Reply to: “Global Conservation of Phylogenetic Diversity Captures More Than Just Functional Diversity”

Academic biologists have long advocated for conserving phylogenetic diversity (PD), often (but not exclusively) on the basis that PD is a useful proxy for “feature diversity”, defined as the variety of forms and functions represented in set of organisms (see below for an extended discussion of this definition). In a recent paper, we assess the extent to which this proxy (which we coined the “phylogenetic gambit”) holds in three empirical datasets (terrestrial mammals, birds, and tropical marine fishes) when using functional traits and functional diversity (FD) to operationalize feature diversity. Owen et al. offer a criticism of our methods for quantifying feature diversity with FD and disagree with our conclusions. We are grateful that Owen et al. have engaged thoughtfully with our work, but we believe there are more points of agreement than Owen et al. imply

Prioritizing Phylogenetic Diversity Captures Functional Diversity Unreliably

In the face of the biodiversity crisis, it is argued that we should prioritize species in order to capture high functional diversity (FD). Because species traits often reflect shared evolutionary history, many researchers have assumed that maximizing phylogenetic diversity (PD) should indirectly capture FD, a hypothesis that we name the “phylogenetic gambit”. Here, we empirically test this gambit using data on ecologically relevant traits from \u3e15,000 vertebrate species. Specifically, we estimate a measure of surrogacy of PD for FD. We find that maximizing PD results in an average gain of 18% of FD relative to random choice. However, this average gain obscures the fact that in over one-third of the comparisons, maximum PD sets contain less FD than randomly chosen sets of species. These results suggest that, while maximizing PD protection can help to protect FD, it represents a risky conservation strategy

The web and the tree : on the interplay between ecological processes and evolutionary histories.

In this thesis, we introduce and explore a mathematical framework in which to study the evolution of and within ecological networks. Hence, we focus on a peculiar interpretation of the “biodiversity” concept, namely one that includes the complex pattern of interactions among species, along with the species abundancy and evolutionary distinctiveness. Our objects of inquiry are species communities as complex wholes. Classically, communities have been approached from two distinct points of view: on one hand, we can consider the graph describing the energy flows among species in an ecosystem (i.e., an ecosystem’s food web); on the other hand, we can consider the species’ phylogeny, the tree graph describing the evolutionary relatedness of those species. The structure of an ecosystem (its biological diversity and the topology of its interactions) is the product of fast ecological processes within food webs and of the long-term evolutionary processes that give shape to the tree of life. In particular, early ecological literature recognized that the evolutionary history of a species (or its taxonomical classification, in the pre-Darwin era) helps to determine the species’ role as part of an ecological network of interacting species. Conversely, the “ghost of past competition” and arms races are famous examples of the fact that a species’ interactions with its resources and consumers helps to determine the evolutionary trajectory of that species. As the empirical research presents strong evidence that the ecology-evolution (eco-evo) feedback loop is, indeed, significant, the ecological and evolutionary points of view are laboriously being connected more and more strongly. A theoretical framework has been developed for some important scenario (e.g., the co-evolution of hosts and parasites, butterfly and flowers, or plants and pollinators). The case of complex food webs, where is not possible to distinguish two neatly separated trophic layers, has resisted such a treatment. We argue that this can be partially addressed by moving from a rigidly binary view of food webs to the representation of species interactions in a continuous metric space, where species evolution can be gradual. In Chapter 3 we show how this metric space representation of a food web can be estimated efficiently and gather insights about the evolutionary signature of food webs. Species’ ecological interdependency, arising from their role as part of complex food webs, is something that the classic model of trait evolution has avoided. One reason is that it is hard to give a model determining the presence (and strength) of species interactions throughout their history. In Chapter 3 Appendix we show how the metric space representation of food webs may constitute a suitable environment in which to define such a model. Assessing species’ contribution to biodiversity is an important task that scientifically informs conservation efforts. In Chapter 4 we define a family of measures 6 assessing the relative ecological importance of a species in a food web. These measures are defined directly on the food web’s metric space representation we propose in the first chapter. We explore the relationship between evolutionary and ecological uniqueness. In Chapter 5 we tackle the “mode” of food web evolution more directly exploiting, once again, the functional trait representation of food webs. In particular, we formulate two contrasting hypotheses on the evolution of frugivore birds’ functional ecological niches and test it on a dataset of frugivore birds in the Andes. Finally, in Chapter 6 we make a little detour from food webs and consider a different kind of ecological network: geographically grounded population networks composed of patches and corridors among patches. Population networks play a crucial role in evolution (e.g., determining the dynamics of genes’ flows). The insight we gained throughout the previous work (especially in the second chapter) supports the notion that the relevance of a species in a network is not always perfectly captured by the species’ local properties (such as its number of connections). In this spirit, we assess the importance of a patch in a geographic network by the global effect that removing that patch has on the whole network. All the code and data used in this thesis will be available on a public Github repository (see gvdr.github.io)

Data from: Conserving phylogenetic diversity can be a poor strategy for conserving functional diversity

For decades, academic biologists have advocated for making conservation decisions in light of evolutionary history. Specifically, they suggest that policy makers should prioritize conserving phylogenetically diverse assemblages. The most prominent argument is that conserving phylogenetic diversity (PD) will also conserve diversity in traits and features (functional diversity [FD]), which may be valuable for a number of reasons. The claim that PD-maximized (“maxPD”) sets of taxa will also have high FD is often taken at face value and in cases where researchers have actually tested it, they have done so by measuring the phylogenetic signal in ecologically important functional traits. The rationale is that if traits closely mirror phylogeny, then saving the maxPD set of taxa will tend to maximize FD and if traits do not have phylogenetic structure, then saving the maxPD set of taxa will be no better at capturing FD than criteria that ignore PD. Here, we suggest that measuring the phylogenetic signal in traits is uninformative for evaluating the effectiveness of using PD in conservation. We evolve traits under several different models and, for the first time, directly compare the FD of a set of taxa that maximize PD to the FD of a random set of the same size. Under many common models of trait evolution and tree shapes, conserving the maxPD set of taxa will conserve more FD than conserving a random set of the same size. However, this result cannot be generalized to other classes of models. We find that under biologically plausible scenarios, using PD to select species can actually lead to less FD compared with a random set. Critically, this can occur even when there is phylogenetic signal in the traits. Predicting exactly when we expect using PD to be a good strategy for conserving FD is challenging, as it depends on complex interactions between tree shape and the assumptions of the evolutionary model. Nonetheless, if our goal is to maintain trait diversity, the fact that conserving taxa based on PD will not reliably conserve at least as much FD as choosing randomly raises serious concerns about the general utility of PD in conservation

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COVID-19 infodemic on Facebook and containment measures in Italy, United Kingdom and New Zealand.

The COVID-19 pandemic has been characterized by a social media "infodemic": an overabundance of information whose authenticity may not always be guaranteed. With the potential to lead individuals to harmful decisions for the society, this infodemic represents a severe threat to information security, public health and democracy. In this paper, we assess the interplay between the infodemic and specific aspects of the pandemic, such as the number of cases, the strictness of containment measures, and the news media coverage. We perform a comparative study on three countries that employed different managements of the COVID-19 pandemic in 2020-namely Italy, the United Kingdom, and New Zealand. We first analyze the three countries from an epidemiological perspective to characterize the impact of the pandemic and the strictness of the restrictions adopted. Then, we collect a total of 6 million posts from Facebook to describe user news consumption behaviors with respect to the reliability of such posts. Finally, we quantify the relationship between the number of posts published in each of the three countries and the number of confirmed cases, the strictness of the restrictions adopted, and the online news media coverage about the pandemic. Our results show that posts referring to reliable sources are consistently predominant in the news circulation, and that users engage more with reliable posts rather than with posts referring to questionable sources. Furthermore, our modelling results suggest that factors related to the epidemiological and informational ecosystems can serve as proxies to assess the evolution of the infodemic

Datasets S1 to S10. Phylogenetic datasets

Phylogenetic datasets used in our analyses. Each dataset is a nexus file including a tree distribution with 100 trees (except for planktonic foraminifera)

Clinical relevant pancreatic fistula after pancreatoduodenectomy: when negative amylase levels tell the truth

Drain Amylase level are routinely determined to diagnose pancreatic fistula after Pancreatocoduodenectomy. Consensus is lacking regarding the cut-off value of amylase to diagnosis clinically relevant postoperative pancreatic fistulae (POPF). The present study proposes a model based on Amylase Value in the Drain (AVD) measured in the first three postoperative days to predict a POPF. Amylase cut-offs were selected from a previous published systematic review and the accuracy were validated in a multicentre database from 12 centres in 2 countries. The present study defined POPF the 2016 ISGPS criteria (3 times the upper limit of normal serum amylase). A learning machine method was used to correlate AVD with the diagnosis of POPF. Overall, 454 (27%) of 1638 patients developed POPF. Machine learning excluded a clinically relevant postoperative pancreatic fistulae with an AUC of 0.962 (95% CI 0.940-0.984) in the first five postoperative days. An AVD at a cut-off of 270 U/L in 2 days in the first three postoperative days excluded a POPF with an AUC of 0.869 (CI 0.81-0.90, p < 0.0001). A single AVD in the first three postoperative days may not exclude POPF after pancreatoduodenectomy. The levels should be monitored until day 3 and have two negative values before removing the drain. In the group with a positive level, the drain should be kept in and AVD monitored until postoperative day five

Clinical relevant pancreatic fistula after pancreatoduodenectomy:when negative amylase levels tell the truth

Drain Amylase level are routinely determined to diagnose pancreatic fistula after Pancreatocoduodenectomy. Consensus is lacking regarding the cut-off value of amylase to diagnosis clinically relevant postoperative pancreatic fistulae (POPF). The present study proposes a model based on Amylase Value in the Drain (AVD) measured in the first three postoperative days to predict a POPF. Amylase cut-offs were selected from a previous published systematic review and the accuracy were validated in a multicentre database from 12 centres in 2 countries. The present study defined POPF the 2016 ISGPS criteria (3 times the upper limit of normal serum amylase). A learning machine method was used to correlate AVD with the diagnosis of POPF. Overall, 454 (27%) of 1638 patients developed POPF. Machine learning excluded a clinically relevant postoperative pancreatic fistulae with an AUC of 0.962 (95% CI 0.940-0.984) in the first five postoperative days. An AVD at a cut-off of 270 U/L in 2 days in the first three postoperative days excluded a POPF with an AUC of 0.869 (CI 0.81-0.90, p < 0.0001). A single AVD in the first three postoperative days may not exclude POPF after pancreatoduodenectomy. The levels should be monitored until day 3 and have two negative values before removing the drain. In the group with a positive level, the drain should be kept in and AVD monitored until postoperative day five