Spatial variability in water quality and surface sediment diatom assemblages in a complex lake basin,lake of the woods,ontario,canada

Lake of the Woods (LOW) is an international waterbody spanning the Canadian provinces of Ontario and Manitoba, and the U.S. state of Minnesota. In recent years, there has been a perception that water quality has deteriorated in northern regions of the lake, with all increase in the frequency and intensity of toxin-producing cyanobacterial blooms. However, given the lack of long-term data these trends are difficult to verify. As a first step, we examine spatial and seasonal patterns in water quality in this highly complex lake on the Canadian Shield. Further, we examine surface sediment diatom assemblages across multiple sites to determine if they track within-take differences in environmental conditions. Our results show that there are significant spatial patterns in water quality in LOW. Principal Component Analysis divides the lake into three geographic zones based primarily on algal nutrients (i.e., total phosphorus, TP), with the highest concentrations at sites proximal to Rainy River. This variation is closely tracked by sedimentary diatom assemblages, with [TP] explaining 43% of the variation in diatom assemblages across sites. The close correlation between water quality and the surface sediment diatom record indicate that paleoecological models could be used to provide data on the relative importance of natural and anthropogenic sources of nutrients to the lake.

Mitochondrial variation of the "eyed" turtles (Sacalia) based on known-locality and trade specimens

Bryan L. Stuart is thanked for his hard work to collect wild specimens, as well as providing insightful and useful comments on the data. We thank Abigail Wolf of the Field Museum for providing photographs of specimens. Robert Murphy of the Royal Ontario M

A NEW SPECIES FROM SOUTHWESTERN CHINA IN THE AFRO-PALEARCTIC LINEAGE OF THE HORSESHOE BATS (RHINOLOPHUS)

A new species of horseshoe bat (Chiroptera: Rhinolophidae) is described from southwestern China. The presence of a wedge-shaped sella and pointed connecting process of the nose leaf aligns the new species to the landeri group in the Afro-Palearctic lineag

Vertical distribution and migration of planktonic rotifers in Xiangxi Bay of the three Gorges Reservoir, China

We investigated diel vertical migrations (DVM) and distributions of rotifers in summer, 2004 and spring, 2005, in Xiangxi Bay of the Three Gorges Reservoir, China. Water temperature, pH, conductivity, and phytoplankton were closely related to rotifer vertical distribution, while dissolved oxygen had no relationship with the vertical distribution of rotifers. The species composition and population density of rotifers changed significantly between seasons. However, rotifer vertical distributions in both seasons were similar. They aggregated at specific depths in the water column. All the rotifer species inhabited the surface layers (0.5-5 m). Generally, the rotifers did not display DVM except for Polyarthra vulgaris (in summer), which performed reverse migration. The reason that rotifers did not perform DVM may be explained by the low abundance of competitors and predators and the high density of food resources at the surface strata.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

Dynamic power management approaches based on neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system. by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level policies. We proposed two PAY policies-Back propagation Power Management (BPPM) and Radial Basis Function Power management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79,145,1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

Cancer classification based on direction-basis-function neural networks

Automatic molecular classification of cancer based on DNA microarray has many advantages over conventional classification based on morphological appearance of the tumor. Using artificial neural networks is a general approach for automatic classification. In this paper, Direction-Basis-Function neuron and Priority-Ordered algorithm are applied to neural networks. And the leukemia gene expression dataset is used as an example to testify the classifier. The result of our method is compared to that of SVM. It shows that our method makes a better performance than SVM.