Modified Light Use Efficiency Model for Assessment of Carbon Sequestration in Grasslands of Kazakhstan: Combining Ground Biomass Data and Remote-sensing

A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (n) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of n suggested in this study can be used in grassland regions where no carbon flux measurements are accessible

Remote sensing of annual terrestrial gross primary productivity from MODIS: An assessment using the FLUXNET La Thuile dataset

Gross primary productivity (GPP) is the largest and most variable component of theglobal terrestrial carbon cycle. Repeatable and accurate monitoring of terrestrial GPPis therefore critical for quantifying dynamics in regional-to-global carbon budgets. Re-mote sensing provides high frequency observations of terrestrial ecosystems and is widely used to monitor and model spatiotemporal variability in ecosystem propertiesand processes that affect terrestrial GPP. We used data from the Moderate ResolutionImaging Spectroradiometer (MODIS) and FLUXNET to assess how well four metricsderived from remotely sensed vegetation indices (hereafter referred to as proxies) andsix remote sensing-based models capture spatial and temporal variations in annual GPP. Specifically, we used the FLUXNET “La Thuile” data set, which includes sev-eral times more sites (144) and site years (422) than previous efforts have used. Ourresults show that remotely sensed proxies and modeled GPP are able to capture sta-tistically significant amounts of spatial variation in mean annual GPP in every biomeexcept croplands, but that the total variance explained differed substantially across15biomes (R2≈0.1−0.8). The ability of remotely sensed proxies and models to explaininterannual variability GPP was even more limited. Remotely sensed proxies explained40–60 % of interannual variance in annual GPP in moisture-limited biomes includinggrasslands and shrublands. However, none of the models or remotely sensed proxiesexplained statistically significant amounts of interannual variation in GPP in croplands, evergreen needleleaf forests, and deciduous broadleaf forests. Because important fac-tors that affect year-to-year variation in GPP are not explicitly captured or included inthe remote sensing proxies and models we examined (e.g., interactions between bioticand abiotic conditions, and lagged ecosystems responses to environmental process),our results are not surprising. Nevertheless, robust and repeatable characterization of interannual variability in carbon budgets is critically important and the carbon cycle sci-ence community is increasingly relying on remotely sensing data. As larger and morecomprehensive data sets derived from the FLUXNET community become available, additional systematic assessment and refinement of remote sensing-based methodsfor monitoring annual GPP is warranted.ISSN:1810-6277ISSN:1810-628

Water supply and ancient society in the Lake Balkhash Basin: Runoff variability along the historical Silk Road

Expansion of agricultural practices from the Fertile Crescent to China during the mid and late Holocene are believed to have shaped the early network of Silk Road routes and possibly regulated the dynamics of trade and exchange in the urban oases along the Silk Road throughout its existence. While the impacts of climate change on the Silk Road are more or less documented for the medieval period, they remain poorly understood for early history of the Silk Road, especially in Central Asia. We analyze hydroclimatic proxies derived from fluvial stratigraphy, geochronology, and tree-ring records that acted on various time scales in the Lake Balkhash Basin to learn how changes in water supply could have influenced the early farmers in the Semirechye region of southern Kazakhstan. Our approach aims to identify short-term and long-term variability of regional runoff and to compare the hydrological data with cultural dynamics coupled with the archaeological settlement pattern and agricultural production. The reconstructed runoff variability underscore the contribution of winter precipitation driven by the interaction between the Arctic oscillation and the Siberian High-Pressure System, to Central Asian river discharge. We show that Saka people of the Iron Age employed extensive ravine agriculture on the alluvial fans of the Tian Shan piedmont, where floodwater farming peaked between 400 BC and 200 BC. The early Silk Road farmers on the alluvial fans favored periods of reduced flood flows, river stability and glacier retreat in the Tian Shan Mountains. Moreover, they were able to apply simple flow control structures to lead water across the fan surface. It is very unlikely that changes in water supply ever significantly constricted agricultural expansion in this region