Growing season precipitation from D/H ratios of Eastern White Pine

Nature ◽  
1984 ◽  
Vol 311 (5986) ◽  
pp. 558-560 ◽  
Author(s):  
J. R. Lawrence ◽  
J. W. C. White
1988 ◽  
Vol 6 (2) ◽  
pp. 42-45
Author(s):  
L. Eric Hinesley ◽  
Robert D. Wright

Eastern white pine (Pinus strobus L.) were potted and solution fed once weekly during 2 growing seasons with 5 levels of N in the irrigation water: 50, 100, 200, 300 and 400 ppm. Leaders were treated with 750 ppm 6-benzylaminopurine (BA) in late June of the first year. The higher N levels resulted in greater stem diameter, greater foliage dry weight, longer and heavier needle fascicles, better foliage color, greater budset after application of BA, and more and longer branches on the BA-treated leader the second growing season. BA should be applied to trees with N concentration ≥ 1.5% in one-year-old foliage.


1968 ◽  
Vol 46 (12) ◽  
pp. 1565-1574 ◽  
Author(s):  
S. N. Linzon

The results of etiological studies on semimature-tissue needle blight (SNB) of eastern white pine (Pinus strobus L.) deny any role to needle fungi as the primary cause. No mycelium was found in newly blighted semimature tissue by either cultural or histological methods. Mycelia of several saprophytic fungi were isolated from the blighted portions of current year needles about 2 weeks after the onset of SNB, and fruit-bodies of different organisms were found to occur both in the interior and on the exterior of blighted needles about 4 weeks after the first occurrence of disease symptoms. The fruit-bodies of two Ascomycetes, Cenangium acuum Peck & Cooke and Hypoderma desmazierii Duby (= Lophodermium brachysporum (Rostrup) Tub.), were found on the necrotic terminals of attached 1-year-old needles which had been blighted in the previous year. The morphological development of apothecia of C. acuum was studied. Hysterothecia of Lophodermium spp. (L. pinastri (Schrad. ex Fr.) Chev. and L. nitens Darker) occurred ubiquitously on fallen white pine needles. Aerial spore trapping snowed that ascospores of C. acuum were abundant, those of Lophodermium spp. were prevalent, and those of H. desmazierii were practically non-existent in the area investigated. There was little coincidence between the occurrence of SNB outbreaks and peak populations of air-borne ascospores of these fungi. Ascospore suspensions and needles bearing fructifications of C. acuum and Lophodermium spp. were used to inoculate the newly developing needles of SNB-susceptible and non-susceptible field trees and potted seedlings, but the typical symptoms of SNB did not develop as a result of these inoculations. Two fungicides, captan and Bordeaux mixture, were applied to SNB-susceptible and non-susceptible field trees throughout the growing season, but neither fungicide prevented the symptoms of SNB from appearing on the new needles of susceptible trees at the same time as they appeared on untreated susceptible trees in the area. The fungicidal sprays, however, did prevent saprophytic fungi from invading blighted portions of the needles. It is concluded from this investigation that SNB is not a disease of fungal origin.


2012 ◽  
Vol 42 (1) ◽  
pp. 67-74
Author(s):  
Pengxin Lu ◽  
Darren Derbowka

Seedling age at the time of artificial white pine blister rust ( Cronartium ribicola J.C. Fisch.) inoculation can affect the duration and accuracy of resistance assessments for eastern white pine ( Pinus strobus L.) and its hybrid backcrosses and thereby affect advances in breeding programs intended to enhance genetic resistance to the pathogen. Based on postinoculation seedling mortality rates, up to 5 years were required to rank resistance of eastern white pine genotypes when seedlings were inoculated with C. ribicola at 2 years of age compared with less than 2 years when they were inoculated after the first growing season. In this study, we evaluated and compared consistency of genotype rankings in seedling mortality rates between the two inoculation approaches. Assessment results from inoculating seedlings after the first growing season proved as reliable as those achieved by inoculating them after the second growing season. Inoculating seedlings at a younger age not only substantially reduced experimental time and costs but also allowed a larger number of seedlings to be screened for resistance, leading to higher experimental precision.


1987 ◽  
Vol 25 (2) ◽  
pp. 137-158 ◽  
Author(s):  
Michael B. Richman ◽  
Peter J. Lamb

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Terence Epule Epule ◽  
Driss Dhiba ◽  
Daniel Etongo ◽  
Changhui Peng ◽  
Laurent Lepage

AbstractIn sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered.


2010 ◽  
Vol 40 (3) ◽  
pp. 423-435 ◽  
Author(s):  
Charles R. Drever ◽  
James Snider ◽  
Mark C. Drever

Our objective was to assess the relative rarity and representation within protected areas of Standard Forest Units (SFUs) in northeastern Ontario by applying the concepts of geographic range, habitat specificity, and local population size. SFUs are stand type classifications, routinely employed by forest managers, based on tree composition, disturbance history, and prescribed silvicultural system. We identified several SFUs as rare because of a narrow distribution, association with only one landform type, or lack of at least one stand larger than an ecoregion-specific threshold. In the Boreal forest, rare SFUs comprised stands dominated by eastern hemlock ( Tsuga canadensis (L.) Carrière), red oak ( Quercus rubra L.), yellow birch ( Betula alleghaniensis Britt.), or eastern white-cedar ( Thuja occidentalis L.). Rare SFUs also included eastern white pine ( Pinus strobus L.) and (or) red pine ( Pinus resinosa Ait.) leading stands managed by shelterwood or seed tree silviculture as well as low-lying deciduous stands and selection-managed stands of shade-tolerant species. In the Great Lakes – St. Lawrence forest, rare SFUs were yellow birch stands, stands dominated by conifer species abundant in the Boreal, and shelterwood-managed hardwood stands. Several rare SFUs had <12% of their total area in protection, i.e., stands dominated by eastern white pine, yellow birch, eastern white pine – red oak, or eastern white-cedar. These rare stand types require increased protection in reserves and tailored silvicultural practices to maintain their probability of persistence.


Weed Science ◽  
2007 ◽  
Vol 55 (6) ◽  
pp. 652-664 ◽  
Author(s):  
N. C. Wagner ◽  
B. D. Maxwell ◽  
M. L. Taper ◽  
L. J. Rew

To develop a more complete understanding of the ecological factors that regulate crop productivity, we tested the relative predictive power of yield models driven by five predictor variables: wheat and wild oat density, nitrogen and herbicide rate, and growing-season precipitation. Existing data sets were collected and used in a meta-analysis of the ability of at least two predictor variables to explain variations in wheat yield. Yield responses were asymptotic with increasing crop and weed density; however, asymptotic trends were lacking as herbicide and fertilizer levels were increased. Based on the independent field data, the three best-fitting models (in order) from the candidate set of models were a multiple regression equation that included all five predictor variables (R2= 0.71), a double-hyperbolic equation including three input predictor variables (R2= 0.63), and a nonlinear model including all five predictor variables (R2= 0.56). The double-hyperbolic, three-predictor model, which did not include herbicide and fertilizer influence on yield, performed slightly better than the five-variable nonlinear model including these predictors, illustrating the large amount of variation in wheat yield and the lack of concrete knowledge upon which farmers base their fertilizer and herbicide management decisions, especially when weed infestation causes competition for limited nitrogen and water. It was difficult to elucidate the ecological first principles in the noisy field data and to build effective models based on disjointed data sets, where none of the studies measured all five variables. To address this disparity, we conducted a five-variable full-factorial greenhouse experiment. Based on our five-variable greenhouse experiment, the best-fitting model was a new nonlinear equation including all five predictor variables and was shown to fit the greenhouse data better than four previously developed agronomic models with anR2of 0.66. Development of this mathematical model, through model selection and parameterization with field and greenhouse data, represents the initial step in building a decision support system for site-specific and variable-rate management of herbicide, fertilizer, and crop seeding rate that considers varying levels of available water and weed infestation.


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