Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century

Abstract

Phenology is the study of recurring life‐cycle events, classic examples being the flowering of plants and animal migration. Phenological responses are increasingly relevant for addressing applied environmental issues. Yet, challenges remain with respect to spanning scales of observation, integrating observations across taxa, and modeling phenological sequences to enable ecological forecasts in light of future climate change. Recent advances that are helping to address these questions include refined landscape‐scale phenology estimates from satellite data, advanced, instrument‐based approaches for field measurements, and new cyberinfrastructure for archiving and distribution of products. These breakthroughs are improving our understanding in diverse areas, including modeling land‐surface exchange, evaluating climate–phenology relationships, and making land‐management decisions.

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

“…From the perspective of global change science, the results presented here are important because (1) phenology is sensitive to climate change and variability; and (2) phenology controls many vegetation feedbacks to the climate system (Morisette et al, 2009). Analyses of diverse data sets provide compelling evidence for phenological shifts toward earlier spring onset and delayed autumn senescence over the last four decades (Peñ uelas et al, 2002;Badeck et al, 2004;Schwartz et al, 2006;Parmesan, 2007;Parry et al, 2007).…”

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

“…Visible light digital cameras are increasingly being used in environmental sensing (Hamilton et al, 2007;Morisette et al, 2009;Porter et al, 2009). Automatic image segmentation by thresholding is a commonly used image processing technique in ecological applications (Cescatti, 2007;Graham et al, 2009).…”

“…Automatic image segmentation by thresholding is a commonly used image processing technique in ecological applications (Cescatti, 2007;Graham et al, 2009). Simple image processing techniques are making standard the use of digital cameras for the detection of plant phenological events (Crimmins and Crimmins, 2008;Graham et al, 2009, in press;Morisette et al, 2009;Richardson et al, 2009) as well as for automating a range of agricultural monitoring practices (Jia et al, 2004;Slaughter et al, 2008). The uses of cameras in these studies have been primarily based on the color reflectance of plants.…”

Long-Term Detection of Global Vegetation Phenology from Satellite Instruments

“…These products include: (1) the MODIS Land Cover Dynamics Product (MCD12Q2) derived from MODIS NBAR (nadir bidirectional reflectance distribution function adjusted reflectance) EVI (enhanced vegetation index) (500m-1000m), which is the only global product that is produced on an operational basis from 2001 to present Ganguly et al, 2010); (2) the MODIS-based product generated at NASA-GSFC (Goddard Space Flight Center) in support of the North American Carbon Program, which was produced using MODIS data at a spatial resolution of 250m-500m (Morisette et al, 2009;Tan et al, 2011); (3) the MODIS phenology product being generated for the contiguous United States (CONUS) by the US Forest Service (Hargrove et al, 2009); (4) the USGS long-term 1-km AVHRR phenology product for CONUS (1989-present;Reed et al, 1994); (5) the NOAA 4-km GVIx phenology over North America from 1982(Zhang et al, 2007; (6) the global 4.6 km product for 2005 from the Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) (Dash et al, 2010); and (6) the global product based on FPAR (Fraction of Photosynthetically Active Radiation) developed by the European Space Agency (Verstraete et al, 2008).…”