Api selvatiche urbane a Milano

La stagione primaverile porta con sé l'esplosione della vita. Non solo le fioriture, ma anche gli impollinatori tornano in azione.

Sono dr. Paolo Biella, e insieme al gruppo di ricerca di cui faccio parte (Zooplantlab, Università di Milano-Bicocca, Dip. di Biotecnologie e Bioscienze) durante la primavera corrente e la prossima estate studierò impollinatori del gruppo delle api. In particolare, mi concentrerò su api selvatiche che non producono né miele né colonia (che in realtà costituiscono la stragrande maggioranza della diversità di api). Le api che studierò hanno la particolarità di fare nidi in cavità di varie tipologie, solitamente in muri o nel legno.

Istallerò nidi per attrarre api solitarie, nidi che abbiamo preparato nei nostri laboratori con il paziente aiuto e l'immensa passione degli studenti di dottorato e laureandi. I nidi saranno posizionati in vari contesti della città di Milano, grazie all'appoggio di associazioni ed enti territoriali (si veda mappa di seguito). Raccoglieremo dati concernenti il tasso di nidificazione e la diversità di pollini raccolti da questi affascinanti organismi del gruppo delle api.

Questo studio ci permetterà di comprendere come il paesaggio urbano possa sostenere le popolazioni selvatiche di impollinatori, e ci consentirà di comprendere meglio quali parametri ambientali urbani favoriscono alti tassi di nidificazione. In altre parole, potremo capire come rendere più sostenibili i paesaggi urbani dalla prospettiva delle api (il video seguente che mostra api nidificanti è di A. Ferrari).

Mappa dei siti in cui sono stati collocati i nidi

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Le persone che hanno contribuito alla realizzazione dei nidi sono:

Federica Barreca

Luca Caprotti

Matteo Ferrara

Andrea Ferrari

Andrea Galimberti

Tiziano Galimberti

Rosanna Giacovelli

Alberto Mattia Nodari

Emiliano Pioltelli

Nicola Tommasi

Luca Tonietti

Hanno anche contribuito:

Fem2Ambiente

Vivaio Bicocca

Isola Pepe Verde

Orti di via Padova

Boscoincittà

Cascinet

Parco Nord Milano

Are generalist pollinated plants the most important out there?

Those who are familiar with how habitats are being altered by human or natural activities also know that usually these alterations tend to be more harmful to some species and less harmful to other ones. As pollinators rely a lot on flower resources (that is pollen and nectar), an habitat alteration could target specific types of plants with some effects on pollinators too. To facilitate our understanding of how pollinators respond to habitat alteration we run an experimental test in which we removed several highly generalist plants from the plant community.

We found that removing these key plants had strong effects on the interactions between plants and pollinators. Earlier on, I presented some of the effects on pollinators (here) including how some insects preferred to go away rather than using local alternative flowers, and those who shifted flowers followed preferential flower types features. However, the pollinator responses also negatively impacted the ways pollinators interact with plants and the rate by which pollinators shifted to new plants. You will find all results at this link, or write me for more details.

Here below a “lay” summary presenting the paper in non-technical way, a requirement from the journal which I am not sure if was used eventually.

Field experiments reveal the alteration of plant and pollinator interactions when the generalist plants are removed

Paolo Biella, University of Milano-Bicocca, and colleagues

Species interact with each other in complex ways. Within these tangled systems, some species cover more prominent roles than others: in the case of plants and pollinators, some plants are highly abundant or provide very attractive floral resources to pollinators and thus they are highly visited. In this study we tested the effects, on pollinator richness and on the species interactions, generated by the experimental removal of these important plants from the system. In particular, we planned to remove 4 plant species from natural communities, one plant species at a time, based on the number of pollinators they had previously received. We discovered some important aspects of how a pollinator guild depends on the scenario set by the plant assemblage. We found that knocking out the most visited plants triggered the disappearance of many pollinators, and that these local extinctions were more in number than what expected from computer-based simulation models. On top of that, we discovered that the framework set by the interacting species changed towards more fragile states when the most visited plants were removed, which contrasts previous expectations that these multi-species systems are stable against species loss. Furthermore, the data showed that novel interactions were established after the important plant were lost. In particular, those generalist pollinators which visited both the plants targeted of removal and the non-target plants tended to establish novel links more often than the other pollinators. Additional interesting results from the experiment regard the emergence of opportunistic interactions established in a random fashion, and structural unpredictability of the network of species interactions when plants were removed. These latter aspects are fundamental because reveal that the framework of interactions set between plants and pollinators changed in their inner dynamics and rules of assembly. Overall, these findings supported the idea that generalist, highly visited, flowers play a key role in sustaining local pollinator guilds, and that otherwise the framework of interactions is perturbed. Nevertheless, our study indicates that some pollinators can find alternative resources by establishing novel links, a reorganizational ability that possibly buffers against even more dramatic effects of generalist plants loss.

Finding biologically reliable tresholds

Consider a biological sample, for example pollen on an insect body. If you aim at sorting the pollen’s species according to their abundance, you will inevitably find that some pollen is super-dominant (i.e. very abundant) and other pollen is extremely rare, with a gradient in between. So far so good, but if you calculate any diversity statistics, the chosen metric will be influenced by the very abundant taxa which will shadow the other diversity. There are many ways to possible handle or correct for this, but I will not deal with it now. Another face of the problem comes from species that are very rare in the samples. Are these less abundant ones biologically reliable? Say, a bee collected two pollen grains from plant #1 and 100 from plant#2, could we confidently say the bee collects heterogeneous resources? Or would rather be better to ignore the 2 grains of species #1 (that resulted of stochastic event? Or from cross contamination between flowers?)? I would go for excluding the two grains… but the same issue arises from DNA data. In recent times, pollen have been identified with DNA metabarcoding, probably the best way to identify at species level given the difficulties at sorting species of pollen morphologically. The output of these type of data are matrices where sequenced pollen species are associated to a given number of DNA sequencing “reads” for each sample, that are quantitative numbers saying how much DNA you got from your DNA analysis protocol. Well, again, some species will be very rare, others will not be. How to behave? Some suggestions would be to remove everything below 1% of the reads abundance, while others would suggest to use the number of reads resulted from sequencing blanks (that are empty vials put in the machine to calculate possible machine-related contamination). While the second option seems very reasonable, it ignores the differences between species in amplification procedure: you could get few reads because a species has very thick pollen walls and hardly released any DNA; if so, should it be excluded because it resulted less abundant than a blank? Maybe not. On the other hand, using a fixed 1% threshold ignores the read counts distribution in the samples: say you have one species with 98% of the pollen and three species with about 0.66% of the reads, should we exclude the three? With such skewed distribution using fixed threshold is very risky. That is why I usually prefer using a ROC threshold calculation procedure. It is very simple but robust and everyone loves it, yet it is hardly ever used in ecological or DNA data.

The procedure consists in statistically estimating the rate of false and true positives and negatives for each sample by associating the number of reads to these categories, and thus obtaining a sample-dependent threshold based on how the reads are actually distributed in your sample (b.t.w., you can also obtain a cross-samples threshold if you prefer having a constant one). I used this approach in both a pollen based study (see here!) and a microbe-based study (in revision), and the results always make more sense to me than using other cleaning approaches (the above mentioned ones) that basically clean too much, or not cleaning at all, where you risk to have too much diversity involved and you would dilute the important information in a mess of data. However, the possible solution is to try different approaches and decide according to the data you have, because sometimes even ROC cleans “too much”.

The figures are about pollen (the first) and a reconstructed DNA molecule (the second), are taken from Pxfuel and hold a CC licence.