scholarly journals Anatomical and hydraulic responses to desiccation in emergent conifer seedlings

2020 ◽  
Vol 107 (8) ◽  
pp. 1177-1188
Author(s):  
Megan L. Miller ◽  
Adam B. Roddy ◽  
Craig R. Brodersen ◽  
Andrew J. McElrone ◽  
Daniel M. Johnson
Keyword(s):  
Conifer Seedlings

Cylindrocarpon and Fusarium root colonization of Douglas-fir seedlings from British Columbia reforestation sites

1998 ◽  
Vol 28 (8) ◽  
pp. 1198-1206 ◽  
Author(s):  
Paige E Axelrood ◽  
William K Chapman ◽  
Keith A Seifert ◽  
David B Trotter ◽  
Gwen Shrimpton
Keyword(s):  
British Columbia ◽  
Pseudotsuga Menziesii ◽  
Root Colonization ◽  
Linear Trend ◽  
Poor Performance ◽  
Douglas Fir ◽  
Root Infection ◽  
Significant Linear Trend ◽  
Conifer Seedlings ◽  
Cylindrocarpon Destructans

Poor performance of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) plantations established in 1987 has occurred in southwestern British Columbia. Affected sites were planted with 1-year-old container stock that exhibited some root dieback in the nursery. A study was initiated in 1991 to assess Cylindrocarpon and Fusarium root infection in planted and naturally regenerating (natural) Douglas-fir seedlings from seven affected plantations. Percentages of seedlings harboring Cylindrocarpon spp.and percent root colonization were significantly greater for planted seedlings compared with natural seedlings. A significant linear trend in Cylindrocarpon root colonization was observed for planted seedlings with colonization levels being highest for roots closest to the remnants of the root plug and decreasing at distances greater than 10cm from that region. This trend in Cylindrocarpon colonization was not observed for natural seedlings. Cylindrocarpon destructans (Zins.) Scholten var. destructans and C.cylindroides Wollenw. var. cylindroides were the only species isolated from planted and natural conifer seedlings. For most sites, percentage of seedlings harboring Fusarium spp.and percent Fusarium root colonization were less than for Cylindrocarpon. Recovery of Fusarium spp.from seedlings and root colonization levels were not significantly different for planted and natural seedlings from all sites.

Integrated vegetation management in California – advances and future

1991 ◽  
Vol 67 (5) ◽  
pp. 528-531 ◽  
Author(s):  
Gary O. Fiddler ◽  
Philip M. McDonald
Keyword(s):  
Good Control ◽  
Vegetation Management ◽  
Bureau Of Land Management ◽  
Private Industry ◽  
Conifer Seedlings ◽  
Central California ◽  
Competing Vegetation ◽  
Growing Seasons ◽  
Survival And Growth ◽  
Mechanical Release

A study on alternatives for releasing young conifer plantations on National Forests in northern and central California was started in 1980, and enlarged to include State of California, Bureau of Land Management, and private industry lands. Forty studies involving chemical, manual, mechanical, mulch, and animal treatments have been established and their effect on the survival and growth of conifer seedlings is being quantified. Plant diversity and succession on both treated and untreated sites are being recorded. The oldest study has had 10 growing seasons since the first treatments were applied. To release conifer seedlings, a treatment radius of at least 1.5 meters is required; smaller radii do not provide enough site resources for acceptable growth. Diameter, rather than height, is the best indicator of release. Some non-phenoxy chemicals show promise for good control of competing vegetation. Mechanical release requires additional treatments to effectively control shrubs. Mulching has given limited results to date. Manual treatments, if applied to non-sprouting and nonrhizomatous plants soon after planting, and usually more than once, provide adequate control of competing vegetation, but are costly.

scholarly journals Optimizing growth of conifer seedlings in vitro

1989 ◽  
Vol 46 (Supplement) ◽  
pp. 168s-170s
Author(s):  
G. Flygh ◽  
R. Grönroos ◽  
S. von Arnold
Keyword(s):  
Conifer Seedlings

Copper requirements of container-grown conifer seedlings

1982 ◽  
Vol 12 (4) ◽  
pp. 848-852 ◽  
Author(s):  
D. H. Lambert ◽  
T. C. Weidensaul
Keyword(s):  
Maximum Growth ◽  
Douglas Fir ◽  
Optimum Growth ◽  
White Pine ◽  
Eastern White Pine ◽  
Conifer Seedlings ◽  
Blue Spruce ◽  
Noble Fir ◽  
Fertilizer Rates ◽  
Nutrient Solutions

Blue spruce (Piceapungens Engelm.), Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco, Noble fir (Abiesprocera Rehd.), and eastern white pine (Pinusstrobus L.) seedlings grown in the greenhouse in peat–vermiculite medium were fertilized with nutrient solutions containing 0.00–0.64 ppm Cu. Maximum growth generally occurred at levels higher than the conventional fertilizer rates of 0.02–0.06 ppm, particularly for Douglas-fir, with subsequent shoot or needle concentrations of 3 or more ppm. Optimum growth of Douglas-fir in a peat–vermiculite medium treated with a single initial drench of 0–100 ppm Cu/L mix occurred over a broad range of foliar Cu concentrations greater than 4 ppm. Supplemental Cu for container-grown conifers thus appears necessary in some cases, but not harmful in others.

Aphanomyces euteiches. [Descriptions of Fungi and Bacteria].

1978 ◽  
Author(s):  
D. J. Stamps
Keyword(s):  
Population Dynamics ◽  
Geographical Distribution ◽  
Root Rot ◽  
Aphanomyces Euteiches ◽  
Conifer Seedlings ◽  
Alternative Hosts ◽  
Pea Root ◽  
Pea Root Rot ◽  
Sweet Pea

Abstract A description is provided for Aphanomyces euteiches. Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. HOSTS: Pea, Arabis, pansy, sweet pea, clover, bean, lupin, vetch, lucerne, Melilotus, barley, oats, Echinodorus brevipedicellatus. Conifer seedlings and other hosts were infected by inoculation. DISEASE: Root rot of pea. GEOGRAPHICAL DISTRIBUTION: Asia (Japan); Australia (Tasmania); Europe (UK, Denmark, France, Norway, Sweden, USSR); N. America (USA). (CMI Map 78, ed. 3, 1977). TRANSMISSION: Soil-borne, persisting in the soil for many years. Studies in Wisconsin suggested that A. euteiches may live as a weak parasite in the roots of many plants and occur naturally in some virgin soils (6, 523). Oospores were indicated to be the primary inocula for new outbreaks of pea root rot, zoospores the primary infective agents (39, 646). Survival between pea crops depended on oospore durability and possible alternative hosts, not saprophytic activity (41, 689). Studies were made of population dynamics in the soil (48, 2067) and penetration and infection of roots by zoospores (42, 287).

Responses of Five Species of Conifer Seedlings to Aluminum Stress

1986 ◽  
pp. 1337-1348
Author(s):  
Thomas C. Hutchinson ◽  
Leah Bozic ◽  
Guadalupe Munoz-Vega
Keyword(s):  
Aluminum Stress ◽  
Conifer Seedlings

scholarly journals Automated Detection of Conifer Seedlings in Drone Imagery Using Convolutional Neural Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 2585 ◽  
Author(s):  
Michael Fromm ◽  
Matthias Schubert ◽  
Guillermo Castilla ◽  
Julia Linke ◽  
Greg McDermid
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Forest Restoration ◽  
Oil And Gas ◽  
Significant Loss ◽  
Tree Regeneration ◽  
Training Dataset ◽  
Conifer Seedlings ◽  
Oil And Gas Exploration ◽  
Combining Data

Monitoring tree regeneration in forest areas disturbed by resource extraction is a requirement for sustainably managing the boreal forest of Alberta, Canada. Small remotely piloted aircraft systems (sRPAS, a.k.a. drones) have the potential to decrease the cost of field surveys drastically, but produce large quantities of data that will require specialized processing techniques. In this study, we explored the possibility of using convolutional neural networks (CNNs) on this data for automatically detecting conifer seedlings along recovering seismic lines: a common legacy footprint from oil and gas exploration. We assessed three different CNN architectures, of which faster region-CNN (R-CNN) performed best (mean average precision 81%). Furthermore, we evaluated the effects of training-set size, season, seedling size, and spatial resolution on the detection performance. Our results indicate that drone imagery analyzed by artificial intelligence can be used to detect conifer seedling in regenerating sites with high accuracy, which increases with the size in pixels of the seedlings. By using a pre-trained network, the size of the training dataset can be reduced to a couple hundred seedlings without any significant loss of accuracy. Furthermore, we show that combining data from different seasons yields the best results. The proposed method is a first step towards automated monitoring of forest restoration/regeneration.

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