The timing of leaf senescence (coloring and subsequent fall; i.e., phenology) during autumn has potentially large impacts on energy and carbon exchange between mid-latitude land surfaces and the lower atmosphere. However, spatial variations in autumn phenological timing at the plant community level have not been widely measured or analyzed, and underlying environmental drivers are not well understood. Thus, detailed autumn phenological data offer considerable opportunities for assessing landscape-level spatial variations crucial for accurate scaling-up measurements to larger areas or downscaling information from atmospheric general circulation models. In this project, spatial variability of autumn phenological data will be measured and analyzed at the community level, compared to microclimatic, carbon flux, and remote sensing measurements, with an overall goal of contributing to increased accuracy of energy/carbon flux estimates at continental to global scales.
This project will address issues that are significant for advancement across the fields of climatology, plant physiology, ecology, and remote sensing. The nature of autumn phenological variability in space and time has not been previously recorded over a large area and combined with supporting measurements. Results from recent studies strongly suggest that understanding stand-level (~50 x 50 m) spatial patterns of autumn plant phenological development (and the environmental processes that drive them) will provide key knowledge needed to improve landscape level estimates of carbon accumulation across the entire growing season when combined with existing data for spring phenology. The spatially concentrated phenological measures produced by this project will provide future near-surface and satellite-derived remote sensing studies with a record of autumn plant development and growth involving species differences, spatial variability, and precise event timing that has not been recorded in the past. Overall, the results of this project will contribute to better understanding of the impacts of climate change on the biosphere, which will increase knowledge of potential future changes, and may allow for better planning relative to societal impacts of anticipated forest vegetation change.
Phenology is the study of recurring plant and animal life cycle stages (i.e., first spring leaves, fall leaf coloring, or return of migrating birds), especially their timing and relationships with weather and climate. Studying these changes in plants during spring and autumn improves understanding of the relationships among plant growth, temperatures, and other environmental factors that affect growing season length. Such information contributes to better understanding of potential climate change (atmospheric) impacts on the biosphere (living things), which will increase knowledge, and may allow for better societal planning. However, complicating this goal, plant phenology is measured in a variety of ways, each with particular advantages. Combinations are beneficial, but many of the measurement types are not readily comparable without effort. This project expanded on previous successful work (conducted near the WLEF/Park Falls Ameriflux tall tower, 45.946°N, 90.272°W) to characterize the connections among satellite-derived measures (which combine information over large areas), traditional surface data (systematically recorded by ground-based observers for large numbers of individual trees), and instrumental measurements of carbon flux (which indicate composite photosynthesis-driven responses of all plants) during spring leaf development to the autumn leaf senescence period, thus allowing characterization of these interrelationships at both ends of the growing season. Spatial variations in ground-based autumn phenological timing (leaf coloring and leaf drop) have not previously been systematically measured and analyzed, and underlying environmental drivers (temperature, day length, moisture stress, etc.) are not well understood. The results of this project demonstrated that satellite-derived measurements of phenology (MODIS sensor-based vegetation indices) are able to estimate ground-based autumn observations of tree full leaf coloration and full leaf fall timing successfully. These findings support the usefulness of MODIS data for monitoring autumn phenology in mixed forests. Similar studies replicated in other vegetated environments are needed for more comprehensive validation of satellite-derived autumn phenology. The results also showed the considerable variations in the progression of annual leaf coloring/fall among major tree species, and the confounding issues regarding environmental drivers of leaf coloring/fall in autumn. Lastly, the results showed progress in understanding how to utilize techniques that allow good correlations among concurrent acquisitions of under-canopy light sensor measurements, visually recorded (ground-based) autumn tree phenology, and end of Autumn/Fall dates derived from eddy covariance system carbon flux measurements. Overall, this study suggests an effective approach for building more reliable phenological monitoring systems by linking remote sensing and ground-based observations during the crucial, but less studied autumn season, and provides the foundations for on-going and future investigations into autumn phenological measurements and relationships.
