Nutrient Cycling in Forage Production Systems

In most forage production systems, the nutrients needed for plant growth are provided by microbially mediated breakdown and release of plant-available mineral nutrients from dead plant tissues, livestock excreta, soil organic matter, and geochemically bound mineral forms. Even in fertilized forage systems, determining appropriate fertilizer application rates requires a systems approach on the part of the manager (e.g., Di and Cameron, 2000; Rotz et al., 2002). Fertilizer additions are simply one input in the system of inputs, outputs, pools, and fluxes that characterize nutrient cycling in a particular ecosystem

Smoothed Analysis of Tensor Decompositions

Low rank tensor decompositions are a powerful tool for learning generative models, and uniqueness results give them a significant advantage over matrix decomposition methods. However, tensors pose significant algorithmic challenges and tensors analogs of much of the matrix algebra toolkit are unlikely to exist because of hardness results. Efficient decomposition in the overcomplete case (where rank exceeds dimension) is particularly challenging. We introduce a smoothed analysis model for studying these questions and develop an efficient algorithm for tensor decomposition in the highly overcomplete case (rank polynomial in the dimension). In this setting, we show that our algorithm is robust to inverse polynomial error -- a crucial property for applications in learning since we are only allowed a polynomial number of samples. While algorithms are known for exact tensor decomposition in some overcomplete settings, our main contribution is in analyzing their stability in the framework of smoothed analysis. Our main technical contribution is to show that tensor products of perturbed vectors are linearly independent in a robust sense (i.e. the associated matrix has singular values that are at least an inverse polynomial). This key result paves the way for applying tensor methods to learning problems in the smoothed setting. In particular, we use it to obtain results for learning multi-view models and mixtures of axis-aligned Gaussians where there are many more "components" than dimensions. The assumption here is that the model is not adversarially chosen, formalized by a perturbation of model parameters. We believe this an appealing way to analyze realistic instances of learning problems, since this framework allows us to overcome many of the usual limitations of using tensor methods.Comment: 32 pages (including appendix

Ponderosa Pine Regeneration,Wildland Fuels Management, and Habitat Conservation: Identifying Trade-Offs Following Wildfire

Increasing wildfires in western North American conifer forests have led to debates surrounding the application of post-fire management practices. There is a lack of consensus on whether (and to what extent) post-fire management assists or hinders managers in achieving goals, particularly in under-studied regions like eastern ponderosa pine forests. This makes it difficult for forest managers to balance among competing interests. We contrast structural and community characteristics across unburned ponderosa pine forest, severely burned ponderosa pine forest, and severely burned ponderosa pine forest treated with post-fire management with respect to three management objectives: ponderosa pine regeneration, wildland fuels control, and habitat conservation. Ponderosa pine saplings were more abundant in treated burned sites than untreated burned sites, suggesting increases in tree regeneration following tree planting; however, natural regeneration was evident in both unburned and untreated burned sites. Wildland fuels management greatly reduced snags and coarse woody debris in treated burned sites. Understory cover measurements revealed bare ground and fine woody debris were more strongly associated with untreated burned sites, and greater levels of forbs and grass were more strongly associated with treated burned sites. Wildlife habitat was greatly reduced following post-fire treatments. There were no tree cavities in treated burned sites, whereas untreated burned sites had an average of 27 ± 7.68 cavities per hectare. Correspondingly, we found almost double the avian species richness in untreated burned sites compared to treated burned sites (22 species versus 12 species). Unburned forests and untreated burned areas had the same species richness, but hosted unique avian communities. Our results indicate conflicting outcomes with respect to management objectives, most evident in the clear costs to habitat conservation following post-fire management application

Coupling dendroecological and remote sensing techniques to assess the biophysical traits of \u3ci\u3eJuniperus virginiana\u3c/i\u3e and \u3ci\u3ePinus ponderosa\u3c/i\u3e within the Semi-Arid grasslands of the Nebraska Sandhills

Woody species encroachment is occurring within the semi-arid grasslands of the Nebraska Sandhills U.S., primarily driven by native Juniperus virginiana and Pinus ponderosa, altering ecosystems and the services they provide. Effective, low cost, and cross-scale monitoring of woody species growth and performance is necessary for integrated grassland and forest management in the face of climate variability and change. In this study, we sought to establish a relationship between remote sensing-derived vegetation indices (VIs), tree dendrochronological (raw and standardized tree ring width) measurements, and the abiotic environment [(precipitation, temperature, Palmer Drought Severity Index (PDSI), and soil water content (0–300 cm depth)], over a 30-year period (1984–2013), to assess the performance of encroaching woody J. virginiana and P. ponderosa within the Nebraska Sandhills. We also investigated whether VIs can be used as an effective alternative tool to replace or complement ground measurements. Our results indicate that precipitation, temperature, and PDSI were significant (p \u3c 0.05) predictors of J. virginiana and P. ponderosa growth based on dendrochronological measurements and VIs, while soil water content from 40 to 300 cm depth was a significant predictor of J. virginiana performance. Out of the six VIs that were investigated, four were significant predictors of tree ring growth. R2 values between grassland VIs and growing season climate were greater than those of J. virginiana or P. ponderosa, while grassland performance was decoupled from soil water content. Additionally, climatic conditions in the previous year were significant determinants of current year growth of tree species but did not affect current year grassland performance. This study provides evidence for the efficacy of remote sensing-based VIs in monitoring interannual variation in the growth of woody species, while determining abiotic factors impacting the growth of grassland vegetation, J. virginiana, and P. ponderosa in the Nebraska Sandhills

Comparison of Dinitrogen Fixation and Nitrogen Transfer Potentials of Four Red Clover Cultivars

The capacity to fix atmospheric N2 and thus reduce the use of N fertilizer is an important reason for including legumes in forage mixtures. Selection for more efficient N2 fixation could improve red clover (Trifolium prateme L.) (RC) production and its contribution to soil fertility. An isotope dilution study was conducted in two greenhouse experiments to compare the N2 fixation and N transfer potentials of three commercial and one experimental RC cultivars. The experimental cultivar APR-8701 was selected for traits related to increased N2 fixation (rate of acetylene reduction, root size and branch number, and nodule mass). \u27Dawn\u27 orchardgrass (Dactylis glomerata L.) (OG) was used as the grass in mixture and as the reference crop for the isotope dilution study. Four harvests were taken from each of the two experiments. Herbage was analyzed first for total N and then for isotopic composition by mass spectrometry. Under the conditions of this study, the particular traits selected for in the development of the cultivar APR-8701 resulted in a high N2 fixation rate, ranging from 88.9 to 99.8 %N derived from the atmosphere (%Ndfa) in pure and mixed stands of both experiments, that paralleled the other three cultivars tested (ranging between 86.8 and 99. 9 %Ndfa in pure and mixed stands of both experiments). However, APR-8701 was average when N transfer potentials were compared. Average %N in grass derived from the atmosphere (%Ngdfa) was 32.2 and 46.3% for OG grown with APR-8701 in experiments 1 and 2, respectively, and ranged between 30. 5 and 50.1% for OG grown with the other three cultivars. We conclude that the experimental cultivar APR-8701 showed N2 fixation rates similar to that of other superior, commercially available cultivars, however, APR-8701 only showed average N transfer capability

Large differences in carbohydrate degradation and transport potential among lichen fungal symbionts.

Lichen symbioses are thought to be stabilized by the transfer of fixed carbon from a photosynthesizing symbiont to a fungus. In other fungal symbioses, carbohydrate subsidies correlate with reductions in plant cell wall-degrading enzymes, but whether this is true of lichen fungal symbionts (LFSs) is unknown. Here, we predict genes encoding carbohydrate-active enzymes (CAZymes) and sugar transporters in 46 genomes from the Lecanoromycetes, the largest extant clade of LFSs. All LFSs possess a robust CAZyme arsenal including enzymes acting on cellulose and hemicellulose, confirmed by experimental assays. However, the number of genes and predicted functions of CAZymes vary widely, with some fungal symbionts possessing arsenals on par with well-known saprotrophic fungi. These results suggest that stable fungal association with a phototroph does not in itself result in fungal CAZyme loss, and lends support to long-standing hypotheses that some lichens may augment fixed CO2 with carbon from external sources

Order-of-magnitude speedup for steady states and traveling waves via Stokes preconditioning in Channelflow and Openpipeflow

Steady states and traveling waves play a fundamental role in understanding hydrodynamic problems. Even when unstable, these states provide the bifurcation-theoretic explanation for the origin of the observed states. In turbulent wall-bounded shear flows, these states have been hypothesized to be saddle points organizing the trajectories within a chaotic attractor. These states must be computed with Newton's method or one of its generalizations, since time-integration cannot converge to unstable equilibria. The bottleneck is the solution of linear systems involving the Jacobian of the Navier-Stokes or Boussinesq equations. Originally such computations were carried out by constructing and directly inverting the Jacobian, but this is unfeasible for the matrices arising from three-dimensional hydrodynamic configurations in large domains. A popular method is to seek states that are invariant under numerical time integration. Surprisingly, equilibria may also be found by seeking flows that are invariant under a single very large Backwards-Euler Forwards-Euler timestep. We show that this method, called Stokes preconditioning, is 10 to 50 times faster at computing steady states in plane Couette flow and traveling waves in pipe flow. Moreover, it can be carried out using Channelflow (by Gibson) and Openpipeflow (by Willis) without any changes to these popular spectral codes. We explain the convergence rate as a function of the integration period and Reynolds number by computing the full spectra of the operators corresponding to the Jacobians of both methods.Comment: in Computational Modelling of Bifurcations and Instabilities in Fluid Dynamics, ed. Alexander Gelfgat (Springer, 2018