Net changes in aboveground woody carbon stock in western juniper woodlands, 1946–1998

Abstract

[1] Although regional increases in woody plant cover in semiarid ecosystems have been identified as a worldwide phenomenon affecting the global carbon budget, quantifying the impact of these vegetation shifts on C pools and fluxes is challenging. Challenges arise because woody encroachment is governed by ecological processes that occur at fine spatial resolutions (1-10 m) and, in many cases, at slow (decadal-scale) temporal rates over large areas. We therefore analyzed time series aerial photography, which exhibits both the necessary spatial precision and temporal extent, to quantify the expansion of western juniper into sagebrush steppe landscapes in southwestern Idaho. We established upper and lower bounds of aboveground woody carbon change across the landscape via two-dimensional spatial wavelet analysis, image texture analysis, and field data collection. Forty-eight 100-ha blocks across a 330,000-ha region were stratified by topography, soil characteristics, and land stewardship for analyses. Across the area we estimate aboveground woody carbon accumulation rates of 3.3 gCm À2 yr À1 and 10.0 gCm À2 yr À1 using the wavelet and texture method, respectively, during the time period 1946-1998. Carbon accumulation rates were significantly affected by soil properties and were highly dependent on the spatial and temporal scales of analysis. For example, at a 100-ha scale the aboveground carbon accumulation varied from À1.7 to 9.9 gCm À2 yr À1 , while at the 1-ha scale the range of variability increased to À11 to 22 gCm À2 yr À1 . These values are an order of magnitude lower than those previously suggested due to woody encroachment, highlighting the need for examining multiple spatial scales when accounting for changes in terrestrial carbon storage.

Canopy Area and Aboveground Mass of Individual Redberry Juniper (Juniperus pinchotii) Trees

“…Additionally, the quantification of biomass at the landscape scale is also needed to prioritize fuel management strategies, predict fire behavior, and calculate carbon fluxes (Strand et al 2008;Huang et al 2009;Chuvieco et al 2010;McGinnis et al 2010). The ability to measure biomass of the dominant species can contribute to a better understanding of resource allocation such as the use of water resources and nutrients (Miller et al 1987;Roundy et al 2014b), and the potential use of P-J woodlands for biofuel (Skog et al 2009).…”

QUANTIFYING FOREST ABOVEGROUND CARBON POOLS AND FLUXES USING MULTI-TEMPORAL LIDAR A report on field monitoring, remote sensing MMV, GIS integration, and modeling results for forestry field validation test to quantify aboveground tree biomass and carbon

“…Assessing biomass accumulation over large areas and extended time periods is essential for improved estimates of carbon pools and fluxes and potential effects on the global carbon budget (Strand et al 2008). Stand age has been shown by several researchers to affect ecosystem carbon uptakes.…”

“…In a study by Asner et al (2003), researchers studied pools and fluxes of carbon in semiarid woodlands, using texture analysis of black and white aerial photographs from 1937 compared to spectral mixture analysis of Landsat data from 1999 to estimate the change in above ground woody carbon pools and the net flux over the 62 year time period. Strand et al (2008) estimated net change in above ground woody carbon over a 52 year time period using 2-D spatial wavelet analysis on time series black and white aerial photography and allometric relationships. Tree growth in a conifer plantation was estimated over a 19 year time period using synthetic aperture radar (SAR) backscattering changes, with a resulting root mean square error (RMSE) in tree growth of 8.2 meters (m) (Balzter et al 2003).…”

Remote Sensing and Ecosystem Services: Current Status and Future Opportunities for the Study of Bees and Pollination-Related Services

“…Aerial photography, which has been available in the USA since the 1930s, is one of the most spatially and temporally complete records of landscape change [53]. It has played a critical role in quantifying human impacts on the landscape such as deforestation, reforestation, or afforestation [54,55]; changing agricultural practices and land use [56]; and urban encroachment [57]. Complementing these data is the ever growing suite of satellite data (e.g., those sensors listed in Table 1), enabling analyses of landscape change using a record of multispectral data reaching back to the early 1970s.…”