Get access

Debating the greening vs. browning of the North American boreal forest: differences between satellite datasets

Authors

  • DOMINGO ALCARAZ-SEGURA,

    1. Environmental Sciences Department, University of Virginia. 291 McCormick Road, Charlottesville, VA 22904, USA
    2. Laboratorio de Análisis Regional y Teledetección – IFEVA, Universidad de Buenos Aires and CONICET. Av. San Martín, 4453, Buenos Aires 1417, Argentina
    3. Departamento de Biología Vegetal y Ecología, Universidad de Almería. Ctra. Sacramento s/n, La Cañada de San Urbano, Almería 04120, Spain
    Search for more papers by this author
  • EMILIO CHUVIECO,

    1. Departamento de Geografía, Universidad de Alcalá. Colegios 2, Alcalá de Henares, Madrid 28801, Spain
    Search for more papers by this author
  • HOWARD E. EPSTEIN,

    1. Environmental Sciences Department, University of Virginia. 291 McCormick Road, Charlottesville, VA 22904, USA
    Search for more papers by this author
  • ERIC S. KASISCHKE,

    1. Department of Geography, University of Maryland, College Park, MD 20742, USA
    Search for more papers by this author
  • ALEXANDER TRISHCHENKO

    1. Canada Centre for Remote Sensing, Natural Resources Canada. 588 Booth Str., Ottawa, ON, Canada K1A 0Y7
    Search for more papers by this author

Domingo Alcaraz-Segura, Environmental Sciences Department, University of Virginia. 291 McCormick Road, Charlottesville, VA 22904, USA, tel. +34 950 015 932, fax +34 950 015 069, e-mail: dalcaraz@ual.es

Abstract

A number of remote sensing studies have evaluated the temporal trends of the normalized difference vegetation index (NDVI or vegetation greenness) in the North American boreal forest during the last two decades, often getting quite different results. To examine the effect that the use of different datasets might be having on the estimated trends, we compared the temporal trends of recently burned and unburned sites of boreal forest in central Canada calculated from two datasets: the Global Inventory, Monitoring, and Modeling Studies (GIMMS), which is the most commonly used 8 km dataset, and a new 1 km dataset developed by the Canadian Centre for Remote Sensing (CCRS). We compared the NDVI trends of both datasets along a fire severity gradient in order to evaluate the variance in regeneration rates. Temporal trends were calculated using the seasonal Mann–Kendall trend test, a rank-based, nonparametric test, which is robust against seasonality, nonnormality, heteroscedasticity, missing values, and serial dependence. The results showed contrasting NDVI trends between the CCRS and the GIMMS datasets. The CCRS dataset showed NDVI increases in all recently burned sites and in 50% of the unburned sites. Surprisingly, the GIMMS dataset did not capture the NDVI recovery in most burned sites and even showed NDVI declines in some burned sites one decade after fire. Between 50% and 75% of GIMMS pixels showed NDVI decreases in the unburned forest compared with <1% of CCRS pixels. Being the most broadly used dataset for monitoring ecosystem and carbon balance changes, the bias towards negative trends in the GIMMS dataset in the North American boreal forest has broad implications for the evaluation of vegetation and carbon dynamics in this region and globally.

Ancillary