scholarly journals Estimating predator functional responses using the times between prey captures

2020 ◽  
Author(s):  
Kyle E. Coblentz ◽  
John P. DeLong
Keyword(s):  
Experimental Design ◽  
Statistical Method ◽  
Experimental Method ◽  
Functional Response ◽  
List Type ◽  
Proof Of Concept ◽  
Functional Responses ◽  
Predator Prey ◽  
Jumping Spiders ◽  
Wide Range

AbstractPredator functional responses, which describe how predator feeding rates change with prey densities, are a core component of predator-prey theory. Given their importance, ecologists have measured thousands of predator functional responses. However, most of these studies have used a single standard experimental method that is ill-suited to address many current, pressing questions regarding functional responses.We derive a new experimental design and statistical analysis that quantifies the parameters of predator functional responses by using the time between a predator’s feeding events and can be used with individual predators requiring only one or a few trials. We examine the feasibility of this experimental method and analysis by using simulations to examine the ability of the statistical model to estimate the ‘true’ functional response parameters from simulated data. We also perform a proof-of-concept experiment estimating the functional responses of two individual jumping spiders feeding on midges.Our simulations show that the statistical method is capable of reliably estimating functional response parameters under a wide range of parameter values and sample sizes. Our proof-of-concept experiment illustrates that the experimental design and statistical method provided reasonable estimates of functional response parameters and good fits to the data for individual jumping spiders using only a few trials per individual.By virtue of the fewer number of trials required to measure a functional response, the method derived here promises to expand the questions that can be addressed using functional response experiments and the systems for which functional responses can be measured. For example, this method is well-poised to address questions such as intraspecific variation in predator functional response parameters and the role of predator and prey traits and abiotic conditions on shaping functional responses. We hope, therefore, that this time-between-captures method will refine our understanding of functional responses and thereby our understanding of predator-prey interactions more generally.

scholarly journals Applying predator-prey theory to modelling immune-mediated, within-host interspecific parasite interactions

Parasitology ◽  
2010 ◽  
Vol 137 (6) ◽  
pp. 1027-1038 ◽  
Author(s):  
ANDY FENTON ◽  
SARAH E. PERKINS
Keyword(s):  
Functional Response ◽  
Interspecific Interactions ◽  
Parasite Load ◽  
Multiple Infections ◽  
Functional Responses ◽  
Predator Prey ◽  
Immune Activity ◽  
Parasite Communities ◽  
Immune Mediated ◽  
Predator Prey Models

SUMMARYPredator-prey models are often applied to the interactions between host immunity and parasite growth. A key component of these models is the immune system's functional response, the relationship between immune activity and parasite load. Typically, models assume a simple, linear functional response. However, based on the mechanistic interactions between parasites and immunity we argue that alternative forms are more likely, resulting in very different predictions, ranging from parasite exclusion to chronic infection. By extending this framework to consider multiple infections we show that combinations of parasites eliciting different functional responses greatly affect community stability. Indeed, some parasites may stabilize other species that would be unstable if infecting alone. Therefore hosts' immune systems may have adapted to tolerate certain parasites, rather than clear them and risk erratic parasite dynamics. We urge for more detailed empirical information relating immune activity to parasite load to enable better predictions of the dynamic consequences of immune-mediated interspecific interactions within parasite communities.

scholarly journals Permanence of Periodic Predator-Prey System with Functional Responses and Stage Structure for Prey

2008 ◽  
Vol 2008 ◽  
pp. 1-15 ◽  
Author(s):  
Can-Yun Huang ◽  
Min Zhao ◽  
Hai-Feng Huo
Keyword(s):  
Functional Response ◽  
Prey Species ◽  
Necessary Conditions ◽  
Stage Structure ◽  
Functional Responses ◽  
Predator Prey ◽  
Predator Prey Model ◽  
Prey System ◽  
Sufficient And Necessary Conditions ◽  
Holling Ii Functional Response

A stage-structured three-species predator-prey model with Beddington-DeAngelis and Holling II functional response is introduced. Based on the comparison theorem, sufficient and necessary conditions which guarantee the predator and the prey species to be permanent are obtained. An example is also presented to illustrate our main results.

Use of Functional Response Modeling to Evaluate the Effect of Temperature on Predation of Amblyseius swirskii (Acari: Phytoseiidae) Adults Preying on Tetranychus urticae (Acari: Tetranychidae) Nymphs

2021 ◽  
Author(s):  
Azadeh Farazmand ◽  
Masood Amir-Maafi
Keyword(s):  
Functional Response ◽  
Tetranychus Urticae ◽  
Attack Rate ◽  
Handling Time ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Temperature Threshold ◽  
Amblyseius Swirskii ◽  
Functional Responses ◽  
Wide Range

Abstract In this research, functional responses of Amblyseius swirskii Athias-Henriot preying on different Tetranychus urticae Koch nymphal densities (2, 4, 8, 16, 32, 64, and 128) were studied at eight constant temperatures (15, 20, 25, 27.5, 30, 32.5, 35 and 37.5°C) in a circular Petri dish (3-cm diameter × 1-cm height) under lab conditions. At all temperatures, the logistic regression showed a type II functional response. A nonlinear relationship was found between temperature and attack rate and the reciprocal of handling time. The reciprocal of handling time decreased exponentially with increasing temperature. In contrast, the attack rate grew rapidly with increasing temperatures up to an optimum, showing a decreasing trend at higher temperatures. In order to quantify the functional response of A. swirskii over a broad range of temperatures and to gain a better estimation of attack rate and handling time, a temperature-settled functional response equation was suited to our data. Our model showed that the number of prey consumed increased with rising prey density. Also, the predation rates increased with increasing temperatures but decreased at extremely high temperatures. Based on our model, the predation rate begins at the lower temperature threshold (11.73°C) and reaches its peak at upper temperature threshold (29.43°C). The coefficient of determination (R2) of the random predator model was 0.99 for all temperatures. The capability of A. swirskii to search and consume T. urticae over a wide range of temperatures makes it a good agent for natural control of T. urticae in greenhouses.

BIFURCATION AND CHAOS IN A DISCRETE PREDATOR–PREY MODEL WITH HOLLING TYPE-III FUNCTIONAL RESPONSE AND HARVESTING EFFECT

2021 ◽  
pp. 1-28
Author(s):  
ANURAJ SINGH ◽  
PREETI DEOLIA
Keyword(s):  
Functional Response ◽  
Sufficient Conditions ◽  
Flip Bifurcation ◽  
Bifurcation Structure ◽  
Bifurcation And Chaos ◽  
Predator Prey ◽  
Type Iii ◽  
Predator Prey Model ◽  
Prey Model ◽  
Wide Range

In this paper, we study a discrete-time predator–prey model with Holling type-III functional response and harvesting in both species. A detailed bifurcation analysis, depending on some parameter, reveals a rich bifurcation structure, including transcritical bifurcation, flip bifurcation and Neimark–Sacker bifurcation. However, some sufficient conditions to guarantee the global asymptotic stability of the trivial fixed point and unique positive fixed points are also given. The existence of chaos in the sense of Li–Yorke has been established for the discrete system. The extensive numerical simulations are given to support the analytical findings. The system exhibits flip bifurcation and Neimark–Sacker bifurcation followed by wide range of dense chaos. Further, the chaos occurred in the system can be controlled by choosing suitable value of prey harvesting.

Predator Ecology

2021 ◽  
Author(s):  
John P. DeLong
Keyword(s):  
Food Webs ◽  
Functional Response ◽  
Behavioral Ecology ◽  
Evolutionary Dynamics ◽  
Ecological Systems ◽  
Ecological Communities ◽  
Functional Responses ◽  
Predator Prey ◽  
Top Predators ◽  
Integrative Science

Predator-prey interactions form an essential part of ecological communities, determining the flow of energy from autotrophs to top predators. The rate of predation is a key regulator of that energy flow, and that rate is determined by the functional response. Functional responses themselves are emergent ecological phenomena – they reflect morphology, behavior, and physiology of both predator and prey and are both outcomes of evolution and the source of additional evolution. The functional response is thus a concept that connects many aspects of biology from behavioral ecology to eco-evolutionary dynamics to food webs, and as a result, the functional response is the key to an integrative science of predatory ecology. In this book, I provide a synthesis of research on functional responses, starting with the basics. I then break the functional response down into foraging components and connect these to the traits and behaviors that connect species in food webs. I conclude that contrary to appearances, we know very little about functional responses, and additional work is necessary for us to understand how environmental change and management will impact ecological systems

scholarly journals Space race functional responses

2015 ◽  
Vol 282 (1801) ◽  
pp. 20142121 ◽  
Author(s):  
Henrik Sjödin ◽  
Åke Brännström ◽  
Göran Englund
Keyword(s):  
Functional Response ◽  
Community Dynamics ◽  
Simple Structure ◽  
Functional Responses ◽  
Response Models ◽  
Predator Prey ◽  
Prey System ◽  
Space Race ◽  
Functional Response Models ◽  
The Relationship

We derive functional responses under the assumption that predators and prey are engaged in a space race in which prey avoid patches with many predators and predators avoid patches with few or no prey. The resulting functional response models have a simple structure and include functions describing how the emigration of prey and predators depend on interspecific densities. As such, they provide a link between dispersal behaviours and community dynamics. The derived functional response is general but is here modelled in accordance with empirically documented emigration responses. We find that the prey emigration response to predators has stabilizing effects similar to that of the DeAngelis–Beddington functional response, and that the predator emigration response to prey has destabilizing effects similar to that of the Holling type II response. A stability criterion describing the net effect of the two emigration responses on a Lotka–Volterra predator–prey system is presented. The winner of the space race (i.e. whether predators or prey are favoured) is determined by the relationship between the slopes of the species' emigration responses. It is predicted that predators win the space race in poor habitats, where predator and prey densities are low, and that prey are more successful in richer habitats.

scholarly journals Sequential experimental design for predator–prey functional response experiments

2020 ◽  
Vol 17 (166) ◽  
pp. 20200156 ◽  
Author(s):  
Hayden Moffat ◽  
Markus Hainy ◽  
Nikos E. Papanikolaou ◽  
Christopher Drovandi
Keyword(s):  
Experimental Design ◽  
Functional Response ◽  
Statistical Models ◽  
Sequential Monte Carlo ◽  
Design Method ◽  
Computationally Efficient ◽  
Estimation Model ◽  
Predator Prey ◽  
Experimental Design Method ◽  
Experimental Runs

Understanding functional response within a predator–prey dynamic is a cornerstone for many quantitative ecological studies. Over the past 60 years, the methodology for modelling functional response has gradually transitioned from the classic mechanistic models to more statistically oriented models. To obtain inferences on these statistical models, a substantial number of experiments need to be conducted. The obvious disadvantages of collecting this volume of data include cost, time and the sacrificing of animals. Therefore, optimally designed experiments are useful as they may reduce the total number of experimental runs required to attain the same statistical results. In this paper, we develop the first sequential experimental design method for predator–prey functional response experiments. To make inferences on the parameters in each of the statistical models we consider, we use sequential Monte Carlo, which is computationally efficient and facilitates convenient estimation of important utility functions. It provides coverage of experimental goals including parameter estimation, model discrimination as well as a combination of these. The results of our simulation study illustrate that for predator–prey functional response experiments sequential design outperforms static design for our experimental goals. R code for implementing the methodology is available via https://github.com/haydenmoffat/sequential_design_for_predator_prey_experiments .

scholarly journals Derivation of predator functional responses using a mechanistic approach in a natural system

2020 ◽  
Author(s):  
Andréanne Beardsell ◽  
Dominique Gravel ◽  
Dominique Berteaux ◽  
Gilles Gauthier ◽  
Jeanne Clermont ◽  
...  
Keyword(s):  
Functional Response ◽  
Prey Species ◽  
Mechanistic Model ◽  
Natural System ◽  
Field Observations ◽  
Functional Responses ◽  
Acquisition Rate ◽  
Predator Prey ◽  
Mechanistic Approach ◽  
Acquisition Rates

AbstractThe functional response is central to our understanding of any predator–prey system as it establishes the link between trophic levels. Most functional responses are evaluated using phenomenological models linking predator acquisition rate and prey density. However, our ability to measure functional responses using such an approach is often limited in natural systems and the use of inaccurate functions can profoundly affect the outcomes of population and community models. Here, we develop a mechanistic model based on extensive data to assess the functional response of a generalist predator, the arctic fox (Vulpes lagopus), to various tundra prey species (lemmings and the nests of geese, passerines and sandpipers). We found that predator acquisition rates derived from the mechanistic model were consistent with field observations. Although sigmoidal functional responses were previously used to model fox-prey population dynamics, none of our simulations resulted in a saturating response in all prey species. Our results highlight the importance of predator searching components in predator-prey interactions, especially predator speed, while predator acquisition rates were not limited by handling processes. By combining theory with field observations, our study provides evidences that predator acquisition rate is not systematically limited at the highest prey densities observed in a natural system. We reinforce the idea that functional response categories, typically types I, II, and III, should be considered as particular cases along a continuum. Specific functions derived with a mechanistic approach for a range of densities observed in natural communities should improve our ability to model and understand predator-prey systems.

scholarly journals Permanence of Periodic Predator-Prey System with General Nonlinear Functional Response and Stage Structure for Both Predator and Prey

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Xuming Huang ◽  
Xiangzeng Kong ◽  
Wensheng Yang
Keyword(s):  
Functional Response ◽  
Prey Species ◽  
Stage Structure ◽  
Functional Responses ◽  
Nonlinear Functional ◽  
Predator Prey ◽  
Prey System

We study the permanence of periodic predator-prey system with general nonlinear functional responses and stage structure for both predator and prey and obtain that the predator and the prey species are permanent.

scholarly journals Optimal experimental design for predator–prey functional response experiments

2018 ◽  
Vol 15 (144) ◽  
pp. 20180186 ◽  
Author(s):  
Jeff F. Zhang ◽  
Nikos E. Papanikolaou ◽  
Theodore Kypraios ◽  
Christopher C. Drovandi
Keyword(s):  
Experimental Design ◽  
Optimal Design ◽  
Functional Response ◽  
Optimal Parameter ◽  
Aphis Fabae ◽  
Optimal Experimental Design ◽  
Statistical Efficiency ◽  
Predator Prey ◽  
Designed Experiments ◽  
Robust Optimal Design

Functional response models are important in understanding predator–prey interactions. The development of functional response methodology has progressed from mechanistic models to more statistically motivated models that can account for variance and the over-dispersion commonly seen in the datasets collected from functional response experiments. However, little information seems to be available for those wishing to prepare optimal parameter estimation designs for functional response experiments. It is worth noting that optimally designed experiments may require smaller sample sizes to achieve the same statistical outcomes as non-optimally designed experiments. In this paper, we develop a model-based approach to optimal experimental design for functional response experiments in the presence of parameter uncertainty (also known as a robust optimal design approach). Further, we develop and compare new utility functions which better focus on the statistical efficiency of the designs; these utilities are generally applicable for robust optimal design in other applications (not just in functional response). The methods are illustrated using a beta-binomial functional response model for two published datasets: an experiment involving the freshwater predator Notonecta glauca (an aquatic insect) preying on Asellus aquaticus (a small crustacean), and another experiment involving a ladybird beetle ( Propylea quatuordecimpunctata L.) preying on the black bean aphid ( Aphis fabae Scopoli). As a by-product, we also derive necessary quantities to perform optimal design for beta-binomial regression models, which may be useful in other applications.

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