Yesterday I went to the Scottish Conference on Animal Behaviour (SCAB) at the University of St Andrews. It's still very early in my PhD and I was unsure whether I'd have enough for a good talk, so I decided to present a poster. I think it was a good call that allowed me to enjoy all the brilliant talks without feeling stressed.
I enjoyed the day and was really impressed by everyone presenting. The talks included: use of landmarks in hummingbirds, information use and transit in nuthatches, cognition and nest building in birds, morphometrics of tools used by crows... And even observational learning in African Greys!*
My poster won the best poster prize** too! First poster presented at a conference :] Pretty chuffed :]
*parrot geek here
**chocolates. One should always be fed chocolates for presenting stuff!
Sunday, 29 March 2015
Sunday, 22 March 2015
Course: Spatial Analysis in R
Course title: Spatial Analysis of Ecological Data in R, organised by PR~statistics.
The course was really extensive. Each day we did at least one new "module". Have a look at their website for the list: Spatial analysis course.
It was one of the hardest courses, if not the hardest one, I have ever done. By Wednesday afternoon I was nearly in tears. Frustration with R was taking over - the course material was really tough and pretty much all new to me and on top of that we had to write our R scripts from scratch. Which for me was as close to impossible as one can get. While I understood the concepts I really struggled to apply the knowledge effectively and work through assigned tasks, as my coding knowledge was letting me down.
I have to admit, during the course I wasn't sure how much use it all would be, since I felt like I wasn't getting through enough of the practicals. However (and this is a big however!) during the last day we split into smaller groups and discussed our own data. I managed to get some feedback on my ideas and some tips about future analyses. It was really, really, really useful! In the end we were also given copies of all the code necessary to complete all the practical tasks. I really think that I should be able to go over things again in my own time and use everything I learned.
This course ate more than half my yearly PhD-expenses budget, but I think it was worth it in the end and I would recommend it if you are interested in spatial analysis. Things would probably be easier if you know a bit of R (even better if you know a lot of R). If you don't know R, but you want to do it, be prepared for some really hard work and likely a bit of confusion and frustration too.
There is something more this course reminded me of, which I think is really important: if you struggle, talk to other people! I can't stress this enough. So many others on the course struggled and knowing that made me feel less alone and less hopeless.
The course was really extensive. Each day we did at least one new "module". Have a look at their website for the list: Spatial analysis course.
It was one of the hardest courses, if not the hardest one, I have ever done. By Wednesday afternoon I was nearly in tears. Frustration with R was taking over - the course material was really tough and pretty much all new to me and on top of that we had to write our R scripts from scratch. Which for me was as close to impossible as one can get. While I understood the concepts I really struggled to apply the knowledge effectively and work through assigned tasks, as my coding knowledge was letting me down.
I have to admit, during the course I wasn't sure how much use it all would be, since I felt like I wasn't getting through enough of the practicals. However (and this is a big however!) during the last day we split into smaller groups and discussed our own data. I managed to get some feedback on my ideas and some tips about future analyses. It was really, really, really useful! In the end we were also given copies of all the code necessary to complete all the practical tasks. I really think that I should be able to go over things again in my own time and use everything I learned.
This course ate more than half my yearly PhD-expenses budget, but I think it was worth it in the end and I would recommend it if you are interested in spatial analysis. Things would probably be easier if you know a bit of R (even better if you know a lot of R). If you don't know R, but you want to do it, be prepared for some really hard work and likely a bit of confusion and frustration too.
There is something more this course reminded me of, which I think is really important: if you struggle, talk to other people! I can't stress this enough. So many others on the course struggled and knowing that made me feel less alone and less hopeless.
Thursday, 12 February 2015
Scrivener + Mendeley + LaTeX and references
There is a comment under my PhD Tools blog post asking about the workflow and using a reference manager with Scrivener. As I said in the comments, as far as I’m aware there isn’t a good and easy solution to that, although some workarounds have been suggested (I’ll try to find them and post links).
First, if you don’t know how LaTeX deals with references, it’s fairy simple. I store my references in Mendeley, assigning a unique cite-key to each paper. The library can be exported as .bib file, which will be automatically updated every time you add a new reference in Mendeley (it’s a one time setup, which is great). Imagine you have a paper written by Smith et al. in 2005. My cite-key for that reference would be Smith_etal2005. I tell LaTeX where it can find the .bib file (I give it the path to that file), so that it can access all the data.
When I write in LaTeX and want to cite this particular paper I use the cite-key Smith_etal2005 and a bit of code that tells LaTeX that this is a reference - it would look like \citep{Smith_etal2005}. LaTeX then goes to the .bib library, pulls out the full reference and sticks it in the “References” section at the end of the document. In the body of the text itself the reference is output as it should be i.e. "some text about the thing (Smith et al., 2005)”.
The beauty of this is that if I were to remove the reference from the body of the text LaTeX will automatically remove it from the reference list at the end. It saves me worrying about having references in text, but not in the reference list and vice versa. I really like it and plan on keeping using LaTeX and Mendeley combo to format and output my documents, likely including the thesis.
Now I am adding Scrivener to the mix. Scrivener will be used mainly for note-taking, early drafts, re-drafting, reverse outlining etc. Anything that doesn’t need to be formatted and look pretty will be done in Scrivener, saving me dealing with the majority of LaTeX syntax in everyday life and formatting once the text is ready to be seen by the outside world. Having said that I don’t want to wait with inputting all reference till the last minute, it’s just so much more efficient to deal with them as you go!
There are two options here.
(1) I can input references in the-LaTeX-way, as I go, just like I would have done if I were writing in LaTeX itself (i.e. use the \citep{Smith_etal2005} in Scrivener). Then, I can simply export (or even copy-and-paste) that document from Scrivener to LaTeX for outputting, compile it and voila! references are sorted.
(2) Alternatively, I could set up Scrivener with Multimarkdown (which is a syntax that allows you to write in plain text and then convert to a more complex format e.g. HTML), write using MMD to keep it simple and avoid having to put LaTeX-like bits of code in (the \citep{} in this case). It is then possible to export from Scrivener to LaTeX through MMD; all MMD specific syntax will be changed to LaTeX specific syntax.
I feel like after the initial set up the second option i.e. using MMD would be cleaner. But then again, I don’t really have issues with using LaTeX-style citation syntax, so that’s what I have stuck with for now, as I only needed to write fairly short pieces of text. For anything of a length greater than 5000-6000 words it might well be worth spending a couple of hours sorting MMD out and getting used to it*.
If you are interested in learning more about any of the above, check out the links below. If that’s not enough - google! There seems to be dozens of tutorials on those things out there already, hence my post is rather simple, no need to re-invent the wheel.
http://timbrandes.com/blog/2012/02/28/howto-write-your-thesis-in-latex-using-scrivener-2-multimarkdown-3-and-bibdesk/
http://timbrandes.com/blog/2014/04/08/optimize-bibdesk-multimarkdown-and-scrivener-for-a-nice-scientific-bibliography-and-citation-workflow/
More here: http://harrisonsweeney.com/posts/scrivener-multimarkdown-and-latex.html
Some good posts on having words too: https://onhavingwords.wordpress.com/2013/03/19/scrivener-multimarkdown-latex/
Using LaTeX code in Scrivener: https://onhavingwords.wordpress.com/2013/07/27/any-latex-scrivener/
Also replacements, if you are really into it all now! https://onhavingwords.wordpress.com/2013/10/06/replacements-latex-scrivener/
On Multimarkdown, from its creator: http://fletcher.github.io/peg-multimarkdown/mmd-manual.pdf
*but it’s not just because of the references, it’s because of the heading, subheading and other bits and pieces.
Saturday, 7 February 2015
Fieldwork. Of sorts
I have just spent two full weeks in Australia. Yes, it’s not much, considering how long it takes to get there from the UK.
The trip was an odd one. The length was dictated by several factors - I wanted to get out and meet my Australian supervisor, as well as see the set up and my study system, in order to get a better idea of what I’m dealing with and discuss my PhD project in a bit more detail. On the other hand though it’s quite late in the year and the breeding season is pretty much over by now, hence there wasn’t much point in staying down under for a prolonged period of time.
I think that the trip was a successful one. The people are great there and the supervisor was happy to share his insights about all kinds of things. It was helpful to see the birds I’m working on and get a look at the field site. I hope it will aid me in fleshing out my ideas for next season’s fieldwork (behavioural observations, yay!), so that I’ll be off to a good start when I come back in September. Additionally, I feel like I managed to do some networking and for the first time it came easy to me - maybe it’s just the atmosphere there in general, but everyone was so chatty, nice and helpful that having a conversation was a pleasure.
If anybody I have met over there ever reads this I’d like to say thank you for all your hospitality. I really appreciate it and I hope our paths cross in the future and maybe one day I can return the favour.
On top of a successful PhD trip I also managed to spent some time bird watching, chasing the wild parrots (I’m a bit of a parrot geek). Some of the photos of Oz wildlife below if you fancy seeing them.
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| Crimson rosella |
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| Superb fairy-wren chick |
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| Wallaby |
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| Sulphur crested cockatoos on a bird feeder |
Sunday, 11 January 2015
Course: Quantifying the environment
The full title of the course was "Core and advanced environmental statistics training: Quantifying the environment – Part II" at the University of Glasgow. As a NERC funded student I could attend the course for free - thank you NERC!
It was a week long course, it was rather intense and it covered three areas: flexible regression methods, spatio-temporal modelling and functional data analysis (FDA). I was particularly interested in the spatial modelling as I might do a chapter on it for my PhD.
The course was very much aimed at statisticians and quite a bit of previous knowledge was assumed. For instance, on one of the days we had a set of lectures which were a condensed version of a 20 h long course for people doing Masters in statistics. As I have no real background in stats I found a lot of it rather hard. Keep in mind that I haven't attended Part I, maybe things would have been easier if I did.
What I found a bit suprising is that a lot of things we were doing were "at the edge of statistical knowledge and research". For some reason I have expected the field of statistics to be more advanced. This might sound silly, I guess, but I just never thought deeper about where our statistical knowledge is at. Now I know! It seems that some things I was planning to do might be harder than I thought, yet the majority of them should be doable, which is great. There were a couple of things that are not-so-doable yet, mainly due to lack of packages available - the knowledge is there, but there is no easy way to utilise it by an average non-statistician.
Yet despite the fact that the stats were hard, I found the course really informative. I think this was due to a clever delivery strategy. The lectures were clear and accompanies by practical sessions. All the R scripts for the practicals were provided. This way I could work through the material and focus on trying to understand it, instead of fighting with R. I think if I had to come up with R scripts by myself I would have been completely lost. Additionally, I have all the scripts for future reference and I can be sure that the code is decent and without errors.
All in all I'd recommend the course, but be prepared for a long week and quite a bit of work!
It was a week long course, it was rather intense and it covered three areas: flexible regression methods, spatio-temporal modelling and functional data analysis (FDA). I was particularly interested in the spatial modelling as I might do a chapter on it for my PhD.
The course was very much aimed at statisticians and quite a bit of previous knowledge was assumed. For instance, on one of the days we had a set of lectures which were a condensed version of a 20 h long course for people doing Masters in statistics. As I have no real background in stats I found a lot of it rather hard. Keep in mind that I haven't attended Part I, maybe things would have been easier if I did.
What I found a bit suprising is that a lot of things we were doing were "at the edge of statistical knowledge and research". For some reason I have expected the field of statistics to be more advanced. This might sound silly, I guess, but I just never thought deeper about where our statistical knowledge is at. Now I know! It seems that some things I was planning to do might be harder than I thought, yet the majority of them should be doable, which is great. There were a couple of things that are not-so-doable yet, mainly due to lack of packages available - the knowledge is there, but there is no easy way to utilise it by an average non-statistician.
Yet despite the fact that the stats were hard, I found the course really informative. I think this was due to a clever delivery strategy. The lectures were clear and accompanies by practical sessions. All the R scripts for the practicals were provided. This way I could work through the material and focus on trying to understand it, instead of fighting with R. I think if I had to come up with R scripts by myself I would have been completely lost. Additionally, I have all the scripts for future reference and I can be sure that the code is decent and without errors.
All in all I'd recommend the course, but be prepared for a long week and quite a bit of work!
Saturday, 10 January 2015
Resolutions, reminders, goals
It's the beginning of a new year, which means blogs and websites are flooded with new years resolutions. I don't really believe in new years resolutions and most of the ones that I came across were pretty silly (e.g. jumping off of the highest diving board at a swimming pool). If there is one list that everyone should read it's this one: Resolutions for a (Mentally) Healthier New Year.
I have a list. Not a list of resolutions, but a list of reminders.
I try to reassess my life on a fairly regular basis, a few times a year. Splitting it up means I can keep an eye on whether I'm doing OK and making progress. If something is not working I can start over and try another way of achieving the same result. It also helps me to keep the balance when my circumstances change - for instance, everything has been turned on its head when I started the PhD. I moved, I got even busier than before and I am already experiencing the infamous two body problem. But I can still look at my list and remind myself what I want my life to be like.
Anyhow, in the spirit of the new year I am going to post some of the things I have on the list.
Climb regularly. I need to fix my climbing schedule. I used to climb 2-3 times a week, but since the move in September I have been struggling to establish a proper climbing routine, so this needs correcting. I would like to climb at least once per week. Part of the problem is how far the wall is from my house/work.
Exercise regularly. This normally gets covered by climbing. Since distance is making it harder to climb I'm thinking of including some other activity - fitness classes, maybe pilates? I made plans to try a weekly "Body Balance" class with a friend.
Draw. When I was young I used to draw and paint quite a bit. I was never amazing at it, but it's one of those activities that can take your mind off of everything else. A while back I bought a graphics tablet and tried drawing/painting digitally (emulating natural media) in an attempt to get back into it but without the need to buy and store supplies (and without the mess too!). I need to work it into my schedule again.
Read (for pleasure). I used to read all the time. All the time. Not so much recently, at least not things unrelated to my work - I need to fix that! I love fiction and it would be a good break from biology-related reading. I am hugely impressed by what Eva achieved in 2014. She read over 90 books last year!
Socialise. I'm not naturally the most social person, I am perfectly happy by myself drawing, reading or going for a walk. Seeing that I have moved and know hardly anyone over here I am trying to make an effort and make some friends.
Meal plan. I used to do some meal planning with my partner and it worked really well, making shopping and cooking a lot easier and helping to reduce waste. Since I moved and started commuting regularly to see my partner my cooking has been rather ad hoc, as I don't spend all nights at my flat.
Culture. I want to take advantage of where I live - I'll make a list of things that need to be done in the city and start ticking them off.
Meditation. Try it. People seem to keep talking about it. Who knows, maybe I'll like it.
Cooking & Baking. Schedule time for some culinary fun. Maybe even sign up for a course to learn something new? Baking was my go-to de-stresser during undergrad exams. I always joked that opening a bakery was my Plan B. I want to get back into it; cookies and breads, here I come.
Blogging. I have been failing miserably at regular blogging and Twitter. I want to get back to it. I probably have to schedule it in or it won't happen.
I think it's pretty obvious that the main challenge since I started my PhD is time; some things don't happen as easily and naturally as they used to. I will have to actually schedule "me time" and relaxing activities in order to make sure that I keep at them instead of getting sucked into the vortex of pointless procrastination and hermit life. I will come up with strategies and actionable ways of achieving all of the above and staying on track. I will set little goals and review them regularly - weekly and monthly.
Work related plans?
Shut up & Write sessions! There are none in my department as far as I can tell, so I want to set up some. Hopefully I can find some folk who will be interested :] I also want to play some more with different types of working schedules.
I have a list. Not a list of resolutions, but a list of reminders.
I try to reassess my life on a fairly regular basis, a few times a year. Splitting it up means I can keep an eye on whether I'm doing OK and making progress. If something is not working I can start over and try another way of achieving the same result. It also helps me to keep the balance when my circumstances change - for instance, everything has been turned on its head when I started the PhD. I moved, I got even busier than before and I am already experiencing the infamous two body problem. But I can still look at my list and remind myself what I want my life to be like.
Anyhow, in the spirit of the new year I am going to post some of the things I have on the list.
Climb regularly. I need to fix my climbing schedule. I used to climb 2-3 times a week, but since the move in September I have been struggling to establish a proper climbing routine, so this needs correcting. I would like to climb at least once per week. Part of the problem is how far the wall is from my house/work.
Exercise regularly. This normally gets covered by climbing. Since distance is making it harder to climb I'm thinking of including some other activity - fitness classes, maybe pilates? I made plans to try a weekly "Body Balance" class with a friend.
Draw. When I was young I used to draw and paint quite a bit. I was never amazing at it, but it's one of those activities that can take your mind off of everything else. A while back I bought a graphics tablet and tried drawing/painting digitally (emulating natural media) in an attempt to get back into it but without the need to buy and store supplies (and without the mess too!). I need to work it into my schedule again.
Read (for pleasure). I used to read all the time. All the time. Not so much recently, at least not things unrelated to my work - I need to fix that! I love fiction and it would be a good break from biology-related reading. I am hugely impressed by what Eva achieved in 2014. She read over 90 books last year!
Socialise. I'm not naturally the most social person, I am perfectly happy by myself drawing, reading or going for a walk. Seeing that I have moved and know hardly anyone over here I am trying to make an effort and make some friends.
Meal plan. I used to do some meal planning with my partner and it worked really well, making shopping and cooking a lot easier and helping to reduce waste. Since I moved and started commuting regularly to see my partner my cooking has been rather ad hoc, as I don't spend all nights at my flat.
Culture. I want to take advantage of where I live - I'll make a list of things that need to be done in the city and start ticking them off.
Meditation. Try it. People seem to keep talking about it. Who knows, maybe I'll like it.
Cooking & Baking. Schedule time for some culinary fun. Maybe even sign up for a course to learn something new? Baking was my go-to de-stresser during undergrad exams. I always joked that opening a bakery was my Plan B. I want to get back into it; cookies and breads, here I come.
Blogging. I have been failing miserably at regular blogging and Twitter. I want to get back to it. I probably have to schedule it in or it won't happen.
I think it's pretty obvious that the main challenge since I started my PhD is time; some things don't happen as easily and naturally as they used to. I will have to actually schedule "me time" and relaxing activities in order to make sure that I keep at them instead of getting sucked into the vortex of pointless procrastination and hermit life. I will come up with strategies and actionable ways of achieving all of the above and staying on track. I will set little goals and review them regularly - weekly and monthly.
Work related plans?
Shut up & Write sessions! There are none in my department as far as I can tell, so I want to set up some. Hopefully I can find some folk who will be interested :] I also want to play some more with different types of working schedules.
Monday, 5 January 2015
Busy year ahead!
I'm looking forward to this year, but it looks like it will be a fairly busy one. I'm away for at least a week every month till foreseeable future! Courses, demonstrating, conferences, workshops, fieldwork - you name it, I'm doing it.
I'm excited, but also a bit apprehensive, as I've been struggling with my schedule a bit so far and this is likely to upset things. Hopefully I can figure out a way to deal with it.
I'm excited, but also a bit apprehensive, as I've been struggling with my schedule a bit so far and this is likely to upset things. Hopefully I can figure out a way to deal with it.
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