Environmental Science and Engineering Seminar
Developing a better understanding of the spatial and temporal distribution of vegetation is important not only for terrestrial ecosystem science, but for climate science as well. In the first part of this talk I will describe some of my landscape-scale work, combining remotely sensed data from the Carnegie Airborne Observatory with field sampling and geostatistics to map and assess spatial patterns of vegetation. This work shows that while the 'static' environmental gradients typically used in global vegetation models are important drivers of plant patterns, dynamic processes like fire and human impacts are also critical to our understanding of why different plants grow in different places. In the second part of the talk I will describe some of the global-scale work I am now doing at NCAR, looking at how well the Community Land Model captures seasonal vegetation patterns in semi-arid ecosystems, and what we can do to improve model performance. Finally, I'll make a few comments about what it's been like to try to combine field ecology, remote sensing, and earth system modeling in a meaningful way.