Maxwell J. Farrell

The macroecology of infectious diseases: a new perspective on global-scale drivers of pathogen distributions and impacts

Identifying drivers of infectious disease patterns and impacts at the broadest scales of organisation is one of the most crucial challenges for modern science, yet answers to many fundamental questions remain elusive. These include what factors commonly facilitate transmission of pathogens to novel host species, what drives variation in immune investment among host species, and more generally what drives global patterns of parasite diversity and distribution? Here we consider how the perspectives and tools of macroecology, a field that investigates patterns and processes at broad spatial, temporal and taxonomic scales, are expanding scientific understanding of global infectious disease ecology. In particular, emerging approaches are providing new insights about scaling properties across all living taxa, and new strategies for mapping pathogen biodiversity and infection risk. Ultimately, macroecology is establishing a framework to more accurately predict global patterns of infectious disease distribution and emergence.

The study of parasite sharing for surveillance of zoonotic diseases

Abstract Determining the factors that influence the transmission of parasites among hosts is important for directing surveillance of animal parasites before they successfully emerge in humans, and increasing the efficacy of programs for the control and management of zoonotic diseases. Here we present a review of recent advances in the study of parasite sharing, wildlife ecology, and epidemiology that could be extended and incorporated into proactive surveillance frameworks for multi-host infectious diseases. These methods reflect emerging interdisciplinary techniques with significant promise for the identification of future zoonotic parasites and unknown reservoirs of current zoonoses, strategies for the reduction of parasite prevalence and transmission among hosts, and decreasing the burden of infectious diseases.

Characterizing the phylogenetic specialism–generalism spectrum of mammal parasites

The distribution of parasites across mammalian hosts is complex and represents a differential ability or opportunity to infect different host species. Here, we take a macroecological approach to investigate factors influencing why some parasites show a tendency to infect species widely distributed in the host phylogeny (phylogenetic generalism) while others infect only closely related hosts. Using a database on over 1400 parasite species that have been documented to infect up to 69 terrestrial mammal host species, we characterize the phylogenetic generalism of parasites using standard effect sizes for three metrics: mean pairwise phylogenetic distance (PD), maximum PD and phylogenetic aggregation. We identify a trend towards phylogenetic specialism, though statistically host relatedness is most often equivalent to that expected from a random sample of host species. Bacteria and arthropod parasites are typically the most generalist, viruses and helminths exhibit intermediate generalism, and protozoa are on average the most specialist. While viruses and helminths have similar mean pairwise PD on average, the viruses exhibit higher variation as a group. Close-contact transmission is the transmission mode most associated with specialism. Most parasites exhibiting phylogenetic aggregation (associating with discrete groups of species dispersed across the host phylogeny) are helminths and viruses.

Response to Strona & Fattorini: are generalist parasites being lost from their hosts?

We respond to criticism of our recent paper by examining assumptions about the structure of host-parasite networks, and discuss the implications of host extinction on our perception of parasite specificity.

Disease mortality in domesticated animals is predicted by host evolutionary relationships

Infectious diseases of domesticated animals impact human well-being via food insecurity, loss of livelihoods, and human infections. While much research has focused on parasites that infect single host species, most parasites of domesticated mammals infect multiple species. The impact of multi-host parasites varies across hosts; some rarely result in death, whereas others are nearly always fatal. Despite their high ecological and societal costs, we currently lack theory for predicting the lethality of multi-host parasites. Here, using a global dataset of over 4000 case-fatality rates for 65 infectious diseases (caused by micro and macro-parasites) and 12 domesticated host species, we show that the average evolutionary distance from an infected host to other mammal host species is a strong predictor of disease-induced mortality. We find that as parasites infect species outside of their documented phy-1 logenetic host range, they are more likely to result in lethal infections, with the odds of death doubling for each additional 10 million years of evolutionary distance. Our results for domesticated animal diseases reveal patterns in the evolution of highly lethal parasites that are difficult to observe in the wild, and further suggest that the severity of infectious diseases may be predicted from evolutionary relationships among hosts.

Global macroevolution and macroecology of passerine song

Studying the macroevolution of the songs of Passeriformes (perching birds) has proved challenging. The complexity of the task stems not just from the macroevolutionary and macroecological challenge of modeling so many species, but also from the difficulty in collecting and quantifying birdsong itself. Using machine learning techniques, we extracted songs from a large citizen science dataset, and then analyzed the evolution, and biotic and abiotic predictors of variation in birdsong across 578 passerine species. Contrary to expectations, we found few links between life‐history traits (monogamy and sexual dimorphism) and the evolution of song pitch (peak frequency) or song complexity (standard deviation of frequency). However, we found significant support for morphological constraints on birdsong, as reflected in a negative correlation between bird size and song pitch. We also found that broad‐scale biogeographical and climate factors such as net primary productivity, temperature, and regional species richness were significantly associated with both the evolution and present‐day distribution of bird song features. Our analysis integrates comparative and spatial modeling with newly developed data cleaning and curation tools, and suggests that evolutionary history, morphology, and present‐day ecological processes shape the distribution of song diversity in these charismatic and important birds.

Tongues on the EDGE: language preservation priorities based on threat and lexical distinctiveness

Languages are being lost at rates exceeding the global loss of biodiversity. With the extinction of a language we lose irreplaceable dimensions of culture and the insight it provides on human history and the evolution of linguistic diversity. When setting conservation goals, biologists give higher priority to species likely to go extinct. Recent methods now integrate information on species evolutionary relationships to prioritize the conservation of those with a few close relatives. Advances in the construction of language trees allow us to use these methods to develop language preservation priorities that minimize loss of linguistic diversity. The evolutionarily distinct and globally endangered (EDGE) metric, used in conservation biology, accounts for a species’ originality (evolutionary distinctiveness—ED) and its likelihood of extinction (global endangerment—GE). Here, we use a similar framework to inform priorities for language preservation by generating rankings for 350 Austronesian languages. Kavalan, Tanibili, Waropen and Sengseng obtained the highest EDGE scores, while Xârâcùù (Canala), Nengone and Palauan are among the most linguistically distinct, but are not currently threatened. We further provide a way of dealing with incomplete trees, a common issue for both species and language trees.