Areal Changes Research Articles

Clinical profile of patients undergoing percutaneous stellate ganglion block for electrical storm and association with antiarrhythmic efficacy

Abstract Background Percutaneous stellate ganglion block (PSGB) usage for patients with refractory ventricular arrhythmias (VAs) in form of electrical storm (ES) is in quickly expanding. The clinical profile of patients and the potential association with the antiarrhythmic efficacy of the procedure are mostly unexplored. Purpose To better characterize clinical profile and potential association with antiarrhythmic efficacy of patients undergoing PSGB for ES. Methods Patients undergoing PSGB for ES in our Center from 2/2021 to 2/2024 were enrolled; all the dynamic variables were evaluated in a per procedure analysis. Results 45 patients (93% male, 64 ± 10 years) received a total of 80 PSGB performed with the lateral, ultrasound (US) guided technique; most PSGB consisted of a single bolus anesthetic injection (lidocaine + ropivacaine), 26% in an additional continuous infusion, mostly with ropivacaine. All procedures except for 3 in a single patient who had previously received left cardiac sympathetic denervation, were performed on the left side. Most of the patients (60%) suffered ischemic cardiomyopathy (CMP), including 10 with an acute coronary syndrome; the rest had non-ischemic CMP; 60% had an ICD. The type of VAs was ventricular tachycardia (VTs) only in 86% of the procedures (cycle length 404 ± 143 msec), VT and VF in 10% and VF only in 3 (4%). Most PSGB (81%) were performed in the setting of impending or manifest cardiogenic shock (SCAI classification B or more), including 20% with sepsis. Cardiac US performed before (within 12 hours) each PSGB showed a severely depressed left ventricular (LV) function (mean LVEF 22 ± 10%, mean LV outflow tract velocity time integral 12 ± 4 cm), calculated at a mean heart rate of 81 ± 16 bpm. Mean LVEDV was 252 ± 104 ml, 79% had mitral regurgitation (MR) ≥2+/4+ (including 39% severe MR), 50% had ≥ moderate diastolic dysfunction, 29% had right ventricular dysfunction (mean fractional areal change 33± 7%). Most cases (75%) experienced a complete VAs suppression (sustained or treated) in the 12 hours after PSGB; only 3/80 cases required additional urgent antiarrhythmic strategies (intra-aortic ballon pump in one case, urgent pacing in another one, urgent revascularization in the last one). None of the assessed clinical or echocardiographic characteristics was significantly associated with VT cycle length or the response to PSGB. Only 1 (1%) major complication occurred (respiratory arrest), that was quickly and effectively treated with lipid emulsion. Conclusions PSGB in our Center was mostly performed in the setting of primary impending or manifest cardiogenic shock with severely impaired cardiac function, with an excellent safety profile. None of the assessed clinical or echocardiographic variables were associated with response to PSGB. Our data, despite preliminary and requiring confirmation, suggests always considering PSGB in the urgent/emergent setting independently from patients’ characteristics.

Oil and Gas Content of the South Caspian Basin

Abstract —We have compiled maps of areal isotope composition changes and constructed graphs of gas HC distribution depending on the stratigraphic age of the host rocks and graphs of isotope composition changes depending on the depth of sampling to study the hydrocarbon potential of the deep-seated oil and gas pools of the South Caspian Basin. The genesis of gas was studied using the techniques elaborated by M. Schoell and A. James. Two stages of hydrocarbon formation have been established by study of various kinds of gas manifestation. The first stage (Miocene–Eocene) began in the deposits underlying the Productive Series and continued up to the deposits of the latter. This stage was characterized by a frequent change in the directions of both downward and upward movements of gases. The second stage of hydrocarbon formation (Anthropogene–Pliocene) began in the deposits of the Productive Series and was characterized by a change in the regional geodynamic setting. Avalanche sedimentation and the predominance of downward movements over upward ones favored the accumulation of thick sediments at the time when the Productive Series formed. The sedimentation and tectonic processes (downwarping) in the deep-water zone of the basin led to harsh thermobaric conditions in the sedimentary strata. A detailed analysis of the results of gas survey in the deep-water zone of the South Caspian Basin has shown gas generation with a predominance of two components, methane and ethane. Study of the trends of temporal and areal hydrocarbon migration and of the areas of oil and gas generation makes it possible to reveal structures with evidence for large and giant hydrocarbon reserves. We have established that gas hydrocarbons in the bottom and upper-section sediments of the southern Caspian Sea are intimately related to the sources of hydrocarbons, their migration, and other processes running in the deep-seated sediments and in the upper section.

Geo-spatial Analysis of Erosion Accretion Dynamics and Areal Changes Along Digha Coastline in West Bengal, India

Geo-spatial Analysis of Erosion Accretion Dynamics and Areal Changes Along Digha Coastline in West Bengal, India

God and Group: The Religious Ecology of Hate Crimes Against Jews and Muslims in the United States

In the United States, hate crimes that are motivated by religious bias disproportionately impact minoritized religious groups. This study investigates religious ecological predictors of hate crimes against Jews and Muslims in the US, drawing on theories of religion and intergroup offending. Measures of areal religious composition and change are drawn from two waves of the US Religion Census. Multilevel logistic regression models predict incidence of anti-Jewish and anti-Muslim hate crimes across county-years (2010–2018), adjusting for law enforcement agency coverage, hate crime reporting, and social and political factors. Christian adherence and overall religious diversity are associated with lower incidence of anti-Jewish hate crime. Jewish and Muslim adherence are positively associated with anti-Jewish and anti-Muslim hate crime, respectively, and counties undergoing relatively large increases in Muslim adherence have heightened incidence of anti-Muslim hate crime. Implications for theory and policy, as well as opportunities for future research, are discussed.

Decadal Changes (1980–2021) of Shoreline and Mangrove Cover in Sundarban Delta, India, Using Remote Sensing and GIS

Abstract Being situated in the estuary of the flood-dominated Hooghly River system, the macrotidal Indian Sundarban Delta (ISD) has become one of the most complex, dynamic, and rapidly changing landforms on Earth’s surface. To study the horizontal areal shifting of shoreline and its impact on mangrove cover in the region, the U.S. Geological Survey (USGS) satellite data of 1980, 1990, 2000, 2010, and 2021 were used. Remote sensing and geographic information system (GIS) techniques were employed in the investigation. Simultaneous prograding and retrograding shoreline shifting was distinguished almost in all the parts, although sediment-starved eastern and macrotidally more active southern lobes experienced dominantly retreating shift, and the sediment-engorged western lobe was demonstrated to be more dynamic. Net areal change over north–south tracks followed the trend of decreasing accretion to increasing erosion while going from west to east, whereas that over west–east tracks followed the trend of exponentially increasing erosion while going from north to south. Overall accretion of ∼91 km2 in the ISD accounted for the augmentation of sparse vegetation of ∼13 km2, whereas ∼243 km2 erosion called for the depletion of sparse and moderate vegetation of ∼18 and ∼174 km2, respectively, over the 41-yr period. Various oceanographic and riparian forces and actions, episodic natural events, etc., vis-a-vis several anthropogenic interventions—all together contributed to such changes. The findings may help the coastal environmentalists, professionals, planners, decision-makers, and implementers in formulating and taking up of suitable strategic measures for integrated and effective coastal zone management in this estuarine wetland forest.

Geomorphic changes after the 2021 Central European flood in the Ahr Valley by LiDAR-based differences

BackgroundIn July 2021, destructive floods in Western Europe were triggered by enormous precipitation rates related to a low-pressure system named "Bernd." These catastrophic events led not only to major damage to infrastructure, severe economic losses, and the loss of lives but also to significant landscape changes and modifications. Here, we focus, as a case study, on the flood aftermath of the Ahr Valley in Rhineland-Palatinate state in western Germany, as it was one of the most affected and destroyed regions by the flood. We utilize high-resolution Digital Terrain Models (DTMs) based on airborne Light Detection and Ranging (LiDAR) that were taken shortly before and after the flood to investigate insights into geomorphic changes. ResultsBy calculating Digital Terrain Models of Difference (DoD), we are able to quantify volumetric and areal changes caused by erosional and depositional processes for different sites in the Ahr Valley. Due to the morphology of the narrow Ahr Valley, most of the erosion and deposition is located within the deeply incised canyon of the Ahr River. The comprehensive analysis reveals notable morphological modifications throughout the study area, with a calculated erosion/deposition areal ratio of 0.46 and an erosion/deposition volumetric ratio of 0.63. Our findings indicate massive deposition regarding both areal and volumetric. We selected six different locations along the Ahr Valley that showcase distinct aspects of flood-induced fluvial morpho-dynamics. Deposition occurred mainly in point bars and downstream of destroyed artificial levees, in a braided river style.ConclusionOur investigations contribute to an overview and assessment of the morphological response to the destructive flood in the Ahr Valley. The results emphasize the necessity for implementing effective flood management strategies, as most of the urban areas in the Ahr Valley were flooded. Moreover, our results provide valuable insights into the impacted areas, highlighting vulnerable locations for flood-related erosion and deposition. This information could contribute to future mitigation and protection efforts, aiding in the development of comprehensive strategies to minimize the impact of similar events in the future.

Geospatial analysis of shoreline and areal dynamics in the Ganges deltaic island of Bangladesh using the GIS-DSAS technique

Manpura Island, located at the mouth of the Ganges-Brahmaputra-Meghna (GBM) River estuary, is a well-known Ganges deltaic island prone to severe erosion. This study aims to identify shoreline and areal changes in Manpura Island of Bangladesh from 1990 to 2020 using the digital shoreline analysis system (DSAS), a plugin of ArcGIS. The estimation of shoreline variability was primarily described for four segments of the Island: Segment A in the north, Segment B in the west, Segment C in the south, and segment D in the east. It was observed that all four segments of the study area are vulnerable to high rates of shoreline erosion. Landward movement was high in Segment A where Net Shoreline Movement (NSM) was −4000.1 m. Landward movement was also high in Segments B and C with the NSM of −1084.7 m and −1021.6 m, respectively. According to the End Point Rate (EPR) and Linear Regression Rate (LRR), Segment A exhibited a very dynamic feature, with an average shoreline change rate of −24.7 m/yr and −24.2 m/yr, respectively. In Segment C, the average shoreline change rate was −8.5 m/yr for EPR and −9.1 m/yr for LRR. Approximately 392 transects were constructed in the four segments of the island, with approximately 330–334 showing landward movement and 58–62 showing seaward movement. Nevertheless, the island lost about 28.4 km2 in land area and gained only around 2.3 km2 of its original landmass during the study period. The total loss of shoreline length was about 11.5 km (0.4 km/yr), while the total loss of land area was about 26.1 km2 (0.9 km2/yr). The main factors of shoreline change in the study region is likely to be high river discharge, stormy climate and, human interference. The results of this study are useful for the proper management and planning of Manpura Island. However, they can also be used in statistical approaches to forecasting possible shoreline locations in the future under double pressure of climate change and human activities.

A Greenland-wide empirical reconstruction of paleo ice sheet retreat informed by ice extent markers: PaleoGrIS version 1.0

Abstract. The Greenland Ice Sheet is a large contributor to global sea level rise, and current mass losses are projected to accelerate. However, model projections of future ice sheet evolution are limited by the fact that the ice sheet is not in equilibrium with present-day climate but is still adjusting to past changes that occurred over thousands of years. While the influence of such committed adjustments on future ice sheet evolution remains unquantified, it could be addressed by calibrating numerical ice sheet models over larger timescales and, importantly, against empirical data on ice margin positions. To enable such paleo data–model interactions, we need Greenland-wide empirical reconstructions of past ice sheet extent that combine geomorphological and geochronological evidence. Despite an increasing number of field studies producing new chronologies, such a reconstruction is currently lacking in Greenland. Furthermore, a time slice reconstruction can help to (i) answer open questions regarding the rate and pattern of ice margin evolution in Greenland since the glacial maximum, (ii) develop a standardised record of empirical data, and (iii) identify new sites for future field campaigns. Based on these motivations, we here present PaleoGrIS 1.0, a new Greenland-wide isochrone reconstruction of ice sheet extent evolution through the Late Glacial and early- to mid-Holocene informed by both geomorphological and geochronological markers. Our isochrones have a temporal resolution of 500 years and span ∼ 7.5 kyr from approximately 14 to 6.5 kyr BP. We describe the resulting reconstruction of the shrinking ice sheet and conduct a series of ice-sheet-wide and regional analyses to quantify retreat rates, areal extent change, and their variability across space and time. During the Late Glacial and early- to mid-Holocene, we find the Greenland Ice Sheet has lost about one-third of its areal extent (0.89 million km2). Between ∼ 14 and ∼ 8.5 kyr BP, it experienced a near-constant rate of areal extent loss of 170 ± 27 km2 yr−1. We find that the ice-sheet-scale pattern of margin retreat is well correlated to atmospheric and oceanic temperature variations, which implies a high sensitivity of the ice sheet to deglacial warming. However, during the Holocene, we observe inertia in the ice sheet system that likely caused a centennial- to millennial-scale time lag in ice extent response. At the regional scale, we observe highly heterogeneous deglacial responses in ice extent evident in both the magnitude and rate of retreat. We hypothesise that non-climatic factors, such as the asymmetrical nature of continental shelves and onshore bed topographies, play important roles in determining the regional- to valley-scale dynamics. PaleoGrIS 1.0 is an open-access database designed to be used by both the empirical and numerical modelling communities. It should prove a useful basis for improved future versions of the reconstruction when new geomorphological and geochronological data become available.

A comprehensive research on open surface drinking water resources in Istanbul using remote sensing technologies.

Istanbul is a megacity with a population of 15.5 million and is one of the fastest-growing cities in Europe. Due to the rapidly increasing population and urbanization, Istanbul's daily water needs are constantly increasing. In this study, eight drinking water basins that supply water to Istanbul were comprehensively examined using remote sensing observations and techniques. Water surface area changes were determined monthly, and their relationships with meteorological parameters and climate change were investigated. Monthly water surface areas of natural lakes and dams were determined with the Normalized Difference Water Index (NDWI) applied to Sentinel-2 satellite images. Sentinel-1 Synthetic Aperture Radar (SAR) images were used in months when optical images were unavailable. The study was carried out using 3705 optical and 1167 SAR images on the Google Earth Engine (GEE) platform. Additionally, to determine which areas of water resources are shrinking, water frequency maps of the major drinking water resources were produced. Land use/land cover (LULC) changes that occurred over time were determined, and the effects of the increase in urbanization, especially on drinking water surface areas, were investigated. ESRI LULC data was used to determine LULC changes in watersheds, and the increase in urbanization areas from 2017 to 2022 ranged from 1 to 91.43%. While the basin with the least change was in Istranca, the highest increase in the artificial surface was determined to be in the Büyükçekmece basin with 1833.03ha (2.89%). While there was a 1-12.35% decrease in the surface areas of seven water resources from 2016 to 2022, an increase of 2.65-93% was observed in three water resources (Büyükçekmece, Sazlıdere, and Elmalı), each in different categories depending on their size. In the overall analysis, total WSA decreased by 62.33ha from 2016 to 2022, a percentage change of 0.70%. Besides the areal change analysis, the algae contents of the drinking water resources over the years were examined for the major water basins using the Normalized Difference Chlorophyll Index (NDCI) and revealed their relationship with meteorological factors and urbanization.

High-resolution velocity and strain rate fields in the Kumaun Himalaya: An implication for seismic moment budget

The collision between Indian and Eurasian tectonic plates results in a series of earthquakes, releasing stored elastic strain accumulated over a long period. This research utilizes 22 new and 26 previously published GPS velocities along with nine years of InSAR observations to estimate high-resolution velocity and strain rate fields across the Kumaun Himalaya. The resulting high-resolution velocity field ranges between 0.5 and 14 mm/yr relative to the India-fixed reference frame. The geodetic strain rate is not uniform across the study region and the higher strain rates are observed along the Main Central Thrust. The areal change rate along the Kumaun Himalaya indicates a significant amount of tectonic compression, with an average value of − 0.08 μstrain∕yr, while the maximum shear strain rate in the region has a mean value of 0.08 μstrain∕yr. The moment deficit rate, based on accumulated strain and energy release over 200 years, turns out to be 7.59 × 1018Nm∕yr along the Kumaun Himalaya. This suggests that the study region can generate a great earthquake (Mw 8.1) in the future.

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States.

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the "black-box" nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having "no change" (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

Assessing the conservation status of mangroves in Rakhine, Myanmar

Abstract Ecosystem degradation is a key challenge that human society faces, as ecosystems provide services that are tied to human well‐being. Particularly, mangrove ecosystems provide important services to communities but are suffering heavy degradation, loss and potential collapse due to anthropogenic activities. The IUCN Red List of Ecosystems is a transparent and consistent framework for assessing ecosystems' risk of collapse and is increasingly used to inform legislation and ecosystem management globally. Satellite data have become increasingly common in environmental monitoring due to their extensive spatial and temporal coverage. Here, recent advances in analyses using satellite‐derived data were implemented to reassess the conservation status of the ‘Rakhine mangrove forest on mud’, an important intertidal ecosystem in Myanmar, extending a previous national Red List assessment that assessed the ecosystem as Critically Endangered. By incorporating additional data sources and analyses, the extended assessment produced more robust results and reduced the uncertainty in the previous assessment. Overall, the ecosystem was assessed as Critically Endangered (range: Vulnerable to Critically Endangered) as a result of historical mangrove extent loss. Recent losses and biotic disruptions were also observed, which would have led to the ecosystem being assessed as Vulnerable. While the final outcome of the Red List assessment remained at Critically Endangered due to the historical state of the mangroves pre‐dating the temporal coverage from satellite data, the uncertainty of the ecosystem's status was reduced, and the reassessment highlighted the recent areal changes and mangrove degradation that has occurred. The importance of conducting reassessments when new data become available is discussed, and a template for future mangrove Red List assessments that use satellite data as their primary source of information to improve the robustness of their results is presented.

Attribution Analysis on Areal Change of Main Wetland and Its Influence on Runoff in the Naolihe River Basin

Wetlands have powerful runoff regulation functions, which can effectively store and retain surface runoff. The runoff regulation function of wetlands is affected by wetland areas, which affect the capacity of flood control. To explore the law of the area change of the main wetlands of the Naolihe River Basin (MWNRB), the visual interpretation method was used to extract wetlands. To identify the reasons for area changes in the MWNRB, the maximum likelihood method, minimum distance method, and neural network method were used to classify land use types from remote sensing images; the M-K variation point test and Theil-Sen trend analysis were used to test the variation point and calculate the trend of precipitation and temperature series. To clarify the influence of wetland areas on runoff, the Gini coefficient and SRI of runoff were used to calculate runoff temporal inhomogeneity. The results showed that the area of the MWNRB obviously decreased, with 74.5 × 106 m2/year from 1993 to 2008, and increased slowly from 2008 to 2015, with 27.7 × 106 m2/year. From 1993 to 2008, 50.74% and 38.87% of wetlands were transformed into paddy fields and dry fields, respectively. From 2008 to 2015, 61.69% and 7.76% of wetlands were transformed from paddy fields and dry fields, respectively. The temperature of the MWNRB increased slowly by 0.04 °C/year from 1993 to 2008 and increased obviously by 0.16 °C/year from 2008 to 2015. The precipitation decreased by 5.6–8.1 mm/year and increased by 16.6–41.2 mm/year in 1993–2008 and 2008–2015, respectively. Compared with precipitation and temperature, land use change caused by human activities is the main cause of wetland area change. The area change of the MWNRB has a certain influence on the runoff regulation and storage capacity. The Gini coefficient and SRI index increased from 0.002/year (0.008) to 0.023/year from 1993 to 2008 and decreased from 0.046/year (0.045) to 0.161/year from 2008 to 2015, respectively.

Multi-decadal degradation and fragmentation of palsas and peat plateaus in coastal Labrador, northeastern Canada

Peatland permafrost landforms, such as palsas and peat plateaus, often represent the most southern lowland permafrost occurrences in the Northern Hemisphere. While peatland permafrost is often found in continental conditions, over a thousand permafrost peatlands were recently identified along the previously understudied coastline of the Labrador Sea in northeastern Canada. The vulnerability of these landscapes to thaw is unknown but is expected to have hydrological and ecological impacts on important caribou habitat, the abundance of culturally relevant berries, and permafrost carbon storage. Using a combination of aerial photography (from 1948, 1985, 1992, 1994, and 2021) and high-resolution satellite imagery (from 2017, 2020, and 2021), we assess multi-decadal areal changes to peatland permafrost landforms at seven peatlands along the Labrador Sea coastline spanning from Red Bay (51.7° N) to north of Hopedale (55.7° N). Analyses reveal declines in permafrost extent of 33%–93% at individual sites, occurring at mean rates of 0.8%–1.5%/a. Permafrost loss was found to occur most rapidly at mixed palsa and peat plateau sites (mean rate of 1.4%/a), followed by palsa sites (mean rate of 1.2%/a) and peat plateau sites (mean rate of 0.9%/a). Patterns of permafrost loss also differed between landform types, with more complete loss of individual landforms at palsa sites and more lateral and internal loss of existing landforms at peat plateau and mixed sites. This widespread degradation of peatland permafrost over the past 28–73 years is attributed to regional warming and peatland greening. Understanding recent change to permafrost peatlands in coastal Labrador is an important step towards predicting future habitat change in northeastern Canada and will inform regional land management in areas dominated by these culturally important landforms.

Ecological vulnerability of China's Yellow River Basin: evaluation and socioeconomic driving factors.

The Yellow River Basin (YRB) is a typical ecologically fragile area in both the Chinese and global contexts. This paper built a sensitivity-resilience-pressure model to evaluate the ecological vulnerability (EV) of the YRB at the grid and prefecture-level regional scales; explored the spatiotemporal characteristics of EV; and scrutinized the impacts of socioeconomic driving factors on EV. The results showed that (1) at the grid and prefecture-level regional scales, EV decreased from the upper to lower reaches, and high vulnerability was observed in the provincial capital city. Mild and severe vulnerability constituted the main EV types in the YRB. (2) The EV index of the YRB decreased from 2.71 to 2.56 in the study period, indicating that the ecological environment improved in the YRB. The slightly and lightly vulnerable areas experienced shrinking-expansion changes, and the overall areas of these two EV types showed expanding trends, while the areal changes and overall trends of the moderately, severely, and extremely vulnerable areas were contrary to those of the slightly and lightly vulnerable areas. (3) The impacts of socioeconomic driving factors on EV dynamically strengthened with the improvement of the socioeconomic level. After considering the interactions of all socioeconomic factors, the explanatory power of the spatial differentiation of EV was enhanced, and the influence of these factors became more prominent.

Google Earth Engine Based Spatio-Temporal Changes of Bafa Lake from 1984 to 2022

The water resource management is crucial to protect environment and ecological cycle. The detection of temporal and spatial changes in the lake's water extent is important for sustainable land planning. Therefore, the areal changes over the wetlands must be well monitored. Bafa Lake is an essential downstream water in the Büyük Menderes Basin which is the largest river basin of the Aegean Region. Google Earth Engine (GEE) is an easy-to-use online remote sensing data processing platform based on cloud computing. In this study, the long-term spatio-temporal changes of Bafa Lake between 1984-2022 have been analyzed using Landsat-5/8 satellite images on the GEE platform. A total of 1093 Landsat images were processed. The annual water areas were computed through composite images per year. The water area extraction was done using the normalized water difference index (NDWI). The minimum and maximum lake water areas in 38 years were detected as 5474 ha and 6789 ha in 1990 and 2006, respectively. In the accuracy assessment according to random sampling points, the Overall Accuracy (OA) was calculated as 98% and the kappa coefficient as 0.96. The water surface area was increased by 3.9% from 1984 to 2022. Between 2015-2022, the maximum increase or decrease in the lake area compared to the previous year observed as less than 1%. Therefore, there has not been a notable variation in the water area of Bafa Lake in the past few years.

Reductions in Coastal Salt Marsh Habitat for Wildlife From Sea-Level Rise in the United States

The rate of sea-level rise (SLR) has increased due to climate change, affecting coastal salt marshes. It is uncertain if species can persist with rapid SLR compounded with other effects of climate change and human activity. SLR-induced habitat loss may lead to extirpations and decreased biodiversity. We conducted a literature review of wildlife that use salt marshes and selected 25 species of birds, mammals, and reptiles representing obligate, facultative, and generalist salt marsh users. We developed three regional case studies to quantify the percentage change in species habitat. We used the National Oceanic and Atmospheric Administration Sea Level Rise Viewer and ImageJ to calculate areal habitat changes in Apalachicola Bay, FL; Blackwater National Wildlife Refuge, MD; and Cape Cod Bay, MA. We used available literature to determine land cover types to estimate species-specific habitat changes by 2050 and 2100. The changes in habitat availability varied among species and salt marsh dependence, but by 2100, average losses were projected to range across accretion rates from 56% to 63% for birds, 44% to 53% for mammals, and 65% to 66% loss for reptiles. Mean habitat loss was greater for obligate (70%–77%) than facultative (69%–70%) and generalist (49%–56%) salt marsh users. SLR-induced habitat loss has been examined for individual species, but few multispecies assessments exist. Our results suggest ubiquitous habitat loss by 2100. Protection, restoration, and management of salt marsh habitat are necessary to conserve common and imperiled wildlife species, sustaining the ecosystem services provided by wildlife and salt marshes.

A novel quantitative analysis for diurnal dynamics of Ulva prolifera patch in the Yellow Sea from Geostationary Ocean Color Imager observation

IntroductionIn the last decade, the outbreak of large-scale green tides caused by Ulva prolifera has continuously occurred in the Yellow Sea. Satellite remote sensing techniques have been widely used to monitor the distribution area and duration of green tides due to their advantages of their large-area synchronous observation. Ulva prolifera in the Yellow Sea is mainly distributed in bands or large patches during its flourishing stage. Previous studies have rarely reported the quantitative analysis of a single Ulva prolifera patch and its changes in the short term.MethodsConsidering the high temporal resolution of the Geostationary Ocean Color Imager (GOCI) sensor and the patchy distribution of Ulva prolifera floating on the sea surface, we developed a feasible method for monitoringUlva prolifera by performing clustering analysis with density-based spatial clustering of applications with noise (DBSCAN) to capture the diurnal variation characteristics of a single Ulva prolifera patch.ResultsThis new approach was used to extract informationfrom a single Ulva prolifera patch in the Yellow Sea in 2012 and 2017. The results showed that during the time of GOCI imaging, the tidal current was the main factor driving the drift of Ulva prolifera, and the drifting direction of Ulva prolifera was consistent with the direction of the local tidal current, with a coefficient of determination of 0.94.DiscussionBy changing the normalized difference vegetation index (NDVI) threshold, further more accurate atmospheric correction (AC) of GOCI data during the twilight periods was indirectly achieved. By comparing the areal change in the single patch before and after AC, we speculated that the daily change in signal intensity received by the GOCI sensor may be the main reason for the diurnal variation in the Ulva proliferacoverage area. The results showed the details of the diurnal variation in Ulvaprolifera patches in the dynamic marine environment, and the main reason that may cause this variation was speculated.

Monitoring spatio-temporal changes in wetlands with harmonized image series in Google Earth Engine.

Study of rapidly changing lakes and wetlands with remote sensing methods is critical for understanding the climatic and anthropogenic effects. However, most of the studies search for the change of water body in specific time periods. Although this approach reduces the workload related to downloading and processing a large number of satellite images in computer environment, it actually causes ignoring some criticalchanges that occurred out of specified time periods.On the other hand, this situation reduces the data volume and the limited data causes problems for the management of water resources. The Google Earth Engine (GEE) platform allows the opportunity to rapidly and practically process large-scale temporal data without downloading. In this study, areal changes in Lake Akşehir in Türkiye, from 1985 to 2020, were calculated and mapped by the GEE as a case. In order to calculate the changes, the Landsat 5 TM, 7 ETM + and 8 OLI&TIRS images were harmonized and created annual mosaics. TheNormalized difference water index (NDWI) and theautomated water extraction index (AWEI) were applied to these annual mosaics. By this approach, the change in the water area representing a shrank by 87% on average (according to the calculations91% for the NDWI and 83% for the AWEI) from 1985 to 2020 was assessed practically and rapidly on annual mosaics created from all images between the studied period, instead of assessment based on images taken on only one date in the chosen years as in previous studies. Such an approach will provide time and labour savings and provide more meaningful and uninterrupted data for studies about changes in other wetland areas.

Using knowledge-guided machine learning to assess patterns of areal change in waterbodies across the contiguous US

Using knowledge-guided machine learning to assess patterns of areal change in waterbodies across the contiguous US