Simulating forest cover change in the northeastern U.S.: decreasing forest area and increasing fragmentation

Landscape Ecology - Understanding how the Northern Forest landscape has changed and is likely to change, both in terms of forest extent and forest configuration, has important implications for...     

Modeling carbon storage across a heterogeneous mixed temperate forest: the influence of forest type specificity on regional-scale carbon storage estimates

Purpose

Accurately assessing forest carbon storage on a landscape scale is critical to understanding global carbon cycles and the effects of land cover changes on ecological processes. Calculations of regional-scale forest carbon storage that rely on maps of land cover typically reflect only coarse forest classes. How differences in carbon stored by different tree species may affect such assessments is largely unexplored. We examined a range of forest carbon storage models to understand the effects of forest type specificity on carbon storage estimates in the northeastern United States.

Methods

Models estimated forest carbon in total aboveground and coarse root biomass based on three levels of forest classification specificity: (1) relative basal area by species, (2) species associations, and (3) broad forest types per IPCC (in: IPCC guidelines for national greenhouse gas inventories, IPCC, Japan, 2006) guidelines.

Results

The specificity of forest type classifications influenced results with generally lower carbon storage estimates resulting from higher-specificity forest classifications. The two most specific models, with mean carbon storage estimates of 103–107 Mg/ha, were most accurate compared to field validation points. These estimates are greater than 2013 field-based U.S. Forest Service estimates (84–90 Mg/ha).

Conclusions

There are many sources of uncertainty in landscape-scale carbon storage assessments. Here we show that improving detail in one of these sources, forest stand composition, increases the accuracy of these assessments, and better reflects carbon storage patterns across heterogeneous landscapes. While more work is needed, particularly to improve stand age maps, this information can inform the interpretation of current carbon storage estimates and improve future estimates in heterogeneous forests.