[this is a half-baked reflection after a lab meeting discussion on the EU biodiversity policies. Thanks to the lab and especially to Elena Velado for the discussion]

We are embedded in a culture where the only valid success is complete success. Making compromises, or renouncing something to focus on other priorities is often seen as a weakness if not a failure. There is no better example than what we see every day in the movies. Even when the main character has to make a sacrifice, in the end, he or she ends up gaining everything, including what they sacrificed. For example, you need to let go of your true love, but then you discover that was the way to secure it. You renounce your dream job for your family, and this allows you to find an even better job and be successful also in that dimension. You need to betray your friends to save the galaxy, and your friends still love you for that. You get the point. We are in a culture where we are expected to do small sacrifices to gain it all anyway, so in the end, you really don’t sacrifice anything.

The EU Green Deal is also embedded in this narrative, where we are promised that with a “small” economic sacrifice, we can conserve biodiversity, and in doing so, we will enhance our well-being and our economy. No real sacrifices and a vision that changing gears to support biodiversity will allow us to keep growing economically. I love this story, and it would be great to switch to a more sustainable future with no real costs. In fact, I used the fallacy that conserving pollinators is cost-effective because they will increase your crop yield. But this is not completely true. When going deeper, we also showed that pollinators worth conserving are not usually the ones who deliver crop pollination (Kleinj et al 2016) and that the costs of sustaining pollinators do not always compensate economically via an increase in yield (Scheper et al in prep). This does not mean we shouldn’t safeguard pollinators, but that doing it only for economical reasons is not going to work. At some point, we need to sacrifice something, and it’s our choice.

The danger of a narrative that ignores real situations of compromise where you need to sacrifice things that make your life easier, and not acknowledge that there are trade-offs that force us to choose is that we create false expectations. Expectations that we will always win in all axes. But narratives are important because they prepare society to make decisions. And we need honest narratives now to prepare us to take those decisions tomorrow. Only by being clear on the fact that we will need to make decisions and renounce something in order to gain another thing will set us in the right framework.

We should start the conversation on what are we willing to sacrifice or compromise and what not to conserve biodiversity. Indeed, we may discover some sacrifices are not as hard as they look, especially for the average citizen. Maybe we prefer to have one more species of butterfly in the EU than having a few rich people traveling to space for pleasure. Maybe we prefer to eat strawberries only in spring, but have birds migrating through our wetlands. It’s all about educating ourselves and being aware we decide our future, but not selling fairy tales.

Our behavior is heavily influenced by the context we live in. The first step to change behaviors is to create the adequate context, and for me, this context needs an honest narrative that acknowledges trade-offs and prepares us to take informed decisions.

You will never have as much time as during your PhD to collect high-quality data. I didn’t realize it at that time, but detailed data you really know and understand is a lifetime companion. I used mine for its main purpose during my PhD, but also to test new methods when I needed to test those with data. In addition, it contributed to several synthesis papers, including an ongoing one led by someone at my lab right now. This makes at least five papers I used this data so far. As the data is openly available for a long time it was also used by several other synthesis papers. All this preamble is to encourage you to love your data!

When I collected the data I did most of the bees id’s myself (I had lots of help from experts such as Jordi Bosch, but in the end, it was me who ran through all the samples). This implies I identified several individuals to moprhospecies level, and I couldn’t put a name in all my pollinators. I would say this is typical for many ecological studies, and we always cross fingers this is good enough at the ecological community level. More than 10 years later I decided to properly identify by taxonomonists the full collection (which I managed to keep all this time while traveling through three countries!)

Almost 30% of individuals changed from morphospecies to being properly identified at the species level. Among those, most morphospecies belonged to a single species, but not all. In general, I underestimated the number of species present from 81 to 114. Several similar species were lumped together by my ignorance. However, to my relief, this did not change drastically the relative differences between the 12 sites, as seen in the figure. Connectance and the number of links per species decreased for all sites at similar rates, but some metrics are less consistent, such as nestedness, but nestedness is also a metric known to be quite volatile.

As I said, the data was released in different places. Web Interaction Database has a copy of the data in matrix format, which makes it hard to split the data e.g. by dates. Web of Life has even a more drastic pooling, which I am not sure how they did it, as I was not contacted by them, but I noticed all sites are pooled, including invaded and non invaded sites. FigShare had the best data so far, and it is associated with a paper and its analysis, so it’s better to keep this version at the morphospecies level for historical reasons. Hence, the new release of the data, with all new identifications is at Mangal. The webpage is very nice, and you can access programmatically all the networks in R.

library("rmangal")
mgs <- search_datasets("bartomeus")
mgn <- get_collection(mgs)
mgn; names(mgn)
mgn[[1]]$nodes
mgn[[1]]$interactions
library(tidygraph)
tg <- as_tbl_graph(mgn[[1]])
plot(tg)

I am a bit embarrassed by the lower quality of the original data, but better fixing it now than never. Long life to data!

This is quick post to free some very cool bee icons my good friend Jose Luis Ordóñez drew for our video “What’s happening to the bees?“.

In the spirit of open science, feel free to use them under CC-by-nc licence for your research needs. Note that credit goes to Jose Luis Ordóñez and Ignasi Bartomeus.

Enjoy!

Animated gifs:

And the static versions:

There are important points in life that are prone to self-reflection. Getting tenure in the Spanish research system is one of them. Last week I won a highly competitive permanent position as a researcher at CSIC and I am incredibly happy to get the opportunity to work full time to advance science with the stability required. Since then, three contrasting thoughts have emerged in my mind.

First, I have an immense feeling of gratitude. I am completely conscious that the way I do science is only possible because I am not alone in this journey. A huge number of people has supported my ideas, gave me opportunities to try things, shared their knowledge with me. Thank you all! It was pretty flattering to get so many congratulations over the past week. Plus, I have to admit it the journey has been pretty fun so far.

Second, I still feel uneasy with the full selection process. All 20 candidates competing for the position deserved a stable research position. CSIC keeps evaluating quantity over quality and most positions get filled by researchers over 40, and often older. Being considered a “young researcher” at 39 and with two kids it’s not funny anymore. The hyper-competitiveness we are immersed is damaging careers, but also science itself. Sometimes I feel we are not longer doing science, but running on a hamster-wheel.

Third, I got this position by privilege. My parents supported me while doing my degree and always encouraged me to take risks and explore new paths. It’s easier to do when you have a safety net. Neither me nor my family had remarkable health of economic problems. I am a white man and as such I never experienced harassment of any type. Even with the wind at my back, it was bloody hard to survive in academia in Spain. This implies we are missing a lot of brilliant researchers that didn’t had it that easy.

Now is time to reconsider things. Inertia is very powerful, but now I have the freedom to decide (to certain degree) what science I want to do and how. Let’s use this power wisely. And let’s fight to change the system from the inside.

I quite enjoy writing about what I read, as well as the stories behind the papers I wrote, because there is always much more than what its finally printed. I post here two pieces recently published in other blogs / journals and a new story behind a paper with a looong history.

1- A book review of one of the books about bees I enjoyed the most: The Solitary Bees: Biology, Evolution, Conservation. by Danforth, Bryan N., Minckley, Robert L., and  Neff, John L.: https://onlinelibrary.wiley.com/doi/abs/10.1111/evo.14067

2- The story behind an R package we wrote to better understand species coexistence: htttps://methodsblog.com/2020/08/18/package-to-infer-species-coexistence/

3- A story behind a recently published paper or “Why some bees have big brains?”

Today we publish a paper I am quite proud of, as we break new ground after a very long journey. In a nutshell, we investigate bee brain evolution and show that some surprising results.

Back in 2009 I read “pollinators cognitive ecology” book and I started working with Daniel Sol on cognitive ecology of birds. The seed was planted. Fast forward a couple of years, I assaulted Marc Seid in an Entomological Society of America conference to ask about extracting brains of hymenopterans. He kindly invited me to his lab and I learnt the technique, but that was nothing we can do as a side project without proper funding. In 2015 we finally got funding and Ferran Sayol (the lead author) spent some time with Marc dissecting bee brains. That was a lot of work, complemented with more brains from Europe in the subsequent years. Overall, we weighted brains for > 100 bee species. Probably, we multiplied by 10 the amount of data existing on bee brain size. This is already a huge step forward! The next hurdle was getting a proper phylogeny of those 100 species, which required further collaborations. At the end, all the pieces fell finally together!

First, we show that sociality do not require larger brains. This is not surprising, as it was suggested before for other insect groups, and even for vertebrates it’s controversial. Surprisingly, being specialist do requieres having bigger brains. This was unexpected at first based on what we know for vertebrates, but it may be more intuitive than we think. For bees, navigation skills for locating and remembering resources is essential, specially if you are specialised in a few resources. However, handling different types of flowers is not as challenging as eating very different resources such as insects, grain, etc… Moreover, parasitic species tend to have also larger brains (but our sample size is tiny for those), which reinforce the idea big brains are needed for navigation and location of nests. Have a look at the paper, It’s very cool!

Sayol, F., Collado, M.A., Garcia-Porta, J., Seid, M.A., Gibbs, J., Agorreta, A., San Mauro,
D., Raemakers, I., Sol, D., Bartomeus, I. (2020) Feeding specialisation and longer generation
time are associated with relatively larger brains in bees. Proc. R. Soc. B 20200762

https://dx.doi.org/10.1098/rspb.2020.0762

Violeta and Ignasi Bartomeus

As a simple game with the kids, we started counting daily flower production on a single plant of Cistus albidus that we transplanted last year (so it’s 3-4 year old, and 1.5 meters tall). It turned out quite surprising! I was expecting a clear peak of flowering around a normal distribution, but the flowering went on for > 100 days (very rainy season), with two distinctive flowering peaks. When C. crispus started flowering we did the same with another single individual (1 m tall). In this case, the peak is more clear.

We also recorded nest completion by three Osmia bicornis female bees that regularly visited C. albidus. Bee “O.b1” completed two nests, but the other two only one. Note it took a long time for O.b1 to build the second nest!

Conclusions: Now I have way more questions than when I started. I wonder about individual lifetime flower production over years, variability across individuals, relationship with fitness, how this compare to community level phenology patterns, …

This is basically a quick note for me to remember which bees visited us these last years. As I am keen on promoting pollinator-friendly gardens, this may be interesting for someone else. Maybe.

Context: We moved to this house two springs ago. It has a ~4*8 m garden and is located in a residential area with allotments (great for bees) nearby.

2018: The garden was a perfect lawn without a single flower + a patch of bamboo and a patch of bird-of-paradise flowers (useless for native bees). I don’t remember seeing any bee that year. I stopped watering the lawn (makes no sense in Seville to have a water-consuming lawn).

2019: We dig out the bamboo and the bird-of-paradise flowers (harder than I would ever though!) and planted Rosemary, Lavanda, Rockroses, and Teucrium. I also removed a 1*4m patch of lawn to plant some vegetables. I added vertical bamboo reeds (I had plenty!) in the soil and add a few old logs in a corner.

Bees:

1. Eucera sp. Early season in lavanda.
2. Chalicodoma sicula in Teucrium.
3. Megachile sp nesting in the ground (in a pot!) Entering leaves, Honeybee size.
4. Ceratina curcubitina (?) nesting in the vertical bamboo reeds.
5. Holpitis sp. hovering around the logs.
6. Xylocopa violacea Loves teucrium. Males using some horizontal bamboo reeds to sleep.
7. Apis mellifera Rare, in teucrium.

2020: I installed a couple of bee hotels for megachilids, let the lawn go wild. The grama is still languishing, now intermixed with clover (Trifolium repens), melilotus (Melilotus sp.), and other annuals well-adapted to our climatic conditions.

Bees: (Eucera, Chalicodoma and the big Megachile not seen again)

1. Xylocopa violacea lots in teucrium (March-April), and females using the new bee hotels and expanding the canes.
2. Anthophora sp. Rare in teucrium.
3. Osmia bicornis mainly in Cistus albidus. 3 females, 4 nests and 2 not finished.
4. Hylaeus sp. visiting broccoli. I think they nest in the vertical reeds also.
5. Ceratina curcubitina (?). A real explosion this year. All vertical canes full. Cistus crispus, teucrium, broccoli, strawberries, Melilotus, clover.
6. Anthidium manicatum (?) in Teucrium. Males patroling and females gathering leave hairs. Earl morning to late evening (May).
7. Anthidiellum breviusculum (?) in clover.
8. Hoplitis sp1. Again in the logs. Also in Lavanda from time to time. No idea where are they nesting.
9. Andrena sp. Very rare (seen three times maybe?). In C. crispus and once I saw it digging in the vegetable plot, but never again.
10. Apis mellifera in Teucrium and clover. More common this year, to my disgrace.
11. Lasioglossum sp (the golden one, similar to gemmeus) in Brocoli.
12. Megachile sp. in Melilotus A very small one close to M. apicalis. It nests in the vertical reeds and uses petals to close them.
13. Hoplitis sp2. Late season. Looks like adunca, but I have no echium nearby. Active at dusk, but no nests completed yet (still active, but is already 30ºC). UPDATE: two nests colsed + two not finished by 7 June

Maybe I am missing some super tiny bees, as the ceratinas + hylaeus + lasioglossums sometimes fly fast and who knows what else is mixed there. All ID’s are mine, so maybe some are incorrect.

13 species in 2019, 16 overall! Looks like megachilids are over-represented. I miss more Andrenas, and I did not see a single parasite yet. No bumblebees, but this is expected as they are rare in Seville. Next year, more!

As researchers, we are supposed to be good at a plethora of things. Managing people is one of those things that nobody teaches us, but that ends up being pivotal for the lab functioning. In fact, I would say that researchers, in general, don’t feel comfortable being a boss and see the time invested in managing people as a burden that prevents them to do more important things such as actual research. I’ve been there, and I think that it is pivotal that (we like it or not, we are good at it or not) we assume part of our job as IP is to be a boss, and we try to be a good one.

With this in mind, I have read several pieces on scrum and agile culture and tried to understand how to create an efficient and happy team. The last book I read was Radical Candor, by Kim Scott. It is focused on managing people at big companies, but I think a lot of stuff can be applied to academics.  The main message of the book is that you need to create a culture of caring for people (and for the science you are doing) and of giving clear and honest feedback.

I think that in academia (in general) we are good at caring personally (small labs, with people passionate for science and mind alike, makes it easier), but we don’t always challenge directly. In my own experience, when things go well, it’s super easy for me to give honest feedback and improve the project even more, but when someone is under-performing I have a hard time making that clear, and this is bad for you, for him/her and for the team.

The following are basically notes for me and the lab, with no ambition to be comprehensive or detailed:

The book makes crystal clear that spending a morning listening to your team complain about personal stuff, or about an internal fight or celebrating their success is an integral part of your job. Not a distraction. Your job. This makes it easier to allocate time to that in your daily schedule.

It also encourages focusing not only on people writing the important papers, but on hard workers that make this possible. Having a “stable” lab technician who solves the day to day field and lab work is the best decision I toke as PI so far. Invest in core people. This is really hard in academia where positions depend on short term projects.

Do not personalize. People are not sloppy, they may have done a particular job in a sloppy way. Then, Its easier to fix specific actions. The “Situation-behaviour-impact” chain is the best to describe a problem. The best feedback is given often and in impromptu situations, is specific about the problem and offers solutions.

If you want feedback (or criticism as stated in the book) to be part of your team, cultivate it at all levels. Encourage criticism also towards yourself (or your ideas) and among your peers.  I like the following process to encourage criticisms, starting by listening (not by replying to criticism or cutting it or offering excuses). When you got criticism, ask to give details and strive to understand it. Do not react. (I’ll apply this also to my normal life).

I was reinforced on running retrospectives after papers are published in the lab. The book also recommends blocking time for thinking and for working on personal projects, something I am also doing (albeit I should do more) so I don’t spend the day in meetings.

Finally, It made me think about the lab culture. It’s hard to judge internally, but I would like to think the lab culture is to be open and replicable (even if we often do not achieve it!), to put people first and to be risky in our ideas and approaches (even if this means we often go for the big picture, and miss some of the important details). We also are committed to outreach.

Science is often taught as magic. You pour sodium bicarbonate and Booom, you rocket launches. Which for kids, it is not different from saying “Alohomora” and boom, the magician disappears. Both things are fundamentally different, but if you only see the result, they are hard to tell apart, especially for kids. This is why I became interested in teaching the process and not the result. In fact, the next two ideas I successfully ran at my daughter class focus on playing and experimenting, and not on learning concepts.

Evolution:

Objective: See at play the heritability and natural selection concepts.
Material: Paper and pencil
Time: 45 min

Don’t tell them this activity is about evolution. Start by drawing 4-5 animal shaped sketches. Ask the kids to draw their offspring. Look at the children’s drawings and reflect about inheritance. Are they equal? No. Are they very different? No. Lesson one: There is heritance, but with variability.

Now “kill” a few drawings. Only the ones with long-ish neck survived, or only the ones with thick fur. You are acting as the natural selection. Then ask again the kids to draw the next generation of the surviving animals. I bet some will try to emphasize the surviving characteristics. Repeat the process and kill again the unfitted drawings. If any kid draws a super long neck or a super furry animal (or an animal with newly grown wings), kill it too, as it’s impossible from such parents to create such offspring.

After 3-5 generations wrap up the best you can and compare the first generation with the last one. Are they from the same species? has the species evolved?

Alternative: If the group is big, split it in two after the first generation. The second group will migrate to an island, where selective pressures are different. Now you can compare the original parents with the two evolving lines and see speciation.

Network Theory:

Objective: Understand that networks are everywhere and that network structure matters.
Material: cork, thumbtacks, and rubber bands
Time: 45 min

I started the activity by asking which type of networks they know (P2P, Facebook, trophic networks…). Then I took a well-connected web made out of yarn and knots and ask a volunteer to cut a link. The web was unaffected. Then I took a second web with few connections and ask again to cut a link. The web was easily broken.

However, the main activity consists of running a “bingo” game on a network like the one in the photo above, which mimics a plant-pollinator network with thumbtacks (species) linked by rubber bands (interactions). You give one network to each group. When a plant is randomly selected, you remove the thumbtacks and all rubber bands attached to it. If a bee runs out of rubber bands, it dies. The game ends when a group loses 6 bees. The interesting thing is to see how some groups lose bees way faster than others? Why? Kids tend to say because some networks have more rubber bands, but no. All should have the same number. It only depends on the structure. Hence, you should give them contrasting structures.

Now you can make a nested network and explain this is the shape they have in nature. Next, you can ask half of the groups to start “killing” the smaller, less abundant plants, and the other the larger, more abundant plants. Start by asking the second group if this structure is robust. They will say no! Removing 2-3 plants kills rapidly 6-7 bees. Now ask the second group. They will say it is robust, as removing almost all plants didn’t kill a single bee (see attached presentation). Wrap up explaining that in nature rare plants are gone first, and abundant plants are unlikely to get locally extinct first.

As a final wrap up, I made a fake social network of themselves (again, see presentation). I started by adding nodes strongly connected (best friends), then add modules (gangs or groups of friends) and then connectors (kids that like to play with different groups) and stress that these roles are dynamic, and ALL are important to make a robust network.

Find here the presentation I used and the PDF of the bee drawings made by my friend Paula Pereletegui (Thanks!). Corks can be bought at IKEA.

Disclaimer: These are quick notes for scientists that already know about evolution or plant-pollinator networks and want inspiration to reach out. If you want to do this at your school, but you are not familiar with the basic concepts I am happy to help. Just email me.

Today we celebrate an important day. We celebrate equality in science! Hence, I want to make a post highlighting a few great researchers I have the privilege to work with. I was lucky enough to interact with lots of great female scientists and my stereotype of a scientist’s is not an old white man. I know this is not common, and this is why it’s important to show that there are plenty of awesome female researchers like the ones I met, specially to ensure young girls have a diversity of role models.

So here there are four great researchers in different career stages. First, my PhD Advisor, Montse Vilà. She investigates the impacts of invasive plants and was my first contact with a real scientist. Second, my PostDoc advisor, Rachael Winfree, from whom I learnt a million things. She investigates how bee diversity determines ecosystem functioning. Third, Romina Rader, who studies non bee pollinators. We met as postdocs and has become one of my usual collaborators. Finally, Ainhoa Magrach, which I hired as Postdoc last year and it was super-stimulating to work with. She is now studying the impact of global change on biodiversity. I could name many more because almost half of my coauthors are great female scientists, but I’ll stop here. Today several initiatives are highlighting the awesome work that women do in ecology, for example here (spanish) or here, so check it out and spread the word, specially among young girls and schools!