Science topic

Homing Behavior - Science topic

Homing Behavior are instinctual patterns of activity related to a specific area including ability of certain animals to return to a given place when displaced from it, often over great distances using navigational clues such as those used in migration (ANIMAL MIGRATION).
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I am trying to calculate KDE home ranges for 50 polar bears for a research project. The bears were collared with Argos GPS collars, and each bear has around 200 locations (one location/day).
I am hesitating between using the Least-squares cross validation method (LSCV) or plugin to estimate the h smoothing factor; given my dataset, which of the two would be the best method?
Any advice would be appreciated!
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Cross-validation is a good method but it can take too long if you have 10000 or so. With 50 or 200 there is no problem With it.
You can try also adaptative methods for bandwidth with different sizes for each point.
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We are trying to estimate the Home Range of Dalmatian Pelican in Southeastern Europe and we want to locate any similar research may exist for any other pelican species of the Old World (5 species in total)
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Many thanks Hein!
Giorgos
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I am working on species foraging and roosting data over two different regions. I have worked out for each region what percentage of the data within their home range occurs in native vegetation. However, how do I statistically compare the use of native vegetation as their home ranges differ per region? My primary concern, however, is that the home range sizes are different which means I cannot compare percentages of native vegetation used between these areas. My main hypothesis is: is there a significant difference in native vegetation used between regions (HR1 and HR2)?
Example: HR1: 490km2 native vegetation within HR1: 212km2 foraging in native vegetation: 20% HR2: 41km2 native vegetation within HR2: 9.5km2 foraging in native vegetation: 18%
As usual, it is difficult for me to pin down the best statistical method to compare the use of native vegetation between regions: possibly lme? Any help is greatly appreciated!!
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You use percentage, which in theory does not depend on the difference in tge area between the regions. The values are close, I would not expect any signigicant difference between 20% and 18%. But you need to statistically prove this. Could your regions be divided into smaller units? Eg in 1 sq km quadrats?. Than assess the area of natural vegetation in each unit and create a matrix (Columns for regions and rows for subunits). Then jackknifing, bootstraffing or any other randomisation techique can be used to calculate p-values. GLM can also do.
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Hello,
I just recently started working with the different types of home range estimations and have a few questions about this and that. Maybe you could help me out with that?!
My study animals are Sand Lizards (Lacerta agilis), that I tracked with VHF transmitters along a railway track in eastern Germany. I tracked up to 20 animals at the same time, that’s why I have only 3-7 datapoints per animal per day. The transmitters lasted up to 20 days, but most of them were peeled of by the animals earlier. In average I have 33 datapoints per animal. With this information in mind, you can hopefully get an impression of the data quality I am working with. So here are my questions:
1) I read that it is important to report on autocorrelation of the datasets (and also on site fidelity of the animals). The dataset of most of my animals seems to be autocorrelated. This is probably due to the site fidelity of the animals. My question is: How do I interpret this information about autocorrelation and how does that affect my home range estimation?
2) I would like to check if the number of locations was somehow sufficient to calculate proper home range estimates. Therefor I would like to use “area-observation plots”. I am just wondering what to have on the y-axis: if I have this plot for an MCP analysis (for example), do I take the total area of an animals MCP (in m2) or do I use percentages (where my final MCP is 100%)? In the second case, an asymptote would probably have more that 100 % - is that correct? Additionally: Is there a way how to calculate the number of locations randomly from my dataset (for every single animal) or is that usually done just one by one in the same order as my sampling occurred?
3) During the sampling I took notes when I sighted the animal I was tracking. Is there a way to include this information in any home range estimation? Do you think that is a useful information at all?
I would be really glad if you have at least one or another comment on my questions or could recommend some literature on these topics. Thank you very much!!
Alina
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Hi,
when your additional observation is on the exact position than the position from telemetry you could weight the telemetry point. This would affect a kernel density, but not a 100% mcp. For the mcp data points outside the mcp you get from telemetry alone would be interesting.
Best, Christoph
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Hello, I have mapped the locations of several individuals of a certain species of bird. I have the GPS coordinates, the date and the time data every half hour for several consecutive days and I am trying to apply the Package 'mkde' to get the kernel density maps based on the movement (home range). Is there someone with experience in using this package who can help me?
Thank you very much!
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Alas, don't know that program. But there are a number of others that might serve your needs including the density analytics in, for example, the ESRI tools like ArcGIS and ArcPro.
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Hi,
I'm trying to get the distance between the extreme limits of individuals' home-range estimate (I used AKDE estimation).
I think it is very simple to do it, but since I'm limited in using R program, I can't find a solution for that.
Does anyone have an idea of how to get this distance in R program?
Or have a script to do that? (It's ok if the script is for another home range estimation, I believe I can adapt it to AKDE estimation).
Thank you!
Claire
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Hi! A researcher of the Spatial Ecology and Conservation Lab - Unesp, Brazil, already helped me with this issue. With the authorization of Alan Eduardo de Barros I'm posting below the script for those who can need it in the future.
Calculating the distance between the extreme limits of a home-range AKDE.
library(ctmm) data(buffalo) Cilla <- buffalo$Cilla   # selecting one buffalo within the list
GUESS <- ctmm.guess(Cilla,interactive=FALSE) FIT <- ctmm.fit(Cilla,GUESS) ### UD <- occurrence(Cilla,FIT) # It is possible to calculate the extent for UDs of occurrence as well UDakde <- akde(Cilla,FIT)    # calculate the AKDE HR
plot(Cilla,UD=UDakde) ext_df<-extent(UDakde)   # The resultant output is a dataframe. So you can calculate the distance based on the differences. #           x         y, #min 25066.69 -12154.92 #max 60322.00  11055.91
# Using max and min functions to select max and min in both axes distX <- max(ext_df$x)-min(ext_df$x) disty <- max(ext_df$y)-min(ext_df$y) max(c(distX,disty)) # to give the max dist
# Another way would be to do the same extracting the values from a dataframe using the index for cells # df_name[x, y], where x is the row number and y is the column number of a data frame called df_name distX <- ext_df[2,1]-ext_df[1,1] disty <- ext_df[2,2]-ext_df[1,2] max(c(distX,disty)) # to give the max dist
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Like in some raptors.
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Thanks, Keyur Naria.
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I am conducting a study using wildlife traits, however, home range data is limited.
Pd. I have already used data from Tamburello et al. 2015, but I still have lots of species without home range data.
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Hi!
I'm trying to do an accumulation curve (i.e. number of locations and home-range size) with my data to see if, with the number of radio locations I have, the home-range sizes reach the asymptote.
For this, I have to calculate the home range for every location added. Does someone knows how to do this in R program? Or already has a script for it?
Thank you for any help!
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David Eugene Booth Thank you for your answer, but I think that before following your suggestion, I have to get the home range of each individual for every location added ...
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I am gathering bibliography around home range measurement with the traditional method, alias observation.
  • Do you have studies to suggest?
  • In particular, are you aware of recent publications, say within the last 15 years, still using observation?
  • Do you think this can still be a valuable way to measure home range size of some species, as, free-ranging dogs living around a neighbour?
Thanks!
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Thank you for your valuable opinion and suggestions. I will keep those in mind for considerations and future actions.
Your example of attaching a GPS to dogs would have been ideal, but that was not doable for several reasons. Though, preliminary and specific observations suggesting that dogs have a recurring home range pattern has allowed to gather data by empirical observations.
If you are curious to check at previous empirical data collections, please check infographics by this link:
Would you have any other consideration, idea or suggestion,
I'll be more than glad to hearing from you!
Thank you and Best Wishes.
Marco
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This year we plan to sample coleopterans withing home ranges of breeding Lesser Grey Shrikes. The species feed on ground-dwelling beetles. We would like to use non-lethal methods to sample them. I would deeply appreciate advice on suitable techniques or any articles on this subject. Thank you very much! Katarina
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Katarina:
To sample ground-dwelling coleoptera you can use Winkler’s bags without alcohol in the collection container. Also you can use pitfall traps without alcohol.
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I have read some papers regarding distance sampling with camera traps, but there doesn't appear to be a clear reason why particular distances between camera traps are used. In mark-recpature it is species specific, but I don't think that appears to be important in the distance sampling method. Can I just use a sensible distance that allows me to sample a good sized area? I am looking at Leopard in South Africa for reference, considering a grid with 5 km distances between cameras, assuming their home range is not a necessary factor to consider when using this method.
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dude I used distance sampling for cape hare density survey.distance samplings assumptions apply for three samplings method.line.point count and marine survey.although you can read a paper published by Indian author niha...
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Hello All,
We are conducting a home range study on aquatic turtle species and need to constrain the MCP or Home Range to a river. Any suggestions on how to do this using ArcGIS or an ArcGIS extension?
Many thanks for any advice you can provide.
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Hi Elizabeth, We used telemetry to determine river ranges of female Barbour's map turtles (see attached file). We calculated home ranges in Arc GIS using Home Range Tools and clipped the MCPs and KDEs to the surface area of the creek as determined with sonar mapping, so the ranges were constrained to the creek. Hope this is helpful.
Best,
Lora Smith
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I ave tried with the adehabitaHR package but my boundary does not satisfy the angle criteria between lines and I can't fiddle with that.
Any other solution??
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Does it need to be Kernel? What about Local Convex Hull? It may be a satisfactory alternative for your problem?
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I'm using a software called BIOTAS to analyse riverine fish movement. I wonder if it relevant to study the fish home range using the software. because whenever I plot the minimum convex polygon, the home range would include the non-river habitat. so, is that legit? help!
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Hi Shazanna. Take a look at this paper:
We used 'linear span' as per Hodder 2007 to calculate home ranges to account for the issue you mention with including non riverine habitats in the elipse.
Have a read of our paper and the refs within...then we can chat more if you like
Paul
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Usually I record the GPS coordinates of the identified spotted deer individual within a 50 m radius, will it be erroneous to utilise those points and compute a year-long Kernel Density Estimates for the animal
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follow
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I would like to measure home-range overlap of radiotagged individuals monitored during the same time.
Is it possible with some R packages?
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I've never done this myself but I've collected quite the amount of resources on spatial analysis with GIS and R in the past year...
Maybe is not useful in your case, but at least I can point you in the right direction: for what I know you need to use adehabitatHR (https://cran.r-project.org/web/packages/adehabitatHR/vignettes/adehabitatHR.pdf) and then use a UDOI ( Utilization Distribution Overlap Index ) or a percentage of the overlapping area.
Finally, in this paper the author compare two model (2D and 3D) and the formula for the last model is the same of the UDOI used in adehabitatHR, so I think it can be useful.
Sorry for reporting only others examples and models, and to not answer with a direct, concise and practical explanation! If someone can provide some new inspirational way to analyse the overlap, I'm interested in it too!
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I am currently investigating how to best discriminate between animal movement tracks based on space-use patterns and characteristics of the moves themselves. Ideally I would like to use several complementary (i.e. non-correlated) statistics to be able to come up with statements like: "these two tracks resembled each other, as they covered areas of similar size, but one of the tracks was characterised by a larger number of highly directed and highly area-restricted moves than the other". The first statement could be measured using home range statistics, but I have not found a good way to measure distribution of moves. And perhaps there are other independent characteristics of animal moves that I haven't thought about. Suggestions are warmly welcomed!
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Dear Jacob, make sure to have look at the recent papers by Justin Calabrese and coworkers. They use time-continuous, not time discrete ones, to fit tracking data, which allows them to better take autocorrelation into account. They also developed a powerful R script to actually use this new approach. I am not an expert on all this, but it seems to me that this is the best you can find in movement ecology. Cheers, Volker
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Dear All,
   How do perform Maternal Odor Preference/Homing Behavior in pups? and how many day old pups should be used for this behavior study??
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An alternative to avoiding litter effects is to test multiple subjects in the litter, but run statistics on litter means, not individual scores.
Yes, pups are sensitive to temperature and should be handled with gloves. The ideal temperature you wish to test them at depends on the behavior of interest and their age. We ran most of our experiments on P1 pups (24-hours after birth); to ensure behavioral activity, we ran in a regulated environment at 34-35°C. Cooler than that and they cannot maintain body temperature and will thermally crash over 20-30 min.