INCUBATION BEHAVIORS AND PATTERNS OF NEST ATTENDANCE IN COMMON GOLDENEYES IN INTERIOR ALASKA

The Condor ◽  
10.1650/7655 ◽  
2005 ◽  
Vol 107 (1) ◽  
pp. 167 ◽  
Author(s):  
Joshua H. Schmidt ◽  
Eric J. Taylor ◽  
Eric A. Rexstad
Keyword(s):  
Nest Attendance ◽  
Interior Alaska

Factors Influencing Nest Attendance and Time-activity Budgets of Peregrine Falcons in Interior Alaska

ARCTIC ◽  
2001 ◽  
Vol 54 (2) ◽  
Author(s):  
Angela G. Palmer ◽  
Dana L. Nordmeyer ◽  
Daniel D. Roby
Keyword(s):  
Nest Attendance ◽  
Activity Budgets ◽  
Time Activity ◽  
Interior Alaska ◽  
Factors Influencing ◽  
Peregrine Falcons

scholarly journals Incubation Behaviors and Patterns of Nest Attendance in Common Goldeneyes in Interior Alaska

The Condor ◽  
2005 ◽  
Vol 107 (1) ◽  
pp. 167-172 ◽  
Author(s):  
Joshua H. Schmidt ◽  
Eric J. Taylor ◽  
Eric A. Rexstad
Keyword(s):  
Environmental Variables ◽  
Nest Attendance ◽  
Northern Limit ◽  
Bucephala Clangula ◽  
Endogenous Factors ◽  
Incubation Behavior ◽  
Interior Alaska ◽  
Data Loggers ◽  
Common Goldeneye ◽  
Female Specific

AbstractWe hypothesized that nest attendance characteristics in Common Goldeneyes (Bucephala clangula) at the northern limit of their range differ from those of more southern populations. In 2002 and 2003, we used artificial eggs containing temperature-sensing data loggers to obtain nest attendance data from 20 incubating females over 515 days. On average (± SE), each female spent 79.8 ± 0.3% of the day on the nest, and took 2.9 ± 0.1 recesses per day, each averaging 100.7 ± 1.5 minutes. These recess characteristics were comparable to those reported for other Common Goldeneye populations. Most recesses (88%) occurred between 09:00 and 22:00 Alaskan Daylight Time although recesses were initiated at all times of day. Female incubation behavior does not appear to be strongly influenced by coarse-level environmental variables or the female-specific variables that we measured, but could be related to a complex assortment of fine-scale environmental or endogenous factors.Comportamientos de Incubación y Patrones de Permanencia en el Nido en Bucephala clangula en el Interior de AlaskaResumen. Hipotetizamos que las características de permanencia en el nido por parte de Bucephala clangula en el límite norte de su distribución difieren de aquellas de poblaciones más meridionales. A través de 515 días en 2002 y 2003, empleamos huevos artificiales que contenían medidores automáticos de temperatura para obtener datos sobre la permanencia en los nidos por parte de 20 hembras que estaban incubando. En promedio (±EE), las hembras pasaron el 79.8% ± 0.3% del día en el nido y tomaron 2.9 ± 0.1 descansos de 100.7 ± 1.5 minutos de duración diariamente. Estas características de descanso fueron comparables a las documentadas para otras poblaciones de B. clangula. La mayoría de los descansos (88%) se presentaron entre las 09:00 y 22:00, aunque las aves descansaron a toda hora del día. El comportamiento de incubación de las hembras no parece estar fuertemente influenciado por las variables ambientales que medimos a un nivel general, ni por variables específicas de las hembras, pero podría estar relacionado con una combinación compleja de factores ambientales a pequeña escala o por factores endógenos.

Potential for economical recovery of fuel from land clearing residue in interior Alaska.

1983 ◽  
Author(s):  
George R. Sampson ◽  
Forrest A. Ruppert
Keyword(s):  
Land Clearing ◽  
Interior Alaska

Combustion efficiency and emissions analysis for a school wood energy system in interior Alaska

2020 ◽  
Author(s):  
David L. Nicholls ◽  
Daisy Huang
Keyword(s):  
Energy System ◽  
Combustion Efficiency ◽  
Interior Alaska ◽  
Wood Energy

Geologic Map of Central (Interior) Alaska

1998 ◽  
Author(s):  
Frederic H. Wilson ◽  
James H. Dover ◽  
Dwight C. Bradley ◽  
Florence R. Weber ◽  
Thomas K. Bundtzen ◽  
...  
Keyword(s):  
Interior Alaska ◽  
Geologic Map

scholarly journals Effect of fire on dissolved organic carbon and inorganic solutes in spruce forest in the permafrost region of interior Alaska

2003 ◽  
Vol 49 (1) ◽  
pp. 25-29 ◽  
Author(s):  
Hideaki Shibata ◽  
Kevin C. Petrone ◽  
Larry D. Hinzman ◽  
Richard D. Boone
Keyword(s):  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Permafrost Region ◽  
Spruce Forest ◽  
Interior Alaska ◽  
Inorganic Solutes

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 Spatial variations in the growth rate of Hylocomium splendens and the thickness of the organic layer on a north-facing slope in Interior Alaska

Polar Science ◽  
2021 ◽  
pp. 100654
Author(s):  
Jumpei Toriyama ◽  
Tomoaki Morishita ◽  
Yojiro Matsuura ◽  
Kyotaro Noguchi
Keyword(s):  
Growth Rate ◽  
Spatial Variations ◽  
Organic Layer ◽  
Hylocomium Splendens ◽  
Interior Alaska

Comparative drought sensitivity of co‐occurring white spruce and paper birch in interior Alaska

2021 ◽  
Author(s):  
Patrick F. Sullivan ◽  
Annalis H. Brownlee ◽  
Sarah B.Z. Ellison ◽  
Sean M.P. Cahoon
Keyword(s):  
White Spruce ◽  
Drought Sensitivity ◽  
Interior Alaska ◽  
Paper Birch
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