This year, Ana Bastos has received the Outstanding Early-career scientist award of the Biogeosciences Division. The BG team wants to truly congratulate them on this achievement! In this interview, we would like to know a bit more about their research and career, seeking inspiration for the young generation of biogeoscientists.
Could you explain a bit about yourself and what made you choose a career in biogeosciences?
It happened a bit by chance. I always had two passions: physics and arts. I was divided between the two so that when I applied to University my first choice was physics, followed by sculpture and history of arts. After two years in a strongly conservative physics department, my passion for physics was fading and I was re-thinking my decision. Until I attended a workshop on climate change and the influence on the drought and unprecedented fire seasons that happened in Portugal in 2003-05. I decided that if I was going to stay in science, I wanted to do something about it. So, I switched that summer to a degree in Energy and Environmental Engineering in Lisbon, which brought me to the geosciences, and where I rediscovered my passion for physics through meteorology and climate science.
During my MSc, I started collaborating on a project on forest fires in Portugal, and took the first steps into the biogeosciences domain. But I think the cornerstone was an essay on the Kyoto Protocol and carbon trading I had to write for an MSc course. I read a lot, and became fascinated with the carbon cycle, its role in the Earth system, but also how its relevance extends to the social and political domains. I had a somewhat provocative presentation about the limitations of the carbon trading system, which ended with one of the teachers almost falling off his chair in anger. It seems to have pleased the other, Ricardo Trigo, who later suggested I apply for a PhD in his group working on carbon cycle variability – an offer I accepted without a doubt. In the first years of my PhD, I found the “green section” at EGU very intimidating since I lacked a strong background in ecology. It took me many years to feel at home here.
Your research focuses on the inter-annual to long-term variability of the global carbon cycle. What have been your specific contributions to the topic?
I am interested in the role of natural climate variability on variability in the carbon cycle. Natural climate variability emerges from chaotic dynamics of the atmosphere and oceans and their interactions and limits the predictability of variations in climatic variables at time-scales from years to several decades. It also adds considerable uncertainty to future climate projections. As many ecosystem processes are controlled by weather and climate conditions, this uncertainty trickles down to inter-annual to multi-decadal variability in ecosystem dynamics and the land carbon-cycle.
The observational records of ecological variables cover only a few decades, in the best cases of 20-30 years. This is still short, compared to the longer time-scales of certain patterns driven by natural variability that can vary over multiple decades (e.g., atmospheric circulation patterns). Ignoring this uncertainty might lead to misinterpretation of variability and trends in the data. For example, I showed that an apparent saturation of the European CO2 sink in the early 2000s could rather be explained by particular combinations of two important modes of atmospheric circulation that affect European weather – the North Atlantic Oscillation (NAO) and the East-Atlantic pattern (EA).
At the same time, understanding the links between large-scale patterns of atmosphere or ocean-atmosphere variability and ecosystem dynamics also offers several opportunities. One aspect is that some of these patterns have some degree of regularity. This allows for a limited, but effective, degree of predictability of the systems affected. For example, knowing whether an El-Niño is developing might help farmers in tropical regions make decisions about crop management some months in advance. Another aspect is that net carbon fluxes result from a balance of different processes, the most important being primary productivity, ecosystem respiration, and disturbance, each of them controlled by multiple climate variables in distinct ways. This makes the study of variability in the land carbon cycle quite a complex multivariate problem.
Since large-scale patterns of atmospheric circulation affect anomalies of multiple variables at a given time, they might better represent co-variability of drivers of ecosystem dynamics, or the occurrence of particular high-impact combinations of climate anomalies. In a study with Zaichun Zhu from Peking University, we showed that large-scale patterns of atmosphere or ocean-atmosphere variability influence primary productivity of more than 80% of the land surface. For the NAO-EA example above, I showed found that both anti-phase combinations of NAO and EA were associated with reduced CO2 uptake at continental scale, but corresponded to different climate anomalies and distinct impacts on productivity vs. ecosystem respiration. This framework can also help to better understand ecological extremes: in another study, we showed that the extreme greening in the Northern Hemisphere in 2015 could be explained by a particular combination of states of the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation (Figure 1).
FIgure 1. Predicting interannual variability in Normalized Difference Vegetation Index (NVDI). a) Northern Hemisphere average NDVI interannual variability observed (green) and corresponding multiple linear regression models fit for 2000-2014 (black) and predicted for 2015 (dashed) and 95% confidence interval (grey). b) Time-series of Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) during December to February between 2000-2015, the best predictors of NDVI interannual variability in 2000-2014, and their corresponding correlation with NDVI interannual variability. c) Spatial distribution of the corresponding prediction, calculated from the coefficients a and b.
What are the gaps that we still need to better understand?
There is still so much to learn! On the one hand, there are still large uncertainties about the relative importance of natural variability vs. climate change in observed patterns and trends, which is partly due to the limited length of available time-series, as I mentioned before, but also process understanding. One challenge is that ecosystems do not simply respond passively to environmental changes, but also have internal dynamics that operate at multiple time scales (e.g. stomatal regulation, growth, disturbance, competition, succession) and modulate responses to those changes. On the other hand, there is still a lot to learn about extreme events and their impacts, and how these might change in the future, and how vegetation responses influence the development of extreme events themselves. Our ability to model some of these processes is still limited, but there is been a steep increase in data availability and spatio-temporal coverage in terms of monitoring networks, remote-sensing datasets, manipulation experiments, which will allow us to better quantify and attribute variability in the land carbon cycle. There is a lot of excellent work and exciting advances coming out every year, so to me, this is a really stimulating scientific domain.
What have been the biggest challenges and greatest opportunities in your career?
The biggest challenge was mental health without a doubt. I believe it is important to talk openly about this because it is a challenge many young career scientists face, usually in silence. My biggest struggles were balancing my anxious character with the inherent uncertainty of our careers, fighting the emotional weariness that came with moving from one place to another every couple of years, and juggling work with a long-distance relationship with another equally mobile scientist. I was extremely lucky that my PhD advisors were always supportive and that I was able to find help from colleagues, family, and friends but also health professionals that kept me afloat. I know that not everyone can find such a level of support. Without it, I would not be in academia anymore.
A challenge of being a PhD student in Portugal was its remoteness compared to other countries in Europe and reduced funding availability. So, I applied as much as I could to exchange programs and travel grants, and these turned out to be the greatest opportunities: I met excellent scientists who were to become my mentors, and started building collaborations that I still keep today. So, I would like to highlight the importance of funding to support the mobility of young scientists.
Do you think that some factors are relevant for a scientist’s career?
I think two aspects play a huge role in the success of young scientists: good mentors and good collaborations. Academia can be a very harsh environment from the emotional point of view. Having mentors that challenge and encourage us scientifically, but that can at the same time be caring and supportive in our personal challenges makes a big difference. But also having mentors that give us the freedom to explore ideas and to establish independent collaboration networks early on in our careers. For me, collaboration is (almost) all science is about: mutual learning and discussion, sharing ideas and data, going further together.
For sure there are still biases in academia, and graduating at certain universities, in certain countries, or with certain people, makes things easier for some. But this should not discourage young scientists with diverse backgrounds, and I do hope that the extra effort required to overcome these barriers starts to become more and more recognized.
What would be your general advice for early-career scientists?
Each person’s experience is so different, I find it hard to give advice! I think above all it is important to have fun and find meaning in the work we do, and to take care of our well-being and that of our peers. Seems pretty basic, but unfortunately, it is not a given, so I guess my advice would be to keep these things in mind when deciding about mentors and positions, the projects we develop, and the colleagues we choose to collaborate with.
