Vegetative and reproductive dry weight inhibition in nitrogen‐ and phosphorus‐deficient Pima cotton 1

Whether the extent of dry weight inhibition by nitrogen (N) or phosphorus (P) deficiencies on different plant parts is the same and whether imposing moderate N and P deficiencies selectively suppress undesirable vegetative growth has not been studied in Pima cotton (Gossypium barbadense L.). The purpose of this study was to determine the extent to which dry matter accumulation in leaves, stems, and reproductive structures is inhibited by N and P deficiencies in Pima cotton. The study was conducted in 1991 and 1992 in a Uvalde silty clay loam soil (fine‐silty, mixed, hyperthermic Aridic Calciustolls). The treatments included applied rates of 0, 67, 135, 202, and 269 kg N ha^‐1 in a factorial combination with 0, 15, 29, and 44 kg P ha^‐1. Nitrogen deficiency (0 kg N ha^‐1) significantly (P≤0.05) reduced leaf (LDW) and stem (SDW) dry weights in both years and reproductive dry weight (RDW) in 1992. Nitrogen deficiency suppressed dry weight accumulation in leaves to a greater extent than in stems. Relative to 269 kg N ha^‐1, the 0 kg N ha^‐1 treatment resulted in a maximum LDW reduction of 62% at 144 DAP (days after planting) in 1991 and 36% at 121 DAP in 1992, compared with a corresponding SDW reduction of only 39% in 1991 and 25% in 1992. Dry weight accumulation in reproductive parts was the least affected by N deficiency. The decline in LDW associated with senescence and defoliation began earlier in treatments that received 0 or 67 kg N ha^‐1 than treatments that received ≥135 kg N ha^‐1. Phosphorus affected LDW and SDW in 1991, but its differential effect on LDW, SDW, and RDW was much smaller than that of N. Imposing a moderate level of N deficiency, not P deficiency, may be an effective Pima cotton management strategy to selectively suppress undesirable vegetative growth and enhance maturity.     

EFFICIENCY OF PRE-PLANT,TOPDRESS, AND VARIABLE RATE APPLICATION OF NITROGEN IN WINTER WHEAT

Past research about the efficiency of nitrogen application in winter wheat (Triticum aestivum L.) based on source and timing has produced inconsistent results. The majority of the literature used data from few locations over short time periods. This study used a unique data set of yields and nitrogen quantities from 2002–2009 at ten different locations in Oklahoma, USA. The objective of this research was to determine wheat yield response for granular pre-plant, uniform foliar topdress, and variable rate foliar topdress. Topdress liquid nitrogen had a 19% higher NUE than pre-plant urea, and was the most profitable source of nitrogen.     

Ecological Prediction With Nonlinear Multivariate Time-Frequency Functional Data Models

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.     

Linking vegetation patterns to environmental gradients and human impacts in a mediterranean-type island ecosystem

Vegetation patterns at the landscape scale are shaped by myriad processes and historical events, and understanding the relative importance of these processes aids in predicting current and future plant distributions. To quantify the influence of different environmental and anthropogenic patterns on observed vegetation patterns, we used simultaneous autoregressive modeling to analyze data collected by the Carnegie Airborne Observatory over Santa Cruz Island (SCI; California, USA). SCI is a large continental island, and its limited suite of species and well documented land use history allowed us to consider many potential determinants of vegetation patterns, such as topography, substrate, and historical grazing intensity. As a metric of vegetation heterogeneity, we used the normalized difference vegetation index (NDVI) stratified into three vegetation height classes using LiDAR (short, medium, and tall). In the SAR models topography and substrate type were important controls, together explaining 8–15 % of the total variation in NDVI, but historical grazing and spatial autocorrelation were also key components of the models, together explaining 17–21 % of the variation in NDVI. Optimal spatial autocorrelation distances in the short and medium height vegetation models (600–700 m) were similar to the home range sizes of two crucial seed dispersers on the island– the island fox (Urocyon littoralis santacruzae) and the island scrub-jay (Aphelocoma insularis)—suggesting that these animals may be important drivers of the island’s vegetation patterns. This study highlights the importance of dynamic processes like dispersal limitation and disturbance history in determining present-day vegetation patterns.     

Dynamic connectivity of temporary wetlands in the southern Great Plains

We quantified fluctuations in the status of individual patches (wetlands) in supporting connectivity within a network of playas, temporary wetlands of the southern Great Plains of North America that are loci for regional biodiversity. We used remote sensing imagery to delineate the location of surface waters in >8,000 playa basins in a ~31,900 km² portion of Texas and quantified connectivity in this region from 2007 to 2011. We ranked playas as stepping-stones, cutpoints, and hubs at different levels of environmental conditions (regionally wet, dry, and average periods of precipitation) for dispersal distances ranging from 0.5 to 34 km, representing a range of species’ vagilities, to provide baseline dynamics within an area likely to experience disrupted connectivity due to anthropogenic activities. An individual playa’s status as a stepping-stone, cutpoint, or hub was highly variable over time (only a single playa was a top 20 stepping-stone, cutpoint, or hub in >50 % of all of the dates examined). Coalescence of the inundated playa network usually occurred at ≥10 km dispersal distance and depended on wetland density, indicating that critical thresholds in connectivity arose from synergistic effects of dispersal ability (spatial scale) and wet playa occurrence (a function of precipitation). Organisms with dispersal capabilities limited to <10 km routinely experienced effective isolation during our study. Connectivity is thus a dynamic emergent landscape property, so management to maintain connectivity for wildlife within ephemeral habitats like inundated playas will need to move beyond a patch-based focus to a network focus by including connectivity as a dynamic landscape property.     

Predation of lowbush blueberry insect pests by ground beetles (Coleoptera: Carabidae) in the laboratory

Agriculture relies on ecosystem services, such as biological control of pests, for economic success and sustainability. Commercially managed lowbush blueberries are an important crop in eastern North America, but pest control by natural enemies has not been well studied. In this paper we address questions about consumption of two blueberry pests by ground beetles (Carabidae) that are common in blueberry fields. In the first experiment, a Poecilus l. lucublandus, Carabus nemoralis, or Pterostichus mutus beetle was placed with two blueberry spanworm larvae, Itame argillacearia, in a simple (cup only or cup + soil) or more complex (cup + soil + blueberry sprigs) treatment arena. In most cases, probability of spanworm consumption reached 100 % in simple arenas by the end of the experiment (48 h) but was 25–50 % lower in more complex arenas. In a second experiment, a male or female Pterostichus melanarius or Harpalus rufipes beetle was placed in a plastic container with saturated or dry soil into which mature blueberry maggots, Rhagoletis mendax, dropped from blueberries to pupate. Approximately 40–80 and 35 % fewer pupae were recovered when a P. melanarius and H. rufipes beetle was present, respectively, but soil moisture and beetle sex were not significant factors. Our results demonstrate that ground beetles can prey upon important blueberry pests, but suggest that consumption may be influenced by microhabitat structure.     

Identification and mapping of adult‐plant stripe rust resistance in soft red winter wheat cultivar ‘USG 3555’

Little is known about the extent or diversity of resistance in soft red winter wheat (Triticum aestivum L.) to stripe rust, caused by the fungal pathogen Puccinia striiformis f.sp. tritici. The soft red winter (SRW) wheat cultivar ‘USG 3555’ has effective adult‐plant resistance to stripe rust, which was characterized in a population derived from ‘USG 3555’/‘Neuse’. The mapping population consisted of 99 recombinant inbred lines, which were evaluated for stripe rust infection type (IT) and severity to race PST‐100 in field trials in North Carolina in 2010 and 2011. Genome‐wide molecular‐marker screenings with 119 simple sequence repeats and 560 Diversity Arrays Technology (DArT) markers were employed to identify quantitative trait loci (QTL) for stripe rust resistance. QTL on chromosomes 1AS, 4BL and 7D of ‘USG 3555’ explained 12.8, 73.0 and 13.6% of the variation in stripe rust IT, and 13.5, 72.3 and 10.5% of the variation in stripe rust severity, respectively. Use of these and additional diagnostic markers for these QTL will facilitate the introgression of this source of stripe rust resistance into SRW wheat lines via marker‐assisted selection.