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Biology subjects

Nova, N.

Publications and source records attributed to Nova, N..

2 recordsLinked to original sources

Return of an apex predator to a suburban preserve triggers a rapid trophic cascade

Absence of apex predators simplifies food chains, leading to trophic degradation of ecosystems and diminution of the services they provide1. However, most predators do not coexist well with humans, which has resulted in a decline of carnivores and functional ecosystems worldwide2. In some instances, cryptic carnivores manage to survive amidst human settlements, finding refuge in small biological islands surrounded by urban landscapes. In such a system, we used two non-invasive data collection methods (camera trapping and fecal sampling) to investigate the multiannual relationship between predators and prey, and between competitors, through analysis of: (1) relative abundance and detection probability of species over time, (2) causal interactions via empirical dynamic modeling, (3) diet, and (4) diel activity patterns. All approaches show concordance in the results: the natural return of an apex predator, the puma (Puma concolor), triggered a trophic cascade, affecting the abundance and behavior of its main prey, subordinate predators and other prey in the studied system. Our study demonstrates that trophic recovery can occur rapidly following the return of a top predator, even in small protected areas in increasingly urbanized landscapes.

ecology

Mosquito and primate ecology predict human risk of yellow fever virus spillover in Brazil

Many (re)emerging infectious diseases in humans arise from pathogen spillover from wildlife or livestock, and accurately predicting pathogen spillover is an important public health goal. In the Americas, yellow fever in humans primarily occurs following spillover from non-human primates via mosquitoes. Predicting yellow fever spillover can improve public health responses through vector control and mass vaccination. Here, we develop and test a mechanistic model of pathogen spillover to predict human risk for yellow fever in Brazil. Our environmental risk model, based on the ecology of mosquito vectors and non-human primate hosts, distinguished municipality-months with yellow fever spillover from 2001 to 2016 with high accuracy (AUC = 0.71). Incorporating hypothesized cyclical dynamics of infected primates improved accuracy (AUC = 0.79). Using boosted regression trees to identify gaps in the mechanistic model, we found that important predictors include current and lagged (mechanistic) environmental risk, vaccine coverage, population density, temperature, and precipitation. More broadly, we show that for a widespread human viral pathogen, the ecological interactions between environment, vectors, reservoir hosts, and humans can predict spillover with surprising accuracy, suggesting the potential to improve preventative action to reduce yellow fever spillover and prevent onward epidemics in humans.

ecology