concentrated in the upper reaches, characterized by steep slopes. These findings underscore the strong correlation between erosion rates and topography, which makes the region highly vulnerable to erosion. The prioritization of such regions and potential conservation methods need to be adopted to protect such precious natural resources in mountainous regions.

Urbanisation on the coastline of the most populous and developed state of Brazil: the extent of coastal hardening and occupations in low-elevation zones

Worldwide, coastlines have been replaced and altered by hard infrastructures to protect cities and accommodate human activities. In addition, human settlements are common and increasing in lowland areas threatened by coastal risk hazards. These urbanisation processes cause severe socioeconomic and ecological losses which demand policy reforms towards better coastal management and climate resilience. A first step in that direction is to comprehend the status of coastal hardening and occupation of vulnerable areas. Here, we mapped the coastline of the most populous and developed state of Brazil: São Paulo (SP). Our goal was to quantify the linear extent of natural habitats, artificial structures (AS), and occupations in low-elevation coastal zones (≤ 5 m) within 100 m from marine environments (LECZ100m) along the coastline and within estuaries. SP coast has a total extent of 244 km of AS, of which 125 and 119 km correspond to AS running along the coastline (e.g., seawalls, breakwaters) and extending from the shoreline into adjacent waters (e.g., jetties, pontoons, groynes), respectively. 63% of the total extent of AS is located in the most urbanised region. Breakwalls were the most common infrastructure (108 km), followed by jetties and wharves (~40 km each), and aquaculture and fishing apparatus (~24 km). Over 300 km of the SP coastline has inland occupations in LECZ100m: 235 and 67 km are adjacent to sandy beaches and estuarine/river margins, respectively. Coastal hardening is advanced in the central region of SP resulting from intense port activities and armoured shorelines. In other regions, much of coastal urbanisation seems to be driven by secondary usage of the cities, such as real estate development for beach houses and tourism. Our findings suggest that coastal urbanisation poses a major but often neglected source of environmental impact and risk hazards in SP and Brazil.

Bias-corrected high-resolution precipitation datasets assessment over a tropical mountainous region in Colombia: A case of study in Upper Cauca River Basin

Surface gauge measurements have been commonly employed to analyze the precipitation's high spatial and temporal variability. However, incomplete area coverage and deficiencies over most tropical and complex topography mean significant limitations of this measurement type. Satellite-derived datasets, combined with the integration of in-situ observations with satellite data, are an alternative to address these limitations by offering a more spatially homogeneous and temporally comprehensive coverage for scarce data areas of the globe. Nevertheless, applying a bias correction technique on the precipitation datasets is still necessary before they are used for research due to their considerable bias. Here, we analyze the performance of CHIRPS, WorldClim, and TerraClimate datasets compared to data from 30 rain gauge stations over the South-West of Colombia, specifically in the Upper Cauca River Basin-UCRB between 1981 and 2018. Additionally, we applied the Quantile Mapping correction to all gridded precipitation products, and subsequently, the corrected rainfall is compared to the observed data on the monthly, seasonal, and annual scale. Our results show that the CHIRPS dataset better captures the seasonal and monthly variability. CHIRPS presents the best performance during less rainy seasons and at low elevation zones (900–2000 m above sea level-m.a.s.l.), followed by TerraClimate. Utilizing the bias correction methodology, we generated a new, corrected, and more reliable monthly precipitation time series for each location from all gridded precipitation products. Additionally, we found that the correction of the CHIRPS dataset presented the best performance across all spatiotemporal scales in the UCRB. Therefore, this study provides an accurate precipitation database for a complex topographic tropical region with limited data availability.

Rain-on-snow responses to warmer Pyrenees: a sensitivity analysis using a physically based snow hydrological model

Abstract. Climate warming is changing the magnitude, timing, and spatial patterns of mountain snowpacks. A warmer atmosphere may also induce precipitation phase shifts, resulting in a decreased snowfall fraction (Sf). The combination of Sf and snowpack directly influences the frequency and intensity of rain-on-snow (ROS) events, a common cause of flash-flood events in snow-dominated regions. In this work, we investigate ROS patterns and their sensitivity to temperature and precipitation changes in the Pyrenees by modeling ROS through a physically based snow model. This model is forced with reanalysis climate data for elevations of 1500, 1800, and 2400 m perturbed using a range of temperature and precipitation values consistent with 21st century climate projections. ROS patterns are characterized by their frequency, rainfall quantity, and snow ablation. The highest ROS frequency for the historical climate period (1980–2019) is found in the 2400 m zones of the southwest Pyrenees (17 d yr−1). The maximum ROS rainfall amount is detected in 1800 m areas of the southeast (45 mm d−1, autumn), whereas the highest ROS ablation is found in the 2400 m zones of the northwest (−10 cm d−1, summer). When air temperature increases from 1 to 4 ∘C compared to the historical climate period, ROS rainfall amount and frequency increase at a constant rate during winter and early spring for all elevation zones. For the rest of the seasons, non-linear responses of ROS frequency and ablation to warming are found. Overall, ROS frequency decreases in the shoulders of the season across eastern low-elevation zones due to snow cover depletion. However, ROS increases in cold, high-elevation zones where long-lasting snow cover exists until late spring. Similarly, warming induces greater ROS ablation (+10 % ∘C−1) during the coldest months of the season, 2400 m elevations, and northern sectors, where the deepest snow depths are found. In contrast, small differences in ROS ablation are found for warm and marginal snowpacks. These results highlight the different ROS responses to warming across the mountain range, suggest similar ROS sensitivities in near-mid-latitude zones, and will help anticipate future ROS impacts in hydrological, environmental, and socioeconomic mountain systems.

Spatiotemporal heterogeneity of inundation pattern of floodplain lake wetlands and impact on wetland vegetation

The inundation pattern is an important ecohydrological indicator for studying floodplain lake wetlands, as it is the key factor affecting the wetland vegetation distribution patterns. Poyang Lake, the largest freshwater lake in China, is a typical floodplain lake wetland. This study presents a hydrodynamic model and vegetation survey of Poyang Lake, analyzed the spatiotemporal heterogeneity of the inundation pattern (inundation duration and depth), assessed the response patterns of wetland vegetation concerning the inundation pattern, and examined the impact of the proposed Poyang Lake Water Conservancy Hub (PLWCH) on the inundation pattern and wetland vegetation. The results revealed that the inundation pattern of Poyang Lake had significant spatial heterogeneity. Inundation pattern was found to have a significant impact on the vegetation succession. The response relationship between the distribution areas of different wetland vegetation types and inundation pattern was in accordance with the Gaussian curve, and the ecological threshold range of the Carex spp. community was the greatest. Owing to factors such as climate change and anthropogenic activities, the inundation pattern of Poyang Lake varied significantly since 2003, with the average inundation duration and average inundation depth decreasing by 15 d and 0.32 m, respectively. Consequently, the spatial distribution of wetland vegetation changed significantly, whereby the Carex spp., Polygonum criopolitanum, and Phalaris arundinacea communities extended down to the lower elevation zone. In the future, the PLWCH may result in increases in the inundation duration and depth, restrain the downward vegetation extension trend, and promote the vegetation to move to higher elevations similar to the status prior to 2003. These findings provide a detailed description of the spatiotemporal heterogeneity of the inundation pattern and the drivers of wetland vegetation distribution patterns in floodplain lake wetlands, serving as a scientific basis for conservation and restoration of these ecosystems.

Restoration and resilience to sea level rise of a salt marsh affected by dieback events

AbstractThe frequency of salt marsh dieback events has increased over the last 25 years with unknown consequences to the resilience of the ecosystem to accelerated sea level rise (SLR). Salt marsh ecosystems impacted by sudden vegetation dieback events were previously thought to recover naturally within a few months to years. In this study, we used a 13‐year collection of remotely sensed imagery to provide evidence that approximately 14% of total marsh area has not revegetated 10 years after a dieback event in Charleston, SC. Dieback onset coincided with a severe drought in 2012, as indicated by the Palmer drought stress index. A second dieback event occurred in 2016 after a historic flood influenced by Hurricane Joaquin in 2015. Unvegetated zones reached nearly 30% of the total marsh area in 2017. We used a light detection and ranging‐derived digital elevation model to determine that most affected areas were associated with lower elevation zones in the interior of the marsh. Further, restoration by grass planting was effective, with pilot‐scale restored plots having greater aboveground biomass than reference sites after two years of transplanting. A positive outcome indicated that the stressors that caused the dieback are no longer present. Despite that, many affected areas have not recovered naturally, even though they are located within the typical elevation range of healthy marshes. A mechanistic modeling approach was used to assess the effects of vegetation dieback on salt marsh resilience to SLR. Predictions indicate that a highly productive restored marsh (2000 g m−2 year−1) would persist at a moderate SLR rate of 60 cm in 100 years, whereas a nonrestored mudflat would lose all its elevation capital after 100 years. Thus, rapid restoration of marsh dieback is critical to avoid further degradation. Also, failure to incorporate the increasing frequency and intensity of extreme climatic events that trigger irreversible marsh diebacks underestimates salt marsh vulnerability to climate change. Finally, at an elevated SLR rate of 122 cm in 100 years, which is most likely an extreme climate change scenario, even highly productive ecosystems augmented by sediment placement would not keep pace with SLR. Thus, climate change mitigation actions are also urgently needed to preserve present‐day marsh ecosystems.

Multi-temporal high-resolution marsh vegetation mapping using unoccupied aircraft system remote sensing and machine learning

Coastal wetlands are among the most productive ecosystems in the world and provide important ecosystem services related to improved water quality, carbon sequestration, and biodiversity. In many locations, wetlands are threatened by coastal development and rising sea levels, prompting an era of tidal wetland restoration. The creation and restoration of tidal marshes necessitate the need for ecosystem monitoring. While satellite remote sensing is a valuable monitoring tool; the spatial and temporal resolution of imagery often places operational constraints, especially in small or spatially complex environments. Unoccupied aircraft systems (UAS) are an emerging remote sensing platform that collects data with flexible on-demand capabilities at much greater spatial resolution than sensors on aircraft and satellites, and resultant imagery can be readily rendered in three dimensions through Structure from Motion (SfM) photogrammetric processing. In this study, UAS data at 5 cm resolution was collected at an engineered wetland at Poplar Island, located in Chesapeake Bay, MD United States five times throughout 2019 to 2022. The wetland is dominated by two vegetation species: Spartina alterniflora and Spartina patens that were originally planted in 2005 in low and high marsh elevation zones respectively. During each survey, UAS multispectral reflectance, canopy elevation, and texture were derived and used as input into supervised random forest classification models to classify species-specific marsh vegetation. Overall accuracy ranged from 97% to 99%, with texture and canopy elevation variables being the most important across all datasets. Random forest classifications were also applied to down-sampled UAS data which resulted in a decline in classification accuracy as spatial resolution decreased (pixels became larger), indicating the benefit of using ultra-high resolution imagery to accurately and precisely distinguish between wetland vegetation. High resolution vegetation classification maps were compared to the 2005 as-built planting plans, demonstrating significant changes in vegetation and potential instances of marsh migration. The amount of vegetation change in the high marsh zone positively correlated with interannual variations in local sea level, suggesting a feedback between vegetation and tidal inundation. This study demonstrates that UAS remote sensing has great potential to assist in large-scale estimates of vegetation changes and can improve restoration monitoring success.

Spatio-temporal assessment of Gridded precipitation products across topographic and climatic gradients in Colombia

Gridded precipitation products (GPPs) represent an alternative to and a complement to gauge-based observations of precipitation, improving the representation of spatio-temporal precipitation variability in regions with scarce gauge networks. However, GPPs' accuracy varies among products, temporal resolution, and regions, indicating the need for particular regional performance assessments. In this study, we evaluate the performance of eight state-of-the-art GPPs (CHIRPSv2, CMORPHv1, ERA5, ERA5-Land, IMERG, MSWEPv2.8, PERSIANN-CCS, and PERSIANN-CDR) over the steep topographic and climatic gradients of Colombia, in northwestern South America. We use a point-to-pixel comparison between ground-based observations from 1334 gauges with the corresponding grid cell of each GPP at 3-day, monthly, seasonal (DJF, MAM, JJA, SON), and annual scales over 2005–2014. Five categorical indices are used to assess the ability of each GPP to capture different 3-day precipitation intensity events correctly. The Kling-Gupta efficiency and its components are used to assess the GPPs' performance over Colombia and its five natural regions. Our results show that, at the 3-day scale, GPPs can correctly identify the occurrence of no-precipitation events (< 1 mm/day), but their capacity to classify precipitation events (≥ 1 mm/day) is low. The best performance is observed at the monthly scale, particularly at low elevation zones (0–1000 m.a.s.l), compared to 3-day and annual scales. Seasonally, GPPs tend to perform better during the dry season compared to the wet season in all regions. Overall, CHIRPSv2 outperforms other GPPs throughout the country and its five natural regions for all elevation zones and temporal scales, followed closely by MSWEPv2.8 and IMERG. PERSIANN-CCS and ERA5 products had the lowest performance, mainly over the driest and higher-altitude regions, respectively. This study provides insights into the performance of GPPs in complex climatic and topographic settings and, importantly, suggests the most suitable products for climate, hydrological, or ecological studies in a climatic, hydrological, and ecologically-strategic region.

Combining APHRODITE Rain Gauges-Based Precipitation with Downscaled-TRMM Data to Translate High-Resolution Precipitation Estimates in the Indus Basin

Understanding the pixel-scale hydrology and the spatiotemporal distribution of regional precipitation requires high precision and high-resolution precipitation data. Satellite-based precipitation products have coarse spatial resolutions (~10 km–75 km), rendering them incapable of translating high-resolution precipitation variability induced by dynamic interactions between climatic forcing, ground cover, and altitude variations. This study investigates the performance of a downscaled-calibration procedure to generate fine-scale (1 km × 1 km) gridded precipitation estimates from the coarser resolution of TRMM data (~25 km) in the Indus Basin. The mixed geographically weighted regression (MGWR) and random forest (RF) models were utilized to spatially downscale the TRMM precipitation data using high-resolution (1 km × 1 km) explanatory variables. Downscaled precipitation estimates were combined with APHRODITE rain gauge-based data using the calibration procedure (geographical ratio analysis (GRA)). Results indicated that the MGWR model performed better on fit and accuracy than the RF model to predict the precipitation. Annual TRMM estimates after downscaling and calibration not only translate the spatial heterogeneity of precipitation but also improved the agreement with rain gauge observations with a reduction in RMSE and bias of ~88 mm/year and 27%, respectively. Significant improvement was also observed in monthly (and daily) precipitation estimates with a higher reduction in RMSE and bias of ~30 mm mm/month (0.92 mm/day) and 10.57% (3.93%), respectively, after downscaling and calibration procedures. In general, the higher reduction in bias values after downscaling and calibration procedures was noted across the downstream low elevation zones (e.g., zone 1 correspond to elevation changes from 0 to 500 m). The low performance of precipitation products across the elevation zone 3 (&gt;1000 m) might be associated with the fact that satellite observations at high-altitude regions with glacier coverage are most likely subjected to higher uncertainties. The high-resolution grided precipitation data generated by the MGWR-based proposed framework can facilitate the characterization of distributed hydrology in the Indus Basin. The method may have strong adoptability in the other catchments of the world, with varying climates and topography conditions.

Population specific methylome remodeling in high and low elevation populations of Indian west Himalayan Arabidopsis thaliana in response to elevated CO2

Unravelling the plants responses towards rising atmospheric [CO 2 ] have largely been explored in genetical and morpho-physiological contexts. However, epigenetic factors including DNA methylation which play critical roles in adaptation are largely unexplored. Here we investigated the methylome, transcriptome and morpho-physiological responses of the two Arabidopsis thaliana populations evolved at high (3400 m amsl) and low elevation (700 m amsl) zones to elevated [CO 2 ] (e[CO 2 ]). We show that depending on the origin of the population, there were local level variations in DNA methylation when exposed to e[CO 2 ], but global methyl cytosine (mC) content remained unchanged. Further, there was loss of methylation and more protein coding genes were differentially methylated than transposable elements and non-coding RNA genes, in both the populations but more so in the low elevation one. The differentially methylated genes of the two populations belonged to distinct functional categories. More genes related to methylation machinery were down-regulated in the high elevation population than the low elevation one. Although there was no correlation between methylation and gene expression at the global scale but a few genes exhibited methylation dependent expression level. Finally the hyper- and hypo-methylated status of a few genes due to e[CO 2 ] treatment were validated. Overall, our data suggested the two populations responded differently towards e[CO 2 ] with respect to methylome remodeling, phenotypic and molecular plasticity. However, methylome remodeling and molecular plasticity were more prominent in the low elevation population. Understanding the evolution of epigenetic response towards e[CO 2 ] may help in future crop improvement strategies. • Elevated CO 2 affects DNA methylation remodeling in Arabidopsis thaliana depending on origin of the population. • Methylome remodeling and molecular plasticity of the low elevation population were more than the higher elevation one. • More protein coding genes were differentially methylated in response to elevated CO 2. • Elevated CO 2 induced global gene expression and methylation is not co-linear.

Soil Salinity Patterns in an Olive Grove Irrigated with Reclaimed Table Olive Processing Wastewater

The agricultural use of saline table olive processing wastewater enables the implementation of closed water cycles in this socioeconomically important industry for rural southern Spain and relieves environmental, economic, and legal burdens. To allow growers to evaluate and guarantee adequate long-term soil and plant conditions when irrigating with such regenerated wastewaters, efficient soil monitoring strategies are needed. Field-scale monitoring with electromagnetic induction sensing, after one (2013) and five years (2017) of irrigation with regenerated wastewater with average electrical conductivity (EC) near 6 dS m−1 in an olive orchard in southern Spain, showed accumulation of highly conductive material in the subsoil in relation to local topography and soil characteristics. Laboratory analysis of the soil water revealed strongly varying patterns of EC during the growing season and across the olive grove, which were attributed to dilution and concentration effects due to rainfall and evaporation, respectively. Visual inspection and leaf analyses revealed no negative effects on the olive trees. Apparent electrical conductivity (ECa), measured in between the tree rows in 2013, showed a linear relationship with surface soil EC1:5 under the drippers and allowed identification of areas with high ECa in the low elevation zones of the farm, due to the presence of shallow perched saline water tables. A second ECa measurement in 2017 showed similar spatial ECa patterns and was used to estimate the distribution of soil EC across the soil profile using inversion software, although no unique field-wide relationships with soil properties could be inferred, possibly as a consequence of spatially variable soil clay and water contents, due to the influence of the topography. Despite the implementation of a more conservative irrigation strategy since 2015, results showed that the salinity has increased since 2013 in about 15% of the study area, with the largest increments in the deepest horizons.

Evaluating irrigation status in the Mekong Delta through polarimetric L-band SAR data assimilation

For sustainable food production in the Mekong Delta, local information on irrigation status is essential for allocating water resources efficiently at the community level. ALOS-2 PALSAR-2 L-band SAR can be used to detect submerged and nonsubmerged soil covered by rice plants at a spatial resolution compatible with field observation but a low temporal resolution. In this study, a new multiscale data assimilation technique is developed to estimate the spatiotemporal dynamics of field water levels at a temporal resolution appropriate to inform decision-making on when to initiate irrigation. The method employs an irrigation model based on parameters representing farmers' irrigation practices. ALOS-2 PALSAR-2 data are used to derive the hydrological parameters of the model, including an irrigation parameter representing how deep the field water level dropped until the next round of irrigation was initiated. We developed observation operators for the soil submersion status under vegetation and spatial submersion percentages instead of assimilating soil moisture products. The study uses ALOS-2 PALSAR-2 data (25–100 m spatial resolution, approximately every 42 days) over the Mekong Delta and experimental data collected in situ for model initialization and validation. The estimated irrigation parameter controlling the maximum depth of field water level showed spatio-temporal consistency with the ground-observed value (RMSE = 4.24 cm). The values of the parameters also showed spatial consistency with respect to DEM data; he paddies with low irrigation model parameter values were prone to be located in low-elevation zones (<2 m), whereas high model parameters values tended to be located in paddies in the high-elevation zones (>3 m).The results show promising applications using L-band SAR observations for monitoring paddy field water level, for irrigation practices and for estimation of the water consumption and of methane emissions.

Influence of Anthropogenic Pressure on the Plant Species Richness and Diversity Along the Elevation Gradients of Indian Himalayan High-Altitude Protected Areas

Plant biodiversity of some of the high-altitude national parks of Indian Himalaya is increasingly experiencing anthropogenic pressure. Consequently, plant species composition, vegetation structure, and diversity patterns of these protected areas are assumed to be substantially altered. However, limited efforts are made to quantify the impact of anthropogenic disturbances on the species richness of such high-altitude national parks of Indian Himalaya. To overcome this data gap, this study is aimed at quantifying the impact of anthropogenic disturbances on the vegetation community patterns of two Indian Himalayan National Parks along elevation transects, i.e., the Valley of Flowers National Park (VoFNP, altitude ranging from 3,200 to 6,700 m a.s.l.) and the Great Himalayan National Park (GHNP, altitude ranging from 1,500 to 6,000 m a.s.l.), India. The impact of anthropogenic disturbances along the elevation zone (3,200–4,500 m) on the vegetation community patterns was assessed by comparing plant species richness and diversity between selected disturbed and undisturbed sites along the altitudinal gradient. The disturbed sites, near to pathways within each national park, experienced the frequent human interventions than the undisturbed sites which were beyond 25–50 m from the pathway within each national park. Diversity profiles calculated as hill numbers (q = 0, 1, 2) showed significant variation between disturbed and undisturbed sites exhibiting high level of disturbance, especially in VoFNP. The non-metric multidimensional scaling of species composition data along the elevation of both national parks indicated that heterogeneously grouped plant species were much higher for disturbed sites than undisturbed ones. The quantum of anthropogenic pressure on disturbed sites of both VoFNP and GHNP was discernible through statistically significant lower values of soil moisture, bulk density, porosity, potassium, and phosphorous content than the undisturbed sites. As a consequence, disturbed sites were clearly noted to have lower numbers of threatened and endemic species (20 and 17, respectively) in comparison with undisturbed sites (32 and 31, respectively). The canonical correlation analyses of species compositions and soil properties of VoFNP and GHNP indicated that soil moisture and pH were the two major factors that control species composition for both disturbed and undisturbed sites, whereas soil porosity played a major role in species composition of undisturbed sites. The disturbed sites of lower elevation zones (3,200–3,500 m) of both parks were found with a higher density of invasive species (i.e., Polygonum polystachyum, Impatiens sulcata, Cuscuta europaea, etc.). Our study indicated that anthropogenic pressures on the high-altitude national parks of India not only altered the soil properties, but potentially threatened the species composition, thus accelerating urgent need to implement mitigation measures for restoration of degrading habitat of the native, endemic, and threatened plants in both the parks.

Spatial Distribution of Bat Species on Hispaniola Island, the Greater Antilles

Hispaniola shows the highest environmental heterogeneity among the Greater Antilles mainly due to its complex land relief, encompassing a high ecosystemic heterogeineity, and bats as one o the most representative group of vertebrates. However, the island remains the least studied in the greater Antilles. In this work, we present a first comprehensive approach to the distribution of chiropterans of Hispaniola, product of the synthesis of 5,212 unpublished locality records, and bioclimatic and topographic variables, we fitted Habitat Suitability Models (HSM) and projected bat potential distribution maps, using Maxent. Individual distribution maps were overlapped to obtain a chiropteran richness map, which showed an inverse relationship between species and the elevation. Only three out of the 20 species present on the island were found above 1,500 m a.s.l. As a trend, species richness concentrated in humid forests and dry subtropical forests, typical of the low and medium elevation zones.

Assessing Soil Organic Carbon Stock Dynamics under Future Climate Change Scenarios in the Middle Qilian Mountains

Soil organic carbon (SOC) simply cannot be managed if its amounts, changes and locations are not well known. Thus, evaluations of the spatio-temporal dynamics of SOC stock under future climate change are crucial for the adaptive management of regional carbon sequestration. Here, we evaluated the dynamics of SOC stock to a 60 cm depth in the middle Qilian Mountains (1755–5051 m a.s.l.) by combining systematic measurements from 138 sampling sites with a machine learning model. Our results reveal that the combination of systematic measurements with the machine learning model allowed spatially explicit estimates of SOC change to be made. The average SOC stock in the middle Qilian Mountains was expected to decrease under future climate change, while the size and direction of SOC stock changes seemed to be elevation-dependent. Specifically, in comparison with the 2000s, the mean annual precipitation was projected to increase by 18.37, 19.80 and 30.80 mm, and the mean annual temperature was projected to increase by 1.9, 2.4 and 2.9 °C under the Representative Concentration Pathway (RCP) 2.6 (low-emissions pathway), RCP4.5 (low-to-moderate-emissions pathway), and RCP8.5 (high-emissions pathway) scenarios by the 2050s, respectively. Accordingly, the area-weighted SOC stock and total storage for the whole study area were estimated to decrease by 0.43, 0.63 and 1.01 kg m–2 and 4.55, 6.66 and 10.62 Tg under the RCP2.6, RCP4.5 and RCP8.5 scenarios, respectively. In addition, the mid-elevation zones (3100–3900 m), especially the subalpine shrub-meadow Mollic Leptosols, were projected to experience the most intense carbon loss. However, the higher elevation zones (&gt;3900 m), especially the alpine desert zone, were characterized by significant carbon accumulation. As for the low-elevation zones (&lt;2900 m), SOC was projected to be less varied under future climate change scenarios. Thus, the mid-elevation zones, especially the subalpine shrub-meadows and Mollic Leptosols, should be given priority in terms of reducing CO2 emissions in the Qilian Mountains.

Displacement evolution of reverse-dip rock slope considering the change of the reservoir level

The fluctuation and periodic change of reservoir level are the important incentives that affect the stability of the reverse-dip rock slope. Based on the field monitoring data, this paper investigates the topping deformation evolution characteristics of a typical reverse-dip slope containing different geological partitions considering the fluctuation of reservoir level. A typical reverse-dip rock slope was taken as an engineering case, whose geological factors including elevation, slope angle, and aspect were first obtained by a field survey. Subsequently, the factors were superimposed through ArcGIS to obtain the geological partitions. Afterwards, a spatiotemporal evolution nephogram of the topping displacement was obtained by discrete monitoring data of surface displacement of the slope. Finally, the deformation characteristic of the prone zone was analyzed by superposing the nephogram of the displacement and the geometrical partition, considering the change of the reservoir level. The results show that the largest geological and geometric characteristic zone is at the bottom elevation, medium slope, and north aspect. The zone with significant horizontal displacement is distributed in the front and middle edges of the slope, which increases with the increase of the reservoir level and vice versa. The vertical displacement mainly occurs in the trailing of the slope. The area of superimposed displacement in strong deformation zones increases as either the reservoir level rises or falls. After the superposition, zones with strong deformation increase with the variation of the reservoir level, and the area with the largest displacement is distributed at the medium gradient, low elevation, and north aspect zones.

Pore water exchange‐driven inorganic carbon export from intertidal salt marshes

AbstractRespiration in intertidal salt marshes generates dissolved inorganic carbon (DIC) that is exported to the coastal ocean by tidal exchange with the marsh platform. Understanding the link between physical drivers of water exchange and chemical flux is a key to constraining coastal wetland contributions to regional carbon budgets. The spatial and temporal (seasonal, annual) variability of marsh pore water exchange and DIC export was assessed from a microtidal salt marsh (Sage Lot Pond, Massachusetts). Spatial variability was constrained from224Ra :228Th disequilibria across two hydrologic units within the marsh sediments. Disequilibrium between the more soluble224Ra and its sediment‐bound parent228Th reveals significant pore water exchange in the upper 5 cm of the marsh surface (0–36 L m−2d−1) that is most intense in low marsh elevation zones, driven by tidal overtopping. Surficial sediment DIC transport ranges from 0.0 to 0.7 g C m−2d−1. The sub‐surface sediment horizon intersected by mean low tide was disproportionately impacted by tidal pumping (20–80 L m−2d−1) and supplied a seasonal DIC flux of 1.7–5.4 g C m−2d−1. Export exceeded 10 g C m−2d−1for another marsh unit, demonstrating that fluxes can vary substantially across salt marshes under similar conditions within the same estuary. Seasonal and annual variability in marsh pore water exchange, constrained from tidal time‐series of radium isotopes, was driven in part by variability in mean sea level. Rising sea levels will further inundate high marsh elevation zones, which may lead to greater DIC export.

Cyprinid Fishes: An Overview on the Present Status in Meghalaya, India

Cyprinid fishes of Meghalaya were investigated from twin drainage basins Brahmaputra and Barak-Surma-Meghna. 27 cyprinid fishes under 14 genus and 7 sub families were recorded from rivers and reservoirs of four different gradient zones. The diversity of Cyprinid fishes was highest with 49% representation of Cyprinids at lower elevation Zone IV below 500 m above MSL and bio diversity indices estimated as H: 3.05, 1-D: 0.10. In contrary lowest diversity with 7% representation of fishes was observed at elevation 1501 to 2000 m above MSL in Zone I with bio diversity indices H: 0.25, 1-D: 0.57. Distribution of commercially important cyprinids under genus Labeo, Systomus and Cirrhinus were found to be restricted to rivers of Barak-Surma-Meghna drainage basin. Catch percentage of cyprinids indicates that 70% of fishes exhibit occasional occurrence and 30% as common occurrence. High percentage of occasional occurrence, low catch composition percentage and with restricted distribution of commercially important fishes to only certain rivers of Barak-Surma-Meghna drainage is an indication of depletion of cyprinid resources in the state and requires taking multi prong conservation measures to protect cyprinid fishes in Meghalaya.

Patterns of dengue in Nepal from 2010-2019 in relation to elevation and climate.

Understanding and describing the regional and climatic patterns associated with increasing dengue epidemics in Nepal is critical to improving vector and disease surveillance and targeting control efforts. We investigated the spatial and temporal patterns of annual dengue incidence in Nepal from 2010 to 2019, and the impacts of seasonal meteorological conditions (mean maximum, minimum temperature and precipitation) and elevation on those patterns. More than 25 000 laboratory-confirmed dengue cases were reported from 2010 to 2019. Epidemiological trends suggest that dengue epidemics are cyclical with major outbreaks occurring at 2- to 3-y intervals. A significant negative relationship between dengue incidence and increasing elevation (metres above sea level) driven by temperature was observed (p<0.05) with dengue risk being greatest below 500 m. Risk was moderate between 500 and 1500 m and decreased substantially above 1500 m. Over the last decade, increased nightly temperatures during the monsoon months correlated with increased transmission (p<0.05). No other significant relationship was observed between annual dengue cases or incidence and climatological factors. The spatial analysis and interpretation of dengue incidence over the last decade in Nepal confirms that dengue is now a well-established public health threat of increasing importance, particularly in low elevation zones and urbanised areas with a tropical or subtropical climate. Seasonal variations in temperature during the monsoon months are associated with increased transmission.

Increased Surface Broadband Emissivity Driven by Denser Vegetation on the Tibetan Plateau Grassland Area

Global changes are profoundly affecting the global terrestrial ecosystems, especially for the vegetation. Simultaneously, the affected vegetation gives feedback to the climates. The Tibetan Plateau (TP), one of the most sensitive areas to global changes, has undergone extraordinary changes on its ecosystem processes. In the multitudinous land surface ecosystem processes affecting the climate, the process of land surface energy balance affecting by vegetation activity is one of the most important and still has not been well recognized. The spatial and temporal patterns of the broadband emissivity (BBE) on the TP and its relations to the vegetation activity and land surface temperature were examined in this research. We find that elevated BBE is regulated by increasing vegetation activity for grasslands over the TP from 2000 to 2015. The spatial patterns of BBE and its interannual changes are highly correlated with vegetation activity. The BBE changing rate generally declines along rising elevation, due to the shrunk effects from vegetation activity. A greater sensitivity of BBE to vegetation activity occurs in the sparse vegetation area or high elevation zone than in the dense vegetation area or low elevation zone. Increasing BBE has a cooling effect on the land surface, especially at night. This cooling effect is related to wind speed. The growing season BBE trend as regulated by vegetation activity highlights the importance to take mounting notice of the growing season long-wave energy fluxes of surface energy balance studies in the future.