John Paul Schmidt

Rodent reservoirs of future zoonotic diseases

Significance Forecasting reservoirs of zoonotic disease is a pressing public health priority. We apply machine learning to datasets describing the biological, ecological, and life history traits of rodents, which collectively carry a disproportionate number of zoonotic pathogens. We identify particular rodent species predicted to be novel zoonotic reservoirs and geographic regions from which new emerging pathogens are most likely to arise. We also describe trait profiles—complexes of biological features—that distinguish reservoirs from nonreservoirs. Generally, the most permissive rodent reservoirs display a fast-paced life history strategy, maximizing near-term fitness by having many altricial young that begin reproduction early and reproduce frequently. These findings may constitute an important lead in guiding the search for novel disease reservoirs in the wild. The increasing frequency of zoonotic disease events underscores a need to develop forecasting tools toward a more preemptive approach to outbreak investigation. We apply machine learning to data describing the traits and zoonotic pathogen diversity of the most speciose group of mammals, the rodents, which also comprise a disproportionate number of zoonotic disease reservoirs. Our models predict reservoir status in this group with over 90% accuracy, identifying species with high probabilities of harboring undiscovered zoonotic pathogens based on trait profiles that may serve as rules of thumb to distinguish reservoirs from nonreservoir species. Key predictors of zoonotic reservoirs include biogeographical properties, such as range size, as well as intrinsic host traits associated with lifetime reproductive output. Predicted hotspots of novel rodent reservoir diversity occur in the Middle East and Central Asia and the Midwestern United States.

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.

Time since Introduction, Seed Mass, and Genome Size Predict Successful Invaders among the Cultivated Vascular Plants of Hawaii

Extensive economic and environmental damage has been caused by invasive exotic plant species in many ecosystems worldwide. Many comparative studies have therefore attempted to predict, from biological traits, which species among the pool of naturalized non-natives become invasive. However, few studies have investigated which species establish and/or become pests from the larger pool of introduced species and controlled for time since introduction. Here we present results from a study aimed at quantifying predicting three classes of invasive species cultivated in Hawaii. Of 7,866 ornamental species cultivated in Hawaii between 1840 and 1999, 420 (5.3%) species naturalized, 141 (1.8%) have been classified as weeds, and 39 (0.5%) were listed by the state of Hawaii as noxious. Of the 815 species introduced >80 years ago, 253 (31%) have naturalized, 90 (11%) are classed as weeds, and 22 (3%) as noxious by the state of Hawaii. Using boosted regression trees we classified each group with nearly 90% accuracy, despite incompleteness of data and the low proportion of naturalized or pest species. Key biological predictors were seed mass and highest chromosome number standardized by genus which, when data on residence time was removed, were able to predict all three groups with 76–82% accuracy. We conclude that, when focused on a single region, screening for potential weeds or noxious plants based on a small set of biological traits can be achieved with sufficient accuracy for policy and management purposes.

Sex ratio and spatial pattern of males and females in the dioecious sandhill shrub, Ceratiola ericoides ericoides (Empetraceae) Michx

Sex ratio, size, age, and spatial pattern were investigated for males and females of the dioecious shrub Ceratiola ericoides ericoides (Empetraceae) Michx. within seven mapped populations in Georgia and South Carolina, USA. Among the sites studied, two are regularly burned and one site long-unburned. Age was estimated from node counts of individual shrubs. Only one (fire-suppressed) population showed a female-biased sex ratio, while all others did not differ significantly from 1:1. Mean age estimates did not differ between sexes at any site nor did mean shrub canopy diameter. Bivariate Ripley’s K analysis with a null hypothesis of random labeling was used to investigate whether any of the mapped populations exhibited spatial segregation of the sexes (SSS). No population showed strong evidence of SSS. Rather all sites but one showed males and females to be associated (though not significantly) at a scale of 1–10xa0m. At a scale of 10–35xa0m male and female shrubs were located randomly with respect to one another at all sites.

Why are some plant genera more invasive than others

Determining how biological traits are related to the ability of groups of organisms to become economically damaging when established outside of their native ranges is a major goal of population biology, and important in the management of invasive species. Little is known about why some taxonomic groups are more likely to become pests than others among plants. We investigated traits that discriminate vascular plant genera, a level of taxonomic generality at which risk assessment and screening could be more effectively performed, according to the proportion of naturalized species which are pests. We focused on the United States and Canada, and, because our purpose is ultimately regulatory, considered species classified as weeds or noxious. Using contingency tables, we identified 11 genera of vascular plants that are disproportionately represented by invasive species. Results from boosted regression tree analyses show that these categories reflect biological differences. In summary, approximately 25% of variation in genus proportions of weeds or noxious species was explained by biological covariates. Key explanatory traits included genus means for wetland habitat affinity, chromosome number, and seed mass.

Global Mammal Parasite Database version 2.0

Illuminating the ecological and evolutionary dynamics of parasites is one of the most pressing issues facing modern science, and is critical for basic science, the global economy, and human health. Extremely important to this effort are data on the disease-causing organisms of wild animal hosts (including viruses, bacteria, protozoa, helminths, arthropods, and fungi). Here we present an updated version of the Global Mammal Parasite Database, a database of the parasites of wild ungulates (artiodactyls and perissodactyls), carnivores, and primates, and make it available for download as complete flat files. The updated database has more than 24,000 entries in the main data file alone, representing data from over 2700 literature sources. We include data on sampling method and sample sizes when reported, as well as both reported and corrected (i.e., standardized) binomials for each host and parasite species. Also included are current higher taxonomies and data on transmission modes used by the majority of species of parasites in the database. In the associated metadata we describe the methods used to identify sources and extract data from the primary literature, how entries were checked for errors, methods used to georeference entries, and how host and parasite taxonomies were standardized across the database. We also provide definitions of the data fields in each of the four files that users can download.

Bioeconomic forecasting of invasive species by ecological syndrome

Invasive non-native species cause enormous economic damage. Although there is both regulative and legislative precedent for policies restricting introduction of potentially invasive species, lack of a unified theory of invasions—particularly with respect to plants—has impeded efforts to implement screening despite empirical patterns suggesting the existence of “invasion syndromes”. Motivated by recent advances in the comparative biology of invasive species, we sought to develop a cost-sensitive model that would associate groups of species according to biological traits and assign them to risk categories based on their invasion potential. Focusing on invasive plants in the US, which are estimated to generate costs of

Undiscovered Bat Hosts of Filoviruses

US 34.7 billion/year, we then combined this scheme with estimates of the per species expected economic losses associated with forgoing trade and with benchmark values for the economic costs associated with plant pests to obtain a decision tool that would maximize economic benefits. If used for screening, this tool is estimated to yield expected net benefits of

Two sides of the same coin? Rare and pest plants native to the United States and Canada

80,000–

Characterizing the phylogenetic specialism–generalism spectrum of mammal parasites

140,000 per species assessed under very conservative estimates of losses due to invasion.