@article {KNZ001934,
	title = {Hyperspectral analysis of leaf pigments and nutritional elements in tallgrass prairie vegetation},
	journal = {Frontiers in Plant Science},
	volume = {10},
	year = {2019},
	chapter = {142},
	abstract = {<p>Understanding the spatial distribution of forage quality is important to address critical research questions in grassland science. Due to its efficiency and accuracy, there has been a widespread interest in mapping the canopy vegetation characteristics using remote sensing methods. In this study, foliar chlorophylls, carotenoids, and nutritional elements across multiple tallgrass prairie functional groups were quantified at the leaf level using hyperspectral analysis in the region of 470\&ndash;800 nm, which was expected to be a precursor to further remote sensing of canopy vegetation quality. A method of spectral standardization was developed using a form of the normalized difference, which proved feasible to reduce the interference from background effects in the leaf reflectance measurements. Chlorophylls and carotenoids were retrieved through inverting the physical model PROSPECT 5. The foliar nutritional elements were modeled empirically. Partial least squares regression was used to build the linkages between the high-dimensional spectral predictor variables and the foliar biochemical contents. Results showed that the retrieval of leaf biochemistry through hyperspectral analysis can be accurate and robust across different tallgrass prairie functional groups. In addition, correlations were found between the leaf pigments and nutritional elements. Results provided insight into the use of pigment-related vegetation indices as the proxy of plant nutrition quality.</p>},
	keywords = {LTER-KNZ, Hyperspectral analysis, Leaf pigments, Nutritional elements, remote sensing, tallgrass prairie},
	doi = {10.3389/fpls.2019.00142},
	url = {https://www.frontiersin.org/articles/10.3389/fpls.2019.00142/full},
	author = {Ling, B.H. and Goodin, D.G. and Raynor, Edward J. and Anthony Joern}
}
@article {KNZ001806,
	title = {Complex variation in habitat selection strategies among individuals driven by extrinsic factors},
	journal = {Ecology and Evolution},
	volume = {7},
	year = {2017},
	pages = {1802-1822},
	abstract = {<p>Understanding behavioral strategies employed by animals to maximize fitness in the face of environmental heterogeneity, variability, and uncertainty is a central aim of animal ecology. Flexibility in behavior may be key to how animals respond to climate and environmental change. Using a mechanistic modeling framework for simultaneously quantifying the effects of habitat preference and intrinsic movement on space use at the landscape scale, we investigate how movement and habitat selection vary among individuals and years in response to forage quality\&ndash;quantity tradeoffs, environmental conditions, and variable annual climate. We evaluated the association of dynamic, biotic forage resources and static, abiotic landscape features with large grazer movement decisions in an experimental landscape, where forage resources vary in response to prescribed burning, grazing by a native herbivore, the plains bison (Bison bison bison), and a continental climate. Our goal was to determine how biotic and abiotic factors mediate bison movement decisions in a nutritionally heterogeneous grassland. We integrated spatially explicit relocations of GPS-collared bison and extensive vegetation surveys to relate movement paths to grassland attributes over a time period spanning a regionwide drought and average weather conditions. Movement decisions were affected by foliar crude content and low stature forage biomass across years with substantial interannual variation in the magnitude of selection for forage quality and quantity. These differences were associated with interannual differences in climate and growing conditions from the previous year. Our results provide experimental evidence for understanding how the forage quality\&ndash;quantity tradeoff and fine-scale topography drives fine-scale movement decisions under varying environmental conditions.</p>},
	keywords = {LTER-KNZ},
	doi = {10.1002/ece3.2764},
	url = {https://onlinelibrary.wiley.com/doi/full/10.1002/ece3.2764},
	author = {Raynor, Edward J. and Beyer, Hawthorne L. and J. M. Briggs and Anthony Joern}
}
