Determining Parameters of the Numerical Response

Montagnes, David J. S.; Berges, John A.

doi:10.1007/s00248-003-9000-y

Cited by 24 publications

(25 citation statements)

References 13 publications

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“…Specifically, the solution of Equation (1) (that is, Equation 2) was fit to the responses of prey abundance (P t ) vs time (t), using the Marquardt-Levenberg algorithm (SigmaPlot, V 11, Systat Software Inc., San Jose, CA, USA) to obtain estimates of K, m and y (see Table 2). Revising microbial predator-prey models Z Yang et al O. marina response to prey and temperature O. marina was acclimated (2 days) to constant experimental prey levels (with more measurements at low levels; see Montagnes and Berges, 2004) at 20 1C and 26 1C, under the conditions described above (see D. primolecta growth response). Prey treatment levels ranged from near zero to where prey growth reached stationary phase (as determined experimentally, see Results section); such high levels of prey (similar to D. primolecta) can occur in coastal waters where O. marina exists (for example, Begun et al, 2004).…”

Section: Primolecta Growth Responsementioning

confidence: 99%

“…It may seem that the scatter of our data is high, but it is typical for estimates of functional and numerical responses of protozoa (for example, Kimmance et al, 2006), and by performing many measurements across the prey range, especially with a focus on lower prey abundances, it is possible to obtain powerful, average estimates of parameters associated with the functional and numerical responses (Montagnes and Berges, 2004). Following this procedure, we have established functional and numerical responses that reveal significant differences in their parameters (Figure 3).…”

Section: Multiple Predator Responsesmentioning

confidence: 99%

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Strain-specific functional and numerical responses are required to evaluate impacts on predator–prey dynamics

et al. 2012

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We used strains recently collected from the field to establish cultures; then, through laboratory studies we investigated how among strain variation in protozoan ingestion and growth rates influences population dynamics and intraspecific competition. We focused on the impact of changing temperature because of its well-established effects on protozoan rates and its ecological relevance, from daily fluctuations to climate change. We showed, first, that there was considerable inter-strain variability in thermal sensitivity of maximum growth rate, revealing distinct differences among multiple strains of our model species Oxyrrhis marina. We then intensively examined two representative strains that exhibited distinctly different thermal responses and parameterised the influence of temperature on their functional and numerical responses. Finally, we assessed how these responses alter predatorprey population dynamics. We did this first considering a standard approach, which assumes that functional and numerical responses are directly coupled, and then compared these results with a novel framework that incorporates both functional and numerical responses in a fully parameterised model. We conclude that: (i) including functional diversity of protozoa at the sub-species level alters model predictions and (ii) including directly measured, independent functional and numerical responses in a model provides a more realistic account of predator-prey dynamics.

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Section: Primolecta Growth Responsementioning

confidence: 99%

Section: Multiple Predator Responsesmentioning

confidence: 99%

Strain-specific functional and numerical responses are required to evaluate impacts on predator–prey dynamics

et al. 2012

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“…Possibly the relationship between p′ and temperature is species-specific. On the other hand, experimental error or methodological limitations may also result in deviations (Montagnes & Berges 2004). Nevertheless, higher p′ values at high temperatures would mean that a predator dies from starvation rather than being consumed by other predators, and this is critical for modeling food webs (Montagnes 1996). )…”

Section: Threshold Prey Concentrationmentioning

confidence: 99%

Growth and grazing responses to temperature and prey concentration of Condylostoma spatiosum, a large benthic ciliate, feeding on Oxyrrhis marina

Chengchun¹,

Xu²,

Lei³

2011

Aquat. Microb. Ecol.

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Condylostoma is as a group of very large-sized ciliates frequently dominant in various marine benthic microbial communities. However, little is known about the effects of temperature and food concentration on its growth and grazing. Here, using the heterotrophic dinoflagellate Oxyrrhis marina as prey, we determined the specific growth rate, cell volume, specific production, and ingestion rate of C. spatiosum at different temperatures and prey concentrations. These growth and grazing parameters typically followed a hyperbolic response to prey concentration. By applying iterative curve-fitting to the data at each temperature, we found that, with increasing temperature, the maximum specific growth rate, maximum specific production, and maximum ingestion rate of C. spatiosum generally increased, while the maximum cell volume decreased. The gross growth efficiency of C. spatiosum generally decreased at saturated prey concentration from about 45 to 25% as the temperature increased from 12 to 24°C. By fitting these data iteratively to multi-variable nonlinear models, we obtained predictive equations for the growth rate, cell volume, and ingestion rate with respect to temperature and prey concentration. KEY WORDS: Benthic ciliate · Growth rate · Ingestion rate · Gross growth efficiency · Prey concentration · TemperatureResale or republication not permitted without written consent of the publisher Aquat Microb Ecol 64: 97-104, 2011 dinoflagellate that has the potential to control red-tide organisms (Jeong et al. 2003, Lowe et al. 2005. In order to gain a better understanding of the effects of temperature and prey concentration on benthic ciliate population dynamics, we investigated the growth and grazing responses of C. spatiosum feeding on O. marina at a range of temperatures and food concentrations. Based on the data obtained, we developed predictive models that will allow us to estimate the growth and grazing rate of C. spatiosum within given ranges of temperature and food concentration. MATERIALS AND METHODSStudy organisms. The size of the ciliate Condylostoma spatiosum was on average 700 × 80 µm (n = 20) and the dinoflagellate Oxyrrhis marina was on average 29 × 16 µm (n = 20) in vivo. Both species were isolated from the intertidal sediment of the Licun River estuary at Qingdao, China, in July 2007 and were maintained in Petri dishes containing bacterized rice-grain medium at room temperature.Experimental design. Experiments were run in Petri dishes (diameter 90 mm) in dim light (1.2 to 2.0 µmol m -2 s -1) under a 12 h light:12 h dark cycle. The experimental volume in each plate was 20 ml. Ciliates were taken from the exponential growth phase and were adapted to the experimental temperature and prey concentration for at least 24 h before the beginning of the experiments.Growth and ingestion experiments were run separately at the temperatures of 12, 15, 18, 21, and 24°C. Each treatment was conducted with 20 prey concentrations ranging from about 8 × 10 2 to 1.3 × 10 4 cells ml -1 (corresponding to 0.21 t...

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“…We also encourage continued careful design of experiments, e.g. considering pseudoreplication (Hurlbert 1984), the number of replicates (Roa 1992), and even whether or not to replicate at all (Montagnes & Berges 2004).…”

Section: Experimental Designmentioning

confidence: 99%

Selective feeding behaviour of key free-living protists: avenues for continued study

Montagnes¹,

Barbosa²,

Boenigk³

et al. 2008

Aquat. Microb. Ecol.

177

154

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Phagotrophic protists are diverse and abundant in aquatic and terrestrial environments, making them fundamental to the transfer of matter/energy within their respective food webs. Recognising their grazing impact is essential to evaluate the role of protists in ecosystems, and this includes appreciating prey selectivity. Efforts have been made by groups and individuals to understand selective grazing behaviour by protists: many approaches and perspectives have been pursued, not all of which are compatible. This article, which is not a review, is the product of our discourse on this subject at the SAME 10 meeting. It is the work of individuals, assembled for their breadth of backgrounds, approaches, views, and expertise. Firstly, to communicate ideas and approaches, we develop a framework for selective feeding processes and suggest 6 steps: searching, contact, capture, processing, ingestion, digestion. We then separate study approaches into 2 categories: (1) those examining whole organisms at the community, population, and individual levels, and (2) those examining physiology and molecular attributes. Finally, we explore general problems associated with the field of protistan selective feeding (e.g. linking food selection into food webs and modeling). We do not present all views on any one topic, nor do we cover all topics; instead, we offer opinions and suggest avenues for continued study. Overall, this paper should stimulate further discourse on the subject and provide a roadmap for the future.

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Determining Parameters of the Numerical Response

Cited by 24 publications

References 13 publications

Strain-specific functional and numerical responses are required to evaluate impacts on predator–prey dynamics

Strain-specific functional and numerical responses are required to evaluate impacts on predator–prey dynamics

Growth and grazing responses to temperature and prey concentration of Condylostoma spatiosum, a large benthic ciliate, feeding on Oxyrrhis marina

Selective feeding behaviour of key free-living protists: avenues for continued study

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