Genetic, morphological, and spectral characterization of relictual Niobrara River hybrid aspens (Populus × smithii).

PREMISE OF THE STUDY: Aspen groves along the Niobrara River in Nebraska have long been a biogeographic curiosity due to morphological differences from nearby remnant Populus tremuloides populations. Pleistocene hybridization between P. tremuloides and P. grandidentata has been proposed, but the nearest P. grandidentata populations are currently several hundred kilometers east. We tested the hybrid-origin hypothesis using genetic data and characterized putative hybrids phenotypically. METHODS: We compared nuclear microsatellite loci and chloroplast sequences of Niobrara River aspens to their putative parental species. Parental species and putative hybrids were also grown in a common garden for phenotypic comparison. On the common garden plants, we measured leaf morphological traits and leaf-level spectral reflectance profiles, from which chemical traits were derived. KEY RESULTS: The genetic composition of the three unique Niobrara aspen genotypes is consistent with the hybridization hypothesis and with maternal chloroplast inheritance from P. grandidentata. Leaf margin dentition and abaxial pubescence differentiated taxa, with the hybrids showing intermediate values. Spectral profiles allowed statistical separation of taxa in short-wave infrared wavelengths, with hybrids showing intermediate values, indicating that traits associated with internal structure of leaves and water absorption may vary among taxa. However, reflectance values in the visible region did not differentiate taxa, indicating that traits related to pigments are not differentiated. CONCLUSIONS: Both genetic and phenotypic results support the hypothesis of a hybrid origin for these genetically unique aspens. However, low genetic diversity and ongoing ecological and climatic threats to the hybrid taxon present a challenge for conservation of these relictual boreal communities.

Spectral differentiation of oak wilt from foliar fungal disease and drought is correlated with physiological changes.

Hyperspectral reflectance tools have been used to detect multiple pathogens in agricultural settings and single sources of infection or broad declines in forest stands. However, differentiation of any one disease from other sources of tree stress is integral for stand and landscape-level applications in mixed species systems. We tested the ability of spectral models to differentiate oak wilt, a fatal disease in oaks caused by Bretziella fagacearum ``Bretz'', from among other mechanisms of decline. We subjected greenhouse-grown oak seedlings (Quercus ellipsoidalis ``E.J. Hill'' and Quercus macrocarpa ``Michx.'') to chronic drought or inoculation with the oak wilt fungus or bur oak blight fungus (Tubakia iowensis ``T.C. Harr. & D. McNew''). We measured leaf and canopy spectroscopic reflectance (400-2400 nm) and instantaneous photosynthetic and stomatal conductance rates, then used partial least-squares discriminant analysis to predict treatment from hyperspectral data. We detected oak wilt before symptom appearance, and classified the disease with high accuracy in symptomatic leaves. Classification accuracy from spectra increased with declines in photosynthetic function in oak wilt-inoculated plants. Wavelengths diagnostic of oak wilt were only found in non-visible spectral regions and are associated with water status, non-structural carbohydrates and photosynthetic mechanisms. We show that hyperspectral models can differentiate oak wilt from other causes of tree decline and that detection is correlated with biological mechanisms of oak wilt infection and disease progression. We also show that within the canopy, symptom heterogeneity can reduce detection, but that symptomatic leaves and tree canopies are suitable for highly accurate diagnosis. Remote application of hyperspectral tools can be used for specific detection of disease across a multi-species forest stand exhibiting multiple stress symptoms.