Post provided by Cléber Rodrigo de Souza
Each year Methods in Ecology and Evolution awards the Robert May Prize to the best paper published in the journal by an author at the start of their career. Ten Early Career Researchers made the shortlist for this year’s prize, including Cléber Rodrigo de Souza who is a data scientist at the Federal University of Lavras in Brazil. In this interview, Cléber shares insights on their paper ‘Tropical forests structure and diversity: a comparison of methodological choices’.
Tell us about your career stage, research, your hobbies and interests
My name is Cléber Rodrigo de Souza, I am a Brazilian forestry engineer, and I recently completed my PhD in forest sciences. Throughout my academic career, I have been working to understand the role of environment and historical legacy on forest structure, dynamics and phytogeography, with a focus on the often-overlooked dry tropical forests.
I am still working to address this issue, while also working as a data scientist in an intelligence and innovation agency in the Federal University of Lavras (Zetta Agency). The innovation agency provides services to Brazilian and foreign government agencies by offering technological solutions for a variety of problems. Research is an important part of my life and is tightly linked with my daily routine and hobbies. In my spare time, I am usually in contact with nature, through hiking, cycling, and swimming.
How would you pitch your article to someone if you had just 30 seconds in an elevator?
Tropical forests play a crucial role in mitigating current and predicted climate change. However, to fully appreciate the importance of tropical forests in the global carbon cycle it is vital to estimate carbon gains, stocks and the diversity of species within a given area. Tackling this issue is particularly important in the often-overlooked seasonal tropical forests (deciduous and semi-deciduous) which are often found in drier environments than rainforests.
I found that applying widely used protocols for assessing rainforest function and diversity were ineffective for estimating the same values in dry tropical forests and gave inaccurate data. This may be because many species in these more seasonal forests do not grow to the same sizes as species used in rainforest sampling procedures. Our findings encourage other researchers to consider key ecosystem factors when applying standard procedures to estimate forest structure, dynamics and diversity.
Where did the idea to develop this method come from?
The idea for this work arose in the most natural place for forest ecologists to conceive ideas… during fieldwork (specifically while monitoring a seasonal semi-deciduous forest). It is important to highlight that the research group was undergoing important changes in the way we dealt with data collection, mainly instigated through the need to include our plot data in a collaborative research network called ForestPlots.net. So, at this point in time, we were adapting our local methods of collecting, recording and storing data to meet the collaborative network standards.
As there were no protocols written for seasonal dry forests, it was recommended we used the general procedure for rainforests. We ran sampling procedures from the network’s standards (such as lianas quantification and tree canopy position evaluation) with our own local standards (such as minimum size of inclusion and inclusion method). However, we noticed inconsistencies between the two datasets. For example, a tree with 25 isolated stems all with a diameter <5cm at chest height would be included in our own local methodology but not in the collaborative network’s methodology. This was a problem because a tree of this size is ecologically representative of the area, in which many trees were smaller in diameter with a greater number of stems.
At this point, we talked about all the possible data lost by using widely adopted rainforest methodologies in a dry forest ecosystem, where many trees are generally smaller and multi-stemmed. More importantly, we wondered how this data loss impacted our understanding of vital ecosystem functions. That’s when we first started discussing how to adapt widely used rainforest protocols to better measure dry forests structure and dynamics.
What were the major challenges in developing this method? How did you overcome this?
After deciding to carry out this study, we began searching the literature for the fundamental basis of methodological choices used in data collection in tropical forests. For example, we wanted to understand the reasons for using a certain criterion, such as a minimum stem diameter of 10 cm widely adopted in rainforests. We wondered what were the specific reasons to use this widely applied threshold? Why 10 cm diameter and not 9 or 11 cm, for example?
At this point we faced the first difficulty, there was a very limited amount of work that address this specific issue. Thus, the definition of methodologies were more a result of a repetition of methods used by researchers and pioneering groups through history, and not following quantitative criteria and robust methods. In this sense, developing our analysis with limited theoretical bases was really a challenge.
We also faced difficulties in developing a quantitative approach associated with methodological choices, which are considered in a discrete rather than in a continuous way. For example, 10 or 5 cm minimum size and inclusion method by tree or stem. What are the consequences of these choices and should we avoid using an approach of simple category comparison? It was then that we decided to simulate scenarios of these distinct methodological approaches, simulating two variations of the inclusion method and an extensive range of minimum inclusion size to quantify the variables of tropical forests functioning and diversity.
Who will benefit from your method?
These methods have direct benefits for research projects in tropical dry forests, by informing their data collection and guiding towards methodological choices that are more appropriate to the ecology of these dry ecosystems. Our results have helped modify collection techniques used by our partner groups in Brazil which also work with this type of forest, and we expect that this will extend to research groups that work with dry forests worldwide.
This will give a broader understanding of the diversity of these forests, which can aid conservation policies and strategies that are more suited to their ecological niche. Thus, tropical dry forest ecosystems and the many threatened species that live within them will benefit from our study.
If you could travel back in time, would you add to or change anything about your method?
We used an innovative approach to develop our technique, which was challenged by the scarcity of associated literature. However, if we repeated the study it would be interesting to include a greater number of sites and expand into other very important vegetation types, such as fire driven tropical savannahs. So, if I could use a time machine, I would try to find collaborators working with data from other sites and vegetation types.
You can read Cléber’s full paper here
and learn more about the Robert May Prize 2022 shortlist here.