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  • 1
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Long-distance dispersal (LDD) is central to species expansion following climate change, re-colonization of disturbed areas and control of pests. The current paradigm is that the frequency and spatial extent of LDD events are extremely difficult to predict. Here we show that mechanistic models ...
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1365-2486
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering , Geography
    Notes: Volatile organic compounds (VOCs) emitted by woody vegetation influence global climate forcing and the formation of tropospheric ozone. We use data from over 250 000 re-surveyed forest plots in the eastern US to estimate emission rates for the two most important biogenic VOCs (isoprene and monoterpenes) in the 1980s and 1990s, and then compare these estimates to give a decadal change in emission rate. Over much of the region, particularly the southeast, we estimate that there were large changes in biogenic VOC emissions: half of the grid cells (1°× 1°) had decadal changes in emission rate outside the range −2.3% to +16.8% for isoprene, and outside the range 0.2–17.1% for monoterpenes. For an average grid cell the estimated decadal change in heatwave biogenic VOC emissions (usually an increase) was three times greater than the decadal change in heatwave anthropogenic VOC emissions (usually a decrease, caused by legislation). Leaf-area increases in forests, caused by anthropogenic disturbance, were the most important process increasing biogenic VOC emissions. However, in the southeast, which had the largest estimated changes, there were substantial effects of ecological succession (which decreased monoterpene emissions and had location-specific effects on isoprene emissions), harvesting (which decreased monoterpene emissions and increased isoprene emissions) and plantation management (which increased isoprene emissions, and decreased monoterpene emissions in some states but increased monoterpene emissions in others). In any given region, changes in a very few tree species caused most of the changes in emissions: the rapid changes in the southeast were caused almost entirely by increases in sweetgum (Liquidambar styraciflua) and a few pine species. Therefore, in these regions, a more detailed ecological understanding of just a few species could greatly improve our understanding of the relationship between natural ecological processes, forest management, and biogenic VOC emissions.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 66 (1985), S. 256-263 
    ISSN: 1432-1939
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary We developed models of inter-individual interference to predict the fecundity of individuals in populations of the annual plant species, Arabidopsis thaliana. An individual plant is modeled as having a neighborhood which is a circular area of fixed radius with the plant at its center. Other plants which share the circle with the focal plant are termed neighbors of the focal plant. We developed an index of neighborhood interference which is the independent variable in a non-linear regression model that predicts individual plant fecundity. We present methods of exploratory data analysis that are useful in determining a best neighborhood radius, defined as that radius which minimizes residual sum of squares, and in deciding on the functional form of the interference index. In developing the interference index for Arabidopsis, we focus on aspects of the spatial distribution of neighbors: their number, distance and angular dispersion. We found that a best (or optimal) neighborhood radius can be resolved, which provides the best predictor of plant performance. Fecundity predictors based on adult neighbors were noticeably better than those based on neighbors at the seedling stage. Rosettes of Arabidopsis may change location during development (they fall over) and the new “fallen” positions do provide some improvement in the predictor. Taking into account distance to neighbors within the neighborhood provided only negligible improvement in the model. Finally, the incorporation of angular dispersion in the crowding index produced a considerably better fit. The fecundity predictor that included number of neighbors and angular dispersion in the crowding index explained about 70% of the variation in individual seed set.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Evolutionary ecology 10 (1996), S. 127-165 
    ISSN: 1573-8477
    Keywords: information transfer ; social interaction ; group size ; task allocation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary Social animals exchange information during social interaction. The rate of interaction and, hence, the rate of information exchange, typically changes with density and density may be affected by the size of the social group. We investigate models in which each individual may be engaged in one of several tasks. For example, the different tasks could represent alternative foraging locations exploited by an ant colony. An individual's decision about which task to pursue depends both on environmental stimuli and on interactions among individuals. We examine how group size affects the allocation of individuals among the various tasks. Analysis of the models shows the following. (1) Simple interactions among individuals with limited ability to process information can lead to group behaviour that closely approximates the predictions of evolutionary optimality models, (2) Because per capita rates of social interaction may increase with group size, larger groups may be more efficient than smaller ones at tracking a changing environment, (3) Group behaviour is determined both by each individual's interaction with environmental stimuli and by social exchange of information. To keep these processes in balance across a range of group sizes, organisms are predicted to regulate per capita rates of social interaction and (4) Stochastic models show, at least in some cases, that the results described here occur even in small groups of approximately ten individuals.
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  • 5
    Publication Date: 2014-06-01
    Description: Efforts to test and improve terrestrial biosphere models (TBMs) using a variety of data sources have become increasingly common. Yet, geographically extensive forest inventories have been under-exploited in previous model?data fusion efforts. Inventory observations of forest growth, mortality, and biomass integrate processes across a range of timescales, including slow timescale processes such as species turnover, that are likely to have important effects on ecosystem responses to environmental variation. However, the large number (thousands) of inventory plots precludes detailed measurements at each location, so that uncertainty in climate, soil properties, and other environmental drivers may be large. Errors in driver variables, if ignored, introduce bias into model?data fusion. We estimated errors in climate and soil drivers at U.S. Forest Inventory and Analysis (FIA) plots, and we explored the effects of these errors on model?data fusion with the Geophysical Fluid Dynamics Laboratory LM3V dynamic global vegetation model. When driver errors were ignored or assumed small at FIA plots, responses of biomass production in LM3V to precipitation and soil available water capacity appeared steeper than the corresponding responses estimated from FIA data. These differences became nonsignificant if driver errors at FIA plots were assumed to be large. Ignoring driver errors when optimizing LM3V parameter values yielded estimates for fine-root allocation that were larger than biometric estimates, which is consistent with the expected direction of bias. To explore whether complications posed by driver errors could be circumvented by relying on intensive study sites where driver errors are small, we performed a power analysis. To accurately quantify the response of biomass production to spatial variation in mean annual precipitation within the eastern United States would require at least 40 intensive study sites, which is larger than the number of sites typically available for individual biomes in existing plot networks. Driver errors may be accommodated by several existing model?data fusion approaches, including hierarchical Bayesian methods and ensemble filtering methods; however, these methods are computationally expensive. We propose a new approach, in which the TBM functional response is fit directly to the driver-error-corrected functional response estimated from data, rather than to the raw observations. # doi:10.1890/13-0600.1
    Print ISSN: 1051-0761
    Electronic ISSN: 1939-5582
    Topics: Biology
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