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Reposted by Carlos P Carmona

Giacomo Puglielli @gpuglielli.bsky.social · 7d

Working with individual trait data and functional trait spaces and bored about means?

With @cpcarmona.bsky.social, Agnese Bissi and @etordoni.bsky.social, we put together a perspective to test the effect of individual observations on trait space properties 👇👇

www.nature.com/articles/s44...

Quantifying the influence of intraspecific variability in trait spaces - npj Biodiversity

npj Biodiversity - Quantifying the influence of intraspecific variability in trait spaces

www.nature.com

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Reposted by Carlos P Carmona

New Phytologist @newphyt.bsky.social · 12d

✨ Paper spotlight ✨

(🧵 1/6) The path towards a unified trait space: synthesizing plant functional diversity
nph.onlinelibrary.wiley.com/doi/10.1111/...

Fig. 1 Schematic representation of broad groups of traits measurable across plant organs.

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Carlos P Carmona @cpcarmona.bsky.social · 20d

New Tansley Insight in New Phytologist: The path toward a unified plant trait space: synthesizing plant functional diversity.

Why a common trait space matters, how to build it, and what it enables.

With @e-beccari.bsky.social
doi.org/10.1111/nph....

#PlantTraits #FunctionalDiversity

doi.org

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Reposted by Carlos P Carmona

Kerry Stewart @kerrys189.bsky.social · Aug 13

Thank you to my excellent examiners @alexpigot.bsky.social & @vlboult.bsky.social and my wonderful supervisors, @mgs-cielo-azul.bsky.social, @josephtobias.bsky.social, @cpcarmona.bsky.social, @expecocons.bsky.social & Chris Venditti. I am very grateful to have had the chance to learn from you all.

Manuela Gonzalez Suarez @mgs-cielo-azul.bsky.social · Aug 9

Super happy that @kerrys189.bsky.social passed her viva with no corrections!! 🥳🥳🥳

Congratulations, Dr. Stewart!!

The EcCo lab will miss you, but we know you are off to do amazing things

Thanks to the excellent examiners @alexpigot.bsky.social & @vlboult.bsky.social

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Carlos P Carmona @cpcarmona.bsky.social · Aug 14

I think I’ll learn more from you than you did from me 😅
Congratulations, Kerry!

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Reposted by Carlos P Carmona

Manuela Gonzalez Suarez @mgs-cielo-azul.bsky.social · Aug 9

Super happy that @kerrys189.bsky.social passed her viva with no corrections!! 🥳🥳🥳

Congratulations, Dr. Stewart!!

The EcCo lab will miss you, but we know you are off to do amazing things

Thanks to the excellent examiners @alexpigot.bsky.social & @vlboult.bsky.social

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Carlos P Carmona @cpcarmona.bsky.social · Jul 8

with @stefanomammola.bsky.social, @gracoroza.bsky.social, Gianluigi Ottaviani and Francesco de Bello

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Carlos P Carmona @cpcarmona.bsky.social · Jul 8

Hot off the press 🔥 New Ecological Monographs paper shows why, when and how to include intraspecific trait variability to enhance functional diversity research. Huge shout out to Facundo Palacio for his vision and leadership. Read here 👉 doi.org/10.1002/ecm....
#traits #functionaldiversity 📏🌐

Integrating intraspecific trait variability in functional diversity: An overview of methods and a guide for ecologists

Variability in traits within species (intraspecific trait variability; ITV) has attracted increased interest in functional ecology, as it can profoundly influence the detection of functional trait pa....

doi.org

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Carlos P Carmona @cpcarmona.bsky.social · Jul 7

Too many metrics, I agree! But accumulation curves make sense only for metrics that have set monotonicity/concavity. Divergence or evenness do not meet those properties, so the z slope loses meaning. We still need to match each metric to the facet we want to study.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

2. I think they are fundamentally different aspects; a single number wont suffice. For example, some aspects are related to different aspects of the raw distribution of traits (richness, divergence, evennes), but other aspects require species identities (redundancy). But good luck with the search!

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

1. Yes, papers should report different indices, carefully chosen so that they are suitable for your question.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

I would say that the field nowadays treats those criteria as facet-specific (richness, divergence, evenness) rather than universal.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

My main concern is that the paper frames the 14 requirements as must-haves for any reliable FD metric, then counts how many each index meets. That creates the impression that indices are flawed.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

So, if functional structure (or functional diversity if you prefer) is a distribution, you cannot simply characterize it with a single number, like you cant characterize a probabilistic distribution only with the mean, or the variance, or the kurtosis

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

The two aspects of extinction are relevant, so you need to estimate both things simultaneously (among other things) to understand well what is going on with functional structure (the distribution of species in the trait space)

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

But if what you are losing are redundant species, then divergence indices will increase, which matches their expected behaviour (you end up with communities with fewer but more unique species).

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

In the scenarios related to extinctions (7-8), you expect functional diversity to decrease. This expectation matches the behaviour of richness indices, which work well.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

In your ecosystem scenarios, you test different things. For example in scenarios 2, 3 & 4 you are essentially increasing divergence, and this is well detected by divergence indices, but not by richness indices.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

And so on. At the end, you can see from your tests that thare are sets of indices that tend to respond in similar ways (like the two sets I mentioned above). And these are the ways one would expect them to respond according to their original conception.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

Indices of functional richness (FaD, mFaD, FD) should be insensitive to addition of redundant species and to changes in abundances, an only change when something modifies the boundaries of the distribution of species in the trait space.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

Hi Adji! It was just an example. What I mean is that not all criteria should be fulfilled at once for an index to be useful. For example, dispersion indices (Rao, FDiv, FDis) by definition should not fulfil set monotonicity, because they reflect the average dissimilarity among components (species).

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

You would not judge a hammer by how well it drives a screw; likewise, do not blame a spread metric for failing a richness test. Functional diversity is multifaceted and needs a toolbox, not a universal index.

Francisco Rodriguez-Sanchez @frodsan.bsky.social · Jul 5

Rethinking Ecological Measures Of Functional Diversity

'none of the widely used metrics satisfy the requirements. Critical flaws leave them blind to the very biodiversity loss they're intended to detect. There's urgent need to develop new generation of FD metrics'

arxiv.org/abs/2506.17839 #ecopubs

Understanding functional diversity, the range and variability of species' roles and actions within their communities, is key to predicting and preserving the functions that sustain both nature and human well-being. In this paper, we provide a comprehensive review of the literature on functional diversity measurement. We begin by consolidating essential criteria that effective measures of functional diversity should meet. We then evaluate fifteen widely used functional diversity metrics against these criteria and assess their performance across six synthetic ecosystem scenarios where optimal behavior is known. Surprisingly, our analysis reveals that none of the widely used metrics fully satisfy all the established requirements, and all fail in at least one ecosystem scenario. In particular, we find that almost all metrics flagrantly violate set monotonicity and distance monotonicity, requirements that adding a novel species should increase diversity, and that the magnitude of that increase should grow with trait dissimilarity. We also find that metrics fail to decline when rare, functionally extreme species are lost, and even increase when a perfectly redundant species is added. These critical flaws leave them blind to the very biodiversity loss that functional diversity measures are intended to detect. Our findings underscore the urgent need to develop a new generation of functional diversity metrics that more accurately reflect ecological realities.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 6

You would not judge a hammer by how well it drives a screw; likewise, do not blame a spread metric for failing a richness test. Functional diversity is multifaceted and needs a toolbox, not a universal index.

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Carlos P Carmona @cpcarmona.bsky.social · Jul 1

👏👏👏

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Reposted by Carlos P Carmona

Pedro Peres-Neto @comecology.bsky.social · Jun 27

🌍 Excited to be part of the Global Ecology Starter Pack - a great way to discover and connect with people interested in ecology at large scales! go.bsky.app/F86HYqj

👉 If you’d like to join the next pack (Vol_3 is in the works), DM @global-ecology.bsky.social. 🌐

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