University of Minnesota
University of Minnesota
College of Biological Sciences
http://www.cbs.umn.edu/

Experiments

Experiment 290 - Linking remotely sensed optical diversity to genetic, phylogenetic and functional diversity to predict ecosystem processes

Novel remote sensing methods for monitoring the Earth???s biodiversity will be applied to experimental manipulations of plant diversity???allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution.
We propose to test this hypotheses within the long-term prairie biodiversity experiment (Big Bio), the newly established Forest and Biodiversity (FAB) experiment, and the Biodiversity of Willows and Poplars (BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest.
The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.

Methods for e290

Datasets


Dataset IDTitleRange of Years (# years with data)