Recent relevant publications of various authors, environmental science, aquatic sciences, ecology:
**
Evaluating marine ecosystem health: Case studies of indicators using direct observations and modelling methods
- I. Romboutsa, b,
,
,
- G. Beaugranda, b,
- L.F. Artigasa, c,
- J.-C. Dauvind,
- F. Gevaertb,
- E. Gobervilleb,
- D. Koppb, e,
- S. Lefebvreb,
- C. Luczakb, f,
- N. Spilmontb, g,
- M. Travers-Trolete,
- M.C. Villanuevae,
- R.R. Kirbyh,
isabelle.rombouts@univ-lille1.fr, gregory.beaugrand@univ-lille1.fr, felipe.artigas@univ-littoral.fr,
jean-claude.dauvin@unicaen.fr, francois.gevaert@univ-lille1.fr, eric.goberville@univ-lille1.fr,
dorothee.kopp@ifremer.fr, sebastien.lefebvre@univ-lille1.fr, christophe.luczak@univ-lille1.fr,
**
- a Centre National de la Recherche Scientifique (CNRS), Laboratoire d’Océanologie et de Géosciences, Université de Lille 1, UMR CNRS 8187 (LOG), 28 Avenue Foch, 62930 Wimereux, France
- b Université de Lille 1, UMR CNRS 8187 (LOG), Station Marine de Wimereux, 28 Avenue Foch, 62930 Wimereux, France
- c Université du Littoral Côte d’Opale, UMR CNRS 8187 (LOG), Maison de la Recherche et de l’Environnement, 32 Avenue Foch, 62930 Wimereux, France
- d Université de Caen Basse Normandie, Laboratoire Morphodynamique Continentale et Côtière, UMR CNRS 6143 M2C, 24 rue des Tilleuls, 14000 Caen, France
- e Institut Français de Recherche pour l’Exploitation de la Mer (IFREMER), Laboratoire Ressources Halieutiques, 150 quai Gambetta, BP699, 62321 Boulogne/mer, France
- f Université d’Artois, IUFM, Centre de Gravelines, 40 rue V. Hugo – BP 129, 59820 Gravelines, France
- g Environmental Futures Centre and School of Environment, Griffith University, Gold Coast Campus, QLD 4222, Australia
- h University of Plymouth, School of Marine Science and Engineering, Drake Circus, Plymouth PL4 8AA, UK
**
Staehr, Peter A., Jeremy M. Testa, W. Michael Kemp, Jon J. Cole, Kaj Sand-Jensen, and Stephen V. Smith. "The metabolism of aquatic ecosystems: history, applications, and future challenges." Aquatic sciences 74, no. 1 (2012): 15-29.
**
ScientificWorldJournal. 2002 Feb 12;2:387-406.
Recent trends in the development of ecological models applied on aquatic ecosystems.
Source
DFH, Institute A, Environmental Chemistry, University Park 2, Copenhagen East, 2100 Denmark. sej@dfh.dk
**
J Environ Monit. 2006 May;8(5):512.
Aquatic processes and systems in perspective.
Source
Water Resources Cetner, 173 McNeal Hall, University of Minnesota, St. Paul, 55108, USA.
PMID:16791969
[PubMed - indexed for MEDLINE]
**
Environ Manage. 2006 Dec;38(6):1020-30. Epub 2006 Oct 20.
Using relative risk to compare the effects of aquatic stressors at a regional scale.
National Health and Environmental Effects Research Laboratory, Western Ecology Division, U.S. Environmental Protection Agency, 200 SW 35th Street, Corvallis, Oregon 97333, USA. VanSickle.John@epa.gov
Abstract
The regional-scale importance of an aquatic stressor depends both on its regional extent (i.e., how widespread it is) and on the severity of its effects in ecosystems where it is found. Sample surveys, such as those developed by the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP), are designed to estimate and compare the extents, throughout a large region, of elevated conditions for various aquatic stressors. In this article, we propose relative risk as a complementary measure of the severity of each stressor's effect on a response variable that characterizes aquatic ecological condition. Specifically, relative risk measures the strength of association between stressor and response variables that can be classified as either "good" (i.e., reference) or "poor" (i.e., different from reference). We present formulae for estimating relative risk and its confidence interval, adapted for the unequal sample inclusion probabilities employed in EMAP surveys. For a recent EMAP survey of streams in five Mid-Atlantic states, we estimated the relative extents of eight stressors as well as their relative risks to aquatic macroinvertebrate assemblages, with assemblage condition measured by an index of biotic integrity (IBI). For example, a measure of excess sedimentation had a relative risk of 1.60 for macroinvertebrate IBI, with the meaning that poor IBI conditions were 1.6 times more likely to be found in streams having poor conditions of sedimentation than in streams having good sedimentation conditions. We show how stressor extent and relative risk estimates, viewed together, offer a compact and comprehensive assessment of the relative importances of multiple stressors.
PMID:17058032
[PubMed - indexed for MEDLINE]
**
J Environ Sci Eng. 2007 Oct;49(4):317-24.
Bioindicators of pollution in lentic water bodies of Nagpur city.
Indian Council of Medical Research, New Delhi.
Abstract
The present study deals with assessment of water quality of four selected lakes in the Nagpur city using physicochemical and biological parameters especially phytoplankton and zooplankton community. Tropic level and pollution status of lakes were assessed on the basis of the Palmer's Pollution Index, Shannon Wiener Index and physico-chemical parameters. 57 genera belonging to 7 groups of phytoplankton and 10 genera belonging to 3 groups of zooplankton were identified from the lakes. Different patterns of dominance and sub-dominance of indicator plankton community and species along with physico-chemical quality observed confirm the pollution status of the lakes.
PMID:
18476381
[PubMed - indexed for MEDLINE]
**
Math Biosci Eng. 2008 Oct;5(4):771-87.
Model analysis of a simple aquatic ecosystems with sublethal toxic effects.
Department of Theoretical Biology, Vrije Universiteit, de Boelelaan 1087, 1081 HV Amsterdam, Netherlands. kooi@bio.vu.nl
Abstract
The dynamic behaviour of simple aquatic ecosystems with nutrient recycling in a chemostat, stressed by limited food availability and a toxicant, is analysed. The aim is to find effects of toxicants on the structure and functioning of the ecosystem. The starting point is an unstressed ecosystem model for nutrients, populations, detritus and their intra- and interspecific interactions, as well as the interaction with the physical environment. The fate of the toxicant includes transport and exchange between the water and the populations via two routes, directly from water via diffusion over the outer membrane of the organism and via consumption of contaminated food. These processes are modelled using mass-balance formulations and diffusion equations. At the population level the toxicant affects different biotic processes such as assimilation, growth, maintenance, reproduction, and survival, thereby changing their biological functioning. This is modelled by taking the parameters that described these processes to be dependent on the internal toxicant concentration. As a consequence, the structure of the ecosystem, that is its species composition, persistence, extinction or invasion of species and dynamics behaviour, steady state oscillatory and chaotic, can change. To analyse the long-term dynamics we use the bifurcation analysis approach. In ecotoxicological studies the concentration of the toxicant in the environment can be taken as the bifurcation parameter. The value of the concentration at a bifurcation point marks a structural change of the ecosystem. This indicates that chemical stressors are analysed mathematically in the same way as environmental (e.g. temperature) and ecological (e.g. predation) stressors. Hence, this allows an integrated approach where different type of stressors are analysed simultaneously. Environmental regimes and toxic stress levels at which no toxic effects occur and where the ecosystem is resistant will be derived. A numerical continuation technique to calculate the boundaries of these regions will be given.
PMID:19278281
[PubMed - indexed for MEDLINE]
**
