Results 171 to 180 of about 69,262 (347)
Detecting extirpation: A localized approach to a global problem
The global biodiversity crisis stems from a cascading series of extirpations driving species toward extinction. Addressing this crisis requires methods for early detection of extinction at local scales, where communities can mobilize conservation efforts.
Andrew D. F. Simon +4 more
wiley +1 more source
A Simple Phenology-Based Vegetation Index for Mapping Invasive Spartina Alterniflora Using Google Earth Engine [PDF]
Ronglong Xu, Siqing Zhao, Yinghai Ke
openalex +1 more source
Made in the shade: Leaf responses of native wildflowers to single‐axis photovoltaic solar energy
As solar energy expands globally, balancing renewable power generation with biodiversity and ecosystem health has become an urgent challenge. This study investigated how native wildflowers respond at leaf level to the unique microclimates created by rotating solar panels in California's Central Valley.
Yudi Li +3 more
wiley +1 more source
Animating blossom: Time‐lapse to encourage plant awareness in the YouTube era
Time‐lapse videos can effectively capture key traits of flower blossoms, such as color, 3D structure, and temporal changes, making them valuable complements to herbarium specimens and other botanical collections. Despite the abundance of such videos on YouTube, most provide no ecological and botanical insights.
Tae Kyung Yoon
wiley +1 more source
Biodiversity is threatened by human activities, with extinction debt accumulating rapidly. Many of these activities change the connectivity of populations, fragmenting existing population systems or bringing previously isolated populations or species into contact.
Zhiqin Long +7 more
wiley +1 more source
Understanding and protecting plant life is essential for tackling the twin challenges of biodiversity loss and climate change. To support this, we have developed a new digital approach that helps identify plant species more quickly and accurately.
Jed Arno +10 more
wiley +1 more source
DATimeS: A machine learning time series GUI toolbox for gap-filling and vegetation phenology trends detection. [PDF]
Belda S +6 more
europepmc +1 more source
An Earlier Spring Phenology Reduces Vegetation Growth Rate during the Green-Up Period in Temperate Forests [PDF]
Boheng Wang +7 more
openalex +1 more source

