A Review on the Application of Natural Computing in Environmental Informatics

Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201

On Diagnostic Index and Method of Healthy Wetland Food Chain

Abstract: Wetland food chain is the channel of the matter and energy transfer or flow in the wetland ecosystem. From wetland food chain scission mechanism, the structure and functional characteristics of the wetland food chain scission were analyzed, while building a healthy wetland food chain diagnostic index system. Depending on wetland ecosystem health research results, this study brought forward the wetland food chain structure stability and functions of wetland energy measures and their quantitative calculation formula and finally we gave the healthy wetland food chain diagnosis process in order to provide scientific basis for wetland food chain restoration

Phytoplankton community dynamics of two adjacent Dutch lakes in response to seasons and eutrophication control unravelled by non-supervised artificial neural networks

Copyright © 2006 Published by Elsevier B.V.Long-term time-series of the eutrophic Dutch lakes Veluwemeer and Wolderwijd were subject to ordination and clustering by means of non-supervised artificial neural networks (ANN). A combination of bottom-up and top-down eutrophication control measures has been implemented in both lakes since 1979. Dividing time-series data from 1976 to 1993 into three distinctive management periods has facilitated a comparative analysis of the two lakes regarding both the seasonal and long-term dynamics in response to eutrophication control. Results of the study have demonstrated that non-supervised ANN are an alternative technique: (1) to elucidate causal relationships of complex ecological processes, and (2) to reveal long-term behaviours of ecosystems in response to different management approaches. It has been shown that external nutrient control combined with food web manipulation have turned both lakes from nitrogen to phosphorus limitation, and from blue-green algae to diatom and green algae dominance. © 2006.Friedrich Recknagel, Anita Talib and Diederik van der Molenhttp://www.elsevier.com/wps/find/journaldescription.cws_home/705192/description#descriptio

Factors affecting local, regional, and global scale cyanobacterial dominance and secondary metabolite occurrence

Cyanobacteria are photosynthetic bacteria that serve as a primary producer in aquatic ecosystems. Cyanobacterial harmful algal blooms (CyanoHABs) are a major cause of water quality degradation in rivers, lakes, and estuaries worldwide because they disrupt food-webs and cause substantial changes in pH and dissolved oxygen. Additionally, many cyanobacterial species are capable of producing a suite of potent toxins and other secondary metabolites that cause taste and odor problems in drinking water supplies. The primary goal of my dissertation is to better understand the factors controlling CyanoHABs and their associated secondary metabolites at local, regional, and global scales. I examined the factors that control local-scale CyanoHABs and the cyanobacterial metabolites microcystin and geosmin by comparing 12 linear and non-linear regression modeling techniques using a continuous 14 year dataset collected from Cheney Reservoir, Kansas. In Chapter 2, I explored the factors that control regional-scale cyanobacterial abundance, microcystin, geosmin, and 2-methylisoborneol concentrations in 4 Midwestern US reservoirs. Then, I used a meta-analysis to evaluate the relation of persistent organic pollutants, which include herbicides, pesticides, pharmaceutical, personal care products, and industrial chemicals, to CyanoHABs on a global scale in Chapter 3. Overall, the three chapters indicate that cyanobacterial blooms and their associated metabolites are driven by numerous factors at different scales