Resources
Here are some useful resources related to conservation and ecology.
Communities
We gain so much from being in community with others. I recommend finding a local organisation you can volunteer with. If you're in the UK, The Conservation Volunteers or a local Wildlife Trust will likely have a volunteering session near you. Often, local parks have "Friends of" groups that meet regularly to upkeep the area. Here in Manchester every park and scrap of grass seems to have such a group! There are also place-specific conservation organisations, like Cambridge Conservation Volunteers.
This one's not ecology related, but if you're in Cambridge and not volunteering at Cambridge Community Kitchen, you're missing out! Free food, anarchist friends and feeding the city - what's not to love?
If you're interested in coppicing, which you should be, check out the National Coppice Federation (NCFed). It is a federation of local coppice groups, and aims to support the coppice industry and related areas like hedgelaying and crafts. I'm their social media officer, so follow them on Instagram and Facebook while you're at it, and get involved with the discussion group. I'm part of Coppice Association North West and am going to start going to the free monthly Urban Bodgers events at Islington Mill. You don't have to be a CANW member to join in, so if you fancy woodworking come along.
Online communities can be a great way to make friends across the globe. I'm in a really supportive, inclusive and active Discord server called Biodiverse. Discussions are organised into groups of organisms (e.g. plants, mammals, fungi), other aspects of natural sciences (e.g. ecology) and topics like career and education. People help eachother with species identification, and it's generally a lot of fun to make friends all around the world.
I'm also planning to join FLAME, which is the youth branch of the Land Worker's Alliance (LWA). I love that the LWA has a queer identity group, which is called Out On The Land.
Data for Ecologists
I used to think I didn't like maths, but then I got tried statistics for the first time during an A Level Geography field trip and my world was changed! We plugged in measurements we'd taken on a beach using a stripy stick to a spreadsheet with pre-prepared formulas, and suddenly a graph showing the cross-section of the beach appeared. I found it really cool that something in the real world could be represented visually after collecting a bunch of numbers. I'm so glad that lesson with beach profile taught me that numbers can be really fun to work with.
I've since developed my stats skills. I learned R during the fab Statistics for Natural Scientists mini-module, taught by Tucker Gilman at UoM. Sidenote - as R is a coding language, this also got me into coding which is how I got into writing my own website code. I've sinced used R, along with packages like ggplot, to analyse vegetation community data for my dissertation, marine invertebrate assemblage during my year in industry, and more! I also did some modules using ArcGIS, and hope to carry this knowledge over and learn some QGIS to help map a local doorknocking initiative.
Currently, I'm starting to learn SQL so I can manage databases. So, here are some resources you can use, and we can become data-whizzes together!
These two books by Mark Gardener are really useful guides on how to do specificly ecology-related analyses using R and Excel. They have step-by-step guides, exercises as you go, and sample datasets. The second one is especially handy when analysing groups of different organisms - it explains diversity metrics, similarity, clustering, ordination and so on.
The handbook I used when starting out in R was written by my lecturer, Tucker Gilman himself, but not published anywhere. Send me an email if you're interested in having a look at it though.
I'm making my way through this free online course about SQL. It's all ecology-focused, including the sample data.
Other useful resources when learning to code are forums like Stack Overflow and Reddit. Just search up your question and see if anyone else has asked it before. Other useful sites are R-bloggers, Statology and R manuals themselves.