Results 181 to 190 of about 31,599 (314)

Camera trap survey of mammal diversity and activity rhythms of threatened species in a subtropical forest of Huangshan Mountain, China. [PDF]

open access: yesBiodivers Data J
Zhao W   +11 more
europepmc   +1 more source

Effects of enemy exclusion on biodiversity-productivity relationships in a subtropical forest experiment. [PDF]

open access: yesJ Ecol, 2022
Huang Y   +8 more
europepmc   +1 more source

17‐epi‐Melianodiol, a new protolimonoid from Melia azedarach fruits, exhibits larvicidal activity and is associated with oxidative imbalance and midgut epithelial damage in Aedes aegypti larvae

open access: yesPest Management Science, EarlyView.
The bio‐guided phytochemical study resulted in the new compound 17‐epi‐melianodiol. The compound eliminated 100% of Aedes aegypti larvae at 100 ppm, causing pronounced morphological changes, cuticular damage, and extensive vacuolization. Abstract BACKGROUND In Brazil, Aedes aegypti is the primary vector of arboviruses such as dengue, chikungunya ...
Kethleen Duarte Crespo Soares   +8 more
wiley   +1 more source

Compartment and Plant Identity Shape Tree Mycobiome in a Subtropical Forest. [PDF]

open access: yesMicrobiol Spectr, 2022
Yang H   +7 more
europepmc   +1 more source

Seasonal Variation in Carbon Dynamics in the Lower Tocantins River: Influence of Discharge and Environmental Drivers

open access: yesRiver Research and Applications, EarlyView.
ABSTRACT Tropical rivers play a key role in regional carbon budgets, yet greenhouse gas (GHG) dynamics in regulated systems remain poorly understood. This study investigates the seasonal variability of carbon dioxide (CO2) and methane (CH4) concentrations, isotopic composition (δ13C), and river‐atmosphere fluxes in the lower Tocantins River, a ...
Maria Gabriella da S. Araújo   +5 more
wiley   +1 more source

Using Deep Learning AI to Detect Riparian Vegetation Recovery Following a Major Flood in the Brisbane River

open access: yesRiver Research and Applications, EarlyView.
ABSTRACT Post‐flood riparian vegetation recovery demands significant attention; however, the complexity of traditional remote sensing methods often hinders environmental managers from implementing rapid vegetation monitoring. This paper developed a model using a Deep Learning Model within ArcGIS to classify and detect recovery of vegetation with high ...
Sydney O'Hare, Jinghan Li, Yongping Wei
wiley   +1 more source

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