Monkey Forest Tales: Working with locals and getting help from them to collect data

Working in countries where social unrest and political insecurity is part of our daily lives means that research is not always possible using standard methodologies. This means we usually need to relay in local people from those unstable remote areas to collect the data need it. It also means you need to be flexible enough to train them and learn to trust in the data they collect. So, in today’s post I was to talk a bit about this topic.

Over the years I had worked with local people from different backgrounds and education, who had help me and other researcher to collect important data to understand monkey’s ecology and behavior. Although not always easy and sometimes conflicting, local people is an important part of research in many remote and dangerous parts. With time you learn to choose the people who is committed to collect good quality data and who really care about your research and not only the money you give them.

Training is an important part of that process, as well as taking the time to learn about their lives and hear what worries them. One element that for me seems to be clear of working with indigenous people, peasants or cattle rancher is that they all want to improve their lives and not necessarily do that while destroying the environment. Most of them are aware of the importance that forest have to preserve water on their lands and even some of them care about the wildlife living in their land. So, an important part of doing research with them is to hear their concerns and find solutions to their problems at the same time we preserve wildlife in those areas.

However, working with local people also have some limitations. Most of the time those limitations came from not enough training for data collection and a miscommunication about why is so important that data is collected in certain ways and with certain detail. All this can be overcome by making sure to train them well and explain to them in the simplest language possible why is important for them as well as for us the information they are collecting.

In our current global situation, COVID19 pandemics, collaborations and data collected by local people is even more important due to travel restrictions and general health situation. Today, most countries also have reduced economic stability, making even more important to involve local people on our research not only as a support to their local economies but also as a measure to control the spread of the new variations of the virus, an increase protection for the local wildlife. Research funding to cover those expenses are not always easy to get, however new technologies can help to increase our access, communication, and training possibilities if we are flexible enough to incorporate them.

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Monkey Forest Tales: Importance of learning about plants and arthropods when studying monkeys

Today’s post is about the importance of leaning about plants and arthropods while studying monkeys, especially if you are interested in ecology and feeding behavior of this incredible animals.

Most species of primates (monkeys, lemurs and apes) consume plant parts (fruits, flowers, leaves) and arthropods in different quantities every year. When studying their feeding behavior an important part of describing that behavior is to know the identity of the plant from which they are consuming a fruit, flower or leave, as well as the identity of the arthropod group they are consuming. Those are elements important to understand how they live and how can we implement effective tools to conserve them in their natural habitat.

However, most of us don’t see the importance of learning from other groups of organisms apart from the ones we like the most, because we focus only on those interesting animals that capture our attention.

Learn from other groups of animals is not always easy, especially if what you need to learn is their taxonomy (how to identify them), so for most of us is a painful process and we usually need help from people expert on those topics to teach us during our fieldwork. Over the years I had learned that taking detailed notes, good quality pictures or drawing, when you are good at that, are useful tool that can make your taxonomy learning easier. Also, ask for help with identifications is important and can help you speed the process. I had been lucky enough to had help from friends over the years who had teach me a lot about plants especially. And during this process I had develop a small and simple photograph guide of plant from the Zocay Project area based on pictures of fruits, leave and sometime flowers of some of the plant that are used by monkeys in the study area.

In this post I want to share with you that picture guide, so you can also use it if it will help you with your plant identifications. Most of the plant are from secondary forest from the piedmont of Colombian Llanos, but some species are also found in the Amazon Forest. I apologize if some of the taxonomy is not updated, as you know I’m not a botanic, so some families may have change in recent years. But still, I think, it can be useful. I have found fruit guide very useful to identify plants when you are not an expert botanic. Please feel free to download it if you need it.

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Monkey Forest Tales: What to do with old data? Collaborate

Sometimes when we collect data, we not always published immediately, it not necessarily is data we will use in the current project. In today’s post we will talk a bit about what to do with all that extra and most of the time old data you have.

Most of my professional life, I had been in the field following monkeys and collecting different types of data. Mostly detailed behavioral and ecological data. This means over the years my databases had grown a lot and some of that data is from a long time ago. So, what to do with that data? How can I publish data from several years, or even decades ago? One option is collaborating with other researchers.

You can compare old data with recent data from the same area or compare old data with data from multiple sites and compare that data with more recent data. If you have spatial data, share that spatial data in repositories, so other researcher looking at historical data can use your old data in multiple year comparisons.

We had been taught that most of the data we collected needs to be published immediately, otherwise it lost its value, but the publishing process is not always easy of fast enough, so we finish with a lot of old data and not always know what to do with it. Sharing data is an important part of doing science that can make science more open, it will depend on all of us to make easier to share raw data, just remember to give credit to the people who collect it, they are as important as the people who analyzed and publish it.

For those of my generation, we all experience at some time unethical practices that makes us guard our data even more carefully than people from new generations, but that shouldn’t stop us to share data collected a few decades ago that can be used to save the animals we study and love. It has been a long and sometimes not so nice process for me, but I still believe there is a lot of opportunities in sharing data, new and old with researcher from different disciplines if we do it based on respect for each other.

So, if you think some of the data of Zocay Project can be used to your project, please don’t hesitate to contact me and I’m sure we can arrange for you to use some of this project data…you just have to ask.

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Monkey Forest Tales: Why is important a good, detailed database when studying monkey behavior?

As a mention in my last post, while working with my own and other databases I had the opportunity to reflect a lot about data, but also about how we store that data. So, in today’s post, we are going to talk about databases and why is important to make good and detailed databases. This can be applied to working with other groups and in different topics, but we will focus on monkeys because it is what this blog is about.

As mentioned before, when I started, I was trained as a naturalist, which means that I was trained to collect a lot of detailed data in notebooks. However, after coming back from fieldwork, all that data needs to be stored in a more practical way and with the introduction of computers, in a way that allow us to make multiple and different types of analysis. Remember I’m from the generation that started to use computers when I was in the university, not primary school, plus during my first ever fieldwork with red howler monkeys back in 1995, computers were not widely available as they are today. So, I must learn to use databases or excel spreadsheet when it was at its beginnings, and it took me a lot of time to understand all the tools that it has.

It was also not always easy to learn how much detail was good enough to make analysis and how to put all detailed data in a way that will allow me to filter by specific features and extract only what I was going to use for the analysis. Over the years I had tried to teach my own students about how important is that they do a good database, so they can extract data easily if new questions arise when they are analyzing their data or if they see patterns that can be good to explore in their data. Unfortunately, this has not been so easily to achieve, and they just introduce the data they use for analysis.

A good and detailed data is particularly important when you survey an area for several years and look at different data over those years, it will make easy to extract the data useful for questions using data from multiple years and multiple sites. Especially, if you are interested in temporal or spatial data associated to behavioral or ecological data of multiple species. Databases can make you analysis more practical and you can store data in compact way and in multiple sites without having to go back to your field notebooks very often. It can also help you associate information from other resources collected while doing behavioral and ecological studies. So, the best advise I can give if you are starting your career is to take time and make a good and detailed database that you can feed over years and allows you to explore more complex questions over time…

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