Forest Sciences
http://hdl.handle.net/11122/13100
2024-03-28T11:23:05ZRemote sensing aspen leaf miner (Phyllocnistis populiella chamb) infestations near Ester Dome in Fairbanks, Alaska
http://hdl.handle.net/11122/12845
Remote sensing aspen leaf miner (Phyllocnistis populiella chamb) infestations near Ester Dome in Fairbanks, Alaska
Smart, Douglas D.
"Mapping trembling aspen stands (Populous tremuloides Michx.) versus Alaskan birch (Betula neoalaskana Sarg.) in interior Alaska is possible as a byproduct of remote sensing aspen leaf miner (Phyllocnistis populiella Chamb.) damage. P. populiella is a defoliator of trembling aspen that has been observed in epidemic proportions in Alaska since 2001. Where it is observed it is ubiquitous. Unlike most remote sensing studies of insect damage, I found no significant change in the near-infrared related to leaf miner damage. The feeding morphology of P. populiella is different from most other leaf defoliating insects. P. populiella feeds only in the epidermal tissue of aspen leaves whereas most other leaf mining insect pests consume mesophyll tissue. This means that P. populiella causes no significant change in near-infrared reflectance whereas most other defoliators do. This lack of change in near-infrared range coupled with the timing of leaf miner foraging can be used to discriminate P. populiella damage from that of other leaf defoliators. The ability to remotely sense damage in aspen stands provides an opportunity to identify P. tremuloides in locations where damage is epidemic. If new image acquisition and historic image purchases are timed to correspond with P. populiella outbreak conditions, it will be possible to identify areas that are P. tremuloides stands and not other species"--Leaf iii
Thesis (M.S.) University of Alaska Fairbanks, 2008
2008-12-01T00:00:00ZSensitivity of boreal forest carbon dynamics to long-term (1989-2005) throughfall exclusion in Interior Alaska)
http://hdl.handle.net/11122/12839
Sensitivity of boreal forest carbon dynamics to long-term (1989-2005) throughfall exclusion in Interior Alaska)
Runck, Sarah A.
"The objective of this study was to assess the effect of throughfall exclusion (1989-2005) on forest vegetation and soil in upland and floodplain landscape positions. In uplands, imposed drought reduced soil moisture at 5, 10, and 20 cm depths and increased soil C storage by slowing decomposer activity at the surface. In the drought plots, aboveground tree growth was reduced and root biomass in mineral soil was increased. In floodplains, imposed drought did not reduce soil moisture as strongly as it did in uplands, though near-surface soil C storage was still increased as a result of reduced decomposer activity. Floodplain vegetation response to imposed drought differed from that of uplands; imposed drought did not reduce aboveground tree growth but instead reduced root biomass in mineral soil. At both landscape positions, imposed drought accelerated the loss of understory vegetation. Overall, the results of the throughfall exclusion indicated that chronic soil drying is likely to increase forest C storage only in floodplains. In uplands, where soil moisture is more limited, forest C storage is not as likely to change because an increase in soil C may be offset by reduced tree growth"--Leaf iii
Thesis (M.S.) University of Alaska Fairbanks, 2008
2008-12-01T00:00:00ZRemote sensing of browning trends in the Alaskan boreal forest
http://hdl.handle.net/11122/12687
Remote sensing of browning trends in the Alaskan boreal forest
Parent, Mary Elizabeth
Vegetation health can be monitored using a time series of remotely sensed images by calculating the Normalized Difference Vegetation Index (NDVI). We assessed temporal trends throughout an NDVI time series with three sensors: Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+). There has been debate over the reliability of AVHRR sensor NDVI data in the circumboreal region. Therefore, the purpose of this paper was to first use MODIS and Landsat TM/ETM+ data and assess declining trends within twelve Landsat scene footprints across boreal Alaska and second use Landsat TM/ETM+ data to assess NDVI trends at a stand-level in eastern boreal Alaska. For the first objective, there were significant (p-value <0.05) declining trends in eastern boreal Alaska and no significant trends in the western region due to an east-west climate gradient. For the second objective, there were significant declining trends scattered across our two research areas. It was determined that many factors need to be included when determining where declining stands in NDVI are located such as site climate, site landscape position and other unique site conditions.
Thesis (M.S.) University of Alaska Fairbanks, 2011
2011-12-01T00:00:00ZSpatial and temporal trends in vegetation index in the Bonanza Creek Experimental Forest
http://hdl.handle.net/11122/11328
Spatial and temporal trends in vegetation index in the Bonanza Creek Experimental Forest
Baird, Rebecca A.
Climate has warmed substantially in boreal Alaska since the mid-1970s. The direct effects of rising temperatures on sub-Arctic ecosystems are already being observed in the form of drought stress, increased fire frequency and severity, and increased frequency and severity of herbivorous insect outbreaks. These effects of climate change are having a direct impact on the vegetation of the boreal forest and leading to a decreased remotely sensed normalized difference vegetation index (NDVI), which is an effective proxy for landscape-scale plant productivity and photosynthesis. Therefore, NDVI is a useful tool to examine landscape-scale changes in vegetation over time, especially in the context of known climate change. The overarching goal of my research was to assess the change in vegetation index at multiple scales over a period of 23 years at Bonanza Creek Experimental Forest. I used a combination of remote sensing and field sampling to examine trends in NDVI across landscape units, topographic classes, and plant communities. My project consists of two main parts: 1) Create a floristically-based landcover classification through field sampling and incorporating the field data into a map using satellite imagery and 2) Examine trends in the vegetation index using 11 Landsat TM and ETM+ images from 1986-2009. By using Landsat imagery and doing a landcover classification of my study area I was able define trends in NDVI to specific landscape units, topographic classes, and plant communities in the study area.
Thesis (M.S.) University of Alaska Fairbanks, 2011
2011-08-01T00:00:00Z