Community Dynamics

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Covariation between zooplankton community composition and cyanobacterial community dynamics in Lake Blaarmeersen (Belgium)

Covariation between zooplankton community composition and cyanobacterial community dynamics in Lake Blaarmeersen (Belgium)

zooplankton and phytoplankton communities are generally not independent of each other (Shapiro, 1995; Sarnelle, 2005; Abrantes et al., 2006), a significant and independent relationship was found with the cyanobacterial community composition, suggestive of direct effects. The rather low but significant correlation between the phytoplankton and the cyanobacterial community composition might reflect me- chanisms of phytoplankton succession and competition (Huszar & Caraco, 1998; Domingues et al., 2005; Huisman & Hulot, 2005). The correlation between the zooplankton and cyanobacterial community composition is relatively high. When this relationship is analysed further, it appears that the genus or species identity of zooplankton is more important than the major zooplankton group (copepods, cladocerans and rotifers) to which they belong. The impor- tance of the different zooplankton species present in the lake was confirmed by Mantel tests on the community composi- tion of the copepods, cladocerans and rotifers, respectively. Only the cladoceran community composition had a strong and unique influence on the cyanobacterial community dynamics. However, this finding needs to be interpreted with caution because of the lower taxonomic resolution of the copepod data (calanoids, cyclopoids, copepodites and nauplii) compared with those of cladocerans and rotifers (which were identified at the species or genus level), which may have obscured significant relationships. Daphnia and Bosmina were the most important grazing cladocerans in Lake Blaarmeersen and mainly Bosmina considerably influ- enced the cyanobacterial community dynamics. While Daphnia is a nonselective grazer, Bosmina grazes selectively (DeMott & Kerfoot, 1982) and can consume small as well as large food particles (Bleiwas & Stokes, 1985). Additionally, Bosmina might also indirectly influence the cyanobacterial community composition by grazing on heterotrophic nano- flagellates (DeMott & Kerfoot, 1982) because heterotrophic nanoflagellates graze in turn on small cyanobacteria (Nishibe et al., 2002). In principle, it is also possible that the cyanobacterial community influences the zooplankton abundance and composition, because some cyanobacteria
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A stochastic dispersal-limited trait-based model of community dynamics

A stochastic dispersal-limited trait-based model of community dynamics

Accepted manuscript Accepted manuscript lead to the exclusion of the most similar species (limiting similarity, MacArthur and Levins 1967). This limiting similarity should produce a statistical overdispersion of the traits present in a community. In species-rich communities like tropical forests, where understanding community dynamics is particularly challenging, the inclusion of data on species traits has proven fruitful: easily-measurable traits have been shown to explain roughly half of the variation in growth and mortality of trees (Poorter et al. 2008), and a significant part of their ranges and local abundances (Baltzer et al. 2008, Engelbrecht et al. 2007). This indicates that traits do bring relevant information in our understanding of community dynamics (Grime 2006, McGill et al. 2006, Westoby and Wright 2006). In this quest for a trait-based ecology, various statistical methods have been developed to relate the trait composition of a community to putative ecological mechanisms of community assembly. Tests for competition (Cornwell and Ackerly 2009, Kraft et al. 2008, Stubbs and Wilson 2004), and for environmental filtering (Cornwell et al. 2006, Villéger et al. 2008), enable to detect significant departures from a null model of random community assembly. The fourth-corner method (Dray and Legendre 2008, Legendre et al. 1997) relates traits to environmental features in order to explain species presence or abundances in given environmental conditions. Despite the rich insights brought by these approaches, they all suffer from a common shortcoming. Because they are not based on an explicit model of community dynamics, they are unable to quantify the impact of environmental constraints on basic properties of community dynamics such as immigration rate and difference in competitive ability among species. Also, they ignore stochasticity (Hubbell 2001), although the real community dynamics is certainly stochastic (Ellner & Fussmann 2003, Erjnaes et al. 2006, Fukami et al. 2005).
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Phytoplankton community dynamics during late spring coccolithophore blooms at the continental margin of the Celtic Sea (North East Atlantic, 2006–2008)

Phytoplankton community dynamics during late spring coccolithophore blooms at the continental margin of the Celtic Sea (North East Atlantic, 2006–2008)

2.1. Study area and general set-up of the campaigns The study area along the continental margin of the northern Bay of Biscay, on the shelf of the Celtic Sea included the La Chapelle Bank (LC), the Meriadzek Terrace (M), the Goban Spur (GS) area, and one station on the Armorican shelf ( Fig. 1 and Table 1 ). Three campaigns were carried out from the 31st of May to the 9th of June 2006, from the 10th to the 24th of May 2007, and from the 7th to the 23rd of May 2008, onboard RV Belgica. Eighteen stations were located in the vicinity of the La Chapelle Bank (47°N, 8°W) while eight stations were located over the shallow part (<200 m depth) of the Goban Spur (50°N, 10°W) ( Fig. 1 ). Eight deeper stations (from 450 to 1400 m depth) were located over the continental slope at the Meriadzek Terrace (48°N, 9°W) and the La Chapelle Bank ( Table 1 ). Each campaign consisted of two legs allowing some stations to be revisited with a 1–2 week interval ( Fig. 2 ). Revisited stations are denoted with a ‘‘b’’ following their numeral identifier. Due to shorter ship-time, sampling during the June 2006 campaign was limited to the area around the La Chapelle Bank, while during the two following campaigns sampling was carried in the whole area outlined above ( Fig. 1 and Table 1 ). Near real-time MODIS Aqua remote sensing images were used to track phytoplankton community dynamics through phases of emergence and disinte- gration of coccolithophorid blooms during the campaigns (see also Suykens et al., 2010 for SeaWIFS images of ths study area). In order to put the campaign periods into context we generated time-series of [chl a], normalised water-leaving radiance at 555 nm (Lwn (555)), and photosynthetically active radiation (PAR) using data from NASA’s Giovanni Ocean Color Radiometry 8-day Data Product Visualization portal ( http://gdata1.sci.gsfc.nasa.gov/ ; accessed on January 6th 2011) ( Fig. 3 ). Topographical information in Figs. 1 and 2 was obtained using ODV software (Schlitzer, R., Ocean Data View, http://odv.awi.de , 2011).
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Understanding social and community dynamics from taxi GPS data

Understanding social and community dynamics from taxi GPS data

CHAPTER 7. CONCLUSION AND FUTURE WORK 125 data sources from multiple domains become increasingly available. For example, many city agencies and authorities are making their data accessible for public usage (i.e., open data) 1 , which provides us with unprecedented opportunities to understand social and community dynamics in an integrated and holistic view. We believe that many more interesting ap- plications and urban services can be enabled if we couple the taxi GPS data with other complementary data sources. Our work in Chapter 6 has demonstrated the advantages of fusing the taxi GPS data and Foursquare check-in data. The future work will focus on exploring the complementary information provided by the cross-domain data sources to offer city planners and dwellers many insights and services that bring them closer to the vision of a smart city. Along this line, we list three promising directions for future research. ♦ Fusing personal mobile phone and smart card data to re/design better transportation network. The very basic problem of transportation network design is the estimation of city-wide OD flow. More accurate estimation of OD flow can be achieved if we integrate multiple data sources, such as mobile phone data, public transportation usage records data (i.e. smart card data), and taxi GPS data. Specifically, given the fact that mobile phone have become an essential element in the lives of most people in many countries, it is clear that it can reveal the population movement flows among different city regions to a large degree. The public transportation usage records data reflect the actual OD flow in the current transportation networks in a fine spatial and temporal granularity (i.e. the actual OD flow among different stations at different time slots). The taxi GPS data can inform us a very high resolution of taxi passenger flow (i.e., from which point to which point in the city at what time). These different data sources reflect different aspects of the OD flow, and therefore, with appropriately integrating them, we can plan new effective public routes, examine and redefine the current transportation networks. Further more, coupling with the POI data, we can design even better transportation network.
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Community dynamics and sensitivity to model structure: toward a 1 probabilistic view of process-based model predictions 2

Community dynamics and sensitivity to model structure: toward a 1 probabilistic view of process-based model predictions 2

All panels are drawn similarly as in earlier figures: (a) functional responses are fitted to data by a HMCMC algorithm; (b) av- erage qualitative predictions (probabilistic bifurcation d[r]

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Microbial community dynamics during composting of sewage sludge and straw studied through phospholipid and neutral lipid analysis

Microbial community dynamics during composting of sewage sludge and straw studied through phospholipid and neutral lipid analysis

This shift in the composition of fatty acids and sterols dur- ing composting points to a change from Gram-negative bacteria to a community with more Gram-positive bacteria and fungi. In fact, Gram-positive bacteria are often reported as being the part of the microbial community responsible for the decomposition of organic residues in the thermophilic phase [8,38,54–55] . Some fungi continue the decomposition process instead of bacteria in the maturation mesophilic phase, because they are more efficient at breaking down more recalcitrant organic polymers such as lignins or “tough debris”. Thus, at the end of composting, the decline of the bacterial population resulting from the exhaustion of readily degradable substrate, and the predominance of fungi which prolif- erate on the remaining less degradable organic matter indicates the good progress of decomposition and stability of the initial material to be composted, and hence the good quality of the end compost. 4. Conclusion
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Frenkelia parasites in a small mammal community. Dynamics of infection and effect on the host.

Frenkelia parasites in a small mammal community. Dynamics of infection and effect on the host.

Year, season, habitat, host sex, age and relative density effects on prevalence were analysed with a multiple logistic regression using a binary factor (infected = 1, non infected = [r]

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Effects of elevated carbon dioxide on freshwater plankton community dynamics

Effects of elevated carbon dioxide on freshwater plankton community dynamics

In a whole-ecosystem experimental manipulation of a stratified lake, we demonstrated that when epilimnetic dissolved C02 levels were doubled (pC02 raised from 700ppm to 1400[r]

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Structure, long-term dynamics, and demography of the tree community

Structure, long-term dynamics, and demography of the tree community

depth, e.g., Crossopteryx febrifuga, during the dryseason [48]. Konat´ e et al. [47] measured a slower leaf fall for Crossopteryx febrifuga trees growing on termite mounds, which are spots of higher shallow water availability, than for trees growing in the open; this difference was absent for a deep rooted species like Cussonia arborea. On the contrary, water affects community dynamics when it is too abundant, e.g., in the hydromorphic soils of flat areas domi- nated bythe grass Loudetia simplex (Sect. 5.2). In these areas, tree survival seems impossible except on mounds located above the water table (Fig. 18.1). However, there is evidence that water stress in these areas is even stronger than in the Andropogoneae savannas.
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Challenges in microbial ecology: building predictive understanding of community function and dynamics

Challenges in microbial ecology: building predictive understanding of community function and dynamics

Kinetic models for community dynamics Kinetic models, such as the widely used Monod equation, aim to predict microbial growth rate, given the concentrations of essential nutrients and/or inhibitory chemicals, and species-dependent parameters such as the maximal growth rate (Figure 3). Extending this approach to the commu- nity level is attractive because it is conceptually simple, computationally tractable and provides dynamical predictions. However, its success depends on identification of the most important microbial species to include in the model, and the interactions between them. Moreover, the reliability of the approach depends crucially on the underlying kinetic growth model and its parameters—thus large- scale measurement of kinetic growth parameters for a variety of microbial species would be extremely useful. More fundamentally, existing kinetic growth models are often ‘ad hoc’ and may miss aspects of the growth kinetics that are important in community function, such as product inhibition. To address this problem, new kinetic models are being developed that include features like condition-dependent changes in the maximal growth rate (Bonachela et al., 2011; Desmond-Le Quemener and Bouchez, 2014) and the thermodynamics of microbial meta- bolism (Jin et al., 2013). In particular, the inclusion of thermodynamics in kinetic growth models has contributed to improved modelling of MCs, for example in anaerobic waste treatment (Gonzalez- Cabaleiro et al., 2013).
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Eco-evolutionary dynamics of nested Darwinian populations and the emergence of community-level heredity

Eco-evolutionary dynamics of nested Darwinian populations and the emergence of community-level heredity

The extent to which the conclusions based on our simple abstract model are generally applicable to the evolution of more complex associations, such as symbioses leading to new forms of life, will require future exploration of a broader range of particle-level ecologies. Possibilities to make community dynamics more realistic by complexifying mathematical descriptions of particle-level processes are plentiful ( Williams and Lenton , 2007 ; Zomorrodi and Segr`e , 2016 ). Of particular interest for the evolution of efficient developmental correc- tion are cases when community ecology has multiple attractors ( Penn and Harvey , 2004 ), is highly sensitive to initial conditions ( Swenson et al. , 2000b ), or presents finite-e↵ect muta- tions sustaining “eco-evolutionary tunnelling” ( Kotil and Vetsigian , 2018 ). Besides enlarging the spectrum of possible within-collective interactions, future relevant extensions may ex- plore the role of physical coupling among particles and of horizontal transmission between collectives ( van Vliet and Doebeli , 2019 ) in enhancing or hampering efficient inheritance of collective-level characters.
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Empirical phylogenies and species abundance distributions are consistent with preequilibrium dynamics of neutral community models with gene flow

Empirical phylogenies and species abundance distributions are consistent with preequilibrium dynamics of neutral community models with gene flow

12 conditions, where the founding species occupies a single deme (Fig. 2A), but we were still able to do so in our mixed colonisation conditions, where the founding species occupies half of the demes (Fig. 2B). In summary, we found that a necessary condition for obtaining realistic trees with our model was that an initially abundant and widespread species diversifies through local speciation into a set of rarer species. Such initial conditions may correspond to an ecological scenario in which a virgin territory is colonised from a distant source, with the initial species first dispersing across the entire territory before starting to speciate. An alternative scenario is the colonisation of a new niche after the evolution of an innovation, if this results in a new species that is very successful and thus abundant and widespread. Whilst this setting invokes an adaptive (i.e. non-neutral) explanation for the formation of a new guild, the following radiation dynamics within that guild can be neutral. Indeed, our results suggest that if the original widespread species diversifies into rarer (less likely to diversify) species, a slowdown in diversification rates emerges even if these new species are all functionally equivalent, and thus does not necessarily reflect the saturation of ecological niche space.
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Survey on Social Community Detection

Survey on Social Community Detection

TThis class of methods remains atypical, yet a number of authors have at- tempted its implementation. The input data is a normal graph, while the out- put is a list of node groups representing the communities of the initial graph; these communities may indeed overlap. The result could be represented as a hypergraph. The survey [57] mentions several methods without providing any description along with two surveys [18, 54] that describe methods found in this class. The most famous of such methods is ”Clique percolation”; this algorithm devised by Palla et al. [15] speculates that the internal edges of a community are likely to form cliques due to their high density. On the other hand, it is unlikely that intercommunity edges form cliques. Palla et al. use the term k-clique in reference to a complete graph with k vertices. Two k-cliques are adjacent if they share k-1 vertices. The union of adjacent k-cliques constitutes s a k-clique chain. Two k-cliques are connected if they form part of a k-clique chain. Moreover, a k-clique community is the largest connected subgraph obtained by uniting a k-clique with all k-cliques con- nected to it. Several authors have proposed improvements to this method given that the computing time may increase exponentially with the number of nodes or edges in the graph. This method has been determined to provide good results.
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Community-Driven Language Development

Community-Driven Language Development

II. T OWARDS A COMMUNITY - DRIVEN DEVELOPMENT PROCESS FOR DSL S In this section we will show how we propose to transform traditional language development processes into community- aware ones. We call community to the group of users of the DSL, where by users we mean both the (1) technical level users (i.e., the language developers) and (2) domain expert users (i.e., the end-users of the language). These categories may be overlapping, especially when the DSL is a technical DSL (e.g., if the DSL is aimed to write configuration files then the domain experts may be also technical-savy enough to create the language themselves). In any case, the collaboration needs in both cases are the same.
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Modeling the fish community population dynamics and forecasting the eradication success of an exotic fish from an alpine stream

Modeling the fish community population dynamics and forecasting the eradication success of an exotic fish from an alpine stream

juveniles to become adults in the removal area, Right Hand Fork). In addition, exotic brown trout that emigrated out of the tributary could just as easily migrate further upstream in the mainstem (versus down- stream into the study area). Nonetheless, evaluating the importance of tributaries on mainstem population dynamics could be possible by si- mulating our 1D model over interconnected stream sections composing the river's hydrological network. Running the model at this extended spatial scale would require either (1) more assumptions regarding whether or not stream section specific parameters are equal or similar to each other, (2) more data, across the hydrological network in order to calibrate stream section specific parameters, or (3) well-defined re- lationships between model parameters and covariates (also requiring data for calibration) that could be used to predict stream section-spe- cific parameter values. This is another area fruitful for future con- sideration, but it would require acquisition of some data currently un- available even for this well studied population. In addition, Mohn (2016) found little evidence of spatial population structure in a recent complimentary mark-recapture and genetics study.
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Reflections on the Prison as Community

Reflections on the Prison as Community

PCAP is a bridge that helps prisoners rediscover and reconnect to themselves and to the community. I am blessed to have access to such a valued bridge. REFERENCES Pew Center on the States (2008) One in 100: Behind Bars in America 2008, Washington: The Pew Charitable Trusts – February. Retrieved from http://www. pewcenteronthestates.org/uploadedFiles/8015PCTS_Prison08_FINAL_2-1-1_ FORWEB.pdf.

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Community data portraiture : perceiving events, people, & ideas within a research community

Community data portraiture : perceiving events, people, & ideas within a research community

determining what questions are applicable to represent a community data portrait for communities of the size and scale of the MIT Media Lab.. A third contribution is the un[r]

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Multiple Local Community Detection

Multiple Local Community Detection

6.3 Synthetic data We evaluate our algorithm on synthetic graphs generated with the Stochastic Block Model (SBM) [10]. We illustrate the results of MULTICOM on such a synthetic graph in Figure 3. In the sub-figure (a), we display the new seeds found by the algorithm when initialized with an initial seed colored in red in the figure. In the sub-figure (b), we display the corre- sponding communities returned by the algorithm. Note that some communities are overlapping i.e. some nodes belong to more than one community.

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Individual-based simulation of the spatial and temporal dynamics of macroinvertebrate functional groups provides insights into benthic community assembly mechanisms

Individual-based simulation of the spatial and temporal dynamics of macroinvertebrate functional groups provides insights into benthic community assembly mechanisms

Spatial correlation Mantel correlograms were used to quantify spatial correlation in the multivariate domain of functional group abundances. The technique is based on calculation of the normalized Mantel statistic between pairs of site dissimilarity matrices. One matrix in each pair quantifies differences in multivariate community composition and the other is derived by attributing the value 0 to pairs of sites that belong to the same distance class and the value 1 to all other pairs of sites. The process is repeated for each distance class and values of the Mantel statistic are tested by permutations. Mantel correlograms were produced for the 113 stations that were sampled in the Rance estuary in 1995 and the output of the 1st, 2nd, 3rd and 10th year of the benchmark simulation in 113 cells selected out of the 230 cells of the coarse-scale model (see section Sensitivity analysis). Distances in the model were measured between the cells’ centers of symmetry, by assuming cell dimensions of 450 m  450 m. The tables of group abundances were Hellinger- transformed and Holm’s correction for multiple testing was applied to the permutation tests. The number of distance classes was in each case based on Sturge’s rule and the correlograms were restricted to distances that included all sites ( Borcard, Gillet & Legendre, 2011 ).
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Banking on the future : the role of bank community development corporations in community development

Banking on the future : the role of bank community development corporations in community development

This thesis presents case studies of three models of bank CDCs-- Black Business Investment Corporations, North Carolina National Bank CDC, and Chemical Community De[r]

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