Chapter 7 Vegetation Dynamics of Yellowstone's Grazing System

Theme Primary production in Yellowstone National Park is constrained by long winters to a short, intense growing season characteristic of high-altitude, temperate environments. In systems like this, vegetation phenology plays a governing role in terrestrial herbivore ecology by determining temporal fluctuations in the quantity and quality of forage. Phenology and productivity vary considerably at the patch level, and this spatio-temporal heterogeneity in the forage base provides much of the impetus for the distributions and movement patterns of the dominant herbivores that structure this system (Frank et al. 2002, Gates et al. 2005). Phenology and productivity are modulated by climate variability and disturbances, thereby providing the trophic link between these exogenous influences and animal populations. The growing collection of fine-scale, spatial datasets describing animal locations and landscape attributes, coupled with increasingly sophisticated modern scientific analyses, allow a fuller understanding of wildlife-vegetation interactions at the patch scale. Similarly, population studies also benefit from a better understanding of the variations in phenological patterns and overall productivity at regional scales. Using the normalized difference vegetation index (NDVI) derived from daily satellite imagery spanning July 1, 2000 to December 31, 2006, we generated phenological profiles that characterize the dynamic patterns of vegetation green-up and senescence at the large-patch scale ( ca. 250 m). We used these seasonal profiles to describe the vegetation dynamics of Yellowstone's grasslands and shrub-grasslands, paying particular attention to patterns of spring green-up.

[1]  Douglas A. Frank,et al.  CONSUMER CONTROL OF GRASSLAND PLANT PRODUCTION , 2002 .

[2]  S. McNaughton,et al.  The Ecology of Plants, Large Mammalian Herbivores, and Drought in Yellowstone National Park , 1992 .

[3]  C. Tucker,et al.  North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer , 1985, Vegetatio.

[4]  Y. Yamaguchi,et al.  Global correlation analysis for NDVI and climatic variables and NDVI trends: 1982-1990 , 2002 .

[5]  Mark D. Schwartz,et al.  Assessing satellite‐derived start‐of‐season measures in the conterminous USA , 2002 .

[6]  George Wittemyer,et al.  Breeding phenology in relation to NDVI variability in free‐ranging African elephant , 2007 .

[7]  N. Pettorelli,et al.  Using a proxy of plant productivity (NDVI) to find key periods for animal performance: the case of roe deer , 2006 .

[8]  Jesslyn F. Brown,et al.  Measuring phenological variability from satellite imagery , 1994 .

[9]  Douglas A. Frank,et al.  The ecology of the earth's grazing ecosystems: Profound functional similarities exist between the Serengeti and Yellowstone , 1998 .

[10]  S. E. Alexander,et al.  Optimal sampling schemes for estimating mean snow water equivalents in stratified heterogeneous landscapes , 2006 .

[11]  Nathalie Pettorelli,et al.  Early onset of vegetation growth vs. rapid green-up: impacts on juvenile mountain ungulates. , 2007, Ecology.

[12]  D. Rubenstein,et al.  Herbivore-initiated interaction cascades and their modulation by productivity in an African savanna , 2007, Proceedings of the National Academy of Sciences.

[13]  A. Mysterud,et al.  Plant phenology, migration and geographical variation in body weight of a large herbivore: the effect of a variable topography , 2001 .

[14]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[15]  C. Russell Seasonal Migration of Mule Deer , 1932 .

[16]  O. W. Archibold Ecology of World Vegetation , 1994, Springer Netherlands.

[17]  C. Justice,et al.  Analysis of the phenology of global vegetation using meteorological satellite data , 1985 .

[18]  T. Seastedt,et al.  Detritus Accumulation Limits Productivity of Tallgrass PrairieThe effects of its plant litter on ecosystem function make the tallgrass prairie unique among North American biomes , 1986 .

[19]  J. Eisenberg,et al.  Serengeti: Dynamics of an Ecosystem , 1980 .

[20]  C. Dormann,et al.  Trading forage quality for quantity? Plant phenology and patch choice by Svalbard reindeer , 2000, Oecologia.

[21]  M. D. Fleming,et al.  Characteristics of vegetation phenology over the Alaskan landscape using AVHRR time-series data , 1995, Polar Record.

[22]  S. Hess Aerial survey methodology for bison population estimation in Yellowstone National Park , 2002 .

[23]  G. Dedieu,et al.  Global-Scale Assessment of Vegetation Phenology Using NOAA/AVHRR Satellite Measurements , 1997 .

[24]  Cleveland P. Hickman,et al.  Integrated Principles of Zoology , 1970 .

[25]  M. Boyce Migratory behavior and management of elk (Cervus elaphus) , 1991 .

[26]  N. Pettorelli,et al.  Using the satellite-derived NDVI to assess ecological responses to environmental change. , 2005, Trends in ecology & evolution.

[27]  Per Jönsson,et al.  Seasonality extraction by function fitting to time-series of satellite sensor data , 2002, IEEE Trans. Geosci. Remote. Sens..

[28]  Sharon E. Nicholson,et al.  On the relation between rainfall and the Normalized Difference Vegetation Index for diverse vegetation types in East Africa , 1993 .

[29]  D. Wester,et al.  Phenological Effects on Forage Quality of Five Grass Species , 2004 .

[30]  D. Lloyd,et al.  A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery , 1990 .

[31]  D. Brown,et al.  Spatial patterns of primary productivity in the Greater Yellowstone Ecosystem , 2000, Landscape Ecology.

[32]  N. Pettorelli,et al.  The relative role of winter and spring conditions: linking climate and landscape-scale plant phenology to alpine reindeer body mass , 2005, Biology Letters.

[33]  R. White Foraging patterns and their multiplier effects on productivity of northern ungulates , 1983 .

[34]  A. Anyamba,et al.  Interannual variability of NDVI over Africa and its relation to El Niño/Southern Oscillation , 1996 .

[35]  George Wittemyer,et al.  Predicting time-specific changes in demographic processes using remote-sensing data , 2006 .

[36]  C. Cormack Gates,et al.  Ungulate foraging strategies: energy maximizing or time minimizing? , 2001 .

[37]  S. Albon,et al.  Plant phenology and the benefits of migration in a temperate ungulate , 1992 .

[38]  F. Lindsay,et al.  Dynamics of urban growth in the Washington DC metropolitan area, 1973-1996, from Landsat observations , 2000 .

[39]  A. Fischer A model for the seasonal variations of vegetation indices in coarse resolution data and its inversion to extract crop parameters , 1994 .

[40]  Nathalie Pettorelli,et al.  Importance of climatological downscaling and plant phenology for red deer in heterogeneous landscapes , 2005, Proceedings of the Royal Society B: Biological Sciences.

[41]  Per Jönsson,et al.  TIMESAT - a program for analyzing time-series of satellite sensor data , 2004, Comput. Geosci..

[42]  M. D. Schwartz,et al.  Determining the growing season of land vegetation on the basis of plant phenology and satellite data in Northern China , 2000, International journal of biometeorology.

[43]  J. Adegoke,et al.  Relations between Soil Moisture and Satellite Vegetation Indices in the U.S. Corn Belt , 2002 .

[44]  D. Despain Yellowstone Vegetation: Consequences of Environment and History in a Natural Setting , 1990 .

[45]  Nils Chr. Stenseth,et al.  CLIMATIC VARIABILITY, PLANT PHENOLOGY, AND NORTHERN UNGULATES , 1999 .

[46]  Partial migration and philopatry of Yellowstone pronghorn , 2007 .

[47]  M. Oesterheld,et al.  RELATION BETWEEN NOAA‐AVHRR SATELLITE DATA AND STOCKING RATE OF RANGELANDS , 1998 .

[48]  S. Running,et al.  A continental phenology model for monitoring vegetation responses to interannual climatic variability , 1997 .

[49]  S. McNaughton,et al.  Evidence for the promotion of aboveground grassland production by native large herbivores in Yellowstone National Park , 1993, Oecologia.

[50]  M. Boyce,et al.  Estimation of green herbaceous phytomass from Landsat MSS data in Yellowstone National Park. , 1993 .

[51]  N. Delbart,et al.  Remote sensing of spring phenology in boreal regions: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982-2004) , 2006 .