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Articles 1 - 4 of 4
Full-Text Articles in Life Sciences
Short-Term Regeneration Dynamics Of Wyoming Big Sagebrush At Two Sites In Northern Utah, Sara J. Germain, Rebecca K. Mann, Thomas A. Monaco, Kari E. Veblen
Short-Term Regeneration Dynamics Of Wyoming Big Sagebrush At Two Sites In Northern Utah, Sara J. Germain, Rebecca K. Mann, Thomas A. Monaco, Kari E. Veblen
Wildland Resources Faculty Publications
Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) is a widespread shrub across the western United States, and there is great interest among scientists and land managers in its ecology and conservation, particularly with regard to maintaining structural heterogeneity of sagebrush stands for wildlife habitat and livestock forage. Yet little is known about its short-term regeneration dynamics and the implications of those dynamics for changes in stand structure. We examined changes among sagebrush size classes across 3 years, as well as emergence of sagebrush from seed bank and seed rain samples at 2 sagebrush shrub land sites in northern …
Herbivory And Drought Generate Short‐Term Stochasticity And Long‐Term Stability In A Savanna Understory Community, Corinna Riginos, Lauren M. Porensky, Kari E. Veblen, Truman P. Young
Herbivory And Drought Generate Short‐Term Stochasticity And Long‐Term Stability In A Savanna Understory Community, Corinna Riginos, Lauren M. Porensky, Kari E. Veblen, Truman P. Young
Wildland Resources Faculty Publications
Rainfall and herbivory are fundamental drivers of grassland plant dynamics, yet few studies have examined long‐term interactions between these factors in an experimental setting. Understanding such interactions is important, as rainfall is becoming increasingly erratic and native wild herbivores are being replaced by livestock. Livestock grazing and episodic low rainfall are thought to interact, leading to greater community change than either factor alone. We examined patterns of change and stability in herbaceous community composition through four dry periods, or droughts, over 15 years of the Kenya Long‐term Exclosure Experiment (KLEE), which consists of six different combinations of cattle, native wild …
Is Doping Of Cognitive Performance An Anti‐Herbivore Adaptation? Alkaloids Inhibiting Acetylcholinesterase As A Case, Maciej J. Ejsmond, Frederick D. Provenza
Is Doping Of Cognitive Performance An Anti‐Herbivore Adaptation? Alkaloids Inhibiting Acetylcholinesterase As A Case, Maciej J. Ejsmond, Frederick D. Provenza
Wildland Resources Faculty Publications
Historically, people who study interactions between plants and herbivores focused on the ecological costs and benefits of synthesizing secondary metabolites. These compounds have diverse functions including defenses against herbivores. Some plants produce alkaloids that act as acetylcholinesterase inhibitors, increasing both the level and duration of action of the neurotransmitter acetylcholine with potential toxic effects in insects and mammals. Yet, among a number of neuroactive plant chemicals, alkaloids that inhibit acetylcholinesterase (AIA) display nootropic activities, that is, positively affect cognition, learning, and memory in mammals. This creates a paradox: Neuroactive AIA, expected to punish herbivores, enhance cognition, learning, and memory. A …
Plant Identity And Shallow Soil Moisture Are Primary Drivers Of Stomatal Conductance In The Savannas Of Kruger National Park, Rebecca L. Tobin, Andrew Kulmatiski
Plant Identity And Shallow Soil Moisture Are Primary Drivers Of Stomatal Conductance In The Savannas Of Kruger National Park, Rebecca L. Tobin, Andrew Kulmatiski
Wildland Resources Faculty Publications
Our goal was to describe stomatal conductance (gs) and the site-scale environmental parameters that best predict gs in Kruger National Park (KNP), South Africa. Dominant grass and woody species were measured over two growing seasons in each of four study sites that represented the natural factorial combination of mean annual precipitation [wet (750 mm) or dry (450 mm)] and soil type (clay or sand) found in KNP. A machine-learning (random forest) model was used to describe gs as a function of plant type (species or functional group) and site-level environmental parameters (CO2, season, shortwave radiation, soil type, soil moisture, time …