Marking bees with glow-in-the-dark powder

Lab notebook style post to keep record of pilot experiments I run. We used one day this spring to see if we can track what bumblebee queens are doing. We captured queens and applied a colored powder to them. The idea is to see if we can find the powder in flowers after that, to see where and what they visit.

Lessons learned:

  • Capturing queens is time-consuming. 12 queens – 6 hours.
  • Marking them is super easy. Only a tiny bit of powder in the vial is enough. Inside the vial bees buzz and cover themselves completely.
  • First tests with too much powder were bad (bees too covered, see photo below)
  • We used glowing in the dark powder (sold in 8 colors in amazon) in case it helps spot it later with a UV light (also very cheap at amazon).
  • Very few flowers are open at this stage of the year, so we targeted a few Salix at different distances from the marking area along a power line corridor, and look for powder in Salix flowers after 6 hours.
  • We recovered a single flower with powder, but was in a Salix 500m down the corridor (not bad)
  • Not convinced on this technique for queens, but may work better for workers, when you can mark 100’s of bees.

As always we only had bad phone cameras, here is a photo of the first trial with way too much powder used. This bee was seen 1 h. after the release flying happily.Bee_glow

 

Pollinator contribution to yield quality (and my preprint experience)

I already shared a preprint and post about this paper some time ago, but now is officially peer reviewed and online. You can download the final version here: https://peerj.com/articles/328/

My experience with preprints? The publication process at ThePeerJ was super fast (~ 3 months from submission to publication). In this 3 months 84 people visited the PrePrint and only 52 downloaded the PDF. Nobody commented on it. Taking into account that we are 11 authors (who should account for some of this downloads), you may think that the visibility of the paper didn’t increase much from being out there in advance, but I can prove you wrong. Maybe not much people read it, but I was contacted by one PhD student with a question about the paper. She was working on the topic and preparing the next filed season, so for her, reading it in January, instead of in April was useful. Plus, she found it by google-ing about the topic, proving that preprints are discoverable. So, not always by publishing preprints you reach more people, or get amazing feedback, but at least you can reach the right people, and that’s important enough for me.

Communicating science with comics II: the oikos meeting

I have been exploring how to effectively communicate my results and engage with the audience. I just attended this week the Nordic Oikos meeting and presented a risky poster explaining one of my side projects in a comic stile. But I did one very clever thing: Partner with an artists (and friend, and scientific). I designed the outline and place a first draft of the graphs and text. Then I asked him to do whatever he wants on the cartoons to illustrate pollinators, soil, pests… He could choose the drawing technique and in summary, he had absolute freedom. It was so amazing that he even place myself and Vesna in the poster!

Oikos_final_lowresThe poster had very good critiques, and fulfilled its mission. Drawing the attention of the people and making a story easy to follow. I am looking forward to collaborate again with Jose Luis in another project to enhance science communication!

Full resolution PDF

One more paper showing pollinators matters

We have a new PrePrint up at the peerJ (note that it is not peer-reviewed yet, but already citable) showing that pollinators increase not only yield, but also the quality of four european crops. While the evidence that pollinators are important for crop production is quite strong now, specially after Klein et al. 2007 review and Garibaldi et al 2013 synthesis, I think our paper still contributes to the field by quantifying the contribution to yield (and quality!) in a experimental way along a landscape gradient. Moreover, I think the introduction and discussion is well crafted and points out some aspects that are difficult to cover in short high impact papers (i.e. like our “Garibaldi” science paper). Which points? You will need to read the paper.

You can see the data were collected in 2005, so it has a long, long story I prefer not to dig in. In any case, it ended up in my table and I experienced the pains (and joys) of working with someone else data. That’s why, after waiting 8 years in a messy excel file, I felt that the data deserved to see the light as fast as possible and I pushed to publish it as a preprint. This is an awesome way to make it public probably ~ 6 months earlier than the final reviewed version. I am also happy to try a new Journal that is doing very nice and innovative things. Taking together this preprint and my F1000Research experience, I really think it makes no sense to hide a paper ready to be read until its final version. This can only slow down science. Read more about preprints here.

PS: Also read Klatt et al 2014 paper on strawberries, which spoiled a bit our findings, but is really good.

Native bees buffer the negative impact of climate warming on honey bee pollination

We have a new paper in GCB lead by Romina. In this paper we do a very cool thing. We characterize the daily activity period of a bunch of bee species and how this activity is modulated by temperature. We show that while honeybees decrease visitation to watermelon at very high temperatures (literature suggest that the reason is that honeybees need to go for water more often when hot, hence have less time to visit flowers), some native bees concentrate its visits on the warmer hours. I think that understanding behavioural differences among species is neat to answer BEF questions.

wtbeeIn addition, we play a bit with future temperature scenarios to see if (all else being equal) visitation and pollen deposition will change with warmer temperatures. We show that the visitation reduction predicted for honeybees is compensated by an increased visitation rate by native bees (taken altogether). Despite this predictions should be interpreted with care, it adds up to the several lines of evidence suggesting that conserving all species is needed in order to have flexible ecosystems able to cope with environmental change.

 

 

Is there a pollination crisis?

After some months writing this blog, finally I can do some self-promotion and post about our new article just published in PNAS.

Do you think we are experiencing a pollinator crisis? Take note of your answer and keep reading.

In this paper, we show that most Northeastern US bee species persisted along the last 100 year. And those are 100 years that has transformed the landscape dramatically. However, we show that community composition changed markedly. The loser species are some big species, often specialists and with short activity periods. See a quick figure I made trying to capture the essence to outreach people who only have one minute to spare.

BartomeusPNAS

So, what that tell us about a possible pollination crisis? A crisis is something that leads to an unstable and dangerous situation, in this case regarding the fate of pollinators and the service they deliver. Nobody talks about a bird crisis. Some bird species are doing great, some are threatened with extinction, but nobody would dare to generalize about the fate of all bird species as a whole. I think is time we take the same approach with such a diverse group as the pollinators (including bats, birds, butterflies, bees and a long etc…). In this paper we show that some bumblebees (e.g. Bombus impatiens) are doing great, while others are on the brink of extinction (e.g. Bombus affinis). We need to understand better species responses and stop crying wolf for all pollinators. There is a fine line between raising general aware among citizens about the importance of pollinators and their conservation and an overestimated alarmist call. Every time a farmer reads about the pollination crisis while seeing that his field is full of bees buzzing around, we (scientists) are loosing credibility.

Moreover, if is crop pollination and food security what concerns you, it may be that the winner pollinator species, those that thrive in human dominated landscapes, are also the best ecosystem service providers. And if it’s biodiversity (and its overall functioning) what you want to protect, then we should look at which species/habitats needs maximum conservation. We need to move forward and pose the relevant questions, instead of looking for a general declining pattern that hopefully is not really there.

I am expanding too much for my taste, so more on that next week. But to make clear my point: we need to keep studying pollinators (keep funding me!), but next time you cite worldwide pollinator declines, cite me also (i.e. Pots et al 2010, but see Bartomeus et al 2013).

Bartomeus I., Ascher J.S., Gibbs J., Danforth B.N., Wagner D.L., Hedtke S.M. & Winfree R.  Historical changes in northeastern US bee pollinators related to shared ecological traits, Proceedings of the National Academy of Sciences,   DOI:

*Giving the importance of the subject, it was specially important for us to make all historical bee data available @datadryad (dx.doi.org/10.5061/dryad.…) for further analysis and replicability.

Pollination effectiveness landscape

I want to show you a pollination landscape, but this is not a pollinator landscape with flowers and nesting sites, but a plot showing two components of pollination. Quantity and quality. A recent paper by Pedro Jordano (see here for other work on seed dispersal landscapes) inspired me to plot my data that way, which I think is just awesome. I am a little ashamed I can not fully follow the part of his code (but is great that people is sharing code!) dealing with plotting the z axis… but if you have a hammer, all your problems will look like nails. And I had used recently expand.grid( ) and loess( ), so I used those to do my z axis. I also think is nice that people has two options to plot the data. So here is the plot:

plot

Here you just see that bumblebees and Lasioglossum provide similar total pollination levels (yellow), but through different mechanisms (quantity or quality).

Here you can find the code to reproduce the plot.

We know nothing

Today I read a paper about bee population dynamics published in Ecology (Franzen and Nilsson 2013). Given the current concern about bee declines (more on that in a few weeks) one can assume we (scientists) understand the basic dynamics of bee populations, or at least we have an idea of their life histories. Well, the paper monitored one metapopulation of one species during 9 years and found that fluctuations on the number of nests among years are huge (more than one order of magnitude). Why? We don’t know and It is not correlated with floral resources or climate. Some speculations include source-sink dynamics, a prolonged diapause or bet hedging strategies to avoid natural enemies. We know nothing. And you may ask, why is this published in Ecology? Well, because I think is a good paper that at least shows some data. That means that given the knowledge we currently have, this tiny bit of information advances our understanding.

Really basic research is not sexy but can we (and I am the first guilty) understand a pollinator crisis if we don’t know if it is predation or it is competition what is driving bee fitness. Or can we understand the actual structure of plant-pollinator networks, which are characterised by an incredible turn over among years, without knowing if bed hedging strategies are the norm or the exception (Danforth 1999). Can we assess the effect of landscape configuration on bee populations without the basic natural history information like eggs per female, or growth rates?

Image

Franzen M. & Nilsson S.G. (2013). High population variability and source-sink dynamics in a solitary bee species, Ecology, 130204095918002. DOI:

Who are the pollinators? (with R plot)

I’ve been dreaming on writing a manuscript about who are the pollinators for a while, but it looks I’m not going to have the time soon, so here is an early draft of what the main figure should look like:

pollinators.001

It’s surprisingly difficult to gather quantitative information on which animals are the main pollinators, and on which aspects of pollination they are good at. That figure can cover more aspects, or split the pollinator guilds in finer sub-groups, but this is just a first pass. As expected, bees are the clear winners!

I used guesstimates based on Winfree et al 2011 and the following articles:

Number of species:  How many species of a given taxa are described based on different taxonomical resources. But not all species on a given taxa are necessarily good pollinators!

Efficiency: That one will vary a lot among species of the same group, but based on Sahli and Conner 2007, and other few cross taxa studies measuring pollen deposition I gave values from 1 to 10 to the different taxa.

Frequency of visits: This is based on Neff and Simpson 1993 descriptive work. An update to that with recent datasets is really needed! Values from 1 to 10.

Distribution: Some taxa are widespread, while others restricted to some areas, like to the tropics. Ranked from 1 to 10.

Number of plants pollinated: A complete guesstimate. Using Ollerton et al 2011 approach may give us better numbers.

Number of crops pollinated: Based on Klein et al 2007.

And as I know that the R code is what readers really want, here it is as a gist. I used function diamondplot{plotrix}, but I needed to edit the function first in order to scale the axes. The original function scale the groups (pollinators taxa, in my case) instead of the axes (pollination aspects) which was not desirable for my plot.

See you late January after a break!

 

Can niche and fitness differences explain biological invasions

Following up with my “Theory vs Data” post, I want to share an example of a beautiful theoretical framework to understand the invasion processes and an idea on which can be the perfect study system to validate it.

Mc Dougall et al (2009) have one of the more compelling figures I saw summarising the hypothesis that niche and competitive differences between exotic and native species can explain the outcome of the invasion process. The figure speaks for itself:

While I was in the US I planned to use this framework to understand the effects of Osmia cornifrons (a mason bee) invasion on the native Osmia lignaria, but I had no time to follow-up on this. Anyway, for that end you would need to prove the following:

1) Are their niches overlapping? Both bees are on the same genus, have similar size, phenology, nesting habits, and probably visit similar flowers, you just need to put numbers on those things (e.g. which hole diameter they prefer to nest on). For example, this data is from a preliminary experiments I did on its phenology. Interestingly, the result suggest the invader emerge slightly (but significantly) earlier than the native. So, quantifying all this can be important.

2) Is their fitness different when raised alone? Buying this bees and monitoring its nests is easy. Moreover, measuring offspring (a fairly good proxy of fitness) is a piece of cake compared with other species. Well, at least in theory, because I tried it in 2011 and an April snowstorm killed 80% of both populations. Hence, I have no data here.

3) It’s the native fitness lowered when they are raised together? That’s an important part (especially the effect size), because they may coexists just fine (even if sharing niches).

I am not in the US anymore, so, is impossible for me to do the experiments. If anyone wants to explore this idea further (undergraduates seeking for a project, jump in!), the idea is here, and it’s for free!

———————————————————————————————-
MacDougall A.S., Gilbert B. & Levine J.M. (2009). Plant invasions and the niche, Journal of Ecology, 97 (4) 609-615. DOI: ———————————————————————————————-

And now, what can occur with this post? 

– Worst thing it can happen is that nothing happens.

– Will be pretty cool if someone does this or similar experiments, even if I never know of its existence (well, I hope at least not to miss the article when it gets published!). I would be happy with that because despite I did some thinking on this I assume this ideas are “on the air”, and that’s precisely why I post them here.

– Will be awesome if that someone also contact me and we end up collaborating. (incentive: I have also some ideas on how to analyse it)

– Will be terrific (I am running out of superlatives) if people start reporting they have data on niche and fitness differences for other systems and we end up with a meta-analysis proving (or disproving) that this theory can correctly predict invasion outcome with some generality. For example, where is propagule pressure fitting in this framework? Niche and population growth/species traits hypothesis clearly are captured here, you can even account for lowered native fitness due to disturbance (wow!), but the number of invaders arriving may be a missing piece. Also scaling up to the community level seems a daunting task.