Name
Abstract | ||
|---|---|---|
Assessing the effects of human land use and management decisions requires an understanding of how temporal changes in biodiversity influence the rate of ecosystem functions and subsequent delivery of ecosystem services. In highly modified anthromes, the spatial distribution of natural vegetation types is often unknown or coarsely represented challenging comparative analyses seeking to assess changes in biodiversity and potential downstream effects on ecosystem processes and functions. In this context, the objectives of this study were to construct a multi-resolution representation of potential natural vegetation at four hierarchical classification levels of increasing floristic and physiognomic detail for the state of Minnesota, USA. Using a collection of natural/near-natural vegetation relevés, a series of Random Forest classification models were used to project the potential distribution of natural vegetation types based on their association with a variety of environmental variables. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.ecoinf.2017.07.006 | Ecological Informatics |
Keywords | Field | DocType |
MN,MN DNR,LCLUC,PNV,RF,NMDS,m,C,CV | Biodiversity,Ecology,Vegetation,Ecosystem services,Multidimensional scaling,Computer science,Potential natural vegetation,Ecosystem model,Ecosystem,Land use | Journal |
Volume | ISSN | Citations |
41 | 1574-9541 | 1 |
PageRank | References | Authors |
0.37 | 3 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seth R. Fore | 1 | 1 | 0.37 |
| Michael J. Hill | 2 | 42 | 12.10 |