COS 82-3
Restoration and carbon sequestration potential of sub-humid shrublands in a changing climate

Wednesday, August 12, 2015: 2:10 PM
321, Baltimore Convention Center
Arjun Adhikari, Ecology, Montana State University, Bozeman, MT
Joseph D. White, The Institute of Ecological, Earth, and Environmental Science, Baylor University, Waco, TX

Over the past century, various anthropogenic activities have resulted into loss of more than 95% shrub cover from the Lower Rio Grande Valley (LRGV), TX, USA.  Restoration of these shrublands has been a priority for two endangered felids, ocelots and jaguarondis, that require contiguous shrub cover.  While woody shrub restoration may be considered the antithesis of shrub encroachment, this type of habitat restoration also provides a substantial opportunity of increasing carbon sequestration.  Restoration of these shrublands by U.S. federal refuge managers during the past three decades have resulted some successful reestablishment of native shrub communities. We assessed restoration efficacy, carbon storage capacity, and future climate change impacts using combined remote sensing and modeling techniques.  We first developed a canopy identification algorithm using a spectral vegetation index from the Digital Ortho Quarter Quadrangle data to estimate individual shrub canopy area. The area was used as input into allometric equations to estimate aboveground biomass for dominant shrub species across this region.


The accuracy of the automated canopy identification by the algorithm was 79% when compared to the number of visually-determined, hand-digitized shrub canopies.  From this analysis, we found that naturally regenerated sites had higher average shrub densities of 174/ha when compared with 156 individuals/ha for replanted sites. However, average biomass for naturally regenerated sites (3.28 Mg C/ha) stored less biomass compared to that of replanted sites (3.71 Mg C/ha). We found that average biomass per shrub in naturally regenerated sites was lower compared to that of replanted sites (p < 0.05).  Shrub density and biomass estimated from the remote sensing data was used as input for the Physiological Principles in Predicting Growth model to predict future shrub biomass for three GCM scenarios projected by IPCC (2007). Modeling showed that the LRGV may produce lower biomass per ha though not directly related to the emission rate predicted by each scenario. We conclude that restoration efforts within LRGV have contributed to increasing shrub density with positive habitat benefits for the target felid species, but future climate change is likely to reduce both habitat and carbon sequestration potential.