Interactive effects of nocturnal transpiration and climate change on the root hydraulic redistribution and carbon and water budgets of southern United States pine plantations

Deep root water uptake and hydraulic redistribution (HR) have been shown to play a major role in forest ecosystems during drought, but little is known about the impact of climate change, fertilization and soil characteristics on HR and its consequences on water and carbon fluxes. Using data from three mid-rotation loblolly pine plantations, and simulations with the process-based model MuSICA, this study indicated that HR can mitigate the effects of soil drying and had important implications for carbon uptake potential and net ecosystem exchange (NEE), especially when N fertilization is considered. At the coastal site (C), characterized by deep organic soil, HR increased dry season tree transpiration (T) by up to 40%, and such an increase affected NEE through major changes in gross primary productivity (GPP). Deep-rooted trees did not necessarily translate into a large volume of HR unless soil texture allowed large water potential gradients to occur, as was the case at the sandy site (S). At the Piedmont site (P) characterized by a shallow clay-loam soil, HR was low but not negligible, representing up to 10% of T. In the absence of HR, it was predicted that at the C, S and P sites, annual GPP would have been diminished by 19, 7 and 9%, respectively. Under future climate conditions HR was predicted to be reduced by up to 25% at the C site, reducing the resilience of trees to precipitation deficits. The effect of HR on T and GPP was predicted to diminish under future conditions by 12 and 6% at the C and P sites, respectively. Under future conditions, T was predicted to stay the same at the P site, but to be marginally reduced at the C site and slightly increased at the S site. Future conditions and N fertilization would decrease T by 25% at the C site, by 15% at the P site and by 8% at the S site. At the C and S sites, GPP was estimated to increase by 18% and by >70% under future conditions, respectively, with little effect of N fertilization. At the P site, future conditions would stimulate GPP by only 12%, but future conditions plus N fertilization would increase GPP by 24%. As a consequence, in all sites, water use efficiency was predicted to improve dramatically with future conditions. Modeling the effect of reduced annual precipitation indicated that limited water availability would decrease all carbon fluxes, including NEE and respiration. Our simulations highlight the interactive effects of nutrients and elevated CO(2), and showed that the effect of N fertilization would be greater under future climate conditions.     

Inorganic sediment budget in the mangrove-fringed Fly River Delta,Papua New Guinea

Six oceanographic moorings were maintained for 8 weeks across the mouth of the mangrove-fringed Fly River estuary from April to June 1995 in the southeast trade wind season. A further 4 moorings were deployed for 8 weeks along the estuary channel in 1992, also in the southeast trade wind season. These data were used to estimate net exchange of suspended sediment between the estuary and the Gulf of Papua. A net inflow of fine sediment into the estuary from the coastal ocean was found to be considerable, about 40 tonnes s^-1 or about 10 times the riverine inflow rate, resulting in a calculated, spatially averaged vertical accretion rate of 2 mm year^-1. Mangroves may account for trapping 6% of the riverine sediment inflow or about 1/4 of the riverine clay inflow. If this sediment was distributed only over the observed accumulation zones near islands the local accumulation rates in these zones would reach 4 cm year^-1. Estimates of soft sediment mass accumulation rates (1–10 kg m^-2 year^-1) in the channel from Pb-210 and C-14 measurements from cores of deltaic mangrove mud cannot account for this accumulation rate on a 100–1000 year time scale. The fate of the remaining sediment is unknown, it may be exported from the estuary in the monsoon season.     

Evaluating changes in switchgrass physiology,biomass, and light-use efficiency under artificial shade to estimate yields if intercropped with Pinus taeda L.

There is growing interest in using switchgrass (Panicum virgatum L.) as a biofuel intercrop in forestry systems. However, there are limited data on the longevity of intercropped bioenergy crops, particularly with respect to light availability as the overstory tree canopy matures. Therefore, we conducted a greenhouse study to determine the effects of shading on switchgrass growth. Four treatments, each with different photosynthetically active radiation (PAR) levels, were investigated inside the greenhouse: control (no shade cloth, 49 % of full sunlight), low (under 36 % shade cloth), medium (under 52 % shade cloth), and heavy shade (under 78 % shade cloth). We determined the effect of shading from March to October 2011 on individually potted, multi-tillered switchgrass transplants cut to a stubble height of 10 cm. In the greenhouse, there was a reduction in tiller number, tiller height, gas exchange rates (photosynthesis and stomatal conductance), leaf area, above- and belowground biomass and light-use efficiency with increasing shade. Total (above- and belowground) biomass in the control measured 374 ± 22 compared to 9 ± 2 g pot^?1 under heavy shade (11 % of full sunlight). Corresponding light-use efficiencies were 3.7 ± 0.2 and 1.4 ± 0.2 g MJ^?1, respectively. We also compared PAR levels and associated aboveground switchgrass biomass from inside the greenhouse to PAR levels in the inter-row regions of a range of loblolly pine (Pinus taeda L.) stands from across the southeastern United States (U.S.) to estimate when light may limit the growth of intercropped species under field conditions. Results from the light environment of loblolly pine plantations in the field suggest that switchgrass biomass will be significantly reduced at a loblolly pine leaf area index between 1.95 and 2.25, which occurs on average between ages 6 and 8 years across the U.S. Southeast in intensively managed pine plantations. These leaf area indices correspond to a 60–65 % reduction in PAR from open sky.     

Evaluation of maternal parent and puroindoline allele on kernel texture in a reciprocal cross between two hard spring wheat cultivars

Kernel texture is an important characteristic for both the milling and the end-use quality of wheat (Triticum aestivum L.). Gene sequence variation and mutations to the two puroindoline genes (Pina and Pinb), located at the Ha locus on chromosome 5DS, account for the majority of variation in wheat kernel texture. Other factors also influence kernel texture, including effects associated with different maternal parent backgrounds. To investigate the effect of two hard puroindoline alleles in different maternal backgrounds, a population of 228 recombinant inbred lines (RILs) derived from a reciprocal cross between two wheat cultivars ID377s (Pina-D1b/Pinb-D1a) and Klasic (Pina-D1a/Pinb-D1b) were examined in two succeeding generations (F₇ & F₈). Kernel texture was determined using the Single Kernel Characterization System (SKCS) and the RIL puroindoline haplotype was identified by the sequence-specific PCR amplification of each gene. Analysis of variance identified a significant (P 0.001) effect of the maternal parent and puroindoline mutation on kernel texture. RILs containing the Pina-D1b mutation were significantly harder than lines containing the Pinb-D1b mutation. RILs which had Klasic as the maternal parent were significantly harder than those which had ID377s as the maternal parent. When the maternal parent and puroindoline allele were analyzed in combination, RILs derived from Klasic as the maternal parent and the Pina-D1b allele were significantly harder (P 0.001) than those containing the same allele but ID377s as the maternal parent. The same occurred for RILs containing the Pinb-D1b allele, lines with Klasic as the maternal parent were harder than lines with ID377s as the maternal parent. These results corroborate the harder phenotype of the Pina-D1b allele and indicate a significant maternally-inherited contribution to kernel texture variation.     

Bayesian Methods for Hierarchical Distance Sampling Models

The few distance sampling studies that use Bayesian methods typically consider only line transect sampling with a half-normal detection function. We present a Bayesian approach to analyse distance sampling data applicable to line and point transects, exact and interval distance data and any detection function possibly including covariates affecting detection probabilities. We use an integrated likelihood which combines the detection and density models. For the latter, densities are related to covariates in a log-linear mixed effect Poisson model which accommodates correlated counts. We use a Metropolis-Hastings algorithm for updating parameters and a reversible jump algorithm to include model selection for both the detection function and density models. The approach is applied to a large-scale experimental design study of northern bobwhite coveys where the interest was to assess the effect of establishing herbaceous buffers around agricultural fields in several states in the US on bird densities. Results were compared with those from an existing maximum likelihood approach that analyses the detection and density models in two stages. Both methods revealed an increase of covey densities on buffered fields. Our approach gave estimates with higher precision even though it does not condition on a known detection function for the density model.     

A Comprehensive Genotype and Environment Assessment of Wheat Grain Ash Content in Oregon and Washington: Analysis of Variation

A comprehensive analysis of the variation in wheat grain ash content has not been previously conducted. This study assessed the relative contribution of genotype and environment to variation in ash content, with a particular aim of ascertaining the potential for manipulating the trait using contemporary adapted germplasm. A total of 2,240 samples were drawn from four years of multilocation field plots grown in the wheat production areas of Oregon and Washington states. Genotypes included commercial cultivars and advanced breeding lines of soft and hard winter, and soft and hard spring wheats with red and white kernel color, several soft white club wheats, and one soft white spring waxy wheat cultivar. In addition to ash, protein content, test weight, and Single Kernel Characterization System kernel hardness, weight and size were also measured. In total, 20 separate fully balanced ANOVA results were conducted. Whole model R² values were highly significant, 0.62–0.91. Nineteen of the 20 ANOVA results indicated significant genotype effects, but the effects were not large. In contrast, environment effects were always highly significant with F values often one to two orders of magnitude larger than the genotype F values. The grand mean for all samples was 1.368% ash. For individual data sets, genotype means across environments varied ≈0.1–0.3% ash. The genotypes judged noteworthy because they had the highest least squares mean ash content were OR9900553 and ClearFirst soft white winter, NuHills hard red winter, Waxy‐Pen and Cataldo soft white spring, and WA8010 and Lochsa hard spring wheats. Genotypes with lowest least squares mean ash were Edwin (club) soft white winter, OR2040073H hard red winter, WA7952 soft white spring, and WA8038 hard spring wheats. In conclusion, wheat grain ash is more greatly influenced by crop year and location than by genotype. However, sufficient genotype variation is present to plausibly manipulate this grain trait through traditional plant breeding.     

Guest Editor’s Introduction to the Special Issue on “Animal Movement Modeling”

In this introduction, we provide a brief overview to statistical models for animal trajectories and then summarize the set of invited articles that comprise the issue.