The backbone of the climate network

We propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system, relying on the nonlinear mutual information of time series analysis and betweenness centrality of complex network theory. We show, that this approach reveals a rich internal structure in complex climate networks constructed from reanalysis and model surface air temperature data. Our novel method uncovers peculiar wave-like structures of high energy flow, that we relate to global surface ocean currents. This points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). We find that these results cannot be obtained using classical linear methods of multivariate data analysis, and have ensured their robustness by intensive significance testing.Comment: 6 pages, 5 figure

Direct Observation of Self-Assembled Chain-Like Water Structures in a Nanoscopic Water Meniscus

Sawtooth-like oscillatory forces generated by water molecules confined between two oxidized silicon surfaces were observed using a cantilever-based optical interfacial force microscope when the two surfaces approached each other in ambient environments. The humidity-dependent oscillatory amplitude and periodicity were 3-12 nN and 3-4 water diameters, respectively. Half of each period was matched with a freely jointed chain model, possibly suggesting that the confined water behaved like a bundle of water chains. The analysis also indicated that water molecules self-assembled to form chain-like structures in a nanoscopic meniscus between two hydrophilic surfaces in air. From the friction force data measured simultaneously, the viscosity of the chain-like water was estimated to be between 108 and 1010 times greater than that of bulk water. The suggested chain-like structure resolves many unexplained properties of confined water at the nanometer scale, thus dramatically improving the understanding of a variety of water systems in nature

The effects of dispersal and river spatial structure on asynchrony in consumer–resource metacommunities

River network structure influences many important population and community processes. Previous work examining ecological dynamics in river networks has focused on within-trophic-level dynamics, with less emphasis on food-web interactions. Yet, trophic interactions in rivers are influenced by processes that may interact with network structure and position. Using a spatially explicit consumer–resource model, we explore how trophic dynamics are influenced by the branching nature of river networks. We focus on cases where the consumer–resource interaction is prone to temporal oscillations and periodic low population sizes. In these cases, we find that the influence of network structure and dispersal can reduce temporal variability and increase persistence of consumers and resources at the metacommunity scale. The effects of network structure and dispersal on our observed metacommunity dynamics result from asynchrony among dynamics of local communities: when asynchronous local fluctuations are averaged, consumer–resource dynamics become less variable and bounded higher above zero at regional spatial scales. Fluctuations synchronise across clusters of linked local communities. Communities that connect to only one other downstream community typically vary independently of other patches and show high variability, while communities that are linked to multiple upstream and downstream habitats show greater clustering and less variability. These patterns suggest that headwater versus mainstem locations in river networks may show different levels of population variability and thus differential responses to management and restoration efforts

Hyperparathyroidism-jaw tumor syndrome: the HRPT2 locus is within a 0.7-cM region on chromosome 1q.

Hyperparathyroidism-jaw tumor syndrome (HPT-JT) is an autosomal dominant disease characterized by the development of multiple parathyroid adenomas and multiple fibro-osseous tumors of the maxilla and mandible. Some families have had affected members with involvement of the kidneys, variously reported as Wilms tumors, nephroblastomas, and hamartomas. The HPT-JT gene (HRPT2) maps to chromosome 1q25-q31. We describe further investigation of two HPT-JT families (K3304 and K3349) identified through the literature. These two expanded families and two previously reported families were investigated jointly for linkage with 21 new, closely linked markers. Multipoint linkage analysis resulted in a maximum LOD score of 7.83 (at recombination fraction 0) for markers D1S2848-D1S191. Recombination events in these families reduced the HRPT2 region to approximately 14.7 cM. In addition, two of these four study families (i.e., K3304 and K11687) share a 2.2-cM length of their (expanded) affected haplotype, indicating a possible common origin. Combining the linkage data and shared-haplotype data, we propose a 0.7-cM candidate region for HRPT2