Vegetation Landscape,Ecological Characteristics and Soil Fixation for Riverbank in Taiwan,China

This study is aimed to investigate and analyze the vegetation landscape around Rivers of Hou-lung, Fa-tz, Da-li, Ching-shuei and Gau- ping, and to select the suitable plant species that could be applied for the area of riverbank ecological engineering in Taiwan. Studying the vegetation established the key point and procedure of ecological engineering in the riverside and revetment, to compile and edit the dominant plants＇ types, life form, propagating method, root systems＇ characteristics and functions for soil conservation. This research choses three dominant plants for roots strength test. The fitting models of plants pulling resistance（Rp, kg） between plant height （H, cm）, diameter near ground （Dn, mm）, diameter above ground 100 mm （Da, mm）, The research finished the relative abundant, types and cluster analysis of riverbank dominant plants that generalize vegetative distribution and ecological restoration for different river types to apply and manage in Taiwan.

i-Tree Eco Analysis of Landscape Vegetation on Remediated Areas of Oak Ridge National Laboratory

The Oak Ridge National Laboratory (ORNL) is the largest and most diverse energy, research, and development institution within the Department of Energy (DOE) system in the United States. As such, the site endures constant land development that creates rigorous growing conditions for urban vegetation. Natural resource managers at ORNL recognize that trees are an integral component of the landscape and are interested in characterizing the urban forest and their associated ecosystem services benefits. We evaluated the urban forest structure, quantified ecosystem services and benefits, and estimated economic value of resources using i-Tree Eco at ORNL. While this assessment captured over 1100 landscape trees, the ORNL Natural Resources Management for landscape vegetation can be expanded to include unmanaged landscapes, e.g. riparian areas, greenspace, and other vegetative attributes to increase ecosystem services benefits. Assigning a monetary value to urban forest benefits help to inform decisions about urban forest management, ideally on cost-benefit analysis.

Phenological basis of determining tourism seasons for ornamental plants in central and eastern China

Many plants have high ornamental value during specific phenophases, and plant phenology correlates highly with seasonal vegetation landscape. Determination of the span and spatiotemporal patterns of the tourism season for ornamental plants could provide tourism administrators and the tourists themselves with a theoretical basis for making travel arrangements. Based on data derived from on-the-ground observations of three phenophases, specifically first leafing date, full flowering date, and end of leaf coloring date, and corre- sponding meteorological data at 12 sites in China, we divided the tourism season into its starting date, peak （best date） and end date for ornamental plants by computing frequency distributions of these phenophases. We also determined how the peak of this tourism season changed during the course of the past 50 years. We found that： （1） The peak of the tourism season ranged from March 16 （in Guilin） to May 5 （in Harbin） for first leafing, from April 3 （in Kunming） to May 24 （in Mudanjiang） for full flowering, and from October 1 （in Mudanjiang） to November 30 （in Shanghai） for leaf coloring. As might be expected, the peaks of both the first leafing and full flowering tourism seasons were positively associated with latitude, while for leaf coloring it was negatively correlated with latitude. （2） The ideal tourism season for first leafing and full flowering advanced by more than 0.16 days/year over the past 50 years in Beijing and Xi＇an, while the peak of the tourism season for leaf coloring became significantly delayed （by 0.16 days/year in Beijing and 0.21 days/year in Xi＇an）. （3） The tourism season was significantly associated with temperature across related phenological observation sites. The ideal time for first leafing and full flowering was determined to have advanced, respectively, by 4.02 days and 4.04 days per 1℃ increase in the spring （March-May） temperature. From September to November, the best time for leaf coloring correlated significantly and positively with average temperature, and the spatial sensitivity was 2.98 days/℃.

Prediction of bedload transport inside vegetation canopies with natural morphology

Due to vegetation drag and vegetation-generated turbulence,bedload transport in vegetated channels is more complicated than that in nonvegetated channels.It is challenging to obtain accurate predictions of bedload transport in vegetated channels.Previous studies generally used rigid circular cylinders to simulate vegetation,and the impact of plant morphology on bedload transport was typically ignored;these methods deviate from natural scenarios,resulting in prediction errors in transport rates of more than an order of magnitude.This study measured bedload transport rates inside P.australis,A.calamus and T.latifolia canopies and in arrays of rigid cylinders for comparison.The impact of plant morphology on bedload transport in vegetated channels was examined.Inside the canopies of natural morphology,the primary factor driving bedload transport is the near-bed turbulent kinetic energy(TKE),which consists of both bed-generated and vegetation-generated turbulence.A method was proposed to predict the near-bed TKE inside canopies with natural morphology.For the same solid volume fraction of plants,the transport rate inside canopies with a natural morphology is greater than or equal to that within an array of rigid cylinders,depending on the plant shape.This finding indicates that plant morphology has a significant impact on transport rates in vegetated regions and cannot be ignored,which is typical in practice.Four classic bedload transport equations(the Meyer-Peter-Müller,Einstein,Engelund and Dou equations),which are suitable for bare channels(no vegetation),were modified in terms of the near-bed TKE.The predicted near-bed TKE was inserted into these four equations to predict the transport rate in canopies with natural morphology.A comparison of the predictions indicated that the Meyer-Peter-Müller equation had the highest accuracy in predicting the transport rate in vegetated landscapes.