scholarly journals Spatial variability in pollen and resource limitation for fruit production of two species in interior Alaska: Vaccinium uliginosum and V. vitis-idaea

2019 ◽  
Author(s):  
Lindsey Viann Parkinson ◽  
Christa P.H. Mulder
Keyword(s):  
Soil Moisture ◽  
Boreal Forest ◽  
Resource Availability ◽  
Pollen Limitation ◽  
Canopy Cover ◽  
Fruit Production ◽  
Floral Resources ◽  
Soil Conditions ◽  
Vaccinium Uliginosum ◽  
Interior Alaska

AbstractMany recent studies assessing fruit productivity of plants in the boreal forest focus on interannual variability across a forested region, rather than on environmental variability within the forest. Frequency and severity of wildfires in the boreal forest affect soil moisture, canopy, and community structure at the landscape level, all of which may influence overall fruit production at a site directly (through resource availability) or indirectly (through impacts on pollinators). We evaluated how fruit production in two boreal shrubs, Vaccinium uliginosum (blueberry) and V. vitis-idaea (lingonberry), was explained by factors associated with resource availability (such as canopy cover and soil conditions) and pollen limitation (such as floral resources for pollinators and pollen deposition) across boreal forest sites of Interior Alaska. We classified our study sites into upland and lowland sites, which differed in elevation, soil moisture (lower in upland sites), and active layer (deeper in upland sites). We found that resource and pollen limitation differed between the two species and between uplands and lowlands. Lingonberry was more pollen limited than blueberry, and plants in lowland sites were more pollen limited relative to other sites while plants in upland sites were relatively more resource limited. Additionally, canopy cover had a significant negative effect in upland sites on a ramet’s investment in reproductive tissues and leaves versus structural growth, but little effect in lowland sites. These results point to importance of including pollinator abundance as well as resource availability in predictions for changes in berry abundance.

The reproductive biology of boreal forest herbs. II. Phenology of flowering and fruiting

1987 ◽  
Vol 65 (10) ◽  
pp. 2047-2056 ◽  
Author(s):  
Kaius Helenurm ◽  
Spencer C. H. Barrett
Keyword(s):  
Boreal Forest ◽  
Fruit Set ◽  
Pollen Limitation ◽  
Fruit Production ◽  
Fruit Removal ◽  
Cornus Canadensis ◽  
Forest Herbs ◽  
Pollinator Service ◽  
Maianthemum Canadense ◽  
Major Factors

The flowering and fruiting phenologies of 12 boreal forest herbs were recorded during 1979 (flowering and fruiting) and 1980 (flowering only) in spruce–fir forests of central New Brunswick. The species studied were Aralia nudicaulis, Chimaphila umbellata, Clintonia borealis, Cornus canadensis, Cypripedium acaule, Linnaea borealis, Maianthemum canadense, Medeola virginiana, Oxalis montana, Pyrola secunda, Trientalis borealis, and Trillium undulatum. Flowering in the community occurred from mid-May to the end of July. The order of flowering was maintained in the 2 years, but the degree of synchronization of inflorescences differed in several species. Fruiting in the community began in mid-July and extended beyond the end of September. The percentage of buds that ultimately bore fruit ranged from 0 (Cypripedium acaule) to 61% (Aralia nudicaulis). With the exception of Cypripedium acaule, which received little pollinator service, the self-incompatible species, Cornus canadensis, Maianthemum canadense, and Medeola virginiana, experienced the lowest levels of fruit-set. Pollen limitation and predation of developing fruit appear to be the major factors limiting percentage fruit-set in boreal forest herbs. Fruit production varied with time of flowering of inflorescences in several species, with periods of low fruit-set tending to coincide with lower densities of flowering inflorescences. Significant rates of fruit removal by herbivores occurred in all sarocochorous species. Disappearance of fruits from infructescences ranged from 31 (Medeola virginiana) to 95% (Aralia nudicaulis), with highest removal rates occurring during periods of greatest fruit availability.

scholarly journals Assessing Wildfire Burn Severity and Its Relationship with Environmental Factors: A Case Study in Interior Alaska Boreal Forest

2021 ◽  
Vol 13 (10) ◽  
pp. 1966
Author(s):  
Christopher W Smith ◽  
Santosh K Panda ◽  
Uma S Bhatt ◽  
Franz J Meyer ◽  
Anushree Badola ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Ground Truth ◽  
Burn Severity ◽  
Classification Methods ◽  
Spectral Indices ◽  
Ground Truth Data ◽  
Burn Scar ◽  
Interior Alaska ◽  
Remote Sensing Methods ◽  
The Relationship

In recent years, there have been rapid improvements in both remote sensing methods and satellite image availability that have the potential to massively improve burn severity assessments of the Alaskan boreal forest. In this study, we utilized recent pre- and post-fire Sentinel-2 satellite imagery of the 2019 Nugget Creek and Shovel Creek burn scars located in Interior Alaska to both assess burn severity across the burn scars and test the effectiveness of several remote sensing methods for generating accurate map products: Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and Random Forest (RF) and Support Vector Machine (SVM) supervised classification. We used 52 Composite Burn Index (CBI) plots from the Shovel Creek burn scar and 28 from the Nugget Creek burn scar for training classifiers and product validation. For the Shovel Creek burn scar, the RF and SVM machine learning (ML) classification methods outperformed the traditional spectral indices that use linear regression to separate burn severity classes (RF and SVM accuracy, 83.33%, versus NBR accuracy, 73.08%). However, for the Nugget Creek burn scar, the NDVI product (accuracy: 96%) outperformed the other indices and ML classifiers. In this study, we demonstrated that when sufficient ground truth data is available, the ML classifiers can be very effective for reliable mapping of burn severity in the Alaskan boreal forest. Since the performance of ML classifiers are dependent on the quantity of ground truth data, when sufficient ground truth data is available, the ML classification methods would be better at assessing burn severity, whereas with limited ground truth data the traditional spectral indices would be better suited. We also looked at the relationship between burn severity, fuel type, and topography (aspect and slope) and found that the relationship is site-dependent.

scholarly journals Field-Scale Soil Moisture Retrieval Using PALSAR-2 Polarimetric Decomposition and Machine Learning

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 35
Author(s):  
Xiaodong Huang ◽  
Beth Ziniti ◽  
Michael H. Cosh ◽  
Michele Reba ◽  
Jinfei Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Canopy Cover ◽  
The United States ◽  
Optical Data ◽  
Study Region ◽  
Model Based ◽  
Key Indicator ◽  
Ground Measurement ◽  
L Band

Soil moisture is a key indicator to assess cropland drought and irrigation status as well as forecast production. Compared with the optical data which are obscured by the crop canopy cover, the Synthetic Aperture Radar (SAR) is an efficient tool to detect the surface soil moisture under the vegetation cover due to its strong penetration capability. This paper studies the soil moisture retrieval using the L-band polarimetric Phased Array-type L-band SAR 2 (PALSAR-2) data acquired over the study region in Arkansas in the United States. Both two-component model-based decomposition (SAR data alone) and machine learning (SAR + optical indices) methods are tested and compared in this paper. Validation using independent ground measurement shows that the both methods achieved a Root Mean Square Error (RMSE) of less than 10 (vol.%), while the machine learning methods outperform the model-based decomposition, achieving an RMSE of 7.70 (vol.%) and R2 of 0.60.

scholarly journals Effects of Soil Abiotic and Biotic Factors on Tree Seedling Regeneration Following a Boreal Forest Wildfire

Ecosystems ◽  
2021 ◽  
Author(s):  
Theresa S. Ibáñez ◽  
David A. Wardle ◽  
Michael J. Gundale ◽  
Marie-Charlotte Nilsson
Keyword(s):  
Boreal Forest ◽  
Betula Pendula ◽  
Fire Severity ◽  
Tree Regeneration ◽  
Soil Biota ◽  
Fire Disturbance ◽  
Burn Severity ◽  
Soil Conditions ◽  
Tree Seedling ◽  
Seedling Regeneration

AbstractWildfire disturbance is important for tree regeneration in boreal ecosystems. A considerable amount of literature has been published on how wildfires affect boreal forest regeneration. However, we lack understanding about how soil-mediated effects of fire disturbance on seedlings occur via soil abiotic properties versus soil biota. We collected soil from stands with three different severities of burning (high, low and unburned) and conducted two greenhouse experiments to explore how seedlings of tree species (Betula pendula, Pinus sylvestris and Picea abies) performed in live soils and in sterilized soil inoculated by live soil from each of the three burning severities. Seedlings grown in live soil grew best in unburned soil. When sterilized soils were reinoculated with live soil, seedlings of P. abies and P. sylvestris grew better in soil from low burn severity stands than soil from either high severity or unburned stands, demonstrating that fire disturbance may favor post-fire regeneration of conifers in part due to the presence of soil biota that persists when fire severity is low or recovers quickly post-fire. Betula pendula did not respond to soil biota and was instead driven by changes in abiotic soil properties following fire. Our study provides strong evidence that high fire severity creates soil conditions that are adverse for seedling regeneration, but that low burn severity promotes soil biota that stimulates growth and potential regeneration of conifers. It also shows that species-specific responses to abiotic and biotic soil characteristics are altered by variation in fire severity. This has important implications for tree regeneration because it points to the role of plant–soil–microbial feedbacks in promoting successful establishment, and potentially successional trajectories and species dominance in boreal forests in the future as fire regimes become increasingly severe through climate change.

scholarly journals Root Response to Soil Water Status via Interaction of Crop Genotype and Environment

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 708
Author(s):  
Phanthasin Khanthavong ◽  
Shin Yabuta ◽  
Hidetoshi Asai ◽  
Md. Amzad Hossain ◽  
Isao Akagi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Root Distribution ◽  
Water Status ◽  
Soil Layer ◽  
Shoot Biomass ◽  
Soil Conditions ◽  
Crop Adaptation ◽  
Soil Moisture Status ◽  
Root Distributions

Flooding and drought are major causes of reductions in crop productivity. Root distribution indicates crop adaptation to water stress. Therefore, we aimed to identify crop roots response based on root distribution under various soil conditions. The root distribution of four crops—maize, millet, sorghum, and rice—was evaluated under continuous soil waterlogging (CSW), moderate soil moisture (MSM), and gradual soil drying (GSD) conditions. Roots extended largely to the shallow soil layer in CSW and grew longer to the deeper soil layer in GSD in maize and sorghum. GSD tended to promote the root and shoot biomass across soil moisture status regardless of the crop species. The change of specific root density in rice and millet was small compared with maize and sorghum between different soil moisture statuses. Crop response in shoot and root biomass to various soil moisture status was highest in maize and lowest in rice among the tested crops as per the regression coefficient. Thus, we describe different root distributions associated with crop plasticity, which signify root spread changes, depending on soil water conditions in different crop genotypes as well as root distributions that vary depending on crop adaptation from anaerobic to aerobic conditions.

scholarly journals Impacts of soil moisture level and organic matter content on growth of two Juncus species and Poa pratensis grown under acid soil conditions

Weed Research ◽  
2019 ◽  
Vol 59 (6) ◽  
pp. 490-500
Author(s):  
W Kaczmarek‐Derda ◽  
M Helgheim ◽  
J Netland ◽  
H Riley ◽  
K Wærnhus ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Poa Pratensis ◽  
Acid Soil ◽  
Organic Matter Content ◽  
Matter Content ◽  
Moisture Level ◽  
Soil Conditions ◽  
Soil Moisture Level

The potentiation of zinc toxicity by soil moisture in a boreal forest ecosystem

2015 ◽  
Vol 34 (3) ◽  
pp. 600-607 ◽  
Author(s):  
Olugbenga J. Owojori ◽  
Steven D. Siciliano
Keyword(s):  
Soil Moisture ◽  
Boreal Forest ◽  
Forest Ecosystem ◽  
Zinc Toxicity

scholarly journals White Root Rot of Raspberries

1951 ◽  
Vol 4 (3) ◽  
pp. 211
Author(s):  
GC Wade
Keyword(s):  
Soil Moisture ◽  
Root Rot ◽  
Soil Moisture Content ◽  
Soil Conditions ◽  
Causal Organism ◽  
White Root Rot ◽  
High Soil Moisture ◽  
High Soil ◽  
Soil Temperatures ◽  
Dry Soil

The disease known as white root rot affects raspberries, and to a less extent loganberries, in Victoria. The causal organism is a white, sterile fungus that has not been identified. The disease is favoured by dry soil conditions and high soil temperatures. It spreads externally to the host by means of undifferentiated rhizomorphs; and requires a food base for the establishment of infection. The spread of rhizomorphs through the soil is hindered by high soil moisture content and consequent poor aeration of the soil.

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