Questions related to Population Dynamics
Imaging that for modelling convenience we take dependent variables as independent in order to simplify the world, that would lead to conflicting schools of thoughts addressing the same issue in a compartamentalized manner. In other words using independent variable thinking to address system stability analysis should be expected to lead different rootcausality, and to different, a competing approaches on how to address the same system stability issue. Think for example.of system stability frameworks based on market dynamics and population dynamics and environmental concerns. Which lead to the question: Would wrongly assuming that dependent variables are independent provide a distorted view of the problem?
What do you think?
What is the difference between social evolution and social progress and type of evolutionary force occurs when a population decreases to a small breeding population?
As length data is used to estimate different population dynamics parameters, I want to know what parameters are obtained using the age data and how the data of age of the fish needs to be framed to get accurate results.
How do we calculate theoretical age at zero length (to) in fish population dynamics? Can we take the antilog of Pauly's equation of Log (to) to calculate the same?
Population dynamics is usually linked to system stability. For example, over population is linked to system unsustainability, and possible system collapse through overshooting behavior like ecological overshoot. Population dynamics is rarely linked to market pricing structures as markets are usually presented as supply and demand interactions consistent with their price structures. But market price structures can be seen as linked to the nature of the population they serve. Hence, population dynamics appears to be the connection between market price structure and system stability.
And this raises the question, Is population dynamics the link between market pricing and system stability? I think yes, what do you think?
Please, feel free to share your comments, Yes and why you think is Yes or No, and why you think is No.
I am wondering how one determines the appropriate size of a Leslie Matrix. This is one of the first decisions made in constructing a Leslie matrix model and it determines the number of age groups, the age class width, and the projection interval. Is bigger always better? In other words, is it always better to have more age classes if the data allow?
We hear about environmental problems or social problems or socio-environmental problems associated with business as usual, problems being exacerbated currently by over population pressures and overshooting pressures. Hence, all those problems and pressures seem to be associated with non-optimal market conditions in practice, but conditions that are assumed to be optimal in theory, hinting towards a practice-theory inconsistency problem.
And this raises the question, Is the destruction of full optimality at the heart of system unsustainability problems? I think yes, what do you think?
Note: Moving away from full optimality thinking is what is meant here when saying "the destruction of full optimality".
Please, feel free to express your own views on the question, Yes, and why you think so? No, and why you think so?
I have 3 large household cross-section data sets each 13 years apart, starting 1992-93. I want to test the stability of coefficients across the 3 points estimated from structural reduced form single equation demographic transition model.
According to the census 2011 uttarakhand had 1048 uninhabited village. in 2017, 734 more villages added in the list. According to some resources and agencies there are more than 800 villages which have the decreasing population more than 50% from 2017 to 2021.
i am working on my PG thesis on above topic. any lead for the same will be appreciated and much helpful for my report.
The objective is to (1) determine the distribution and limits of a population in a given area, (2) to determine all species present in the area, (3) to determine the relative abundance (apparent density) of each species present in time and space. I would be grateful for your input on challanges and solutions for these tasks... i.e. what are the requirements for a baseline-survey etc.
(Landscape scale would be approx. 900 ha or more.)
I plan to estimate the probability that the Ussuri dhole (Cuon alpinus alpinus) is extant in Russia and test the null hypothesis that extinction has not occurred. Based on several analytical papers and reviews (Solow, 2005; Rivadeneira et al., 2009; Lee et al., 2013; Clements et al., 2013; Boakes et al., 2015) I choose the Bayesian approach (Solow, 1993) and Optimal Linear Estimation (OLE) (Roberts and Solow, 2003).
I decided to use 'sExtinct' R-package (Clements, 2013) for OLE calculation.
Firstly, I tested the package on the sighting record of the Caribbean monk seal (Solow, 2005) and the Dodo (Roberts and Solow, 2003) (I attached a file with my script). Surprisingly, but the output of calculation in the package (lowerCI and upperCI) is discordant with the corresponding estimation in the original papers (Solow, 2005; Roberts and Solow, 2003).
For example, according to Solow's estimation (2005), the upper bound of the 0.95 confidence interval for the Caribbean monk seal is 2028. The 'sExtinction' package estimated the upper bound as 2093.799.
I received a similar result for Dodo: Roberts and Solow estimated the upper bound (95%) as 1797; the 'sExtinction' package gave out 1834.568.
I am at a loss. Where is the bug?
So, there is the question:
Can I use the 'sExtinction' package or I should write my own code by the description in original papers?
I invite @Christopher_Clements, @T_Lee2, @Marcelo_Rivadeneira, @Simon_Blomberg, @Diana_Fisher, and everyone for discussion.
I highly appreciate if the suggested topic relates on the application of graph theory in environmental science, particularly on the population/competition dynamics.
In a Next Generation Matrix, the dominant eigenvalue (or spectral radius) corresponds to R0 (Diekmann, O., Heesterbeek, J. A., & Roberts, M. G., 2010).
What information then carry the remaining (non-dominant) eigenvalues of this matrix? Can they inform us about other dynamics of an epidemic?
A population decline (or depopulation) in humans is a reduction in a human population caused by events such as long-term demographic trends, as in sub-replacement fertility, urban decay due to violence, disease, or other catastrophes. According to a controversial theory: shrink and prosper, the accompanying benefits of depopulation could be identified after the post-Civil War Gilded Age, post-World War I economic boom, and the post-World War II economic boom.
I have come across some Nonlinear Control System problems where I need to implement Matlab code but unfortunately, it's getting too tough to start with. I can some of the problems such as,
1. Population Dynamics using Lotka–Volterra differential equations.
2. Continuous Stirred Tank Reactor (CSTR) using van–der–Vusse
3. PI Controller for Linear and Nonlinear system
A total of 50 individuals of the species were collected monthly from sampling area for 13 months to study population dynamics of this bivalve. I have always understood that we need at least 30 to be able to reasonably expect a statistical analysis, but I heard lately that it was not enough! what do you think about this please? Is there a specific condition for determining the sample size?
I am interested in identifying sex-specific survival rates. I have a long-term dataset of individually marked birds from one breeding colony. Of these, I am able to genetically sex a subset. Additionally, I have access to mark-recapture data on nearby breeding colonies and so can estimate emigration from my target breeding colony. However, I am only able to sex individuals from my focal breeding colony.
My research project addresses both survival and dispersal (permanent emigration). So I'd like to disentangle these as much as possible and look at effects of sex. One approach is to only model the subset of birds I'm able to sex. Another approach would be to model all individuals, including unknown sex, and apply the techniques in Nichols et al. (2004) to apply probabilities of "male or female" to unknown-sex birds (I may be summarizing that poorly).
Can I use a multi-site model if I only include individuals marked on one colony, but do have data for permanent emigration to other colonies? Would it make sense to use a multi-site model with all individuals from all colonies but only have sex information from one colony?
Thanks in advance!
Nichols, J.D., Kendall, W.L., Hines, J.E. and Spendelow, J.A. 2004. Estimation of sex‐specific survival from capture–recapture data when sex is not always known. Ecology 85(12):3192-3201.
Fluctuations in population numbers, abundance, or density from one time step to the next are the norm. Population cycles make up a special type of population fluctuation, and the growth curves in population cycles are marked by distinct amplitudes and periods that set them apart from other population fluctuations. In the animal kingdom, it may be explained that this fluctuation is the result of a change in the food chain and the density of consumers' arrangement, which over the years entails increases and decreases in the size of the population. But the situation is different in the plant kingdom: the plant may be lost and disappear for a long time in one region, and then it will return strongly and disappear in another region and so on. Some may explain this by the presence of seeds in the soil, which allow the plant to return from the dark. The reason for its disappearance may be natural as a result of climate change or the destruction of environments and others. Generally, this fluctuation is normal, but when is the matter dangerous, worrying and warranting intervention? How can we expect that the plant will return after its disappearance in a region?
I am working on a paper that looks into the dynamics of the spread of Wolbachia and its potential impact on dengue transmission, particularly in the Philippines.
Are there any cyclical animal populations in the tropic?
I've been writing an evolutionary biology hypothesis, that claims that cyclical animal populations are actually a population-wide multi-year hormone cycles; not that different from menstrual cycles: https://www.researchgate.net/project/80-year-generational-hypothalamic-hormone-cycle-spanning-across-4-generations
The current assumption is that the annual changes in daylight enables the "counting" of years for biology, but since the amount of daylight is quite stable in the tropic, the "counting" of years wouldn't be possible there. This is why I'm asking: are there any cyclical animal populations in the tropic? The requirements are that the cycle is multi-year and has similar characteristics compared to the other cyclical populations (of lemmings, voles, hares, etc.)
In a population dynamical system, the non-explosion property is often not good enough but the property of ultimate boundedness is more desired. The conditions for the ultimate boundedness are much more complicated than the conditions for the non-explosion.
The nonexplosion property in a population dynamical system is often not good enough but the property of ultimate boundedness is more desired
What is the effect of increasing or decreasing population size and the number of iterations on the quality of solutions and the computational effort required by the Swarm Intelligence algorithms?
Kite diagramme that i am expecting to draw is population dynamics of animals in a national park Sri Lanka over period from Jan 2018 to Dec 2019.
I am currently pursuing my Ph.D. in fisheries, Can you assist me with knowing how to apply R in fish modeling as this would help me in analyzing my data. If there is any opportunity to use your lab too I will be very grateful.
I am studying Lake Tana Fisheries. Some species currently found under the IUCN list.
Some driving forces are irrigation and sand mining on their spawning grounds, overfishing, drought, waste from agriculture and urbanization, invasive species like water hyacinth. So, recently, some species are critically treated. I want to know the whole the species population structure from the lake, their status from their spawning grounds (tributary rivers), population dynamics, the extent of impact levels due to the above driving forces, population genetics from lake and rivers.
So, I am happy any one help me which type of models, methodology and share me your experience or any recent related works
In many publications on the topic of modelling residential mobility I read, agents are regarded as households and can only make decisions (here relocating) as one single entity. The question whether an agent with given characteristics has a propensity for changing housing or not is often answered for an entire household. Restricting households to only be able to stay or move as a whole seems not appropriate. An alternative would be to compute/model on the individual level and take the household type into consideration. However, individuals as part of a household should still be able to move together which would be rather unlikely in this case. How is this taking care of in research?
I'm performing a length-weight relationship in two populations of caridean shrimps (they are from two distinct seasonal periods), the pooled data was divided into males, females, non-ovigerous females and ovigerous females. I performed the equation and obtained the b slopes of each sub-sample analyzed, but now I want to compare those slopes to know if there is any different between them. I read that I could do an ANCOVA to compare, but I'm not sure if there is another methodology. Thank you.
I was able to set the scenario (code provided) but bit unsatisfied. I would like ghost population to reach near 0 or 1 (time scale) as I am not sure whether unsampled population exists today. How to set the code so that ghost population appears distinct in the scenario picture and reaches to current time scale?
I have observed that the population dynamics models are having non-negativeness, boundedness and uniqueness as their essential part and it is mentioned in the literature many times, but I do not know the reason behind it. Please put light on it.
Thank You in advance.
I have done morphology, population dynamics and Phylogenetic analysis of some cockroach nematodes. How to do advance work in that. Please suggest.
A two year insect population dynamics data shows slight variation in their performances w.r.t meteorological parameters. Data pooling will be helpful for me?
I am seeking suggestions on some field methods for analyzing Population Viability Analysis (PVA).
Is there any paper on how floaters develop 'territoriality' between them in birds? As they are not territorial individuals per se, I wondering if there is some background on how they exploit resources on different ways, being some of them more associated with high-quality resources whereas others not, mainly due to agonistic behavior.
I am searching for ways to promote lizard and amphibian capacities as a profit from the restauration of their habitat in private gardens.
Therefore I need evidence of these actions
Second picture shows the mosaic highly found in our project of okra under the varietal screening under the different control practices. But difficult to say what may be this??
Similarly the first picture shows the reddening on the vein on under surface of leaves. This case was found even after the spray of different pesticides i.e. botanicals to chemicals. The pest population dynamics was high with majority of nymph of jassids and whitefly too.
I encounter this species every spring while completing surveys around the NSW Central Coast. This species is listed as vulnerable under both the NSW Biodiversity Conservation Act and the Commonwealth EPBC Act.
Its a beautiful little plant, but I often hear botanists complain that this species is too common to be considered rare, and therefore should be delisted from each of the acts.
I'm interested in what other botanists think about this. Particularly, those with knowledge of plant population dynamics and evolution.
I have gathered samples of Dreissenid mussels at different locations in a lake. After counting and measuring the mussels, histograms featuring the number of individuals per shell length ranging from ≤0.4cm to 3.5cm have been created, most of which are showing multimodal distributions but some are unimodal, too.
What is being tried to do, apart from visually determining the size-frequency distributions, is to apply a statistical mathematical tool in R that goes through all of these data and attempts to classify recurring groups that then ideally represent age-groups (cohorts, populations) of the mussels.
It seems like packages in R that might be helpful are 'mclust' and 'Rmixmod' both of which have already been tried. However, in the end, always a dead-end has been reached so it got me wondering whether the arrangement of my data may be the problem or there is another underlying cause.
Has anyone already encountered and maybe solved equal problems and might possibly be up to having a look into the organisation of my size-frequency data?
Similar methods to what I am trying to do have been exercised for example in:
Comtet, Desbruyeres (1998) Population structure and recruitment in mytilid bivalves from the Lucky Strike and Menez Gwen hydrothermal vent fields (37'17'N and 37"501N on the Mid-Atlantic Ridge)
Taylor et al (2009) Using length-frequency data to elucidate the population dynamics of Argulus foliaceus (Crustacea: Branchiura)
Thanks to everyone wanting to help!
Hello ResearchGate community,
Our lab has recently adopted GBS SNP data to gain a better insight into population dynamics of endangered non-model species in Australia (mainly amphibians, geckos and marsupials).
For most projects, after gaining a first insight into current population structure, we would like to understand whether the observed structure is a result of recent or ancient splits. As most of us are relatively new to the world of GBS and SNP data, we would really appreciate if you could point us to the best methodologies for doing so.
Any help is much appreciated.
I would like to derive a mathematical model that can explain the change in frequencies of two genes that cause resistance to a particular antibiotic. Based on the literature, one of the genes is expressed only constitutive, while the other is a membrane protein. I would like to know the methods and protocols to follow for using evolutionary game theory. As I am learning it right now, any reference to similar articles or texts would be much appreciated.
Turing spoke of population dynamics. I would start with a cellular structure with 12 connections. Move on to development of awareness, Self, Other and Environment using multi-sensory inputs and a sematosensory cortex. You will need to dynamically encode, store, sort and delete memory. Your internal clock will be points, not intervals as explained by Oliver Sacks in the river of consciousness. Your synthetic must have time to incubate in a safe environment. Sacks was wrong about salience, it is dynamically selected. But emotion in evolution is generated by the dance of the sympathic and parasympathic nervous systems, not the CNS. Hope this helps.
In the last 117 years the population of the US has only once declined against a steady background of population growth. The world was hit by a massive influenza pandemic during that period but could that alone have accounted for this anomaly or was there another factor operating
July 1, 1919 104,514,000 1,306,000 1.26
July 1, 1918 103,208,000 -60,000 -0.06
July 1, 1917 103,268,000 1,307,000 1.27
I want to analyze the role of spatial vs environmental effect (through variation partitioning) on Notonecta species distribution among fishless ponds. I have been using adespatial package to do that.
After calculating the MEMs, I need to estimate the Moran`s I spatial autocorrelation values, in addition, to the positive and negative part of this index for the ten MEMs I have.
In adespatial package, in the dbMEM example of mite data, Moran`s I is calculated using moran.randtest, without using the listw function as follows:
However, in the explanation of the test itself, listw is been used:
moran.randtest(x, listw, nrepet = 999, ...)
I have analyzed my data with and without using the listw and I get different results. I was not sure which one of the two methods is more appropriate since both examples are given in the same package. I was wondering if anyone has used the function moran.randtest and if yes, do I need to use listw to calculate the Moran`s I index?
I would really appreciate your kind guidance!
I studied Monochamus saltuarius, a major insect vector of pine wood nematode, in Korean White Pine forests using Mark-Release-Recapture based on pheromone traps.
However, their recapture rate is very low about 2~3% during study periods, i.e., 4~6 individuals were only recaptured (total marked and released individuals were about 168~243 individuals).
Thus, in each session, only 1 beetle or no beetles were recaptured (My experiments were conducted 11 occasions).
In this case, can I analyze population size of M. saltuarius using estimation methods, such as Jolly-Seber model?
I have some individual interest to understand a little bit more these two phenomena, because the apparent mathematical similarities between them, and because some particularities, too. The overview to direct possible concerned researchers to solve this question can be seen in the attached link. Thanks for you interest.
Deleted research item The research item mentioned here has been deleted
I'm doing a master on moose populations estimations with a citizen science approch.
I want to simulate a hunter and a moose population (of known size) in the same landscape, "make them meet", and see how the abundance estimations are biaised depending of the proportion of "cheaters" (hunters who don't say the right number of moose seen).
I explored the SELES and RAMAS/GIS softwares, but I'm not sure they are appropriate tools to simulate two animal populations movements in a static landscape.
This is to provide insight into whether or not human settlement density is affected by latitudinal position.
Climate refugia have been presented as possible mechanism allowing species to survive rapid climate shifts (e.g. Keppel et al. 2012, 2015; Franklin et al. 2014; Barrows and Fisher 2014; Barrows et al. 2016). Modeling where climate refugia might occur is straightforward; zones of overlap between current distribution models and climate-shifted models could be such refugia. My question relates to both validating such models, and more to the point what are the population metrics that might characterize a population residing in a climate refugia? Here in California we have (possibly) emerged from a 5-year drought that may have been a window into how populations behave in response to climate change-like conditions. We are tracking communities/populations of lizards across a broad elevation gradient. None went extinct; all declined during the worst of the drought but then behaved differently along this gradient as the drought became less severe.
1. some have remained at drought-level densities even after near-average rainfall returned.
2. some population densities increased linearly and others exponentially with increasing rainfall.
3. Some maintained at least moderate to expected levels of reproductive recruitment even during the worst dry years, while others showed little or no recruitment until the near-average rains returned.
Conceptually, how should a population behave during severe climate change-like conditions, and can we use those responses to identify and/or validate the location of climate refugia?
Hi. I want to assess the diversity of fish from 10 sampling sites at temporal scales. However, at each site I am going to use only 1 fishing gear to catch the fishes. If I want to prepare 5 replicates per site/sampling, is it valid if I take the replicates from the same fishing gear? I'm planning to use stratified random sampling technique to prepare these replicates. Thank you.
Insect-pest component in most of the models is weak, in some model dealt through input of pest population at various stages of crop growth to assess the yield loss associated with crops and cropping systems.
there is a need to develop population dynamics for major insect-pests of a region, and integrate with the crop simulation tools.
,my interest is to know the related work on this important aspect?
I am looking for a quick and easy proxy measurement to estimate age in Boophone disticha (L.f.) Herb. for demographic monitoring. The number of leaf scales in a bulb can be used for this purpose, but I would prefer a non-invasive method that disturbs the plants as little as possible.
We are creating a customized PVA program that can predict the extinction threshold depending on the years input. Some example and specific scientific data needed are current population of the crocodiles, age structure, vital rates, mortality rates, hatchlings, carrying capacity, mean survival for each stage, sex ratio, number of occupied patches, and etc.
The only PVA factor we can only do is Density dependence. Spatial PVA related is not included.
If you guys have existing PVA studies of other animals, it would help us construct a program for it. We can change the subject animal because of the limited data of crocs. Any help would be appreciated.
I am calculating biomass differentiation associated with different fishing mortalities but it is too hard to understand the FAO or other resources.
We have distribution data for larvae of 2 species that were first ransdomly spread on an experimental square arena. After some time, the area was divided in 100 quadrats of 1*1cm and the number of larvae of each species in each quadrat was counted.
What is the best way (i.e. agregation index) to 1/evidence that the observed distribution of larvae is aggregative and 2/evidence that this agregation is interspecific? There are several index and methods reported in the litterature, but I was unable to find the best way to answers these 2 questions according to our dataset (quadrat).
Deep-water fishes are commonly considered widespread and not a speciose group, but could this conservative group be used as a good (or even the best) indicative of a center of speciation? The recent increase of deep-water elasmobranch descriptions and records off the Brazilian coast (119 to 162 species from 1989 to 2007) has raised the question if there is a much higher diversity than previously expected.
What group of fishes will be considered for your project? Thank you very much!
Logistic population models can be used for human population dynamics. The model have a factor. usually denoted by K, the carrying capacity.
Not so complicated. Hizimura & Matsuyama (1999) suggested a model to characterize and describe eruptions (crashes) in population dynamics. I'm testing some hypothesis and I'd like to test the second derivative (equation 7) and compare with some time series. Unfortunately they didn't calculate this. Anyone here likes a mathematical trouble? If you want to help me I could describe such details. Thanks a lot.
I have microsat data for multiple fish populations, and I'd like to get the best estimates of effective population size as I possibly can, but my problem is I have no age or size class data. Therefore my dataset contains overlapping generations, and I have no way of discerning what individuals are of what age class. Is there an accepted way to calculate Ne despite this overlap? Most every method I see requires you have age class information or discrete generations. Any help is appreciated.
I want to analyse the diversity of two populations with SSR markers.
I managed to calculate the FST value with the hierfstat package. But now I want to test whether FST is significant. I tried to do this by bootstrapping with the function boot.ppfst, but I don't understand the output (lots of pairwise tables). And I don't know how I can get something like a p-value that tells me whether my FST value is significance or not.
Does anyone know how this works? Is there a R script available?
There are severals predictions about that populations with a history of inbreeding would show less inbreeding depression (because deleterious mutations had been purged) tha populations with little or no prior inbreeding.The history of inbreeding was inferred by severals methods, including average inbreeding coefficients, morphology flower and populations size, and others. Inbreeding depression was usually estimated by comparing fitness components in experimental inbred populations to noninbred populations and estimating of severals parameters in the populations.
I'm looking for data or information on the yearly fluctuations of duck populations (and other anatidae) in Alaska. Do numbers stay roughly the same or can there be major differences from year to year? Thanks
I'm (as HEAD of BIOMONITORING laboratory) looking for interested scientists to assist us in the preparation of articles and in future on collaboration work. We need qualified help in English and possible statistical analysis. Interests ornithology (population dynamics, spatial heterogeneity, climate change), ichthyology (fish populations(assemblages) and environmental parameters). Only without money relations help is welcome. The opportunity to be a co-author of articles only is welcomed. Post-docs, young PhD, PhD student from Europe and North America is welcomed.
My email firstname.lastname@example.org