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Colonization sequence influences selection and complementarit y effects on biomass production in experimental algal microcosms: Oikos, Vol. 116, No. 10. (2007), pp. 1748-1758..

Source: Oikos, Vol. 116, No. 10. (2007), pp. 1748-1758.
Application of acoustic Doppler current profiler combined with a scientific echo sounder for krill Euphausia pacifica density estimation: Fisheries Science, Vol. 70, No. 6., 1051.

Source: Fisheries Science, Vol. 70, No. 6., 1051.
Distribution and seasonal biomass of drift macroalgae in the Indian River Lagoon (Florida, USA) estimated with acoustic seafloor classification (QTCView, Echoplus): Journal of Experimental Marine Biology and Ecology, Vol. 326, No. 1. (6 December 2005), pp. 89-104.Three areas of the Indian River Lagoon, Florida (USA) were surveyed to show seasonal changes in the distribution and biomass of macroalgae and seagrass. Acoustic seafloor discrimination based on first and second echo returns of a 50 kHz and 200 kHz signal, and two different survey systems (QTCView and ECHOplus) were used. System verification in both the field and a controlled environment showed it was possible to distinguish acoustically between seagrass, sparse algae, and dense algae. Accuracy of distinction of three classes (algae, seagrass, bare substratum) was around 60%. Maps were produced by regridding the survey area to a regular grid and using a nearest-neighb or interpolation to provide filled polygons. Biomass was calculated by counting pixels assigned to substratum classes with known wet-weight biomass values (sparse algae 250 g m- 2, dense algae 2000 g m- 2, seagrass 100 g m- 2) that were measured in the field. In three study areas (Melbourne, Sebastian Inlet, and Cocoa Beach), a dependence of algal biomass on depth and season was observed. Seagrass most frequently occurred in water less than 1 m deep, and in November, seagrass beds tended to be covered by dense algae that also extended up- and downstream of shoals in the Lagoon. In March, the pattern was similar, with the exception that some areas of previously dense algae had started thinning into sparse algae. Macrophyte biomass was lowest in May in the Melbourne and Cocoa Beach study areas, with the opposite situation in the Sebastian Inlet study area. In May, seagrass areas were largely devoid of dense algae and most algae accumulations were sparse. In August, dense algae covered large areas of the deep Lagoon floor while shoals were largely free of algae or had only sparse cover. We suggest this summer pattern to reflect moribund algae being washed from the shallows to deeper channels and from there being removed from the lagoonal ecosystem either through tidal passages into the open ocean or by degradation and breakdown in situ. The differences between the study areas indicate high spatial and temporal variability in biomass and distribution of macrophyte biomass in the Indian River Lagoon.

Source: Journal of Experimental Marine Biology and Ecology, Vol. 326, No. 1. (6 December 2005), pp. 89-104.
Monitoring biomass burning in the Brazilian Amazonia: International Journal of Remote Sensing, Vol. 25, No. 24. (2004), 5537.

Source: International Journal of Remote Sensing, Vol. 25, No. 24. (2004), 5537.
Oceanography: Plankton in a warmer world: Nature, Vol. 444, No. 7120. (06 December 2006), pp. 695-696.

Source: Nature, Vol. 444, No. 7120. (06 December 2006), pp. 695-696.
Indirect remote sensing of a cryptic forest understorey invasive species: Forest Ecology and Management, Vol. 225, No. 1-3. (15 April 2006), pp. 245-256.Remote sensing has successfully been applied to map the distribution of canopy dominating invasive species. Many invaders however, do not dominate the canopy, and remote sensing has so far not been applied to map such species. In this study, an indirect method was used to map the seed production of Chromolaena odorata, one of the world's 100 worst invasive species. The study was executed in lowland Shorea robusta forest in Nepal, where Chromolaena invaded the understorey of degraded forest. A Landsat ETM+ image processed through a neural network predicted 89% and 81% of forest canopy density and light intensity reaching the understorey, respectively. We inverted these models to predict Chromolaena seed productivity. Light intensity determined 93% of the variation in log10 seed production per plant. Chromolaena failed to produce seed below a light intensity of 6.5 mJ m-2 day-1. Further analysis revealed that Chromolaena was absent above this light intensity in case of a high biomass of other shrub and herb species, a situation occurring in the absence of grazing. We therefore suggest that other species control Chromolaena through competitive exclusion in the absence of grazing, whereas grazing breaks the dominance of these other species thus creating the conditions for Chromolaena attain canopy dominance. The presence of grazing was related to distance from the forest edge, a variable that together with light intensity allowed us to map 64% of variation in Chromolaena cover. Predicted Chromolaena cover and seed production per plant were combined into a map displaying the total seed production per unit area. Such map displaying seed producing sites could be used to significantly reduce the costs of controlling Chromolaena infestation by providing information on the spatial segregation of source and sink populations, which will support efficient habitat ranking to restore invaded areas and protect non-invaded ecosystems. This may prove particularly valuable when implementing control measures under circumstances of limited capital and manpower.

Source: Forest Ecology and Management, Vol. 225, No. 1-3. (15 April 2006), pp. 245-256.
In situ detection of protein-hydrol ysing microorganisms in activated sludge.: FEMS Microbiol Ecol, Vol. 60, No. 1. (April 2007), pp. 156-165.Protei n hydrolysis plays an important role in the transformation of organic matter in activated sludge wastewater treatment plants, but no information is currently available regarding the identity and ecophysiology of protein-hydrol ysing organisms (PHOs). In this study, fluorescence in situ enzyme staining with casein and bovine serum albumin conjugated with BODIPY dye was applied and optimized to label PHOs in activated sludge plants. A strong fluorescent labeling of the surface of microorganisms expressing protease activity was achieved. Metabolic inhibitors were applied to inhibit the metabolic activity to prevent uptake of the fluorescent hydrolysates by oligopeptide-c onsuming bacteria. In five full-scale, nutrient-remov ing activated sludge plants examined, the dominant PHOs were always different morphotypes of filamentous bacteria and the epiflora attached to many of these. The PHOs were identified by FISH using a range of available oligonucleotid e probes. The filamentous PHOs belonged to the candidate phylum TM7, the phylum Chloroflexi and the class Betaproteobact eria. In total they comprised 1-5% of the bacterial biovolume. Most of the epiflora-PHOs hybridized with probe SAP-309 targeting Saprospiraceae in the phylum Bacteroidetes and accounted for 8-12% of the total bacterial biovolume in most plants and were thus an important and dominant part of the microbial communities.

Source: FEMS Microbiol Ecol, Vol. 60, No. 1. (April 2007), pp. 156-165.
A forest growth and biomass module for a landscape simulation model, LANDIS: design, validation, and application: Ecological Modelling, Vol. 180, No. 1. (10 December 2004), pp. 211-229.Predic ting the long-term dynamics of forest systems depends on understanding multiple processes that often operate at vastly different scales. Disturbance and seed dispersal are landscape-scal e phenomena and are spatially linked across the landscape. Ecosystem processes (e.g., growth and decomposition) have high annual and inter-specific variation and are generally quantified at the scale of a forest stand. To link these widely scaled processes, we used biomass (living and dead) as an integrating variable that provides feedbacks between disturbance and ecosystem processes and feedbacks among multiple disturbances. We integrated a simple model of biomass growth, mortality, and decay into LANDIS, a spatially dynamic landscape simulation model. The new biomass module was statically linked to PnET-II, a generalized ecosystem process model. The combined model simulates disturbances (fire, wind, harvesting), dispersal, forest biomass growth and mortality, and inter- and intra-specific competition. We used the model to quantify how fire and windthrow alter forest succession, living biomass and dead biomass across an artificial landscape representative of northern Wisconsin, USA. In addition, model validation and a sensitivity analysis were conducted.

Source: Ecological Modelling, Vol. 180, No. 1. (10 December 2004), pp. 211-229.
Tree stand biomass and carbon content in an age sequence of drained pine mires in southern Finland: pp. 161-169.Biomas s and carbon accumulation into tree stand and distribution between tree and components was studied in two undrained and four drained Scots pine (Pinus sylvestris L.) dominated peatland stands in southern Finland. On the drained sites, the amount and distribution of biomass above-ground was rather similar to pine-dominated stands on upland sites when drainage age of the site was thought to represent the stand age. The proportion of estimated below-ground biomass of the total pine biomass was ca. 30% on all sites studied which is more than on upland sites with supposedly similar growth potential. Due to the bigger amount of below-ground biomass, there is, on average, more biomass and thus also carbon in relation to stem volume in peatland stands than upland stands, when southern boreal Scots pine stands are examined. Equations for estimating the amount of carbon accumulating in the tree stand along with increasing stem volume are presented.

Source: pp. 161-169.
Modeling forest growth II. Biomass partitioning in Scots pine: Ecological Modelling, Vol. 86, No. 1. (April 1996), pp. 73-89.Biomass budgets of Scots pine (Pinus sylvestris) are analyzed with a canonical S-system model. The model is constructed with standardized methods of power-law representation , and a complete set of parameter values is derived from experimentally measured compartment sizes, fluxes and nitrogen contents. None of the typical assumptions about growth rates, relationships between roots and shoots, or allometry are made. All these phenomena are produced by the model as outputs. Specifically, the model correctly predicts the different long-term growth patterns of leaves, stems, and roots; relationships between these compartments, biomass production, and growth rates; and relationships that constitute the concept of functional balance. The model also predicts allocation patterns for biomass under different fertilization regimens and during the ageing of a stand. These latter predictions are more complicated than expected but appear reasonable, though definitive data for validation are lacking.

Source: Ecological Modelling, Vol. 86, No. 1. (April 1996), pp. 73-89.

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