Skip to main content
Advanced Search

Filters: Tags: correlation analysis (X)

2 results (10ms)   

View Results as: JSON ATOM CSV
This data release contains data used in an associated publication: Petrakis, R.E., Norman, L.M., Vaughn, K., Pritzlaff, R., Weaver, C., Rader, A., and Pulliam, H.R., 2021, Hierarchical Clustering for Paired Watershed Experiments: Case Study in Southeastern Arizona, U.S.A.: Water, v. 13, no. 21, p. 2955, The overarching effects and benefits of land management decisions, such as through watershed restoration, are often not fully understood due to a lacking control within an experimental design. This can be addressed through the application of a paired watershed approach, allowing for comparison between treatment and control watersheds. We developed and applied a statistic-based...
Climate change has significant effects on critical ecosystem functions such as carbon and water cycling. Vegetation and especially forest ecosystems play an important role in the carbon and hydrological cycles. Vegetation models that include detailed belowground processes require accurate soil data to decrease uncertainty and increase realism in their simulations. The MC2 DGVM uses three modules to simulate biogeography, biogeochemistry and fire effects, all three of which use soil data either directly or indirectly. This study includes a correlation analysis of the MC2 model to soil depth by comparing a subset of the model’s carbon and hydrological outputs using soil depth data of different scales and qualities....