Young students, satellites aid understanding of climate‐biosphere link

Abstract

Data collected by young students from kindergarten through high school are being combined with satellite data to develop a more consistent understanding of the intimate connection between climate dynamics and the terrestrial biosphere. Comparison of the two sets of data involving the onset of budburst among trees and other vegetation has been extremely encouraging. Surface‐atmosphere interactions involving exchanges of carbon, water, and energy are strongly affected by interannual variability in the timing and length of the vegetation growing season, and satellite remote sensing has the unique ability to consistently monitor global spatiotemporal variability in growing season dynamics. But without a clear picture of how satellite information (Figure 1) relates to ground conditions, the application of satellite growing season estimates for monitoring of climate‐vegetation interactions, calculation of energy budgets, and large‐scale ecological modeling is extremely limited.The integrated phenological analysis of field data, satellite observations, and climate advocated by Schwartz [1998], for example, has been primarily limited by the lack of geographically extensive and consistently measured phenology databases.

Changes in North American spring

“…Thus, these trends merit careful watching for future developments. Our results underline the utility of phenological data and models for regional, continental and global change studies, as well as the critical need for global-scale surface observation networks to complement satellite sensor-derived data (Myneni et al, 1997;Schwartz, 1998Schwartz, , 1999Schwartz and Reed, 1999;White et al, 2000).…”

Assessing satellite‐derived start‐of‐season measures in the conterminous USA

“…Figure 1 shows the process by which SOS and end of the growing 02 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Year Mean annual NDVI season (not used here) are predicted. The SMN method, though quite simple, has been shown to be related to initial leaf expansion of the broad leaf forest overstory in New England (White et al, 1997), the Global Observations to Benefit the Environment phenology project (White et al, 1999b), and deciduous forests in France (Bondeau et al, 2000). The SMN threshold, as shown in Figure 1, is defined as the average of the nine annual seasonal midpoint NDVIs.…”

“…The SMN methodology employs techniques originally developed by White et al (1997) and subsequently modified (White et al, 1999b(White et al, , 2002. Figure 1 shows the process by which SOS and end of the growing 02 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Year Mean annual NDVI season (not used here) are predicted.…”

“…A second approach is to use conventional native plant phenological data, which are observations of specific events in individual species at selected sites, such as bud-burst or first flower bloom. These events offer improved temporal resolution, and detailed information on interspecies dynamics at specific sites, but have limited spatial coverage (Menzel and Fabian, 1999;White et al, 1999b;Rötzer and Chmielewski, 2001). A third approach is to develop climate data-driven phenological models based on cloned (genetically identical) plant event data for a few 'indicator' species that are adaptable to a wide range of climates.…”

Diurnal Soil Temperature Effects within the GLOBE® Program Dataset

“…GLOBE R is a worldwide, hands-on, primary and secondary school-based education and science program that allows for data collection and entry into an Internet database. Data range from land cover mapping and phenology (Bombaugh et al 2000;Sparrow 2001), water quality (Clemmons 2000), atmospheric variables (White et al 2000;Brooks and Mims 2001), and characteristics of soil such as temperature, moisture, and texture. These data are collected by a network of classrooms spanning the globe using protocols developed and standardized by scientists in their respective fields of study.…”