scholarly journals Links between fluctuations in sockeye salmon abundance and riparian forest productivity identified by remote sensing

Ecosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
Author(s):  
Celeste N. Kieran ◽  
Debora S. Obrist ◽  
Nicolas J. Muñoz ◽  
Patrick J. Hanly ◽  
John D. Reynolds
Keyword(s):  
Remote Sensing ◽  
Sockeye Salmon ◽  
Riparian Forest ◽  
Forest Productivity

Integrating remote sensing and climate data with process-based models to map forest productivity within west-central Alberta's boreal forest: Ecoleap-West

2006 ◽  
Vol 82 (2) ◽  
pp. 159-176 ◽  
Author(s):  
R J Hall ◽  
F. Raulier ◽  
D T Price ◽  
E. Arsenault ◽  
P Y Bernier ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Management Practices ◽  
Forest Productivity ◽  
Process Models ◽  
Growth And Yield ◽  
Area Index ◽  
Study Region

Forest yield forecasting typically employs statistically derived growth and yield (G&Y) functions that will yield biased growth estimates if changes in climate seriously influence future site conditions. Significant climate warming anticipated for the Prairie Provinces may result in increased moisture deficits, reductions in average site productivity and changes to natural species composition. Process-based stand growth models that respond realistically to simulated changes in climate can be used to assess the potential impacts of climate change on forest productivity, and hence can provide information for adapting forest management practices. We present an application of such a model, StandLEAP, to estimate stand-level net primary productivity (NPP) within a 2700 km2 study region in western Alberta. StandLEAP requires satellite remote-sensing derived estimates of canopy light absorption or leaf area index, in addition to spatial data on climate, topography and soil physical characteristics. The model was applied to some 80 000 stand-level inventory polygons across the study region. The resulting estimates of NPP correlate well with timber productivity values based on stand-level site index (height in metres at 50 years). This agreement demonstrates the potential to make site-based G&Y estimates using process models and to further investigate possible effects of climate change on future timber supply. Key words: forest productivity, NPP, climate change, process-based model, StandLEAP, leaf area index, above-ground biomass

scholarly journals DIRECT ESTIMATION OF ABOVEGROUND FOREST PRODUCTIVITY THROUGH HYPERSPECTRAL REMOTE SENSING OF CANOPY NITROGEN

2002 ◽  
Vol 12 (5) ◽  
pp. 1286-1302 ◽  
Author(s):  
Marie-Louise Smith ◽  
Scott V. Ollinger ◽  
Mary E. Martin ◽  
John D. Aber ◽  
Richard A. Hallett ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Productivity ◽  
Hyperspectral Remote Sensing ◽  
Direct Estimation ◽  
Canopy Nitrogen

Linking ecophysiology and forest productivity: An overview of the ECOLEAP project

1999 ◽  
Vol 75 (3) ◽  
pp. 417-421 ◽  
Author(s):  
P. Y. Bernier ◽  
R. A. Fournier ◽  
C. H. Ung ◽  
G. Robitaille ◽  
G. R. Larocque ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Process Model ◽  
Spatial Databases ◽  
Net Primary Productivity ◽  
Forest Productivity ◽  
Forest Service ◽  
Service Research ◽  
Spatially Explicit ◽  
Quebec City ◽  
Environmental Controls

ECOLEAP is a Canadian Forest Service research project that is aimed at improving our understanding of the environmental controls on boreal and sub-boreal forest productivity and at developing tools for predicting stand-level forest productivity over large areas. This interdisciplinary project combines, in a coordinated manner, ecophysiological and soils research, remote sensing research, development of scaling up procedures and process modelling of net primary productivity on a common set of field sites. The process research is carried out in different forest types across large climatic and productivity gradients. Remote sensing provides timely stand information such as composition, leaf area, and absorbed radiation that are not currently available in existing spatial databases. A geographic information system is used to integrate the diverse sources of data. Models serve both as integrators of knowledge and as vehicles for the transfer of the information and methodologies to resource managers. Currently there are three interrelated modelling exercises being carried out within ECOLEAP to address different objectives of the project: an empirical, spatially explicit model of site index, a site-specific process model of productivity, and a spatially explicit process model of productivity. Application of the spatially explicit models will be conducted on extensive pilot regions, the first of which is located north of Quebec City. Key words: modelling, GIS, remote sensing, Canadian Forest Service

Desert riparian forest colonization in the lower reaches of Tarim River based on remote sensing analysis

2013 ◽  
Vol 71 (10) ◽  
pp. 4579-4589 ◽  
Author(s):  
Guilin Liu ◽  
Alishir Kurban ◽  
Huanming Duan ◽  
Umut Halik ◽  
Abdimijit Ablekim ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Riparian Forest ◽  
Tarim River ◽  
Desert Riparian Forest

scholarly journals Erratum to: Desert riparian forest colonization in the lower reaches of Tarim River based on remote sensing analysis

2013 ◽  
Vol 71 (10) ◽  
pp. 4591-4591
Author(s):  
Guilin Liu ◽  
Alishir Kurban ◽  
Hanming Duan ◽  
Umut Halik ◽  
Abdimijit Ablekim ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Riparian Forest ◽  
Tarim River ◽  
Desert Riparian Forest
Sign in / Sign up

Export Citation Format

Share Document