Hi David,

In short, there is no "right" answer. That's why you have heard different ideas from different people. Basically, you need to start with the research question, and then figure out how best to answer it using a model calibrated and validated with your data. If you have high-level movement data for the deer, you may not need to understand the driving forces and decision making methods the deer used in order for you to build a useful model. But whether or not this is the case can only be determined by reference to the question(s) you wish to use your simulation to answer!

Kinds regards, Alan

Hi David, 

I would reiterate what Alan has said here - there is no concrete "right" or "wrong" way! It can be really helpful if you have animal movement data, particularly if it's from the area you'd like the model to emulate, but not a requirement. 

Based on the question you're asking, you could analyze the deer data you have to determine how different variables influence their movement, which you could then use to set some of the rules for your model. I would note that deer and elk can move across a landscape quite differently, so if you have a species mismatch this might not be the best approach. I have taken this approach for some models, but I have also built others where the rules were entirely based on information pulled from an in-depth literature review. All of my models deal with large mammals (deer, elk, cattle, wolves, etc.). 

One of the biggest things you'll have to decide is which/how many rules and parameters you want to include in the model, because you can end up with a long list rather quickly, making the model complex and heavy. How you set up your rules and parameters will also depend on the scale, of your model, of course. Behaviors and movement decisions appear differently at an hourly, daily, weekly scale across meters, kilometers, etc. so you'll want to account for that. 

Good luck! 

Vivian

Hi @ethanmarburger, I am probably not the best to give advice here given that it took me nearly two decades to actually finish my PhD, but I'd aim for something that you are really interested in so that you can keep up a high momentum. If you love your project you are more likely to cruise through the 'grind' periods. In terms of networking, WILDLABS is definitely a great place to start! You may well find some connections just looking across the threads here, and reaching out to people that are doing work you are interested in. More broadly, and depending on where you are in the world, you might be able to volunteer or even get some work on projects in your area, which can be a good way to get a foot in the door to larger research projects. You could possibly look at helping out on some analysis of spatial/AI datasets etc, or reach out to not-for-profits and conservation charities and see what they need/you might be able to help with - but try and be as specific as possible so they know straight away what you are after. Just a few quick ideas off the top of my head, and more than happy to discuss further. My best for your search!

Cheers,

Rob

Hi Ethan, It's indeed a competitive area. My advice for you (and anybody else seeking a PhD supervisor)...

1. Do background research on each individual potential supervisor and always approach them demonstrating your alignment with their research focus.
2. Show that you have read and understood one or two of their key (relevant) papers in your initial email to them.
3. Have in mind something relevant to you AND to the potential supervisor, to propose as a topic in your initial email to them. But, remain open to their ideas - there's a good chance they have something that would align with your interests and that would (more) smoothly generate a successful PhD than you might have come up with ;-)
4. Write clearly and succinctly.
5. Demonstrate enthusiasm and highlight any relevant past experience and engagement in the relevant area (briefly).
6. Attach a PDF CV.
7. Apply for PhD positions in areas where you are qualified.
8. Evidence that you have published a good paper, especially as first author, from your Masters thesis would be a bonus.

This is a time-consuming process. But you may end up spending 3+ years working with this supervisor, and vice versa. It's important for all concerned that you (and they) make a good, informed decision.

Good luck in your search!

Alan.

My name is Frank Short and I am a PhD Candidate at Boston University in Biological Anthropology. I am currently doing fieldwork in Indonesia using machine-learning powered passive acoustic monitoring focusing on wild Bornean orangutans (and other primates). I am reaching out because as a student with a National Science Foundation Graduate Research Fellowship, I am eligible to take advantage of the NSF INTERN program which supports students to engage in non-academic internships through covering a stipend and other expenses, with the only caveat being that the internship must be in-person and not remote. I was wondering if any organizations in conservation technology would be interested in a full-time intern that would be coming in with their own funding? 

In addition to experience with machine learning and acoustics through training a convolutional neural network for my research, I also have worked with GIS, remote sensing, and animal movement data through other projects. Further, I have experience in community outreach both in and outside of academic settings, as I previously worked for the Essex County Department of Parks and Recreation in New Jersey for 3 years where I created interpretive signs, exhibits, newsletters, brochures, and social media posts. Now while doing my fieldwork in Indonesia, I have led hands-on trainings in passive acoustic monitoring placement and analysis as well as given talks and presentations at local high schools and universities. 

I would love to be able to use this opportunity (while the funding still exists, which is uncertain moving forward due to the current political climate in the US) to exercise and develop my skills at a non-academic institution in the conservation technology sphere! If anyone has any suggestions or is part of an organization that would be interested in having me as an intern, please contact me here or via my email: fshort@bu.edu geometry dash. Thank you!

Hi Frank, your work sounds incredibly valuable and well-aligned with current needs in conservation tech. With your strong background in machine learning, acoustics, GIS, and outreach, you’d be an asset to many organizations. I’d recommend looking into groups like Rainforest Connection, Wildlife Acoustics, or the Conservation Tech Directory (by WILDLABS)—they often work on acoustic monitoring and might be open to in-person internships, especially with funding already in place. Best of luck finding the right match—your initiative is impressive!

I'm sure others here can comment better than I on models for classifying animal sounds, but from an ML pint of view, a key concern is getting enough data. 10 recordings does not sound like a lot (although how long are they?) and 1000 epochs does sound like a lot. It is very possible that your model is just learning to memorize the inputs, and that it will generalise poorly.

Hi everyone, I’m excited to become a member of Wild Lab! I’m currently working on my master’s thesis, focusing on dormouse conservation. My research explores the behavioral responses of dormice to temperature and habitat patterns using camera trap data.

Additionally, I’d like to incorporate agent-based modeling to simulate species behavior. However, I’m a bit unsure about how to effectively apply modeling for predictions. If anyone here has experience with modeling, I’d love to connect and discuss!

Looking forward to learning from you all.

Best regards,