Datasets

subject: Climate Change date: 2019

Total is 11 Results
Distributional shifts of regional forest communities in the eastern United States

10.4231/831Y-Z846

Christopher M. Oswalt , Jonathan Knott , Michael A. Jenkins , Songlin Fei ORCID logo

12/10/2019

This dataset contains the distribution of forest communities across the eastern United States at T1 (1980-1995) and T2 (2015-2017) and the species comprising these communities.

Climate Change Forest Inventory and Analysis Forestry and Natural Resources Latent Dirichlet Allocation Regional Forest Communities Spatial Shifts Tree Migration

Responses of dominant tree-mycorrhizal associations to anthropogenic impacts in the USA

10.4231/R76D5R7S

Insu Jo , Songlin Fei ORCID logo

03/12/2019

Data published here are used to understand anthropogenic influences on tree mycorrhizal associations in USA forests

Climate Change Forest Forestry and Natural Resources Mycorrhizal Nutrient cycling

Distributional shifts of regional forest communities in the eastern United States

10.4231/F0BT-GN15

Christopher M. Oswalt , Jonathan Knott , Michael A. Jenkins , Songlin Fei ORCID logo

07/24/2019

This dataset contains the distribution of forest communities across the eastern United States at T1 (1980-1995) and T2 (2015-2017) and the species comprising these communities.

Climate Change Forest Inventory and Analysis Forestry and Natural Resources Latent Dirichlet Allocation Regional Forest Communities Spatial Shifts

Microbial decomposition processes and vulnerable arctic soil organic carbon in the 21st century

10.4231/ANMV-J384

Junrong Zha , Qianlai Zhuang ORCID logo

07/25/2019

Various levels of representations of biogeochemical processes in current biogeochemistry models contribute to uncertainty in carbon budget quantification. Detailed microbial mechanisms were incorporated into TEM 5.0 (Terrestrial Ecosystem Model).

Arctic Region Biogeochemistry Carbon Dynamics Climate Change EAPS Earth and Atmospheric Sciences Microbial-Based Model Terrestrial Ecosystem Model (TEM)

Modeling the Sea Level Changes in Guam

10.4231/0A0F-7A84

Avnika Manaktala ORCID logo

10/14/2019

This project works on understanding the different statistical models that are available to analyze and predict mean sea level changes in Guam.

Climate Change Data Education Earth and Atmospheric Sciences FAIR Data Machine Learning Sea level rise Statistical analysis Statistical Methods

Display #

Results 1 - 10 of 11