Percent Cover Research Articles

Kondisi Terumbu Karang Di Perairan Leato Selatan Kecamatan Dumbo Raya Provinsi Gorontalo

Coral reefs are one of the tropical aquatic ecosystems which have a very important function both for the organisms that build this ecosystem and the surrounding ecosystems, namely seagrass ecosystems and mangrove ecosystems. Coral reef ecosystems are coastal area resources that are very vulnerable to damage, especially caused by human behavior/surrounding communities. The aim of the research is to determine the percentage of coral cover and coral reef mortality index in South Leato waters. This research was carried out from February to March 2024, located in South Leato Waters, Dumbo Raya District, Gorontalo Province. The research uses the Underwater Photo Transect (UPT) method, where the data is processed and analyzed with CPCe software. Based on the percentage of live coral cover from each station, namely Station I of 48.53% is in the medium category, Station II of 27.56% is in the medium category, Station III of 39.97% is in the medium category. With an average live coral cover of 38.69%, it is in the medium category, referring to the Decree of the Minister of Environment No. 4 of 2001 concerning Standard Criteria for Coral Reef Damage. The percentage level of coral reef damage calculated using the Mortality Index is station I at 0.46, station II at 0.66, station III at 0.67. The average mortality index for coral reefs in South Leato waters is 0.59, falling into the high mortality index category.

Long-term legacy of phytoremediation on plant succession and soil microbial communities in petroleum-contaminated sub-Arctic soils

Abstract. Phytoremediation can be a cost-effective method of restoring contaminated soils using plants and associated microorganisms. Most studies follow the impacts of phytoremediation solely across the treatment period and have not explored long-term ecological effects. In 1995, a phytoremediation study was initiated near Fairbanks, Alaska, to determine how the introduction of annual grasses and/or fertilizer would influence degradation of petroleum hydrocarbons (PHCs). After 1 year, grass and/or fertilizer-treated soils showed greater decreases in PHC concentrations compared to untreated plots. The site was then left for 15 years with no active site management. In 2011, we re-examined the site to explore the legacy of phytoremediation on contaminant disappearance, as well as on plant and soil microbial ecology. We found that the recruited vegetation and the current bulk soil microbial community structure and functioning were all heavily influenced by initial phytoremediation treatment. The number of diesel-degrading microorganisms (DDMs) was positively correlated with the percentage cover of vegetation at the site, which was influenced by initial treatment. Even 15 years later, the initial use of fertilizer had significant effects on microbial biomass, community structure, and activity. We conclude that phytoremediation treatment has long-term, legacy effects on the plant community, which, in turn, impact microbial community structure and functioning. It is therefore important to consider phytoremediation strategies that not only influence site remediation rates in the short-term but also prime the site for the restoration of vegetation over the long-term.

Image analysis and LSTM methods for forecasting surficial displacements of a landslide triggered by snowfall and rainfall

AbstractLandslide-prone areas, predominantly located in mountainous regions with abundant rainfall, present unique challenges when subject to significant snowfall at high altitudes. Understanding the role of snow accumulation and melting, alongside rainfall and other environmental variables like temperature and humidity, is crucial for assessing landslide stability. To pursue this aim, the present study focuses first on the quantification of snow accumulated on a slope through a simple parameter obtained with image processing. Then, this parameter is included in a slope displacement prediction analysis carried out with long short-term memory (LSTM) neural network. By employing image processing algorithms and filtering out noise from white-shown rocks, the methodology evaluates the percentage of snow cover in RGB images. Subsequent LSTM forecasts of landslide displacement utilize 28-day historical data on rainfall, snow, and slope movements. The presented procedure is applied to the case of a deep-seated landslide in Italy, a site that in winter 2020–2021 experienced heavy snowfall, leading to significant snow accumulation on the slope. These episodes motivated a study aimed at forecasting the superficial displacements of this landslide, considering the presence of snow both at that time and in the following days, along with humidity and temperature. This approach indirectly incorporates snow accumulation and potential melting phenomena into the model. Although the subsequent winters were characterized by reduced snowfall, including this information in the LSTM model for the period characterized by snow on the slope demonstrated a dependency of the predictions on this parameter, thus suggesting that snow is indeed a significant factor in accelerating landslide movements. In this context, detecting snow and incorporating it into the predictive model emerges as a significant aspect for considering the effects of winter snowfall. The method aims to propose an innovative strategy that can be applied in the future to the study of the landslide analyzed in this paper during upcoming winters characterized by significant snowfall, as well as to other case studies of landslides at high altitudes that lack precise snow precipitation recording instruments.

A novel intrasaccular aneurysm device with high complete occlusion rate: initial results in a rabbit model

BackgroundIntrasaccular flow-disrupting devices are a safe and effective treatment strategy for intracranial aneurysms. We utilized high-frequency optical coherence tomography (HF-OCT) and digital subtraction angiography (DSA) to evaluate SEAL Arc, a...

Development and validation of coreLang: A threat modeling language for the ICT domain

ICT infrastructures are getting increasingly complex, and defending them against cyber attacks is cumbersome. As cyber threats continue to increase and expert resources are limited, organizations must find more efficient ways to evaluate their resilience and take proactive measures. Threat modeling is an excellent method of assessing the resilience of ICT systems, for example, by building Attack Graphs that illustrate an adversary’s attack vectors. Previously, the Meta Attack Language (MAL) was proposed, which serves as a framework to develop Domain Specific Languages (DSLs) and generate Attack Graphs for modeled infrastructures. coreLang is a MAL-based threat modeling language that utilizes Attack Graphs to enable attack simulations and security assessments. In this work, we present the first release version of coreLang in which MITRE ATT&CK tactics and techniques are mapped onto to serve as a validation and identify strengths and weaknesses to benefit the development cycle. Our validation showed that coreLang does cover 46% of all the techniques included in the matrix, while if we additionally exclude the tactics that are intrinsically not covered by coreLang and MAL, the coverage percentage increases to 64%.

Quantifying the main and interactive effects of the dominant factors on the diurnal cycles of land surface temperature in typical urban functional zones

The urban heat island (UHI) effect exists both during daytime and nighttime and varies with urban characteristics, such as 2D/3D urban morphology and socio-economics. However, there is a lack of quantitative understanding of the roles of these characteristics in influencing land surface temperature (LST) variations in different urban functional zones (UFZs) throughout the diurnal cycle. In this study, we examined the responses of diurnal LSTs in different UFZs to 2D/3D urban morphology and socio-economic variables. Results showed the following: (1) During daytime, the main drivers of LST varied with not only the UFZs but also the observation times; during nighttime, the LST variations across different UFZs were largely controlled by 3D urban morphology and socio-economic factors. (2) At 10:37, LST declined most rapidly when the percentage of tree cover (PER_Tree) exceeded a certain threshold. The threshold values of PER_Tree were 85%, 70%, 50%, and 60% for the residential, industrial, commercial, and public service zones, respectively. Irrespective of the UFZs, a nighttime cooling effect occurred only when sky view factor (SVF) exceeded 0.8. (3) For locations with high population density (Pop_Den) in the residential zone, whether urban trees induced a cooling effect depended on both the observation time and PER_Tree during daytime; however, a higher SVF tended to result in an increased LST during nighttime. In the public service zone, when Pop_Den exceeded 50, urban trees with high height contributed to nighttime LST cooling, whereas a warming effect occurred with trees with low height. The direct implications of this study suggest that 3D urban morphology and socio-economics are more efficient mitigation strategies for all UFZs at night, and the interactive effects between the dominant drivers of diurnal LSTs should be considered to cool the city most effectively.

Habitat characteristics shaping zoantharians’ distribution at intertidal habitats of the Canary Islands

Ocean warming is facilitating the proliferation of zoantharians worldwide due to their thermophilic affinities. However, other anthropogenic factors, such as declining water quality, have been appointed to favour the occurrence of zoantharians dominated areas and barrens. Subtropical and tropical intertidal habitats are especially vulnerable to zoantharians outbreaks due to the progressive increase in ocean temperature and because it is where most human pressure is concentrated. The aim of this study was to evaluate the abundance of intertidal zoantharians populations, related to habitat characteristics (rugosity and submerged substrate) and the presence of other benthic organisms, such as sessile invertebrates and macroalgae. Number and coverage of zoantharian colonies were recorded in transects (20 × 4 m) along 25 intertidal rocky platforms of the Canarian Archipelago, and photographic techniques in quadrats were used to examine the relationships between the percentage of substrate cover of zoantharians, macroalgae and sessile invertebrates by means of correlations analyses. Results indicated that high levels of rugosity favour the abundance and coverage of Palythoa aff. clavata and Zoanthus pulchellus, and the proportion of submerged substrate was also important in determining Zoanthus coverages. The presence of extensive macroalgae communities was seen to reduce zoantharian coverages, being the only sessile organisms that were able to outcompete them for space in the Canary Islands. Thus, this study provided valuable information about patterns of abundances and coverages of intertidal zoantharians useful for future monitoring of intertidal populations of zoantharians in Canary Islands and their interaction with surrounding marine organisms.

Nest-site selection of Eurasian Curlew (Numenius arquata) in the centre of its European range: adaptation to local macrohabitat factors

AbstractThe most important cause of the declining numbers of wading birds is a combination of habitat loss and degradation, as well as low productivity due to predation. Knowledge of the habitat requirements of this endangered group of species is critical for maintaining and restoring suitable breeding habitats. The aim of this paper is to characterize those habitat components of the Eurasian Curlew (Numenius arquata) which determine its choice of nesting site. This study was undertaken in three sites in Poland, the most important breeding areas of this species in this country. Our results showed that macrohabitat factors affect curlew nest-site selection in different ways. The most important ones were distance to a forest edge, the percentage cover of managed farmland in the vicinity and the number of farmland plots close to the nest. Other habitat components, such as distance to scattered trees, distance to roads and soil category, were of lesser importance and could be treated as localized. This study is a contribution to the knowledge of the Eurasian Curlew’s nest-site selection in farmland grasslands, which may have implications for its conservation.

Disentangling associations of human wellbeing with green infrastructure, degree of urbanity, and social factors around an Asian megacity

ContextOften called a ‘Garden city’, Bengaluru is renowned for its green infrastructure. However, the association of human wellbeing with the amount of tree cover (as an example of green infrastructure), degree of urbanization, and local people's socio-demographics has not been explored.ObjectiveWe investigated how human wellbeing is related to the amount of tree cover at household and neighborhood levels, the degree of urbanity, and underlying social factors among respondents.MethodsThe study was conducted in 61 towns along the rural–urban gradient of Bengaluru, surveying 836 respondents in total. Data on multiple dimensions of respondents’ wellbeing was collected between December 2016 and May 2017. The percentage of tree cover at the household and neighborhood levels was obtained based on WorldView-3 images. Logistic regression models were applied to assess correlations between human wellbeing and tree cover. Kruskal–Wallis tests, Mann–Whitney tests, and cross tabulation with chi-square tests were conducted to investigate relations of human wellbeing with the degree of urbanity, and with social factors.ResultsWe found that several variables of human wellbeing were positively associated with tree cover. Measures of wellbeing also differed along the rural–urban gradient and among social groups.ConclusionsThough urbanization is often considered to promote material wellbeing, non-material aspects (e.g., community activities and social relationships) are also important components of overall human wellbeing in urbanizing landscapes. Holistic interactions among natural, spatial, and social factors should be considered while designing interventions for equitable urban landscapes that promote human wellbeing and ecological restoration.

Pathological evaluation of predictors for delayed endothelial coverage after currently available drug-eluting stent implantation in coronary arteries: Impact of lesions with acute and chronic coronary syndromes

BackgroundThe optimal duration of dual antiplatelet therapy after currently available drug-eluting stent (DES) implantation to prevent stent thrombosis (ST) remains controversial. Delayed healing is frequently identified as a leading cause of ST in the early phase. However, a thorough pathological investigation into strut coverage after currently available DES implantation is lacking—a gap addressed in the current study. MethodsFrom our autopsy registry of 199 stented lesions, 4,713 struts from 66 currently available DES-stented lesions with an implant duration ≤370 days were histologically evaluated. Endothelial coverage was defined as the presence of luminal endothelial cells overlying struts and an underlying smooth muscle cell layer. The stented lesions were classified into acute coronary syndrome (ACS) (n = 40) and chronic coronary syndrome (CCS) (n = 26) groups and were compared. Endothelial coverage predictors were identified through logistic analysis. ResultsAlthough ACS and CCS lesions presented comparable clinical characteristics, including age, sex, and cause of death, the latter exhibited a significantly higher prevalence of chronic kidney disease and hemodialysis than the former (33.3% vs. 65.2%; p = 0.02, 7.7% vs. 30.4%; p = 0.02). The poststent implant median duration was significantly shorter in ACS lesions than in CCS lesions (13 [IQR 5–26 days] vs. 40 [IQR 16–233 days]; p < 0.01). The endothelial coverage percentage was 3.5% at 30 days and 27.7% at 90 days after currently available DES implantation. Multivariable logistic regression analysis implicated implant duration of ≤90 days [odds ratio (OR), 0.009; 95% confidence interval (CI), 0.006–0.012; p < 0.01], superficial calcification (OR, 0.11; 95% CI, 0.07–0.17; p < 0.01), ACS culprit site (OR, 0.29; 95% CI, 0.09–0.94; p = 0.039), and circumferentially durable polymer-coated DES (OR, 0.32; 95% CI, 0.24–0.41; p < 0.01) as delayed endothelial coverage predictors. ConclusionsEndothelial coverage was limited at 90 days after currently available DES implantation, and the ACS culprit site and circumferentially durable polymer-coated DES were identified as independent predictors of delayed endothelial coverage. Our findings suggest the importance of underlying plaque morphology and stent technology for vessel healing after such implantation.

Landscape structure influences the spatial distribution of urban bird attractiveness

ContextLandscape change affects biological diversity and the distribution of species traits related to spiritual, educational, and recreational benefits people derive from nature. These traits are associated with color, song and behavioral characteristics that influence people's perceptions of how attractive an assemblage is. However, the environmental variables that affect the spatial distribution of traits related to the attractiveness of biological diversity remain unexplored.ObjectivesWe tested how landscape structure influences patterns of perceived bird attractiveness (trait diversity associated with colorfulness, behavioral and song categories) across an urbanization gradient.MethodsWe used data from standardized surveys of birds and landscapes within 42 landscape units of 1km2 across the city of Brisbane in eastern Australia. We used structural equation modeling to test effects of landscape composition (built infrastructure, percentage of tree cover) and landscape configuration (fragmentation of tree cover) on mean bird community attractiveness. Relationships between individual traits and landscape structure were analyzed using multinomial logistic regression models.ResultsOur analysis across 82 bird species shows that the relative amount of built infrastructure in a landscape interacts with fragmentation to reduce the overall attractiveness of the landscape’s bird assemblage. However, built areas can exhibit high overall bird attractiveness where there is (1) reduced fragmentation and (2) increased diversity of vegetation structure that provides key habitats for many colorful species with a high diversity of calls. Relationships between bird attractiveness and landscape structure change when they are analyzed at the guild level (insectivores vs frugivores/nectarivores). In addition, body size moderates the effects of landscape structure on song complexity, personality, and color.ConclusionsSmall bodied, colorful and melodious species are negatively affected by built infrastructure and fragmentation. By learning how habitat loss and fragmentation affect the distribution of species-rich, attractive bird assemblages, our findings can inform how urban landscapes might be structured to increase people’s connection with nature.

Using sea lion-borne video to map diverse benthic habitats in southern Australia

Across the world’s oceans, our knowledge of the habitats on the seabed is limited. Increasingly, video/imagery data from remotely operated underwater vehicles (ROVs) and towed and drop cameras, deployed from vessels, are providing critical new information to map unexplored benthic (seabed) habitats. However, these vessel-based surveys involve considerable time and personnel, are costly, require favorable weather conditions, and are difficult to conduct in remote, offshore, and deep marine habitats, which makes mapping and surveying large areas of the benthos challenging. In this study, we present a novel and efficient method for mapping diverse benthic habitats on the continental shelf, using animal-borne video and movement data from a benthic predator, the Australian sea lion (Neophoca cinerea). Six benthic habitats (between 5-110m depth) were identified from data collected by eight Australian sea lions from two colonies in South Australia. These habitats were macroalgae reef, macroalgae meadow, bare sand, sponge/sand, invertebrate reef and invertebrate boulder habitats. Percent cover of benthic habitats differed on the foraging paths of sea lions from both colonies. The distributions of these benthic habitats were combined with oceanographic data to build Random Forest models for predicting benthic habitats on the continental shelf. Random forest models performed well (validated models had a &amp;gt;98% accuracy), predicting large areas of macroalgae reef, bare sand, sponge/sand and invertebrate reef habitats on the continental shelf in southern Australia. Modelling of benthic habitats from animal-borne video data provides an effective approach for mapping extensive areas of the continental shelf. These data provide valuable new information on the seabed and complement traditional methods of mapping and surveying benthic habitats. Better understanding and preserving these habitats is crucial, amid increasing human impacts on benthic environments around the world.

Effects of Seed Proportion on Forage Yield of Greenleaf Desmodium (&amp;lt;i&amp;gt;Desmodium intortum)&amp;lt;/i&amp;gt; and Guinea Grass (&amp;lt;i&amp;gt;Panicum maximum)&amp;lt;/i&amp;gt; Mixture at Adami Tulu Agricultural Research Center

Establishing of grass-legume pastures is one of the recognized strategies for enhancing both quantity and quality of feed resources. Therefore, determining the impact of seed proportion on the nutritional qualities and forage yield of combinations of guinea grass and green leaf desmodium is the goal of this study. A Randomized Complete Block Design (RCBD) with three replications was used to arrange five seed proportions of desmodium and guinea grass. Analysis of variance revealed that variations in treatments have significant differences (p&amp;lt;0.05) on panicum heights, desmodium tillers, and Desmodium height. In addition, the effects of years showed significant (p&amp;lt;0.05) effects on panicum tiller, desmodium height, and percentage of coverages. Interaction of treatments with years showed a significant effect on tiller per plant and plant heights while the other parameters weren’t influenced. The combined mean of dry matter and percentage of coverage have showed significant differences (p&amp;lt;0.05) between the treatments. This result reveals that the seed proportion have effect on the dry matter and percentage of plant coverages. The aggressivity index also has significant mean differences (P&amp;lt;0.05) between the treatments. Legumes with the lowest proportion (25%) performed less competently than those with the highest proportions (75%) and 50% D. intortum. The crowding coefficient of P. maximum and D. intortum mixed forage showed significance differences (P&amp;lt;0.05). However, the value of seed proportion on crowding coefficient of panicum maximum and desmodium intortium were more than one. The LER has significant differences (P&amp;lt;0.05) due to ratio of P.maximum and D.intortium mixture and its value at T2, T3, and T4 showed as to be (LER&amp;gt;1) that revealed the yield advantages. Cobined mean results showed that there is significance difference (P&amp;lt;0.05) of CP, Ash, ADF, NDF and ADL due to different seed proportion mixture. In addition the CP of panicum incurred from 8.24% to 18.55% by mixing different seed proportion of D.intortium. An integration of legume forage with grasses improves the feed quality and quantity. Thus, based on the dry matter, yield advantage and nutritive values the integration of 75% and 50% desmodium is recommended for use in the study areas and similar agro-ecologies.

Shrub encroachment of coastal ecosystems depends on dune elevation

Woody plant encroachment is influenced by interactions between the physical environment and vegetation, which create heterogenous microenvironments some of which favor shrub recruitment through mitigation of the abiotic environment. Encroachment of native shrub, Morella cerifera into grasslands on Hog Island, Virginia has been attributed to warmer winter temperature; however, recruitment of seedlings in grasslands may be impacted by multiple factors at the level of the microhabitat. Our study focuses on a critical gap in understanding factors specifically influencing M. cerifera seedling recruitment and survival. By experimentally planting M. cerifera seedlings at varying dune elevations and grass densities, we tested hypotheses that dune elevation influences the microclimate, soil characteristics and vegetation cover and that grass cover/density is related to shrub establishment. We tested these hypotheses through gathering data from temperature data loggers, conducting soil water content and chloride analyses, and determining percent cover of grasses relative to dune elevation. Results indicate that dune elevation was positively related to moderated temperatures with reduced temperature extremes and vegetation cover/composition that led to favorable locations for M. cerifera establishment and growth. Where dune elevation is > 2 m, we document an upper limit of grass cover on natural seedling establishment, suggesting a switch from facilitative to competitive effects with grass density. Overall, our work demonstrates interactions between dune elevation and medium grass density has a facilitative influence on M. cerifera establishment and can be used for future predictions of shrub growth with rising sea-levels.

Abundance, diversity and composition of understory plants along the altitudinal gradient and dominant overstory composition types in the temperate Himalayan region

IntroductionThe Indian Himalayan forests are remarkable landforms experiencing tremendous climatic variation, constituting complex and diversified ecosystems with prominent vegetation zones. Despite their global significance and substantial research efforts focused on plant diversity in the temperate Himalayan region, only a few studies have explicitly assessed the distribution patterns of understory vegetation in relation to forest compositional types along altitudinal gradients.MethodsTo cover a wide range of altitudes and diverse overstory compositions, stands were sampled across four altitudinal ranges from 1500 to 3500 meters above mean sea level with increments of 500 meters in elevation steps. The overstory compositions were classified on the basis of dominant tree species in each stand on the similar sites. Vegetation in the shrub and ground layers was surveyed by visually estimating the percentage coverage within circular plots.ResultsA total of 99 understory species including 37 species each in the shrub layer, 62 species in the herb layer vegetation were recorded. The abundance, species diversity and composition of understory vegetation differed significantly along the altitudinal gradient and dominant overstory composition types. Moreover, distinct understory vegetation communities were observed at lower elevations compared to higher elevations, with middle elevations exhibiting intermediate vegetation characteristics. The study also highlighted the importance of dominant overstory composition types in shaping the pattern of understory vegetation abundance, species diversity and composition in the temperate Himalayan region. The higher resource conditions associated with broadleaved stands supported higher understory species abundance at lower elevations, while the heterogeneous conditions induced by the mixedwood stands promoted higher understory species diversity.ConclusionThe hump shaped pattern along the altitudinal gradient appeared to be the most dominant pattern of plant abundance and species diversity and call for more conservation concern towards the middle elevation zones in the temperate Himalayan region. Furthermore, the management interventions should aim at maintaining diverse range of overstory composition types for conserving biodiversity and their ecological functions in the temperate Himalayan region.

Percentage of Live Coral Cover in The Regional Water Conservation Area of the Sawo – Lahewa Water Tourism Park, North Nias District

Coral reefs are vital ecosystems facing serious threats due to climate change and human activities. This research aims to evaluate the condition of live coral cover in the Sawo-Lahewa Aquatic Tourism Park (TWP) Regional Marine Conservation Area (KKPD), North Nias Regency, as an important step in conservation and sustainable management efforts. Data was collected at 8 research stations using the Underwater Photo Transect (UPT) method. The research results show that the condition of coral reefs in this area is in the damaged to moderate category, with the percentage of live coral cover ranging between 12.33-45.37% and an average of 26.65%. The highest percentage of coral cover was found on Sarangbaung Island (45.37%) in the medium category, followed by Makora Island (42.13%), Gita Island (35.35%), and Lafau Island (31.07%). Meanwhile, locations with the lowest cover in the damaged category include Gosobaohi_01 Island (18.25%), Gosobaohi_02 Island (15.60%), Sifahandro Sea Waters (13.13%), and Bengkuang Bay Waters (12.33%). This research also looks at the abundance of coral juveniles, coral fish, and megabenthos to provide a broad picture of the health of the coral reef ecosystem. The results of this research can become a scientific basis for developing more effective management strategies. Apart from that, it is also a form of supporting conservation efforts, helping restore damaged ecosystems, and increasing the resilience of coral reefs to future environmental threats.Keywords: Coral Reefs, Regional Marine Conservation Area, North Nias

Russian olive distribution and invasion dynamics along the Powder River, Montana and Wyoming, USA

The invasive shrub, Russian olive (Elaeagnus augustifolia), is widely established within riparian areas across North America and eastern Europe. Limited information on its distribution and invasion dynamics in northern regions has hampered understanding and management efforts. Given this lack of spatial and ecological information we worked with local stakeholders and developed two main objectives: (1) map the distribution of Russian olive along the Powder River (Montana and Wyoming, United States) as of 2020 with field data and remote sensing; and (2) relate that distribution to environmental variables to understand its habitat suitability and community/invasion dynamics. Field data showed Russian olive has reached near equal canopy cover (18.3%) to native Plains cottonwood (Populus deltoides; 19.1%) and has a broader distribution. At the watershed scale, we modeled Russian olive distribution using field surveys, ocular sampling of aerial imagery, and spectral variables from Sentinel-2 MultiSpectral Instrument using a random forest model (RMSE = 15.42, R2 = 0.64). A statistical model linking the resulting Russian olive percent cover detection map to environmental variables for the entire watershed indicated Russian olive cover increased with flow accumulation and decreased with elevation, and was associated with poorer soil types. We attribute the success of Russian olive to its broad habitat suitability combined with changing hydrologic conditions favoring it over natives. The maps of Russian olive cover along the Powder River and its main tributaries in northern Wyoming and southern Montana revealed regions of the watershed with high and low cover, which can guide landscape-scale management prioritization. This study provides a repeatable Russian olive detection method due to the use of Sentinel-2 imagery that is available worldwide and provides insight into Russian olive’s ecological relationships and success with relevance for management across areas with similar environmental conditions.

Abstract We072: Effects of electronic cigarettes on mouse cardiac lymphatic vessels after TAC surgery

Introduction: Heart failure is a public health concern worldwide. It is known that tobacco smoking is a risk factor of heart failure. Tobacco smoking also causes inflammation reaction and lymphatic dysfunction in the lung. However, the effects of electronic cigarettes (ECIG), as a new method of smoking, on the heart and cardiac lymphatic vessels (lymphatics) are not clear yet. The lymphatic vessels play an important role in maintaining cardiac function by modulating fluid homeostasis and transporting macromolecules. It has been reported that cardiac lymphatic vessel formation limits pressure overload-induced heart failure in C57Bl/6 but not in Balb/c mice. How cardiac lymphatics might contribute to the pathogenesis induced by ECIG is not known. Research Questions: The roles of cardiac lymphatic vessels in responses to ECIG exposure are not investigated. I hypothesize that the toxic effects of ECIG on the heart are partially caused by damaging the cardiac lymphatic vessels. Aim: To determine the effects of ECIG exposure on cardiac lymphatics after Transverse aortic constriction (TAC). Methods: I perform TAC surgery on mice as a heart hypertrophy and chronic heart failure model. Mice after TAC or Sham surgery are treated with different vaping components from ECIG: ECIG, propylene glycol and glycerin (PGVG) as vehicle, and air. After 4 weeks of treatment, hearts were harvested for histological analyses. The lymphatic vessel coverage percentage and morphology were examined by immunostaining. Results: Prior research suggested that genetic background in mice might affect the responses of cardiac lymphatic vessels to TAC-induced heart failure. I have established the TAC model using CD-1 mice. My results showed that CD-1 mice treated with PGVG after TAC do not show a significant difference in cardiac lymphatic vessel density compared to Sham group (p value=0.5951). ECIG treatment also did not affect the lymphatic density significantly compared to PGVG treated mice after sham operation (p value=0.8937). ECIG treated mice after TAC surgery showed a trend of increased lymphatic coverage and more mice are still being processed and will be presented at the conference. Conclusion: PGVG treated CD-1 mice do not show changes in lymphatic vessel density 4 weeks post TAC. Longer time points and more mouse numbers are needed to compare the effects of PGVG and ECIG after TAC induced hypertrophy and heart failure. This research is supported by California TRDRP grant.

Not population density, but city size and per capita income influence the urban forest carbon sequestration: A case of growing cities in Arkansas, USA

While urban trees provides significant ecosystem services, the impact of increasing urbanization and population on their carbon sequestration potential remains relatively underexplored in interior sprawling cities, highlighting a critical research gap amid growing urban environmental challenges. Although existing studies suggest a strongly correlation between urban forest cover and carbon sequestration, this study aims to investigate how the urban demography factors influence land cover and carbon sequestration across cities with low, medium, and high population densities. Using the i-Tree Canopy tool, we sampled 18,814 random points to estimate city land cover and carbon sequestration in Arkansas, interior state of the US. Results from the principal component analysis revealed that 74% of the variation in a city's land cover among population density classes is attributed to tree and soil cover percentages. The mean annual (1.40 ± 0.08 T ha-1) and total carbon sequestration rates (35.30 ± 5.57 T ha-1) were significantly higher in the areas with low population density due to a higher average tree cover percentage (46%). Carbon sequestration rate was negatively associated with land cover types such as impervious surfaces like buildings (r = -0.44), roads (r = -0.28), grass cover (r = -0.46), and impervious other (r = -0.53). The log-linear model with scaled variables suggested that factors such as city's size and tree cover has positive influence urban trees' annual and total carbon sequestration, while spatial distribution and per capita income negatively affect these ecosystem befits in growing cities, regardless of population density. Travel time within city may have negative impact, while decadal population change may positively impact on carbon sequestration alongside management effort. Valuing this potential urban forest carbon sequestration for emerging carbon market could provide monetary benefits to the urban communities, city managers, and policymakers, enabling the development of effective urban forest management strategies in the context of urban climate change.

Prediction of runoff characteristics in permeable pavements using experimental data and intelligent models.

Considering the growing use of permeable pavements, the prediction of runoff passing through this pavement model is of considerable importance. The prediction of rainfall-runoff relationships can be a challenge because of several factors including data uncertainty, non-linear relationships, and high temporal and spatial variability. To deal with these challenges, intelligent algorithms are often used to predict such complex phenomena. In this research, runoff control parameters were investigated in two types of permeable pavements (permeable interlocking concrete pavement (PICP) and high strength clogging resistant permeable pavement (CRP)) using support vector machine (SVM), support vector machine-bat (SVM-BA) and support vector machine-grasshopper (SVM-GOA). Variables used in the models included percentage of coverage by permeable pavement (A), rainfall intensity (I), slope (S), and pavement type coefficient (K) as input data, and runoff coefficient (C), time to runoff (Tr), and peak discharge (Qp) as output data. In this research, from the total of 108 data extracted from the experimental results, 86 data were used in the training period, and 22 data were used in the test period. The results of the test period show that the SVM-BA model has the best performance with values of MAE = 0.010 in predicting C, MAE = 1.330 min in predicting Tr, and MAE = 0.029 lit/min in predicting Qp. The SVM-GOA model is ranked second with values of MAE = 0.051 in predicting C, MAE = 3.285 min in predicting Tr, and MAE = 0.097 lit/min in predicting Qp. Also, the SVM model is ranked third with values of MAE = 0.063 in predicting C, MAE = 4.470 min in predicting Tr, and MAE = 0.121 lit/min in predicting Qp. In summary, the SVM-BA algorithm showed the best performance and the SVM algorithm showed the weakest performance in predicting runoff characteristics in permeable pavements.