Climate sensitivity of understory trees differs from overstory trees in temperate mesic forests

Ecology ◽  
2020 ◽  
Author(s):  
Christine R. Rollinson ◽  
M. Ross Alexander ◽  
Alex W. Dye ◽  
David J.P. Moore ◽  
Neil Pederson ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Understory Trees ◽  
Overstory Trees

scholarly journals Arbuscular Mycorrhizal Community in Roots and Nitrogen Uptake Patterns of Understory Trees Beneath Ectomycorrhizal and Non-ectomycorrhizal Overstory Trees

2021 ◽  
Vol 11 ◽  
Author(s):  
Chikae Tatsumi ◽  
Fujio Hyodo ◽  
Takeshi Taniguchi ◽  
Weiyu Shi ◽  
Keisuke Koba ◽  
...  
Keyword(s):  
Community Composition ◽  
Mycorrhizal Fungi ◽  
N Uptake ◽  
Arbuscular Mycorrhizal ◽  
Nitrate Content ◽  
N Availability ◽  
Fungal Community Composition ◽  
Mycorrhizal Association ◽  
Understory Trees ◽  
Overstory Trees

Nitrogen (N) is an essential plant nutrient, and plants can take up N from several sources, including via mycorrhizal fungal associations. The N uptake patterns of understory plants may vary beneath different types of overstory trees, especially through the difference in their type of mycorrhizal association (arbuscular mycorrhizal, AM; or ectomycorrhizal, ECM), because soil mycorrhizal community and N availability differ beneath AM (non-ECM) and ECM overstory trees (e.g., relatively low nitrate content beneath ECM overstory trees). To test this hypothesis, we examined six co-existing AM-symbiotic understory tree species common beneath both AM-symbiotic black locust (non-ECM) and ECM-symbiotic oak trees of dryland forests in China. We measured AM fungal community composition of roots and natural abundance stable isotopic composition of N (δ15N) in plant leaves, roots, and soils. The root mycorrhizal community composition of understory trees did not significantly differ between beneath non-ECM and ECM overstory trees, although some OTUs more frequently appeared beneath non-ECM trees. Understory trees beneath non-ECM overstory trees had similar δ15N values in leaves and soil nitrate, suggesting that they took up most of their nitrogen as nitrate. Beneath ECM overstory trees, understory trees had consistently lower leaf than root δ15N, suggesting they depended on mycorrhizal fungi for N acquisition since mycorrhizal fungi transfer isotopically light N to host plants. Additionally, leaf N concentrations in the understory trees were lower beneath ECM than the non-ECM overstory trees. Our results show that, without large differences in root mycorrhizal community, the N uptake patterns of understory trees vary between beneath different overstory trees.

scholarly journals Seven Ways a Warming Climate Can Kill the Southern Boreal Forest

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 560
Author(s):  
Lee E. Frelich ◽  
Rebecca A. Montgomery ◽  
Peter B. Reich
Keyword(s):  
Boreal Forest ◽  
Boreal Forests ◽  
Temperate Forest ◽  
Sudden Change ◽  
Wildlife Habitat ◽  
Gradual Change ◽  
Temperate Trees ◽  
Coniferous Boreal Forest ◽  
Understory Trees ◽  
Overstory Trees

The southern boreal forests of North America are susceptible to large changes in composition as temperate forests or grasslands may replace them as the climate warms. A number of mechanisms for this have been shown to occur in recent years: (1) Gradual replacement of boreal trees by temperate trees through gap dynamics; (2) Sudden replacement of boreal overstory trees after gradual understory invasion by temperate tree species; (3) Trophic cascades causing delayed invasion by temperate species, followed by moderately sudden change from boreal to temperate forest; (4) Wind and/or hail storms removing large swaths of boreal forest and suddenly releasing temperate understory trees; (4) Compound disturbances: wind and fire combination; (5) Long, warm summers and increased drought stress; (6) Insect infestation due to lack of extreme winter cold; (7) Phenological disturbance, due to early springs, that has the potential to kill enormous swaths of coniferous boreal forest within a few years. Although most models project gradual change from boreal forest to temperate forest or savanna, most of these mechanisms have the capability to transform large swaths (size range tens to millions of square kilometers) of boreal forest to other vegetation types during the 21st century. Therefore, many surprises are likely to occur in the southern boreal forest over the next century, with major impacts on forest productivity, ecosystem services, and wildlife habitat.

SAMPLING THE EGG STAGES OF THE TWO-YEAR-CYCLE SPRUCE BUDWORM NEAR BABINE LAKE, BRITISH COLUMBIA

1963 ◽  
Vol 39 (2) ◽  
pp. 199-204 ◽  
Author(s):  
J. W. E. Harris
Keyword(s):  
British Columbia ◽  
Sample Size ◽  
Choristoneura Fumiferana ◽  
Spruce Budworm ◽  
High Population ◽  
Immature Stages ◽  
Egg Masses ◽  
Egg Stages ◽  
Understory Trees ◽  
Overstory Trees

Methods of sampling the immature stages of the two-year-cycle spruce bud-worm, Choristoneura fumiferana (Clem.), were studied at Babine hake in west-central British Columbia; this paper deals with the egg stage. At high population levels there was no difference in the number of egg masses per square foot of foliage surface between hosts, study areas, direction or sample size. Significant differences existed between crown levels and trees. Samples from understory trees were not representative of the egg populations from overstory trees. An acceptable estimate of egg numbers may be obtained by sampling one 18-inch branch tip from the mid-crown portion of as many trees as possible. Significant differences between sample areas at low population levels indicate that more localities would have to be sampled to obtain a representative estimate of egg numbers when fewer insects are present.

THE EFFECT ON VARIATIONS IN DECAY OF MOISTURE CONTENT AND RATE OF GROWTH IN SUBALPINE SPRUCE

1958 ◽  
Vol 36 (1) ◽  
pp. 187-206 ◽  
Author(s):  
D. E. Etheridge
Keyword(s):  
Moisture Content ◽  
Laboratory Tests ◽  
Moisture Contents ◽  
Test Pieces ◽  
Significant Difference ◽  
Rate Of Decay ◽  
Laboratory Infection ◽  
Basal Portion ◽  
Understory Trees ◽  
Overstory Trees

The moisture content in subalpine spruce was highest in overstory trees and lowest in understory trees, and it was higher in trees on a moist site than in trees of similar vigor classes on a dry site. Moisture contents of 10% of saturation for the more vigorous trees on the moist site and 7% of saturation for the less vigorous trees on the dry site represented a statistically significant difference which appeared to restrict the development of heartwood fungi to the wetter trees. A similar difference in the moisture content existed between the 1.5-ft. and the 20-ft. level of the trees, the occurrence of fungi being restricted to the wetter basal portion of the stems. In the laboratory, infection did not take place in test blocks at moisture contents lower than 8% of saturation. It is suggested that the threshold moisture content for infection in the trees occurs around the 7 to 8% saturation level. In the laboratory tests a difference in the moisture content of 3.4% of saturation in wood resulted in a statistically significant difference in the rate of decay by Coniophora puteana (Schum. ex Fr.) Karst., but differences in ring frequency and specific gravity in the test pieces corresponding to the differences between these properties in the living trees did not appreciably affect the decay rate. There was no evidence that variations in the distribution of decay-promoting or decay-retarding substances occurred in the trees from the two sites.

CLIMATE SENSITIVITY AND GROWTH RESPONSE OF TWO CONIFERS ON HIGH ELEVATION RIDGE AT WOLF KNOB, SHOSHONE FOREST, WY

2020 ◽  
Author(s):  
Laura Dye ◽  
◽  
Cori Butkiewicz ◽  
Zane Cooper ◽  
Bethany Coulthard ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Growth Response ◽  
High Elevation

scholarly journals Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

2021 ◽  
Author(s):  
Zhiting Chen ◽  
Hongyan Liu ◽  
Chongyang Xu ◽  
Xiuchen Wu ◽  
Boyi Liang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Climate Sensitivity ◽  
Learning Technology ◽  
Vegetation Greenness
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