B44A-01 INVITED 16:00h
Future Phenology: Challenges for an Integrative Environmental Science
Phenology is an interdisciplinary environmental science, and as such brings together individuals from many different scientific backgrounds, but the full benefits of their combined disciplinary perspectives to enrich phenological research have yet to be realized. The last few years have seen rapid progress in the transmission of "phenological perspectives" into the mainstream of science, especially related to the needs of global change research. While other parts of phenological research are still important and need to progress, it is global change science that will stimulate, challenge, and transform the discipline of phenology most in the coming decades. In order to maximize the benefits of phenology for global change research as rapidly as possible, commitments to integrative thinking and large-scale data collection must be accelerated. First of all, the limitations of the primary forms of data collection (remote sensing derived, native species, cloned indicator species, and model output) must be accepted. None of these data sources can meet the needs of all research questions, and an "integrative approach" that combines data types provides synergistic benefits. The most needed data are traditional native and cloned plant species observations. Networks that select a small number of common plants for coordinated observation among national and global scale networks will prove the most useful. These networks should be embraced and integrated into the missions of national weather services around the world, as is now the case in many European countries. A little more than one hundred years ago, the countries of the world began to cooperate in a global-scale network of weather and climate monitoring stations. The results of this long-term investment are the considerable progress that has been made in understanding the workings of the earth's climate systems. We have a similar opportunity with phenological data--small investments in national and global-scale observation networks are crucial to global change science, and will yield an impressive return in the years ahead.
B44A-02 16:30h
A strategy for global phenological observatories
We propose and implement a cluster-based approach for identifying global phenological observatories in which phenologically and climatologically self-similar pixel clusters are monitored. We developed clusters based on a wavelet-filtered subset of the 1982-1999 global Pathfinder Advanced Very High Resolution Radiometer (AVHRR) Land (PAL) Normalized Difference Vegetation Index (NDVI) dataset, a global 10-minute resolution climatology, and the clustering approach developed by the Oak Ridge National Laboratories (ORNL). In the ORNL approach: (1) n cluster centers are defined based on the multi-dimensional NDVI/climate space; (2) pixel distances from the centroids are calculated; (3) pixels are assigned to the minimum distance cluster. While any number of clusters may be specified, we found that a global 500-cluster approach provided a satisfactory global distribution. In traditional rectangular approaches a group of pixels could contain desert, grassland, and tropical forest. Here, longitudinally extensive but latitudinally limited regions such as the Sahel exist as distinct groups. Thus, our approach avoids problems affecting single-pixel approaches (misregistration, cloud contamination) and rectangular approaches (mixed phenological signals). Using the 1982-2003 GIMMS AVHRR dataset, we extracted phenological metrics such as the onset and offset of greenness for each cluster. We then ranked each cluster based on land cover homogeneity, evidence of human impacts, and political diversity. For each biome, we then identified the highest ranked clusters within four climate zones (hot/wet, hot/dry, cold/wet, cold/dry). This strategy provides: (1) selection of regions for which a strong annual is detectable, (2) a method of identifying regions least likely to be impacted by non-climatic factors, and (3) a strategy for ground validation.
B44A-03 16:45h
Monitoring Phenological Trends From Satellite Imagery
While there is convincing evidence that global climate change is taking place, there is still considerable controversy over the magnitude and consequences of any changes. One of the primary manifestations of climate change is the effect on patterns of vegetation growth; the timing of the growing season, the vigor of vegetation, and vegetation composition. The satellite data record provides an objective view of vegetation activity by measuring surface reflectance values at regular time intervals. Time-series analyses of satellite data can provide information on emerging trends of vegetation dynamics that may be related to global change. The objective of this project is to conduct a trend analysis of vegetation dynamics in the conterminous United States, as measured by satellite data, to assess regions of changing vegetation activity, and to evaluate the regions to determine the driving forces of these changes. To assess vegetation dynamics we analyze phenological metrics (e.g., time of start of season , end of season, duration of season, and seasonally integrated greenness) derived from satellite data and evaluate trends in these metrics by studying the climate record, agricultural statistics, and land cover data bases to assess the driving forces of the trends. The types of trends that we identify include trends toward earlier/later start and end of season, longer/shorter growing seasons, and greater/lesser vegetation production. Early results indicate geographically specific drivers across various ecoregions of the US.
B44A-04 17:00h
Regional Climate Change Influences Frequency of Frost Damage via Changes in Phenology: Effects of the North Pacific Oscillation (Pacific Decadal Oscillation) on Rocky Mountain Wildflowers
There is a significant correlation (P = .049) between the state of the North Pacific Oscillation (Pacific Decadal Oscillation) and the amount of winter snowfall at the Rocky Mountain Biological Laboratory (2,800m in the Colorado Rocky Mountains). The 1998 change of this inter-decadal mode of variability of the north Pacific atmosphere system to a dry phase has resulted in decreased snowpack, reversing a trend for increasing snowfall since the previous phase change in 1976. The seasonal timing (phenology) of plant growth and flowering at high altitudes is determined almost entirely by the timing of spring snowmelt, even for species that flower at the end of the season, and the decreased snowpack since 1998 combined with warming air temperatures has resulted in significantly earlier initiation of the growing season and subsequent flowering. Flowering in 2002, for example, was the earliest recorded during my 31-year study, and probably the earliest since at least 1935. Frost (with temperatures as low as -6 or -7°C) is still likely to occur as late as mid-June, however, and a consequence of the earlier beginning of the growing season is that many species have developed sensitive flower buds or other tissues by mid-June that are likely to be killed by frost. From 1994-1998 the average percentage of flower buds of Helianthella quinquenervis (Asteraceae; aspen sunflower) killed by frost was 26 percent(range 0-81), but since the 1998 NPO phase change a mean of 75 percent of flower buds have been killed (range 0-100; over 90 percent for each of the past four years). The loss of flowers from these frosts has consequences for plant demography (fewer seeds results in fewer seedlings), pollinators (which have fewer floral resources), seed predators (e.g., tephritid flies), and parasitoids (e.g., wasps, which have fewer seed predators to parasitize). A suite of wildflower species whose flowering abundance is positively correlated with the amount of winter snowfall has also produced fewer flowers since 1998, potentially exacerbating the effects of frost. Thus this regional climate event appears to be having ecosystem-wide consequences in the Colorado Rocky Mountains. Given the 50-75 year cycle length of the NPO, this area may be at the beginning of a decades-long change in snowfall that will reinforce the effects of global climate warming and result in significant ecosystem responses.
B44A-05 17:15h
Land Surface Phenologies in the North American Great Plains: Detecting Climate Change Amidst Climate Variation
The continental climate of the North American Great Plains is characterized by high interannual variability in growing season weather. Local averages of temperature and precipitation are not very helpful for predicting expected growing season conditions for vegetation production. We examined the temperature and precipitation records from a network of 'sentinel' weather stations across Kansas, Nebraska, and South Dakota. We assigned these stations into one or more of Wendland and Bryson's airstream regions (ASRs). For each station for each year, we calculated the day of year that the accumulated growing degree-days using a base of 0 oC reaches particular thermal thresholds. We call these Threshold Arrival Dates (TADs). Within each ASR we analyzed the station time series of TADs for two thermal thresholds--at the beginning and at the middle of the growing season for C4 grasses--using 30 year moving averages and Mann-Kendall trend tests. We found that the interannual variation of the onset of the growing season for C4 has increased over the period of record and especially in the last 30 years. At the same time, the central tendencies of the TADs have not changed significantly over the period of record. We also analyzed the TAD series using frequency domain analyses to identify characteristic periodicities. The spectral densities of the TADs point to possible linkages with climate modes. Finally, using the NASA Pathfinder AVHRR Land NDVI dataset, we demonstrate how to interpret the land surface phenologies revealed by synoptic sensors within the broader context of the regions' climatic envelopes.
B44A-06 INVITED 17:30h
Changes in Winegrape Phenology and Relationships with Climate and Wine Quality
During the phenological cycle of winegrapes, the timing of specific events and the length between the events are critical to the production of quality fruit and wine. In addition, winegrapes are typically grown in climates that optimize the ripening characteristics for specific varieties. These narrow geographical zones place the production of wine at a greater risk from climate variability and change than other more broadly based agricultural crops. To analyze the relationships between phenology, climate, and wine quality, data from three prominent regions in France-Bordeaux, Burgundy, and Champagne-are used. Long-term phenological data for bud break, flowering, veraison, and harvest dates for Pinot Noir in Burgundy and Champagne and for Merlot and Cabernet Sauvignon are examined for trends, climatic influences, and the general effects on wine quality. The results reveal significantly earlier events (6-14 days) with shorter intervals between events (5-12 days) across all regions. In addition, warmer growing seasons have clearly influenced these changes in the phenological cycle of winegrapes in France. Furthermore, changes in phenology and growing season temperatures are related to better fruit composition and increases in vintage ratings over the last 30-40 years. However, some of the warmest growing seasons, with very early phenology and short intervals, have resulted in lower quality. The results point to potential threshold issues whereby any further warming will likely compromise the phenological characteristics, ripening profiles, and wine quality of the varieties currently being grown.
B44A-07 17:45h
A generalized, bioclimatic index to predict foliar phenology in response to climate
The phenological state of vegetation significantly affects exchanges of heat, mass, and momentum between the Earth's surface and the atmosphere. Although current patterns can be estimated from satellites, we lack the ability to predict future trends in response to climate change. We searched the literature for a common set of variables that might be combined into an index to quantify the greenness of vegetation throughout the year. We selected as variables: daylength (photoperiod), evaporative demand (vapor pressure deficit), and suboptimal (minimum) temperatures. For each variable we set threshold limits, within which the relative phenological performance of the vegetation was assumed to vary from inactive (0) to unconstrained (1). A combined Growing Season Index (GSI) was derived as the product of the three indices. Ten-day mean GSI values for nine widely dispersed ecosystems showed good agreement (r $<$ 0.8) with the satellite-derived Normalized Difference Vegetation Index (NDVI). We also tested the model at a temperate deciduous forest by comparing model estimates to average field observations of leaf flush and leaf coloration. The mean absolute error of predictions at this site was 3 days for average leaf flush dates and 2 days for leaf coloration dates. Finally, we used this model to produce a global map that distinguishes major differences in regional phenological controls. The model appears sufficiently robust to reconstruct historical variation as well as to forecast future phenological responses to changing climatic conditions.