Increasing Vegetation Density Research Articles

IDENTIFIKASI PERUBAHAN KERAPATAN VEGETASI DI KAWASAN HUTAN DENGAN TUJUAN KHUSUS UNIVERSITAS LAMBUNG MANGKURAT

The Forest Area with a Special Purpose of Lambung Mangkurat University has an area of approximately 2000 Ha, divided into 2 areas, namely Bukit Babaris and Bukit Waringin. Identification of changes in land cover and vegetation density has never been carried out, especially in the Babaris mountain area (1,617 hectares). This study aims to compare the results of the accuracy of the Maximum Likelihood Classification (MLC) method with the Normalized Different Vegetation Index (NDVI) method in identifying vegetation density from 2018 to 2022. The results of the accuracy test for the vegetation density method using the confusion matrix show that the Overall Accuracy value of the MLC method is low lower, namely 92.5%, and the NDVI method 93.75%. It can be concluded that the NDVI method is more sensitive in detecting vegetation than the MLC method. Factors that affect the inaccuracy of the MLC method depend on the accuracy and the number of class class training samples taken. Based on the results of the interpretation of density changes from the two methods, from 2018 to 2022 the area of vegetation classes tends to increase and looks fluctuating. The area of change in vegetation density in the MLC method of the non-vegetation classification class is relatively stable at over 9 ha/year, although the classification class rarely dominates over the year. Changes in the density of non-vegetation class vegetation in the NDVI method tend to decrease significantly in 2020 and 2021. Based on the two most accurate methods obtained by the NDVI method, that there is an increase in vegetation density in the KHDTK ULM area of the Babaris hill.

Modeling of non-equilibrium suspended sediment transport process in open channel flows with vegetation

A mathematical model based on advection-diffusion theory is established to study the non-equilibrium sediment transport process in vegetated channels. The effects of vegetation on velocity distribution and sediment diffusion coefficients were considered, respectively. Validation against experimental data from flume studies confirms the model's ability to accurately predict the longitudinal sediment deposition rate and the vertical distribution of suspended sediment concentration (SSC). A comparative analysis of three sediment diffusion coefficient formulations indicates that the linear-exponential formula provides a more precise estimate of εsz, and the linear-exponential formula performs well in predicting the turbulent diffusion coefficients of both rigid and flexible vegetation when gently swaying. Moreover, the distance required for SSC to regain equilibrium is influenced by the submergence level of the vegetation canopy. At lower submergence levels, the canopy shear vortices significantly affect the vertical exchange of sediment, and the sediment diffusion coefficients exhibit pronounced stratification near the vegetation canopy. An increase in vegetation density at these lower submergence levels intensifies the shear vortices, thereby extending the distance needed for SSC to reach equilibrium. At higher submergence levels, the impact of canopy shear vortices is lessened, which reduces sediment diffusion coefficient stratification characteristics, and the flow is similar to rough boundary layer flow. An increase in vegetation density increases flow resistance, which shortens the distance required for SSC to attain equilibrium. However, further efforts are required to explore turbulent characteristics with highly flexible vegetation motion and the grain size distribution of non-uniform sediments in vegetated flows.

A multivariate approach to assessing landscape structure effects on wildlife crossing structure use

BackgroundComplexity in landscape structure is often assessed using individual metrics related to ecological processes. However, this rarely incorporates important relationships among metrics and may miss landscape structure effects. Multivariate statistics provide techniques for assessing overall landscape structure effects. We assessed how multivariate statistics could be used to connect landscape structure with an ecological process [bobcat (Lynx rufus) wildlife crossing structure (WCS) use]. We tested how landscape structure at WCS sites compared to the surrounding landscape and how structure affected detections at WCS sites. Our study was conducted in Cameron County, Texas, USA where WCSs are in various stages of construction and monitoring. We used a classified land use/land cover map and aerial LiDAR to calculate configuration and density metrics at WCS and random sites. We created indices for configuration and density using principal components analysis to assess landscape structure effects on camera trap detections at WCSs.ResultsLandscape structure at WCSs did not differ from random locations. Wildlife crossing structure use increased with greater woody cover and decreased with increasing vegetation density. Our indices allowed identification of differences in how configuration and density impacted WCS use. Ordination methods helped identify individual contributions of landscape metrics to the overall landscape structure effect.ConclusionsWildlife crossing structures are permanent fixtures on landscapes, so selecting appropriate locations using broad-scale landscape structure likely increases target species use. Using indices of landscape structure provides planners with a more holistic approach to WCS placement and provides a more comprehensive picture of landscape pattern and process relationships.

Identifying toxic elements in water, sediments, and roots of mangrove forest (Avicennia marina) in Chabahar Bay, Sea of Oman

Mangroves play a crucial role in filtering pollutants from water and sediments. However, excessive accumulation of potentially toxic elements (PTEs) has harmful effects on marine organisms. This article investigates the concentration and distribution of PTEs in water, sediment, and the roots of endangered mangrove species in Chabahar Bay, a subtropical coastal wetland. The relationship between PTE absorption and accumulation rates with flow rate, mangrove extent, and sedimentation was also explored. Water, sediments, and aerial roots samples were taken at four stations along the wetland from upstream fresh water toward outfall. According to the results, Cd had more distribution in sediment and water samples and plants did not play as adsorbent in the study area. The lowest and highest PTEs concentrations were detected in water and sediment media, respectively. The average concentrations of PTEs in the sediments in the Chabahar Bay were Fe > Cr > Zn > Ni > Cu > Pb > Co > As > Cd while in aerial roots of the mangroves were Fe > Zn > Ni > Cr > Cu > Co > As > Pb > Cd. Except Zn, As, and Cd, there was a good correlation between increasing PTEs content in the sediments with decreasing flow velocity and increasing vegetation density along stations 3 to 4. In addition, the amount of PTEs uptake by the mangroves was less than that of global wetlands. The results also demonstrated a greater uptake in aerial roots in saline water for Cr, Ni and Co. Since the absorption rate of PTEs by the aerial roots of pneumatophores is slower than that in sediments, elevated concentrations of PTEs in the sediment can disrupt the entire ecosystem, leading to a potential decline in biodiversity. These toxins can enter the food chain, affecting not only organisms directly interacting with the sediment but also higher trophic levels, such as fish and birds.

The Response of NDVI to Drought at Different Temporal Scales in the Yellow River Basin from 2003 to 2020

Ecological protection in the Yellow River Basin (YRB) is a major strategy for China’s sustainable development. Amid global warming, droughts have occurred more frequently, severely affecting vegetation growth. Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI) at different time scales from 2003 to 2020, this study employed the linear trend method and the Spearman correlation coefficient method to calculate the trends and correlation coefficients of NDVI and SPEI at different scales at the pixel scale and explored the spatial distribution pattern of the sensitivity of vegetation growth in the YRB to drought. The results show that: (1) NDVI and SPEI are positively correlated in 77% of the area, negatively correlated in 9%, and are positively correlated in the arid and semi-arid areas, while negatively correlated in the humid and subhumid areas. The significant negative correlation between NDVI and drought at high altitudes may be due to the fact that Gramineae vegetation is more sensitive to drought, with heat being more affected than water. (2) Urbanization has a relatively obvious impact on the distribution of drought. Extreme drought mainly occurs in the middle and upper reaches of the Wei River; severe drought mainly occurs in the central area of the Guanzhong Plain centered on Xi’an; the central area of the Loess Plateau; and the surrounding areas of the Zhengzhou-centered Central Plains City Group. (3) The NDVI showed an upward trend from 2003 to 2020, indicating an increase in vegetation density or an expansion of vegetation coverage. From the temporal trend, SPEI decreased at a rate of −0.17/decade, indicating that the entire watershed has a drought trend on an annual scale. (4) Spring NDVI is more sensitive to the water supply provided by SPEI-1, while the positive correlation between SPEI and NDVI begins to rise in June and reaches its peak in July, then starts to decline in August. In autumn and winter, NDVI is more sensitive to 3–6-month accumulated drought. (5) From the dynamic transmission laws of different levels of positive correlation, the positive impact of the 3-month accumulated drought on NDVI is most significant, and the influence of SPEI-1 on the negative correlation between SPEI and NDVI is most significant. This paper aims to clarify the sensitivity of vegetation to different time-scale droughts, provide a basis for alleviating drought in the YRB, and promote sustainable development of ecological environmental protection. The research findings enable us to gain a profound insight into the responsiveness of vegetation growth to drought in the context of global warming and offer a valuable theoretical foundation for devising pertinent measures to alleviate stress on vegetation growth in regions prone to frequent droughts.

Evaluating Vegetation Effects on Wave Attenuation and Dune Erosion during Hurricane

This study employs the XBeach surfbeat model (XBSB) to explore the effects of vegetation on wave attenuation and dune erosion in a case study of Mexico Beach during Hurricane Michael. The XBSB model was validated against laboratory experiments of wave-induced dune erosion and wave attenuation by vegetation. In the case study of vegetation on dunes in Mexico Beach during Hurricane Michael, different vegetation drag coefficients were evaluated to investigate the effects of vegetation on wave attenuation and dune erosion. LiDAR data of dune profiles before and after Hurricane Michael were used for model validation. The findings reveal that vegetation on dunes significantly affects wave attenuation and dune erosion. Under vegetated conditions, as the vegetation drag coefficient value increases, wave attenuation also increases, leading to a reduction of dune erosion. An increase in vegetation density enhances wave attenuation in the vegetated area, including reductions in significant wave height and flow velocity. However, the rate of change in attenuation decreases as the vegetation density increases. Through simulations under regular wave condition on Mexico Beach, an optimal vegetation density was identified as 800 units/m2. Beyond this density, additional vegetation does not substantially improve wave attenuation. Furthermore, the position of the dune crest elevation is related to the location where the alongshore flow velocity begins to decrease. The findings highlight the essential role of coastal vegetation in enhancing coastal resilience against hurricanes.

Flow resistance of emergent rigid vegetation in steady flow

Abstract Enhanced understanding of flow resistance in open channels with emergent vegetation is essential for flood management and river ecosystem restoration. The presence of vegetation can significantly alter bed resistance, leading to a challenge in accurately predicting flow discharge, water levels, sediment transport, and bed deformation. Previous studies on vegetated flows have focused on vegetation resistance, on which the impact of vegetation has been ignored or poorly estimated. This study proposes a new analytical model, built upon the momentum conservation law, to predict flow resistance to vegetated zones in a plain bed without bed forms, explicitly quantifying bed resistance and vegetation resistance in a corollary manner. The proposed model is benchmarked against five typical sets of laboratory experiments. It is demonstrated that the present model using a modified logarithmic velocity distribution performs best, whereas that assuming a uniform velocity profile considerably overestimates the vegetation resistance and neglects the effect of vegetation on bed resistance. The ratio of bed resistance to the total resistance is shown to range between 5% and 40%, and it decreases with increasing vegetation density and decreases with water depth. Therefore, bed resistance cannot be ignored when modelling shallow water flow with sparsely distributed vegetation. It is also revealed that vegetation arrangements significantly affect flow resistance, and therefore a model incorporating the effect of vegetation arrangement performs better. Overall, the present model facilitates a viable and promising tool for quantifying flow resistance in emergent vegetated channels.

Deformation of vegetated channel bed under ice-covered flow conditions

A common feature of cold regions is the presence of ice cover on water surface. In the presence of vegetation in the channel bed which is normally leafless in winter, interaction between river ice and vegetated channel bed becomes very complex. In the present study, the impacts of ice cover and submerged leafless vegetation on channel bed deformation and flow resistance have been investigated based on 144 experiments conducted in a large-scale outdoor flume. The independent variables associated with the maximum scour depth around vegetation elements have been assessed and equations have been developed. Results indicate that the most important variable affecting the maximum scour depth around vegetation under ice-covered flow conditions is the ratio of the ice cover roughness to the bed roughness (ni/nb). However, under open channel flow conditions, the flow Froude number is the most important variable influencing the maximum scour depth. The methods based on the law of the wall provide reliable Manning's coefficient for both smooth and rough ice covers in the presence of submerged vegetation in the channel bed. As the vegetation density increases, the size of scour holes becomes smaller. With the increase in vegetation density, the median grain size of the armour layer in scour holes decreases correspondingly. When vegetation elements are placed in a staggered configuration, the median grain size of the armour layer in scour holes is less than that of squared configuration of vegetation elements. Regardless of the roughness of ice cover on water surface and the grain size of sediment in the bed, the maximum depth of scour holes always occurs at the upstream front face of each vegetation element. Under the rough ice-covered flow condition, the maximum depth of scour holes is more than that under the smooth ice-covered and open flow conditions.

An analytical study for predicting incipient motion velocity of sediments in ecological open channel flows

Sediment movements on the riverbeds are crucial in fluvial processes. Therefore, studying incipient sediment motion is valuable for predicting changes in sediment behavior. In this study, the influence of aquatic vegetation is introduced into the momentum balance equation under the condition of a bare bed. The presented model for incipient sediment motion in open channels covered by vegetation is derived, in consideration of vegetation density and relative submergence. This study simplifies the model format. The model and its coefficients demonstrate good applicability to various working conditions without requiring numerous changes. The predicted velocity determined by the proposed model is validated against experimental data. Results show excellent agreement between the two in various scenarios, including combinations of rigid or flexible conditions and submerged or emergent states. Additionally, the velocity for incipient sediment motion is observed to decrease with increasing vegetation density. However, a further increase in vegetation density may amplify vegetation resistance, hindering incipient sediment motion. Meanwhile, sediment movement becomes challenging as water depth increases, assuming that flow discharge and vegetation conditions remain constant.

Enhancing nutrient absorption through the influence of mangrove ecosystem on flow rate and retention time in salt marshes

This study investigates the impact of pneumatophores (the aerial roots of Avicenna marina) on water flow rate, retention time, contact time, and consequently on nutrient absorption through the sediment in sub-tropical salt marshes. The goal is to realize how the density of mangroves in salt marshes influences the kinematic factors of streamflow at estuaries. To this end, a field experiment was carried out to assess nutrient and organic compound levels in the sediment and water samples, spanning six sampling stations along the Chabahar River discharging to the Chabahar Bay, Iran. Then, we delved into the influence of altering environmental parameters, such as density and geometry, on the kinematic features of the flow through statistical analysis and hydraulic modeling. The results showed that the aerial roots reduce the flow rate and increase both retention and contact times. The longest retention time was observed at station #5 due to increased vegetation density and decreased instream velocity. In addition, measurements of total organic matter, total organic carbon, and total nitrogen indicated that an extended contact time resulted in increased absorption flux to the stream by sediments. As a result, pneumatophores can serve as an effective sink for organic matter in ecotones in salt marshes.

Abstract PR-009: Associations between PM2.5, vegetation density and childhood brain tumors: a case-control registry-based study from Texas 1995-2011

Abstract Background: Air pollution has been reported to be associated with some childhood cancers, namely leukemias. Less is known about air pollution and childhood brain tumor risk. In adult cancers, increasing vegetation density, or greenness, has been inversely associated with cancer incidence and survival. The interplay between air pollution and greenness, which co-occur, in childhood cancer etiology is unclear. Therefore, we sought to estimate the association between prenatal and early life exposure to air pollution, greenness, and childhood cancer in Texas (1995-2011). Materials and Methods: We included 1,316 individuals with a childhood brain tumor diagnosed <17 years of age and 109,762 age- and sex-matched controls. We linked birth certificate residential address to census tract annual average particulate matter 2.5 µg/m³ (PM2.5) and Normalized Difference Vegetation Index (NDVI) to approximate prenatal and early life exposure to greenness and air pollution. We estimated odds ratios (OR) and 95% confidence intervals (95% CI) as the measure of association between PM2.5 and NDVI interquartile range (IQR) increases and brain tumors. Models were adjusted for birth year, sex, maternal race/ethnicity, and area-level socioeconomic status (Yost index). Results: The following brain tumor types were included: ependymoma (n=136), astrocytoma (n=619), medulloblastoma (n=187), PNET (n=57), ATRT (n=54), and other gliomas (n=263). Average birth year PM2.5 and NDVI exposure levels were similar in cases and controls, 11 µg/m³ and 0.4, respectively. Each IQR increase (2.6 µg/m³) in PM2.5 was associated with ependymoma (OR: 1.27, 95% CI: 1.01-1.60) when adjusting for control-derived quartiles of NDVI. Conversely, after adjusting for PM2.5 quartiles, each IQR increase in NDVI (0.13) was inversely associated with ependymoma in those diagnosed at 0-4 years of age (OR: 0.75, 95% CI: 0.56-0.97) and with medulloblastoma in those aged 0-16 years at diagnosis (OR: 0.75, 95% CI: 0.62-0.91). There was no evidence of statistical interaction between NDVI and PM2.5 (all Likelihood Ratio Test p-values>0.05) for any brain tumors. Conclusions: Increasing residential air pollution during prenatal and early life increased the risk of childhood ependymoma in Texas independent of greenness. Conversely, increasing greenness exposure in prenatal and early life decreased the risk of ependymoma and medulloblastoma independent of PM2.5. These findings highlight the complex relationship between air pollution and greenness in childhood cancer etiology. Citation Format: Lindsay Williams, David Haynes, Jeannette Sample, Laura McGuinn, Thanh Hoang, Philip Lupo, Michael Scheurer. Associations between PM2.5, vegetation density and childhood brain tumors: a case-control registry-based study from Texas 1995-2011 [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr PR-009.

EPID-29. ASSOCIATIONS BETWEEN PM2.5, VEGETATION DENSITY AND CHILDHOOD BRAIN TUMORS: A CASE-CONTROL REGISTRY-BASED STUDY FROM TEXAS 1995-2011

Abstract BACKGROUND Air pollution has been reported to be associated with childhood leukemia, and increasing vegetation density (greenness) has been inversely associated with adult cancer incidence. However, the interplay between air pollution and greenness in childhood brain tumor (CBT) etiology is unclear. We sought to estimate the association between prenatal exposure to air pollution, greenness, and CBTs in Texas (1995-2011). Materials and METHODS We included 1,316 individuals with a CBT diagnosed ≤ 16 years of age and 109,762 age- and sex-matched controls. We linked birth certificate residential address to census tract annual average particulate matter 2.5 µg/m³ (PM2.5) and Normalized Difference Vegetation Index (NDVI) to approximate prenatal exposure to air pollution and greenness. We estimated odds ratios (OR) and 95% confidence intervals (95% CI) between CBTs, PM2.5 and NDVI interquartile range (IQR) increases. Models were adjusted for birth year, sex, race/ethnicity, and area-level socioeconomic status. RESULTS Ependymoma (n=136), astrocytoma (n=619), medulloblastoma (n=187), PNET (n=57), ATRT (n=54), and other gliomas (n=263) were included. Average birth year PM2.5 and NDVI exposure levels were similar in cases and controls, 11 µg/m³ and 0.4, respectively. Each IQR increase (2.6µg/m³) in PM2.5 was associated with ependymoma (OR: 1.27, 95% CI: 1.01-1.60), adjusting for NDVI. After adjusting for PM2.5 quartiles, each IQR increase in NDVI (0.13) was inversely associated with ependymoma in those diagnosed at 0-4 years of age (OR: 0.75, 95% CI: 0.56-0.97) and medulloblastoma in those aged 0-16 years at diagnosis (OR: 0.75, 95% CI: 0.62-0.91). There was no evidence of statistical interaction for any CBT. CONCLUSIONS Increasing air pollution during the prenatal period increased risk of childhood ependymoma, independent of greenness. Conversely, increasing greenness prenatal exposure decreased the risk of ependymoma and medulloblastoma, independent of PM2.5. These findings highlight the complex relationship between air pollution and greenness in CBT etiology.

Monitoring the impacts of crop residue cover on agricultural productivity and soil chemical and physical characteristics

To the best of our knowledge, the impacts of crop residue cover (CRC) on agricultural productivity and soil fertility have not been studied by previous researchers. In this regard, this study aims to apply an integrated approach of remote sensing and geospatial analysis to detect CRC and monitor the effects of CRC on agricultural productivity, as well as soil chemical and physical characteristics. To achieve this, a series of Landsat images and 275 ground control points (GCPs) collected from the study areas for the years 2013, 2015, and 2021 were used. A convolutional neural network (CNN), a class of artificial neural network has commonly applied to analyze visual imagery, was employed in this study for CRC detection in two classes (Not-CRC and CRC) for the years 2013, 2015, and 2021. To assess the effects of CRC, the Normalized Difference Vegetation Index (NDVI) was applied to Landsat image series for the years 2015 (22 images), 2019 (20 images), and 2022 (23 images). Furthermore, this study evaluates the impacts of CRC on soil fertility based on collected field observation data. The results show a high performance (Accuracy of > 0.95) of the CNN for CRC detection and mapping. The findings also reveal positive effects of CRC on agricultural productivity, indicating an increase in vegetation density by about 0.1909 and 0.1377 for study areas 1 and 2, respectively, from 2015 to 2022. The results also indicate an increase in soil chemical and physical characteristics, including EC, PH, Na, Mg, HCO3, K, silt, sand, and clay from 2015 to 2022, based on physical examination. In general, the findings underscore that the value of an integrated approach of remote sensing and geospatial analysis for detecting CRC and monitoring its impacts on agricultural productivity and soil fertility. This research can offer valuable insight to researchers and decision-makers in the field of soil science, land management and agriculture.

Increased Riparian Vegetation Density and Its Effect on Flow Conditions

The physical and biological structure of riparian vegetation fundamentally influences floodplain roughness, and thus the flood velocity and flood levels of a river. The study aims to provide detailed spatial data on the vegetation density of a floodplain, and to model the effect of the actual vegetation and various scenarios on flow conditions. LiDAR data were applied to evaluate the density and roughness of the submerged understory vegetation over the densely vegetated floodplain of Lower Tisza, Hungary. Then, HEC–RAS 2D modelling was applied to analyse the effect of the actual vegetation on flow conditions. Further scenarios were also created to predict the effect of (i) invasive plant control, (ii) no maintenance, and (iii) riparian vegetation restoration (meadows). According to the results, since the 19th Century, the increased vegetation density is responsible for a 17-cm flood level increase, and if the vegetation grows even denser, a further 7 cm could be expected. As the vegetation density increases, the overbank flow velocity decreases, and the crevasses and flood conveyance zones gradually lose their function. Simultaneously, the flow velocity increases in the channel (from 1 m/s to 1.4 m/s), resulting in an incision. Applying LiDAR-based 2D flow modelling makes it possible to plan sustainable riparian vegetation maintenance (e.g., forestry, invasive species clearance) from both ecology and flood control perspectives.

Global Climate Impacts of Land‐Surface and Atmospheric Processes Over the Tibetan Plateau

AbstractThe Tibetan Plateau (TP) impacts local and remote atmospheric circulations, wherein it mechanically and thermally affects air masses or airflows. Moreover, the TP provides a key channel for substance transport between the troposphere and the stratosphere. This study reviews recent advances in research regarding land–atmosphere coupling processes over the TP. The TP experiences climate warming and wetting. Climate warming has caused glacier retreat, permafrost degradation, and a general increase in vegetation density, while climate wetting has led to a significant increase in the number of major lakes, primarily through increased precipitation. Local and regional climates are affected by interactions between the land and the atmosphere. Namely, the TP drives surface pollutants to the upper troposphere in an Asian summer monsoon (ASM) anticyclone circulation, before spreading to the lower stratosphere. Further, the thermal forcing of the TP plays an essential role in the ASM. TP forcing can modulate hemispheric‐scale atmospheric circulations across all seasons. The TP interacts with remote oceans through a forced atmospheric response and is substantially affected by the evolution of the Earth's climate via promoting Atlantic meridional overturning circulation and eliminating Pacific meridional overturning circulation. The extensive influence of the TP is facilitated by its coupling with the ASM in the summer; whereas its winter influence on climate mainly occurs through Rossby waves. The observed increasing trends of temperature and precipitation over the TP are projected to continue throughout the 21st century.

Quantifying the impacts of an invasive weed on habitat quality and prey availability for tiger snakes (Notechis scutatus) in urban wetlands

Invasive plants are a threat to natural ecosystems worldwide, with urban wetlands being some of the most susceptible and highly modified environments of all. The tiger snake (Notechis scutatus) is a top predator that persists in urban wetlands of south-western Australia, many of which have been degraded by introduced kikuyu grass (Cenchrus clandestinus). To evaluate the potential impact of kikuyu grass on habitat quality for tiger snakes we quantified the structural features of habitats within wetlands degraded by kikuyu grass and compared them to wetlands with native vegetation. We also examined tiger snake prey availability, assessed predation risk for juvenile snakes using clay models, and measured the thermal quality of the vegetation. Proliferation of kikuyu grass has reduced habitat structural heterogeneity by reducing available bare ground and increasing vegetation density. This homogenisation of habitat structure had little effect on the predation risk for juveniles or the thermal properties of tiger snake shelter sites; however, one key prey species, the motorbike frog, had significantly lower abundance in the most impacted habitat. Habitat types with more structural complexity also offered tiger snakes more stable thermal regimes and lower predation risk. These findings indicate that the current extent of kikuyu grass invasion offers overall similar habitat quality for tiger snakes to native vegetation and may contribute to their persistence in urban wetlands; however, both tiger snakes and their anuran prey may benefit from increased habitat structural complexity.

On the timing of megafaunal extinction and associated floristic consequences in Australia through the lens of functional palaeoecology

The timing and cause of megafaunal extinctions are an enduring focus of research interest and debate. Despite the developments in the analysis of coprophilous fungal spores (CFS), the proxy for reconstructing past megaherbivore changes, the environmental consequences of this fauna loss remain understudied. This is partly due to the general obscurity of such a signal in pollen records, as well as limitations in disentangling human and extinction ecological impact, and the lack of spatial information of megafauna changes in site-level sedimentary records. In Australia, the debate centres on the possibility that habitat loss through climate change, vegetation-fire change, human intervention, or a combination of these factors led to the extinction of some large animals during the Late Pleistocene. Pollen and plant isotope studies have also demonstrated that vegetation-fire responses following the Late Pleistocene megafaunal extinctions were characterized by increased vegetation density and fire activity due to reduced grazing/browsing pressure. Here, we use a well-dated marine sedimentary core record from the Murray Darling Basin in southern Australia and apply palynological and functional palaeoecological approaches to reconstruct the Late Pleistocene megafaunal abundance changes, the timing and potential cause of extinction across the basin and investigate if extinction was associated with any signal of trait-based vegetation changes. We infer megafaunal abundance changes from the abundance of CFS and compare this with climatic proxies from the same core. We then link modern observations of fruit, seed and fire response traits of plant genera within the basin to the fossil pollen record to reconstruct palaeo vegetation community traits and determine if extinction was associated with any changes in plant community trait composition. Closely-spaced 14C dates obtained from planktonic foraminifera and δ18O tie points place a major decline in CFS, and thus the timing of extinction, within the basin at ∼43.3 ka. While climate-driven environmental changes largely controlled megafaunal presence, human arrival and frequent landscape burning are considered the most likely primary cause of extinction or, at the very least, megafauna decline in the Murray Darling Basin. We also found that the proposed period of megafaunal decline was also accompanied and followed by a decline in the prevalence of plants with larger seeds and fruits that were likely to have been once dispersed by megaherbivores. Our study supports the idea of a human-driven megafaunal extinction in mainland Australia and that the extinction caused changes in vegetation due to reduced plant dispersal and herbivory. However, high fire activity primarily linked to these vegetation changes was not observed, as humans were already practicing landscape burning before the period of megafaunal extinction and likely continued to do so afterward.

Investigation approaching flow to bridge and prediction of bridge pier scour with floodplain vegetation in compound channels under pressurized flow conditions

The local scouring around the pier, is one of major cause of the bridges failure worldwide. Compared to the flow hydraulics in single channels, the flow pattern in compound channels is completely different with flood plains covered with vegetation and this issue can affect the amount of scouring in the area of bridge piers. However, the combined effect of these factors has not been systematically investigated. Therefore, due to the complex nature of the local scouring phenomenon and the absence one of an accurate prediction model, in this research, an experimental study on the hydraulic characteristics of the flow approaching the bridge deck in compound channels with floodplain vegetation in pressurized flow conditions, has been done. It was found that increasing vegetation density on average will reduce scour depth by 15% for the same floodplain width and relative depth. In free-flow conditions, increasing the vegetation density on average will increase the scour depth. The aim is to develop an optimized model to estimate the bridge pier scour in consideration of the combined effect. The newly developed relationship shows a good correlation coefficient of more than 92% with the experimental data and yielded better results than the previous equations. The finding of this study will have potential applications for the prediction of the bridge pier scour in clear water conditions.

PREDIKSI EROSI DAN PERENCANAAN KONSERVASI TANAH DAN AIR DI DAERAH ALIRAN SUNGAI PAKERISAN PROVINSI BALI

Pakerisan watershed is one of the watershed that has not followed the rules of soil and water conservation. This can destroy soil aggregates and cause high erosion. This study aims to predict the level of erosion and to plan soil and water conservation. Erosion prediction uses the USLE (Universal Soil Loss Equation). The prediction erosion showed that erosion is classified from slight to severe. The erosion rate is very light covering an area of 6,426.26 ha (71.28%) with natural forests, dryland agriculture, and paddy fields. The moderate erosion rate is 583.83 ha (6.48 %) on dryland and paddy fields farming. The severe erosion rate is 1,087.99 ha (12.07%) on land use in the form of dryland agriculture. The very severe erosion covering an area of 916.85 (10.17%) with the use of dryland agriculture. Conservation planning can be carried out by increasing vegetation density, adding mulch and conservation measures of making terraces with good construction.
 Keywords: Soil; Prediction Erosion; Conservation; Watershed

Assessing the Contributions of Urban Green Space Indices and Spatial Structure in Mitigating Urban Thermal Environment

Urban green space takes a dominant role in alleviating the urban heat island (UHI) effect. Most investigations into the effects of cooling factors from urban green spaces on the UHI have evaluated the correlation between each factor and land surface temperature (LST) separately, and the contribution weights of various typical cooling factors in mitigating the thermal environment have rarely been analyzed. For this research, three periods of Landsat 8 data captured between 2014 and 2018 of Xuzhou during the summer and autumn seasons were selected along with corresponding meteorological and flux measurements. The mono-window method was employed to retrieve LST. Based on the characteristics of the vegetation and spatial features of the green space, eight factors related to green space were selected and computed, consisting of three indices that measure vegetation and five metrics that evaluate landscape patterns: vegetation density (VD), evapotranspiration (ET), green space shading degree (GSSD), patch area ratio (PLAND), largest patch index (LPI), patch natural connectivity (COHESION), patch aggregation (AI), and patch mean shape index distribution (SHPAE_MN). Linear regression and bivariate spatial autocorrelation analyses between each green space factor and LST showed that there were significant negative linear and spatial correlations between all factors and LST, which proved that the eight factors were all cooling factors. In addition, LST was strongly correlated with all factors (|r| > 0.5) except for SHPAE_MN, which was moderately correlated (0.3 < |r| < 0.5). Based on this, two principal components were extracted by applying principal component analysis with all standardized green space factors as the original variables. To determine the contribution weight of each green space factor in mitigating the urban heat island (UHI) effect, we multiplied the influence coefficient matrix of the initial variables with the standardized multiple linear regression coefficients between the two principal component variables and LST. The final results indicated that the vegetation indices of green space contribute more to the alleviation of the UHI than its landscape pattern metrics, and the contribution weights are ranked as VD ≥ ET > GSSD > PLAND ≈ LPI > COHESION > AI > SHAPE_MN. Our study suggests that increasing vegetation density is preferred in urban planning to mitigate urban thermal environment, and increasing broadleaf forests with high evapotranspiration and shade levels in urban greening is also an effective way to reduce ambient temperature. For urban green space planning, a priority is to multiply the regional green space proportion or the area of largest patches. Second, improving the connectivity or aggregation among patches of green space can enhance their ability to cool the surrounding environment. Altering the green space spatial shape is likely the least significant factor to consider.