Proximity to ice fields and lake depth as modulators of paleoclimate records: a regional study from southwest Yukon,Canada

Pronounced climate warming during the past century has been well documented in high-latitude regions. Nonetheless, considerable heterogeneity exists in northern climate trends. We examined the roles of cryospheric landscape and lake depth in modulating the rate and magnitude of local climate responses through a paleolimnological study of lakes from southwest Yukon, Canada. By sampling lakes at varying distances from the Wrangell-St. Elias ice fields, we hypothesized that, for lakes of similar maximum depth, sites closest to the ice fields would be relatively complacent in terms of their chironomid and diatom assemblage changes over the past ~200 years. This hypothesis is based on the moderating effect of the glaciers on local climate, which would be most pronounced in the lakes nearest to the ice fields. However, given the known ecological differences between deep and shallow lakes, we further predicted that, for a given distance from the ice fields, a sediment record from a shallower lake would show the greatest change in stratigraphic subfossil assemblages. Because of the complicated shape of the ice fields, we applied the longitude for each site (which decreases from west to east) to approximate the proximity of our study lakes to the ice fields. Consistent with our predictions, we observed a space-transgressive pattern in the chironomid assemblage turnover that was associated with their proximity to the ice fields (r = ?0.75, P = 0.034, n = 8) across lakes of similar depth (mean maximum depth ± 1, SE = 18.1 ± 2.6 m). Considering a broader network of lakes that represented a greater range in maximum depth (4.9–29 m), we found that differences in subfossil chironomid assemblages between the modern and ca. AD 1800 sediment layers were strongly related to lake depth (r = ?0.77, P < 0.001, n = 15), but failed to detect a significant relationship with latitude or longitude (i.e. our proxy for proximity to the ice fields). Similarly, our comparative high-resolution analyses of two lakes with distinct lake morphometries, but similar proximities to the ice fields, demonstrated the predicted contrasting pattern: we observed pronounced post-1880 changes in the biotic assemblages in the shallow lake and a muted and delayed response (i.e. ~1970s) in the deeper lake. Our findings confirm that cryospheric landscape features can strongly modulate regional climate. Furthermore, our work shows that investigators need to be conscious of how climate change affects the structure and functioning of lakes of different typologies, which influences the way in which paleoclimate signals are recorded and interpreted.     

A hierarchical indexing strategy for optimizing Apache Spark with HDFS to efficiently query big geospatial raster data

ABSTRACT

Earth observations and model simulations are generating big multidimensional array-based raster data. However, it is difficult to efficiently query these big raster data due to the inconsistency among the geospatial raster data model, distributed physical data storage model, and the data pipeline in distributed computing frameworks. To efficiently process big geospatial data, this paper proposes a three-layer hierarchical indexing strategy to optimize Apache Spark with Hadoop Distributed File System (HDFS) from the following aspects: (1) improve I/O efficiency by adopting the chunking data structure; (2) keep the workload balance and high data locality by building the global index (k-d tree); (3) enable Spark and HDFS to natively support geospatial raster data formats (e.g., HDF4, NetCDF4, GeoTiff) by building the local index (hash table); (4) index the in-memory data to further improve geospatial data queries; (5) develop a data repartition strategy to tune the query parallelism while keeping high data locality. The above strategies are implemented by developing the customized RDDs, and evaluated by comparing the performance with that of Spark SQL and SciSpark. The proposed indexing strategy can be applied to other distributed frameworks or cloud-based computing systems to natively support big geospatial data query with high efficiency.     

Calibration of regional pollen data to construct maps of former forest types in southern Sweden

A method was developed to construct maps of former forest types based on regional pollen data in southern Sweden. The considered species were Alnus, Betula, Carpinus, Corylus, Fagus, Fraxinus, Juniperus, Picea, Pinus, Populus, Quercus, Salix, Tilia and Ulmus. A network of 37 regional pollen sites with high data quality from lakes and peat deposits were selected from Sweden south of 60 ° N. Pollen percentage values were calculated and converted into estimates of tree composition. For controlling the reliability of the reconstruction, the estimates from the core-tops were compared with present day forest inventory data, and local pollen diagrams were compared with the regional pollen diagrams. An inverse distance weighted interpolation algorithm was used to generate maps for each tree species distribution at 2000 BP, 1500 BP, 1000 BP, 500 BP and 0 BP. A supervised classification routine was implemented to generate nine different forest types common to the five studied time intervals. The maps show that the amounts and patterns of distribution of the species and the forest types have varied in a significant but systematic manner through time. The changes are due to human activities, migrational patterns and changes in climate. These maps will be of value as a basis for future landscape planning, forestry and conservation of biodiversity.This is the 20th in a series of papers published in this special AMQUA issue. These papers were presented at the 1994 meeting of the American Quaternary Association held 19–22 June, 1994, at the University of Minnesota, Minneapolis, Minnesota, USA. Dr Linda C. K. Shane served as guest editor for these papers.     

Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods

Accurate estimations of spatio-temporal fields at unsampled locations are important in a number of applications. Often, spatio-temporal fields are advected, which means the change in field values over time at a particular point in space stems to a large extent from motion of a more or less constant spatial field. For such dynamic fields, interpolation methods including information on the motion behaviour of the field are promising extensions of solely spatial (snapshot) and symmetric spatio-temporal methods. In this paper, the performance of different deterministic and geostatistical interpolation methods is compared for precipitation estimation from 1-minute time series of spatially distributed rain gauges. The focus is on spatio-temporal methods that include information on the motion behaviour of the rainfield, estimated from weather radar using optical flow. The different interpolation methods are introduced and evaluated using rain gauge measurements of a 15-day period and cross-validation. The results show that including information on the motion behaviour significantly improves interpolation quality in terms of RMSE.     

Sedimentary roles on hyporheic exchange in karst conduits at low Reynolds numbers by laboratory experiments

Hydrogeology Journal - The relative roles of the sediment grain size/permeability, conduit flow rate and conduit geometry/angle on the hyporheic exchange between a karst conduit and its underlying...     

The droughts of 1996–1997 and 2004–2005 in Amazonia: hydrological response in the river main‐stem

Severe hydrological droughts in the Amazon have generally been associated with strong El Niño events. More than 100 years of stage record at Manaus harbour confirms that minimum water levels generally coincide with intense warming in the tropical Pacific sea waters. During 2005, however, the Amazon experienced a severe drought which was not associated with an El Niño event. Unless what usually occurs during strong El Niño events, when negative rainfall anomalies usually affect central and eastern Amazon drainage basin; rainfall deficiencies in the drought of 2005 were spatially constrained to the west and southwest of the basin. In spite of this, discharge stations at the main‐stem recorded minimum water levels as low as those observed during the basin‐wide 1996–1997 El Niño‐related drought. The analysis of river discharges along the main‐stem and major tributaries during the drought of 2004–2005 revealed that the recession on major tributaries began almost simultaneously. This was not the case in the 1996–1997 drought, when above‐normal contribution of some tributaries for a short period during high water was crucial to partially counterbalance high discharge deficits of the other tributaries. Since time‐lagged contributions of major tributaries are fundamental to damp the extremes in the main‐stem, an almost coincident recession in almost all tributaries caused a rapid decrease in water discharges during the 2005 event. Copyright © 2010 John Wiley & Sons, Ltd.