1656Abstract. Humans have grazed on the Qinghai-Tibetan Plateau (QTP) for many thousands of years. In recent decades, the intensity of grazing has increased and several new management strategies have been put into place to address the resulting changes in rangeland condition. Effective management of grazing activities in this region requires understanding the impact of livestock grazing across the diverse array of alpine grassland ecosystems present in the QTP, but recent studies have identified a number of critical uncertainties in the ecological science that underlies these management principles. To address these uncertainties, we carried out a synthesis analysis of the effect of livestock grazing on 26 indicators of ecosystem structure and function based on 61 studies from 88 independent research sites within the QTP. Our synthesis results indicate that livestock grazing exerts complex controls on ecosystem structure and function, which vary according to local landscape characteristics. We found that grazing contributes to greater plant species diversity (Shannon-Wiener index, Simpson dominance index, and Pielou evenness index significantly increased 0.18, 0.05, and 0.03, respectively, due to grazing), but decreased aboveground biomass (47.15%), soil organic carbon (12.41%), soil total nitrogen (12.75%), and microbial biomass carbon (9.42%). Further, ecosystem function is controlled by interactions between grazing and other landscape characteristics such as elevation and mean annual temperature. The management regime currently in place in the QTP, which involves complete exclusion of grazing in some areas, can have variable effects on grassland health. Therefore, the complexity of these responses is an indication that livestock and grassland management may benefit from a more nuanced management regime than is currently utilized in the QTP.

Maps of forest biomass are important tools for managing natural resources and reporting terrestrial carbon stocks. Using the San Juan National Forest in Southwest Colorado as a case study, we evaluate regional biomass maps created using physical variables, spectral vegetation indices, and image textural analysis on Landsat TM imagery. We investigate eight gray level co-occurrence matrix based texture measures (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation) on four window sizes (3 × 3, 5 × 5, 7 × 7, 9 × 9) at four offsets ([1,0] , and the Coefficient of Variation of the Root Mean Square Error is 0.31. We find that models including image texture variables are more strongly correlated with biomass than models using only physical and spectral variables. Additionally, we suggest that the use of texture appears to better capture the magnitude and direction of biomass change following disturbance compared to spectral approaches. The biomass mapping methods we present here are widely applicable throughout the US, as they are based on publically available datasets and utilize relatively simple analytical routines. OPEN ACCESSRemote Sens. 2014, 6 6408

Tundra dominates two‐thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community‐specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil.

The advancement of spring and the differential ability of organisms to respond to changes in plant phenology may lead to “phenological mismatches” as a result of climate change. One potential for considerable mismatch is between migratory birds and food availability in northern breeding ranges, and these mismatches may have consequences for ecosystem function. We conducted a three‐year experiment to examine the consequences for CO2 exchange of advanced spring green‐up and altered timing of grazing by migratory Pacific black brant in a coastal wetland in western Alaska. Experimental treatments represent the variation in green‐up and timing of peak grazing intensity that currently exists in the system. Delayed grazing resulted in greater net ecosystem exchange (NEE) and gross primary productivity (GPP), while early grazing reduced CO2 uptake with the potential of causing net ecosystem carbon (C) loss in late spring and early summer. Conversely, advancing the growing season only influenced ecosystem respiration (ER), resulting in a small increase in ER with no concomitant impact on GPP or NEE. The experimental treatment that represents the most likely future, with green‐up advancing more rapidly than arrival of migratory geese, results in NEE changing by 1.2 µmol m−2 s−1 toward a greater CO2 sink in spring and summer. Increased sink strength, however, may be mitigated by early arrival of migratory geese, which would reduce CO2 uptake. Importantly, while the direct effect of climate warming on phenology of green‐up has a minimal influence on NEE, the indirect effect of climate warming manifest through changes in the timing of peak grazing can have a significant impact on C balance in northern coastal wetlands. Furthermore, processes influencing the timing of goose migration in the winter range can significantly influence ecosystem function in summer habitats.